%0 Journal Article %J Circ Cardiovasc Genet %D 2010 %T Candidate gene association resource (CARe): design, methods, and proof of concept. %A Musunuru, Kiran %A Lettre, Guillaume %A Young, Taylor %A Farlow, Deborah N %A Pirruccello, James P %A Ejebe, Kenechi G %A Keating, Brendan J %A Yang, Qiong %A Chen, Ming-Huei %A Lapchyk, Nina %A Crenshaw, Andrew %A Ziaugra, Liuda %A Rachupka, Anthony %A Benjamin, Emelia J %A Cupples, L Adrienne %A Fornage, Myriam %A Fox, Ervin R %A Heckbert, Susan R %A Hirschhorn, Joel N %A Newton-Cheh, Christopher %A Nizzari, Marcia M %A Paltoo, Dina N %A Papanicolaou, George J %A Patel, Sanjay R %A Psaty, Bruce M %A Rader, Daniel J %A Redline, Susan %A Rich, Stephen S %A Rotter, Jerome I %A Taylor, Herman A %A Tracy, Russell P %A Vasan, Ramachandran S %A Wilson, James G %A Kathiresan, Sekar %A Fabsitz, Richard R %A Boerwinkle, Eric %A Gabriel, Stacey B %K African Americans %K Cholesterol, HDL %K Cholesterol, LDL %K Cohort Studies %K Databases, Genetic %K European Continental Ancestry Group %K Genetic Association Studies %K Genotype %K Humans %K Phenotype %K Pilot Projects %K Polymorphism, Single Nucleotide %K Research Design %K Triglycerides %X

BACKGROUND: The National Heart, Lung, and Blood Institute's Candidate Gene Association Resource (CARe), a planned cross-cohort analysis of genetic variation in cardiovascular, pulmonary, hematologic, and sleep-related traits, comprises >40,000 participants representing 4 ethnic groups in 9 community-based cohorts. The goals of CARe include the discovery of new variants associated with traits using a candidate gene approach and the discovery of new variants using the genome-wide association mapping approach specifically in African Americans.

METHODS AND RESULTS: CARe has assembled DNA samples for >40,000 individuals self-identified as European American, African American, Hispanic, or Chinese American, with accompanying data on hundreds of phenotypes that have been standardized and deposited in the CARe Phenotype Database. All participants were genotyped for 7 single-nucleotide polymorphisms (SNPs) selected based on prior association evidence. We performed association analyses relating each of these SNPs to lipid traits, stratified by sex and ethnicity, and adjusted for age and age squared. In at least 2 of the ethnic groups, SNPs near CETP, LIPC, and LPL strongly replicated for association with high-density lipoprotein cholesterol concentrations, PCSK9 with low-density lipoprotein cholesterol levels, and LPL and APOA5 with serum triglycerides. Notably, some SNPs showed varying effect sizes and significance of association in different ethnic groups.

CONCLUSIONS: The CARe Pilot Study validates the operational framework for phenotype collection, SNP genotyping, and analytic pipeline of the CARe project and validates the planned candidate gene study of approximately 2000 biological candidate loci in all participants and genome-wide association study in approximately 8000 African American participants. CARe will serve as a valuable resource for the scientific community.

%B Circ Cardiovasc Genet %V 3 %P 267-75 %8 2010 Jun %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/20400780?dopt=Abstract %R 10.1161/CIRCGENETICS.109.882696 %0 Journal Article %J PLoS Genet %D 2011 %T Genetic loci associated with plasma phospholipid n-3 fatty acids: a meta-analysis of genome-wide association studies from the CHARGE Consortium. %A Lemaitre, Rozenn N %A Tanaka, Toshiko %A Tang, Weihong %A Manichaikul, Ani %A Foy, Millennia %A Kabagambe, Edmond K %A Nettleton, Jennifer A %A King, Irena B %A Weng, Lu-Chen %A Bhattacharya, Sayanti %A Bandinelli, Stefania %A Bis, Joshua C %A Rich, Stephen S %A Jacobs, David R %A Cherubini, Antonio %A McKnight, Barbara %A Liang, Shuang %A Gu, Xiangjun %A Rice, Kenneth %A Laurie, Cathy C %A Lumley, Thomas %A Browning, Brian L %A Psaty, Bruce M %A Chen, Yii-der I %A Friedlander, Yechiel %A Djoussé, Luc %A Wu, Jason H Y %A Siscovick, David S %A Uitterlinden, André G %A Arnett, Donna K %A Ferrucci, Luigi %A Fornage, Myriam %A Tsai, Michael Y %A Mozaffarian, Dariush %A Steffen, Lyn M %K Alleles %K Continental Population Groups %K Fatty Acids, Omega-3 %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Male %K Metabolic Networks and Pathways %K Polymorphism, Single Nucleotide %X

Long-chain n-3 polyunsaturated fatty acids (PUFAs) can derive from diet or from α-linolenic acid (ALA) by elongation and desaturation. We investigated the association of common genetic variation with plasma phospholipid levels of the four major n-3 PUFAs by performing genome-wide association studies in five population-based cohorts comprising 8,866 subjects of European ancestry. Minor alleles of SNPs in FADS1 and FADS2 (desaturases) were associated with higher levels of ALA (p = 3 x 10⁻⁶⁴) and lower levels of eicosapentaenoic acid (EPA, p = 5 x 10⁻⁵⁸) and docosapentaenoic acid (DPA, p = 4 x 10⁻¹⁵⁴). Minor alleles of SNPs in ELOVL2 (elongase) were associated with higher EPA (p = 2 x 10⁻¹²) and DPA (p = 1 x 10⁻⁴³) and lower docosahexaenoic acid (DHA, p = 1 x 10⁻¹⁵). In addition to genes in the n-3 pathway, we identified a novel association of DPA with several SNPs in GCKR (glucokinase regulator, p = 1 x 10⁻⁸). We observed a weaker association between ALA and EPA among carriers of the minor allele of a representative SNP in FADS2 (rs1535), suggesting a lower rate of ALA-to-EPA conversion in these subjects. In samples of African, Chinese, and Hispanic ancestry, associations of n-3 PUFAs were similar with a representative SNP in FADS1 but less consistent with a representative SNP in ELOVL2. Our findings show that common variation in n-3 metabolic pathway genes and in GCKR influences plasma phospholipid levels of n-3 PUFAs in populations of European ancestry and, for FADS1, in other ancestries.

%B PLoS Genet %V 7 %P e1002193 %8 2011 Jul %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/21829377?dopt=Abstract %R 10.1371/journal.pgen.1002193 %0 Journal Article %J Nat Genet %D 2011 %T Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function. %A Soler Artigas, Maria %A Loth, Daan W %A Wain, Louise V %A Gharib, Sina A %A Obeidat, Ma'en %A Tang, Wenbo %A Zhai, Guangju %A Zhao, Jing Hua %A Smith, Albert Vernon %A Huffman, Jennifer E %A Albrecht, Eva %A Jackson, Catherine M %A Evans, David M %A Cadby, Gemma %A Fornage, Myriam %A Manichaikul, Ani %A Lopez, Lorna M %A Johnson, Toby %A Aldrich, Melinda C %A Aspelund, Thor %A Barroso, Inês %A Campbell, Harry %A Cassano, Patricia A %A Couper, David J %A Eiriksdottir, Gudny %A Franceschini, Nora %A Garcia, Melissa %A Gieger, Christian %A Gislason, Gauti Kjartan %A Grkovic, Ivica %A Hammond, Christopher J %A Hancock, Dana B %A Harris, Tamara B %A Ramasamy, Adaikalavan %A Heckbert, Susan R %A Heliövaara, Markku %A Homuth, Georg %A Hysi, Pirro G %A James, Alan L %A Jankovic, Stipan %A Joubert, Bonnie R %A Karrasch, Stefan %A Klopp, Norman %A Koch, Beate %A Kritchevsky, Stephen B %A Launer, Lenore J %A Liu, Yongmei %A Loehr, Laura R %A Lohman, Kurt %A Loos, Ruth J F %A Lumley, Thomas %A Al Balushi, Khalid A %A Ang, Wei Q %A Barr, R Graham %A Beilby, John %A Blakey, John D %A Boban, Mladen %A Boraska, Vesna %A Brisman, Jonas %A Britton, John R %A Brusselle, Guy G %A Cooper, Cyrus %A Curjuric, Ivan %A Dahgam, Santosh %A Deary, Ian J %A Ebrahim, Shah %A Eijgelsheim, Mark %A Francks, Clyde %A Gaysina, Darya %A Granell, Raquel %A Gu, Xiangjun %A Hankinson, John L %A Hardy, Rebecca %A Harris, Sarah E %A Henderson, John %A Henry, Amanda %A Hingorani, Aroon D %A Hofman, Albert %A Holt, Patrick G %A Hui, Jennie %A Hunter, Michael L %A Imboden, Medea %A Jameson, Karen A %A Kerr, Shona M %A Kolcic, Ivana %A Kronenberg, Florian %A Liu, Jason Z %A Marchini, Jonathan %A McKeever, Tricia %A Morris, Andrew D %A Olin, Anna-Carin %A Porteous, David J %A Postma, Dirkje S %A Rich, Stephen S %A Ring, Susan M %A Rivadeneira, Fernando %A Rochat, Thierry %A Sayer, Avan Aihie %A Sayers, Ian %A Sly, Peter D %A Smith, George Davey %A Sood, Akshay %A Starr, John M %A Uitterlinden, André G %A Vonk, Judith M %A Wannamethee, S Goya %A Whincup, Peter H %A Wijmenga, Cisca %A Williams, O Dale %A Wong, Andrew %A Mangino, Massimo %A Marciante, Kristin D %A McArdle, Wendy L %A Meibohm, Bernd %A Morrison, Alanna C %A North, Kari E %A Omenaas, Ernst %A Palmer, Lyle J %A Pietiläinen, Kirsi H %A Pin, Isabelle %A Pola Sbreve Ek, Ozren %A Pouta, Anneli %A Psaty, Bruce M %A Hartikainen, Anna-Liisa %A Rantanen, Taina %A Ripatti, Samuli %A Rotter, Jerome I %A Rudan, Igor %A Rudnicka, Alicja R %A Schulz, Holger %A Shin, So-Youn %A Spector, Tim D %A Surakka, Ida %A Vitart, Veronique %A Völzke, Henry %A Wareham, Nicholas J %A Warrington, Nicole M %A Wichmann, H-Erich %A Wild, Sarah H %A Wilk, Jemma B %A Wjst, Matthias %A Wright, Alan F %A Zgaga, Lina %A Zemunik, Tatijana %A Pennell, Craig E %A Nyberg, Fredrik %A Kuh, Diana %A Holloway, John W %A Boezen, H Marike %A Lawlor, Debbie A %A Morris, Richard W %A Probst-Hensch, Nicole %A Kaprio, Jaakko %A Wilson, James F %A Hayward, Caroline %A Kähönen, Mika %A Heinrich, Joachim %A Musk, Arthur W %A Jarvis, Deborah L %A Gläser, Sven %A Jarvelin, Marjo-Riitta %A Ch Stricker, Bruno H %A Elliott, Paul %A O'Connor, George T %A Strachan, David P %A London, Stephanie J %A Hall, Ian P %A Gudnason, Vilmundur %A Tobin, Martin D %K Child %K European Continental Ancestry Group %K Genome-Wide Association Study %K Humans %K Pulmonary Disease, Chronic Obstructive %K Respiratory Function Tests %X

Pulmonary function measures reflect respiratory health and are used in the diagnosis of chronic obstructive pulmonary disease. We tested genome-wide association with forced expiratory volume in 1 second and the ratio of forced expiratory volume in 1 second to forced vital capacity in 48,201 individuals of European ancestry with follow up of the top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P < 5 × 10(-8)) with pulmonary function in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (also known as EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1 and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.

%B Nat Genet %V 43 %P 1082-90 %8 2011 Sep 25 %G eng %N 11 %1 http://www.ncbi.nlm.nih.gov/pubmed/21946350?dopt=Abstract %R 10.1038/ng.941 %0 Journal Article %J Am J Respir Crit Care Med %D 2012 %T Genome-wide association studies identify CHRNA5/3 and HTR4 in the development of airflow obstruction. %A Wilk, Jemma B %A Shrine, Nick R G %A Loehr, Laura R %A Zhao, Jing Hua %A Manichaikul, Ani %A Lopez, Lorna M %A Smith, Albert Vernon %A Heckbert, Susan R %A Smolonska, Joanna %A Tang, Wenbo %A Loth, Daan W %A Curjuric, Ivan %A Hui, Jennie %A Cho, Michael H %A Latourelle, Jeanne C %A Henry, Amanda P %A Aldrich, Melinda %A Bakke, Per %A Beaty, Terri H %A Bentley, Amy R %A Borecki, Ingrid B %A Brusselle, Guy G %A Burkart, Kristin M %A Chen, Ting-Hsu %A Couper, David %A Crapo, James D %A Davies, Gail %A Dupuis, Josée %A Franceschini, Nora %A Gulsvik, Amund %A Hancock, Dana B %A Harris, Tamara B %A Hofman, Albert %A Imboden, Medea %A James, Alan L %A Khaw, Kay-Tee %A Lahousse, Lies %A Launer, Lenore J %A Litonjua, Augusto %A Liu, Yongmei %A Lohman, Kurt K %A Lomas, David A %A Lumley, Thomas %A Marciante, Kristin D %A McArdle, Wendy L %A Meibohm, Bernd %A Morrison, Alanna C %A Musk, Arthur W %A Myers, Richard H %A North, Kari E %A Postma, Dirkje S %A Psaty, Bruce M %A Rich, Stephen S %A Rivadeneira, Fernando %A Rochat, Thierry %A Rotter, Jerome I %A Soler Artigas, Maria %A Starr, John M %A Uitterlinden, André G %A Wareham, Nicholas J %A Wijmenga, Cisca %A Zanen, Pieter %A Province, Michael A %A Silverman, Edwin K %A Deary, Ian J %A Palmer, Lyle J %A Cassano, Patricia A %A Gudnason, Vilmundur %A Barr, R Graham %A Loos, Ruth J F %A Strachan, David P %A London, Stephanie J %A Boezen, H Marike %A Probst-Hensch, Nicole %A Gharib, Sina A %A Hall, Ian P %A O'Connor, George T %A Tobin, Martin D %A Stricker, Bruno H %K Aged %K Female %K Forced Expiratory Volume %K Genome-Wide Association Study %K Humans %K Male %K Middle Aged %K Nerve Tissue Proteins %K Polymorphism, Single Nucleotide %K Pulmonary Disease, Chronic Obstructive %K Receptors, Nicotinic %K Receptors, Serotonin, 5-HT4 %K Smoking %K Vital Capacity %X

RATIONALE: Genome-wide association studies (GWAS) have identified loci influencing lung function, but fewer genes influencing chronic obstructive pulmonary disease (COPD) are known.

OBJECTIVES: Perform meta-analyses of GWAS for airflow obstruction, a key pathophysiologic characteristic of COPD assessed by spirometry, in population-based cohorts examining all participants, ever smokers, never smokers, asthma-free participants, and more severe cases.

METHODS: Fifteen cohorts were studied for discovery (3,368 affected; 29,507 unaffected), and a population-based family study and a meta-analysis of case-control studies were used for replication and regional follow-up (3,837 cases; 4,479 control subjects). Airflow obstruction was defined as FEV(1) and its ratio to FVC (FEV(1)/FVC) both less than their respective lower limits of normal as determined by published reference equations.

MEASUREMENTS AND MAIN RESULTS: The discovery meta-analyses identified one region on chromosome 15q25.1 meeting genome-wide significance in ever smokers that includes AGPHD1, IREB2, and CHRNA5/CHRNA3 genes. The region was also modestly associated among never smokers. Gene expression studies confirmed the presence of CHRNA5/3 in lung, airway smooth muscle, and bronchial epithelial cells. A single-nucleotide polymorphism in HTR4, a gene previously related to FEV(1)/FVC, achieved genome-wide statistical significance in combined meta-analysis. Top single-nucleotide polymorphisms in ADAM19, RARB, PPAP2B, and ADAMTS19 were nominally replicated in the COPD meta-analysis.

CONCLUSIONS: These results suggest an important role for the CHRNA5/3 region as a genetic risk factor for airflow obstruction that may be independent of smoking and implicate the HTR4 gene in the etiology of airflow obstruction.

%B Am J Respir Crit Care Med %V 186 %P 622-32 %8 2012 Oct 01 %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/22837378?dopt=Abstract %R 10.1164/rccm.201202-0366OC %0 Journal Article %J PLoS Genet %D 2012 %T Genome-wide joint meta-analysis of SNP and SNP-by-smoking interaction identifies novel loci for pulmonary function. %A Hancock, Dana B %A Soler Artigas, Maria %A Gharib, Sina A %A Henry, Amanda %A Manichaikul, Ani %A Ramasamy, Adaikalavan %A Loth, Daan W %A Imboden, Medea %A Koch, Beate %A McArdle, Wendy L %A Smith, Albert V %A Smolonska, Joanna %A Sood, Akshay %A Tang, Wenbo %A Wilk, Jemma B %A Zhai, Guangju %A Zhao, Jing Hua %A Aschard, Hugues %A Burkart, Kristin M %A Curjuric, Ivan %A Eijgelsheim, Mark %A Elliott, Paul %A Gu, Xiangjun %A Harris, Tamara B %A Janson, Christer %A Homuth, Georg %A Hysi, Pirro G %A Liu, Jason Z %A Loehr, Laura R %A Lohman, Kurt %A Loos, Ruth J F %A Manning, Alisa K %A Marciante, Kristin D %A Obeidat, Ma'en %A Postma, Dirkje S %A Aldrich, Melinda C %A Brusselle, Guy G %A Chen, Ting-Hsu %A Eiriksdottir, Gudny %A Franceschini, Nora %A Heinrich, Joachim %A Rotter, Jerome I %A Wijmenga, Cisca %A Williams, O Dale %A Bentley, Amy R %A Hofman, Albert %A Laurie, Cathy C %A Lumley, Thomas %A Morrison, Alanna C %A Joubert, Bonnie R %A Rivadeneira, Fernando %A Couper, David J %A Kritchevsky, Stephen B %A Liu, Yongmei %A Wjst, Matthias %A Wain, Louise V %A Vonk, Judith M %A Uitterlinden, André G %A Rochat, Thierry %A Rich, Stephen S %A Psaty, Bruce M %A O'Connor, George T %A North, Kari E %A Mirel, Daniel B %A Meibohm, Bernd %A Launer, Lenore J %A Khaw, Kay-Tee %A Hartikainen, Anna-Liisa %A Hammond, Christopher J %A Gläser, Sven %A Marchini, Jonathan %A Kraft, Peter %A Wareham, Nicholas J %A Völzke, Henry %A Stricker, Bruno H C %A Spector, Timothy D %A Probst-Hensch, Nicole M %A Jarvis, Deborah %A Jarvelin, Marjo-Riitta %A Heckbert, Susan R %A Gudnason, Vilmundur %A Boezen, H Marike %A Barr, R Graham %A Cassano, Patricia A %A Strachan, David P %A Fornage, Myriam %A Hall, Ian P %A Dupuis, Josée %A Tobin, Martin D %A London, Stephanie J %K Forced Expiratory Volume %K Gene Expression %K Genome, Human %K Genome-Wide Association Study %K HLA-DQ Antigens %K HLA-DQ beta-Chains %K Humans %K Lung %K Nerve Tissue Proteins %K Polymorphism, Single Nucleotide %K Potassium Channels, Inwardly Rectifying %K Pulmonary Disease, Chronic Obstructive %K Receptors, Cell Surface %K Smoking %K SOX9 Transcription Factor %K Vital Capacity %X

Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV(1)), and its ratio to forced vital capacity (FEV(1)/FVC). Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA) of single nucleotide polymorphism (SNP) and SNP-by-smoking (ever-smoking or pack-years) associations on FEV(1) and FEV(1)/FVC across 19 studies (total N = 50,047). We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest P(JMA = )5.00×10(-11)), HLA-DQB1 and HLA-DQA2 (smallest P(JMA = )4.35×10(-9)), and KCNJ2 and SOX9 (smallest P(JMA = )1.28×10(-8)) were associated with FEV(1)/FVC or FEV(1) in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years) interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.

%B PLoS Genet %V 8 %P e1003098 %8 2012 %G eng %N 12 %1 http://www.ncbi.nlm.nih.gov/pubmed/23284291?dopt=Abstract %R 10.1371/journal.pgen.1003098 %0 Journal Article %J PLoS One %D 2012 %T Multi-ethnic analysis of lipid-associated loci: the NHLBI CARe project. %A Musunuru, Kiran %A Romaine, Simon P R %A Lettre, Guillaume %A Wilson, James G %A Volcik, Kelly A %A Tsai, Michael Y %A Taylor, Herman A %A Schreiner, Pamela J %A Rotter, Jerome I %A Rich, Stephen S %A Redline, Susan %A Psaty, Bruce M %A Papanicolaou, George J %A Ordovas, Jose M %A Liu, Kiang %A Krauss, Ronald M %A Glazer, Nicole L %A Gabriel, Stacey B %A Fornage, Myriam %A Cupples, L Adrienne %A Buxbaum, Sarah G %A Boerwinkle, Eric %A Ballantyne, Christie M %A Kathiresan, Sekar %A Rader, Daniel J %K African Americans %K Cholesterol, HDL %K Cholesterol, LDL %K European Continental Ancestry Group %K Genetic Association Studies %K Genetic Loci %K Humans %K Polymorphism, Single Nucleotide %K Triglycerides %X

BACKGROUND: Whereas it is well established that plasma lipid levels have substantial heritability within populations, it remains unclear how many of the genetic determinants reported in previous studies (largely performed in European American cohorts) are relevant in different ethnicities.

METHODOLOGY/PRINCIPAL FINDINGS: We tested a set of ∼50,000 polymorphisms from ∼2,000 candidate genes and genetic loci from genome-wide association studies (GWAS) for association with low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) in 25,000 European Americans and 9,000 African Americans in the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe). We replicated associations for a number of genes in one or both ethnicities and identified a novel lipid-associated variant in a locus harboring ICAM1. We compared the architecture of genetic loci associated with lipids in both African Americans and European Americans and found that the same genes were relevant across ethnic groups but the specific associated variants at each gene often differed.

CONCLUSIONS/SIGNIFICANCE: We identify or provide further evidence for a number of genetic determinants of plasma lipid levels through population association studies. In many loci the determinants appear to differ substantially between African Americans and European Americans.

%B PLoS One %V 7 %P e36473 %8 2012 %G eng %N 5 %1 http://www.ncbi.nlm.nih.gov/pubmed/22629316?dopt=Abstract %R 10.1371/journal.pone.0036473 %0 Journal Article %J PLoS One %D 2013 %T Best practices and joint calling of the HumanExome BeadChip: the CHARGE Consortium. %A Grove, Megan L %A Yu, Bing %A Cochran, Barbara J %A Haritunians, Talin %A Bis, Joshua C %A Taylor, Kent D %A Hansen, Mark %A Borecki, Ingrid B %A Cupples, L Adrienne %A Fornage, Myriam %A Gudnason, Vilmundur %A Harris, Tamara B %A Kathiresan, Sekar %A Kraaij, Robert %A Launer, Lenore J %A Levy, Daniel %A Liu, Yongmei %A Mosley, Thomas %A Peloso, Gina M %A Psaty, Bruce M %A Rich, Stephen S %A Rivadeneira, Fernando %A Siscovick, David S %A Smith, Albert V %A Uitterlinden, Andre %A van Duijn, Cornelia M %A Wilson, James G %A O'Donnell, Christopher J %A Rotter, Jerome I %A Boerwinkle, Eric %K Aging %K Alleles %K Cluster Analysis %K Cohort Studies %K Continental Population Groups %K Exome %K Female %K Gene Frequency %K Genomics %K Genotype %K Heart %K Humans %K Male %K Oligonucleotide Array Sequence Analysis %K Polymorphism, Single Nucleotide %K Sample Size %K Self Report %K Sequence Analysis, DNA %X

Genotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleven Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium cohorts were genotyped with the Illumina HumanExome BeadChip across seven genotyping centers. The raw data files for the samples were assembled into a single project for joint calling. To assess the quality of the joint calling, concordance of genotypes in a subset of individuals having both exome chip and exome sequence data was analyzed. After exclusion of low performing SNPs on the exome chip and non-overlap of SNPs derived from sequence data, genotypes of 185,119 variants (11,356 were monomorphic) were compared in 530 individuals that had whole exome sequence data. A total of 98,113,070 pairs of genotypes were tested and 99.77% were concordant, 0.14% had missing data, and 0.09% were discordant. We report that joint calling allows the ability to accurately genotype rare variation using array technology when large sample sizes are available and best practices are followed. The cluster file from this experiment is available at www.chargeconsortium.com/main/exomechip.

%B PLoS One %V 8 %P e68095 %8 2013 %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/23874508?dopt=Abstract %R 10.1371/journal.pone.0068095 %0 Journal Article %J Nat Genet %D 2013 %T Common variants associated with plasma triglycerides and risk for coronary artery disease. %A Do, Ron %A Willer, Cristen J %A Schmidt, Ellen M %A Sengupta, Sebanti %A Gao, Chi %A Peloso, Gina M %A Gustafsson, Stefan %A Kanoni, Stavroula %A Ganna, Andrea %A Chen, Jin %A Buchkovich, Martin L %A Mora, Samia %A Beckmann, Jacques S %A Bragg-Gresham, Jennifer L %A Chang, Hsing-Yi %A Demirkan, Ayse %A Den Hertog, Heleen M %A Donnelly, Louise A %A Ehret, Georg B %A Esko, Tõnu %A Feitosa, Mary F %A Ferreira, Teresa %A Fischer, Krista %A Fontanillas, Pierre %A Fraser, Ross M %A Freitag, Daniel F %A Gurdasani, Deepti %A Heikkilä, Kauko %A Hyppönen, Elina %A Isaacs, Aaron %A Jackson, Anne U %A Johansson, Asa %A Johnson, Toby %A Kaakinen, Marika %A Kettunen, Johannes %A Kleber, Marcus E %A Li, Xiaohui %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Magnusson, Patrik K E %A Mangino, Massimo %A Mihailov, Evelin %A Montasser, May E %A Müller-Nurasyid, Martina %A Nolte, Ilja M %A O'Connell, Jeffrey R %A Palmer, Cameron D %A Perola, Markus %A Petersen, Ann-Kristin %A Sanna, Serena %A Saxena, Richa %A Service, Susan K %A Shah, Sonia %A Shungin, Dmitry %A Sidore, Carlo %A Song, Ci %A Strawbridge, Rona J %A Surakka, Ida %A Tanaka, Toshiko %A Teslovich, Tanya M %A Thorleifsson, Gudmar %A van den Herik, Evita G %A Voight, Benjamin F %A Volcik, Kelly A %A Waite, Lindsay L %A Wong, Andrew %A Wu, Ying %A Zhang, Weihua %A Absher, Devin %A Asiki, Gershim %A Barroso, Inês %A Been, Latonya F %A Bolton, Jennifer L %A Bonnycastle, Lori L %A Brambilla, Paolo %A Burnett, Mary S %A Cesana, Giancarlo %A Dimitriou, Maria %A Doney, Alex S F %A Döring, Angela %A Elliott, Paul %A Epstein, Stephen E %A Eyjolfsson, Gudmundur Ingi %A Gigante, Bruna %A Goodarzi, Mark O %A Grallert, Harald %A Gravito, Martha L %A Groves, Christopher J %A Hallmans, Göran %A Hartikainen, Anna-Liisa %A Hayward, Caroline %A Hernandez, Dena %A Hicks, Andrew A %A Holm, Hilma %A Hung, Yi-Jen %A Illig, Thomas %A Jones, Michelle R %A Kaleebu, Pontiano %A Kastelein, John J P %A Khaw, Kay-Tee %A Kim, Eric %A Klopp, Norman %A Komulainen, Pirjo %A Kumari, Meena %A Langenberg, Claudia %A Lehtimäki, Terho %A Lin, Shih-Yi %A Lindström, Jaana %A Loos, Ruth J F %A Mach, François %A McArdle, Wendy L %A Meisinger, Christa %A Mitchell, Braxton D %A Müller, Gabrielle %A Nagaraja, Ramaiah %A Narisu, Narisu %A Nieminen, Tuomo V M %A Nsubuga, Rebecca N %A Olafsson, Isleifur %A Ong, Ken K %A Palotie, Aarno %A Papamarkou, Theodore %A Pomilla, Cristina %A Pouta, Anneli %A Rader, Daniel J %A Reilly, Muredach P %A Ridker, Paul M %A Rivadeneira, Fernando %A Rudan, Igor %A Ruokonen, Aimo %A Samani, Nilesh %A Scharnagl, Hubert %A Seeley, Janet %A Silander, Kaisa %A Stančáková, Alena %A Stirrups, Kathleen %A Swift, Amy J %A Tiret, Laurence %A Uitterlinden, André G %A van Pelt, L Joost %A Vedantam, Sailaja %A Wainwright, Nicholas %A Wijmenga, Cisca %A Wild, Sarah H %A Willemsen, Gonneke %A Wilsgaard, Tom %A Wilson, James F %A Young, Elizabeth H %A Zhao, Jing Hua %A Adair, Linda S %A Arveiler, Dominique %A Assimes, Themistocles L %A Bandinelli, Stefania %A Bennett, Franklyn %A Bochud, Murielle %A Boehm, Bernhard O %A Boomsma, Dorret I %A Borecki, Ingrid B %A Bornstein, Stefan R %A Bovet, Pascal %A Burnier, Michel %A Campbell, Harry %A Chakravarti, Aravinda %A Chambers, John C %A Chen, Yii-Der Ida %A Collins, Francis S %A Cooper, Richard S %A Danesh, John %A Dedoussis, George %A de Faire, Ulf %A Feranil, Alan B %A Ferrieres, Jean %A Ferrucci, Luigi %A Freimer, Nelson B %A Gieger, Christian %A Groop, Leif C %A Gudnason, Vilmundur %A Gyllensten, Ulf %A Hamsten, Anders %A Harris, Tamara B %A Hingorani, Aroon %A Hirschhorn, Joel N %A Hofman, Albert %A Hovingh, G Kees %A Hsiung, Chao Agnes %A Humphries, Steve E %A Hunt, Steven C %A Hveem, Kristian %A Iribarren, Carlos %A Jarvelin, Marjo-Riitta %A Jula, Antti %A Kähönen, Mika %A Kaprio, Jaakko %A Kesäniemi, Antero %A Kivimaki, Mika %A Kooner, Jaspal S %A Koudstaal, Peter J %A Krauss, Ronald M %A Kuh, Diana %A Kuusisto, Johanna %A Kyvik, Kirsten O %A Laakso, Markku %A Lakka, Timo A %A Lind, Lars %A Lindgren, Cecilia M %A Martin, Nicholas G %A März, Winfried %A McCarthy, Mark I %A McKenzie, Colin A %A Meneton, Pierre %A Metspalu, Andres %A Moilanen, Leena %A Morris, Andrew D %A Munroe, Patricia B %A Njølstad, Inger %A Pedersen, Nancy L %A Power, Chris %A Pramstaller, Peter P %A Price, Jackie F %A Psaty, Bruce M %A Quertermous, Thomas %A Rauramaa, Rainer %A Saleheen, Danish %A Salomaa, Veikko %A Sanghera, Dharambir K %A Saramies, Jouko %A Schwarz, Peter E H %A Sheu, Wayne H-H %A Shuldiner, Alan R %A Siegbahn, Agneta %A Spector, Tim D %A Stefansson, Kari %A Strachan, David P %A Tayo, Bamidele O %A Tremoli, Elena %A Tuomilehto, Jaakko %A Uusitupa, Matti %A van Duijn, Cornelia M %A Vollenweider, Peter %A Wallentin, Lars %A Wareham, Nicholas J %A Whitfield, John B %A Wolffenbuttel, Bruce H R %A Altshuler, David %A Ordovas, Jose M %A Boerwinkle, Eric %A Palmer, Colin N A %A Thorsteinsdottir, Unnur %A Chasman, Daniel I %A Rotter, Jerome I %A Franks, Paul W %A Ripatti, Samuli %A Cupples, L Adrienne %A Sandhu, Manjinder S %A Rich, Stephen S %A Boehnke, Michael %A Deloukas, Panos %A Mohlke, Karen L %A Ingelsson, Erik %A Abecasis, Goncalo R %A Daly, Mark J %A Neale, Benjamin M %A Kathiresan, Sekar %K Biological Transport %K Cholesterol, HDL %K Cholesterol, LDL %K Coronary Artery Disease %K Humans %K Polymorphism, Single Nucleotide %K Risk Factors %K Triglycerides %X

Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

%B Nat Genet %V 45 %P 1345-52 %8 2013 Nov %G eng %N 11 %R 10.1038/ng.2795 %0 Journal Article %J Nat Genet %D 2013 %T Discovery and refinement of loci associated with lipid levels. %A Willer, Cristen J %A Schmidt, Ellen M %A Sengupta, Sebanti %A Peloso, Gina M %A Gustafsson, Stefan %A Kanoni, Stavroula %A Ganna, Andrea %A Chen, Jin %A Buchkovich, Martin L %A Mora, Samia %A Beckmann, Jacques S %A Bragg-Gresham, Jennifer L %A Chang, Hsing-Yi %A Demirkan, Ayse %A Den Hertog, Heleen M %A Do, Ron %A Donnelly, Louise A %A Ehret, Georg B %A Esko, Tõnu %A Feitosa, Mary F %A Ferreira, Teresa %A Fischer, Krista %A Fontanillas, Pierre %A Fraser, Ross M %A Freitag, Daniel F %A Gurdasani, Deepti %A Heikkilä, Kauko %A Hyppönen, Elina %A Isaacs, Aaron %A Jackson, Anne U %A Johansson, Asa %A Johnson, Toby %A Kaakinen, Marika %A Kettunen, Johannes %A Kleber, Marcus E %A Li, Xiaohui %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Magnusson, Patrik K E %A Mangino, Massimo %A Mihailov, Evelin %A Montasser, May E %A Müller-Nurasyid, Martina %A Nolte, Ilja M %A O'Connell, Jeffrey R %A Palmer, Cameron D %A Perola, Markus %A Petersen, Ann-Kristin %A Sanna, Serena %A Saxena, Richa %A Service, Susan K %A Shah, Sonia %A Shungin, Dmitry %A Sidore, Carlo %A Song, Ci %A Strawbridge, Rona J %A Surakka, Ida %A Tanaka, Toshiko %A Teslovich, Tanya M %A Thorleifsson, Gudmar %A van den Herik, Evita G %A Voight, Benjamin F %A Volcik, Kelly A %A Waite, Lindsay L %A Wong, Andrew %A Wu, Ying %A Zhang, Weihua %A Absher, Devin %A Asiki, Gershim %A Barroso, Inês %A Been, Latonya F %A Bolton, Jennifer L %A Bonnycastle, Lori L %A Brambilla, Paolo %A Burnett, Mary S %A Cesana, Giancarlo %A Dimitriou, Maria %A Doney, Alex S F %A Döring, Angela %A Elliott, Paul %A Epstein, Stephen E %A Ingi Eyjolfsson, Gudmundur %A Gigante, Bruna %A Goodarzi, Mark O %A Grallert, Harald %A Gravito, Martha L %A Groves, Christopher J %A Hallmans, Göran %A Hartikainen, Anna-Liisa %A Hayward, Caroline %A Hernandez, Dena %A Hicks, Andrew A %A Holm, Hilma %A Hung, Yi-Jen %A Illig, Thomas %A Jones, Michelle R %A Kaleebu, Pontiano %A Kastelein, John J P %A Khaw, Kay-Tee %A Kim, Eric %A Klopp, Norman %A Komulainen, Pirjo %A Kumari, Meena %A Langenberg, Claudia %A Lehtimäki, Terho %A Lin, Shih-Yi %A Lindström, Jaana %A Loos, Ruth J F %A Mach, François %A McArdle, Wendy L %A Meisinger, Christa %A Mitchell, Braxton D %A Müller, Gabrielle %A Nagaraja, Ramaiah %A Narisu, Narisu %A Nieminen, Tuomo V M %A Nsubuga, Rebecca N %A Olafsson, Isleifur %A Ong, Ken K %A Palotie, Aarno %A Papamarkou, Theodore %A Pomilla, Cristina %A Pouta, Anneli %A Rader, Daniel J %A Reilly, Muredach P %A Ridker, Paul M %A Rivadeneira, Fernando %A Rudan, Igor %A Ruokonen, Aimo %A Samani, Nilesh %A Scharnagl, Hubert %A Seeley, Janet %A Silander, Kaisa %A Stančáková, Alena %A Stirrups, Kathleen %A Swift, Amy J %A Tiret, Laurence %A Uitterlinden, André G %A van Pelt, L Joost %A Vedantam, Sailaja %A Wainwright, Nicholas %A Wijmenga, Cisca %A Wild, Sarah H %A Willemsen, Gonneke %A Wilsgaard, Tom %A Wilson, James F %A Young, Elizabeth H %A Zhao, Jing Hua %A Adair, Linda S %A Arveiler, Dominique %A Assimes, Themistocles L %A Bandinelli, Stefania %A Bennett, Franklyn %A Bochud, Murielle %A Boehm, Bernhard O %A Boomsma, Dorret I %A Borecki, Ingrid B %A Bornstein, Stefan R %A Bovet, Pascal %A Burnier, Michel %A Campbell, Harry %A Chakravarti, Aravinda %A Chambers, John C %A Chen, Yii-Der Ida %A Collins, Francis S %A Cooper, Richard S %A Danesh, John %A Dedoussis, George %A de Faire, Ulf %A Feranil, Alan B %A Ferrieres, Jean %A Ferrucci, Luigi %A Freimer, Nelson B %A Gieger, Christian %A Groop, Leif C %A Gudnason, Vilmundur %A Gyllensten, Ulf %A Hamsten, Anders %A Harris, Tamara B %A Hingorani, Aroon %A Hirschhorn, Joel N %A Hofman, Albert %A Hovingh, G Kees %A Hsiung, Chao Agnes %A Humphries, Steve E %A Hunt, Steven C %A Hveem, Kristian %A Iribarren, Carlos %A Jarvelin, Marjo-Riitta %A Jula, Antti %A Kähönen, Mika %A Kaprio, Jaakko %A Kesäniemi, Antero %A Kivimaki, Mika %A Kooner, Jaspal S %A Koudstaal, Peter J %A Krauss, Ronald M %A Kuh, Diana %A Kuusisto, Johanna %A Kyvik, Kirsten O %A Laakso, Markku %A Lakka, Timo A %A Lind, Lars %A Lindgren, Cecilia M %A Martin, Nicholas G %A März, Winfried %A McCarthy, Mark I %A McKenzie, Colin A %A Meneton, Pierre %A Metspalu, Andres %A Moilanen, Leena %A Morris, Andrew D %A Munroe, Patricia B %A Njølstad, Inger %A Pedersen, Nancy L %A Power, Chris %A Pramstaller, Peter P %A Price, Jackie F %A Psaty, Bruce M %A Quertermous, Thomas %A Rauramaa, Rainer %A Saleheen, Danish %A Salomaa, Veikko %A Sanghera, Dharambir K %A Saramies, Jouko %A Schwarz, Peter E H %A Sheu, Wayne H-H %A Shuldiner, Alan R %A Siegbahn, Agneta %A Spector, Tim D %A Stefansson, Kari %A Strachan, David P %A Tayo, Bamidele O %A Tremoli, Elena %A Tuomilehto, Jaakko %A Uusitupa, Matti %A van Duijn, Cornelia M %A Vollenweider, Peter %A Wallentin, Lars %A Wareham, Nicholas J %A Whitfield, John B %A Wolffenbuttel, Bruce H R %A Ordovas, Jose M %A Boerwinkle, Eric %A Palmer, Colin N A %A Thorsteinsdottir, Unnur %A Chasman, Daniel I %A Rotter, Jerome I %A Franks, Paul W %A Ripatti, Samuli %A Cupples, L Adrienne %A Sandhu, Manjinder S %A Rich, Stephen S %A Boehnke, Michael %A Deloukas, Panos %A Kathiresan, Sekar %A Mohlke, Karen L %A Ingelsson, Erik %A Abecasis, Goncalo R %K African Continental Ancestry Group %K Asian Continental Ancestry Group %K Cholesterol, HDL %K Cholesterol, LDL %K Coronary Artery Disease %K European Continental Ancestry Group %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genotype %K Humans %K Lipids %K Triglycerides %X

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

%B Nat Genet %V 45 %P 1274-1283 %8 2013 Nov %G eng %N 11 %1 http://www.ncbi.nlm.nih.gov/pubmed/24097068?dopt=Abstract %R 10.1038/ng.2797 %0 Journal Article %J Circ Cardiovasc Genet %D 2013 %T Genome-wide association study identifies novel loci associated with concentrations of four plasma phospholipid fatty acids in the de novo lipogenesis pathway: results from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortiu %A Wu, Jason H Y %A Lemaitre, Rozenn N %A Manichaikul, Ani %A Guan, Weihua %A Tanaka, Toshiko %A Foy, Millennia %A Kabagambe, Edmond K %A Djoussé, Luc %A Siscovick, David %A Fretts, Amanda M %A Johnson, Catherine %A King, Irena B %A Psaty, Bruce M %A McKnight, Barbara %A Rich, Stephen S %A Chen, Yii-der I %A Nettleton, Jennifer A %A Tang, Weihong %A Bandinelli, Stefania %A Jacobs, David R %A Browning, Brian L %A Laurie, Cathy C %A Gu, Xiangjun %A Tsai, Michael Y %A Steffen, Lyn M %A Ferrucci, Luigi %A Fornage, Myriam %A Mozaffarian, Dariush %K Adult %K Aged %K Chromosomes, Human, Pair 2 %K Cohort Studies %K Coronary Disease %K Diabetes Mellitus, Type 2 %K Fatty Acids, Monounsaturated %K Female %K Genetic Loci %K Genome-Wide Association Study %K Genotype %K Humans %K Linkage Disequilibrium %K Lipogenesis %K Male %K Middle Aged %K Oleic Acid %K Palmitic Acid %K Polymorphism, Single Nucleotide %K Stearic Acids %X

BACKGROUND- Palmitic acid (16:0), stearic acid (18:0), palmitoleic acid (16:1n-7), and oleic acid (18:1n-9) are major saturated and monounsaturated fatty acids that affect cellular signaling and metabolic pathways. They are synthesized via de novo lipogenesis and are the main saturated and monounsaturated fatty acids in the diet. Levels of these fatty acids have been linked to diseases including type 2 diabetes mellitus and coronary heart disease. METHODS AND RESULTS- Genome-wide association studies were conducted in 5 population-based cohorts comprising 8961 participants of European ancestry to investigate the association of common genetic variation with plasma levels of these 4 fatty acids. We identified polymorphisms in 7 novel loci associated with circulating levels of ≥1 of these fatty acids. ALG14 (asparagine-linked glycosylation 14 homolog) polymorphisms were associated with higher 16:0 (P=2.7×10(-11)) and lower 18:0 (P=2.2×10(-18)). FADS1 and FADS2 (desaturases) polymorphisms were associated with higher 16:1n-7 (P=6.6×10(-13)) and 18:1n-9 (P=2.2×10(-32)) and lower 18:0 (P=1.3×10(-20)). LPGAT1 (lysophosphatidylglycerol acyltransferase) polymorphisms were associated with lower 18:0 (P=2.8×10(-9)). GCKR (glucokinase regulator; P=9.8×10(-10)) and HIF1AN (factor inhibiting hypoxia-inducible factor-1; P=5.7×10(-9)) polymorphisms were associated with higher 16:1n-7, whereas PKD2L1 (polycystic kidney disease 2-like 1; P=5.7×10(-15)) and a locus on chromosome 2 (not near known genes) were associated with lower 16:1n-7 (P=4.1×10(-8)). CONCLUSIONS- Our findings provide novel evidence that common variations in genes with diverse functions, including protein-glycosylation, polyunsaturated fatty acid metabolism, phospholipid modeling, and glucose- and oxygen-sensing pathways, are associated with circulating levels of 4 fatty acids in the de novo lipogenesis pathway. These results expand our knowledge of genetic factors relevant to de novo lipogenesis and fatty acid biology.

%B Circ Cardiovasc Genet %V 6 %P 171-83 %8 2013 Apr %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/23362303?dopt=Abstract %R 10.1161/CIRCGENETICS.112.964619 %0 Journal Article %J Am J Hum Genet %D 2014 %T Association of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks. %A Peloso, Gina M %A Auer, Paul L %A Bis, Joshua C %A Voorman, Arend %A Morrison, Alanna C %A Stitziel, Nathan O %A Brody, Jennifer A %A Khetarpal, Sumeet A %A Crosby, Jacy R %A Fornage, Myriam %A Isaacs, Aaron %A Jakobsdottir, Johanna %A Feitosa, Mary F %A Davies, Gail %A Huffman, Jennifer E %A Manichaikul, Ani %A Davis, Brian %A Lohman, Kurt %A Joon, Aron Y %A Smith, Albert V %A Grove, Megan L %A Zanoni, Paolo %A Redon, Valeska %A Demissie, Serkalem %A Lawson, Kim %A Peters, Ulrike %A Carlson, Christopher %A Jackson, Rebecca D %A Ryckman, Kelli K %A Mackey, Rachel H %A Robinson, Jennifer G %A Siscovick, David S %A Schreiner, Pamela J %A Mychaleckyj, Josyf C %A Pankow, James S %A Hofman, Albert %A Uitterlinden, André G %A Harris, Tamara B %A Taylor, Kent D %A Stafford, Jeanette M %A Reynolds, Lindsay M %A Marioni, Riccardo E %A Dehghan, Abbas %A Franco, Oscar H %A Patel, Aniruddh P %A Lu, Yingchang %A Hindy, George %A Gottesman, Omri %A Bottinger, Erwin P %A Melander, Olle %A Orho-Melander, Marju %A Loos, Ruth J F %A Duga, Stefano %A Merlini, Piera Angelica %A Farrall, Martin %A Goel, Anuj %A Asselta, Rosanna %A Girelli, Domenico %A Martinelli, Nicola %A Shah, Svati H %A Kraus, William E %A Li, Mingyao %A Rader, Daniel J %A Reilly, Muredach P %A McPherson, Ruth %A Watkins, Hugh %A Ardissino, Diego %A Zhang, Qunyuan %A Wang, Judy %A Tsai, Michael Y %A Taylor, Herman A %A Correa, Adolfo %A Griswold, Michael E %A Lange, Leslie A %A Starr, John M %A Rudan, Igor %A Eiriksdottir, Gudny %A Launer, Lenore J %A Ordovas, Jose M %A Levy, Daniel %A Chen, Y-D Ida %A Reiner, Alexander P %A Hayward, Caroline %A Polasek, Ozren %A Deary, Ian J %A Borecki, Ingrid B %A Liu, Yongmei %A Gudnason, Vilmundur %A Wilson, James G %A van Duijn, Cornelia M %A Kooperberg, Charles %A Rich, Stephen S %A Psaty, Bruce M %A Rotter, Jerome I %A O'Donnell, Christopher J %A Rice, Kenneth %A Boerwinkle, Eric %A Kathiresan, Sekar %A Cupples, L Adrienne %K 1-Alkyl-2-acetylglycerophosphocholine Esterase %K Adult %K African Continental Ancestry Group %K Aged %K Alleles %K Animals %K Cholesterol, HDL %K Cholesterol, LDL %K Cohort Studies %K Coronary Disease %K European Continental Ancestry Group %K Female %K Gene Frequency %K Genetic Association Studies %K Genetic Code %K Genetic Variation %K Humans %K Linear Models %K Male %K Mice %K Mice, Inbred C57BL %K Microtubule-Associated Proteins %K Middle Aged %K Phenotype %K Sequence Analysis, DNA %K Subtilisins %K Triglycerides %X

Low-frequency coding DNA sequence variants in the proprotein convertase subtilisin/kexin type 9 gene (PCSK9) lower plasma low-density lipoprotein cholesterol (LDL-C), protect against risk of coronary heart disease (CHD), and have prompted the development of a new class of therapeutics. It is uncertain whether the PCSK9 example represents a paradigm or an isolated exception. We used the "Exome Array" to genotype >200,000 low-frequency and rare coding sequence variants across the genome in 56,538 individuals (42,208 European ancestry [EA] and 14,330 African ancestry [AA]) and tested these variants for association with LDL-C, high-density lipoprotein cholesterol (HDL-C), and triglycerides. Although we did not identify new genes associated with LDL-C, we did identify four low-frequency (frequencies between 0.1% and 2%) variants (ANGPTL8 rs145464906 [c.361C>T; p.Gln121*], PAFAH1B2 rs186808413 [c.482C>T; p.Ser161Leu], COL18A1 rs114139997 [c.331G>A; p.Gly111Arg], and PCSK7 rs142953140 [c.1511G>A; p.Arg504His]) with large effects on HDL-C and/or triglycerides. None of these four variants was associated with risk for CHD, suggesting that examples of low-frequency coding variants with robust effects on both lipids and CHD will be limited.

%B Am J Hum Genet %V 94 %P 223-32 %8 2014 Feb 06 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/24507774?dopt=Abstract %R 10.1016/j.ajhg.2014.01.009 %0 Journal Article %J Thromb Res %D 2014 %T A genetic association study of D-dimer levels with 50K SNPs from a candidate gene chip in four ethnic groups. %A Weng, Lu-Chen %A Tang, Weihong %A Rich, Stephen S %A Smith, Nicholas L %A Redline, Susan %A O'Donnell, Christopher J %A Basu, Saonli %A Reiner, Alexander P %A Delaney, Joseph A %A Tracy, Russell P %A Palmer, Cameron D %A Young, Taylor %A Yang, Qiong %A Folsom, Aaron R %A Cushman, Mary %K Adult %K Aged %K Cardiovascular Diseases %K Ethnic Groups %K Factor V %K Female %K Fibrin Fibrinogen Degradation Products %K Fibrinogen %K Genetic Association Studies %K Genotype %K Humans %K Male %K Middle Aged %K Oligonucleotide Array Sequence Analysis %K Polymorphism, Single Nucleotide %K Young Adult %X

INTRODUCTION: D-dimer, a fibrin degradation product, is related to risk of cardiovascular disease and venous thromboembolism. Genetic determinants of D-dimer are not well characterized; notably, few data have been reported for African American (AA), Asian, and Hispanic populations.

MATERIALS AND METHODS: We conducted a large-scale candidate gene association study to identify variants in genes associated with D-dimer levels in multi-ethnic populations. Four cohorts, comprising 6,848 European Americans (EAs), 2,192 AAs, 670 Asians, and 1,286 Hispanics in the National Heart, Lung, and Blood Institute Candidate Gene Association Resource consortium, were assembled. Approximately 50,000 genotyped single nucleotide polymorphisms (SNPs) in 2,000 cardiovascular disease gene loci were analyzed by linear regression, adjusting for age, sex, study site, and principal components in each cohort and ethnic group. Results across studies were combined within each ethnic group by meta-analysis.

RESULTS: Twelve SNPs in coagulation factor V (F5) and 3 SNPs in the fibrinogen alpha chain (FGA) were significantly associated with D-dimer level in EAs with p<2.0×10(-6). The signal for the most associated SNP in F5 (rs6025, factor V Leiden) was replicated in Hispanics (p=0.023), while that for the top functional SNP in FGA (rs6050) was replicated in AAs (p=0.006). No additional SNPs were significantly associated with D-dimer.

CONCLUSIONS: Our study replicated previously reported associations of D-dimer with SNPs in F5 and FGA in EAs; we demonstrated replication of the association of D-dimer with FGA rs6050 in AAs and the factor V Leiden variant in Hispanics.

%B Thromb Res %V 134 %P 462-7 %8 2014 Aug %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/24908450?dopt=Abstract %R 10.1016/j.thromres.2014.05.018 %0 Journal Article %J Nat Genet %D 2014 %T Genome-wide association analysis identifies six new loci associated with forced vital capacity. %A Loth, Daan W %A Soler Artigas, Maria %A Gharib, Sina A %A Wain, Louise V %A Franceschini, Nora %A Koch, Beate %A Pottinger, Tess D %A Smith, Albert Vernon %A Duan, Qing %A Oldmeadow, Chris %A Lee, Mi Kyeong %A Strachan, David P %A James, Alan L %A Huffman, Jennifer E %A Vitart, Veronique %A Ramasamy, Adaikalavan %A Wareham, Nicholas J %A Kaprio, Jaakko %A Wang, Xin-Qun %A Trochet, Holly %A Kähönen, Mika %A Flexeder, Claudia %A Albrecht, Eva %A Lopez, Lorna M %A de Jong, Kim %A Thyagarajan, Bharat %A Alves, Alexessander Couto %A Enroth, Stefan %A Omenaas, Ernst %A Joshi, Peter K %A Fall, Tove %A Viñuela, Ana %A Launer, Lenore J %A Loehr, Laura R %A Fornage, Myriam %A Li, Guo %A Wilk, Jemma B %A Tang, Wenbo %A Manichaikul, Ani %A Lahousse, Lies %A Harris, Tamara B %A North, Kari E %A Rudnicka, Alicja R %A Hui, Jennie %A Gu, Xiangjun %A Lumley, Thomas %A Wright, Alan F %A Hastie, Nicholas D %A Campbell, Susan %A Kumar, Rajesh %A Pin, Isabelle %A Scott, Robert A %A Pietiläinen, Kirsi H %A Surakka, Ida %A Liu, Yongmei %A Holliday, Elizabeth G %A Schulz, Holger %A Heinrich, Joachim %A Davies, Gail %A Vonk, Judith M %A Wojczynski, Mary %A Pouta, Anneli %A Johansson, Asa %A Wild, Sarah H %A Ingelsson, Erik %A Rivadeneira, Fernando %A Völzke, Henry %A Hysi, Pirro G %A Eiriksdottir, Gudny %A Morrison, Alanna C %A Rotter, Jerome I %A Gao, Wei %A Postma, Dirkje S %A White, Wendy B %A Rich, Stephen S %A Hofman, Albert %A Aspelund, Thor %A Couper, David %A Smith, Lewis J %A Psaty, Bruce M %A Lohman, Kurt %A Burchard, Esteban G %A Uitterlinden, André G %A Garcia, Melissa %A Joubert, Bonnie R %A McArdle, Wendy L %A Musk, A Bill %A Hansel, Nadia %A Heckbert, Susan R %A Zgaga, Lina %A van Meurs, Joyce B J %A Navarro, Pau %A Rudan, Igor %A Oh, Yeon-Mok %A Redline, Susan %A Jarvis, Deborah L %A Zhao, Jing Hua %A Rantanen, Taina %A O'Connor, George T %A Ripatti, Samuli %A Scott, Rodney J %A Karrasch, Stefan %A Grallert, Harald %A Gaddis, Nathan C %A Starr, John M %A Wijmenga, Cisca %A Minster, Ryan L %A Lederer, David J %A Pekkanen, Juha %A Gyllensten, Ulf %A Campbell, Harry %A Morris, Andrew P %A Gläser, Sven %A Hammond, Christopher J %A Burkart, Kristin M %A Beilby, John %A Kritchevsky, Stephen B %A Gudnason, Vilmundur %A Hancock, Dana B %A Williams, O Dale %A Polasek, Ozren %A Zemunik, Tatijana %A Kolcic, Ivana %A Petrini, Marcy F %A Wjst, Matthias %A Kim, Woo Jin %A Porteous, David J %A Scotland, Generation %A Smith, Blair H %A Viljanen, Anne %A Heliövaara, Markku %A Attia, John R %A Sayers, Ian %A Hampel, Regina %A Gieger, Christian %A Deary, Ian J %A Boezen, H Marike %A Newman, Anne %A Jarvelin, Marjo-Riitta %A Wilson, James F %A Lind, Lars %A Stricker, Bruno H %A Teumer, Alexander %A Spector, Timothy D %A Melén, Erik %A Peters, Marjolein J %A Lange, Leslie A %A Barr, R Graham %A Bracke, Ken R %A Verhamme, Fien M %A Sung, Joohon %A Hiemstra, Pieter S %A Cassano, Patricia A %A Sood, Akshay %A Hayward, Caroline %A Dupuis, Josée %A Hall, Ian P %A Brusselle, Guy G %A Tobin, Martin D %A London, Stephanie J %K Cohort Studies %K Databases, Genetic %K Follow-Up Studies %K Forced Expiratory Volume %K Genetic Loci %K Genetic Predisposition to Disease %K Genome, Human %K Genome-Wide Association Study %K Humans %K Lung Diseases %K Meta-Analysis as Topic %K Polymorphism, Single Nucleotide %K Prognosis %K Quantitative Trait Loci %K Respiratory Function Tests %K Spirometry %K Vital Capacity %X

Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analysis of FVC in 52,253 individuals from 26 studies and followed up the top associations in 32,917 additional individuals of European ancestry. We found six new regions associated at genome-wide significance (P < 5 × 10(-8)) with FVC in or near EFEMP1, BMP6, MIR129-2-HSD17B12, PRDM11, WWOX and KCNJ2. Two loci previously associated with spirometric measures (GSTCD and PTCH1) were related to FVC. Newly implicated regions were followed up in samples from African-American, Korean, Chinese and Hispanic individuals. We detected transcripts for all six newly implicated genes in human lung tissue. The new loci may inform mechanisms involved in lung development and the pathogenesis of restrictive lung disease.

%B Nat Genet %V 46 %P 669-77 %8 2014 Jul %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/24929828?dopt=Abstract %R 10.1038/ng.3011 %0 Journal Article %J Circ Cardiovasc Genet %D 2014 %T Genome-wide association study of plasma N6 polyunsaturated fatty acids within the cohorts for heart and aging research in genomic epidemiology consortium. %A Guan, Weihua %A Steffen, Brian T %A Lemaitre, Rozenn N %A Wu, Jason H Y %A Tanaka, Toshiko %A Manichaikul, Ani %A Foy, Millennia %A Rich, Stephen S %A Wang, Lu %A Nettleton, Jennifer A %A Tang, Weihong %A Gu, Xiangjun %A Bandinelli, Stafania %A King, Irena B %A McKnight, Barbara %A Psaty, Bruce M %A Siscovick, David %A Djoussé, Luc %A Chen, Yii-Der Ida %A Ferrucci, Luigi %A Fornage, Myriam %A Mozafarrian, Dariush %A Tsai, Michael Y %A Steffen, Lyn M %K Adult %K Aged %K Aged, 80 and over %K Aging %K Chromosomes, Human, Pair 10 %K Chromosomes, Human, Pair 16 %K Chromosomes, Human, Pair 6 %K Fatty Acid Desaturases %K Fatty Acids, Omega-6 %K Female %K Genome-Wide Association Study %K Genomics %K Heart Diseases %K Humans %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Prospective Studies %K Sequence Analysis, DNA %X

BACKGROUND: Omega6 (n6) polyunsaturated fatty acids (PUFAs) and their metabolites are involved in cell signaling, inflammation, clot formation, and other crucial biological processes. Genetic components, such as variants of fatty acid desaturase (FADS) genes, determine the composition of n6 PUFAs.

METHODS AND RESULTS: To elucidate undiscovered biological pathways that may influence n6 PUFA composition, we conducted genome-wide association studies and meta-analyses of associations of common genetic variants with 6 plasma n6 PUFAs in 8631 white adults (55% women) across 5 prospective studies. Plasma phospholipid or total plasma fatty acids were analyzed by similar gas chromatography techniques. The n6 fatty acids linoleic acid (LA), γ-linolenic acid (GLA), dihomo-GLA, arachidonic acid, and adrenic acid were expressed as percentage of total fatty acids. We performed linear regression with robust SEs to test for single-nucleotide polymorphism-fatty acid associations, with pooling using inverse-variance-weighted meta-analysis. Novel regions were identified on chromosome 10 associated with LA (rs10740118; P=8.1×10(-9); near NRBF2), on chromosome 16 with LA, GLA, dihomo-GLA, and arachidonic acid (rs16966952; P=1.2×10(-15), 5.0×10(-11), 7.6×10(-65), and 2.4×10(-10), respectively; NTAN1), and on chromosome 6 with adrenic acid after adjustment for arachidonic acid (rs3134950; P=2.1×10(-10); AGPAT1). We confirmed previous findings of the FADS cluster on chromosome 11 with LA and arachidonic acid, and further observed novel genome-wide significant association of this cluster with GLA, dihomo-GLA, and adrenic acid (P=2.3×10(-72), 2.6×10(-151), and 6.3×10(-140), respectively).

CONCLUSIONS: Our findings suggest that along with the FADS gene cluster, additional genes may influence n6 PUFA composition.

%B Circ Cardiovasc Genet %V 7 %P 321-331 %8 2014 Jun %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/24823311?dopt=Abstract %R 10.1161/CIRCGENETICS.113.000208 %0 Journal Article %J N Engl J Med %D 2014 %T Loss-of-function mutations in APOC3, triglycerides, and coronary disease. %A Crosby, Jacy %A Peloso, Gina M %A Auer, Paul L %A Crosslin, David R %A Stitziel, Nathan O %A Lange, Leslie A %A Lu, Yingchang %A Tang, Zheng-Zheng %A Zhang, He %A Hindy, George %A Masca, Nicholas %A Stirrups, Kathleen %A Kanoni, Stavroula %A Do, Ron %A Jun, Goo %A Hu, Youna %A Kang, Hyun Min %A Xue, Chenyi %A Goel, Anuj %A Farrall, Martin %A Duga, Stefano %A Merlini, Pier Angelica %A Asselta, Rosanna %A Girelli, Domenico %A Olivieri, Oliviero %A Martinelli, Nicola %A Yin, Wu %A Reilly, Dermot %A Speliotes, Elizabeth %A Fox, Caroline S %A Hveem, Kristian %A Holmen, Oddgeir L %A Nikpay, Majid %A Farlow, Deborah N %A Assimes, Themistocles L %A Franceschini, Nora %A Robinson, Jennifer %A North, Kari E %A Martin, Lisa W %A DePristo, Mark %A Gupta, Namrata %A Escher, Stefan A %A Jansson, Jan-Håkan %A Van Zuydam, Natalie %A Palmer, Colin N A %A Wareham, Nicholas %A Koch, Werner %A Meitinger, Thomas %A Peters, Annette %A Lieb, Wolfgang %A Erbel, Raimund %A König, Inke R %A Kruppa, Jochen %A Degenhardt, Franziska %A Gottesman, Omri %A Bottinger, Erwin P %A O'Donnell, Christopher J %A Psaty, Bruce M %A Ballantyne, Christie M %A Abecasis, Goncalo %A Ordovas, Jose M %A Melander, Olle %A Watkins, Hugh %A Orho-Melander, Marju %A Ardissino, Diego %A Loos, Ruth J F %A McPherson, Ruth %A Willer, Cristen J %A Erdmann, Jeanette %A Hall, Alistair S %A Samani, Nilesh J %A Deloukas, Panos %A Schunkert, Heribert %A Wilson, James G %A Kooperberg, Charles %A Rich, Stephen S %A Tracy, Russell P %A Lin, Dan-Yu %A Altshuler, David %A Gabriel, Stacey %A Nickerson, Deborah A %A Jarvik, Gail P %A Cupples, L Adrienne %A Reiner, Alex P %A Boerwinkle, Eric %A Kathiresan, Sekar %K African Continental Ancestry Group %K Apolipoprotein C-III %K Coronary Disease %K European Continental Ancestry Group %K Exome %K Genotype %K Heterozygote %K Humans %K Liver %K Mutation %K Risk Factors %K Sequence Analysis, DNA %K Triglycerides %X

BACKGROUND: Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype.

METHODS: We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons.

RESULTS: An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10(-6)).

CONCLUSIONS: Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).

%B N Engl J Med %V 371 %P 22-31 %8 2014 Jul 3 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/24941081?dopt=Abstract %R 10.1056/NEJMoa1307095 %0 Journal Article %J PLoS Genet %D 2014 %T Meta-analysis of genome-wide association studies in African Americans provides insights into the genetic architecture of type 2 diabetes. %A Ng, Maggie C Y %A Shriner, Daniel %A Chen, Brian H %A Li, Jiang %A Chen, Wei-Min %A Guo, Xiuqing %A Liu, Jiankang %A Bielinski, Suzette J %A Yanek, Lisa R %A Nalls, Michael A %A Comeau, Mary E %A Rasmussen-Torvik, Laura J %A Jensen, Richard A %A Evans, Daniel S %A Sun, Yan V %A An, Ping %A Patel, Sanjay R %A Lu, Yingchang %A Long, Jirong %A Armstrong, Loren L %A Wagenknecht, Lynne %A Yang, Lingyao %A Snively, Beverly M %A Palmer, Nicholette D %A Mudgal, Poorva %A Langefeld, Carl D %A Keene, Keith L %A Freedman, Barry I %A Mychaleckyj, Josyf C %A Nayak, Uma %A Raffel, Leslie J %A Goodarzi, Mark O %A Chen, Y-D Ida %A Taylor, Herman A %A Correa, Adolfo %A Sims, Mario %A Couper, David %A Pankow, James S %A Boerwinkle, Eric %A Adeyemo, Adebowale %A Doumatey, Ayo %A Chen, Guanjie %A Mathias, Rasika A %A Vaidya, Dhananjay %A Singleton, Andrew B %A Zonderman, Alan B %A Igo, Robert P %A Sedor, John R %A Kabagambe, Edmond K %A Siscovick, David S %A McKnight, Barbara %A Rice, Kenneth %A Liu, Yongmei %A Hsueh, Wen-Chi %A Zhao, Wei %A Bielak, Lawrence F %A Kraja, Aldi %A Province, Michael A %A Bottinger, Erwin P %A Gottesman, Omri %A Cai, Qiuyin %A Zheng, Wei %A Blot, William J %A Lowe, William L %A Pacheco, Jennifer A %A Crawford, Dana C %A Grundberg, Elin %A Rich, Stephen S %A Hayes, M Geoffrey %A Shu, Xiao-Ou %A Loos, Ruth J F %A Borecki, Ingrid B %A Peyser, Patricia A %A Cummings, Steven R %A Psaty, Bruce M %A Fornage, Myriam %A Iyengar, Sudha K %A Evans, Michele K %A Becker, Diane M %A Kao, W H Linda %A Wilson, James G %A Rotter, Jerome I %A Sale, Michèle M %A Liu, Simin %A Rotimi, Charles N %A Bowden, Donald W %K African Americans %K Diabetes Mellitus, Type 2 %K Genome-Wide Association Study %K HLA-B27 Antigen %K HMGA2 Protein %K Humans %K KCNQ1 Potassium Channel %K Mutant Chimeric Proteins %K Polymorphism, Single Nucleotide %K Transcription Factor 7-Like 2 Protein %X

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94) %B PLoS Genet %V 10 %P e1004517 %8 2014 Aug %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/25102180?dopt=Abstract %R 10.1371/journal.pgen.1004517 %0 Journal Article %J Hum Mol Genet %D 2014 %T Quantifying rare, deleterious variation in 12 human cytochrome P450 drug-metabolism genes in a large-scale exome dataset. %A Gordon, Adam S %A Tabor, Holly K %A Johnson, Andrew D %A Snively, Beverly M %A Assimes, Themistocles L %A Auer, Paul L %A Ioannidis, John P A %A Peters, Ulrike %A Robinson, Jennifer G %A Sucheston, Lara E %A Wang, Danxin %A Sotoodehnia, Nona %A Rotter, Jerome I %A Psaty, Bruce M %A Jackson, Rebecca D %A Herrington, David M %A O'Donnell, Christopher J %A Reiner, Alexander P %A Rich, Stephen S %A Rieder, Mark J %A Bamshad, Michael J %A Nickerson, Deborah A %K Cytochrome P-450 Enzyme System %K Databases, Genetic %K European Continental Ancestry Group %K Exome %K Humans %K Pharmaceutical Preparations %K Pharmacogenetics %K Polymorphism, Genetic %X

The study of genetic influences on drug response and efficacy ('pharmacogenetics') has existed for over 50 years. Yet, we still lack a complete picture of how genetic variation, both common and rare, affects each individual's responses to medications. Exome sequencing is a promising alternative method for pharmacogenetic discovery as it provides information on both common and rare variation in large numbers of individuals. Using exome data from 2203 AA and 4300 Caucasian individuals through the NHLBI Exome Sequencing Project, we conducted a survey of coding variation within 12 Cytochrome P450 (CYP) genes that are collectively responsible for catalyzing nearly 75% of all known Phase I drug oxidation reactions. In addition to identifying many polymorphisms with known pharmacogenetic effects, we discovered over 730 novel nonsynonymous alleles across the 12 CYP genes of interest. These alleles include many with diverse functional effects such as premature stop codons, aberrant splicesites and mutations at conserved active site residues. Our analysis considering both novel, predicted functional alleles as well as known, actionable CYP alleles reveals that rare, deleterious variation contributes markedly to the overall burden of pharmacogenetic alleles within the populations considered, and that the contribution of rare variation to this burden is over three times greater in AA individuals as compared with Caucasians. While most of these impactful alleles are individually rare, 7.6-11.7% of individuals interrogated in the study carry at least one newly described potentially deleterious alleles in a major drug-metabolizing CYP.

%B Hum Mol Genet %V 23 %P 1957-63 %8 2014 Apr 15 %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/24282029?dopt=Abstract %R 10.1093/hmg/ddt588 %0 Journal Article %J Circ Cardiovasc Genet %D 2014 %T Sequencing of SCN5A identifies rare and common variants associated with cardiac conduction: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. %A Magnani, Jared W %A Brody, Jennifer A %A Prins, Bram P %A Arking, Dan E %A Lin, Honghuang %A Yin, Xiaoyan %A Liu, Ching-Ti %A Morrison, Alanna C %A Zhang, Feng %A Spector, Tim D %A Alonso, Alvaro %A Bis, Joshua C %A Heckbert, Susan R %A Lumley, Thomas %A Sitlani, Colleen M %A Cupples, L Adrienne %A Lubitz, Steven A %A Soliman, Elsayed Z %A Pulit, Sara L %A Newton-Cheh, Christopher %A O'Donnell, Christopher J %A Ellinor, Patrick T %A Benjamin, Emelia J %A Muzny, Donna M %A Gibbs, Richard A %A Santibanez, Jireh %A Taylor, Herman A %A Rotter, Jerome I %A Lange, Leslie A %A Psaty, Bruce M %A Jackson, Rebecca %A Rich, Stephen S %A Boerwinkle, Eric %A Jamshidi, Yalda %A Sotoodehnia, Nona %K Adult %K Aged %K Aged, 80 and over %K Aging %K Cohort Studies %K Female %K Genetic Variation %K Genome-Wide Association Study %K Genomics %K Heart Conduction System %K Heart Diseases %K Humans %K Male %K Middle Aged %K NAV1.5 Voltage-Gated Sodium Channel %K Polymorphism, Single Nucleotide %K Sequence Analysis, DNA %X

BACKGROUND: The cardiac sodium channel SCN5A regulates atrioventricular and ventricular conduction. Genetic variants in this gene are associated with PR and QRS intervals. We sought to characterize further the contribution of rare and common coding variation in SCN5A to cardiac conduction.

METHODS AND RESULTS: In Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study, we performed targeted exonic sequencing of SCN5A (n=3699, European ancestry individuals) and identified 4 common (minor allele frequency >1%) and 157 rare variants. Common and rare SCN5A coding variants were examined for association with PR and QRS intervals through meta-analysis of European ancestry participants from CHARGE, National Heart, Lung, and Blood Institute's Exome Sequencing Project (n=607), and the UK10K (n=1275) and by examining Exome Sequencing Project African ancestry participants (n=972). Rare coding SCN5A variants in aggregate were associated with PR interval in European and African ancestry participants (P=1.3×10(-3)). Three common variants were associated with PR and QRS interval duration among European ancestry participants and one among African ancestry participants. These included 2 well-known missense variants: rs1805124 (H558R) was associated with PR and QRS shortening in European ancestry participants (P=6.25×10(-4) and P=5.2×10(-3), respectively) and rs7626962 (S1102Y) was associated with PR shortening in those of African ancestry (P=2.82×10(-3)). Among European ancestry participants, 2 novel synonymous variants, rs1805126 and rs6599230, were associated with cardiac conduction. Our top signal, rs1805126 was associated with PR and QRS lengthening (P=3.35×10(-7) and P=2.69×10(-4), respectively) and rs6599230 was associated with PR shortening (P=2.67×10(-5)).

CONCLUSIONS: By sequencing SCN5A, we identified novel common and rare coding variants associated with cardiac conduction.

%B Circ Cardiovasc Genet %V 7 %P 365-73 %8 2014 Jun %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/24951663?dopt=Abstract %R 10.1161/CIRCGENETICS.113.000098 %0 Journal Article %J Am J Hum Genet %D 2014 %T Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol. %A Lange, Leslie A %A Hu, Youna %A Zhang, He %A Xue, Chenyi %A Schmidt, Ellen M %A Tang, Zheng-Zheng %A Bizon, Chris %A Lange, Ethan M %A Smith, Joshua D %A Turner, Emily H %A Jun, Goo %A Kang, Hyun Min %A Peloso, Gina %A Auer, Paul %A Li, Kuo-Ping %A Flannick, Jason %A Zhang, Ji %A Fuchsberger, Christian %A Gaulton, Kyle %A Lindgren, Cecilia %A Locke, Adam %A Manning, Alisa %A Sim, Xueling %A Rivas, Manuel A %A Holmen, Oddgeir L %A Gottesman, Omri %A Lu, Yingchang %A Ruderfer, Douglas %A Stahl, Eli A %A Duan, Qing %A Li, Yun %A Durda, Peter %A Jiao, Shuo %A Isaacs, Aaron %A Hofman, Albert %A Bis, Joshua C %A Correa, Adolfo %A Griswold, Michael E %A Jakobsdottir, Johanna %A Smith, Albert V %A Schreiner, Pamela J %A Feitosa, Mary F %A Zhang, Qunyuan %A Huffman, Jennifer E %A Crosby, Jacy %A Wassel, Christina L %A Do, Ron %A Franceschini, Nora %A Martin, Lisa W %A Robinson, Jennifer G %A Assimes, Themistocles L %A Crosslin, David R %A Rosenthal, Elisabeth A %A Tsai, Michael %A Rieder, Mark J %A Farlow, Deborah N %A Folsom, Aaron R %A Lumley, Thomas %A Fox, Ervin R %A Carlson, Christopher S %A Peters, Ulrike %A Jackson, Rebecca D %A van Duijn, Cornelia M %A Uitterlinden, André G %A Levy, Daniel %A Rotter, Jerome I %A Taylor, Herman A %A Gudnason, Vilmundur %A Siscovick, David S %A Fornage, Myriam %A Borecki, Ingrid B %A Hayward, Caroline %A Rudan, Igor %A Chen, Y Eugene %A Bottinger, Erwin P %A Loos, Ruth J F %A Sætrom, Pål %A Hveem, Kristian %A Boehnke, Michael %A Groop, Leif %A McCarthy, Mark %A Meitinger, Thomas %A Ballantyne, Christie M %A Gabriel, Stacey B %A O'Donnell, Christopher J %A Post, Wendy S %A North, Kari E %A Reiner, Alexander P %A Boerwinkle, Eric %A Psaty, Bruce M %A Altshuler, David %A Kathiresan, Sekar %A Lin, Dan-Yu %A Jarvik, Gail P %A Cupples, L Adrienne %A Kooperberg, Charles %A Wilson, James G %A Nickerson, Deborah A %A Abecasis, Goncalo R %A Rich, Stephen S %A Tracy, Russell P %A Willer, Cristen J %K Adult %K Aged %K Apolipoproteins E %K Cholesterol, LDL %K Cohort Studies %K Dyslipidemias %K Exome %K Female %K Follow-Up Studies %K Gene Frequency %K Genetic Code %K Genome-Wide Association Study %K Genotype %K Humans %K Lipase %K Male %K Middle Aged %K Phenotype %K Polymorphism, Single Nucleotide %K Proprotein Convertase 9 %K Proprotein Convertases %K Receptors, LDL %K Sequence Analysis, DNA %K Serine Endopeptidases %X

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.

%B Am J Hum Genet %V 94 %P 233-45 %8 2014 Feb 06 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/24507775?dopt=Abstract %R 10.1016/j.ajhg.2014.01.010 %0 Journal Article %J Hum Mol Genet %D 2015 %T Association of exome sequences with plasma C-reactive protein levels in >9000 participants. %A Schick, Ursula M %A Auer, Paul L %A Bis, Joshua C %A Lin, Honghuang %A Wei, Peng %A Pankratz, Nathan %A Lange, Leslie A %A Brody, Jennifer %A Stitziel, Nathan O %A Kim, Daniel S %A Carlson, Christopher S %A Fornage, Myriam %A Haessler, Jeffery %A Hsu, Li %A Jackson, Rebecca D %A Kooperberg, Charles %A Leal, Suzanne M %A Psaty, Bruce M %A Boerwinkle, Eric %A Tracy, Russell %A Ardissino, Diego %A Shah, Svati %A Willer, Cristen %A Loos, Ruth %A Melander, Olle %A McPherson, Ruth %A Hovingh, Kees %A Reilly, Muredach %A Watkins, Hugh %A Girelli, Domenico %A Fontanillas, Pierre %A Chasman, Daniel I %A Gabriel, Stacey B %A Gibbs, Richard %A Nickerson, Deborah A %A Kathiresan, Sekar %A Peters, Ulrike %A Dupuis, Josée %A Wilson, James G %A Rich, Stephen S %A Morrison, Alanna C %A Benjamin, Emelia J %A Gross, Myron D %A Reiner, Alex P %K Adult %K African Americans %K C-Reactive Protein %K Cardiovascular Diseases %K Cohort Studies %K European Continental Ancestry Group %K Exome %K Female %K Gene Frequency %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Hepatocyte Nuclear Factor 1-alpha %K Humans %K Male %K Plasma %K Polymorphism, Single Nucleotide %K Receptors, Interleukin-6 %K Risk Factors %X

C-reactive protein (CRP) concentration is a heritable systemic marker of inflammation that is associated with cardiovascular disease risk. Genome-wide association studies have identified CRP-associated common variants associated in ∼25 genes. Our aims were to apply exome sequencing to (1) assess whether the candidate loci contain rare coding variants associated with CRP levels and (2) perform an exome-wide search for rare variants in novel genes associated with CRP levels. We exome-sequenced 6050 European-Americans (EAs) and 3109 African-Americans (AAs) from the NHLBI-ESP and the CHARGE consortia, and performed association tests of sequence data with measured CRP levels. In single-variant tests across candidate loci, a novel rare (minor allele frequency = 0.16%) CRP-coding variant (rs77832441-A; p.Thr59Met) was associated with 53% lower mean CRP levels (P = 2.9 × 10(-6)). We replicated the association of rs77832441 in an exome array analysis of 11 414 EAs (P = 3.0 × 10(-15)). Despite a strong effect on CRP levels, rs77832441 was not associated with inflammation-related phenotypes including coronary heart disease. We also found evidence for an AA-specific association of APOE-ε2 rs7214 with higher CRP levels. At the exome-wide significance level (P < 5.0 × 10(-8)), we confirmed associations for reported common variants of HNF1A, CRP, IL6R and TOMM40-APOE. In gene-based tests, a burden of rare/lower frequency variation in CRP in EAs (P ≤ 6.8 × 10(-4)) and in retinoic acid receptor-related orphan receptor α (RORA) in AAs (P = 1.7 × 10(-3)) were associated with CRP levels at the candidate gene level (P < 2.0 × 10(-3)). This inquiry did not elucidate novel genes, but instead demonstrated that variants distributed across the allele frequency spectrum within candidate genes contribute to CRP levels.

%B Hum Mol Genet %V 24 %P 559-71 %8 2015 Jan 15 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/25187575?dopt=Abstract %R 10.1093/hmg/ddu450 %0 Journal Article %J Mol Nutr Food Res %D 2015 %T Dietary fatty acids modulate associations between genetic variants and circulating fatty acids in plasma and erythrocyte membranes: Meta-analysis of nine studies in the CHARGE consortium. %A Smith, Caren E %A Follis, Jack L %A Nettleton, Jennifer A %A Foy, Millennia %A Wu, Jason H Y %A Ma, Yiyi %A Tanaka, Toshiko %A Manichakul, Ani W %A Wu, Hongyu %A Chu, Audrey Y %A Steffen, Lyn M %A Fornage, Myriam %A Mozaffarian, Dariush %A Kabagambe, Edmond K %A Ferruci, Luigi %A Chen, Yii-Der Ida %A Rich, Stephen S %A Djoussé, Luc %A Ridker, Paul M %A Tang, Weihong %A McKnight, Barbara %A Tsai, Michael Y %A Bandinelli, Stefania %A Rotter, Jerome I %A Hu, Frank B %A Chasman, Daniel I %A Psaty, Bruce M %A Arnett, Donna K %A King, Irena B %A Sun, Qi %A Wang, Lu %A Lumley, Thomas %A Chiuve, Stephanie E %A Siscovick, David S %A Ordovas, Jose M %A Lemaitre, Rozenn N %K Acetyltransferases %K Acyltransferases %K Adaptor Proteins, Signal Transducing %K Carboxy-Lyases %K Diet %K Docosahexaenoic Acids %K Eicosapentaenoic Acid %K Erythrocyte Membrane %K Fatty Acid Desaturases %K Fatty Acids %K Fatty Acids, Omega-3 %K Female %K Humans %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %X

SCOPE: Tissue concentrations of omega-3 fatty acids may reduce cardiovascular disease risk, and genetic variants are associated with circulating fatty acids concentrations. Whether dietary fatty acids interact with genetic variants to modify circulating omega-3 fatty acids is unclear. We evaluated interactions between genetic variants and fatty acid intakes for circulating alpha-linoleic acid, eicosapentaenoic acid, docosahexaenoic acid, and docosapentaenoic acid.

METHODS AND RESULTS: We conducted meta-analyses (N = 11 668) evaluating interactions between dietary fatty acids and genetic variants (rs174538 and rs174548 in FADS1 (fatty acid desaturase 1), rs7435 in AGPAT3 (1-acyl-sn-glycerol-3-phosphate), rs4985167 in PDXDC1 (pyridoxal-dependent decarboxylase domain-containing 1), rs780094 in GCKR (glucokinase regulatory protein), and rs3734398 in ELOVL2 (fatty acid elongase 2)). Stratification by measurement compartment (plasma versus erthyrocyte) revealed compartment-specific interactions between FADS1 rs174538 and rs174548 and dietary alpha-linolenic acid and linoleic acid for docosahexaenoic acid and docosapentaenoic acid.

CONCLUSION: Our findings reinforce earlier reports that genetically based differences in circulating fatty acids may be partially due to differences in the conversion of fatty acid precursors. Further, fatty acids measurement compartment may modify gene-diet relationships, and considering compartment may improve the detection of gene-fatty acids interactions for circulating fatty acid outcomes.

%B Mol Nutr Food Res %V 59 %P 1373-83 %8 2015 Jul %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/25626431?dopt=Abstract %R 10.1002/mnfr.201400734 %0 Journal Article %J Nature %D 2015 %T Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. %A Do, Ron %A Stitziel, Nathan O %A Won, Hong-Hee %A Jørgensen, Anders Berg %A Duga, Stefano %A Angelica Merlini, Pier %A Kiezun, Adam %A Farrall, Martin %A Goel, Anuj %A Zuk, Or %A Guella, Illaria %A Asselta, Rosanna %A Lange, Leslie A %A Peloso, Gina M %A Auer, Paul L %A Girelli, Domenico %A Martinelli, Nicola %A Farlow, Deborah N %A DePristo, Mark A %A Roberts, Robert %A Stewart, Alexander F R %A Saleheen, Danish %A Danesh, John %A Epstein, Stephen E %A Sivapalaratnam, Suthesh %A Hovingh, G Kees %A Kastelein, John J %A Samani, Nilesh J %A Schunkert, Heribert %A Erdmann, Jeanette %A Shah, Svati H %A Kraus, William E %A Davies, Robert %A Nikpay, Majid %A Johansen, Christopher T %A Wang, Jian %A Hegele, Robert A %A Hechter, Eliana %A März, Winfried %A Kleber, Marcus E %A Huang, Jie %A Johnson, Andrew D %A Li, Mingyao %A Burke, Greg L %A Gross, Myron %A Liu, Yongmei %A Assimes, Themistocles L %A Heiss, Gerardo %A Lange, Ethan M %A Folsom, Aaron R %A Taylor, Herman A %A Olivieri, Oliviero %A Hamsten, Anders %A Clarke, Robert %A Reilly, Dermot F %A Yin, Wu %A Rivas, Manuel A %A Donnelly, Peter %A Rossouw, Jacques E %A Psaty, Bruce M %A Herrington, David M %A Wilson, James G %A Rich, Stephen S %A Bamshad, Michael J %A Tracy, Russell P %A Cupples, L Adrienne %A Rader, Daniel J %A Reilly, Muredach P %A Spertus, John A %A Cresci, Sharon %A Hartiala, Jaana %A Tang, W H Wilson %A Hazen, Stanley L %A Allayee, Hooman %A Reiner, Alex P %A Carlson, Christopher S %A Kooperberg, Charles %A Jackson, Rebecca D %A Boerwinkle, Eric %A Lander, Eric S %A Schwartz, Stephen M %A Siscovick, David S %A McPherson, Ruth %A Tybjaerg-Hansen, Anne %A Abecasis, Goncalo R %A Watkins, Hugh %A Nickerson, Deborah A %A Ardissino, Diego %A Sunyaev, Shamil R %A O'Donnell, Christopher J %A Altshuler, David %A Gabriel, Stacey %A Kathiresan, Sekar %K Age Factors %K Age of Onset %K Alleles %K Apolipoproteins A %K Case-Control Studies %K Cholesterol, LDL %K Coronary Artery Disease %K Exome %K Female %K Genetic Predisposition to Disease %K Genetics, Population %K Heterozygote %K Humans %K Male %K Middle Aged %K Mutation %K Myocardial Infarction %K National Heart, Lung, and Blood Institute (U.S.) %K Receptors, LDL %K Triglycerides %K United States %X

Myocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance. When MI occurs early in life, genetic inheritance is a major component to risk. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families, whereas common variants at more than 45 loci have been associated with MI risk in the population. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl(-1). At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase and apolipoprotein C-III (refs 18, 19). Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.

%B Nature %V 518 %P 102-6 %8 2015 Feb 5 %G eng %N 7537 %1 http://www.ncbi.nlm.nih.gov/pubmed/25487149?dopt=Abstract %R 10.1038/nature13917 %0 Journal Article %J Am J Hematol %D 2015 %T Gene-centric approach identifies new and known loci for FVIII activity and VWF antigen levels in European Americans and African Americans. %A Tang, Weihong %A Cushman, Mary %A Green, David %A Rich, Stephen S %A Lange, Leslie A %A Yang, Qiong %A Tracy, Russell P %A Tofler, Geoffrey H %A Basu, Saonli %A Wilson, James G %A Keating, Brendan J %A Weng, Lu-Chen %A Taylor, Herman A %A Jacobs, David R %A Delaney, Joseph A %A Palmer, Cameron D %A Young, Taylor %A Pankow, James S %A O'Donnell, Christopher J %A Smith, Nicholas L %A Reiner, Alexander P %A Folsom, Aaron R %K Adult %K African Americans %K Aged %K European Continental Ancestry Group %K Factor VIII %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Male %K Methionine Adenosyltransferase %K Middle Aged %K Polymorphism, Single Nucleotide %K Venous Thromboembolism %K von Willebrand Factor %X

Coagulation factor VIII and von Willebrand factor (VWF) are key proteins in procoagulant activation. Higher FVIII coagulant activity (FVIII :C) and VWF antigen (VWF :Ag) are risk factors for cardiovascular disease and venous thromboembolism. Beyond associations with ABO blood group, genetic determinants of FVIII and VWF are not well understood, especially in non European-American populations. We performed a genetic association study of FVIII :C and VWF:Ag that assessed 50,000 gene-centric single nucleotide polymorphisms (SNPs) in 18,556 European Americans (EAs) and 5,047 African Americans (AAs) from five population-based cohorts. Previously unreported associations for FVIII :C were identified in both AAs and EAs with KNG1 (most significantly associated SNP rs710446, Ile581Thr, Ile581Thr, P = 5.10 × 10(-7) in EAs and P = 3.88 × 10(-3) in AAs) and VWF rs7962217 (Gly2705Arg,P = 6.30 × 10(-9) in EAs and P = 2.98 × 10(-2) in AAs. Significant associations for FVIII :C were also observed with F8/TMLHE region SNP rs12557310 in EAs (P = 8.02 × 10(-10) ), with VWF rs1800380 in AAs (P = 5.62 × 10(-11) ), and with MAT1A rs2236568 in AAs (P51.69 × 10(-6) ). We replicated previously reported associations of FVIII :C and VWF :Ag with the ABO blood group, VWF rs1063856(Thr789Ala), rs216321 (Ala852Gln), and VWF rs2229446 (Arg2185Gln). Findings from this study expand our understanding of genetic influences for FVIII :C and VWF :Ag in both EAs and AAs.

%B Am J Hematol %V 90 %P 534-40 %8 2015 Jun %G eng %N 6 %R 10.1002/ajh.24005 %0 Journal Article %J J Lipid Res %D 2015 %T Genetic loci associated with circulating levels of very long-chain saturated fatty acids. %A Lemaitre, Rozenn N %A King, Irena B %A Kabagambe, Edmond K %A Wu, Jason H Y %A McKnight, Barbara %A Manichaikul, Ani %A Guan, Weihua %A Sun, Qi %A Chasman, Daniel I %A Foy, Millennia %A Wang, Lu %A Zhu, Jingwen %A Siscovick, David S %A Tsai, Michael Y %A Arnett, Donna K %A Psaty, Bruce M %A Djoussé, Luc %A Chen, Yii-der I %A Tang, Weihong %A Weng, Lu-Chen %A Wu, Hongyu %A Jensen, Majken K %A Chu, Audrey Y %A Jacobs, David R %A Rich, Stephen S %A Mozaffarian, Dariush %A Steffen, Lyn %A Rimm, Eric B %A Hu, Frank B %A Ridker, Paul M %A Fornage, Myriam %A Friedlander, Yechiel %K Cohort Studies %K Fatty Acids %K Genetic Loci %K Genetic Variation %K Genome-Wide Association Study %K Humans %X

Very long-chain saturated fatty acids (VLSFAs) are saturated fatty acids with 20 or more carbons. In contrast to the more abundant saturated fatty acids, such as palmitic acid, there is growing evidence that circulating VLSFAs may have beneficial biological properties. Whether genetic factors influence circulating levels of VLSFAs is not known. We investigated the association of common genetic variation with plasma phospholipid/erythrocyte levels of three VLSFAs by performing genome-wide association studies in seven population-based cohorts comprising 10,129 subjects of European ancestry. We observed associations of circulating VLSFA concentrations with common variants in two genes, serine palmitoyl-transferase long-chain base subunit 3 (SPTLC3), a gene involved in the rate-limiting step of de novo sphingolipid synthesis, and ceramide synthase 4 (CERS4). The SPTLC3 variant at rs680379 was associated with higher arachidic acid (20:0 , P = 5.81 × 10(-13)). The CERS4 variant at rs2100944 was associated with higher levels of 20:0 (P = 2.65 × 10(-40)) and in analyses that adjusted for 20:0, with lower levels of behenic acid (P = 4.22 × 10(-26)) and lignoceric acid (P = 3.20 × 10(-21)). These novel associations suggest an inter-relationship of circulating VLSFAs and sphingolipid synthesis.

%B J Lipid Res %V 56 %P 176-84 %8 2015 Jan %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/25378659?dopt=Abstract %R 10.1194/jlr.M052456 %0 Journal Article %J Am J Clin Nutr %D 2015 %T Genetic loci associated with circulating phospholipid trans fatty acids: a meta-analysis of genome-wide association studies from the CHARGE Consortium. %A Mozaffarian, Dariush %A Kabagambe, Edmond K %A Johnson, Catherine O %A Lemaitre, Rozenn N %A Manichaikul, Ani %A Sun, Qi %A Foy, Millennia %A Wang, Lu %A Wiener, Howard %A Irvin, Marguerite R %A Rich, Stephen S %A Wu, Hongyu %A Jensen, Majken K %A Chasman, Daniel I %A Chu, Audrey Y %A Fornage, Myriam %A Steffen, Lyn %A King, Irena B %A McKnight, Barbara %A Psaty, Bruce M %A Djoussé, Luc %A Chen, Ida Y-D %A Wu, Jason H Y %A Siscovick, David S %A Ridker, Paul M %A Tsai, Michael Y %A Rimm, Eric B %A Hu, Frank B %A Arnett, Donna K %K African Americans %K Arachidonic Acid %K Asian Americans %K Biomarkers %K European Continental Ancestry Group %K Fatty Acids, Omega-6 %K Gene Frequency %K Genetic Association Studies %K Genetic Loci %K Genotyping Techniques %K Humans %K Phospholipids %K Polymorphism, Single Nucleotide %K Trans Fatty Acids %X

BACKGROUND: Circulating trans fatty acids (TFAs), which cannot be synthesized by humans, are linked to adverse health outcomes. Although TFAs are obtained from diet, little is known about subsequent influences (e.g., relating to incorporation, metabolism, or intercompetition with other fatty acids) that could alter circulating concentrations and possibly modulate or mediate impacts on health.

OBJECTIVE: The objective was to elucidate novel biologic pathways that may influence circulating TFAs by evaluating associations between common genetic variation and TFA biomarkers.

DESIGN: We performed meta-analyses using 7 cohorts of European-ancestry participants (n = 8013) having measured genome-wide variation in single-nucleotide polymorphisms (SNPs) and circulating TFA biomarkers (erythrocyte or plasma phospholipids), including trans-16:1n-7, total trans-18:1, trans/cis-18:2, cis/trans-18:2, and trans/trans-18:2. We further evaluated SNPs with genome-wide significant associations among African Americans (n = 1082), Chinese Americans (n = 669), and Hispanic Americans (n = 657) from 2 of these cohorts.

RESULTS: Among European-ancestry participants, 31 SNPs in or near the fatty acid desaturase (FADS) 1 and 2 cluster were associated with cis/trans-18:2; a top hit was rs174548 (β = 0.0035, P = 4.90 × 10(-15)), an SNP previously associated with circulating n-3 and n-6 polyunsaturated fatty acid concentrations. No significant association was identified for other TFAs. rs174548 in FADS1/2 was also associated with cis/trans-18:2 in Hispanic Americans (β = 0.0053, P = 1.05 × 10(-6)) and Chinese Americans (β = 0.0028, P = 0.002) but not African Americans (β = 0.0009, P = 0.34); however, in African Americans, fine mapping identified a top hit in FADS2 associated with cis/trans-18:2 (rs174579: β = 0.0118, P = 4.05 × 10(-5)). The association between rs174548 and cis/trans-18:2 remained significant after further adjustment for individual circulating n-3 and n-6 fatty acids, except arachidonic acid. After adjustment for arachidonic acid concentrations, the association between rs174548 and cis/trans-18:2 was nearly eliminated in European-ancestry participants (β-coefficient reduced by 86%), with similar reductions in Hispanic Americans and Chinese Americans.

CONCLUSIONS: Our findings provide novel evidence for genetic regulation of cis/trans-18:2 by the FADS1/2 cluster and suggest that this regulation may be influenced/mediated by concentrations of arachidonic acid, an n-6 polyunsaturated fat.

%B Am J Clin Nutr %V 101 %P 398-406 %8 2015 Feb %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/25646338?dopt=Abstract %R 10.3945/ajcn.114.094557 %0 Journal Article %J Nat Commun %D 2015 %T Genome of The Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels. %A van Leeuwen, Elisabeth M %A Karssen, Lennart C %A Deelen, Joris %A Isaacs, Aaron %A Medina-Gómez, Carolina %A Mbarek, Hamdi %A Kanterakis, Alexandros %A Trompet, Stella %A Postmus, Iris %A Verweij, Niek %A van Enckevort, David J %A Huffman, Jennifer E %A White, Charles C %A Feitosa, Mary F %A Bartz, Traci M %A Manichaikul, Ani %A Joshi, Peter K %A Peloso, Gina M %A Deelen, Patrick %A van Dijk, Freerk %A Willemsen, Gonneke %A de Geus, Eco J %A Milaneschi, Yuri %A Penninx, Brenda W J H %A Francioli, Laurent C %A Menelaou, Androniki %A Pulit, Sara L %A Rivadeneira, Fernando %A Hofman, Albert %A Oostra, Ben A %A Franco, Oscar H %A Mateo Leach, Irene %A Beekman, Marian %A de Craen, Anton J M %A Uh, Hae-Won %A Trochet, Holly %A Hocking, Lynne J %A Porteous, David J %A Sattar, Naveed %A Packard, Chris J %A Buckley, Brendan M %A Brody, Jennifer A %A Bis, Joshua C %A Rotter, Jerome I %A Mychaleckyj, Josyf C %A Campbell, Harry %A Duan, Qing %A Lange, Leslie A %A Wilson, James F %A Hayward, Caroline %A Polasek, Ozren %A Vitart, Veronique %A Rudan, Igor %A Wright, Alan F %A Rich, Stephen S %A Psaty, Bruce M %A Borecki, Ingrid B %A Kearney, Patricia M %A Stott, David J %A Adrienne Cupples, L %A Jukema, J Wouter %A van der Harst, Pim %A Sijbrands, Eric J %A Hottenga, Jouke-Jan %A Uitterlinden, André G %A Swertz, Morris A %A van Ommen, Gert-Jan B %A de Bakker, Paul I W %A Eline Slagboom, P %A Boomsma, Dorret I %A Wijmenga, Cisca %A van Duijn, Cornelia M %K ATP-Binding Cassette Transporters %K Cholesterol %K Gene Frequency %K Genetic Association Studies %K Humans %K Mutation, Missense %K Netherlands %X

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of The Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10(-4)), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (βLDL-C=0.135, βTC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.

%B Nat Commun %V 6 %P 6065 %8 2015 %G eng %1 http://www.ncbi.nlm.nih.gov/pubmed/25751400?dopt=Abstract %R 10.1038/ncomms7065 %0 Journal Article %J Am J Clin Nutr %D 2015 %T Habitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants. %A Dashti, Hassan S %A Follis, Jack L %A Smith, Caren E %A Tanaka, Toshiko %A Cade, Brian E %A Gottlieb, Daniel J %A Hruby, Adela %A Jacques, Paul F %A Lamon-Fava, Stefania %A Richardson, Kris %A Saxena, Richa %A Scheer, Frank A J L %A Kovanen, Leena %A Bartz, Traci M %A Perälä, Mia-Maria %A Jonsson, Anna %A Frazier-Wood, Alexis C %A Kalafati, Ioanna-Panagiota %A Mikkilä, Vera %A Partonen, Timo %A Lemaitre, Rozenn N %A Lahti, Jari %A Hernandez, Dena G %A Toft, Ulla %A Johnson, W Craig %A Kanoni, Stavroula %A Raitakari, Olli T %A Perola, Markus %A Psaty, Bruce M %A Ferrucci, Luigi %A Grarup, Niels %A Highland, Heather M %A Rallidis, Loukianos %A Kähönen, Mika %A Havulinna, Aki S %A Siscovick, David S %A Räikkönen, Katri %A Jørgensen, Torben %A Rotter, Jerome I %A Deloukas, Panos %A Viikari, Jorma S A %A Mozaffarian, Dariush %A Linneberg, Allan %A Seppälä, Ilkka %A Hansen, Torben %A Salomaa, Veikko %A Gharib, Sina A %A Eriksson, Johan G %A Bandinelli, Stefania %A Pedersen, Oluf %A Rich, Stephen S %A Dedoussis, George %A Lehtimäki, Terho %A Ordovas, Jose M %K Adult %K Body Mass Index %K CLOCK Proteins %K Cohort Studies %K Cross-Sectional Studies %K Diet %K Dietary Proteins %K Energy Intake %K European Continental Ancestry Group %K Fatty Acids, Unsaturated %K Female %K Gene-Environment Interaction %K Genetic Predisposition to Disease %K Humans %K Male %K Middle Aged %K Obesity %K Polymorphism, Single Nucleotide %K Sleep %K Young Adult %X

BACKGROUND: Short sleep duration has been associated with greater risks of obesity, hypertension, diabetes, and cardiovascular disease. Also, common genetic variants in the human Circadian Locomotor Output Cycles Kaput (CLOCK) show associations with ghrelin and total energy intake.

OBJECTIVES: We examined associations between habitual sleep duration, body mass index (BMI), and macronutrient intake and assessed whether CLOCK variants modify these associations.

DESIGN: We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations of sleep duration and BMI and macronutrient intake as percentages of total energy as well as interactions with CLOCK variants from 9 cohort studies including up to 14,906 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium.

RESULTS: We observed a significant association between sleep duration and lower BMI (β ± SE = 0.16 ± 0.04, P < 0.0001) in the overall sample; however, associations between sleep duration and relative macronutrient intake were evident in age- and sex-stratified analyses only. We observed a significant association between sleep duration and lower saturated fatty acid intake in younger (aged 20-64 y) adults (men: 0.11 ± 0.06%, P = 0.03; women: 0.10 ± 0.05%, P = 0.04) and with lower carbohydrate (-0.31 ± 0.12%, P < 0.01), higher total fat (0.18 ± 0.09%, P = 0.05), and higher PUFA (0.05 ± 0.02%, P = 0.02) intakes in older (aged 65-80 y) women. In addition, the following 2 nominally significant interactions were observed: between sleep duration and rs12649507 on PUFA intake and between sleep duration and rs6858749 on protein intake.

CONCLUSIONS: Our results indicate that longer habitual sleep duration is associated with lower BMI and age- and sex-specific favorable dietary behaviors. Differences in the relative intake of specific macronutrients associated with short sleep duration could, at least in part, explain previously reported associations between short sleep duration and chronic metabolic abnormalities. In addition, the influence of obesity-associated CLOCK variants on the association between sleep duration and macronutrient intake suggests that longer habitual sleep duration could ameliorate the genetic predisposition to obesity via a favorable dietary profile.

%B Am J Clin Nutr %V 101 %P 135-43 %8 2015 Jan %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/25527757?dopt=Abstract %R 10.3945/ajcn.114.095026 %0 Journal Article %J Nat Commun %D 2015 %T Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility. %A Wessel, Jennifer %A Chu, Audrey Y %A Willems, Sara M %A Wang, Shuai %A Yaghootkar, Hanieh %A Brody, Jennifer A %A Dauriz, Marco %A Hivert, Marie-France %A Raghavan, Sridharan %A Lipovich, Leonard %A Hidalgo, Bertha %A Fox, Keolu %A Huffman, Jennifer E %A An, Ping %A Lu, Yingchang %A Rasmussen-Torvik, Laura J %A Grarup, Niels %A Ehm, Margaret G %A Li, Li %A Baldridge, Abigail S %A Stančáková, Alena %A Abrol, Ravinder %A Besse, Céline %A Boland, Anne %A Bork-Jensen, Jette %A Fornage, Myriam %A Freitag, Daniel F %A Garcia, Melissa E %A Guo, Xiuqing %A Hara, Kazuo %A Isaacs, Aaron %A Jakobsdottir, Johanna %A Lange, Leslie A %A Layton, Jill C %A Li, Man %A Hua Zhao, Jing %A Meidtner, Karina %A Morrison, Alanna C %A Nalls, Mike A %A Peters, Marjolein J %A Sabater-Lleal, Maria %A Schurmann, Claudia %A Silveira, Angela %A Smith, Albert V %A Southam, Lorraine %A Stoiber, Marcus H %A Strawbridge, Rona J %A Taylor, Kent D %A Varga, Tibor V %A Allin, Kristine H %A Amin, Najaf %A Aponte, Jennifer L %A Aung, Tin %A Barbieri, Caterina %A Bihlmeyer, Nathan A %A Boehnke, Michael %A Bombieri, Cristina %A Bowden, Donald W %A Burns, Sean M %A Chen, Yuning %A Chen, Yii-DerI %A Cheng, Ching-Yu %A Correa, Adolfo %A Czajkowski, Jacek %A Dehghan, Abbas %A Ehret, Georg B %A Eiriksdottir, Gudny %A Escher, Stefan A %A Farmaki, Aliki-Eleni %A Frånberg, Mattias %A Gambaro, Giovanni %A Giulianini, Franco %A Goddard, William A %A Goel, Anuj %A Gottesman, Omri %A Grove, Megan L %A Gustafsson, Stefan %A Hai, Yang %A Hallmans, Göran %A Heo, Jiyoung %A Hoffmann, Per %A Ikram, Mohammad K %A Jensen, Richard A %A Jørgensen, Marit E %A Jørgensen, Torben %A Karaleftheri, Maria %A Khor, Chiea C %A Kirkpatrick, Andrea %A Kraja, Aldi T %A Kuusisto, Johanna %A Lange, Ethan M %A Lee, I T %A Lee, Wen-Jane %A Leong, Aaron %A Liao, Jiemin %A Liu, Chunyu %A Liu, Yongmei %A Lindgren, Cecilia M %A Linneberg, Allan %A Malerba, Giovanni %A Mamakou, Vasiliki %A Marouli, Eirini %A Maruthur, Nisa M %A Matchan, Angela %A McKean-Cowdin, Roberta %A McLeod, Olga %A Metcalf, Ginger A %A Mohlke, Karen L %A Muzny, Donna M %A Ntalla, Ioanna %A Palmer, Nicholette D %A Pasko, Dorota %A Peter, Andreas %A Rayner, Nigel W %A Renstrom, Frida %A Rice, Ken %A Sala, Cinzia F %A Sennblad, Bengt %A Serafetinidis, Ioannis %A Smith, Jennifer A %A Soranzo, Nicole %A Speliotes, Elizabeth K %A Stahl, Eli A %A Stirrups, Kathleen %A Tentolouris, Nikos %A Thanopoulou, Anastasia %A Torres, Mina %A Traglia, Michela %A Tsafantakis, Emmanouil %A Javad, Sundas %A Yanek, Lisa R %A Zengini, Eleni %A Becker, Diane M %A Bis, Joshua C %A Brown, James B %A Cupples, L Adrienne %A Hansen, Torben %A Ingelsson, Erik %A Karter, Andrew J %A Lorenzo, Carlos %A Mathias, Rasika A %A Norris, Jill M %A Peloso, Gina M %A Sheu, Wayne H-H %A Toniolo, Daniela %A Vaidya, Dhananjay %A Varma, Rohit %A Wagenknecht, Lynne E %A Boeing, Heiner %A Bottinger, Erwin P %A Dedoussis, George %A Deloukas, Panos %A Ferrannini, Ele %A Franco, Oscar H %A Franks, Paul W %A Gibbs, Richard A %A Gudnason, Vilmundur %A Hamsten, Anders %A Harris, Tamara B %A Hattersley, Andrew T %A Hayward, Caroline %A Hofman, Albert %A Jansson, Jan-Håkan %A Langenberg, Claudia %A Launer, Lenore J %A Levy, Daniel %A Oostra, Ben A %A O'Donnell, Christopher J %A O'Rahilly, Stephen %A Padmanabhan, Sandosh %A Pankow, James S %A Polasek, Ozren %A Province, Michael A %A Rich, Stephen S %A Ridker, Paul M %A Rudan, Igor %A Schulze, Matthias B %A Smith, Blair H %A Uitterlinden, André G %A Walker, Mark %A Watkins, Hugh %A Wong, Tien Y %A Zeggini, Eleftheria %A Laakso, Markku %A Borecki, Ingrid B %A Chasman, Daniel I %A Pedersen, Oluf %A Psaty, Bruce M %A Tai, E Shyong %A van Duijn, Cornelia M %A Wareham, Nicholas J %A Waterworth, Dawn M %A Boerwinkle, Eric %A Kao, W H Linda %A Florez, Jose C %A Loos, Ruth J F %A Wilson, James G %A Frayling, Timothy M %A Siscovick, David S %A Dupuis, Josée %A Rotter, Jerome I %A Meigs, James B %A Scott, Robert A %A Goodarzi, Mark O %K African Continental Ancestry Group %K Blood Glucose %K Diabetes Mellitus, Type 2 %K European Continental Ancestry Group %K Exome %K Fasting %K Genetic Association Studies %K Genetic Loci %K Genetic Predisposition to Disease %K Genetic Variation %K Glucagon-Like Peptide-1 Receptor %K Glucose-6-Phosphatase %K Humans %K Insulin %K Mutation Rate %K Oligonucleotide Array Sequence Analysis %K Polymorphism, Single Nucleotide %X

Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.

%B Nat Commun %V 6 %P 5897 %8 2015 %G eng %1 http://www.ncbi.nlm.nih.gov/pubmed/25631608?dopt=Abstract %R 10.1038/ncomms6897 %0 Journal Article %J Eur Heart J %D 2015 %T Mendelian randomization of blood lipids for coronary heart disease. %A Holmes, Michael V %A Asselbergs, Folkert W %A Palmer, Tom M %A Drenos, Fotios %A Lanktree, Matthew B %A Nelson, Christopher P %A Dale, Caroline E %A Padmanabhan, Sandosh %A Finan, Chris %A Swerdlow, Daniel I %A Tragante, Vinicius %A van Iperen, Erik P A %A Sivapalaratnam, Suthesh %A Shah, Sonia %A Elbers, Clara C %A Shah, Tina %A Engmann, Jorgen %A Giambartolomei, Claudia %A White, Jon %A Zabaneh, Delilah %A Sofat, Reecha %A McLachlan, Stela %A Doevendans, Pieter A %A Balmforth, Anthony J %A Hall, Alistair S %A North, Kari E %A Almoguera, Berta %A Hoogeveen, Ron C %A Cushman, Mary %A Fornage, Myriam %A Patel, Sanjay R %A Redline, Susan %A Siscovick, David S %A Tsai, Michael Y %A Karczewski, Konrad J %A Hofker, Marten H %A Verschuren, W Monique %A Bots, Michiel L %A van der Schouw, Yvonne T %A Melander, Olle %A Dominiczak, Anna F %A Morris, Richard %A Ben-Shlomo, Yoav %A Price, Jackie %A Kumari, Meena %A Baumert, Jens %A Peters, Annette %A Thorand, Barbara %A Koenig, Wolfgang %A Gaunt, Tom R %A Humphries, Steve E %A Clarke, Robert %A Watkins, Hugh %A Farrall, Martin %A Wilson, James G %A Rich, Stephen S %A de Bakker, Paul I W %A Lange, Leslie A %A Davey Smith, George %A Reiner, Alex P %A Talmud, Philippa J %A Kivimaki, Mika %A Lawlor, Debbie A %A Dudbridge, Frank %A Samani, Nilesh J %A Keating, Brendan J %A Hingorani, Aroon D %A Casas, Juan P %K Case-Control Studies %K Cholesterol, HDL %K Coronary Artery Disease %K Female %K Gene Frequency %K Genotype %K Genotyping Techniques %K Humans %K Male %K Mendelian Randomization Analysis %K Middle Aged %K Polymorphism, Single Nucleotide %K Risk Assessment %K Triglycerides %X

AIMS: To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization.

METHODS AND RESULTS: We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75).

CONCLUSION: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.

%B Eur Heart J %V 36 %P 539-50 %8 2015 Mar 01 %G eng %N 9 %1 http://www.ncbi.nlm.nih.gov/pubmed/24474739?dopt=Abstract %R 10.1093/eurheartj/eht571 %0 Journal Article %J Stroke %D 2015 %T Meta-Analysis of Genome-Wide Association Studies Identifies Genetic Risk Factors for Stroke in African Americans. %A Carty, Cara L %A Keene, Keith L %A Cheng, Yu-Ching %A Meschia, James F %A Chen, Wei-Min %A Nalls, Mike %A Bis, Joshua C %A Kittner, Steven J %A Rich, Stephen S %A Tajuddin, Salman %A Zonderman, Alan B %A Evans, Michele K %A Langefeld, Carl D %A Gottesman, Rebecca %A Mosley, Thomas H %A Shahar, Eyal %A Woo, Daniel %A Yaffe, Kristine %A Liu, Yongmei %A Sale, Michèle M %A Dichgans, Martin %A Malik, Rainer %A Longstreth, W T %A Mitchell, Braxton D %A Psaty, Bruce M %A Kooperberg, Charles %A Reiner, Alexander %A Worrall, Bradford B %A Fornage, Myriam %K African Americans %K Case-Control Studies %K Cohort Studies %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Polymorphism, Single Nucleotide %K Risk Factors %K Stroke %X

BACKGROUND AND PURPOSE: The majority of genome-wide association studies (GWAS) of stroke have focused on European-ancestry populations; however, none has been conducted in African Americans, despite the disproportionately high burden of stroke in this population. The Consortium of Minority Population Genome-Wide Association Studies of Stroke (COMPASS) was established to identify stroke susceptibility loci in minority populations.

METHODS: Using METAL, we conducted meta-analyses of GWAS in 14 746 African Americans (1365 ischemic and 1592 total stroke cases) from COMPASS, and tested genetic variants with P<10(-6) for validation in METASTROKE, a consortium of ischemic stroke genetic studies in European-ancestry populations. We also evaluated stroke loci previously identified in European-ancestry populations.

RESULTS: The 15q21.3 locus linked with lipid levels and hypertension was associated with total stroke (rs4471613; P=3.9×10(-8)) in African Americans. Nominal associations (P<10(-6)) for total or ischemic stroke were observed for 18 variants in or near genes implicated in cell cycle/mRNA presplicing (PTPRG, CDC5L), platelet function (HPS4), blood-brain barrier permeability (CLDN17), immune response (ELTD1, WDFY4, and IL1F10-IL1RN), and histone modification (HDAC9). Two of these loci achieved nominal significance in METASTROKE: 5q35.2 (P=0.03), and 1p31.1 (P=0.018). Four of 7 previously reported ischemic stroke loci (PITX2, HDAC9, CDKN2A/CDKN2B, and ZFHX3) were nominally associated (P<0.05) with stroke in COMPASS.

CONCLUSIONS: We identified a novel genetic variant associated with total stroke in African Americans and found that ischemic stroke loci identified in European-ancestry populations may also be relevant for African Americans. Our findings support investigation of diverse populations to identify and characterize genetic risk factors, and the importance of shared genetic risk across populations.

%B Stroke %V 46 %P 2063-8 %8 2015 Aug %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/26089329?dopt=Abstract %R 10.1161/STROKEAHA.115.009044 %0 Journal Article %J JAMA Neurol %D 2015 %T Rare and Coding Region Genetic Variants Associated With Risk of Ischemic Stroke: The NHLBI Exome Sequence Project. %A Auer, Paul L %A Nalls, Mike %A Meschia, James F %A Worrall, Bradford B %A Longstreth, W T %A Seshadri, Sudha %A Kooperberg, Charles %A Burger, Kathleen M %A Carlson, Christopher S %A Carty, Cara L %A Chen, Wei-Min %A Cupples, L Adrienne %A DeStefano, Anita L %A Fornage, Myriam %A Hardy, John %A Hsu, Li %A Jackson, Rebecca D %A Jarvik, Gail P %A Kim, Daniel S %A Lakshminarayan, Kamakshi %A Lange, Leslie A %A Manichaikul, Ani %A Quinlan, Aaron R %A Singleton, Andrew B %A Thornton, Timothy A %A Nickerson, Deborah A %A Peters, Ulrike %A Rich, Stephen S %K Aged %K Brain Ischemia %K Exome %K Female %K Genetic Predisposition to Disease %K Genetic Variation %K Genome-Wide Association Study %K Humans %K Male %K Middle Aged %K Muscle Proteins %K National Heart, Lung, and Blood Institute (U.S.) %K Nuclear Proteins %K Open Reading Frames %K Palmitoyl-CoA Hydrolase %K Stroke %K United States %X

IMPORTANCE: Stroke is the second leading cause of death and the third leading cause of years of life lost. Genetic factors contribute to stroke prevalence, and candidate gene and genome-wide association studies (GWAS) have identified variants associated with ischemic stroke risk. These variants often have small effects without obvious biological significance. Exome sequencing may discover predicted protein-altering variants with a potentially large effect on ischemic stroke risk.

OBJECTIVE: To investigate the contribution of rare and common genetic variants to ischemic stroke risk by targeting the protein-coding regions of the human genome.

DESIGN, SETTING, AND PARTICIPANTS: The National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP) analyzed approximately 6000 participants from numerous cohorts of European and African ancestry. For discovery, 365 cases of ischemic stroke (small-vessel and large-vessel subtypes) and 809 European ancestry controls were sequenced; for replication, 47 affected sibpairs concordant for stroke subtype and an African American case-control series were sequenced, with 1672 cases and 4509 European ancestry controls genotyped. The ESP's exome sequencing and genotyping started on January 1, 2010, and continued through June 30, 2012. Analyses were conducted on the full data set between July 12, 2012, and July 13, 2013.

MAIN OUTCOMES AND MEASURES: Discovery of new variants or genes contributing to ischemic stroke risk and subtype (primary analysis) and determination of support for protein-coding variants contributing to risk in previously published candidate genes (secondary analysis).

RESULTS: We identified 2 novel genes associated with an increased risk of ischemic stroke: a protein-coding variant in PDE4DIP (rs1778155; odds ratio, 2.15; P = 2.63 × 10(-8)) with an intracellular signal transduction mechanism and in ACOT4 (rs35724886; odds ratio, 2.04; P = 1.24 × 10(-7)) with a fatty acid metabolism; confirmation of PDE4DIP was observed in affected sibpair families with large-vessel stroke subtype and in African Americans. Replication of protein-coding variants in candidate genes was observed for 2 previously reported GWAS associations: ZFHX3 (cardioembolic stroke) and ABCA1 (large-vessel stroke).

CONCLUSIONS AND RELEVANCE: Exome sequencing discovered 2 novel genes and mechanisms, PDE4DIP and ACOT4, associated with increased risk for ischemic stroke. In addition, ZFHX3 and ABCA1 were discovered to have protein-coding variants associated with ischemic stroke. These results suggest that genetic variation in novel pathways contributes to ischemic stroke risk and serves as a target for prediction, prevention, and therapy.

%B JAMA Neurol %V 72 %P 781-8 %8 2015 Jul %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/25961151?dopt=Abstract %R 10.1001/jamaneurol.2015.0582 %0 Journal Article %J Am J Clin Nutr %D 2016 %T Interaction of methylation-related genetic variants with circulating fatty acids on plasma lipids: a meta-analysis of 7 studies and methylation analysis of 3 studies in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. %A Ma, Yiyi %A Follis, Jack L %A Smith, Caren E %A Tanaka, Toshiko %A Manichaikul, Ani W %A Chu, Audrey Y %A Samieri, Cecilia %A Zhou, Xia %A Guan, Weihua %A Wang, Lu %A Biggs, Mary L %A Chen, Yii-der I %A Hernandez, Dena G %A Borecki, Ingrid %A Chasman, Daniel I %A Rich, Stephen S %A Ferrucci, Luigi %A Irvin, Marguerite Ryan %A Aslibekyan, Stella %A Zhi, Degui %A Tiwari, Hemant K %A Claas, Steven A %A Sha, Jin %A Kabagambe, Edmond K %A Lai, Chao-Qiang %A Parnell, Laurence D %A Lee, Yu-Chi %A Amouyel, Philippe %A Lambert, Jean-Charles %A Psaty, Bruce M %A King, Irena B %A Mozaffarian, Dariush %A McKnight, Barbara %A Bandinelli, Stefania %A Tsai, Michael Y %A Ridker, Paul M %A Ding, Jingzhong %A Mstat, Kurt Lohmant %A Liu, Yongmei %A Sotoodehnia, Nona %A Barberger-Gateau, Pascale %A Steffen, Lyn M %A Siscovick, David S %A Absher, Devin %A Arnett, Donna K %A Ordovas, Jose M %A Lemaitre, Rozenn N %K Apolipoproteins E %K ATP Binding Cassette Transporter 1 %K Cholesterol, HDL %K Cohort Studies %K Diet %K DNA Methylation %K Eicosapentaenoic Acid %K Epigenesis, Genetic %K Fatty Acids %K Gene Expression Regulation %K Humans %K Lipids %K Polymorphism, Single Nucleotide %K Promoter Regions, Genetic %K Triglycerides %X

BACKGROUND: DNA methylation is influenced by diet and single nucleotide polymorphisms (SNPs), and methylation modulates gene expression.

OBJECTIVE: We aimed to explore whether the gene-by-diet interactions on blood lipids act through DNA methylation.

DESIGN: We selected 7 SNPs on the basis of predicted relations in fatty acids, methylation, and lipids. We conducted a meta-analysis and a methylation and mediation analysis with the use of data from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium and the ENCODE (Encyclopedia of DNA Elements) consortium.

RESULTS: On the basis of the meta-analysis of 7 cohorts in the CHARGE consortium, higher plasma HDL cholesterol was associated with fewer C alleles at ATP-binding cassette subfamily A member 1 (ABCA1) rs2246293 (β = -0.6 mg/dL, P = 0.015) and higher circulating eicosapentaenoic acid (EPA) (β = 3.87 mg/dL, P = 5.62 × 10(21)). The difference in HDL cholesterol associated with higher circulating EPA was dependent on genotypes at rs2246293, and it was greater for each additional C allele (β = 1.69 mg/dL, P = 0.006). In the GOLDN (Genetics of Lipid Lowering Drugs and Diet Network) study, higher ABCA1 promoter cg14019050 methylation was associated with more C alleles at rs2246293 (β = 8.84%, P = 3.51 × 10(18)) and lower circulating EPA (β = -1.46%, P = 0.009), and the mean difference in methylation of cg14019050 that was associated with higher EPA was smaller with each additional C allele of rs2246293 (β = -2.83%, P = 0.007). Higher ABCA1 cg14019050 methylation was correlated with lower ABCA1 expression (r = -0.61, P = 0.009) in the ENCODE consortium and lower plasma HDL cholesterol in the GOLDN study (r = -0.12, P = 0.0002). An additional mediation analysis was meta-analyzed across the GOLDN study, Cardiovascular Health Study, and the Multi-Ethnic Study of Atherosclerosis. Compared with the model without the adjustment of cg14019050 methylation, the model with such adjustment provided smaller estimates of the mean plasma HDL cholesterol concentration in association with both the rs2246293 C allele and EPA and a smaller difference by rs2246293 genotypes in the EPA-associated HDL cholesterol. However, the differences between 2 nested models were NS (P > 0.05).

CONCLUSION: We obtained little evidence that the gene-by-fatty acid interactions on blood lipids act through DNA methylation.

%B Am J Clin Nutr %V 103 %P 567-78 %8 2016 Feb %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/26791180?dopt=Abstract %R 10.3945/ajcn.115.112987 %0 Journal Article %J Am J Hum Genet %D 2016 %T Large-Scale Exome-wide Association Analysis Identifies Loci for White Blood Cell Traits and Pleiotropy with Immune-Mediated Diseases. %A Tajuddin, Salman M %A Schick, Ursula M %A Eicher, John D %A Chami, Nathalie %A Giri, Ayush %A Brody, Jennifer A %A Hill, W David %A Kacprowski, Tim %A Li, Jin %A Lyytikäinen, Leo-Pekka %A Manichaikul, Ani %A Mihailov, Evelin %A O'Donoghue, Michelle L %A Pankratz, Nathan %A Pazoki, Raha %A Polfus, Linda M %A Smith, Albert Vernon %A Schurmann, Claudia %A Vacchi-Suzzi, Caterina %A Waterworth, Dawn M %A Evangelou, Evangelos %A Yanek, Lisa R %A Burt, Amber %A Chen, Ming-Huei %A van Rooij, Frank J A %A Floyd, James S %A Greinacher, Andreas %A Harris, Tamara B %A Highland, Heather M %A Lange, Leslie A %A Liu, Yongmei %A Mägi, Reedik %A Nalls, Mike A %A Mathias, Rasika A %A Nickerson, Deborah A %A Nikus, Kjell %A Starr, John M %A Tardif, Jean-Claude %A Tzoulaki, Ioanna %A Velez Edwards, Digna R %A Wallentin, Lars %A Bartz, Traci M %A Becker, Lewis C %A Denny, Joshua C %A Raffield, Laura M %A Rioux, John D %A Friedrich, Nele %A Fornage, Myriam %A Gao, He %A Hirschhorn, Joel N %A Liewald, David C M %A Rich, Stephen S %A Uitterlinden, Andre %A Bastarache, Lisa %A Becker, Diane M %A Boerwinkle, Eric %A de Denus, Simon %A Bottinger, Erwin P %A Hayward, Caroline %A Hofman, Albert %A Homuth, Georg %A Lange, Ethan %A Launer, Lenore J %A Lehtimäki, Terho %A Lu, Yingchang %A Metspalu, Andres %A O'Donnell, Chris J %A Quarells, Rakale C %A Richard, Melissa %A Torstenson, Eric S %A Taylor, Kent D %A Vergnaud, Anne-Claire %A Zonderman, Alan B %A Crosslin, David R %A Deary, Ian J %A Dörr, Marcus %A Elliott, Paul %A Evans, Michele K %A Gudnason, Vilmundur %A Kähönen, Mika %A Psaty, Bruce M %A Rotter, Jerome I %A Slater, Andrew J %A Dehghan, Abbas %A White, Harvey D %A Ganesh, Santhi K %A Loos, Ruth J F %A Esko, Tõnu %A Faraday, Nauder %A Wilson, James G %A Cushman, Mary %A Johnson, Andrew D %A Edwards, Todd L %A Zakai, Neil A %A Lettre, Guillaume %A Reiner, Alex P %A Auer, Paul L %X

White blood cells play diverse roles in innate and adaptive immunity. Genetic association analyses of phenotypic variation in circulating white blood cell (WBC) counts from large samples of otherwise healthy individuals can provide insights into genes and biologic pathways involved in production, differentiation, or clearance of particular WBC lineages (myeloid, lymphoid) and also potentially inform the genetic basis of autoimmune, allergic, and blood diseases. We performed an exome array-based meta-analysis of total WBC and subtype counts (neutrophils, monocytes, lymphocytes, basophils, and eosinophils) in a multi-ancestry discovery and replication sample of ∼157,622 individuals from 25 studies. We identified 16 common variants (8 of which were coding variants) associated with one or more WBC traits, the majority of which are pleiotropically associated with autoimmune diseases. Based on functional annotation, these loci included genes encoding surface markers of myeloid, lymphoid, or hematopoietic stem cell differentiation (CD69, CD33, CD87), transcription factors regulating lineage specification during hematopoiesis (ASXL1, IRF8, IKZF1, JMJD1C, ETS2-PSMG1), and molecules involved in neutrophil clearance/apoptosis (C10orf54, LTA), adhesion (TNXB), or centrosome and microtubule structure/function (KIF9, TUBD1). Together with recent reports of somatic ASXL1 mutations among individuals with idiopathic cytopenias or clonal hematopoiesis of undetermined significance, the identification of a common regulatory 3' UTR variant of ASXL1 suggests that both germline and somatic ASXL1 mutations contribute to lower blood counts in otherwise asymptomatic individuals. These association results shed light on genetic mechanisms that regulate circulating WBC counts and suggest a prominent shared genetic architecture with inflammatory and autoimmune diseases.

%B Am J Hum Genet %V 99 %P 22-39 %8 2016 Jul 7 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/27346689?dopt=Abstract %R 10.1016/j.ajhg.2016.05.003 %0 Journal Article %J J Med Genet %D 2016 %T Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels. %A van Leeuwen, Elisabeth M %A Sabo, Aniko %A Bis, Joshua C %A Huffman, Jennifer E %A Manichaikul, Ani %A Smith, Albert V %A Feitosa, Mary F %A Demissie, Serkalem %A Joshi, Peter K %A Duan, Qing %A Marten, Jonathan %A van Klinken, Jan B %A Surakka, Ida %A Nolte, Ilja M %A Zhang, Weihua %A Mbarek, Hamdi %A Li-Gao, Ruifang %A Trompet, Stella %A Verweij, Niek %A Evangelou, Evangelos %A Lyytikäinen, Leo-Pekka %A Tayo, Bamidele O %A Deelen, Joris %A van der Most, Peter J %A van der Laan, Sander W %A Arking, Dan E %A Morrison, Alanna %A Dehghan, Abbas %A Franco, Oscar H %A Hofman, Albert %A Rivadeneira, Fernando %A Sijbrands, Eric J %A Uitterlinden, André G %A Mychaleckyj, Josyf C %A Campbell, Archie %A Hocking, Lynne J %A Padmanabhan, Sandosh %A Brody, Jennifer A %A Rice, Kenneth M %A White, Charles C %A Harris, Tamara %A Isaacs, Aaron %A Campbell, Harry %A Lange, Leslie A %A Rudan, Igor %A Kolcic, Ivana %A Navarro, Pau %A Zemunik, Tatijana %A Salomaa, Veikko %A Kooner, Angad S %A Kooner, Jaspal S %A Lehne, Benjamin %A Scott, William R %A Tan, Sian-Tsung %A de Geus, Eco J %A Milaneschi, Yuri %A Penninx, Brenda W J H %A Willemsen, Gonneke %A de Mutsert, Renée %A Ford, Ian %A Gansevoort, Ron T %A Segura-Lepe, Marcelo P %A Raitakari, Olli T %A Viikari, Jorma S %A Nikus, Kjell %A Forrester, Terrence %A McKenzie, Colin A %A de Craen, Anton J M %A de Ruijter, Hester M %A Pasterkamp, Gerard %A Snieder, Harold %A Oldehinkel, Albertine J %A Slagboom, P Eline %A Cooper, Richard S %A Kähönen, Mika %A Lehtimäki, Terho %A Elliott, Paul %A van der Harst, Pim %A Jukema, J Wouter %A Mook-Kanamori, Dennis O %A Boomsma, Dorret I %A Chambers, John C %A Swertz, Morris %A Ripatti, Samuli %A Willems van Dijk, Ko %A Vitart, Veronique %A Polasek, Ozren %A Hayward, Caroline %A Wilson, James G %A Wilson, James F %A Gudnason, Vilmundur %A Rich, Stephen S %A Psaty, Bruce M %A Borecki, Ingrid B %A Boerwinkle, Eric %A Rotter, Jerome I %A Cupples, L Adrienne %A van Duijn, Cornelia M %X

BACKGROUND: So far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels.

METHODS: We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ∼60 000 individuals in the discovery stage and ∼90 000 samples in the replication stage.

RESULTS: Our study resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene.

CONCLUSIONS: This study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels.

%B J Med Genet %V 53 %P 441-9 %8 2016 Jul %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/27036123?dopt=Abstract %R 10.1136/jmedgenet-2015-103439 %0 Journal Article %J J Med Genet %D 2016 %T Meta-analysis of genome-wide association studies of HDL cholesterol response to statins. %A Postmus, Iris %A Warren, Helen R %A Trompet, Stella %A Arsenault, Benoit J %A Avery, Christy L %A Bis, Joshua C %A Chasman, Daniel I %A de Keyser, Catherine E %A Deshmukh, Harshal A %A Evans, Daniel S %A Feng, QiPing %A Li, Xiaohui %A Smit, Roelof A J %A Smith, Albert V %A Sun, Fangui %A Taylor, Kent D %A Arnold, Alice M %A Barnes, Michael R %A Barratt, Bryan J %A Betteridge, John %A Boekholdt, S Matthijs %A Boerwinkle, Eric %A Buckley, Brendan M %A Chen, Y-D Ida %A de Craen, Anton J M %A Cummings, Steven R %A Denny, Joshua C %A Dubé, Marie Pierre %A Durrington, Paul N %A Eiriksdottir, Gudny %A Ford, Ian %A Guo, Xiuqing %A Harris, Tamara B %A Heckbert, Susan R %A Hofman, Albert %A Hovingh, G Kees %A Kastelein, John J P %A Launer, Leonore J %A Liu, Ching-Ti %A Liu, Yongmei %A Lumley, Thomas %A McKeigue, Paul M %A Munroe, Patricia B %A Neil, Andrew %A Nickerson, Deborah A %A Nyberg, Fredrik %A O'Brien, Eoin %A O'Donnell, Christopher J %A Post, Wendy %A Poulter, Neil %A Vasan, Ramachandran S %A Rice, Kenneth %A Rich, Stephen S %A Rivadeneira, Fernando %A Sattar, Naveed %A Sever, Peter %A Shaw-Hawkins, Sue %A Shields, Denis C %A Slagboom, P Eline %A Smith, Nicholas L %A Smith, Joshua D %A Sotoodehnia, Nona %A Stanton, Alice %A Stott, David J %A Stricker, Bruno H %A Stürmer, Til %A Uitterlinden, André G %A Wei, Wei-Qi %A Westendorp, Rudi G J %A Whitsel, Eric A %A Wiggins, Kerri L %A Wilke, Russell A %A Ballantyne, Christie M %A Colhoun, Helen M %A Cupples, L Adrienne %A Franco, Oscar H %A Gudnason, Vilmundur %A Hitman, Graham %A Palmer, Colin N A %A Psaty, Bruce M %A Ridker, Paul M %A Stafford, Jeanette M %A Stein, Charles M %A Tardif, Jean-Claude %A Caulfield, Mark J %A Jukema, J Wouter %A Rotter, Jerome I %A Krauss, Ronald M %X

BACKGROUND: In addition to lowering low density lipoprotein cholesterol (LDL-C), statin therapy also raises high density lipoprotein cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation.

METHODS AND RESULTS: We performed a meta-analysis of genome-wide association studies (GWAS) to identify variants with an effect on statin-induced high density lipoprotein cholesterol (HDL-C) changes. The 123 most promising signals with p<1×10(-4) from the 16 769 statin-treated participants in the first analysis stage were followed up in an independent group of 10 951 statin-treated individuals, providing a total sample size of 27 720 individuals. The only associations of genome-wide significance (p<5×10(-8)) were between minor alleles at the CETP locus and greater HDL-C response to statin treatment.

CONCLUSIONS: Based on results from this study that included a relatively large sample size, we suggest that CETP may be the only detectable locus with common genetic variants that influence HDL-C response to statins substantially in individuals of European descent. Although CETP is known to be associated with HDL-C, we provide evidence that this pharmacogenetic effect is independent of its association with baseline HDL-C levels.

%B J Med Genet %V 53 %P 835-845 %8 2016 Dec %G eng %N 12 %R 10.1136/jmedgenet-2016-103966 %0 Journal Article %J Am J Hum Genet %D 2016 %T Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals. %A Eicher, John D %A Chami, Nathalie %A Kacprowski, Tim %A Nomura, Akihiro %A Chen, Ming-Huei %A Yanek, Lisa R %A Tajuddin, Salman M %A Schick, Ursula M %A Slater, Andrew J %A Pankratz, Nathan %A Polfus, Linda %A Schurmann, Claudia %A Giri, Ayush %A Brody, Jennifer A %A Lange, Leslie A %A Manichaikul, Ani %A Hill, W David %A Pazoki, Raha %A Elliot, Paul %A Evangelou, Evangelos %A Tzoulaki, Ioanna %A Gao, He %A Vergnaud, Anne-Claire %A Mathias, Rasika A %A Becker, Diane M %A Becker, Lewis C %A Burt, Amber %A Crosslin, David R %A Lyytikäinen, Leo-Pekka %A Nikus, Kjell %A Hernesniemi, Jussi %A Kähönen, Mika %A Raitoharju, Emma %A Mononen, Nina %A Raitakari, Olli T %A Lehtimäki, Terho %A Cushman, Mary %A Zakai, Neil A %A Nickerson, Deborah A %A Raffield, Laura M %A Quarells, Rakale %A Willer, Cristen J %A Peloso, Gina M %A Abecasis, Goncalo R %A Liu, Dajiang J %A Deloukas, Panos %A Samani, Nilesh J %A Schunkert, Heribert %A Erdmann, Jeanette %A Fornage, Myriam %A Richard, Melissa %A Tardif, Jean-Claude %A Rioux, John D %A Dubé, Marie-Pierre %A de Denus, Simon %A Lu, Yingchang %A Bottinger, Erwin P %A Loos, Ruth J F %A Smith, Albert Vernon %A Harris, Tamara B %A Launer, Lenore J %A Gudnason, Vilmundur %A Velez Edwards, Digna R %A Torstenson, Eric S %A Liu, Yongmei %A Tracy, Russell P %A Rotter, Jerome I %A Rich, Stephen S %A Highland, Heather M %A Boerwinkle, Eric %A Li, Jin %A Lange, Ethan %A Wilson, James G %A Mihailov, Evelin %A Mägi, Reedik %A Hirschhorn, Joel %A Metspalu, Andres %A Esko, Tõnu %A Vacchi-Suzzi, Caterina %A Nalls, Mike A %A Zonderman, Alan B %A Evans, Michele K %A Engström, Gunnar %A Orho-Melander, Marju %A Melander, Olle %A O'Donoghue, Michelle L %A Waterworth, Dawn M %A Wallentin, Lars %A White, Harvey D %A Floyd, James S %A Bartz, Traci M %A Rice, Kenneth M %A Psaty, Bruce M %A Starr, J M %A Liewald, David C M %A Hayward, Caroline %A Deary, Ian J %A Greinacher, Andreas %A Völker, Uwe %A Thiele, Thomas %A Völzke, Henry %A van Rooij, Frank J A %A Uitterlinden, André G %A Franco, Oscar H %A Dehghan, Abbas %A Edwards, Todd L %A Ganesh, Santhi K %A Kathiresan, Sekar %A Faraday, Nauder %A Auer, Paul L %A Reiner, Alex P %A Lettre, Guillaume %A Johnson, Andrew D %X

Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets' important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors.

%B Am J Hum Genet %V 99 %P 40-55 %8 2016 Jul 7 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/27346686?dopt=Abstract %R 10.1016/j.ajhg.2016.05.005 %0 Journal Article %J Am J Hum Genet %D 2016 %T Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin. %A Liu, Ching-Ti %A Raghavan, Sridharan %A Maruthur, Nisa %A Kabagambe, Edmond Kato %A Hong, Jaeyoung %A Ng, Maggie C Y %A Hivert, Marie-France %A Lu, Yingchang %A An, Ping %A Bentley, Amy R %A Drolet, Anne M %A Gaulton, Kyle J %A Guo, Xiuqing %A Armstrong, Loren L %A Irvin, Marguerite R %A Li, Man %A Lipovich, Leonard %A Rybin, Denis V %A Taylor, Kent D %A Agyemang, Charles %A Palmer, Nicholette D %A Cade, Brian E %A Chen, Wei-Min %A Dauriz, Marco %A Delaney, Joseph A C %A Edwards, Todd L %A Evans, Daniel S %A Evans, Michele K %A Lange, Leslie A %A Leong, Aaron %A Liu, Jingmin %A Liu, Yongmei %A Nayak, Uma %A Patel, Sanjay R %A Porneala, Bianca C %A Rasmussen-Torvik, Laura J %A Snijder, Marieke B %A Stallings, Sarah C %A Tanaka, Toshiko %A Yanek, Lisa R %A Zhao, Wei %A Becker, Diane M %A Bielak, Lawrence F %A Biggs, Mary L %A Bottinger, Erwin P %A Bowden, Donald W %A Chen, Guanjie %A Correa, Adolfo %A Couper, David J %A Crawford, Dana C %A Cushman, Mary %A Eicher, John D %A Fornage, Myriam %A Franceschini, Nora %A Fu, Yi-Ping %A Goodarzi, Mark O %A Gottesman, Omri %A Hara, Kazuo %A Harris, Tamara B %A Jensen, Richard A %A Johnson, Andrew D %A Jhun, Min A %A Karter, Andrew J %A Keller, Margaux F %A Kho, Abel N %A Kizer, Jorge R %A Krauss, Ronald M %A Langefeld, Carl D %A Li, Xiaohui %A Liang, Jingling %A Liu, Simin %A Lowe, William L %A Mosley, Thomas H %A North, Kari E %A Pacheco, Jennifer A %A Peyser, Patricia A %A Patrick, Alan L %A Rice, Kenneth M %A Selvin, Elizabeth %A Sims, Mario %A Smith, Jennifer A %A Tajuddin, Salman M %A Vaidya, Dhananjay %A Wren, Mary P %A Yao, Jie %A Zhu, Xiaofeng %A Ziegler, Julie T %A Zmuda, Joseph M %A Zonderman, Alan B %A Zwinderman, Aeilko H %A Adeyemo, Adebowale %A Boerwinkle, Eric %A Ferrucci, Luigi %A Hayes, M Geoffrey %A Kardia, Sharon L R %A Miljkovic, Iva %A Pankow, James S %A Rotimi, Charles N %A Sale, Michèle M %A Wagenknecht, Lynne E %A Arnett, Donna K %A Chen, Yii-Der Ida %A Nalls, Michael A %A Province, Michael A %A Kao, W H Linda %A Siscovick, David S %A Psaty, Bruce M %A Wilson, James G %A Loos, Ruth J F %A Dupuis, Josée %A Rich, Stephen S %A Florez, Jose C %A Rotter, Jerome I %A Morris, Andrew P %A Meigs, James B %X

Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.

%B Am J Hum Genet %V 99 %P 56-75 %8 2016 Jul 7 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/27321945?dopt=Abstract %R 10.1016/j.ajhg.2016.05.006 %0 Journal Article %J Am J Hum Genet %D 2016 %T Whole-Exome Sequencing Identifies Loci Associated with Blood Cell Traits and Reveals a Role for Alternative GFI1B Splice Variants in Human Hematopoiesis. %A Polfus, Linda M %A Khajuria, Rajiv K %A Schick, Ursula M %A Pankratz, Nathan %A Pazoki, Raha %A Brody, Jennifer A %A Chen, Ming-Huei %A Auer, Paul L %A Floyd, James S %A Huang, Jie %A Lange, Leslie %A van Rooij, Frank J A %A Gibbs, Richard A %A Metcalf, Ginger %A Muzny, Donna %A Veeraraghavan, Narayanan %A Walter, Klaudia %A Chen, Lu %A Yanek, Lisa %A Becker, Lewis C %A Peloso, Gina M %A Wakabayashi, Aoi %A Kals, Mart %A Metspalu, Andres %A Esko, Tõnu %A Fox, Keolu %A Wallace, Robert %A Franceschini, Nora %A Matijevic, Nena %A Rice, Kenneth M %A Bartz, Traci M %A Lyytikäinen, Leo-Pekka %A Kähönen, Mika %A Lehtimäki, Terho %A Raitakari, Olli T %A Li-Gao, Ruifang %A Mook-Kanamori, Dennis O %A Lettre, Guillaume %A van Duijn, Cornelia M %A Franco, Oscar H %A Rich, Stephen S %A Rivadeneira, Fernando %A Hofman, Albert %A Uitterlinden, André G %A Wilson, James G %A Psaty, Bruce M %A Soranzo, Nicole %A Dehghan, Abbas %A Boerwinkle, Eric %A Zhang, Xiaoling %A Johnson, Andrew D %A O'Donnell, Christopher J %A Johnsen, Jill M %A Reiner, Alexander P %A Ganesh, Santhi K %A Sankaran, Vijay G %B Am J Hum Genet %V 99 %P 785 %8 2016 Sep 01 %G eng %N 3 %R 10.1016/j.ajhg.2016.08.002 %0 Journal Article %J Nat Genet %D 2017 %T Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology. %A Brody, Jennifer A %A Morrison, Alanna C %A Bis, Joshua C %A O'Connell, Jeffrey R %A Brown, Michael R %A Huffman, Jennifer E %A Ames, Darren C %A Carroll, Andrew %A Conomos, Matthew P %A Gabriel, Stacey %A Gibbs, Richard A %A Gogarten, Stephanie M %A Gupta, Namrata %A Jaquish, Cashell E %A Johnson, Andrew D %A Lewis, Joshua P %A Liu, Xiaoming %A Manning, Alisa K %A Papanicolaou, George J %A Pitsillides, Achilleas N %A Rice, Kenneth M %A Salerno, William %A Sitlani, Colleen M %A Smith, Nicholas L %A Heckbert, Susan R %A Laurie, Cathy C %A Mitchell, Braxton D %A Vasan, Ramachandran S %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Boerwinkle, Eric %A Psaty, Bruce M %A Cupples, L Adrienne %B Nat Genet %V 49 %P 1560-1563 %8 2017 Oct 27 %G eng %N 11 %R 10.1038/ng.3968 %0 Journal Article %J J Lipid Res %D 2017 %T Discovery and fine-mapping of loci associated with monounsaturated fatty acids through trans-ethnic meta-analysis in Chinese and European populations. %A Hu, Yao %A Tanaka, Toshiko %A Zhu, Jingwen %A Guan, Weihua %A Wu, Jason H Y %A Psaty, Bruce M %A McKnight, Barbara %A King, Irena B %A Sun, Qi %A Richard, Melissa %A Manichaikul, Ani %A Frazier-Wood, Alexis C %A Kabagambe, Edmond K %A Hopkins, Paul N %A Ordovas, Jose M %A Ferrucci, Luigi %A Bandinelli, Stefania %A Arnett, Donna K %A Chen, Yii-der I %A Liang, Shuang %A Siscovick, David S %A Tsai, Michael Y %A Rich, Stephen S %A Fornage, Myriam %A Hu, Frank B %A Rimm, Eric B %A Jensen, Majken K %A Lemaitre, Rozenn N %A Mozaffarian, Dariush %A Steffen, Lyn M %A Morris, Andrew P %A Li, Huaixing %A Lin, Xu %X

Monounsaturated fatty acids (MUFAs) are unsaturated fatty acids with one double bond and are derived from endogenous synthesis and dietary intake. Accumulating evidence has suggested that plasma and erythrocyte MUFA levels were associated with cardiometabolic disorders including cardiovascular disease (CVD), type 2 diabetes (T2D) and metabolic syndrome (MS). Previous genome-wide association studies (GWAS) have identified seven loci for plasma and erythrocyte palmitoleic acid and oleic acid levels in populations of European origin. To identify additional MUFA-associated loci and the potential causal variant at each locus, we performed ethnic-specific GWAS meta-analyses and trans-ethnic meta-analyses in over 15,000 participants of Chinese- and European-ancestry. We identified novel genome-wide significant associations for vaccenic acid at FADS1/2 and PKD2L1 [log10(Bayes factor)>=8.07] and for gondoic acid at FADS1/2 and GCKR [log10(Bayes factor)>=61619;6.22], and also observed improved fine-mapping resolutions at FADS1/2 and GCKR loci. The greatest improvement was observed at GCKR, where the number of variants in the 99% credible set was reduced from 16 (covering ~95kb) to five (covering ~20kb, including a missense variant rs1260326) after trans-ethnic meta-analysis. We also confirmed the previously reported associations of PKD2L1, FADS1/2, GCKR and HIF1AN with palmitoleic acid and of FADS1/2 and LPCAT3 with oleic acid in the Chinese-specific GWAS and trans-ethnic meta-analyses. Pathway-based analyses suggested that the identified loci were enriched in unsaturated fatty acids metabolism and signaling pathways. Our findings provided novel insight into the genetic basis relevant to MUFA metabolism and biology.

%B J Lipid Res %8 2017 Mar 15 %G eng %R 10.1194/jlr.P071860 %0 Journal Article %J Nat Genet %D 2017 %T Exome-wide association study of plasma lipids in >300,000 individuals. %A Liu, Dajiang J %A Peloso, Gina M %A Yu, Haojie %A Butterworth, Adam S %A Wang, Xiao %A Mahajan, Anubha %A Saleheen, Danish %A Emdin, Connor %A Alam, Dewan %A Alves, Alexessander Couto %A Amouyel, Philippe %A Di Angelantonio, Emanuele %A Arveiler, Dominique %A Assimes, Themistocles L %A Auer, Paul L %A Baber, Usman %A Ballantyne, Christie M %A Bang, Lia E %A Benn, Marianne %A Bis, Joshua C %A Boehnke, Michael %A Boerwinkle, Eric %A Bork-Jensen, Jette %A Bottinger, Erwin P %A Brandslund, Ivan %A Brown, Morris %A Busonero, Fabio %A Caulfield, Mark J %A Chambers, John C %A Chasman, Daniel I %A Chen, Y Eugene %A Chen, Yii-Der Ida %A Chowdhury, Rajiv %A Christensen, Cramer %A Chu, Audrey Y %A Connell, John M %A Cucca, Francesco %A Cupples, L Adrienne %A Damrauer, Scott M %A Davies, Gail %A Deary, Ian J %A Dedoussis, George %A Denny, Joshua C %A Dominiczak, Anna %A Dubé, Marie-Pierre %A Ebeling, Tapani %A Eiriksdottir, Gudny %A Esko, Tõnu %A Farmaki, Aliki-Eleni %A Feitosa, Mary F %A Ferrario, Marco %A Ferrieres, Jean %A Ford, Ian %A Fornage, Myriam %A Franks, Paul W %A Frayling, Timothy M %A Frikke-Schmidt, Ruth %A Fritsche, Lars G %A Frossard, Philippe %A Fuster, Valentin %A Ganesh, Santhi K %A Gao, Wei %A Garcia, Melissa E %A Gieger, Christian %A Giulianini, Franco %A Goodarzi, Mark O %A Grallert, Harald %A Grarup, Niels %A Groop, Leif %A Grove, Megan L %A Gudnason, Vilmundur %A Hansen, Torben %A Harris, Tamara B %A Hayward, Caroline %A Hirschhorn, Joel N %A Holmen, Oddgeir L %A Huffman, Jennifer %A Huo, Yong %A Hveem, Kristian %A Jabeen, Sehrish %A Jackson, Anne U %A Jakobsdottir, Johanna %A Jarvelin, Marjo-Riitta %A Jensen, Gorm B %A Jørgensen, Marit E %A Jukema, J Wouter %A Justesen, Johanne M %A Kamstrup, Pia R %A Kanoni, Stavroula %A Karpe, Fredrik %A Kee, Frank %A Khera, Amit V %A Klarin, Derek %A Koistinen, Heikki A %A Kooner, Jaspal S %A Kooperberg, Charles %A Kuulasmaa, Kari %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo %A Langenberg, Claudia %A Langsted, Anne %A Launer, Lenore J %A Lauritzen, Torsten %A Liewald, David C M %A Lin, Li An %A Linneberg, Allan %A Loos, Ruth J F %A Lu, Yingchang %A Lu, Xiangfeng %A Mägi, Reedik %A Mälarstig, Anders %A Manichaikul, Ani %A Manning, Alisa K %A Mäntyselkä, Pekka %A Marouli, Eirini %A Masca, Nicholas G D %A Maschio, Andrea %A Meigs, James B %A Melander, Olle %A Metspalu, Andres %A Morris, Andrew P %A Morrison, Alanna C %A Mulas, Antonella %A Müller-Nurasyid, Martina %A Munroe, Patricia B %A Neville, Matt J %A Nielsen, Jonas B %A Nielsen, Sune F %A Nordestgaard, Børge G %A Ordovas, Jose M %A Mehran, Roxana %A O'Donnell, Christoper J %A Orho-Melander, Marju %A Molony, Cliona M %A Muntendam, Pieter %A Padmanabhan, Sandosh %A Palmer, Colin N A %A Pasko, Dorota %A Patel, Aniruddh P %A Pedersen, Oluf %A Perola, Markus %A Peters, Annette %A Pisinger, Charlotta %A Pistis, Giorgio %A Polasek, Ozren %A Poulter, Neil %A Psaty, Bruce M %A Rader, Daniel J %A Rasheed, Asif %A Rauramaa, Rainer %A Reilly, Dermot F %A Reiner, Alex P %A Renstrom, Frida %A Rich, Stephen S %A Ridker, Paul M %A Rioux, John D %A Robertson, Neil R %A Roden, Dan M %A Rotter, Jerome I %A Rudan, Igor %A Salomaa, Veikko %A Samani, Nilesh J %A Sanna, Serena %A Sattar, Naveed %A Schmidt, Ellen M %A Scott, Robert A %A Sever, Peter %A Sevilla, Raquel S %A Shaffer, Christian M %A Sim, Xueling %A Sivapalaratnam, Suthesh %A Small, Kerrin S %A Smith, Albert V %A Smith, Blair H %A Somayajula, Sangeetha %A Southam, Lorraine %A Spector, Timothy D %A Speliotes, Elizabeth K %A Starr, John M %A Stirrups, Kathleen E %A Stitziel, Nathan %A Strauch, Konstantin %A Stringham, Heather M %A Surendran, Praveen %A Tada, Hayato %A Tall, Alan R %A Tang, Hua %A Tardif, Jean-Claude %A Taylor, Kent D %A Trompet, Stella %A Tsao, Philip S %A Tuomilehto, Jaakko %A Tybjaerg-Hansen, Anne %A van Zuydam, Natalie R %A Varbo, Anette %A Varga, Tibor V %A Virtamo, Jarmo %A Waldenberger, Melanie %A Wang, Nan %A Wareham, Nick J %A Warren, Helen R %A Weeke, Peter E %A Weinstock, Joshua %A Wessel, Jennifer %A Wilson, James G %A Wilson, Peter W F %A Xu, Ming %A Yaghootkar, Hanieh %A Young, Robin %A Zeggini, Eleftheria %A Zhang, He %A Zheng, Neil S %A Zhang, Weihua %A Zhang, Yan %A Zhou, Wei %A Zhou, Yanhua %A Zoledziewska, Magdalena %A Howson, Joanna M M %A Danesh, John %A McCarthy, Mark I %A Cowan, Chad A %A Abecasis, Goncalo %A Deloukas, Panos %A Musunuru, Kiran %A Willer, Cristen J %A Kathiresan, Sekar %K Coronary Artery Disease %K Diabetes Mellitus, Type 2 %K Exome %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genetic Variation %K Genotype %K Humans %K Lipids %K Macular Degeneration %K Phenotype %K Risk Factors %X

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

%B Nat Genet %V 49 %P 1758-1766 %8 2017 Dec %G eng %N 12 %R 10.1038/ng.3977 %0 Journal Article %J Heart Rhythm %D 2017 %T Fine mapping of QT interval regions in global populations refines previously identified QT interval loci and identifies signals unique to African and Hispanic descent populations. %A Avery, Christy L %A Wassel, Christina L %A Richard, Melissa A %A Highland, Heather M %A Bien, Stephanie %A Zubair, Niha %A Soliman, Elsayed Z %A Fornage, Myriam %A Bielinski, Suzette J %A Tao, Ran %A Seyerle, Amanda A %A Shah, Sanjiv J %A Lloyd-Jones, Donald M %A Buyske, Steven %A Rotter, Jerome I %A Post, Wendy S %A Rich, Stephen S %A Hindorff, Lucia A %A Jeff, Janina M %A Shohet, Ralph V %A Sotoodehnia, Nona %A Lin, Dan Yu %A Whitsel, Eric A %A Peters, Ulrike %A Haiman, Christopher A %A Crawford, Dana C %A Kooperberg, Charles %A North, Kari E %X

BACKGROUND: The electrocardiographically measured QT interval (QT) is heritable and its prolongation is an established risk factor for several cardiovascular diseases. Yet, most QT genetic studies have been performed in European ancestral populations, possibly reducing their global relevance.

OBJECTIVE: To leverage diversity and improve biological insight, we fine mapped 16 of the 35 previously identified QT loci (46%) in populations of African American (n = 12,410) and Hispanic/Latino (n = 14,837) ancestry.

METHODS: Racial/ethnic-specific multiple linear regression analyses adjusted for heart rate and clinical covariates were examined separately and in combination after inverse-variance weighted trans-ethnic meta-analysis.

RESULTS: The 16 fine-mapped QT loci included on the Illumina Metabochip represented 21 independent signals, of which 16 (76%) were significantly (P-value≤9.1×10(-5)) associated with QT. Through sequential conditional analysis we also identified three trans-ethnic novel SNPs at ATP1B1, SCN5A-SCN10A, and KCNQ1 and three Hispanic/Latino-specific novel SNPs at NOS1AP and SCN5A-SCN10A (two novel SNPs) with evidence of associations with QT independent of previous identified GWAS lead SNPs. Linkage disequilibrium patterns helped to narrow the region likely to contain the functional variants at several loci, including NOS1AP, USP50-TRPM7, and PRKCA, although intervals surrounding SLC35F1-PLN and CNOT1 remained broad in size (>100 kb). Finally, bioinformatics-based functional characterization suggested a regulatory function in cardiac tissues for the majority of independent signals that generalized and the novel SNPs.

CONCLUSION: Our findings suggest that a majority of identified SNPs implicate gene regulatory dysfunction in QT prolongation, that the same loci influence variation in QT across global populations, and that additional, novel, population-specific QT signals exist.

%B Heart Rhythm %V 14 %P 572-580 %8 2017 Apr %G eng %N 4 %R 10.1016/j.hrthm.2016.12.021 %0 Journal Article %J Nat Genet %D 2017 %T Genetic loci associated with chronic obstructive pulmonary disease overlap with loci for lung function and pulmonary fibrosis. %A Hobbs, Brian D %A de Jong, Kim %A Lamontagne, Maxime %A Bossé, Yohan %A Shrine, Nick %A Artigas, Maria Soler %A Wain, Louise V %A Hall, Ian P %A Jackson, Victoria E %A Wyss, Annah B %A London, Stephanie J %A North, Kari E %A Franceschini, Nora %A Strachan, David P %A Beaty, Terri H %A Hokanson, John E %A Crapo, James D %A Castaldi, Peter J %A Chase, Robert P %A Bartz, Traci M %A Heckbert, Susan R %A Psaty, Bruce M %A Gharib, Sina A %A Zanen, Pieter %A Lammers, Jan W %A Oudkerk, Matthijs %A Groen, H J %A Locantore, Nicholas %A Tal-Singer, Ruth %A Rennard, Stephen I %A Vestbo, Jørgen %A Timens, Wim %A Paré, Peter D %A Latourelle, Jeanne C %A Dupuis, Josée %A O'Connor, George T %A Wilk, Jemma B %A Kim, Woo Jin %A Lee, Mi Kyeong %A Oh, Yeon-Mok %A Vonk, Judith M %A de Koning, Harry J %A Leng, Shuguang %A Belinsky, Steven A %A Tesfaigzi, Yohannes %A Manichaikul, Ani %A Wang, Xin-Qun %A Rich, Stephen S %A Barr, R Graham %A Sparrow, David %A Litonjua, Augusto A %A Bakke, Per %A Gulsvik, Amund %A Lahousse, Lies %A Brusselle, Guy G %A Stricker, Bruno H %A Uitterlinden, André G %A Ampleford, Elizabeth J %A Bleecker, Eugene R %A Woodruff, Prescott G %A Meyers, Deborah A %A Qiao, Dandi %A Lomas, David A %A Yim, Jae-Joon %A Kim, Deog Kyeom %A Hawrylkiewicz, Iwona %A Sliwinski, Pawel %A Hardin, Megan %A Fingerlin, Tasha E %A Schwartz, David A %A Postma, Dirkje S %A MacNee, William %A Tobin, Martin D %A Silverman, Edwin K %A Boezen, H Marike %A Cho, Michael H %X

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide. We performed a genetic association study in 15,256 cases and 47,936 controls, with replication of select top results (P < 5 × 10(-6)) in 9,498 cases and 9,748 controls. In the combined meta-analysis, we identified 22 loci associated at genome-wide significance, including 13 new associations with COPD. Nine of these 13 loci have been associated with lung function in general population samples, while 4 (EEFSEC, DSP, MTCL1, and SFTPD) are new. We noted two loci shared with pulmonary fibrosis (FAM13A and DSP) but that had opposite risk alleles for COPD. None of our loci overlapped with genome-wide associations for asthma, although one locus has been implicated in joint susceptibility to asthma and obesity. We also identified genetic correlation between COPD and asthma. Our findings highlight new loci associated with COPD, demonstrate the importance of specific loci associated with lung function to COPD, and identify potential regions of genetic overlap between COPD and other respiratory diseases.

%B Nat Genet %V 49 %P 426-432 %8 2017 Mar %G eng %N 3 %R 10.1038/ng.3752 %0 Journal Article %J Mol Nutr Food Res %D 2017 %T Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent. %A Smith, Caren E %A Follis, Jack L %A Dashti, Hassan S %A Tanaka, Toshiko %A Graff, Mariaelisa %A Fretts, Amanda M %A Kilpeläinen, Tuomas O %A Wojczynski, Mary K %A Richardson, Kris %A Nalls, Mike A %A Schulz, Christina-Alexandra %A Liu, Yongmei %A Frazier-Wood, Alexis C %A van Eekelen, Esther %A Wang, Carol %A de Vries, Paul S %A Mikkilä, Vera %A Rohde, Rebecca %A Psaty, Bruce M %A Hansen, Torben %A Feitosa, Mary F %A Lai, Chao-Qiang %A Houston, Denise K %A Ferruci, Luigi %A Ericson, Ulrika %A Wang, Zhe %A de Mutsert, Renée %A Oddy, Wendy H %A de Jonge, Ester A L %A Seppälä, Ilkka %A Justice, Anne E %A Lemaitre, Rozenn N %A Sørensen, Thorkild I A %A Province, Michael A %A Parnell, Laurence D %A Garcia, Melissa E %A Bandinelli, Stefania %A Orho-Melander, Marju %A Rich, Stephen S %A Rosendaal, Frits R %A Pennell, Craig E %A Kiefte-de Jong, Jessica C %A Kähönen, Mika %A Young, Kristin L %A Pedersen, Oluf %A Aslibekyan, Stella %A Rotter, Jerome I %A Mook-Kanamori, Dennis O %A Zillikens, M Carola %A Raitakari, Olli T %A North, Kari E %A Overvad, Kim %A Arnett, Donna K %A Hofman, Albert %A Lehtimäki, Terho %A Tjønneland, Anne %A Uitterlinden, André G %A Rivadeneira, Fernando %A Franco, Oscar H %A German, J Bruce %A Siscovick, David S %A Cupples, L Adrienne %A Ordovas, Jose M %X

SCOPE: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption.

METHODS AND RESULTS: A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10-7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 10-8) such that each serving of low-fat dairy was associated with 0.225 kg m-2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure.

CONCLUSION: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight.

%B Mol Nutr Food Res %8 2017 Sep 21 %G eng %R 10.1002/mnfr.201700347 %0 Journal Article %J PLoS Med %D 2017 %T Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis. %A Wheeler, Eleanor %A Leong, Aaron %A Liu, Ching-Ti %A Hivert, Marie-France %A Strawbridge, Rona J %A Podmore, Clara %A Li, Man %A Yao, Jie %A Sim, Xueling %A Hong, Jaeyoung %A Chu, Audrey Y %A Zhang, Weihua %A Wang, Xu %A Chen, Peng %A Maruthur, Nisa M %A Porneala, Bianca C %A Sharp, Stephen J %A Jia, Yucheng %A Kabagambe, Edmond K %A Chang, Li-Ching %A Chen, Wei-Min %A Elks, Cathy E %A Evans, Daniel S %A Fan, Qiao %A Giulianini, Franco %A Go, Min Jin %A Hottenga, Jouke-Jan %A Hu, Yao %A Jackson, Anne U %A Kanoni, Stavroula %A Kim, Young Jin %A Kleber, Marcus E %A Ladenvall, Claes %A Lecoeur, Cécile %A Lim, Sing-Hui %A Lu, Yingchang %A Mahajan, Anubha %A Marzi, Carola %A Nalls, Mike A %A Navarro, Pau %A Nolte, Ilja M %A Rose, Lynda M %A Rybin, Denis V %A Sanna, Serena %A Shi, Yuan %A Stram, Daniel O %A Takeuchi, Fumihiko %A Tan, Shu Pei %A van der Most, Peter J %A van Vliet-Ostaptchouk, Jana V %A Wong, Andrew %A Yengo, Loic %A Zhao, Wanting %A Goel, Anuj %A Martinez Larrad, Maria Teresa %A Radke, Dörte %A Salo, Perttu %A Tanaka, Toshiko %A van Iperen, Erik P A %A Abecasis, Goncalo %A Afaq, Saima %A Alizadeh, Behrooz Z %A Bertoni, Alain G %A Bonnefond, Amélie %A Böttcher, Yvonne %A Bottinger, Erwin P %A Campbell, Harry %A Carlson, Olga D %A Chen, Chien-Hsiun %A Cho, Yoon Shin %A Garvey, W Timothy %A Gieger, Christian %A Goodarzi, Mark O %A Grallert, Harald %A Hamsten, Anders %A Hartman, Catharina A %A Herder, Christian %A Hsiung, Chao Agnes %A Huang, Jie %A Igase, Michiya %A Isono, Masato %A Katsuya, Tomohiro %A Khor, Chiea-Chuen %A Kiess, Wieland %A Kohara, Katsuhiko %A Kovacs, Peter %A Lee, Juyoung %A Lee, Wen-Jane %A Lehne, Benjamin %A Li, Huaixing %A Liu, Jianjun %A Lobbens, Stephane %A Luan, Jian'an %A Lyssenko, Valeriya %A Meitinger, Thomas %A Miki, Tetsuro %A Miljkovic, Iva %A Moon, Sanghoon %A Mulas, Antonella %A Müller, Gabriele %A Müller-Nurasyid, Martina %A Nagaraja, Ramaiah %A Nauck, Matthias %A Pankow, James S %A Polasek, Ozren %A Prokopenko, Inga %A Ramos, Paula S %A Rasmussen-Torvik, Laura %A Rathmann, Wolfgang %A Rich, Stephen S %A Robertson, Neil R %A Roden, Michael %A Roussel, Ronan %A Rudan, Igor %A Scott, Robert A %A Scott, William R %A Sennblad, Bengt %A Siscovick, David S %A Strauch, Konstantin %A Sun, Liang %A Swertz, Morris %A Tajuddin, Salman M %A Taylor, Kent D %A Teo, Yik-Ying %A Tham, Yih Chung %A Tönjes, Anke %A Wareham, Nicholas J %A Willemsen, Gonneke %A Wilsgaard, Tom %A Hingorani, Aroon D %A Egan, Josephine %A Ferrucci, Luigi %A Hovingh, G Kees %A Jula, Antti %A Kivimaki, Mika %A Kumari, Meena %A Njølstad, Inger %A Palmer, Colin N A %A Serrano Ríos, Manuel %A Stumvoll, Michael %A Watkins, Hugh %A Aung, Tin %A Blüher, Matthias %A Boehnke, Michael %A Boomsma, Dorret I %A Bornstein, Stefan R %A Chambers, John C %A Chasman, Daniel I %A Chen, Yii-Der Ida %A Chen, Yduan-Tsong %A Cheng, Ching-Yu %A Cucca, Francesco %A de Geus, Eco J C %A Deloukas, Panos %A Evans, Michele K %A Fornage, Myriam %A Friedlander, Yechiel %A Froguel, Philippe %A Groop, Leif %A Gross, Myron D %A Harris, Tamara B %A Hayward, Caroline %A Heng, Chew-Kiat %A Ingelsson, Erik %A Kato, Norihiro %A Kim, Bong-Jo %A Koh, Woon-Puay %A Kooner, Jaspal S %A Körner, Antje %A Kuh, Diana %A Kuusisto, Johanna %A Laakso, Markku %A Lin, Xu %A Liu, Yongmei %A Loos, Ruth J F %A Magnusson, Patrik K E %A März, Winfried %A McCarthy, Mark I %A Oldehinkel, Albertine J %A Ong, Ken K %A Pedersen, Nancy L %A Pereira, Mark A %A Peters, Annette %A Ridker, Paul M %A Sabanayagam, Charumathi %A Sale, Michele %A Saleheen, Danish %A Saltevo, Juha %A Schwarz, Peter Eh %A Sheu, Wayne H H %A Snieder, Harold %A Spector, Timothy D %A Tabara, Yasuharu %A Tuomilehto, Jaakko %A van Dam, Rob M %A Wilson, James G %A Wilson, James F %A Wolffenbuttel, Bruce H R %A Wong, Tien Yin %A Wu, Jer-Yuarn %A Yuan, Jian-Min %A Zonderman, Alan B %A Soranzo, Nicole %A Guo, Xiuqing %A Roberts, David J %A Florez, Jose C %A Sladek, Robert %A Dupuis, Josée %A Morris, Andrew P %A Tai, E-Shyong %A Selvin, Elizabeth %A Rotter, Jerome I %A Langenberg, Claudia %A Barroso, Inês %A Meigs, James B %K Diabetes Mellitus, Type 2 %K Genetic Variation %K Genome-Wide Association Study %K Glycated Hemoglobin A %K Humans %K Phenotype %K Risk %X

BACKGROUND: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.

METHODS & FINDINGS: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 × 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.

CONCLUSIONS: As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.

%B PLoS Med %V 14 %P e1002383 %8 2017 Sep %G eng %N 9 %R 10.1371/journal.pmed.1002383 %0 Journal Article %J Circ Genom Precis Med %D 2018 %T Common Coding Variants in Are Associated With the Nav1.8 Late Current and Cardiac Conduction. %A Macri, Vincenzo %A Brody, Jennifer A %A Arking, Dan E %A Hucker, William J %A Yin, Xiaoyan %A Lin, Honghuang %A Mills, Robert W %A Sinner, Moritz F %A Lubitz, Steven A %A Liu, Ching-Ti %A Morrison, Alanna C %A Alonso, Alvaro %A Li, Ning %A Fedorov, Vadim V %A Janssen, Paul M %A Bis, Joshua C %A Heckbert, Susan R %A Dolmatova, Elena V %A Lumley, Thomas %A Sitlani, Colleen M %A Cupples, L Adrienne %A Pulit, Sara L %A Newton-Cheh, Christopher %A Barnard, John %A Smith, Jonathan D %A Van Wagoner, David R %A Chung, Mina K %A Vlahakes, Gus J %A O'Donnell, Christopher J %A Rotter, Jerome I %A Margulies, Kenneth B %A Morley, Michael P %A Cappola, Thomas P %A Benjamin, Emelia J %A Muzny, Donna %A Gibbs, Richard A %A Jackson, Rebecca D %A Magnani, Jared W %A Herndon, Caroline N %A Rich, Stephen S %A Psaty, Bruce M %A Milan, David J %A Boerwinkle, Eric %A Mohler, Peter J %A Sotoodehnia, Nona %A Ellinor, Patrick T %X

BACKGROUND: Genetic variants at the / locus are strongly associated with electrocardiographic PR and QRS intervals. While is the canonical cardiac sodium channel gene, the role of in cardiac conduction is less well characterized.

METHODS: We sequenced the locus in 3699 European-ancestry individuals to identify variants associated with cardiac conduction, and replicated our findings in 21,000 individuals of European ancestry. We examined association with expression in human atrial tissue. We explored the biophysical effect of variation on channel function using cellular electrophysiology.

RESULTS: We identified 2 intronic single nucleotide polymorphisms in high linkage disequilibrium (  =0.86) with each other to be the strongest signals for PR (rs10428132, β=-4.74, =1.52×10) and QRS intervals (rs6599251, QRS β=-0.73; =1.2×10), respectively. Although these variants were not associated with or expression in human atrial tissue (n=490), they were in high linkage disequilibrium (  ≥0.72) with a common missense variant, rs6795970 (V1073A). In total, we identified 7 missense variants, 4 of which (I962V, P1045T, V1073A, and L1092P) were associated with cardiac conduction. These 4 missense variants cluster in the cytoplasmic linker of the second and third domains of the SCN10A protein and together form 6 common haplotypes. Using cellular electrophysiology, we found that haplotypes associated with shorter PR intervals had a significantly larger percentage of late current compared with wild-type (I962V+V1073A+L1092P, 20.2±3.3%, =0.03, and I962V+V1073A, 22.4±0.8%, =0.0004 versus wild-type 11.7±1.6%), and the haplotype associated with the longest PR interval had a significantly smaller late current percentage (P1045T, 6.4±1.2%, =0.03).

CONCLUSIONS: Our findings suggest an association between genetic variation in , the late sodium current, and alterations in cardiac conduction.

%B Circ Genom Precis Med %V 11 %P e001663 %8 2018 May %G eng %N 5 %R 10.1161/CIRCGEN.116.001663 %0 Journal Article %J PLoS One %D 2018 %T Genome-wide association meta-analysis of circulating odd-numbered chain saturated fatty acids: Results from the CHARGE Consortium. %A de Oliveira Otto, Marcia C %A Lemaitre, Rozenn N %A Sun, Qi %A King, Irena B %A Wu, Jason H Y %A Manichaikul, Ani %A Rich, Stephen S %A Tsai, Michael Y %A Chen, Y D %A Fornage, Myriam %A Weihua, Guan %A Aslibekyan, Stella %A Irvin, Marguerite R %A Kabagambe, Edmond K %A Arnett, Donna K %A Jensen, Majken K %A McKnight, Barbara %A Psaty, Bruce M %A Steffen, Lyn M %A Smith, Caren E %A Riserus, Ulf %A Lind, Lars %A Hu, Frank B %A Rimm, Eric B %A Siscovick, David S %A Mozaffarian, Dariush %K Fatty Acids %K Genome-Wide Association Study %K Humans %K Introns %K Lactase %K Myosins %K Polymorphism, Single Nucleotide %K Sphingomyelins %K Sphingosine N-Acyltransferase %K Tumor Suppressor Proteins %X

BACKGROUND: Odd-numbered chain saturated fatty acids (OCSFA) have been associated with potential health benefits. Although some OCSFA (e.g., C15:0 and C17:0) are found in meats and dairy products, sources and metabolism of C19:0 and C23:0 are relatively unknown, and the influence of non-dietary determinants, including genetic factors, on circulating levels of OCSFA is not established.

OBJECTIVE: To elucidate the biological processes that influence circulating levels of OCSFA by investigating associations between genetic variation and OCSFA.

DESIGN: We performed a meta-analysis of genome-wide association studies (GWAS) of plasma phospholipid/erythrocyte levels of C15:0, C17:0, C19:0, and C23:0 among 11,494 individuals of European descent. We also investigated relationships between specific single nucleotide polymorphisms (SNPs) in the lactase (LCT) gene, associated with adult-onset lactase intolerance, with circulating levels of dairy-derived OCSFA, and evaluated associations of candidate sphingolipid genes with C23:0 levels.

RESULTS: We found no genome-wide significant evidence that common genetic variation is associated with circulating levels of C15:0 or C23:0. In two cohorts with available data, we identified one intronic SNP (rs13361131) in myosin X gene (MYO10) associated with C17:0 level (P = 1.37×10-8), and two intronic SNP (rs12874278 and rs17363566) in deleted in lymphocytic leukemia 1 (DLEU1) region associated with C19:0 level (P = 7.07×10-9). In contrast, when using a candidate-gene approach, we found evidence that three SNPs in LCT (rs11884924, rs16832067, and rs3816088) are associated with circulating C17:0 level (adjusted P = 4×10-2). In addition, nine SNPs in the ceramide synthase 4 (CERS4) region were associated with circulating C23:0 levels (adjusted P<5×10-2).

CONCLUSIONS: Our findings suggest that circulating levels of OCSFA may be predominantly influenced by non-genetic factors. SNPs associated with C17:0 level in the LCT gene may reflect genetic influence in dairy consumption or in metabolism of dairy foods. SNPs associated with C23:0 may reflect a role of genetic factors in the synthesis of sphingomyelin.

%B PLoS One %V 13 %P e0196951 %8 2018 %G eng %N 5 %R 10.1371/journal.pone.0196951 %0 Journal Article %J Nat Commun %D 2018 %T Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels. %A Jiang, Xia %A O'Reilly, Paul F %A Aschard, Hugues %A Hsu, Yi-Hsiang %A Richards, J Brent %A Dupuis, Josée %A Ingelsson, Erik %A Karasik, David %A Pilz, Stefan %A Berry, Diane %A Kestenbaum, Bryan %A Zheng, Jusheng %A Luan, Jianan %A Sofianopoulou, Eleni %A Streeten, Elizabeth A %A Albanes, Demetrius %A Lutsey, Pamela L %A Yao, Lu %A Tang, Weihong %A Econs, Michael J %A Wallaschofski, Henri %A Völzke, Henry %A Zhou, Ang %A Power, Chris %A McCarthy, Mark I %A Michos, Erin D %A Boerwinkle, Eric %A Weinstein, Stephanie J %A Freedman, Neal D %A Huang, Wen-Yi %A van Schoor, Natasja M %A van der Velde, Nathalie %A Groot, Lisette C P G M de %A Enneman, Anke %A Cupples, L Adrienne %A Booth, Sarah L %A Vasan, Ramachandran S %A Liu, Ching-Ti %A Zhou, Yanhua %A Ripatti, Samuli %A Ohlsson, Claes %A Vandenput, Liesbeth %A Lorentzon, Mattias %A Eriksson, Johan G %A Shea, M Kyla %A Houston, Denise K %A Kritchevsky, Stephen B %A Liu, Yongmei %A Lohman, Kurt K %A Ferrucci, Luigi %A Peacock, Munro %A Gieger, Christian %A Beekman, Marian %A Slagboom, Eline %A Deelen, Joris %A Heemst, Diana van %A Kleber, Marcus E %A März, Winfried %A de Boer, Ian H %A Wood, Alexis C %A Rotter, Jerome I %A Rich, Stephen S %A Robinson-Cohen, Cassianne %A den Heijer, Martin %A Jarvelin, Marjo-Riitta %A Cavadino, Alana %A Joshi, Peter K %A Wilson, James F %A Hayward, Caroline %A Lind, Lars %A Michaëlsson, Karl %A Trompet, Stella %A Zillikens, M Carola %A Uitterlinden, André G %A Rivadeneira, Fernando %A Broer, Linda %A Zgaga, Lina %A Campbell, Harry %A Theodoratou, Evropi %A Farrington, Susan M %A Timofeeva, Maria %A Dunlop, Malcolm G %A Valdes, Ana M %A Tikkanen, Emmi %A Lehtimäki, Terho %A Lyytikäinen, Leo-Pekka %A Kähönen, Mika %A Raitakari, Olli T %A Mikkilä, Vera %A Ikram, M Arfan %A Sattar, Naveed %A Jukema, J Wouter %A Wareham, Nicholas J %A Langenberg, Claudia %A Forouhi, Nita G %A Gundersen, Thomas E %A Khaw, Kay-Tee %A Butterworth, Adam S %A Danesh, John %A Spector, Timothy %A Wang, Thomas J %A Hyppönen, Elina %A Kraft, Peter %A Kiel, Douglas P %X

Vitamin D is a steroid hormone precursor that is associated with a range of human traits and diseases. Previous GWAS of serum 25-hydroxyvitamin D concentrations have identified four genome-wide significant loci (GC, NADSYN1/DHCR7, CYP2R1, CYP24A1). In this study, we expand the previous SUNLIGHT Consortium GWAS discovery sample size from 16,125 to 79,366 (all European descent). This larger GWAS yields two additional loci harboring genome-wide significant variants (P = 4.7×10 at rs8018720 in SEC23A, and P = 1.9×10 at rs10745742 in AMDHD1). The overall estimate of heritability of 25-hydroxyvitamin D serum concentrations attributable to GWAS common SNPs is 7.5%, with statistically significant loci explaining 38% of this total. Further investigation identifies signal enrichment in immune and hematopoietic tissues, and clustering with autoimmune diseases in cell-type-specific analysis. Larger studies are required to identify additional common SNPs, and to explore the role of rare or structural variants and gene-gene interactions in the heritability of circulating 25-hydroxyvitamin D levels.

%B Nat Commun %V 9 %P 260 %8 2018 Jan 17 %G eng %N 1 %R 10.1038/s41467-017-02662-2 %0 Journal Article %J Br J Nutr %D 2018 %T Meta-analysis across Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium provides evidence for an association of serum vitamin D with pulmonary function. %A Xu, Jiayi %A Bartz, Traci M %A Chittoor, Geetha %A Eiriksdottir, Gudny %A Manichaikul, Ani W %A Sun, Fangui %A Terzikhan, Natalie %A Zhou, Xia %A Booth, Sarah L %A Brusselle, Guy G %A de Boer, Ian H %A Fornage, Myriam %A Frazier-Wood, Alexis C %A Graff, Mariaelisa %A Gudnason, Vilmundur %A Harris, Tamara B %A Hofman, Albert %A Hou, Ruixue %A Houston, Denise K %A Jacobs, David R %A Kritchevsky, Stephen B %A Latourelle, Jeanne %A Lemaitre, Rozenn N %A Lutsey, Pamela L %A O'Connor, George %A Oelsner, Elizabeth C %A Pankow, James S %A Psaty, Bruce M %A Rohde, Rebecca R %A Rich, Stephen S %A Rotter, Jerome I %A Smith, Lewis J %A Stricker, Bruno H %A Voruganti, V Saroja %A Wang, Thomas J %A Zillikens, M Carola %A Barr, R Graham %A Dupuis, Josée %A Gharib, Sina A %A Lahousse, Lies %A London, Stephanie J %A North, Kari E %A Smith, Albert V %A Steffen, Lyn M %A Hancock, Dana B %A Cassano, Patricia A %X

The role that vitamin D plays in pulmonary function remains uncertain. Epidemiological studies reported mixed findings for serum 25-hydroxyvitamin D (25(OH)D)-pulmonary function association. We conducted the largest cross-sectional meta-analysis of the 25(OH)D-pulmonary function association to date, based on nine European ancestry (EA) cohorts (n 22 838) and five African ancestry (AA) cohorts (n 4290) in the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium. Data were analysed using linear models by cohort and ancestry. Effect modification by smoking status (current/former/never) was tested. Results were combined using fixed-effects meta-analysis. Mean serum 25(OH)D was 68 (sd 29) nmol/l for EA and 49 (sd 21) nmol/l for AA. For each 1 nmol/l higher 25(OH)D, forced expiratory volume in the 1st second (FEV1) was higher by 1·1 ml in EA (95 % CI 0·9, 1·3; P<0·0001) and 1·8 ml (95 % CI 1·1, 2·5; P<0·0001) in AA (P race difference=0·06), and forced vital capacity (FVC) was higher by 1·3 ml in EA (95 % CI 1·0, 1·6; P<0·0001) and 1·5 ml (95 % CI 0·8, 2·3; P=0·0001) in AA (P race difference=0·56). Among EA, the 25(OH)D-FVC association was stronger in smokers: per 1 nmol/l higher 25(OH)D, FVC was higher by 1·7 ml (95 % CI 1·1, 2·3) for current smokers and 1·7 ml (95 % CI 1·2, 2·1) for former smokers, compared with 0·8 ml (95 % CI 0·4, 1·2) for never smokers. In summary, the 25(OH)D associations with FEV1 and FVC were positive in both ancestries. In EA, a stronger association was observed for smokers compared with never smokers, which supports the importance of vitamin D in vulnerable populations.

%B Br J Nutr %P 1-12 %8 2018 Sep 12 %G eng %R 10.1017/S0007114518002180 %0 Journal Article %J Wellcome Open Res %D 2018 %T Meta-analysis of exome array data identifies six novel genetic loci for lung function. %A Jackson, Victoria E %A Latourelle, Jeanne C %A Wain, Louise V %A Smith, Albert V %A Grove, Megan L %A Bartz, Traci M %A Obeidat, Ma'en %A Province, Michael A %A Gao, Wei %A Qaiser, Beenish %A Porteous, David J %A Cassano, Patricia A %A Ahluwalia, Tarunveer S %A Grarup, Niels %A Li, Jin %A Altmaier, Elisabeth %A Marten, Jonathan %A Harris, Sarah E %A Manichaikul, Ani %A Pottinger, Tess D %A Li-Gao, Ruifang %A Lind-Thomsen, Allan %A Mahajan, Anubha %A Lahousse, Lies %A Imboden, Medea %A Teumer, Alexander %A Prins, Bram %A Lyytikäinen, Leo-Pekka %A Eiriksdottir, Gudny %A Franceschini, Nora %A Sitlani, Colleen M %A Brody, Jennifer A %A Bossé, Yohan %A Timens, Wim %A Kraja, Aldi %A Loukola, Anu %A Tang, Wenbo %A Liu, Yongmei %A Bork-Jensen, Jette %A Justesen, Johanne M %A Linneberg, Allan %A Lange, Leslie A %A Rawal, Rajesh %A Karrasch, Stefan %A Huffman, Jennifer E %A Smith, Blair H %A Davies, Gail %A Burkart, Kristin M %A Mychaleckyj, Josyf C %A Bonten, Tobias N %A Enroth, Stefan %A Lind, Lars %A Brusselle, Guy G %A Kumar, Ashish %A Stubbe, Beate %A Kähönen, Mika %A Wyss, Annah B %A Psaty, Bruce M %A Heckbert, Susan R %A Hao, Ke %A Rantanen, Taina %A Kritchevsky, Stephen B %A Lohman, Kurt %A Skaaby, Tea %A Pisinger, Charlotta %A Hansen, Torben %A Schulz, Holger %A Polasek, Ozren %A Campbell, Archie %A Starr, John M %A Rich, Stephen S %A Mook-Kanamori, Dennis O %A Johansson, Asa %A Ingelsson, Erik %A Uitterlinden, André G %A Weiss, Stefan %A Raitakari, Olli T %A Gudnason, Vilmundur %A North, Kari E %A Gharib, Sina A %A Sin, Don D %A Taylor, Kent D %A O'Connor, George T %A Kaprio, Jaakko %A Harris, Tamara B %A Pederson, Oluf %A Vestergaard, Henrik %A Wilson, James G %A Strauch, Konstantin %A Hayward, Caroline %A Kerr, Shona %A Deary, Ian J %A Barr, R Graham %A de Mutsert, Renée %A Gyllensten, Ulf %A Morris, Andrew P %A Ikram, M Arfan %A Probst-Hensch, Nicole %A Gläser, Sven %A Zeggini, Eleftheria %A Lehtimäki, Terho %A Strachan, David P %A Dupuis, Josée %A Morrison, Alanna C %A Hall, Ian P %A Tobin, Martin D %A London, Stephanie J %X

Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV ), forced vital capacity (FVC) and the ratio of FEV to FVC (FEV /FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. We identified significant (P<2·8x10 ) associations with six SNPs: a nonsynonymous variant in , which is predicted to be damaging, three intronic SNPs ( and ) and two intergenic SNPs near to and Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including and . Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease.

%B Wellcome Open Res %V 3 %P 4 %8 2018 %G eng %R 10.12688/wellcomeopenres.12583.3 %0 Journal Article %J Nat Genet %D 2018 %T Multiancestry association study identifies new asthma risk loci that colocalize with immune-cell enhancer marks. %A Demenais, Florence %A Margaritte-Jeannin, Patricia %A Barnes, Kathleen C %A Cookson, William O C %A Altmüller, Janine %A Ang, Wei %A Barr, R Graham %A Beaty, Terri H %A Becker, Allan B %A Beilby, John %A Bisgaard, Hans %A Bjornsdottir, Unnur Steina %A Bleecker, Eugene %A Bønnelykke, Klaus %A Boomsma, Dorret I %A Bouzigon, Emmanuelle %A Brightling, Christopher E %A Brossard, Myriam %A Brusselle, Guy G %A Burchard, Esteban %A Burkart, Kristin M %A Bush, Andrew %A Chan-Yeung, Moira %A Chung, Kian Fan %A Couto Alves, Alexessander %A Curtin, John A %A Custovic, Adnan %A Daley, Denise %A de Jongste, Johan C %A Del-Rio-Navarro, Blanca E %A Donohue, Kathleen M %A Duijts, Liesbeth %A Eng, Celeste %A Eriksson, Johan G %A Farrall, Martin %A Fedorova, Yuliya %A Feenstra, Bjarke %A Ferreira, Manuel A %A Freidin, Maxim B %A Gajdos, Zofia %A Gauderman, Jim %A Gehring, Ulrike %A Geller, Frank %A Genuneit, Jon %A Gharib, Sina A %A Gilliland, Frank %A Granell, Raquel %A Graves, Penelope E %A Gudbjartsson, Daniel F %A Haahtela, Tari %A Heckbert, Susan R %A Heederik, Dick %A Heinrich, Joachim %A Heliövaara, Markku %A Henderson, John %A Himes, Blanca E %A Hirose, Hiroshi %A Hirschhorn, Joel N %A Hofman, Albert %A Holt, Patrick %A Hottenga, Jouke %A Hudson, Thomas J %A Hui, Jennie %A Imboden, Medea %A Ivanov, Vladimir %A Jaddoe, Vincent W V %A James, Alan %A Janson, Christer %A Jarvelin, Marjo-Riitta %A Jarvis, Deborah %A Jones, Graham %A Jonsdottir, Ingileif %A Jousilahti, Pekka %A Kabesch, Michael %A Kähönen, Mika %A Kantor, David B %A Karunas, Alexandra S %A Khusnutdinova, Elza %A Koppelman, Gerard H %A Kozyrskyj, Anita L %A Kreiner, Eskil %A Kubo, Michiaki %A Kumar, Rajesh %A Kumar, Ashish %A Kuokkanen, Mikko %A Lahousse, Lies %A Laitinen, Tarja %A Laprise, Catherine %A Lathrop, Mark %A Lau, Susanne %A Lee, Young-Ae %A Lehtimäki, Terho %A Letort, Sébastien %A Levin, Albert M %A Li, Guo %A Liang, Liming %A Loehr, Laura R %A London, Stephanie J %A Loth, Daan W %A Manichaikul, Ani %A Marenholz, Ingo %A Martinez, Fernando J %A Matheson, Melanie C %A Mathias, Rasika A %A Matsumoto, Kenji %A Mbarek, Hamdi %A McArdle, Wendy L %A Melbye, Mads %A Melén, Erik %A Meyers, Deborah %A Michel, Sven %A Mohamdi, Hamida %A Musk, Arthur W %A Myers, Rachel A %A Nieuwenhuis, Maartje A E %A Noguchi, Emiko %A O'Connor, George T %A Ogorodova, Ludmila M %A Palmer, Cameron D %A Palotie, Aarno %A Park, Julie E %A Pennell, Craig E %A Pershagen, Göran %A Polonikov, Alexey %A Postma, Dirkje S %A Probst-Hensch, Nicole %A Puzyrev, Valery P %A Raby, Benjamin A %A Raitakari, Olli T %A Ramasamy, Adaikalavan %A Rich, Stephen S %A Robertson, Colin F %A Romieu, Isabelle %A Salam, Muhammad T %A Salomaa, Veikko %A Schlünssen, Vivi %A Scott, Robert %A Selivanova, Polina A %A Sigsgaard, Torben %A Simpson, Angela %A Siroux, Valérie %A Smith, Lewis J %A Solodilova, Maria %A Standl, Marie %A Stefansson, Kari %A Strachan, David P %A Stricker, Bruno H %A Takahashi, Atsushi %A Thompson, Philip J %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Tiesler, Carla M T %A Torgerson, Dara G %A Tsunoda, Tatsuhiko %A Uitterlinden, André G %A van der Valk, Ralf J P %A Vaysse, Amaury %A Vedantam, Sailaja %A von Berg, Andrea %A von Mutius, Erika %A Vonk, Judith M %A Waage, Johannes %A Wareham, Nick J %A Weiss, Scott T %A White, Wendy B %A Wickman, Magnus %A Widen, Elisabeth %A Willemsen, Gonneke %A Williams, L Keoki %A Wouters, Inge M %A Yang, James J %A Zhao, Jing Hua %A Moffatt, Miriam F %A Ober, Carole %A Nicolae, Dan L %X

We examined common variation in asthma risk by conducting a meta-analysis of worldwide asthma genome-wide association studies (23,948 asthma cases, 118,538 controls) of individuals from ethnically diverse populations. We identified five new asthma loci, found two new associations at two known asthma loci, established asthma associations at two loci previously implicated in the comorbidity of asthma plus hay fever, and confirmed nine known loci. Investigation of pleiotropy showed large overlaps in genetic variants with autoimmune and inflammatory diseases. The enrichment in enhancer marks at asthma risk loci, especially in immune cells, suggested a major role of these loci in the regulation of immunologically related mechanisms.

%B Nat Genet %V 50 %P 42-53 %8 2018 Jan %G eng %N 1 %R 10.1038/s41588-017-0014-7 %0 Journal Article %J Nat Genet %D 2018 %T Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. %A Malik, Rainer %A Chauhan, Ganesh %A Traylor, Matthew %A Sargurupremraj, Muralidharan %A Okada, Yukinori %A Mishra, Aniket %A Rutten-Jacobs, Loes %A Giese, Anne-Katrin %A van der Laan, Sander W %A Gretarsdottir, Solveig %A Anderson, Christopher D %A Chong, Michael %A Adams, Hieab H H %A Ago, Tetsuro %A Almgren, Peter %A Amouyel, Philippe %A Ay, Hakan %A Bartz, Traci M %A Benavente, Oscar R %A Bevan, Steve %A Boncoraglio, Giorgio B %A Brown, Robert D %A Butterworth, Adam S %A Carrera, Caty %A Carty, Cara L %A Chasman, Daniel I %A Chen, Wei-Min %A Cole, John W %A Correa, Adolfo %A Cotlarciuc, Ioana %A Cruchaga, Carlos %A Danesh, John %A de Bakker, Paul I W %A DeStefano, Anita L %A den Hoed, Marcel %A Duan, Qing %A Engelter, Stefan T %A Falcone, Guido J %A Gottesman, Rebecca F %A Grewal, Raji P %A Gudnason, Vilmundur %A Gustafsson, Stefan %A Haessler, Jeffrey %A Harris, Tamara B %A Hassan, Ahamad %A Havulinna, Aki S %A Heckbert, Susan R %A Holliday, Elizabeth G %A Howard, George %A Hsu, Fang-Chi %A Hyacinth, Hyacinth I %A Ikram, M Arfan %A Ingelsson, Erik %A Irvin, Marguerite R %A Jian, Xueqiu %A Jimenez-Conde, Jordi %A Johnson, Julie A %A Jukema, J Wouter %A Kanai, Masahiro %A Keene, Keith L %A Kissela, Brett M %A Kleindorfer, Dawn O %A Kooperberg, Charles %A Kubo, Michiaki %A Lange, Leslie A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lee, Jin-Moo %A Lemmens, Robin %A Leys, Didier %A Lewis, Cathryn M %A Lin, Wei-Yu %A Lindgren, Arne G %A Lorentzen, Erik %A Magnusson, Patrik K %A Maguire, Jane %A Manichaikul, Ani %A McArdle, Patrick F %A Meschia, James F %A Mitchell, Braxton D %A Mosley, Thomas H %A Nalls, Michael A %A Ninomiya, Toshiharu %A O'Donnell, Martin J %A Psaty, Bruce M %A Pulit, Sara L %A Rannikmae, Kristiina %A Reiner, Alexander P %A Rexrode, Kathryn M %A Rice, Kenneth %A Rich, Stephen S %A Ridker, Paul M %A Rost, Natalia S %A Rothwell, Peter M %A Rotter, Jerome I %A Rundek, Tatjana %A Sacco, Ralph L %A Sakaue, Saori %A Sale, Michèle M %A Salomaa, Veikko %A Sapkota, Bishwa R %A Schmidt, Reinhold %A Schmidt, Carsten O %A Schminke, Ulf %A Sharma, Pankaj %A Slowik, Agnieszka %A Sudlow, Cathie L M %A Tanislav, Christian %A Tatlisumak, Turgut %A Taylor, Kent D %A Thijs, Vincent N S %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Tiedt, Steffen %A Trompet, Stella %A Tzourio, Christophe %A van Duijn, Cornelia M %A Walters, Matthew %A Wareham, Nicholas J %A Wassertheil-Smoller, Sylvia %A Wilson, James G %A Wiggins, Kerri L %A Yang, Qiong %A Yusuf, Salim %A Bis, Joshua C %A Pastinen, Tomi %A Ruusalepp, Arno %A Schadt, Eric E %A Koplev, Simon %A Björkegren, Johan L M %A Codoni, Veronica %A Civelek, Mete %A Smith, Nicholas L %A Trégouët, David A %A Christophersen, Ingrid E %A Roselli, Carolina %A Lubitz, Steven A %A Ellinor, Patrick T %A Tai, E Shyong %A Kooner, Jaspal S %A Kato, Norihiro %A He, Jiang %A van der Harst, Pim %A Elliott, Paul %A Chambers, John C %A Takeuchi, Fumihiko %A Johnson, Andrew D %A Sanghera, Dharambir K %A Melander, Olle %A Jern, Christina %A Strbian, Daniel %A Fernandez-Cadenas, Israel %A Longstreth, W T %A Rolfs, Arndt %A Hata, Jun %A Woo, Daniel %A Rosand, Jonathan %A Paré, Guillaume %A Hopewell, Jemma C %A Saleheen, Danish %A Stefansson, Kari %A Worrall, Bradford B %A Kittner, Steven J %A Seshadri, Sudha %A Fornage, Myriam %A Markus, Hugh S %A Howson, Joanna M M %A Kamatani, Yoichiro %A Debette, Stephanie %A Dichgans, Martin %A Malik, Rainer %A Chauhan, Ganesh %A Traylor, Matthew %A Sargurupremraj, Muralidharan %A Okada, Yukinori %A Mishra, Aniket %A Rutten-Jacobs, Loes %A Giese, Anne-Katrin %A van der Laan, Sander W %A Gretarsdottir, Solveig %A Anderson, Christopher D %A Chong, Michael %A Adams, Hieab H H %A Ago, Tetsuro %A Almgren, Peter %A Amouyel, Philippe %A Ay, Hakan %A Bartz, Traci M %A Benavente, Oscar R %A Bevan, Steve %A Boncoraglio, Giorgio B %A Brown, Robert D %A Butterworth, Adam S %A Carrera, Caty %A Carty, Cara L %A Chasman, Daniel I %A Chen, Wei-Min %A Cole, John W %A Correa, Adolfo %A Cotlarciuc, Ioana %A Cruchaga, Carlos %A Danesh, John %A de Bakker, Paul I W %A DeStefano, Anita L %A Hoed, Marcel den %A Duan, Qing %A Engelter, Stefan T %A Falcone, Guido J %A Gottesman, Rebecca F %A Grewal, Raji P %A Gudnason, Vilmundur %A Gustafsson, Stefan %A Haessler, Jeffrey %A Harris, Tamara B %A Hassan, Ahamad %A Havulinna, Aki S %A Heckbert, Susan R %A Holliday, Elizabeth G %A Howard, George %A Hsu, Fang-Chi %A Hyacinth, Hyacinth I %A Ikram, M Arfan %A Ingelsson, Erik %A Irvin, Marguerite R %A Jian, Xueqiu %A Jimenez-Conde, Jordi %A Johnson, Julie A %A Jukema, J Wouter %A Kanai, Masahiro %A Keene, Keith L %A Kissela, Brett M %A Kleindorfer, Dawn O %A Kooperberg, Charles %A Kubo, Michiaki %A Lange, Leslie A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lee, Jin-Moo %A Lemmens, Robin %A Leys, Didier %A Lewis, Cathryn M %A Lin, Wei-Yu %A Lindgren, Arne G %A Lorentzen, Erik %A Magnusson, Patrik K %A Maguire, Jane %A Manichaikul, Ani %A McArdle, Patrick F %A Meschia, James F %A Mitchell, Braxton D %A Mosley, Thomas H %A Nalls, Michael A %A Ninomiya, Toshiharu %A O'Donnell, Martin J %A Psaty, Bruce M %A Pulit, Sara L %A Rannikmae, Kristiina %A Reiner, Alexander P %A Rexrode, Kathryn M %A Rice, Kenneth %A Rich, Stephen S %A Ridker, Paul M %A Rost, Natalia S %A Rothwell, Peter M %A Rotter, Jerome I %A Rundek, Tatjana %A Sacco, Ralph L %A Sakaue, Saori %A Sale, Michèle M %A Salomaa, Veikko %A Sapkota, Bishwa R %A Schmidt, Reinhold %A Schmidt, Carsten O %A Schminke, Ulf %A Sharma, Pankaj %A Slowik, Agnieszka %A Sudlow, Cathie L M %A Tanislav, Christian %A Tatlisumak, Turgut %A Taylor, Kent D %A Thijs, Vincent N S %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Tiedt, Steffen %A Trompet, Stella %A Tzourio, Christophe %A van Duijn, Cornelia M %A Walters, Matthew %A Wareham, Nicholas J %A Wassertheil-Smoller, Sylvia %A Wilson, James G %A Wiggins, Kerri L %A Yang, Qiong %A Yusuf, Salim %A Amin, Najaf %A Aparicio, Hugo S %A Arnett, Donna K %A Attia, John %A Beiser, Alexa S %A Berr, Claudine %A Buring, Julie E %A Bustamante, Mariana %A Caso, Valeria %A Cheng, Yu-Ching %A Choi, Seung Hoan %A Chowhan, Ayesha %A Cullell, Natalia %A Dartigues, Jean-François %A Delavaran, Hossein %A Delgado, Pilar %A Dörr, Marcus %A Engström, Gunnar %A Ford, Ian %A Gurpreet, Wander S %A Hamsten, Anders %A Heitsch, Laura %A Hozawa, Atsushi %A Ibanez, Laura %A Ilinca, Andreea %A Ingelsson, Martin %A Iwasaki, Motoki %A Jackson, Rebecca D %A Jood, Katarina %A Jousilahti, Pekka %A Kaffashian, Sara %A Kalra, Lalit %A Kamouchi, Masahiro %A Kitazono, Takanari %A Kjartansson, Olafur %A Kloss, Manja %A Koudstaal, Peter J %A Krupinski, Jerzy %A Labovitz, Daniel L %A Laurie, Cathy C %A Levi, Christopher R %A Li, Linxin %A Lind, Lars %A Lindgren, Cecilia M %A Lioutas, Vasileios %A Liu, Yong Mei %A Lopez, Oscar L %A Makoto, Hirata %A Martinez-Majander, Nicolas %A Matsuda, Koichi %A Minegishi, Naoko %A Montaner, Joan %A Morris, Andrew P %A Muiño, Elena %A Müller-Nurasyid, Martina %A Norrving, Bo %A Ogishima, Soichi %A Parati, Eugenio A %A Peddareddygari, Leema Reddy %A Pedersen, Nancy L %A Pera, Joanna %A Perola, Markus %A Pezzini, Alessandro %A Pileggi, Silvana %A Rabionet, Raquel %A Riba-Llena, Iolanda %A Ribasés, Marta %A Romero, Jose R %A Roquer, Jaume %A Rudd, Anthony G %A Sarin, Antti-Pekka %A Sarju, Ralhan %A Sarnowski, Chloe %A Sasaki, Makoto %A Satizabal, Claudia L %A Satoh, Mamoru %A Sattar, Naveed %A Sawada, Norie %A Sibolt, Gerli %A Sigurdsson, Ásgeir %A Smith, Albert %A Sobue, Kenji %A Soriano-Tárraga, Carolina %A Stanne, Tara %A Stine, O Colin %A Stott, David J %A Strauch, Konstantin %A Takai, Takako %A Tanaka, Hideo %A Tanno, Kozo %A Teumer, Alexander %A Tomppo, Liisa %A Torres-Aguila, Nuria P %A Touze, Emmanuel %A Tsugane, Shoichiro %A Uitterlinden, André G %A Valdimarsson, Einar M %A van der Lee, Sven J %A Völzke, Henry %A Wakai, Kenji %A Weir, David %A Williams, Stephen R %A Wolfe, Charles D A %A Wong, Quenna %A Xu, Huichun %A Yamaji, Taiki %A Sanghera, Dharambir K %A Melander, Olle %A Jern, Christina %A Strbian, Daniel %A Fernandez-Cadenas, Israel %A Longstreth, W T %A Rolfs, Arndt %A Hata, Jun %A Woo, Daniel %A Rosand, Jonathan %A Paré, Guillaume %A Hopewell, Jemma C %A Saleheen, Danish %A Stefansson, Kari %A Worrall, Bradford B %A Kittner, Steven J %A Seshadri, Sudha %A Fornage, Myriam %A Markus, Hugh S %A Howson, Joanna M M %A Kamatani, Yoichiro %A Debette, Stephanie %A Dichgans, Martin %X

Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.

%B Nat Genet %V 50 %P 524-537 %8 2018 Apr %G eng %N 4 %R 10.1038/s41588-018-0058-3 %0 Journal Article %J Nat Commun %D 2018 %T Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function. %A Wyss, Annah B %A Sofer, Tamar %A Lee, Mi Kyeong %A Terzikhan, Natalie %A Nguyen, Jennifer N %A Lahousse, Lies %A Latourelle, Jeanne C %A Smith, Albert Vernon %A Bartz, Traci M %A Feitosa, Mary F %A Gao, Wei %A Ahluwalia, Tarunveer S %A Tang, Wenbo %A Oldmeadow, Christopher %A Duan, Qing %A de Jong, Kim %A Wojczynski, Mary K %A Wang, Xin-Qun %A Noordam, Raymond %A Hartwig, Fernando Pires %A Jackson, Victoria E %A Wang, Tianyuan %A Obeidat, Ma'en %A Hobbs, Brian D %A Huan, Tianxiao %A Gui, Hongsheng %A Parker, Margaret M %A Hu, Donglei %A Mogil, Lauren S %A Kichaev, Gleb %A Jin, Jianping %A Graff, Mariaelisa %A Harris, Tamara B %A Kalhan, Ravi %A Heckbert, Susan R %A Paternoster, Lavinia %A Burkart, Kristin M %A Liu, Yongmei %A Holliday, Elizabeth G %A Wilson, James G %A Vonk, Judith M %A Sanders, Jason L %A Barr, R Graham %A de Mutsert, Renée %A Menezes, Ana Maria Baptista %A Adams, Hieab H H %A van den Berge, Maarten %A Joehanes, Roby %A Levin, Albert M %A Liberto, Jennifer %A Launer, Lenore J %A Morrison, Alanna C %A Sitlani, Colleen M %A Celedón, Juan C %A Kritchevsky, Stephen B %A Scott, Rodney J %A Christensen, Kaare %A Rotter, Jerome I %A Bonten, Tobias N %A Wehrmeister, Fernando César %A Bossé, Yohan %A Xiao, Shujie %A Oh, Sam %A Franceschini, Nora %A Brody, Jennifer A %A Kaplan, Robert C %A Lohman, Kurt %A McEvoy, Mark %A Province, Michael A %A Rosendaal, Frits R %A Taylor, Kent D %A Nickle, David C %A Williams, L Keoki %A Burchard, Esteban G %A Wheeler, Heather E %A Sin, Don D %A Gudnason, Vilmundur %A North, Kari E %A Fornage, Myriam %A Psaty, Bruce M %A Myers, Richard H %A O'Connor, George %A Hansen, Torben %A Laurie, Cathy C %A Cassano, Patricia A %A Sung, Joohon %A Kim, Woo Jin %A Attia, John R %A Lange, Leslie %A Boezen, H Marike %A Thyagarajan, Bharat %A Rich, Stephen S %A Mook-Kanamori, Dennis O %A Horta, Bernardo Lessa %A Uitterlinden, André G %A Im, Hae Kyung %A Cho, Michael H %A Brusselle, Guy G %A Gharib, Sina A %A Dupuis, Josée %A Manichaikul, Ani %A London, Stephanie J %X

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of lung function and clinical relevance of implicated loci.

%B Nat Commun %V 9 %P 2976 %8 2018 Jul 30 %G eng %N 1 %R 10.1038/s41467-018-05369-0 %0 Journal Article %J Am J Respir Crit Care Med %D 2018 %T Omega-3 Fatty Acids and Genome-wide Interaction Analyses Reveal DPP10-Pulmonary Function Association. %A Xu, Jiayi %A Gaddis, Nathan C %A Bartz, Traci M %A Hou, Ruixue %A Manichaikul, Ani W %A Pankratz, Nathan %A Smith, Albert V %A Sun, Fangui %A Terzikhan, Natalie %A Markunas, Christina A %A Patchen, Bonnie K %A Schu, Matthew %A Beydoun, May A %A Brusselle, Guy G %A Eiriksdottir, Gudny %A Zhou, Xia %A Wood, Alexis C %A Graff, Mariaelisa %A Harris, Tamara B %A Ikram, M Arfan %A Jacobs, David R %A Launer, Lenore J %A Lemaitre, Rozenn N %A O'Connor, George %A Oelsner, Elizabeth C %A Psaty, Bruce M %A Ramachandran, Vasan S %A Rohde, Rebecca R %A Rich, Stephen S %A Rotter, Jerome I %A Seshadri, Sudha %A Smith, Lewis J %A Tiemeier, Henning %A Tsai, Michael Y %A Uitterlinden, André G %A Voruganti, V Saroja %A Xu, Hanfei %A Zilhão, Nuno R %A Fornage, Myriam %A Zillikens, M Carola %A London, Stephanie J %A Barr, R Graham %A Dupuis, Josée %A Gharib, Sina A %A Gudnason, Vilmundur %A Lahousse, Lies %A North, Kari E %A Steffen, Lyn M %A Cassano, Patricia A %A Hancock, Dana B %X

RATIONALE: Omega-3 poly-unsaturated fatty acids (n-3 PUFAs) have anti-inflammatory properties that could benefit adults with comprised pulmonary health.

OBJECTIVE: To investigate n-3 PUFA associations with spirometric measures of pulmonary function tests (PFTs) and determine underlying genetic susceptibility.

METHODS: Associations of n-3 PUFA biomarkers (alpha-linolenic acid, eicosapentaenoic acid, docosapentaenoic acid [DPA], and docosahexaenoic acid [DHA]) were evaluated with PFTs (forced expiratory volume in the first second [FEV], forced vital capacity [FVC], and [FEV/FVC]) in meta-analyses across seven cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (N=16,134 of European or African ancestry). PFT-associated n-3 PUFAs were carried forward to genome-wide interaction analyses in the four largest cohorts (N=11,962) and replicated in one cohort (N=1,687). Cohort-specific results were combined using joint 2 degree-of-freedom (2df) meta-analyses of single nucleotide polymorphism (SNP) associations and their interactions with n-3 PUFAs.

RESULTS: DPA and DHA were positively associated with FEV1 and FVC (P<0.025), with evidence for effect modification by smoking and by sex. Genome-wide analyses identified a novel association of rs11693320-an intronic DPP10 SNP-with FVC when incorporating an interaction with DHA, and the finding was replicated (P=9.4×10 across discovery and replication cohorts). The rs11693320-A allele (frequency~80%) was associated with lower FVC (P=2.1×10; β= -161.0mL), and the association was attenuated by higher DHA levels (P=2.1×10; β=36.2mL).

CONCLUSIONS: We corroborated beneficial effects of n-3 PUFAs on pulmonary function. By modeling genome-wide n-3 PUFA interactions, we identified a novel DPP10 SNP association with FVC that was not detectable in much larger studies ignoring this interaction.

%B Am J Respir Crit Care Med %8 2018 Sep 10 %G eng %R 10.1164/rccm.201802-0304OC %0 Journal Article %J Nat Genet %D 2018 %T Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. %A Mahajan, Anubha %A Wessel, Jennifer %A Willems, Sara M %A Zhao, Wei %A Robertson, Neil R %A Chu, Audrey Y %A Gan, Wei %A Kitajima, Hidetoshi %A Taliun, Daniel %A Rayner, N William %A Guo, Xiuqing %A Lu, Yingchang %A Li, Man %A Jensen, Richard A %A Hu, Yao %A Huo, Shaofeng %A Lohman, Kurt K %A Zhang, Weihua %A Cook, James P %A Prins, Bram Peter %A Flannick, Jason %A Grarup, Niels %A Trubetskoy, Vassily Vladimirovich %A Kravic, Jasmina %A Kim, Young Jin %A Rybin, Denis V %A Yaghootkar, Hanieh %A Müller-Nurasyid, Martina %A Meidtner, Karina %A Li-Gao, Ruifang %A Varga, Tibor V %A Marten, Jonathan %A Li, Jin %A Smith, Albert Vernon %A An, Ping %A Ligthart, Symen %A Gustafsson, Stefan %A Malerba, Giovanni %A Demirkan, Ayse %A Tajes, Juan Fernandez %A Steinthorsdottir, Valgerdur %A Wuttke, Matthias %A Lecoeur, Cécile %A Preuss, Michael %A Bielak, Lawrence F %A Graff, Marielisa %A Highland, Heather M %A Justice, Anne E %A Liu, Dajiang J %A Marouli, Eirini %A Peloso, Gina Marie %A Warren, Helen R %A Afaq, Saima %A Afzal, Shoaib %A Ahlqvist, Emma %A Almgren, Peter %A Amin, Najaf %A Bang, Lia B %A Bertoni, Alain G %A Bombieri, Cristina %A Bork-Jensen, Jette %A Brandslund, Ivan %A Brody, Jennifer A %A Burtt, Noel P %A Canouil, Mickaël %A Chen, Yii-Der Ida %A Cho, Yoon Shin %A Christensen, Cramer %A Eastwood, Sophie V %A Eckardt, Kai-Uwe %A Fischer, Krista %A Gambaro, Giovanni %A Giedraitis, Vilmantas %A Grove, Megan L %A de Haan, Hugoline G %A Hackinger, Sophie %A Hai, Yang %A Han, Sohee %A Tybjærg-Hansen, Anne %A Hivert, Marie-France %A Isomaa, Bo %A Jäger, Susanne %A Jørgensen, Marit E %A Jørgensen, Torben %A Käräjämäki, AnneMari %A Kim, Bong-Jo %A Kim, Sung Soo %A Koistinen, Heikki A %A Kovacs, Peter %A Kriebel, Jennifer %A Kronenberg, Florian %A Läll, Kristi %A Lange, Leslie A %A Lee, Jung-Jin %A Lehne, Benjamin %A Li, Huaixing %A Lin, Keng-Hung %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jun %A Loh, Marie %A Mägi, Reedik %A Mamakou, Vasiliki %A McKean-Cowdin, Roberta %A Nadkarni, Girish %A Neville, Matt %A Nielsen, Sune F %A Ntalla, Ioanna %A Peyser, Patricia A %A Rathmann, Wolfgang %A Rice, Kenneth %A Rich, Stephen S %A Rode, Line %A Rolandsson, Olov %A Schönherr, Sebastian %A Selvin, Elizabeth %A Small, Kerrin S %A Stančáková, Alena %A Surendran, Praveen %A Taylor, Kent D %A Teslovich, Tanya M %A Thorand, Barbara %A Thorleifsson, Gudmar %A Tin, Adrienne %A Tönjes, Anke %A Varbo, Anette %A Witte, Daniel R %A Wood, Andrew R %A Yajnik, Pranav %A Yao, Jie %A Yengo, Loic %A Young, Robin %A Amouyel, Philippe %A Boeing, Heiner %A Boerwinkle, Eric %A Bottinger, Erwin P %A Chowdhury, Rajiv %A Collins, Francis S %A Dedoussis, George %A Dehghan, Abbas %A Deloukas, Panos %A Ferrario, Marco M %A Ferrieres, Jean %A Florez, Jose C %A Frossard, Philippe %A Gudnason, Vilmundur %A Harris, Tamara B %A Heckbert, Susan R %A Howson, Joanna M M %A Ingelsson, Martin %A Kathiresan, Sekar %A Kee, Frank %A Kuusisto, Johanna %A Langenberg, Claudia %A Launer, Lenore J %A Lindgren, Cecilia M %A Männistö, Satu %A Meitinger, Thomas %A Melander, Olle %A Mohlke, Karen L %A Moitry, Marie %A Morris, Andrew D %A Murray, Alison D %A de Mutsert, Renée %A Orho-Melander, Marju %A Owen, Katharine R %A Perola, Markus %A Peters, Annette %A Province, Michael A %A Rasheed, Asif %A Ridker, Paul M %A Rivadineira, Fernando %A Rosendaal, Frits R %A Rosengren, Anders H %A Salomaa, Veikko %A Sheu, Wayne H-H %A Sladek, Rob %A Smith, Blair H %A Strauch, Konstantin %A Uitterlinden, André G %A Varma, Rohit %A Willer, Cristen J %A Blüher, Matthias %A Butterworth, Adam S %A Chambers, John Campbell %A Chasman, Daniel I %A Danesh, John %A van Duijn, Cornelia %A Dupuis, Josée %A Franco, Oscar H %A Franks, Paul W %A Froguel, Philippe %A Grallert, Harald %A Groop, Leif %A Han, Bok-Ghee %A Hansen, Torben %A Hattersley, Andrew T %A Hayward, Caroline %A Ingelsson, Erik %A Kardia, Sharon L R %A Karpe, Fredrik %A Kooner, Jaspal Singh %A Köttgen, Anna %A Kuulasmaa, Kari %A Laakso, Markku %A Lin, Xu %A Lind, Lars %A Liu, Yongmei %A Loos, Ruth J F %A Marchini, Jonathan %A Metspalu, Andres %A Mook-Kanamori, Dennis %A Nordestgaard, Børge G %A Palmer, Colin N A %A Pankow, James S %A Pedersen, Oluf %A Psaty, Bruce M %A Rauramaa, Rainer %A Sattar, Naveed %A Schulze, Matthias B %A Soranzo, Nicole %A Spector, Timothy D %A Stefansson, Kari %A Stumvoll, Michael %A Thorsteinsdottir, Unnur %A Tuomi, Tiinamaija %A Tuomilehto, Jaakko %A Wareham, Nicholas J %A Wilson, James G %A Zeggini, Eleftheria %A Scott, Robert A %A Barroso, Inês %A Frayling, Timothy M %A Goodarzi, Mark O %A Meigs, James B %A Boehnke, Michael %A Saleheen, Danish %A Morris, Andrew P %A Rotter, Jerome I %A McCarthy, Mark I %X

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.

%B Nat Genet %V 50 %P 559-571 %8 2018 Apr %G eng %N 4 %R 10.1038/s41588-018-0084-1 %0 Journal Article %J Diabetologia %D 2018 %T Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis. %A McKeown, Nicola M %A Dashti, Hassan S %A Ma, Jiantao %A Haslam, Danielle E %A Kiefte-de Jong, Jessica C %A Smith, Caren E %A Tanaka, Toshiko %A Graff, Mariaelisa %A Lemaitre, Rozenn N %A Rybin, Denis %A Sonestedt, Emily %A Frazier-Wood, Alexis C %A Mook-Kanamori, Dennis O %A Li, Yanping %A Wang, Carol A %A Leermakers, Elisabeth T M %A Mikkilä, Vera %A Young, Kristin L %A Mukamal, Kenneth J %A Cupples, L Adrienne %A Schulz, Christina-Alexandra %A Chen, Tzu-An %A Li-Gao, Ruifang %A Huang, Tao %A Oddy, Wendy H %A Raitakari, Olli %A Rice, Kenneth %A Meigs, James B %A Ericson, Ulrika %A Steffen, Lyn M %A Rosendaal, Frits R %A Hofman, Albert %A Kähönen, Mika %A Psaty, Bruce M %A Brunkwall, Louise %A Uitterlinden, André G %A Viikari, Jorma %A Siscovick, David S %A Seppälä, Ilkka %A North, Kari E %A Mozaffarian, Dariush %A Dupuis, Josée %A Orho-Melander, Marju %A Rich, Stephen S %A de Mutsert, Renée %A Qi, Lu %A Pennell, Craig E %A Franco, Oscar H %A Lehtimäki, Terho %A Herman, Mark A %X

AIMS/HYPOTHESIS: Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits.

METHODS: Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway.

RESULTS: In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β ± SE 0.014 ± 0.004 [mmol/l], p = 1.5 × 10-3) and higher fasting insulin (0.030 ± 0.005 [log e pmol/l], p = 2.0 × 10-10). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the β-Klotho (KLB) locus on fasting insulin (0.030 ± 0.011 log e pmol/l, uncorrected p = 0.006), results in the replication cohorts and combined meta-analyses were non-significant.

CONCLUSIONS/INTERPRETATION: In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis.

TRIAL REGISTRATION: Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses' Health Study).

%B Diabetologia %V 61 %P 317-330 %8 2018 Feb %G eng %N 2 %R 10.1007/s00125-017-4475-0 %0 Journal Article %J Nat Commun %D 2019 %T Associations of autozygosity with a broad range of human phenotypes. %A Clark, David W %A Okada, Yukinori %A Moore, Kristjan H S %A Mason, Dan %A Pirastu, Nicola %A Gandin, Ilaria %A Mattsson, Hannele %A Barnes, Catriona L K %A Lin, Kuang %A Zhao, Jing Hua %A Deelen, Patrick %A Rohde, Rebecca %A Schurmann, Claudia %A Guo, Xiuqing %A Giulianini, Franco %A Zhang, Weihua %A Medina-Gómez, Carolina %A Karlsson, Robert %A Bao, Yanchun %A Bartz, Traci M %A Baumbach, Clemens %A Biino, Ginevra %A Bixley, Matthew J %A Brumat, Marco %A Chai, Jin-Fang %A Corre, Tanguy %A Cousminer, Diana L %A Dekker, Annelot M %A Eccles, David A %A van Eijk, Kristel R %A Fuchsberger, Christian %A Gao, He %A Germain, Marine %A Gordon, Scott D %A de Haan, Hugoline G %A Harris, Sarah E %A Hofer, Edith %A Huerta-Chagoya, Alicia %A Igartua, Catherine %A Jansen, Iris E %A Jia, Yucheng %A Kacprowski, Tim %A Karlsson, Torgny %A Kleber, Marcus E %A Li, Shengchao Alfred %A Li-Gao, Ruifang %A Mahajan, Anubha %A Matsuda, Koichi %A Meidtner, Karina %A Meng, Weihua %A Montasser, May E %A van der Most, Peter J %A Munz, Matthias %A Nutile, Teresa %A Palviainen, Teemu %A Prasad, Gauri %A Prasad, Rashmi B %A Priyanka, Tallapragada Divya Sri %A Rizzi, Federica %A Salvi, Erika %A Sapkota, Bishwa R %A Shriner, Daniel %A Skotte, Line %A Smart, Melissa C %A Smith, Albert Vernon %A van der Spek, Ashley %A Spracklen, Cassandra N %A Strawbridge, Rona J %A Tajuddin, Salman M %A Trompet, Stella %A Turman, Constance %A Verweij, Niek %A Viberti, Clara %A Wang, Lihua %A Warren, Helen R %A Wootton, Robyn E %A Yanek, Lisa R %A Yao, Jie %A Yousri, Noha A %A Zhao, Wei %A Adeyemo, Adebowale A %A Afaq, Saima %A Aguilar-Salinas, Carlos Alberto %A Akiyama, Masato %A Albert, Matthew L %A Allison, Matthew A %A Alver, Maris %A Aung, Tin %A Azizi, Fereidoun %A Bentley, Amy R %A Boeing, Heiner %A Boerwinkle, Eric %A Borja, Judith B %A de Borst, Gert J %A Bottinger, Erwin P %A Broer, Linda %A Campbell, Harry %A Chanock, Stephen %A Chee, Miao-Li %A Chen, Guanjie %A Chen, Yii-der I %A Chen, Zhengming %A Chiu, Yen-Feng %A Cocca, Massimiliano %A Collins, Francis S %A Concas, Maria Pina %A Corley, Janie %A Cugliari, Giovanni %A van Dam, Rob M %A Damulina, Anna %A Daneshpour, Maryam S %A Day, Felix R %A Delgado, Graciela E %A Dhana, Klodian %A Doney, Alexander S F %A Dörr, Marcus %A Doumatey, Ayo P %A Dzimiri, Nduna %A Ebenesersdóttir, S Sunna %A Elliott, Joshua %A Elliott, Paul %A Ewert, Ralf %A Felix, Janine F %A Fischer, Krista %A Freedman, Barry I %A Girotto, Giorgia %A Goel, Anuj %A Gögele, Martin %A Goodarzi, Mark O %A Graff, Mariaelisa %A Granot-Hershkovitz, Einat %A Grodstein, Francine %A Guarrera, Simonetta %A Gudbjartsson, Daniel F %A Guity, Kamran %A Gunnarsson, Bjarni %A Guo, Yu %A Hagenaars, Saskia P %A Haiman, Christopher A %A Halevy, Avner %A Harris, Tamara B %A Hedayati, Mehdi %A van Heel, David A %A Hirata, Makoto %A Höfer, Imo %A Hsiung, Chao Agnes %A Huang, Jinyan %A Hung, Yi-Jen %A Ikram, M Arfan %A Jagadeesan, Anuradha %A Jousilahti, Pekka %A Kamatani, Yoichiro %A Kanai, Masahiro %A Kerrison, Nicola D %A Kessler, Thorsten %A Khaw, Kay-Tee %A Khor, Chiea Chuen %A de Kleijn, Dominique P V %A Koh, Woon-Puay %A Kolcic, Ivana %A Kraft, Peter %A Krämer, Bernhard K %A Kutalik, Zoltán %A Kuusisto, Johanna %A Langenberg, Claudia %A Launer, Lenore J %A Lawlor, Deborah A %A Lee, I-Te %A Lee, Wen-Jane %A Lerch, Markus M %A Li, Liming %A Liu, Jianjun %A Loh, Marie %A London, Stephanie J %A Loomis, Stephanie %A Lu, Yingchang %A Luan, Jian'an %A Mägi, Reedik %A Manichaikul, Ani W %A Manunta, Paolo %A Másson, Gísli %A Matoba, Nana %A Mei, Xue W %A Meisinger, Christa %A Meitinger, Thomas %A Mezzavilla, Massimo %A Milani, Lili %A Millwood, Iona Y %A Momozawa, Yukihide %A Moore, Amy %A Morange, Pierre-Emmanuel %A Moreno-Macias, Hortensia %A Mori, Trevor A %A Morrison, Alanna C %A Muka, Taulant %A Murakami, Yoshinori %A Murray, Alison D %A de Mutsert, Renée %A Mychaleckyj, Josyf C %A Nalls, Mike A %A Nauck, Matthias %A Neville, Matt J %A Nolte, Ilja M %A Ong, Ken K %A Orozco, Lorena %A Padmanabhan, Sandosh %A Pálsson, Gunnar %A Pankow, James S %A Pattaro, Cristian %A Pattie, Alison %A Polasek, Ozren %A Poulter, Neil %A Pramstaller, Peter P %A Quintana-Murci, Lluis %A Räikkönen, Katri %A Ralhan, Sarju %A Rao, Dabeeru C %A van Rheenen, Wouter %A Rich, Stephen S %A Ridker, Paul M %A Rietveld, Cornelius A %A Robino, Antonietta %A van Rooij, Frank J A %A Ruggiero, Daniela %A Saba, Yasaman %A Sabanayagam, Charumathi %A Sabater-Lleal, Maria %A Sala, Cinzia Felicita %A Salomaa, Veikko %A Sandow, Kevin %A Schmidt, Helena %A Scott, Laura J %A Scott, William R %A Sedaghati-Khayat, Bahareh %A Sennblad, Bengt %A van Setten, Jessica %A Sever, Peter J %A Sheu, Wayne H-H %A Shi, Yuan %A Shrestha, Smeeta %A Shukla, Sharvari Rahul %A Sigurdsson, Jon K %A Sikka, Timo Tonis %A Singh, Jai Rup %A Smith, Blair H %A Stančáková, Alena %A Stanton, Alice %A Starr, John M %A Stefansdottir, Lilja %A Straker, Leon %A Sulem, Patrick %A Sveinbjornsson, Gardar %A Swertz, Morris A %A Taylor, Adele M %A Taylor, Kent D %A Terzikhan, Natalie %A Tham, Yih-Chung %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Tillander, Annika %A Tracy, Russell P %A Tusié-Luna, Teresa %A Tzoulaki, Ioanna %A Vaccargiu, Simona %A Vangipurapu, Jagadish %A Veldink, Jan H %A Vitart, Veronique %A Völker, Uwe %A Vuoksimaa, Eero %A Wakil, Salma M %A Waldenberger, Melanie %A Wander, Gurpreet S %A Wang, Ya Xing %A Wareham, Nicholas J %A Wild, Sarah %A Yajnik, Chittaranjan S %A Yuan, Jian-Min %A Zeng, Lingyao %A Zhang, Liang %A Zhou, Jie %A Amin, Najaf %A Asselbergs, Folkert W %A Bakker, Stephan J L %A Becker, Diane M %A Lehne, Benjamin %A Bennett, David A %A van den Berg, Leonard H %A Berndt, Sonja I %A Bharadwaj, Dwaipayan %A Bielak, Lawrence F %A Bochud, Murielle %A Boehnke, Mike %A Bouchard, Claude %A Bradfield, Jonathan P %A Brody, Jennifer A %A Campbell, Archie %A Carmi, Shai %A Caulfield, Mark J %A Cesarini, David %A Chambers, John C %A Chandak, Giriraj Ratan %A Cheng, Ching-Yu %A Ciullo, Marina %A Cornelis, Marilyn %A Cusi, Daniele %A Smith, George Davey %A Deary, Ian J %A Dorajoo, Rajkumar %A van Duijn, Cornelia M %A Ellinghaus, David %A Erdmann, Jeanette %A Eriksson, Johan G %A Evangelou, Evangelos %A Evans, Michele K %A Faul, Jessica D %A Feenstra, Bjarke %A Feitosa, Mary %A Foisy, Sylvain %A Franke, Andre %A Friedlander, Yechiel %A Gasparini, Paolo %A Gieger, Christian %A Gonzalez, Clicerio %A Goyette, Philippe %A Grant, Struan F A %A Griffiths, Lyn R %A Groop, Leif %A Gudnason, Vilmundur %A Gyllensten, Ulf %A Hakonarson, Hakon %A Hamsten, Anders %A van der Harst, Pim %A Heng, Chew-Kiat %A Hicks, Andrew A %A Hochner, Hagit %A Huikuri, Heikki %A Hunt, Steven C %A Jaddoe, Vincent W V %A De Jager, Philip L %A Johannesson, Magnus %A Johansson, Asa %A Jonas, Jost B %A Jukema, J Wouter %A Junttila, Juhani %A Kaprio, Jaakko %A Kardia, Sharon L R %A Karpe, Fredrik %A Kumari, Meena %A Laakso, Markku %A van der Laan, Sander W %A Lahti, Jari %A Laudes, Matthias %A Lea, Rodney A %A Lieb, Wolfgang %A Lumley, Thomas %A Martin, Nicholas G %A März, Winfried %A Matullo, Giuseppe %A McCarthy, Mark I %A Medland, Sarah E %A Merriman, Tony R %A Metspalu, Andres %A Meyer, Brian F %A Mohlke, Karen L %A Montgomery, Grant W %A Mook-Kanamori, Dennis %A Munroe, Patricia B %A North, Kari E %A Nyholt, Dale R %A O'Connell, Jeffery R %A Ober, Carole %A Oldehinkel, Albertine J %A Palmas, Walter %A Palmer, Colin %A Pasterkamp, Gerard G %A Patin, Etienne %A Pennell, Craig E %A Perusse, Louis %A Peyser, Patricia A %A Pirastu, Mario %A Polderman, Tinca J C %A Porteous, David J %A Posthuma, Danielle %A Psaty, Bruce M %A Rioux, John D %A Rivadeneira, Fernando %A Rotimi, Charles %A Rotter, Jerome I %A Rudan, Igor %A den Ruijter, Hester M %A Sanghera, Dharambir K %A Sattar, Naveed %A Schmidt, Reinhold %A Schulze, Matthias B %A Schunkert, Heribert %A Scott, Robert A %A Shuldiner, Alan R %A Sim, Xueling %A Small, Neil %A Smith, Jennifer A %A Sotoodehnia, Nona %A Tai, E-Shyong %A Teumer, Alexander %A Timpson, Nicholas J %A Toniolo, Daniela %A Trégouët, David-Alexandre %A Tuomi, Tiinamaija %A Vollenweider, Peter %A Wang, Carol A %A Weir, David R %A Whitfield, John B %A Wijmenga, Cisca %A Wong, Tien-Yin %A Wright, John %A Yang, Jingyun %A Yu, Lei %A Zemel, Babette S %A Zonderman, Alan B %A Perola, Markus %A Magnusson, Patrik K E %A Uitterlinden, André G %A Kooner, Jaspal S %A Chasman, Daniel I %A Loos, Ruth J F %A Franceschini, Nora %A Franke, Lude %A Haley, Chris S %A Hayward, Caroline %A Walters, Robin G %A Perry, John R B %A Esko, Tõnu %A Helgason, Agnar %A Stefansson, Kari %A Joshi, Peter K %A Kubo, Michiaki %A Wilson, James F %X

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (F) for >1.4 million individuals, we show that F is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: F equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of F are confirmed within full-sibling pairs, where the variation in F is independent of all environmental confounding.

%B Nat Commun %V 10 %P 4957 %8 2019 Oct 31 %G eng %N 1 %R 10.1038/s41467-019-12283-6 %0 Journal Article %J Am J Hum Genet %D 2019 %T Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program. %A Sarnowski, Chloe %A Leong, Aaron %A Raffield, Laura M %A Wu, Peitao %A de Vries, Paul S %A DiCorpo, Daniel %A Guo, Xiuqing %A Xu, Huichun %A Liu, Yongmei %A Zheng, Xiuwen %A Hu, Yao %A Brody, Jennifer A %A Goodarzi, Mark O %A Hidalgo, Bertha A %A Highland, Heather M %A Jain, Deepti %A Liu, Ching-Ti %A Naik, Rakhi P %A O'Connell, Jeffrey R %A Perry, James A %A Porneala, Bianca C %A Selvin, Elizabeth %A Wessel, Jennifer %A Psaty, Bruce M %A Curran, Joanne E %A Peralta, Juan M %A Blangero, John %A Kooperberg, Charles %A Mathias, Rasika %A Johnson, Andrew D %A Reiner, Alexander P %A Mitchell, Braxton D %A Cupples, L Adrienne %A Vasan, Ramachandran S %A Correa, Adolfo %A Morrison, Alanna C %A Boerwinkle, Eric %A Rotter, Jerome I %A Rich, Stephen S %A Manning, Alisa K %A Dupuis, Josée %A Meigs, James B %X

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.

%B Am J Hum Genet %V 105 %P 706-718 %8 2019 Oct 03 %G eng %N 4 %R 10.1016/j.ajhg.2019.08.010 %0 Journal Article %J Am J Epidemiol %D 2019 %T Multi-Ancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions. %A de Vries, Paul S %A Brown, Michael R %A Bentley, Amy R %A Sung, Yun J %A Winkler, Thomas W %A Ntalla, Ioanna %A Schwander, Karen %A Kraja, Aldi T %A Guo, Xiuqing %A Franceschini, Nora %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Huffman, Jennifer E %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Richard, Melissa A %A Noordam, Raymond %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Deng, Xuan %A Dorajoo, Rajkumar %A Lohman, Kurt K %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Evangelou, Evangelos %A Graff, Mariaelisa %A Alver, Maris %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Gandin, Ilaria %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A Hartwig, Fernando P %A He, Meian %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Jackson, Anne U %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kuhnel, Brigitte %A Laguzzi, Federica %A Lee, Joseph H %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Matoba, Nana %A Nolte, Ilja M %A Pietzner, Maik %A Riaz, Muhammad %A Said, M Abdullah %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Wang, Yajuan %A Ware, Erin B %A Wen, Wanqing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Aung, Tin %A Ballantyne, Christie %A Boerwinkle, Eric %A Broeckel, Ulrich %A Campbell, Archie %A Canouil, Mickaël %A Charumathi, Sabanayagam %A Chen, Yii-Der Ida %A Connell, John M %A de Faire, Ulf %A de Las Fuentes, Lisa %A de Mutsert, Renée %A de Silva, H Janaka %A Ding, Jingzhong %A Dominiczak, Anna F %A Duan, Qing %A Eaton, Charles B %A Eppinga, Ruben N %A Faul, Jessica D %A Fisher, Virginia %A Forrester, Terrence %A Franco, Oscar H %A Friedlander, Yechiel %A Ghanbari, Mohsen %A Giulianini, Franco %A Grabe, Hans J %A Grove, Megan L %A Gu, C Charles %A Harris, Tamara B %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hixson, James E %A Howard, Barbara V %A Ikram, M Arfan %A Jacobs, David R %A Johnson, Craig %A Jonas, Jost Bruno %A Kammerer, Candace M %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Koistinen, Heikki A %A Kolcic, Ivana %A Kooperberg, Charles %A Krieger, Jose E %A Kritchevsky, Steve B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lemaitre, Rozenn N %A Li, Yize %A Liang, Jingjing %A Liu, Jianjun %A Liu, Kiang %A Loh, Marie %A Louie, Tin %A Mägi, Reedik %A Manichaikul, Ani W %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Mosley, Thomas H %A Mukamal, Kenneth J %A Nalls, Mike A %A Nauck, Matthias %A Nelson, Christopher P %A Sotoodehnia, Nona %A O'Connell, Jeff R %A Palmer, Nicholette D %A Pazoki, Raha %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Poulter, Neil %A Raffel, Leslie J %A Raitakari, Olli T %A Reiner, Alex P %A Rice, Treva K %A Rich, Stephen S %A Robino, Antonietta %A Robinson, Jennifer G %A Rose, Lynda M %A Rudan, Igor %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Sever, Peter %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Smith, Blair H %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Tan, Nicholas %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Uitterlinden, André G %A van Heemst, Diana %A Vuckovic, Dragana %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Yujie %A Wang, Zhe %A Wei, Wen Bin %A Williams, Christine %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Yu, Bing %A Yu, Caizheng %A Yuan, Jian-Min %A Zhao, Wei %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Deary, Ian J %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo L %A Kamatani, Yoichiro %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Leander, Karin %A Lehtimäki, Terho %A Magnusson, Patrik K E %A Penninx, Brenda %A Pereira, Alexandre C %A Rauramaa, Rainer %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wang, Ya Xing %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Zheng, Wei %A Elliott, Paul %A North, Kari E %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Liu, Ching-Ti %A Liu, Yongmei %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Kardia, Sharon L R %A Zhu, Xiaofeng %A Rotimi, Charles N %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Liu, Jingmin %A Rotter, Jerome I %A Gauderman, W James %A Province, Michael A %A Munroe, Patricia B %A Rice, Kenneth %A Chasman, Daniel I %A Cupples, L Adrienne %A Rao, Dabeeru C %A Morrison, Alanna C %X

An individual's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multi-ancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in Stage 1 (genome-wide discovery) and 66 studies in Stage 2 (focused follow-up), for a total of 394,584 individuals from five ancestry groups. Genetic main and interaction effects were jointly assessed by a 2 degrees of freedom (DF) test, and a 1 DF test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in Stage 1 and were evaluated in Stage 2, followed by combined analyses of Stage 1 and Stage 2. In the combined analysis of Stage 1 and Stage 2, 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2 DF tests, of which 18 were novel. No genome-wide significant associations were found testing the interaction effect alone. The novel loci included several genes (PCSK5, VEGFB, and A1CF) with a putative role in lipid metabolism based on existing evidence from cellular and experimental models.

%B Am J Epidemiol %8 2019 Jan 29 %G eng %R 10.1093/aje/kwz005 %0 Journal Article %J Nat Genet %D 2019 %T Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids. %A Bentley, Amy R %A Sung, Yun J %A Brown, Michael R %A Winkler, Thomas W %A Kraja, Aldi T %A Ntalla, Ioanna %A Schwander, Karen %A Chasman, Daniel I %A Lim, Elise %A Deng, Xuan %A Guo, Xiuqing %A Liu, Jingmin %A Lu, Yingchang %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Huffman, Jennifer E %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Richard, Melissa A %A Noordam, Raymond %A Baker, Jenna %A Chen, Guanjie %A Aschard, Hugues %A Bartz, Traci M %A Ding, Jingzhong %A Dorajoo, Rajkumar %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert V %A Tajuddin, Salman M %A Zhao, Wei %A Graff, Mariaelisa %A Alver, Maris %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Evangelou, Evangelos %A Gao, Chuan %A Goel, Anuj %A Hagemeijer, Yanick %A Harris, Sarah E %A Hartwig, Fernando P %A He, Meian %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Hung, Yi-Jen %A Jackson, Anne U %A Kasturiratne, Anuradhani %A Komulainen, Pirjo %A Kuhnel, Brigitte %A Leander, Karin %A Lin, Keng-Hung %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Matoba, Nana %A Nolte, Ilja M %A Pietzner, Maik %A Prins, Bram %A Riaz, Muhammad %A Robino, Antonietta %A Said, M Abdullah %A Schupf, Nicole %A Scott, Robert A %A Sofer, Tamar %A Stančáková, Alena %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Varga, Tibor V %A Wang, Tzung-Dau %A Wang, Yajuan %A Ware, Erin B %A Wen, Wanqing %A Xiang, Yong-Bing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Adeyemo, Adebowale %A Afaq, Saima %A Amin, Najaf %A Amini, Marzyeh %A Arking, Dan E %A Arzumanyan, Zorayr %A Aung, Tin %A Ballantyne, Christie %A Barr, R Graham %A Bielak, Lawrence F %A Boerwinkle, Eric %A Bottinger, Erwin P %A Broeckel, Ulrich %A Brown, Morris %A Cade, Brian E %A Campbell, Archie %A Canouil, Mickaël %A Charumathi, Sabanayagam %A Chen, Yii-Der Ida %A Christensen, Kaare %A Concas, Maria Pina %A Connell, John M %A de Las Fuentes, Lisa %A de Silva, H Janaka %A de Vries, Paul S %A Doumatey, Ayo %A Duan, Qing %A Eaton, Charles B %A Eppinga, Ruben N %A Faul, Jessica D %A Floyd, James S %A Forouhi, Nita G %A Forrester, Terrence %A Friedlander, Yechiel %A Gandin, Ilaria %A Gao, He %A Ghanbari, Mohsen %A Gharib, Sina A %A Gigante, Bruna %A Giulianini, Franco %A Grabe, Hans J %A Gu, C Charles %A Harris, Tamara B %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hixson, James E %A Ikram, M Arfan %A Jia, Yucheng %A Joehanes, Roby %A Johnson, Craig %A Jonas, Jost Bruno %A Justice, Anne E %A Katsuya, Tomohiro %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Kolcic, Ivana %A Kooperberg, Charles %A Krieger, Jose E %A Kritchevsky, Stephen B %A Kubo, Michiaki %A Kuusisto, Johanna %A Lakka, Timo A %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lewis, Cora E %A Li, Yize %A Liang, Jingjing %A Lin, Shiow %A Liu, Ching-Ti %A Liu, Jianjun %A Liu, Kiang %A Loh, Marie %A Lohman, Kurt K %A Louie, Tin %A Luzzi, Anna %A Mägi, Reedik %A Mahajan, Anubha %A Manichaikul, Ani W %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mohlke, Karen L %A Momozawa, Yukihide %A Morris, Andrew P %A Murray, Alison D %A Nalls, Mike A %A Nauck, Matthias %A Nelson, Christopher P %A North, Kari E %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Papanicolau, George J %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Poulter, Neil %A Raitakari, Olli T %A Reiner, Alex P %A Renstrom, Frida %A Rice, Treva K %A Rich, Stephen S %A Robinson, Jennifer G %A Rose, Lynda M %A Rosendaal, Frits R %A Rudan, Igor %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Sever, Peter %A Shi, Yuan %A Sidney, Stephen %A Sims, Mario %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Stringham, Heather M %A Tan, Nicholas Y Q %A Tang, Hua %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Tiemeier, Henning %A Turner, Stephen T %A Uitterlinden, André G %A van Heemst, Diana %A Waldenberger, Melanie %A Wang, Heming %A Wang, Lan %A Wang, Lihua %A Wei, Wen Bin %A Williams, Christine A %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Young, Kristin %A Yu, Caizheng %A Yuan, Jian-Min %A Zhou, Jie %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Cooper, Richard S %A de Faire, Ulf %A Deary, Ian J %A Elliott, Paul %A Esko, Tõnu %A Farrall, Martin %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo L %A Juang, Jyh-Ming Jimmy %A Kamatani, Yoichiro %A Kammerer, Candace M %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Laurie, Cathy C %A Lee, I-Te %A Lehtimäki, Terho %A Magnusson, Patrik K E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Pereira, Alexandre C %A Rauramaa, Rainer %A Redline, Susan %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wang, Jun-Sing %A Wang, Ya Xing %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Wu, Tangchun %A Zeggini, Eleftheria %A Zheng, Wei %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Kardia, Sharon L R %A Liu, Yongmei %A Psaty, Bruce M %A Ridker, Paul M %A van Dam, Rob M %A Mook-Kanamori, Dennis O %A Fornage, Myriam %A Province, Michael A %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Loos, Ruth J F %A Franceschini, Nora %A Rotter, Jerome I %A Zhu, Xiaofeng %A Bierut, Laura J %A Gauderman, W James %A Rice, Kenneth %A Munroe, Patricia B %A Morrison, Alanna C %A Rao, Dabeeru C %A Rotimi, Charles N %A Cupples, L Adrienne %X

The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.

%B Nat Genet %V 51 %P 636-648 %8 2019 Apr %G eng %N 4 %R 10.1038/s41588-019-0378-y %0 Journal Article %J Nat Commun %D 2019 %T Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration. %A Noordam, Raymond %A Bos, Maxime M %A Wang, Heming %A Winkler, Thomas W %A Bentley, Amy R %A Kilpeläinen, Tuomas O %A de Vries, Paul S %A Sung, Yun Ju %A Schwander, Karen %A Cade, Brian E %A Manning, Alisa %A Aschard, Hugues %A Brown, Michael R %A Chen, Han %A Franceschini, Nora %A Musani, Solomon K %A Richard, Melissa %A Vojinovic, Dina %A Aslibekyan, Stella %A Bartz, Traci M %A de Las Fuentes, Lisa %A Feitosa, Mary %A Horimoto, Andrea R %A Ilkov, Marjan %A Kho, Minjung %A Kraja, Aldi %A Li, Changwei %A Lim, Elise %A Liu, Yongmei %A Mook-Kanamori, Dennis O %A Rankinen, Tuomo %A Tajuddin, Salman M %A van der Spek, Ashley %A Wang, Zhe %A Marten, Jonathan %A Laville, Vincent %A Alver, Maris %A Evangelou, Evangelos %A Graff, Maria E %A He, Meian %A Kuhnel, Brigitte %A Lyytikäinen, Leo-Pekka %A Marques-Vidal, Pedro %A Nolte, Ilja M %A Palmer, Nicholette D %A Rauramaa, Rainer %A Shu, Xiao-Ou %A Snieder, Harold %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Adolfo, Correa %A Ballantyne, Christie %A Bielak, Larry %A Biermasz, Nienke R %A Boerwinkle, Eric %A Dimou, Niki %A Eiriksdottir, Gudny %A Gao, Chuan %A Gharib, Sina A %A Gottlieb, Daniel J %A Haba-Rubio, José %A Harris, Tamara B %A Heikkinen, Sami %A Heinzer, Raphael %A Hixson, James E %A Homuth, Georg %A Ikram, M Arfan %A Komulainen, Pirjo %A Krieger, Jose E %A Lee, Jiwon %A Liu, Jingmin %A Lohman, Kurt K %A Luik, Annemarie I %A Mägi, Reedik %A Martin, Lisa W %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Nalls, Mike A %A O'Connell, Jeff %A Peters, Annette %A Peyser, Patricia %A Raitakari, Olli T %A Reiner, Alex P %A Rensen, Patrick C N %A Rice, Treva K %A Rich, Stephen S %A Roenneberg, Till %A Rotter, Jerome I %A Schreiner, Pamela J %A Shikany, James %A Sidney, Stephen S %A Sims, Mario %A Sitlani, Colleen M %A Sofer, Tamar %A Strauch, Konstantin %A Swertz, Morris A %A Taylor, Kent D %A Uitterlinden, André G %A van Duijn, Cornelia M %A Völzke, Henry %A Waldenberger, Melanie %A Wallance, Robert B %A van Dijk, Ko Willems %A Yu, Caizheng %A Zonderman, Alan B %A Becker, Diane M %A Elliott, Paul %A Esko, Tõnu %A Gieger, Christian %A Grabe, Hans J %A Lakka, Timo A %A Lehtimäki, Terho %A North, Kari E %A Penninx, Brenda W J H %A Vollenweider, Peter %A Wagenknecht, Lynne E %A Wu, Tangchun %A Xiang, Yong-Bing %A Zheng, Wei %A Arnett, Donna K %A Bouchard, Claude %A Evans, Michele K %A Gudnason, Vilmundur %A Kardia, Sharon %A Kelly, Tanika N %A Kritchevsky, Stephen B %A Loos, Ruth J F %A Pereira, Alexandre C %A Province, Mike %A Psaty, Bruce M %A Rotimi, Charles %A Zhu, Xiaofeng %A Amin, Najaf %A Cupples, L Adrienne %A Fornage, Myriam %A Fox, Ervin F %A Guo, Xiuqing %A Gauderman, W James %A Rice, Kenneth %A Kooperberg, Charles %A Munroe, Patricia B %A Liu, Ching-Ti %A Morrison, Alanna C %A Rao, Dabeeru C %A van Heemst, Diana %A Redline, Susan %X

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.

%B Nat Commun %V 10 %P 5121 %8 2019 Nov 12 %G eng %N 1 %R 10.1038/s41467-019-12958-0 %0 Journal Article %J Nat Commun %D 2019 %T Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity. %A Kilpeläinen, Tuomas O %A Bentley, Amy R %A Noordam, Raymond %A Sung, Yun Ju %A Schwander, Karen %A Winkler, Thomas W %A Jakupović, Hermina %A Chasman, Daniel I %A Manning, Alisa %A Ntalla, Ioanna %A Aschard, Hugues %A Brown, Michael R %A de Las Fuentes, Lisa %A Franceschini, Nora %A Guo, Xiuqing %A Vojinovic, Dina %A Aslibekyan, Stella %A Feitosa, Mary F %A Kho, Minjung %A Musani, Solomon K %A Richard, Melissa %A Wang, Heming %A Wang, Zhe %A Bartz, Traci M %A Bielak, Lawrence F %A Campbell, Archie %A Dorajoo, Rajkumar %A Fisher, Virginia %A Hartwig, Fernando P %A Horimoto, Andrea R V R %A Li, Changwei %A Lohman, Kurt K %A Marten, Jonathan %A Sim, Xueling %A Smith, Albert V %A Tajuddin, Salman M %A Alver, Maris %A Amini, Marzyeh %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Evangelou, Evangelos %A Gao, Chuan %A Graff, Mariaelisa %A Harris, Sarah E %A He, Meian %A Hsu, Fang-Chi %A Jackson, Anne U %A Zhao, Jing Hua %A Kraja, Aldi T %A Kuhnel, Brigitte %A Laguzzi, Federica %A Lyytikäinen, Leo-Pekka %A Nolte, Ilja M %A Rauramaa, Rainer %A Riaz, Muhammad %A Robino, Antonietta %A Rueedi, Rico %A Stringham, Heather M %A Takeuchi, Fumihiko %A van der Most, Peter J %A Varga, Tibor V %A Verweij, Niek %A Ware, Erin B %A Wen, Wanqing %A Li, Xiaoyin %A Yanek, Lisa R %A Amin, Najaf %A Arnett, Donna K %A Boerwinkle, Eric %A Brumat, Marco %A Cade, Brian %A Canouil, Mickaël %A Chen, Yii-Der Ida %A Concas, Maria Pina %A Connell, John %A de Mutsert, Renée %A de Silva, H Janaka %A de Vries, Paul S %A Demirkan, Ayse %A Ding, Jingzhong %A Eaton, Charles B %A Faul, Jessica D %A Friedlander, Yechiel %A Gabriel, Kelley P %A Ghanbari, Mohsen %A Giulianini, Franco %A Gu, Chi Charles %A Gu, Dongfeng %A Harris, Tamara B %A He, Jiang %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hunt, Steven C %A Ikram, M Arfan %A Jonas, Jost B %A Koh, Woon-Puay %A Komulainen, Pirjo %A Krieger, Jose E %A Kritchevsky, Stephen B %A Kutalik, Zoltán %A Kuusisto, Johanna %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Leander, Karin %A Lemaitre, Rozenn N %A Lewis, Cora E %A Liang, Jingjing %A Liu, Jianjun %A Mägi, Reedik %A Manichaikul, Ani %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Mohlke, Karen L %A Mosley, Thomas H %A Murray, Alison D %A Nalls, Mike A %A Nang, Ei-Ei Khaing %A Nelson, Christopher P %A Nona, Sotoodehnia %A Norris, Jill M %A Nwuba, Chiamaka Vivian %A O'Connell, Jeff %A Palmer, Nicholette D %A Papanicolau, George J %A Pazoki, Raha %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Porteous, David J %A Poveda, Alaitz %A Raitakari, Olli T %A Rich, Stephen S %A Risch, Neil %A Robinson, Jennifer G %A Rose, Lynda M %A Rudan, Igor %A Schreiner, Pamela J %A Scott, Robert A %A Sidney, Stephen S %A Sims, Mario %A Smith, Jennifer A %A Snieder, Harold %A Sofer, Tamar %A Starr, John M %A Sternfeld, Barbara %A Strauch, Konstantin %A Tang, Hua %A Taylor, Kent D %A Tsai, Michael Y %A Tuomilehto, Jaakko %A Uitterlinden, André G %A van der Ende, M Yldau %A van Heemst, Diana %A Voortman, Trudy %A Waldenberger, Melanie %A Wennberg, Patrik %A Wilson, Gregory %A Xiang, Yong-Bing %A Yao, Jie %A Yu, Caizheng %A Yuan, Jian-Min %A Zhao, Wei %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A de Faire, Ulf %A Deary, Ian J %A Elliott, Paul %A Esko, Tõnu %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Kato, Norihiro %A Laakso, Markku %A Lakka, Timo A %A Lehtimäki, Terho %A Magnusson, Patrik K E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Samani, Nilesh J %A Shu, Xiao-Ou %A van der Harst, Pim %A van Vliet-Ostaptchouk, Jana V %A Vollenweider, Peter %A Wagenknecht, Lynne E %A Wang, Ya X %A Wareham, Nicholas J %A Weir, David R %A Wu, Tangchun %A Zheng, Wei %A Zhu, Xiaofeng %A Evans, Michele K %A Franks, Paul W %A Gudnason, Vilmundur %A Hayward, Caroline %A Horta, Bernardo L %A Kelly, Tanika N %A Liu, Yongmei %A North, Kari E %A Pereira, Alexandre C %A Ridker, Paul M %A Tai, E Shyong %A van Dam, Rob M %A Fox, Ervin R %A Kardia, Sharon L R %A Liu, Ching-Ti %A Mook-Kanamori, Dennis O %A Province, Michael A %A Redline, Susan %A van Duijn, Cornelia M %A Rotter, Jerome I %A Kooperberg, Charles B %A Gauderman, W James %A Psaty, Bruce M %A Rice, Kenneth %A Munroe, Patricia B %A Fornage, Myriam %A Cupples, L Adrienne %A Rotimi, Charles N %A Morrison, Alanna C %A Rao, Dabeeru C %A Loos, Ruth J F %K Adolescent %K Adult %K African Continental Ancestry Group %K Aged %K Aged, 80 and over %K Asian Continental Ancestry Group %K Brazil %K Calcium-Binding Proteins %K Cholesterol %K Cholesterol, HDL %K Cholesterol, LDL %K European Continental Ancestry Group %K Exercise %K Female %K Genetic Loci %K Genome-Wide Association Study %K Genotype %K Hispanic Americans %K Humans %K LIM-Homeodomain Proteins %K Lipid Metabolism %K Lipids %K Male %K Membrane Proteins %K Microtubule-Associated Proteins %K Middle Aged %K Muscle Proteins %K Nerve Tissue Proteins %K Transcription Factors %K Triglycerides %K Young Adult %X

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.

%B Nat Commun %V 10 %P 376 %8 2019 01 22 %G eng %N 1 %R 10.1038/s41467-018-08008-w %0 Journal Article %J Am J Hum Genet %D 2019 %T Sequencing Analysis at 8p23 Identifies Multiple Rare Variants in DLC1 Associated with Sleep-Related Oxyhemoglobin Saturation Level. %A Liang, Jingjing %A Cade, Brian E %A He, Karen Y %A Wang, Heming %A Lee, Jiwon %A Sofer, Tamar %A Williams, Stephanie %A Li, Ruitong %A Chen, Han %A Gottlieb, Daniel J %A Evans, Daniel S %A Guo, Xiuqing %A Gharib, Sina A %A Hale, Lauren %A Hillman, David R %A Lutsey, Pamela L %A Mukherjee, Sutapa %A Ochs-Balcom, Heather M %A Palmer, Lyle J %A Rhodes, Jessica %A Purcell, Shaun %A Patel, Sanjay R %A Saxena, Richa %A Stone, Katie L %A Tang, Weihong %A Tranah, Gregory J %A Boerwinkle, Eric %A Lin, Xihong %A Liu, Yongmei %A Psaty, Bruce M %A Vasan, Ramachandran S %A Cho, Michael H %A Manichaikul, Ani %A Silverman, Edwin K %A Barr, R Graham %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Redline, Susan %A Zhu, Xiaofeng %X

Average arterial oxyhemoglobin saturation during sleep (AvSpOS) is a clinically relevant measure of physiological stress associated with sleep-disordered breathing, and this measure predicts incident cardiovascular disease and mortality. Using high-depth whole-genome sequencing data from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) project and focusing on genes with linkage evidence on chromosome 8p23, we observed that six coding and 51 noncoding variants in a gene that encodes the GTPase-activating protein (DLC1) are significantly associated with AvSpOS and replicated in independent subjects. The combined DLC1 association evidence of discovery and replication cohorts reaches genome-wide significance in European Americans (p = 7.9 × 10). A risk score for these variants, built on an independent dataset, explains 0.97% of the AvSpOS variation and contributes to the linkage evidence. The 51 noncoding variants are enriched in regulatory features in a human lung fibroblast cell line and contribute to DLC1 expression variation. Mendelian randomization analysis using these variants indicates a significant causal effect of DLC1 expression in fibroblasts on AvSpOS. Multiple sources of information, including genetic variants, gene expression, and methylation, consistently suggest that DLC1 is a gene associated with AvSpOS.

%B Am J Hum Genet %V 105 %P 1057-1068 %8 2019 Nov 07 %G eng %N 5 %R 10.1016/j.ajhg.2019.10.002 %0 Journal Article %J Lancet Respir Med %D 2020 %T Chronic obstructive pulmonary disease and related phenotypes: polygenic risk scores in population-based and case-control cohorts. %A Moll, Matthew %A Sakornsakolpat, Phuwanat %A Shrine, Nick %A Hobbs, Brian D %A DeMeo, Dawn L %A John, Catherine %A Guyatt, Anna L %A McGeachie, Michael J %A Gharib, Sina A %A Obeidat, Ma'en %A Lahousse, Lies %A Wijnant, Sara R A %A Brusselle, Guy %A Meyers, Deborah A %A Bleecker, Eugene R %A Li, Xingnan %A Tal-Singer, Ruth %A Manichaikul, Ani %A Rich, Stephen S %A Won, Sungho %A Kim, Woo Jin %A Do, Ah Ra %A Washko, George R %A Barr, R Graham %A Psaty, Bruce M %A Bartz, Traci M %A Hansel, Nadia N %A Barnes, Kathleen %A Hokanson, John E %A Crapo, James D %A Lynch, David %A Bakke, Per %A Gulsvik, Amund %A Hall, Ian P %A Wain, Louise %A Weiss, Scott T %A Silverman, Edwin K %A Dudbridge, Frank %A Tobin, Martin D %A Cho, Michael H %K Adult %K Case-Control Studies %K Cohort Studies %K Female %K Forced Expiratory Volume %K Genome-Wide Association Study %K Humans %K Male %K Middle Aged %K Phenotype %K Pulmonary Disease, Chronic Obstructive %K Risk Factors %K Vital Capacity %X

BACKGROUND: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes.

METHODS: We constructed a polygenic risk score using a genome-wide association study of lung function (FEV and FEV/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV/FVC <0·7 and FEV <80% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth.

FINDINGS: The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1·81 [95% CI 1·74-1·88] and non-European (1·42 [1·34-1·51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7·99 (6·56-9·72) in European ancestry and 4·83 (3·45-6·77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0·80 [0·79-0·81] vs 0·76 [0·75-0·76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The polygenic risk score was associated with a reduced lung growth pattern.

INTERPRETATION: A risk score comprised of genetic variants can identify a small subset of individuals at markedly increased risk for moderate-to-severe COPD, emphysema subtypes associated with cigarette smoking, and patterns of reduced lung growth.

FUNDING: US National Institutes of Health, Wellcome Trust.

%B Lancet Respir Med %V 8 %P 696-708 %8 2020 07 %G eng %N 7 %R 10.1016/S2213-2600(20)30101-6 %0 Journal Article %J PLoS One %D 2020 %T Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. %A Hahn, Julie %A Fu, Yi-Ping %A Brown, Michael R %A Bis, Joshua C %A de Vries, Paul S %A Feitosa, Mary F %A Yanek, Lisa R %A Weiss, Stefan %A Giulianini, Franco %A Smith, Albert Vernon %A Guo, Xiuqing %A Bartz, Traci M %A Becker, Diane M %A Becker, Lewis C %A Boerwinkle, Eric %A Brody, Jennifer A %A Chen, Yii-Der Ida %A Franco, Oscar H %A Grove, Megan %A Harris, Tamara B %A Hofman, Albert %A Hwang, Shih-Jen %A Kral, Brian G %A Launer, Lenore J %A Markus, Marcello R P %A Rice, Kenneth M %A Rich, Stephen S %A Ridker, Paul M %A Rivadeneira, Fernando %A Rotter, Jerome I %A Sotoodehnia, Nona %A Taylor, Kent D %A Uitterlinden, André G %A Völker, Uwe %A Völzke, Henry %A Yao, Jie %A Chasman, Daniel I %A Dörr, Marcus %A Gudnason, Vilmundur %A Mathias, Rasika A %A Post, Wendy %A Psaty, Bruce M %A Dehghan, Abbas %A O'Donnell, Christopher J %A Morrison, Alanna C %K Aging %K Coronary Artery Disease %K Cross-Sectional Studies %K Europe %K European Continental Ancestry Group %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Myocardial Infarction %K Polymorphism, Single Nucleotide %K Prospective Studies %X

BACKGROUND: Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome.

METHODS AND RESULTS: Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10-7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) ≥ 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event.

CONCLUSION: This study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation.

%B PLoS One %V 15 %P e0230035 %8 2020 %G eng %N 11 %R 10.1371/journal.pone.0230035 %0 Journal Article %J Nature %D 2020 %T Inherited causes of clonal haematopoiesis in 97,691 whole genomes. %A Bick, Alexander G %A Weinstock, Joshua S %A Nandakumar, Satish K %A Fulco, Charles P %A Bao, Erik L %A Zekavat, Seyedeh M %A Szeto, Mindy D %A Liao, Xiaotian %A Leventhal, Matthew J %A Nasser, Joseph %A Chang, Kyle %A Laurie, Cecelia %A Burugula, Bala Bharathi %A Gibson, Christopher J %A Lin, Amy E %A Taub, Margaret A %A Aguet, Francois %A Ardlie, Kristin %A Mitchell, Braxton D %A Barnes, Kathleen C %A Moscati, Arden %A Fornage, Myriam %A Redline, Susan %A Psaty, Bruce M %A Silverman, Edwin K %A Weiss, Scott T %A Palmer, Nicholette D %A Vasan, Ramachandran S %A Burchard, Esteban G %A Kardia, Sharon L R %A He, Jiang %A Kaplan, Robert C %A Smith, Nicholas L %A Arnett, Donna K %A Schwartz, David A %A Correa, Adolfo %A de Andrade, Mariza %A Guo, Xiuqing %A Konkle, Barbara A %A Custer, Brian %A Peralta, Juan M %A Gui, Hongsheng %A Meyers, Deborah A %A McGarvey, Stephen T %A Chen, Ida Yii-Der %A Shoemaker, M Benjamin %A Peyser, Patricia A %A Broome, Jai G %A Gogarten, Stephanie M %A Wang, Fei Fei %A Wong, Quenna %A Montasser, May E %A Daya, Michelle %A Kenny, Eimear E %A North, Kari E %A Launer, Lenore J %A Cade, Brian E %A Bis, Joshua C %A Cho, Michael H %A Lasky-Su, Jessica %A Bowden, Donald W %A Cupples, L Adrienne %A Mak, Angel C Y %A Becker, Lewis C %A Smith, Jennifer A %A Kelly, Tanika N %A Aslibekyan, Stella %A Heckbert, Susan R %A Tiwari, Hemant K %A Yang, Ivana V %A Heit, John A %A Lubitz, Steven A %A Johnsen, Jill M %A Curran, Joanne E %A Wenzel, Sally E %A Weeks, Daniel E %A Rao, Dabeeru C %A Darbar, Dawood %A Moon, Jee-Young %A Tracy, Russell P %A Buth, Erin J %A Rafaels, Nicholas %A Loos, Ruth J F %A Durda, Peter %A Liu, Yongmei %A Hou, Lifang %A Lee, Jiwon %A Kachroo, Priyadarshini %A Freedman, Barry I %A Levy, Daniel %A Bielak, Lawrence F %A Hixson, James E %A Floyd, James S %A Whitsel, Eric A %A Ellinor, Patrick T %A Irvin, Marguerite R %A Fingerlin, Tasha E %A Raffield, Laura M %A Armasu, Sebastian M %A Wheeler, Marsha M %A Sabino, Ester C %A Blangero, John %A Williams, L Keoki %A Levy, Bruce D %A Sheu, Wayne Huey-Herng %A Roden, Dan M %A Boerwinkle, Eric %A Manson, JoAnn E %A Mathias, Rasika A %A Desai, Pinkal %A Taylor, Kent D %A Johnson, Andrew D %A Auer, Paul L %A Kooperberg, Charles %A Laurie, Cathy C %A Blackwell, Thomas W %A Smith, Albert V %A Zhao, Hongyu %A Lange, Ethan %A Lange, Leslie %A Rich, Stephen S %A Rotter, Jerome I %A Wilson, James G %A Scheet, Paul %A Kitzman, Jacob O %A Lander, Eric S %A Engreitz, Jesse M %A Ebert, Benjamin L %A Reiner, Alexander P %A Jaiswal, Siddhartha %A Abecasis, Goncalo %A Sankaran, Vijay G %A Kathiresan, Sekar %A Natarajan, Pradeep %X

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

%B Nature %V 586 %P 763-768 %8 2020 10 %G eng %N 7831 %R 10.1038/s41586-020-2819-2 %0 Journal Article %J Cell %D 2020 %T The Polygenic and Monogenic Basis of Blood Traits and Diseases. %A Vuckovic, Dragana %A Bao, Erik L %A Akbari, Parsa %A Lareau, Caleb A %A Mousas, Abdou %A Jiang, Tao %A Chen, Ming-Huei %A Raffield, Laura M %A Tardaguila, Manuel %A Huffman, Jennifer E %A Ritchie, Scott C %A Megy, Karyn %A Ponstingl, Hannes %A Penkett, Christopher J %A Albers, Patrick K %A Wigdor, Emilie M %A Sakaue, Saori %A Moscati, Arden %A Manansala, Regina %A Lo, Ken Sin %A Qian, Huijun %A Akiyama, Masato %A Bartz, Traci M %A Ben-Shlomo, Yoav %A Beswick, Andrew %A Bork-Jensen, Jette %A Bottinger, Erwin P %A Brody, Jennifer A %A van Rooij, Frank J A %A Chitrala, Kumaraswamy N %A Wilson, Peter W F %A Choquet, Helene %A Danesh, John %A Di Angelantonio, Emanuele %A Dimou, Niki %A Ding, Jingzhong %A Elliott, Paul %A Esko, Tõnu %A Evans, Michele K %A Felix, Stephan B %A Floyd, James S %A Broer, Linda %A Grarup, Niels %A Guo, Michael H %A Guo, Qi %A Greinacher, Andreas %A Haessler, Jeff %A Hansen, Torben %A Howson, Joanna M M %A Huang, Wei %A Jorgenson, Eric %A Kacprowski, Tim %A Kähönen, Mika %A Kamatani, Yoichiro %A Kanai, Masahiro %A Karthikeyan, Savita %A Koskeridis, Fotios %A Lange, Leslie A %A Lehtimäki, Terho %A Linneberg, Allan %A Liu, Yongmei %A Lyytikäinen, Leo-Pekka %A Manichaikul, Ani %A Matsuda, Koichi %A Mohlke, Karen L %A Mononen, Nina %A Murakami, Yoshinori %A Nadkarni, Girish N %A Nikus, Kjell %A Pankratz, Nathan %A Pedersen, Oluf %A Preuss, Michael %A Psaty, Bruce M %A Raitakari, Olli T %A Rich, Stephen S %A Rodriguez, Benjamin A T %A Rosen, Jonathan D %A Rotter, Jerome I %A Schubert, Petra %A Spracklen, Cassandra N %A Surendran, Praveen %A Tang, Hua %A Tardif, Jean-Claude %A Ghanbari, Mohsen %A Völker, Uwe %A Völzke, Henry %A Watkins, Nicholas A %A Weiss, Stefan %A Cai, Na %A Kundu, Kousik %A Watt, Stephen B %A Walter, Klaudia %A Zonderman, Alan B %A Cho, Kelly %A Li, Yun %A Loos, Ruth J F %A Knight, Julian C %A Georges, Michel %A Stegle, Oliver %A Evangelou, Evangelos %A Okada, Yukinori %A Roberts, David J %A Inouye, Michael %A Johnson, Andrew D %A Auer, Paul L %A Astle, William J %A Reiner, Alexander P %A Butterworth, Adam S %A Ouwehand, Willem H %A Lettre, Guillaume %A Sankaran, Vijay G %A Soranzo, Nicole %X

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.

%B Cell %V 182 %P 1214-1231.e11 %8 2020 Sep 03 %G eng %N 5 %R 10.1016/j.cell.2020.08.008 %0 Journal Article %J Circ Genom Precis Med %D 2020 %T Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels. %A Wang, Zhe %A Chen, Han %A Bartz, Traci M %A Bielak, Lawrence F %A Chasman, Daniel I %A Feitosa, Mary F %A Franceschini, Nora %A Guo, Xiuqing %A Lim, Elise %A Noordam, Raymond %A Richard, Melissa A %A Wang, Heming %A Cade, Brian %A Cupples, L Adrienne %A de Vries, Paul S %A Giulanini, Franco %A Lee, Jiwon %A Lemaitre, Rozenn N %A Martin, Lisa W %A Reiner, Alex P %A Rich, Stephen S %A Schreiner, Pamela J %A Sidney, Stephen %A Sitlani, Colleen M %A Smith, Jennifer A %A Willems van Dijk, Ko %A Yao, Jie %A Zhao, Wei %A Fornage, Myriam %A Kardia, Sharon L R %A Kooperberg, Charles %A Liu, Ching-Ti %A Mook-Kanamori, Dennis O %A Province, Michael A %A Psaty, Bruce M %A Redline, Susan %A Ridker, Paul M %A Rotter, Jerome I %A Boerwinkle, Eric %A Morrison, Alanna C %X

BACKGROUND: Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.

METHODS: In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.

RESULTS: We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (, , , , , , , and ) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (=6.65×10 for the interaction test) and replicated at nominal significance level (=0.013) in .

CONCLUSIONS: In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.

%B Circ Genom Precis Med %V 13 %P e002772 %8 2020 Aug %G eng %N 4 %R 10.1161/CIRCGEN.119.002772 %0 Journal Article %J Cell %D 2020 %T Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations. %A Chen, Ming-Huei %A Raffield, Laura M %A Mousas, Abdou %A Sakaue, Saori %A Huffman, Jennifer E %A Moscati, Arden %A Trivedi, Bhavi %A Jiang, Tao %A Akbari, Parsa %A Vuckovic, Dragana %A Bao, Erik L %A Zhong, Xue %A Manansala, Regina %A Laplante, Véronique %A Chen, Minhui %A Lo, Ken Sin %A Qian, Huijun %A Lareau, Caleb A %A Beaudoin, Mélissa %A Hunt, Karen A %A Akiyama, Masato %A Bartz, Traci M %A Ben-Shlomo, Yoav %A Beswick, Andrew %A Bork-Jensen, Jette %A Bottinger, Erwin P %A Brody, Jennifer A %A van Rooij, Frank J A %A Chitrala, Kumaraswamynaidu %A Cho, Kelly %A Choquet, Helene %A Correa, Adolfo %A Danesh, John %A Di Angelantonio, Emanuele %A Dimou, Niki %A Ding, Jingzhong %A Elliott, Paul %A Esko, Tõnu %A Evans, Michele K %A Floyd, James S %A Broer, Linda %A Grarup, Niels %A Guo, Michael H %A Greinacher, Andreas %A Haessler, Jeff %A Hansen, Torben %A Howson, Joanna M M %A Huang, Qin Qin %A Huang, Wei %A Jorgenson, Eric %A Kacprowski, Tim %A Kähönen, Mika %A Kamatani, Yoichiro %A Kanai, Masahiro %A Karthikeyan, Savita %A Koskeridis, Fotis %A Lange, Leslie A %A Lehtimäki, Terho %A Lerch, Markus M %A Linneberg, Allan %A Liu, Yongmei %A Lyytikäinen, Leo-Pekka %A Manichaikul, Ani %A Martin, Hilary C %A Matsuda, Koichi %A Mohlke, Karen L %A Mononen, Nina %A Murakami, Yoshinori %A Nadkarni, Girish N %A Nauck, Matthias %A Nikus, Kjell %A Ouwehand, Willem H %A Pankratz, Nathan %A Pedersen, Oluf %A Preuss, Michael %A Psaty, Bruce M %A Raitakari, Olli T %A Roberts, David J %A Rich, Stephen S %A Rodriguez, Benjamin A T %A Rosen, Jonathan D %A Rotter, Jerome I %A Schubert, Petra %A Spracklen, Cassandra N %A Surendran, Praveen %A Tang, Hua %A Tardif, Jean-Claude %A Trembath, Richard C %A Ghanbari, Mohsen %A Völker, Uwe %A Völzke, Henry %A Watkins, Nicholas A %A Zonderman, Alan B %A Wilson, Peter W F %A Li, Yun %A Butterworth, Adam S %A Gauchat, Jean-François %A Chiang, Charleston W K %A Li, Bingshan %A Loos, Ruth J F %A Astle, William J %A Evangelou, Evangelos %A van Heel, David A %A Sankaran, Vijay G %A Okada, Yukinori %A Soranzo, Nicole %A Johnson, Andrew D %A Reiner, Alexander P %A Auer, Paul L %A Lettre, Guillaume %X

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

%B Cell %V 182 %P 1198-1213.e14 %8 2020 Sep 03 %G eng %N 5 %R 10.1016/j.cell.2020.06.045 %0 Journal Article %J Nat Commun %D 2020 %T Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants. %A Zhao, Xutong %A Qiao, Dandi %A Yang, Chaojie %A Kasela, Silva %A Kim, Wonji %A Ma, Yanlin %A Shrine, Nick %A Batini, Chiara %A Sofer, Tamar %A Taliun, Sarah A Gagliano %A Sakornsakolpat, Phuwanat %A Balte, Pallavi P %A Prokopenko, Dmitry %A Yu, Bing %A Lange, Leslie A %A Dupuis, Josée %A Cade, Brian E %A Lee, Jiwon %A Gharib, Sina A %A Daya, Michelle %A Laurie, Cecelia A %A Ruczinski, Ingo %A Cupples, L Adrienne %A Loehr, Laura R %A Bartz, Traci M %A Morrison, Alanna C %A Psaty, Bruce M %A Vasan, Ramachandran S %A Wilson, James G %A Taylor, Kent D %A Durda, Peter %A Johnson, W Craig %A Cornell, Elaine %A Guo, Xiuqing %A Liu, Yongmei %A Tracy, Russell P %A Ardlie, Kristin G %A Aguet, Francois %A VanDenBerg, David J %A Papanicolaou, George J %A Rotter, Jerome I %A Barnes, Kathleen C %A Jain, Deepti %A Nickerson, Deborah A %A Muzny, Donna M %A Metcalf, Ginger A %A Doddapaneni, Harshavardhan %A Dugan-Perez, Shannon %A Gupta, Namrata %A Gabriel, Stacey %A Rich, Stephen S %A O'Connor, George T %A Redline, Susan %A Reed, Robert M %A Laurie, Cathy C %A Daviglus, Martha L %A Preudhomme, Liana K %A Burkart, Kristin M %A Kaplan, Robert C %A Wain, Louise V %A Tobin, Martin D %A London, Stephanie J %A Lappalainen, Tuuli %A Oelsner, Elizabeth C %A Abecasis, Goncalo R %A Silverman, Edwin K %A Barr, R Graham %A Cho, Michael H %A Manichaikul, Ani %K Adult %K African Americans %K Aged %K Aged, 80 and over %K Alpha-Ketoglutarate-Dependent Dioxygenase FTO %K Calcium-Binding Proteins %K Feasibility Studies %K Female %K Follow-Up Studies %K Genetic Loci %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Intracellular Signaling Peptides and Proteins %K Lung %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Protein Inhibitors of Activated STAT %K Pulmonary Disease, Chronic Obstructive %K Respiratory Physiological Phenomena %K Small Ubiquitin-Related Modifier Proteins %K Whole Genome Sequencing %X

Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry.

%B Nat Commun %V 11 %P 5182 %8 2020 10 14 %G eng %N 1 %R 10.1038/s41467-020-18334-7 %0 Journal Article %J Cell Genom %D 2021 %T Association of mitochondrial DNA copy number with cardiometabolic diseases. %A Liu, Xue %A Longchamps, Ryan J %A Wiggins, Kerri L %A Raffield, Laura M %A Bielak, Lawrence F %A Zhao, Wei %A Pitsillides, Achilleas %A Blackwell, Thomas W %A Yao, Jie %A Guo, Xiuqing %A Kurniansyah, Nuzulul %A Thyagarajan, Bharat %A Pankratz, Nathan %A Rich, Stephen S %A Taylor, Kent D %A Peyser, Patricia A %A Heckbert, Susan R %A Seshadri, Sudha %A Cupples, L Adrienne %A Boerwinkle, Eric %A Grove, Megan L %A Larson, Nicholas B %A Smith, Jennifer A %A Vasan, Ramachandran S %A Sofer, Tamar %A Fitzpatrick, Annette L %A Fornage, Myriam %A Ding, Jun %A Correa, Adolfo %A Abecasis, Goncalo %A Psaty, Bruce M %A Wilson, James G %A Levy, Daniel %A Rotter, Jerome I %A Bis, Joshua C %A Satizabal, Claudia L %A Arking, Dan E %A Liu, Chunyu %X

Mitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (<65 years of age), each additional 10 years of age was associated with 0.03 standard deviation (s.d.) higher level of mtDNA CN ( = 0.0014) versus a 0.14 s.d. lower level of mtDNA CN ( = 1.82 × 10) among older participants (≥65 years). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity ( = 5.6 × 10), hypertension ( = 2.8 × 10), diabetes ( = 3.6 × 10), and hyperlipidemia ( = 6.3 × 10). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.

%B Cell Genom %V 1 %8 2021 Oct 13 %G eng %N 1 %R 10.1016/j.xgen.2021.100006 %0 Journal Article %J HGG Adv %D 2021 %T BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion. %A Sofer, Tamar %A Lee, Jiwon %A Kurniansyah, Nuzulul %A Jain, Deepti %A Laurie, Cecelia A %A Gogarten, Stephanie M %A Conomos, Matthew P %A Heavner, Ben %A Hu, Yao %A Kooperberg, Charles %A Haessler, Jeffrey %A Vasan, Ramachandran S %A Cupples, L Adrienne %A Coombes, Brandon J %A Seyerle, Amanda %A Gharib, Sina A %A Chen, Han %A O'Connell, Jeffrey R %A Zhang, Man %A Gottlieb, Daniel J %A Psaty, Bruce M %A Longstreth, W T %A Rotter, Jerome I %A Taylor, Kent D %A Rich, Stephen S %A Guo, Xiuqing %A Boerwinkle, Eric %A Morrison, Alanna C %A Pankow, James S %A Johnson, Andrew D %A Pankratz, Nathan %A Reiner, Alex P %A Redline, Susan %A Smith, Nicholas L %A Rice, Kenneth M %A Schifano, Elizabeth D %X

Whole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.

%B HGG Adv %V 2 %8 2021 Jul 08 %G eng %N 3 %R 10.1016/j.xhgg.2021.100040 %0 Journal Article %J Nat Commun %D 2021 %T Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices. %A Natarajan, Pradeep %A Pampana, Akhil %A Graham, Sarah E %A Ruotsalainen, Sanni E %A Perry, James A %A de Vries, Paul S %A Broome, Jai G %A Pirruccello, James P %A Honigberg, Michael C %A Aragam, Krishna %A Wolford, Brooke %A Brody, Jennifer A %A Antonacci-Fulton, Lucinda %A Arden, Moscati %A Aslibekyan, Stella %A Assimes, Themistocles L %A Ballantyne, Christie M %A Bielak, Lawrence F %A Bis, Joshua C %A Cade, Brian E %A Do, Ron %A Doddapaneni, Harsha %A Emery, Leslie S %A Hung, Yi-Jen %A Irvin, Marguerite R %A Khan, Alyna T %A Lange, Leslie %A Lee, Jiwon %A Lemaitre, Rozenn N %A Martin, Lisa W %A Metcalf, Ginger %A Montasser, May E %A Moon, Jee-Young %A Muzny, Donna %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peralta, Juan M %A Peyser, Patricia A %A Stilp, Adrienne M %A Tsai, Michael %A Wang, Fei Fei %A Weeks, Daniel E %A Yanek, Lisa R %A Wilson, James G %A Abecasis, Goncalo %A Arnett, Donna K %A Becker, Lewis C %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Chang, Yi-Cheng %A Chen, Yii-der I %A Choi, Won Jung %A Correa, Adolfo %A Curran, Joanne E %A Daly, Mark J %A Dutcher, Susan K %A Ellinor, Patrick T %A Fornage, Myriam %A Freedman, Barry I %A Gabriel, Stacey %A Germer, Soren %A Gibbs, Richard A %A He, Jiang %A Hveem, Kristian %A Jarvik, Gail P %A Kaplan, Robert C %A Kardia, Sharon L R %A Kenny, Eimear %A Kim, Ryan W %A Kooperberg, Charles %A Laurie, Cathy C %A Lee, Seonwook %A Lloyd-Jones, Don M %A Loos, Ruth J F %A Lubitz, Steven A %A Mathias, Rasika A %A Martinez, Karine A Viaud %A McGarvey, Stephen T %A Mitchell, Braxton D %A Nickerson, Deborah A %A North, Kari E %A Palotie, Aarno %A Park, Cheol Joo %A Psaty, Bruce M %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Seo, Daekwan %A Seo, Jeong-Sun %A Smith, Albert V %A Tracy, Russell P %A Vasan, Ramachandran S %A Kathiresan, Sekar %A Cupples, L Adrienne %A Rotter, Jerome I %A Morrison, Alanna C %A Rich, Stephen S %A Ripatti, Samuli %A Willer, Cristen %A Peloso, Gina M %X

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.

%B Nat Commun %V 12 %P 2182 %8 2021 04 12 %G eng %N 1 %R 10.1038/s41467-021-22339-1 %0 Journal Article %J Nat Commun %D 2021 %T Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes. %A Goodrich, Julia K %A Singer-Berk, Moriel %A Son, Rachel %A Sveden, Abigail %A Wood, Jordan %A England, Eleina %A Cole, Joanne B %A Weisburd, Ben %A Watts, Nick %A Caulkins, Lizz %A Dornbos, Peter %A Koesterer, Ryan %A Zappala, Zachary %A Zhang, Haichen %A Maloney, Kristin A %A Dahl, Andy %A Aguilar-Salinas, Carlos A %A Atzmon, Gil %A Barajas-Olmos, Francisco %A Barzilai, Nir %A Blangero, John %A Boerwinkle, Eric %A Bonnycastle, Lori L %A Bottinger, Erwin %A Bowden, Donald W %A Centeno-Cruz, Federico %A Chambers, John C %A Chami, Nathalie %A Chan, Edmund %A Chan, Juliana %A Cheng, Ching-Yu %A Cho, Yoon Shin %A Contreras-Cubas, Cecilia %A Córdova, Emilio %A Correa, Adolfo %A DeFronzo, Ralph A %A Duggirala, Ravindranath %A Dupuis, Josée %A Garay-Sevilla, Ma Eugenia %A García-Ortiz, Humberto %A Gieger, Christian %A Glaser, Benjamin %A González-Villalpando, Clicerio %A Gonzalez, Ma Elena %A Grarup, Niels %A Groop, Leif %A Gross, Myron %A Haiman, Christopher %A Han, Sohee %A Hanis, Craig L %A Hansen, Torben %A Heard-Costa, Nancy L %A Henderson, Brian E %A Hernandez, Juan Manuel Malacara %A Hwang, Mi Yeong %A Islas-Andrade, Sergio %A Jørgensen, Marit E %A Kang, Hyun Min %A Kim, Bong-Jo %A Kim, Young Jin %A Koistinen, Heikki A %A Kooner, Jaspal Singh %A Kuusisto, Johanna %A Kwak, Soo-Heon %A Laakso, Markku %A Lange, Leslie %A Lee, Jong-Young %A Lee, Juyoung %A Lehman, Donna M %A Linneberg, Allan %A Liu, Jianjun %A Loos, Ruth J F %A Lyssenko, Valeriya %A Ma, Ronald C W %A Martínez-Hernández, Angélica %A Meigs, James B %A Meitinger, Thomas %A Mendoza-Caamal, Elvia %A Mohlke, Karen L %A Morris, Andrew D %A Morrison, Alanna C %A Ng, Maggie C Y %A Nilsson, Peter M %A O'Donnell, Christopher J %A Orozco, Lorena %A Palmer, Colin N A %A Park, Kyong Soo %A Post, Wendy S %A Pedersen, Oluf %A Preuss, Michael %A Psaty, Bruce M %A Reiner, Alexander P %A Revilla-Monsalve, Cristina %A Rich, Stephen S %A Rotter, Jerome I %A Saleheen, Danish %A Schurmann, Claudia %A Sim, Xueling %A Sladek, Rob %A Small, Kerrin S %A So, Wing Yee %A Spector, Timothy D %A Strauch, Konstantin %A Strom, Tim M %A Tai, E Shyong %A Tam, Claudia H T %A Teo, Yik Ying %A Thameem, Farook %A Tomlinson, Brian %A Tracy, Russell P %A Tuomi, Tiinamaija %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A van Dam, Rob M %A Vasan, Ramachandran S %A Wilson, James G %A Witte, Daniel R %A Wong, Tien-Yin %A Burtt, Noel P %A Zaitlen, Noah %A McCarthy, Mark I %A Boehnke, Michael %A Pollin, Toni I %A Flannick, Jason %A Mercader, Josep M %A O'Donnell-Luria, Anne %A Baxter, Samantha %A Florez, Jose C %A MacArthur, Daniel G %A Udler, Miriam S %K Adult %K Biological Variation, Population %K Biomarkers %K Diabetes Mellitus, Type 2 %K Dyslipidemias %K Exome %K Genetic Predisposition to Disease %K Genotype %K Humans %K Multifactorial Inheritance %K Penetrance %K Risk Assessment %X

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.

%B Nat Commun %V 12 %P 3505 %8 2021 06 09 %G eng %N 1 %R 10.1038/s41467-021-23556-4 %0 Journal Article %J Mol Psychiatry %D 2021 %T Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure. %A Wang, Heming %A Noordam, Raymond %A Cade, Brian E %A Schwander, Karen %A Winkler, Thomas W %A Lee, Jiwon %A Sung, Yun Ju %A Bentley, Amy R %A Manning, Alisa K %A Aschard, Hugues %A Kilpeläinen, Tuomas O %A Ilkov, Marjan %A Brown, Michael R %A Horimoto, Andrea R %A Richard, Melissa %A Bartz, Traci M %A Vojinovic, Dina %A Lim, Elise %A Nierenberg, Jovia L %A Liu, Yongmei %A Chitrala, Kumaraswamynaidu %A Rankinen, Tuomo %A Musani, Solomon K %A Franceschini, Nora %A Rauramaa, Rainer %A Alver, Maris %A Zee, Phyllis C %A Harris, Sarah E %A van der Most, Peter J %A Nolte, Ilja M %A Munroe, Patricia B %A Palmer, Nicholette D %A Kuhnel, Brigitte %A Weiss, Stefan %A Wen, Wanqing %A Hall, Kelly A %A Lyytikäinen, Leo-Pekka %A O'Connell, Jeff %A Eiriksdottir, Gudny %A Launer, Lenore J %A de Vries, Paul S %A Arking, Dan E %A Chen, Han %A Boerwinkle, Eric %A Krieger, Jose E %A Schreiner, Pamela J %A Sidney, Stephen %A Shikany, James M %A Rice, Kenneth %A Chen, Yii-Der Ida %A Gharib, Sina A %A Bis, Joshua C %A Luik, Annemarie I %A Ikram, M Arfan %A Uitterlinden, André G %A Amin, Najaf %A Xu, Hanfei %A Levy, Daniel %A He, Jiang %A Lohman, Kurt K %A Zonderman, Alan B %A Rice, Treva K %A Sims, Mario %A Wilson, Gregory %A Sofer, Tamar %A Rich, Stephen S %A Palmas, Walter %A Yao, Jie %A Guo, Xiuqing %A Rotter, Jerome I %A Biermasz, Nienke R %A Mook-Kanamori, Dennis O %A Martin, Lisa W %A Barac, Ana %A Wallace, Robert B %A Gottlieb, Daniel J %A Komulainen, Pirjo %A Heikkinen, Sami %A Mägi, Reedik %A Milani, Lili %A Metspalu, Andres %A Starr, John M %A Milaneschi, Yuri %A Waken, R J %A Gao, Chuan %A Waldenberger, Melanie %A Peters, Annette %A Strauch, Konstantin %A Meitinger, Thomas %A Roenneberg, Till %A Völker, Uwe %A Dörr, Marcus %A Shu, Xiao-Ou %A Mukherjee, Sutapa %A Hillman, David R %A Kähönen, Mika %A Wagenknecht, Lynne E %A Gieger, Christian %A Grabe, Hans J %A Zheng, Wei %A Palmer, Lyle J %A Lehtimäki, Terho %A Gudnason, Vilmundur %A Morrison, Alanna C %A Pereira, Alexandre C %A Fornage, Myriam %A Psaty, Bruce M %A van Duijn, Cornelia M %A Liu, Ching-Ti %A Kelly, Tanika N %A Evans, Michele K %A Bouchard, Claude %A Fox, Ervin R %A Kooperberg, Charles %A Zhu, Xiaofeng %A Lakka, Timo A %A Esko, Tõnu %A North, Kari E %A Deary, Ian J %A Snieder, Harold %A Penninx, Brenda W J H %A Gauderman, W James %A Rao, Dabeeru C %A Redline, Susan %A van Heemst, Diana %X

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 × 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 × 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 × 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.

%B Mol Psychiatry %8 2021 Apr 15 %G eng %R 10.1038/s41380-021-01087-0 %0 Journal Article %J Nature %D 2021 %T Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. %A Taliun, Daniel %A Harris, Daniel N %A Kessler, Michael D %A Carlson, Jedidiah %A Szpiech, Zachary A %A Torres, Raul %A Taliun, Sarah A Gagliano %A Corvelo, André %A Gogarten, Stephanie M %A Kang, Hyun Min %A Pitsillides, Achilleas N %A LeFaive, Jonathon %A Lee, Seung-Been %A Tian, Xiaowen %A Browning, Brian L %A Das, Sayantan %A Emde, Anne-Katrin %A Clarke, Wayne E %A Loesch, Douglas P %A Shetty, Amol C %A Blackwell, Thomas W %A Smith, Albert V %A Wong, Quenna %A Liu, Xiaoming %A Conomos, Matthew P %A Bobo, Dean M %A Aguet, Francois %A Albert, Christine %A Alonso, Alvaro %A Ardlie, Kristin G %A Arking, Dan E %A Aslibekyan, Stella %A Auer, Paul L %A Barnard, John %A Barr, R Graham %A Barwick, Lucas %A Becker, Lewis C %A Beer, Rebecca L %A Benjamin, Emelia J %A Bielak, Lawrence F %A Blangero, John %A Boehnke, Michael %A Bowden, Donald W %A Brody, Jennifer A %A Burchard, Esteban G %A Cade, Brian E %A Casella, James F %A Chalazan, Brandon %A Chasman, Daniel I %A Chen, Yii-Der Ida %A Cho, Michael H %A Choi, Seung Hoan %A Chung, Mina K %A Clish, Clary B %A Correa, Adolfo %A Curran, Joanne E %A Custer, Brian %A Darbar, Dawood %A Daya, Michelle %A de Andrade, Mariza %A DeMeo, Dawn L %A Dutcher, Susan K %A Ellinor, Patrick T %A Emery, Leslie S %A Eng, Celeste %A Fatkin, Diane %A Fingerlin, Tasha %A Forer, Lukas %A Fornage, Myriam %A Franceschini, Nora %A Fuchsberger, Christian %A Fullerton, Stephanie M %A Germer, Soren %A Gladwin, Mark T %A Gottlieb, Daniel J %A Guo, Xiuqing %A Hall, Michael E %A He, Jiang %A Heard-Costa, Nancy L %A Heckbert, Susan R %A Irvin, Marguerite R %A Johnsen, Jill M %A Johnson, Andrew D %A Kaplan, Robert %A Kardia, Sharon L R %A Kelly, Tanika %A Kelly, Shannon %A Kenny, Eimear E %A Kiel, Douglas P %A Klemmer, Robert %A Konkle, Barbara A %A Kooperberg, Charles %A Köttgen, Anna %A Lange, Leslie A %A Lasky-Su, Jessica %A Levy, Daniel %A Lin, Xihong %A Lin, Keng-Han %A Liu, Chunyu %A Loos, Ruth J F %A Garman, Lori %A Gerszten, Robert %A Lubitz, Steven A %A Lunetta, Kathryn L %A Mak, Angel C Y %A Manichaikul, Ani %A Manning, Alisa K %A Mathias, Rasika A %A McManus, David D %A McGarvey, Stephen T %A Meigs, James B %A Meyers, Deborah A %A Mikulla, Julie L %A Minear, Mollie A %A Mitchell, Braxton D %A Mohanty, Sanghamitra %A Montasser, May E %A Montgomery, Courtney %A Morrison, Alanna C %A Murabito, Joanne M %A Natale, Andrea %A Natarajan, Pradeep %A Nelson, Sarah C %A North, Kari E %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Pankratz, Nathan %A Peloso, Gina M %A Peyser, Patricia A %A Pleiness, Jacob %A Post, Wendy S %A Psaty, Bruce M %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Roden, Dan %A Rotter, Jerome I %A Ruczinski, Ingo %A Sarnowski, Chloe %A Schoenherr, Sebastian %A Schwartz, David A %A Seo, Jeong-Sun %A Seshadri, Sudha %A Sheehan, Vivien A %A Sheu, Wayne H %A Shoemaker, M Benjamin %A Smith, Nicholas L %A Smith, Jennifer A %A Sotoodehnia, Nona %A Stilp, Adrienne M %A Tang, Weihong %A Taylor, Kent D %A Telen, Marilyn %A Thornton, Timothy A %A Tracy, Russell P %A Van Den Berg, David J %A Vasan, Ramachandran S %A Viaud-Martinez, Karine A %A Vrieze, Scott %A Weeks, Daniel E %A Weir, Bruce S %A Weiss, Scott T %A Weng, Lu-Chen %A Willer, Cristen J %A Zhang, Yingze %A Zhao, Xutong %A Arnett, Donna K %A Ashley-Koch, Allison E %A Barnes, Kathleen C %A Boerwinkle, Eric %A Gabriel, Stacey %A Gibbs, Richard %A Rice, Kenneth M %A Rich, Stephen S %A Silverman, Edwin K %A Qasba, Pankaj %A Gan, Weiniu %A Papanicolaou, George J %A Nickerson, Deborah A %A Browning, Sharon R %A Zody, Michael C %A Zöllner, Sebastian %A Wilson, James G %A Cupples, L Adrienne %A Laurie, Cathy C %A Jaquish, Cashell E %A Hernandez, Ryan D %A O'Connor, Timothy D %A Abecasis, Goncalo R %X

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes). In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

%B Nature %V 590 %P 290-299 %8 2021 02 %G eng %N 7845 %R 10.1038/s41586-021-03205-y %0 Journal Article %J Am J Epidemiol %D 2021 %T A System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. %A Stilp, Adrienne M %A Emery, Leslie S %A Broome, Jai G %A Buth, Erin J %A Khan, Alyna T %A Laurie, Cecelia A %A Wang, Fei Fei %A Wong, Quenna %A Chen, Dongquan %A D'Augustine, Catherine M %A Heard-Costa, Nancy L %A Hohensee, Chancellor R %A Johnson, William Craig %A Juarez, Lucia D %A Liu, Jingmin %A Mutalik, Karen M %A Raffield, Laura M %A Wiggins, Kerri L %A de Vries, Paul S %A Kelly, Tanika N %A Kooperberg, Charles %A Natarajan, Pradeep %A Peloso, Gina M %A Peyser, Patricia A %A Reiner, Alex P %A Arnett, Donna K %A Aslibekyan, Stella %A Barnes, Kathleen C %A Bielak, Lawrence F %A Bis, Joshua C %A Cade, Brian E %A Chen, Ming-Huei %A Correa, Adolfo %A Cupples, L Adrienne %A de Andrade, Mariza %A Ellinor, Patrick T %A Fornage, Myriam %A Franceschini, Nora %A Gan, Weiniu %A Ganesh, Santhi K %A Graffelman, Jan %A Grove, Megan L %A Guo, Xiuqing %A Hawley, Nicola L %A Hsu, Wan-Ling %A Jackson, Rebecca D %A Jaquish, Cashell E %A Johnson, Andrew D %A Kardia, Sharon L R %A Kelly, Shannon %A Lee, Jiwon %A Mathias, Rasika A %A McGarvey, Stephen T %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A North, Kari E %A Nouraie, Seyed Mehdi %A Oelsner, Elizabeth C %A Pankratz, Nathan %A Rich, Stephen S %A Rotter, Jerome I %A Smith, Jennifer A %A Taylor, Kent D %A Vasan, Ramachandran S %A Weeks, Daniel E %A Weiss, Scott T %A Wilson, Carla G %A Yanek, Lisa R %A Psaty, Bruce M %A Heckbert, Susan R %A Laurie, Cathy C %X

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institute's Trans-Omics for Precision Medicine program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 studies per phenotype (participants recruited 1948-2012). We discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.

%B Am J Epidemiol %8 2021 Apr 16 %G eng %R 10.1093/aje/kwab115 %0 Journal Article %J EBioMedicine %D 2021 %T Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium. %A Lin, Bridget M %A Grinde, Kelsey E %A Brody, Jennifer A %A Breeze, Charles E %A Raffield, Laura M %A Mychaleckyj, Josyf C %A Thornton, Timothy A %A Perry, James A %A Baier, Leslie J %A de Las Fuentes, Lisa %A Guo, Xiuqing %A Heavner, Benjamin D %A Hanson, Robert L %A Hung, Yi-Jen %A Qian, Huijun %A Hsiung, Chao A %A Hwang, Shih-Jen %A Irvin, Margaret R %A Jain, Deepti %A Kelly, Tanika N %A Kobes, Sayuko %A Lange, Leslie %A Lash, James P %A Li, Yun %A Liu, Xiaoming %A Mi, Xuenan %A Musani, Solomon K %A Papanicolaou, George J %A Parsa, Afshin %A Reiner, Alex P %A Salimi, Shabnam %A Sheu, Wayne H-H %A Shuldiner, Alan R %A Taylor, Kent D %A Smith, Albert V %A Smith, Jennifer A %A Tin, Adrienne %A Vaidya, Dhananjay %A Wallace, Robert B %A Yamamoto, Kenichi %A Sakaue, Saori %A Matsuda, Koichi %A Kamatani, Yoichiro %A Momozawa, Yukihide %A Yanek, Lisa R %A Young, Betsi A %A Zhao, Wei %A Okada, Yukinori %A Abecasis, Gonzalo %A Psaty, Bruce M %A Arnett, Donna K %A Boerwinkle, Eric %A Cai, Jianwen %A Yii-Der Chen, Ida %A Correa, Adolfo %A Cupples, L Adrienne %A He, Jiang %A Kardia, Sharon Lr %A Kooperberg, Charles %A Mathias, Rasika A %A Mitchell, Braxton D %A Nickerson, Deborah A %A Turner, Steve T %A Vasan, Ramachandran S %A Rotter, Jerome I %A Levy, Daniel %A Kramer, Holly J %A Köttgen, Anna %A Rich, Stephen S %A Lin, Dan-Yu %A Browning, Sharon R %A Franceschini, Nora %X

BACKGROUND: Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.

METHODS: We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity.

FINDINGS: When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants.

INTERPRETATION: This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.

%B EBioMedicine %V 63 %P 103157 %8 2021 Jan %G eng %R 10.1016/j.ebiom.2020.103157 %0 Journal Article %J Hum Mol Genet %D 2021 %T Whole genome sequence analysis of platelet traits in the NHLBI trans-omics for precision medicine initiative. %A Little, Amarise %A Hu, Yao %A Sun, Quan %A Jain, Deepti %A Broome, Jai %A Chen, Ming-Huei %A Thibord, Florian %A McHugh, Caitlin %A Surendran, Praveen %A Blackwell, Thomas W %A Brody, Jennifer A %A Bhan, Arunoday %A Chami, Nathalie %A Vries, Paul S %A Ekunwe, Lynette %A Heard-Costa, Nancy %A Hobbs, Brian D %A Manichaikul, Ani %A Moon, Jee-Young %A Preuss, Michael H %A Ryan, Kathleen %A Wang, Zhe %A Wheeler, Marsha %A Yanek, Lisa R %A Abecasis, Goncalo R %A Almasy, Laura %A Beaty, Terri H %A Becker, Lewis C %A Blangero, John %A Boerwinkle, Eric %A Butterworth, Adam S %A Choquet, Helene %A Correa, Adolfo %A Curran, Joanne E %A Faraday, Nauder %A Fornage, Myriam %A Glahn, David C %A Hou, Lifang %A Jorgenson, Eric %A Kooperberg, Charles %A Lewis, Joshua P %A Lloyd-Jones, Donald M %A Loos, Ruth J F %A Min, Nancy %A Mitchell, Braxton D %A Morrison, Alanna C %A Nickerson, Debbie %A North, Kari E %A O'Connell, Jeffrey R %A Pankratz, Nathan %A Psaty, Bruce M %A Vasan, Ramachandran S %A Rich, Stephen S %A Rotter, Jerome I %A Smith, Albert V %A Smith, Nicholas L %A Tang, Hua %A Tracy, Russell P %A Conomos, Matthew P %A Laurie, Cecelia A %A Mathias, Rasika A %A Li, Yun %A Auer, Paul L %A Thornton, Timothy %A Reiner, Alexander P %A Johnson, Andrew D %A Raffield, Laura M %X

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing from NHLBI's Trans-Omics for Precision Medicine Initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several GWAS identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of whole genome sequencing in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.

%B Hum Mol Genet %8 2021 Sep 06 %G eng %R 10.1093/hmg/ddab252 %0 Journal Article %J Genome Med %D 2021 %T Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program. %A Cade, Brian E %A Lee, Jiwon %A Sofer, Tamar %A Wang, Heming %A Zhang, Man %A Chen, Han %A Gharib, Sina A %A Gottlieb, Daniel J %A Guo, Xiuqing %A Lane, Jacqueline M %A Liang, Jingjing %A Lin, Xihong %A Mei, Hao %A Patel, Sanjay R %A Purcell, Shaun M %A Saxena, Richa %A Shah, Neomi A %A Evans, Daniel S %A Hanis, Craig L %A Hillman, David R %A Mukherjee, Sutapa %A Palmer, Lyle J %A Stone, Katie L %A Tranah, Gregory J %A Abecasis, Goncalo R %A Boerwinkle, Eric A %A Correa, Adolfo %A Cupples, L Adrienne %A Kaplan, Robert C %A Nickerson, Deborah A %A North, Kari E %A Psaty, Bruce M %A Rotter, Jerome I %A Rich, Stephen S %A Tracy, Russell P %A Vasan, Ramachandran S %A Wilson, James G %A Zhu, Xiaofeng %A Redline, Susan %X

BACKGROUND: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.

METHODS: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.

RESULTS: We identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.

CONCLUSIONS: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.

%B Genome Med %V 13 %P 136 %8 2021 08 26 %G eng %N 1 %R 10.1186/s13073-021-00917-8 %0 Journal Article %J Am J Hum Genet %D 2021 %T Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program. %A Hu, Yao %A Stilp, Adrienne M %A McHugh, Caitlin P %A Rao, Shuquan %A Jain, Deepti %A Zheng, Xiuwen %A Lane, John %A Méric de Bellefon, Sébastian %A Raffield, Laura M %A Chen, Ming-Huei %A Yanek, Lisa R %A Wheeler, Marsha %A Yao, Yao %A Ren, Chunyan %A Broome, Jai %A Moon, Jee-Young %A de Vries, Paul S %A Hobbs, Brian D %A Sun, Quan %A Surendran, Praveen %A Brody, Jennifer A %A Blackwell, Thomas W %A Choquet, Helene %A Ryan, Kathleen %A Duggirala, Ravindranath %A Heard-Costa, Nancy %A Wang, Zhe %A Chami, Nathalie %A Preuss, Michael H %A Min, Nancy %A Ekunwe, Lynette %A Lange, Leslie A %A Cushman, Mary %A Faraday, Nauder %A Curran, Joanne E %A Almasy, Laura %A Kundu, Kousik %A Smith, Albert V %A Gabriel, Stacey %A Rotter, Jerome I %A Fornage, Myriam %A Lloyd-Jones, Donald M %A Vasan, Ramachandran S %A Smith, Nicholas L %A North, Kari E %A Boerwinkle, Eric %A Becker, Lewis C %A Lewis, Joshua P %A Abecasis, Goncalo R %A Hou, Lifang %A O'Connell, Jeffrey R %A Morrison, Alanna C %A Beaty, Terri H %A Kaplan, Robert %A Correa, Adolfo %A Blangero, John %A Jorgenson, Eric %A Psaty, Bruce M %A Kooperberg, Charles %A Walton, Russell T %A Kleinstiver, Benjamin P %A Tang, Hua %A Loos, Ruth J F %A Soranzo, Nicole %A Butterworth, Adam S %A Nickerson, Debbie %A Rich, Stephen S %A Mitchell, Braxton D %A Johnson, Andrew D %A Auer, Paul L %A Li, Yun %A Mathias, Rasika A %A Lettre, Guillaume %A Pankratz, Nathan %A Laurie, Cathy C %A Laurie, Cecelia A %A Bauer, Daniel E %A Conomos, Matthew P %A Reiner, Alexander P %K Adult %K Aged %K Chromosomes, Human, Pair 16 %K Datasets as Topic %K Erythrocytes %K Female %K Gene Editing %K Genetic Variation %K Genome-Wide Association Study %K HEK293 Cells %K Humans %K Male %K Middle Aged %K National Heart, Lung, and Blood Institute (U.S.) %K Phenotype %K Quality Control %K Reproducibility of Results %K United States %X

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

%B Am J Hum Genet %V 108 %P 874-893 %8 2021 05 06 %G eng %N 5 %R 10.1016/j.ajhg.2021.04.003 %0 Journal Article %J Am J Hum Genet %D 2021 %T Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program. %A Mikhaylova, Anna V %A McHugh, Caitlin P %A Polfus, Linda M %A Raffield, Laura M %A Boorgula, Meher Preethi %A Blackwell, Thomas W %A Brody, Jennifer A %A Broome, Jai %A Chami, Nathalie %A Chen, Ming-Huei %A Conomos, Matthew P %A Cox, Corey %A Curran, Joanne E %A Daya, Michelle %A Ekunwe, Lynette %A Glahn, David C %A Heard-Costa, Nancy %A Highland, Heather M %A Hobbs, Brian D %A Ilboudo, Yann %A Jain, Deepti %A Lange, Leslie A %A Miller-Fleming, Tyne W %A Min, Nancy %A Moon, Jee-Young %A Preuss, Michael H %A Rosen, Jonathon %A Ryan, Kathleen %A Smith, Albert V %A Sun, Quan %A Surendran, Praveen %A de Vries, Paul S %A Walter, Klaudia %A Wang, Zhe %A Wheeler, Marsha %A Yanek, Lisa R %A Zhong, Xue %A Abecasis, Goncalo R %A Almasy, Laura %A Barnes, Kathleen C %A Beaty, Terri H %A Becker, Lewis C %A Blangero, John %A Boerwinkle, Eric %A Butterworth, Adam S %A Chavan, Sameer %A Cho, Michael H %A Choquet, Helene %A Correa, Adolfo %A Cox, Nancy %A DeMeo, Dawn L %A Faraday, Nauder %A Fornage, Myriam %A Gerszten, Robert E %A Hou, Lifang %A Johnson, Andrew D %A Jorgenson, Eric %A Kaplan, Robert %A Kooperberg, Charles %A Kundu, Kousik %A Laurie, Cecelia A %A Lettre, Guillaume %A Lewis, Joshua P %A Li, Bingshan %A Li, Yun %A Lloyd-Jones, Donald M %A Loos, Ruth J F %A Manichaikul, Ani %A Meyers, Deborah A %A Mitchell, Braxton D %A Morrison, Alanna C %A Ngo, Debby %A Nickerson, Deborah A %A Nongmaithem, Suraj %A North, Kari E %A O'Connell, Jeffrey R %A Ortega, Victor E %A Pankratz, Nathan %A Perry, James A %A Psaty, Bruce M %A Rich, Stephen S %A Soranzo, Nicole %A Rotter, Jerome I %A Silverman, Edwin K %A Smith, Nicholas L %A Tang, Hua %A Tracy, Russell P %A Thornton, Timothy A %A Vasan, Ramachandran S %A Zein, Joe %A Mathias, Rasika A %A Reiner, Alexander P %A Auer, Paul L %K Asthma %K Biomarkers %K Dermatitis, Atopic %K Genetic Predisposition to Disease %K Genome, Human %K Genome-Wide Association Study %K Humans %K Leukocytes %K National Heart, Lung, and Blood Institute (U.S.) %K Phenotype %K Polymorphism, Single Nucleotide %K Prognosis %K Proteome %K Pulmonary Disease, Chronic Obstructive %K Quantitative Trait Loci %K United Kingdom %K United States %K Whole Genome Sequencing %X

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

%B Am J Hum Genet %V 108 %P 1836-1851 %8 2021 10 07 %G eng %N 10 %R 10.1016/j.ajhg.2021.08.007 %0 Journal Article %J Nat Genet %D 2022 %T Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data. %A Wainschtein, Pierrick %A Jain, Deepti %A Zheng, Zhili %A Cupples, L Adrienne %A Shadyab, Aladdin H %A McKnight, Barbara %A Shoemaker, Benjamin M %A Mitchell, Braxton D %A Psaty, Bruce M %A Kooperberg, Charles %A Liu, Ching-Ti %A Albert, Christine M %A Roden, Dan %A Chasman, Daniel I %A Darbar, Dawood %A Lloyd-Jones, Donald M %A Arnett, Donna K %A Regan, Elizabeth A %A Boerwinkle, Eric %A Rotter, Jerome I %A O'Connell, Jeffrey R %A Yanek, Lisa R %A de Andrade, Mariza %A Allison, Matthew A %A McDonald, Merry-Lynn N %A Chung, Mina K %A Fornage, Myriam %A Chami, Nathalie %A Smith, Nicholas L %A Ellinor, Patrick T %A Vasan, Ramachandran S %A Mathias, Rasika A %A Loos, Ruth J F %A Rich, Stephen S %A Lubitz, Steven A %A Heckbert, Susan R %A Redline, Susan %A Guo, Xiuqing %A Chen, Y -D Ida %A Laurie, Cecelia A %A Hernandez, Ryan D %A McGarvey, Stephen T %A Goddard, Michael E %A Laurie, Cathy C %A North, Kari E %A Lange, Leslie A %A Weir, Bruce S %A Yengo, Loic %A Yang, Jian %A Visscher, Peter M %X

Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.

%B Nat Genet %V 54 %P 263-273 %8 2022 Mar %G eng %N 3 %R 10.1038/s41588-021-00997-7 %0 Journal Article %J Stroke %D 2022 %T Clonal Hematopoiesis Is Associated With Higher Risk of Stroke. %A Bhattacharya, Romit %A Zekavat, Seyedeh M %A Haessler, Jeffrey %A Fornage, Myriam %A Raffield, Laura %A Uddin, Md Mesbah %A Bick, Alexander G %A Niroula, Abhishek %A Yu, Bing %A Gibson, Christopher %A Griffin, Gabriel %A Morrison, Alanna C %A Psaty, Bruce M %A Longstreth, William T %A Bis, Joshua C %A Rich, Stephen S %A Rotter, Jerome I %A Tracy, Russell P %A Correa, Adolfo %A Seshadri, Sudha %A Johnson, Andrew %A Collins, Jason M %A Hayden, Kathleen M %A Madsen, Tracy E %A Ballantyne, Christie M %A Jaiswal, Siddhartha %A Ebert, Benjamin L %A Kooperberg, Charles %A Manson, JoAnn E %A Whitsel, Eric A %A Natarajan, Pradeep %A Reiner, Alexander P %X

BACKGROUND AND PURPOSE: Clonal hematopoiesis of indeterminate potential (CHIP) is a novel age-related risk factor for cardiovascular disease-related morbidity and mortality. The association of CHIP with risk of incident ischemic stroke was reported previously in an exploratory analysis including a small number of incident stroke cases without replication and lack of stroke subphenotyping. The purpose of this study was to discover whether CHIP is a risk factor for ischemic or hemorrhagic stroke.

METHODS: We utilized plasma genome sequence data of blood DNA to identify CHIP in 78 752 individuals from 8 prospective cohorts and biobanks. We then assessed the association of CHIP and commonly mutated individual CHIP driver genes (, , and ) with any stroke, ischemic stroke, and hemorrhagic stroke.

RESULTS: CHIP was associated with an increased risk of total stroke (hazard ratio, 1.14 [95% CI, 1.03-1.27]; =0.01) after adjustment for age, sex, and race. We observed associations with CHIP with risk of hemorrhagic stroke (hazard ratio, 1.24 [95% CI, 1.01-1.51]; =0.04) and with small vessel ischemic stroke subtypes. In gene-specific association results, showed the strongest association with total stroke and ischemic stroke, whereas and were each associated with increased risk of hemorrhagic stroke.

CONCLUSIONS: CHIP is associated with an increased risk of stroke, particularly with hemorrhagic and small vessel ischemic stroke. Future studies clarifying the relationship between CHIP and subtypes of stroke are needed.

%B Stroke %V 53 %P 788-797 %8 2022 Mar %G eng %N 3 %R 10.1161/STROKEAHA.121.037388 %0 Journal Article %J Cell Rep Med %D 2022 %T Correlations between complex human phenotypes vary by genetic background, gender, and environment. %A Elgart, Michael %A Goodman, Matthew O %A Isasi, Carmen %A Chen, Han %A Morrison, Alanna C %A de Vries, Paul S %A Xu, Huichun %A Manichaikul, Ani W %A Guo, Xiuqing %A Franceschini, Nora %A Psaty, Bruce M %A Rich, Stephen S %A Rotter, Jerome I %A Lloyd-Jones, Donald M %A Fornage, Myriam %A Correa, Adolfo %A Heard-Costa, Nancy L %A Vasan, Ramachandran S %A Hernandez, Ryan %A Kaplan, Robert C %A Redline, Susan %A Sofer, Tamar %K Female %K Genetic Background %K Humans %K Male %K Phenotype %X

We develop a closed-form Haseman-Elston estimator for genetic and environmental correlation coefficients between complex phenotypes, which we term HEc, that is as precise as GCTA yet ∼20× faster. We estimate genetic and environmental correlations between over 7,000 phenotype pairs in subgroups from the Trans-Omics in Precision Medicine (TOPMed) program. We demonstrate substantial differences in both heritabilities and genetic correlations for multiple phenotypes and phenotype pairs between individuals of self-reported Black, Hispanic/Latino, and White backgrounds. We similarly observe differences in many of the genetic and environmental correlations between genders. To estimate the contribution of genetics to the observed phenotypic correlation, we introduce "fractional genetic correlation" as the fraction of phenotypic correlation explained by genetics. Finally, we quantify the enrichment of correlations between phenotypic domains, each of which is comprised of multiple phenotypes. Altogether, we demonstrate that the observed correlations between complex human phenotypes depend on the genetic background of the individuals, their gender, and their environment.

%B Cell Rep Med %V 3 %P 100844 %8 2022 Dec 20 %G eng %N 12 %R 10.1016/j.xcrm.2022.100844 %0 Journal Article %J Circulation %D 2022 %T Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors. %A Thibord, Florian %A Klarin, Derek %A Brody, Jennifer A %A Chen, Ming-Huei %A Levin, Michael G %A Chasman, Daniel I %A Goode, Ellen L %A Hveem, Kristian %A Teder-Laving, Maris %A Martinez-Perez, Angel %A Aïssi, Dylan %A Daian-Bacq, Delphine %A Ito, Kaoru %A Natarajan, Pradeep %A Lutsey, Pamela L %A Nadkarni, Girish N %A de Vries, Paul S %A Cuellar-Partida, Gabriel %A Wolford, Brooke N %A Pattee, Jack W %A Kooperberg, Charles %A Braekkan, Sigrid K %A Li-Gao, Ruifang %A Saut, Noémie %A Sept, Corriene %A Germain, Marine %A Judy, Renae L %A Wiggins, Kerri L %A Ko, Darae %A O'Donnell, Christopher J %A Taylor, Kent D %A Giulianini, Franco %A de Andrade, Mariza %A Nøst, Therese H %A Boland, Anne %A Empana, Jean-Philippe %A Koyama, Satoshi %A Gilliland, Thomas %A Do, Ron %A Huffman, Jennifer E %A Wang, Xin %A Zhou, Wei %A Manuel Soria, Jose %A Carlos Souto, Juan %A Pankratz, Nathan %A Haessler, Jeffery %A Hindberg, Kristian %A Rosendaal, Frits R %A Turman, Constance %A Olaso, Robert %A Kember, Rachel L %A Bartz, Traci M %A Lynch, Julie A %A Heckbert, Susan R %A Armasu, Sebastian M %A Brumpton, Ben %A Smadja, David M %A Jouven, Xavier %A Komuro, Issei %A Clapham, Katharine R %A Loos, Ruth J F %A Willer, Cristen J %A Sabater-Lleal, Maria %A Pankow, James S %A Reiner, Alexander P %A Morelli, Vania M %A Ridker, Paul M %A Vlieg, Astrid van Hylckama %A Deleuze, Jean-Francois %A Kraft, Peter %A Rader, Daniel J %A Min Lee, Kyung %A Psaty, Bruce M %A Heidi Skogholt, Anne %A Emmerich, Joseph %A Suchon, Pierre %A Rich, Stephen S %A Vy, Ha My T %A Tang, Weihong %A Jackson, Rebecca D %A Hansen, John-Bjarne %A Morange, Pierre-Emmanuel %A Kabrhel, Christopher %A Trégouët, David-Alexandre %A Damrauer, Scott M %A Johnson, Andrew D %A Smith, Nicholas L %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genomics %K Humans %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Thrombosis %K Venous Thromboembolism %X

BACKGROUND: Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources.

METHODS: We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations.

RESULTS: In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis.

CONCLUSIONS: Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.

%B Circulation %V 146 %P 1225-1242 %8 2022 Oct 18 %G eng %N 16 %R 10.1161/CIRCULATIONAHA.122.059675 %0 Journal Article %J Nat Commun %D 2022 %T Endophenotype effect sizes support variant pathogenicity in monogenic disease susceptibility genes. %A Halford, Jennifer L %A Morrill, Valerie N %A Choi, Seung Hoan %A Jurgens, Sean J %A Melloni, Giorgio %A Marston, Nicholas A %A Weng, Lu-Chen %A Nauffal, Victor %A Hall, Amelia W %A Gunn, Sophia %A Austin-Tse, Christina A %A Pirruccello, James P %A Khurshid, Shaan %A Rehm, Heidi L %A Benjamin, Emelia J %A Boerwinkle, Eric %A Brody, Jennifer A %A Correa, Adolfo %A Fornwalt, Brandon K %A Gupta, Namrata %A Haggerty, Christopher M %A Harris, Stephanie %A Heckbert, Susan R %A Hong, Charles C %A Kooperberg, Charles %A Lin, Henry J %A Loos, Ruth J F %A Mitchell, Braxton D %A Morrison, Alanna C %A Post, Wendy %A Psaty, Bruce M %A Redline, Susan %A Rice, Kenneth M %A Rich, Stephen S %A Rotter, Jerome I %A Schnatz, Peter F %A Soliman, Elsayed Z %A Sotoodehnia, Nona %A Wong, Eugene K %A Sabatine, Marc S %A Ruff, Christian T %A Lunetta, Kathryn L %A Ellinor, Patrick T %A Lubitz, Steven A %K Disease Susceptibility %K Endophenotypes %K Humans %K Long QT Syndrome %K Virulence %X

Accurate and efficient classification of variant pathogenicity is critical for research and clinical care. Using data from three large studies, we demonstrate that population-based associations between rare variants and quantitative endophenotypes for three monogenic diseases (low-density-lipoprotein cholesterol for familial hypercholesterolemia, electrocardiographic QTc interval for long QT syndrome, and glycosylated hemoglobin for maturity-onset diabetes of the young) provide evidence for variant pathogenicity. Effect sizes are associated with pathogenic ClinVar assertions (P < 0.001 for each trait) and discriminate pathogenic from non-pathogenic variants (area under the curve 0.82-0.84 across endophenotypes). An effect size threshold of ≥ 0.5 times the endophenotype standard deviation nominates up to 35% of rare variants of uncertain significance or not in ClinVar in disease susceptibility genes with pathogenic potential. We propose that variant associations with quantitative endophenotypes for monogenic diseases can provide evidence supporting pathogenicity.

%B Nat Commun %V 13 %P 5106 %8 2022 08 30 %G eng %N 1 %R 10.1038/s41467-022-32009-5 %0 Journal Article %J Nat Methods %D 2022 %T A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies. %A Li, Zilin %A Li, Xihao %A Zhou, Hufeng %A Gaynor, Sheila M %A Selvaraj, Margaret Sunitha %A Arapoglou, Theodore %A Quick, Corbin %A Liu, Yaowu %A Chen, Han %A Sun, Ryan %A Dey, Rounak %A Arnett, Donna K %A Auer, Paul L %A Bielak, Lawrence F %A Bis, Joshua C %A Blackwell, Thomas W %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Conomos, Matthew P %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A de Vries, Paul S %A Duggirala, Ravindranath %A Franceschini, Nora %A Freedman, Barry I %A Göring, Harald H H %A Guo, Xiuqing %A Kalyani, Rita R %A Kooperberg, Charles %A Kral, Brian G %A Lange, Leslie A %A Lin, Bridget M %A Manichaikul, Ani %A Manning, Alisa K %A Martin, Lisa W %A Mathias, Rasika A %A Meigs, James B %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peyser, Patricia A %A Psaty, Bruce M %A Raffield, Laura M %A Redline, Susan %A Reiner, Alexander P %A Reupena, Muagututi'a Sefuiva %A Rice, Kenneth M %A Rich, Stephen S %A Smith, Jennifer A %A Taylor, Kent D %A Taub, Margaret A %A Vasan, Ramachandran S %A Weeks, Daniel E %A Wilson, James G %A Yanek, Lisa R %A Zhao, Wei %A Rotter, Jerome I %A Willer, Cristen J %A Natarajan, Pradeep %A Peloso, Gina M %A Lin, Xihong %K Genetic Variation %K Genome %K Genome-Wide Association Study %K Humans %K Phenotype %K Whole Genome Sequencing %X

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

%B Nat Methods %V 19 %P 1599-1611 %8 2022 Dec %G eng %N 12 %R 10.1038/s41592-022-01640-x %0 Journal Article %J Hypertension %D 2022 %T Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. %A Kelly, Tanika N %A Sun, Xiao %A He, Karen Y %A Brown, Michael R %A Taliun, Sarah A Gagliano %A Hellwege, Jacklyn N %A Irvin, Marguerite R %A Mi, Xuenan %A Brody, Jennifer A %A Franceschini, Nora %A Guo, Xiuqing %A Hwang, Shih-Jen %A de Vries, Paul S %A Gao, Yan %A Moscati, Arden %A Nadkarni, Girish N %A Yanek, Lisa R %A Elfassy, Tali %A Smith, Jennifer A %A Chung, Ren-Hua %A Beitelshees, Amber L %A Patki, Amit %A Aslibekyan, Stella %A Blobner, Brandon M %A Peralta, Juan M %A Assimes, Themistocles L %A Palmas, Walter R %A Liu, Chunyu %A Bress, Adam P %A Huang, Zhijie %A Becker, Lewis C %A Hwa, Chii-Min %A O'Connell, Jeffrey R %A Carlson, Jenna C %A Warren, Helen R %A Das, Sayantan %A Giri, Ayush %A Martin, Lisa W %A Craig Johnson, W %A Fox, Ervin R %A Bottinger, Erwin P %A Razavi, Alexander C %A Vaidya, Dhananjay %A Chuang, Lee-Ming %A Chang, Yen-Pei C %A Naseri, Take %A Jain, Deepti %A Kang, Hyun Min %A Hung, Adriana M %A Srinivasasainagendra, Vinodh %A Snively, Beverly M %A Gu, Dongfeng %A Montasser, May E %A Reupena, Muagututi'a Sefuiva %A Heavner, Benjamin D %A LeFaive, Jonathon %A Hixson, James E %A Rice, Kenneth M %A Wang, Fei Fei %A Nielsen, Jonas B %A Huang, Jianfeng %A Khan, Alyna T %A Zhou, Wei %A Nierenberg, Jovia L %A Laurie, Cathy C %A Armstrong, Nicole D %A Shi, Mengyao %A Pan, Yang %A Stilp, Adrienne M %A Emery, Leslie %A Wong, Quenna %A Hawley, Nicola L %A Minster, Ryan L %A Curran, Joanne E %A Munroe, Patricia B %A Weeks, Daniel E %A North, Kari E %A Tracy, Russell P %A Kenny, Eimear E %A Shimbo, Daichi %A Chakravarti, Aravinda %A Rich, Stephen S %A Reiner, Alex P %A Blangero, John %A Redline, Susan %A Mitchell, Braxton D %A Rao, Dabeeru C %A Ida Chen, Yii-Der %A Kardia, Sharon L R %A Kaplan, Robert C %A Mathias, Rasika A %A He, Jiang %A Psaty, Bruce M %A Fornage, Myriam %A Loos, Ruth J F %A Correa, Adolfo %A Boerwinkle, Eric %A Rotter, Jerome I %A Kooperberg, Charles %A Edwards, Todd L %A Abecasis, Goncalo R %A Zhu, Xiaofeng %A Levy, Daniel %A Arnett, Donna K %A Morrison, Alanna C %X

BACKGROUND: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure.

METHODS: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants.

RESULTS: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (<5×10). Among them, a rare intergenic variant at novel locus, , was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; =4.99×10) but not stage-2 analysis (=0.11). Furthermore, a novel common variant at the known locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; =4.18×10) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; =7.28×10). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (<1×10 and <1×10, respectively).

DISCUSSION: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.

%B Hypertension %P 101161HYPERTENSIONAHA12219324 %8 2022 Jun 02 %G eng %R 10.1161/HYPERTENSIONAHA.122.19324 %0 Journal Article %J Circulation %D 2022 %T Monogenic and Polygenic Contributions to QTc Prolongation in the Population. %A Nauffal, Victor %A Morrill, Valerie N %A Jurgens, Sean J %A Choi, Seung Hoan %A Hall, Amelia W %A Weng, Lu-Chen %A Halford, Jennifer L %A Austin-Tse, Christina %A Haggerty, Christopher M %A Harris, Stephanie L %A Wong, Eugene K %A Alonso, Alvaro %A Arking, Dan E %A Benjamin, Emelia J %A Boerwinkle, Eric %A Min, Yuan-I %A Correa, Adolfo %A Fornwalt, Brandon K %A Heckbert, Susan R %A Kooperberg, Charles %A Lin, Henry J %A Loos, Ruth J F %A Rice, Kenneth M %A Gupta, Namrata %A Blackwell, Thomas W %A Mitchell, Braxton D %A Morrison, Alanna C %A Psaty, Bruce M %A Post, Wendy S %A Redline, Susan %A Rehm, Heidi L %A Rich, Stephen S %A Rotter, Jerome I %A Soliman, Elsayed Z %A Sotoodehnia, Nona %A Lunetta, Kathryn L %A Ellinor, Patrick T %A Lubitz, Steven A %X

Rare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variation to the QT interval in the population. We performed a genome wide association study (GWAS) of the QTc in 84,630 United Kingdom Biobank (UKB) participants and created a polygenic risk score (PRS). Among 26,976 participants with whole genome sequencing and electrocardiogram data in the Trans-Omics for Precision Medicine (TOPMed) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed. Fifty-four independent loci were identified by GWAS in the UKB. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS comprising 1,110,494 common variants was significantly associated with the QTc in TOPMed (ΔQTc/ = 1.4 ms, 95% CI 1.3 -1.5; p-value=1.1×10). Carriers of putative pathogenic rare variants had longer QTc than non-carriers (ΔQTc=10.9 ms [7.4-14.4]). 23.7% of individuals with QTc>480 ms carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS). QTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.

%B Circulation %8 2022 Apr 07 %G eng %R 10.1161/CIRCULATIONAHA.121.057261 %0 Journal Article %J Nat Genet %D 2022 %T Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. %A Mahajan, Anubha %A Spracklen, Cassandra N %A Zhang, Weihua %A Ng, Maggie C Y %A Petty, Lauren E %A Kitajima, Hidetoshi %A Yu, Grace Z %A Rüeger, Sina %A Speidel, Leo %A Kim, Young Jin %A Horikoshi, Momoko %A Mercader, Josep M %A Taliun, Daniel %A Moon, Sanghoon %A Kwak, Soo-Heon %A Robertson, Neil R %A Rayner, Nigel W %A Loh, Marie %A Kim, Bong-Jo %A Chiou, Joshua %A Miguel-Escalada, Irene %A Della Briotta Parolo, Pietro %A Lin, Kuang %A Bragg, Fiona %A Preuss, Michael H %A Takeuchi, Fumihiko %A Nano, Jana %A Guo, Xiuqing %A Lamri, Amel %A Nakatochi, Masahiro %A Scott, Robert A %A Lee, Jung-Jin %A Huerta-Chagoya, Alicia %A Graff, Mariaelisa %A Chai, Jin-Fang %A Parra, Esteban J %A Yao, Jie %A Bielak, Lawrence F %A Tabara, Yasuharu %A Hai, Yang %A Steinthorsdottir, Valgerdur %A Cook, James P %A Kals, Mart %A Grarup, Niels %A Schmidt, Ellen M %A Pan, Ian %A Sofer, Tamar %A Wuttke, Matthias %A Sarnowski, Chloe %A Gieger, Christian %A Nousome, Darryl %A Trompet, Stella %A Long, Jirong %A Sun, Meng %A Tong, Lin %A Chen, Wei-Min %A Ahmad, Meraj %A Noordam, Raymond %A Lim, Victor J Y %A Tam, Claudia H T %A Joo, Yoonjung Yoonie %A Chen, Chien-Hsiun %A Raffield, Laura M %A Lecoeur, Cécile %A Prins, Bram Peter %A Nicolas, Aude %A Yanek, Lisa R %A Chen, Guanjie %A Jensen, Richard A %A Tajuddin, Salman %A Kabagambe, Edmond K %A An, Ping %A Xiang, Anny H %A Choi, Hyeok Sun %A Cade, Brian E %A Tan, Jingyi %A Flanagan, Jack %A Abaitua, Fernando %A Adair, Linda S %A Adeyemo, Adebowale %A Aguilar-Salinas, Carlos A %A Akiyama, Masato %A Anand, Sonia S %A Bertoni, Alain %A Bian, Zheng %A Bork-Jensen, Jette %A Brandslund, Ivan %A Brody, Jennifer A %A Brummett, Chad M %A Buchanan, Thomas A %A Canouil, Mickaël %A Chan, Juliana C N %A Chang, Li-Ching %A Chee, Miao-Li %A Chen, Ji %A Chen, Shyh-Huei %A Chen, Yuan-Tsong %A Chen, Zhengming %A Chuang, Lee-Ming %A Cushman, Mary %A Das, Swapan K %A de Silva, H Janaka %A Dedoussis, George %A Dimitrov, Latchezar %A Doumatey, Ayo P %A Du, Shufa %A Duan, Qing %A Eckardt, Kai-Uwe %A Emery, Leslie S %A Evans, Daniel S %A Evans, Michele K %A Fischer, Krista %A Floyd, James S %A Ford, Ian %A Fornage, Myriam %A Franco, Oscar H %A Frayling, Timothy M %A Freedman, Barry I %A Fuchsberger, Christian %A Genter, Pauline %A Gerstein, Hertzel C %A Giedraitis, Vilmantas %A González-Villalpando, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Goodarzi, Mark O %A Gordon-Larsen, Penny %A Gorkin, David %A Gross, Myron %A Guo, Yu %A Hackinger, Sophie %A Han, Sohee %A Hattersley, Andrew T %A Herder, Christian %A Howard, Annie-Green %A Hsueh, Willa %A Huang, Mengna %A Huang, Wei %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Hwu, Chii-Min %A Ichihara, Sahoko %A Ikram, Mohammad Arfan %A Ingelsson, Martin %A Islam, Md Tariqul %A Isono, Masato %A Jang, Hye-Mi %A Jasmine, Farzana %A Jiang, Guozhi %A Jonas, Jost B %A Jørgensen, Marit E %A Jørgensen, Torben %A Kamatani, Yoichiro %A Kandeel, Fouad R %A Kasturiratne, Anuradhani %A Katsuya, Tomohiro %A Kaur, Varinderpal %A Kawaguchi, Takahisa %A Keaton, Jacob M %A Kho, Abel N %A Khor, Chiea-Chuen %A Kibriya, Muhammad G %A Kim, Duk-Hwan %A Kohara, Katsuhiko %A Kriebel, Jennifer %A Kronenberg, Florian %A Kuusisto, Johanna %A Läll, Kristi %A Lange, Leslie A %A Lee, Myung-Shik %A Lee, Nanette R %A Leong, Aaron %A Li, Liming %A Li, Yun %A Li-Gao, Ruifang %A Ligthart, Symen %A Lindgren, Cecilia M %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Locke, Adam E %A Louie, Tin %A Luan, Jian'an %A Luk, Andrea O %A Luo, Xi %A Lv, Jun %A Lyssenko, Valeriya %A Mamakou, Vasiliki %A Mani, K Radha %A Meitinger, Thomas %A Metspalu, Andres %A Morris, Andrew D %A Nadkarni, Girish N %A Nadler, Jerry L %A Nalls, Michael A %A Nayak, Uma %A Nongmaithem, Suraj S %A Ntalla, Ioanna %A Okada, Yukinori %A Orozco, Lorena %A Patel, Sanjay R %A Pereira, Mark A %A Peters, Annette %A Pirie, Fraser J %A Porneala, Bianca %A Prasad, Gauri %A Preissl, Sebastian %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Roden, Michael %A Rohde, Rebecca %A Roll, Kathryn %A Sabanayagam, Charumathi %A Sander, Maike %A Sandow, Kevin %A Sattar, Naveed %A Schönherr, Sebastian %A Schurmann, Claudia %A Shahriar, Mohammad %A Shi, Jinxiu %A Shin, Dong Mun %A Shriner, Daniel %A Smith, Jennifer A %A So, Wing Yee %A Stančáková, Alena %A Stilp, Adrienne M %A Strauch, Konstantin %A Suzuki, Ken %A Takahashi, Atsushi %A Taylor, Kent D %A Thorand, Barbara %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Tomlinson, Brian %A Torres, Jason M %A Tsai, Fuu-Jen %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A Valladares-Salgado, Adan %A van Dam, Rob M %A van Klinken, Jan B %A Varma, Rohit %A Vujkovic, Marijana %A Wacher-Rodarte, Niels %A Wheeler, Eleanor %A Whitsel, Eric A %A Wickremasinghe, Ananda R %A van Dijk, Ko Willems %A Witte, Daniel R %A Yajnik, Chittaranjan S %A Yamamoto, Ken %A Yamauchi, Toshimasa %A Yengo, Loic %A Yoon, Kyungheon %A Yu, Canqing %A Yuan, Jian-Min %A Yusuf, Salim %A Zhang, Liang %A Zheng, Wei %A Raffel, Leslie J %A Igase, Michiya %A Ipp, Eli %A Redline, Susan %A Cho, Yoon Shin %A Lind, Lars %A Province, Michael A %A Hanis, Craig L %A Peyser, Patricia A %A Ingelsson, Erik %A Zonderman, Alan B %A Psaty, Bruce M %A Wang, Ya-Xing %A Rotimi, Charles N %A Becker, Diane M %A Matsuda, Fumihiko %A Liu, Yongmei %A Zeggini, Eleftheria %A Yokota, Mitsuhiro %A Rich, Stephen S %A Kooperberg, Charles %A Pankow, James S %A Engert, James C %A Chen, Yii-Der Ida %A Froguel, Philippe %A Wilson, James G %A Sheu, Wayne H H %A Kardia, Sharon L R %A Wu, Jer-Yuarn %A Hayes, M Geoffrey %A Ma, Ronald C W %A Wong, Tien-Yin %A Groop, Leif %A Mook-Kanamori, Dennis O %A Chandak, Giriraj R %A Collins, Francis S %A Bharadwaj, Dwaipayan %A Paré, Guillaume %A Sale, Michèle M %A Ahsan, Habibul %A Motala, Ayesha A %A Shu, Xiao-Ou %A Park, Kyong-Soo %A Jukema, J Wouter %A Cruz, Miguel %A McKean-Cowdin, Roberta %A Grallert, Harald %A Cheng, Ching-Yu %A Bottinger, Erwin P %A Dehghan, Abbas %A Tai, E-Shyong %A Dupuis, Josée %A Kato, Norihiro %A Laakso, Markku %A Köttgen, Anna %A Koh, Woon-Puay %A Palmer, Colin N A %A Liu, Simin %A Abecasis, Goncalo %A Kooner, Jaspal S %A Loos, Ruth J F %A North, Kari E %A Haiman, Christopher A %A Florez, Jose C %A Saleheen, Danish %A Hansen, Torben %A Pedersen, Oluf %A Mägi, Reedik %A Langenberg, Claudia %A Wareham, Nicholas J %A Maeda, Shiro %A Kadowaki, Takashi %A Lee, Juyoung %A Millwood, Iona Y %A Walters, Robin G %A Stefansson, Kari %A Myers, Simon R %A Ferrer, Jorge %A Gaulton, Kyle J %A Meigs, James B %A Mohlke, Karen L %A Gloyn, Anna L %A Bowden, Donald W %A Below, Jennifer E %A Chambers, John C %A Sim, Xueling %A Boehnke, Michael %A Rotter, Jerome I %A McCarthy, Mark I %A Morris, Andrew P %K Diabetes Mellitus, Type 2 %K Ethnicity %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Polymorphism, Single Nucleotide %K Risk Factors %X

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

%B Nat Genet %V 54 %P 560-572 %8 2022 May %G eng %N 5 %R 10.1038/s41588-022-01058-3 %0 Journal Article %J Nat Commun %D 2022 %T A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood. %A Kurniansyah, Nuzulul %A Goodman, Matthew O %A Kelly, Tanika N %A Elfassy, Tali %A Wiggins, Kerri L %A Bis, Joshua C %A Guo, Xiuqing %A Palmas, Walter %A Taylor, Kent D %A Lin, Henry J %A Haessler, Jeffrey %A Gao, Yan %A Shimbo, Daichi %A Smith, Jennifer A %A Yu, Bing %A Feofanova, Elena V %A Smit, Roelof A J %A Wang, Zhe %A Hwang, Shih-Jen %A Liu, Simin %A Wassertheil-Smoller, Sylvia %A Manson, JoAnn E %A Lloyd-Jones, Donald M %A Rich, Stephen S %A Loos, Ruth J F %A Redline, Susan %A Correa, Adolfo %A Kooperberg, Charles %A Fornage, Myriam %A Kaplan, Robert C %A Psaty, Bruce M %A Rotter, Jerome I %A Arnett, Donna K %A Morrison, Alanna C %A Franceschini, Nora %A Levy, Daniel %A Sofer, Tamar %K Adult %K Diabetes Mellitus, Type 2 %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Hypertension %K Multifactorial Inheritance %K Prevalence %K Risk Factors %X

In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.

%B Nat Commun %V 13 %P 3549 %8 2022 Jun 21 %G eng %N 1 %R 10.1038/s41467-022-31080-2 %0 Journal Article %J Commun Biol %D 2022 %T Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations. %A Elgart, Michael %A Lyons, Genevieve %A Romero-Brufau, Santiago %A Kurniansyah, Nuzulul %A Brody, Jennifer A %A Guo, Xiuqing %A Lin, Henry J %A Raffield, Laura %A Gao, Yan %A Chen, Han %A de Vries, Paul %A Lloyd-Jones, Donald M %A Lange, Leslie A %A Peloso, Gina M %A Fornage, Myriam %A Rotter, Jerome I %A Rich, Stephen S %A Morrison, Alanna C %A Psaty, Bruce M %A Levy, Daniel %A Redline, Susan %A Sofer, Tamar %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Machine Learning %K Multifactorial Inheritance %K Polymorphism, Single Nucleotide %X

Polygenic risk scores (PRS) are commonly used to quantify the inherited susceptibility for a trait, yet they fail to account for non-linear and interaction effects between single nucleotide polymorphisms (SNPs). We address this via a machine learning approach, validated in nine complex phenotypes in a multi-ancestry population. We use an ensemble method of SNP selection followed by gradient boosted trees (XGBoost) to allow for non-linearities and interaction effects. We compare our results to the standard, linear PRS model developed using PRSice, LDpred2, and lassosum2. Combining a PRS as a feature in an XGBoost model results in a relative increase in the percentage variance explained compared to the standard linear PRS model by 22% for height, 27% for HDL cholesterol, 43% for body mass index, 50% for sleep duration, 58% for systolic blood pressure, 64% for total cholesterol, 66% for triglycerides, 77% for LDL cholesterol, and 100% for diastolic blood pressure. Multi-ancestry trained models perform similarly to specific racial/ethnic group trained models and are consistently superior to the standard linear PRS models. This work demonstrates an effective method to account for non-linearities and interaction effects in genetics-based prediction models.

%B Commun Biol %V 5 %P 856 %8 2022 08 22 %G eng %N 1 %R 10.1038/s42003-022-03812-z %0 Journal Article %J Am J Hum Genet %D 2022 %T Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program. %A Hu, Xiaowei %A Qiao, Dandi %A Kim, Wonji %A Moll, Matthew %A Balte, Pallavi P %A Lange, Leslie A %A Bartz, Traci M %A Kumar, Rajesh %A Li, Xingnan %A Yu, Bing %A Cade, Brian E %A Laurie, Cecelia A %A Sofer, Tamar %A Ruczinski, Ingo %A Nickerson, Deborah A %A Muzny, Donna M %A Metcalf, Ginger A %A Doddapaneni, Harshavardhan %A Gabriel, Stacy %A Gupta, Namrata %A Dugan-Perez, Shannon %A Cupples, L Adrienne %A Loehr, Laura R %A Jain, Deepti %A Rotter, Jerome I %A Wilson, James G %A Psaty, Bruce M %A Fornage, Myriam %A Morrison, Alanna C %A Vasan, Ramachandran S %A Washko, George %A Rich, Stephen S %A O'Connor, George T %A Bleecker, Eugene %A Kaplan, Robert C %A Kalhan, Ravi %A Redline, Susan %A Gharib, Sina A %A Meyers, Deborah %A Ortega, Victor %A Dupuis, Josée %A London, Stephanie J %A Lappalainen, Tuuli %A Oelsner, Elizabeth C %A Silverman, Edwin K %A Barr, R Graham %A Thornton, Timothy A %A Wheeler, Heather E %A Cho, Michael H %A Im, Hae Kyung %A Manichaikul, Ani %X

While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV] and its ratio to forced vital capacity [FEV/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV and FEV/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08-1.43] for PTRS versus 1.10 [0.96-1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p < 2.2 × 10 with portability gains ranging from 5% to 28%) for both dichotomous COPD traits and across all smoking strata. Our study demonstrates the value of PTRS for improved cross-ethnic portability compared to PRS in predicting COPD risk.

%B Am J Hum Genet %8 2022 Mar 31 %G eng %R 10.1016/j.ajhg.2022.03.007 %0 Journal Article %J Am J Hum Genet %D 2022 %T Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes. %A Hindy, George %A Dornbos, Peter %A Chaffin, Mark D %A Liu, Dajiang J %A Wang, Minxian %A Selvaraj, Margaret Sunitha %A Zhang, David %A Park, Joseph %A Aguilar-Salinas, Carlos A %A Antonacci-Fulton, Lucinda %A Ardissino, Diego %A Arnett, Donna K %A Aslibekyan, Stella %A Atzmon, Gil %A Ballantyne, Christie M %A Barajas-Olmos, Francisco %A Barzilai, Nir %A Becker, Lewis C %A Bielak, Lawrence F %A Bis, Joshua C %A Blangero, John %A Boerwinkle, Eric %A Bonnycastle, Lori L %A Bottinger, Erwin %A Bowden, Donald W %A Bown, Matthew J %A Brody, Jennifer A %A Broome, Jai G %A Burtt, Noel P %A Cade, Brian E %A Centeno-Cruz, Federico %A Chan, Edmund %A Chang, Yi-Cheng %A Chen, Yii-der I %A Cheng, Ching-Yu %A Choi, Won Jung %A Chowdhury, Rajiv %A Contreras-Cubas, Cecilia %A Córdova, Emilio J %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A Danesh, John %A de Vries, Paul S %A DeFronzo, Ralph A %A Doddapaneni, Harsha %A Duggirala, Ravindranath %A Dutcher, Susan K %A Ellinor, Patrick T %A Emery, Leslie S %A Florez, Jose C %A Fornage, Myriam %A Freedman, Barry I %A Fuster, Valentin %A Garay-Sevilla, Ma Eugenia %A García-Ortiz, Humberto %A Germer, Soren %A Gibbs, Richard A %A Gieger, Christian %A Glaser, Benjamin %A Gonzalez, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Graff, Mariaelisa %A Graham, Sarah E %A Grarup, Niels %A Groop, Leif C %A Guo, Xiuqing %A Gupta, Namrata %A Han, Sohee %A Hanis, Craig L %A Hansen, Torben %A He, Jiang %A Heard-Costa, Nancy L %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Irvin, Marguerite R %A Islas-Andrade, Sergio %A Jarvik, Gail P %A Kang, Hyun Min %A Kardia, Sharon L R %A Kelly, Tanika %A Kenny, Eimear E %A Khan, Alyna T %A Kim, Bong-Jo %A Kim, Ryan W %A Kim, Young Jin %A Koistinen, Heikki A %A Kooperberg, Charles %A Kuusisto, Johanna %A Kwak, Soo Heon %A Laakso, Markku %A Lange, Leslie A %A Lee, Jiwon %A Lee, Juyoung %A Lee, Seonwook %A Lehman, Donna M %A Lemaitre, Rozenn N %A Linneberg, Allan %A Liu, Jianjun %A Loos, Ruth J F %A Lubitz, Steven A %A Lyssenko, Valeriya %A Ma, Ronald C W %A Martin, Lisa Warsinger %A Martínez-Hernández, Angélica %A Mathias, Rasika A %A McGarvey, Stephen T %A McPherson, Ruth %A Meigs, James B %A Meitinger, Thomas %A Melander, Olle %A Mendoza-Caamal, Elvia %A Metcalf, Ginger A %A Mi, Xuenan %A Mohlke, Karen L %A Montasser, May E %A Moon, Jee-Young %A Moreno-Macias, Hortensia %A Morrison, Alanna C %A Muzny, Donna M %A Nelson, Sarah C %A Nilsson, Peter M %A O'Connell, Jeffrey R %A Orho-Melander, Marju %A Orozco, Lorena %A Palmer, Colin N A %A Palmer, Nicholette D %A Park, Cheol Joo %A Park, Kyong Soo %A Pedersen, Oluf %A Peralta, Juan M %A Peyser, Patricia A %A Post, Wendy S %A Preuss, Michael %A Psaty, Bruce M %A Qi, Qibin %A Rao, D C %A Redline, Susan %A Reiner, Alexander P %A Revilla-Monsalve, Cristina %A Rich, Stephen S %A Samani, Nilesh %A Schunkert, Heribert %A Schurmann, Claudia %A Seo, Daekwan %A Seo, Jeong-Sun %A Sim, Xueling %A Sladek, Rob %A Small, Kerrin S %A So, Wing Yee %A Stilp, Adrienne M %A Tai, E Shyong %A Tam, Claudia H T %A Taylor, Kent D %A Teo, Yik Ying %A Thameem, Farook %A Tomlinson, Brian %A Tsai, Michael Y %A Tuomi, Tiinamaija %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A van Dam, Rob M %A Vasan, Ramachandran S %A Viaud Martinez, Karine A %A Wang, Fei Fei %A Wang, Xuzhi %A Watkins, Hugh %A Weeks, Daniel E %A Wilson, James G %A Witte, Daniel R %A Wong, Tien-Yin %A Yanek, Lisa R %A Kathiresan, Sekar %A Rader, Daniel J %A Rotter, Jerome I %A Boehnke, Michael %A McCarthy, Mark I %A Willer, Cristen J %A Natarajan, Pradeep %A Flannick, Jason A %A Khera, Amit V %A Peloso, Gina M %K Alleles %K Blood Glucose %K Case-Control Studies %K Computational Biology %K Databases, Genetic %K Diabetes Mellitus, Type 2 %K Exome %K Genetic Predisposition to Disease %K Genetic Variation %K Genetics, Population %K Genome-Wide Association Study %K Humans %K Lipid Metabolism %K Lipids %K Liver %K Molecular Sequence Annotation %K Multifactorial Inheritance %K Open Reading Frames %K Phenotype %K Polymorphism, Single Nucleotide %X

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

%B Am J Hum Genet %V 109 %P 81-96 %8 2022 01 06 %G eng %N 1 %R 10.1016/j.ajhg.2021.11.021 %0 Journal Article %J Nat Hum Behav %D 2022 %T Rare genetic variants explain missing heritability in smoking. %A Jang, Seon-Kyeong %A Evans, Luke %A Fialkowski, Allison %A Arnett, Donna K %A Ashley-Koch, Allison E %A Barnes, Kathleen C %A Becker, Diane M %A Bis, Joshua C %A Blangero, John %A Bleecker, Eugene R %A Boorgula, Meher Preethi %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Jenkins, Brenda W Campbell %A Carson, April P %A Chavan, Sameer %A Cupples, L Adrienne %A Custer, Brian %A Damrauer, Scott M %A David, Sean P %A de Andrade, Mariza %A Dinardo, Carla L %A Fingerlin, Tasha E %A Fornage, Myriam %A Freedman, Barry I %A Garrett, Melanie E %A Gharib, Sina A %A Glahn, David C %A Haessler, Jeffrey %A Heckbert, Susan R %A Hokanson, John E %A Hou, Lifang %A Hwang, Shih-Jen %A Hyman, Matthew C %A Judy, Renae %A Justice, Anne E %A Kaplan, Robert C %A Kardia, Sharon L R %A Kelly, Shannon %A Kim, Wonji %A Kooperberg, Charles %A Levy, Daniel %A Lloyd-Jones, Donald M %A Loos, Ruth J F %A Manichaikul, Ani W %A Gladwin, Mark T %A Martin, Lisa Warsinger %A Nouraie, Mehdi %A Melander, Olle %A Meyers, Deborah A %A Montgomery, Courtney G %A North, Kari E %A Oelsner, Elizabeth C %A Palmer, Nicholette D %A Payton, Marinelle %A Peljto, Anna L %A Peyser, Patricia A %A Preuss, Michael %A Psaty, Bruce M %A Qiao, Dandi %A Rader, Daniel J %A Rafaels, Nicholas %A Redline, Susan %A Reed, Robert M %A Reiner, Alexander P %A Rich, Stephen S %A Rotter, Jerome I %A Schwartz, David A %A Shadyab, Aladdin H %A Silverman, Edwin K %A Smith, Nicholas L %A Smith, J Gustav %A Smith, Albert V %A Smith, Jennifer A %A Tang, Weihong %A Taylor, Kent D %A Telen, Marilyn J %A Vasan, Ramachandran S %A Gordeuk, Victor R %A Wang, Zhe %A Wiggins, Kerri L %A Yanek, Lisa R %A Yang, Ivana V %A Young, Kendra A %A Young, Kristin L %A Zhang, Yingze %A Liu, Dajiang J %A Keller, Matthew C %A Vrieze, Scott %X

Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.

%B Nat Hum Behav %8 2022 Aug 04 %G eng %R 10.1038/s41562-022-01408-5 %0 Journal Article %J Nature %D 2022 %T Stroke genetics informs drug discovery and risk prediction across ancestries. %A Mishra, Aniket %A Malik, Rainer %A Hachiya, Tsuyoshi %A Jürgenson, Tuuli %A Namba, Shinichi %A Posner, Daniel C %A Kamanu, Frederick K %A Koido, Masaru %A Le Grand, Quentin %A Shi, Mingyang %A He, Yunye %A Georgakis, Marios K %A Caro, Ilana %A Krebs, Kristi %A Liaw, Yi-Ching %A Vaura, Felix C %A Lin, Kuang %A Winsvold, Bendik Slagsvold %A Srinivasasainagendra, Vinodh %A Parodi, Livia %A Bae, Hee-Joon %A Chauhan, Ganesh %A Chong, Michael R %A Tomppo, Liisa %A Akinyemi, Rufus %A Roshchupkin, Gennady V %A Habib, Naomi %A Jee, Yon Ho %A Thomassen, Jesper Qvist %A Abedi, Vida %A Cárcel-Márquez, Jara %A Nygaard, Marianne %A Leonard, Hampton L %A Yang, Chaojie %A Yonova-Doing, Ekaterina %A Knol, Maria J %A Lewis, Adam J %A Judy, Renae L %A Ago, Tetsuro %A Amouyel, Philippe %A Armstrong, Nicole D %A Bakker, Mark K %A Bartz, Traci M %A Bennett, David A %A Bis, Joshua C %A Bordes, Constance %A Børte, Sigrid %A Cain, Anael %A Ridker, Paul M %A Cho, Kelly %A Chen, Zhengming %A Cruchaga, Carlos %A Cole, John W %A De Jager, Phil L %A de Cid, Rafael %A Endres, Matthias %A Ferreira, Leslie E %A Geerlings, Mirjam I %A Gasca, Natalie C %A Gudnason, Vilmundur %A Hata, Jun %A He, Jing %A Heath, Alicia K %A Ho, Yuk-Lam %A Havulinna, Aki S %A Hopewell, Jemma C %A Hyacinth, Hyacinth I %A Inouye, Michael %A Jacob, Mina A %A Jeon, Christina E %A Jern, Christina %A Kamouchi, Masahiro %A Keene, Keith L %A Kitazono, Takanari %A Kittner, Steven J %A Konuma, Takahiro %A Kumar, Amit %A Lacaze, Paul %A Launer, Lenore J %A Lee, Keon-Joo %A Lepik, Kaido %A Li, Jiang %A Li, Liming %A Manichaikul, Ani %A Markus, Hugh S %A Marston, Nicholas A %A Meitinger, Thomas %A Mitchell, Braxton D %A Montellano, Felipe A %A Morisaki, Takayuki %A Mosley, Thomas H %A Nalls, Mike A %A Nordestgaard, Børge G %A O'Donnell, Martin J %A Okada, Yukinori %A Onland-Moret, N Charlotte %A Ovbiagele, Bruce %A Peters, Annette %A Psaty, Bruce M %A Rich, Stephen S %A Rosand, Jonathan %A Sabatine, Marc S %A Sacco, Ralph L %A Saleheen, Danish %A Sandset, Else Charlotte %A Salomaa, Veikko %A Sargurupremraj, Muralidharan %A Sasaki, Makoto %A Satizabal, Claudia L %A Schmidt, Carsten O %A Shimizu, Atsushi %A Smith, Nicholas L %A Sloane, Kelly L %A Sutoh, Yoichi %A Sun, Yan V %A Tanno, Kozo %A Tiedt, Steffen %A Tatlisumak, Turgut %A Torres-Aguila, Nuria P %A Tiwari, Hemant K %A Trégouët, David-Alexandre %A Trompet, Stella %A Tuladhar, Anil Man %A Tybjærg-Hansen, Anne %A van Vugt, Marion %A Vibo, Riina %A Verma, Shefali S %A Wiggins, Kerri L %A Wennberg, Patrik %A Woo, Daniel %A Wilson, Peter W F %A Xu, Huichun %A Yang, Qiong %A Yoon, Kyungheon %A Millwood, Iona Y %A Gieger, Christian %A Ninomiya, Toshiharu %A Grabe, Hans J %A Jukema, J Wouter %A Rissanen, Ina L %A Strbian, Daniel %A Kim, Young Jin %A Chen, Pei-Hsin %A Mayerhofer, Ernst %A Howson, Joanna M M %A Irvin, Marguerite R %A Adams, Hieab %A Wassertheil-Smoller, Sylvia %A Christensen, Kaare %A Ikram, Mohammad A %A Rundek, Tatjana %A Worrall, Bradford B %A Lathrop, G Mark %A Riaz, Moeen %A Simonsick, Eleanor M %A Kõrv, Janika %A França, Paulo H C %A Zand, Ramin %A Prasad, Kameshwar %A Frikke-Schmidt, Ruth %A de Leeuw, Frank-Erik %A Liman, Thomas %A Haeusler, Karl Georg %A Ruigrok, Ynte M %A Heuschmann, Peter Ulrich %A Longstreth, W T %A Jung, Keum Ji %A Bastarache, Lisa %A Paré, Guillaume %A Damrauer, Scott M %A Chasman, Daniel I %A Rotter, Jerome I %A Anderson, Christopher D %A Zwart, John-Anker %A Niiranen, Teemu J %A Fornage, Myriam %A Liaw, Yung-Po %A Seshadri, Sudha %A Fernandez-Cadenas, Israel %A Walters, Robin G %A Ruff, Christian T %A Owolabi, Mayowa O %A Huffman, Jennifer E %A Milani, Lili %A Kamatani, Yoichiro %A Dichgans, Martin %A Debette, Stephanie %X

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

%B Nature %8 2022 Sep 30 %G eng %R 10.1038/s41586-022-05165-3 %0 Journal Article %J Am J Respir Crit Care Med %D 2022 %T Targeted Genome Sequencing Identifies Multiple Rare Variants in Caveolin-1 Associated with Obstructive Sleep Apnea. %A Liang, Jingjing %A Wang, Heming %A Cade, Brian E %A Kurniansyah, Nuzulul %A He, Karen Y %A Lee, Jiwon %A Sands, Scott A %A Brody, Jennifer %A Chen, Han %A Gottlieb, Daniel J %A Evans, Daniel S %A Guo, Xiuqing %A Gharib, Sina A %A Hale, Lauren %A Hillman, David R %A Lutsey, Pamela L %A Mukherjee, Sutapa %A Ochs-Balcom, Heather M %A Palmer, Lyle J %A Purcell, Shaun %A Saxena, Richa %A Patel, Sanjay R %A Stone, Katie L %A Tranah, Gregory J %A Boerwinkle, Eric %A Lin, Xihong %A Liu, Yongmei %A Psaty, Bruce M %A Vasan, Ramachandran S %A Manichaikul, Ani %A Rich, Stephen S %A Rotter, Jerome I %A Sofer, Tamar %A Redline, Susan %A Zhu, Xiaofeng %X

INTRODUCTION: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. There is strong clinical and epi-demiologic evidence supporting the importance of genetic factors influencing OSA, but limited data implicating specific genes.

METHODS: Leveraging high depth genomic sequencing data from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program and imputed genotype data from multiple population-based studies, we performed linkage analysis in the Cleve-land Family Study (CFS) followed by multi-stage gene-based association analyses in independent cohorts to search for rare variants contributing to OSA severity as assessed by the apnea-hypopnea index (AHI) in a total of 7,708 individuals of European ancestry.

RESULTS: Linkage analysis in CFS identified a suggestive linkage peak on chromosome 7q31 (LOD=2.31). Gene-based analysis identified 21 non-coding rare variants in Caveolin-1 (CAV1) associated with lower AHI after accounting for multiple comparisons (p=7.4×10-8). These non-coding variants together significantly contributed to the linkage evidence (p<10-3). Follow-up anal-ysis revealed significant associations between these variants and increased CAV1 expression, and increased CAV1 expression in peripheral monocytes was associated with lower AHI (p=0.024) and higher minimum overnight oxygen saturation (p=0.007).

CONCLUSION: Rare variants in CAV1, a membrane scaffolding protein essential in multiple cellular and metabolic functions, are associated with higher CAV1 gene expression and lower OSA severity, suggesting a novel target for modulating OSA severity.

%B Am J Respir Crit Care Med %8 2022 Jul 13 %G eng %R 10.1164/rccm.202203-0618OC %0 Journal Article %J Front Endocrinol (Lausanne) %D 2022 %T The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations. %A Wang, Zhe %A Choi, Shing Wan %A Chami, Nathalie %A Boerwinkle, Eric %A Fornage, Myriam %A Redline, Susan %A Bis, Joshua C %A Brody, Jennifer A %A Psaty, Bruce M %A Kim, Wonji %A McDonald, Merry-Lynn N %A Regan, Elizabeth A %A Silverman, Edwin K %A Liu, Ching-Ti %A Vasan, Ramachandran S %A Kalyani, Rita R %A Mathias, Rasika A %A Yanek, Lisa R %A Arnett, Donna K %A Justice, Anne E %A North, Kari E %A Kaplan, Robert %A Heckbert, Susan R %A de Andrade, Mariza %A Guo, Xiuqing %A Lange, Leslie A %A Rich, Stephen S %A Rotter, Jerome I %A Ellinor, Patrick T %A Lubitz, Steven A %A Blangero, John %A Shoemaker, M Benjamin %A Darbar, Dawood %A Gladwin, Mark T %A Albert, Christine M %A Chasman, Daniel I %A Jackson, Rebecca D %A Kooperberg, Charles %A Reiner, Alexander P %A O'Reilly, Paul F %A Loos, Ruth J F %K Gene Frequency %K Genetic Variation %K Genome-Wide Association Study %K Humans %K Obesity %K Whole Genome Sequencing %X

Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRS) with a rare variant PRS (PRS) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m), obesity (BMI ≥ 30 kg/m), and extreme obesity (BMI ≥ 40 kg/m). We built PRSs and PRSs using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRS explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRS explained 1.49%, and 2.97% and 3.68%, respectively. The PRS was associated with an increased risk of obesity and extreme obesity (OR = 1.37 per SD, = 1.7x10; OR = 1.55 per SD, = 3.8x10), which was attenuated, after adjusting for PRS (OR = 1.08 per SD, = 9.8x10; OR= 1.09 per SD, = 0.02). When PRS and PRS are combined, the increase in explained variance attributed to PRS was small (incremental Nagelkerke R = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRS to PRS provided little improvement to the prediction of obesity (PRS AUC = 0.591; PRS AUC = 0.708; PRS AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRS provides limited improvement over PRS in the prediction of obesity risk, based on these large populations.

%B Front Endocrinol (Lausanne) %V 13 %P 863893 %8 2022 %G eng %R 10.3389/fendo.2022.863893 %0 Journal Article %J Commun Biol %D 2022 %T Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program. %A DiCorpo, Daniel %A Gaynor, Sheila M %A Russell, Emily M %A Westerman, Kenneth E %A Raffield, Laura M %A Majarian, Timothy D %A Wu, Peitao %A Sarnowski, Chloe %A Highland, Heather M %A Jackson, Anne %A Hasbani, Natalie R %A de Vries, Paul S %A Brody, Jennifer A %A Hidalgo, Bertha %A Guo, Xiuqing %A Perry, James A %A O'Connell, Jeffrey R %A Lent, Samantha %A Montasser, May E %A Cade, Brian E %A Jain, Deepti %A Wang, Heming %A D'Oliveira Albanus, Ricardo %A Varshney, Arushi %A Yanek, Lisa R %A Lange, Leslie %A Palmer, Nicholette D %A Almeida, Marcio %A Peralta, Juan M %A Aslibekyan, Stella %A Baldridge, Abigail S %A Bertoni, Alain G %A Bielak, Lawrence F %A Chen, Chung-Shiuan %A Chen, Yii-Der Ida %A Choi, Won Jung %A Goodarzi, Mark O %A Floyd, James S %A Irvin, Marguerite R %A Kalyani, Rita R %A Kelly, Tanika N %A Lee, Seonwook %A Liu, Ching-Ti %A Loesch, Douglas %A Manson, JoAnn E %A Minster, Ryan L %A Naseri, Take %A Pankow, James S %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Reupena, Muagututi'a Sefuiva %A Selvin, Elizabeth %A Smith, Jennifer A %A Weeks, Daniel E %A Xu, Huichun %A Yao, Jie %A Zhao, Wei %A Parker, Stephen %A Alonso, Alvaro %A Arnett, Donna K %A Blangero, John %A Boerwinkle, Eric %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A Duggirala, Ravindranath %A He, Jiang %A Heckbert, Susan R %A Kardia, Sharon L R %A Kim, Ryan W %A Kooperberg, Charles %A Liu, Simin %A Mathias, Rasika A %A McGarvey, Stephen T %A Mitchell, Braxton D %A Morrison, Alanna C %A Peyser, Patricia A %A Psaty, Bruce M %A Redline, Susan %A Shuldiner, Alan R %A Taylor, Kent D %A Vasan, Ramachandran S %A Viaud-Martinez, Karine A %A Florez, Jose C %A Wilson, James G %A Sladek, Robert %A Rich, Stephen S %A Rotter, Jerome I %A Lin, Xihong %A Dupuis, Josée %A Meigs, James B %A Wessel, Jennifer %A Manning, Alisa K %K Diabetes Mellitus, Type 2 %K Fasting %K Glucose %K Humans %K Insulin %K National Heart, Lung, and Blood Institute (U.S.) %K Nerve Tissue Proteins %K Polymorphism, Single Nucleotide %K Precision Medicine %K Receptors, Immunologic %K United States %X

The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.

%B Commun Biol %V 5 %P 756 %8 2022 07 28 %G eng %N 1 %R 10.1038/s42003-022-03702-4 %0 Journal Article %J Nat Commun %D 2022 %T Whole genome sequencing identifies structural variants contributing to hematologic traits in the NHLBI TOPMed program. %A Wheeler, Marsha M %A Stilp, Adrienne M %A Rao, Shuquan %A Halldorsson, Bjarni V %A Beyter, Doruk %A Wen, Jia %A Mihkaylova, Anna V %A McHugh, Caitlin P %A Lane, John %A Jiang, Min-Zhi %A Raffield, Laura M %A Jun, Goo %A Sedlazeck, Fritz J %A Metcalf, Ginger %A Yao, Yao %A Bis, Joshua B %A Chami, Nathalie %A de Vries, Paul S %A Desai, Pinkal %A Floyd, James S %A Gao, Yan %A Kammers, Kai %A Kim, Wonji %A Moon, Jee-Young %A Ratan, Aakrosh %A Yanek, Lisa R %A Almasy, Laura %A Becker, Lewis C %A Blangero, John %A Cho, Michael H %A Curran, Joanne E %A Fornage, Myriam %A Kaplan, Robert C %A Lewis, Joshua P %A Loos, Ruth J F %A Mitchell, Braxton D %A Morrison, Alanna C %A Preuss, Michael %A Psaty, Bruce M %A Rich, Stephen S %A Rotter, Jerome I %A Tang, Hua %A Tracy, Russell P %A Boerwinkle, Eric %A Abecasis, Goncalo R %A Blackwell, Thomas W %A Smith, Albert V %A Johnson, Andrew D %A Mathias, Rasika A %A Nickerson, Deborah A %A Conomos, Matthew P %A Li, Yun %A Þorsteinsdottir, Unnur %A Magnússon, Magnús K %A Stefansson, Kari %A Pankratz, Nathan D %A Bauer, Daniel E %A Auer, Paul L %A Reiner, Alex P %K Blood Cells %K Genome-Wide Association Study %K Humans %K Whole Genome Sequencing %X

Genome-wide association studies have identified thousands of single nucleotide variants and small indels that contribute to variation in hematologic traits. While structural variants are known to cause rare blood or hematopoietic disorders, the genome-wide contribution of structural variants to quantitative blood cell trait variation is unknown. Here we utilized whole genome sequencing data in ancestrally diverse participants of the NHLBI Trans Omics for Precision Medicine program (N = 50,675) to detect structural variants associated with hematologic traits. Using single variant tests, we assessed the association of common and rare structural variants with red cell-, white cell-, and platelet-related quantitative traits and observed 21 independent signals (12 common and 9 rare) reaching genome-wide significance. The majority of these associations (N = 18) replicated in independent datasets. In genome-editing experiments, we provide evidence that a deletion associated with lower monocyte counts leads to disruption of an S1PR3 monocyte enhancer and decreased S1PR3 expression.

%B Nat Commun %V 13 %P 7592 %8 2022 Dec 08 %G eng %N 1 %R 10.1038/s41467-022-35354-7 %0 Journal Article %J Nature %D 2023 %T Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis. %A Weinstock, Joshua S %A Gopakumar, Jayakrishnan %A Burugula, Bala Bharathi %A Uddin, Md Mesbah %A Jahn, Nikolaus %A Belk, Julia A %A Bouzid, Hind %A Daniel, Bence %A Miao, Zhuang %A Ly, Nghi %A Mack, Taralynn M %A Luna, Sofia E %A Prothro, Katherine P %A Mitchell, Shaneice R %A Laurie, Cecelia A %A Broome, Jai G %A Taylor, Kent D %A Guo, Xiuqing %A Sinner, Moritz F %A von Falkenhausen, Aenne S %A Kääb, Stefan %A Shuldiner, Alan R %A O'Connell, Jeffrey R %A Lewis, Joshua P %A Boerwinkle, Eric %A Barnes, Kathleen C %A Chami, Nathalie %A Kenny, Eimear E %A Loos, Ruth J F %A Fornage, Myriam %A Hou, Lifang %A Lloyd-Jones, Donald M %A Redline, Susan %A Cade, Brian E %A Psaty, Bruce M %A Bis, Joshua C %A Brody, Jennifer A %A Silverman, Edwin K %A Yun, Jeong H %A Qiao, Dandi %A Palmer, Nicholette D %A Freedman, Barry I %A Bowden, Donald W %A Cho, Michael H %A DeMeo, Dawn L %A Vasan, Ramachandran S %A Yanek, Lisa R %A Becker, Lewis C %A Kardia, Sharon L R %A Peyser, Patricia A %A He, Jiang %A Rienstra, Michiel %A van der Harst, Pim %A Kaplan, Robert %A Heckbert, Susan R %A Smith, Nicholas L %A Wiggins, Kerri L %A Arnett, Donna K %A Irvin, Marguerite R %A Tiwari, Hemant %A Cutler, Michael J %A Knight, Stacey %A Muhlestein, J Brent %A Correa, Adolfo %A Raffield, Laura M %A Gao, Yan %A de Andrade, Mariza %A Rotter, Jerome I %A Rich, Stephen S %A Tracy, Russell P %A Konkle, Barbara A %A Johnsen, Jill M %A Wheeler, Marsha M %A Smith, J Gustav %A Melander, Olle %A Nilsson, Peter M %A Custer, Brian S %A Duggirala, Ravindranath %A Curran, Joanne E %A Blangero, John %A McGarvey, Stephen %A Williams, L Keoki %A Xiao, Shujie %A Yang, Mao %A Gu, C Charles %A Chen, Yii-Der Ida %A Lee, Wen-Jane %A Marcus, Gregory M %A Kane, John P %A Pullinger, Clive R %A Shoemaker, M Benjamin %A Darbar, Dawood %A Roden, Dan M %A Albert, Christine %A Kooperberg, Charles %A Zhou, Ying %A Manson, JoAnn E %A Desai, Pinkal %A Johnson, Andrew D %A Mathias, Rasika A %A Blackwell, Thomas W %A Abecasis, Goncalo R %A Smith, Albert V %A Kang, Hyun M %A Satpathy, Ansuman T %A Natarajan, Pradeep %A Kitzman, Jacob O %A Whitsel, Eric A %A Reiner, Alexander P %A Bick, Alexander G %A Jaiswal, Siddhartha %K Alleles %K Animals %K Clonal Hematopoiesis %K Genome-Wide Association Study %K Hematopoiesis %K Hematopoietic Stem Cells %K Humans %K Mice %K Mutation %K Promoter Regions, Genetic %X

Mutations in a diverse set of driver genes increase the fitness of haematopoietic stem cells (HSCs), leading to clonal haematopoiesis. These lesions are precursors for blood cancers, but the basis of their fitness advantage remains largely unknown, partly owing to a paucity of large cohorts in which the clonal expansion rate has been assessed by longitudinal sampling. Here, to circumvent this limitation, we developed a method to infer the expansion rate from data from a single time point. We applied this method to 5,071 people with clonal haematopoiesis. A genome-wide association study revealed that a common inherited polymorphism in the TCL1A promoter was associated with a slower expansion rate in clonal haematopoiesis overall, but the effect varied by driver gene. Those carrying this protective allele exhibited markedly reduced growth rates or prevalence of clones with driver mutations in TET2, ASXL1, SF3B1 and SRSF2, but this effect was not seen in clones with driver mutations in DNMT3A. TCL1A was not expressed in normal or DNMT3A-mutated HSCs, but the introduction of mutations in TET2 or ASXL1 led to the expression of TCL1A protein and the expansion of HSCs in vitro. The protective allele restricted TCL1A expression and expansion of mutant HSCs, as did experimental knockdown of TCL1A expression. Forced expression of TCL1A promoted the expansion of human HSCs in vitro and mouse HSCs in vivo. Our results indicate that the fitness advantage of several commonly mutated driver genes in clonal haematopoiesis may be mediated by TCL1A activation.

%B Nature %V 616 %P 755-763 %8 2023 Apr %G eng %N 7958 %R 10.1038/s41586-023-05806-1 %0 Journal Article %J J Am Heart Assoc %D 2023 %T Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk. %A Liu, Xue %A Sun, Xianbang %A Zhang, Yuankai %A Jiang, Wenqing %A Lai, Meng %A Wiggins, Kerri L %A Raffield, Laura M %A Bielak, Lawrence F %A Zhao, Wei %A Pitsillides, Achilleas %A Haessler, Jeffrey %A Zheng, Yinan %A Blackwell, Thomas W %A Yao, Jie %A Guo, Xiuqing %A Qian, Yong %A Thyagarajan, Bharat %A Pankratz, Nathan %A Rich, Stephen S %A Taylor, Kent D %A Peyser, Patricia A %A Heckbert, Susan R %A Seshadri, Sudha %A Boerwinkle, Eric %A Grove, Megan L %A Larson, Nicholas B %A Smith, Jennifer A %A Vasan, Ramachandran S %A Fitzpatrick, Annette L %A Fornage, Myriam %A Ding, Jun %A Carson, April P %A Abecasis, Goncalo %A Dupuis, Josée %A Reiner, Alexander %A Kooperberg, Charles %A Hou, Lifang %A Psaty, Bruce M %A Wilson, James G %A Levy, Daniel %A Rotter, Jerome I %A Bis, Joshua C %A Satizabal, Claudia L %A Arking, Dan E %A Liu, Chunyu %X

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). <0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1-SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04-1.12; <0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; =0.11) or in the reverse direction (β=-0.012; =0.076). Additional bidirectional Mendelian randomization analyses revealed that low-density lipoprotein cholesterol had a causal effect on mtDNA CN (β=-0.084; <0.001), but the reverse direction was not significant (=0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low-density lipoprotein cholesterol level (=0.52), whereas there was a strong direct causal effect of higher low-density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=-0.092; <0.001). Conclusions Our findings indicate that high low-density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.

%B J Am Heart Assoc %P e029090 %8 2023 Oct 07 %G eng %R 10.1161/JAHA.122.029090 %0 Journal Article %J Neurology %D 2023 %T Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-analysis of Community-Based Cohorts. %A Zhang, Yuankai %A Liu, Xue %A Wiggins, Kerri L %A Kurniansyah, Nuzulul %A Guo, Xiuqing %A Rodrigue, Amanda L %A Zhao, Wei %A Yanek, Lisa R %A Ratliff, Scott M %A Pitsillides, Achilleas %A Aguirre Patiño, Juan Sebastian %A Sofer, Tamar %A Arking, Dan E %A Austin, Thomas R %A Beiser, Alexa S %A Blangero, John %A Boerwinkle, Eric %A Bressler, Jan %A Curran, Joanne E %A Hou, Lifang %A Hughes, Timothy M %A Kardia, Sharon L %A Launer, Lenore %A Levy, Daniel %A Mosley, Tom H %A Nasrallah, Ilya M %A Rich, Stephen S %A Rotter, Jerome I %A Seshadri, Sudha %A Tarraf, Wassim %A González, Kevin A %A Ramachandran, Vasan %A Yaffe, Kristine %A Nyquist, Paul A %A Psaty, Bruce M %A DeCarli, Charles S %A Smith, Jennifer A %A Glahn, David C %A González, Hector M %A Bis, Joshua C %A Fornage, Myriam %A Heckbert, Susan R %A Fitzpatrick, Annette L %A Liu, Chunyu %A Satizabal, Claudia L %X

BACKGROUND AND OBJECTIVES: Previous studies suggest lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer's disease (AD) and AD related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults.

METHODS: We included dementia-free participants from nine diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within ±5 years (i.e., cross-sectional analyses) or 5 to 20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (<60 vs. ≥60 years). Fixed-effects or sample size-weighted meta-analyses were performed to combine results. Finally, we performed Mendelian randomization (MR) analyses to assess causality.

RESULTS: We included up to 19,152 participants (mean age 59 years, 57% women). Higher mtDNA CN was cross-sectionally associated with better general cognitive function (Beta=0.04; 95% CI 0.02, 0.06) independent of age, sex, batch effects, race/ethnicity, time between blood draw and cognitive evaluation, cohort-specific variables, and education. Additional adjustment for blood cell counts or cardiometabolic traits led to slightly attenuated results. We observed similar significant associations with cognition in prospective analyses, although of reduced magnitude. We found no significant associations between mtDNA CN and brain MRI measures in meta-analyses. MR analyses did not reveal a causal relation between mtDNA CN in blood and cognition.

DISCUSSION: Higher mtDNA CN in blood is associated with better current and future general cognitive function in large and diverse communities across the US. Although MR analyses did not support a causal role, additional research is needed to assess causality. Circulating mtDNA CN could serve nevertheless as a biomarker of current and future cognitive function in the community.

%B Neurology %8 2023 Mar 16 %G eng %R 10.1212/WNL.0000000000207157 %0 Journal Article %J BMJ %D 2023 %T Association of omega 3 polyunsaturated fatty acids with incident chronic kidney disease: pooled analysis of 19 cohorts. %A Ong, Kwok Leung %A Marklund, Matti %A Huang, Liping %A Rye, Kerry-Anne %A Hui, Nicholas %A Pan, Xiong-Fei %A Rebholz, Casey M %A Kim, Hyunju %A Steffen, Lyn M %A van Westing, Anniek C %A Geleijnse, Johanna M %A Hoogeveen, Ellen K %A Chen, Yun-Yu %A Chien, Kuo-Liong %A Fretts, Amanda M %A Lemaitre, Rozenn N %A Imamura, Fumiaki %A Forouhi, Nita G %A Wareham, Nicholas J %A Birukov, Anna %A Jäger, Susanne %A Kuxhaus, Olga %A Schulze, Matthias B %A de Mello, Vanessa Derenji %A Tuomilehto, Jaakko %A Uusitupa, Matti %A Lindström, Jaana %A Tintle, Nathan %A Harris, William S %A Yamasaki, Keisuke %A Hirakawa, Yoichiro %A Ninomiya, Toshiharu %A Tanaka, Toshiko %A Ferrucci, Luigi %A Bandinelli, Stefania %A Virtanen, Jyrki K %A Voutilainen, Ari %A Jayasena, Tharusha %A Thalamuthu, Anbupalam %A Poljak, Anne %A Bustamante, Sonia %A Sachdev, Perminder S %A Senn, Mackenzie K %A Rich, Stephen S %A Tsai, Michael Y %A Wood, Alexis C %A Laakso, Markku %A Lankinen, Maria %A Yang, Xiaowei %A Sun, Liang %A Li, Huaixing %A Lin, Xu %A Nowak, Christoph %A Arnlöv, Johan %A Riserus, Ulf %A Lind, Lars %A Le Goff, Mélanie %A Samieri, Cecilia %A Helmer, Catherine %A Qian, Frank %A Micha, Renata %A Tin, Adrienne %A Köttgen, Anna %A de Boer, Ian H %A Siscovick, David S %A Mozaffarian, Dariush %A Wu, Jason HY %K alpha-Linolenic Acid %K Fatty Acids, Omega-3 %K Fatty Acids, Unsaturated %K Humans %K Middle Aged %K Prospective Studies %K Renal Insufficiency, Chronic %K Risk Factors %X

OBJECTIVE: To assess the prospective associations of circulating levels of omega 3 polyunsaturated fatty acid (n-3 PUFA) biomarkers (including plant derived α linolenic acid and seafood derived eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid) with incident chronic kidney disease (CKD).

DESIGN: Pooled analysis.

DATA SOURCES: A consortium of 19 studies from 12 countries identified up to May 2020.

STUDY SELECTION: Prospective studies with measured n-3 PUFA biomarker data and incident CKD based on estimated glomerular filtration rate.

DATA EXTRACTION AND SYNTHESIS: Each participating cohort conducted de novo analysis with prespecified and consistent exposures, outcomes, covariates, and models. The results were pooled across cohorts using inverse variance weighted meta-analysis.

MAIN OUTCOME MEASURES: Primary outcome of incident CKD was defined as new onset estimated glomerular filtration rate <60 mL/min/1.73 m. In a sensitivity analysis, incident CKD was defined as new onset estimated glomerular filtration rate <60 mL/min/1.73 m and <75% of baseline rate.

RESULTS: 25 570 participants were included in the primary outcome analysis and 4944 (19.3%) developed incident CKD during follow-up (weighted median 11.3 years). In multivariable adjusted models, higher levels of total seafood n-3 PUFAs were associated with a lower incident CKD risk (relative risk per interquintile range 0.92, 95% confidence interval 0.86 to 0.98; P=0.009, I=9.9%). In categorical analyses, participants with total seafood n-3 PUFA level in the highest fifth had 13% lower risk of incident CKD compared with those in the lowest fifth (0.87, 0.80 to 0.96; P=0.005, I=0.0%). Plant derived α linolenic acid levels were not associated with incident CKD (1.00, 0.94 to 1.06; P=0.94, I=5.8%). Similar results were obtained in the sensitivity analysis. The association appeared consistent across subgroups by age (≥60 <60 years), estimated glomerular filtration rate (60-89 ≥90 mL/min/1.73 m), hypertension, diabetes, and coronary heart disease at baseline.

CONCLUSIONS: Higher seafood derived n-3 PUFA levels were associated with lower risk of incident CKD, although this association was not found for plant derived n-3 PUFAs. These results support a favourable role for seafood derived n-3 PUFAs in preventing CKD.

%B BMJ %V 380 %P e072909 %8 2023 Jan 18 %G eng %R 10.1136/bmj-2022-072909 %0 Journal Article %J JAMA Cardiol %D 2023 %T Association of Rare Protein-Truncating DNA Variants in APOB or PCSK9 With Low-density Lipoprotein Cholesterol Level and Risk of Coronary Heart Disease. %A Dron, Jacqueline S %A Patel, Aniruddh P %A Zhang, Yiyi %A Jurgens, Sean J %A Maamari, Dimitri J %A Wang, Minxian %A Boerwinkle, Eric %A Morrison, Alanna C %A de Vries, Paul S %A Fornage, Myriam %A Hou, Lifang %A Lloyd-Jones, Donald M %A Psaty, Bruce M %A Tracy, Russell P %A Bis, Joshua C %A Vasan, Ramachandran S %A Levy, Daniel %A Heard-Costa, Nancy %A Rich, Stephen S %A Guo, Xiuqing %A Taylor, Kent D %A Gibbs, Richard A %A Rotter, Jerome I %A Willer, Cristen J %A Oelsner, Elizabeth C %A Moran, Andrew E %A Peloso, Gina M %A Natarajan, Pradeep %A Khera, Amit V %X

IMPORTANCE: Protein-truncating variants (PTVs) in apolipoprotein B (APOB) and proprotein convertase subtilisin/kexin type 9 (PCSK9) are associated with significantly lower low-density lipoprotein (LDL) cholesterol concentrations. The association of these PTVs with coronary heart disease (CHD) warrants further characterization in large, multiracial prospective cohort studies.

OBJECTIVE: To evaluate the association of PTVs in APOB and PCSK9 with LDL cholesterol concentrations and CHD risk.

DESIGN, SETTING, AND PARTICIPANTS: This studied included participants from 5 National Heart, Lung, and Blood Institute (NHLBI) studies and the UK Biobank. NHLBI study participants aged 5 to 84 years were recruited between 1971 and 2002 across the US and underwent whole-genome sequencing. UK Biobank participants aged 40 to 69 years were recruited between 2006 and 2010 in the UK and underwent whole-exome sequencing. Data were analyzed from June 2021 to October 2022.

EXPOSURES: PTVs in APOB and PCSK9.

MAIN OUTCOMES AND MEASURES: Estimated untreated LDL cholesterol levels and CHD.

RESULTS: Among 19 073 NHLBI participants (10 598 [55.6%] female; mean [SD] age, 52 [17] years), 139 (0.7%) carried an APOB or PCSK9 PTV, which was associated with 49 mg/dL (95% CI, 43-56) lower estimated untreated LDL cholesterol level. Over a median (IQR) follow-up of 21.5 (13.9-29.4) years, incident CHD was observed in 12 of 139 carriers (8.6%) vs 3029 of 18 934 noncarriers (16.0%), corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.28-0.89; P = .02). Among 190 464 UK Biobank participants (104 831 [55.0%] female; mean [SD] age, 57 [8] years), 662 (0.4%) carried a PTV, which was associated with 45 mg/dL (95% CI, 42-47) lower estimated untreated LDL cholesterol level. Estimated CHD risk by age 75 years was 3.7% (95% CI, 2.0-5.3) in carriers vs 7.0% (95% CI, 6.9-7.2) in noncarriers, corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.32-0.81; P = .004).

CONCLUSIONS AND RELEVANCE: Among 209 537 individuals in this study, 0.4% carried an APOB or PCSK9 PTV that was associated with less exposure to LDL cholesterol and a 49% lower risk of CHD.

%B JAMA Cardiol %8 2023 Feb 01 %G eng %R 10.1001/jamacardio.2022.5271 %0 Journal Article %J Circulation %D 2023 %T Association of Severe Hypercholesterolemia and Familial Hypercholesterolemia Genotype With Risk of Coronary Heart Disease. %A Zhang, Yiyi %A Dron, Jacqueline S %A Bellows, Brandon K %A Khera, Amit V %A Liu, Junxiu %A Balte, Pallavi P %A Oelsner, Elizabeth C %A Amr, Sami Samir %A Lebo, Matthew S %A Nagy, Anna %A Peloso, Gina M %A Natarajan, Pradeep %A Rotter, Jerome I %A Willer, Cristen %A Boerwinkle, Eric %A Ballantyne, Christie M %A Lutsey, Pamela L %A Fornage, Myriam %A Lloyd-Jones, Donald M %A Hou, Lifang %A Psaty, Bruce M %A Bis, Joshua C %A Floyd, James S %A Vasan, Ramachandran S %A Heard-Costa, Nancy L %A Carson, April P %A Hall, Michael E %A Rich, Stephen S %A Guo, Xiuqing %A Kazi, Dhruv S %A de Ferranti, Sarah D %A Moran, Andrew E %K Coronary Disease %K Genotype %K Humans %K Hypercholesterolemia %K Hyperlipoproteinemia Type II %B Circulation %V 147 %P 1556-1559 %8 2023 May 16 %G eng %N 20 %R 10.1161/CIRCULATIONAHA.123.064168 %0 Journal Article %J medRxiv %D 2023 %T Carriers of rare damaging genetic variants are at lower risk of atherosclerotic disease. %A Georgakis, Marios K %A Malik, Rainer %A Hasbani, Natalie R %A Shakt, Gabrielle %A Morrison, Alanna C %A Tsao, Noah L %A Judy, Renae %A Mitchell, Braxton D %A Xu, Huichun %A Montasser, May E %A Do, Ron %A Kenny, Eimear E %A Loos, Ruth J F %A Terry, James G %A Carr, John Jeffrey %A Bis, Joshua C %A Psaty, Bruce M %A Longstreth, W T %A Young, Kendra A %A Lutz, Sharon M %A Cho, Michael H %A Broome, Jai %A Khan, Alyna T %A Wang, Fei Fei %A Heard-Costa, Nancy %A Seshadri, Sudha %A Vasan, Ramachandran S %A Palmer, Nicholette D %A Freedman, Barry I %A Bowden, Donald W %A Yanek, Lisa R %A Kral, Brian G %A Becker, Lewis C %A Peyser, Patricia A %A Bielak, Lawrence F %A Ammous, Farah %A Carson, April P %A Hall, Michael E %A Raffield, Laura M %A Rich, Stephen S %A Post, Wendy S %A Tracy, Russel P %A Taylor, Kent D %A Guo, Xiuqing %A Mahaney, Michael C %A Curran, Joanne E %A Blangero, John %A Clarke, Shoa L %A Haessler, Jeffrey W %A Hu, Yao %A Assimes, Themistocles L %A Kooperberg, Charles %A Damrauer, Scott M %A Rotter, Jerome I %A de Vries, Paul S %A Dichgans, Martin %X

BACKGROUND: The CCL2/CCR2 axis governs monocyte trafficking and recruitment to atherosclerotic lesions. Human genetic analyses and population-based studies support an association between circulating CCL2 levels and atherosclerosis. Still, it remains unknown whether pharmacological targeting of CCR2, the main CCL2 receptor, would provide protection against human atherosclerotic disease.

METHODS: In whole-exome sequencing data from 454,775 UK Biobank participants (40-69 years), we identified predicted loss-of-function (LoF) or damaging missense (REVEL score >0.5) variants within the gene. We prioritized variants associated with lower monocyte count (p<0.05) and tested associations with vascular risk factors and risk of atherosclerotic disease over a mean follow-up of 14 years. The results were replicated in a pooled cohort of three independent datasets (TOPMed, deCODE and Penn Medicine BioBank; total n=441,445) and the effect of the most frequent damaging variant was experimentally validated.

RESULTS: A total of 45 predicted LoF or damaging missense variants were identified in the gene, 4 of which were also significantly associated with lower monocyte count, but not with other white blood cell counts. Heterozygous carriers of these variants were at a lower risk of a combined atherosclerosis outcome, showed a lower burden of atherosclerosis across four vascular beds, and were at a lower lifetime risk of coronary artery disease and myocardial infarction. There was no evidence of association with vascular risk factors including LDL-cholesterol, blood pressure, glycemic status, or C-reactive protein. Using a cAMP assay, we found that cells transfected with the most frequent damaging variant (3:46358273:T:A, M249K, 547 carriers, frequency: 0.14%) show a decrease in signaling in response to CCL2. The associations of the M249K variant with myocardial infarction were consistent across cohorts (OR : 0.62 95%CI: 0.39-0.96; OR : 0.64 95%CI: 0.34-1.19; OR : 0.64 95%CI: 0.45-0.90). In a phenome-wide association study, we found no evidence for higher risk of common infections or mortality among carriers of damaging variants.

CONCLUSIONS: Heterozygous carriers of damaging variants have a lower burden of atherosclerosis and lower lifetime risk of myocardial infarction. In conjunction with previous evidence from experimental and epidemiological studies, our findings highlight the translational potential of CCR2-targeting as an atheroprotective approach.

%B medRxiv %8 2023 Aug 16 %G eng %R 10.1101/2023.08.14.23294063 %0 Journal Article %J Diabetes Care %D 2023 %T Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk. %A Tobias, Deirdre K %A Manning, Alisa K %A Wessel, Jennifer %A Raghavan, Sridharan %A Westerman, Kenneth E %A Bick, Alexander G %A DiCorpo, Daniel %A Whitsel, Eric A %A Collins, Jason %A Correa, Adolfo %A Cupples, L Adrienne %A Dupuis, Josée %A Goodarzi, Mark O %A Guo, Xiuqing %A Howard, Barbara %A Lange, Leslie A %A Liu, Simin %A Raffield, Laura M %A Reiner, Alex P %A Rich, Stephen S %A Taylor, Kent D %A Tinker, Lesley %A Wilson, James G %A Wu, Peitao %A Carson, April P %A Vasan, Ramachandran S %A Fornage, Myriam %A Psaty, Bruce M %A Kooperberg, Charles %A Rotter, Jerome I %A Meigs, James %A Manson, JoAnn E %X

OBJECTIVE: Clonal hematopoiesis of indeterminate potential (CHIP) is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in atherosclerotic coronary heart disease (CHD) and all-cause mortality, but its association with incident type 2 diabetes (T2D) is unknown. We hypothesized that CHIP is associated with elevated risk of T2D.

RESEARCH DESIGN AND METHODS: CHIP was derived from whole-genome sequencing of blood DNA in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) prospective cohorts. We performed analysis for 17,637 participants from six cohorts, without prior T2D, cardiovascular disease, or cancer. We evaluated baseline CHIP versus no CHIP prevalence with incident T2D, including associations with DNMT3A, TET2, ASXL1, JAK2, and TP53 variants. We estimated multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for age, sex, BMI, smoking, alcohol, education, self-reported race/ethnicity, and combined cohorts' estimates via fixed-effects meta-analysis.

RESULTS: Mean (SD) age was 63.4 (11.5) years, 76% were female, and CHIP prevalence was 6.0% (n = 1,055) at baseline. T2D was diagnosed in n = 2,467 over mean follow-up of 9.8 years. Participants with CHIP had 23% (CI = 1.04, 1.45) higher risk of T2D than those with no CHIP. Specifically, higher risk was for TET2 (HR 1.48; CI = 1.05, 2.08) and ASXL1 (HR 1.76; CI = 1.03, 2.99) mutations; DNMT3A was nonsignificant (HR 1.15; CI = 0.93, 1.43). Statistical power was limited for JAK2 and TP53 analyses.

CONCLUSIONS: CHIP was associated with higher incidence of T2D. CHIP mutations located on genes implicated in CHD and mortality were also related to T2D, suggesting shared aging-related pathology.

%B Diabetes Care %8 2023 Sep 27 %G eng %R 10.2337/dc23-0805 %0 Journal Article %J medRxiv %D 2023 %T Determinants of mosaic chromosomal alteration fitness. %A Pershad, Yash %A Mack, Taralynn %A Poisner, Hannah %A Jakubek, Yasminka A %A Stilp, Adrienne M %A Mitchell, Braxton D %A Lewis, Joshua P %A Boerwinkle, Eric %A Loos, Ruth J %A Chami, Nathalie %A Wang, Zhe %A Barnes, Kathleen %A Pankratz, Nathan %A Fornage, Myriam %A Redline, Susan %A Psaty, Bruce M %A Bis, Joshua C %A Shojaie, Ali %A Silverman, Edwin K %A Cho, Michael H %A Yun, Jeong %A DeMeo, Dawn %A Levy, Daniel %A Johnson, Andrew %A Mathias, Rasika %A Taub, Margaret %A Arnett, Donna %A North, Kari %A Raffield, Laura M %A Carson, April %A Doyle, Margaret F %A Rich, Stephen S %A Rotter, Jerome I %A Guo, Xiuqing %A Cox, Nancy %A Roden, Dan M %A Franceschini, Nora %A Desai, Pinkal %A Reiner, Alex %A Auer, Paul L %A Scheet, Paul %A Jaiswal, Siddhartha %A Weinstock, Joshua S %A Bick, Alexander G %X

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well-understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our estimates of mCA fitness were correlated (R = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using a theoretical probability distribution. Individuals with lymphoid-associated mCAs had a significantly higher white blood cell count and faster clonal expansion rate. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified , , and locus variants as modulators of mCA clonal expansion rate.

%B medRxiv %8 2023 Oct 21 %G eng %R 10.1101/2023.10.20.23297280 %0 Journal Article %J Nat Commun %D 2023 %T Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups. %A Kurniansyah, Nuzulul %A Goodman, Matthew O %A Khan, Alyna T %A Wang, Jiongming %A Feofanova, Elena %A Bis, Joshua C %A Wiggins, Kerri L %A Huffman, Jennifer E %A Kelly, Tanika %A Elfassy, Tali %A Guo, Xiuqing %A Palmas, Walter %A Lin, Henry J %A Hwang, Shih-Jen %A Gao, Yan %A Young, Kendra %A Kinney, Gregory L %A Smith, Jennifer A %A Yu, Bing %A Liu, Simin %A Wassertheil-Smoller, Sylvia %A Manson, JoAnn E %A Zhu, Xiaofeng %A Chen, Yii-Der Ida %A Lee, I-Te %A Gu, C Charles %A Lloyd-Jones, Donald M %A Zöllner, Sebastian %A Fornage, Myriam %A Kooperberg, Charles %A Correa, Adolfo %A Psaty, Bruce M %A Arnett, Donna K %A Isasi, Carmen R %A Rich, Stephen S %A Kaplan, Robert C %A Redline, Susan %A Mitchell, Braxton D %A Franceschini, Nora %A Levy, Daniel %A Rotter, Jerome I %A Morrison, Alanna C %A Sofer, Tamar %K Blood Pressure %K Ethnicity %K Female %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Male %K Multifactorial Inheritance %K Population Health %K Risk Factors %X

We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.

%B Nat Commun %V 14 %P 3202 %8 2023 Jun 02 %G eng %N 1 %R 10.1038/s41467-023-38990-9 %0 Journal Article %J Front Genet %D 2023 %T Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci. %A de Las Fuentes, Lisa %A Schwander, Karen L %A Brown, Michael R %A Bentley, Amy R %A Winkler, Thomas W %A Sung, Yun Ju %A Munroe, Patricia B %A Miller, Clint L %A Aschard, Hugo %A Aslibekyan, Stella %A Bartz, Traci M %A Bielak, Lawrence F %A Chai, Jin Fang %A Cheng, Ching-Yu %A Dorajoo, Rajkumar %A Feitosa, Mary F %A Guo, Xiuqing %A Hartwig, Fernando P %A Horimoto, Andrea %A Kolcic, Ivana %A Lim, Elise %A Liu, Yongmei %A Manning, Alisa K %A Marten, Jonathan %A Musani, Solomon K %A Noordam, Raymond %A Padmanabhan, Sandosh %A Rankinen, Tuomo %A Richard, Melissa A %A Ridker, Paul M %A Smith, Albert V %A Vojinovic, Dina %A Zonderman, Alan B %A Alver, Maris %A Boissel, Mathilde %A Christensen, Kaare %A Freedman, Barry I %A Gao, Chuan %A Giulianini, Franco %A Harris, Sarah E %A He, Meian %A Hsu, Fang-Chi %A Kuhnel, Brigitte %A Laguzzi, Federica %A Li, Xiaoyin %A Lyytikäinen, Leo-Pekka %A Nolte, Ilja M %A Poveda, Alaitz %A Rauramaa, Rainer %A Riaz, Muhammad %A Robino, Antonietta %A Sofer, Tamar %A Takeuchi, Fumihiko %A Tayo, Bamidele O %A van der Most, Peter J %A Verweij, Niek %A Ware, Erin B %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Zhan, Yiqiang %A Amin, Najaf %A Arking, Dan E %A Ballantyne, Christie %A Boerwinkle, Eric %A Brody, Jennifer A %A Broeckel, Ulrich %A Campbell, Archie %A Canouil, Mickaël %A Chai, Xiaoran %A Chen, Yii-Der Ida %A Chen, Xu %A Chitrala, Kumaraswamy Naidu %A Concas, Maria Pina %A de Faire, Ulf %A de Mutsert, Renée %A de Silva, H Janaka %A de Vries, Paul S %A Do, Ahn %A Faul, Jessica D %A Fisher, Virginia %A Floyd, James S %A Forrester, Terrence %A Friedlander, Yechiel %A Girotto, Giorgia %A Gu, C Charles %A Hallmans, Göran %A Heikkinen, Sami %A Heng, Chew-Kiat %A Homuth, Georg %A Hunt, Steven %A Ikram, M Arfan %A Jacobs, David R %A Kavousi, Maryam %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Komulainen, Pirjo %A Langefeld, Carl D %A Liang, Jingjing %A Liu, Kiang %A Liu, Jianjun %A Lohman, Kurt %A Mägi, Reedik %A Manichaikul, Ani W %A McKenzie, Colin A %A Meitinger, Thomas %A Milaneschi, Yuri %A Nauck, Matthias %A Nelson, Christopher P %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Pereira, Alexandre C %A Perls, Thomas %A Peters, Annette %A Polasek, Ozren %A Raitakari, Olli T %A Rice, Kenneth %A Rice, Treva K %A Rich, Stephen S %A Sabanayagam, Charumathi %A Schreiner, Pamela J %A Shu, Xiao-Ou %A Sidney, Stephen %A Sims, Mario %A Smith, Jennifer A %A Starr, John M %A Strauch, Konstantin %A Tai, E Shyong %A Taylor, Kent D %A Tsai, Michael Y %A Uitterlinden, André G %A van Heemst, Diana %A Waldenberger, Melanie %A Wang, Ya-Xing %A Wei, Wen-Bin %A Wilson, Gregory %A Xuan, Deng %A Yao, Jie %A Yu, Caizheng %A Yuan, Jian-Min %A Zhao, Wei %A Becker, Diane M %A Bonnefond, Amélie %A Bowden, Donald W %A Cooper, Richard S %A Deary, Ian J %A Divers, Jasmin %A Esko, Tõnu %A Franks, Paul W %A Froguel, Philippe %A Gieger, Christian %A Jonas, Jost B %A Kato, Norihiro %A Lakka, Timo A %A Leander, Karin %A Lehtimäki, Terho %A Magnusson, Patrik K E %A North, Kari E %A Ntalla, Ioanna %A Penninx, Brenda %A Samani, Nilesh J %A Snieder, Harold %A Spedicati, Beatrice %A van der Harst, Pim %A Völzke, Henry %A Wagenknecht, Lynne E %A Weir, David R %A Wojczynski, Mary K %A Wu, Tangchun %A Zheng, Wei %A Zhu, Xiaofeng %A Bouchard, Claude %A Chasman, Daniel I %A Evans, Michele K %A Fox, Ervin R %A Gudnason, Vilmundur %A Hayward, Caroline %A Horta, Bernardo L %A Kardia, Sharon L R %A Krieger, Jose Eduardo %A Mook-Kanamori, Dennis O %A Peyser, Patricia A %A Province, Michael M %A Psaty, Bruce M %A Rudan, Igor %A Sim, Xueling %A Smith, Blair H %A van Dam, Rob M %A van Duijn, Cornelia M %A Wong, Tien Yin %A Arnett, Donna K %A Rao, Dabeeru C %A Gauderman, James %A Liu, Ching-Ti %A Morrison, Alanna C %A Rotter, Jerome I %A Fornage, Myriam %X

Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes. A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: "Some College" (yes/no, for any education beyond high school) and "Graduated College" (yes/no, for completing a 4-year college degree). Genome-wide significant ( < 5 × 10) and suggestive ( < 1 × 10) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals). In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (), brain (), and liver () biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue. Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.

%B Front Genet %V 14 %P 1235337 %8 2023 %G eng %R 10.3389/fgene.2023.1235337 %0 Journal Article %J bioRxiv %D 2023 %T Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants. %A Einson, Jonah %A Glinos, Dafni %A Boerwinkle, Eric %A Castaldi, Peter %A Darbar, Dawood %A de Andrade, Mariza %A Ellinor, Patrick %A Fornage, Myriam %A Gabriel, Stacey %A Germer, Soren %A Gibbs, Richard %A Hersh, Craig P %A Johnsen, Jill %A Kaplan, Robert %A Konkle, Barbara A %A Kooperberg, Charles %A Nassir, Rami %A Loos, Ruth J F %A Meyers, Deborah A %A Mitchell, Braxton D %A Psaty, Bruce %A Vasan, Ramachandran S %A Rich, Stephen S %A Rienstra, Michael %A Rotter, Jerome I %A Saferali, Aabida %A Shoemaker, M Benjamin %A Silverman, Edwin %A Smith, Albert Vernon %A Mohammadi, Pejman %A Castel, Stephane E %A Iossifov, Ivan %A Lappalainen, Tuuli %X

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-seq data in GTEx v8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased WGS data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

%B bioRxiv %8 2023 Jan 31 %G eng %R 10.1101/2023.01.31.526505 %0 Journal Article %J Sci Adv %D 2023 %T The genetic determinants of recurrent somatic mutations in 43,693 blood genomes. %A Weinstock, Joshua S %A Laurie, Cecelia A %A Broome, Jai G %A Taylor, Kent D %A Guo, Xiuqing %A Shuldiner, Alan R %A O'Connell, Jeffrey R %A Lewis, Joshua P %A Boerwinkle, Eric %A Barnes, Kathleen C %A Chami, Nathalie %A Kenny, Eimear E %A Loos, Ruth J F %A Fornage, Myriam %A Redline, Susan %A Cade, Brian E %A Gilliland, Frank D %A Chen, Zhanghua %A Gauderman, W James %A Kumar, Rajesh %A Grammer, Leslie %A Schleimer, Robert P %A Psaty, Bruce M %A Bis, Joshua C %A Brody, Jennifer A %A Silverman, Edwin K %A Yun, Jeong H %A Qiao, Dandi %A Weiss, Scott T %A Lasky-Su, Jessica %A DeMeo, Dawn L %A Palmer, Nicholette D %A Freedman, Barry I %A Bowden, Donald W %A Cho, Michael H %A Vasan, Ramachandran S %A Johnson, Andrew D %A Yanek, Lisa R %A Becker, Lewis C %A Kardia, Sharon %A He, Jiang %A Kaplan, Robert %A Heckbert, Susan R %A Smith, Nicholas L %A Wiggins, Kerri L %A Arnett, Donna K %A Irvin, Marguerite R %A Tiwari, Hemant %A Correa, Adolfo %A Raffield, Laura M %A Gao, Yan %A de Andrade, Mariza %A Rotter, Jerome I %A Rich, Stephen S %A Manichaikul, Ani W %A Konkle, Barbara A %A Johnsen, Jill M %A Wheeler, Marsha M %A Custer, Brian S %A Duggirala, Ravindranath %A Curran, Joanne E %A Blangero, John %A Gui, Hongsheng %A Xiao, Shujie %A Williams, L Keoki %A Meyers, Deborah A %A Li, Xingnan %A Ortega, Victor %A McGarvey, Stephen %A Gu, C Charles %A Chen, Yii-Der Ida %A Lee, Wen-Jane %A Shoemaker, M Benjamin %A Darbar, Dawood %A Roden, Dan %A Albert, Christine %A Kooperberg, Charles %A Desai, Pinkal %A Blackwell, Thomas W %A Abecasis, Goncalo R %A Smith, Albert V %A Kang, Hyun M %A Mathias, Rasika %A Natarajan, Pradeep %A Jaiswal, Siddhartha %A Reiner, Alexander P %A Bick, Alexander G %K Germ-Line Mutation %K Hematopoiesis %K Humans %K Middle Aged %K Mutation %K Mutation, Missense %K Phenotype %X

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

%B Sci Adv %V 9 %P eabm4945 %8 2023 Apr 28 %G eng %N 17 %R 10.1126/sciadv.abm4945 %0 Journal Article %J medRxiv %D 2023 %T Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores. %A Hrytsenko, Yana %A Shea, Benjamin %A Elgart, Michael %A Kurniansyah, Nuzulul %A Lyons, Genevieve %A Morrison, Alanna C %A Carson, April P %A Haring, Bernhard %A Mitchel, Braxton D %A Psaty, Bruce M %A Jaeger, Byron C %A Gu, C Charles %A Kooperberg, Charles %A Levy, Daniel %A Lloyd-Jones, Donald %A Choi, Eunhee %A Brody, Jennifer A %A Smith, Jennifer A %A Rotter, Jerome I %A Moll, Matthew %A Fornage, Myriam %A Simon, Noah %A Castaldi, Peter %A Casanova, Ramon %A Chung, Ren-Hua %A Kaplan, Robert %A Loos, Ruth J F %A Kardia, Sharon L R %A Rich, Stephen S %A Redline, Susan %A Kelly, Tanika %A O'Connor, Timothy %A Zhao, Wei %A Kim, Wonji %A Guo, Xiuqing %A Der Ida Chen, Yii %A Sofer, Tamar %X

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1% to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8% to 5.1% (SBP) and 4.7% to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs.

%B medRxiv %8 2023 Dec 14 %G eng %R 10.1101/2023.12.13.23299909 %0 Journal Article %J Nat Genet %D 2023 %T Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing. %A Jakubek, Yasminka A %A Zhou, Ying %A Stilp, Adrienne %A Bacon, Jason %A Wong, Justin W %A Ozcan, Zuhal %A Arnett, Donna %A Barnes, Kathleen %A Bis, Joshua C %A Boerwinkle, Eric %A Brody, Jennifer A %A Carson, April P %A Chasman, Daniel I %A Chen, Jiawen %A Cho, Michael %A Conomos, Matthew P %A Cox, Nancy %A Doyle, Margaret F %A Fornage, Myriam %A Guo, Xiuqing %A Kardia, Sharon L R %A Lewis, Joshua P %A Loos, Ruth J F %A Ma, Xiaolong %A Machiela, Mitchell J %A Mack, Taralynn M %A Mathias, Rasika A %A Mitchell, Braxton D %A Mychaleckyj, Josyf C %A North, Kari %A Pankratz, Nathan %A Peyser, Patricia A %A Preuss, Michael H %A Psaty, Bruce %A Raffield, Laura M %A Vasan, Ramachandran S %A Redline, Susan %A Rich, Stephen S %A Rotter, Jerome I %A Silverman, Edwin K %A Smith, Jennifer A %A Smith, Aaron P %A Taub, Margaret %A Taylor, Kent D %A Yun, Jeong %A Li, Yun %A Desai, Pinkal %A Bick, Alexander G %A Reiner, Alexander P %A Scheet, Paul %A Auer, Paul L %K Black People %K Genome, Human %K Genome-Wide Association Study %K Hispanic or Latino %K Humans %K Mosaicism %K Precision Medicine %X

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis.

%B Nat Genet %V 55 %P 1912-1919 %8 2023 Nov %G eng %N 11 %R 10.1038/s41588-023-01553-1 %0 Journal Article %J medRxiv %D 2023 %T Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications. %A Suzuki, Ken %A Hatzikotoulas, Konstantinos %A Southam, Lorraine %A Taylor, Henry J %A Yin, Xianyong %A Lorenz, Kim M %A Mandla, Ravi %A Huerta-Chagoya, Alicia %A Rayner, Nigel W %A Bocher, Ozvan %A Ana Luiza de, S V Arruda %A Sonehara, Kyuto %A Namba, Shinichi %A Lee, Simon S K %A Preuss, Michael H %A Petty, Lauren E %A Schroeder, Philip %A Vanderwerff, Brett %A Kals, Mart %A Bragg, Fiona %A Lin, Kuang %A Guo, Xiuqing %A Zhang, Weihua %A Yao, Jie %A Kim, Young Jin %A Graff, Mariaelisa %A Takeuchi, Fumihiko %A Nano, Jana %A Lamri, Amel %A Nakatochi, Masahiro %A Moon, Sanghoon %A Scott, Robert A %A Cook, James P %A Lee, Jung-Jin %A Pan, Ian %A Taliun, Daniel %A Parra, Esteban J %A Chai, Jin-Fang %A Bielak, Lawrence F %A Tabara, Yasuharu %A Hai, Yang %A Thorleifsson, Gudmar %A Grarup, Niels %A Sofer, Tamar %A Wuttke, Matthias %A Sarnowski, Chloe %A Gieger, Christian %A Nousome, Darryl %A Trompet, Stella %A Kwak, Soo-Heon %A Long, Jirong %A Sun, Meng %A Tong, Lin %A Chen, Wei-Min %A Nongmaithem, Suraj S %A Noordam, Raymond %A Lim, Victor J Y %A Tam, Claudia H T %A Joo, Yoonjung Yoonie %A Chen, Chien-Hsiun %A Raffield, Laura M %A Prins, Bram Peter %A Nicolas, Aude %A Yanek, Lisa R %A Chen, Guanjie %A Brody, Jennifer A %A Kabagambe, Edmond %A An, Ping %A Xiang, Anny H %A Choi, Hyeok Sun %A Cade, Brian E %A Tan, Jingyi %A Alaine Broadaway, K %A Williamson, Alice %A Kamali, Zoha %A Cui, Jinrui %A Adair, Linda S %A Adeyemo, Adebowale %A Aguilar-Salinas, Carlos A %A Ahluwalia, Tarunveer S %A Anand, Sonia S %A Bertoni, Alain %A Bork-Jensen, Jette %A Brandslund, Ivan %A Buchanan, Thomas A %A Burant, Charles F %A Butterworth, Adam S %A Canouil, Mickaël %A Chan, Juliana C N %A Chang, Li-Ching %A Chee, Miao-Li %A Chen, Ji %A Chen, Shyh-Huei %A Chen, Yuan-Tsong %A Chen, Zhengming %A Chuang, Lee-Ming %A Cushman, Mary %A Danesh, John %A Das, Swapan K %A Janaka de Silva, H %A Dedoussis, George %A Dimitrov, Latchezar %A Doumatey, Ayo P %A Du, Shufa %A Duan, Qing %A Eckardt, Kai-Uwe %A Emery, Leslie S %A Evans, Daniel S %A Evans, Michele K %A Fischer, Krista %A Floyd, James S %A Ford, Ian %A Franco, Oscar H %A Frayling, Timothy M %A Freedman, Barry I %A Genter, Pauline %A Gerstein, Hertzel C %A Giedraitis, Vilmantas %A González-Villalpando, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Gordon-Larsen, Penny %A Gross, Myron %A Guare, Lindsay A %A Hackinger, Sophie %A Han, Sohee %A Hattersley, Andrew T %A Herder, Christian %A Horikoshi, Momoko %A Howard, Annie-Green %A Hsueh, Willa %A Huang, Mengna %A Huang, Wei %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Hwu, Chii-Min %A Ichihara, Sahoko %A Ikram, Mohammad Arfan %A Ingelsson, Martin %A Islam, Md Tariqul %A Isono, Masato %A Jang, Hye-Mi %A Jasmine, Farzana %A Jiang, Guozhi %A Jonas, Jost B %A Jørgensen, Torben %A Kandeel, Fouad R %A Kasturiratne, Anuradhani %A Katsuya, Tomohiro %A Kaur, Varinderpal %A Kawaguchi, Takahisa %A Keaton, Jacob M %A Kho, Abel N %A Khor, Chiea-Chuen %A Kibriya, Muhammad G %A Kim, Duk-Hwan %A Kronenberg, Florian %A Kuusisto, Johanna %A Läll, Kristi %A Lange, Leslie A %A Lee, Kyung Min %A Lee, Myung-Shik %A Lee, Nanette R %A Leong, Aaron %A Li, Liming %A Li, Yun %A Li-Gao, Ruifang %A Lithgart, Symen %A Lindgren, Cecilia M %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Locke, Adam E %A Louie, Tin %A Luan, Jian'an %A Luk, Andrea O %A Luo, Xi %A Lv, Jun %A Lynch, Julie A %A Lyssenko, Valeriya %A Maeda, Shiro %A Mamakou, Vasiliki %A Mansuri, Sohail Rafik %A Matsuda, Koichi %A Meitinger, Thomas %A Metspalu, Andres %A Mo, Huan %A Morris, Andrew D %A Nadler, Jerry L %A Nalls, Michael A %A Nayak, Uma %A Ntalla, Ioanna %A Okada, Yukinori %A Orozco, Lorena %A Patel, Sanjay R %A Patil, Snehal %A Pei, Pei %A Pereira, Mark A %A Peters, Annette %A Pirie, Fraser J %A Polikowsky, Hannah G %A Porneala, Bianca %A Prasad, Gauri %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Roden, Michael %A Rohde, Rebecca %A Roll, Katheryn %A Sabanayagam, Charumathi %A Sandow, Kevin %A Sankareswaran, Alagu %A Sattar, Naveed %A Schönherr, Sebastian %A Shahriar, Mohammad %A Shen, Botong %A Shi, Jinxiu %A Shin, Dong Mun %A Shojima, Nobuhiro %A Smith, Jennifer A %A So, Wing Yee %A Stančáková, Alena %A Steinthorsdottir, Valgerdur %A Stilp, Adrienne M %A Strauch, Konstantin %A Taylor, Kent D %A Thorand, Barbara %A Thorsteinsdottir, Unnur %A Tomlinson, Brian %A Tran, Tam C %A Tsai, Fuu-Jen %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A Valladares-Salgado, Adan %A van Dam, Rob M %A van Klinken, Jan B %A Varma, Rohit %A Wacher-Rodarte, Niels %A Wheeler, Eleanor %A Wickremasinghe, Ananda R %A van Dijk, Ko Willems %A Witte, Daniel R %A Yajnik, Chittaranjan S %A Yamamoto, Ken %A Yamamoto, Kenichi %A Yoon, Kyungheon %A Yu, Canqing %A Yuan, Jian-Min %A Yusuf, Salim %A Zawistowski, Matthew %A Zhang, Liang %A Zheng, Wei %A Project, Biobank Japan %A BioBank, Penn Medicine %A Center, Regeneron Genetics %A Consortium, eMERGE %A Raffel, Leslie J %A Igase, Michiya %A Ipp, Eli %A Redline, Susan %A Cho, Yoon Shin %A Lind, Lars %A Province, Michael A %A Fornage, Myriam %A Hanis, Craig L %A Ingelsson, Erik %A Zonderman, Alan B %A Psaty, Bruce M %A Wang, Ya-Xing %A Rotimi, Charles N %A Becker, Diane M %A Matsuda, Fumihiko %A Liu, Yongmei %A Yokota, Mitsuhiro %A Kardia, Sharon L R %A Peyser, Patricia A %A Pankow, James S %A Engert, James C %A Bonnefond, Amélie %A Froguel, Philippe %A Wilson, James G %A Sheu, Wayne H H %A Wu, Jer-Yuarn %A Geoffrey Hayes, M %A Ma, Ronald C W %A Wong, Tien-Yin %A Mook-Kanamori, Dennis O %A Tuomi, Tiinamaija %A Chandak, Giriraj R %A Collins, Francis S %A Bharadwaj, Dwaipayan %A Paré, Guillaume %A Sale, Michèle M %A Ahsan, Habibul %A Motala, Ayesha A %A Shu, Xiao-Ou %A Park, Kyong-Soo %A Jukema, J Wouter %A Cruz, Miguel %A Chen, Yii-Der Ida %A Rich, Stephen S %A McKean-Cowdin, Roberta %A Grallert, Harald %A Cheng, Ching-Yu %A Ghanbari, Mohsen %A Tai, E-Shyong %A Dupuis, Josée %A Kato, Norihiro %A Laakso, Markku %A Köttgen, Anna %A Koh, Woon-Puay %A Bowden, Donald W %A Palmer, Colin N A %A Kooner, Jaspal S %A Kooperberg, Charles %A Liu, Simin %A North, Kari E %A Saleheen, Danish %A Hansen, Torben %A Pedersen, Oluf %A Wareham, Nicholas J %A Lee, Juyoung %A Kim, Bong-Jo %A Millwood, Iona Y %A Walters, Robin G %A Stefansson, Kari %A Goodarzi, Mark O %A Mohlke, Karen L %A Langenberg, Claudia %A Haiman, Christopher A %A Loos, Ruth J F %A Florez, Jose C %A Rader, Daniel J %A Ritchie, Marylyn D %A Zöllner, Sebastian %A Mägi, Reedik %A Denny, Joshua C %A Yamauchi, Toshimasa %A Kadowaki, Takashi %A Chambers, John C %A Ng, Maggie C Y %A Sim, Xueling %A Below, Jennifer E %A Tsao, Philip S %A Chang, Kyong-Mi %A McCarthy, Mark I %A Meigs, James B %A Mahajan, Anubha %A Spracklen, Cassandra N %A Mercader, Josep M %A Boehnke, Michael %A Rotter, Jerome I %A Vujkovic, Marijana %A Voight, Benjamin F %A Morris, Andrew P %A Zeggini, Eleftheria %X

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10 ) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.

%B medRxiv %8 2023 Mar 31 %G eng %R 10.1101/2023.03.31.23287839 %0 Journal Article %J Nat Genet %D 2023 %T Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing. %A Chen, Fang %A Wang, Xingyan %A Jang, Seon-Kyeong %A Quach, Bryan C %A Weissenkampen, J Dylan %A Khunsriraksakul, Chachrit %A Yang, Lina %A Sauteraud, Renan %A Albert, Christine M %A Allred, Nicholette D D %A Arnett, Donna K %A Ashley-Koch, Allison E %A Barnes, Kathleen C %A Barr, R Graham %A Becker, Diane M %A Bielak, Lawrence F %A Bis, Joshua C %A Blangero, John %A Boorgula, Meher Preethi %A Chasman, Daniel I %A Chavan, Sameer %A Chen, Yii-der I %A Chuang, Lee-Ming %A Correa, Adolfo %A Curran, Joanne E %A David, Sean P %A Fuentes, Lisa de Las %A Deka, Ranjan %A Duggirala, Ravindranath %A Faul, Jessica D %A Garrett, Melanie E %A Gharib, Sina A %A Guo, Xiuqing %A Hall, Michael E %A Hawley, Nicola L %A He, Jiang %A Hobbs, Brian D %A Hokanson, John E %A Hsiung, Chao A %A Hwang, Shih-Jen %A Hyde, Thomas M %A Irvin, Marguerite R %A Jaffe, Andrew E %A Johnson, Eric O %A Kaplan, Robert %A Kardia, Sharon L R %A Kaufman, Joel D %A Kelly, Tanika N %A Kleinman, Joel E %A Kooperberg, Charles %A Lee, I-Te %A Levy, Daniel %A Lutz, Sharon M %A Manichaikul, Ani W %A Martin, Lisa W %A Marx, Olivia %A McGarvey, Stephen T %A Minster, Ryan L %A Moll, Matthew %A Moussa, Karine A %A Naseri, Take %A North, Kari E %A Oelsner, Elizabeth C %A Peralta, Juan M %A Peyser, Patricia A %A Psaty, Bruce M %A Rafaels, Nicholas %A Raffield, Laura M %A Reupena, Muagututi'a Sefuiva %A Rich, Stephen S %A Rotter, Jerome I %A Schwartz, David A %A Shadyab, Aladdin H %A Sheu, Wayne H-H %A Sims, Mario %A Smith, Jennifer A %A Sun, Xiao %A Taylor, Kent D %A Telen, Marilyn J %A Watson, Harold %A Weeks, Daniel E %A Weir, David R %A Yanek, Lisa R %A Young, Kendra A %A Young, Kristin L %A Zhao, Wei %A Hancock, Dana B %A Jiang, Bibo %A Vrieze, Scott %A Liu, Dajiang J %K Biology %K Drug Repositioning %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Polymorphism, Single Nucleotide %K Tobacco Use %K Transcriptome %X

Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

%B Nat Genet %V 55 %P 291-300 %8 2023 Feb %G eng %N 2 %R 10.1038/s41588-022-01282-x %0 Journal Article %J Nat Genet %D 2023 %T Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies. %A Li, Xihao %A Quick, Corbin %A Zhou, Hufeng %A Gaynor, Sheila M %A Liu, Yaowu %A Chen, Han %A Selvaraj, Margaret Sunitha %A Sun, Ryan %A Dey, Rounak %A Arnett, Donna K %A Bielak, Lawrence F %A Bis, Joshua C %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A de Vries, Paul S %A Duggirala, Ravindranath %A Freedman, Barry I %A Göring, Harald H H %A Guo, Xiuqing %A Haessler, Jeffrey %A Kalyani, Rita R %A Kooperberg, Charles %A Kral, Brian G %A Lange, Leslie A %A Manichaikul, Ani %A Martin, Lisa W %A McGarvey, Stephen T %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Peyser, Patricia A %A Psaty, Bruce M %A Raffield, Laura M %A Redline, Susan %A Reiner, Alexander P %A Reupena, Muagututi'a Sefuiva %A Rice, Kenneth M %A Rich, Stephen S %A Sitlani, Colleen M %A Smith, Jennifer A %A Taylor, Kent D %A Vasan, Ramachandran S %A Willer, Cristen J %A Wilson, James G %A Yanek, Lisa R %A Zhao, Wei %A Rotter, Jerome I %A Natarajan, Pradeep %A Peloso, Gina M %A Li, Zilin %A Lin, Xihong %K Exome Sequencing %K Genome-Wide Association Study %K Lipids %K Phenotype %K Whole Genome Sequencing %X

Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.

%B Nat Genet %V 55 %P 154-164 %8 2023 Jan %G eng %N 1 %R 10.1038/s41588-022-01225-6 %0 Journal Article %J medRxiv %D 2023 %T Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study. %A Wang, Yuxuan %A Selvaraj, Margaret Sunitha %A Li, Xihao %A Li, Zilin %A Holdcraft, Jacob A %A Arnett, Donna K %A Bis, Joshua C %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Cade, Brian E %A Carlson, Jenna C %A Carson, April P %A Chen, Yii-Der Ida %A Curran, Joanne E %A de Vries, Paul S %A Dutcher, Susan K %A Ellinor, Patrick T %A Floyd, James S %A Fornage, Myriam %A Freedman, Barry I %A Gabriel, Stacey %A Germer, Soren %A Gibbs, Richard A %A Guo, Xiuqing %A He, Jiang %A Heard-Costa, Nancy %A Hildalgo, Bertha %A Hou, Lifang %A Irvin, Marguerite R %A Joehanes, Roby %A Kaplan, Robert C %A Kardia, Sharon Lr %A Kelly, Tanika N %A Kim, Ryan %A Kooperberg, Charles %A Kral, Brian G %A Levy, Daniel %A Li, Changwei %A Liu, Chunyu %A Lloyd-Jone, Don %A Loos, Ruth Jf %A Mahaney, Michael C %A Martin, Lisa W %A Mathias, Rasika A %A Minster, Ryan L %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Murabito, Joanne M %A Naseri, Take %A O'Connell, Jeffrey R %A Palmer, Nicholette D %A Preuss, Michael H %A Psaty, Bruce M %A Raffield, Laura M %A Rao, Dabeeru C %A Redline, Susan %A Reiner, Alexander P %A Rich, Stephen S %A Ruepena, Muagututi'a Sefuiva %A Sheu, Wayne H-H %A Smith, Jennifer A %A Smith, Albert %A Tiwari, Hemant K %A Tsai, Michael Y %A Viaud-Martinez, Karine A %A Wang, Zhe %A Yanek, Lisa R %A Zhao, Wei %A Rotter, Jerome I %A Lin, Xihong %A Natarajan, Pradeep %A Peloso, Gina M %X

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.

%B medRxiv %8 2023 Jun 29 %G eng %R 10.1101/2023.06.28.23291966 %0 Journal Article %J bioRxiv %D 2023 %T A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies. %A Li, Xihao %A Chen, Han %A Selvaraj, Margaret Sunitha %A Van Buren, Eric %A Zhou, Hufeng %A Wang, Yuxuan %A Sun, Ryan %A McCaw, Zachary R %A Yu, Zhi %A Arnett, Donna K %A Bis, Joshua C %A Blangero, John %A Boerwinkle, Eric %A Bowden, Donald W %A Brody, Jennifer A %A Cade, Brian E %A Carson, April P %A Carlson, Jenna C %A Chami, Nathalie %A Chen, Yii-Der Ida %A Curran, Joanne E %A de Vries, Paul S %A Fornage, Myriam %A Franceschini, Nora %A Freedman, Barry I %A Gu, Charles %A Heard-Costa, Nancy L %A He, Jiang %A Hou, Lifang %A Hung, Yi-Jen %A Irvin, Marguerite R %A Kaplan, Robert C %A Kardia, Sharon L R %A Kelly, Tanika %A Konigsberg, Iain %A Kooperberg, Charles %A Kral, Brian G %A Li, Changwei %A Loos, Ruth J F %A Mahaney, Michael C %A Martin, Lisa W %A Mathias, Rasika A %A Minster, Ryan L %A Mitchell, Braxton D %A Montasser, May E %A Morrison, Alanna C %A Palmer, Nicholette D %A Peyser, Patricia A %A Psaty, Bruce M %A Raffield, Laura M %A Redline, Susan %A Reiner, Alexander P %A Rich, Stephen S %A Sitlani, Colleen M %A Smith, Jennifer A %A Taylor, Kent D %A Tiwari, Hemant %A Vasan, Ramachandran S %A Wang, Zhe %A Yanek, Lisa R %A Yu, Bing %A Rice, Kenneth M %A Rotter, Jerome I %A Peloso, Gina M %A Natarajan, Pradeep %A Li, Zilin %A Liu, Zhonghua %A Lin, Xihong %X

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of and an intergenic region on chromosome 1.

%B bioRxiv %8 2023 Nov 02 %G eng %R 10.1101/2023.10.30.564764 %0 Journal Article %J medRxiv %D 2023 %T Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus. %A Kwak, Soo Heon %A Hernandez-Cancela, Ryan B %A DiCorpo, Daniel A %A Condon, David E %A Merino, Jordi %A Wu, Peitao %A Brody, Jennifer A %A Yao, Jie %A Guo, Xiuqing %A Ahmadizar, Fariba %A Meyer, Mariah %A Sincan, Murat %A Mercader, Josep M %A Lee, Sujin %A Haessler, Jeffrey %A Vy, Ha My T %A Lin, Zhaotong %A Armstrong, Nicole D %A Gu, Shaopeng %A Tsao, Noah L %A Lange, Leslie A %A Wang, Ningyuan %A Wiggins, Kerri L %A Trompet, Stella %A Liu, Simin %A Loos, Ruth J F %A Judy, Renae %A Schroeder, Philip H %A Hasbani, Natalie R %A Bos, Maxime M %A Morrison, Alanna C %A Jackson, Rebecca D %A Reiner, Alexander P %A Manson, JoAnn E %A Chaudhary, Ninad S %A Carmichael, Lynn K %A Chen, Yii-Der Ida %A Taylor, Kent D %A Ghanbari, Mohsen %A van Meurs, Joyce %A Pitsillides, Achilleas N %A Psaty, Bruce M %A Noordam, Raymond %A Do, Ron %A Park, Kyong Soo %A Jukema, J Wouter %A Kavousi, Maryam %A Correa, Adolfo %A Rich, Stephen S %A Damrauer, Scott M %A Hajek, Catherine %A Cho, Nam H %A Irvin, Marguerite R %A Pankow, James S %A Nadkarni, Girish N %A Sladek, Robert %A Goodarzi, Mark O %A Florez, Jose C %A Chasman, Daniel I %A Heckbert, Susan R %A Kooperberg, Charles %A Dupuis, Josée %A Malhotra, Rajeev %A de Vries, Paul S %A Liu, Ching-Ti %A Rotter, Jerome I %A Meigs, James B %X

BACKGROUND: Type 2 diabetes mellitus (T2D) confers a two- to three-fold increased risk of cardiovascular disease (CVD). However, the mechanisms underlying increased CVD risk among people with T2D are only partially understood. We hypothesized that a genetic association study among people with T2D at risk for developing incident cardiovascular complications could provide insights into molecular genetic aspects underlying CVD.

METHODS: From 16 studies of the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) Consortium, we conducted a multi-ancestry time-to-event genome-wide association study (GWAS) for incident CVD among people with T2D using Cox proportional hazards models. Incident CVD was defined based on a composite of coronary artery disease (CAD), stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. Cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. We also tested 204 known CAD variants for association with incident CVD among patients with T2D.

RESULTS: A total of 49,230 participants with T2D were included in the analyses (31,118 European ancestries and 18,112 non-European ancestries) which consisted of 8,956 incident CVD cases over a range of mean follow-up duration between 3.2 and 33.7 years (event rate 18.2%). We identified three novel, distinct genetic loci for incident CVD among individuals with T2D that reached the threshold for genome-wide significance ( <5.0×10 ): rs147138607 (intergenic variant between and ) with a hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.15 - 1.32, =3.6×10 , rs11444867 (intergenic variant near ) with HR 1.89, 95% CI 1.52 - 2.35, =9.9×10 , and rs335407 (intergenic variant between and ) HR 1.25, 95% CI 1.16 - 1.35, =1.5×10 . Among 204 known CAD loci, 32 were associated with incident CVD in people with T2D with <0.05, and 5 were significant after Bonferroni correction ( <0.00024, 0.05/204). A polygenic score of these 204 variants was significantly associated with incident CVD with HR 1.14 (95% CI 1.12 - 1.16) per 1 standard deviation increase ( =1.0×10 ).

CONCLUSIONS: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.

CLINICAL PERSPECTIVE: We conducted a large-scale multi-ancestry time-to-event GWAS to identify genetic variants associated with CVD among people with T2D. Three variants were significantly associated with incident CVD in people with T2D: rs147138607 (intergenic variant between and ), rs11444867 (intergenic variant near ), and rs335407 (intergenic variant between and ). A polygenic score composed of known CAD variants identified in the general population was significantly associated with the risk of CVD in people with T2D. There are genetic risk factors specific to T2D that could at least partially explain the excess risk of CVD in people with T2D.In addition, we show that people with T2D have enrichment of known CAD association signals which could also explain the excess risk of CVD.

%B medRxiv %8 2023 Jul 28 %G eng %R 10.1101/2023.07.25.23293180 %0 Journal Article %J J Endocr Soc %D 2023 %T A Type 1 Diabetes Polygenic Score Is Not Associated With Prevalent Type 2 Diabetes in Large Population Studies. %A Srinivasan, Shylaja %A Wu, Peitao %A Mercader, Josep M %A Udler, Miriam S %A Porneala, Bianca C %A Bartz, Traci M %A Floyd, James S %A Sitlani, Colleen %A Guo, Xiquing %A Haessler, Jeffrey %A Kooperberg, Charles %A Liu, Jun %A Ahmad, Shahzad %A van Duijn, Cornelia %A Liu, Ching-Ti %A Goodarzi, Mark O %A Florez, Jose C %A Meigs, James B %A Rotter, Jerome I %A Rich, Stephen S %A Dupuis, Josée %A Leong, Aaron %X

CONTEXT: Both type 1 diabetes (T1D) and type 2 diabetes (T2D) have significant genetic contributions to risk and understanding their overlap can offer clinical insight.

OBJECTIVE: We examined whether a T1D polygenic score (PS) was associated with a diagnosis of T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.

METHODS: We constructed a T1D PS using 79 known single nucleotide polymorphisms associated with T1D risk. We analyzed 13 792 T2D cases and 14 169 controls from CHARGE cohorts to determine the association between the T1D PS and T2D prevalence. We validated findings in an independent sample of 2256 T2D cases and 27 052 controls from the Mass General Brigham Biobank (MGB Biobank). As secondary analyses in 5228 T2D cases from CHARGE, we used multivariable regression models to assess the association of the T1D PS with clinical outcomes associated with T1D.

RESULTS: The T1D PS was not associated with T2D both in CHARGE ( = .15) and in the MGB Biobank ( = .87). The partitioned human leukocyte antigens only PS was associated with T2D in CHARGE (OR 1.02 per 1 SD increase in PS, 95% CI 1.01-1.03, = .006) but not in the MGB Biobank. The T1D PS was weakly associated with insulin use (OR 1.007, 95% CI 1.001-1.012, = .03) in CHARGE T2D cases but not with other outcomes.

CONCLUSION: In large biobank samples, a common variant PS for T1D was not consistently associated with prevalent T2D. However, possible heterogeneity in T2D cannot be ruled out and future studies are needed do subphenotyping.

%B J Endocr Soc %V 7 %P bvad123 %8 2023 Oct 09 %G eng %N 11 %R 10.1210/jendso/bvad123 %0 Journal Article %J Circ Genom Precis Med %D 2023 %T Type 2 Diabetes Modifies the Association of CAD Genomic Risk Variants With Subclinical Atherosclerosis. %A Hasbani, Natalie R %A Westerman, Kenneth E %A Heon Kwak, Soo %A Chen, Han %A Li, Xihao %A DiCorpo, Daniel %A Wessel, Jennifer %A Bis, Joshua C %A Sarnowski, Chloe %A Wu, Peitao %A Bielak, Lawrence F %A Guo, Xiuqing %A Heard-Costa, Nancy %A Kinney, Gregory %A Mahaney, Michael C %A Montasser, May E %A Palmer, Nicholette D %A Raffield, Laura M %A Terry, James G %A Yanek, Lisa R %A Bon, Jessica %A Bowden, Donald W %A Brody, Jennifer A %A Duggirala, Ravindranath %A Jacobs, David R %A Kalyani, Rita R %A Lange, Leslie A %A Mitchell, Braxton D %A Smith, Jennifer A %A Taylor, Kent D %A Carson, April %A Curran, Joanne E %A Fornage, Myriam %A Freedman, Barry I %A Gabriel, Stacey %A Gibbs, Richard A %A Gupta, Namrata %A Kardia, Sharon L R %A Kral, Brian G %A Momin, Zeineen %A Newman, Anne B %A Post, Wendy S %A Viaud-Martinez, Karine A %A Young, Kendra A %A Becker, Lewis C %A Bertoni, Alain %A Blangero, John %A Carr, John J %A Pratte, Katherine %A Psaty, Bruce M %A Rich, Stephen S %A Wu, Joseph C %A Malhotra, Rajeev %A Peyser, Patricia A %A Morrison, Alanna C %A Vasan, Ramachandran S %A Lin, Xihong %A Rotter, Jerome I %A Meigs, James B %A Manning, Alisa K %A de Vries, Paul S %X

BACKGROUND: Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D.

METHODS: We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test.

RESULTS: Using a Bonferroni-corrected significance threshold of <1.6×10, we identified 3 genes (, , and ) associated with CAC and 2 genes ( and ) associated with carotid intima-media thickness and carotid plaque, respectively, through gene-based rare variant set analysis. Both and also had significantly different associations for CAC in T2D cases versus controls. No significant interaction tests were identified through the candidate single-variant analysis.

CONCLUSIONS: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC.

%B Circ Genom Precis Med %P e004176 %8 2023 Nov 28 %G eng %R 10.1161/CIRCGEN.123.004176 %0 Journal Article %J medRxiv %D 2023 %T Whole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles. %A Huffman, Jennifer E %A Nicolas, Jayna %A Hahn, Julie %A Heath, Adam S %A Raffield, Laura M %A Yanek, Lisa R %A Brody, Jennifer A %A Thibord, Florian %A Almasy, Laura %A Bartz, Traci M %A Bielak, Lawrence F %A Bowler, Russell P %A Carrasquilla, Germán D %A Chasman, Daniel I %A Chen, Ming-Huei %A Emmert, David B %A Ghanbari, Mohsen %A Haessle, Jeffery %A Hottenga, Jouke-Jan %A Kleber, Marcus E %A Le, Ngoc-Quynh %A Lee, Jiwon %A Lewis, Joshua P %A Li-Gao, Ruifang %A Luan, Jian'an %A Malmberg, Anni %A Mangino, Massimo %A Marioni, Riccardo E %A Martinez-Perez, Angel %A Pankratz, Nathan %A Polasek, Ozren %A Richmond, Anne %A Rodriguez, Benjamin At %A Rotter, Jerome I %A Steri, Maristella %A Suchon, Pierre %A Trompet, Stella %A Weiss, Stefan %A Zare, Marjan %A Auer, Paul %A Cho, Michael H %A Christofidou, Paraskevi %A Davies, Gail %A de Geus, Eco %A Deleuze, Jean-Francois %A Delgado, Graciela E %A Ekunwe, Lynette %A Faraday, Nauder %A Gögele, Martin %A Greinacher, Andreas %A He, Gao %A Howard, Tom %A Joshi, Peter K %A Kilpeläinen, Tuomas O %A Lahti, Jari %A Linneberg, Allan %A Naitza, Silvia %A Noordam, Raymond %A Paüls-Vergés, Ferran %A Rich, Stephen S %A Rosendaal, Frits R %A Rudan, Igor %A Ryan, Kathleen A %A Souto, Juan Carlos %A van Rooij, Frank Ja %A Wang, Heming %A Zhao, Wei %A Becker, Lewis C %A Beswick, Andrew %A Brown, Michael R %A Cade, Brian E %A Campbell, Harry %A Cho, Kelly %A Crapo, James D %A Curran, Joanne E %A de Maat, Moniek Pm %A Doyle, Margaret %A Elliott, Paul %A Floyd, James S %A Fuchsberger, Christian %A Grarup, Niels %A Guo, Xiuqing %A Harris, Sarah E %A Hou, Lifang %A Kolcic, Ivana %A Kooperberg, Charles %A Menni, Cristina %A Nauck, Matthias %A O'Connell, Jeffrey R %A Orrù, Valeria %A Psaty, Bruce M %A Räikkönen, Katri %A Smith, Jennifer A %A Soria, José Manuel %A Stott, David J %A van Hylckama Vlieg, Astrid %A Watkins, Hugh %A Willemsen, Gonneke %A Wilson, Peter %A Ben-Shlomo, Yoav %A Blangero, John %A Boomsma, Dorret %A Cox, Simon R %A Dehghan, Abbas %A Eriksson, Johan G %A Fiorillo, Edoardo %A Fornage, Myriam %A Hansen, Torben %A Hayward, Caroline %A Ikram, M Arfan %A Jukema, J Wouter %A Kardia, Sharon Lr %A Lange, Leslie A %A März, Winfried %A Mathias, Rasika A %A Mitchell, Braxton D %A Mook-Kanamori, Dennis O %A Morange, Pierre-Emmanuel %A Pedersen, Oluf %A Pramstaller, Peter P %A Redline, Susan %A Reiner, Alexander %A Ridker, Paul M %A Silverman, Edwin K %A Spector, Tim D %A Völker, Uwe %A Wareham, Nick %A Wilson, James F %A Yao, Jie %A Trégouët, David-Alexandre %A Johnson, Andrew D %A Wolberg, Alisa S %A de Vries, Paul S %A Sabater-Lleal, Maria %A Morrison, Alanna C %A Smith, Nicholas L %X

UNLABELLED: Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI's Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10% higher in African populations. Three ( , and signals contain predicted deleterious missense variants. Two loci, and , each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits ( ), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation.

KEY POINTS: Largest and most diverse genetic study of plasma fibrinogen identifies 54 regions (18 novel), housing 69 conditionally distinct variants (20 novel).Sufficient power achieved to identify signal driven by African population variant.Links to (1) liver enzyme, blood cell and lipid genetic signals, (2) liver regulatory elements, and (3) thrombotic and inflammatory disease.

%B medRxiv %8 2023 Jun 12 %G eng %R 10.1101/2023.06.07.23291095 %0 Journal Article %J Front Genet %D 2023 %T Whole genome sequence analysis of apparent treatment resistant hypertension status in participants from the Trans-Omics for Precision Medicine program. %A Armstrong, Nicole D %A Srinivasasainagendra, Vinodh %A Ammous, Farah %A Assimes, Themistocles L %A Beitelshees, Amber L %A Brody, Jennifer %A Cade, Brian E %A Ida Chen, Yii-Der %A Chen, Han %A de Vries, Paul S %A Floyd, James S %A Franceschini, Nora %A Guo, Xiuqing %A Hellwege, Jacklyn N %A House, John S %A Hwu, Chii-Min %A Kardia, Sharon L R %A Lange, Ethan M %A Lange, Leslie A %A McDonough, Caitrin W %A Montasser, May E %A O'Connell, Jeffrey R %A Shuey, Megan M %A Sun, Xiao %A Tanner, Rikki M %A Wang, Zhe %A Zhao, Wei %A Carson, April P %A Edwards, Todd L %A Kelly, Tanika N %A Kenny, Eimear E %A Kooperberg, Charles %A Loos, Ruth J F %A Morrison, Alanna C %A Motsinger-Reif, Alison %A Psaty, Bruce M %A Rao, Dabeeru C %A Redline, Susan %A Rich, Stephen S %A Rotter, Jerome I %A Smith, Jennifer A %A Smith, Albert V %A Irvin, Marguerite R %A Arnett, Donna K %X

Apparent treatment-resistant hypertension (aTRH) is characterized by the use of four or more antihypertensive (AHT) classes to achieve blood pressure (BP) control. In the current study, we conducted single-variant and gene-based analyses of aTRH among individuals from 12 Trans-Omics for Precision Medicine cohorts with whole-genome sequencing data. Cases were defined as individuals treated for hypertension (HTN) taking three different AHT classes, with average systolic BP ≥ 140 or diastolic BP ≥ 90 mmHg, or four or more medications regardless of BP ( = 1,705). A normotensive control group was defined as individuals with BP < 140/90 mmHg ( = 22,079), not on AHT medication. A second control group comprised individuals who were treatment responsive on one AHT medication with BP < 140/ 90 mmHg ( = 5,424). Logistic regression with kinship adjustment using the Scalable and Accurate Implementation of Generalized mixed models (SAIGE) was performed, adjusting for age, sex, and genetic ancestry. We assessed variants using SKAT-O in rare-variant analyses. Single-variant and gene-based tests were conducted in a pooled multi-ethnicity stratum, as well as self-reported ethnic/racial strata (European and African American). One variant in the known HTN locus, , was a top finding in the multi-ethnic analysis ( = 8.23E-07) for the normotensive control group [rs12476527, odds ratio (95% confidence interval) = 0.80 (0.74-0.88)]. This variant was replicated in the Vanderbilt University Medical Center's DNA repository data. Aggregate gene-based signals included the genes and . Additional work validating these loci in larger, more diverse populations, is warranted to determine whether these regions influence the pathobiology of aTRH.

%B Front Genet %V 14 %P 1278215 %8 2023 %G eng %R 10.3389/fgene.2023.1278215 %0 Journal Article %J medRxiv %D 2023 %T WHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE. %A Zhang, Xinruo %A Brody, Jennifer A %A Graff, Mariaelisa %A Highland, Heather M %A Chami, Nathalie %A Xu, Hanfei %A Wang, Zhe %A Ferrier, Kendra %A Chittoor, Geetha %A Josyula, Navya S %A Li, Xihao %A Li, Zilin %A Allison, Matthew A %A Becker, Diane M %A Bielak, Lawrence F %A Bis, Joshua C %A Boorgula, Meher Preethi %A Bowden, Donald W %A Broome, Jai G %A Buth, Erin J %A Carlson, Christopher S %A Chang, Kyong-Mi %A Chavan, Sameer %A Chiu, Yen-Feng %A Chuang, Lee-Ming %A Conomos, Matthew P %A DeMeo, Dawn L %A Du, Margaret %A Duggirala, Ravindranath %A Eng, Celeste %A Fohner, Alison E %A Freedman, Barry I %A Garrett, Melanie E %A Guo, Xiuqing %A Haiman, Chris %A Heavner, Benjamin D %A Hidalgo, Bertha %A Hixson, James E %A Ho, Yuk-Lam %A Hobbs, Brian D %A Hu, Donglei %A Hui, Qin %A Hwu, Chii-Min %A Jackson, Rebecca D %A Jain, Deepti %A Kalyani, Rita R %A Kardia, Sharon L R %A Kelly, Tanika N %A Lange, Ethan M %A LeNoir, Michael %A Li, Changwei %A Marchand, Loic Le %A McDonald, Merry-Lynn N %A McHugh, Caitlin P %A Morrison, Alanna C %A Naseri, Take %A O'Connell, Jeffrey %A O'Donnell, Christopher J %A Palmer, Nicholette D %A Pankow, James S %A Perry, James A %A Peters, Ulrike %A Preuss, Michael H %A Rao, D C %A Regan, Elizabeth A %A Reupena, Sefuiva M %A Roden, Dan M %A Rodriguez-Santana, Jose %A Sitlani, Colleen M %A Smith, Jennifer A %A Tiwari, Hemant K %A Vasan, Ramachandran S %A Wang, Zeyuan %A Weeks, Daniel E %A Wessel, Jennifer %A Wiggins, Kerri L %A Wilkens, Lynne R %A Wilson, Peter W F %A Yanek, Lisa R %A Yoneda, Zachary T %A Zhao, Wei %A Zöllner, Sebastian %A Arnett, Donna K %A Ashley-Koch, Allison E %A Barnes, Kathleen C %A Blangero, John %A Boerwinkle, Eric %A Burchard, Esteban G %A Carson, April P %A Chasman, Daniel I %A Chen, Yii-Der Ida %A Curran, Joanne E %A Fornage, Myriam %A Gordeuk, Victor R %A He, Jiang %A Heckbert, Susan R %A Hou, Lifang %A Irvin, Marguerite R %A Kooperberg, Charles %A Minster, Ryan L %A Mitchell, Braxton D %A Nouraie, Mehdi %A Psaty, Bruce M %A Raffield, Laura M %A Reiner, Alexander P %A Rich, Stephen S %A Rotter, Jerome I %A Shoemaker, M Benjamin %A Smith, Nicholas L %A Taylor, Kent D %A Telen, Marilyn J %A Weiss, Scott T %A Zhang, Yingze %A Costa, Nancy Heard- %A Sun, Yan V %A Lin, Xihong %A Cupples, L Adrienne %A Lange, Leslie A %A Liu, Ching-Ti %A Loos, Ruth J F %A North, Kari E %A Justice, Anne E %X

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals ( < 5 × 10 ). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the and loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

%B medRxiv %8 2023 Aug 22 %G eng %R 10.1101/2023.08.21.23293271 %0 Journal Article %J bioRxiv %D 2023 %T Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium. %A Jiang, Min-Zhi %A Gaynor, Sheila M %A Li, Xihao %A Van Buren, Eric %A Stilp, Adrienne %A Buth, Erin %A Wang, Fei Fei %A Manansala, Regina %A Gogarten, Stephanie M %A Li, Zilin %A Polfus, Linda M %A Salimi, Shabnam %A Bis, Joshua C %A Pankratz, Nathan %A Yanek, Lisa R %A Durda, Peter %A Tracy, Russell P %A Rich, Stephen S %A Rotter, Jerome I %A Mitchell, Braxton D %A Lewis, Joshua P %A Psaty, Bruce M %A Pratte, Katherine A %A Silverman, Edwin K %A Kaplan, Robert C %A Avery, Christy %A North, Kari %A Mathias, Rasika A %A Faraday, Nauder %A Lin, Honghuang %A Wang, Biqi %A Carson, April P %A Norwood, Arnita F %A Gibbs, Richard A %A Kooperberg, Charles %A Lundin, Jessica %A Peters, Ulrike %A Dupuis, Josée %A Hou, Lifang %A Fornage, Myriam %A Benjamin, Emelia J %A Reiner, Alexander P %A Bowler, Russell P %A Lin, Xihong %A Auer, Paul L %A Raffield, Laura M %X

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

%B bioRxiv %8 2023 Sep 12 %G eng %R 10.1101/2023.09.10.555215 %0 Journal Article %J medRxiv %D 2024 %T Association analysis of mitochondrial DNA heteroplasmic variants: methods and application. %A Sun, Xianbang %A Bulekova, Katia %A Yang, Jian %A Lai, Meng %A Pitsillides, Achilleas N %A Liu, Xue %A Zhang, Yuankai %A Guo, Xiuqing %A Yong, Qian %A Raffield, Laura M %A Rotter, Jerome I %A Rich, Stephen S %A Abecasis, Goncalo %A Carson, April P %A Vasan, Ramachandran S %A Bis, Joshua C %A Psaty, Bruce M %A Boerwinkle, Eric %A Fitzpatrick, Annette L %A Satizabal, Claudia L %A Arking, Dan E %A Ding, Jun %A Levy, Daniel %A Liu, Chunyu %X

We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at α=0.001. Notably, when 5% or more heteroplasmic variants within a target region were linked to an outcome, burden-extension tests (including the adaptive burden test, variable threshold burden test, and z-score weighting burden test) outperformed the sequence kernel association test (SKAT) and the original burden test. Applying this framework, we conducted association analyses on whole-blood derived heteroplasmy in 17,507 individuals of African and European ancestries (31% of African Ancestry, mean age of 62, with 58% women) with whole genome sequencing data. We performed both cohort- and ancestry-specific association analyses, followed by meta-analysis on bothpooled samples and within each ancestry group. Our results suggest that mtDNA-Enco ded genes/regions are likely to exhibit varying rates in somatic aging, with the notably strong associations observed between heteroplasmy in the and genes ( <0.001) and advance aging by the Original Burden test. In contrast, SKAT identified significant associations ( <0.001) between diabetes and the aggregated effects of heteroplasmy in several protein-coding genes. Further research is warranted to validate these findings. In summary, our proposed statistical framework represents a valuable tool for facilitating association testing of heteroplasmy with disease traits in large human populations.

%B medRxiv %8 2024 Jan 13 %G eng %R 10.1101/2024.01.12.24301233 %0 Journal Article %J JAMA Cardiol %D 2024 %T Familial Hypercholesterolemia Variant and Cardiovascular Risk in Individuals With Elevated Cholesterol. %A Zhang, Yiyi %A Dron, Jacqueline S %A Bellows, Brandon K %A Khera, Amit V %A Liu, Junxiu %A Balte, Pallavi P %A Oelsner, Elizabeth C %A Amr, Sami Samir %A Lebo, Matthew S %A Nagy, Anna %A Peloso, Gina M %A Natarajan, Pradeep %A Rotter, Jerome I %A Willer, Cristen %A Boerwinkle, Eric %A Ballantyne, Christie M %A Lutsey, Pamela L %A Fornage, Myriam %A Lloyd-Jones, Donald M %A Hou, Lifang %A Psaty, Bruce M %A Bis, Joshua C %A Floyd, James S %A Vasan, Ramachandran S %A Heard-Costa, Nancy L %A Carson, April P %A Hall, Michael E %A Rich, Stephen S %A Guo, Xiuqing %A Kazi, Dhruv S %A de Ferranti, Sarah D %A Moran, Andrew E %X

IMPORTANCE: Familial hypercholesterolemia (FH) is a genetic disorder that often results in severely high low-density lipoprotein cholesterol (LDL-C) and high risk of premature coronary heart disease (CHD). However, the impact of FH variants on CHD risk among individuals with moderately elevated LDL-C is not well quantified.

OBJECTIVE: To assess CHD risk associated with FH variants among individuals with moderately (130-189 mg/dL) and severely (≥190 mg/dL) elevated LDL-C and to quantify excess CHD deaths attributable to FH variants in US adults.

DESIGN, SETTING, AND PARTICIPANTS: A total of 21 426 individuals without preexisting CHD from 6 US cohort studies (Atherosclerosis Risk in Communities study, Coronary Artery Risk Development in Young Adults study, Cardiovascular Health Study, Framingham Heart Study Offspring cohort, Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis) were included, 63 of whom had an FH variant. Data were collected from 1971 to 2018, and the median (IQR) follow-up was 18 (13-28) years. Data were analyzed from March to May 2023.

EXPOSURES: LDL-C, cumulative past LDL-C, FH variant status.

MAIN OUTCOMES AND MEASURES: Cox proportional hazards models estimated associations between FH variants and incident CHD. The Cardiovascular Disease Policy Model projected excess CHD deaths associated with FH variants in US adults.

RESULTS: Of the 21 426 individuals without preexisting CHD (mean [SD] age 52.1 [15.5] years; 12 041 [56.2%] female), an FH variant was found in 22 individuals with moderately elevated LDL-C (0.3%) and in 33 individuals with severely elevated LDL-C (2.5%). The adjusted hazard ratios for incident CHD comparing those with and without FH variants were 2.9 (95% CI, 1.4-6.0) and 2.6 (95% CI, 1.4-4.9) among individuals with moderately and severely elevated LDL-C, respectively. The association between FH variants and CHD was slightly attenuated when further adjusting for baseline LDL-C level, whereas the association was no longer statistically significant after adjusting for cumulative past LDL-C exposure. Among US adults 20 years and older with no history of CHD and LDL-C 130 mg/dL or higher, more than 417 000 carry an FH variant and were projected to experience more than 12 000 excess CHD deaths in those with moderately elevated LDL-C and 15 000 in those with severely elevated LDL-C compared with individuals without an FH variant.

CONCLUSIONS AND RELEVANCE: In this pooled cohort study, the presence of FH variants was associated with a 2-fold higher CHD risk, even when LDL-C was only moderately elevated. The increased CHD risk appeared to be largely explained by the higher cumulative LDL-C exposure in individuals with an FH variant compared to those without. Further research is needed to assess the value of adding genetic testing to traditional phenotypic FH screening.

%B JAMA Cardiol %8 2024 Jan 31 %G eng %R 10.1001/jamacardio.2023.5366 %0 Journal Article %J Nature %D 2024 %T Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. %A Suzuki, Ken %A Hatzikotoulas, Konstantinos %A Southam, Lorraine %A Taylor, Henry J %A Yin, Xianyong %A Lorenz, Kim M %A Mandla, Ravi %A Huerta-Chagoya, Alicia %A Melloni, Giorgio E M %A Kanoni, Stavroula %A Rayner, Nigel W %A Bocher, Ozvan %A Arruda, Ana Luiza %A Sonehara, Kyuto %A Namba, Shinichi %A Lee, Simon S K %A Preuss, Michael H %A Petty, Lauren E %A Schroeder, Philip %A Vanderwerff, Brett %A Kals, Mart %A Bragg, Fiona %A Lin, Kuang %A Guo, Xiuqing %A Zhang, Weihua %A Yao, Jie %A Kim, Young Jin %A Graff, Mariaelisa %A Takeuchi, Fumihiko %A Nano, Jana %A Lamri, Amel %A Nakatochi, Masahiro %A Moon, Sanghoon %A Scott, Robert A %A Cook, James P %A Lee, Jung-Jin %A Pan, Ian %A Taliun, Daniel %A Parra, Esteban J %A Chai, Jin-Fang %A Bielak, Lawrence F %A Tabara, Yasuharu %A Hai, Yang %A Thorleifsson, Gudmar %A Grarup, Niels %A Sofer, Tamar %A Wuttke, Matthias %A Sarnowski, Chloe %A Gieger, Christian %A Nousome, Darryl %A Trompet, Stella %A Kwak, Soo-Heon %A Long, Jirong %A Sun, Meng %A Tong, Lin %A Chen, Wei-Min %A Nongmaithem, Suraj S %A Noordam, Raymond %A Lim, Victor J Y %A Tam, Claudia H T %A Joo, Yoonjung Yoonie %A Chen, Chien-Hsiun %A Raffield, Laura M %A Prins, Bram Peter %A Nicolas, Aude %A Yanek, Lisa R %A Chen, Guanjie %A Brody, Jennifer A %A Kabagambe, Edmond %A An, Ping %A Xiang, Anny H %A Choi, Hyeok Sun %A Cade, Brian E %A Tan, Jingyi %A Broadaway, K Alaine %A Williamson, Alice %A Kamali, Zoha %A Cui, Jinrui %A Thangam, Manonanthini %A Adair, Linda S %A Adeyemo, Adebowale %A Aguilar-Salinas, Carlos A %A Ahluwalia, Tarunveer S %A Anand, Sonia S %A Bertoni, Alain %A Bork-Jensen, Jette %A Brandslund, Ivan %A Buchanan, Thomas A %A Burant, Charles F %A Butterworth, Adam S %A Canouil, Mickaël %A Chan, Juliana C N %A Chang, Li-Ching %A Chee, Miao-Li %A Chen, Ji %A Chen, Shyh-Huei %A Chen, Yuan-Tsong %A Chen, Zhengming %A Chuang, Lee-Ming %A Cushman, Mary %A Danesh, John %A Das, Swapan K %A de Silva, H Janaka %A Dedoussis, George %A Dimitrov, Latchezar %A Doumatey, Ayo P %A Du, Shufa %A Duan, Qing %A Eckardt, Kai-Uwe %A Emery, Leslie S %A Evans, Daniel S %A Evans, Michele K %A Fischer, Krista %A Floyd, James S %A Ford, Ian %A Franco, Oscar H %A Frayling, Timothy M %A Freedman, Barry I %A Genter, Pauline %A Gerstein, Hertzel C %A Giedraitis, Vilmantas %A González-Villalpando, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Gordon-Larsen, Penny %A Gross, Myron %A Guare, Lindsay A %A Hackinger, Sophie %A Hakaste, Liisa %A Han, Sohee %A Hattersley, Andrew T %A Herder, Christian %A Horikoshi, Momoko %A Howard, Annie-Green %A Hsueh, Willa %A Huang, Mengna %A Huang, Wei %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Hwu, Chii-Min %A Ichihara, Sahoko %A Ikram, Mohammad Arfan %A Ingelsson, Martin %A Islam, Md Tariqul %A Isono, Masato %A Jang, Hye-Mi %A Jasmine, Farzana %A Jiang, Guozhi %A Jonas, Jost B %A Jørgensen, Torben %A Kamanu, Frederick K %A Kandeel, Fouad R %A Kasturiratne, Anuradhani %A Katsuya, Tomohiro %A Kaur, Varinderpal %A Kawaguchi, Takahisa %A Keaton, Jacob M %A Kho, Abel N %A Khor, Chiea-Chuen %A Kibriya, Muhammad G %A Kim, Duk-Hwan %A Kronenberg, Florian %A Kuusisto, Johanna %A Läll, Kristi %A Lange, Leslie A %A Lee, Kyung Min %A Lee, Myung-Shik %A Lee, Nanette R %A Leong, Aaron %A Li, Liming %A Li, Yun %A Li-Gao, Ruifang %A Ligthart, Symen %A Lindgren, Cecilia M %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Locke, Adam E %A Louie, Tin %A Luan, Jian'an %A Luk, Andrea O %A Luo, Xi %A Lv, Jun %A Lynch, Julie A %A Lyssenko, Valeriya %A Maeda, Shiro %A Mamakou, Vasiliki %A Mansuri, Sohail Rafik %A Matsuda, Koichi %A Meitinger, Thomas %A Melander, Olle %A Metspalu, Andres %A Mo, Huan %A Morris, Andrew D %A Moura, Filipe A %A Nadler, Jerry L %A Nalls, Michael A %A Nayak, Uma %A Ntalla, Ioanna %A Okada, Yukinori %A Orozco, Lorena %A Patel, Sanjay R %A Patil, Snehal %A Pei, Pei %A Pereira, Mark A %A Peters, Annette %A Pirie, Fraser J %A Polikowsky, Hannah G %A Porneala, Bianca %A Prasad, Gauri %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Roden, Michael %A Rohde, Rebecca %A Roll, Katheryn %A Sabanayagam, Charumathi %A Sandow, Kevin %A Sankareswaran, Alagu %A Sattar, Naveed %A Schönherr, Sebastian %A Shahriar, Mohammad %A Shen, Botong %A Shi, Jinxiu %A Shin, Dong Mun %A Shojima, Nobuhiro %A Smith, Jennifer A %A So, Wing Yee %A Stančáková, Alena %A Steinthorsdottir, Valgerdur %A Stilp, Adrienne M %A Strauch, Konstantin %A Taylor, Kent D %A Thorand, Barbara %A Thorsteinsdottir, Unnur %A Tomlinson, Brian %A Tran, Tam C %A Tsai, Fuu-Jen %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A Valladares-Salgado, Adan %A van Dam, Rob M %A van Klinken, Jan B %A Varma, Rohit %A Wacher-Rodarte, Niels %A Wheeler, Eleanor %A Wickremasinghe, Ananda R %A van Dijk, Ko Willems %A Witte, Daniel R %A Yajnik, Chittaranjan S %A Yamamoto, Ken %A Yamamoto, Kenichi %A Yoon, Kyungheon %A Yu, Canqing %A Yuan, Jian-Min %A Yusuf, Salim %A Zawistowski, Matthew %A Zhang, Liang %A Zheng, Wei %A Raffel, Leslie J %A Igase, Michiya %A Ipp, Eli %A Redline, Susan %A Cho, Yoon Shin %A Lind, Lars %A Province, Michael A %A Fornage, Myriam %A Hanis, Craig L %A Ingelsson, Erik %A Zonderman, Alan B %A Psaty, Bruce M %A Wang, Ya-Xing %A Rotimi, Charles N %A Becker, Diane M %A Matsuda, Fumihiko %A Liu, Yongmei %A Yokota, Mitsuhiro %A Kardia, Sharon L R %A Peyser, Patricia A %A Pankow, James S %A Engert, James C %A Bonnefond, Amélie %A Froguel, Philippe %A Wilson, James G %A Sheu, Wayne H H %A Wu, Jer-Yuarn %A Hayes, M Geoffrey %A Ma, Ronald C W %A Wong, Tien-Yin %A Mook-Kanamori, Dennis O %A Tuomi, Tiinamaija %A Chandak, Giriraj R %A Collins, Francis S %A Bharadwaj, Dwaipayan %A Paré, Guillaume %A Sale, Michèle M %A Ahsan, Habibul %A Motala, Ayesha A %A Shu, Xiao-Ou %A Park, Kyong-Soo %A Jukema, J Wouter %A Cruz, Miguel %A Chen, Yii-Der Ida %A Rich, Stephen S %A McKean-Cowdin, Roberta %A Grallert, Harald %A Cheng, Ching-Yu %A Ghanbari, Mohsen %A Tai, E-Shyong %A Dupuis, Josée %A Kato, Norihiro %A Laakso, Markku %A Köttgen, Anna %A Koh, Woon-Puay %A Bowden, Donald W %A Palmer, Colin N A %A Kooner, Jaspal S %A Kooperberg, Charles %A Liu, Simin %A North, Kari E %A Saleheen, Danish %A Hansen, Torben %A Pedersen, Oluf %A Wareham, Nicholas J %A Lee, Juyoung %A Kim, Bong-Jo %A Millwood, Iona Y %A Walters, Robin G %A Stefansson, Kari %A Ahlqvist, Emma %A Goodarzi, Mark O %A Mohlke, Karen L %A Langenberg, Claudia %A Haiman, Christopher A %A Loos, Ruth J F %A Florez, Jose C %A Rader, Daniel J %A Ritchie, Marylyn D %A Zöllner, Sebastian %A Mägi, Reedik %A Marston, Nicholas A %A Ruff, Christian T %A van Heel, David A %A Finer, Sarah %A Denny, Joshua C %A Yamauchi, Toshimasa %A Kadowaki, Takashi %A Chambers, John C %A Ng, Maggie C Y %A Sim, Xueling %A Below, Jennifer E %A Tsao, Philip S %A Chang, Kyong-Mi %A McCarthy, Mark I %A Meigs, James B %A Mahajan, Anubha %A Spracklen, Cassandra N %A Mercader, Josep M %A Boehnke, Michael %A Rotter, Jerome I %A Vujkovic, Marijana %A Voight, Benjamin F %A Morris, Andrew P %A Zeggini, Eleftheria %X

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

%B Nature %8 2024 Feb 19 %G eng %R 10.1038/s41586-024-07019-6