%0 Journal Article %J JAMA %D 2009 %T Genetic variants associated with cardiac structure and function: a meta-analysis and replication of genome-wide association data. %A Vasan, Ramachandran S %A Glazer, Nicole L %A Felix, Janine F %A Lieb, Wolfgang %A Wild, Philipp S %A Felix, Stephan B %A Watzinger, Norbert %A Larson, Martin G %A Smith, Nicholas L %A Dehghan, Abbas %A Grosshennig, Anika %A Schillert, Arne %A Teumer, Alexander %A Schmidt, Reinhold %A Kathiresan, Sekar %A Lumley, Thomas %A Aulchenko, Yurii S %A König, Inke R %A Zeller, Tanja %A Homuth, Georg %A Struchalin, Maksim %A Aragam, Jayashri %A Bis, Joshua C %A Rivadeneira, Fernando %A Erdmann, Jeanette %A Schnabel, Renate B %A Dörr, Marcus %A Zweiker, Robert %A Lind, Lars %A Rodeheffer, Richard J %A Greiser, Karin Halina %A Levy, Daniel %A Haritunians, Talin %A Deckers, Jaap W %A Stritzke, Jan %A Lackner, Karl J %A Völker, Uwe %A Ingelsson, Erik %A Kullo, Iftikhar %A Haerting, Johannes %A O'Donnell, Christopher J %A Heckbert, Susan R %A Stricker, Bruno H %A Ziegler, Andreas %A Reffelmann, Thorsten %A Redfield, Margaret M %A Werdan, Karl %A Mitchell, Gary F %A Rice, Kenneth %A Arnett, Donna K %A Hofman, Albert %A Gottdiener, John S %A Uitterlinden, André G %A Meitinger, Thomas %A Blettner, Maria %A Friedrich, Nele %A Wang, Thomas J %A Psaty, Bruce M %A van Duijn, Cornelia M %A Wichmann, H-Erich %A Munzel, Thomas F %A Kroemer, Heyo K %A Benjamin, Emelia J %A Rotter, Jerome I %A Witteman, Jacqueline C %A Schunkert, Heribert %A Schmidt, Helena %A Völzke, Henry %A Blankenberg, Stefan %K Adult %K Aged %K Aged, 80 and over %K Aorta %K Cardiovascular Diseases %K Echocardiography %K European Continental Ancestry Group %K Female %K Genome-Wide Association Study %K Genotype %K Heart Atria %K Heart Ventricles %K Humans %K Male %K Middle Aged %K Organ Size %K Phenotype %K Polymorphism, Single Nucleotide %K Risk Factors %K Ventricular Dysfunction, Left %K Ventricular Function, Left %X

CONTEXT: Echocardiographic measures of left ventricular (LV) structure and function are heritable phenotypes of cardiovascular disease.

OBJECTIVE: To identify common genetic variants associated with cardiac structure and function by conducting a meta-analysis of genome-wide association data in 5 population-based cohort studies (stage 1) with replication (stage 2) in 2 other community-based samples.

DESIGN, SETTING, AND PARTICIPANTS: Within each of 5 community-based cohorts comprising the EchoGen consortium (stage 1; n = 12 612 individuals of European ancestry; 55% women, aged 26-95 years; examinations between 1978-2008), we estimated the association between approximately 2.5 million single-nucleotide polymorphisms (SNPs; imputed to the HapMap CEU panel) and echocardiographic traits. In stage 2, SNPs significantly associated with traits in stage 1 were tested for association in 2 other cohorts (n = 4094 people of European ancestry). Using a prespecified P value threshold of 5 x 10(-7) to indicate genome-wide significance, we performed an inverse variance-weighted fixed-effects meta-analysis of genome-wide association data from each cohort.

MAIN OUTCOME MEASURES: Echocardiographic traits: LV mass, internal dimensions, wall thickness, systolic dysfunction, aortic root, and left atrial size.

RESULTS: In stage 1, 16 genetic loci were associated with 5 echocardiographic traits: 1 each with LV internal dimensions and systolic dysfunction, 3 each with LV mass and wall thickness, and 8 with aortic root size. In stage 2, 5 loci replicated (6q22 locus associated with LV diastolic dimensions, explaining <1% of trait variance; 5q23, 12p12, 12q14, and 17p13 associated with aortic root size, explaining 1%-3% of trait variance).

CONCLUSIONS: We identified 5 genetic loci harboring common variants that were associated with variation in LV diastolic dimensions and aortic root size, but such findings explained a very small proportion of variance. Further studies are required to replicate these findings, identify the causal variants at or near these loci, characterize their functional significance, and determine whether they are related to overt cardiovascular disease.

%B JAMA %V 302 %P 168-78 %8 2009 Jul 08 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/19584346?dopt=Abstract %R 10.1001/jama.2009.978-a %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 Hum Mol Genet %D 2012 %T Genome-wide meta-analysis points to CTC1 and ZNF676 as genes regulating telomere homeostasis in humans. %A Mangino, Massimo %A Hwang, Shih-Jen %A Spector, Timothy D %A Hunt, Steven C %A Kimura, Masayuki %A Fitzpatrick, Annette L %A Christiansen, Lene %A Petersen, Inge %A Elbers, Clara C %A Harris, Tamara %A Chen, Wei %A Srinivasan, Sathanur R %A Kark, Jeremy D %A Benetos, Athanase %A El Shamieh, Said %A Visvikis-Siest, Sophie %A Christensen, Kaare %A Berenson, Gerald S %A Valdes, Ana M %A Viñuela, Ana %A Garcia, Melissa %A Arnett, Donna K %A Broeckel, Ulrich %A Province, Michael A %A Pankow, James S %A Kammerer, Candace %A Liu, Yongmei %A Nalls, Michael %A Tishkoff, Sarah %A Thomas, Fridtjof %A Ziv, Elad %A Psaty, Bruce M %A Bis, Joshua C %A Rotter, Jerome I %A Taylor, Kent D %A Smith, Erin %A Schork, Nicholas J %A Levy, Daniel %A Aviv, Abraham %K Genome-Wide Association Study %K Humans %K Kruppel-Like Transcription Factors %K Telomere %K Telomere Homeostasis %K Telomere-Binding Proteins %X

Leukocyte telomere length (LTL) is associated with a number of common age-related diseases and is a heritable trait. Previous genome-wide association studies (GWASs) identified two loci on chromosomes 3q26.2 (TERC) and 10q24.33 (OBFC1) that are associated with the inter-individual LTL variation. We performed a meta-analysis of 9190 individuals from six independent GWAS and validated our findings in 2226 individuals from four additional studies. We confirmed previously reported associations with OBFC1 (rs9419958 P = 9.1 × 10(-11)) and with the telomerase RNA component TERC (rs1317082, P = 1.1 × 10(-8)). We also identified two novel genomic regions associated with LTL variation that map near a conserved telomere maintenance complex component 1 (CTC1; rs3027234, P = 3.6 × 10(-8)) on chromosome17p13.1 and zinc finger protein 676 (ZNF676; rs412658, P = 3.3 × 10(-8)) on 19p12. The minor allele of rs3027234 was associated with both shorter LTL and lower expression of CTC1. Our findings are consistent with the recent observations that point mutations in CTC1 cause short telomeres in both Arabidopsis and humans affected by a rare Mendelian syndrome. Overall, our results provide novel insights into the genetic architecture of inter-individual LTL variation in the general population.

%B Hum Mol Genet %V 21 %P 5385-94 %8 2012 Dec 15 %G eng %N 24 %1 http://www.ncbi.nlm.nih.gov/pubmed/23001564?dopt=Abstract %R 10.1093/hmg/dds382 %0 Journal Article %J Circ Cardiovasc Genet %D 2013 %T Genome-wide association study of cardiac structure and systolic function in African Americans: the Candidate Gene Association Resource (CARe) study. %A Fox, Ervin R %A Musani, Solomon K %A Barbalic, Maja %A Lin, Honghuang %A Yu, Bing %A Ogunyankin, Kofo O %A Smith, Nicholas L %A Kutlar, Abdullah %A Glazer, Nicole L %A Post, Wendy S %A Paltoo, Dina N %A Dries, Daniel L %A Farlow, Deborah N %A Duarte, Christine W %A Kardia, Sharon L %A Meyers, Kristin J %A Sun, Yan V %A Arnett, Donna K %A Patki, Amit A %A Sha, Jin %A Cui, Xiangqui %A Samdarshi, Tandaw E %A Penman, Alan D %A Bibbins-Domingo, Kirsten %A Bůzková, Petra %A Benjamin, Emelia J %A Bluemke, David A %A Morrison, Alanna C %A Heiss, Gerardo %A Carr, J Jeffrey %A Tracy, Russell P %A Mosley, Thomas H %A Taylor, Herman A %A Psaty, Bruce M %A Heckbert, Susan R %A Cappola, Thomas P %A Vasan, Ramachandran S %K African Americans %K Aged %K Cohort Studies %K Diastole %K Echocardiography %K European Continental Ancestry Group %K Female %K Genome-Wide Association Study %K Genotype %K Heart %K Humans %K Male %K Middle Aged %K Phenotype %K Polymorphism, Single Nucleotide %K Systole %X

BACKGROUND: Using data from 4 community-based cohorts of African Americans, we tested the association between genome-wide markers (single-nucleotide polymorphisms) and cardiac phenotypes in the Candidate-gene Association Resource study.

METHODS AND RESULTS: Among 6765 African Americans, we related age, sex, height, and weight-adjusted residuals for 9 cardiac phenotypes (assessed by echocardiogram or magnetic resonance imaging) to 2.5 million single-nucleotide polymorphisms genotyped using Genome-wide Affymetrix Human SNP Array 6.0 (Affy6.0) and the remainder imputed. Within the cohort, genome-wide association analysis was conducted, followed by meta-analysis across cohorts using inverse variance weights (genome-wide significance threshold=4.0 ×10(-7)). Supplementary pathway analysis was performed. We attempted replication in 3 smaller cohorts of African ancestry and tested lookups in 1 consortium of European ancestry (EchoGEN). Across the 9 phenotypes, variants in 4 genetic loci reached genome-wide significance: rs4552931 in UBE2V2 (P=1.43×10(-7)) for left ventricular mass, rs7213314 in WIPI1 (P=1.68×10(-7)) for left ventricular internal diastolic diameter, rs1571099 in PPAPDC1A (P=2.57×10(-8)) for interventricular septal wall thickness, and rs9530176 in KLF5 (P=4.02×10(-7)) for ejection fraction. Associated variants were enriched in 3 signaling pathways involved in cardiac remodeling. None of the 4 loci replicated in cohorts of African ancestry was confirmed in lookups in EchoGEN.

CONCLUSIONS: In the largest genome-wide association study of cardiac structure and function to date in African Americans, we identified 4 genetic loci related to left ventricular mass, interventricular septal wall thickness, left ventricular internal diastolic diameter, and ejection fraction, which reached genome-wide significance. Replication results suggest that these loci may be unique to individuals of African ancestry. Additional large-scale studies are warranted for these complex phenotypes.

%B Circ Cardiovasc Genet %V 6 %P 37-46 %8 2013 Feb %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/23275298?dopt=Abstract %R 10.1161/CIRCGENETICS.111.962365 %0 Journal Article %J Am J Clin Nutr %D 2013 %T Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake. %A Tanaka, Toshiko %A Ngwa, Julius S %A van Rooij, Frank J A %A Zillikens, M Carola %A Wojczynski, Mary K %A Frazier-Wood, Alexis C %A Houston, Denise K %A Kanoni, Stavroula %A Lemaitre, Rozenn N %A Luan, Jian'an %A Mikkilä, Vera %A Renstrom, Frida %A Sonestedt, Emily %A Zhao, Jing Hua %A Chu, Audrey Y %A Qi, Lu %A Chasman, Daniel I %A de Oliveira Otto, Marcia C %A Dhurandhar, Emily J %A Feitosa, Mary F %A Johansson, Ingegerd %A Khaw, Kay-Tee %A Lohman, Kurt K %A Manichaikul, Ani %A McKeown, Nicola M %A Mozaffarian, Dariush %A Singleton, Andrew %A Stirrups, Kathleen %A Viikari, Jorma %A Ye, Zheng %A Bandinelli, Stefania %A Barroso, Inês %A Deloukas, Panos %A Forouhi, Nita G %A Hofman, Albert %A Liu, Yongmei %A Lyytikäinen, Leo-Pekka %A North, Kari E %A Dimitriou, Maria %A Hallmans, Göran %A Kähönen, Mika %A Langenberg, Claudia %A Ordovas, Jose M %A Uitterlinden, André G %A Hu, Frank B %A Kalafati, Ioanna-Panagiota %A Raitakari, Olli %A Franco, Oscar H %A Johnson, Andrew %A Emilsson, Valur %A Schrack, Jennifer A %A Semba, Richard D %A Siscovick, David S %A Arnett, Donna K %A Borecki, Ingrid B %A Franks, Paul W %A Kritchevsky, Stephen B %A Lehtimäki, Terho %A Loos, Ruth J F %A Orho-Melander, Marju %A Rotter, Jerome I %A Wareham, Nicholas J %A Witteman, Jacqueline C M %A Ferrucci, Luigi %A Dedoussis, George %A Cupples, L Adrienne %A Nettleton, Jennifer A %K Alleles %K Atherosclerosis %K Body Mass Index %K Dietary Carbohydrates %K Dietary Fats %K Dietary Proteins %K Energy Intake %K European Continental Ancestry Group %K Fibroblast Growth Factors %K Follow-Up Studies %K Gene-Environment Interaction %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genotype %K Humans %K Life Style %K Obesity %K Polymorphism, Single Nucleotide %K Prospective Studies %K Quantitative Trait Loci %K Surveys and Questionnaires %X

BACKGROUND: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.

OBJECTIVE: The objective of the study was to identify common genetic variants that are associated with macronutrient intake.

DESIGN: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10(-6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data.

RESULTS: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10(-8)) and lower fat (β ± SE: -0.21 ± 0.04%; P = 1.57 × 10(-9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)-increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10(-10)), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10(-7)).

CONCLUSION: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

%B Am J Clin Nutr %V 97 %P 1395-402 %8 2013 Jun %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/23636237?dopt=Abstract %R 10.3945/ajcn.112.052183 %0 Journal Article %J Nat Genet %D 2013 %T A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry. %A Monda, Keri L %A Chen, Gary K %A Taylor, Kira C %A Palmer, Cameron %A Edwards, Todd L %A Lange, Leslie A %A Ng, Maggie C Y %A Adeyemo, Adebowale A %A Allison, Matthew A %A Bielak, Lawrence F %A Chen, Guanjie %A Graff, Mariaelisa %A Irvin, Marguerite R %A Rhie, Suhn K %A Li, Guo %A Liu, Yongmei %A Liu, Youfang %A Lu, Yingchang %A Nalls, Michael A %A Sun, Yan V %A Wojczynski, Mary K %A Yanek, Lisa R %A Aldrich, Melinda C %A Ademola, Adeyinka %A Amos, Christopher I %A Bandera, Elisa V %A Bock, Cathryn H %A Britton, Angela %A Broeckel, Ulrich %A Cai, Quiyin %A Caporaso, Neil E %A Carlson, Chris S %A Carpten, John %A Casey, Graham %A Chen, Wei-Min %A Chen, Fang %A Chen, Yii-der I %A Chiang, Charleston W K %A Coetzee, Gerhard A %A Demerath, Ellen %A Deming-Halverson, Sandra L %A Driver, Ryan W %A Dubbert, Patricia %A Feitosa, Mary F %A Feng, Ye %A Freedman, Barry I %A Gillanders, Elizabeth M %A Gottesman, Omri %A Guo, Xiuqing %A Haritunians, Talin %A Harris, Tamara %A Harris, Curtis C %A Hennis, Anselm J M %A Hernandez, Dena G %A McNeill, Lorna H %A Howard, Timothy D %A Howard, Barbara V %A Howard, Virginia J %A Johnson, Karen C %A Kang, Sun J %A Keating, Brendan J %A Kolb, Suzanne %A Kuller, Lewis H %A Kutlar, Abdullah %A Langefeld, Carl D %A Lettre, Guillaume %A Lohman, Kurt %A Lotay, Vaneet %A Lyon, Helen %A Manson, JoAnn E %A Maixner, William %A Meng, Yan A %A Monroe, Kristine R %A Morhason-Bello, Imran %A Murphy, Adam B %A Mychaleckyj, Josyf C %A Nadukuru, Rajiv %A Nathanson, Katherine L %A Nayak, Uma %A N'diaye, Amidou %A Nemesure, Barbara %A Wu, Suh-Yuh %A Leske, M Cristina %A Neslund-Dudas, Christine %A Neuhouser, Marian %A Nyante, Sarah %A Ochs-Balcom, Heather %A Ogunniyi, Adesola %A Ogundiran, Temidayo O %A Ojengbede, Oladosu %A Olopade, Olufunmilayo I %A Palmer, Julie R %A Ruiz-Narvaez, Edward A %A Palmer, Nicholette D %A Press, Michael F %A Rampersaud, Evandine %A Rasmussen-Torvik, Laura J %A Rodriguez-Gil, Jorge L %A Salako, Babatunde %A Schadt, Eric E %A Schwartz, Ann G %A Shriner, Daniel A %A Siscovick, David %A Smith, Shad B %A Wassertheil-Smoller, Sylvia %A Speliotes, Elizabeth K %A Spitz, Margaret R %A Sucheston, Lara %A Taylor, Herman %A Tayo, Bamidele O %A Tucker, Margaret A %A Van Den Berg, David J %A Edwards, Digna R Velez %A Wang, Zhaoming %A Wiencke, John K %A Winkler, Thomas W %A Witte, John S %A Wrensch, Margaret %A Wu, Xifeng %A Yang, James J %A Levin, Albert M %A Young, Taylor R %A Zakai, Neil A %A Cushman, Mary %A Zanetti, Krista A %A Zhao, Jing Hua %A Zhao, Wei %A Zheng, Yonglan %A Zhou, Jie %A Ziegler, Regina G %A Zmuda, Joseph M %A Fernandes, Jyotika K %A Gilkeson, Gary S %A Kamen, Diane L %A Hunt, Kelly J %A Spruill, Ida J %A Ambrosone, Christine B %A Ambs, Stefan %A Arnett, Donna K %A Atwood, Larry %A Becker, Diane M %A Berndt, Sonja I %A Bernstein, Leslie %A Blot, William J %A Borecki, Ingrid B %A Bottinger, Erwin P %A Bowden, Donald W %A Burke, Gregory %A Chanock, Stephen J %A Cooper, Richard S %A Ding, Jingzhong %A Duggan, David %A Evans, Michele K %A Fox, Caroline %A Garvey, W Timothy %A Bradfield, Jonathan P %A Hakonarson, Hakon %A Grant, Struan F A %A Hsing, Ann %A Chu, Lisa %A Hu, Jennifer J %A Huo, Dezheng %A Ingles, Sue A %A John, Esther M %A Jordan, Joanne M %A Kabagambe, Edmond K %A Kardia, Sharon L R %A Kittles, Rick A %A Goodman, Phyllis J %A Klein, Eric A %A Kolonel, Laurence N %A Le Marchand, Loïc %A Liu, Simin %A McKnight, Barbara %A Millikan, Robert C %A Mosley, Thomas H %A Padhukasahasram, Badri %A Williams, L Keoki %A Patel, Sanjay R %A Peters, Ulrike %A Pettaway, Curtis A %A Peyser, Patricia A %A Psaty, Bruce M %A Redline, Susan %A Rotimi, Charles N %A Rybicki, Benjamin A %A Sale, Michèle M %A Schreiner, Pamela J %A Signorello, Lisa B %A Singleton, Andrew B %A Stanford, Janet L %A Strom, Sara S %A Thun, Michael J %A Vitolins, Mara %A Zheng, Wei %A Moore, Jason H %A Williams, Scott M %A Ketkar, Shamika %A Zhu, Xiaofeng %A Zonderman, Alan B %A Kooperberg, Charles %A Papanicolaou, George J %A Henderson, Brian E %A Reiner, Alex P %A Hirschhorn, Joel N %A Loos, Ruth J F %A North, Kari E %A Haiman, Christopher A %K African Americans %K Body Mass Index %K Case-Control Studies %K Gene Frequency %K Genetic Loci %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Linkage Disequilibrium %K Obesity %K Polymorphism, Single Nucleotide %X

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.

%B Nat Genet %V 45 %P 690-6 %8 2013 Jun %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/23583978?dopt=Abstract %R 10.1038/ng.2608 %0 Journal Article %J PLoS Genet %D 2013 %T Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained. %A Wu, Ying %A Waite, Lindsay L %A Jackson, Anne U %A Sheu, Wayne H-H %A Buyske, Steven %A Absher, Devin %A Arnett, Donna K %A Boerwinkle, Eric %A Bonnycastle, Lori L %A Carty, Cara L %A Cheng, Iona %A Cochran, Barbara %A Croteau-Chonka, Damien C %A Dumitrescu, Logan %A Eaton, Charles B %A Franceschini, Nora %A Guo, Xiuqing %A Henderson, Brian E %A Hindorff, Lucia A %A Kim, Eric %A Kinnunen, Leena %A Komulainen, Pirjo %A Lee, Wen-Jane %A Le Marchand, Loïc %A Lin, Yi %A Lindström, Jaana %A Lingaas-Holmen, Oddgeir %A Mitchell, Sabrina L %A Narisu, Narisu %A Robinson, Jennifer G %A Schumacher, Fred %A Stančáková, Alena %A Sundvall, Jouko %A Sung, Yun-Ju %A Swift, Amy J %A Wang, Wen-Chang %A Wilkens, Lynne %A Wilsgaard, Tom %A Young, Alicia M %A Adair, Linda S %A Ballantyne, Christie M %A Bůzková, Petra %A Chakravarti, Aravinda %A Collins, Francis S %A Duggan, David %A Feranil, Alan B %A Ho, Low-Tone %A Hung, Yi-Jen %A Hunt, Steven C %A Hveem, Kristian %A Juang, Jyh-Ming J %A Kesäniemi, Antero Y %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo A %A Lee, I-Te %A Leppert, Mark F %A Matise, Tara C %A Moilanen, Leena %A Njølstad, Inger %A Peters, Ulrike %A Quertermous, Thomas %A Rauramaa, Rainer %A Rotter, Jerome I %A Saramies, Jouko %A Tuomilehto, Jaakko %A Uusitupa, Matti %A Wang, Tzung-Dau %A Boehnke, Michael %A Haiman, Christopher A %A Chen, Yii-der I %A Kooperberg, Charles %A Assimes, Themistocles L %A Crawford, Dana C %A Hsiung, Chao A %A North, Kari E %A Mohlke, Karen L %K African Americans %K Apolipoproteins A %K Cholesterol, HDL %K Cholesterol, LDL %K European Continental Ancestry Group %K Genome-Wide Association Study %K Humans %K Lipoproteins, HDL %K Lipoproteins, LDL %K Proprotein Convertases %K Serine Endopeptidases %K Triglycerides %X

Genome-wide association studies (GWAS) have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 × 10(-4) in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.

%B PLoS Genet %V 9 %P e1003379 %8 2013 Mar %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/23555291?dopt=Abstract %R 10.1371/journal.pgen.1003379 %0 Journal Article %J Am J Clin Nutr %D 2015 %T Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians. %A Fretts, Amanda M %A Follis, Jack L %A Nettleton, Jennifer A %A Lemaitre, Rozenn N %A Ngwa, Julius S %A Wojczynski, Mary K %A Kalafati, Ioanna Panagiota %A Varga, Tibor V %A Frazier-Wood, Alexis C %A Houston, Denise K %A Lahti, Jari %A Ericson, Ulrika %A van den Hooven, Edith H %A Mikkilä, Vera %A Kiefte-de Jong, Jessica C %A Mozaffarian, Dariush %A Rice, Kenneth %A Renstrom, Frida %A North, Kari E %A McKeown, Nicola M %A Feitosa, Mary F %A Kanoni, Stavroula %A Smith, Caren E %A Garcia, Melissa E %A Tiainen, Anna-Maija %A Sonestedt, Emily %A Manichaikul, Ani %A van Rooij, Frank J A %A Dimitriou, Maria %A Raitakari, Olli %A Pankow, James S %A Djoussé, Luc %A Province, Michael A %A Hu, Frank B %A Lai, Chao-Qiang %A Keller, Margaux F %A Perälä, Mia-Maria %A Rotter, Jerome I %A Hofman, Albert %A Graff, Misa %A Kähönen, Mika %A Mukamal, Kenneth %A Johansson, Ingegerd %A Ordovas, Jose M %A Liu, Yongmei %A Männistö, Satu %A Uitterlinden, André G %A Deloukas, Panos %A Seppälä, Ilkka %A Psaty, Bruce M %A Cupples, L Adrienne %A Borecki, Ingrid B %A Franks, Paul W %A Arnett, Donna K %A Nalls, Mike A %A Eriksson, Johan G %A Orho-Melander, Marju %A Franco, Oscar H %A Lehtimäki, Terho %A Dedoussis, George V %A Meigs, James B %A Siscovick, David S %K Blood Glucose %K Cohort Studies %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Hyperglycemia %K Hyperinsulinism %K Insulin %K Insulin Resistance %K Insulin-Secreting Cells %K Meat %K Meat Products %K Middle Aged %K Polymorphism, Single Nucleotide %K Risk Factors %X

BACKGROUND: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.

OBJECTIVE: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.

DESIGN: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.

RESULTS: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.

CONCLUSION: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

%B Am J Clin Nutr %V 102 %P 1266-78 %8 2015 Nov %G eng %N 5 %1 http://www.ncbi.nlm.nih.gov/pubmed/26354543?dopt=Abstract %R 10.3945/ajcn.114.101238 %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 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 Genome Biol %D 2016 %T DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases. %A Ligthart, Symen %A Marzi, Carola %A Aslibekyan, Stella %A Mendelson, Michael M %A Conneely, Karen N %A Tanaka, Toshiko %A Colicino, Elena %A Waite, Lindsay L %A Joehanes, Roby %A Guan, Weihua %A Brody, Jennifer A %A Elks, Cathy %A Marioni, Riccardo %A Jhun, Min A %A Agha, Golareh %A Bressler, Jan %A Ward-Caviness, Cavin K %A Chen, Brian H %A Huan, Tianxiao %A Bakulski, Kelly %A Salfati, Elias L %A Fiorito, Giovanni %A Wahl, Simone %A Schramm, Katharina %A Sha, Jin %A Hernandez, Dena G %A Just, Allan C %A Smith, Jennifer A %A Sotoodehnia, Nona %A Pilling, Luke C %A Pankow, James S %A Tsao, Phil S %A Liu, Chunyu %A Zhao, Wei %A Guarrera, Simonetta %A Michopoulos, Vasiliki J %A Smith, Alicia K %A Peters, Marjolein J %A Melzer, David %A Vokonas, Pantel %A Fornage, Myriam %A Prokisch, Holger %A Bis, Joshua C %A Chu, Audrey Y %A Herder, Christian %A Grallert, Harald %A Yao, Chen %A Shah, Sonia %A McRae, Allan F %A Lin, Honghuang %A Horvath, Steve %A Fallin, Daniele %A Hofman, Albert %A Wareham, Nicholas J %A Wiggins, Kerri L %A Feinberg, Andrew P %A Starr, John M %A Visscher, Peter M %A Murabito, Joanne M %A Kardia, Sharon L R %A Absher, Devin M %A Binder, Elisabeth B %A Singleton, Andrew B %A Bandinelli, Stefania %A Peters, Annette %A Waldenberger, Melanie %A Matullo, Giuseppe %A Schwartz, Joel D %A Demerath, Ellen W %A Uitterlinden, André G %A van Meurs, Joyce B J %A Franco, Oscar H %A Chen, Yii-Der Ida %A Levy, Daniel %A Turner, Stephen T %A Deary, Ian J %A Ressler, Kerry J %A Dupuis, Josée %A Ferrucci, Luigi %A Ong, Ken K %A Assimes, Themistocles L %A Boerwinkle, Eric %A Koenig, Wolfgang %A Arnett, Donna K %A Baccarelli, Andrea A %A Benjamin, Emelia J %A Dehghan, Abbas %X

BACKGROUND: Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation.

RESULTS: We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 × 10(-7)) in the discovery panel of European ancestry and replicated (P < 2.29 × 10(-4)) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 × 10(-5)), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 × 10(-3)), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58 × 10(-5)). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants.

CONCLUSION: We have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation.

%B Genome Biol %V 17 %P 255 %8 2016 Dec 12 %G eng %N 1 %R 10.1186/s13059-016-1119-5 %0 Journal Article %J Circ Cardiovasc Genet %D 2016 %T Epigenetic Signatures of Cigarette Smoking. %A Joehanes, Roby %A Just, Allan C %A Marioni, Riccardo E %A Pilling, Luke C %A Reynolds, Lindsay M %A Mandaviya, Pooja R %A Guan, Weihua %A Xu, Tao %A Elks, Cathy E %A Aslibekyan, Stella %A Moreno-Macias, Hortensia %A Smith, Jennifer A %A Brody, Jennifer A %A Dhingra, Radhika %A Yousefi, Paul %A Pankow, James S %A Kunze, Sonja %A Shah, Sonia H %A McRae, Allan F %A Lohman, Kurt %A Sha, Jin %A Absher, Devin M %A Ferrucci, Luigi %A Zhao, Wei %A Demerath, Ellen W %A Bressler, Jan %A Grove, Megan L %A Huan, Tianxiao %A Liu, Chunyu %A Mendelson, Michael M %A Yao, Chen %A Kiel, Douglas P %A Peters, Annette %A Wang-Sattler, Rui %A Visscher, Peter M %A Wray, Naomi R %A Starr, John M %A Ding, Jingzhong %A Rodriguez, Carlos J %A Wareham, Nicholas J %A Irvin, Marguerite R %A Zhi, Degui %A Barrdahl, Myrto %A Vineis, Paolo %A Ambatipudi, Srikant %A Uitterlinden, André G %A Hofman, Albert %A Schwartz, Joel %A Colicino, Elena %A Hou, Lifang %A Vokonas, Pantel S %A Hernandez, Dena G %A Singleton, Andrew B %A Bandinelli, Stefania %A Turner, Stephen T %A Ware, Erin B %A Smith, Alicia K %A Klengel, Torsten %A Binder, Elisabeth B %A Psaty, Bruce M %A Taylor, Kent D %A Gharib, Sina A %A Swenson, Brenton R %A Liang, Liming %A DeMeo, Dawn L %A O'Connor, George T %A Herceg, Zdenko %A Ressler, Kerry J %A Conneely, Karen N %A Sotoodehnia, Nona %A Kardia, Sharon L R %A Melzer, David %A Baccarelli, Andrea A %A van Meurs, Joyce B J %A Romieu, Isabelle %A Arnett, Donna K %A Ong, Ken K %A Liu, Yongmei %A Waldenberger, Melanie %A Deary, Ian J %A Fornage, Myriam %A Levy, Daniel %A London, Stephanie J %X

BACKGROUND: DNA methylation leaves a long-term signature of smoking exposure and is one potential mechanism by which tobacco exposure predisposes to adverse health outcomes, such as cancers, osteoporosis, lung, and cardiovascular disorders.

METHODS AND RESULTS: To comprehensively determine the association between cigarette smoking and DNA methylation, we conducted a meta-analysis of genome-wide DNA methylation assessed using the Illumina BeadChip 450K array on 15 907 blood-derived DNA samples from participants in 16 cohorts (including 2433 current, 6518 former, and 6956 never smokers). Comparing current versus never smokers, 2623 cytosine-phosphate-guanine sites (CpGs), annotated to 1405 genes, were statistically significantly differentially methylated at Bonferroni threshold of P<1×10(-7) (18 760 CpGs at false discovery rate <0.05). Genes annotated to these CpGs were enriched for associations with several smoking-related traits in genome-wide studies including pulmonary function, cancers, inflammatory diseases, and heart disease. Comparing former versus never smokers, 185 of the CpGs that differed between current and never smokers were significant P<1×10(-7) (2623 CpGs at false discovery rate <0.05), indicating a pattern of persistent altered methylation, with attenuation, after smoking cessation. Transcriptomic integration identified effects on gene expression at many differentially methylated CpGs.

CONCLUSIONS: Cigarette smoking has a broad impact on genome-wide methylation that, at many loci, persists many years after smoking cessation. Many of the differentially methylated genes were novel genes with respect to biological effects of smoking and might represent therapeutic targets for prevention or treatment of tobacco-related diseases. Methylation at these sites could also serve as sensitive and stable biomarkers of lifetime exposure to tobacco smoke.

%B Circ Cardiovasc Genet %V 9 %P 436-447 %8 2016 Oct %G eng %N 5 %R 10.1161/CIRCGENETICS.116.001506 %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 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 PLoS Genet %D 2017 %T Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African ancestry anthropometry genetics consortium. %A Ng, Maggie C Y %A Graff, Mariaelisa %A Lu, Yingchang %A Justice, Anne E %A Mudgal, Poorva %A Liu, Ching-Ti %A Young, Kristin %A Yanek, Lisa R %A Feitosa, Mary F %A Wojczynski, Mary K %A Rand, Kristin %A Brody, Jennifer A %A Cade, Brian E %A Dimitrov, Latchezar %A Duan, Qing %A Guo, Xiuqing %A Lange, Leslie A %A Nalls, Michael A %A Okut, Hayrettin %A Tajuddin, Salman M %A Tayo, Bamidele O %A Vedantam, Sailaja %A Bradfield, Jonathan P %A Chen, Guanjie %A Chen, Wei-Min %A Chesi, Alessandra %A Irvin, Marguerite R %A Padhukasahasram, Badri %A Smith, Jennifer A %A Zheng, Wei %A Allison, Matthew A %A Ambrosone, Christine B %A Bandera, Elisa V %A Bartz, Traci M %A Berndt, Sonja I %A Bernstein, Leslie %A Blot, William J %A Bottinger, Erwin P %A Carpten, John %A Chanock, Stephen J %A Chen, Yii-Der Ida %A Conti, David V %A Cooper, Richard S %A Fornage, Myriam %A Freedman, Barry I %A Garcia, Melissa %A Goodman, Phyllis J %A Hsu, Yu-Han H %A Hu, Jennifer %A Huff, Chad D %A Ingles, Sue A %A John, Esther M %A Kittles, Rick %A Klein, Eric %A Li, Jin %A McKnight, Barbara %A Nayak, Uma %A Nemesure, Barbara %A Ogunniyi, Adesola %A Olshan, Andrew %A Press, Michael F %A Rohde, Rebecca %A Rybicki, Benjamin A %A Salako, Babatunde %A Sanderson, Maureen %A Shao, Yaming %A Siscovick, David S %A Stanford, Janet L %A Stevens, Victoria L %A Stram, Alex %A Strom, Sara S %A Vaidya, Dhananjay %A Witte, John S %A Yao, Jie %A Zhu, Xiaofeng %A Ziegler, Regina G %A Zonderman, Alan B %A Adeyemo, Adebowale %A Ambs, Stefan %A Cushman, Mary %A Faul, Jessica D %A Hakonarson, Hakon %A Levin, Albert M %A Nathanson, Katherine L %A Ware, Erin B %A Weir, David R %A Zhao, Wei %A Zhi, Degui %A Arnett, Donna K %A Grant, Struan F A %A Kardia, Sharon L R %A Oloapde, Olufunmilayo I %A Rao, D C %A Rotimi, Charles N %A Sale, Michèle M %A Williams, L Keoki %A Zemel, Babette S %A Becker, Diane M %A Borecki, Ingrid B %A Evans, Michele K %A Harris, Tamara B %A Hirschhorn, Joel N %A Li, Yun %A Patel, Sanjay R %A Psaty, Bruce M %A Rotter, Jerome I %A Wilson, James G %A Bowden, Donald W %A Cupples, L Adrienne %A Haiman, Christopher A %A Loos, Ruth J F %A North, Kari E %X

Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.

%B PLoS Genet %V 13 %P e1006719 %8 2017 Apr 21 %G eng %N 4 %R 10.1371/journal.pgen.1006719 %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 Am J Hum Genet %D 2017 %T DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation. %A Richard, Melissa A %A Huan, Tianxiao %A Ligthart, Symen %A Gondalia, Rahul %A Jhun, Min A %A Brody, Jennifer A %A Irvin, Marguerite R %A Marioni, Riccardo %A Shen, Jincheng %A Tsai, Pei-Chien %A Montasser, May E %A Jia, Yucheng %A Syme, Catriona %A Salfati, Elias L %A Boerwinkle, Eric %A Guan, Weihua %A Mosley, Thomas H %A Bressler, Jan %A Morrison, Alanna C %A Liu, Chunyu %A Mendelson, Michael M %A Uitterlinden, André G %A van Meurs, Joyce B %A Franco, Oscar H %A Zhang, Guosheng %A Li, Yun %A Stewart, James D %A Bis, Joshua C %A Psaty, Bruce M %A Chen, Yii-Der Ida %A Kardia, Sharon L R %A Zhao, Wei %A Turner, Stephen T %A Absher, Devin %A Aslibekyan, Stella %A Starr, John M %A McRae, Allan F %A Hou, Lifang %A Just, Allan C %A Schwartz, Joel D %A Vokonas, Pantel S %A Menni, Cristina %A Spector, Tim D %A Shuldiner, Alan %A Damcott, Coleen M %A Rotter, Jerome I %A Palmas, Walter %A Liu, Yongmei %A Paus, Tomáš %A Horvath, Steve %A O'Connell, Jeffrey R %A Guo, Xiuqing %A Pausova, Zdenka %A Assimes, Themistocles L %A Sotoodehnia, Nona %A Smith, Jennifer A %A Arnett, Donna K %A Deary, Ian J %A Baccarelli, Andrea A %A Bell, Jordana T %A Whitsel, Eric %A Dehghan, Abbas %A Levy, Daniel %A Fornage, Myriam %K Aged %K Blood Pressure %K CpG Islands %K Cross-Sectional Studies %K DNA Methylation %K Epigenesis, Genetic %K Genetic Variation %K Genome-Wide Association Study %K Humans %K Mendelian Randomization Analysis %K Middle Aged %K Nerve Tissue Proteins %K Quantitative Trait Loci %K Tetraspanins %X

Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0 × 10-7; replication: N = 7,182, p < 1.6 × 10-3). The replicated methylation sites are heritable (h2 > 30%) and independent of known BP genetic variants, explaining an additional 1.4% and 2.0% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

%B Am J Hum Genet %V 101 %P 888-902 %8 2017 Dec 07 %G eng %N 6 %R 10.1016/j.ajhg.2017.09.028 %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 J Clin Invest %D 2017 %T Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function. %A Wild, Philipp S %A Felix, Janine F %A Schillert, Arne %A Teumer, Alexander %A Chen, Ming-Huei %A Leening, Maarten J G %A Völker, Uwe %A Großmann, Vera %A Brody, Jennifer A %A Irvin, Marguerite R %A Shah, Sanjiv J %A Pramana, Setia %A Lieb, Wolfgang %A Schmidt, Reinhold %A Stanton, Alice V %A Malzahn, Dörthe %A Smith, Albert Vernon %A Sundström, Johan %A Minelli, Cosetta %A Ruggiero, Daniela %A Lyytikäinen, Leo-Pekka %A Tiller, Daniel %A Smith, J Gustav %A Monnereau, Claire %A Di Tullio, Marco R %A Musani, Solomon K %A Morrison, Alanna C %A Pers, Tune H %A Morley, Michael %A Kleber, Marcus E %A Aragam, Jayashri %A Benjamin, Emelia J %A Bis, Joshua C %A Bisping, Egbert %A Broeckel, Ulrich %A Cheng, Susan %A Deckers, Jaap W %A del Greco M, Fabiola %A Edelmann, Frank %A Fornage, Myriam %A Franke, Lude %A Friedrich, Nele %A Harris, Tamara B %A Hofer, Edith %A Hofman, Albert %A Huang, Jie %A Hughes, Alun D %A Kähönen, Mika %A Investigators, Knhi %A Kruppa, Jochen %A Lackner, Karl J %A Lannfelt, Lars %A Laskowski, Rafael %A Launer, Lenore J %A Leosdottir, Margrét %A Lin, Honghuang %A Lindgren, Cecilia M %A Loley, Christina %A MacRae, Calum A %A Mascalzoni, Deborah %A Mayet, Jamil %A Medenwald, Daniel %A Morris, Andrew P %A Müller, Christian %A Müller-Nurasyid, Martina %A Nappo, Stefania %A Nilsson, Peter M %A Nuding, Sebastian %A Nutile, Teresa %A Peters, Annette %A Pfeufer, Arne %A Pietzner, Diana %A Pramstaller, Peter P %A Raitakari, Olli T %A Rice, Kenneth M %A Rivadeneira, Fernando %A Rotter, Jerome I %A Ruohonen, Saku T %A Sacco, Ralph L %A Samdarshi, Tandaw E %A Schmidt, Helena %A Sharp, Andrew S P %A Shields, Denis C %A Sorice, Rossella %A Sotoodehnia, Nona %A Stricker, Bruno H %A Surendran, Praveen %A Thom, Simon %A Töglhofer, Anna M %A Uitterlinden, André G %A Wachter, Rolf %A Völzke, Henry %A Ziegler, Andreas %A Münzel, Thomas %A März, Winfried %A Cappola, Thomas P %A Hirschhorn, Joel N %A Mitchell, Gary F %A Smith, Nicholas L %A Fox, Ervin R %A Dueker, Nicole D %A Jaddoe, Vincent W V %A Melander, Olle %A Russ, Martin %A Lehtimäki, Terho %A Ciullo, Marina %A Hicks, Andrew A %A Lind, Lars %A Gudnason, Vilmundur %A Pieske, Burkert %A Barron, Anthony J %A Zweiker, Robert %A Schunkert, Heribert %A Ingelsson, Erik %A Liu, Kiang %A Arnett, Donna K %A Psaty, Bruce M %A Blankenberg, Stefan %A Larson, Martin G %A Felix, Stephan B %A Franco, Oscar H %A Zeller, Tanja %A Vasan, Ramachandran S %A Dörr, Marcus %X

BACKGROUND: Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function.

METHODS: A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function.

RESULTS: The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue.

CONCLUSION: The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies.

FUNDING: For detailed information per study, see Acknowledgments.

%B J Clin Invest %V 127 %P 1798-1812 %8 2017 May 01 %G eng %N 5 %R 10.1172/JCI84840 %0 Journal Article %J PLoS Genet %D 2017 %T Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations. %A Liang, Jingjing %A Le, Thu H %A Edwards, Digna R Velez %A Tayo, Bamidele O %A Gaulton, Kyle J %A Smith, Jennifer A %A Lu, Yingchang %A Jensen, Richard A %A Chen, Guanjie %A Yanek, Lisa R %A Schwander, Karen %A Tajuddin, Salman M %A Sofer, Tamar %A Kim, Wonji %A Kayima, James %A McKenzie, Colin A %A Fox, Ervin %A Nalls, Michael A %A Young, J Hunter %A Sun, Yan V %A Lane, Jacqueline M %A Cechova, Sylvia %A Zhou, Jie %A Tang, Hua %A Fornage, Myriam %A Musani, Solomon K %A Wang, Heming %A Lee, Juyoung %A Adeyemo, Adebowale %A Dreisbach, Albert W %A Forrester, Terrence %A Chu, Pei-Lun %A Cappola, Anne %A Evans, Michele K %A Morrison, Alanna C %A Martin, Lisa W %A Wiggins, Kerri L %A Hui, Qin %A Zhao, Wei %A Jackson, Rebecca D %A Ware, Erin B %A Faul, Jessica D %A Reiner, Alex P %A Bray, Michael %A Denny, Joshua C %A Mosley, Thomas H %A Palmas, Walter %A Guo, Xiuqing %A Papanicolaou, George J %A Penman, Alan D %A Polak, Joseph F %A Rice, Kenneth %A Taylor, Ken D %A Boerwinkle, Eric %A Bottinger, Erwin P %A Liu, Kiang %A Risch, Neil %A Hunt, Steven C %A Kooperberg, Charles %A Zonderman, Alan B %A Laurie, Cathy C %A Becker, Diane M %A Cai, Jianwen %A Loos, Ruth J F %A Psaty, Bruce M %A Weir, David R %A Kardia, Sharon L R %A Arnett, Donna K %A Won, Sungho %A Edwards, Todd L %A Redline, Susan %A Cooper, Richard S %A Rao, D C %A Rotter, Jerome I %A Rotimi, Charles %A Levy, Daniel %A Chakravarti, Aravinda %A Zhu, Xiaofeng %A Franceschini, Nora %K African Americans %K Animals %K Basic Helix-Loop-Helix Transcription Factors %K Blood Pressure %K Cadherins %K Case-Control Studies %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Hypertension %K Male %K Membrane Proteins %K Mice %K Multifactorial Inheritance %K Polymorphism, Single Nucleotide %X

Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.

%B PLoS Genet %V 13 %P e1006728 %8 2017 May %G eng %N 5 %R 10.1371/journal.pgen.1006728 %0 Journal Article %J Am J Hum Genet %D 2018 %T Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders. %A Ligthart, Symen %A Vaez, Ahmad %A Võsa, Urmo %A Stathopoulou, Maria G %A de Vries, Paul S %A Prins, Bram P %A van der Most, Peter J %A Tanaka, Toshiko %A Naderi, Elnaz %A Rose, Lynda M %A Wu, Ying %A Karlsson, Robert %A Barbalic, Maja %A Lin, Honghuang %A Pool, Rene %A Zhu, Gu %A Mace, Aurelien %A Sidore, Carlo %A Trompet, Stella %A Mangino, Massimo %A Sabater-Lleal, Maria %A Kemp, John P %A Abbasi, Ali %A Kacprowski, Tim %A Verweij, Niek %A Smith, Albert V %A Huang, Tao %A Marzi, Carola %A Feitosa, Mary F %A Lohman, Kurt K %A Kleber, Marcus E %A Milaneschi, Yuri %A Mueller, Christian %A Huq, Mahmudul %A Vlachopoulou, Efthymia %A Lyytikäinen, Leo-Pekka %A Oldmeadow, Christopher %A Deelen, Joris %A Perola, Markus %A Zhao, Jing Hua %A Feenstra, Bjarke %A Amini, Marzyeh %A Lahti, Jari %A Schraut, Katharina E %A Fornage, Myriam %A Suktitipat, Bhoom %A Chen, Wei-Min %A Li, Xiaohui %A Nutile, Teresa %A Malerba, Giovanni %A Luan, Jian'an %A Bak, Tom %A Schork, Nicholas %A del Greco M, Fabiola %A Thiering, Elisabeth %A Mahajan, Anubha %A Marioni, Riccardo E %A Mihailov, Evelin %A Eriksson, Joel %A Ozel, Ayse Bilge %A Zhang, Weihua %A Nethander, Maria %A Cheng, Yu-Ching %A Aslibekyan, Stella %A Ang, Wei %A Gandin, Ilaria %A Yengo, Loic %A Portas, Laura %A Kooperberg, Charles %A Hofer, Edith %A Rajan, Kumar B %A Schurmann, Claudia %A den Hollander, Wouter %A Ahluwalia, Tarunveer S %A Zhao, Jing %A Draisma, Harmen H M %A Ford, Ian %A Timpson, Nicholas %A Teumer, Alexander %A Huang, Hongyan %A Wahl, Simone %A Liu, Yongmei %A Huang, Jie %A Uh, Hae-Won %A Geller, Frank %A Joshi, Peter K %A Yanek, Lisa R %A Trabetti, Elisabetta %A Lehne, Benjamin %A Vozzi, Diego %A Verbanck, Marie %A Biino, Ginevra %A Saba, Yasaman %A Meulenbelt, Ingrid %A O'Connell, Jeff R %A Laakso, Markku %A Giulianini, Franco %A Magnusson, Patrik K E %A Ballantyne, Christie M %A Hottenga, Jouke Jan %A Montgomery, Grant W %A Rivadineira, Fernando %A Rueedi, Rico %A Steri, Maristella %A Herzig, Karl-Heinz %A Stott, David J %A Menni, Cristina %A Frånberg, Mattias %A St Pourcain, Beate %A Felix, Stephan B %A Pers, Tune H %A Bakker, Stephan J L %A Kraft, Peter %A Peters, Annette %A Vaidya, Dhananjay %A Delgado, Graciela %A Smit, Johannes H %A Großmann, Vera %A Sinisalo, Juha %A Seppälä, Ilkka %A Williams, Stephen R %A Holliday, Elizabeth G %A Moed, Matthijs %A Langenberg, Claudia %A Räikkönen, Katri %A Ding, Jingzhong %A Campbell, Harry %A Sale, Michèle M %A Chen, Yii-der I %A James, Alan L %A Ruggiero, Daniela %A Soranzo, Nicole %A Hartman, Catharina A %A Smith, Erin N %A Berenson, Gerald S %A Fuchsberger, Christian %A Hernandez, Dena %A Tiesler, Carla M T %A Giedraitis, Vilmantas %A Liewald, David %A Fischer, Krista %A Mellström, Dan %A Larsson, Anders %A Wang, Yunmei %A Scott, William R %A Lorentzon, Matthias %A Beilby, John %A Ryan, Kathleen A %A Pennell, Craig E %A Vuckovic, Dragana %A Balkau, Beverly %A Concas, Maria Pina %A Schmidt, Reinhold %A Mendes de Leon, Carlos F %A Bottinger, Erwin P %A Kloppenburg, Margreet %A Paternoster, Lavinia %A Boehnke, Michael %A Musk, A W %A Willemsen, Gonneke %A Evans, David M %A Madden, Pamela A F %A Kähönen, Mika %A Kutalik, Zoltán %A Zoledziewska, Magdalena %A Karhunen, Ville %A Kritchevsky, Stephen B %A Sattar, Naveed %A Lachance, Genevieve %A Clarke, Robert %A Harris, Tamara B %A Raitakari, Olli T %A Attia, John R %A van Heemst, Diana %A Kajantie, Eero %A Sorice, Rossella %A Gambaro, Giovanni %A Scott, Robert A %A Hicks, Andrew A %A Ferrucci, Luigi %A Standl, Marie %A Lindgren, Cecilia M %A Starr, John M %A Karlsson, Magnus %A Lind, Lars %A Li, Jun Z %A Chambers, John C %A Mori, Trevor A %A de Geus, Eco J C N %A Heath, Andrew C %A Martin, Nicholas G %A Auvinen, Juha %A Buckley, Brendan M %A de Craen, Anton J M %A Waldenberger, Melanie %A Strauch, Konstantin %A Meitinger, Thomas %A Scott, Rodney J %A McEvoy, Mark %A Beekman, Marian %A Bombieri, Cristina %A Ridker, Paul M %A Mohlke, Karen L %A Pedersen, Nancy L %A Morrison, Alanna C %A Boomsma, Dorret I %A Whitfield, John B %A Strachan, David P %A Hofman, Albert %A Vollenweider, Peter %A Cucca, Francesco %A Jarvelin, Marjo-Riitta %A Jukema, J Wouter %A Spector, Tim D %A Hamsten, Anders %A Zeller, Tanja %A Uitterlinden, André G %A Nauck, Matthias %A Gudnason, Vilmundur %A Qi, Lu %A Grallert, Harald %A Borecki, Ingrid B %A Rotter, Jerome I %A März, Winfried %A Wild, Philipp S %A Lokki, Marja-Liisa %A Boyle, Michael %A Salomaa, Veikko %A Melbye, Mads %A Eriksson, Johan G %A Wilson, James F %A Penninx, Brenda W J H %A Becker, Diane M %A Worrall, Bradford B %A Gibson, Greg %A Krauss, Ronald M %A Ciullo, Marina %A Zaza, Gianluigi %A Wareham, Nicholas J %A Oldehinkel, Albertine J %A Palmer, Lyle J %A Murray, Sarah S %A Pramstaller, Peter P %A Bandinelli, Stefania %A Heinrich, Joachim %A Ingelsson, Erik %A Deary, Ian J %A Mägi, Reedik %A Vandenput, Liesbeth %A van der Harst, Pim %A Desch, Karl C %A Kooner, Jaspal S %A Ohlsson, Claes %A Hayward, Caroline %A Lehtimäki, Terho %A Shuldiner, Alan R %A Arnett, Donna K %A Beilin, Lawrence J %A Robino, Antonietta %A Froguel, Philippe %A Pirastu, Mario %A Jess, Tine %A Koenig, Wolfgang %A Loos, Ruth J F %A Evans, Denis A %A Schmidt, Helena %A Smith, George Davey %A Slagboom, P Eline %A Eiriksdottir, Gudny %A Morris, Andrew P %A Psaty, Bruce M %A Tracy, Russell P %A Nolte, Ilja M %A Boerwinkle, Eric %A Visvikis-Siest, Sophie %A Reiner, Alex P %A Gross, Myron %A Bis, Joshua C %A Franke, Lude %A Franco, Oscar H %A Benjamin, Emelia J %A Chasman, Daniel I %A Dupuis, Josée %A Snieder, Harold %A Dehghan, Abbas %A Alizadeh, Behrooz Z %X

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

%B Am J Hum Genet %V 103 %P 691-706 %8 2018 Nov 01 %G eng %N 5 %R 10.1016/j.ajhg.2018.09.009 %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 Pharmacogenomics J %D 2018 %T Genome-wide meta-analysis of SNP-by9-ACEI/ARB and SNP-by-thiazide diuretic and effect on serum potassium in cohorts of European and African ancestry. %A Irvin, Marguerite R %A Sitlani, Colleen M %A Noordam, Raymond %A Avery, Christie L %A Bis, Joshua C %A Floyd, James S %A Li, Jin %A Limdi, Nita A %A Srinivasasainagendra, Vinodh %A Stewart, James %A de Mutsert, Renée %A Mook-Kanamori, Dennis O %A Lipovich, Leonard %A Kleinbrink, Erica L %A Smith, Albert %A Bartz, Traci M %A Whitsel, Eric A %A Uitterlinden, André G %A Wiggins, Kerri L %A Wilson, James G %A Zhi, Degui %A Stricker, Bruno H %A Rotter, Jerome I %A Arnett, Donna K %A Psaty, Bruce M %A Lange, Leslie A %X

We evaluated interactions of SNP-by-ACE-I/ARB and SNP-by-TD on serum potassium (K+) among users of antihypertensive treatments (anti-HTN). Our study included seven European-ancestry (EA) (N = 4835) and four African-ancestry (AA) cohorts (N = 2016). We performed race-stratified, fixed-effect, inverse-variance-weighted meta-analyses of 2.5 million SNP-by-drug interaction estimates; race-combined meta-analysis; and trans-ethnic fine-mapping. Among EAs, we identified 11 significant SNPs (P < 5 × 10) for SNP-ACE-I/ARB interactions on serum K+ that were located between NR2F1-AS1 and ARRDC3-AS1 on chromosome 5 (top SNP rs6878413 P = 1.7 × 10; ratio of serum K+ in ACE-I/ARB exposed compared to unexposed is 1.0476, 1.0280, 1.0088 for the TT, AT, and AA genotypes, respectively). Trans-ethnic fine mapping identified the same group of SNPs on chromosome 5 as genome-wide significant for the ACE-I/ARB analysis. In conclusion, SNP-by-ACE-I /ARB interaction analyses uncovered loci that, if replicated, could have future implications for the prevention of arrhythmias due to anti-HTN treatment-related hyperkalemia. Before these loci can be identified as clinically relevant, future validation studies of equal or greater size in comparison to our discovery effort are needed.

%B Pharmacogenomics J %8 2018 Jun 01 %G eng %R 10.1038/s41397-018-0021-9 %0 Journal Article %J Am J Hum Genet %D 2018 %T A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure. %A Sung, Yun J %A Winkler, Thomas W %A de Las Fuentes, Lisa %A Bentley, Amy R %A Brown, Michael R %A Kraja, Aldi T %A Schwander, Karen %A Ntalla, Ioanna %A Guo, Xiuqing %A Franceschini, Nora %A Lu, Yingchang %A Cheng, Ching-Yu %A Sim, Xueling %A Vojinovic, Dina %A Marten, Jonathan %A Musani, Solomon K %A Li, Changwei %A Feitosa, Mary F %A Kilpeläinen, Tuomas O %A Richard, Melissa A %A Noordam, Raymond %A Aslibekyan, Stella %A Aschard, Hugues %A Bartz, Traci M %A Dorajoo, Rajkumar %A Liu, Yongmei %A Manning, Alisa K %A Rankinen, Tuomo %A Smith, Albert Vernon %A Tajuddin, Salman M %A Tayo, Bamidele O %A Warren, Helen R %A Zhao, Wei %A Zhou, Yanhua %A Matoba, Nana %A Sofer, Tamar %A Alver, Maris %A Amini, Marzyeh %A Boissel, Mathilde %A Chai, Jin Fang %A Chen, Xu %A Divers, Jasmin %A Gandin, Ilaria %A Gao, Chuan %A Giulianini, Franco %A Goel, Anuj %A Harris, Sarah E %A Hartwig, Fernando Pires %A Horimoto, Andrea R V R %A Hsu, Fang-Chi %A Jackson, Anne U %A Kähönen, Mika %A Kasturiratne, Anuradhani %A Kuhnel, Brigitte %A Leander, Karin %A Lee, Wen-Jane %A Lin, Keng-Hung %A 'an Luan, Jian %A McKenzie, Colin A %A Meian, He %A Nelson, Christopher P %A Rauramaa, Rainer %A Schupf, Nicole %A Scott, Robert A %A Sheu, Wayne H H %A Stančáková, Alena %A Takeuchi, Fumihiko %A van der Most, Peter J %A Varga, Tibor V %A Wang, Heming %A Wang, Yajuan %A Ware, Erin B %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Zhang, Weihua %A Zhao, Jing Hua %A Afaq, Saima %A Alfred, Tamuno %A Amin, Najaf %A Arking, Dan %A Aung, Tin %A Barr, R Graham %A Bielak, Lawrence F %A Boerwinkle, Eric %A Bottinger, Erwin P %A Braund, Peter S %A Brody, Jennifer A %A Broeckel, Ulrich %A Cabrera, Claudia P %A Cade, Brian %A Caizheng, Yu %A Campbell, Archie %A Canouil, Mickaël %A Chakravarti, Aravinda %A Chauhan, Ganesh %A Christensen, Kaare %A Cocca, Massimiliano %A Collins, Francis S %A Connell, John M %A de Mutsert, Renée %A de Silva, H Janaka %A Debette, Stephanie %A Dörr, Marcus %A Duan, Qing %A Eaton, Charles B %A Ehret, Georg %A Evangelou, Evangelos %A Faul, Jessica D %A Fisher, Virginia A %A Forouhi, Nita G %A Franco, Oscar H %A Friedlander, Yechiel %A Gao, He %A Gigante, Bruna %A Graff, Misa %A Gu, C Charles %A Gu, Dongfeng %A Gupta, Preeti %A Hagenaars, Saskia P %A Harris, Tamara B %A He, Jiang %A Heikkinen, Sami %A Heng, Chew-Kiat %A Hirata, Makoto %A Hofman, Albert %A Howard, Barbara V %A Hunt, Steven %A Irvin, Marguerite R %A Jia, Yucheng %A Joehanes, Roby %A Justice, Anne E %A Katsuya, Tomohiro %A Kaufman, Joel %A Kerrison, Nicola D %A Khor, Chiea Chuen %A Koh, Woon-Puay %A Koistinen, Heikki A %A Komulainen, Pirjo %A Kooperberg, Charles %A Krieger, Jose E %A Kubo, Michiaki %A Kuusisto, Johanna %A Langefeld, Carl D %A Langenberg, Claudia %A Launer, Lenore J %A Lehne, Benjamin %A Lewis, Cora E %A Li, Yize %A Lim, Sing Hui %A Lin, Shiow %A Liu, Ching-Ti %A Liu, Jianjun %A Liu, Jingmin %A Liu, Kiang %A Liu, Yeheng %A Loh, Marie %A Lohman, Kurt K %A Long, Jirong %A Louie, Tin %A Mägi, Reedik %A Mahajan, Anubha %A Meitinger, Thomas %A Metspalu, Andres %A Milani, Lili %A Momozawa, Yukihide %A Morris, Andrew P %A Mosley, Thomas H %A Munson, Peter %A Murray, Alison D %A Nalls, Mike A %A Nasri, Ubaydah %A Norris, Jill M %A North, Kari %A Ogunniyi, Adesola %A Padmanabhan, Sandosh %A Palmas, Walter R %A Palmer, Nicholette D %A Pankow, James S %A Pedersen, Nancy L %A Peters, Annette %A Peyser, Patricia A %A Polasek, Ozren %A Raitakari, Olli T %A Renstrom, Frida %A Rice, Treva K %A Ridker, Paul M %A Robino, Antonietta %A Robinson, Jennifer G %A Rose, Lynda M %A Rudan, Igor %A Sabanayagam, Charumathi %A Salako, Babatunde L %A Sandow, Kevin %A Schmidt, Carsten O %A Schreiner, Pamela J %A Scott, William R %A Seshadri, Sudha %A Sever, Peter %A Sitlani, Colleen M %A Smith, Jennifer A %A Snieder, Harold %A Starr, John M %A Strauch, Konstantin %A Tang, Hua %A Taylor, Kent D %A Teo, Yik Ying %A Tham, Yih Chung %A Uitterlinden, André G %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Ya X %A Wei, Wen Bin %A Williams, Christine %A Wilson, Gregory %A Wojczynski, Mary K %A Yao, Jie %A Yuan, Jian-Min %A Zonderman, Alan B %A Becker, Diane M %A Boehnke, Michael %A Bowden, Donald W %A Chambers, John C %A Chen, Yii-Der Ida %A de Faire, Ulf %A Deary, Ian J %A Esko, Tõnu %A Farrall, Martin %A Forrester, Terrence %A Franks, Paul W %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Horta, Bernardo Lessa %A Hung, Yi-Jen %A Jonas, Jost B %A Kato, Norihiro %A Kooner, Jaspal S %A Laakso, Markku %A Lehtimäki, Terho %A Liang, Kae-Woei %A Magnusson, Patrik K E %A Newman, Anne B %A Oldehinkel, Albertine J %A Pereira, Alexandre C %A Redline, Susan %A Rettig, Rainer %A Samani, Nilesh J %A Scott, James %A Shu, Xiao-Ou %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wareham, Nicholas J %A Watkins, Hugh %A Weir, David R %A Wickremasinghe, Ananda R %A Wu, Tangchun %A Zheng, Wei %A Kamatani, Yoichiro %A Laurie, Cathy C %A Bouchard, Claude %A Cooper, Richard S %A Evans, Michele K %A Gudnason, Vilmundur %A Kardia, Sharon L R %A Kritchevsky, Stephen B %A Levy, Daniel %A O'Connell, Jeff R %A Psaty, Bruce M %A van Dam, Rob M %A Sims, Mario %A Arnett, Donna K %A Mook-Kanamori, Dennis O %A Kelly, Tanika N %A Fox, Ervin R %A Hayward, Caroline %A Fornage, Myriam %A Rotimi, Charles N %A Province, Michael A %A van Duijn, Cornelia M %A Tai, E Shyong %A Wong, Tien Yin %A Loos, Ruth J F %A Reiner, Alex P %A Rotter, Jerome I %A Zhu, Xiaofeng %A Bierut, Laura J %A Gauderman, W James %A Caulfield, Mark J %A Elliott, Paul %A Rice, Kenneth %A Munroe, Patricia B %A Morrison, Alanna C %A Cupples, L Adrienne %A Rao, Dabeeru C %A Chasman, Daniel I %X

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).

%B Am J Hum Genet %V 102 %P 375-400 %8 2018 Mar 01 %G eng %N 3 %R 10.1016/j.ajhg.2018.01.015 %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 Am J Hypertens %D 2019 %T Genome-Wide Association Study of Apparent Treatment-Resistant Hypertension in the CHARGE Consortium: The CHARGE Pharmacogenetics Working Group. %A Irvin, Marguerite R %A Sitlani, Colleen M %A Floyd, James S %A Psaty, Bruce M %A Bis, Joshua C %A Wiggins, Kerri L %A Whitsel, Eric A %A Stürmer, Til %A Stewart, James %A Raffield, Laura %A Sun, Fangui %A Liu, Ching-Ti %A Xu, Hanfei %A Cupples, Adrienne L %A Tanner, Rikki M %A Rossing, Peter %A Smith, Albert %A Zilhão, Nuno R %A Launer, Lenore J %A Noordam, Raymond %A Rotter, Jerome I %A Yao, Jie %A Li, Xiaohui %A Guo, Xiuqing %A Limdi, Nita %A Sundaresan, Aishwarya %A Lange, Leslie %A Correa, Adolfo %A Stott, David J %A Ford, Ian %A Jukema, J Wouter %A Gudnason, Vilmundur %A Mook-Kanamori, Dennis O %A Trompet, Stella %A Palmas, Walter %A Warren, Helen R %A Hellwege, Jacklyn N %A Giri, Ayush %A O'donnell, Christopher %A Hung, Adriana M %A Edwards, Todd L %A Ahluwalia, Tarunveer S %A Arnett, Donna K %A Avery, Christy L %K Aged %K Antihypertensive Agents %K Black or African American %K Blood Pressure %K Case-Control Studies %K DNA (Cytosine-5-)-Methyltransferases %K DNA Methyltransferase 3A %K DNA-Binding Proteins %K Drug Resistance %K Dystrophin-Associated Proteins %K Europe %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Hypertension %K Male %K Middle Aged %K Myosin Heavy Chains %K Myosin Type V %K Neuropeptides %K Pharmacogenetics %K Pharmacogenomic Variants %K Polymorphism, Single Nucleotide %K Risk Assessment %K Risk Factors %K Transcription Factors %K United States %K White People %X

BACKGROUND: Only a handful of genetic discovery efforts in apparent treatment-resistant hypertension (aTRH) have been described.

METHODS: We conducted a case-control genome-wide association study of aTRH among persons treated for hypertension, using data from 10 cohorts of European ancestry (EA) and 5 cohorts of African ancestry (AA). Cases were treated with 3 different antihypertensive medication classes and had blood pressure (BP) above goal (systolic BP ≥ 140 mm Hg and/or diastolic BP ≥ 90 mm Hg) or 4 or more medication classes regardless of BP control (nEA = 931, nAA = 228). Both a normotensive control group and a treatment-responsive control group were considered in separate analyses. Normotensive controls were untreated (nEA = 14,210, nAA = 2,480) and had systolic BP/diastolic BP < 140/90 mm Hg. Treatment-responsive controls (nEA = 5,266, nAA = 1,817) had BP at goal (<140/90 mm Hg), while treated with one antihypertensive medication class. Individual cohorts used logistic regression with adjustment for age, sex, study site, and principal components for ancestry to examine the association of single-nucleotide polymorphisms with case-control status. Inverse variance-weighted fixed-effects meta-analyses were carried out using METAL.

RESULTS: The known hypertension locus, CASZ1, was a top finding among EAs (P = 1.1 × 10-8) and in the race-combined analysis (P = 1.5 × 10-9) using the normotensive control group (rs12046278, odds ratio = 0.71 (95% confidence interval: 0.6-0.8)). Single-nucleotide polymorphisms in this locus were robustly replicated in the Million Veterans Program (MVP) study in consideration of a treatment-responsive control group. There were no statistically significant findings for the discovery analyses including treatment-responsive controls.

CONCLUSION: This genomic discovery effort for aTRH identified CASZ1 as an aTRH risk locus.

%B Am J Hypertens %V 32 %P 1146-1153 %8 2019 Nov 15 %G eng %N 12 %R 10.1093/ajh/hpz150 %0 Journal Article %J Mol Genet Genomic Med %D 2019 %T Genome-wide meta-analysis of SNP and antihypertensive medication interactions on left ventricular traits in African Americans. %A Do, Anh N %A Zhao, Wei %A Baldridge, Abigail S %A Raffield, Laura M %A Wiggins, Kerri L %A Shah, Sanjiv J %A Aslibekyan, Stella %A Tiwari, Hemant K %A Limdi, Nita %A Zhi, Degui %A Sitlani, Colleen M %A Taylor, Kent D %A Psaty, Bruce M %A Sotoodehnia, Nona %A Brody, Jennifer A %A Rasmussen-Torvik, Laura J %A Lloyd-Jones, Donald %A Lange, Leslie A %A Wilson, James G %A Smith, Jennifer A %A Kardia, Sharon L R %A Mosley, Thomas H %A Vasan, Ramachandran S %A Arnett, Donna K %A Irvin, Marguerite R %K African Americans %K Angiotensin-Converting Enzyme Inhibitors %K Antihypertensive Agents %K Calcium Channel Blockers %K Humans %K Observational Studies as Topic %K Pharmacogenomic Variants %K Polymorphism, Single Nucleotide %K Sodium Chloride Symporter Inhibitors %K Ventricular Dysfunction, Left %X

BACKGROUND: Left ventricular (LV) hypertrophy affects up to 43% of African Americans (AAs). Antihypertensive treatment reduces LV mass (LVM). However, interindividual variation in LV traits in response to antihypertensive treatments exists. We hypothesized that genetic variants may modify the association of antihypertensive treatment class with LV traits measured by echocardiography.

METHODS: We evaluated the main effects of the three most common antihypertensive treatments for AAs as well as the single nucleotide polymorphism (SNP)-by-drug interaction on LVM and relative wall thickness (RWT) in 2,068 participants across five community-based cohorts. Treatments included thiazide diuretics (TDs), angiotensin converting enzyme inhibitors (ACE-Is), and dihydropyridine calcium channel blockers (dCCBs) and were compared in a pairwise manner. We performed fixed effects inverse variance weighted meta-analyses of main effects of drugs and 2.5 million SNP-by-drug interaction estimates.

RESULTS: We observed that dCCBs versus TDs were associated with higher LVM after adjusting for covariates (p = 0.001). We report three SNPs at a single locus on chromosome 20 that modified the association between RWT and treatment when comparing dCCBs to ACE-Is with consistent effects across cohorts (smallest p = 4.7 × 10 , minor allele frequency range 0.09-0.12). This locus has been linked to LV hypertrophy in a previous study. A marginally significant locus in BICD1 (rs326641) was validated in an external population.

CONCLUSIONS: Our study identified one locus having genome-wide significant SNP-by-drug interaction effect on RWT among dCCB users in comparison to ACE-I users. Upon additional validation in future studies, our findings can enhance the precision of medical approaches in hypertension treatment.

%B Mol Genet Genomic Med %V 7 %P e00788 %8 2019 10 %G eng %N 10 %R 10.1002/mgg3.788 %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 Mol Psychiatry %D 2020 %T Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci. %A de Las Fuentes, Lisa %A Sung, Yun Ju %A Noordam, Raymond %A Winkler, Thomas %A Feitosa, Mary F %A Schwander, Karen %A Bentley, Amy R %A Brown, Michael R %A Guo, Xiuqing %A Manning, Alisa %A Chasman, Daniel I %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Campbell, Archie %A Cheng, Ching-Yu %A Dorajoo, Rajkumar %A Hartwig, Fernando P %A Horimoto, A R V R %A Li, Changwei %A Li-Gao, Ruifang %A Liu, Yongmei %A Marten, Jonathan %A Musani, Solomon K %A Ntalla, Ioanna %A Rankinen, Tuomo %A Richard, Melissa %A Sim, Xueling %A Smith, Albert V %A Tajuddin, Salman M %A Tayo, Bamidele O %A Vojinovic, Dina %A Warren, Helen R %A Xuan, Deng %A Alver, Maris %A Boissel, Mathilde %A Chai, Jin-Fang %A Chen, Xu %A Christensen, Kaare %A Divers, Jasmin %A Evangelou, Evangelos %A Gao, Chuan %A Girotto, Giorgia %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 Rueedi, Rico %A Shu, Xiao-Ou %A Snieder, Harold %A Sofer, Tamar %A Takeuchi, Fumihiko %A Verweij, Niek %A Ware, Erin B %A Weiss, Stefan %A Yanek, Lisa R %A Amin, Najaf %A Arking, Dan E %A Arnett, Donna K %A Bergmann, Sven %A Boerwinkle, Eric %A Brody, Jennifer A %A Broeckel, Ulrich %A Brumat, Marco %A Burke, Gregory %A Cabrera, Claudia P %A Canouil, Mickaël %A Chee, Miao Li %A Chen, Yii-Der Ida %A Cocca, Massimiliano %A Connell, John %A de Silva, H Janaka %A de Vries, Paul S %A Eiriksdottir, Gudny %A Faul, Jessica D %A Fisher, Virginia %A Forrester, Terrence %A Fox, Ervin F %A Friedlander, Yechiel %A Gao, He %A Gigante, Bruna %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 %A Ikram, M Arfan %A Irvin, Marguerite R %A Kähönen, Mika %A Kavousi, Maryam %A Khor, Chiea Chuen %A Kilpeläinen, Tuomas O %A Koh, Woon-Puay %A Komulainen, Pirjo %A Kraja, Aldi T %A Krieger, J E %A Langefeld, Carl D %A Li, Yize %A Liang, Jingjing %A Liewald, David C M %A Liu, Ching-Ti %A Liu, Jianjun %A Lohman, Kurt K %A Mägi, Reedik %A McKenzie, Colin A %A Meitinger, Thomas %A Metspalu, Andres %A Milaneschi, Yuri %A Milani, Lili %A Mook-Kanamori, Dennis O %A Nalls, Mike A %A Nelson, Christopher P %A Norris, Jill M %A O'Connell, Jeff %A Ogunniyi, Adesola %A Padmanabhan, Sandosh %A Palmer, Nicholette D %A Pedersen, Nancy L %A Perls, Thomas %A Peters, Annette %A Petersmann, Astrid %A Peyser, Patricia A %A Polasek, Ozren %A Porteous, David J %A Raffel, Leslie J %A Rice, Treva K %A Rotter, Jerome I %A Rudan, Igor %A Rueda-Ochoa, Oscar-Leonel %A Sabanayagam, Charumathi %A Salako, Babatunde L %A Schreiner, Pamela J %A Shikany, James M %A Sidney, Stephen S %A Sims, Mario %A Sitlani, Colleen M %A Smith, Jennifer A %A Starr, John M %A Strauch, Konstantin %A Swertz, Morris A %A Teumer, Alexander %A Tham, Yih Chung %A Uitterlinden, André G %A Vaidya, Dhananjay %A van der Ende, M Yldau %A Waldenberger, Melanie %A Wang, Lihua %A Wang, Ya-Xing %A Wei, Wen-Bin %A Weir, David R %A Wen, Wanqing %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 Bowden, Donald W %A Deary, Ian J %A Dörr, Marcus %A Esko, Tõnu %A Freedman, Barry I %A Froguel, Philippe %A Gasparini, Paolo %A Gieger, Christian %A Jonas, Jost Bruno %A Kammerer, Candace M %A Kato, Norihiro %A Lakka, Timo A %A Leander, Karin %A Lehtimäki, Terho %A Magnusson, Patrik K E %A Marques-Vidal, Pedro %A Penninx, Brenda W J H %A Samani, Nilesh J %A van der Harst, Pim %A Wagenknecht, Lynne E %A Wu, Tangchun %A Zheng, Wei %A Zhu, Xiaofeng %A Bouchard, Claude %A Cooper, Richard S %A Correa, Adolfo %A Evans, Michele K %A Gudnason, Vilmundur %A Hayward, Caroline %A Horta, Bernardo L %A Kelly, Tanika N %A Kritchevsky, Stephen B %A Levy, Daniel %A Palmas, Walter R %A Pereira, A C %A Province, Michael M %A Psaty, Bruce M %A Ridker, Paul M %A Rotimi, Charles N %A Tai, E Shyong %A van Dam, Rob M %A van Duijn, Cornelia M %A Wong, Tien Yin %A Rice, Kenneth %A Gauderman, W James %A Morrison, Alanna C %A North, Kari E %A Kardia, Sharon L R %A Caulfield, Mark J %A Elliott, Paul %A Munroe, Patricia B %A Franks, Paul W %A Rao, Dabeeru C %A Fornage, Myriam %X

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.

%B Mol Psychiatry %8 2020 May 05 %G eng %R 10.1038/s41380-020-0719-3 %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 Eur J Epidemiol %D 2020 %T Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood. %A Zheng, Yan %A Huang, Tao %A Wang, Tiange %A Mei, Zhendong %A Sun, Zhonghan %A Zhang, Tao %A Ellervik, Christina %A Chai, Jin-Fang %A Sim, Xueling %A van Dam, Rob M %A Tai, E-Shyong %A Koh, Woon-Puay %A Dorajoo, Rajkumar %A Saw, Seang-Mei %A Sabanayagam, Charumathi %A Wong, Tien Yin %A Gupta, Preeti %A Rossing, Peter %A Ahluwalia, Tarunveer S %A Vinding, Rebecca K %A Bisgaard, Hans %A Bønnelykke, Klaus %A Wang, Yujie %A Graff, Mariaelisa %A Voortman, Trudy %A van Rooij, Frank J A %A Hofman, Albert %A van Heemst, Diana %A Noordam, Raymond %A Estampador, Angela C %A Varga, Tibor V %A Enzenbach, Cornelia %A Scholz, Markus %A Thiery, Joachim %A Burkhardt, Ralph %A Orho-Melander, Marju %A Schulz, Christina-Alexandra %A Ericson, Ulrika %A Sonestedt, Emily %A Kubo, Michiaki %A Akiyama, Masato %A Zhou, Ang %A Kilpeläinen, Tuomas O %A Hansen, Torben %A Kleber, Marcus E %A Delgado, Graciela %A McCarthy, Mark %A Lemaitre, Rozenn N %A Felix, Janine F %A Jaddoe, Vincent W V %A Wu, Ying %A Mohlke, Karen L %A Lehtimäki, Terho %A Wang, Carol A %A Pennell, Craig E %A Schunkert, Heribert %A Kessler, Thorsten %A Zeng, Lingyao %A Willenborg, Christina %A Peters, Annette %A Lieb, Wolfgang %A Grote, Veit %A Rzehak, Peter %A Koletzko, Berthold %A Erdmann, Jeanette %A Munz, Matthias %A Wu, Tangchun %A He, Meian %A Yu, Caizheng %A Lecoeur, Cécile %A Froguel, Philippe %A Corella, Dolores %A Moreno, Luis A %A Lai, Chao-Qiang %A Pitkänen, Niina %A Boreham, Colin A %A Ridker, Paul M %A Rosendaal, Frits R %A de Mutsert, Renée %A Power, Chris %A Paternoster, Lavinia %A Sørensen, Thorkild I A %A Tjønneland, Anne %A Overvad, Kim %A Djoussé, Luc %A Rivadeneira, Fernando %A Lee, Nanette R %A Raitakari, Olli T %A Kähönen, Mika %A Viikari, Jorma %A Langhendries, Jean-Paul %A Escribano, Joaquin %A Verduci, Elvira %A Dedoussis, George %A König, Inke %A Balkau, Beverley %A Coltell, Oscar %A Dallongeville, Jean %A Meirhaeghe, Aline %A Amouyel, Philippe %A Gottrand, Frédéric %A Pahkala, Katja %A Niinikoski, Harri %A Hyppönen, Elina %A März, Winfried %A Mackey, David A %A Gruszfeld, Dariusz %A Tucker, Katherine L %A Fumeron, Frédéric %A Estruch, Ramon %A Ordovas, Jose M %A Arnett, Donna K %A Mook-Kanamori, Dennis O %A Mozaffarian, Dariush %A Psaty, Bruce M %A North, Kari E %A Chasman, Daniel I %A Qi, Lu %X

Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (β = - 0.76, 95% CI - 2.45 to 1.08 mmHg), 0.06 mmHg lower diastolic blood pressure (β = - 0.06, 95% CI - 0.93 to 0.87 mmHg), or pulse pressure (β = - 0.65, 95% CI - 1.38 to 0.69 mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses.

%B Eur J Epidemiol %V 35 %P 685-697 %8 2020 Jul %G eng %N 7 %R 10.1007/s10654-020-00638-z %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 Am J Hum Genet %D 2021 %T Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry. %A Graff, Mariaelisa %A Justice, Anne E %A Young, Kristin L %A Marouli, Eirini %A Zhang, Xinruo %A Fine, Rebecca S %A Lim, Elise %A Buchanan, Victoria %A Rand, Kristin %A Feitosa, Mary F %A Wojczynski, Mary K %A Yanek, Lisa R %A Shao, Yaming %A Rohde, Rebecca %A Adeyemo, Adebowale A %A Aldrich, Melinda C %A Allison, Matthew A %A Ambrosone, Christine B %A Ambs, Stefan %A Amos, Christopher %A Arnett, Donna K %A Atwood, Larry %A Bandera, Elisa V %A Bartz, Traci %A Becker, Diane M %A Berndt, Sonja I %A Bernstein, Leslie %A Bielak, Lawrence F %A Blot, William J %A Bottinger, Erwin P %A Bowden, Donald W %A Bradfield, Jonathan P %A Brody, Jennifer A %A Broeckel, Ulrich %A Burke, Gregory %A Cade, Brian E %A Cai, Qiuyin %A Caporaso, Neil %A Carlson, Chris %A Carpten, John %A Casey, Graham %A Chanock, Stephen J %A Chen, Guanjie %A Chen, Minhui %A Chen, Yii-der I %A Chen, Wei-Min %A Chesi, Alessandra %A Chiang, Charleston W K %A Chu, Lisa %A Coetzee, Gerry A %A Conti, David V %A Cooper, Richard S %A Cushman, Mary %A Demerath, Ellen %A Deming, Sandra L %A Dimitrov, Latchezar %A Ding, Jingzhong %A Diver, W Ryan %A Duan, Qing %A Evans, Michele K %A Falusi, Adeyinka G %A Faul, Jessica D %A Fornage, Myriam %A Fox, Caroline %A Freedman, Barry I %A Garcia, Melissa %A Gillanders, Elizabeth M %A Goodman, Phyllis %A Gottesman, Omri %A Grant, Struan F A %A Guo, Xiuqing %A Hakonarson, Hakon %A Haritunians, Talin %A Harris, Tamara B %A Harris, Curtis C %A Henderson, Brian E %A Hennis, Anselm %A Hernandez, Dena G %A Hirschhorn, Joel N %A McNeill, Lorna Haughton %A Howard, Timothy D %A Howard, Barbara %A Hsing, Ann W %A Hsu, Yu-Han H %A Hu, Jennifer J %A Huff, Chad D %A Huo, Dezheng %A Ingles, Sue A %A Irvin, Marguerite R %A John, Esther M %A Johnson, Karen C %A Jordan, Joanne M %A Kabagambe, Edmond K %A Kang, Sun J %A Kardia, Sharon L %A Keating, Brendan J %A Kittles, Rick A %A Klein, Eric A %A Kolb, Suzanne %A Kolonel, Laurence N %A Kooperberg, Charles %A Kuller, Lewis %A Kutlar, Abdullah %A Lange, Leslie %A Langefeld, Carl D %A Le Marchand, Loïc %A Leonard, Hampton %A Lettre, Guillaume %A Levin, Albert M %A Li, Yun %A Li, Jin %A Liu, Yongmei %A Liu, Youfang %A Liu, Simin %A Lohman, Kurt %A Lotay, Vaneet %A Lu, Yingchang %A Maixner, William %A Manson, JoAnn E %A McKnight, Barbara %A Meng, Yan %A Monda, Keri L %A Monroe, Kris %A Moore, Jason H %A Mosley, Thomas H %A Mudgal, Poorva %A Murphy, Adam B %A Nadukuru, Rajiv %A Nalls, Mike A %A Nathanson, Katherine L %A Nayak, Uma %A N'diaye, Amidou %A Nemesure, Barbara %A Neslund-Dudas, Christine %A Neuhouser, Marian L %A Nyante, Sarah %A Ochs-Balcom, Heather %A Ogundiran, Temidayo O %A Ogunniyi, Adesola %A Ojengbede, Oladosu %A Okut, Hayrettin %A Olopade, Olufunmilayo I %A Olshan, Andrew %A Padhukasahasram, Badri %A Palmer, Julie %A Palmer, Cameron D %A Palmer, Nicholette D %A Papanicolaou, George %A Patel, Sanjay R %A Pettaway, Curtis A %A Peyser, Patricia A %A Press, Michael F %A Rao, D C %A Rasmussen-Torvik, Laura J %A Redline, Susan %A Reiner, Alex P %A Rhie, Suhn K %A Rodriguez-Gil, Jorge L %A Rotimi, Charles N %A Rotter, Jerome I %A Ruiz-Narvaez, Edward A %A Rybicki, Benjamin A %A Salako, Babatunde %A Sale, Michèle M %A Sanderson, Maureen %A Schadt, Eric %A Schreiner, Pamela J %A Schurmann, Claudia %A Schwartz, Ann G %A Shriner, Daniel A %A Signorello, Lisa B %A Singleton, Andrew B %A Siscovick, David S %A Smith, Jennifer A %A Smith, Shad %A Speliotes, Elizabeth %A Spitz, Margaret %A Stanford, Janet L %A Stevens, Victoria L %A Stram, Alex %A Strom, Sara S %A Sucheston, Lara %A Sun, Yan V %A Tajuddin, Salman M %A Taylor, Herman %A Taylor, Kira %A Tayo, Bamidele O %A Thun, Michael J %A Tucker, Margaret A %A Vaidya, Dhananjay %A Van Den Berg, David J %A Vedantam, Sailaja %A Vitolins, Mara %A Wang, Zhaoming %A Ware, Erin B %A Wassertheil-Smoller, Sylvia %A Weir, David R %A Wiencke, John K %A Williams, Scott M %A Williams, L Keoki %A Wilson, James G %A Witte, John S %A Wrensch, Margaret %A Wu, Xifeng %A Yao, Jie %A Zakai, Neil %A Zanetti, Krista %A Zemel, Babette S %A Zhao, Wei %A Zhao, Jing Hua %A Zheng, Wei %A Zhi, Degui %A Zhou, Jie %A Zhu, Xiaofeng %A Ziegler, Regina G %A Zmuda, Joe %A Zonderman, Alan B %A Psaty, Bruce M %A Borecki, Ingrid B %A Cupples, L Adrienne %A Liu, Ching-Ti %A Haiman, Christopher A %A Loos, Ruth %A Ng, Maggie C Y %A North, Kari E %X

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

%B Am J Hum Genet %V 108 %P 564-582 %8 2021 Apr 01 %G eng %N 4 %R 10.1016/j.ajhg.2021.02.011 %0 Journal Article %J PLoS One %D 2021 %T Identification of novel and rare variants associated with handgrip strength using whole genome sequence data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program. %A Sarnowski, Chloe %A Chen, Han %A Biggs, Mary L %A Wassertheil-Smoller, Sylvia %A Bressler, Jan %A Irvin, Marguerite R %A Ryan, Kathleen A %A Karasik, David %A Arnett, Donna K %A Cupples, L Adrienne %A Fardo, David W %A Gogarten, Stephanie M %A Heavner, Benjamin D %A Jain, Deepti %A Kang, Hyun Min %A Kooperberg, Charles %A Mainous, Arch G %A Mitchell, Braxton D %A Morrison, Alanna C %A O'Connell, Jeffrey R %A Psaty, Bruce M %A Rice, Kenneth %A Smith, Albert V %A Vasan, Ramachandran S %A Windham, B Gwen %A Kiel, Douglas P %A Murabito, Joanne M %A Lunetta, Kathryn L %X

Handgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7-12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings.

%B PLoS One %V 16 %P e0253611 %8 2021 %G eng %N 7 %R 10.1371/journal.pone.0253611 %0 Journal Article %J HGG Adv %D 2021 %T Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. %A Sun, Daokun %A Richard, Melissa %A Musani, Solomon K %A Sung, Yun Ju %A Winkler, Thomas W %A Schwander, Karen %A Chai, Jin Fang %A Guo, Xiuqing %A Kilpeläinen, Tuomas O %A Vojinovic, Dina %A Aschard, Hugues %A Bartz, Traci M %A Bielak, Lawrence F %A Brown, Michael R %A Chitrala, Kumaraswamy %A Hartwig, Fernando P %A Horimoto, Andrea R V R %A Liu, Yongmei %A Manning, Alisa K %A Noordam, Raymond %A Smith, Albert V %A Harris, Sarah E %A Kuhnel, Brigitte %A Lyytikäinen, Leo-Pekka %A Nolte, Ilja M %A Rauramaa, Rainer %A van der Most, Peter J %A Wang, Rujia %A Ware, Erin B %A Weiss, Stefan %A Wen, Wanqing %A Yanek, Lisa R %A Arking, Dan E %A Arnett, Donna K %A Barac, Ana %A Boerwinkle, Eric %A Broeckel, Ulrich %A Chakravarti, Aravinda %A Chen, Yii-Der Ida %A Cupples, L Adrienne %A Davigulus, Martha L %A de Las Fuentes, Lisa %A de Mutsert, Renée %A de Vries, Paul S %A Delaney, Joseph A C %A Roux, Ana V Diez %A Dörr, Marcus %A Faul, Jessica D %A Fretts, Amanda M %A Gallo, Linda C %A Grabe, Hans Jörgen %A Gu, C Charles %A Harris, Tamara B %A Hartman, Catharina C A %A Heikkinen, Sami %A Ikram, M Arfan %A Isasi, Carmen %A Johnson, W Craig %A Jonas, Jost Bruno %A Kaplan, Robert C %A Komulainen, Pirjo %A Krieger, Jose E %A Levy, Daniel %A Liu, Jianjun %A Lohman, Kurt %A Luik, Annemarie I %A Martin, Lisa W %A Meitinger, Thomas %A Milaneschi, Yuri %A O'Connell, Jeff R %A Palmas, Walter R %A Peters, Annette %A Peyser, Patricia A %A Pulkki-Råback, Laura %A Raffel, Leslie J %A Reiner, Alex P %A Rice, Kenneth %A Robinson, Jennifer G %A Rosendaal, Frits R %A Schmidt, Carsten Oliver %A Schreiner, Pamela J %A Schwettmann, Lars %A Shikany, James M %A Shu, Xiao-Ou %A Sidney, Stephen %A Sims, Mario %A Smith, Jennifer A %A Sotoodehnia, Nona %A Strauch, Konstantin %A Tai, E Shyong %A Taylor, Kent %A Uitterlinden, André G %A van Duijn, Cornelia M %A Waldenberger, Melanie %A Wee, Hwee-Lin %A Wei, Wen-Bin %A Wilson, Gregory %A Xuan, Deng %A Yao, Jie %A Zeng, Donglin %A Zhao, Wei %A Zhu, Xiaofeng %A Zonderman, Alan B %A Becker, Diane M %A Deary, Ian J %A Gieger, Christian %A Lakka, Timo A %A Lehtimäki, Terho %A North, Kari E %A Oldehinkel, Albertine J %A Penninx, Brenda W J H %A Snieder, Harold %A Wang, Ya-Xing %A Weir, David R %A Zheng, Wei %A Evans, Michele K %A Gauderman, W James %A Gudnason, Vilmundur %A Horta, Bernardo L %A Liu, Ching-Ti %A Mook-Kanamori, Dennis O %A Morrison, Alanna C %A Pereira, Alexandre C %A Psaty, Bruce M %A Amin, Najaf %A Fox, Ervin R %A Kooperberg, Charles %A Sim, Xueling %A Bierut, Laura %A Rotter, Jerome I %A Kardia, Sharon L R %A Franceschini, Nora %A Rao, Dabeeru C %A Fornage, Myriam %X

Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p value <5e-8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (), synaptic function and neurotransmission (), as well as genes previously implicated in neuropsychiatric or stress-related disorders (). These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.

%B HGG Adv %V 2 %8 2021 Jan 14 %G eng %N 1 %R 10.1016/j.xhgg.2020.100013 %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 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 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 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 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 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 Hum Mol Genet %D 2022 %T Whole-Exome Sequencing Study Identifies Four Novel Gene Loci Associated with Diabetic Kidney Disease. %A Pan, Yang %A Sun, Xiao %A Mi, Xuenan %A Huang, Zhijie %A Hsu, Yenchih %A Hixson, James E %A Munzy, Donna %A Metcalf, Ginger %A Franceschini, Nora %A Tin, Adrienne %A Köttgen, Anna %A Francis, Michael %A Brody, Jennifer A %A Kestenbaum, Bryan %A Sitlani, Colleen M %A Mychaleckyj, Josyf C %A Kramer, Holly %A Lange, Leslie A %A Guo, Xiuqing %A Hwang, Shih-Jen %A Irvin, Marguerite R %A Smith, Jennifer A %A Yanek, Lisa R %A Vaidya, Dhananjay %A Chen, Yii-Der Ida %A Fornage, Myriam %A Lloyd-Jones, Donald M %A Hou, Lifang %A Mathias, Rasika A %A Mitchell, Braxton D %A Peyser, Patricia A %A Kardia, Sharon L R %A Arnett, Donna K %A Correa, Adolfo %A Raffield, Laura M %A Vasan, Ramachandran S %A Cupple, L Adrienne %A Levy, Daniel %A Kaplan, Robert C %A North, Kari E %A Rotter, Jerome I %A Kooperberg, Charles %A Reiner, Alexander P %A Psaty, Bruce M %A Tracy, Russell P %A Gibbs, Richard A %A Morrison, Alanna C %A Feldman, Harold %A Boerwinkle, Eric %A He, Jiang %A Kelly, Tanika N %X

Diabetic kidney disease (DKD) is recognized as an important public health challenge. However, its genomic mechanisms are poorly understood. To identify rare variants for DKD, we conducted a whole-exome sequencing (WES) study leveraging large cohorts well-phenotyped for chronic kidney disease (CKD) and diabetes. Our two-stage whole-exome sequencing study included 4372 European and African ancestry participants from the Chronic Renal Insufficiency Cohort (CRIC) and Atherosclerosis Risk in Communities (ARIC) studies (stage-1) and 11 487 multi-ancestry Trans-Omics for Precision Medicine (TOPMed) participants (stage-2). Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex, and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test (SKAT-O) implemented within our mixed model framework. We identified four novel exome-wide significant DKD-related loci through initiating diabetes. In single variant analyses, participants carrying a rare, in-frame insertion in the DIS3L2 gene (rs141560952) exhibited a 193-fold increased odds (95% confidence interval: 33.6, 1105) of DKD compared with non-carriers (P = 3.59 × 10-9). Likewise, each copy of a low-frequency KRT6B splice-site variant (rs425827) conferred a 5.31-fold higher odds (95% confidence interval: 3.06, 9.21) of DKD (P = 2.72 × 10-9). Aggregate gene-based analyses further identified ERAP2 (P = 4.03 × 10-8) and NPEPPS (P = 1.51 × 10-7), which are both expressed in the kidney and implicated in renin-angiotensin-aldosterone system modulated immune response. In the largest WES study of DKD, we identified novel rare variant loci attaining exome-wide significance. These findings provide new insights into the molecular mechanisms underlying DKD.

%B Hum Mol Genet %8 2022 Nov 29 %G eng %R 10.1093/hmg/ddac290 %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 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 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 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 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