TY - JOUR T1 - Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study. JF - Hum Mol Genet Y1 - 2011 A1 - Fox, Ervin R A1 - Young, J Hunter A1 - Li, Yali A1 - Dreisbach, Albert W A1 - Keating, Brendan J A1 - Musani, Solomon K A1 - Liu, Kiang A1 - Morrison, Alanna C A1 - Ganesh, Santhi A1 - Kutlar, Abdullah A1 - Ramachandran, Vasan S A1 - Polak, Josef F A1 - Fabsitz, Richard R A1 - Dries, Daniel L A1 - Farlow, Deborah N A1 - Redline, Susan A1 - Adeyemo, Adebowale A1 - Hirschorn, Joel N A1 - Sun, Yan V A1 - Wyatt, Sharon B A1 - Penman, Alan D A1 - Palmas, Walter A1 - Rotter, Jerome I A1 - Townsend, Raymond R A1 - Doumatey, Ayo P A1 - Tayo, Bamidele O A1 - Mosley, Thomas H A1 - Lyon, Helen N A1 - Kang, Sun J A1 - Rotimi, Charles N A1 - Cooper, Richard S A1 - Franceschini, Nora A1 - Curb, J David A1 - Martin, Lisa W A1 - Eaton, Charles B A1 - Kardia, Sharon L R A1 - Taylor, Herman A A1 - Caulfield, Mark J A1 - Ehret, Georg B A1 - Johnson, Toby A1 - Chakravarti, Aravinda A1 - Zhu, Xiaofeng A1 - Levy, Daniel KW - Adult KW - African Americans KW - Aged KW - Blood Pressure KW - Cohort Studies KW - Diastole KW - European Continental Ancestry Group KW - Female KW - Genetic Loci KW - Genome-Wide Association Study KW - Genotype KW - Humans KW - Hypertension KW - Male KW - Middle Aged KW - Phenotype KW - Polymorphism, Single Nucleotide KW - Systole AB -

The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10(-8)) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10(-8)). The top IBC association for SBP was rs2012318 (P= 6.4 × 10(-6)) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10(-6)) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexity.

VL - 20 IS - 11 U1 - http://www.ncbi.nlm.nih.gov/pubmed/21378095?dopt=Abstract ER - TY - JOUR T1 - Associations between incident ischemic stroke events and stroke and cardiovascular disease-related genome-wide association studies single nucleotide polymorphisms in the Population Architecture Using Genomics and Epidemiology study. JF - Circ Cardiovasc Genet Y1 - 2012 A1 - Carty, Cara L A1 - Bůzková, Petra A1 - Fornage, Myriam A1 - Franceschini, Nora A1 - Cole, Shelley A1 - Heiss, Gerardo A1 - Hindorff, Lucia A A1 - Howard, Barbara V A1 - Mann, Sue A1 - Martin, Lisa W A1 - Zhang, Ying A1 - Matise, Tara C A1 - Prentice, Ross A1 - Reiner, Alexander P A1 - Kooperberg, Charles KW - Aged KW - Aged, 80 and over KW - Cardiovascular Diseases KW - Cholesterol, HDL KW - Cholesterol, LDL KW - European Continental Ancestry Group KW - Female KW - Genetics, Population KW - Genome-Wide Association Study KW - Genomics KW - Humans KW - Male KW - Middle Aged KW - Polymorphism, Single Nucleotide KW - Risk Factors KW - Stroke KW - Triglycerides AB -

BACKGROUND: Genome-wide association studies (GWAS) have identified loci associated with ischemic stroke (IS) and cardiovascular disease (CVD) in European-descent individuals, but their replication in different populations has been largely unexplored.

METHODS AND RESULTS: Nine single nucleotide polymorphisms (SNPs) selected from GWAS and meta-analyses of stroke, and 86 SNPs previously associated with myocardial infarction and CVD risk factors, including blood lipids (high density lipoprotein [HDL], low density lipoprotein [LDL], and triglycerides), type 2 diabetes, and body mass index (BMI), were investigated for associations with incident IS in European Americans (EA) N=26 276, African-Americans (AA) N=8970, and American Indians (AI) N=3570 from the Population Architecture using Genomics and Epidemiology Study. Ancestry-specific fixed effects meta-analysis with inverse variance weighting was used to combine study-specific log hazard ratios from Cox proportional hazards models. Two of 9 stroke SNPs (rs783396 and rs1804689) were significantly associated with [corrected] IS hazard in AA; none were significant in this large EA cohort. Of 73 CVD risk factor SNPs tested in EA, 2 (HDL and triglycerides SNPs) were associated with IS. In AA, SNPs associated with LDL, HDL, and BMI were significantly associated with IS (3 of 86 SNPs tested). Out of 58 SNPs tested in AI, 1 LDL SNP was significantly associated with IS.

CONCLUSIONS: Our analyses showing lack of replication in spite of reasonable power for many stroke SNPs and differing results by ancestry highlight the need to follow up on GWAS findings and conduct genetic association studies in diverse populations. We found modest IS associations with BMI and lipids SNPs, though these findings require confirmation.

VL - 5 IS - 2 U1 - http://www.ncbi.nlm.nih.gov/pubmed/22403240?dopt=Abstract ER - TY - JOUR T1 - Evidence of heterogeneity by race/ethnicity in genetic determinants of QT interval. JF - Epidemiology Y1 - 2014 A1 - Seyerle, Amanda A A1 - Young, Alicia M A1 - Jeff, Janina M A1 - Melton, Phillip E A1 - Jorgensen, Neal W A1 - Lin, Yi A1 - Carty, Cara L A1 - Deelman, Ewa A1 - Heckbert, Susan R A1 - Hindorff, Lucia A A1 - Jackson, Rebecca D A1 - Martin, Lisa W A1 - Okin, Peter M A1 - Perez, Marco V A1 - Psaty, Bruce M A1 - Soliman, Elsayed Z A1 - Whitsel, Eric A A1 - North, Kari E A1 - Laston, Sandra A1 - Kooperberg, Charles A1 - Avery, Christy L KW - Aged KW - Continental Population Groups KW - Electrocardiography KW - Female KW - Genetic Predisposition to Disease KW - Haplotypes KW - Humans KW - Long QT Syndrome KW - Male KW - Middle Aged KW - Phenotype KW - Polymorphism, Single Nucleotide KW - Quantitative Trait Loci KW - Quantitative Trait, Heritable KW - Risk Factors AB -

BACKGROUND: QT interval (QT) prolongation is an established risk factor for ventricular tachyarrhythmia and sudden cardiac death. Previous genome-wide association studies in populations of the European descent have identified multiple genetic loci that influence QT, but few have examined these loci in ethnically diverse populations.

METHODS: Here, we examine the direction, magnitude, and precision of effect sizes for 21 previously reported SNPs from 12 QT loci, in populations of European (n = 16,398), African (n = 5,437), American Indian (n = 5,032), Hispanic (n = 1,143), and Asian (n = 932) descent as part of the Population Architecture using Genomics and Epidemiology (PAGE) study. Estimates obtained from linear regression models stratified by race/ethnicity were combined using inverse-variance weighted meta-analysis. Heterogeneity was evaluated using Cochran's Q test.

RESULTS: Of 21 SNPs, 7 showed consistent direction of effect across all 5 populations, and an additional 9 had estimated effects that were consistent across 4 populations. Despite consistent direction of effect, 9 of 16 SNPs had evidence (P < 0.05) of heterogeneity by race/ethnicity. For these 9 SNPs, linkage disequilibrium plots often indicated substantial variation in linkage disequilibrium patterns among the various racial/ethnic groups, as well as possible allelic heterogeneity.

CONCLUSIONS: These results emphasize the importance of analyzing racial/ethnic groups separately in genetic studies. Furthermore, they underscore the possible utility of trans-ethnic studies to pinpoint underlying casual variants influencing heritable traits such as QT.

VL - 25 IS - 6 U1 - http://www.ncbi.nlm.nih.gov/pubmed/25166880?dopt=Abstract ER - TY - JOUR T1 - Large multiethnic Candidate Gene Study for C-reactive protein levels: identification of a novel association at CD36 in African Americans. JF - Hum Genet Y1 - 2014 A1 - Ellis, Jaclyn A1 - Lange, Ethan M A1 - Li, Jin A1 - Dupuis, Josée A1 - Baumert, Jens A1 - Walston, Jeremy D A1 - Keating, Brendan J A1 - Durda, Peter A1 - Fox, Ervin R A1 - Palmer, Cameron D A1 - Meng, Yan A A1 - Young, Taylor A1 - Farlow, Deborah N A1 - Schnabel, Renate B A1 - Marzi, Carola S A1 - Larkin, Emma A1 - Martin, Lisa W A1 - Bis, Joshua C A1 - Auer, Paul A1 - Ramachandran, Vasan S A1 - Gabriel, Stacey B A1 - Willis, Monte S A1 - Pankow, James S A1 - Papanicolaou, George J A1 - Rotter, Jerome I A1 - Ballantyne, Christie M A1 - Gross, Myron D A1 - Lettre, Guillaume A1 - Wilson, James G A1 - Peters, Ulrike A1 - Koenig, Wolfgang A1 - Tracy, Russell P A1 - Redline, Susan A1 - Reiner, Alex P A1 - Benjamin, Emelia J A1 - Lange, Leslie A KW - Adult KW - African Americans KW - Aged KW - Biomarkers KW - C-Reactive Protein KW - Cardiovascular Diseases KW - CD36 Antigens KW - Female KW - Genetic Loci KW - Genetic Predisposition to Disease KW - Genetics, Population KW - Genome-Wide Association Study KW - Humans KW - Meta-Analysis as Topic KW - Middle Aged KW - Polymorphism, Single Nucleotide KW - Risk Factors AB -

C-reactive protein (CRP) is a heritable biomarker of systemic inflammation and a predictor of cardiovascular disease (CVD). Large-scale genetic association studies for CRP have largely focused on individuals of European descent. We sought to uncover novel genetic variants for CRP in a multiethnic sample using the ITMAT Broad-CARe (IBC) array, a custom 50,000 SNP gene-centric array having dense coverage of over 2,000 candidate CVD genes. We performed analyses on 7,570 African Americans (AA) from the Candidate gene Association Resource (CARe) study and race-combined meta-analyses that included 29,939 additional individuals of European descent from CARe, the Women's Health Initiative (WHI) and KORA studies. We observed array-wide significance (p < 2.2 × 10(-6)) for four loci in AA, three of which have been reported previously in individuals of European descent (IL6R, p = 2.0 × 10(-6); CRP, p = 4.2 × 10(-71); APOE, p = 1.6 × 10(-6)). The fourth significant locus, CD36 (p = 1.6 × 10(-6)), was observed at a functional variant (rs3211938) that is extremely rare in individuals of European descent. We replicated the CD36 finding (p = 1.8 × 10(-5)) in an independent sample of 8,041 AA women from WHI; a meta-analysis combining the CARe and WHI AA results at rs3211938 reached genome-wide significance (p = 1.5 × 10(-10)). In the race-combined meta-analyses, 13 loci reached significance, including ten (CRP, TOMM40/APOE/APOC1, HNF1A, LEPR, GCKR, IL6R, IL1RN, NLRP3, HNF4A and BAZ1B/BCL7B) previously associated with CRP, and one (ARNTL) previously reported to be nominally associated with CRP. Two novel loci were also detected (RPS6KB1, p = 2.0 × 10(-6); CD36, p = 1.4 × 10(-6)). These results highlight both shared and unique genetic risk factors for CRP in AA compared to populations of European descent.

VL - 133 IS - 8 U1 - http://www.ncbi.nlm.nih.gov/pubmed/24643644?dopt=Abstract ER - TY - JOUR T1 - Loss-of-function mutations in APOC3, triglycerides, and coronary disease. JF - N Engl J Med Y1 - 2014 A1 - Crosby, Jacy A1 - Peloso, Gina M A1 - Auer, Paul L A1 - Crosslin, David R A1 - Stitziel, Nathan O A1 - Lange, Leslie A A1 - Lu, Yingchang A1 - Tang, Zheng-Zheng A1 - Zhang, He A1 - Hindy, George A1 - Masca, Nicholas A1 - Stirrups, Kathleen A1 - Kanoni, Stavroula A1 - Do, Ron A1 - Jun, Goo A1 - Hu, Youna A1 - Kang, Hyun Min A1 - Xue, Chenyi A1 - Goel, Anuj A1 - Farrall, Martin A1 - Duga, Stefano A1 - Merlini, Pier Angelica A1 - Asselta, Rosanna A1 - Girelli, Domenico A1 - Olivieri, Oliviero A1 - Martinelli, Nicola A1 - Yin, Wu A1 - Reilly, Dermot A1 - Speliotes, Elizabeth A1 - Fox, Caroline S A1 - Hveem, Kristian A1 - Holmen, Oddgeir L A1 - Nikpay, Majid A1 - Farlow, Deborah N A1 - Assimes, Themistocles L A1 - Franceschini, Nora A1 - Robinson, Jennifer A1 - North, Kari E A1 - Martin, Lisa W A1 - DePristo, Mark A1 - Gupta, Namrata A1 - Escher, Stefan A A1 - Jansson, Jan-Håkan A1 - Van Zuydam, Natalie A1 - Palmer, Colin N A A1 - Wareham, Nicholas A1 - Koch, Werner A1 - Meitinger, Thomas A1 - Peters, Annette A1 - Lieb, Wolfgang A1 - Erbel, Raimund A1 - König, Inke R A1 - Kruppa, Jochen A1 - Degenhardt, Franziska A1 - Gottesman, Omri A1 - Bottinger, Erwin P A1 - O'Donnell, Christopher J A1 - Psaty, Bruce M A1 - Ballantyne, Christie M A1 - Abecasis, Goncalo A1 - Ordovas, Jose M A1 - Melander, Olle A1 - Watkins, Hugh A1 - Orho-Melander, Marju A1 - Ardissino, Diego A1 - Loos, Ruth J F A1 - McPherson, Ruth A1 - Willer, Cristen J A1 - Erdmann, Jeanette A1 - Hall, Alistair S A1 - Samani, Nilesh J A1 - Deloukas, Panos A1 - Schunkert, Heribert A1 - Wilson, James G A1 - Kooperberg, Charles A1 - Rich, Stephen S A1 - Tracy, Russell P A1 - Lin, Dan-Yu A1 - Altshuler, David A1 - Gabriel, Stacey A1 - Nickerson, Deborah A A1 - Jarvik, Gail P A1 - Cupples, L Adrienne A1 - Reiner, Alex P A1 - Boerwinkle, Eric A1 - Kathiresan, Sekar KW - African Continental Ancestry Group KW - Apolipoprotein C-III KW - Coronary Disease KW - European Continental Ancestry Group KW - Exome KW - Genotype KW - Heterozygote KW - Humans KW - Liver KW - Mutation KW - Risk Factors KW - Sequence Analysis, DNA KW - Triglycerides AB -

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

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

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

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

VL - 371 IS - 1 U1 - http://www.ncbi.nlm.nih.gov/pubmed/24941081?dopt=Abstract ER - TY - JOUR T1 - Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol. JF - Am J Hum Genet Y1 - 2014 A1 - Lange, Leslie A A1 - Hu, Youna A1 - Zhang, He A1 - Xue, Chenyi A1 - Schmidt, Ellen M A1 - Tang, Zheng-Zheng A1 - Bizon, Chris A1 - Lange, Ethan M A1 - Smith, Joshua D A1 - Turner, Emily H A1 - Jun, Goo A1 - Kang, Hyun Min A1 - Peloso, Gina A1 - Auer, Paul A1 - Li, Kuo-Ping A1 - Flannick, Jason A1 - Zhang, Ji A1 - Fuchsberger, Christian A1 - Gaulton, Kyle A1 - Lindgren, Cecilia A1 - Locke, Adam A1 - Manning, Alisa A1 - Sim, Xueling A1 - Rivas, Manuel A A1 - Holmen, Oddgeir L A1 - Gottesman, Omri A1 - Lu, Yingchang A1 - Ruderfer, Douglas A1 - Stahl, Eli A A1 - Duan, Qing A1 - Li, Yun A1 - Durda, Peter A1 - Jiao, Shuo A1 - Isaacs, Aaron A1 - Hofman, Albert A1 - Bis, Joshua C A1 - Correa, Adolfo A1 - Griswold, Michael E A1 - Jakobsdottir, Johanna A1 - Smith, Albert V A1 - Schreiner, Pamela J A1 - Feitosa, Mary F A1 - Zhang, Qunyuan A1 - Huffman, Jennifer E A1 - Crosby, Jacy A1 - Wassel, Christina L A1 - Do, Ron A1 - Franceschini, Nora A1 - Martin, Lisa W A1 - Robinson, Jennifer G A1 - Assimes, Themistocles L A1 - Crosslin, David R A1 - Rosenthal, Elisabeth A A1 - Tsai, Michael A1 - Rieder, Mark J A1 - Farlow, Deborah N A1 - Folsom, Aaron R A1 - Lumley, Thomas A1 - Fox, Ervin R A1 - Carlson, Christopher S A1 - Peters, Ulrike A1 - Jackson, Rebecca D A1 - van Duijn, Cornelia M A1 - Uitterlinden, André G A1 - Levy, Daniel A1 - Rotter, Jerome I A1 - Taylor, Herman A A1 - Gudnason, Vilmundur A1 - Siscovick, David S A1 - Fornage, Myriam A1 - Borecki, Ingrid B A1 - Hayward, Caroline A1 - Rudan, Igor A1 - Chen, Y Eugene A1 - Bottinger, Erwin P A1 - Loos, Ruth J F A1 - Sætrom, Pål A1 - Hveem, Kristian A1 - Boehnke, Michael A1 - Groop, Leif A1 - McCarthy, Mark A1 - Meitinger, Thomas A1 - Ballantyne, Christie M A1 - Gabriel, Stacey B A1 - O'Donnell, Christopher J A1 - Post, Wendy S A1 - North, Kari E A1 - Reiner, Alexander P A1 - Boerwinkle, Eric A1 - Psaty, Bruce M A1 - Altshuler, David A1 - Kathiresan, Sekar A1 - Lin, Dan-Yu A1 - Jarvik, Gail P A1 - Cupples, L Adrienne A1 - Kooperberg, Charles A1 - Wilson, James G A1 - Nickerson, Deborah A A1 - Abecasis, Goncalo R A1 - Rich, Stephen S A1 - Tracy, Russell P A1 - Willer, Cristen J KW - Adult KW - Aged KW - Apolipoproteins E KW - Cholesterol, LDL KW - Cohort Studies KW - Dyslipidemias KW - Exome KW - Female KW - Follow-Up Studies KW - Gene Frequency KW - Genetic Code KW - Genome-Wide Association Study KW - Genotype KW - Humans KW - Lipase KW - Male KW - Middle Aged KW - Phenotype KW - Polymorphism, Single Nucleotide KW - Proprotein Convertase 9 KW - Proprotein Convertases KW - Receptors, LDL KW - Sequence Analysis, DNA KW - Serine Endopeptidases AB -

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

VL - 94 IS - 2 U1 - http://www.ncbi.nlm.nih.gov/pubmed/24507775?dopt=Abstract ER - TY - JOUR T1 - Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci. JF - Nat Genet Y1 - 2016 A1 - Liu, Chunyu A1 - Kraja, Aldi T A1 - Smith, Jennifer A A1 - Brody, Jennifer A A1 - Franceschini, Nora A1 - Bis, Joshua C A1 - Rice, Kenneth A1 - Morrison, Alanna C A1 - Lu, Yingchang A1 - Weiss, Stefan A1 - Guo, Xiuqing A1 - Palmas, Walter A1 - Martin, Lisa W A1 - Chen, Yii-Der Ida A1 - Surendran, Praveen A1 - Drenos, Fotios A1 - Cook, James P A1 - Auer, Paul L A1 - Chu, Audrey Y A1 - Giri, Ayush A1 - Zhao, Wei A1 - Jakobsdottir, Johanna A1 - Lin, Li-An A1 - Stafford, Jeanette M A1 - Amin, Najaf A1 - Mei, Hao A1 - Yao, Jie A1 - Voorman, Arend A1 - Larson, Martin G A1 - Grove, Megan L A1 - Smith, Albert V A1 - Hwang, Shih-Jen A1 - Chen, Han A1 - Huan, Tianxiao A1 - Kosova, Gulum A1 - Stitziel, Nathan O A1 - Kathiresan, Sekar A1 - Samani, Nilesh A1 - Schunkert, Heribert A1 - Deloukas, Panos A1 - Li, Man A1 - Fuchsberger, Christian A1 - Pattaro, Cristian A1 - Gorski, Mathias A1 - Kooperberg, Charles A1 - Papanicolaou, George J A1 - Rossouw, Jacques E A1 - Faul, Jessica D A1 - Kardia, Sharon L R A1 - Bouchard, Claude A1 - Raffel, Leslie J A1 - Uitterlinden, André G A1 - Franco, Oscar H A1 - Vasan, Ramachandran S A1 - O'Donnell, Christopher J A1 - Taylor, Kent D A1 - Liu, Kiang A1 - Bottinger, Erwin P A1 - Gottesman, Omri A1 - Daw, E Warwick A1 - Giulianini, Franco A1 - Ganesh, Santhi A1 - Salfati, Elias A1 - Harris, Tamara B A1 - Launer, Lenore J A1 - Dörr, Marcus A1 - Felix, Stephan B A1 - Rettig, Rainer A1 - Völzke, Henry A1 - Kim, Eric A1 - Lee, Wen-Jane A1 - Lee, I-Te A1 - Sheu, Wayne H-H A1 - Tsosie, Krystal S A1 - Edwards, Digna R Velez A1 - Liu, Yongmei A1 - Correa, Adolfo A1 - Weir, David R A1 - Völker, Uwe A1 - Ridker, Paul M A1 - Boerwinkle, Eric A1 - Gudnason, Vilmundur A1 - Reiner, Alexander P A1 - van Duijn, Cornelia M A1 - Borecki, Ingrid B A1 - Edwards, Todd L A1 - Chakravarti, Aravinda A1 - Rotter, Jerome I A1 - Psaty, Bruce M A1 - Loos, Ruth J F A1 - Fornage, Myriam A1 - Ehret, Georg B A1 - Newton-Cheh, Christopher A1 - Levy, Daniel A1 - Chasman, Daniel I AB -

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure-associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein-protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure-associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

VL - 48 IS - 10 ER - TY - JOUR T1 - Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations. JF - PLoS Genet Y1 - 2017 A1 - Liang, Jingjing A1 - Le, Thu H A1 - Edwards, Digna R Velez A1 - Tayo, Bamidele O A1 - Gaulton, Kyle J A1 - Smith, Jennifer A A1 - Lu, Yingchang A1 - Jensen, Richard A A1 - Chen, Guanjie A1 - Yanek, Lisa R A1 - Schwander, Karen A1 - Tajuddin, Salman M A1 - Sofer, Tamar A1 - Kim, Wonji A1 - Kayima, James A1 - McKenzie, Colin A A1 - Fox, Ervin A1 - Nalls, Michael A A1 - Young, J Hunter A1 - Sun, Yan V A1 - Lane, Jacqueline M A1 - Cechova, Sylvia A1 - Zhou, Jie A1 - Tang, Hua A1 - Fornage, Myriam A1 - Musani, Solomon K A1 - Wang, Heming A1 - Lee, Juyoung A1 - Adeyemo, Adebowale A1 - Dreisbach, Albert W A1 - Forrester, Terrence A1 - Chu, Pei-Lun A1 - Cappola, Anne A1 - Evans, Michele K A1 - Morrison, Alanna C A1 - Martin, Lisa W A1 - Wiggins, Kerri L A1 - Hui, Qin A1 - Zhao, Wei A1 - Jackson, Rebecca D A1 - Ware, Erin B A1 - Faul, Jessica D A1 - Reiner, Alex P A1 - Bray, Michael A1 - Denny, Joshua C A1 - Mosley, Thomas H A1 - Palmas, Walter A1 - Guo, Xiuqing A1 - Papanicolaou, George J A1 - Penman, Alan D A1 - Polak, Joseph F A1 - Rice, Kenneth A1 - Taylor, Ken D A1 - Boerwinkle, Eric A1 - Bottinger, Erwin P A1 - Liu, Kiang A1 - Risch, Neil A1 - Hunt, Steven C A1 - Kooperberg, Charles A1 - Zonderman, Alan B A1 - Laurie, Cathy C A1 - Becker, Diane M A1 - Cai, Jianwen A1 - Loos, Ruth J F A1 - Psaty, Bruce M A1 - Weir, David R A1 - Kardia, Sharon L R A1 - Arnett, Donna K A1 - Won, Sungho A1 - Edwards, Todd L A1 - Redline, Susan A1 - Cooper, Richard S A1 - Rao, D C A1 - Rotter, Jerome I A1 - Rotimi, Charles A1 - Levy, Daniel A1 - Chakravarti, Aravinda A1 - Zhu, Xiaofeng A1 - Franceschini, Nora KW - African Americans KW - Animals KW - Basic Helix-Loop-Helix Transcription Factors KW - Blood Pressure KW - Cadherins KW - Case-Control Studies KW - Female KW - Genetic Loci KW - Genome-Wide Association Study KW - Humans KW - Hypertension KW - Male KW - Membrane Proteins KW - Mice KW - Multifactorial Inheritance KW - Polymorphism, Single Nucleotide AB -

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.

VL - 13 IS - 5 ER - TY - JOUR T1 - Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration. JF - Nat Commun Y1 - 2019 A1 - Noordam, Raymond A1 - Bos, Maxime M A1 - Wang, Heming A1 - Winkler, Thomas W A1 - Bentley, Amy R A1 - Kilpeläinen, Tuomas O A1 - de Vries, Paul S A1 - Sung, Yun Ju A1 - Schwander, Karen A1 - Cade, Brian E A1 - Manning, Alisa A1 - Aschard, Hugues A1 - Brown, Michael R A1 - Chen, Han A1 - Franceschini, Nora A1 - Musani, Solomon K A1 - Richard, Melissa A1 - Vojinovic, Dina A1 - Aslibekyan, Stella A1 - Bartz, Traci M A1 - de Las Fuentes, Lisa A1 - Feitosa, Mary A1 - Horimoto, Andrea R A1 - Ilkov, Marjan A1 - Kho, Minjung A1 - Kraja, Aldi A1 - Li, Changwei A1 - Lim, Elise A1 - Liu, Yongmei A1 - Mook-Kanamori, Dennis O A1 - Rankinen, Tuomo A1 - Tajuddin, Salman M A1 - van der Spek, Ashley A1 - Wang, Zhe A1 - Marten, Jonathan A1 - Laville, Vincent A1 - Alver, Maris A1 - Evangelou, Evangelos A1 - Graff, Maria E A1 - He, Meian A1 - Kuhnel, Brigitte A1 - Lyytikäinen, Leo-Pekka A1 - Marques-Vidal, Pedro A1 - Nolte, Ilja M A1 - Palmer, Nicholette D A1 - Rauramaa, Rainer A1 - Shu, Xiao-Ou A1 - Snieder, Harold A1 - Weiss, Stefan A1 - Wen, Wanqing A1 - Yanek, Lisa R A1 - Adolfo, Correa A1 - Ballantyne, Christie A1 - Bielak, Larry A1 - Biermasz, Nienke R A1 - Boerwinkle, Eric A1 - Dimou, Niki A1 - Eiriksdottir, Gudny A1 - Gao, Chuan A1 - Gharib, Sina A A1 - Gottlieb, Daniel J A1 - Haba-Rubio, José A1 - Harris, Tamara B A1 - Heikkinen, Sami A1 - Heinzer, Raphael A1 - Hixson, James E A1 - Homuth, Georg A1 - Ikram, M Arfan A1 - Komulainen, Pirjo A1 - Krieger, Jose E A1 - Lee, Jiwon A1 - Liu, Jingmin A1 - Lohman, Kurt K A1 - Luik, Annemarie I A1 - Mägi, Reedik A1 - Martin, Lisa W A1 - Meitinger, Thomas A1 - Metspalu, Andres A1 - Milaneschi, Yuri A1 - Nalls, Mike A A1 - O'Connell, Jeff A1 - Peters, Annette A1 - Peyser, Patricia A1 - Raitakari, Olli T A1 - Reiner, Alex P A1 - Rensen, Patrick C N A1 - Rice, Treva K A1 - Rich, Stephen S A1 - Roenneberg, Till A1 - Rotter, Jerome I A1 - Schreiner, Pamela J A1 - Shikany, James A1 - Sidney, Stephen S A1 - Sims, Mario A1 - Sitlani, Colleen M A1 - Sofer, Tamar A1 - Strauch, Konstantin A1 - Swertz, Morris A A1 - Taylor, Kent D A1 - Uitterlinden, André G A1 - van Duijn, Cornelia M A1 - Völzke, Henry A1 - Waldenberger, Melanie A1 - Wallance, Robert B A1 - van Dijk, Ko Willems A1 - Yu, Caizheng A1 - Zonderman, Alan B A1 - Becker, Diane M A1 - Elliott, Paul A1 - Esko, Tõnu A1 - Gieger, Christian A1 - Grabe, Hans J A1 - Lakka, Timo A A1 - Lehtimäki, Terho A1 - North, Kari E A1 - Penninx, Brenda W J H A1 - Vollenweider, Peter A1 - Wagenknecht, Lynne E A1 - Wu, Tangchun A1 - Xiang, Yong-Bing A1 - Zheng, Wei A1 - Arnett, Donna K A1 - Bouchard, Claude A1 - Evans, Michele K A1 - Gudnason, Vilmundur A1 - Kardia, Sharon A1 - Kelly, Tanika N A1 - Kritchevsky, Stephen B A1 - Loos, Ruth J F A1 - Pereira, Alexandre C A1 - Province, Mike A1 - Psaty, Bruce M A1 - Rotimi, Charles A1 - Zhu, Xiaofeng A1 - Amin, Najaf A1 - Cupples, L Adrienne A1 - Fornage, Myriam A1 - Fox, Ervin F A1 - Guo, Xiuqing A1 - Gauderman, W James A1 - Rice, Kenneth A1 - Kooperberg, Charles A1 - Munroe, Patricia B A1 - Liu, Ching-Ti A1 - Morrison, Alanna C A1 - Rao, Dabeeru C A1 - van Heemst, Diana A1 - Redline, Susan AB -

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.

VL - 10 IS - 1 ER - TY - JOUR T1 - Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels. JF - Circ Genom Precis Med Y1 - 2020 A1 - Wang, Zhe A1 - Chen, Han A1 - Bartz, Traci M A1 - Bielak, Lawrence F A1 - Chasman, Daniel I A1 - Feitosa, Mary F A1 - Franceschini, Nora A1 - Guo, Xiuqing A1 - Lim, Elise A1 - Noordam, Raymond A1 - Richard, Melissa A A1 - Wang, Heming A1 - Cade, Brian A1 - Cupples, L Adrienne A1 - de Vries, Paul S A1 - Giulanini, Franco A1 - Lee, Jiwon A1 - Lemaitre, Rozenn N A1 - Martin, Lisa W A1 - Reiner, Alex P A1 - Rich, Stephen S A1 - Schreiner, Pamela J A1 - Sidney, Stephen A1 - Sitlani, Colleen M A1 - Smith, Jennifer A A1 - Willems van Dijk, Ko A1 - Yao, Jie A1 - Zhao, Wei A1 - Fornage, Myriam A1 - Kardia, Sharon L R A1 - Kooperberg, Charles A1 - Liu, Ching-Ti A1 - Mook-Kanamori, Dennis O A1 - Province, Michael A A1 - Psaty, Bruce M A1 - Redline, Susan A1 - Ridker, Paul M A1 - Rotter, Jerome I A1 - Boerwinkle, Eric A1 - Morrison, Alanna C AB -

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

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

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

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

VL - 13 IS - 4 ER - TY - JOUR T1 - Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices. JF - Nat Commun Y1 - 2021 A1 - Natarajan, Pradeep A1 - Pampana, Akhil A1 - Graham, Sarah E A1 - Ruotsalainen, Sanni E A1 - Perry, James A A1 - de Vries, Paul S A1 - Broome, Jai G A1 - Pirruccello, James P A1 - Honigberg, Michael C A1 - Aragam, Krishna A1 - Wolford, Brooke A1 - Brody, Jennifer A A1 - Antonacci-Fulton, Lucinda A1 - Arden, Moscati A1 - Aslibekyan, Stella A1 - Assimes, Themistocles L A1 - Ballantyne, Christie M A1 - Bielak, Lawrence F A1 - Bis, Joshua C A1 - Cade, Brian E A1 - Do, Ron A1 - Doddapaneni, Harsha A1 - Emery, Leslie S A1 - Hung, Yi-Jen A1 - Irvin, Marguerite R A1 - Khan, Alyna T A1 - Lange, Leslie A1 - Lee, Jiwon A1 - Lemaitre, Rozenn N A1 - Martin, Lisa W A1 - Metcalf, Ginger A1 - Montasser, May E A1 - Moon, Jee-Young A1 - Muzny, Donna A1 - O'Connell, Jeffrey R A1 - Palmer, Nicholette D A1 - Peralta, Juan M A1 - Peyser, Patricia A A1 - Stilp, Adrienne M A1 - Tsai, Michael A1 - Wang, Fei Fei A1 - Weeks, Daniel E A1 - Yanek, Lisa R A1 - Wilson, James G A1 - Abecasis, Goncalo A1 - Arnett, Donna K A1 - Becker, Lewis C A1 - Blangero, John A1 - Boerwinkle, Eric A1 - Bowden, Donald W A1 - Chang, Yi-Cheng A1 - Chen, Yii-der I A1 - Choi, Won Jung A1 - Correa, Adolfo A1 - Curran, Joanne E A1 - Daly, Mark J A1 - Dutcher, Susan K A1 - Ellinor, Patrick T A1 - Fornage, Myriam A1 - Freedman, Barry I A1 - Gabriel, Stacey A1 - Germer, Soren A1 - Gibbs, Richard A A1 - He, Jiang A1 - Hveem, Kristian A1 - Jarvik, Gail P A1 - Kaplan, Robert C A1 - Kardia, Sharon L R A1 - Kenny, Eimear A1 - Kim, Ryan W A1 - Kooperberg, Charles A1 - Laurie, Cathy C A1 - Lee, Seonwook A1 - Lloyd-Jones, Don M A1 - Loos, Ruth J F A1 - Lubitz, Steven A A1 - Mathias, Rasika A A1 - Martinez, Karine A Viaud A1 - McGarvey, Stephen T A1 - Mitchell, Braxton D A1 - Nickerson, Deborah A A1 - North, Kari E A1 - Palotie, Aarno A1 - Park, Cheol Joo A1 - Psaty, Bruce M A1 - Rao, D C A1 - Redline, Susan A1 - Reiner, Alexander P A1 - Seo, Daekwan A1 - Seo, Jeong-Sun A1 - Smith, Albert V A1 - Tracy, Russell P A1 - Vasan, Ramachandran S A1 - Kathiresan, Sekar A1 - Cupples, L Adrienne A1 - Rotter, Jerome I A1 - Morrison, Alanna C A1 - Rich, Stephen S A1 - Ripatti, Samuli A1 - Willer, Cristen A1 - Peloso, Gina M AB -

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.

VL - 12 IS - 1 ER - TY - JOUR T1 - Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits. JF - HGG Adv Y1 - 2021 A1 - Sun, Daokun A1 - Richard, Melissa A1 - Musani, Solomon K A1 - Sung, Yun Ju A1 - Winkler, Thomas W A1 - Schwander, Karen A1 - Chai, Jin Fang A1 - Guo, Xiuqing A1 - Kilpeläinen, Tuomas O A1 - Vojinovic, Dina A1 - Aschard, Hugues A1 - Bartz, Traci M A1 - Bielak, Lawrence F A1 - Brown, Michael R A1 - Chitrala, Kumaraswamy A1 - Hartwig, Fernando P A1 - Horimoto, Andrea R V R A1 - Liu, Yongmei A1 - Manning, Alisa K A1 - Noordam, Raymond A1 - Smith, Albert V A1 - Harris, Sarah E A1 - Kuhnel, Brigitte A1 - Lyytikäinen, Leo-Pekka A1 - Nolte, Ilja M A1 - Rauramaa, Rainer A1 - van der Most, Peter J A1 - Wang, Rujia A1 - Ware, Erin B A1 - Weiss, Stefan A1 - Wen, Wanqing A1 - Yanek, Lisa R A1 - Arking, Dan E A1 - Arnett, Donna K A1 - Barac, Ana A1 - Boerwinkle, Eric A1 - Broeckel, Ulrich A1 - Chakravarti, Aravinda A1 - Chen, Yii-Der Ida A1 - Cupples, L Adrienne A1 - Davigulus, Martha L A1 - de Las Fuentes, Lisa A1 - de Mutsert, Renée A1 - de Vries, Paul S A1 - Delaney, Joseph A C A1 - Roux, Ana V Diez A1 - Dörr, Marcus A1 - Faul, Jessica D A1 - Fretts, Amanda M A1 - Gallo, Linda C A1 - Grabe, Hans Jörgen A1 - Gu, C Charles A1 - Harris, Tamara B A1 - Hartman, Catharina C A A1 - Heikkinen, Sami A1 - Ikram, M Arfan A1 - Isasi, Carmen A1 - Johnson, W Craig A1 - Jonas, Jost Bruno A1 - Kaplan, Robert C A1 - Komulainen, Pirjo A1 - Krieger, Jose E A1 - Levy, Daniel A1 - Liu, Jianjun A1 - Lohman, Kurt A1 - Luik, Annemarie I A1 - Martin, Lisa W A1 - Meitinger, Thomas A1 - Milaneschi, Yuri A1 - O'Connell, Jeff R A1 - Palmas, Walter R A1 - Peters, Annette A1 - Peyser, Patricia A A1 - Pulkki-Råback, Laura A1 - Raffel, Leslie J A1 - Reiner, Alex P A1 - Rice, Kenneth A1 - Robinson, Jennifer G A1 - Rosendaal, Frits R A1 - Schmidt, Carsten Oliver A1 - Schreiner, Pamela J A1 - Schwettmann, Lars A1 - Shikany, James M A1 - Shu, Xiao-Ou A1 - Sidney, Stephen A1 - Sims, Mario A1 - Smith, Jennifer A A1 - Sotoodehnia, Nona A1 - Strauch, Konstantin A1 - Tai, E Shyong A1 - Taylor, Kent A1 - Uitterlinden, André G A1 - van Duijn, Cornelia M A1 - Waldenberger, Melanie A1 - Wee, Hwee-Lin A1 - Wei, Wen-Bin A1 - Wilson, Gregory A1 - Xuan, Deng A1 - Yao, Jie A1 - Zeng, Donglin A1 - Zhao, Wei A1 - Zhu, Xiaofeng A1 - Zonderman, Alan B A1 - Becker, Diane M A1 - Deary, Ian J A1 - Gieger, Christian A1 - Lakka, Timo A A1 - Lehtimäki, Terho A1 - North, Kari E A1 - Oldehinkel, Albertine J A1 - Penninx, Brenda W J H A1 - Snieder, Harold A1 - Wang, Ya-Xing A1 - Weir, David R A1 - Zheng, Wei A1 - Evans, Michele K A1 - Gauderman, W James A1 - Gudnason, Vilmundur A1 - Horta, Bernardo L A1 - Liu, Ching-Ti A1 - Mook-Kanamori, Dennis O A1 - Morrison, Alanna C A1 - Pereira, Alexandre C A1 - Psaty, Bruce M A1 - Amin, Najaf A1 - Fox, Ervin R A1 - Kooperberg, Charles A1 - Sim, Xueling A1 - Bierut, Laura A1 - Rotter, Jerome I A1 - Kardia, Sharon L R A1 - Franceschini, Nora A1 - Rao, Dabeeru C A1 - Fornage, Myriam AB -

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.

VL - 2 IS - 1 ER - TY - JOUR T1 - Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure. JF - Mol Psychiatry Y1 - 2021 A1 - Wang, Heming A1 - Noordam, Raymond A1 - Cade, Brian E A1 - Schwander, Karen A1 - Winkler, Thomas W A1 - Lee, Jiwon A1 - Sung, Yun Ju A1 - Bentley, Amy R A1 - Manning, Alisa K A1 - Aschard, Hugues A1 - Kilpeläinen, Tuomas O A1 - Ilkov, Marjan A1 - Brown, Michael R A1 - Horimoto, Andrea R A1 - Richard, Melissa A1 - Bartz, Traci M A1 - Vojinovic, Dina A1 - Lim, Elise A1 - Nierenberg, Jovia L A1 - Liu, Yongmei A1 - Chitrala, Kumaraswamynaidu A1 - Rankinen, Tuomo A1 - Musani, Solomon K A1 - Franceschini, Nora A1 - Rauramaa, Rainer A1 - Alver, Maris A1 - Zee, Phyllis C A1 - Harris, Sarah E A1 - van der Most, Peter J A1 - Nolte, Ilja M A1 - Munroe, Patricia B A1 - Palmer, Nicholette D A1 - Kuhnel, Brigitte A1 - Weiss, Stefan A1 - Wen, Wanqing A1 - Hall, Kelly A A1 - Lyytikäinen, Leo-Pekka A1 - O'Connell, Jeff A1 - Eiriksdottir, Gudny A1 - Launer, Lenore J A1 - de Vries, Paul S A1 - Arking, Dan E A1 - Chen, Han A1 - Boerwinkle, Eric A1 - Krieger, Jose E A1 - Schreiner, Pamela J A1 - Sidney, Stephen A1 - Shikany, James M A1 - Rice, Kenneth A1 - Chen, Yii-Der Ida A1 - Gharib, Sina A A1 - Bis, Joshua C A1 - Luik, Annemarie I A1 - Ikram, M Arfan A1 - Uitterlinden, André G A1 - Amin, Najaf A1 - Xu, Hanfei A1 - Levy, Daniel A1 - He, Jiang A1 - Lohman, Kurt K A1 - Zonderman, Alan B A1 - Rice, Treva K A1 - Sims, Mario A1 - Wilson, Gregory A1 - Sofer, Tamar A1 - Rich, Stephen S A1 - Palmas, Walter A1 - Yao, Jie A1 - Guo, Xiuqing A1 - Rotter, Jerome I A1 - Biermasz, Nienke R A1 - Mook-Kanamori, Dennis O A1 - Martin, Lisa W A1 - Barac, Ana A1 - Wallace, Robert B A1 - Gottlieb, Daniel J A1 - Komulainen, Pirjo A1 - Heikkinen, Sami A1 - Mägi, Reedik A1 - Milani, Lili A1 - Metspalu, Andres A1 - Starr, John M A1 - Milaneschi, Yuri A1 - Waken, R J A1 - Gao, Chuan A1 - Waldenberger, Melanie A1 - Peters, Annette A1 - Strauch, Konstantin A1 - Meitinger, Thomas A1 - Roenneberg, Till A1 - Völker, Uwe A1 - Dörr, Marcus A1 - Shu, Xiao-Ou A1 - Mukherjee, Sutapa A1 - Hillman, David R A1 - Kähönen, Mika A1 - Wagenknecht, Lynne E A1 - Gieger, Christian A1 - Grabe, Hans J A1 - Zheng, Wei A1 - Palmer, Lyle J A1 - Lehtimäki, Terho A1 - Gudnason, Vilmundur A1 - Morrison, Alanna C A1 - Pereira, Alexandre C A1 - Fornage, Myriam A1 - Psaty, Bruce M A1 - van Duijn, Cornelia M A1 - Liu, Ching-Ti A1 - Kelly, Tanika N A1 - Evans, Michele K A1 - Bouchard, Claude A1 - Fox, Ervin R A1 - Kooperberg, Charles A1 - Zhu, Xiaofeng A1 - Lakka, Timo A A1 - Esko, Tõnu A1 - North, Kari E A1 - Deary, Ian J A1 - Snieder, Harold A1 - Penninx, Brenda W J H A1 - Gauderman, W James A1 - Rao, Dabeeru C A1 - Redline, Susan A1 - van Heemst, Diana AB -

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

ER - TY - JOUR T1 - Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations. JF - Circ Genom Precis Med Y1 - 2021 A1 - Haslam, Danielle E A1 - Peloso, Gina M A1 - Guirette, Melanie A1 - Imamura, Fumiaki A1 - Bartz, Traci M A1 - Pitsillides, Achilleas N A1 - Wang, Carol A A1 - Li-Gao, Ruifang A1 - Westra, Jason M A1 - Pitkänen, Niina A1 - Young, Kristin L A1 - Graff, Mariaelisa A1 - Wood, Alexis C A1 - Braun, Kim V E A1 - Luan, Jian'an A1 - Kähönen, Mika A1 - Kiefte-de Jong, Jessica C A1 - Ghanbari, Mohsen A1 - Tintle, Nathan A1 - Lemaitre, Rozenn N A1 - Mook-Kanamori, Dennis O A1 - North, Kari A1 - Helminen, Mika A1 - Mossavar-Rahmani, Yasmin A1 - Snetselaar, Linda A1 - Martin, Lisa W A1 - Viikari, Jorma S A1 - Oddy, Wendy H A1 - Pennell, Craig E A1 - Rosendall, Frits R A1 - Ikram, M Arfan A1 - Uitterlinden, André G A1 - Psaty, Bruce M A1 - Mozaffarian, Dariush A1 - Rotter, Jerome I A1 - Taylor, Kent D A1 - Lehtimäki, Terho A1 - Raitakari, Olli T A1 - Livingston, Kara A A1 - Voortman, Trudy A1 - Forouhi, Nita G A1 - Wareham, Nick J A1 - de Mutsert, Renée A1 - Rich, Steven S A1 - Manson, JoAnn E A1 - Mora, Samia A1 - Ridker, Paul M A1 - Merino, Jordi A1 - Meigs, James B A1 - Dashti, Hassan S A1 - Chasman, Daniel I A1 - Lichtenstein, Alice H A1 - Smith, Caren E A1 - Dupuis, Josée A1 - Herman, Mark A A1 - McKeown, Nicola M AB -

BACKGROUND: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the locus and dyslipidemia.

METHODS: Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake.

RESULTS: In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; <0.0001), but not significantly among the lowest SSB consumers (=0.81; <0.0001). Similar results were observed for 2 additional variants (rs35709627 and rs71556736). For triglyceride, rs55673514 was positively associated with triglyceride concentrations only among the highest SSB consumers (β, 0.06 [95% CI, 0.02-0.09] ln-mg/dL per allele, =0.001) but not the lowest SSB consumers (=0.84; =0.0005).

CONCLUSIONS: Our results identified genetic variants in the locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in triglyceride concentrations. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005133, NCT00005121, NCT00005487, and NCT00000479.

VL - 14 IS - 4 ER - TY - JOUR T1 - A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies. JF - Nat Methods Y1 - 2022 A1 - Li, Zilin A1 - Li, Xihao A1 - Zhou, Hufeng A1 - Gaynor, Sheila M A1 - Selvaraj, Margaret Sunitha A1 - Arapoglou, Theodore A1 - Quick, Corbin A1 - Liu, Yaowu A1 - Chen, Han A1 - Sun, Ryan A1 - Dey, Rounak A1 - Arnett, Donna K A1 - Auer, Paul L A1 - Bielak, Lawrence F A1 - Bis, Joshua C A1 - Blackwell, Thomas W A1 - Blangero, John A1 - Boerwinkle, Eric A1 - Bowden, Donald W A1 - Brody, Jennifer A A1 - Cade, Brian E A1 - Conomos, Matthew P A1 - Correa, Adolfo A1 - Cupples, L Adrienne A1 - Curran, Joanne E A1 - de Vries, Paul S A1 - Duggirala, Ravindranath A1 - Franceschini, Nora A1 - Freedman, Barry I A1 - Göring, Harald H H A1 - Guo, Xiuqing A1 - Kalyani, Rita R A1 - Kooperberg, Charles A1 - Kral, Brian G A1 - Lange, Leslie A A1 - Lin, Bridget M A1 - Manichaikul, Ani A1 - Manning, Alisa K A1 - Martin, Lisa W A1 - Mathias, Rasika A A1 - Meigs, James B A1 - Mitchell, Braxton D A1 - Montasser, May E A1 - Morrison, Alanna C A1 - Naseri, Take A1 - O'Connell, Jeffrey R A1 - Palmer, Nicholette D A1 - Peyser, Patricia A A1 - Psaty, Bruce M A1 - Raffield, Laura M A1 - Redline, Susan A1 - Reiner, Alexander P A1 - Reupena, Muagututi'a Sefuiva A1 - Rice, Kenneth M A1 - Rich, Stephen S A1 - Smith, Jennifer A A1 - Taylor, Kent D A1 - Taub, Margaret A A1 - Vasan, Ramachandran S A1 - Weeks, Daniel E A1 - Wilson, James G A1 - Yanek, Lisa R A1 - Zhao, Wei A1 - Rotter, Jerome I A1 - Willer, Cristen J A1 - Natarajan, Pradeep A1 - Peloso, Gina M A1 - Lin, Xihong KW - Genetic Variation KW - Genome KW - Genome-Wide Association Study KW - Humans KW - Phenotype KW - Whole Genome Sequencing AB -

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.

VL - 19 IS - 12 ER - TY - JOUR T1 - Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. JF - Hypertension Y1 - 2022 A1 - Kelly, Tanika N A1 - Sun, Xiao A1 - He, Karen Y A1 - Brown, Michael R A1 - Taliun, Sarah A Gagliano A1 - Hellwege, Jacklyn N A1 - Irvin, Marguerite R A1 - Mi, Xuenan A1 - Brody, Jennifer A A1 - Franceschini, Nora A1 - Guo, Xiuqing A1 - Hwang, Shih-Jen A1 - de Vries, Paul S A1 - Gao, Yan A1 - Moscati, Arden A1 - Nadkarni, Girish N A1 - Yanek, Lisa R A1 - Elfassy, Tali A1 - Smith, Jennifer A A1 - Chung, Ren-Hua A1 - Beitelshees, Amber L A1 - Patki, Amit A1 - Aslibekyan, Stella A1 - Blobner, Brandon M A1 - Peralta, Juan M A1 - Assimes, Themistocles L A1 - Palmas, Walter R A1 - Liu, Chunyu A1 - Bress, Adam P A1 - Huang, Zhijie A1 - Becker, Lewis C A1 - Hwa, Chii-Min A1 - O'Connell, Jeffrey R A1 - Carlson, Jenna C A1 - Warren, Helen R A1 - Das, Sayantan A1 - Giri, Ayush A1 - Martin, Lisa W A1 - Craig Johnson, W A1 - Fox, Ervin R A1 - Bottinger, Erwin P A1 - Razavi, Alexander C A1 - Vaidya, Dhananjay A1 - Chuang, Lee-Ming A1 - Chang, Yen-Pei C A1 - Naseri, Take A1 - Jain, Deepti A1 - Kang, Hyun Min A1 - Hung, Adriana M A1 - Srinivasasainagendra, Vinodh A1 - Snively, Beverly M A1 - Gu, Dongfeng A1 - Montasser, May E A1 - Reupena, Muagututi'a Sefuiva A1 - Heavner, Benjamin D A1 - LeFaive, Jonathon A1 - Hixson, James E A1 - Rice, Kenneth M A1 - Wang, Fei Fei A1 - Nielsen, Jonas B A1 - Huang, Jianfeng A1 - Khan, Alyna T A1 - Zhou, Wei A1 - Nierenberg, Jovia L A1 - Laurie, Cathy C A1 - Armstrong, Nicole D A1 - Shi, Mengyao A1 - Pan, Yang A1 - Stilp, Adrienne M A1 - Emery, Leslie A1 - Wong, Quenna A1 - Hawley, Nicola L A1 - Minster, Ryan L A1 - Curran, Joanne E A1 - Munroe, Patricia B A1 - Weeks, Daniel E A1 - North, Kari E A1 - Tracy, Russell P A1 - Kenny, Eimear E A1 - Shimbo, Daichi A1 - Chakravarti, Aravinda A1 - Rich, Stephen S A1 - Reiner, Alex P A1 - Blangero, John A1 - Redline, Susan A1 - Mitchell, Braxton D A1 - Rao, Dabeeru C A1 - Ida Chen, Yii-Der A1 - Kardia, Sharon L R A1 - Kaplan, Robert C A1 - Mathias, Rasika A A1 - He, Jiang A1 - Psaty, Bruce M A1 - Fornage, Myriam A1 - Loos, Ruth J F A1 - Correa, Adolfo A1 - Boerwinkle, Eric A1 - Rotter, Jerome I A1 - Kooperberg, Charles A1 - Edwards, Todd L A1 - Abecasis, Goncalo R A1 - Zhu, Xiaofeng A1 - Levy, Daniel A1 - Arnett, Donna K A1 - Morrison, Alanna C AB -

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.

ER - TY - JOUR T1 - Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing. JF - Nat Genet Y1 - 2023 A1 - Chen, Fang A1 - Wang, Xingyan A1 - Jang, Seon-Kyeong A1 - Quach, Bryan C A1 - Weissenkampen, J Dylan A1 - Khunsriraksakul, Chachrit A1 - Yang, Lina A1 - Sauteraud, Renan A1 - Albert, Christine M A1 - Allred, Nicholette D D A1 - Arnett, Donna K A1 - Ashley-Koch, Allison E A1 - Barnes, Kathleen C A1 - Barr, R Graham A1 - Becker, Diane M A1 - Bielak, Lawrence F A1 - Bis, Joshua C A1 - Blangero, John A1 - Boorgula, Meher Preethi A1 - Chasman, Daniel I A1 - Chavan, Sameer A1 - Chen, Yii-der I A1 - Chuang, Lee-Ming A1 - Correa, Adolfo A1 - Curran, Joanne E A1 - David, Sean P A1 - Fuentes, Lisa de Las A1 - Deka, Ranjan A1 - Duggirala, Ravindranath A1 - Faul, Jessica D A1 - Garrett, Melanie E A1 - Gharib, Sina A A1 - Guo, Xiuqing A1 - Hall, Michael E A1 - Hawley, Nicola L A1 - He, Jiang A1 - Hobbs, Brian D A1 - Hokanson, John E A1 - Hsiung, Chao A A1 - Hwang, Shih-Jen A1 - Hyde, Thomas M A1 - Irvin, Marguerite R A1 - Jaffe, Andrew E A1 - Johnson, Eric O A1 - Kaplan, Robert A1 - Kardia, Sharon L R A1 - Kaufman, Joel D A1 - Kelly, Tanika N A1 - Kleinman, Joel E A1 - Kooperberg, Charles A1 - Lee, I-Te A1 - Levy, Daniel A1 - Lutz, Sharon M A1 - Manichaikul, Ani W A1 - Martin, Lisa W A1 - Marx, Olivia A1 - McGarvey, Stephen T A1 - Minster, Ryan L A1 - Moll, Matthew A1 - Moussa, Karine A A1 - Naseri, Take A1 - North, Kari E A1 - Oelsner, Elizabeth C A1 - Peralta, Juan M A1 - Peyser, Patricia A A1 - Psaty, Bruce M A1 - Rafaels, Nicholas A1 - Raffield, Laura M A1 - Reupena, Muagututi'a Sefuiva A1 - Rich, Stephen S A1 - Rotter, Jerome I A1 - Schwartz, David A A1 - Shadyab, Aladdin H A1 - Sheu, Wayne H-H A1 - Sims, Mario A1 - Smith, Jennifer A A1 - Sun, Xiao A1 - Taylor, Kent D A1 - Telen, Marilyn J A1 - Watson, Harold A1 - Weeks, Daniel E A1 - Weir, David R A1 - Yanek, Lisa R A1 - Young, Kendra A A1 - Young, Kristin L A1 - Zhao, Wei A1 - Hancock, Dana B A1 - Jiang, Bibo A1 - Vrieze, Scott A1 - Liu, Dajiang J KW - Biology KW - Drug Repositioning KW - Genetic Predisposition to Disease KW - Genome-Wide Association Study KW - Humans KW - Polymorphism, Single Nucleotide KW - Tobacco Use KW - Transcriptome AB -

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.

VL - 55 IS - 2 ER - TY - JOUR T1 - Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies. JF - Nat Genet Y1 - 2023 A1 - Li, Xihao A1 - Quick, Corbin A1 - Zhou, Hufeng A1 - Gaynor, Sheila M A1 - Liu, Yaowu A1 - Chen, Han A1 - Selvaraj, Margaret Sunitha A1 - Sun, Ryan A1 - Dey, Rounak A1 - Arnett, Donna K A1 - Bielak, Lawrence F A1 - Bis, Joshua C A1 - Blangero, John A1 - Boerwinkle, Eric A1 - Bowden, Donald W A1 - Brody, Jennifer A A1 - Cade, Brian E A1 - Correa, Adolfo A1 - Cupples, L Adrienne A1 - Curran, Joanne E A1 - de Vries, Paul S A1 - Duggirala, Ravindranath A1 - Freedman, Barry I A1 - Göring, Harald H H A1 - Guo, Xiuqing A1 - Haessler, Jeffrey A1 - Kalyani, Rita R A1 - Kooperberg, Charles A1 - Kral, Brian G A1 - Lange, Leslie A A1 - Manichaikul, Ani A1 - Martin, Lisa W A1 - McGarvey, Stephen T A1 - Mitchell, Braxton D A1 - Montasser, May E A1 - Morrison, Alanna C A1 - Naseri, Take A1 - O'Connell, Jeffrey R A1 - Palmer, Nicholette D A1 - Peyser, Patricia A A1 - Psaty, Bruce M A1 - Raffield, Laura M A1 - Redline, Susan A1 - Reiner, Alexander P A1 - Reupena, Muagututi'a Sefuiva A1 - Rice, Kenneth M A1 - Rich, Stephen S A1 - Sitlani, Colleen M A1 - Smith, Jennifer A A1 - Taylor, Kent D A1 - Vasan, Ramachandran S A1 - Willer, Cristen J A1 - Wilson, James G A1 - Yanek, Lisa R A1 - Zhao, Wei A1 - Rotter, Jerome I A1 - Natarajan, Pradeep A1 - Peloso, Gina M A1 - Li, Zilin A1 - Lin, Xihong KW - Exome Sequencing KW - Genome-Wide Association Study KW - Lipids KW - Phenotype KW - Whole Genome Sequencing AB -

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.

VL - 55 IS - 1 ER - TY - JOUR T1 - Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study. JF - medRxiv Y1 - 2023 A1 - Wang, Yuxuan A1 - Selvaraj, Margaret Sunitha A1 - Li, Xihao A1 - Li, Zilin A1 - Holdcraft, Jacob A A1 - Arnett, Donna K A1 - Bis, Joshua C A1 - Blangero, John A1 - Boerwinkle, Eric A1 - Bowden, Donald W A1 - Cade, Brian E A1 - Carlson, Jenna C A1 - Carson, April P A1 - Chen, Yii-Der Ida A1 - Curran, Joanne E A1 - de Vries, Paul S A1 - Dutcher, Susan K A1 - Ellinor, Patrick T A1 - Floyd, James S A1 - Fornage, Myriam A1 - Freedman, Barry I A1 - Gabriel, Stacey A1 - Germer, Soren A1 - Gibbs, Richard A A1 - Guo, Xiuqing A1 - He, Jiang A1 - Heard-Costa, Nancy A1 - Hildalgo, Bertha A1 - Hou, Lifang A1 - Irvin, Marguerite R A1 - Joehanes, Roby A1 - Kaplan, Robert C A1 - Kardia, Sharon Lr A1 - Kelly, Tanika N A1 - Kim, Ryan A1 - Kooperberg, Charles A1 - Kral, Brian G A1 - Levy, Daniel A1 - Li, Changwei A1 - Liu, Chunyu A1 - Lloyd-Jone, Don A1 - Loos, Ruth Jf A1 - Mahaney, Michael C A1 - Martin, Lisa W A1 - Mathias, Rasika A A1 - Minster, Ryan L A1 - Mitchell, Braxton D A1 - Montasser, May E A1 - Morrison, Alanna C A1 - Murabito, Joanne M A1 - Naseri, Take A1 - O'Connell, Jeffrey R A1 - Palmer, Nicholette D A1 - Preuss, Michael H A1 - Psaty, Bruce M A1 - Raffield, Laura M A1 - Rao, Dabeeru C A1 - Redline, Susan A1 - Reiner, Alexander P A1 - Rich, Stephen S A1 - Ruepena, Muagututi'a Sefuiva A1 - Sheu, Wayne H-H A1 - Smith, Jennifer A A1 - Smith, Albert A1 - Tiwari, Hemant K A1 - Tsai, Michael Y A1 - Viaud-Martinez, Karine A A1 - Wang, Zhe A1 - Yanek, Lisa R A1 - Zhao, Wei A1 - Rotter, Jerome I A1 - Lin, Xihong A1 - Natarajan, Pradeep A1 - Peloso, Gina M AB -

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.

ER - TY - JOUR T1 - A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies. JF - bioRxiv Y1 - 2023 A1 - Li, Xihao A1 - Chen, Han A1 - Selvaraj, Margaret Sunitha A1 - Van Buren, Eric A1 - Zhou, Hufeng A1 - Wang, Yuxuan A1 - Sun, Ryan A1 - McCaw, Zachary R A1 - Yu, Zhi A1 - Arnett, Donna K A1 - Bis, Joshua C A1 - Blangero, John A1 - Boerwinkle, Eric A1 - Bowden, Donald W A1 - Brody, Jennifer A A1 - Cade, Brian E A1 - Carson, April P A1 - Carlson, Jenna C A1 - Chami, Nathalie A1 - Chen, Yii-Der Ida A1 - Curran, Joanne E A1 - de Vries, Paul S A1 - Fornage, Myriam A1 - Franceschini, Nora A1 - Freedman, Barry I A1 - Gu, Charles A1 - Heard-Costa, Nancy L A1 - He, Jiang A1 - Hou, Lifang A1 - Hung, Yi-Jen A1 - Irvin, Marguerite R A1 - Kaplan, Robert C A1 - Kardia, Sharon L R A1 - Kelly, Tanika A1 - Konigsberg, Iain A1 - Kooperberg, Charles A1 - Kral, Brian G A1 - Li, Changwei A1 - Loos, Ruth J F A1 - Mahaney, Michael C A1 - Martin, Lisa W A1 - Mathias, Rasika A A1 - Minster, Ryan L A1 - Mitchell, Braxton D A1 - Montasser, May E A1 - Morrison, Alanna C A1 - Palmer, Nicholette D A1 - Peyser, Patricia A A1 - Psaty, Bruce M A1 - Raffield, Laura M A1 - Redline, Susan A1 - Reiner, Alexander P A1 - Rich, Stephen S A1 - Sitlani, Colleen M A1 - Smith, Jennifer A A1 - Taylor, Kent D A1 - Tiwari, Hemant A1 - Vasan, Ramachandran S A1 - Wang, Zhe A1 - Yanek, Lisa R A1 - Yu, Bing A1 - Rice, Kenneth M A1 - Rotter, Jerome I A1 - Peloso, Gina M A1 - Natarajan, Pradeep A1 - Li, Zilin A1 - Liu, Zhonghua A1 - Lin, Xihong AB -

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.

ER -