@article {6083, title = {Fine-mapping and initial characterization of QT interval loci in African Americans.}, journal = {PLoS Genet}, volume = {8}, year = {2012}, month = {2012}, pages = {e1002870}, abstract = {

The QT interval (QT) is heritable and its prolongation is a risk factor for ventricular tachyarrhythmias and sudden death. Most genetic studies of QT have examined European ancestral populations; however, the increased genetic diversity in African Americans provides opportunities to narrow association signals and identify population-specific variants. We therefore evaluated 6,670 SNPs spanning eleven previously identified QT loci in 8,644 African American participants from two Population Architecture using Genomics and Epidemiology (PAGE) studies: the Atherosclerosis Risk in Communities study and Women{\textquoteright}s Health Initiative Clinical Trial. Of the fifteen known independent QT variants at the eleven previously identified loci, six were significantly associated with QT in African American populations (P<=1.20{\texttimes}10(-4)): ATP1B1, PLN1, KCNQ1, NDRG4, and two NOS1AP independent signals. We also identified three population-specific signals significantly associated with QT in African Americans (P<=1.37{\texttimes}10(-5)): one at NOS1AP and two at ATP1B1. Linkage disequilibrium (LD) patterns in African Americans assisted in narrowing the region likely to contain the functional variants for several loci. For example, African American LD patterns showed that 0 SNPs were in LD with NOS1AP signal rs12143842, compared with European LD patterns that indicated 87 SNPs, which spanned 114.2 Kb, were in LD with rs12143842. Finally, bioinformatic-based characterization of the nine African American signals pointed to functional candidates located exclusively within non-coding regions, including predicted binding sites for transcription factors such as TBX5, which has been implicated in cardiac structure and conductance. In this detailed evaluation of QT loci, we identified several African Americans SNPs that better define the association with QT and successfully narrowed intervals surrounding established loci. These results demonstrate that the same loci influence variation in QT across multiple populations, that novel signals exist in African Americans, and that the SNPs identified as strong candidates for functional evaluation implicate gene regulatory dysfunction in QT prolongation.

}, keywords = {African Americans, Aged, Computational Biology, Electrocardiography, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Metagenomics, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Risk Factors, Tachycardia, United States}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002870}, author = {Avery, Christy L and Sethupathy, Praveen and Buyske, Steven and He, Qianchuan and Lin, Dan-Yu and Arking, Dan E and Carty, Cara L and Duggan, David and Fesinmeyer, Megan D and Hindorff, Lucia A and Jeff, Janina M and Klein, Liviu and Patton, Kristen K and Peters, Ulrike and Shohet, Ralph V and Sotoodehnia, Nona and Young, Alicia M and Kooperberg, Charles and Haiman, Christopher A and Mohlke, Karen L and Whitsel, Eric A and North, Kari E} } @article {6179, title = {Impact of ancestry and common genetic variants on QT interval in African Americans.}, journal = {Circ Cardiovasc Genet}, volume = {5}, year = {2012}, month = {2012 Dec}, pages = {647-55}, abstract = {

BACKGROUND: Ethnic differences in cardiac arrhythmia incidence have been reported, with a particularly high incidence of sudden cardiac death and low incidence of atrial fibrillation in individuals of African ancestry. We tested the hypotheses that African ancestry and common genetic variants are associated with prolonged duration of cardiac repolarization, a central pathophysiological determinant of arrhythmia, as measured by the electrocardiographic QT interval.

METHODS AND RESULTS: First, individual estimates of African and European ancestry were inferred from genome-wide single-nucleotide polymorphism (SNP) data in 7 population-based cohorts of African Americans (n=12,097) and regressed on measured QT interval from ECGs. Second, imputation was performed for 2.8 million SNPs, and a genome-wide association study of QT interval was performed in 10 cohorts (n=13,105). There was no evidence of association between genetic ancestry and QT interval (P=0.94). Genome-wide significant associations (P<2.5 {\texttimes} 10(-8)) were identified with SNPs at 2 loci, upstream of the genes NOS1AP (rs12143842, P=2 {\texttimes} 10(-15)) and ATP1B1 (rs1320976, P=2 {\texttimes} 10(-10)). The most significant SNP in NOS1AP was the same as the strongest SNP previously associated with QT interval in individuals of European ancestry. Low probability values (P<10(-5)) were observed for SNPs at several other loci previously identified in genome-wide association studies in individuals of European ancestry, including KCNQ1, KCNH2, LITAF, and PLN.

CONCLUSIONS: We observed no difference in duration of cardiac repolarization with global genetic indices of African American ancestry. In addition, our genome-wide association study extends the association of polymorphisms at several loci associated with repolarization in individuals of European ancestry to include individuals of African ancestry.

}, keywords = {Adult, African Americans, Aged, Electrocardiography, European Continental Ancestry Group, Female, Genealogy and Heraldry, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.112.962787}, author = {Smith, J Gustav and Avery, Christy L and Evans, Daniel S and Nalls, Michael A and Meng, Yan A and Smith, Erin N and Palmer, Cameron and Tanaka, Toshiko and Mehra, Reena and Butler, Anne M and Young, Taylor and Buxbaum, Sarah G and Kerr, Kathleen F and Berenson, Gerald S and Schnabel, Renate B and Li, Guo and Ellinor, Patrick T and Magnani, Jared W and Chen, Wei and Bis, Joshua C and Curb, J David and Hsueh, Wen-Chi and Rotter, Jerome I and Liu, Yongmei and Newman, Anne B and Limacher, Marian C and North, Kari E and Reiner, Alexander P and Quibrera, P Miguel and Schork, Nicholas J and Singleton, Andrew B and Psaty, Bruce M and Soliman, Elsayed Z and Solomon, Allen J and Srinivasan, Sathanur R and Alonso, Alvaro and Wallace, Robert and Redline, Susan and Zhang, Zhu-Ming and Post, Wendy S and Zonderman, Alan B and Taylor, Herman A and Murray, Sarah S and Ferrucci, Luigi and Arking, Dan E and Evans, Michele K and Fox, Ervin R and Sotoodehnia, Nona and Heckbert, Susan R and Whitsel, Eric A and Newton-Cheh, Christopher} } @article {6084, title = {Novel loci associated with PR interval in a genome-wide association study of 10 African American cohorts.}, journal = {Circ Cardiovasc Genet}, volume = {5}, year = {2012}, month = {2012 Dec}, pages = {639-46}, abstract = {

BACKGROUND: The PR interval, as measured by the resting, standard 12-lead ECG, reflects the duration of atrial/atrioventricular nodal depolarization. Substantial evidence exists for a genetic contribution to PR, including genome-wide association studies that have identified common genetic variants at 9 loci influencing PR in populations of European and Asian descent. However, few studies have examined loci associated with PR in African Americans.

METHODS AND RESULTS: We present results from the largest genome-wide association study to date of PR in 13 415 adults of African descent from 10 cohorts. We tested for association between PR (ms) and ≈2.8 million genotyped and imputed single-nucleotide polymorphisms. Imputation was performed using HapMap 2 YRI and CEU panels. Study-specific results, adjusted for global ancestry and clinical correlates of PR, were meta-analyzed using the inverse variance method. Variation in genome-wide test statistic distributions was noted within studies (λ range: 0.9-1.1), although not after genomic control correction was applied to the overall meta-analysis (λ: 1.008). In addition to generalizing previously reported associations with MEIS1, SCN5A, ARHGAP24, CAV1, and TBX5 to African American populations at the genome-wide significance level (P<5.0 {\texttimes} 10(-8)), we also identified a novel locus: ITGA9, located in a region previously implicated in SCN5A expression. The 3p21 region harboring SCN5A also contained 2 additional independent secondary signals influencing PR (P<5.0 {\texttimes} 10(-8)).

CONCLUSIONS: This study demonstrates the ability to map novel loci in African Americans as well as the generalizability of loci associated with PR across populations of African, European, and Asian descent.

}, keywords = {Adult, African Americans, Cohort Studies, Electrocardiography, Female, Genetic Loci, Genome-Wide Association Study, Humans, Male, Meta-Analysis as Topic, Middle Aged, Polymorphism, Single Nucleotide}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.112.963991}, author = {Butler, Anne M and Yin, Xiaoyan and Evans, Daniel S and Nalls, Michael A and Smith, Erin N and Tanaka, Toshiko and Li, Guo and Buxbaum, Sarah G and Whitsel, Eric A and Alonso, Alvaro and Arking, Dan E and Benjamin, Emelia J and Berenson, Gerald S and Bis, Josh C and Chen, Wei and Deo, Rajat and Ellinor, Patrick T and Heckbert, Susan R and Heiss, Gerardo and Hsueh, Wen-Chi and Keating, Brendan J and Kerr, Kathleen F and Li, Yun and Limacher, Marian C and Liu, Yongmei and Lubitz, Steven A and Marciante, Kristin D and Mehra, Reena and Meng, Yan A and Newman, Anne B and Newton-Cheh, Christopher and North, Kari E and Palmer, Cameron D and Psaty, Bruce M and Quibrera, P Miguel and Redline, Susan and Reiner, Alex P and Rotter, Jerome I and Schnabel, Renate B and Schork, Nicholas J and Singleton, Andrew B and Smith, J Gustav and Soliman, Elsayed Z and Srinivasan, Sathanur R and Zhang, Zhu-Ming and Zonderman, Alan B and Ferrucci, Luigi and Murray, Sarah S and Evans, Michele K and Sotoodehnia, Nona and Magnani, Jared W and Avery, Christy L} } @article {6598, title = {Evidence of heterogeneity by race/ethnicity in genetic determinants of QT interval.}, journal = {Epidemiology}, volume = {25}, year = {2014}, month = {2014 Nov}, pages = {790-8}, abstract = {

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{\textquoteright}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.

}, keywords = {Aged, Continental Population Groups, Electrocardiography, Female, Genetic Predisposition to Disease, Haplotypes, Humans, Long QT Syndrome, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Risk Factors}, issn = {1531-5487}, doi = {10.1097/EDE.0000000000000168}, author = {Seyerle, Amanda A and Young, Alicia M and Jeff, Janina M and Melton, Phillip E and Jorgensen, Neal W and Lin, Yi and Carty, Cara L and Deelman, Ewa and Heckbert, Susan R and Hindorff, Lucia A and Jackson, Rebecca D and Martin, Lisa W and Okin, Peter M and Perez, Marco V and Psaty, Bruce M and Soliman, Elsayed Z and Whitsel, Eric A and North, Kari E and Laston, Sandra and Kooperberg, Charles and Avery, Christy L} } @article {6591, title = {Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins.}, journal = {Nat Commun}, volume = {5}, year = {2014}, month = {2014 Oct 28}, pages = {5068}, abstract = {

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.

}, keywords = {Cholesterol, LDL, Genome-Wide Association Study, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Pharmacogenetics, Polymorphism, Single Nucleotide}, issn = {2041-1723}, doi = {10.1038/ncomms6068}, author = {Postmus, Iris and Trompet, Stella and Deshmukh, Harshal A and Barnes, Michael R and Li, Xiaohui and Warren, Helen R and Chasman, Daniel I and Zhou, Kaixin and Arsenault, Benoit J and Donnelly, Louise A and Wiggins, Kerri L and Avery, Christy L and Griffin, Paula and Feng, QiPing and Taylor, Kent D and Li, Guo and Evans, Daniel S and Smith, Albert V and de Keyser, Catherine E and Johnson, Andrew D and de Craen, Anton J M and Stott, David J and Buckley, Brendan M and Ford, Ian and Westendorp, Rudi G J and Slagboom, P Eline and Sattar, Naveed and Munroe, Patricia B and Sever, Peter and Poulter, Neil and Stanton, Alice and Shields, Denis C and O{\textquoteright}Brien, Eoin and Shaw-Hawkins, Sue and Chen, Y-D Ida and Nickerson, Deborah A and Smith, Joshua D and Dub{\'e}, Marie Pierre and Boekholdt, S Matthijs and Hovingh, G Kees and Kastelein, John J P and McKeigue, Paul M and Betteridge, John and Neil, Andrew and Durrington, Paul N and Doney, Alex and Carr, Fiona and Morris, Andrew and McCarthy, Mark I and Groop, Leif and Ahlqvist, Emma and Bis, Joshua C and Rice, Kenneth and Smith, Nicholas L and Lumley, Thomas and Whitsel, Eric A and St{\"u}rmer, Til and Boerwinkle, Eric and Ngwa, Julius S and O{\textquoteright}Donnell, Christopher J and Vasan, Ramachandran S and Wei, Wei-Qi and Wilke, Russell A and Liu, Ching-Ti and Sun, Fangui and Guo, Xiuqing and Heckbert, Susan R and Post, Wendy and Sotoodehnia, Nona and Arnold, Alice M and Stafford, Jeanette M and Ding, Jingzhong and Herrington, David M and Kritchevsky, Stephen B and Eiriksdottir, Gudny and Launer, Leonore J and Harris, Tamara B and Chu, Audrey Y and Giulianini, Franco and MacFadyen, Jean G and Barratt, Bryan J and Nyberg, Fredrik and Stricker, Bruno H and Uitterlinden, Andr{\'e} G and Hofman, Albert and Rivadeneira, Fernando and Emilsson, Valur and Franco, Oscar H and Ridker, Paul M and Gudnason, Vilmundur and Liu, Yongmei and Denny, Joshua C and Ballantyne, Christie M and Rotter, Jerome I and Adrienne Cupples, L and Psaty, Bruce M and Palmer, Colin N A and Tardif, Jean-Claude and Colhoun, Helen M and Hitman, Graham and Krauss, Ronald M and Wouter Jukema, J and Caulfield, Mark J} } @article {6811, title = {Association of Cardiometabolic Multimorbidity With Mortality.}, journal = {JAMA}, volume = {314}, year = {2015}, month = {2015 Jul 7}, pages = {52-60}, abstract = {

IMPORTANCE: The prevalence of cardiometabolic multimorbidity is increasing.

OBJECTIVE: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity.

DESIGN, SETTING, AND PARTICIPANTS: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates.

EXPOSURES: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI).

MAIN OUTCOMES AND MEASURES: All-cause mortality and estimated reductions in life expectancy.

RESULTS: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95\% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95\% CI, 2.0-2.2) in those with stroke, 2.0 (95\% CI, 1.9-2.2) in those with MI, 3.7 (95\% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95\% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95\% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95\% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy.

CONCLUSIONS AND RELEVANCE: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.

}, keywords = {Adult, Aged, Comorbidity, Diabetes Mellitus, Female, Humans, Life Expectancy, Male, Middle Aged, Mortality, Myocardial Infarction, Risk Factors, Stroke}, issn = {1538-3598}, doi = {10.1001/jama.2015.7008}, author = {Di Angelantonio, Emanuele and Kaptoge, Stephen and Wormser, David and Willeit, Peter and Butterworth, Adam S and Bansal, Narinder and O{\textquoteright}Keeffe, Linda M and Gao, Pei and Wood, Angela M and Burgess, Stephen and Freitag, Daniel F and Pennells, Lisa and Peters, Sanne A and Hart, Carole L and H{\r a}heim, Lise Lund and Gillum, Richard F and Nordestgaard, B{\o}rge G and Psaty, Bruce M and Yeap, Bu B and Knuiman, Matthew W and Nietert, Paul J and Kauhanen, Jussi and Salonen, Jukka T and Kuller, Lewis H and Simons, Leon A and van der Schouw, Yvonne T and Barrett-Connor, Elizabeth and Selmer, Randi and Crespo, Carlos J and Rodriguez, Beatriz and Verschuren, W M Monique and Salomaa, Veikko and Sv{\"a}rdsudd, Kurt and van der Harst, Pim and Bj{\"o}rkelund, Cecilia and Wilhelmsen, Lars and Wallace, Robert B and Brenner, Hermann and Amouyel, Philippe and Barr, Elizabeth L M and Iso, Hiroyasu and Onat, Altan and Trevisan, Maurizio and D{\textquoteright}Agostino, Ralph B and Cooper, Cyrus and Kavousi, Maryam and Welin, Lennart and Roussel, Ronan and Hu, Frank B and Sato, Shinichi and Davidson, Karina W and Howard, Barbara V and Leening, Maarten J G and Leening, Maarten and Rosengren, Annika and D{\"o}rr, Marcus and Deeg, Dorly J H and Kiechl, Stefan and Stehouwer, Coen D A and Nissinen, Aulikki and Giampaoli, Simona and Donfrancesco, Chiara and Kromhout, Daan and Price, Jackie F and Peters, Annette and Meade, Tom W and Casiglia, Edoardo and Lawlor, Debbie A and Gallacher, John and Nagel, Dorothea and Franco, Oscar H and Assmann, Gerd and Dagenais, Gilles R and Jukema, J Wouter and Sundstr{\"o}m, Johan and Woodward, Mark and Brunner, Eric J and Khaw, Kay-Tee and Wareham, Nicholas J and Whitsel, Eric A and Nj{\o}lstad, Inger and Hedblad, Bo and Wassertheil-Smoller, Sylvia and Engstr{\"o}m, Gunnar and Rosamond, Wayne D and Selvin, Elizabeth and Sattar, Naveed and Thompson, Simon G and Danesh, John} } @article {6875, title = {Drug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease: A Pharmacogenomics Study from the CHARGE Consortium.}, journal = {PLoS One}, volume = {10}, year = {2015}, month = {2015}, pages = {e0140496}, abstract = {

BACKGROUND: Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals.

METHODS: Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases).

RESULTS: Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0{\texttimes}10-8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction >= 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD.

}, keywords = {African Americans, Aged, Antihypertensive Agents, Cardiovascular Diseases, European Continental Ancestry Group, Female, Genome-Wide Association Study, Humans, Hypertension, Incidence, Male, Middle Aged, Polymorphism, Single Nucleotide, Treatment Outcome}, issn = {1932-6203}, doi = {10.1371/journal.pone.0140496}, author = {Bis, Joshua C and Sitlani, Colleen and Irvin, Ryan and Avery, Christy L and Smith, Albert Vernon and Sun, Fangui and Evans, Daniel S and Musani, Solomon K and Li, Xiaohui and Trompet, Stella and Krijthe, Bouwe P and Harris, Tamara B and Quibrera, P Miguel and Brody, Jennifer A and Demissie, Serkalem and Davis, Barry R and Wiggins, Kerri L and Tranah, Gregory J and Lange, Leslie A and Sotoodehnia, Nona and Stott, David J and Franco, Oscar H and Launer, Lenore J and St{\"u}rmer, Til and Taylor, Kent D and Cupples, L Adrienne and Eckfeldt, John H and Smith, Nicholas L and Liu, Yongmei and Wilson, James G and Heckbert, Susan R and Buckley, Brendan M and Ikram, M Arfan and Boerwinkle, Eric and Chen, Yii-Der Ida and de Craen, Anton J M and Uitterlinden, Andr{\'e} G and Rotter, Jerome I and Ford, Ian and Hofman, Albert and Sattar, Naveed and Slagboom, P Eline and Westendorp, Rudi G J and Gudnason, Vilmundur and Vasan, Ramachandran S and Lumley, Thomas and Cummings, Steven R and Taylor, Herman A and Post, Wendy and Jukema, J Wouter and Stricker, Bruno H and Whitsel, Eric A and Psaty, Bruce M and Arnett, Donna} } @article {6602, title = {Generalized estimating equations for genome-wide association studies using longitudinal phenotype data.}, journal = {Stat Med}, volume = {34}, year = {2015}, month = {2015 Jan 15}, pages = {118-30}, abstract = {

Many longitudinal cohort studies have both genome-wide measures of genetic variation and repeated measures of phenotypes and environmental exposures. Genome-wide association study analyses have typically used only cross-sectional data to evaluate quantitative phenotypes and binary traits. Incorporation of repeated measures may increase power to detect associations, but also requires specialized analysis methods. Here, we discuss one such method-generalized estimating equations (GEE)-in the contexts of analysis of main effects of rare genetic variants and analysis of gene-environment interactions. We illustrate the potential for increased power using GEE analyses instead of cross-sectional analyses. We also address challenges that arise, such as the need for small-sample corrections when the minor allele frequency of a genetic variant and/or the prevalence of an environmental exposure is low. To illustrate methods for detection of gene-drug interactions on a genome-wide scale, using repeated measures data, we conduct single-study analyses and meta-analyses across studies in three large cohort studies participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium-the Atherosclerosis Risk in Communities study, the Cardiovascular Health Study, and the Rotterdam Study.

}, keywords = {Aged, Aging, Cardiovascular Diseases, Cohort Studies, Computer Simulation, Cross-Sectional Studies, Epidemiologic Research Design, Gene-Environment Interaction, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, Longitudinal Studies, Meta-Analysis as Topic, Models, Genetic, Pharmacogenetics, Risk Assessment, United States}, issn = {1097-0258}, doi = {10.1002/sim.6323}, author = {Sitlani, Colleen M and Rice, Kenneth M and Lumley, Thomas and McKnight, Barbara and Cupples, L Adrienne and Avery, Christy L and Noordam, Raymond and Stricker, Bruno H C and Whitsel, Eric A and Psaty, Bruce M} } @article {7557, title = {Fifteen Genetic Loci Associated With the Electrocardiographic P Wave.}, journal = {Circ Cardiovasc Genet}, volume = {10}, year = {2017}, month = {2017 Aug}, abstract = {

BACKGROUND: The P wave on an ECG is a measure of atrial electric function, and its characteristics may serve as predictors for atrial arrhythmias. Increased mean P-wave duration and P-wave terminal force traditionally have been used as markers for left atrial enlargement, and both have been associated with increased risk of atrial fibrillation. Here, we explore the genetic basis of P-wave morphology through meta-analysis of genome-wide association study results for P-wave duration and P-wave terminal force from 12 cohort studies.

METHODS AND RESULTS: We included 44 456 individuals, of which 6778 (16\%) were of African ancestry. Genotyping, imputation, and genome-wide association study were performed at each study site. Summary-level results were meta-analyzed centrally using inverse-variance weighting. In meta-analyses of P-wave duration, we identified 6 significant (P<5{\texttimes}10-8) novel loci and replicated a prior association with SCN10A. We identified 3 loci at SCN5A, TBX5, and CAV1/CAV2 that were jointly associated with the PR interval, PR segment, and P-wave duration. We identified 6 novel loci in meta-analysis of P-wave terminal force. Four of the identified genetic loci were significantly associated with gene expression in 329 left atrial samples. Finally, we observed that some of the loci associated with the P wave were linked to overall atrial conduction, whereas others identified distinct phases of atrial conduction.

CONCLUSIONS: We have identified 6 novel genetic loci associated with P-wave duration and 6 novel loci associated with P-wave terminal force. Future studies of these loci may aid in identifying new targets for drugs that may modify atrial conduction or treat atrial arrhythmias.

}, keywords = {Arrhythmias, Cardiac, Caveolin 1, Caveolin 2, Electrocardiography, Genetic Loci, Genome-Wide Association Study, Genotype, Heart Atria, Humans, NAV1.5 Voltage-Gated Sodium Channel, NAV1.8 Voltage-Gated Sodium Channel, T-Box Domain Proteins}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.116.001667}, author = {Christophersen, Ingrid E and Magnani, Jared W and Yin, Xiaoyan and Barnard, John and Weng, Lu-Chen and Arking, Dan E and Niemeijer, Maartje N and Lubitz, Steven A and Avery, Christy L and Duan, Qing and Felix, Stephan B and Bis, Joshua C and Kerr, Kathleen F and Isaacs, Aaron and M{\"u}ller-Nurasyid, Martina and M{\"u}ller, Christian and North, Kari E and Reiner, Alex P and Tinker, Lesley F and Kors, Jan A and Teumer, Alexander and Petersmann, Astrid and Sinner, Moritz F and B{\r u}zkov{\'a}, Petra and Smith, Jonathan D and Van Wagoner, David R and V{\"o}lker, Uwe and Waldenberger, Melanie and Peters, Annette and Meitinger, Thomas and Limacher, Marian C and Wilhelmsen, Kirk C and Psaty, Bruce M and Hofman, Albert and Uitterlinden, Andre and Krijthe, Bouwe P and Zhang, Zhu-Ming and Schnabel, Renate B and K{\"a}{\"a}b, Stefan and van Duijn, Cornelia and Rotter, Jerome I and Sotoodehnia, Nona and D{\"o}rr, Marcus and Li, Yun and Chung, Mina K and Soliman, Elsayed Z and Alonso, Alvaro and Whitsel, Eric A and Stricker, Bruno H and Benjamin, Emelia J and Heckbert, Susan R and Ellinor, Patrick T} } @article {8507, title = {Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease.}, journal = {Circulation}, volume = {140}, year = {2019}, month = {2019 08 20}, pages = {645-657}, abstract = {

BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts.

METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts.

RESULTS: Among 11 461 individuals (mean age 64 years, 67\% women, 35\% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts.

CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.

}, keywords = {Adult, Aged, Cohort Studies, Coronary Disease, CpG Islands, DNA Methylation, Europe, Female, Genome-Wide Association Study, Humans, Incidence, Leukocytes, Male, Middle Aged, Myocardial Infarction, Population Groups, Prognosis, Prospective Studies, Risk, United States}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.118.039357}, author = {Agha, Golareh and Mendelson, Michael M and Ward-Caviness, Cavin K and Joehanes, Roby and Huan, Tianxiao and Gondalia, Rahul and Salfati, Elias and Brody, Jennifer A and Fiorito, Giovanni and Bressler, Jan and Chen, Brian H and Ligthart, Symen and Guarrera, Simonetta and Colicino, Elena and Just, Allan C and Wahl, Simone and Gieger, Christian and Vandiver, Amy R and Tanaka, Toshiko and Hernandez, Dena G and Pilling, Luke C and Singleton, Andrew B and Sacerdote, Carlotta and Krogh, Vittorio and Panico, Salvatore and Tumino, Rosario and Li, Yun and Zhang, Guosheng and Stewart, James D and Floyd, James S and Wiggins, Kerri L and Rotter, Jerome I and Multhaup, Michael and Bakulski, Kelly and Horvath, Steven and Tsao, Philip S and Absher, Devin M and Vokonas, Pantel and Hirschhorn, Joel and Fallin, M Daniele and Liu, Chunyu and Bandinelli, Stefania and Boerwinkle, Eric and Dehghan, Abbas and Schwartz, Joel D and Psaty, Bruce M and Feinberg, Andrew P and Hou, Lifang and Ferrucci, Luigi and Sotoodehnia, Nona and Matullo, Giuseppe and Peters, Annette and Fornage, Myriam and Assimes, Themistocles L and Whitsel, Eric A and Levy, Daniel and Baccarelli, Andrea A} } @article {9372, title = {Genome-Wide Association Study of Apparent Treatment-Resistant Hypertension in the CHARGE Consortium: The CHARGE Pharmacogenetics Working Group.}, journal = {Am J Hypertens}, volume = {32}, year = {2019}, month = {2019 Nov 15}, pages = {1146-1153}, abstract = {

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 {\texttimes} 10-8) and in the race-combined analysis (P = 1.5 {\texttimes} 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.

}, keywords = {Aged, Antihypertensive Agents, Black or African American, Blood Pressure, Case-Control Studies, DNA (Cytosine-5-)-Methyltransferases, DNA Methyltransferase 3A, DNA-Binding Proteins, Drug Resistance, Dystrophin-Associated Proteins, Europe, Female, Genetic Loci, Genome-Wide Association Study, Humans, Hypertension, Male, Middle Aged, Myosin Heavy Chains, Myosin Type V, Neuropeptides, Pharmacogenetics, Pharmacogenomic Variants, Polymorphism, Single Nucleotide, Risk Assessment, Risk Factors, Transcription Factors, United States, White People}, issn = {1941-7225}, doi = {10.1093/ajh/hpz150}, author = {Irvin, Marguerite R and Sitlani, Colleen M and Floyd, James S and Psaty, Bruce M and Bis, Joshua C and Wiggins, Kerri L and Whitsel, Eric A and St{\"u}rmer, Til and Stewart, James and Raffield, Laura and Sun, Fangui and Liu, Ching-Ti and Xu, Hanfei and Cupples, Adrienne L and Tanner, Rikki M and Rossing, Peter and Smith, Albert and Zilh{\~a}o, Nuno R and Launer, Lenore J and Noordam, Raymond and Rotter, Jerome I and Yao, Jie and Li, Xiaohui and Guo, Xiuqing and Limdi, Nita and Sundaresan, Aishwarya and Lange, Leslie and Correa, Adolfo and Stott, David J and Ford, Ian and Jukema, J Wouter and Gudnason, Vilmundur and Mook-Kanamori, Dennis O and Trompet, Stella and Palmas, Walter and Warren, Helen R and Hellwege, Jacklyn N and Giri, Ayush and O{\textquoteright}donnell, Christopher and Hung, Adriana M and Edwards, Todd L and Ahluwalia, Tarunveer S and Arnett, Donna K and Avery, Christy L} } @article {8839, title = {Supplemental Association of Clonal Hematopoiesis With Incident Heart~Failure.}, journal = {J Am Coll Cardiol}, volume = {78}, year = {2021}, month = {2021 07 06}, pages = {42-52}, abstract = {

BACKGROUND: Age-related clonal hematopoiesis of indeterminate potential (CHIP), defined as clonally expanded leukemogenic sequence variations (particularly in DNMT3A, TET2, ASXL1, and JAK2) in asymptomatic individuals, is associated with cardiovascular events, including recurrent heart failure (HF).

OBJECTIVES: This study sought to evaluate whether CHIP is associated with incident HF.

METHODS: CHIP status was obtained from whole exome or genome sequencing of blood DNA in participants without prevalent HF or hematological malignancy from 5 cohorts. Cox proportional hazards models were performed within each cohort, adjusting for demographic and clinical risk factors, followed by fixed-effect meta-analyses. Large CHIP clones (defined as variant allele frequency >10\%), HF with or without baseline coronary heart disease, and left ventricular ejection fraction were evaluated in secondary analyses.

RESULTS: Of 56,597 individuals (59\% women, mean age 58 years at baseline), 3,406 (6\%) had CHIP, and 4,694 developed HF (8.3\%) over up to 20 years of follow-up. CHIP was prospectively associated with a 25\% increased risk of HF in meta-analysis (hazard ratio: 1.25; 95\% confidence interval: 1.13-1.38) with consistent associations across cohorts. ASXL1, TET2, and JAK2 sequence variations were each associated with an increased risk of HF, whereas DNMT3A sequence variations were not associated with HF. Secondary analyses suggested large CHIP was associated with a greater risk of HF (hazard ratio: 1.29; 95\% confidence interval: 1.15-1.44), and the associations for CHIP on HF with and without prior coronary heart disease were homogenous. ASXL1 sequence variations were associated with reduced left ventricular ejection fraction.

CONCLUSIONS: CHIP, particularly sequence variations in ASXL1, TET2, and JAK2, represents a new risk factor for HF.

}, keywords = {Aged, Clonal Hematopoiesis, Correlation of Data, Demography, DNA-Binding Proteins, Female, Heart Failure, Humans, Janus Kinase 2, Male, Middle Aged, Mutation, Proportional Hazards Models, Proto-Oncogene Proteins, Repressor Proteins, Risk Factors, Stroke Volume, Ventricular Dysfunction, Left, Whole Exome Sequencing}, issn = {1558-3597}, doi = {10.1016/j.jacc.2021.04.085}, author = {Yu, Bing and Roberts, Mary B and Raffield, Laura M and Zekavat, Seyedeh Maryam and Nguyen, Ngoc Quynh H and Biggs, Mary L and Brown, Michael R and Griffin, Gabriel and Desai, Pinkal and Correa, Adolfo and Morrison, Alanna C and Shah, Amil M and Niroula, Abhishek and Uddin, Md Mesbah and Honigberg, Michael C and Ebert, Benjamin L and Psaty, Bruce M and Whitsel, Eric A and Manson, JoAnn E and Kooperberg, Charles and Bick, Alexander G and Ballantyne, Christie M and Reiner, Alex P and Natarajan, Pradeep and Eaton, Charles B} } @article {9104, title = {Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.}, journal = {Nat Genet}, volume = {54}, year = {2022}, month = {2022 May}, pages = {560-572}, abstract = {

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

}, keywords = {Diabetes Mellitus, Type 2, Ethnicity, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1546-1718}, doi = {10.1038/s41588-022-01058-3}, author = {Mahajan, Anubha and Spracklen, Cassandra N and Zhang, Weihua and Ng, Maggie C Y and Petty, Lauren E and Kitajima, Hidetoshi and Yu, Grace Z and R{\"u}eger, Sina and Speidel, Leo and Kim, Young Jin and Horikoshi, Momoko and Mercader, Josep M and Taliun, Daniel and Moon, Sanghoon and Kwak, Soo-Heon and Robertson, Neil R and Rayner, Nigel W and Loh, Marie and Kim, Bong-Jo and Chiou, Joshua and Miguel-Escalada, Irene and Della Briotta Parolo, Pietro and Lin, Kuang and Bragg, Fiona and Preuss, Michael H and Takeuchi, Fumihiko and Nano, Jana and Guo, Xiuqing and Lamri, Amel and Nakatochi, Masahiro and Scott, Robert A and Lee, Jung-Jin and Huerta-Chagoya, Alicia and Graff, Mariaelisa and Chai, Jin-Fang and Parra, Esteban J and Yao, Jie and Bielak, Lawrence F and Tabara, Yasuharu and Hai, Yang and Steinthorsdottir, Valgerdur and Cook, James P and Kals, Mart and Grarup, Niels and Schmidt, Ellen M and Pan, Ian and Sofer, Tamar and Wuttke, Matthias and Sarnowski, Chloe and Gieger, Christian and Nousome, Darryl and Trompet, Stella and Long, Jirong and Sun, Meng and Tong, Lin and Chen, Wei-Min and Ahmad, Meraj and Noordam, Raymond and Lim, Victor J Y and Tam, Claudia H T and Joo, Yoonjung Yoonie and Chen, Chien-Hsiun and Raffield, Laura M and Lecoeur, C{\'e}cile and Prins, Bram Peter and Nicolas, Aude and Yanek, Lisa R and Chen, Guanjie and Jensen, Richard A and Tajuddin, Salman and Kabagambe, Edmond K and An, Ping and Xiang, Anny H and Choi, Hyeok Sun and Cade, Brian E and Tan, Jingyi and Flanagan, Jack and Abaitua, Fernando and Adair, Linda S and Adeyemo, Adebowale and Aguilar-Salinas, Carlos A and Akiyama, Masato and Anand, Sonia S and Bertoni, Alain and Bian, Zheng and Bork-Jensen, Jette and Brandslund, Ivan and Brody, Jennifer A and Brummett, Chad M and Buchanan, Thomas A and Canouil, Micka{\"e}l and Chan, Juliana C N and Chang, Li-Ching and Chee, Miao-Li and Chen, Ji and Chen, Shyh-Huei and Chen, Yuan-Tsong and Chen, Zhengming and Chuang, Lee-Ming and Cushman, Mary and Das, Swapan K and de Silva, H Janaka and Dedoussis, George and Dimitrov, Latchezar and Doumatey, Ayo P and Du, Shufa and Duan, Qing and Eckardt, Kai-Uwe and Emery, Leslie S and Evans, Daniel S and Evans, Michele K and Fischer, Krista and Floyd, James S and Ford, Ian and Fornage, Myriam and Franco, Oscar H and Frayling, Timothy M and Freedman, Barry I and Fuchsberger, Christian and Genter, Pauline and Gerstein, Hertzel C and Giedraitis, Vilmantas and Gonz{\'a}lez-Villalpando, Clicerio and Gonzalez-Villalpando, Maria Elena and Goodarzi, Mark O and Gordon-Larsen, Penny and Gorkin, David and Gross, Myron and Guo, Yu and Hackinger, Sophie and Han, Sohee and Hattersley, Andrew T and Herder, Christian and Howard, Annie-Green and Hsueh, Willa and Huang, Mengna and Huang, Wei and Hung, Yi-Jen and Hwang, Mi Yeong and Hwu, Chii-Min and Ichihara, Sahoko and Ikram, Mohammad Arfan and Ingelsson, Martin and Islam, Md Tariqul and Isono, Masato and Jang, Hye-Mi and Jasmine, Farzana and Jiang, Guozhi and Jonas, Jost B and J{\o}rgensen, Marit E and J{\o}rgensen, Torben and Kamatani, Yoichiro and Kandeel, Fouad R and Kasturiratne, Anuradhani and Katsuya, Tomohiro and Kaur, Varinderpal and Kawaguchi, Takahisa and Keaton, Jacob M and Kho, Abel N and Khor, Chiea-Chuen and Kibriya, Muhammad G and Kim, Duk-Hwan and Kohara, Katsuhiko and Kriebel, Jennifer and Kronenberg, Florian and Kuusisto, Johanna and L{\"a}ll, Kristi and Lange, Leslie A and Lee, Myung-Shik and Lee, Nanette R and Leong, Aaron and Li, Liming and Li, Yun and Li-Gao, Ruifang and Ligthart, Symen and Lindgren, Cecilia M and Linneberg, Allan and Liu, Ching-Ti and Liu, Jianjun and Locke, Adam E and Louie, Tin and Luan, Jian{\textquoteright}an and Luk, Andrea O and Luo, Xi and Lv, Jun and Lyssenko, Valeriya and Mamakou, Vasiliki and Mani, K Radha and Meitinger, Thomas and Metspalu, Andres and Morris, Andrew D and Nadkarni, Girish N and Nadler, Jerry L and Nalls, Michael A and Nayak, Uma and Nongmaithem, Suraj S and Ntalla, Ioanna and Okada, Yukinori and Orozco, Lorena and Patel, Sanjay R and Pereira, Mark A and Peters, Annette and Pirie, Fraser J and Porneala, Bianca and Prasad, Gauri and Preissl, Sebastian and Rasmussen-Torvik, Laura J and Reiner, Alexander P and Roden, Michael and Rohde, Rebecca and Roll, Kathryn and Sabanayagam, Charumathi and Sander, Maike and Sandow, Kevin and Sattar, Naveed and Sch{\"o}nherr, Sebastian and Schurmann, Claudia and Shahriar, Mohammad and Shi, Jinxiu and Shin, Dong Mun and Shriner, Daniel and Smith, Jennifer A and So, Wing Yee and Stan{\v c}{\'a}kov{\'a}, Alena and Stilp, Adrienne M and Strauch, Konstantin and Suzuki, Ken and Takahashi, Atsushi and Taylor, Kent D and Thorand, Barbara and Thorleifsson, Gudmar and Thorsteinsdottir, Unnur and Tomlinson, Brian and Torres, Jason M and Tsai, Fuu-Jen and Tuomilehto, Jaakko and Tusi{\'e}-Luna, Teresa and Udler, Miriam S and Valladares-Salgado, Adan and van Dam, Rob M and van Klinken, Jan B and Varma, Rohit and Vujkovic, Marijana and Wacher-Rodarte, Niels and Wheeler, Eleanor and Whitsel, Eric A and Wickremasinghe, Ananda R and van Dijk, Ko Willems and Witte, Daniel R and Yajnik, Chittaranjan S and Yamamoto, Ken and Yamauchi, Toshimasa and Yengo, Loic and Yoon, Kyungheon and Yu, Canqing and Yuan, Jian-Min and Yusuf, Salim and Zhang, Liang and Zheng, Wei and Raffel, Leslie J and Igase, Michiya and Ipp, Eli and Redline, Susan and Cho, Yoon Shin and Lind, Lars and Province, Michael A and Hanis, Craig L and Peyser, Patricia A and Ingelsson, Erik and Zonderman, Alan B and Psaty, Bruce M and Wang, Ya-Xing and Rotimi, Charles N and Becker, Diane M and Matsuda, Fumihiko and Liu, Yongmei and Zeggini, Eleftheria and Yokota, Mitsuhiro and Rich, Stephen S and Kooperberg, Charles and Pankow, James S and Engert, James C and Chen, Yii-Der Ida and Froguel, Philippe and Wilson, James G and Sheu, Wayne H H and Kardia, Sharon L R and Wu, Jer-Yuarn and Hayes, M Geoffrey and Ma, Ronald C W and Wong, Tien-Yin and Groop, Leif and Mook-Kanamori, Dennis O and Chandak, Giriraj R and Collins, Francis S and Bharadwaj, Dwaipayan and Par{\'e}, Guillaume and Sale, Mich{\`e}le M and Ahsan, Habibul and Motala, Ayesha A and Shu, Xiao-Ou and Park, Kyong-Soo and Jukema, J Wouter and Cruz, Miguel and McKean-Cowdin, Roberta and Grallert, Harald and Cheng, Ching-Yu and Bottinger, Erwin P and Dehghan, Abbas and Tai, E-Shyong and Dupuis, Jos{\'e}e and Kato, Norihiro and Laakso, Markku and K{\"o}ttgen, Anna and Koh, Woon-Puay and Palmer, Colin N A and Liu, Simin and Abecasis, Goncalo and Kooner, Jaspal S and Loos, Ruth J F and North, Kari E and Haiman, Christopher A and Florez, Jose C and Saleheen, Danish and Hansen, Torben and Pedersen, Oluf and M{\"a}gi, Reedik and Langenberg, Claudia and Wareham, Nicholas J and Maeda, Shiro and Kadowaki, Takashi and Lee, Juyoung and Millwood, Iona Y and Walters, Robin G and Stefansson, Kari and Myers, Simon R and Ferrer, Jorge and Gaulton, Kyle J and Meigs, James B and Mohlke, Karen L and Gloyn, Anna L and Bowden, Donald W and Below, Jennifer E and Chambers, John C and Sim, Xueling and Boehnke, Michael and Rotter, Jerome I and McCarthy, Mark I and Morris, Andrew P} } @article {9387, title = {Aberrant activation of TCL1A promotes stem cell expansion in clonal haematopoiesis.}, journal = {Nature}, volume = {616}, year = {2023}, month = {2023 Apr}, pages = {755-763}, abstract = {

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.

}, keywords = {Alleles, Animals, Clonal Hematopoiesis, Genome-Wide Association Study, Hematopoiesis, Hematopoietic Stem Cells, Humans, Mice, Mutation, Promoter Regions, Genetic}, issn = {1476-4687}, doi = {10.1038/s41586-023-05806-1}, author = {Weinstock, Joshua S and Gopakumar, Jayakrishnan and Burugula, Bala Bharathi and Uddin, Md Mesbah and Jahn, Nikolaus and Belk, Julia A and Bouzid, Hind and Daniel, Bence and Miao, Zhuang and Ly, Nghi and Mack, Taralynn M and Luna, Sofia E and Prothro, Katherine P and Mitchell, Shaneice R and Laurie, Cecelia A and Broome, Jai G and Taylor, Kent D and Guo, Xiuqing and Sinner, Moritz F and von Falkenhausen, Aenne S and K{\"a}{\"a}b, Stefan and Shuldiner, Alan R and O{\textquoteright}Connell, Jeffrey R and Lewis, Joshua P and Boerwinkle, Eric and Barnes, Kathleen C and Chami, Nathalie and Kenny, Eimear E and Loos, Ruth J F and Fornage, Myriam and Hou, Lifang and Lloyd-Jones, Donald M and Redline, Susan and Cade, Brian E and Psaty, Bruce M and Bis, Joshua C and Brody, Jennifer A and Silverman, Edwin K and Yun, Jeong H and Qiao, Dandi and Palmer, Nicholette D and Freedman, Barry I and Bowden, Donald W and Cho, Michael H and DeMeo, Dawn L and Vasan, Ramachandran S and Yanek, Lisa R and Becker, Lewis C and Kardia, Sharon L R and Peyser, Patricia A and He, Jiang and Rienstra, Michiel and van der Harst, Pim and Kaplan, Robert and Heckbert, Susan R and Smith, Nicholas L and Wiggins, Kerri L and Arnett, Donna K and Irvin, Marguerite R and Tiwari, Hemant and Cutler, Michael J and Knight, Stacey and Muhlestein, J Brent and Correa, Adolfo and Raffield, Laura M and Gao, Yan and de Andrade, Mariza and Rotter, Jerome I and Rich, Stephen S and Tracy, Russell P and Konkle, Barbara A and Johnsen, Jill M and Wheeler, Marsha M and Smith, J Gustav and Melander, Olle and Nilsson, Peter M and Custer, Brian S and Duggirala, Ravindranath and Curran, Joanne E and Blangero, John and McGarvey, Stephen and Williams, L Keoki and Xiao, Shujie and Yang, Mao and Gu, C Charles and Chen, Yii-Der Ida and Lee, Wen-Jane and Marcus, Gregory M and Kane, John P and Pullinger, Clive R and Shoemaker, M Benjamin and Darbar, Dawood and Roden, Dan M and Albert, Christine and Kooperberg, Charles and Zhou, Ying and Manson, JoAnn E and Desai, Pinkal and Johnson, Andrew D and Mathias, Rasika A and Blackwell, Thomas W and Abecasis, Goncalo R and Smith, Albert V and Kang, Hyun M and Satpathy, Ansuman T and Natarajan, Pradeep and Kitzman, Jacob O and Whitsel, Eric A and Reiner, Alexander P and Bick, Alexander G and Jaiswal, Siddhartha} } @article {9322, title = {Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.}, journal = {Nat Commun}, volume = {14}, year = {2023}, month = {2023 Mar 14}, pages = {1411}, abstract = {

The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration.~Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism~and~genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle~and~their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.

}, keywords = {Arrhythmias, Cardiac, Atrioventricular Block, Biomarkers, Cardiovascular Diseases, Electrocardiography, Genome-Wide Association Study, Humans, Risk Factors}, issn = {2041-1723}, doi = {10.1038/s41467-023-36997-w}, author = {Young, William J and Haessler, Jeffrey and Benjamins, Jan-Walter and Repetto, Linda and Yao, Jie and Isaacs, Aaron and Harper, Andrew R and Ramirez, Julia and Garnier, Sophie and Van Duijvenboden, Stefan and Baldassari, Antoine R and Concas, Maria Pina and Duong, ThuyVy and Foco, Luisa and Isaksen, Jonas L and Mei, Hao and Noordam, Raymond and Nursyifa, Casia and Richmond, Anne and Santolalla, Meddly L and Sitlani, Colleen M and Soroush, Negin and Th{\'e}riault, S{\'e}bastien and Trompet, Stella and Aeschbacher, Stefanie and Ahmadizar, Fariba and Alonso, Alvaro and Brody, Jennifer A and Campbell, Archie and Correa, Adolfo and Darbar, Dawood and De Luca, Antonio and Deleuze, Jean-Francois and Ellervik, Christina and Fuchsberger, Christian and Goel, Anuj and Grace, Christopher and Guo, Xiuqing and Hansen, Torben and Heckbert, Susan R and Jackson, Rebecca D and Kors, Jan A and Lima-Costa, Maria Fernanda and Linneberg, Allan and Macfarlane, Peter W and Morrison, Alanna C and Navarro, Pau and Porteous, David J and Pramstaller, Peter P and Reiner, Alexander P and Risch, Lorenz and Schotten, Ulrich and Shen, Xia and Sinagra, Gianfranco and Soliman, Elsayed Z and Stoll, Monika and Tarazona-Santos, Eduardo and Tinker, Andrew and Trajanoska, Katerina and Villard, Eric and Warren, Helen R and Whitsel, Eric A and Wiggins, Kerri L and Arking, Dan E and Avery, Christy L and Conen, David and Girotto, Giorgia and Grarup, Niels and Hayward, Caroline and Jukema, J Wouter and Mook-Kanamori, Dennis O and Olesen, Morten Salling and Padmanabhan, Sandosh and Psaty, Bruce M and Pattaro, Cristian and Ribeiro, Antonio Luiz P and Rotter, Jerome I and Stricker, Bruno H and van der Harst, Pim and van Duijn, Cornelia M and Verweij, Niek and Wilson, James G and Orini, Michele and Charron, Philippe and Watkins, Hugh and Kooperberg, Charles and Lin, Henry J and Wilson, James F and Kanters, J{\o}rgen K and Sotoodehnia, Nona and Mifsud, Borbala and Lambiase, Pier D and Tereshchenko, Larisa G and Munroe, Patricia B} } @article {9911, title = {Methylome-wide association analyses of lipids and modifying effects of behavioral factors in diverse race and ethnicity participants.}, journal = {Clin Epigenetics}, volume = {17}, year = {2025}, month = {2025 Apr 02}, pages = {54}, abstract = {

Circulating lipid concentrations are clinically associated with cardiometabolic diseases. The phenotypic variance explained by identified genetic variants remains limited, highlighting the importance of searching for additional factors beyond genetic sequence variants. DNA methylation has been linked to lipid concentrations in previous studies, although most of the studies harbored moderate sample sizes and exhibited underrepresentation of non-European ancestry populations. In addition, knowledge of nongenetic factors on lipid profiles is extremely limited. In the Population Architecture Using Genomics and Epidemiology (PAGE) Study, we performed methylome-wide association analysis on 9,561 participants from diverse race and ethnicity backgrounds for HDL-c, LDL-c, TC, and TG levels, and also tested interactions between smoking or alcohol intake and methylation in their association with lipid levels. We identified novel CpG sites at 16 loci (P < 1.18E-7) with successful replication on 3,215 participants. One additional novel locus was identified in the self-reported White participants (P = 4.66E-8). Although no additional CpG sites were identified in the genome-wide interaction analysis, 13 reported CpG sites showed significant heterogeneous association across smoking or alcohol intake strata. By mapping novel and reported CpG sites to genes, we identified enriched pathways directly linked to lipid metabolism as well as ones spanning various biological functions. These findings provide new insights into the regulation of lipid concentrations.

}, keywords = {Adult, Aged, Alcohol Drinking, CpG Islands, DNA Methylation, Ethnicity, Female, Genome-Wide Association Study, Humans, Lipids, Male, Middle Aged, Racial Groups, Smoking, White People}, issn = {1868-7083}, doi = {10.1186/s13148-025-01859-3}, author = {Hu, Yao and Haessler, Jeff and Lundin, Jessica I and Darst, Burcu F and Whitsel, Eric A and Grove, Megan and Guan, Weihua and Xia, Rui and Szeto, Mindy and Raffield, Laura M and Ratliff, Scott and Wang, Yuxuan and Wang, Xuzhi and Fohner, Alison E and Lynch, Megan T and Patel, Yesha M and Lani Park, S and Xu, Huichun and Mitchell, Braxton D and Bis, Joshua C and Sotoodehnia, Nona and Brody, Jennifer A and Psaty, Bruce M and Peloso, Gina M and Tsai, Michael Y and Rich, Stephen S and Rotter, Jerome I and Smith, Jennifer A and Kardia, Sharon L R and Reiner, Alex P and Lange, Leslie and Fornage, Myriam and Pankow, James S and Graff, Mariaelisa and North, Kari E and Kooperberg, Charles and Peters, Ulrike} }