@article {1345, title = {A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Oct}, pages = {e1002322}, abstract = {

Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55\% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.

}, keywords = {African Americans, Apolipoprotein C-I, Blood Glucose, Dyslipidemias, European Continental Ancestry Group, Genetic Association Studies, Genetic Predisposition to Disease, Genome, Human, Humans, Metabolic Syndrome, Obesity, Abdominal, Phenotype, Phospholipase C gamma, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Ubiquitin-Protein Ligases, Vascular Diseases}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002322}, author = {Avery, Christy L and He, Qianchuan and North, Kari E and Ambite, Jos{\'e} L and Boerwinkle, Eric and Fornage, Myriam and Hindorff, Lucia A and Kooperberg, Charles and Meigs, James B and Pankow, James S and Pendergrass, Sarah A and Psaty, Bruce M and Ritchie, Marylyn D and Rotter, Jerome I and Taylor, Kent D and Wilkens, Lynne R and Heiss, Gerardo and Lin, Dan Yu} } @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 {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} }