@article {1274, title = {A bivariate genome-wide approach to metabolic syndrome: STAMPEED consortium.}, journal = {Diabetes}, volume = {60}, year = {2011}, month = {2011 Apr}, pages = {1329-39}, abstract = {

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of \~{}2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from \~{}9\% of the variance in triglycerides, 5.8\% of high-density lipoprotein cholesterol, 3.6\% of fasting glucose, and 1.4\% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.

}, keywords = {Adult, Aged, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Meta-Analysis as Topic, Metabolic Syndrome, Middle Aged, Phenotype, Polymorphism, Single Nucleotide}, issn = {1939-327X}, doi = {10.2337/db10-1011}, author = {Kraja, Aldi T and Vaidya, Dhananjay and Pankow, James S and Goodarzi, Mark O and Assimes, Themistocles L and Kullo, Iftikhar J and Sovio, Ulla and Mathias, Rasika A and Sun, Yan V and Franceschini, Nora and Absher, Devin and Li, Guo and Zhang, Qunyuan and Feitosa, Mary F and Glazer, Nicole L and Haritunians, Talin and Hartikainen, Anna-Liisa and Knowles, Joshua W and North, Kari E and Iribarren, Carlos and Kral, Brian and Yanek, Lisa and O{\textquoteright}Reilly, Paul F and McCarthy, Mark I and Jaquish, Cashell and Couper, David J and Chakravarti, Aravinda and Psaty, Bruce M and Becker, Lewis C and Province, Michael A and Boerwinkle, Eric and Quertermous, Thomas and Palotie, Leena and Jarvelin, Marjo-Riitta and Becker, Diane M and Kardia, Sharon L R and Rotter, Jerome I and Chen, Yii-Der Ida and Borecki, Ingrid B} } @article {8290, title = {Burden of rare exome sequence variants in PROC gene is associated with venous thromboembolism: a population-based study.}, journal = {J Thromb Haemost}, volume = {18}, year = {2020}, month = {2020 Feb}, pages = {445-453}, abstract = {

BACKGROUND: Rare coding mutations underlying deficiencies of antithrombin and proteins C and S contribute to familial venous thromboembolism (VTE). It is uncertain whether rare variants play a role in the etiology of VTE in the general population.

OBJECTIVES: We conducted a deep whole-exome sequencing (WES) study to investigate the associations between rare coding variants and the risk of VTE in two population-based prospective cohorts.

PATIENTS/METHODS: Whole-exome sequencing was performed in the Longitudinal Investigation of Thromboembolism Etiology (LITE), which combines the Atherosclerosis Risk in Communities (ARIC) study (316 incident VTE events among 3159 African Americans [AAs] and 458 incident VTEs among 7772 European Americans [EAs]) and the Cardiovascular Healthy Study (CHS; 60 incident VTEs among 1751 EAs). We performed gene-based tests of rare variants (allele frequency~<~1\%, exome-wide significance P~<~1.47~{\texttimes}~10 ) separately in each study and ancestry group, and meta-analyzed the results for the EAs in ARIC and CHS.

RESULTS: In the meta-analysis of EAs, we identified one gene, PROC, in which the burden of rare, coding variants was significantly associated with increased risk of VTE (HR~=~5.42 [3.11, 9.42] for carriers versus non-carriers, P~=~2.27~{\texttimes}~10 ). In ARIC EAs, carriers of the PROC rare variants had on average 0.75 standard deviation (SD) lower concentrations of plasma protein C and 0.28 SD higher D-dimer (P~<~.05) than non-carriers. Adjustment for low protein C status did not eliminate the association of PROC burden with VTE. In AAs, rare coding PROC variants were not associated with VTE.

CONCLUSIONS: Rare coding variants in PROC contribute to increased VTE risk in EAs in this general population sample.

}, issn = {1538-7836}, doi = {10.1111/jth.14676}, author = {Tang, Weihong and Stimson, Mary Rachel and Basu, Saonli and Heckbert, Susan R and Cushman, Mary and Pankow, James S and Folsom, Aaron R and Pankratz, Nathan} } @article {8838, title = {BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion.}, journal = {HGG Adv}, volume = {2}, year = {2021}, month = {2021 Jul 08}, abstract = {

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

}, issn = {2666-2477}, doi = {10.1016/j.xhgg.2021.100040}, author = {Sofer, Tamar and Lee, Jiwon and Kurniansyah, Nuzulul and Jain, Deepti and Laurie, Cecelia A and Gogarten, Stephanie M and Conomos, Matthew P and Heavner, Ben and Hu, Yao and Kooperberg, Charles and Haessler, Jeffrey and Vasan, Ramachandran S and Cupples, L Adrienne and Coombes, Brandon J and Seyerle, Amanda and Gharib, Sina A and Chen, Han and O{\textquoteright}Connell, Jeffrey R and Zhang, Man and Gottlieb, Daniel J and Psaty, Bruce M and Longstreth, W T and Rotter, Jerome I and Taylor, Kent D and Rich, Stephen S and Guo, Xiuqing and Boerwinkle, Eric and Morrison, Alanna C and Pankow, James S and Johnson, Andrew D and Pankratz, Nathan and Reiner, Alex P and Redline, Susan and Smith, Nicholas L and Rice, Kenneth M and Schifano, Elizabeth D} }