Genetics of Hypertensive Associated Treatments (GENHAT)

University Of Texas Hlth Sci Ctr Houston, Houston TX

Investigators

Abstract

[unreadable] DESCRIPTION (provided by applicant): [unreadable] This is one of four collaborative R01s, representing the University of Texas Houston, Biostatistics, for the[unreadable] competitive renewal of the Genetics of Hypertension Associated Treatments (GenHAT) study. The goal of[unreadable] this competitive renewal is to comprehensively evaluate the pharmacogenetic basis of antihypertensive[unreadable] treatment response using state-of-the-art methods. There is large between-person variation in response to[unreadable] drugs, and genetic variation contributes to variable treatment response. To determine if genetic variants[unreadable] interact with antihypertensive medications to modify the risk of fatal coronary heart disease and non-fatal[unreadable] myocardial infarction and other cardiovascular disease outcomes in high-risk hypertensive adults. GenHAT[unreadable] is an ancillary study to ALLHAT, a randomized trial of four antihypertensive treatments (chlorthalidone,[unreadable] amlodipine, lisinopri and doxazosin) conducted in 42,418 high-risk hypertensive patients who were followed[unreadable] an average of 4.9 years (3.2 years for the truncated doxazosin arm). Using a case-cohort design, in Aim 1[unreadable] we will examine whether single SNPs (both htSNPs and nonsynonomous SNPs) within genes in candidategene[unreadable] pathways of relevance for the ALLHAT medications (e.g., the renin-angiotensin-aldosterone system,[unreadable] the sodium homeostasis pathway, the endothelial system, and lipid and diabetes pathways) interact with[unreadable] antihypertensive treatments to modify risk of fatal and non-fatal coronary heart disease or stroke, heart[unreadable] failure, peripheral arterial disease, end state renal disease and all-cause mortality. We will genotype 96[unreadable] ancestry-informative markers on all cases and the cohort random sample and use structured association[unreadable] testing (SAT) methods to control for potential population stratification. We will implement false discovery rate[unreadable] (FDR) methods to take multiple testing into account. For Aim 2 we will examine whether multiple SNPs in[unreadable] multiple genes within selected candidate-gene pathways interact with antihypertensive treatments to modify[unreadable] risk of CHD and other outcomes, as outlined for Aim 1. SAT and FDR methods will also be used for Aim 2 to[unreadable] control for population stratification and multiple testing. Finally, Aim 3 will enhance the overall utility of[unreadable] GenHAT data to the scientific community by establishing a mechanism for external investigators to[unreadable] undertake genetic analysis within GenHAT for 20 genetic variants for the case-cohort sample. GenHAT[unreadable] offers an unparalleled opportunity to determine the pharmacogenetic basis of antihypertensive treatment.[unreadable]