Genetic Analysis of CVD Risk Factors

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The objective of Project 1 is to detect, map and characterize genes that contribute to variation in risk of cardiovascular disease (CVD). The focus in this Program Project (the San Antonio Family Heart Study, SAFHS) is on extended Mexican American families ascertained without regard to disease status. Each of the -1400 family members has been genotyped for >400 microsatellite markers in an 8 centimorgan map. In the current grant period significant evidence has been obtained for QTLs that influence HDL-C and other lipoprotein measures; phenotypes related to metabolic syndrome, diabetes, and insulin; obesity-related traits; phenotypes related to blood pressure and its change with age; and several novel CVD-related phenotypes, including risk of infection with Chlamydia pneumoniae. Identification of the functional alleles for a few of the best characterized of these genes will be pursued in Projects 2 and 3, and novel candidate genes will be identified in Project 4. In Project 1, taking advantage of the resource of extensive genotypic and phenotypic data that has been created in the past 15 years as well as a wealth of newly generated expression data and a 550K SNP panel currently being genotyped under other funding, we will (1) utilize the longitudinal data to investigate the genetic basis of phenotypic change, and in particular, to ask whether QTLs identified through analyses of cross-sectional data also influence change over time. (2) perform multivariate analyses of newly available transcript data that yield more than 20,000 quantitative expression phenotypes, and a set of carefully selected CVD risk factors and environmental variables to generate hypotheses concerning gene action. (3) conduct genome-wide association screens with a 550K SNP panel for clinically important traits with significant heritabilities for which no QTLs have yet been localized in the SAFHS. (4) use association with a dense set of SNPs, drawn from the 550K SNP panel, to follow-up suggestive linkage peaks from the current grant period. Thus, Project 1 will be devoted to follow-up of intriguing findings from the current grant period; detection of new QTLs in analyses of newly-available data; genetic analyses of age-related changes in risk factors; and genetic analysis of new risk factors, including information on levels of 20,000+ transcripts.