During the past two decades, genetic research in cardiovascular disease (CVD), as well as other common chronic diseases, has been dominated by single gene linkage and association studies focused on understanding of the genetics of prevalent disease. Rarely have there been studies of the longitudinal predictive value of these genetic variations. Furthermore, few studies have attempted to address the complex and high-dimensional genetic reality that underlies an individual's risk of disease. We believe that a crucial next step in CVD genetic research is to evaluate the contribution of variations in many genes simultaneously, and their interactions with traditional risk factors, to the longitudinal prediction of CVD in individuals and families. Our main objective in this grant proposal is to evaluate how current genetic information about CVD susceptibility genes contributes to the prediction of future CVD outcomes. The Rochester Family Heart Study (RFHS) provides one of the richest genetic epidemiological resources for this type of study. The RFHS represents 3941 individuals distributed among 552 three- generation pedigrees ascertained without regard to health status during two phases of collection. Phase I was from 1984 - 1988 and Phase II was from 1988 - 1991. These participants have extensive demographic, physiological, genetic, and clinical information measured at baseline. In this grant proposal we build upon this already established resource by conducting a longitudinal follow-up of the RFHS participants to address two central questions: 1) Does measured genetic variations in known susceptibility genes provide additional predictive information about risk of future CVD outcomes beyond the information provided by more traditional risk factors? and 2) Do these measured genetic variations explain patterns of disease aggregation in families and can these patterns be used to predict disease in future generations? Overall, we expect this project to contribute significantly to the public health goal of evaluating the utility of genetic factors to predict an individual's, families, or genetic subgroup's risk of developing CVD.
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