Genetic Predictors of Incident Cardiovascular Disease
To evaluate how current genetic information about cardiovascular disease susceptibility genes contributes to the prediction of future cardiovascular disease outcomes.
|Study Start Date:||March 2002|
|Study Completion Date:||December 2007|
|Primary Completion Date:||December 2007 (Final data collection date for primary outcome measure)|
During the 1980s and 1990s, 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. A crucial next step in CVD genetic research is the evaluation of 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.
The study uses participants from the Rochester Family Heart Study (RFHS) which 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. This study builds upon this already established resource by conducting a longitudinal follow-up of the RFHS participants to address two central questions: 1) Do 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?
|Investigator:||Sharon Kardia||University of Michigan|