Background: Coronary artery disease (CAD) is the leading cause of death and a leading cause of disability in the developed world. Early onset (premature) coronary artery disease (EOCAD) is known to have a particularly strong genetic component. However, the actual genes leading to this increased risk of CAD remain obscure.
Methods: The primary goal of the Genetics of Early Onset Cardiovascular Disease (GENECARD) study is to perform a genetic linkage study in 920 families with at least 1 sibling pair having EOCAD. The study sites include a US network of 15 cardiology practices and 5 additional sites located in Europe and the United States. We propose to identify chromosomal regions associated with increased susceptibility to EOCAD in this large sample of affected sibling pairs and nuclear families, where EOCAD is defined on the basis of having acute coronary syndrome (unstable angina or myocardial infarction), a revascularization procedure, or a positive functional imaging study at or before the age of 50 years in men or 55 years in women. To identify which genomic regions and genes are associated with increased susceptibility to EOCAD, we will use a comprehensive strategy comprising genomic screening, fine mapping, candidate gene analysis, and family-based association studies.
Results: Herein we describe the clinical characteristics, family history, and risk factor profiles of the 1168 members from 438 nuclear families included in the first, exploratory analysis. Analysis of the study population revealed a strong concordance of known cardiac risk factors among affected sibling pairs. There was significant concordance (P <. 01) among siblings with EOCAD for presence of diabetes (78% concordance), dyslipoproteinemia (67%), obesity (63%), and hypertension (56%). This level of concordance of risk factors among siblings might be expected, given the significant genetic components demonstrated for these metabolic susceptibility traits. However, there was also substantial sibling pair concordance (P <.01) for smoking history (74%), regular alcohol consumption (81%), and sedentary lifestyle (63%), environmental traits without known inherited predisposition.
Conclusions: Analyses such as these will have implications for stratifying populations for the statistical analysis of the genome scan and on the choice of covariates for the follow-up studies of the initial genome screen analysis.