Creation of a large-scale genetic data bank for cardiovascular association studies
Ramtin Agah1, Stephen Ellis, Sue Chase
1Department of Cardiovascular Medicine, The Cleveland Clinic Foundation, Cleveland, Ohio 44195, USA.
Background:
A prerequisite for undertaking genetic association studies is the need for a genetic data bank with adequate DNA samples and a well-described clinical cohort.
Methods:
We initiated a prospective single-center study enrolling 6,273 patients referred for cardiac catheterization in a genetic data bank (with eventual goal of 10,000 enrollees). Using a prescreening tool, the patients had comprehensive clinical phenotyping, including angiogram, electrocardiogram, echocardiogram, clinical history, and medication profile (Appendix A). Along with this clinical information, DNA, serum, plasma, basic metabolic panel, inflammation, and lipid panel were collected and stored in the database.
Results:
Mean age of the patients enrolled was 64 +/- 12 years; 69% are men, 26% have diabetes, 79% have dyslipidemia, and 72% have coronary artery disease (CAD) > or = 50%. We undertook extensive quality-control measures to ensure the validity of both the clinical and DNA samples acquired into our GenBank. As part of this validation, we undertook a genetic association study to discern the effect of the apoE4 polymorphism on the risk for atherosclerosis. We are able to show that the apoE4 polymorphism is an independent risk factor for CAD.
Conclusions:
We have been able to create a large-scale genetic data bank as a resource to undertake genetic association studies. Key elements in implementation of this GenBank and baseline characteristics of our patient cohort are summarized. Lastly, as a "proof of concept" for the utility of this resource to discern gene variants associated with disease, we validated apoE4 polymorphism as an independent risk factor for CAD.
