Diabetes mellitus is one of the most potent risk factors for coronary artery disease (CAD). This effect results from an acceleration of atherosclerosis induced by hyperglycemia and other aspects of the diabetic milieu. To decrease the cardiovascular burden of this disease, a better understanding of the mechanisms linking diabetes to atherosclerosis is needed, so that new interventions specifically targeted to diabetic subjects can be developed. Our strategy is to gain this knowledge through genetic studies. Genetic factors have long been recognized as important modulators of cardiovascular risk in both the general and the diabetic populations. Evidence from our group indicates that some of these genes may have a synergistic effect with hyperglycemia, resulting into an especially strong effect in the diabetic population. Using a novel DNA-pooling approach, we have completed the first stage of a 300,000 SNP genome-wide association (GWA) study in a small set of CAD-positive and CAD-negative individuals with type 2 diabetes (T2D) from the Joslin Heart Study (JHS). This study has led to the identification of several SNPs showing large differences in allele frequencies between cases and controls, some of which cluster at loci on chromosomes 2, 5, 6, 9, and 14.
The specific aims of the present application are: 1. to complete the GWA study in an expanded set (n=2600) of CAD cases and controls from the JHS. The larger sample size will provide the power to discriminate true associations from false positive results due to multiple testing. 2. To replicate significant findings of association with CAD in T2D in an independent set of cases and controls (n=3200) from the Nurses Health Study and Health Professional Follow-up Study. Replication will enhance the confidence in positive results and will allow more precise estimates of the magnitude of genetic effects. 3. Identify candidate causal variants in the genomic regions showing association with CAD in T2D. Identification of possible functional variants will provide insights on the cellular pathways that modulate the risk of CAD in T2D. Three important features distinguish this study. First, this project has high probability of success, as indicated by our recent identification of a CAD risk allele interacting with hyperglycemia on chromosome 9p21. Second, it concerns a topic that has been so far overlooked by genetic studies. None of the GWA studies that were completed or are in progress are focused on CAD in diabetes, in part because few other investigators have access to large numbers of individuals with CAD and T2D. Third, this research has great significance. Being an unbiased, whole- genome study, it has the potential to identify new molecular pathways linking diabetes to atherogenesis with obvious implications for the development of new drugs specifically targeted to the prevention or treatment of CAD among diabetic patients.

Public Health Relevance

The goal of this project is to identify genes involved in the modulation of coronary artery disease among individuals with type 2 diabetes. This knowledge may point to as yet undiscovered disease mechanisms and suggest novel strategies for developing new pharmacological interventions for preventing or treating this complication of diabetes. Availability of genetic markers of increased susceptibility to CAD would also allow the identification of diabetic individuals at increased risk of cardiovascular disease, so that preventive programs can be specifically targeted at these subjects early in life.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL073168-10
Application #
8282726
Study Section
Cardiovascular and Sleep Epidemiology (CASE)
Program Officer
Ershow, Abby
Project Start
2003-09-29
Project End
2014-05-31
Budget Start
2012-06-01
Budget End
2014-05-31
Support Year
10
Fiscal Year
2012
Total Cost
$589,147
Indirect Cost
$175,282
Name
Joslin Diabetes Center
Department
Type
DUNS #
071723084
City
Boston
State
MA
Country
United States
Zip Code
02215
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