The management of diabetic patients is often complicated by concomitant high blood pressure (hypertension) and high levels of LDL-cholesterol and triglycerides, often coupled with low HDL- cholesterol (dyslipidemia).The majority of diabetes related mortality is due to cardiovascular events, and epidemiological studies have shown that cardiovascular risk increases with increasing levels of blood sugar, blood pressure, and blood lipids. A variety of drugs are available to treat each of these conditions, and some have been shown to have an effect on cardiovascular risk. For example, controlling LDL-cholesterol with statin therapy reduces the rate of cardiovascular events in diabetic patients, but not to the level characteristic of non-diabetic individuals. The ACCORD trial investigated whether intensive pharmacological therapy in diabetic patients, with the goal of normalizing glycemia, blood pressure, and blood lipids, would further reduce cardiovascular events. However, no additional effect was seen with intensive blood pressure or lipid therapy, and intensive glycemia management actually increased mortality. These failures of seemingly rational treatment approaches could be the result of differential response of individuals to particular therapeutic regimens due to genetic polymorphism in genes relating to the metabolism or mechanism of action of the medicines used. Many candidate genes could be advanced as possible sources of this genetic variation, but our knowledge of all genes contributing to metabolic and cardiovascular phenotypes is incomplete, and therefore a candidate gene approach cannot be assured of identifying the relevant genes. We therefore propose a genetic study of the ACCORD trial that looks at functionally significant genetic variation in all genes in the human genome to investigate the following specific aims: 1) Identify genetic variants in patients from the ACCORD Lipid Trial that predict responses to treatment with fenofibrate. 2) Identify genetic variants in patients from the ACCORD Lipid Trial that predict responses to treatment with statins. 3) Identify genetic variants in patients from the ACCORD Glycemia Trial that predict acute responses to treatment with specific anti-hyperglycemic agents, and long-term responses to intensive vs. standard treatment strategies. Identification of genetic variants affecting outcomes of glycemia and lipid modifying therapies would enable the targeting of particular interventions to patients most likely to benefit and least likely to be harmed, improving cardiovascular outcomes and reducing the burden of morbidity and mortality attributable to diabetes. The genes containing these variants may prove to be novel targets for drug development, leading to new medicines for improving outcomes for diabetic patients in the future.

Public Health Relevance

Diabetes is a major cause of morbidity and mortality, due in large measure to effects of the disease on cardiovascular health. The ACCORD clinical trial investigated the hypothesis that intensive management of glycemia, blood pressure, and lipid levels would reduce cardiovascular events in diabetic patients, but failed to demonstrate a benefit for these interventions. The ancillary study proposed here will identify genes responsible for variation in response to the ACCORD lipid and glycemia interventions, which will enable personalized treatment so as to avoid adverse effects and improve patient cardiovascular health, reducing diabetes-related morbidity and mortality.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL110380-02
Application #
8451276
Study Section
Special Emphasis Panel (ZRG1-CVRS-C (50))
Program Officer
Kirby, Ruth
Project Start
2012-04-01
Project End
2016-03-31
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
2
Fiscal Year
2013
Total Cost
$609,477
Indirect Cost
$124,964
Name
University of North Carolina Chapel Hill
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
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Rotroff, Daniel M; Pijut, Sonja S; Marvel, Skylar W et al. (2018) Genetic Variants in HSD17B3, SMAD3, and IPO11 Impact Circulating Lipids in Response to Fenofibrate in Individuals With Type 2 Diabetes. Clin Pharmacol Ther 103:712-721
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Shah, Hetal S; Gao, He; Morieri, Mario Luca et al. (2016) Genetic Predictors of Cardiovascular Mortality During Intensive Glycemic Control in Type 2 Diabetes: Findings From the ACCORD Clinical Trial. Diabetes Care 39:1915-1924
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