Cardiac Risk:Insulin Resistance, Hypertension, &PAI-1

Brigham And Women'S Hospital, Boston MA

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): Patients with diabetes mellitus have an increased risk from cardiovascular morbidity and mortality that is similar to patients, without diabetes, who have had a previous myocardial infarction. Although many explanations for this increased risk have been proposed from studies, the risk for a specific individual is difficult to determine from these studies. Plasminogen activator inhibitor-1 (PAI-1) is an important peptide in the fibrinolytic-thrombotic pathway and elevated levels of PAI-1 have been shown to correlate with cardiovascular events, such as myocardial infarction. Thus, PAI-1 may be a marker for cardiovascular risk. The renin-angiotensin system (RAS) also has profound effects on the cardiovascular system and pharmacologic blockade of the RAS can affect cardiovascular disease. The RAS can also affect levels of greater insulin resistance and a more adverse lipid profile than other sub-groups. However, not every diabetic patient is at equal risk for cardiovascular events or for elevations in PAI-1 levels. Thus, there are environmental and genetic factors that predispose certain individuals to greater cardiovascular risk. A genetic predisposition compounded by adverse environmental factors may highlight those at greatest risk. Genetic polymorphisms in the RAS may increase the adverse cardiovascular risk in diabetic subjects by increasing PAI-1 plasma levels or by creating an adverse metabolic milieu. The studies highlighted in this proposal will categorize diabetic subjects by an intermediate phenotype of the RAS, first demonstrated in hypertensive subjects. The relationship of gene polymorphisms in the RAS and PAI-1 genes and intermediate phenotypes of PAI-1 levels, lipids, obesity, and insulin resistance will be determined. The knowledge of which genotypes and intermediate phenotypes predict a greater risk for cardiovascular risk in patients with diabetes may help identify those individuals at greatest risk, may be able to predict the risk for a specific individuals, and may also help define specific therapy to reduce that risk.