• G M Reaven.
• Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA. greaven@cvmed.stanford.edu
• Panminerva Med. 2005 Dec 1; 47 (4): 201-10.

AbstractInsulin-mediated glucose disposal varies widely in apparently healthy human beings, and the more insulin resistant an individual, the more insulin they must secrete in order to prevent the development of type 2 diabetes. However, the combination of insulin resistance and compensatory hyperinsulinemia increases the likelihood that an individual will be hypertensive, and have a dyslipidemia characterized by a high plasma triglyceride (TG) and low high-density lipoprotein cholesterol (HDL-C) concentration. These changes increase risk of cardiovascular disease (CVD), and in 1988, this cluster of related abnormalities was designated as comprising a syndrome (X). Several other clinical syndromes are now known to be associated with insulin resistance and compensatory hyperinsulinemia. For example, polycystic ovary syndrome appears to be secondary to insulin resistance and compensatory hyperinsulinemia. More recently, studies have shown that the prevalence of insulin resistance/hyperinsulinemia is increased in patients with nonalcoholic fatty liver disease, and there are reports that certain forms of cancer are more likely to occur in insulin resistant/hyperinsulinemic persons. Finally, there is substantial evidence of an association between insulin resistance/hyperinsulinemia, and sleep disordered breathing. Given the rapid increase in the number of clinical syndromes and abnormalities associated with insulin resistance/hyperinsulinemia, it seems reasonable to suggest that the cluster of these changes related to the defect in insulin action be subsumed under the term of the insulin resistance syndrome. In addition to the identification of additional clinical syndromes related to insulin resistance/hyperinsulinemia, a number of new risk factors have been recognized that would increase CVD risk in these individuals. Thus, in addition to a high TG and a low HDL-C, the atherogenic lipoprotein profile in insulin resistant/hyperinsulinemic individuals also includes the appearance of smaller and denser low density lipoprotein particles, and the enhanced postprandial accumulation of remnant lipoproteins; changes identified as increasing risk of CVD. Elevated plasma concentrations of plasminogen activator inhibitor-1 (PAI-1) have been shown to be associated with increased CVD, and there is evidence of a significant relationship between PAI-1 and fibrinogen levels and both insulin resistance and hyperinsulinemia. Evidence is also accumulating that sympathetic nervous system (SNS) activity is increased in insulin resistant, hyperinsulinemic individuals, and, along with the salt sensitivity associated with insulin resistance/hyperinsulinemia, increases the likelihood that these individuals will develop essential hypertension. The first step in the process of atherogenesis is the binding of mononuclear cells to the endothelium, and mononuclear cells isolated from insulin resistant/hyperinsulinemic individuals adhere with greater avidity. This process is modulated by adhesion molecules produced by endothelial cells, and there is a significant relationship between degree of insulin resistance and the plasma concentration of the several of these adhesion molecules. Further evidence of the relationship between insulin resistance and endothelial dysfunction is the finding that asymmetric dimethylarginine, an endogenous inhibitor of the enzyme nitric oxide synthase, is increased in insulin resistant/hyperinsulinemic individuals. Finally, plasma concentrations of several inflammatory markers are elevated in insulin resistant subjects. It is obvious that the cluster of abnormalities associated with insulin resistance and compensatory hyperinsulinemia contains many well-recognized CVD risk factors, choosing which one, or ones, that are primarily responsible for the accelerated atherogenesis that characterizes this syndrome is not a simple task. Indeed, efforts to try to do so by the use of multiple regression analysis of epidemiological data may be more misleading than helpful.

22 keywords...

hide…