Homeostastic model assessment and insulin sensitivity/resistance.

Homeostasis is the manifestation of a large network of integrated metabolic reactions and signaling pathways designed to maintain life and function in a stable manner. Insulin is an integral part of this regulatory network and affects virtually all its parts. The actions of insulin vary in time (1) as well as in the various tissues it affects as demonstrated, for example, by selective receptor deletion studies (2). Moreover, insulin individually affects a large number of reactions within these tissues. Lack of insulin, or of its action(s), results in diabetes. This has historically been viewed from the perspective of glucose metabolism, although, as pointed out by McGarry (3), a similar spectrum of deficiencies would have been identified first if lipids had been the primary focus of investigation. Insulin action as an entity is therefore, necessarily, ill-defined. It is embedded within the network of reactions and signals where it plays critical regulatory roles. In some sense, measuring insulin action must be equally tenuous. When, where, and how it is measured is a matter of physiology, but also of history. Clinically then, resistance to insulin action was first defined on the backdrop of glucose metabolism (4). Specifically, diabetes was divided into insulin-sensitive and -insensitive types. Insulin insensitivity or resistance rose into more prominence when it was associated with other risk factors for the development of type 2 diabetes, such as obesity, dyslipidemia, hypertension, and hypercoagulopathy, grouped under the term hyperinsulinemic/insulin resistance syndrome (X) or currently, the metabolic syndrome. Collectively, this group of pathologies increased the risk of developing diabetes and was associated also with an increased risk of cardiovascular disease (5,6), hence the impetus to quantify insulin resistance. Many methods consequently have been developed and new ones continue to arise. Given the diverse nature of insulin actions, the heterogeneity of the methods is not surprising. In this issue, the careful article by Ader et al. (7) serves to alert us once again to the when/where/how of the assessment of insulin sensitivity. It compares the change in insulin sensitivity in dogs after a high-fat diet, using the hyperinsulinemic-euglycemic clamp (8), an insulinsupplemented intravenous glucose tolerance test (IVGTT) with minimal model analysis (9), and the homeostatic model assessment (HOMA) method for insulin sensitivity/resistance analysis based on fasting glucose and insulin samples (10). It found in pooled studies that HOMA-insulin resistance (IR) did not correlate with the IVGTTand clamp-based methods either before or after the fast. Neither were the diet-induced changes in the insulin sensitivity index (SI) found by the other two methods reflected in the HOMA calculation. In many ways, these results echo the literature on such comparisons. HOMA-SI/IR have been widely applied, often in large-scale population studies, and frequently compared with other methods of SI determination. Largely, they correlate with more detailed indices of SI (clamp, IVGTT) (11–14) and in some longitudinal studies (15,16), but less so in others (17), and not as well in some populations such as African American men (18) and Asian-Indian men that include a preponderance of lean diabetic patients (19). In animal models, mice (20) and rats (21) do not do so well with HOMA, but rhesus monkeys do better (22). Clearly, there is some diversity. This occurs in the comparison of any methods. For HOMA, systematic errors could be expected if the model description does not correspond to the population (or species) being studied.