Failure of homeostatic model assessment of insulin resistance to detect marked diet-induced insulin resistance in dogs.

Accurate quantification of insulin resistance is essential for determining efficacy of treatments to reduce diabetes risk. Gold-standard methods to assess resistance are available (e.g., hyperinsulinemic clamp or minimal model), but surrogate indices based solely on fasting values have attractive simplicity. One such surrogate, the homeostatic model assessment of insulin resistance (HOMA-IR), is widely applied despite known inaccuracies in characterizing resistance across groups. Of greater significance is whether HOMA-IR can detect changes in insulin sensitivity induced by an intervention. We tested the ability of HOMA-IR to detect high-fat diet-induced insulin resistance in 36 healthy canines using clamp and minimal model analysis of the intravenous glucose tolerance test (IVGTT) to document progression of resistance. The influence of pancreatic function on HOMA-IR accuracy was assessed using the acute insulin response during the IVGTT (AIRG). Diet-induced resistance was confirmed by both clamp and minimal model (P < 0.0001), and measures were correlated with each other (P = 0.001). In striking contrast, HOMA-IR ([fasting insulin (μU/mL) × fasting glucose (mmol)]/22.5) did not detect reduced sensitivity induced by fat feeding (P = 0.22). In fact, 13 of 36 animals showed an artifactual decrease in HOMA-IR (i.e., increased sensitivity). The ability of HOMA-IR to detect diet-induced resistance was particularly limited under conditions when insulin secretory function (AIRG) is less than robust. In conclusion, HOMA-IR is of limited utility for detecting diet-induced deterioration of insulin sensitivity quantified by glucose clamp or minimal model. Caution should be exercised when using HOMA-IR to detect insulin resistance when pancreatic function is compromised. It is necessary to use other accurate indices to detect longitudinal changes in insulin resistance with any confidence.

Pubmed ID: 24353184 RIS Download