Plasma Concentration of IGF-I Is Independently Associated With Insulin Sensitivity in Subjects With Different Degrees of Glucose Tolerance

Abstract

OBJECTIVE—We studied the relationships between plasma IGF-I concentrations and insulin sensitivity in subjects with various degrees of glucose tolerance. RESEARCH DESIGN AND METHODS—A total of 357 nondiabetic subjects, 54 subjects with impaired glucose tolerance and 98 newly diagnosed type 2 diabetic subjects, were consecutively recruited, and anthropometric and biochemical characteristics were collected. RESULTS—IGF-I concentrations were negatively correlated with age, BMI, waist-to-hip ratio, triglyceride levels, and systolic and diastolic blood pressure. IGF-I concentrations were positively correlated with HDL cholesterol and homeostasis model assessment of insulin sensitivity (HOMA-S). The correlations remained significant after adjusting for sex, age, and BMI. Correlations for HOMA-S with these metabolic and anthropometric variables were of a similar degree and direction to those for IGF-I concentrations. Stepwise linear regression analysis in a model, which included well-known modulators of insulin sensitivity such as sex, age, BMI, glucose tolerance status, family history of diabetes, waist-to-hip ratio, systolic and diastolic blood pressure, HDL cholesterol, and triglyceride levels, revealed that IGF-I concentrations were independently associated with insulin sensitivity accounting for 10.8% of its variation (P < 0.0001). IGF-I concentrations were significantly lower in subjects with World Health Organization (WHO)-defined metabolic syndrome compared with subjects without metabolic syndrome (P < 0.0001). Logistic regression analysis showed that each unit increase in log-transformed IGF-I concentrations was associated with a 90.5% reduction in the risk of WHO-defined metabolic syndrome. CONCLUSIONS—These data indicate that IGF-I has the characteristics to be a marker for the insulin resistance syndrome. This suggests that low IGF-I levels may be a useful marker for identifying subjects at risk for cardiovascular disease.