Plasma concentration of IGF-I is independently associated with insulin sensitivity in subjects with different degrees of glucose tolerance

OBJECTIVE- We studied the relationships between plasma IGF-1 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-1 concentrations were negatively correlated with age, BMI, waist-to-hip ratio, triglyceride levels, and systolic and diastolic blood pressure. IGF-1 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-1 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-1 concentrations were independently associated with insulin sensitivity accounting for 10.8% of its variation (P < 0.0001). IGF-1 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-1 concentrations was associated with a 90.5% reduction in the risk of WHO-defined metabolic syndrome. CONCLUSIONS - These data indicate that IGF-1 has the characteristics to be a marker for the insulin resistance syndrome. This suggests that low IGF-1 levels may be a useful marker for identifying subjects at risk for cardiovascular disease