Relationship of Circulating miRNAs with Insulin Sensitivity and Associated Metabolic Risk Factors in Humans.

BACKGROUND: Insulin resistance disrupts metabolic processes and leads to various chronic disease states such as diabetes and metabolic syndrome (MetS). However, the mechanism linking insulin resistance with cardiometabolic disease pathophysiology is still unclear. One possibility may be through circulating microRNAs (c-miRs), which can alter gene expression in target tissues. Our goal was to assess the relationship of c-miRs with insulin sensitivity, as measured by the gold standard, hyperinsulinemic-euglycemic clamp technique.

METHODS: Eighty-one nondiabetic, sedentary, and weight-stable patients across a wide range of insulin sensitivities were studied. Measurements were taken for blood pressure, anthropometric data, fasting glucose and lipids, and insulin sensitivity measured by clamp. After an initial screening array to identify candidate miRs in plasma, all samples were assessed for relationships between these c-miRs and insulin sensitivity, as well as associated metabolic factors.

RESULTS: miR-16 and miR-107 were positively associated with insulin sensitivity (R = 0.09, P = 0.0074 and R = 0.08, P = 0.0417, respectively) and remained so after adjustment with body mass index (BMI). After adjusting for BMI, miR-33, -150, and -222 were additionally found to be related to insulin sensitivity. Regarding metabolic risk factors, miR-16 was associated with waist circumference (r = -0.25), triglycerides (r = -0.28), and high-density lipoprotein (r = 0.22), while miR-33 was inversely associated with systolic blood pressure (r = -0.29). No significant relationships were found between any candidate c-miRs and BMI, diastolic blood pressure, or fasting glucose.

CONCLUSIONS: Our results show that relative levels of circulating miR-16, -107, -33, -150, and -222 are associated with insulin sensitivity and metabolic risk factors, and suggest that multiple miRs may act in concert to produce insulin resistance and the clustering of associated traits that comprise the MetS. Therefore, miRs may have potential as novel therapeutic targets or agents in cardiometabolic disease.