Insulin resistance and metabolic syndrome in patients with nonfunctioning adrenal incidentalomas: a cause-effect...

The objective of the study was to assess insulin resistance (IR) and metabolic syndrome (MS) in patients with nonfunctioning adrenal incidentalomas (NFAIs). Among a total cohort of 46 patients with adrenal incidentalomas, we studied 29 patients with NFAIs (mean age, 54 ± 9 years; body mass index, 29 ± 3 kg/m(2)) and 37 age-, sex-, and body mass index-matched healthy controls. Besides the endocrine workup, IR was evaluated using fasting glucose and insulin concentrations, homeostasis model assessment of IR, and quantitative insulin sensitivity check index. In a subgroup of patients undergoing an oral glucose tolerance test, Matsuda index and total area under the curve for glucose and insulin were also evaluated. Total cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides, and other biochemical parameters were measured with standard techniques. Body composition was determined with dual-energy x-ray absorptiometry. Patients with NFAIs exhibited higher fasting glucose, insulin, and homeostasis model assessment of IR values; decreased quantitative insulin sensitivity check index and Matsuda index; and an increased-although not statistically significant-area under the curve for glucose and insulin compared with controls (P < .05). In addition, they exhibited higher systolic and diastolic blood pressure, triglycerides, and γ-glutamyltransferase and lower high-density lipoprotein cholesterol levels compared with controls (P < .05). Patients with NFAIs were all obese with a central type of fat accumulation and increased appendicular lean mass. Indices of IR showed a positive correlation with indices of MS (P < .05), but no correlation with markers of hormonal activity. Nonfunctioning adrenal incidentalomas are characterized by IR, hypertension, dyslipidemia, and fatty liver disease, all of them being components of MS. Thus, patients with NFAIs should be screened for MS during their initial workup to identify those at cardiometabolic risk and implement the appropriate interventions.