Objective:Obese girls with polycystic ovarian syndrome (PCOS) have decreased insulin sensitivity (IS), muscle mitochondrial dysfunction and increased liver fat, which may contribute to their increased risk for type 2 diabetes. Less is known regarding normal-weight girls with PCOS.Methods:Normal-weight girls with PCOS [n =18, age 15.9 ± 1.8 years, body mass index (BMI) percentile 68 ± 18] and normal-weight controls (NWC; n = 20; age 15.0 ± 2.1 years, BMI percentile 60 ± 21) were studied. Tissue-specific IS was assessed with a four-phase hyperinsulinemic-euglycemic clamp with isotope tracers and a 2-hour oral glucose tolerance test (OGTT). Hepatic fat was determined using magnetic resonance imaging. Postexercise muscle mitochondrial function was assessed with 31P MR spectroscopy.Results:Both groups had similar demographics, anthropomorphics, physical attributes, habitual physical activity levels and fasting laboratory values, except for increased total testosterone and DHEAS in PCOS. Clamp-assessed peripheral IS was lower in PCOS (10.4 ± 2.4 mg/kg/min vs 12.7 ± 2.1; P = 0.024). The 120-minute OGTT insulin and glucose concentrations were higher in PCOS (114 IU/mL ± 26 vs 41 ± 25, P = <0.001 and 119 ± 22 mg/dL vs 85 ± 23, P = 0.01, respectively). Muscle mitochondrial ADP and phosphocreatine time constants were slower in PCOS. Despite a higher percentage liver fat in PCOS, hepatic IS was similar between groups, as was adipose IS.Conclusions:Normal-weight girls with PCOS have decreased peripheral IS and muscle mitochondrial dysfunction, abnormal glucose disposal, relative postprandial hyperinsulinemia, and increased hepatic fat compared to NWC. Despite a normal BMI, multiple aspects of metabolism appear altered in normal-weight girls with PCOS.

Adolescents with T1D have adipose, hepatic and peripheral IR. This IR occurs regardless of obesity and metabolic syndrome features. Youth with T1D may benefit from interventions directed at improving IR in these tissues, and this area requires further research.

HbA does not underestimate ASG in CF as previously assumed. No alternate glycemic marker correlated more strongly with ASG than HbA. %GA shows strong correlation with ASG and added to the prediction of ASG beyond HbA. However, we are not advocating use of HbA for diabetes screening in CF based on these results. Further study will determine whether glycemic measures other than ASG differ among different types of diabetes for a given HbA.