Dysglycemia screening with oral glucose tolerance test in adolescents with polycystic ovary syndrome and relationship with obesity

Abstract Background Adolescents with polycystic ovary syndrome (PCOS) are at increased risk of impaired glucose tolerance (IGT) and type 2 diabetes mellitus. The aim of this study is to evaluate dysglycemia and biochemical differences based on BMI status and assess the prognostic ability of elevated hemoglobin A1c (HbA1c) in predicting an abnormal 2 hour oral glucose tolerance test (OGTT). Methods Retrospective cohort of female patients aged 11-18 years who underwent 75-g OGTT and were evaluated for PCOS at an urban tertiary care hospital between January 2002 to December 2017. Results In 106 adolescents with PCOS who had OGTT results available, IGT was markedly pronounced in the ≥95th percentile BMI group (17 out of 72; 23.6%) compared with <95th percentile BMI group (4 out of 34; 11.7%). One patient with obesity met the criteria for type 2 diabetes. Patients with obesity had significantly higher homeostasis model assessment (HOMA-IR) and lower whole body insulin sensitivity index (WBISI) (p < 0.001) compared to patients without obesity. Free testosterone levels were also higher in patients with obesity (p< 0.03) and were significantly associated with HOMA-IR when controlling for body mass index (BMI). HbA1c did not demonstrate a strong ability to predict abnormal OGTT on receiver operating characteristic (ROC) curve analysis [Area under the curve (AUC) = 0.572, 95% CI: 0.428, 0.939]). Conclusions In a study to assess glucose abnormalities in adolescents with PCOS, IGT was found to be markedly increased in patients with obesity, with abnormal glucose metabolism identified in over one-fifth of the patients. HbA1c alone may be a poor test to assess IGT and we recommend that adolescents diagnosed with PCOS and obesity undergo formal oral glucose tolerance testing

A Genetic Risk Score Is Associated with Weight Loss Following Roux-en Y Gastric Bypass Surgery

Currently, Roux-en Y gastric bypass (RYGB) is the most efficient therapy for severe obesity. Weight loss after surgery is, however, highly variable and genetically influenced. Genome-wide association studies have identified several single nucleotide polymorphisms (SNP) associated with body mass index (BMI) and waist-hip ratio (WHR). We aimed to identify two genetic risk scores (GRS) composed of weighted BMI and WHR-associated SNPs to estimate their impact on excess BMI loss (EBMIL) after RYGB surgery. Two hundred and thirty-eight obese patients (BMI 45.1 +/- 6.2 kg/m(2), 74 % women), who underwent RYGB, were genotyped for 35 BMI and WHR-associated SNPs and were followed up after 2 years. SNPs with high impact on post-surgical weight loss were filtered out using a random forest model. The filtered SNPs were combined into a GRS and analyzed in a linear regression model. An up to 11 % lower EBMIL with higher risk score was estimated for two GRS models (P = 0.026 resp. P = 0.021) composed of seven BMI-associated SNPs (closest genes: MC4R, TMEM160, PTBP2, NUDT3, TFAP2B, ZNF608, MAP2K5, GNPDA2, and MTCH2) and of three WHR-associated SNPs (closest genes: HOXC13, LYPLAL1, and DNM3-PIGC). Patients within the lowest GRS quartile had higher EBMIL compared to patients within the other three quartiles in both models. We identified two GRSs composed of BMI and WHR-associated SNPs with significant impact on weight loss after RYGB surgery using random forest analysis as a SNP selection tool. The GRS may be useful to pre-surgically evaluate the risks for patients undergoing RYGB surgery