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Study Question: Is a genetic risk score (GRS) associated with polycystic ovary syndrome (PCOS) and its related clinical features?Summary Answer: The GRS calculated by genome-wide association studies (GWASs) was significantly associated with PCOS status and its related clinical features.What Is Known Already: PCOS is a heterogeneous disorder and is characterized by oligomenorrhea, hyperandrogenism and polycystic ovary morphology. Although recent GWASs have identified multiple genes associated with PCOS, a comprehensive genetic risk study of these loci with PCOS and related traits (e.g. free testosterone, menstruation number/year and ovarian morphology) has not been performed.Study Design, Size, Duration: This study was designed as a cross-sectional case-control study. We recruited 862 women with PCOS and 860 controls. Women with PCOS were divided into four subgroups: (1) oligomenorrhea + hyperandrogenism + polycystic ovary, (2) oligomenorrhea + hyperandrogenism, (3) oligomenorrhea + polycystic ovary and (4) hyperandrogenism + polycystic ovary.Participants/materials, Settings, Methods: Genomic DNA was genotyped for the PCOS susceptibility loci using the HumanOmni1-Quad v1 array. Venous blood was drawn in the early follicular phase to measure baseline metabolic and hormonal parameters. A GRS was calculated by summing the number of risk alleles from 11 single-nucleotide polymorphisms (SNPs) that were identified in previous GWASs on PCOS. A weighted GRS (wGRS) was calculated by multiplying the number of risk alleles for each SNP by its estimated effect (beta) obtained from the association analysis.Main Results and the Role Of Chance: The GRS was higher in women with PCOS than in controls (8.8 versus 8.2, P < 0.01) and was significantly associated with PCOS after adjusting for age and BMI. An analysis of GRS quartiles (Q1 = 3-5, Q2 = 6-8, Q3 = 9-11, Q4 = 12-15) revealed that the subjects in the highest quartile showed a remarkable increased risk of PCOS compared with those in the lowest quartile (odds ratio = 6.28, P < 0.001). Free testosterone level, menstruation number per year, ovarian volume and ovarian follicle numbers were significantly associated with the GRS (in all cases, P < 0.01). The wGRS yielded similar results.Limitations, Reasons For Caution: We used 11 loci for the calculation of GRS, but a higher number of PCOS risk alleles was reported in previous studies. Therefore, further studies should assess the value of GRS including the additional SNPs related to PCOS. Although a GRS of ≥12 was significantly associated with PCOS, the GRS showed a poor predictive value; therefore, the use of genetic information based on current GWAS data only may present problems.Wider Implications Of the Findings: The GRS could be used to identify asymptomatic individuals among people at risk and stratify them into accurate risk categories for the purpose of individualizing treatment approaches, which could potentially improve health outcomes.Study Funding/competing Interests: None of the authors have any conflicts of interest to declare. No funding was obtained for the study. [ABSTRACT FROM AUTHOR]

Background: Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women of reproductive age, and it is affected by both environmental and genetic factors. Although the genetic component of PCOS is evident, studies aiming to identify susceptibility genes have shown controversial results. This study conducted a pathway-based analysis using a dataset obtained through a genome-wide association study (GWAS) to elucidate the biological pathways that contribute to PCOS susceptibility and the associated genes. Methods: We used GWAS data on 636,797 autosomal single nucleotide polymorphisms (SNPs) from 1,221 individuals (432 PCOS patients and 789 controls) for analysis. A pathway analysis was conducted using meta-analysis gene-set enrichment of variant associations (MAGENTA). Top-ranking pathways or gene sets associated with PCOS were identified, and significant genes within the pathways were analyzed. Results: The pathway analysis of the GWAS dataset identified significant pathways related to oocyte meiosis and the regulation of insulin secretion by acetylcholine and free fatty acids (all nominal gene-set enrichment analysis (GSEA) P-values < 0.05). In addition, INS, GNAQ, STXBP1, PLCB3, PLCB2, SMC3 and PLCZ1 were significant genes observed within the biological pathways (all gene P-values < 0.05). Conclusions: By applying MAGENTA pathway analysis to PCOS GWAS data, we identified significant pathways and candidate genes involved in PCOS. Our findings may provide new leads for understanding the mechanisms underlying the development of PCOS. [ABSTRACT FROM AUTHOR]

Objective: To determine the features of polycystic ovary syndrome (PCOS) that are implicated in the associated reproductive and metabolic morbidities. Design: Cross-sectional case–control study. Setting: Academic medical setting. Patient(s): A total of 1,062 women with PCOS and 1,887 women without PCOS. Intervention(s): None. Main Outcome Measure(s): Physical examination including hirsutism scoring, biochemical and hormone measurements, ovarian ultrasound, and a 75-g oral glucose tolerance test to measure glucose and insulin levels. Result(s): A factor analysis identified four dominant factors in women with PCOS. These factors were interpreted as follows: [1] metabolic and hyperandrogenemia factor, [2] oligomenorrhea and hyperandrogenemia factor, [3] blood pressure factor, and [4] ovarian morphology factor. In women with PCOS, hyperandrogenemia was a significant predictor of metabolic syndrome after adjusting for age, body mass index, and insulin resistance in the regression analysis. Conclusion(s): A factor analysis identified multiple factors that are responsible for the abnormalities associated with PCOS. Hyperandrogenemia was a common underlying feature of the metabolic and reproductive abnormalities in women with PCOS but not in women without PCOS. [ABSTRACT FROM AUTHOR]

Objective Visceral fat accumulation is more strongly related to insulin resistance than to excess total adiposity. The visceral adiposity index (VAI) has recently been suggested as an indicator of the visceral adiposity measured by magnetic resonance imaging. To evaluate whether the VAI could replace visceral computed tomography (CT) scanning and predict insulin resistance in young women with polycystic ovary syndrome (PCOS) was presented. Design and Methods One hundred and eighty Korean women aged 16-41 years who were diagnosed with PCOS using the Rotterdam criteria were included. The VAI was derived from a formula using body mass index, waist circumference, triglycerides, and high-density lipoprotein cholesterol. Visceral adiposity was defined as a visceral fat area (VFA) measuring > 100 cm2 by CT scanning. Insulin sensitivity was evaluated by insulin-mediated glucose utilization ( M value), which was obtained using a euglycemic hyperinsulinemic clamp. Results The VAI positively correlated with VFA, the visceral-to-subcutaneous fat ratio, and systolic and diastolic blood pressure, and negatively correlated with the M value. In a linear regression analysis, the VAI was an independent determinant of the insulin sensitivity after controlling for age, systolic blood pressure, fasting glucose, fasting insulin, and testosterone levels. In a logistic regression analysis, the VAI odds ratio was 3.5 (95% CI 1.2-9.8) for predicting visceral adiposity after controlling for the various metabolic parameters and testosterone. Conclusion The VAI can replace visceral CT scanning as a marker for visceral adiposity, and it predicts insulin resistance in young women with PCOS. [ABSTRACT FROM AUTHOR]

Abstract: Commonly used tests for the diagnosis of diabetes include measurements of fasting plasma glucose levels and the oral glucose tolerance test (OGTT). Recently, a hemoglobin A1C (A1C) level of 6.5% has been included as a criterion for diabetes diagnosis by the American Diabetes Association. We aimed to determine appropriate A1C cutoff values for identifying patients with diabetes or prediabetes, including impaired glucose tolerance and impaired fasting glucose among Korean adults and to determine whether these cutoffs vary according to age. We recruited 4616 adults without a history of diabetes from 10 university hospitals. A 75-g OGTT and A1C sampling were performed in all examinees. Pointwise area under the receiver operating characteristic curve was used to evaluate the diagnostic accuracy of the A1C cutoff. An A1C threshold of 6.1% proved to be the optimal limit for diagnosing diabetes, with 63.8% sensitivity and 88.1% specificity. The cutoff value increased with age (5.9% in 18–39 years, 6.2% in 40–64 years, and 6.4% in older than 65 years) and were similar for men and women. An A1C cutoff of 5.7% had reasonable sensitivity (48.6%) and specificity (65.7%) for the identification of prediabetes. Further prospective studies should be carried out to determine whether the application of age-specific diagnostic criteria is appropriate. [Copyright &y& Elsevier]

Objective: To determine the prospective association between endogenous sex hormones and the development of type 2 diabetes in older men and women.Research Design and Methods: A standardized medical history was obtained, an oral glucose tolerance test was performed, and plasma samples for sex hormones and covariates were collected from ambulatory, community-dwelling men and women at baseline from 1984 to 1987. Approximately 8 years later (1992-1996), another medical history was obtained, an oral glucose tolerance test was performed, fasting and 2-h insulin levels were measured, and the homeostasis model assessment for insulin resistance (HOMA-IR) was evaluated. This report is based on the 294 men and 233 women, aged 55-89 years, who completed both visits and who did not have diabetes as determined by history or glucose tolerance test at baseline, as well as women who were postmenopausal and not taking replacement estrogen.Results: In age-adjusted correlation analyses, total testosterone was inversely and significantly related to subsequent levels of fasting and postchallenge glucose and insulin in men, whereas bioavailable testosterone and bioavailable estradiol were positively and significantly related to fasting and postchallenge glucose and insulin in women (all P <0.05). There was similar significant association with insulin resistance (HOMA-IR) in unadjusted and multiply adjusted analyses (P <0.05). There were 26 men and 17 women with new (incident) diabetes. The odds for new diabetes were 2.7 (95% CI 1.1-6.6) for men in the lowest quartile of total testosterone and 2.9 (1.1-8.4) for women in the highest quartile of bioavailable testosterone.Conclusions: Low testosterone levels in men and high testosterone levels in women predict insulin resistance and incident type 2 diabetes in older adults. [ABSTRACT FROM AUTHOR]

Objective: To investigate whether the peripheral blood mtDNA (pb-mtDNA) content is decreased and linked to insulin resistance in the offspring of type 2 diabetic patients.Research Design and Methods: A total of 82 offspring of type 2 diabetic patients and 52 age-, sex-, and BMI-matched normal subjects from the Mokdong, Korea, population were selected for this study by stratified, randomized sampling. Of the offspring of diabetic patients, 52 had normal glucose tolerance (NGT), 21 had impaired glucose tolerance (IGT), and 9 had newly diagnosed type 2 diabetes. The pb-mtDNA content was measured by real-time polymerase chain reaction with a mitochondria-specific fluorescent probe, normalized by a nuclear DNA, 285 rRNA gene. The associations between pb-mtDNA content and several parameters of insulin resistance were studied.Results: The pb-mtDNA contents tended to be lower in the 82 offspring of type 2 diabetic patients (1,084.7 +/- 62.6 vs. 1,304.0 +/- 99.2 in the offspring and control subjects, respectively, P = 0.051) and was significantly lower in the combined NGT and IGT offspring group (NGT+IGT, 1,068.0 +/- 67.8, P < 0.05) than in the control subjects. In NGT+IGT offspring, the pb-mtDNA content was significantly correlated with logarithmically transformed insulin sensitivity (r = 0.253, P < 0.05) and was the main predictor of insulin sensitivity.Conclusions: Quantitative mtDNA status might be a hereditary factor associated with type 2 diabetes and could serve as an indicator for insulin sensitivity. [ABSTRACT FROM AUTHOR]