Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health.

Serum AMH levels decreased with age both in healthy women and in women with PCOS, although they were always 2- to 3-fold higher and remained elevated until 40 years of age in PCOS subjects. Thus, since serum AMH levels correlate well with antral follicle count and serum androgen levels, the measurement of AMH could be used as a tool to assess ovarian ageing, to diagnose polycystic ovaries/PCOS and to evaluate treatment efficacy.

Objective To examine if oral metformin is as effective as insulin in the prevention of fetal macrosomy in pregnancies complicated with gestational diabetes mellitus (GDM).Design Open-label prospective randomised controlled study.Setting Maternity outpatient clinics in a secondary and tertiary level hospital in Finland.Sample One hundred women with GDM who did not attain euglycaemia with diet.Methods Women were randomised to therapy with insulin (n = 50) or oral metformin (n = 50).Main outcome measures Incidence of large-for-gestational-age (LGA) infants and neonatal morbidity.Results There were no statistically significant differences in the incidence of LGA (8.5 versus 10.0%, P = 0.97), mean birthweight, mean cord artery pH or neonatal morbidity between the insulin and metformin groups. Fifteen (31.9%) of the 47 women randomised to metformin needed supplemental insulin. They were more obese (with a body mass index of 36 versus 30 kg/m 2 , P = 0.002), had higher fasting blood glucose levels in an oral glucose tolerance test (6.1 versus 5.0 mmol/l, P = 0.001) and needed medical treatment for GDM earlier (26 versus 31 gestational weeks, P = 0.002) than women who were normoglycemic with metformin. There was a tendency to a higher rate of caesarean sections in the metformin group than in the insulin group (RR 1.9; 95% CI 0.99-3.71).Conclusions Metformin seems to be suitable for the prevention of fetal macrosomy, especially in lean or moderately overweight women developing GDM in late gestation. Women with considerable obesity, high fasting blood glucose and an early need for pharmacological treatment may be more suitable for insulin therapy.

Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8×10−106), PRMT6 (rs17496332, 1p13.3, p = 1.4×10−11), GCKR (rs780093, 2p23.3, p = 2.2×10−16), ZBTB10 (rs440837, 8q21.13, p = 3.4×10−09), JMJD1C (rs7910927, 10q21.3, p = 6.1×10−35), SLCO1B1 (rs4149056, 12p12.1, p = 1.9×10−08), NR2F2 (rs8023580, 15q26.2, p = 8.3×10−12), ZNF652 (rs2411984, 17q21.32, p = 3.5×10−14), TDGF3 (rs1573036, Xq22.3, p = 4.1×10−14), LHCGR (rs10454142, 2p16.3, p = 1.3×10−07), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7×10−08), and UGT2B15 (rs293428, 4q13.2, p = 5.5×10−06). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5×10−08, women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ∼15.6% and ∼8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.