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The state of somatic energy stores in metazoans is communicated to the brain, which regulates key aspects of behaviour, growth, nutrient partitioning and development1. The central melanocortin system acts through melanocortin 4 receptor (MC4R) to control appetite, food intake and energy expenditure2. Here we present evidence that MC3R regulates the timing of sexual maturation, the rate of linear growth and the accrual of lean mass, which are all energy-sensitive processes. We found that humans who carry loss-of-function mutations in MC3R, including a rare homozygote individual, have a later onset of puberty. Consistent with previous findings in mice, they also had reduced linear growth, lean mass and circulating levels of IGF1. Mice lacking Mc3r had delayed sexual maturation and an insensitivity of reproductive cycle length to nutritional perturbation. The expression of Mc3r is enriched in hypothalamic neurons that control reproduction and growth, and expression increases during postnatal development in a manner that is consistent with a role in the regulation of sexual maturation. These findings suggest a bifurcating model of nutrient sensing by the central melanocortin pathway with signalling through MC4R controlling the acquisition and retention of calories, whereas signalling through MC3R primarily regulates the disposition of calories into growth, lean mass and the timing of sexual maturation. MC3R deficiency is associated with a delay in the onset of puberty, and a reduction in growth and lean mass.

Type 2 diabetes (T2D) is a heritable metabolic disorder. While population studies have identified hundreds of common genetic variants associated with T2D, the role of rare (frequency < 0.1%) protein-coding variation is less clear. We performed exome sequence analysis in 418,436 (n = 32,374 T2D cases) individuals in the UK Biobank. We identified previously reported genes (GCK, GIGYF1, HNF1A) in addition to missense variants in ZEB2 (n = 31 carriers; odds ratio [OR] = 5.5 [95% confidence interval = 2.5-12.0]; p = 6.4 × 10-7), MLXIPL (n = 245; OR = 2.3 [1.6-3.2]; p = 3.2 × 10-7), and IGF1R (n = 394; OR = 2.4 [1.8-3.2]; p = 1.3 × 10-10). Carriers of damaging missense variants within IGF1R were also shorter (-2.2 cm [-1.8 to -2.7]; p = 1.2 × 10-19) and had higher circulating insulin-like growth factor-1 (IGF-1) protein levels (2.3 nmol/L [1.7-2.9]; p = 2.8 × 10-14), indicating relative IGF-1 resistance. A likely causal role of IGF-1 resistance was supported by Mendelian randomization analyses using common variants. These results increase understanding of the genetic architecture of T2D and highlight the growth hormone/IGF-1 axis as a potential therapeutic target.

Purpose: The study aimed to systematically ascertain male sex chromosome abnormalities, 47,XXY (Klinefelter syndrome [KS]) and 47,XYY, and characterize their risks of adverse health outcomes. Methods: We analyzed genotyping array or exome sequence data in 207,067 men of European ancestry aged 40 to 70 years from the UK Biobank and related these to extensive routine health record data. Results: Only 49 of 213 (23%) of men whom we identified with KS and only 1 of 143 (0.7%) with 47,XYY had a diagnosis of abnormal karyotype on their medical records or self-report. We observed expected associations for KS with reproductive dysfunction (late puberty: risk ratio [RR] = 2.7; childlessness: RR = 4.2; testosterone concentration: RR = -3.8 nmol/L, all P < 2 x 10(-8)), whereas XYY men appeared to have normal reproductive function. Despite this difference, we identified several higher disease risks shared across both KS and 47,XYY, including type 2 diabetes (RR = 3.0 and 2.6, respectively), venous thrombosis (RR = 6.4 and 7.4, respectively), pulmonary embolism (RR = 3.3 and 3.7, respectively), and chronic obstructive pulmonary disease (RR = 4.4 and 4.6, respectively) (all P Conclusion: KS and 47,XYY were mostly unrecognized but conferred substantially higher risks for metabolic, vascular, and respiratory diseases, which were only partially explained by higher levels of body mass index, deprivation, and smoking. (C) 2022 The Authors. Published by Elsevier Inc. on behalf of American College of Medical Genetics and Genomics.

Aims/hypothesis Type 2 diabetes is a complex metabolic disease with increasing prevalence worldwide. Improving the prediction of incident type 2 diabetes using epigenetic markers could help tailor prevention efforts to those at the highest risk. The aim of this study was to identify predictive methylation markers for incident type 2 diabetes by combining epigenome-wide association study (EWAS) results from five prospective European cohorts. Methods We conducted a meta-analysis of EWASs in blood collected 7–10 years prior to type 2 diabetes diagnosis. DNA methylation was measured with Illumina Infinium Methylation arrays. A total of 1250 cases and 1950 controls from five longitudinal cohorts were included: Doetinchem, ESTHER, KORA1, KORA2 and EPIC-Norfolk. Associations between DNA methylation and incident type 2 diabetes were examined using robust linear regression with adjustment for potential confounders. Inverse-variance fixed-effects meta-analysis of cohort-level individual CpG EWAS estimates was performed using METAL. The methylGSA R package was used for gene set enrichment analysis. Confirmation of genome-wide significant CpG sites was performed in a cohort of Indian Asians (LOLIPOP, UK). Results The meta-analysis identified 76 CpG sites that were differentially methylated in individuals with incident type 2 diabetes compared with control individuals (p values −7). Sixty-four out of 76 (84.2%) CpG sites were confirmed by directionally consistent effects and p values 1c) showed no improvement (AUC 0.757 vs 0.753). Gene set enrichment analysis of the full epigenome-wide results clearly showed enrichment of processes linked to insulin signalling, lipid homeostasis and inflammation. Conclusions/interpretation By combining results from five European cohorts, and thus significantly increasing study sample size, we identified 76 CpG sites associated with incident type 2 diabetes. Replication of 64 CpGs in an independent cohort of Indian Asians suggests that the association between DNA methylation levels and incident type 2 diabetes is robust and independent of ethnicity. Our data also indicate that BMI partly explains the association between DNA methylation and incident type 2 diabetes. Further studies are required to elucidate the underlying biological mechanisms and to determine potential causal roles of the differentially methylated CpG sites in type 2 diabetes development. Graphical abstract

Type 2 diabetes (T2D) is a heritable metabolic disorder. While population studies have identified hundreds of common genetic variants associated with T2D, the role of rare (frequency 0.1%) protein-coding variation is less clear. We performed exome sequence analysis in 418,436 (n = 32,374 T2D cases) individuals in the UK Biobank. We identified previously reported genes (

Type 2 diabetes (T2D) is a chronic metabolic disorder with a significant genetic component. While large-scale population studies have identified hundreds of common genetic variants associated with T2D susceptibility, the role of rare (minor allele frequency < 0.1%) protein coding variation is less clear. To this end, we performed a gene burden analysis of 18,691 genes in 418,436 (n=32,374 T2D cases) individuals sequenced by the UK Biobank (UKBB) study to assess the impact of rare genetic variants on T2D risk. Our analysis identified T2D associations at exome-wide significance (P < 6.9×10-7) with rare, damaging variants within previously identified genes including GCK, GIGYF1, HNF1A, and TNRC6B. In addition, individuals with rare, damaging missense variants in the genes ZEB2 (N=31 carriers; OR=5.5 [95% CI=2.5-12.0]; p=6.4×10-7), MLXIPL (N=245; OR=2.3 [1.6-3.2]; p=3.2×10-7), and IGF1R (N=394; OR=2.4 [1.8-3.2]; p=1.3×10-10) have higher risk of T2D. Carriers of damaging missense variants within IGF1R were also shorter (-2.2cm [-1.8-2.7]; p=1.2×10-19) and had higher circulating protein levels of insulin-like growth factor-1 (IGF-1; 2.3 nmol/L [1.7-2.9] p=2.8×10-14), indicating relative IGF-1 resistance. A likely causal role of IGF-1 resistance on T2D was further supported by Mendelian randomisation analyses using common variants. Our results increase our understanding of the genetic architecture of T2D and highlight a potential therapeutic benefit of targeting the Growth Hormone/IGF-1 axis.

OBJECTIVE Higher plasma vitamin C levels are associated with lower type 2 diabetes risk, but whether this association is causal is uncertain. To investigate this, we studied the association of genetically predicted plasma vitamin C with type 2 diabetes. RESEARCH DESIGN AND METHODS We conducted genome-wide association studies of plasma vitamin C among 52,018 individuals of European ancestry to discover novel genetic variants. We performed Mendelian randomization analyses to estimate the association of genetically predicted differences in plasma vitamin C with type 2 diabetes in up to 80,983 case participants and 842,909 noncase participants. We compared this estimate with the observational association between plasma vitamin C and incident type 2 diabetes, including 8,133 case participants and 11,073 noncase participants. RESULTS We identified 11 genomic regions associated with plasma vitamin C (P < 5 × 10−8), with the strongest signal at SLC23A1, and 10 novel genetic loci including SLC23A3, CHPT1, BCAS3, SNRPF, RER1, MAF, GSTA5, RGS14, AKT1, and FADS1. Plasma vitamin C was inversely associated with type 2 diabetes (hazard ratio per SD 0.88; 95% CI 0.82, 0.94), but there was no association between genetically predicted plasma vitamin C (excluding FADS1 variant due to its apparent pleiotropic effect) and type 2 diabetes (1.03; 95% CI 0.96, 1.10). CONCLUSIONS These findings indicate discordance between biochemically measured and genetically predicted plasma vitamin C levels in the association with type 2 diabetes among European populations. The null Mendelian randomization findings provide no strong evidence to suggest the use of vitamin C supplementation for type 2 diabetes prevention.

Context As many as 75% of patients with polycystic ovary syndrome (PCOS) are estimated to be unidentified in clinical practice. Objective Utilizing polygenic risk prediction, we aim to identify the phenome-wide comorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventive treatment. Design, Patients, and Methods Leveraging the electronic health records (EHRs) of 124 852 individuals, we developed a PCOS risk prediction algorithm by combining polygenic risk scores (PRS) with PCOS component phenotypes into a polygenic and phenotypic risk score (PPRS). We evaluated its predictive capability across different ancestries and perform a PRS-based phenome-wide association study (PheWAS) to assess the phenomic expression of the heightened risk of PCOS. Results The integrated polygenic prediction improved the average performance (pseudo-R2) for PCOS detection by 0.228 (61.5-fold), 0.224 (58.8-fold), 0.211 (57.0-fold) over the null model across European, African, and multi-ancestry participants respectively. The subsequent PRS-powered PheWAS identified a high level of shared biology between PCOS and a range of metabolic and endocrine outcomes, especially with obesity and diabetes: “morbid obesity”, “type 2 diabetes”, “hypercholesterolemia”, “disorders of lipid metabolism”, “hypertension”, and “sleep apnea” reaching phenome-wide significance. Conclusions Our study has expanded the methodological utility of PRS in patient stratification and risk prediction, especially in a multifactorial condition like PCOS, across different genetic origins. By utilizing the individual genome–phenome data available from the EHR, our approach also demonstrates that polygenic prediction by PRS can provide valuable opportunities to discover the pleiotropic phenomic network associated with PCOS pathogenesis.

Context Biological and translational insights from large-scale, array-based genetic studies of fat distribution, a key determinant of metabolic health, have been limited by the difficulty in linking predominantly noncoding variants to specific gene targets. Rare coding variant analyses provide greater confidence that a specific gene is involved, but do not necessarily indicate whether gain or loss of function (LoF) would be of most therapeutic benefit. Objective This work aimed to identify genes/proteins involved in determining fat distribution. Methods We combined the power of genome-wide analysis of array-based rare, nonsynonymous variants in 450 562 individuals in the UK Biobank with exome-sequence-based rare LoF gene burden testing in 184 246 individuals. Results The data indicate that the LoF of 4 genes (PLIN1 [LoF variants, P = 5.86 × 10–7], INSR [LoF variants, P = 6.21 × 10–7], ACVR1C [LoF + moderate impact variants, P = 1.68 × 10–7; moderate impact variants, P = 4.57 × 10–7], and PDE3B [LoF variants, P = 1.41 × 10–6]) is associated with a beneficial effect on body mass index–adjusted waist-to-hip ratio and increased gluteofemoral fat mass, whereas LoF of PLIN4 (LoF variants, P = 5.86 × 10–7 adversely affects these parameters. Phenotypic follow-up suggests that LoF of PLIN1, PDE3B, and ACVR1C favorably affects metabolic phenotypes (eg, triglycerides [TGs] and high-density lipoprotein [HDL] cholesterol concentrations) and reduces the risk of cardiovascular disease, whereas PLIN4 LoF has adverse health consequences. INSR LoF is associated with lower TG and HDL levels but may increase the risk of type 2 diabetes. Conclusion This study robustly implicates these genes in the regulation of fat distribution, providing new and in some cases somewhat counterintuitive insight into the potential consequences of targeting these molecules therapeutically.

Biological and translational insights from large-scale, array-based genetic studies of fat distribution, a key determinant of metabolic health, have been limited by the difficulty in linking identified predominantly non-coding variants to specific gene targets. Rare coding variant analyses provide greater confidence that a specific gene is involved, but do not necessarily indicate whether gain or loss of function would be of most therapeutic benefit. Here we use a dual approach that combines the power of genome-wide analysis of array-based rare, non-synonymous variants in 184,246 individuals of UK Biobank with exome-sequence-based rare loss of function gene burden testing. The data indicates that loss-of-function (LoF) of four genes (PLIN1, INSR, ACVR1C and PDE3B) is associated with a beneficial impact on WHRadjBMI and increased gluteofemoral fat mass, whereas PLIN4 LoF adversely affects these parameters. This study robustly implicates these genes in the regulation of fat distribution, providing new and in some cases somewhat counter-intuitive insight into the potential consequences of targeting these molecules therapeutically.

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease. Hundreds of genetic loci associated with age at menopause, combined with experimental evidence in mice, highlight mechanisms of reproductive ageing across the lifespan.

Funder: Division of Cancer Epidemiology and Genetics, National Cancer Institute; doi: http://dx.doi.org/10.13039/100011541, Funder: National Cancer Institute (NCI), Background: Mosaic chromosomal alterations (mCAs) are large chromosomal gains, losses and copy-neutral losses of heterozygosity (LOH) in peripheral leukocytes. While many individuals with detectable mCAs have no notable adverse outcomes, mCA-associated gene dosage alterations as well as clonal expansion of mutated leukocyte clones could increase susceptibility to disease. Results: We performed a phenome-wide association study (PheWAS) using existing data from 482,396 UK Biobank (UKBB) participants to investigate potential associations between mCAs and incident disease. Of the 1290 ICD codes we examined, our adjusted analysis identified a total of 50 incident disease outcomes associated with mCAs at PheWAS significance levels. We observed striking differences in the diseases associated with each type of alteration, with autosomal mCAs most associated with increased hematologic malignancies, incident infections and possibly cancer therapy-related conditions. Alterations of chromosome X were associated with increased lymphoid leukemia risk and, mCAs of chromosome Y were linked to potential reduced metabolic disease risk. Conclusions: Our findings demonstrate that a wide range of diseases are potential sequelae of mCAs and highlight the critical importance of careful covariate adjustment in mCA disease association studies.

Funder: Department of Health, Mosaic loss of chromosome Y (LOY) in leukocytes is the most common form of clonal mosaicism, caused by dysregulation in cell-cycle and DNA damage response pathways. Previous genetic studies have focussed on identifying common variants associated with LOY, which we now extend to rarer, protein-coding variation using exome sequences from 82,277 male UK Biobank participants. We find that loss of function of two genes-CHEK2 and GIGYF1-reach exome-wide significance. Rare alleles in GIGYF1 have not previously been implicated in any complex trait, but here loss-of-function carriers exhibit six-fold higher susceptibility to LOY (OR = 5.99 [3.04-11.81], p = 1.3 × 10-10). These same alleles are also associated with adverse metabolic health, including higher susceptibility to Type 2 Diabetes (OR = 6.10 [3.51-10.61], p = 1.8 × 10-12), 4 kg higher fat mass (p = 1.3 × 10-4), 2.32 nmol/L lower serum IGF1 levels (p = 1.5 × 10-4) and 4.5 kg lower handgrip strength (p = 4.7 × 10-7) consistent with proposed GIGYF1 enhancement of insulin and IGF-1 receptor signalling. These associations are mirrored by a common variant nearby associated with the expression of GIGYF1. Our observations highlight a potential direct connection between clonal mosaicism and metabolic health.

Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism1–5, yet our knowledge of the causes and consequences of this is limited. Here, using a computational approach, we estimate that 20% of the male population represented in the UK Biobank study (n = 205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes that are involved in cell-cycle regulation and cancer susceptibility, as well as somatic drivers of tumour growth and targets of cancer therapy. We demonstrate that genetic susceptibility to LOY is associated with non-haematological effects on health in both men and women, which supports the hypothesis that clonal haematopoiesis is a biomarker of genomic instability in other tissues. Single-cell RNA sequencing identifies dysregulated expression of autosomal genes in leukocytes with LOY and provides insights into why clonal expansion of these cells may occur. Collectively, these data highlight the value of studying clonal mosaicism to uncover fundamental mechanisms that underlie cancer and other ageing-related diseases. A genome-wide association study of mosaic loss of chromosome Y (LOY) in UK Biobank participants identifies 156 genetic determinants of LOY, showing that LOY is associated with cancer and non-haematological health outcomes.

STUDY QUESTION How is timing of voice break related to other male pubertal milestones as well as to BMI? SUMMARY ANSWER We provide a comprehensive temporal analysis of male pubertal milestones, including reproductive hormone dynamics, confirm voice break as a late milestone of male puberty and report a likely causal relationship between higher BMI and earlier age at voice break in men. WHAT IS KNOWN ALREADY Voice break represents a late pubertal milestone and recalled age at voice break is frequently used in epidemiological studies as a measure of puberty. In contrast, clinical studies use mainly testicular enlargement and/or genital tanner stage as the marker of pubertal onset. However, neither correlation of pubertal milestones nor reproductive hormone dynamics have been assessed in detail previously. Further, although BMI and puberty timing are known to be closely linked, cause and effect between these traits are not known. STUDY DESIGN, SIZE, DURATION The study included a population-based mixed cross-sectional and longitudinal cohort (2006–2014, COPENHAGEN Puberty Study) of 730 healthy Danish boys. Data for 55 871 male research participants from the 23andMe study were obtained, including genome-wide single nucleotide polymorphism data and age at voice break. PARTICIPANTS/MATERIALS, SETTING, METHODS We performed a detailed evaluation of pubertal milestones and reproductive hormone levels (study population 1). A Mendelian randomization (MR) approach was used to determine the likely causal link between BMI and timing of voice break (study population 2). MAIN RESULTS AND THE ROLE OF CHANCE Voice break occurred at mean age 13.6 (95% CI: 13.5–13.8) years. At voice break, mean (95% CI) testosterone levels, LH levels and bi-testicular volume were 10.9 (10.0–11.7) nmol/L, 2.4 (2.2–2.5) IU/L and 24 (23–25) mL, respectively. Voice break correlated moderately strongly with timing of male pubertal milestones, including testicular enlargement, gonadarche, pubarche, sweat odor, axillary hair growth and testosterone above limit of detection (r2 range: 0.43–0.61). Timing of all milestones was negatively associated with age-specific BMI (all P ≤ 0.001). MR analyses inferred likely causal effects of higher BMI on earlier voice break in males (−0.35 years/approximate SD, P LIMITATIONS, REASONS FOR CAUTION Participation rate of the population-based cohort was 25%. Further, boys that were followed longitudinally were examined approximately every 6 months limiting the time resolution of pubertal milestones. Using adult BMI as exposure instead of prepubertal BMI in the MR analysis and the known inaccuracies of the testosterone immunoassay at low testosterone levels may be further limitations. WIDER IMPLICATIONS OF THE FINDINGS We provide valuable normative data on the temporal relation of male pubertal milestones. Further, the likely causal relationship between BMI and puberty timing highlights the importance of preventing obesity in childhood. STUDY FUNDING/COMPETING INTEREST(S) This work was supported by Danish Agency for Science, Technology and Innovation (09-067 180); Danish Ministry of the Environment, CeHoS (MST-621-00 065); Capital Region of Denmark (R129-A3966); Ministry of Higher Education and Science (DFF-1331-00 113); Innovation Fund Denmark (InnovationsFonden, 14-2013-4); The International Center for Research and Research Training in Endocrine Disrupting Effects of Male Reproduction and Child Health. B.H., F.R.D., J.R.B.P. and K.K.O. are supported by the Medical Research Council (MC_UU_12015/2). The 23andMe study is supported by the National Human Genome Research Institute of the National Institutes of Health (R44HG006981). Members of the 23andMe Research Team are employees of 23andMe, Inc. and hold stock or stock options in 23andMe. TRIAL REGISTRATION NUMBER NCT01411527

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P < 1 × 10(−6)) associated with intake of any macronutrient in 91,114 European ancestry participants. Four loci replicated and reached genome-wide significance in a combined meta-analysis including 123,659 European descent participants, unraveling two novel loci; a common variant in RARB locus for carbohydrate intake and a rare variant in DRAM1 locus for protein intake, and corroborating earlier FGF21 and FTO findings. In additional analysis of 144,770 participants from the UK Biobank, all identified associations from the two-stage analysis were confirmed except for DRAM1. Identified loci might have implications in brain and adipose tissue biology and have clinical impact in obesity-related phenotypes. Our findings provide new insight into biological functions related to macronutrient intake.

Funder: NIHR Biomedical Research Centre Cambridge: Nutrition, Diet, and Lifestyle Research Theme; Grant(s): IS-BRC-1215-20014, Dietary intakes of polyunsaturated, monounsaturated and saturated fatty acids (FAs) have been inconsistently associated with puberty timing. We examined longitudinal associations of prepubertal dietary and plasma phospholipid FAs with several puberty timing traits in boys and girls. In the Avon Longitudinal Study of Parents and Children, prepubertal fat intakes at 3-7.5 years and plasma phospholipid FAs at 7.5 years were measured. Timings of Tanner stage 2 genital or breast development and voice breaking or menarche from repeated reports at 8-17 years, and age at peak height velocity (PHV) from repeated height measurements at 5-20 years were estimated. In linear regression models with adjustment for maternal and infant characteristics, dietary substitution of polyunsaturated FAs for saturated FAs, and higher concentrations of dihomo-γ-linolenic acid (20:3n6) and palmitoleic acid (16:1n7) were associated with earlier timing of puberty traits in girls (n = 3872) but not boys (n = 3654). In Mendelian Randomization models, higher genetically predicted circulating dihomo-γ-linolenic acid was associated with earlier menarche in girls. Based on repeated dietary intake data, objectively measured FAs and genetic causal inference, these findings suggest that dietary and endogenous metabolic pathways that increase plasma dihomo-γ-linolenic acid, an intermediate metabolite of n-6 polyunsaturated FAs, may promote earlier puberty timing in girls.

Background Insulin resistance predisposes to cardiometabolic disorders, which are commonly comorbid with schizophrenia and are key contributors to the significant excess mortality in schizophrenia. Mechanisms for the comorbidity remain unclear, but observational studies have implicated inflammation in both schizophrenia and cardiometabolic disorders separately. We aimed to examine whether there is genetic evidence that insulin resistance and 7 related cardiometabolic traits may be causally associated with schizophrenia, and whether evidence supports inflammation as a common mechanism for cardiometabolic disorders and schizophrenia. Methods and findings We used summary data from genome-wide association studies of mostly European adults from large consortia (Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) featuring up to 108,557 participants; Diabetes Genetics Replication And Meta-analysis (DIAGRAM) featuring up to 435,387 participants; Global Lipids Genetics Consortium (GLGC) featuring up to 173,082 participants; Genetic Investigation of Anthropometric Traits (GIANT) featuring up to 339,224 participants; Psychiatric Genomics Consortium (PGC) featuring up to 105,318 participants; and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium featuring up to 204,402 participants). We conducted two-sample uni- and multivariable mendelian randomization (MR) analysis to test whether (i) 10 cardiometabolic traits (fasting insulin, high-density lipoprotein and triglycerides representing an insulin resistance phenotype, and 7 related cardiometabolic traits: low-density lipoprotein, fasting plasma glucose, glycated haemoglobin, leptin, body mass index, glucose tolerance, and type 2 diabetes) could be causally associated with schizophrenia; and (ii) inflammation could be a shared mechanism for these phenotypes. We conducted a detailed set of sensitivity analyses to test the assumptions for a valid MR analysis. We did not find statistically significant evidence in support of a causal relationship between cardiometabolic traits and schizophrenia, or vice versa. However, we report that a genetically predicted inflammation-related insulin resistance phenotype (raised fasting insulin (raised fasting insulin (Wald ratio OR = 2.95, 95% C.I, 1.38–6.34, Holm-Bonferroni corrected p-value (p) = 0.035) and lower high-density lipoprotein (Wald ratio OR = 0.55, 95% C.I., 0.36–0.84; p = 0.035)) was associated with schizophrenia. Evidence for these associations attenuated to the null in multivariable MR analyses after adjusting for C-reactive protein, an archetypal inflammatory marker: (fasting insulin Wald ratio OR = 1.02, 95% C.I, 0.37–2.78, p = 0.975), high-density lipoprotein (Wald ratio OR = 1.00, 95% C.I., 0.85–1.16; p = 0.849), suggesting that the associations could be fully explained by inflammation. One potential limitation of the study is that the full range of gene products from the genetic variants we used as proxies for the exposures is unknown, and so we are unable to comment on potential biological mechanisms of association other than inflammation, which may also be relevant. Conclusions Our findings support a role for inflammation as a common cause for insulin resistance and schizophrenia, which may at least partly explain why the traits commonly co-occur in clinical practice. Inflammation and immune pathways may represent novel therapeutic targets for the prevention or treatment of schizophrenia and comorbid insulin resistance. Future work is needed to understand how inflammation may contribute to the risk of schizophrenia and insulin resistance., In a Mendelian randomization study, Benjamin Perry and colleagues investigate the genetic evidence supporting relationships between inflammation, insulin resistance, and schizophrenia., Author summary Why was this study done? Cardiometabolic disorders such as diabetes are up to 30% more common in people with schizophrenia than in the general population, and are among the predominant causes of a 10- to 15-year shortened life expectancy in people with schizophrenia. Insulin resistance, a precursor to diabetes, is sometimes detectable in young adults suffering their first episode of psychosis, which suggests that chronic lifestyle and clinical factors, such as smoking, physical inactivity, and medication side effects may not fully explain the comorbidity. Inflammation has been consistently associated with schizophrenia and cardiometabolic disorders, and so could be a common mechanism for schizophrenia and cardiometabolic disorders. This could help to at least in part explain why people who have schizophrenia also have higher rates of cardiometabolic disorders, over and above the commonly attributed lifestyle/clinical factors. What did the researchers do and find? To examine whether insulin resistance and 7 related cardiometabolic traits causally influence schizophrenia risk or vice versa, we conducted bidirectional, two-sample, uni- and multivariable mendelian randomizsation (MR) analyses. The MR approach uses genetic variants as proxies for modifiable exposures to untangle the problems of reverse causation and unmeasured confounding. To test a hypothesis that inflammation may be a common mechanism for schizophrenia and cardiometabolic disorders, we also examined a subset of genetic variants which were associated with inflammation as well as the cardiometabolic trait. We also used multivariable MR (MVMR) as a sensitivity analysis to adjust for C-reactive protein (CRP), an archetypal inflammatory marker, as a general downstream marker of systemic inflammation. After correction for multiple testing, overall, there was no significant evidence in support of a causal relationship between cardiometabolic traits and schizophrenia, or vice versa. However, we found evidence that supports a causal relationship of an inflammation-related insulin resistance phenotype with schizophrenia. Evidence for the association of an inflammation-related insulin resistance phenotype with schizophrenia attenuated fully in MVMR analysis after adjusting for CRP, suggesting that these associations may be underpinned by inflammation. What do these findings mean? These results suggest that cardiometabolic traits are unlikely to have a causal role in the pathogenesis of schizophrenia or vice versa. However, our results suggest that inflammation is related to the risk of both schizophrenia and insulin resistance, which may at least partly explain why they commonly occur in clinical practice. Treating or preventing inflammation may be a putative therapeutic option for prevention and/or treatment of both schizophrenia and comorbid insulin resistance. In the future, more research is needed to understand the biological mechanisms underpinning how inflammation may increase the risk of schizophrenia and insulin resistance.

Reproductive longevity is critical for fertility and impacts healthy ageing in women, yet insights into the underlying biological mechanisms and treatments to preserve it are limited. Here, we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in ∼200,000 women of European ancestry. These common alleles influence clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenicFMR1premutations. Identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increase fertility and extend reproductive life in mice. Causal inference analyses using the identified genetic variants indicates that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases risks of hormone-sensitive cancers. These findings provide insight into the mechanisms governing ovarian ageing, when they act across the life-course, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E–06), PCDH7 (P = 2.0E–06), and IPO13 (P = 2.5E–06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg = 0.46 between self- and teacher-assessment to rg = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range $$\left| {r_g} \right|$$ r g : 0.19–1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg = ~−0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range $$\left| {r_g} \right|$$ r g : 0.46–0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.

AimsSingle-frequency segmental Bioelectrical Impedance Analysis (BIA) is commonly used to estimate body composition. To enhance the value of information derived from BIA, especially for use in large-scale epidemiological studies, we developed and validated equations to predict total and regional (arms, legs, trunk, android, gynoid, visceral) body composition parameters (lean mass and fat mass) from anthropometry and single-frequency (50 kHz) segmental BIA variables, using Dual Energy X-ray Absorptiometry (DEXA) as the criterion method.MethodsThe 11,559 adults (age 30 to 65) from the UK population-based Fenland Study with data on DEXA, BIA and anthropometry were randomly assigned to a Derivation sample (4,827 men; 5,732 women) or a Validation sample (500 men; 500 women). Prediction equations based on anthropometry and BIA variables were derived using forward stepwise multiple linear regression in the Fenland Derivation sample. These were validated in the Fenland Validation sample and also in the UK Biobank Imaging Study (2,392 men; 2,606 women) using Pearson correlations and Bland–Altman models.Results and ConclusionsBland Altman analyses revealed no significant mean bias for any predicted DEXA parameter (all P>0.05) for the fenland population. Bias expressed as % of the mean was between -0.6% and 0.5% for all parameters in both men and women, except for visceral FM and subcutaneous abdominal FM (range -3.6 to 1.1%). However, in UK Biobank most predicted parameters showed significant bias: % mean bias was 10% for leg and visceral fat mass in both sexes. In conclusion, new equations based on anthropometry and BIA variables predicted DEXA parameters with sufficient accuracy to assess relative differences between individuals, and were sufficiently accurate to predict absolute values for total body but not regional fat and lean mass.

Background Prior research suggested a differential association of 25-hydroxyvitamin D (25(OH)D) metabolites with type 2 diabetes (T2D), with total 25(OH)D and 25(OH)D3 inversely associated with T2D, but the epimeric form (C3-epi-25(OH)D3) positively associated with T2D. Whether or not these observational associations are causal remains uncertain. We aimed to examine the potential causality of these associations using Mendelian randomisation (MR) analysis. Methods and findings We performed a meta-analysis of genome-wide association studies for total 25(OH)D (N = 120,618), 25(OH)D3 (N = 40,562), and C3-epi-25(OH)D3 (N = 40,562) in participants of European descent (European Prospective Investigation into Cancer and Nutrition [EPIC]–InterAct study, EPIC-Norfolk study, EPIC-CVD study, Ely study, and the SUNLIGHT consortium). We identified genetic variants for MR analysis to investigate the causal association of the 25(OH)D metabolites with T2D (including 80,983 T2D cases and 842,909 non-cases). We also estimated the observational association of 25(OH)D metabolites with T2D by performing random effects meta-analysis of results from previous studies and results from the EPIC-InterAct study. We identified 10 genetic loci associated with total 25(OH)D, 7 loci associated with 25(OH)D3 and 3 loci associated with C3-epi-25(OH)D3. Based on the meta-analysis of observational studies, each 1–standard deviation (SD) higher level of 25(OH)D was associated with a 20% lower risk of T2D (relative risk [RR]: 0.80; 95% CI 0.77, 0.84; p < 0.001), but a genetically predicted 1-SD increase in 25(OH)D was not significantly associated with T2D (odds ratio [OR]: 0.96; 95% CI 0.89, 1.03; p = 0.23); this result was consistent across sensitivity analyses. In EPIC-InterAct, 25(OH)D3 (per 1-SD) was associated with a lower risk of T2D (RR: 0.81; 95% CI 0.77, 0.86; p < 0.001), while C3-epi-25(OH)D3 (above versus below lower limit of quantification) was positively associated with T2D (RR: 1.12; 95% CI 1.03, 1.22; p = 0.006), but neither 25(OH)D3 (OR: 0.97; 95% CI 0.93, 1.01; p = 0.14) nor C3-epi-25(OH)D3 (OR: 0.98; 95% CI 0.93, 1.04; p = 0.53) was causally associated with T2D risk in the MR analysis. Main limitations include the lack of a non-linear MR analysis and of the generalisability of the current findings from European populations to other populations of different ethnicities. Conclusions Our study found discordant associations of biochemically measured and genetically predicted differences in blood 25(OH)D with T2D risk. The findings based on MR analysis in a large sample of European ancestry do not support a causal association of total 25(OH)D or 25(OH)D metabolites with T2D and argue against the use of vitamin D supplementation for the prevention of T2D., Using both observational and genetic analyses, Ju-Sheng Zheng and colleagues investigate the relationship between vitamin D metabolites and type 2 diabetes among European individuals., Author summary Why was this study done? There is ongoing uncertainty on whether the body’s vitamin D status indicated by blood 25-hydroxyvitamin D (25(OH)D) is relevant to the prevention of type 2 diabetes. There are conflicting findings from observational studies and a limited number of randomised controlled trials. Prior research did not distinguish between different metabolites of total 25(OH)D, including 25(OH)D3 and C3-epi-25(OH)D3, an isomer of 25(OH)D3. It is not clear whether the associations of 25(OH)D metabolites with type 2 diabetes are causal, with conflicting findings from prior Mendelian randomisation studies of total 25(OH)D and no previous Mendelian randomisation studies appraising 25(OH)D metabolites. What did the researchers do and find? The current research compared observational estimates of the association between 25(OH)D metabolites and incident type 2 diabetes with Mendelian randomisation estimates based on genetic instruments. Using multiple data sources, we performed genome-wide association studies among 120,618 individuals for total 25(OH)D, and among 40,562 individuals for the other vitamin D metabolites. Among participants of European descent, 10 genetic loci were identified for total 25(OH)D, 7 loci for 25(OH)D3 and 3 loci for C3-epi-25(OH)D3. In meta-analysis of observational studies, we found that each 1–standard deviation higher level of total 25(OH)D was associated with 20% lower risk of type 2 diabetes. The result was similar for 25(OH)D3, but for C3-epi-25(OH)D3, a positive association with type 2 diabetes was found. With up to 80,983 type 2 diabetes cases and 842,909 controls, we assessed the association of genetically predicted differences in total 25(OH)D and its metabolites with type 2 diabetes. Neither genetically predicted higher total 25(OH)D level nor genetically predicted higher levels of 25(OH)D metabolites were significantly associated with type 2 diabetes. What do these findings mean? There were conflicting findings for a link with type 2 diabetes for the observational analysis of biochemically measured 25(OH)D metabolites versus the genetically predicted levels of these metabolites. The null findings based on Mendelian randomisation analysis indicate that blood levels of 25(OH)D or its metabolites are not likely to be causal factors for the development of type 2 diabetes. The current findings together with other evidence from randomised controlled trials do not support the use of vitamin D supplementation for the prevention of type 2 diabetes.

DNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >270,000 independent mQTLs. Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. Here we describe results of DNA methylation-quantitative trait loci (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTL of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We reveal that the genetic architecture of DNAm levels is highly polygenic and DNAm exhibits signatures of negative and positive natural selection. Using shared genetic control between distal DNAm sites we construct networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic factors are associated with both blood DNAm levels and complex diseases but in most cases these associations do not reflect causal relationships from DNAm to trait or vice versa indicating a more complex genotype-phenotype map than has previously been hypothesised.

Circulating testosterone and SHBG levels are associated with type 2 diabetes (T2D). These associations differ between sexes and by total and bioavailable testosterone. For example, in UK Biobank a 1-SD raised bioavailable testosterone is associated with lower risk of T2D in men (OR=0.90 [0.88,0.92]) but higher risk in women (OR=1.24 [1.20,1.29]). Genetic studies provide more robust tests of causality and have indicated that higher circulating SHBG is protective of T2D (OR=0.92 [0.88,0.96], Perry et al 2010), but were limited to few genetic variants. In this study we aimed to: i) expand the set of genetic variants associated with circulating testosterone; ii) separate variants into clusters representing SHBG or direct testosterone effects; and iii) perform Mendelian Randomisation studies to better understand the potential causal effects of SHBG and testosterone on T2D and related traits. We used genome-wide analyses of sex hormones from 425,097 UK Biobank participants. We identified 2,571 genome-wide significant (P Disclosure K.S. Ruth: None. F. Day: None. J. Tyrrell: None. A. Murray: None. K. Ong: None. T. Frayling: Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Sanofi, Servier. Research Support; Self; GlaxoSmithKline plc. J. Perry: None. Funding European Research Council (SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC); UK Wellcome Trust/Royal Society (104150/Z/14/Z); UK Wellcome Trust/Global Challenge Research Fund (SBF004\1079); Medical Research Council UK (MC_UU_12015/1, MC_UU_12015/2)

Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and also identify alleles under present-day selection. Using data in 785,604 individuals of European ancestry, we identify 43 genomic loci associated with either number of children ever born (NEB) or childlessness. These loci span diverse aspects of reproductive biology across the life course, including puberty timing, age at first birth, sex hormone regulation and age at menopause. Missense alleles in ARHGAP27 were associated with increased NEB but reduced reproductive lifespan, suggesting a trade-off between reproductive ageing and intensity. As NEB is one component of evolutionary fitness, our identified associations indicate loci under present-day natural selection. Accordingly, we find that NEB-increasing alleles have increased in frequency over the past two generations. Furthermore, integration with data from ancient selection scans identifies a unique example of an allele—FADS1/2 gene locus—that has been under selection for thousands of years and remains under selection today. Collectively, our findings demonstrate that diverse biological mechanisms contribute to reproductive success, implicating both neuro-endocrine and behavioural influences.

Age at first sexual intercourse (AFS) and age at first birth (AFB) have implications for health and evolutionary fitness. In the largest genome-wide association study to date (AFS, N=387,338; AFB, N=542,901), we identify 370 independent signals, 11 sex-specific, with a 5-6% polygenic score (PGS) prediction. Heritability of AFB shifted from 9% [CI=4-14] for women born in 1940 to 22% [CI=19-25] in 1965. Signals are driven by the genetics of reproductive biology and externalising behaviour, with key genes related to follicle stimulating hormone (FSHB), implantation (ESR1), infertility, and spermatid differentiation. Polycystic Ovarian Syndrome leads to later AFB, linking with infertility. Late AFB is protective against later-life disease and associated with parental longevity. Higher childhood socioeconomic circumstances and those in the highest PGS decile (90%+) experience markedly later reproductive onset. Results are relevant for improving teenage and late-life health, for understanding longevity, and guiding experimentation into mechanisms of infertility.

Background Emerging studies have investigated the association between puberty timing, particularly age at menarche (AAM), and type 2 diabetes. However, whether this association is independent of adiposity is unclear. We aimed to systematically review published evidence on the association between puberty timing and type 2 diabetes (T2D) or impaired glucose tolerance (IGT), with and without adjustment for adiposity, and to estimate the potential contribution of puberty timing to the burden of T2D in the United Kingdom (UK). Methods and findings We searched PubMed, Medline, and Embase databases for publications until February 2019 on the timing of any secondary sexual characteristic in boys or girls in relation to T2D/IGT. Inverse-variance-weighted random-effects meta-analysis was used to pool reported estimates, and meta-regression was used to explore sources of heterogeneity. Twenty-eight observational studies were identified. All assessed AAM in women (combined N = 1,228,306); only 1 study additionally included men. In models without adjustment for adult adiposity, T2D/IGT risk was lower per year later AAM (relative risk [RR] = 0.91, 95% CI 0.89–0.93, p < 0.001, 11 estimates, n = 833,529, I2 = 85.4%) and higher for early versus later menarche (RR = 1.39, 95% CI 1.25–1.55, p < 0.001, 23 estimates, n = 1,185,444, I2 = 87.8%). Associations were weaker but still evident in models adjusted for adiposity (AAM: RR = 0.97 per year, 95% CI 0.95–0.98, p < 0.001, 12 estimates, n = 852,268, I2 = 51.8%; early menarche: RR = 1.19, 95% CI 1.11–1.28, p < 0.001, 21 estimates, n = 890,583, I2 = 68.1%). Associations were stronger among white than Asian women, and in populations with earlier average AAM. The estimated population attributable risk of T2D in white UK women due to early menarche unadjusted and adjusted for adiposity was 12.6% (95% CI 11.0–14.3) and 5.1% (95% CI 3.6–6.7), respectively. Findings in this study are limited by residual and unmeasured confounding, and self-reported AAM. Conclusions Earlier AAM is consistently associated with higher T2D/IGT risk, independent of adiposity. More importantly, this research has identified that a substantial proportion of T2D in women is related to early menarche, which would be expected to increase in light of global secular trends towards earlier puberty timing. These findings highlight the need to identify the underlying mechanisms linking early menarche to T2D/IGT risk., Tuck Seng Cheng and colleagues examine the literature on the association between puberty timing and Type 2 diabetes., Author summary Why was this study done? Secular trends towards earlier puberty timing have led to interest in its long-term disease consequences, particularly the association between early age at menarche in women and the development of type 2 diabetes. An earlier pooled analysis of the association between puberty timing and risk of type 2 diabetes was limited to findings adjusted for adulthood adiposity and included studies mainly among Western women. The present study aimed to evaluate whether puberty timing is associated with type 2 diabetes/impaired glucose tolerance, independent of adiposity. What did the researchers do and find? This systematic review identified 28 observational studies that analysed age at menarche among women and type 2 diabetes/impaired glucose tolerance; 1 study additionally included age at voice breaking in men. Meta-analysis showed that risk for type 2 diabetes and impaired glucose tolerance is higher among women with early than later menarche, independent of adiposity. The risk for type 2 diabetes and impaired glucose tolerance among women with early menarche is even higher in white than Asian women and in populations with younger average age at menarche. What do these findings mean? Girls who experience earlier menarche than their peers within and between populations have a higher risk for type 2 diabetes in adulthood. Preventive strategies that avoid early puberty timing might reduce future risk of type 2 diabetes.

Both extrinsic and intrinsic factors predispose older people to fall. We performed a genome-wide association analysis to investigate how much of an individual’s fall susceptibility can be attributed to genetics in 89,076 cases and 362,103 controls from the UK Biobank Study. The analysis revealed a small, but significant SNP-based heritability (2.7%) and identified three novel fall-associated loci (Pcombined ≤ 5 × 10−8). Polygenic risk scores in two independent settings showed patterns of polygenic inheritance. Risk of falling had positive genetic correlations with fractures, identifying for the first time a pathway independent of bone mineral density. There were also positive genetic correlations with insomnia, neuroticism, depressive symptoms, and different medications. Negative genetic correlations were identified with muscle strength, intelligence and subjective well-being. Brain, and in particular cerebellum tissue, showed the highest gene expression enrichment for fall-associated variants. Overall, despite the highly heterogenic nature underlying fall risk, a proportion of the susceptibility can be attributed to genetics., Katerina Trajanoska et al. report a genome-wide association study of self-reported falls in UK Biobank participants. They identify three novel fall-associated loci and find that risk of falling shows patterns of polygenic inheritance and a SNP-based heritability of 2.7%.

BackgroundPolycystic ovary syndrome (PCOS) is the most common endocrine disorder affecting women of reproductive age. Previous studies have identified genetic variants associated with PCOS identified by different diagnostic criteria. The Rotterdam Criteria is the broadest and able to identify the most PCOS cases.ObjectivesTo identify novel associated genetic variants, we extracted PCOS cases and controls from the electronic health records (EHR) based on the Rotterdam Criteria and performed a genome-wide association study (GWAS).Study DesignWe developed a PCOS phenotyping algorithm based on the Rotterdam criteria and applied it to three EHR-linked biobanks to identify cases and controls for genetic study. In discovery phase, we performed individual GWAS using the Geisinger’s MyCode and the eMERGE cohorts, which were then meta-analyzed. We attempted validation of the significantly association loci (P−6) in the BioVU cohort. All association analyses used logistic regression, assuming an additive genetic model, and adjusted for principal components to control for population stratification. An inverse-variance fixed effect model was adopted for meta-analyses. Additionally, we examined the top variants to evaluate their associations with each criterion in the phenotyping algorithm. We used STRING to identify protein-protein interaction network.ResultsWe identified 2,995 PCOS cases and 53,599 controls in total (2,742cases and 51,438 controls from the discovery phase; 253 cases and 2,161 controls in the validation phase). GWAS identified one novel genome-wide significant variant rs17186366 (OR=1.37 [1.23,1.54], P=2.8×10−8) located nearSOD2. Additionally, two loci with suggestive association were also identified: rs113168128 (OR=1.72 [1.42,2.10], P=5.2 x10−8), an intronic variant ofERBB4that is independent from the previously published variants, and rs144248326 (OR=2.13 [1.52,2.86], P=8.45×10−7), a novel intronic variant inWWTR1. In the further association tests of the top 3 SNPs with each criterion in the PCOS algorithm, we found that rs17186366 was associated with polycystic and hyperandrogenism, while rs11316812 and rs144248326 were mainly associated with oligomenorrhea or infertility. Besides ERBB4, we also validated the association withDENND1A1.ConclusionThrough a discovery-validation GWAS on PCOS cases and controls identified from EHR using an algorithm based on Rotterdam criteria, we identified and validated a novel association with variants withinERBB4. We also identified novel associations nearbySOD2andWWTR1. These results suggest the eGFR and Hippo pathways in the disease etiology. With previously identified PCOS-associated lociYAP1, theERBB4-YAP1-WWTR1network implicates the epidermal growth factor receptor and the Hippo pathway in the multifactorial etiology of PCOS.