Genetic insights into biological mechanisms governing human ovarian ageing.

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.

Genetically proxied therapeutic prolyl-hydroxylase inhibition and cardiovascular risk.

Prolyl hydroxylase (PHD) inhibitors are in clinical development for anaemia in chronic kidney disease. Epidemiological studies have reported conflicting results regarding safety of long-term therapeutic haemoglobin (Hgb) rises through PHD inhibition on risk of cardiovascular disease. Genetic variation in genes encoding PHDs can be used as partial proxies to investigate the potential effects of long-term Hgb rises. We used Mendelian randomization to investigate the effect of long-term Hgb level rises through genetically proxied PHD inhibition on coronary artery disease (CAD: 60 801 cases; 123 504 controls), myocardial infarction (MI: 42 561 cases; 123 504 controls) or stroke (40 585 cases; 406 111 controls). To further characterize long-term effects of Hgb level rises, we performed a phenome-wide association study (PheWAS) in up to 451 099 UK Biobank individuals. Genetically proxied therapeutic PHD inhibition, equivalent to a 1.00 g/dl increase in Hgb levels, was not associated (at P < 0.05) with increased odds of CAD; odd ratio (OR) [95% confidence intervals (CI)] = 1.06 (0.84, 1.35), MI [OR (95% CI) = 1.02 (0.79, 1.33)] or stroke [OR (95% CI) = 0.91 (0.66, 1.24)]. PheWAS revealed associations with blood related phenotypes consistent with EGLN's role, relevant kidney- and liver-related biomarkers like estimated glomerular filtration rate and microalbuminuria, and non-alcoholic fatty liver disease (Bonferroni-adjusted P < 5.42E-05) but these were not clinically meaningful. These findings suggest that long-term alterations in Hgb through PHD inhibition are unlikely to substantially increase cardiovascular disease risk; using large disease genome-wide association study data, we could exclude ORs of 1.35 for cardiovascular risk with a 1.00 g/dl increase in Hgb.

Do sex hormones confound or mediate the effect of chronotype on breast and prostate cancer? A Mendelian randomization study.

Morning-preference chronotype has been found to be protective against breast and prostate cancer. Sex hormones have been implicated in relation to chronotype and the development of both cancers. This study aimed to assess whether sex hormones confound or mediate the effect of chronotype on breast and prostate cancer using a Mendelian Randomization (MR) framework. Genetic variants associated with chronotype and sex hormones (total testosterone, bioavailable testosterone, sex hormone binding globulin, and oestradiol) (p<5×10-8) were obtained from published genome-wide association studies (n≤244,207 females and n≤205,527 males). These variants were used to investigate causal relationships with breast (nCases/nControls = 133,384/113,789) and prostate (nCases/nControls = 79,148/61,106) cancer using univariable, bidirectional and multivariable MR. In females, we found evidence for: I) Reduced risk of breast cancer per category increase in morning-preference (OR = 0.93, 95% CI:0. 88, 1.00); II) Increased risk of breast cancer per SD increase in bioavailable testosterone (OR = 1.10, 95% CI: 1.01, 1.19) and total testosterone (OR = 1.15, 95% CI:1.07, 1.23); III) Bidirectional effects between morning-preference and both bioavailable and total testosterone (e.g. mean SD difference in bioavailable testosterone = -0.08, 95% CI:-0.12, -0.05 per category increase in morning-preference vs difference in morning-preference category = -0.04, 95% CI: -0.08, 0.00 per SD increase in bioavailable testosterone). In males, we found evidence for: I) Reduced risk of prostate cancer per category increase in morning-preference (OR = 0.90, 95% CI: 0.83, 0.97) and II) Increased risk of prostate cancer per SD increase in bioavailable testosterone (OR = 1.22, 95% CI: 1.08, 1.37). No bidirectional effects were found between morning-preference and testosterone in males. While testosterone levels were causally implicated with both chronotype and cancer, there was inconsistent evidence for testosterone as a mediator of the relationship. The protective effect of morning-preference on both breast and prostate cancer is clinically interesting, although it may be difficult to effectively modify chronotype. Further studies are needed to investigate other potentially modifiable intermediates.

Large Copy-Number Variants in UK Biobank Caused by Clonal Hematopoiesis May Confound Penetrance Estimates.

Large copy-number variants (CNVs) are strongly associated with both developmental delay and cancer, but the type of disease depends strongly on when and where the mutation occurred, i.e., germline versus somatic. We used microarray data from UK Biobank to investigate the prevalence and penetrance of large autosomal CNVs and chromosomal aneuploidies using a standard CNV detection algorithm not designed for detecting mosaic variants. We found 160 individuals that carry >10 Mb copy number changes, including 56 with whole chromosome aneuploidies. Nineteen (12%) individuals had a diagnosis of Down syndrome or other developmental disorder, while 84 (52.5%) individuals had a diagnosis of hematological malignancies or chronic myeloproliferative disorders. Notably, there was no evidence of mosaicism in the blood for many of these large CNVs, so they could easily be mistaken for germline alleles even when caused by somatic mutations. We therefore suggest that somatic mutations associated with blood cancers may result in false estimates of rare variant penetrance from population biobanks.

Applying a genetic risk score for prostate cancer to men with lower urinary tract symptoms in primary care to predict prostate cancer diagnosis: a cohort study in the UK Biobank.

BACKGROUND: Prostate cancer is highly heritable, with >250 common variants associated in genome-wide association studies. It commonly presents with non-specific lower urinary tract symptoms that are frequently associated with benign conditions. METHODS: Cohort study using UK Biobank data linked to primary care records. Participants were men with a record showing a general practice consultation for a lower urinary tract symptom. The outcome measure was prostate cancer diagnosis within 2 years of consultation. The predictor was a genetic risk score of 269 genetic variants for prostate cancer. RESULTS: A genetic risk score (GRS) is associated with prostate cancer in symptomatic men (OR per SD increase = 2.12 [1.86-2.41] P = 3.5e-30). An integrated risk model including age and GRS applied to symptomatic men predicted prostate cancer (AUC 0.768 [0.739-0.796]). Prostate cancer incidence was 8.1% (6.7-9.7) in the highest risk quintile. In the lowest quintile, prostate cancer incidence was <1%. CONCLUSIONS: This study is the first to apply GRS in primary care to improve the triage of symptomatic patients. Men with the lowest genetic risk of developing prostate cancer could safely avoid invasive investigation, whilst those identified with the greatest risk could be fast-tracked for further investigation. These results show that a GRS has potential application to improve the diagnostic pathway of symptomatic patients in primary care.

GWAS Identifies Risk Locus for Erectile Dysfunction and Implicates Hypothalamic Neurobiology and Diabetes in Etiology.

Erectile dysfunction (ED) is a common condition affecting more than 20% of men over 60 years, yet little is known about its genetic architecture. We performed a genome-wide association study of ED in 6,175 case subjects among 223,805 European men and identified one locus at 6q16.3 (lead variant rs57989773, OR 1.20 per C-allele; p = 5.71 × 10-14), located between MCHR2 and SIM1. In silico analysis suggests SIM1 to confer ED risk through hypothalamic dysregulation. Mendelian randomization provides evidence that genetic risk of type 2 diabetes mellitus is a cause of ED (OR 1.11 per 1-log unit higher risk of type 2 diabetes). These findings provide insights into the biological underpinnings and the causes of ED and may help prioritize the development of future therapies for this common disorder.

Identifying molecular mediators of the relationship between body mass index and endometrial cancer risk: a Mendelian randomization analysis.

BACKGROUND: Endometrial cancer is the most common gynaecological cancer in high-income countries. Elevated body mass index (BMI) is an established modifiable risk factor for this condition and is estimated to confer a larger effect on endometrial cancer risk than any other cancer site. However, the molecular mechanisms underpinning this association remain unclear. We used Mendelian randomization (MR) to evaluate the causal role of 14 molecular risk factors (hormonal, metabolic and inflammatory markers) in endometrial cancer risk. We then evaluated and quantified the potential mediating role of these molecular traits in the relationship between BMI and endometrial cancer using multivariable MR. METHODS: Genetic instruments to proxy 14 molecular risk factors and BMI were constructed by identifying single-nucleotide polymorphisms (SNPs) reliably associated (P < 5.0 × 10-8) with each respective risk factor in previous genome-wide association studies (GWAS). Summary statistics for the association of these SNPs with overall and subtype-specific endometrial cancer risk (12,906 cases and 108,979 controls) were obtained from a GWAS meta-analysis of the Endometrial Cancer Association Consortium (ECAC), Epidemiology of Endometrial Cancer Consortium (E2C2) and UK Biobank. SNPs were combined into multi-allelic models and odds ratios (ORs) and 95% confidence intervals (95% CIs) were generated using inverse-variance weighted random-effects models. The mediating roles of the molecular risk factors in the relationship between BMI and endometrial cancer were then estimated using multivariable MR. RESULTS: In MR analyses, there was strong evidence that BMI (OR per standard deviation (SD) increase 1.88, 95% CI 1.69 to 2.09, P = 3.87 × 10-31), total testosterone (OR per inverse-normal transformed nmol/L increase 1.64, 95% CI 1.43 to 1.88, P = 1.71 × 10-12), bioavailable testosterone (OR per natural log transformed nmol/L increase: 1.46, 95% CI 1.29 to 1.65, P = 3.48 × 10-9), fasting insulin (OR per natural log transformed pmol/L increase: 3.93, 95% CI 2.29 to 6.74, P = 7.18 × 10-7) and sex hormone-binding globulin (SHBG, OR per inverse-normal transformed nmol/L increase 0.71, 95% CI 0.59 to 0.85, P = 2.07 × 10-4) had a causal effect on endometrial cancer risk. Additionally, there was suggestive evidence that total serum cholesterol (OR per mg/dL increase 0.90, 95% CI 0.81 to 1.00, P = 4.01 × 10-2) had an effect on endometrial cancer risk. In mediation analysis, we found evidence for a mediating role of fasting insulin (19% total effect mediated, 95% CI 5 to 34%, P = 9.17 × 10-3), bioavailable testosterone (15% mediated, 95% CI 10 to 20%, P = 1.43 × 10-8) and SHBG (7% mediated, 95% CI 1 to 12%, P = 1.81 × 10-2) in the relationship between BMI and endometrial cancer risk. CONCLUSIONS: Our comprehensive MR analysis provides insight into potential causal mechanisms linking BMI with endometrial cancer risk and suggests targeting of insulinemic and hormonal traits as a potential strategy for the prevention of endometrial cancer.

Detection and characterization of male sex chromosome abnormalities in the UK Biobank study.

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 × 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 < 7 × 10-6). 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.

Genome-wide association study meta-analysis identifies three novel loci for circulating anti-Müllerian hormone levels in women.

STUDY QUESTION: Can additional genetic variants for circulating anti-Müllerian hormone (AMH) levels be identified through a genome-wide association study (GWAS) meta-analysis including a large sample of premenopausal women? SUMMARY ANSWER: We identified four loci associated with AMH levels at P < 5 × 10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 and CDCA7. WHAT IS KNOWN ALREADY: AMH is expressed by antral stage ovarian follicles in women, and variation in age-specific circulating AMH levels has been associated with disease outcomes. However, the physiological mechanisms underlying these AMH-disease associations are largely unknown. STUDY DESIGN, SIZE, DURATION: We performed a GWAS meta-analysis in which we combined summary statistics of a previous AMH GWAS with GWAS data from 3705 additional women from three different cohorts. PARTICIPANTS/MATERIALS, SETTING, METHODS: In total, we included data from 7049 premenopausal female participants of European ancestry. The median age of study participants ranged from 15.3 to 48 years across cohorts. Circulating AMH levels were measured in either serum or plasma samples using different ELISA assays. Study-specific analyses were adjusted for age at blood collection and population stratification, and summary statistics were meta-analysed using a standard error-weighted approach. Subsequently, we functionally annotated GWAS variants that reached genome-wide significance (P < 5 × 10-8). We also performed a gene-based GWAS, pathway analysis and linkage disequilibrium score regression and Mendelian randomization (MR) analyses. MAIN RESULTS AND THE ROLE OF CHANCE: We identified four loci associated with AMH levels at P < 5 × 10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 and CDCA7. The strongest signal was a missense variant in the AMH gene (rs10417628). Most prioritized genes at the other three identified loci were involved in cell cycle regulation. Genetic correlation analyses indicated a strong positive correlation among single nucleotide polymorphisms for AMH levels and for age at menopause (rg = 0.82, FDR = 0.003). Exploratory two-sample MR analyses did not support causal effects of AMH on breast cancer or polycystic ovary syndrome risk, but should be interpreted with caution as they may be underpowered and the validity of genetic instruments could not be extensively explored. LARGE SCALE DATA: The full AMH GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/). LIMITATIONS, REASONS FOR CAUTION: Whilst this study doubled the sample size of the most recent GWAS, the statistical power is still relatively low. As a result, we may still lack power to identify more genetic variants for AMH and to determine causal effects of AMH on, for example, breast cancer. Also, follow-up studies are needed to investigate whether the signal for the AMH gene is caused by reduced AMH detection by certain assays instead of actual lower circulating AMH levels. WIDER IMPLICATIONS OF THE FINDINGS: Genes mapped to the MCM8, TEX41 and CDCA7 loci are involved in the cell cycle and processes such as DNA replication and apoptosis. The mechanism underlying their associations with AMH may affect the size of the ovarian follicle pool. Altogether, our results provide more insight into the biology of AMH and, accordingly, the biological processes involved in ovarian ageing. STUDY FUNDING/COMPETING INTEREST(S): Nurses' Health Study and Nurses' Health Study II were supported by research grants from the National Institutes of Health (CA172726, CA186107, CA50385, CA87969, CA49449, CA67262, CA178949). The UK Medical Research Council and Wellcome (217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the listed authors, who will serve as guarantors for the contents of this article. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf). Funding for the collection of genotype and phenotype data used here was provided by the British Heart Foundation (SP/07/008/24066), Wellcome (WT092830M and WT08806) and UK Medical Research Council (G1001357). M.C.B., A.L.G.S. and D.A.L. work in a unit that is funded by the University of Bristol and UK Medical Research Council (MC_UU_00011/6). M.C.B.'s contribution to this work was funded by a UK Medical Research Council Skills Development Fellowship (MR/P014054/1) and D.A.L. is a National Institute of Health Research Senior Investigator (NF-0616-10102). A.L.G.S. was supported by the study of Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases (H2020-SC1-2019-Single-Stage-RTD, project ID 874739). The Doetinchem Cohort Study was financially supported by the Ministry of Health, Welfare and Sports of the Netherlands. The funder had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Ansh Labs performed the AMH measurements for the Doetinchem Cohort Study free of charge. Ansh Labs was not involved in the data analysis, interpretation or reporting, nor was it financially involved in any aspect of the study. R.M.G.V. was funded by the Honours Track of MSc Epidemiology, University Medical Center Utrecht with a grant from the Netherlands Organization for Scientific Research (NWO) (022.005.021). The Study of Women's Health Across the Nation (SWAN) has grant support from the National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR) and the NIH Office of Research on Women's Health (ORWH) (U01NR004061; U01AG012505, U01AG012535, U01AG012531, U01AG012539, U01AG012546, U01AG012553, U01AG012554, U01AG012495). The SWAN Genomic Analyses and SWAN Legacy have grant support from the NIA (U01AG017719). The Generations Study was funded by Breast Cancer Now and the Institute of Cancer Research (ICR). The ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent official views of the funders. The Sister Study was funded by the Intramural Research Program of the National Institutes of Health (NIH), National Institute of Environmental Health Sciences (Z01-ES044005 to D.P.S.); the AMH assays were supported by the Avon Foundation (02-2012-065 to H.B. Nichols and D.P.S.). The breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the 'Ministère de l'Économie, de la Science et de l'Innovation du Québec' through Genome Québec and grant PSR-SIIRI-701, The National Institutes of Health (U19 CA148065, X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, C1287/A10710) and The European Union (HEALTH-F2-2009-223175 and H2020 633784 and 634935). All studies and funders are listed in Michailidou et al. (Nature, 2017). F.J.M.B. has received fees and grant support from Merck Serono and Ferring BV. D.A.L. has received financial support from several national and international government and charitable funders as well as from Medtronic Ltd and Roche Diagnostics for research that is unrelated to this study. N.S. is scientific consultant for Ansh Laboratories. The other authors declare no competing interests.

Genome-wide associations for birth weight and correlations with adult disease.

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10-8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = -0.22, P = 5.5 × 10-13), T2D (Rg = -0.27, P = 1.1 × 10-6) and coronary artery disease (Rg = -0.30, P = 6.5 × 10-9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10-4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.

Genome-wide association study of anti-Müllerian hormone levels in pre-menopausal women of late reproductive age and relationship with genetic determinants of reproductive lifespan.

Anti-Müllerian hormone (AMH) is required for sexual differentiation in the fetus, and in adult females AMH is produced by growing ovarian follicles. Consequently, AMH levels are correlated with ovarian reserve, declining towards menopause when the oocyte pool is exhausted. A previous genome-wide association study identified three genetic variants in and around the AMH gene that explained 25% of variation in AMH levels in adolescent males but did not identify any genetic associations reaching genome-wide significance in adolescent females. To explore the role of genetic variation in determining AMH levels in women of late reproductive age, we carried out a genome-wide meta-analysis in 3344 pre-menopausal women from five cohorts (median age 44-48 years at blood draw). A single genetic variant, rs16991615, previously associated with age at menopause, reached genome-wide significance at P = 3.48 × 10-10, with a per allele difference in age-adjusted inverse normal AMH of 0.26 standard deviations (SD) (95% confidence interval (CI) [0.18,0.34]). We investigated whether genetic determinants of female reproductive lifespan were more generally associated with pre-menopausal AMH levels. Genetically-predicted age at menarche had no robust association but genetically-predicted age at menopause was associated with lower AMH levels by 0.18 SD (95% CI [0.14,0.21]) in age-adjusted inverse normal AMH per one-year earlier age at menopause. Our findings provide genetic support for the well-established use of AMH as a marker of ovarian reserve.

Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics.

Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 × 10-8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.

Quantifying the extent to which index event biases influence large genetic association studies.

As genetic association studies increase in size to 100 000s of individuals, subtle biases may influence conclusions. One possible bias is 'index event bias' (IEB) that appears due to the stratification by, or enrichment for, disease status when testing associations between genetic variants and a disease-associated trait. We aimed to test the extent to which IEB influences some known trait associations in a range of study designs and provide a statistical framework for assessing future associations. Analyzing data from 113 203 non-diabetic UK Biobank participants, we observed three (near TCF7L2, CDKN2AB and CDKAL1) overestimated (body mass index (BMI) decreasing) and one (near MTNR1B) underestimated (BMI increasing) associations among 11 type 2 diabetes risk alleles (at P < 0.05). IEB became even stronger when we tested a type 2 diabetes genetic risk score composed of these 11 variants (-0.010 standard deviations BMI per allele, P = 5 × 10- 4), which was confirmed in four additional independent studies. Similar results emerged when examining the effect of blood pressure increasing alleles on BMI in normotensive UK Biobank samples. Furthermore, we demonstrated that, under realistic scenarios, common disease alleles would become associated at P < 5 × 10- 8 with disease-related traits through IEB alone, if disease prevalence in the sample differs appreciably from the background population prevalence. For example, some hypertension and type 2 diabetes alleles will be associated with BMI in sample sizes of >500 000 if the prevalence of those diseases differs by >10% from the background population. In conclusion, IEB may result in false positive or negative genetic associations in very large studies stratified or strongly enriched for/against disease cases.

Mosaic Turner syndrome shows reduced penetrance in an adult population study.

PURPOSE: Many women with X chromosome aneuploidy undergo lifetime clinical monitoring for possible complications. However, ascertainment of cases in the clinic may mean that the penetrance has been overestimated. METHODS: We characterized the prevalence and phenotypic consequences of X chromosome aneuploidy in a population of 244,848 women over 40 years of age from UK Biobank, using single-nucleotide polymorphism (SNP) array data. RESULTS: We detected 30 women with 45,X; 186 with mosaic 45,X/46,XX; and 110 with 47,XXX. The prevalence of nonmosaic 45,X (12/100,000) and 47,XXX (45/100,000) was lower than expected, but was higher for mosaic 45,X/46,XX (76/100,000). The characteristics of women with 45,X were consistent with the characteristics of a clinically recognized Turner syndrome phenotype, including short stature and primary amenorrhea. In contrast, women with mosaic 45,X/46,XX were less short, had a normal reproductive lifespan and birth rate, and no reported cardiovascular complications. The phenotype of women with 47,XXX included taller stature (5.3 cm; SD = 5.52 cm; P = 5.8 × 10-20) and earlier menopause age (5.12 years; SD = 5.1 years; P = 1.2 × 10-14). CONCLUSION: Our results suggest that the clinical management of women with 45,X/46,XX mosaicism should be minimal, particularly those identified incidentally.

Genome-Wide Association Analyses in 128,266 Individuals Identifies New Morningness and Sleep Duration Loci.

Disrupted circadian rhythms and reduced sleep duration are associated with several human diseases, particularly obesity and type 2 diabetes, but until recently, little was known about the genetic factors influencing these heritable traits. We performed genome-wide association studies of self-reported chronotype (morning/evening person) and self-reported sleep duration in 128,266 white British individuals from the UK Biobank study. Sixteen variants were associated with chronotype (P<5x10-8), including variants near the known circadian rhythm genes RGS16 (1.21 odds of morningness, 95% CI [1.15, 1.27], P = 3x10-12) and PER2 (1.09 odds of morningness, 95% CI [1.06, 1.12], P = 4x10-10). The PER2 signal has previously been associated with iris function. We sought replication using self-reported data from 89,283 23andMe participants; thirteen of the chronotype signals remained associated at P<5x10-8 on meta-analysis and eleven of these reached P<0.05 in the same direction in the 23andMe study. We also replicated 9 additional variants identified when the 23andMe study was used as a discovery GWAS of chronotype (all P<0.05 and meta-analysis P<5x10-8). For sleep duration, we replicated one known signal in PAX8 (2.6 minutes per allele, 95% CI [1.9, 3.2], P = 5.7x10-16) and identified and replicated two novel associations at VRK2 (2.0 minutes per allele, 95% CI [1.3, 2.7], P = 1.2x10-9; and 1.6 minutes per allele, 95% CI [1.1, 2.2], P = 7.6x10-9). Although we found genetic correlation between chronotype and BMI (rG = 0.056, P = 0.05); undersleeping and BMI (rG = 0.147, P = 1x10-5) and oversleeping and BMI (rG = 0.097, P = 0.04), Mendelian Randomisation analyses, with limited power, provided no consistent evidence of causal associations between BMI or type 2 diabetes and chronotype or sleep duration. Our study brings the total number of loci associated with chronotype to 22 and with sleep duration to three, and provides new insights into the biology of sleep and circadian rhythms in humans.

Variants in the FTO and CDKAL1 loci have recessive effects on risk of obesity and type 2 diabetes, respectively.

AIMS/HYPOTHESIS: Genome-wide association (GWA) studies have identified hundreds of common genetic variants associated with obesity and type 2 diabetes. These studies have usually focused on additive association tests. Identifying deviations from additivity may provide new biological insights and explain some of the missing heritability for these diseases. METHODS: We performed a GWA study using a dominance deviation model for BMI, obesity (29,925 cases) and type 2 diabetes (4,040 cases) in 120,286 individuals of British ancestry from the UK Biobank study. We also investigated whether single nucleotide polymorphisms previously shown to be associated with these traits showed any enrichment for departures from additivity. RESULTS: Known obesity-associated variants in FTO showed strong evidence of deviation from additivity (p DOMDEV = 3 × 10(-5)) through a recessive effect of the allele associated with higher BMI. The average BMI of individuals carrying zero, one or two BMI-raising alleles was 27.27 (95% CI 27.22, 27.31) kg/m(2), 27.54 (95% CI 27.50, 27.58) kg/m(2) and 28.07 (95% CI 28.00, 28.14) kg/m(2), respectively. A similar effect was observed in 105,643 individuals from the GIANT Consortium (p DOMDEV = 0.003; meta-analysis p DOMDEV = 1 × 10(-7)). For type 2 diabetes, we detected a recessive effect (p DOMDEV = 5 × 10(-4)) at CDKAL1. Relative to homozygous non-risk allele carriers, homozygous risk allele carriers had an OR of 1.48 (95% CI 1.32, 1.65), while the heterozygous group had an OR of 1.06 (95% CI 0.99, 1.14), a result consistent with that of a previous study. We did not identify any novel associations at genome-wide significance. CONCLUSIONS/INTERPRETATION: Although we found no evidence of widespread non-additive genetic effects contributing to obesity and type 2 diabetes risk, we did find robust examples of recessive effects at the FTO and CDKAL1 loci. ACCESS TO RESEARCH MATERIALS: Summary statistics are available at www.t2diabetesgenes.org and by request (a.r.wood@exeter.ac.uk). All underlying data are available on application from the UK Biobank.

Length of FMR1 repeat alleles within the normal range does not substantially affect the risk of early menopause.

STUDY QUESTION: Is the length of FMR1 repeat alleles within the normal range associated with the risk of early menopause? SUMMARY ANSWER: The length of repeat alleles within the normal range does not substantially affect risk of early menopause. WHAT IS KNOWN ALREADY: There is a strong, well-established relationship between length of premutation FMR1 alleles and age at menopause, suggesting that this relationship could continue into the normal range. Within the normal range, there is conflicting evidence; differences in ovarian reserve have been identified with FMR1 repeat allele length, but a recent population-based study did not find any association with age at menopause as a quantitative trait. STUDY DESIGN, SIZE, DURATION: We analysed cross-sectional baseline survey data collected at recruitment from 2004 to 2010 from a population-based, prospective epidemiological cohort study of >110 000 women to investigate whether repeat allele length was associated with early menopause. PARTICIPANTS/MATERIALS, SETTING, METHOD: We included 4333 women from the Breakthrough Generations Study (BGS), of whom 2118 were early menopause cases (menopause under 46 years) and 2215 were controls. We analysed the relationship between length of FMR1 alleles and early menopause using logistic regression with allele length as continuous and categorical variables. We also conducted analyses with the outcome age at menopause as a quantitative trait as well as appropriate sensitivity and exploratory analyses. MAIN RESULTS AND THE ROLE OF CHANCE: There was no association of the shorter or longer FMR1 allele or their combined genotype with the clinically relevant end point of early menopause in our main analysis. Likewise, there were no associations with age at menopause as a quantitative trait in our secondary analysis. LIMITATIONS, REASONS FOR CAUTION: Women with homozygous alleles in the normal range may have undetected FMR1 premutation alleles, although there was no evidence to suggest this. We estimate minor dilution of risk of early menopause from the likely inclusion of some women with menopause at over 45 years in the early menopause cases due to age-rounding bias in self-reports. WIDER IMPLICATIONS OF THE FINDINGS: There is no robust evidence in this large study that variation within the normal range of FMR1 repeat alleles influences timing of menopause in the general population, which contradicts findings from some earlier, mainly smaller studies. The FMR1 CGG repeat polymorphism in the normal range is unlikely to contribute to genetic susceptibility to early menopause. STUDY FUNDING/COMPETING INTERESTS: We thank Breast Cancer Now and The Institute of Cancer Research for funding the BGS. The Institute of Cancer Research acknowledges NHS funding to the NIHR Biomedical Research Centre. The study was funded by the Wellcome Trust (grant number 085943). There are no competing interests. TRIAL REGISTRATION NUMBER: Not applicable.

Genetic evidence that lower circulating FSH levels lengthen menstrual cycle, increase age at menopause and impact female reproductive health.

STUDY QUESTION: How does a genetic variant in the FSHB promoter, known to alter FSH levels, impact female reproductive health? SUMMARY ANSWER: The T allele of the FSHB promoter polymorphism (rs10835638; c.-211G>T) results in longer menstrual cycles and later menopause and, while having detrimental effects on fertility, is protective against endometriosis. WHAT IS KNOWN ALREADY: The FSHB promoter polymorphism (rs10835638; c.-211G>T) affects levels of FSHB transcription and, as a result, circulating levels of FSH. FSH is required for normal fertility and genetic variants at the FSHB locus are associated with age at menopause and polycystic ovary syndrome (PCOS). STUDY DESIGN, SIZE, DURATION: We used cross-sectional data from the UK Biobank to look at associations between the FSHB promoter polymorphism and reproductive traits, and performed a genome-wide association study (GWAS) for length of menstrual cycle. PARTICIPANTS/MATERIALS, SETTING, METHODS: We included white British individuals aged 40-69 years in 2006-2010, in the May 2015 release of genetic data from UK Biobank. We tested the FSH-lowering T allele of the FSHB promoter polymorphism (rs10835638; c.-211G>T) for associations with 29, mainly female, reproductive phenotypes in up to 63 350 women and 56 608 men. We conducted a GWAS in 9534 individuals to identify genetic variants associated with length of menstrual cycle. MAIN RESULTS AND THE ROLE OF CHANCE: The FSH-lowering T allele of the FSHB promoter polymorphism (rs10835638; MAF 0.16) was associated with longer menstrual cycles [0.16 SD (c. 1 day) per minor allele; 95% confidence interval (CI) 0.12-0.20; P = 6 × 10(-16)], later age at menopause (0.13 years per minor allele; 95% CI 0.04-0.22; P = 5.7 × 10(-3)), greater female nulliparity [odds ratio (OR) = 1.06; 95% CI 1.02-1.11; P = 4.8 × 10(-3)] and lower risk of endometriosis (OR = 0.79; 95% CI 0.69-0.90; P = 4.1 × 10(-4)). The FSH-lowering T allele was not associated with other female reproductive illnesses or conditions in our study and we did not replicate associations with male infertility or PCOS. In the GWAS for menstrual cycle length, only variants near the FSHB gene reached genome-wide significance (P < 5 × 10(-9)). LIMITATIONS, REASONS FOR CAUTION: The data included might be affected by recall bias. Cycle length was not available for 25% of women still cycling (1% did not answer, 6% did not know and for 18% cycle length was recorded as 'irregular'). Women with a cycle length recorded were aged over 40 and were approaching menopause; however, we did not find evidence that this affected the results. Many of the groups with illnesses had relatively small sample sizes and so the study may have been under-powered to detect an effect. WIDER IMPLICATIONS OF THE FINDINGS: We found a strong novel association between a genetic variant that lowers FSH levels and longer menstrual cycles, at a locus previously robustly associated with age at menopause. The variant was also associated with nulliparity and endometriosis risk. These findings should now be verified in a second independent group of patients. We conclude that lifetime differences in circulating levels of FSH between individuals can influence menstrual cycle length and a range of reproductive outcomes, including menopause timing, infertility, endometriosis and PCOS. STUDY FUNDING/COMPETING INTERESTS: None. TRIAL REGISTRATION NUMBER: Not applicable.