Testosterone supplementation is commonly used for its effects on sexual function, bone health and body composition, yet its effects on disease outcomes are unknown. To better understand this, we identified genetic determinants of testosterone levels and related sex hormone traits in 425,097 UK Biobank study participants. Using 2,571 genome-wide significant associations, we demonstrate the genetic determinants of testosterone levels are substantially different between sexes, and that genetically higher testosterone is harmful for metabolic diseases in women but beneficial in men. For example, a genetically determined 1-standard deviation higher testosterone increases the risks of Type 2 diabetes (T2D) (OR=1.37 [1.22–1.53]) and polycystic ovary syndrome (OR=1.51 [1.33–1.72]) in women, but reduces T2D risk in men (OR=0.86 [0.76–0.98]). We also show adverse effects of higher testosterone on breast and endometrial cancers in women, and prostate cancer in men. Our findings provide insights into the disease impacts of testosterone and highlight the importance of sex-specific genetic analyses.

In cross-platform analyses of 174 metabolites we identify 499 associations (p<4.9×10 -10 ) characterized by pleiotropy, allelic heterogeneity, large and non-linear effects, and enrichment for nonsynonymous variation. We identify a signal at GLP2R (p.Asp470Asn) shared between higher citrulline levels, body mass index, fasting glucose-dependent insulinotropic peptide and type 2 diabetes, with beta-arrestin signalling as the underlying mechanism. Genetically-higher serine levels are shown to reduce the likelihood (by 95%) and predict development of macular telangiectasia type 2, a rare degenerative retinal disease. Integration of genomic and small molecule data across platforms enables discovery of regulators of human metabolism and translation into clinical insights. M.P. was supported by a fellowship from the German Research Foundation (DFG PI 1446/2-1). C.O. was founded by an early career fellowship at Homerton College, University of Cambridge. L. B. L. W.

IMPORTANCE Body fat distribution, usually measured using waist-to-hip ratio (WHR), is an important contributor to cardiometabolic disease independent of body mass index (BMI). Whether mechanisms that increase WHR via lower gluteofemoral (hip) or via higher abdominal (waist) fat distribution affect cardiometabolic risk is unknown. OBJECTIVE To identify genetic variants associated with higher WHR specifically via lower gluteofemoral or higher abdominal fat distribution and estimate their association with cardiometabolic risk. DESIGN, SETTING, AND PARTICIPANTS Genome-wide association studies (GWAS) for WHR combined data from the UK Biobank cohort and summary statistics from previous GWAS (data collection: 2006-2018). Specific polygenic scores for higher WHR via lower gluteofemoral or via higher abdominal fat distribution were derived using WHR-associated genetic variants showing specific association with hip or waist circumference. Associations of polygenic scores with outcomes were estimated in 3 population-based cohorts, a case-cohort study, and summary statistics from 6 GWAS (data collection: 1991-2018). EXPOSURES More than 2.4 million common genetic variants (GWAS); polygenic scores for higher WHR (follow-up analyses). MAIN OUTCOMES AND MEASURES BMI-adjusted WHR and unadjusted WHR (GWAS); compartmental fat mass measured by dual-energy x-ray absorptiometry, systolic and diastolic blood pressure, low-density lipoprotein cholesterol, triglycerides, fasting glucose, fasting insulin, type 2 diabetes, and coronary disease risk (follow-up analyses). RESULTS Among 452 302 UK Biobank participants of European ancestry, the mean (SD) age was 57 (8) years and the mean (SD) WHR was 0.87 (0.09). In genome-wide analyses, 202 independent genetic variants were associated with higher BMI-adjusted WHR (n = 660 648) and unadjusted WHR (n = 663 598). In dual-energy x-ray absorptiometry analyses (n = 18 330), the hip-and waist-specific polygenic scores for higher WHR were specifically associated with lower gluteofemoral and higher abdominal fat, respectively. In follow-up analyses (n = 636 607), both polygenic scores were associated with higher blood pressure and triglyceride levels and higher risk of diabetes (waist-specific score: odds ratio [OR], 1.57 [95% CI, 1.34-1.83], absolute risk increase per 1000 participant-years [ARI], 4.4 [95% CI,

Circulating levels of glycine have previously been associated with lower incidence of coronary heart disease (CHD) and type 2 diabetes (T2D) but it remains uncertain if glycine plays an aetiological role. We present a meta-analysis of genome-wide association studies for glycine in 80,003 participants and investigate the causality and potential mechanisms of the association between glycine and cardio-metabolic diseases using genetic approaches. We identify 27 genetic loci, of which 22 have not previously been reported for glycine. We show that glycine is genetically associated with lower CHD risk and find that this may be partly driven by blood pressure. Evidence for a genetic association of glycine with T2D is weaker, but we find a strong inverse genetic effect of hyperinsulinaemia on glycine. Our findings strengthen evidence for a protective effect of glycine on CHD and show that the glycine-T2D association may be driven by a glycine-lowering effect of insulin resistance.

Key PointsQuestionAre genetically determined differences in lipoprotein lipase (LPL)–mediated lipolysis and low-density lipoprotein cholesterol (LDL-C)–lowering pathways independently associated with risk of coronary disease and diabetes?FindingsIn this genetic association study including 392 220 people, triglyceride-lowering alleles in LPL or its inhibitor ANGPTL4 were associated with lower risk of coronary artery disease and type 2 diabetes in a consistent fashion across quantiles of the population distribution of LDL-C–lowering alleles. For a given genetic difference in LDL-C, the association with lower risk of coronary disease conveyed by rare loss-of-function variants in ANGPTL3, which are associated with lower LDL-C levels and enhanced LPL lipolysis, was greater than that conveyed by other LDL-C–lowering genetic mechanisms.MeaningLPL-mediated lipolysis and LDL-C–lowering mechanisms independently contribute to the risk of coronary disease and diabetes, which supports the development of LPL-enhancing agents for use in the context of LDL-C–lowering therapy.

Garrod’s concept of ‘chemical individuality’ has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant–metabolite associations (P < 1.25 × 10−11) within 330 genomic regions, with rare variants (minor allele frequency ≤ 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant–metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships.

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe earlyonset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only and its association with lower leptin concentrations was specific to this ancestry (P=2x10-16 , n=3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting leptin regulates early adiposity. * Call rate to exclude individuals for whom genotyping success rate is less than a certain percentage (to exclude 'bad' samples/DNA) **Exome-chip samples from this study CHOP: The authors thank the network of primary care clinicians and the patients and families for their contribution to this project and to clinical research facilitated by the Pediatric Research Consortium [PeRC]-The Children's Hospital of Philadelphia. R. Chiavacci, E. Dabaghyan, A.

Background Obesity is observationally associated with altered risk of many female reproductive conditions. These include polycystic ovary syndrome (PCOS), abnormal uterine bleeding, endometriosis, infertility, and pregnancy-related disorders. However, the roles and mechanisms of obesity in the aetiology of reproductive disorders remain unclear. Thus, we aimed to estimate observational and genetically predicted causal associations between obesity, metabolic hormones, and female reproductive disorders. Methods and findings Logistic regression, generalised additive models, and Mendelian randomisation (MR) (2-sample, non-linear, and multivariable) were applied to obesity and reproductive disease data on up to 257,193 women of European ancestry in UK Biobank and publicly available genome-wide association studies (GWASs). Body mass index (BMI), waist-to-hip ratio (WHR), and WHR adjusted for BMI were observationally (odds ratios [ORs] = 1.02–1.87 per 1-SD increase in obesity trait) and genetically (ORs = 1.06–2.09) associated with uterine fibroids (UF), PCOS, heavy menstrual bleeding (HMB), and pre-eclampsia. Genetically predicted visceral adipose tissue (VAT) mass was associated with the development of HMB (OR [95% CI] per 1-kg increase in predicted VAT mass = 1.32 [1.06–1.64], P = 0.0130), PCOS (OR [95% CI] = 1.15 [1.08–1.23], P = 3.24 × 10−05), and pre-eclampsia (OR [95% CI] = 3.08 [1.98–4.79], P = 6.65 × 10−07). Increased waist circumference posed a higher genetic risk (ORs = 1.16–1.93) for the development of these disorders and UF than did increased hip circumference (ORs = 1.06–1.10). Leptin, fasting insulin, and insulin resistance each mediated between 20% and 50% of the total genetically predicted association of obesity with pre-eclampsia. Reproductive conditions clustered based on shared genetic components of their aetiological relationships with obesity. This study was limited in power by the low prevalence of female reproductive conditions among women in the UK Biobank, with little information on pre-diagnostic anthropometric traits, and by the susceptibility of MR estimates to genetic pleiotropy. Conclusions We found that common indices of overall and central obesity were associated with increased risks of reproductive disorders to heterogenous extents in a systematic, large-scale genetics-based analysis of the aetiological relationships between obesity and female reproductive conditions. Our results suggest the utility of exploring the mechanisms mediating the causal associations of overweight and obesity with gynaecological health to identify targets for disease prevention and treatment.