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Body composition is often altered in psychiatric disorders. Using genome-wide common genetic variation data, we calculate sex-specific genetic correlations amongst body fat %, fat mass, fat-free mass, physical activity, glycemic traits and 17 psychiatric traits (up to N  = 217,568). Two patterns emerge: (1) anorexia nervosa, schizophrenia, obsessive-compulsive disorder, and education years are negatively genetically correlated with body fat % and fat-free mass, whereas (2) attention-deficit/hyperactivity disorder (ADHD), alcohol dependence, insomnia, and heavy smoking are positively correlated. Anorexia nervosa shows a stronger genetic correlation with body fat % in females, whereas education years is more strongly correlated with fat mass in males. Education years and ADHD show genetic overlap with childhood obesity. Mendelian randomization identifies schizophrenia, anorexia nervosa, and higher education as causal for decreased fat mass, with higher body fat % possibly being a causal risk factor for ADHD and heavy smoking. These results suggest new possibilities for targeted preventive strategies. Psychiatric disorders are often accompanied by alterations in BMI and body composition due to changes in eating behaviour and physical activity. Here, Hübel et al. study the genetic overlap between these traits and find that genetic correlations between psychiatric disorders and body composition are sex-specific and evident only in adulthood.

Background Moderate to heavy alcohol consumption is associated with an increased risk of breast cancer. The etiologic role of genetic variation in genes involved in ethanol metabolism has not been established, with little information available among women of African ancestry. Methods Our analysis from the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium included 2889 U.S. Black women who were current drinkers at the time of breast cancer diagnosis (N cases = 715) and had available genetic data for four ethanol metabolism genomic regions ( ADH, ALDH, CYP2E1 , and ALDH2 ). We used generalized estimating equations to calculate genetic effects, gene* alcohol consumption (≥ 7drinks/week vs. < 7/week) interactions, and joint main plus interaction effects of up to 23,247 variants in ethanol metabolism genomic regions on odds of breast cancer. Results Among current drinkers, 21% of cases and 14% of controls reported consuming ≥ 7 drinks per week. We identified statistically significant genetic effects for rs79865122-C in CYP2E1 with odds of ER- breast cancer and odds of triple negative breast cancer, as well as a significant joint effect with odds of ER- breast cancer (≥ 7drinks per week OR = 3.92, < 7 drinks per week OR = 0.24, p joint  = 3.74 × 10 −6 ). In addition, there was a statistically significant interaction of rs3858704-A in ALDH2 with consumption of ≥ 7 drinks/week on odds of triple negative breast cancer (≥ 7drinks per week OR = 4.41, < 7 drinks per week OR = 0.57, p int  = 8.97 × 10 –5 ). Conclusions There is a paucity of information on the impact of genetic variation in alcohol metabolism genes on odds of breast cancer among Black women. Our analysis of variants in four genomic regions harboring ethanol metabolism genes in a large consortium of U.S. Black women identified significant associations between rs79865122-C in CYP2E1 and odds of ER- and triple negative breast cancer. Replication of these findings is warranted.

Investigating genetic architecture of complex traits in ancestrally diverse populations is imperative to understand the etiology of disease. However, the current paucity of genetic research in people of African and Latin American ancestry, Hispanic and indigenous peoples in the United States is likely to exacerbate existing health disparities for many common diseases. The Population Architecture using Genomics and Epidemiology, Phase II (PAGE II), Study was initiated in 2013 by the National Human Genome Research Institute to expand our understanding of complex trait loci in ethnically diverse and well characterized study populations. To meet this goal, the Multi-Ethnic Genotyping Array (MEGA) was designed to substantially improve fine-mapping and functional discovery by increasing variant coverage across multiple ethnicities at known loci for metabolic, cardiovascular, renal, inflammatory, anthropometric, and a variety of lifestyle traits. Studying the frequency distribution of clinically relevant mutations, putative risk alleles, and known functional variants across multiple populations will provide important insight into the genetic architecture of complex diseases and facilitate the discovery of novel, sometimes population-specific, disease associations. DNA samples from 51,650 self-identified African ancestry (17,328), Hispanic/Latino (22,379), Asian/Pacific Islander (8,640), and American Indian (653) and an additional 2,650 participants of either South Asian or European ancestry, and other reference panels have been genotyped on MEGA by PAGE II. MEGA was designed as a new resource for studying ancestrally diverse populations. Here, we describe the methodology for selecting trait-specific content for use in multi-ethnic populations and how enriching MEGA for this content may contribute to deeper biological understanding of the genetic etiology of complex disease.

Aims/hypothesisType 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study.MethodsWe conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci.ResultsFour novel associations were identified (p < 5 × 10−9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis.Conclusions/interpretationOur findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations.Data availabilityFull summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog (https://www.ebi.ac.uk/gwas/downloads/summary-statistics).

Background Circulating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented. Results We performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance ( P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance ( P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations. Conclusions Our results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.

Objective Cardiovascular complications occur in up to 80% of patients with anorexia nervosa (AN), yet the underlying mechanisms warrant further investigation. We assessed the genetic correlation (rg) between AN and cardiovascular disease (CVD) events to inform whether elevated cardiovascular risk among individuals with AN is due to shared genetic effects. Method We used genome‐wide association study summary statistics for AN (N = 72,517), AN with binge eating (N = 12,630), AN without binge eating (N = 12,516), and six CVD events (N = 390,142 to 977,323). We calculated the rgs via linkage disequilibrium score regression and corrected for multiple testing using false discovery rate. Results Significant rgs emerged between AN with heart failure (rg = –0.11, SE = 0.05, q = .04) and myocardial infarction (rg = –0.10, SE = 0.03, q = .01). AN with binge eating had a significant rg with myocardial infarction (rg = –0.15, SE = 0.06, q = .02). No significant rg emerged between AN without binge eating and any CVD event. Discussion Some loci affect the liability to AN and CVD in opposite directions and the shared genetic effects may not be consistent across all CVD events. Our results provide further evidence suggesting that the elevated cardiovascular risk in AN may not be due to shared genetic underpinnings, but more likely a downstream consequence of the disease. We calculated the genetic correlation between three anorexia nervosa (AN) phenotypes and six cardiovascular disease (CVD) events. We observed significant (q<.05) genetic correlations between AN with heart failure and myocardial infarction, and between AN with binge eating and myocardial infarction. No significant genetic correlation emerged between AN without binge eating and any CVD event.

Background Obesity is thought to increase cardiovascular disease (CVD) risk partly through dyslipidemia. Yet, obesity’s effects on dyslipidemia are not uniform. Understanding the shared genetic basis between obesity and lipid traits can provide insight into this heterogeneity and its implications for CVD risk. Methods We examined local genetic correlations between three lipid measures [high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), and triglycerides (TG)] and body mass index (BMI) using genome-wide association study summary statistics from European ancestry UK Biobank participants. We identified genomic loci with opposing genetic effects on obesity and dyslipidemia risk (protective BMI-lipid loci) and those with concordant directions for both obesity and dyslipidemia risk (adverse BMI-lipid loci). Gene-based association analyses were used to prioritize potential causal genes. We then constructed polygenic risk scores for BMI (PRS BMI ) based on protective and adverse loci and assessed their associations with BMI, lipid levels, CVD, and related traits in the diverse Population Architecture using Genomics and Epidemiology (PAGE) study. PheWAS was performed in the All of Us cohort. Mendelian randomization (MR) was conducted to assess the causal impact of protective/adverse loci on cardiometabolic outcomes. Finally, we investigated the associations with fat distribution traits using MRI-based fat measures in the UK Biobank. Results Among 2495 regions, we identified 789 HDL, 26 LDL, and 494 TG loci with significant local genetic correlation with BMI (including overlapping loci). Of these, 3 HDL, 10 LDL, and 8 TG loci showed protective correlations. Gene-based analyses prioritized 18 candidate causal genes. The protective PRS BMI(+)HDL(+) was associated with higher BMI but favorable lipid profiles and reduced CVD risk in PAGE. PheWAS revealed protective associations with hyperlipidemia, atrial fibrillation, and Alzheimer’s disease. MR supported the favorable causal effects of these protective loci on several cardiometabolic outcomes. Notably, protective PRS BMI(+)TG(−) was uniquely associated with decreased visceral-to-abdominal subcutaneous adipose tissue ratio. Conclusions Identifying and validating genomic loci with shared genetic signals between BMI and lipid levels further supports the importance of genetics in defining the heterogeneous impact of obesity on dyslipidemia and CVD.

PurposeCirculating anti-Müllerian hormone (AMH) levels are positively associated with time to menopause and breast cancer risk. We examined breast cancer associations with single nucleotide polymorphisms (SNPs) in the AMH gene or its receptor genes, ACVR1 and AMHR2, among African American women.MethodsIn the AMBER consortium, we tested 65 candidate SNPs, and 1130 total variants, in or near AMH, ACVR1, and AMHR2 and breast cancer risk. Overall, 3649 cases and 4230 controls contributed to analyses. Odds ratios (OR) and 95% confidence intervals (CI) for breast cancer were calculated using multivariable logistic regression.ResultsAfter correction for multiple comparisons (false-discovery rate of 5%), there were no statistically significant associations with breast cancer risk. Without correction for multiple testing, four candidate SNPs in ACVR1 and one near AMH were associated with breast cancer risk. In ACVR1, rs13395576[C] was associated with lower breast cancer risk overall (OR 0.84; 95% CI 0.72, 0.97) and for ER+ disease (OR 0.75; CI 0.62, 0.89) (p < 0.05). Rs1220110[A] and rs1220134[T] each had ORs of 0.89–0.90 for postmenopausal and ER+ breast cancer (p ≤ 0.03). Conversely, rs1682130[T] was associated with higher risk of ER+ breast cancer (OR 1.17; 95% CI 1.04, 1.32). Near AMH, rs6510652[T] had ORs of 0.85–0.90 for breast cancer overall and after menopause (p ≤ 0.02).ConclusionsThe present results, from a large study of African American women, provide limited support for an association between AMH-related polymorphisms and breast cancer risk and require replication in other studies.

ObjectivePR interval (PR) is a heritable electrocardiographic measure of atrial and atrioventricular nodal conduction. Changes in PR duration may be associated with atrial fibrillation, heart failure and all-cause mortality. Hispanic/Latino populations have high burdens of cardiovascular morbidity and mortality, are highly admixed and represent exceptional opportunities for novel locus identification. However, they remain chronically understudied. We present the first genome-wide association study (GWAS) of PR in 14 756 participants of Hispanic/Latino ancestry from three studies.MethodsStudy-specific summary results of the association between 1000 Genomes Phase 1 imputed single-nucleotide polymorphisms (SNPs) and PR assumed an additive genetic model and were adjusted for global ancestry, study centre/region and clinical covariates. Results were combined using fixed-effects, inverse variance weighted meta-analysis. Sequential conditional analyses were used to identify independent signals. Replication of novel loci was performed in populations of Asian, African and European descent. ENCODE and RoadMap data were used to annotate results.ResultsWe identified a novel genome-wide association (P<5×10−8) with PR at ID2 (rs6730558), which replicated in Asian and European populations (P<0.017). Additionally, we generalised 10 previously identified PR loci to Hispanics/Latinos. Bioinformatics annotation provided evidence for regulatory function in cardiac tissue. Further, for six loci that generalised, the Hispanic/Latino index SNP was genome-wide significant and identical to (or in high linkage disequilibrium with) the previously identified GWAS lead SNP.ConclusionsOur results suggest that genetic determinants of PR are consistent across race/ethnicity, but extending studies to admixed populations can identify novel associations, underscoring the importance of conducting genetic studies in diverse populations.