Understanding the genetic complexity of puberty timing across the allele frequency spectrum.

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease.

A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk.

Polygenic scores (PGSs) offer the ability to predict genetic risk for complex diseases across the life course; a key benefit over short-term prediction models. To produce risk estimates relevant to clinical and public health decision-making, it is important to account for varying effects due to age and sex. Here, we develop a novel framework to estimate country-, age-, and sex-specific estimates of cumulative incidence stratified by PGS for 18 high-burden diseases. We integrate PGS associations from seven studies in four countries (N = 1,197,129) with disease incidences from the Global Burden of Disease. PGS has a significant sex-specific effect for asthma, hip osteoarthritis, gout, coronary heart disease and type 2 diabetes (T2D), with all but T2D exhibiting a larger effect in men. PGS has a larger effect in younger individuals for 13 diseases, with effects decreasing linearly with age. We show for breast cancer that, relative to individuals in the bottom 20% of polygenic risk, the top 5% attain an absolute risk for screening eligibility 16.3 years earlier. Our framework increases the generalizability of results from biobank studies and the accuracy of absolute risk estimates by appropriately accounting for age- and sex-specific PGS effects. Our results highlight the potential of PGS as a screening tool which may assist in the early prevention of common diseases.

Genetic drivers and cellular selection of female mosaic X chromosome loss.

Mosaic loss of the X chromosome (mLOX) is the most common clonal somatic alteration in leukocytes of female individuals1,2, but little is known about its genetic determinants or phenotypic consequences. Here, to address this, we used data from 883,574 female participants across 8 biobanks; 12% of participants exhibited detectable mLOX in approximately 2% of leukocytes. Female participants with mLOX had an increased risk of myeloid and lymphoid leukaemias. Genetic analyses identified 56 common variants associated with mLOX, implicating genes with roles in chromosomal missegregation, cancer predisposition and autoimmune diseases. Exome-sequence analyses identified rare missense variants in FBXO10 that confer a twofold increased risk of mLOX. Only a small fraction of associations was shared with mosaic Y chromosome loss, suggesting that distinct biological processes drive formation and clonal expansion of sex chromosome missegregation. Allelic shift analyses identified X chromosome alleles that are preferentially retained in mLOX, demonstrating variation at many loci under cellular selection. A polygenic score including 44 allelic shift loci correctly inferred the retained X chromosomes in 80.7% of mLOX cases in the top decile. Our results support a model in which germline variants predispose female individuals to acquiring mLOX, with the allelic content of the X chromosome possibly shaping the magnitude of clonal expansion.

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning.

Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (ß coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.

Variability of polygenic prediction for body mass index in Africa.

BACKGROUND: Polygenic prediction studies in continental Africans are scarce. Africa's genetic and environmental diversity pose a challenge that limits the generalizability of polygenic risk scores (PRS) for body mass index (BMI) within the continent. Studies to understand the factors that affect PRS variability within Africa are required. METHODS: Using the first multi-ancestry genome-wide association study (GWAS) meta-analysis for BMI involving continental Africans, we derived a multi-ancestry PRS and compared its performance to a European ancestry-specific PRS in continental Africans (AWI-Gen study) and a European cohort (Estonian Biobank). We then evaluated the factors affecting the performance of the PRS in Africans which included fine-mapping resolution, allele frequencies, linkage disequilibrium patterns, and PRS-environment interactions. RESULTS: Polygenic prediction of BMI in continental Africans is poor compared to that in European ancestry individuals. However, we show that the multi-ancestry PRS is more predictive than the European ancestry-specific PRS due to its improved fine-mapping resolution. We noted regional variation in polygenic prediction across Africa's East, South, and West regions, which was driven by a complex interplay of the PRS with environmental factors, such as physical activity, smoking, alcohol intake, and socioeconomic status. CONCLUSIONS: Our findings highlight the role of gene-environment interactions in PRS prediction variability in Africa. PRS methods that correct for these interactions, coupled with the increased representation of Africans in GWAS, may improve PRS prediction in Africa.

Circulating anti-Müllerian hormone levels in pre-menopausal women: novel genetic insights from a genome-wide association meta-analysis.

STUDY QUESTION: Can a genome-wide association study (GWAS) meta-analysis, including a large sample of young premenopausal women from a founder population from Northern Finland, identify novel genetic variants for circulating anti-Müllerian hormone (AMH) levels and provide insights into single-nucleotide polymorphism enrichment in different biological pathways and tissues involved in AMH regulation? SUMMARY ANSWER: The meta-analysis identified a total of six loci associated with AMH levels at P < 5 × 10-8, three of which were novel in or near CHEK2, BMP4, and EIF4EBP1, as well as highlighted significant enrichment in renal system vasculature morphogenesis, and the pituitary gland as the top associated tissue in tissue enrichment analysis. WHAT IS KNOWN ALREADY: AMH is expressed by preantral and small antral stage ovarian follicles in women, and variation in age-specific circulating AMH levels has been associated with several health conditions. However, the biological mechanisms underlying the association between health conditions and AMH levels are not yet fully understood. Previous GWAS have identified loci associated with AMH levels in pre-menopausal women, in or near MCM8, AMH, TEX41, and CDCA7. STUDY DESIGN, SIZE, DURATION: We performed a GWAS meta-analysis for circulating AMH level measurements in 9668 pre-menopausal women. PARTICIPANTS/MATERIALS, SETTING, METHODS: We performed a GWAS meta-analysis in which we combined 2619 AMH measurements (at age 31 years) from a prospective founder population cohort (Northern Finland Birth Cohort 1966, NFBC1966) with a previous GWAS meta-analysis that included 7049 pre-menopausal women (age range 15-48 years) (N = 9668). NFBC1966 AMH measurements were quantified using an automated assay. We annotated the genetic variants, combined different data layers to prioritize potential candidate genes, described significant pathways and tissues enriched by the GWAS signals, identified plausible regulatory roles using colocalization analysis, and leveraged publicly available summary statistics to assess genetic and phenotypic correlations with multiple traits. MAIN RESULTS AND THE ROLE OF CHANCE: Three novel genome-wide significant loci were identified. One of these is in complete linkage disequilibrium with c.1100delC in CHEK2, which is found to be 4-fold enriched in the Finnish population compared to other European populations. We propose a plausible regulatory effect of some of the GWAS variants linked to AMH, as they colocalize with GWAS signals associated with gene expression levels of BMP4, TEX41, and EIFBP41. Gene set analysis highlighted significant enrichment in renal system vasculature morphogenesis, and tissue enrichment analysis ranked the pituitary gland as the top association. LARGE SCALE DATA: The GWAS meta-analysis summary statistics are available for download from the GWAS Catalogue with accession number GCST90428625. LIMITATIONS, REASONS FOR CAUTION: This study only included women of European ancestry and the lack of sufficiently sized relevant tissue data in gene expression datasets hinders the assessment of potential regulatory effects in reproductive tissues. WIDER IMPLICATIONS OF THE FINDINGS: Our results highlight the increased power of founder populations and larger sample sizes to boost the discovery of novel trait-associated variants underlying variation in AMH levels, which aided the characterization of GWAS signals enrichment in different biological pathways and plausible genetic regulatory effects linked with AMH level variation for the first time. STUDY FUNDING/COMPETING INTEREST(S): This work has received funding from the European Union's Horizon 2020 Research and Innovation Programme under the MATER Marie Sklodowska-Curie Grant Agreement No. 813707 and Oulu University Scholarship Foundation and Paulon Säätiö Foundation. (N.P.-G.), Academy of Finland, Sigrid Jusélius Foundation, Novo Nordisk, University of Oulu, Roche Diagnostics (T.T.P.). This work was supported by the Estonian Research Council Grant 1911 (R.M.). J.R. was supported by the European Union's Horizon 2020 Research and Innovation Program under Grant Agreements No. 874739 (LongITools), 824989 (EUCAN-Connect), 848158 (EarlyCause), and 733206 (LifeCycle). U.V. was supported by the Estonian Research Council grant PRG (PRG1291). The NFBC1966 received financial support from University of Oulu Grant No. 24000692, Oulu University Hospital Grant No. 24301140, and ERDF European Regional Development Fund Grant No. 539/2010 A31592. T.T.P. has received grants from Roche, Perkin Elmer, and honoraria for scientific presentations from Gedeon Richter, Exeltis, Astellas, Roche, Stragen, Astra Zeneca, Merck, MSD, Ferring, Duodecim, and Ajaton Terveys. For all other authors, there are no competing interests.

Genetic determinants of plasma protein levels in the Estonian population.

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

Identifying Atopic Dermatitis Risk Loci in 1,094,060 Individuals with Subanalysis of Disease Severity and Onset.

Atopic dermatitis (AD) is a common inflammatory skin disease highly attributable to genetic factors. In this study, we report results from a genome-wide meta-analysis of AD in 37,541 cases and 1,056,519 controls with data from the FinnGen project, the Estonian Biobank, the UK Biobank, the EAGLE Consortium, and the BioBank Japan. We detected 77 independent AD-associated loci, of which 10 were, to our knowledge, previously unreported. The associated loci showed enrichment in various immune regulatory processes. We further performed subgroup analyses of mild and severe AD and of early- and late-onset AD, with data from the FinnGen project. Fifty-five of the 79 tested variants in the associated loci showed larger effect estimates for severe than for mild AD as determined through administered treatment. The age of onset, as determined by the first hospital visit with AD diagnosis, was lower in patients with particular AD-risk alleles. Our findings add to the knowledge of the genetic background of AD and may underlie the development of new therapeutic strategies.

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.

Integrative common and rare variant analyses provide insights into the genetic architecture of liver cirrhosis.

We report a multi-ancestry genome-wide association study on liver cirrhosis and its associated endophenotypes, alanine aminotransferase (ALT) and γ-glutamyl transferase. Using data from 12 cohorts, including 18,265 cases with cirrhosis, 1,782,047 controls, up to 1 million individuals with liver function tests and a validation cohort of 21,689 cases and 617,729 controls, we identify and validate 14 risk associations for cirrhosis. Many variants are located near genes involved in hepatic lipid metabolism. One of these, PNPLA3 p.Ile148Met, interacts with alcohol intake, obesity and diabetes on the risk of cirrhosis and hepatocellular carcinoma (HCC). We develop a polygenic risk score that associates with the progression from cirrhosis to HCC. By focusing on prioritized genes from common variant analyses, we find that rare coding variants in GPAM associate with lower ALT, supporting GPAM as a potential target for therapeutic inhibition. In conclusion, this study provides insights into the genetic underpinnings of cirrhosis.

Body mass index stratified meta-analysis of genome-wide association studies of polycystic ovary syndrome in women of European ancestry.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex multifactorial disorder with a substantial genetic component. However, the clinical manifestations of PCOS are heterogeneous with notable differences between lean and obese women, implying a different pathophysiology manifesting in differential body mass index (BMI). We performed a meta-analysis of genome-wide association study (GWAS) data from six well-characterised cohorts, using a case-control study design stratified by BMI, aiming to identify genetic variants associated with lean and overweight/obese PCOS subtypes. RESULTS: The study comprised 254,588 women (5,937 cases and 248,651 controls) from individual studies performed in Australia, Estonia, Finland, the Netherlands and United States of America, and separated according to three BMI stratifications (lean, overweight and obese). Genome-wide association analyses were performed for each stratification within each cohort, with the data for each BMI group meta-analysed using METAL software. Almost half of the total study population (47%, n = 119,584) were of lean BMI (≤ 25 kg/m2). Two genome-wide significant loci were identified for lean PCOS, led by rs12000707 within DENND1A (P = 1.55 × 10-12) and rs2228260 within XBP1 (P = 3.68 × 10-8). One additional locus, LINC02905, was highlighted as significantly associated with lean PCOS through gene-based analyses (P = 1.76 × 10-6). There were no significant loci observed for the overweight or obese sub-strata when analysed separately, however, when these strata were combined, an association signal led by rs569675099 within DENND1A reached genome-wide significance (P = 3.22 × 10-9) and a gene-based association was identified with ERBB4 (P = 1.59 × 10-6). Nineteen of 28 signals identified in previous GWAS, were replicated with consistent allelic effect in the lean stratum. There were less replicated signals in the overweight and obese groups, and only 4 SNPs were replicated in each of the three BMI strata. CONCLUSIONS: Genetic variation at the XBP1, LINC02905 and ERBB4 loci were associated with PCOS within unique BMI strata, while DENND1A demonstrated associations across multiple strata, providing evidence of both distinct and shared genetic features between lean and overweight/obese PCOS-affected women. This study demonstrated that PCOS-affected women with contrasting body weight are not only phenotypically distinct but also show variation in genetic architecture; lean PCOS women typically display elevated gonadotrophin ratios, lower insulin resistance, higher androgen levels, including adrenal androgens, and more favourable lipid profiles. Overall, these findings add to the growing body of evidence supporting a genetic basis for PCOS as well as differences in genetic patterns relevant to PCOS BMI-subtype.

Rare copy-number variants as modulators of common disease susceptibility.

BACKGROUND: Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described. METHODS: Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank. RESULTS: We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS. CONCLUSIONS: Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.

Distinct and shared genetic architectures of gestational diabetes mellitus and type 2 diabetes.

Gestational diabetes mellitus (GDM) is a common metabolic disorder affecting more than 16 million pregnancies annually worldwide1,2. GDM is related to an increased lifetime risk of type 2 diabetes (T2D)1-3, with over a third of women developing T2D within 15 years of their GDM diagnosis. The diseases are hypothesized to share a genetic predisposition1-7, but few studies have sought to uncover the genetic underpinnings of GDM. Most studies have evaluated the impact of T2D loci only8-10, and the three prior genome-wide association studies of GDM11-13 have identified only five loci, limiting the power to assess to what extent variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen study and identified 13 GDM-associated loci, including nine new loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into the following two distinct categories: one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis and placental expression.

Polygenic risk scores as a marker for epilepsy risk across lifetime and after unspecified seizure events.

A diagnosis of epilepsy has significant consequences for an individual but is often challenging in clinical practice. Novel biomarkers are thus greatly needed. Here, we investigated how common genetic factors (epilepsy polygenic risk scores, [PRSs]) influence epilepsy risk in detailed longitudinal electronic health records (EHRs) of > 360k Finns spanning up to 50 years of individuals' lifetimes. Individuals with a high genetic generalized epilepsy PRS (PRSGGE) in FinnGen had an increased risk for genetic generalized epilepsy (GGE) (hazard ratio [HR] 1.55 per PRSGGE standard deviation [SD]) across their lifetime and after unspecified seizure events. Effect sizes of epilepsy PRSs were comparable to effect sizes in clinically curated data supporting our EHR-derived epilepsy diagnoses. Within 10 years after an unspecified seizure, the GGE rate was 37% when PRSGGE > 2 SD compared to 5.6% when PRSGGE < -2 SD. The effect of PRSGGE was even larger on GGE subtypes of idiopathic generalized epilepsy (IGE) (HR 2.1 per SD PRSGGE). We further report significantly larger effects of PRSGGE on epilepsy in females and in younger age groups. Analogously, we found significant but more modest focal epilepsy PRS burden associated with non-acquired focal epilepsy (NAFE). We found PRSGGE specifically associated with GGE in comparison with >2000 independent diseases while PRSNAFE was also associated with other diseases than NAFE such as back pain. Here, we show that epilepsy specific PRSs have good discriminative ability after a first seizure event i.e. in circumstances where the prior probability of epilepsy is high outlining a potential to serve as biomarkers for an epilepsy diagnosis.

An atlas of genetic determinants of forearm fracture.

Osteoporotic fracture is among the most common and costly of diseases. While reasonably heritable, its genetic determinants have remained elusive. Forearm fractures are the most common clinically recognized osteoporotic fractures with a relatively high heritability. To establish an atlas of the genetic determinants of forearm fractures, we performed genome-wide association analyses including 100,026 forearm fracture cases. We identified 43 loci, including 26 new fracture loci. Although most fracture loci associated with bone mineral density, we also identified loci that primarily regulate bone quality parameters. Functional studies of one such locus, at TAC4, revealed that Tac4-/- mice have reduced mechanical bone strength. The strongest forearm fracture signal, at WNT16, displayed remarkable bone-site-specificity with no association with hip fractures. Tall stature and low body mass index were identified as new causal risk factors for fractures. The insights from this atlas may improve fracture prediction and enable therapeutic development to prevent fractures.

HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases.

The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease.

Genome-wide association study meta-analysis supports association between MUC1 and ectopic pregnancy.

STUDY QUESTION: Can we identify genetic variants associated with ectopic pregnancy by undertaking the first genome-wide association study (GWAS) leveraging two large-scale biobank initiatives? SUMMARY ANSWER: We identified two novel genome-wide significant associations with ectopic pregnancy, highlighting MUC1 (mucin 1) as the most plausible affected gene. WHAT IS KNOWN ALREADY: Ectopic pregnancy is an important cause of maternal morbidity and mortality worldwide. Despite being a common early pregnancy complication, the genetic predisposition to this condition remains understudied and no large scale genetic studies have been performed so far. STUDY DESIGN, SIZE, DURATION: A GWAS meta-analysis including 7070 women with ectopic pregnancy and 248 810 controls from Estonian Biobank and the FinnGen study. PARTICIPANTS/MATERIALS, SETTING, METHODS: We identified ectopic pregnancy cases from national registers by ICD (International Classification of Disease) codes (ICD-10 O00), and all remaining women were considered controls. We carried out standard GWAS meta-analysis and additionally annotated GWAS signals, analysed co-localization with quantitative trait loci, estimated genetic correlations and identified associated phenotypes to characterize the genetic signals, as well as to analyse the genetic and phenotypic relationships with the condition. MAIN RESULTS AND THE ROLE OF CHANCE: We identified two genome-wide significant loci on chromosomes 1 (rs4971091, P = 5.32×10-9) and 10 (rs11598956, P = 2.41×10-8) potentially associated with ectopic pregnancy. Follow-up analyses propose MUC1, which codes for an epithelial glycoprotein with an important role in barrier function, as the most likely candidate gene for the association on chromosome 1. We also characterize the phenotypic and genetic correlations with other phenotypes, identifying a genetic correlation with smoking and diseases of the (genito)urinary and gastrointestinal system, and phenotypic correlations with various reproductive health diagnoses, reflecting the previously known epidemiological associations. LARGE SCALE DATA: The GWAS meta-analysis summary statistics are available from the GWAS Catalogue (GCST90272883). LIMITATIONS, REASONS FOR CAUTION: The main limitation is that the findings are based on European-based ancestry populations, with limited data on other populations, and we only captured maternal genomes. Additionally, further larger meta-analysis or independent studies are needed to validate these findings. WIDER IMPLICATIONS OF THE FINDINGS: This study encourages the use of large-scale genetic datasets to unravel genetic factors linked to ectopic pregnancy, which is difficult to study in experimental settings. Increased sample size might bring additional genetic factors associating with ectopic pregnancy and inform its heritability. Altogether, our results provide more insight into the biology of ectopic pregnancy and, accordingly, the biological processes governing embryo implantation. STUDY FUNDING/COMPETING INTEREST(S): N.P.G. was supported by MATER Marie Sklodowska-Curie which received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 813707. This study was funded by European Union through the European Regional Development Fund Project No. 2014-2020.4.01.15-0012 GENTRANSMED. Computations were performed in the High-Performance Computing Center of University of Tartu. The authors declare no competing interests.

European and multi-ancestry genome-wide association meta-analysis of atopic dermatitis highlights importance of systemic immune regulation.

Atopic dermatitis (AD) is a common inflammatory skin condition and prior genome-wide association studies (GWAS) have identified 71 associated loci. In the current study we conducted the largest AD GWAS to date (discovery N = 1,086,394, replication N = 3,604,027), combining previously reported cohorts with additional available data. We identified 81 loci (29 novel) in the European-only analysis (which all replicated in a separate European analysis) and 10 additional loci in the multi-ancestry analysis (3 novel). Eight variants from the multi-ancestry analysis replicated in at least one of the populations tested (European, Latino or African), while two may be specific to individuals of Japanese ancestry. AD loci showed enrichment for DNAse I hypersensitivity and eQTL associations in blood. At each locus we prioritised candidate genes by integrating multi-omic data. The implicated genes are predominantly in immune pathways of relevance to atopic inflammation and some offer drug repurposing opportunities.

GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification.

Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on 'around the clock' glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals. Of these, 44 loci are new for glycemic traits. Regulatory, glycosylation and metagenomic annotations highlight ileum and colon tissues, indicating an underappreciated role of the gastrointestinal tract in controlling blood glucose. Functional follow-up and molecular dynamics simulations of lower frequency coding variants in glucagon-like peptide-1 receptor (GLP1R), a type 2 diabetes treatment target, reveal that optimal selection of GLP-1R agonist therapy will benefit from tailored genetic stratification. We also provide evidence from Mendelian randomization that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Our investigation yields new insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.