GENETIC STUDY OF PSORIASIS HIGHLIGHTS ITS CLOSE LINK WITH SOCIO-ECONOMIC STATUS AND AFFECTIVE SYMPTOMS.

Psoriasis is an inflammatory skin disease with an estimated heritability of around 70 %. Previous genome-wide association studies (GWASs) have detected several risk loci for psoriasis. To further improve the understanding of the genetic risk factors impacting the disease, we conducted a discovery GWAS in FinnGen and a subsequent replication and meta-analysis with data from the Estonian Biobank and the UK biobank; the study sample included 925 649 individuals (22 659 cases and 902 990 controls), the largest sample for psoriasis yet. In addition, we conducted downstream analyses to find out more about psoriasis' cross-trait genetic correlations and causal relationships. We report 6 risk loci to our knowledge previously unreported, most of which harbor genes related to nuclear factor kappa-light-chain-enhancer of activated B-cells-signaling pathway and overall immunity. Genetic correlations highlight the relationship between psoriasis and smoking, higher body weight, and lower education level. Additionally, we report causal relationships between psoriasis and mood symptoms, as well as two-directioned causal relationship between psoriasis and lower education level. Our results provide further knowledge on psoriasis risk factors, which may be useful in the development of future treatment strategies.

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.

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.

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.

Mapping cell-to-tissue graphs across human placenta histology whole slide images using deep learning with HAPPY.

Accurate placenta pathology assessment is essential for managing maternal and newborn health, but the placenta's heterogeneity and temporal variability pose challenges for histology analysis. To address this issue, we developed the 'Histology Analysis Pipeline.PY' (HAPPY), a deep learning hierarchical method for quantifying the variability of cells and micro-anatomical tissue structures across placenta histology whole slide images. HAPPY differs from patch-based features or segmentation approaches by following an interpretable biological hierarchy, representing cells and cellular communities within tissues at a single-cell resolution across whole slide images. We present a set of quantitative metrics from healthy term placentas as a baseline for future assessments of placenta health and we show how these metrics deviate in placentas with clinically significant placental infarction. HAPPY's cell and tissue predictions closely replicate those from independent clinical experts and placental biology literature.

The endometrial transcriptome of infertile women with and without implantation failure.

INTRODUCTION: Implantation failure after transferring morphologically "good-quality" embryos in in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) may be explained by impaired endometrial receptivity. Analyzing the endometrial transcriptome analysis may reveal the underlying processes and could help in guiding prognosis and using targeted interventions for infertility. This exploratory study investigated whether the endometrial transcriptome profile was associated with short-term or long-term implantation outcomes (ie success or failure). MATERIAL AND METHODS: Mid-luteal phase endometrial biopsies of 107 infertile women with one full failed IVF/ICSI cycle, obtained within an endometrial scratching trial, were subjected to RNA-sequencing and differentially expressed genes analysis with covariate adjustment (age, body mass index, luteinizing hormone [LH]-day). Endometrial transcriptomes were compared between implantation failure and success groups in the short term (after the second fresh IVF/ICSI cycle) and long term (including all fresh and frozen cycles within 12 months). The short-term analysis included 85/107 women (33 ongoing pregnancy vs 52 no pregnancy), excluding 22/107 women. The long-term analysis included 46/107 women (23 'fertile' group, ie infertile women with a live birth after ≤3 embryos transferred vs 23 recurrent implantation failure group, ie no live birth after ≥3 good quality embryos transferred), excluding 61/107 women not fitting these categories. As both analyses drew from the same pool of 107 samples, there was some sample overlap. Additionally, cell type enrichment scores and endometrial receptivity were analyzed, and an endometrial development pseudo-timeline was constructed to estimate transcriptomic deviations from the optimum receptivity day (LH + 7), denoted as ΔWOI (window of implantation). RESULTS: There were no significantly differentially expressed genes between implantation failure and success groups in either the short-term or long-term analyses. Principal component analysis initially showed two clusters in the long-term analysis, unrelated to clinical phenotype and no longer distinct following covariate adjustment. Cell type enrichment scores did not differ significantly between groups in both analyses. However, endometrial receptivity analysis demonstrated a potentially significant displacement of the WOI in the non-pregnant group compared with the ongoing pregnant group in the short-term analysis. CONCLUSIONS: No distinct endometrial transcriptome profile was associated with either implantation failure or success in infertile women. However, there may be differences in the extent to which the WOI is displaced.

Genome-wide association study in Estonia reveals importance of vaginal epithelium associated genes in case of recurrent vaginitis.

Recurrent vaginitis is a leading reason for visiting a gynaecologist, with bacterial vaginosis (BV) and vulvovaginal candidiasis (VVC) being the most common diagnoses. Reasons and mechanisms behind their recurrent nature are poorly understood. We conducted a genome-wide association study (GWAS) to find possible genetic risk factors for recurrent vaginitis using data from a large population-based biobank, the Estonian Biobank. The study included 6870 cases (at least two episodes of vaginitis) and 5945 controls (no vaginitis episodes). GWAS approach included single marker and gene-based analyses, followed by functional annotation of associated variants and candidate gene mapping.In single marker analysis, one statistically significant (P = 7.8 × 10-9) variant rs1036732378 was identified on chromosome 10. The gene-based association analysis identified one gene, KRT6A, that exceeded the recommended significance threshold (P = 2.6 × 10-6). This is a member of the keratin protein family and is expressed during differentiation in epithelial tissues.Functional mapping and annotation of genetic associations by using adjusted significance level identified 22 potential risk loci that may be associated with recurrent vaginitis phenotype. Comparison of our results with previous studies provided nominal support for LBP (associated with immune response to vaginal bacteria) and PRKCH genes (possible role in keratinocyte differentiation and susceptibility to candidiasis).In conclusion, this study is the first highlighting a potential role of the vaginal epithelium in recurrent vaginitis.

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.

Polygenic risk scores for cervical HPV infection, neoplasia and cancer show potential for personalised screening: comparison of two methods.

The era of precision medicine requires the achievement of accurate risk assessment. Polygenic risk scores (PRSs) have strong potential for increasing the benefits of nationwide cancer screening programs. The current pool of evidence on the role of a PRS as a risk stratification model in actual practice and implementation is limited. To better understand the impact of possible method-induced variance, we constructed and validated two PRSs for cervical cancer (CC) using the Estonian Biobank female population (691 CC cases and 13,820 controls) and evaluated their utility in predicting incident cervical neoplasia (CIN), cancer, and human papillomavirus (HPV) infection using two methods (LDPred and BayesRR-RC). This study demonstrated that two genetic risk scores were significantly associated with CIN, CC, and HPV infection incidence. Independent of the method, we demonstrated that women with elevated PRS values reached the observed cumulative risk levels of CIN or CC much earlier. Our results indicated that the PRS-based discrimination rules could differ substantially when the PRSs contain similar predictive information. In summary, our analysis indicated that PRSs represent a personalized genetic component that could be an additional tool for cervical cancer risk stratification, and earlier detection of abnormalities provides invaluable information for those at high risk.

Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants.

The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.

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.

Pregnancy-Associated Bleeding and Genetics: Five Sequence Variants in the Myometrium and Progesterone Signaling Pathway are associated with postpartum hemorrhage.

Bleeding in early pregnancy and postpartum hemorrhage (PPH) bear substantial risks, with the former closely associated with pregnancy loss and the latter being the foremost cause of maternal death, underscoring the severity of these complications in maternal-fetal health. Here, we investigated the genetic variation underlying aspects of pregnancy-associated bleeding and identified five loci associated with PPH through a meta-analysis of 21,512 cases and 259,500 controls. Functional annotation analysis indicated candidate genes, HAND2, TBX3, and RAP2C/FRMD7, at three loci and showed that at each locus, associated variants were located within binding sites for progesterone receptors (PGR). Furthermore, there were strong genetic correlations with birth weight, gestational duration, and uterine fibroids. Early bleeding during pregnancy (28,898 cases and 302,894 controls) yielded no genome-wide association signals, but showed strong genetic correlation with a variety of human traits, indicative of polygenic and pleiotropic effects. Our results suggest that postpartum bleeding is related to myometrium dysregulation, whereas early bleeding is a complex trait related to underlying health and possibly socioeconomic status.

Genetic Risk Factors Associated With Preeclampsia and Hypertensive Disorders of Pregnancy.

Importance: A genetic contribution to preeclampsia susceptibility has been established but is still incompletely understood. Objective: To disentangle the underlying genetic architecture of preeclampsia and preeclampsia or other maternal hypertension during pregnancy with a genome-wide association study (GWAS) of hypertensive disorders of pregnancy. Design, Setting, and Participants: This GWAS included meta-analyses in maternal preeclampsia and a combination phenotype encompassing maternal preeclampsia and preeclampsia or other maternal hypertensive disorders. Two overlapping phenotype groups were selected for examination, namely, preeclampsia and preeclampsia or other maternal hypertension during pregnancy. Data from the Finnish Genetics of Pre-eclampsia Consortium (FINNPEC, 1990-2011), Finnish FinnGen project (1964-2019), Estonian Biobank (1997-2019), and the previously published InterPregGen consortium GWAS were combined. Individuals with preeclampsia or other maternal hypertension during pregnancy and control individuals were selected from the cohorts based on relevant International Classification of Diseases codes. Data were analyzed from July 2020 to February 2023. Exposures: The association of a genome-wide set of genetic variants and clinical risk factors was analyzed for the 2 phenotypes. Results: A total of 16 743 women with prior preeclampsia and 15 200 with preeclampsia or other maternal hypertension during pregnancy were obtained from FINNPEC, FinnGen, Estonian Biobank, and the InterPregGen consortium study (respective mean [SD] ages at diagnosis: 30.3 [5.5], 28.7 [5.6], 29.7 [7.0], and 28 [not available] years). The analysis found 19 genome-wide significant associations, 13 of which were novel. Seven of the novel loci harbor genes previously associated with blood pressure traits (NPPA, NPR3, PLCE1, TNS2, FURIN, RGL3, and PREX1). In line with this, the 2 study phenotypes showed genetic correlation with blood pressure traits. In addition, novel risk loci were identified in the proximity of genes involved in the development of placenta (PGR, TRPC6, ACTN4, and PZP), remodeling of uterine spiral arteries (NPPA, NPPB, NPR3, and ACTN4), kidney function (PLCE1, TNS2, ACTN4, and TRPC6), and maintenance of proteostasis in pregnancy serum (PZP). Conclusions and Relevance: The findings indicate that genes related to blood pressure traits are associated with preeclampsia, but many of these genes have additional pleiotropic effects on cardiometabolic, endothelial, and placental function. Furthermore, several of the associated loci have no known connection with cardiovascular disease but instead harbor genes contributing to maintenance of successful pregnancy, with dysfunctions leading to preeclampsialike symptoms.

Polygenic prediction of preeclampsia and gestational hypertension.

Preeclampsia and gestational hypertension are common pregnancy complications associated with adverse maternal and child outcomes. Current tools for prediction, prevention and treatment are limited. Here we tested the association of maternal DNA sequence variants with preeclampsia in 20,064 cases and 703,117 control individuals and with gestational hypertension in 11,027 cases and 412,788 control individuals across discovery and follow-up cohorts using multi-ancestry meta-analysis. Altogether, we identified 18 independent loci associated with preeclampsia/eclampsia and/or gestational hypertension, 12 of which are new (for example, MTHFR-CLCN6, WNT3A, NPR3, PGR and RGL3), including two loci (PLCE1 and FURIN) identified in the multitrait analysis. Identified loci highlight the role of natriuretic peptide signaling, angiogenesis, renal glomerular function, trophoblast development and immune dysregulation. We derived genome-wide polygenic risk scores that predicted preeclampsia/eclampsia and gestational hypertension in external cohorts, independent of clinical risk factors, and reclassified eligibility for low-dose aspirin to prevent preeclampsia. Collectively, these findings provide mechanistic insights into the hypertensive disorders of pregnancy and have the potential to advance pregnancy risk stratification.

Genetic effects on the timing of parturition and links to fetal birth weight.

The timing of parturition is crucial for neonatal survival and infant health. Yet, its genetic basis remains largely unresolved. We present a maternal genome-wide meta-analysis of gestational duration (n = 195,555), identifying 22 associated loci (24 independent variants) and an enrichment in genes differentially expressed during labor. A meta-analysis of preterm delivery (18,797 cases, 260,246 controls) revealed six associated loci and large genetic similarities with gestational duration. Analysis of the parental transmitted and nontransmitted alleles (n = 136,833) shows that 15 of the gestational duration genetic variants act through the maternal genome, whereas 7 act both through the maternal and fetal genomes and 2 act only via the fetal genome. Finally, the maternal effects on gestational duration show signs of antagonistic pleiotropy with the fetal effects on birth weight: maternal alleles that increase gestational duration have negative fetal effects on birth weight. The present study provides insights into the genetic effects on the timing of parturition and the complex maternal-fetal relationship between gestational duration and birth weight.

GWAS meta-analyses clarify the genetics of cervical phenotypes and inform risk stratification for cervical cancer.

Genome-wide association studies (GWAS) have successfully identified associations for cervical cancer, but the underlying mechanisms of cervical biology and pathology remain uncharacterised. Our GWAS meta-analyses fill this gap, as we characterise the genetic architecture of cervical phenotypes, including cervical ectropion, cervicitis, cervical dysplasia, as well as up to 9229 cases and 490 304 controls for cervical cancer from diverse ancestries. Leveraging the latest computational methods and gene expression data, we refine the association signals for cervical cancer and propose potential causal variants and genes at each locus. We prioritise PAX8/PAX8-AS1, LINC00339, CDC42, CLPTM1L, HLA-DRB1 and GSDMB as the most likely candidate genes for cervical cancer signals, providing insights into cervical cancer pathogenesis and supporting the involvement of reproductive tract development, immune response and cellular proliferation/apoptosis. We construct a genetic risk score (GRS) that is associated with cervical cancer [hazard ratios (HR) = 3.1 (1.7-5.6) for the top 15% vs lowest 15% of individuals], and with other HPV- and immune-system-related diagnoses in a phenome-wide association study analysis. Our results propose valuable leads for further functional studies and present a GRS for cervical cancer that allows additional risk stratification and could potentially be used to personalise the conventional screening strategies for groups more susceptible to cervical cancer.

Proteome-Wide Mendelian Randomization Identifies Causal Links Between Blood Proteins and Acute Pancreatitis.

BACKGROUND & AIMS: Acute pancreatitis (AP) is a complex disease and the leading cause of gastrointestinal disease-related hospital admissions. Few therapeutic options exist for AP prevention. Blood proteins with causal evidence may represent promising drug targets, but few have been causally linked with AP. Our objective was to identify blood proteins linked with AP by combining genome-wide association meta-analysis and proteome-wide Mendelian randomization (MR) studies. METHODS: We performed a genome-wide association meta-analysis totalling 10,630 patients with AP and 844,679 controls and a series of inverse-variance weighted MR analyses using cis-acting variants on 4719 blood proteins from the deCODE study (N = 35,559) and 4979 blood proteins from the Fenland study (N = 10,708). RESULTS: The meta-analysis identified genome-wide significant variants (P <5 × 10-8) at 5 loci (ABCG5/8, TWIST2, SPINK1, PRSS2 and MORC4). The proteome-wide MR analyses identified 68 unique blood proteins that may causally be associated with AP, including 29 proteins validated in both data sets. Functional annotation of these proteins confirmed expression of many proteins in metabolic tissues responsible for digestion and energy metabolism, such as the esophagus, adipose tissue, and liver as well as acinar cells of the pancreas. Genetic colocalization and investigations into the druggable genome also identified potential drug targets for AP. CONCLUSIONS: This large genome-wide association study meta-analysis for AP identified new variants linked with AP as well as several blood proteins that may be causally associated with AP. This study provides new information on the genetic architecture of this disease and identified pathways related to AP, which may be further explored as possible therapeutic targets for AP.

Advancing our understanding of genetic risk factors and potential personalized strategies for pelvic organ prolapse.

Pelvic organ prolapse is a common gynecological condition with limited understanding of its genetic background. In this work, we perform a genome-wide association meta-analysis comprising 28,086 cases and 546,291 controls from European ancestry. We identify 19 novel genome-wide significant loci, highlighting connective tissue, urogenital and cardiometabolic as likely affected systems. Here, we prioritize many genes of potential interest and assess shared genetic and phenotypic links. Additionally, we present the first polygenic risk score, which shows similar predictive ability (Harrell C-statistic (C-stat) 0.583, standard deviation (sd) = 0.007) as five established clinical risk factors combined (number of children, body mass index, ever smoked, constipation and asthma) (C-stat = 0.588, sd = 0.007) and demonstrates a substantial incremental value in combination with these (C-stat = 0.630, sd = 0.007). These findings improve our understanding of genetic factors underlying pelvic organ prolapse and provide a solid start evaluating polygenic risk scores as a potential tool to enhance individual risk prediction.