Background:Premenstrual disorder (PMD) and postpartum depression (PPD) have a strong phenotypic link and echo women's hormone fluctuations. Yet, the extent to which they may be cross-inherited remains poorly understood. Methods:Using the nationwide cohort of 907,841 women who born 1950-2007 and gave birth during 2001-2021 in Sweden, we estimated the cumulative incidence functions-based heritability and genetic correlation for PMD and PPD. We also analyzed genome-wide association study (GWAS) summary statistics from the largest European-ancestry cohorts for PMD (17,511 cases and 54,786 controls) and PPD (16,145 cases and 46,609 controls) using linkage disequilibrium score regression (LDSC). Fixed-effect cross-trait meta-analysis and imputed transcriptome-wide association analyses (TWAS) were conducted to identify shared loci and gene-tissue associations. Results:The register-based heritability was 0.35 (95% CI: 0.29-0.41) for PMD and 0.31 (95% CI: 0.23-0.37) for PPD, with a positive genetic correlation between these disorders (rg = 0.47, 95% CI: 0.25-0.69). LDSC also showed a positive genetic correlation between PMD and PPD (r g = 0.66, SE = 0.10, P = 1.014×10-10), indicating sizable shared heritable influences. Cross-trait meta-analysis identified two novel genome-wide significant loci jointly associated with PMD and PPD, mapping to an intronic region of PCDH9 and the 3' untranslated region of KCTD16. The KCTD16 locus implicates GABAB-mediated inhibitory signaling in both disorders. Consistent with this, TWAS revealed a hippocampus regulatory signal for KCTD16, with no detectable trend effects in other brain regions or peripheral tissues. Beyond the lead loci, TWAS suggested that the shared risk variants may partially act through genetically regulated gene expression across brain, endocrine and immune-related tissues. Conclusions:Together, these findings provide the first evidence for sizable genetic overlap between PMD and PPD and highlight novel and convergent biological mechanisms underlying the abnormal brain response of some women to gonadal hormone fluctuations.

Abstract Polygenic risk scores (PRSs) can effectively identify individuals at risk across various health conditions, yet their association with the gut microbiome remains uncharacterized. We systematically analyzed associations between 4,794 PRSs covering 615 traits and diseases and the gut microbiome within the Estonian Microbiome Cohort (N > 2,500). Microbiome diversity was associated with 62 distinct PRSs across 10 traits, indicating that genetic predisposition is linked to significant alterations in the microbiome composition. At the species level, 282 associations were identified across 100 PRSs for 34 traits, with triglyceride measurements, glucose regulation, and chronotype measurement PRSs showing the strongest signals. Mediation analysis suggests that the microbiome is altered by physiological changes linked to genetic risk but can also mediate this risk. These results help define early microbial biomarkers and explain inter-individual variability. The findings are accessible through the interactive Microbiome And Genomic Interaction (MAGI) Catalog to support future research.

We conducted genome-wide meta-analyses (N = 141,505; Estonian Biobank and Norwegian Mother, Father and Child Cohort Study) with polygenic score-based validation (N = 19,857; Dutch Lifelines cohort) of self-reported attention-deficit/hyperactivity disorder (ADHD) symptoms in adults from the general population. We identified eight genetic loci associated with either total symptoms, inattention or hyperactivity-impulsivity domains. Distinct genetic architectures underlying the two symptom domains were demonstrated by their moderate genetic correlation (r g =0.35, 95% CI 0.26 to 0.43) and by contrasting genetic association patterns across other phenotypes and medical conditions. Hyperactivity-impulsivity showed stronger genetic links with ADHD diagnosis, negative r g -s (-0.28 to -0.19) with educational traits, and more associations with diagnoses in electronic health records. Whereas inattention was weakly genetically associated with ADHD diagnosis, showed positive r g -s (0.24 to 0.29) with educational phenotypes, and fewer links with clinical outcomes. This is the first genome-wide study to detect significant signals associated with adult ADHD symptoms and symptom dimensions.

BACKGROUND:Placental histopathology provides important insights into maternal and fetal health, yet the organ's spatial heterogeneity poses significant challenges for objective and reproducible histological analysis. Systematic assessment of cellular and structural composition across placental slides remains limited by the scale and subjectivity of manual evaluation. Quantitative approaches are therefore needed to characterise placental responses to injury beyond visually apparent lesions. METHODS:We applied the Histology Analysis Pipeline.PY (HAPPY), a biologically inspired hierarchical deep learning framework for quantitative single-cell-resolution analysis of Haematoxylin and Eosin (H&E) slides, to 130 placental parenchyma slides from 62 singleton full-term live births. The dataset included healthy normal controls and four common placental lesion types: infarction, perivillous fibrin, avascular villi, and intervillous thrombosis. Cell-type and tissue-structure compositions were quantified, and slide-level deviation from a healthy reference was assessed using compositional data analysis. RESULTS:Placental slides with lesions exhibited significant cellular composition differences compared with healthy controls, including increased extravillous trophoblast and leukocyte densities and decreased Hofbauer cell densities. These cellular changes were accompanied by tissue-level alterations, particularly increased fibrin deposition and changes in villous structure. Compositional deviation increased with infarction size but not with other lesion types. Notably, compositional differences were also detected in slides without an apparent lesion from placentas with lesion(s) elsewhere, indicating organ-wide responses extending beyond focal pathology. CONCLUSIONS:Quantitative deep phenotyping reveals widespread cellular and structural changes associated with placental lesions, including effects not evident on routine histological assessment. These findings demonstrate the potential of AI-based digital histology to complement conventional placental pathology in research and clinical settings.

Health research increasingly relies on observational datasets that capture systematically different patient populations, affecting the representativeness, comparability, and transportability of study findings. Yet these differences are rarely quantified across clinical domains or explored interactively, and the workflow for pairwise dataset comparison remains fragmented. We present Syrona, a visual analytics workflow for systematic pairwise comparison of datasets and subcohorts on the OMOP Common Data Model. Syrona extracts annual prevalence for conditions, procedures, and drugs from any OMOP CDM database, computes prevalence ratios across demographic strata, and synthesizes them via multilevel meta-analysis. A coordinated dashboard - distributional overviews, stratified heatmaps, forest plots, and absolute prevalence comparisons - enables interactive exploration driven by domain-adaptive SNOMED CT and ATC filtering. Three case studies on Estonian national health data (495,000 persons, 2012-2024) demonstrate how the workflow supports representativeness assessment, institutional practice comparison, and coding artifact detection. Syrona is open-source and applicable to any OMOP CDM database. Explore the demo at: http://omop-apps.cloud.ut.ee/ShinyApps/Syrona/ ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the Estonian Research Council (PRG1844, PRG2078, PSG809, PSG1216, PRG1414, PRG1291). The study was funded by the European Union and co-funded by the Ministry of Education and Research (TEM-TA72). The European Union funded the project under its Horizon Europe research and innovation programme (grant agreement No 101060011, TeamPerMed) and co-funded the research through the European Regional Development Fund (Project No. 2021-2027.1.01.24-0444). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. This work was also supported by the Estonian Centre of Excellence in Artificial Intelligence (EXAI), the Estonian Centre of Excellence in Personalised Medicine (CEPM), and the Center of Excellence for Well-Being Sciences (EstWell) funded by the Estonian Ministry of Education and Research grants TK213, TK214, and TK218 respectively. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This work was approved by the Estonian Bioethics and Human Research Council (1.1-12/653, 1.1-12/1039) and the Ethics Committee of University of Tartu (401/T-34). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced are available online at https://github.com/MaarjaPajusalu/Syrona/

Polycystic ovary syndrome (PCOS) and its underlying features remain poorly understood. In this genetic study (n = 544,513), we expand the number of genetic loci from 16 to 29, and additionally identify 31 associated plasma proteins. Many risk-increasing loci were associated with later age at menopause, underscoring the reproductive longevity related to an increased oocyte number and/or availability across the lifespan. Hormonal regulation in the etiology of this condition, through metabolic and reproductive features, was emphasized. The proteomic analysis highlighted metabolic biology known to be related to PCOS. A polygenic risk score (PRS) was associated with adverse cardiometabolic outcomes, with differing relevance of testosterone and body mass index in women and men. Finally, while oligo-anovulation and anovulatory infertility are features of PCOS, we observed no impact of PCOS susceptibility on childlessness. We suggest that PCOS susceptibility confers balanced pleiotropic influences on fertility in women, and life-long adverse metabolic consequences in both sexes.

Abstract Female genital tract (FGT) polyps are common benign growths affecting up to half of all women. However, they carry malignant potential, and their genetic architecture remains poorly defined. We conducted a genome-wide association study (GWAS) meta-analysis across four biobanks (48,400 cases, 477,134 controls), identifying 26 risk loci for FGT polyps, 12 of which were previously unreported. Integrative gene prioritisation highlighted 193 candidate genes, revealing a potential convergent biological mechanism: where germline variation in DNA replication and maintenance (e.g., PRIM1 , TERT and HMGA1 ) compromises genomic stability in the context of hormone-driven proliferation (e.g., ESR1 and GREB1 ). This susceptibility is further modulated by metabolic drivers of estrogen biosynthesis, underscored by specific adiposity-related loci (e.g. RSPO3 and PLCE1 ) and the aromatase gene CYP19A1 . Mendelian randomisation demonstrated bidirectional causal relationships with endometriosis and fibroids, and endometrial cancer. Leveraging the shared genetic architecture of FGT polyps and other gynaecological disorders via multi-trait analysis revealed an additional 26 loci, validating sub-threshold regions encompassing HMGA1 and GREB1. In total, 52 risk loci were identified (36 novel), 39 of which replicated in an independent cohort. These findings reframe polyps not merely as local gynaecological overgrowths but as manifestations of a systemic proliferative syndrome characterised by dysregulated genome stability and estrogen signalling, which may also impact malignant transformation.

Abstract Educational attainment (EA) is strongly associated with fertility, yet the mechanisms underlying this relationship remain poorly understood. Using data from ∼40,000 women and ∼10,000 men in the Estonian Biobank, we examine sex-specific associations between EA polygenic scores ( PGS EA ) and completed fertility. The PGS EA captures an individual’s genetic predisposition to completing higher levels of education, and can also be constructed separately for cognitive and non-cognitive EA components. We find that PGS EA is negatively associated with fertility among women, with a significantly stronger association for the non-cognitive than the cognitive EA polygenic score. The association of PGS EA with fertility is only partly explained by EA and is moderated by EA and reproductive timing, changing sign across age-at-first-pregnancy strata. Within-family estimates are not attenuated relative to population estimates, consistent with a predominant role of direct genetic effects. Among men, associations between PGS EA and fertility are non-significant or slightly positive. Overall, education-related genetic variation is associated with fertility through pathways largely independent of EA, operating through sex-specific and timing-dependent mechanisms. These results contribute to our understanding of the micro-level mechanisms shaping macro-level demographic change.

Muscle mass is central to physical function and metabolic health 1 , but can decrease with disease, aging 2 and weight loss interventions 3-5 . As such interventions become more widely used, agents that preserve or increase muscle mass are needed. To identify such therapeutic opportunities, we performed genome-wide association meta-analyses (GWAS) of arm, leg, trunk and total lean mass measured by dual-energy X-ray absorptiometry (DXA), a widely used method to estimate muscle mass. We identified 63 loci, including the rare missense variant in MSTN (p.Ile225Thr, rs143242500), which had the largest effect on leg lean mass (β = 0.28 SD [95% CI: 0.19, 0.37], P = 1.9 × 10 -9 ). MSTN encodes myostatin, a negative regulator of skeletal muscle mass and a therapeutic target for muscle wasting disorders 6 . p.Ile225Thr is the first genome-wide significant association in MSTN in humans with functional consequences and could provide further insight into long-term systemic effects of myostatin inhibition.

Hirsutism is a condition characterized by excessive hair growth in women, with a prevalence of 5-10 %. The diagnostic criteria usually include hair appearing in male-pattern areas, such as the face, abdomen, and chest. The contributing factors for hirsutism symptoms are heterogeneous and vary from genetic and ethnic backgrounds to diverse endocrinological causes, most commonly polycystic ovary syndrome. In this cross-ancestry GWAS, including 4834 cases and 352,966 controls, we explored the genetic background of hirsutism and identified 7 loci associated with the condition, 4 of which have not, to our knowledge, been previously reported in GWAS. To capture low-frequency variants, we analyzed the Finnish FinnGen cohort separately, leveraging its bottleneck history, which enriches for rare variants with larger effects. A missense variant, rs199649605 (effect allele frequency = 0.005), enriched in the Finnish population near FGF5, a gene regulating the hair follicle cycle, showed a particularly strong effect (P = 1.39 × 10-10, OR = 5.02, 95 % confidence interval = 3.06-8.21). Genetic correlation analyses revealed a shared genetic architecture between hirsutism, polycystic ovary syndrome, and metabolic traits such as obesity and type 2 diabetes. These findings uncover genetic contributors to hirsutism beyond polycystic ovary syndrome, suggesting that both androgen-dependent and independent mechanisms underlie excessive hair growth in women.

Most pregnancies are affected by nausea and vomiting, but the most severe form-hyperemesis gravidarum-can be life threatening. Here we performed a multi-ancestry genome-wide association study of hyperemesis gravidarum in 10,974 cases and 461,461 controls across European, Asian, African and Latino ancestries. We identified ten associations: four identified previously (GDF15, IGFBP7, PGR and GFRAL) and six additional loci (SLITRK1, SYN3, IGSF11, FSHB, TCF7L2 and CDH9). Downstream analyses revealed GDF15 and TCF7L2 expression primarily in extravillous trophoblasts, with opposing effects for GDF15 between maternal and fetal genotype. Conversely, IGFBP7 and PGR were expressed primarily in maternal spiral arteries, with effects limited to the maternal genome. Selected loci were associated with abnormal pregnancy weight gain, duration, birth weight and pre-eclampsia. Functional studies identified additional associations including antisense IGFBP7-AS1 and protein ACP1. Potential roles for candidate genes in appetite, insulin signaling and brain plasticity provide pathways to explore etiological mechanisms and therapeutic avenues.

Intrahepatic cholestasis of pregnancy, which affects 0.2-2% of pregnancies, is characterized by pruritus, increased aminotransferase activity and elevated serum bile acids. Previous studies have implicated liver-enriched genes in intrahepatic cholestasis of pregnancy. We conducted a meta-analysis of intrahepatic cholestasis of pregnancy genome-wide association studies in the FinnGen study, deCODE, Estonian Biobank, the Danish Blood Donor Study and Copenhagen Hospital Biobank with 4,738 women with prior ICP and 436,834 female controls. The analysis found 26 genome-wide significant associations of which 10 were novel. Genes in the associated loci were prioritized using lead SNP expression quantitative trait loci associations and colocalization analysis to assess potential causality. The associated loci implicate bile acid synthesis, LDL cholesterol, and lipid metabolism. Additionally, comorbidity, genetic correlation and polygenic risk score analyses further indicated a link between intrahepatic cholestasis of pregnancy and pancreatitis, suggesting shared genetic underpinnings.

Background Hormonal contraceptives (HCs) are widely used and have well-documented population-level statistics. Previous studies with short follow-ups have focussed on individual HC use and side effects. However, the same aspects over longer periods, HC formulation switching, and the impact of genetic factors on HC side effects remain understudied due to the limited availability of suitable datasets. We investigated whether the Estonian Biobank (EstBB) is suitable for studying genetic risk for HC side effects. Methods and findings This is a longitudinal descriptive study combining prescribed HC purchase data collected from 2004 to 2022 with genetic and health data from 73,071 female EstBB HC users aged 15-55 at the time of purchase. HC usage was defined by the Anatomical Therapeutic Chemical (ATC) codes G02B, G03A, and G03HB01. Methods included calculating age-stratified annual user prevalence, inferring usage periods from purchases, assessing formulation switching, identifying the International Classification of Diseases, Tenth Revision (ICD-10)-based side effect-related diagnoses and thromboembolism risk factors, and assessing carrier status for Factor V Leiden (FVL, rs6025) and prothrombin G20210A (PTM, rs1799963) genetic variants as proof-of-concept. Over 19 years, 20 HC formulations with five administration routes (oral pills, transdermal patches, vaginal rings, subdermal implants, intrauterine devices) were used. In the EstBB, combined HCs were the most commonly used among users aged 15-29, while progestin-only HC use increased with age and over time, comparable to the Estonian population. Overall, 64.2% (n = 46,920) of users switched formulations at least once, with 17.7% (n = 12,929) being rapid switchers. Side effect-related diagnoses were observed in 23.1% (n = 2,982) of rapid switchers, with excessive/irregular menstrual bleeding being the most common. Genetic analysis revealed that 5.3% (n = 3,886) of users carried at least one variant previously associated with increased thrombosis risk (3.5% (n = 2,556) carried FVL only, 1.8% (n = 1,276) PTM only, and 0.07% (n = 54) both). Carriers of thrombosis-associated variants had a significantly higher percentage of thrombosis (6.5%) than non-carriers (4.2%; OR = 1.61, 95% CI [1.40, 1.84], p < 0.001). The study is limited by the use of administrative medication purchase records, which may not reflect actual HC use. Additionally, diagnoses identified near the HC usage period may not represent true side effects. Conclusions This study provides insights into real-world HC usage with longitudinal, individual-level detail that is not available in population-level statistics. We show that EstBB has a robust dataset for studying the impact of genetic factors on HC side effects and disease risk. The identified HC user profiles offer a framework for genetic analyses of HC rapid switching and discontinuation. Our approach can be replicated in other biobanks to validate findings across populations.

Abstract Rheumatoid arthritis (RA) remains incompletely understood, limiting targeted prevention. In this work, genome-wide association study meta-analyses were performed for RA and seropositive RA, comprising approximately one million participants of European ancestry. Eight and six novel genomic risk loci were defined for RA and seropositive RA, and candidate causal genes were identified, highlighting relevant biological pathways, including established immune pathways and estrogen metabolism. Novel disease-specific polygenic risk scores (PRSs) were constructed, enhancing predictive performance over clinical risk factors (incremental C-statistics of 2.7 and 5.1 for RA and seropositive RA, respectively). In parallel, integrating metabolomic data into high-dimensional models enhanced risk stratification over models based on clinical risk factors and genomics, particularly for seropositive RA, where the hazard ratio of the highest decile increased from 4.869 to 5.697. These findings expand the understanding of genetic factors underlying RA and support the value of including PRSs in risk assessment, while suggesting metabolomic integration may further enhance risk stratification, particularly for seropositive RA.

Eating disorders (EDs) affect 2%–5% of the population, while subclinical symptoms are more prevalent. Previous diagnosis-based genome-wide association studies (GWASs) identified risk variants, but the genetic architecture of ED symptoms in the general population remains unclear. Using the five-item SCOFF screening tool, we conducted six GWASs in the Estonian Biobank (EstBB; N = 212,000): one for higher ED risk and one for each SCOFF item. We estimated genetic correlations with 59 external phenotypes, evaluated polygenic risk scores (PRSs) for uncontrolled eating in an independent subsample, and performed phenome-wide association studies (PheWAS) linking genetic risk to medical diagnoses. We found 14 independent genome-wide significant SNPs associated with increased ED risk and cognitive-behavioral symptoms like loss of control and food dominates , with SNP heritability ranging from 2% to 8%. Notably, variants in FTO and MC4R were linked to both higher ED risk and cognitive-behavioral symptoms , while ROBO2 and TMEM18 correlated with higher ED risk and loss of control , highlighting appetite regulation pathways. Cognitive-behavioral symptoms exhibited moderate-to-strong genetic correlations with anthropometric, psychiatric, lifestyle, personality, and somatic traits. PheWASs identified associations between PRSs of ED symptoms and medical conditions (28, 27, and 24 significant associations for higher ED risk , loss of control , and food dominates , respectively), mainly cardiometabolic. All PRSs predicted uncontrolled eating in the independent subsample. Our findings suggest genetic liability and health burden related to ED symptoms in the general population are predominantly driven by cognitive-behavioral than weight-compensatory symptoms. Symptom-based approach could complement current diagnosis-based methods and lead towards improved intervention and prevention.

INTRODUCTION:Cesarean section (CS) is the most common gynecological surgery globally, with rates increasing in many developed countries. In Estonia, the CS rate rose from 6.4% in 1992 to 20.6% in 2021. While CS can be lifesaving when medically necessary, its rising use without clear medical indication does not have benefits for the mother but is associated with a broad spectrum of long-term complications, including uterine rupture, abnormal placentation, ectopic pregnancy, abnormal uterine bleeding, and chronic pelvic pain. The Estonian Biobank (EstBB) is a population-based biobank that links genetic data with health records from national registries. Between 2007 and 2023, over 200 000 individuals were recruited, providing a valuable dataset for health and genetics research. This study examines maternal health conditions occurring both before and after childbirth, including short- and long-term outcomes associated with CS and vaginal delivery (VD). MATERIAL AND METHODS:We analyzed EstBB health data using International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) codes to compare short- and long-term maternal health conditions occurring before and after childbirth between women with one or more VD (ICD-10 O80, n = 30 898) and women with one or more CS (ICD-10 O82, n = 8285). Women with a history of both VD and CS were excluded. Logistic regression assessed associations between delivery mode and health conditions, adjusting for maternal birth year and body mass index. RESULTS:As expected, the CS group had higher rates of comorbidities and pregnancy complications like gestational diabetes, hypertensive disorders, mental health issues, and possible postsurgical morbidities such as infections, incisional hernia, and chronic pain. In the VD group, conditions like perineal trauma, pelvic organ prolapse, and stress urinary incontinence were more prevalent. Interestingly, cervical inflammatory conditions and cervical dysplasia were also more common in the VD group. CONCLUSION:CS is related to more complications and health problems compared with VD, but the relationship may not be causative. CS risks should be weighed against clinical indications for its use. It is important for healthcare providers to recognize and openly discuss both the immediate and long-term risks associated with the procedure with women requiring or considering CS.

Gestational diabetes mellitus (GDM) affects ~14% of pregnancies and increases maternal type 2 diabetes mellitus (T2DM) risk. The GenDiP Consortium presents trans-generational, multi-ancestry genome-wide association study meta-analyses of GDM and pregnancy glycemic traits in up to 38,305 GDM cases and 776,145 controls. We identify 37 GDM-associated loci (7 novel) and five novel loci for pregnancy glycemic traits, all operating through the maternal genome. We classify 12 GDM variants with stronger effects in GDM than T2DM into five biologically informed categories, revealing pleiotropy patterns, pregnancy-dependent effect modification, and diagnostic heterogeneity. While all these loci overlap with T2DM and/or non-pregnant glycaemic traits, four (G6PC2, CAST-PCSK1, HKDC1, FOXA2) lack genome-wide-significant T2DM associations; GCK shows distinct causal variants for GDM, and MTNR1B exhibits pregnancy-amplified effects. Our findings provide new genetic insights into GDM and highlight the need for larger, ancestrally diverse studies of GDM and glycaemic traits during pregnancy to understand potential pregnancy-specific effects.

Hypertensive disorders of pregnancy are a leading cause of maternal and fetal morbidity and mortality, with preeclampsia (PE) affecting ∼5% of pregnancies worldwide. Both maternal and fetal genomes influence PE risk, but their relative contributions remain unclear. We conducted a meta-analysis of genome-wide association studies assessing maternal and fetal genetic effects on PE, including 401,597 maternal and 435,076 fetal samples. We identified 27 independent PE-associated variants, comprising 12 novel and 3 fetal-specific loci. Maternal and fetal genetic effects were independent, potentially reflecting opposing selective pressures on maternal versus fetal determinants of PE. Most heritable risk arose from maternal variants linked to blood pressure regulation, adiposity, and immune tolerance. Causality analyses supported roles of maternal body mass index and lipid levels in PE susceptibility. In contrast, fetal factors predisposing to PE were associated with increased risk of psychiatric disorders in adulthood, but positive effects on reproductive success. Collectively, these findings delineate distinct maternal and fetal genetic architectures underlying PE and highlight divergent biological pathways contributing to PE risk.