Background and Aims To elucidate the genetic architecture of blood pressure (BP) and heart rate (HR) during early life and assess their potential relevance to adult health outcomes.Methods The largest genome-wide association study (GWAS) meta-analyses to date of childhood systolic BP, diastolic BP, pulse pressure, and mean arterial pressure (n = 28 425) and HR (n = 22 565) were conducted in children of European ancestry aged 4-17 years. Follow-up analyses included comparisons with adult GWAS results, polygenic risk score (PRS) analyses in independent cohorts of diverse ancestries, and a phenome-wide association study in the UK Biobank.Results Eight genome-wide significant loci were identified for childhood BP (KIAA2013, CACNB2, PLCE1, PAX2, COL4A2, RP11-236L14.1, CFDP1, TPX2) and three loci for childhood HR (CCDC141, ACHE, MYH6); all novel in children but previously reported in adults. Childhood PRSs explained up to 1.6% of BP variance and 5.2% of HR variance among children of European ancestry. Genetic correlations between childhood and adulthood BP traits were moderate (rg = 0.4-0.7), suggesting age-specific genetic effects on BP. In the UK Biobank, higher childhood BP PRS levels were significantly associated with a broad range of adult health outcomes, particularly cardiometabolic outcomes such as hypertension, angina, myocardial infarction, and cardiovascular disease-related mortality.Conclusions These findings advance the understanding of the genetic architecture of childhood BP and HR and provide compelling genetic evidence linking childhood BP to a broad spectrum of adult health outcomes-particularly cardiometabolic conditions-which may inform targeted prevention strategies from a young age.

Gain-of-function mutations in SCN9A, encoding the voltage-dependent Nav1.7 sodium channel, cause three autosomal-dominant disorders associated with severe pain: primary erythromelalgia, paroxysmal extreme pain disorder (PEPD), and small fiber neuropathy. On the other hand, biallelic loss-of-function mutations have been linked to impaired pain perception. Notably, the coexistence of both hyperalgesia and hypoalgesia within the same patient harboring the I234T variant has been reported in three independent patients to date. We report a 7-year-old girl harboring co-occurring SCN9A (I234T) and PRRT2 variants who presented with paroxysmal extreme pain disorder, contradictory analgesia, sensitivity to heat, and intractable head-drop attacks. Based on the genetic and clinical analyses, she was diagnosed as having PEPD and PRRT2-related paroxysmal dyskinesia. The intractable head-drop attacks were considered as paroxysmal non-kinesigenic dyskinesia. In addition, she exhibited easy fatigability and hypotonia. Taken together with her cold, cyanotic feet, these findings suggest that she may have also had small fiber neuropathy.

In Japan, the adoption rate of electronic medical records (EMR) in general hospitals has surpassed 50%, leading to the rapid digitization of medical information. However, core components such as clinical notes and nursing records remain accumulated as unstructured data in "natural language" (free text). Consequently, their secondary utilization relies heavily on human interpretation, presenting significant challenges. This paper details the development and utility of a system that automatically generates high-precision patient summaries from EMR free text, leveraging large language models (LLMs) and retrieval-augmented generation (RAG) technologies, which have undergone dramatic evolution in recent years. We developed a medical-specific LLM trained on data accumulated at Tohoku University Hospital and conducted demonstration experiments on: 1) the automated generation of discharge summaries from nursing records, and 2) the extraction of complex cases based on clinical trial eligibility criteria. The results demonstrated that the LLM generated summaries of quality comparable to those created by nurses, suggesting the potential for significant improvements in the efficiency of documentation tasks. Furthermore, in the context of drug discovery support, the system successfully identified cases meeting complex clinical conditions that were impossible to extract using conventional search methods. However, the risk of hallucinations inherent in generative AI was also confirmed, making human oversight (human-in-the-loop) indispensable for clinical implementation.

Polygenic risk scores (PRSs) are typically constructed under the assumption of a single, homogeneous disease phenotype. However, many common diseases exhibit considerable clinical heterogeneity and encompass multiple subtypes with distinct etiologies and clinical characteristics. As a result, conventional PRSs often overlook differences in underlying biological pathways among disease subtypes, consequently limiting predictive accuracy and cross-ancestry transferability. To address this challenge, we propose the palette PRS, a framework that integrates a set of partitioned polygenic scores (pPSs) for biologically interpretable pathways with subtype-specific weights. This approach can flexibly capture the relative contributions of multiple pathways within each individual and provides a unified risk score. We applied this framework to type 2 diabetes (T2D), a clinically highly heterogeneous disease. For T2D, previous machine learning-based studies have identified four distinct subtypes and 12 biologically interpretable pathways derived from 650 genome-wide significant variants. Building on these established findings, we employed an elastic net model incorporating subtype membership probabilities to derive subtype-optimized palette PRS through the weighted integration of the pPSs of these 12 pathways. Our palette PRS showed superior predictive performance, with particularly high accuracy for the severe insulin-deficient diabetes (SIDD) subtype (AUC=0.744), compared with both conventional T2D PRS (AUC = 0.661) or subtype-stratified GWAS-based PRS (AUC = 0.547). Moreover, our palette PRS exhibited substantial cross-ancestry transferability between East Asian and European populations. This strategy represents a major step toward clinically actionable, subtype-optimized risk prediction and personalized prevention in T2D worldwide. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by JSPS KAKENHI (Grant Number JP24K13523), the JST Moonshot R&D Program (Grant Number JPMJMS2023), the Tohoku Medical Megabank Project at Tohoku University (Grant Number JP21tm0124005), AMED (Grant Number JP22tm0424224), and RIKEN AIP through the subsidy for the Advanced Integrated Intelligence Platform project of MEXT, Japan. ### 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 multi-center study was centrally approved by the Institutional Ethics Review Board of the Tohoku University Tohoku Medical Megabank Organization, and the protocol was conducted in accordance with the Declaration of Helsinki. 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 Individual-level data from Japanese cohorts are not publicly available due to ethical restrictions. The UKBB analysis was conducted under application number 76615 (https://www.ukbiobank.ac.uk). GWAS summary statistics used in the calculation of the T2D PRS were obtained from dbGaP under accession number phs001672.v3.p1 (Veterans Administration Million Veteran Program Summary Results from Omics Studies). Subtype-stratified GWAS summary statistics from the study by Mansour Aly et al [21] are publicly available in the GWAS Catalog (www.ebi.ac.uk/gwas/) under accession numbers GCST90026413-GCST90026417. Data from the NHANES III cohort is also publicly available at (https://wwwn.cdc.gov/nchs/nhanes/Default.aspx)

Social isolation, characterized by a lack of social connections with family, friends, and others, is associated with adverse health outcomes. However, the genetic contribution to the susceptibility to social isolation remains unclear. This study aimed to identify genetic loci associated with social isolation using the Lubben Social Network Scale (LSNS-6) in a Japanese population. The Tohoku Medical Megabank Community-Based Cohort Study was conducted between 2013 and 2016. The participants were genotyped using the Affymetrix Axiom Japonica Array. The LSNS-6 was used to assess familial and friend ties through six questions and social isolation statuses were defined using the total scale, family subscale, and friend subscale. Genome-wide association studies (GWASs) were conducted using a generalized linear mixed model, adjusting for age, sex, 10 genetic principal components and batch effects. In total, 63,497 participants who completed genotyping and the LSNS-6 were included. The mean age was 59.4 ± 11.9 years, and 41,126 (64.8%) were female. Significant genetic loci were identified in GWASs for the total scale (rs10736933 near ACADSB and HMX3) and friend subscale of LSNS-6 (rs1778366 near LINC02315 and LRFN5). This study provides the first genome-wide evidence of social isolation in the Japanese population, suggesting associations with ACADSB, HMX3, LINC02315, and LRFN5. These findings could enable personalized prevention and intervention for social isolation and related psychiatric disorders.

Our understanding of the biological role of the Y chromosome remains limited. Here, we systematically profile germline Y haplogroups and somatic loss of the Y chromosome (LOY) in 122,683 East Asian males from BioBank Japan and 181,472 European males from the UK Biobank. A phenome-wide scan uncovers male-specific genetic regulation of complex traits, including pleiotropic effects of the Japanese-specific haplogroup D on height and type 2 diabetes (T2D). LOY increases T2D risk in East Asians but is associated with reduced T2D risk in Europeans. In East Asians, LOY contributes to T2D incidence particularly among males with lower polygenic risk scores, providing a compensatory explanation for disease risk beyond germline genetics. Incorporating sex-chromosome variation improves polygenic prediction of T2D risk in both sexes. Single-cell analyses reveal cell type-specific accumulation of LOY across tissues and disease contexts, with LOY in pancreatic β cells potentially impairing glucose metabolism. Our study demonstrates the clinical relevance of Y chromosome variation for diabetes risk prediction and management.

Myasthenia gravis (MG) is an autoimmune disorder characterized by impaired neuromuscular transmission and motor symptoms. Its genetic background remains unclear, particularly beyond specific subtypes reported in European populations. Here, we perform a genome-wide association study (GWAS) of 1,434 MG cases covering all disease subtypes and 42,913 controls of Japanese, which newly identify the TERT locus (odds ratio [OR] = 1.31, P = 1.7×10-10). Subtype-stratified GWASs show stronger signals for generalized MG (gMG; OR = 1.38, P = 1.6×10-12), anti AChR antibody-positive gMG (g-AChR-Ab(+)MG; OR= 1.49, P = 2.1×10-15), and thymoma-associated gMG (g-TAMG; OR = 1.92, P = 1.1×10-15). Fine-mapping of the major histocompatibility complex region reveal distinct associations of HLA-DRB1 with late onset gMG (g-LOMG) and HLA-A with early onset gMG (g-EOMG). The MG risk TERT lead variant rs2736099 is associated with poor treatment response, especially in g-AChR-Ab(+)MG and g-EOMG (P < 0.0042). The biobank-based phenome-wide association study identify pleiotropic effects on lung cancer, hematological traits, and telomere length. Single cell transcriptomics and immunohistochemistry identified immature lymphocyte-specific TERT expression in thymoma specimens. Full-length transcriptomics reveal allele-specific decreasing effect of rs2736099-A on TERT expression. Our study unveils genetics of MG distinctly across disease subtypes, and involvement of TERT in its pathogenesis.

Here we present the construction of JG2, an updated population-specific reference genome for the Japanese population. Utilizing data from three individuals previously used in the construction of JG1, several methodologies were employed to enhance genomic coverage and assembly quality. Hi-C sequencing technology facilitated phase-aware assembly, generating two haploid assemblies per individual and enabling improved representation of genetic variation. A meta-assembly strategy and a majority decision approach further refined assembly quality by combining the best sequences from multiple assemblies and minimizing the inclusion of rare variants. The resulting JG2 genome comprises chromosome-level sequences, mitochondrial chromosomes and unplaced scaffolds, offering more comprehensive coverage of the Japanese genome. Comparative analyses with other reference genomes demonstrated the accuracy and representativeness of JG2, highlighting its utility for genetic research involving the Japanese population. Overall, by adopting the phased assembly technique, JG2 represents a substantial advancement over the collapsed assembly-based JG1, with improvements including a greater number of identified variants (3,115,695 variants, of which 298,644 had an allele frequency (AF) of 1.0 in the 3.5KJPNv2 AF panel) and a higher N50 value (152,668,378 bp). These enhancements provide researchers with a more precise and comprehensive resource for understanding the genetic landscape of the Japanese population. The sequences and annotations are available on the jMorp website ( https://jmorp.megabank.tohoku.ac.jp/ ). Scientists have developed a new Japanese reference genome called JG2 to better understand the genetic makeup of the Japanese population. The previous version, JG1, had some limitations, so researchers aimed to improve it. The team used advanced techniques to create JG2 from the DNA of three Japanese men. They used a method called phased assembly and Hi-C data to build more accurate genome sequences. Researchers combined data from different technologies, such as PacBio and Oxford Nanopore, to create a comprehensive genome. This approach helped them capture more genetic variations specific to the Japanese population. JG2 showed fewer errors and better represented common genetic features compared with JG1. The study concluded that JG2 is a substantial improvement over JG1, providing a more accurate tool for studying Japanese genetics. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

Gestational diabetes mellitus (GDM) is common in Japanese women, posing serious risks to mothers and offspring. This study investigated the influence of maternal genotypes on the risk of GDM and examined how these genotypes modify the effects of psychological and dietary factors during pregnancy. We analyzed data from 20,399 women in the Tohoku Medical Megabank Project Birth and Three-Generation Cohort. Utilizing two customized SNP arrays for the Japanese population (Affymetrix Axiom Japonica Array v2 and NEO), we performed a meta-analysis to combine the datasets. Gene-environment interactions were assessed by modeling interaction terms between genome-wide significant single nucleotide polymorphisms (SNPs) and psychological and dietary factors. Our analysis identified two SNP variants, rs7643571 (p = 9.14 × 10-9) and rs140353742 (p = 1.24 × 10-8), located in an intron of the MDFIC2 gene, as being associated with an increased risk of GDM. Additionally, although there were suggestive patterns for interactions between these SNPs and both dietary factors (e.g., carbohydrate and fruit intake) and psychological distress, none of the interaction terms remained significant after Bonferroni correction (p < 0.05/8). While nominal significance was observed in some models (e.g., psychological distress, p = 0.04), the data did not provide robust evidence of effect modification on GDM risk once adjusted for multiple comparisons. These findings reveal novel genetic associations with GDM in Japanese women and highlight the importance of gene-environment interactions in its etiology. Given that previous genome-wide association studies (GWAS) on GDM have primarily focused on Western populations, our study provides new insights by examining an Asian population using a population-specific array.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interactions. There is an urgent need to establish objective, simple, and accurate screening and diagnostic methods for ASD in childhood. Recently, the ability to visualize and quantify eye movements has emerged, suggesting that ASD may exhibit characteristic gaze patterns. To examine the potential of gaze patterns as an early marker of ASD, we analyzed the relationship between gaze patterns at ages 4-6 and individual ASD characteristics, as determined by the Autism Spectrum Quotient Japanese version for children (AQ-J-child) at age 6, using data from 4- to 6-year-old children recruited into the BirThree Cohort Study of the Tohoku Medical Megabank Project. The median gaze rate, which represents the percentage of time the subjects spent looking at the screen during the test, was 92%, reflecting the highly versatile nature and proper execution of this test in our study. We found that children with social impairment tend to prefer looking at geometric patterns. In addition, children with communication difficulties tend to spend less time looking at the eyes in still images of human faces. Our analyses of the relationships between various gaze results and ASD characteristics defined by AQ-J-child revealed that specific gaze preferences are significantly associated with communication difficulties, social impairment, and impaired imagination. These findings indicate that the gaze measurement results show strong correlations with specific aspects of ASD. Therefore, gaze patterns demonstrate the potential to reflect one aspect of ASD.

Biological mechanisms underlying multimorbidity remain elusive. To dissect the polygenic heterogeneity of multimorbidity in twelve complex traits across populations, we leveraged biobank resources of genome-wide association studies (GWAS) for 232,987 East Asian individuals (the 1st and 2nd cohorts of BioBank Japan) and 751,051 European individuals (UK Biobank and FinnGen). Cross-trait analyses of respiratory and cardiometabolic diseases, rheumatoid arthritis, and smoking identified negative genetic correlations between respiratory and cardiometabolic diseases in East Asian individuals, opposite from the positive associations in European individuals. Associating genome-wide polygenic risk scores (PRS) with 325 blood metabolome and 2917 proteome biomarkers supported the negative cross-trait genetic correlations in East Asian individuals. Bayesian pathway PRS analysis revealed a negative association between asthma and dyslipidemia in a gene set of peroxisome proliferator-activated receptors. The pathway suggested heterogeneity of cell type specificity in the enrichment analysis of the lung single-cell RNA-sequencing dataset. Our study highlights the heterogeneous pleiotropy of immunometabolic dysfunction in multimorbidity.

Family history of hypertension may reflect genetic and lifestyle factors. Genetic risk can be assessed using polygenic risk score (PRS); however, whether PRS can stratify hypertension risk when combined with family history and lifestyle information is unclear. This prospective cohort study included 9,001 hypertension-free individuals aged ≥20 years from the Tohoku Medical Megabank Community-Based Cohort Study. Participants were scored on lifestyle factors, including body mass index, urinary sodium-to-potassium ratio, physical activity, alcohol consumption, and smoking at recruitment. During the mean follow-up of 4.3 years, 2822 (31.4%) cases of hypertension occurred. High genetic risk and poor lifestyle were associated with increased hypertension risk. Compared with participants with low genetic risk, ideal lifestyle, and no family history, high genetic risk significantly increased hypertension risk, even among those with ideal lifestyle and no family history (relative risk [RR] 1.28 [95% confidence interval [CI] 1.11–1.46]). Participants with low PRS, ideal lifestyle, but with family history had increased hypertension risk (RR 1.32 [95%CI 1.11–1.57]). Poor lifestyle increased hypertension risk across most genetic risk groups, regardless of family history. Integrating PRS into models with family history and lifestyle risk significantly improved predictive accuracy (area under the curve: 0.671 for family history and lifestyle risk and 0.674 for PRS integrated; P for difference <0.05). Integrating PRS with lifestyle and family history enhances the stratification of individuals at high risk for hypertension.

Background Previous genome-wide association studies (GWAS) of bipolar disorder (BD) focused primarily on cohorts of European ancestry, although the most recent multi-ancestry GWAS from the PGC included 17% non-European ancestry samples. The study identified two genome-wide significant (GWS) loci. Moreover, a previous GWAS in Han Chinese individuals also identified one GWS locus. The aim of this study is to perform the largest BD GWAS in individuals of East Asian ancestry. Methods GWAS meta-analyses of BD in cohorts of East Asian ancestry (goal N case ∼ 16,000), including Japanese, Korean, Taiwanese, Han Chinese and Asian-American individuals. We characterized the polygenic architecture of BD by estimation of SNP-heritability, genetic correlation with other phenotypes using LD score regression and Popcorn, and quantification of polygenic overlap using MiXeR. Moreover, we will compare and contrast our results to those from BD in European samples. Results Preliminary findings in a subset (n case = 6,860, n control = 160,954) identified two GWS loci. The first locus is in the MHC region on chromosome six which has previously been implicated in BD and other psychiatric disorders. The second locus on chromosome 10 (lead SNP rs78089757) is not previously associated with BD. The lead SNP within this locus is rare in European and African populations (MAF < 1%), but is common in both East and South Asian populations (MAF ∼ 5%). Discussion This large-scale East Asian ancestry GWAS of BD will allow us to empirically evaluate and compare the genetic architecture of BD between East Asian and other ancestry cohorts. The identification of ancestry-specific loci will increase our understanding of the underlying molecular mechanisms of BD. Moreover, this work will help to reduce disparities in GWAS which have predominantly focused on European ancestry samples.

Plasma amino acids (AAs) have emerged as promising biomarkers for metabolic disorders, yet their causality remains unclear. We aimed to investigate the genetic determinants of AA levels in a cohort of 10,333 individuals and their causal effects on cardiometabolic traits using Mendelian randomization (MR). Plasma levels of 20 AAs were quantified using capillary electrophoresis mass spectrometry. Genome-wide association studies were conducted using BOLT-LMM and heritability estimation via LDSC analysis. Causal effects of AAs on 11 cardiometabolic traits were examined using two-sample MR analyses. We identified 85 locus-metabolite associations across 43 genes for 18 AAs, including 44 novel loci linked to metabolic genes. Heritability for AAs was estimated at 16%. MR analysis demonstrated cystine to positively associate with systolic blood pressure (SBP) (beta = 0.056, SE = 0.010), while serine indicated protective effects on SBP (beta = - 0.040, SE = 0.011), diastolic BP (beta = - 0.044, SE = 0.010), and coronary artery disease (odds ratio 0.888, SE = 0.028). We identified potentially novel genetic loci associated with AA levels and demonstrated robust causal associations between several AAs and cardiometabolic traits. These findings reinforce the importance of AAs as potential biomarkers and therapeutic targets in cardiometabolic health.

INTRODUCTION:While social capital can prevent diabetes, these benefits can be heterogeneous with respect to socioeconomic status. We investigated the association between social capital and gestational diabetes mellitus (GDM) while examining effect modification by household income. MATERIALS AND METHODS:We conducted a secondary data analysis using the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study carried out between July 2013 and March 2017. Social capital (mutual aid, social trust, informal social control, collective action) and covariates were self-reported, while GDM diagnosis and other medical and physiological information were obtained from medical records. To assess the association between social capital and GDM, we conducted logistic regression models. We further tested for interactions between social capital and household income as well as stratified the models by income. RESULTS:Among 20,339 study participants, 700 (3.4%) were diagnosed with GDM. Multivariable logistic regression models found that social trust and collective action were associated with lower GDM prevalence, even after adjustment of covariates. When stratifying household income, however, social capital was significantly associated with the reduced risks of GDM only among participants with higher household income (OR: 0.90, 95% CI: 0.85-0.97). No significant association was observed among those with lower household income. CONCLUSIONS:The health benefit of social capital on GDM prevalence was heterogeneous, and the protective effect of social capital on GDM was found only among women with higher household income. The differential impact of social capital on GDM highlights the need for targeted interventions addressing structural health inequities.

AIMS/INTRODUCTION:Obesity is a known risk factor for several chronic diseases, including type 2 diabetes mellitus, which results from increased insulin resistance and impaired insulin secretion. However, the association between obesity and insulin resistance in Asian populations has not yet been fully elucidated. Therefore, we aimed to investigate the causal relationship between body mass index (BMI) and glycemic traits using Mendelian randomization (MR). MATERIALS AND METHODS:We performed individual-level MR analyses using genetic risk scores based on BMI-related variants in 3,745 individuals without diabetes mellitus from a Japanese cohort. We examined heterogeneity through subgroup analyses based on potential modifiers and determined the shape of the causal relationship using nonlinear MR analyses to further assess the impact of BMI on the homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS:MR analyses revealed a significant positive association between BMI and HOMA-IR (β = 0.077; 95% confidence interval, 0.014-0.141; P = 0.016; outcome variable was log-transformed and standardized). Additional analyses revealed heterogeneity among subgroups differentiated by age, sex, lifestyle habits, and cardiometabolic traits. Nonlinear MR analyses suggested a potential J-shaped causal relationship between BMI and HOMA-IR. CONCLUSIONS:Our findings demonstrated that obesity and low BMI may contribute to increased insulin resistance. Furthermore, the impact of BMI on insulin resistance could vary owing to effect modification. Managing BMI is crucial in individuals at high risk of increased insulin resistance and may have important implications for preventing type 2 diabetes, especially given the low insulin secretory capacity observed in East Asian populations.

Genomic information from pregnant women and the paternal parent of their fetuses may provide effective biomarkers for preeclampsia (PE). This study investigated the association of parental polygenic risk scores (PRSs) for blood pressure (BP) and PE with PE onset and evaluated predictive performances of PRSs using clinical predictive variables. In the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study, 19,836 participants were genotyped using either Affymetrix Axiom Japonica Array v2 (further divided into two cohorts—the PRS training cohort and the internal-validation cohort—at a ratio of 1:2) or Japonica Array NEO (external-validation cohort). PRSs were calculated for systolic BP (SBP), diastolic BP (DBP), and PE and hyperparameters for PRS calculation were optimized in the training cohort. PE onset was associated with maternal SBP-, DBP-, and PE-PRSs and paternal SBP- and DBP-PRSs only in the external-validation cohort. Meta-analysis revealed overall associations with maternal PRSs but highlighted significant heterogeneity between cohorts. Maternal DBP-PRS calculated using “LDpred2” presented the most improvement in prediction models and provided additional predictive information on clinical predictive variables. Paternal DBP-PRS improved prediction models in the internal-validation cohort. In conclusion, Parental PRS, along with clinical predictive variables, is potentially useful for predicting PE.