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PubMed1992

[Assessment of occupational exposures to industrial hazardous substances. V. A proposed method for evaluating employee's exposure averages (8-h TWAs) using a single day measurement].

Daily exposure averages (8-h TWAs) to hazardous substances may vary considerably day to day, even though a worker is engaged in the same job. Previously we proposed a method to evaluate a long-term exposure condition with interday fluctuation using some exposure measurements. As it is assumed that 8-h TWAs are log-normally distributed, geometric standard deviation (sigma g) representing true interday fluctuation of 8-h TWAs should be estimated. If a single day's 8-h TWA of a worker is measured, sigma g of his own distribution of 8-h TWAs cannot be estimated. Therefore, to evaluate a long-term condition using a single day's 8-h TWA, representative sigma g in all industrial workplaces must be determined beforehand. To investigate sigma g observed in many industrial workplaces, two days' 8-h TWAs of each worker were measured in a week on 260 workers exposed to 19 hazardous substances. Sg2 (geometric standard deviation estimated by two samples) ranged from 1.00 to 8.22 with a median of 1.47 and a 90% upper limit of 2.47. Transforming Sg2 into sigma g, median and 90% upper limit of sigma g were 1.75 and 2.47, respectively. According to a classification scheme in the proposed method, exposure levels (I to III) were calculated using sigma g of 1.75 and 2.47. A long-term exposure condition to hazardous substances can be evaluated by comparing a single day's 8-h TWA with the exposure levels.

Environmental Monitoring↗
PubMed2026

Protective TGFβ2/SMAD3 axis identified by TWAS in papillary thyroid cancer.

Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy. Although generally indolent, a subset shows aggressive behaviour. Furthermore, the genetic heterogeneity of PTC is not fully explained by known driver mutations, underscoring the need to identify additional susceptibility genes and regulatory mechanisms. To identify additional susceptibility genes and regulatory mechanisms, we integrated transcriptome-wide association studies (TWAS) with summary-data-based Mendelian randomisation (SMR), joint/conditional testing (JCT), and colocalisation analyses across multiple independent cohorts, followed by heterogeneity in dependent instruments (HEIDI) test. Gene prioritisation analyses consistently highlighted TGFB2 and SMAD3 as candidate susceptibility genes for PTC, with SMR supporting putative protective effects. Besides, GEPIA confirmed the positive correlation between TGFB2 and SMAD3 expression in TCGA-THCA. Functional experiments in TPC-1 cells showed that TGFβ2 treatment inhibited cell proliferation and migration, induced apoptosis, and resulted in G0/G1 cell-cycle arrest, accompanied by increased SMAD3 phosphorylation, suggesting activation of canonical TGFβ signalling. Collectively, these findings bridge population-based genetic inference with mechanistic validation and suggest convergent evidence supporting a tumour-suppressive role of the TGFβ2/SMAD3 axis in PTC.

Humans↗
PubMed2026

Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.

BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood. METHODS: We integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening. RESULTS: The integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure. CONCLUSION: This integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.

Humans↗
PubMed1988

[Assessment of occupational exposures to industrial hazardous substances. I. A proposed method based on interday fluctuation of contaminant concentrations for evaluating employee's exposure averages (TWAs)].

Occupational exposures to potentially hazardous substances may vary considerably because of factors such as sampling and analytical errors, and intraday and interday environmental fluctuations in contaminant concentration. Of these factors, day-to-day environmental fluctuations most likely affect daily exposure averages over days, weeks, months or years. A new method based on day-to-day fluctuations of daily exposure averages (geometric standard deviation) was developed for making reliable assessment of the employee's exposure situation. It is assumed that daily exposure averages of a worker are lognormally and independently distributed statistically. Finally, a classification scheme on the basis of n days measurements is presented. 95% upper limit or arithmetic mean of individual exposure averages (8-h TWAs) can be evaluated in comparison with an established standard. The method may provide an approximate estimate because of statistical premise, but it can be utilized for practical purposes, particularly, in case where only one or two days are being monitored. An action level concept based on random sampling and analytical errors and interday variations developed by OSHA/NIOSH, and a sampling and decision scheme based on one-sided tolerance limits proposed by Tuggle (1982) are also discussed.

Data Interpretation, Statistical↗
PubMed2026

Identification of immune cell type-specific susceptibility genes in multiple cancers using transcriptome-wide association studies.

BACKGROUND: Transcriptome-wide association studies (TWAS) integrate gene expression and genome-wide association studies (GWAS) to identify disease susceptibility genes. Because gene expression varies substantially across cell types within tissues, cell type-specific prediction models may enhance the power of TWAS. METHODS: We conducted cell type-specific TWAS leveraging single-cell RNA sequencing data from the OneK1K cohort (14 immune cell types, 1.27 million cells) and GWAS summary statistics for 7 cancers (>290 000 cases in total). To improve prediction accuracy, we developed a modeling framework that incorporates shared gene expression effects across cell types. RESULTS: At a false discovery rate of 5%, we identified 106 (Bonferroni 5%: 13) previously unreported loci for breast cancer, 51 (4) loci for prostate cancer, 11 (4) loci for lung cancer, 39 (5) loci for melanoma, 9 (1) loci for ovarian cancer, and 2 (1) loci for diffuse large B-cell lymphoma, with most genes exhibiting cell type specificity. Gene set analyses confirmed joint associations of unreported genes with breast and prostate cancer risk in UK Biobank data. Additional lung tissue single-cell RNA sequencing data with 113 individuals validated 18 of 32 (56.3%) statistically significant genes for lung cancer. Across cancers, 139 statistically significant genes were shared by at least 2 cancer types and were primarily enriched in specific immune cell types. CONCLUSION: Cell type-specific TWAS improve the identification of novel cancer susceptibility loci and provide insights into the immune landscape of cancer etiology.

Humans↗
PubMed2026

Transcriptome-wide association analysis of Alzheimer's disease: construction and clinical validation of transcriptomic risk scores.

Early identification of individuals at high risk for Alzheimer's disease (AD) is crucial for disease prevention and intervention. This study aims to develop AD-specific transcriptomic risk scores (TRSs) through multi-tissue transcriptome-wide association study (TWAS) and to evaluate its clinical utility in AD diagnosis and risk prediction. Using GWAS summary statistics combined with expression quantitative trait loci (eQTL) data from 14 tissues, a multi-tissue TWAS approach was applied to identify AD-associated genes. Peripheral blood RNA expression data from the ADNI and GEO databases were used to construct the AD-specific TRSs. The associations of TRSs with AD pathological features and cognitive function were assessed in two independent cohorts. Furthermore, the diagnostic performance, differential diagnostic capability, and risk prediction efficiency of TRSs were evaluated. The TWAS identified 131 genes significantly associated with AD. The TRSs were significantly elevated in patients with AD and mild cognitive impairment (MCI) compared to cognitively normal (CN) individuals, and showed significant correlations with AD pathological markers and cognitive performance. When combined with APOE4 status, the TRSs demonstrated robust diagnostic ability for AD and MCI. When combined with age, the TRSs showed good diagnostic performance in distinguishing AD from frontotemporal dementia (FTD) (AUC = 0.86). Additionally, the TRSs effectively predicted the risk of progression to AD in non-AD individuals (HR = 1.74). The AD-specific TRSs developed in this study shows promising clinical utility in AD diagnosis, differential diagnosis, and risk prediction, providing valuable translational medical evidence for early screening and precision prevention of Alzheimer's disease.

Humans↗
PubMed2026

A novel reusable transcriptome-wide association study workflow used to map key genes linked to important cattle traits.

Transcriptome-wide association studies (TWAS) are a powerful approach for studying the genes underlying complex traits by directly integrating GWAS and gene expression datasets. In cattle, they have been previously applied to identify genes driving fertility, milk production, and health. However, these studies have also highlighted several challenges, from difficulties in reproducing these complex analyses to limitations from poor genotype calls, especially when called directly from RNA sequencing data. To address these and other challenges, for the H2020 BovReg Project, we have developed a streamlined, species-agnostic, and reusable Nextflow TWAS workflow to integrate transcriptomic and GWAS summary statistic datasets. Our workflow first generates accurate genotype calls and gene expression prediction models from transcriptomic datasets and then applies these tools to impute gene expression levels into GWAS cohorts, enabling the association of genes with traits of interest. We explore optimal strategies for calling genetic variants directly from transcriptomic data and illustrate that using imputation approaches specifically designed for low-pass sequencing data can improve variant calling over previously adopted methods. We demonstrate the utility of our TWAS workflow by applying it to both novel and publicly available GWAS cohorts for cattle, detecting novel gene-trait associations for complex traits. Using a new transcriptome annotation of the cattle genome generated for the BovReg project we also illustrate how previously un-assayable associations can be detected. The results and the workflow we present, provide a new resource for the community and contribute to a better understanding of the molecular drivers of complex traits in cattle with the goal of eventually leveraging this information in future breeding decisions.

Animals↗
PubMed1991

Environmental versus analytical variability in exposure measurements.

Measurements of 8-hr time-weighted average (TWA) exposures are subject to environmental variability and collection and analytical error. Environmental variability can be represented by the geometric standard deviation (GSD) of the lognormally distributed 8-hr TWAs; analytical variability can be represented by the coefficient of variation (CV) of the normally distributed collection and analytical errors. A mathematical expression is derived for the variance of the measured 8-hr TWAs as a function of the GSD of the true daily average exposures and the total CV of the industrial hygiene method used in monitoring. For typical values of the GSD and CV, environmental variability is far more important than analytical variability in determining the variance of the measured 8-hr TWAs. A resulting policy implication is that the Occupational Safety and Health Administration inappropriately focuses on analytical variability when determining compliance with its permissible exposure limits.

Bias↗
PubMed2026

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblasts reveals shared allelic effects between Latin American and European ancestries.

BACKGROUND: Quantitative Trait Locus (QTL) analysis of molecular data has identified genetic variants associated with traits such as gene expression, and colocalization of these functional QTL with GWAS risk loci has offered insights into the genetic basis of human disease. We employed gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) obtained from human primary fibroblasts to investigate quantitative trait loci (QTLs) in cohorts ascertained for bipolar disorder of European (n = 150) and Latin American (n = 96) ancestries. RESULTS: Leveraging data from three countries of origin (The Netherlands, Colombia, Costa Rica) within our cohort, we characterized differences among individuals at the SNP, gene, and accessible-chromatin levels to compute ancestry-specific expression (e)QTLs and chromatin-accessibility (ca)QTLs. Across ancestries, we observed R2 ≥ 0.93 for eQTL effect sizes and R2 ≥ 0.95 for caQTLs, indicating a high degree of concordance. Integrating chromatin data with expression and genotype information enabled precise fine-mapping of eQTLs, yielding 203 genes with high-confidence (posterior probability > 90%) candidate regulatory pathways. In downstream analyses, transcriptome-wide (TWAS) and chromatin-wide (CWAS) association studies with brain- and skin-related GWAS identified 36 TWAS-significant genes and 77 CWAS-significant open chromatin regions. CONCLUSIONS: These findings underscore the shared genetic regulatory mechanisms across European and Latin American ancestries, while demonstrating that ancestry-specific reference panels enhance the accuracy of TWAS and CWAS in diverse populations. More broadly, this study highlights the value of paired multi-omic datasets from diverse cohorts for interpreting disease-associated genetic variation.

Humans↗
PubMed2026

A minimal three-arm oral regimen for healthspan: mechanistic alignment with transcriptomic signals from a large parental-lifespan GWAS.

A large genome-wide association study of parental lifespan was reported in 2019. A later transcriptome-wide association study (TWAS) based on those summary statistics identified a set of transcriptional programs associated with longer genetically predicted survival, including increased brain NAD + salvage, especially NMNAT2, reduced glucose-stimulated insulin secretion, a shift toward synaptic pruning with less broad plasticity, and a glial pattern characterized by relatively greater microglial and lower astrocytic signatures, with only weak pan-tissue senescence signals. Building on those directional findings, this short communication proposes a minimal three-arm oral regimen with unequal evidentiary weight: first, the Cheung Glutamatergic Regimen, consisting of low-dose dextromethorphan potentiated by a CYP2D6 inhibitor together with piracetam and L-glutamine, as an exploratory adjunct aimed at preserving residual functional connectivity; second, daily nicotinamide mononucleotide and N-acetylcysteine with pulsed senolytics for NAD + salvage and senescence modulation; and third, GLP-1 receptor agonism for metabolic reprogramming. The NAD+/senescence arm is the primary mechanistic anchor, GLP-1 receptor agonism provides secondary metabolic support, and the glutamatergic arm is exploratory. Each arm targets a separate node within the pruning-plasticity-metabolic triad. The regimen is fully oral, uses conservative dosing, and draws on prior therapeutic or human-exposure data, although the proposed combination has no established safety profile. Although direct combination data are lacking and the foundational TWAS remains a preprint, the components show plausible but uneven mechanistic alignment with the TWAS signals and may justify carefully designed, safety-focused pilot evaluation.

GLP-1↗
PubMed2026

FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies.

Transcriptome-wide association studies (TWAS) integrate genome wide association studies with expression quantitative trait locus reference panels to identify genes associated with traits of interest. However, linkage disequilibrium and correlated gene expression can induce spurious TWAS signals, motivating fine mapping methods to prioritize putatively causal genes within associated loci. The rapid growth of large-scale phenomic resources (e.g. electronic health records (EHRs)) has shifted genetic studies from single-trait analyses to phenome-wide investigations that jointly evaluate many closely related phenotypes. We introduce FM-GPT (Fine-mapping of causal Genes for Phenome-wide Transcriptome-wide association studies), a novel Bayesian fine mapping method for prioritizing causal genes across multiple correlated phenotypes with potentially mixed outcome types (e.g., binary, count or continuous) in phenome-wide TWAS. FM-GPT performs gene-guided dimension reduction of the phenotypes and reveals pleiotropic or phenotype-specific effects of the identified genes. In simulations, FM-GPT identified true causal genes more accurately than other fine mapping methods while controlling false positives. We applied FM-GPT to two applications using data from UK Biobank: a brain-wide genetic analysis of MRI data derived regional cortical thickness measures and a phenome-wide genetic analysis of clinical phenotypes derived from EHR data. FM-GPT greatly narrowed down the set size of putatively causal genes and identified: 1. genes with pleiotropic effects on regional cortical thickness across the cerebral cortex, including five genes BCAS3, LRRC37A, NOS2P3, ARL17B and UBB on chromosome 17 regulating neuronal morphology and cortical organization; and 2. genes that influence multiple medical conditions across the circulatory, metabolic, digestive, respiratory and genitourinary systems, revealing two major axes of variation among these conditions that point to a potential trade-off in gene regulation between immune and metabolic functions. These results highlight FM-GPT's power to disentangle complex gene-phenotype relationships in large-scale phenome-wide studies, uncovering shared biological mechanisms across diverse human traits and advancing translational and comorbidity research.

Bayesian fine mapping↗
PubMed2026

Genetic evidence links hypertension to accelerated brain aging.

Hypertension affects one-third of adults and is a major comorbidity of neurocognitive disorders. The causal relationship, shared genetic architecture, and upstream mechanisms linking hypertension to brain aging remain unclear. Hypertension GWAS datasets from MVP and FinnGen R12 were meta-analyzed as the exposure, and a European-ancestry brain age gap (BAG) GWAS derived from the UK Biobank and LIFE-Adult cohorts was used as the outcome. MR and GSMR assessed causality. LDSC, HDL, and S-LDSC estimated genetic correlation. Four TWAS methods (MAGMA, FUSION, JTI-PrediXcan, FOCUS) mapped associations to genes, followed by SMR for causal validation and PoPS for prioritization. GSMAP with spatial transcriptomics characterized regional and cell-type enrichment. Hypertension and brain aging were genetically correlated, and MR and GSMR analyses suggested a causal effect of hypertension on increased brain age gap. TWAS identified 15 shared Hypertension-BAG genes, 10 supported by SMR. PoPS prioritized TRIM47 as the core gene. Shared signals were enriched in meninges, fiber tracts, cortical layer 1, and CA1 stratum lacunosum/radiatum, with cell-type enrichment in meninges, smooth muscle cells, oligodendrocytes, and astrocyte subtypes. Hypertension is genetically correlated with, and shows evidence of a causal effect on, accelerated brain aging. TRIM47 is a core gene bridging hypertension and BAG. GSMAP-based spatial enrichment provides a hypothesis-generating framework for understanding vascular, meningeal, and myelin-related pathways linking hypertension to increased brain age gap.

Humans↗
PubMed2025

Multi-ancestry genome-wide and transcriptome-wide association analyses identified new risk loci and genes for inflammatory bowel disease.

To advance genetic understanding of inflammatory bowel disease (IBD), we conducted genome-wide association meta-analyses of 63,415 IBD cases of European and East Asian descendants and identified 90 previously unknown risk loci. Integrating multi-ancestry transcriptome-wide association studies (TWAS), cell type-specific TWAS, alternative splicing (AS-WAS), and alternative polyadenylation (APA-WAS) analyses using RNA-seq data from normal colon tissues of 707 European and 364 East Asian individuals, we uncovered 506 high-confidence IBD risk genes, including 384 not previously reported. These genes converge on immune regulation, microbial interaction, and other pathways central to IBD pathogenesis, with over half showing transcriptional dysregulation supported by single-cell and spatial omics analyses. Notably, 46 risk genes are targeted by 225 drugs that have been approved or in Phase II/III trials, including sulfasalazine already used in IBD therapy. Our study findings deepen the understanding of IBD genetics and support the development of precision medicine for its prevention and treatment.

GWAS↗
PubMed2026

Integrative cross-tissue transcriptome-wide association and metabolomic analysis reveals novel genetic risk loci for aortic aneurysm.

BACKGROUND: Aortic aneurysm (AA) is a life-threatening cardiovascular condition with a strong genetic component, however, its molecular mechanisms remain poorly understood. Although genome-wide association studies (GWAS) have identified numerous risk loci, most prior studies have investigated genetic and metabolic factors separately, leaving the causal pathways from genetic variants to disease largely unexplored. METHODS: We established an integrative framework combining cross-tissue transcriptome-wide association studies (TWAS) with metabolomic mediation analysis. First, we integrated GWAS data from FinnGen R12 with multi-tissue expression quantitative trait loci (eQTL) data from Genotype-Tissue Expression Project (GTEx) V8, then performed cross-tissue TWAS using the Unified Test for MOlecular SignaTures (UTMOST) and single-tissue validation with the Functional Summary-based Imputation (FUSION) to prioritize susceptibility genes. Second, we applied Mendelian randomization (MR), colocalization, and Fine-mapping Of CaUsal gene Sets (FOCUS) to assess causality and identify high-confidence genes. Third, we performed metabolite mediation analysis to uncover metabolic pathways linking genetic variants to disease risk. Finally, we validated key findings in mouse models of thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA) using Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction (RT-qPCR) and Western blotting. RESULTS: We identified multiple novel susceptibility genes for AA and its subtypes. Key genes included ADH family members (ADH1A, ADH1B, ADH4, ADH6) and ZNF827, which showed cross-subtype associations with strong colocalization evidence in vascular tissues. Metabolite mediation analysis revealed significant pathways involving N-acetylphenylalanine and methionine sulfoxide. Functional enrichment revealed distinct biological mechanisms: AA and AAA were primarily associated with metabolic pathways, whereas TAA-related genes were enriched in developmental and contractile processes. PheWAS indicated no significant off-target associations. Critically, experimental validation in mouse models confirmed significant upregulation of ZNF827 in TAA and ADH6 in AAA at both mRNA and protein levels, corroborating the genetic predictions. CONCLUSION: This integrated cross-omics analysis identifies novel genetic loci and, crucially, uncovers specific nutrient-related metabolic pathways that mediate genetic risk. These findings provide a mechanistic basis for future nutritional and metabolic intervention studies in AA and its subtypes.

MAGMA↗
PubMed2026

GWAS meta-analysis provides new insights into uveal melanoma risk.

OBJECTIVE: The aim of this research is to identify germline genetic variants that predispose to uveal melanoma (UM) using data from nine studies involving 5839 individuals with UM (3853 novel) and 349,863 healthy controls. METHODS: Five novel UM genome-wide association studies (GWAS) were performed and included for meta-analysis with four previously published UM GWAS. A fixed-effects inverse-variance weighted (IVW) meta-analysis was performed by combining data from these nine UM case-control cohorts. A follow-up transcriptome-wide association study (TWAS) was conducted to identify candidate target genes at UM risk loci. Genetic correlations with melanoma-related phenotypes were measured to elucidate UM's genetic architecture. RESULTS: We identify nine linkage disequilibrium (LD)-independent loci (three novel) with an IVW P value of less than 5 × 10-8. TWAS analysis indicates five potential target genes, including MOB3B, RBAK, and MTSS1, which have established links to multiple cancer types. We note a significant genetic correlation (rg = 0.31, P = 0.01) between UM and cutaneous melanoma (CM), and a non-significant but consistent correlation with naevus count (rg = 0.25, P = 0.08). CONCLUSIONS: This meta-analysis offers new insights into the genetic architecture of UM, highlights potential therapeutic targets, and explores the genetic relationship with CM and skin pigmentation.

Humans↗
PubMed1988

Occupational noise exposure in the printing industry.

The noise exposures of 274 printing production workers in 34 establishments in the New York city area were monitored. Results showed that 43% were exposed to 8-hr time-weighted average (TWA) noise exposures of 85 dBA or greater and that 14% were exposed to 8-hr TWAs of 90 dBA or greater. Within the press department, web press workers were exposed to significantly greater mean 8-hr TWAs than sheetfed press workers. In general, a greater percentage of the workers in the bindery departments were exposed to potentially harmful noise than workers in the press departments. Results of this study indicate that many workers in the printing industry may be at risk of occupational hearing loss. Further research is needed to determine the extent of hearing impairment in this group of workers.

Environmental Exposure↗
PubMed2026

Integrative genomic and transcriptomic analysis of hypertension in a Taiwanese population.

OBJECTIVES: Hypertension is highly prevalent in Asian populations and represents a major cardiovascular risk factor. However, most genome-wide association studies (GWASs) and transcriptome-wide association studies (TWASs) have focused primarily on Caucasian cohorts. This study aimed to identify genetic loci and gene expression signatures associated with hypertension in an Asian population. METHODS: We analyzed 10 739 hypertensive patients and 49 668 controls from the Taiwan Biobank, testing 4 512 191 genome-wide single nucleotide polymorphisms (SNPs). Integrated GWAS, TWAS, and expression quantitative trait locus (eQTL) analyses were conducted to characterize genetic risk. Additionally, a polygenic risk score (PRS) was constructed using a split-sample design to evaluate genetic risk stratification. RESULTS: We identified 14 loci significantly associated with hypertension, including a novel locus at 5p13.1. eQTL analysis linked this locus to DAB2 expression in whole blood. TWAS detected 55 hypertension-associated genes, with 20 (36%) overlapping GWAS loci. Several novel genes outside GWAS loci, including FBXL15, KCNIP2, and CRIP3, were highly significant and implicated in vascular biology and hypertension mechanisms. PRS analysis effectively differentiated hypertension risk, with individuals in the top 10% showing a > 3.5-fold increased risk compared to the bottom 10%. CONCLUSIONS: Our findings provide new insights into the genetic and transcriptomic landscape of hypertension in Asians. The identification of novel loci and genes advances understanding of disease biology and may guide precision medicine approaches for risk prediction and therapeutic development.

Female↗