Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “GWAS”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12Linked to original sources
PubMed2022

Polygenic heterogeneity in antidepressant treatment and placebo response.

The genetic architecture of antidepressant response is poorly understood. Polygenic risk scores (PRS), exploration of placebo response and the use of sub-scales might provide insights. Here, we investigate the association between PRSs for relevant complex traits and response to vortioxetine treatment and placebo using clinical scales, including sub-scales and self-reported assessments. We collected a clinical test sample of Major Depressive Disorder (MDD) patients treated with vortioxetine (N = 907) or placebo (N = 455) from seven randomized, double-blind, clinical trials. In parallel, we obtained data from an observational web-based study of vortioxetine-treated patients (N = 642) with self-reported response. PRSs for antidepressant response, psychiatric disorders, and symptom traits were derived using summary statistics from well-powered genome-wide association studies (GWAS). Association tests were performed between the PRSs and treatment response in each of the two test samples and empirical p-values were evaluated. In the clinical test sample, no PRSs were significantly associated with response to vortioxetine treatment or placebo following Bonferroni correction. However, clinically assessed treatment response PRS was nominally associated with vortioxetine treatment and placebo response given by several secondary outcome scales (improvement on HAM-A, HAM-A Psychic Anxiety sub-scale, CPFQ & PDQ), (P ≤ 0.026). Further, higher subjective well-being PRS (P ≤ 0.033) and lower depression PRS (P = 0.01) were nominally associated with higher placebo response. In the self-reported test sample, higher schizophrenia PRS was significantly associated with poorer self-reported response (P = 0.0001). The identified PRSs explain a low proportion of the variance (1.2-5.3%) in placebo and treatment response. Although the results were limited, we believe that PRS associations bear unredeemed potential as a predictor for treatment response, as more well-powered and phenotypically similar GWAS bases become available.

Humans↗
PubMed2025

Integrative omics of the genetic basis for wheat WUE and drought resilience reveal the function of TaMYB7-A1.

Improving wheat drought resilience and water use efficiency (WUE) is critical for sustaining productivity under increasing water scarcity. Here, we integrate genome-wide association study (GWAS), expression quantitative trait locus (eQTL) mapping, population-transcriptome analysis, and summary-data-based mendelian randomization (SMR), followed by functional validation using indexed EMS mutants and transgenic lines, to systematically identify key WUE regulators. GWAS across water conditions in 228 accessions identifies 73 quantitative trait loci (QTLs) for WUE-traits. Transcriptome profiling of 110 diverse accessions reveals 28 drought-responsive modules. eQTL mapping uncovers 146,966 regulatory variants, including condition-specific hotspots associated with key drought-related pathways. Integrative analysis underscores 85 high-confidence candidate genes, notably TaMYB7-A1. Overexpression of TaMYB7-A1 enhances photosynthesis, WUE, root development, and grain yield under drought condition by activating TaPIP2;2-B1 (water transport), TaRD20-D1 (stomatal regulation), and TaABCB4-B1 (root growth), reflecting reduced water loss and improved physiological resilience. Our study presents a comprehensive regulatory map and robust targets for wheat drought adaptation and resilient cultivar breeding.

Triticum↗
PubMed2026

Genetic modifiers of APOE-ε4-associated cognitive decline.

The APOE-ε4 allele is the strongest genetic risk factor for late-onset Alzheimer's disease. However, APOE-ε4 is not deterministic, highlighting the need to identify additional genetic and environmental factors. APOE-ε4 has been linked to accelerated cognitive decline, so we sought to investigate genetic factors that modify APOE-ε4-associated cognitive decline. We conduct cross-ancestry APOE-ε4-stratified and interaction GWAS using harmonized cognitive data from 32,778 participants, including 29,354 non-Hispanic White and 3,424 non-Hispanic Black individuals. Our primary outcome is late-life cognition, measured using harmonized composite scores for memory, executive function, and language, modeled as continuous traits reflecting both normative cognitive aging and disease-related decline. We identify two genome-wide significant loci in APOE-ε4 carriers, reaching genome-wide significance for executive function. These loci also demonstrate nominal associations across the other domains, suggesting broad effects on cognition. In non-carriers, we identify a genome-wide significant association at ITGB8 restricted to executive function, and another locus associated with language. We further link these loci to SEMA6D, GRIN3A, and ITGB8 through expression and methylation databases. Post-GWAS analyses implicate additional genes including SLCO1A2, and DNAH11. Genetic correlation analyses reveal differences by APOE-ε4 status for immune-related traits, suggesting immune-related predispositions may exacerbate cognitive risk in APOE-ε4 carriers.

Humans↗
PubMed2025

Discovery of ancestry-specific variants associated with clopidogrel response among Caribbean Hispanics.

High on-treatment platelet reactivity (HTPR) with clopidogrel predicts ischemic events in adults with coronary artery disease, and while HTPR varies by ethnicity, no genome-wide association study (GWAS) of clopidogrel response has been conducted in Caribbean Hispanics. This study aimed to identify genetic predictors of HTPR in a cohort of 511 Puerto Rican cardiovascular patients treated with clopidogrel, stratified by P2Y12 reaction units (PRU) into responders and non-responders (HTPR). Local ancestry inference (LAI) and traditional GWAS identified variants in the CYP2C19 region associated with HTPR, primarily in individuals with European ancestry. Three variants (OSBPL10 rs1376606, DERL3 rs5030613, RGS6 rs9323567) showed suggestive significance, and a variant in UNC5C was linked to increased HTPR risk. These findings highlight the unique genetic landscape of Caribbean Hispanics and challenge the significance of CYP2C19*2 in predicting clopidogrel response in patients with high non-European ancestry. Further studies are needed to replicate these results in other diverse cohorts.

Journal Article↗
PubMed2024

Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes.

Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation and WGS to conduct the largest T2D GWAS meta-analysis involving 51,256 cases of T2D and 370,487 controls, targeting variants with a minor allele frequency as low as 5 × 10-5. We identified 12 new variants, including a rare African/African American-enriched enhancer variant near the LEP gene (rs147287548), associated with fourfold increased T2D risk. We also identified a rare missense variant in HNF4A (p.Arg114Trp), associated with eightfold increased T2D risk, previously reported in maturity-onset diabetes of the young with reduced penetrance, but observed here in a T2D GWAS. We further leveraged these data to analyze 1,634 ClinVar variants in 22 genes related to monogenic diabetes, identifying two additional rare variants in HNF1A and GCK associated with fivefold and eightfold increased T2D risk, respectively, the effects of which were modified by the individual's polygenic risk score. For 21% of the variants with conflicting interpretations or uncertain significance in ClinVar, we provided support of being benign based on their lack of association with T2D. Our work provides a framework for using rare variant GWASs to identify large-effect variants and assess variant pathogenicity in monogenic diabetes genes.

Diabetes Mellitus, Type 2↗
PubMed2025

Role of functional genes for seed vigor related traits through genome-wide association mapping in finger millet (Eleusine coracana L. Gaertn.).

Finger millet (Eleusine coracana (L.) Gaertn.) is a calcium-rich, nutritious and resilient crop that thrives even in harsh environmental conditions. In such ecologies, seed longevity and seedling vigor are crucial for sustainable crop production amid climate change. The current study explores the genetics of accelerated aging on seed longevity traits across 221 diverse accessions of finger millet through genome-wide association approach (GWAS). A significant variation was identified in germination percentage, germination rate indices, mean germination time, seedling vigor indices and dry weight upon aging treatment. GWAS model from 11,832 high-quality SNPs identified through Genotyping-by-Sequencing (GBS) approach produced 491 marker-trait associations (MTAs) for 27 traits, of which 54 were FDR-corrected. A pleiotropic SNP, FM_SNP_9478 identified on chromosome 7B was associated with the traits viz., germination after aging, germination index after aging and their relative measures. Functional annotation revealed DET1 and expansin-A2 influenced seed coat integrity, critical for germination and aging resilience. Probable protein phosphatase 2C3 and piezo-type ion channels contributed to mechanical sensing and stress adaptation in seeds. Beta-amylase and acetyl-CoA carboxylase 2 were identified for seed metabolism and stress response. These insights lay the framework for targeted breeding efforts to improve seed quality and resilience under diverse production conditions.

Eleusine↗
PubMed2025

Exploiting pleiotropy to enhance variant discovery with functional false discovery rates.

The cost of recruiting participants for genome-wide association studies (GWASs) can limit sample sizes and hinder the discovery of genetic variants. Here we introduce the surrogate functional false discovery rate (sfFDR) framework that integrates summary statistics of related traits to increase power. The sfFDR framework provides estimates of FDR quantities such as the functional local FDR and q value, and uses these estimates to derive a functional P value for type I error rate control and a functional local Bayes' factor for post-GWAS analyses. Compared with a standard analysis, sfFDR substantially increased power (equivalent to a 52% increase in sample size) in a study of obesity-related traits from the UK Biobank and discovered eight additional lead SNPs near genes linked to immune-related responses in a rare disease GWAS of eosinophilic granulomatosis with polyangiitis. Collectively, these results highlight the utility of exploiting related traits in both small and large studies.

Humans↗
PubMed2026

Genetic evidence and cross-species functional characterization implicate CNN2 in age-related macular degeneration susceptibility.

Age-related macular degeneration (AMD) is a leading cause of irreversible visual impairment in the aging population globally. Although genome-wide association studies (GWAS) have identified many AMD susceptibility loci, the genes and mechanisms underlying many of these associations remain unresolved. Here, we integrated expression quantitative trait locus (eQTL) data with AMD GWAS to prioritize nine putative genes. Through in vivo screening in zebrafish, we demonstrated that the downregulation of cnn2 and sarm1 expression led to ocular structural abnormalities and visual functional impairment. Subsequent mouse model studies confirmed that Cnn2 deficiency affected photoreceptor structure and function, impaired contrast sensitivity, and caused abnormalities in cone cell immunostaining. Given that CNN2 is predominantly expressed in endothelial cells, we propose that endothelial dysfunction may cascade to impair photoreceptor function. Collectively, through in silico prioritization and cross-species functional characterization, we identify CNN2 as a candidate susceptibility gene in AMD pathogenesis, providing vital underlying mechanistic insights.

Animals↗
PubMed2024

Mendelian randomization study on the causal effect of herpes simplex virus infection on idiopathic pulmonary fibrosis.

BACKGROUND: Previous observational studies have shown that past infection of herpes simplex virus (HSV) is associated with idiopathic pulmonary fibrosis (IPF). The present study aims to identify the causal link between HSV infection (exposure factor) and IPF (outcome factor). RESEARCH DESIGN AND METHODS: To date, the largest publicly available genome-wide association study (GWAS) for HSV infection (1,595 cases and 211,856 controls from Finnish ancestry) and for IPF (1,028 cases and 196,986 controls from Finnish ancestry) were used to perform this two-sample Mendelian randomization (MR) study. RESULTS: We found no significant pleiotropy or heterogeneity of all selected nine HSV infection-associated genetic instrumental variants (IVs) in IPF GWAS dataset. Interestingly, we found that as HSV infection genetically increased, IPF risk increased based on an inverse-variance weighted (IVW) analysis (odds ratio [OR] = 1.280, 95% confidence interval [CI]: 1.048-1.563; p = 0.015) and weighted median (OR = 1.321, 95% CI: 1.032-1.692; p = 0.027). CONCLUSIONS: Our analysis suggests a causal effect of genetically increased HSV infection on IPF risk. Thus, HSV infection may be a potential risk factor for IPF.

Humans↗
PubMed2026

bioETH-PRS: confidential polygenic risk scoring with smart contracts on an FHE-enabled blockchain.

Polygenic risk scores (PRSs) aggregate genetic effect estimates to predict disease susceptibility, yet calculating one through an external service can require exposing raw genotype data. Homomorphic encryption hides those data during the calculation but, in prior work, still places a designated evaluator in a position of trust. We present bioETH-PRS, a protocol that replaces the evaluator with publicly auditable smart contracts on a blockchain supporting Fully Homomorphic Ethereum Virtual Machine (fhEVM). Using integer-exact encrypted arithmetic, bioETH-PRS computes the PRS dot product entirely in the encrypted domain, so genotype dosages and, at the model provider's discretion, the GWAS weights stay hidden from the parties performing the computation. A fixed-point encoding represents signed weights as nonnegative integers within a bound that rules out overflow, recovering the score to the precision of the published weights. A four-contract architecture separates data custody, model publication, computation, and output release, and supports both a classic path that stores encrypted inputs and an appreciably cheaper streaming path that discards them. A release oracle can return a randomized risk category instead of the raw score, limiting what a repeated querier learns. Prototype evaluation on real GWAS fixtures, including a run on a public testnet, shows cost growing linearly with variant count and suggests the approach may be practical where transaction fees are low. Trust is redistributed rather than removed: the system still depends on the contracts, the blockchain, and the fhEVM services. We evaluate additive models of moderate size, not genome-wide or clinical use.

Blockchain↗
PubMed2026

SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs.

MOTIVATION: Genome-wide association studies (GWAS) at biobank scale are computationally intensive, especially for admixed populations requiring robust statistical models. SAIGE is a widely used method for generalized linear mixed-model GWAS but is limited by its CPU-based implementation, making phenome-wide association studies impractical for many research groups. RESULTS: We developed SAIGE-GPU, a GPU-accelerated version of SAIGE that replaces CPU-intensive matrix operations with GPU-optimized kernels. The core innovation is distributing genetic relationship matrix calculations across GPUs and communication layers. Applied to 2068 phenotypes from 635 969 participants in the Million Veteran Program, including diverse and admixed populations, SAIGE-GPU achieved a 5-fold speedup in mixed model fitting on supercomputing infrastructure and cloud platforms. We further optimized the variant association testing step through multi-core and multi-trait parallelization. Deployed on Google Cloud Platform and Azure, the method provided substantial cost and time savings. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are available for download at https://github.com/saigegit/SAIGE/tree/SAIGE-GPU-1.3.3. A code snapshot is archived at Zenodo for reproducibility (DOI: [10.5281/zenodo.17642591]). SAIGE-GPU is available in a containerized format for use across HPC and cloud environments and is implemented in R/C++ and runs on Linux systems.

Genome-Wide Association Study↗
PubMed2026

PYRAMA: an open-source tool for advanced meta-analysis of genome wide association studies.

MOTIVATION: Genome-wide association study (GWAS) meta-analysis tools are essential for integrating summary statistics across multiple cohorts, thereby increasing statistical power and validating genetic associations. Widely cited tools, such as METAL, PLINK, and GWAMA, have facilitated numerous significant discoveries in the field of GWAS. Nevertheless, these tools offer a limited set of meta-analysis methods and typically require users to have prior experience with command-line tools to be executed. RESULTS: We present here PYRAMA, an open-source tool which is designed for meta-analysis of genome wide association studies. This work introduces an easy-to-use software package that includes several meta-analysis methods that are absent in similar software packages. PYRAMA is faster compared to other tools, supports robust methods for analysis and meta-analysis, fixed-effects, random-effects and Bayesian meta-analysis and it is currently the only tool that supports meta-analysis with imputation of summary statistics. It is available both as a standalone tool and as a freely available web server. AVAILABILITY AND IMPLEMENTATION: https://github.com/pbagos/PYRAMA, https://doi.org/10.5281/zenodo.17830449.

Genome-Wide Association Study↗
PubMed2026

Tractor workflow: a scalable Nextflow framework for local ancestry-aware genome-wide association studies.

MOTIVATION: The routine exclusion of admixed individuals from traditional genome-wide association studies (GWAS) due to concerns about spurious associations has limited multi-ancestry genetic discovery. Tractor addresses this issue by incorporating local ancestry into association testing, enabling the identification of ancestry-enriched signals and generating ancestry-specific summary statistics. However, adoption has been constrained by the complexity of prerequisite steps, including phasing and local ancestry inference, which require substantial bioinformatics expertise and introduce key analytical decision points. RESULTS: We developed a scalable, automated Nextflow workflow that integrates phasing, local ancestry inference, and Tractor association testing into a reproducible end-to-end pipeline. To demonstrate its utility, we applied the workflow to 32 blood biomarkers in 6245 two-way African-European admixed individuals from the UK Biobank. This pipeline performed efficiently at scale, replicating known associations and uncovering key ancestry-specific loci. These associations were largely driven by variants present on African ancestral tracts but absent from European tracts, underscoring the value of local ancestry-aware methods in uncovering previously masked genetic signals. AVAILABILITY AND IMPLEMENTATION: The workflow is modular, customizable, and compatible with commonly used phasing and local ancestry tools, minimizing manual intervention while preserving analytical flexibility. By lowering technical barriers to implementation, this framework facilitates broader adoption of local ancestry-aware GWAS, paving the way for expanded genetic discovery.

Humans↗
PubMed2026

Chromosome-scale genome assembly and genomic prediction of essential oil compounds in Atractylodes lancea for genomics-assisted breeding.

Atractylodes lancea rhizomes are used as crude drugs. Essential oil compounds, including atractylodin, hinesol, β-eudesmol, and atractylon, are key determinants of crude drug quality. Conventional breeding of A. lancea is difficult because of its perennial growth. In this study, a chromosome-scale reference genome of A. lancea (4.79 Gb) was generated, and genome-wide association studies (GWAS) and genomic predictions of essential oil compounds were conducted to explore the potential for genome-assisted breeding. Genotyping of 480 lines using double-digest restriction-site-associated DNA-sequencing yielded 29,136 high-quality SNPs. All the compounds showed high genomic heritability (h2 = 0.758-0.915), indicating strong genetic control. Despite the high genomic heritability, GWAS detected only one weak association with atractylon and no significant loci for the three compounds. However, genomic prediction achieved moderate to high accuracy across multiple models, particularly the ridge regression, genomic best linear unbiased prediction, and Bayesian approaches. The prediction accuracy, measured as the Pearson correlation coefficient between the observed and predicted values, exceeded 0.6 for all four essential oil compounds. These results demonstrate the efficacy of genomic selection for improving essential oil compound levels in A. lancea and provide a foundation for genome-assisted breeding of medicinal plants with long breeding cycles.

Atractylodes lancea↗
PubMed2026

Genetic determinants of childhood blood pressure and heart rate in relation to adult health outcomes: the consortium of childhood blood pressure.

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.

Humans↗
PubMed2022

Scalable approaches for functional analyses of whole-genome sequencing non-coding variants.

Non-coding genetic variants outside of protein-coding genome regions play an important role in genetic and epigenetic regulation. It has become increasingly important to understand their roles, as non-coding variants often make up the majority of top findings of genome-wide association studies (GWAS). In addition, the growing popularity of disease-specific whole-genome sequencing (WGS) efforts expands the library of and offers unique opportunities for investigating both common and rare non-coding variants, which are typically not detected in more limited GWAS approaches. However, the sheer size and breadth of WGS data introduce additional challenges to predicting functional impacts in terms of data analysis and interpretation. This review focuses on the recent approaches developed for efficient, at-scale annotation and prioritization of non-coding variants uncovered in WGS analyses. In particular, we review the latest scalable annotation tools, databases and functional genomic resources for interpreting the variant findings from WGS based on both experimental data and in silico predictive annotations. We also review machine learning-based predictive models for variant scoring and prioritization. We conclude with a discussion of future research directions which will enhance the data and tools necessary for the effective functional analyses of variants identified by WGS to improve our understanding of disease etiology.

Genome-Wide Association Study↗
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↗
PubMed2025

Plasma metabolites mediate the causal relationship between gut microbiota and erectile dysfunction: insights from Mendelian randomization study.

BACKGROUND: While the relationship between gut microbiota and erectile dysfunction (ED) has been reported, the specific pathways involved remain unclear. AIM: This study aims to investigate the causal relationship between gut microbiota and ED, and to identify the potential role of plasma metabolites as mediators. METHODS: Utilizing aggregated genome-wide association study (GWAS) data, a comprehensive two-sample Mendelian randomization (MR) analysis was performed involving 196 gut microbiota taxa, 1400 plasma metabolites and ED. Causal relationships between gut microbiota, plasma metabolites and ED were explored. In addition, mediation analysis was applied to identify the pathway from gut microbiota to ED mediated by plasma metabolites. OUTCOMES: This study reveals that plasma metabolites act as mediators regulating the influence of gut microbiota on ED. RESULTS: MR analysis identified causal relationships between six gut microbial taxa and ED, with Butyrivibrio increasing the risk of ED, while Alistipes, Prevotella 9, Dialister, Marvinbryantia, and LachnospiraceaeUCG010 exhibited protective effects. Additionally, 45 plasma metabolites demonstrated causal associations with ED. Finally, mediation analysis revealed four mediation relationships. Sensitivity analysis indicated no heterogeneity or pleiotropy in this study. CLINICAL IMPLICATIONS: Modulating gut microbiota or targeting specific metabolites may offer new therapeutic approaches for ED, highlighting the potential for microbiome-based interventions. STRENGTHS AND LIMITATIONS: The MR approach and large-scale GWAS data provide robust causal evidence, but the findings are limited by their focus on European populations and lack of experimental validation. Further studies are needed to confirm these mechanisms in diverse cohorts and functional models. CONCLUSION: This study establishes a causal link between gut microbiota, plasma metabolites, and ED, identifying specific microbial taxa and metabolites as key contributors to ED risk. The mediating role of plasma metabolites highlights potential therapeutic strategies, such as probiotics or dietary interventions targeting harmful metabolites.

Mendelian randomization↗