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PubMed2025

Cross-Phenotype Genome-Wide Association Study on the Shared Genetic Susceptibility to Systemic Sclerosis and Primary Biliary Cholangitis.

OBJECTIVE: An increased risk of primary biliary cholangitis (PBC) has been reported in patients with systemic sclerosis (SSc). Our study aims to investigate the shared genetic susceptibility between the two disorders and to define candidate causal genes using cross-phenotype genome-wide association study (GWAS) meta-analysis. METHODS: We performed cross-phenotype GWAS meta-analysis and Bayesian colocalization analysis for patients with SSc and patients with PBC. We performed both genome-wide and locus-based analysis, including tissue and pathway enrichment analyses, fine-mapping, Bayesian colocalization analyses with expression quantitative trait loci and protein quantitative trait loci (pQTL) datasets, and phenome-wide association studies. Finally, we used an integrative approach to prioritize candidate causal genes from the novel loci. RESULTS: We detected a strong genetic correlation between SSc and PBC (global genetic correlation = 0.84, P = 1.7 × 10-6). In the cross-phenotype GWAS meta-analysis, we identified 44 nonhuman leukocyte antigens loci that reached genome-wide significance (P < 5 × 10-8). Evidence of shared causal variants between patients with SSc and patients with PBC was found for nine loci, five of which were novel. Integrating multiple sources of evidence, we prioritized CD40, ERAP1, PLD4, SPPL3, and CCDC113 as novel candidate causal genes. The CD40 risk locus colocalized with trans-pQTLs of multiple plasma proteins involved in B cell function. CONCLUSION: Our study supports a strong shared genetic susceptibility between SSc and PBC. Using cross-phenotype analyses, we have prioritized several novel candidate causal genes and pathways for these disorders.

Humans↗

PubMed2025

EP300-mediated lactylation leads to ulcerative colitis via CD86-positive plasmacytoid dendritic cells: A Mendelian randomization and mediation analysis.

This study explores the potential mechanism between lactylation and ulcerative colitis (UC) using two-sample Mendelian randomization and multi-omics analysis. This study employed expression quantitative trait loci and protein quantitative trait loci as exposures, with UC from the Finnish database as the outcome, to conduct Mendelian randomization analysis on lactylation-related target genes, aiming to investigate the causal relationships between these exposures and the outcome. Sensitivity and pleiotropy tests, combined with colocalization analysis, are performed to identify the best target genes and ensure the robustness of the results. Finally, immune cells are included for mediation analysis between lactylation and UC to explore potential mechanisms of action. Through Mendelian randomization analysis combined with sensitivity and pleiotropy tests, 2 lactylation target genes were found to have a significant causal relationship with UC. Subsequent colocalization analysis confirmed EP300 as a potential gene target. After including immune cells in the mediation analysis, it was discovered that there is a potential mechanism involving EP300, CD86+ plasmacytoid dendritic cells (pDCs), and UC. There is a significant causal relationship between lactylation and UC. Furthermore, the lactylation-modified gene EP300 may lead to UC occurrence by regulating CD86+ pDCs.

Humans↗

PubMed2025

Multi-omics Mendelian randomization integrating RNA-seq, eQTL and pQTL data revealed CPXM1 as a potential drug target for osteoporosis.

Osteoporosis, a prevalent skeletal disorder characterized by decreased bone mineral density and increased fracture risk, continues to be a major global health concern. Traditional treatments for osteoporosis have limited efficacy and safety profiles, highlighting the need for novel therapeutic targets. This study integrates multi-omics data, including RNA-seq, expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) data, through Mendelian randomization (MR) to identify potential drug targets for osteoporosis. By leveraging bidirectional two-sample MR analysis, we identified CPXM1 (Carboxypeptidase X, M14 family member 1) as a novel gene that is causally linked to osteoporosis risk. Through transcriptomic and proteomic validation, we demonstrate that CPXM1 was upregulated in aged bone tissues and osteoporotic conditions in both human and murine models. Gene set enrichment analysis (GSEA) revealed significant dysregulation of bone homeostasis pathways, including increased extracellular matrix degradation and suppression of osteoblast differentiation in aged mice. Furthermore, phenome-wide association studies (PheWAS) confirmed minimal off-target effects of CPXM1, reinforcing its potential as a therapeutic target. Finally, computational drug repurposing predicted several promising drug candidates, including Doxorubicin, 5-Fluorouracil, and 2-Methylcholine, which may target CPXM1 pathways for osteoporosis treatment. These findings highlight CPXM1 as a potential biomarker and therapeutic target, offering new avenues for osteoporosis therapy.

Osteoporosis↗

PubMed2026

Genetic evidence supports the prioritization of CD40 among prespecified immune-related candidate drug targets in myasthenia gravis.

AIM: To prioritize prespecified immune-related candidate drug targets in myasthenia gravis for further validation based on integrated genetic evidence. METHODS: We integrated drug-target Mendelian randomization (MR) using cis-expression quantitative trait loci (cis-eQTLs), protein-level MR of plasma CD40 abundance using plasma protein quantitative trait loci (pQTLs), and colocalization analyses to evaluate genetically proxied associations with overall MG, early-onset myasthenia gravis (EOMG), and late-onset myasthenia gravis (LOMG). RESULTS: In this study, CD40 showed the most consistent genetic evidence among the six prespecified targets. Effect estimates are reported as odds ratios (ORs) with 95% confidence intervals (CIs). Higher CD40 expression proxied by cis-eQTLs was associated with increased risk of overall MG (OR = 1.14, 95% CI: 1.05-1.24, Bonferroni-adjusted p = 0.022) and EOMG (OR = 1.32, 95% CI: 1.12-1.56, Bonferroni-adjusted p = 0.015). Genetically predicted higher plasma CD40 protein abundance was associated with increased overall MG risk (OR = 1.31, 95% CI: 1.08-1.57, Bonferroni-adjusted p = 0.010), whereas the protein-level MR result for EOMG was directionally consistent but not statistically significant. Colocalization analysis provided suggestive but not definitive evidence of colocalization between CD40 expression and EOMG risk. FCGRT, IL2RA, and SYK showed additional exploratory MR signals requiring further validation. CONCLUSION: CD40 showed the most consistent genetic support among the prespecified targets, supporting its prioritization for functional validation and further therapeutic investigation in MG.

CD40↗

PubMed2026

Plasma proteins are integral to cross-tissue gene regulatory networks implicated in cardiometabolic disorders and coronary artery disease.

The plasma proteome has demonstrated promise for identifying diagnostic markers for cardiometabolic disorders (CMDs) and coronary artery disease (CAD). However, identifying the organ of origin for these biomarkers is critical for establishing biological relevance. We performed a multi-omic integrative analysis across multiple tissues from the STARNET study by profiling 974 plasma proteins in 532 CAD patients, integrating RNA sequencing (RNA-seq) data from the arterial wall, major metabolic organs, and blood. We identified 144 cis-protein quantitative trait loci in plasma, colocalizing with tissue cis-expression quantitative trait loci. Additionally, by mapping tissue mRNA "seed genes," we traced 262 plasma proteins to their source organs, primarily the liver. Crucially, we found that 851 plasma proteins are associated with the activity of cross-tissue gene regulatory networks (GRNs), including GRNs implicated in CMD and CAD development. Our findings demonstrate that plasma proteins are integral components of GRNs, with potential for developing reliable diagnostics and precise therapeutic targets. A record of this paper's transparent peer review process is included in the supplemental information.

cardiometabolic disorders↗

PubMed2026

Proteome-wide Mendelian randomisation of lung function to identify potential therapeutic targets for respiratory disease.

BACKGROUND: Despite multiple clinical trials, disease-modifying treatments for COPD are currently limited. Since many drugs target proteins, identifying causality between proteins and lung function informs understanding of COPD pathophysiology and may suggest novel targets. We used Mendelian randomisation (MR) to prioritise proteins as potentially causal for imparied lung function. For prioritised proteins, we explored their potential suitability as drug targets by predicting their effects on a range of clinical outcomes. METHODS: We used genome-wide association study (GWAS) data on 2923 proteins (n=48 195, UK Biobank) to identify single genetic variants (protein quantitative trait loci (cis-pQTLs)) associated with protein levels (p≤5×10-9, variant ≤100 kb of a transcription start site). We performed cis-pQTL-MR analyses of four spirometric traits (n=149 166, 36 independent cohorts). Sensitivity analyses included colocalisation and reverse direction MR. We report associations between cis-pQTLs for prioritised proteins and multiple clinical respiratory outcomes, and use phenome-wide analysis to explore potential adverse effects or drug repurposing opportunities. FINDINGS: 1841 proteins had a suitable cis-pQTL. We implicated 16 proteins as potentially causal for lung function (p<1.71×10-5): seven proteins have not been implicated by previous lung function GWAS or MR (CCND2, DTD1, PILRA, PTPRK, TDRKH, GRHPR, NUDT5), and we provide corroborative evidence for 10 proteins. We add to the literature identifying surfactant protein D (SFTPD) as a candidate, yet predict that integrin subunit alpha V (ITGAV) inhibition could impair some lung function measures, mimicking adverse results from a recent trial. INTERPRETATION: Our approach identifies proteins (some novel) that are potentially therapeutic targets for respiratory disease, and which warrant follow-up for utility and safety.

Journal Article↗

PubMed2025

Association Analysis of the Circulating Proteome With Sarcopenia-Related Traits Reveals Potential Drug Targets for Sarcopenia.

BACKGROUND: Sarcopenia severely affects the physical health of the elderly. Currently, there is no specific drug available for sarcopenia. This study aims to identify pathogenic proteins and druggable targets for sarcopenia through Mendelian randomization (MR)-based analytical framework. METHODS: A sequential stepwise screening method that includes two-sample MR, Steiger filtering test and colocalization (MRSC) was applied to identify causal proteins associated with sarcopenia-related traits. In the MR analyses, 4372 circulating proteins with valid instrumental variables (IVs) from eight proteomic genome-wide association studies were utilized as exposures, and nine sarcopenia-related traits were utilized as outcomes. IVs were classified into cis-protein quantitative trait loci (pQTLs) and trans-pQTLs based on their positions. We conducted cis-only MRSC analyses and cis + trans MRSC analyses using cis-pQTLs and cis + trans pQTLs as IVs, respectively. Post-MRSC analyses were conducted on the prioritized findings of MRSC, including annotation of protein-altering variants (PAVs), assessment of overlap between pQTLs and expression quantitative trait loci (eQTLs), protein-protein interaction (PPI) analysis, pathway enrichment analysis and annotation of drug targets. Utilizing data from the UK Biobank, we performed an observational study to explore the associations between baseline circulating protein levels and the longitudinal changes in nine sarcopenia-related traits. RESULTS: A total of 181 causal associations for 65 proteins were prioritized by the cis-only MRSC analyses and 227 associations for 91 proteins were prioritized by the cis + trans MRSC analyses. Among the prioritized proteins, the majority of them employed non-PAVs as IVs and most of their cis-pQTLs overlapped with corresponding eQTLs and exhibited consistent directionality, with only one trans-pQTL overlapping with an eQTL. The PPI network of cis-only MRSC-prioritized proteins (p = 4.04 × 10-4) and cis + trans MRSC-prioritized proteins (p = 8.76 × 10-5) showed significantly more interactions than expected. Reactome, KEGG and GO pathway enrichment analyses for cis-only MRSC-prioritized proteins identified 52, 12 and 79 enriched pathways, respectively (adjusted p < 0.05). For proteins identified by cis + trans MRSC analyses, only 15 pathways were enriched through the GO pathway enrichment analyses. In the observational study, 197 circulating proteins were identified to be associated with one or more sarcopenia-related traits (p < 0.05/2923). Among them, the significant associations of CTSB (negative association) and ASGR1 (positive association) with sarcopenia-related traits were observed to have consistent directional associations in both MR-based studies and observational studies. Drug target annotations suggested that 52 MRSC-prioritized proteins and 145 biomarkers are drug targets or druggable. CONCLUSIONS: This study identified 89 potential pathogenic proteins and 197 candidate biomarkers for sarcopenia, providing valuable clues for the development of therapeutic drugs for sarcopenia.

Humans↗

PubMed2026

Integrative proteogenomic and observational analysis identifies potential biomarkers for latent autoimmune diabetes in adults.

BACKGROUND: Latent autoimmune diabetes in adults (LADA) shares core genetic and immunological features with type 1 diabetes (T1D) but is frequently misdiagnosed as type 2 diabetes (T2D). With few biomarkers for its timely diagnosis and management, this study integrated proteome-wide Mendelian randomisation (MR) and observational clinical analysis to identify potential LADA biomarkers. METHODS: We performed proteome-wide MR using cis-protein quantitative trait loci (cis-pQTLs) for 1,389 plasma proteins from the deCODE study (n = 35,559) and genome-wide association study (GWAS) data for LADA (2,634 cases and 5,947 controls, European ancestry). Robustness was enhanced via multiple sensitivity analyses. Pathway enrichment analysis, druggability evaluation, phenome-wide MR, and interaction analyses were performed to investigate the clinical relevance and biological context of candidate proteins. Candidate proteins were further evaluated using enzyme-linked immunosorbent assays in a matched Chinese clinical study (n = 241) to assess their discriminative ability for LADA. RESULTS: Proteome-wide MR and colocalisation analyses indicated associations between genetically predicted plasma levels of C-X-C motif chemokine ligand 10 (CXCL10; OR [95% CI] per 1-SD increase in protein levels: 5.49 [1.74,17.32]), serum amyloid A1 (SAA1; 1.28 [1.14,1.45]), and SAA2 (1.22 [1.11,1.34]) with LADA risk. Replication, multi-tissue eQTL, and multivariable MR supported CXCL10's association. Druggability evaluation suggested CXCL10 as a drug target under investigation, and phenome-wide MR of 1,006 diseases and traits indicated no major safety concerns for CXCL10 as a potential biomarker. In the observational clinical study, CXCL10 differentiated LADA from healthy controls (area under the receiver operating characteristic curve [ROC-AUC]: 0.889; precision-recall area under the curve [PR-AUC]: 0.919) and T2D (ROC-AUC: 0.838; PR-AUC: 0.921), with both models showing adequate calibration. CONCLUSIONS: This study suggests that CXCL10 is a putative biomarker associated with LADA, demonstrating discriminative ability to distinguish LADA from T2D in an observational clinical cohort. These findings contribute to understanding the autoimmune molecular aetiology of LADA and support its diagnostic potential in resolving the clinical ambiguity between LADA and T2D.

Humans↗

PubMed2025

Circulating inflammatory proteins as causal drivers and therapeutic targets in asthma: insights from genetic and pathway-based analyses.

OBJECTIVE: To identify circulating inflammatory proteins with potential causal roles in asthma development through integrated genetic and pathway-based analyses, and to evaluate their potential as therapeutic targets. METHODS: We used genetically anchored instrumental variables from 180 protein quantitative trait loci (pQTLs) to assess the causal effects of 91 circulating inflammatory proteins on asthma risk, using large-scale GWAS datasets. Analytical robustness was evaluated through pleiotropy and heterogeneity testing. Functional enrichment and literature-based pathway analyses were performed to support biological plausibility and validate findings. RESULTS: Four proteins showed significant causal effects on asthma: CCL19 and LIFR were protective (OR = 0.89 and 0.91, p ≤ 6.8E-03), while ARTN and IL6 were associated with increased risk (OR = 1.15 and 1.18, p ≤ 1.1E-04). We also identified reverse causal effects of asthma on 11 cytokines, including MMP10, TGFB1, IL33, and IL18R1. Most of these proteins were enriched in pathways related to cytokine signaling and immune response (p < 0.001). All identified proteins had prior literature support linking them to asthma or airway inflammation. CONCLUSIONS: Our findings highlight a subset of circulating inflammatory proteins that are likely causal in asthma pathogenesis and may serve as promising targets for therapeutic intervention. These results offer novel insights into the immunological mechanisms underlying asthma and support the utility of genetic causal inference in target prioritization.

Asthma↗

PubMed2025

The proteogenomic landscape of the human kidney and implications for cardio-kidney-metabolic health.

Nearly one-third of the global population is affected by cardio-kidney-metabolic (CKM) diseases; however, the molecular mechanisms underlying CKM diseases are poorly understood. Here we show that tissue proteomics provide critical insights not captured by tissue gene expression or blood proteomics information by performing whole-genome and RNA sequencing and proteomics analysis of human kidney samples (n = 337), and we generated a publicly available database. Via Bayesian co-localization and Mendelian randomization analyses of kidney protein quantitative trait loci and 36 CKM genome-wide association studies, we prioritized 89 proteins for CKM traits. We prioritized relationships that could underlie the interconnectedness of CKM traits and discovered multiple and targetable mechanisms for CKM diseases, including the potential role of kidney angiopoietin-like protein 3 (ANGPTL3) in serum lipid levels and kidney function as well as the role of charged multivesicular body protein 1A in kidney function and hypertension. Notably, we identify pathways with confluence of evidence from genetic loci, tissue gene expression and protein levels for CKM traits. In summary, our large-scale kidney proteomics study uncovers proteins and targetable mechanisms prioritized for CKM diseases.

Humans↗

PubMed2026

Disentangling adiposity-related and non-adiposity-related genetic pathways for type 2 diabetes.

OBJECTIVE: To identify circulating proteins associated with type 2 diabetes (T2D) risk through pathways not fully explained by body mass index (BMI), and to assess therapeutic actionability. RESEARCH DESIGN AND METHODS: We applied GWAS-by-subtraction within a genomic structural equation model to European ancestry summary statistics for T2D (74,124 cases, 824,006 controls) and BMI (n = 681,275), partitioning T2D liability into BMI-related and BMI-subtracted components. We then performed proteome-wide Mendelian randomization (MR) using cis-protein quantitative trait loci from four plasma proteomics cohorts: ARIC, deCODE, Fenland, and the UK Biobank Pharma Proteomics Project. Prioritized proteins passed sensitivity analyses with alternative MR methods and were supported by colocalization evidence. Tissue-resolution regulatory support was assessed using cis-eQTL colocalization across GTEx and pancreatic islet, subcutaneous adipose, and whole-blood resources. Actionability was evaluated using the druggable genome and Open Targets. RESULTS: GWAS-by-subtraction attenuated the genetic correlation between BMI and BMI-subtracted T2D from 0.54 (SE 0.02) to 0.35 (SE 0.02). Proteome-wide MR prioritized 29 proteins for BMI-subtracted T2D. Thirteen showed eQTL colocalization in at least one tissue, implicating liver and intermediary metabolism (GCDH, NOTCH2), pancreatic islet biology (CTRB2, MANBA), adipose and Wnt signaling (RSPO3, GALNT3), and whole blood regulatory signals (PAM, SNUPN). Sixteen proteins were classified within druggable-genome Tiers 1-3, and five had existing Open Targets compounds. CONCLUSIONS: Integrating GWAS-by-subtraction, proteome-wide MR, and colocalization nominated 29 proteins associated with T2D liability not fully explained by BMI. These findings highlight genetically supported targets for follow-up studies of T2D therapies that complement weight-centered approaches.

Journal Article↗

PubMed2026

A regulatory network underlying idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease in which genetic susceptibility interacts with epithelial, immune, and mesenchymal remodeling. Although the chromosome 11p15.5 locus contains established IPF susceptibility signals near MUC5B and TOLLIP, the broader regulatory architecture of this region remains incompletely resolved. METHODS: We integrated IPF genome-wide association study summary statistics with methylation, expression, and protein quantitative trait loci using summary-data-based Mendelian randomization (SMR). SMR-prioritized candidates were evaluated in independent transcriptomic and methylation cohorts and further contextualized using microRNA, transcription-factor, protein-interaction, machine-learning, single-cell, and spatial transcriptomic analyses. Fibrosis-associated expression patterns were assessed in a bleomycin-induced pulmonary fibrosis rat model. RESULTS: The analyses recovered the established MUC5B and TOLLIP signals and prioritized BRSK2 as a comparatively underexplored candidate supported by eQTL-based SMR and independent molecular evidence. The BRSK2 pQTL association did not pass the HEIDI test and was therefore not interpreted as convergent protein-level genetic evidence. Network analyses linked BRSK2 to cell-cycle, metabolic-stress, and senescence-related programs, while cross-cohort machine learning prioritized FOXA2, CDC25B, and NFE2 as informative network features. Single-cell and spatial analyses localized BRSK2 preferentially to fibroblast and myofibroblast compartments and to regions with greater histological fibrosis severity. In fibrotic rat lungs, BRSK2 expression increased, whereas FOXA2 and CDC25B decreased at the transcript and protein levels. CONCLUSIONS: These findings refine the molecular landscape of the chromosome 11p15.5 IPF susceptibility locus and prioritize BRSK2 as a candidate component of an IPF-associated profibrotic fibroblast state. Its causal contribution, direct regulatory relationships, and therapeutic tractability require targeted mechanistic validation.

Idiopathic Pulmonary Fibrosis↗

PubMed2026

Multi-omics Mendelian Randomization Prioritizes Neutrophil Extracellular Trap-related Genes Associated with Atrial Fibrillation Risk.

BACKGROUND: Neutrophil extracellular traps (NETs) participate in thrombosis, inflammation, and cardiovascular remodeling, yet whether NET-related genes (NRGs) are associated with atrial fibrillation (AF) risk across multiple molecular layers remains unclear. This study used a multiomics Mendelian randomization framework to prioritize NRGs supported by methylation, expression, and protein quantitative trait loci (QTL) data. METHODS: Genome-wide significant cis instruments (P < 5 × 10-8) were obtained for 90 methylation QTLs (mQTLs), 100 expression QTLs (eQTLs), and 38 protein QTLs (pQTLs) mapped to 137 literature- curated NRG entries. Summary-data-based Mendelian randomization (SMR) coupled with the heterogeneity in dependent instruments (HEIDI) test was applied using whole-blood mQTL data (n = 1,980), eQTLGen blood eQTL data (n = 31,684), and deCODE plasma pQTL data (n = 35,559). AF outcome data were obtained from a meta-analysis including 60,620 cases and 970,216 controls of European ancestry. RESULTS: At the methylation level, 21 CpG-feature associations across 13 genes remained significant after HEIDI filtering and false discovery rate (FDR) correction. Expression-level analysis identified eight significant gene-AF associations, whereas protein-level analysis identified seven significant features representing five unique proteins. Cross-omics integration prioritized C3, MAPK3, and STAT3 as Tier 1 genes, CTSC, LPAR3, and THBD as Tier 2 genes, and fourteen additional genes as Tier 3 candidates. C3 showed risk-increasing protein-level associations together with multiple significant CpG signals, whereas MAPK3 and STAT3 showed directionally protective expression/protein or methylation/protein patterns. DISCUSSION: The cross-omics convergence on C3, MAPK3, and STAT3 is consistent with complement activation, immune-fibrotic signaling, and cytokine-regulatory pathways implicated in AF biology, but the findings should be interpreted as genetic prioritization rather than definitive intervention-ready causality. CpG-level heterogeneity at the C3 locus and the blood/plasma origin of the QTL resources further support a cautious interpretation. Modest colocalization support and the unresolved possibility of pQTL sample overlap further support this cautious, hypothesis-generating interpretation. CONCLUSION: Multi-omics SMR prioritizes C3, MAPK3, and STAT3 as the most consistently supported NET-related genes associated with AF risk. These findings provide a framework for atrialtissue replication and mechanistic validation of NET-related pathways in AF.

Atrial fibrillation↗

PubMed2026

Multitarget interactions of bisphenol A in polycystic ovary syndrome: evidence from integrated network toxicology, mendelian randomization, and molecular docking.

OBJECTIVE: To study the potential pathogenic mechanisms of bisphenol A (BPA) in polycystic ovary syndrome (PCOS) using an integrative computational strategy. DESIGN: Integrative computational study combining network toxicology, Mendelian randomization (MR), and molecular docking. SUBJECTS: For MR analysis, genetic data were sourced from large European-ancestry cohorts, including plasma protein quantitative trait loci data and genome-wide association study summary statistics for PCOS (3,045 cases and 267,780 controls). EXPOSURE: In silico exposure to BPA for target prediction; genetically predicted plasma protein levels for causal inference. MAIN OUTCOME MEASURES: Identification of overlapping targets between BPA and PCOS; functional enrichment pathways; causal effects of prioritized proteins on PCOS risk (odds ratios with 95% confidence intervals); binding affinities between BPA and core targets (kcal/mol). RESULTS: Network toxicology identified 310 overlapping targets between BPA and PCOS. Enrichment analyses revealed significant involvement in endocrine signaling, inflammatory pathways (eg, IL-17), and cellular processes. MR demonstrated that genetically elevated levels of RET, CXCL8, HTR6, MMP1, MMP9, NTRK1, and TNNI2 were significantly associated with increased PCOS risk, whereas higher PSAP and SHBG levels were protective. Molecular docking confirmed stable binding between BPA and all nine key targets, with strongest affinity for SHBG (-8.4 kcal/mol), followed by NTRK1, TNNI2, and RET. CONCLUSION: This integrative investigation suggests that BPA may contribute to PCOS pathogenesis through multitarget interactions involving inflammatory mediators, endocrine regulators, and tissue remodeling proteins. The findings provide prioritized targets and mechanistic insights for future experimental validation and environmental risk assessment.

Female↗

PubMed2026

GWAS Meta-analysis Identifies Novel Associated Loci and Points to Causal Tissues in Central Serous Chorioretinopathy.

OBJECTIVE: To define CSC genetic architecture and identify implicated ocular tissues, cell types, genes, and circulating proteins. DATA SOURCES: Genome-wide data were assembled from FinnGen, All of Us, Mass General Brigham Biobank, Million Veteran Program, and a Dutch chronic CSC cohort. Serum protein quantitative trait loci, human single-cell ocular atlases, and UK Biobank macular optical coherence tomography (OCT) imaging were used for downstream analyses. STUDY SELECTION: Five European-ancestry cohorts with genome-wide data and cohort-specific CSC case-control definitions were included, comprising 2,584 cases and 1,044,455 controls. Variants present in at least 2 cohorts were meta-analyzed. DATA EXTRACTION AND SYNTHESIS: Cohort-level GWASs were adjusted for age, age squared, sex, genotyping array or batch, and 10 genetic principal components, then combined using fixed-effects inverse-variance meta-analysis. Post-GWAS analyses included gene prioritization, colocalization, Mendelian randomization, single-cell disease-relevance scoring, and testing of a CSC genetic risk score in UK Biobank OCT images. MAIN OUTCOMES AND MEASURES: Genome-wide significant CSC loci, effector genes and proteins, tissue and cell-type enrichment, and CSC-relevant OCT abnormalities. RESULTS: Across 11,068,938 variants, 10 loci reached genome-wide significance (P < 5 × 10-8), including 3 novel loci near TGFB1, LINC00551, and LOC105375630 and 7 replicated loci near CFH, CD46, NOTCH4, PREX1, PTPRB, GATA5, and TNFRSF10A. Integrative analyses prioritized 10 candidate effector genes. Colocalization and Mendelian randomization implicated circulating TNFRSF10A, TGFB1, and CASP10 levels. Single-cell analyses localized genetic risk to sclera (P = 2.0 × 10-4) and vascular endothelial cells (P = 4.0 × 10-4), with fibroblast enrichment. In UK Biobank, OCT abnormalities were more frequent in the top vs bottom 1% of CSC genetic risk (18 of 109 [16.5%] vs 8 of 134 [6.0%]; odds ratio, 4.05; 95% CI, 1.65-10.87; P = .002). CONCLUSIONS AND RELEVANCE: In this GWAS meta-analysis, CSC susceptibility localized predominantly to scleral and vascular biology rather than primary retinal pigment epithelial dysfunction. These findings support CSC as a sclerovascular disorder and nominate complement regulation, endothelial signaling, and extracellular matrix pathways for future study.

Journal Article↗

PubMed2025

New evidence for the protective effect of gut microbiota regulation of ferroptosis-related proteins against osteoporosis.

Osteoporosis (OP), characterized by bone degradation and increased fracture susceptibility, constitutes a significant global health burden. Recent findings implicate gut microbiota and ferroptosis in the regulation of bone metabolism; however, causal evidence for the gut microbiota's influence on OP specifically via ferroptosis regulation remains to be established. This study employed two-sample Mendelian randomization (MR) using genome-wide association study (GWAS) summary statistics to investigate these causal relationships and delineate mediating pathways.We assessed causal links between gut microbiota, ferroptosis-related proteins, and OP risk. Associations for gut microbiota abundance and ferroptosis-related proteins were derived from GWAS data and Icelandic blood-derived protein quantitative trait loci, respectively. Outcome data for OP were obtained from the FinnGen Release R12. The primary analysis utilized the inverse variance weighted (IVW) method, supplemented by sensitivity analyses to evaluate heterogeneity and horizontal pleiotropy.  MR analysis identified 33 gut microbial taxa causally associated with OP risk: 13 protective and 20 detrimental. Similarly, 34 ferroptosis-related proteins were categorized as protective (18) or detrimental (16) for OP. Mediation analysis revealed that the protective effect of Terrisporobacter othiniensis on OP is partially mediated by the ferroptosis regulator MDM4 (indirect effect β = -0.020, 95% CI: -0.068 to 0.029), accounting for 6.8% of the total effect. Sensitivity analyses showed no significant evidence of heterogeneity or horizontal pleiotropy. This study provides the first genetically validated evidence supporting a causal relationship between specific gut microbiota, ferroptosis-associated proteins, and OP susceptibility. Specifically, Terrisporobacter othiniensis demonstrates a novel protective mechanism, modulating OP risk partly through the ferroptosis regulator MDM4. These findings broaden understanding of the "gut-bone axis" and highlight the gut microbiota-ferroptosis pathway, particularly the MDM4/p53 axis, as a promising target for novel OP prevention and therapeutic strategies.

Ferroptosis↗

PubMed2025

Soluble Immune Checkpoint Protein and Lipid Network Associations with All-Cause Mortality Risk: Trans-Omics for Precision Medicine (TOPMed) Program.

Adverse cardiovascular events are emerging with the use of immune checkpoint therapies in oncology. Using datasets in the Trans-Omics for Precision Medicine program (Multi-Ethnic Study of Atherosclerosis, Jackson Heart Study [JHS], and Framingham Heart Study), we examined the association of immune checkpoint plasma proteins with each other, their associated protein network with high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C), and the association of HDL-C- and LDL-C-associated protein networks with all-cause mortality risk. Plasma levels of LAG3 and HAVCR2 showed statistically significant associations with mortality risk. Colocalization analysis using genome wide-association studies of HDL-C or LDL-C and protein quantitative trait loci from JHS and the Atherosclerosis Risk in Communities identified TFF3 rs60467699 and CD36 rs3211938 variants as significantly colocalized with HDL-C; in contrast, none colocalized with LDL-C. The measurement of plasma LAG3, HAVCR2, and associated proteins plus targeted genotyping may identify patients at increased mortality risk.

Journal Article↗

PubMed2026

Cross-ancestry proteome-wide Mendelian randomization prioritizes 12 plasma protein candidates for breast cancer risk.

The plasma proteome provides a molecular bridge between genetic variation and disease risk, yet its contribution to breast cancer susceptibility across ancestries remains unclear. We conducted a proteome-wide Mendelian randomization (MR) study of 2,923 plasma proteins using cis-protein quantitative trait loci from 34,557 European participants in the UK Biobank Pharma Proteomics Project, integrated with genome-wide association studies of 156,901 breast cancer cases and 204,634 controls of European, East Asian, and African ancestries. Cross-ancestry meta-analysis identified 12 candidate proteins associated with breast cancer risk (P < 2.5×10-5), including six previously reported and six newly implicated in MR studies. DNPH1 showed cross-ancestry heterogeneity, with a risk-increasing association in European populations and a nominally inverse association in East Asian populations. CASP8, RALB, and USP28 displayed subtype-differentiated associations. Orthogonal validation provided variable support: six demonstrated strong evidence of statistical colocalization; four replicated in an independent European proteomic dataset (deCODE, n = 35,559); two replicated in an independent East Asian proteomic dataset (JCTF, n = 1,384); and four were supported by polygenic-score analyses in the ancestrally diverse All of Us cohort (9,250 cases, 214,857 controls). These findings prioritize a high-confidence subset of plasma proteins, including LRRC25, PARK7, and LRRC37A2, for future mechanistic and translational investigation.

Mendelian randomization↗