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PubMed2026

Genetic overlap between depression and C-reactive protein levels: Evidence from a cross-trait analysis.

Inflammation and depression have been consistently associated, with elevated C-reactive protein (CRP) levels observed in a significant subset of affected individuals. However, the genetic mechanisms underlying this association remain poorly understood. We integrated results from large-scale genome-wide association studies (GWAS) of depression and CRP levels in a cross-trait analysis specifically focusing on identifying horizontally pleiotropic loci. Identified variants were stratified as concordant versus discordant based on their direction of effects on the two traits and followed up using functional annotation, gene set enrichment, and colocalization analyses. We also explored causal relationships using Mendelian Randomization (MR) analysis with extensive sensitivity analyses, including adjustment for body mass index (BMI). We identified 9 novel loci. Functional analyses revealed that concordant loci were enriched in genes linked to immune and inflammatory processes, while discordant loci mostly mapped to metabolic pathways, including lipid regulation. MR provided strong evidence for body mass index driving a causal relationship between the genetic liability of depression on CRP levels. Our findings suggest that the association between depression and CRP levels is partly driven by shared genetic influences, pointing to different biological pathways depending on whether genetic effects are concordant or discordant. These results underscore the importance of considering effect direction when assessing the genetic overlap between depression and inflammatory processes. In addition, they highlight BMI as a key factor in the causal relationship between depression and systemic inflammation.

C-Reactive Protein↗
PubMed2026

The tissue-specific effects of glucose-lowering drug targets on aging mediated through DNA methylation: a multi-omics genetic study.

BACKGROUND: DNA methylation plays a key role in mediating the anti-aging effects of glucose-lowering drugs. This study aims to systematically explore the potential anti-aging effects of target genes of FDA-approved glucose-lowering drugs and the underlying epigenetic mediators. METHODS: We conducted a two-sample Mendelian randomization (MR) study to investigate the putative causal relationships between the gene expression levels of glucose-lowering drug targets and 10 aging-related phenotypes, followed by a two-step MR to estimate the mediation effect of DNA methylation. Drug candidates were selected according to the latest review of clinical drug use for type 2 diabetes, and their target genes were obtained from the DGIdb. Tissue-specific cis-expression quantitative trait loci (eQTLs) from GTEx Consortium were selected as genetic instruments to proxy the expression level of drug-target genes. Glycemic phenotypes were used as positive controls to validate the instruments. The cis- and trans-methylation QTLs of Cytosine-phosphate-Guanine sites near the drug target genes were obtained from GoDMC Consortium. Additionally, we performed enrichment analyses focused on tissue specificity and aging pathways to further corroborate our findings. RESULTS: We obtained 194 target genes interacting with 36 FDA-approved anti-diabetic drugs, of which the tissue-specific eQTLs were used to proxy the drug target effects. MR showed strong evidence that nine interacting genes of six glucose-lowering drugs showed anti-aging potential on one or more aging-related phenotypes mediated by DNA methylation: EHMT2, HSPA4, IGF2BP2, IRS1, LPL, NDUFAF1, NDUFS3, SLC22A3, and TCF7L2. These genes were distributed in 17 tissues, especially in the central nervous system, suggesting a potential neural component in their anti-aging effects. For instance, expression of EHMT2 in several brain basal ganglia regions, where the gene interacted with Tolazamide, showed a protective effect on frailty (odds ratio (OR) in caudate = 1.02, 95%CI = 1.01-1.04, FDR adjusted P = 1.69 × 10-2; OR in putamen = 1.02, 95% CI = 1.01-1.03, PFDR = 3.37 × 10-2, OR in nucleus accumbens = 1.02, 95% CI = 1.01-1.04, PFDR = 3.37 × 10-2). These associations were externally validated by searching literature evidence in existing EWAS and TWAS studies, as well as evidence from enrichment analyses. CONCLUSIONS: This study prioritizes nine glucose-lowering genes as anti-aging drug targets in specific tissues and prioritizes their epigenetic regulation through DNA methylation for future drug development.

DNA Methylation↗
PubMed2026

Causal Relationships Between Oral Microbiota and Inflammatory Skin Diseases.

INTRODUCTION AND AIMS: The oral microbiome has been increasingly linked to systemic inflammation and immune dysregulation, but whether specific oral bacteria causally contribute to inflammatory skin diseases remains unclear due to confounding and reverse causation. This study aimed to assess the causal effects of 43 oral microbiota taxa on the risk of five inflammatory skin diseases using a Mendelian randomization (MR) approach. METHODS: We performed a two-sample MR analysis using genetic instruments for oral microbiota derived from publicly available genome-wide association studies and outcome data from the FinnGen consortium. Causal effects of oral taxa on systemic lupus erythematosus, vitiligo, pemphigus, localized scleroderma, and dermatitis herpetiformis were estimated. The inverse-variance weighted method served as the primary analysis, complemented by sensitivity analyses to evaluate horizontal pleiotropy, heterogeneity, and reverse causality. RESULTS: MR analyses identified several putative causal associations between oral microbiota and inflammatory skin diseases. Genus Granulicatella and an unknown Streptococcus species (ASV0009) showed causal effects on systemic lupus erythematosus. Family Lachnospiraceae_[XIV] and an unknown Rothia species (ASV0016) were associated with vitiligo. Five oral microbiota taxa demonstrated causal associations with pemphigus. Actinomyces species micronuciformis was linked to localized scleroderma. Order Fusobacteriales and an unknown Neisseria species (ASV0004) were associated with dermatitis herpetiformis. No significant heterogeneity or horizontal pleiotropy was detected in sensitivity analyses. CONCLUSION: This MR study provides genetic evidence supporting a causal role of specific oral bacteria in the development of several inflammatory skin diseases, highlighting the oral microbiome as a potential contributor to cutaneous autoimmunity and inflammation. CLINICAL RELEVANCE: Our findings highlight the putative role of the oral microbiome as a plausible candidate for mechanistic and clinical investigations into the prevention or adjunctive management of selected inflammatory skin diseases. However, oral hygiene improvement, targeted antimicrobials, and other microbiota-directed interventions were not directly tested in this MR study and remain hypothetical strategies requiring validation in experimental and clinical studies.

Humans↗
PubMed2026

Assessing the comorbidity between asthma and depression through polygenic risk scoring and time-to-event models.

BACKGROUND: Patients with asthma have an increased risk of developing depression, affecting their quality of life. To date, the processes contributing to this comorbidity remain unclear. METHODS: We integrated two large genome-wide association studies (88,486 patients with asthma and 447,859 controls; 412,024 patients with depression and 1,587,577 controls) with cross-sectional and longitudinal information available from the All of Us Research Program (N = 87,167) through polygenic risk scoring (PRS), Cox proportional-hazards models, one-sample Mendelian randomization (MR), and gene-set and drug-repurposing analyses. RESULTS: We observed that depression PRS was associated with increased asthma risk (hazard ratio, HR = 1.13, 95% CI = 1.09-1.17), also when accounting for comorbidity status (HR = 1.08, 95% CI = 1.04-1.12). Conversely, the effect of asthma PRS was null after accounting for comorbidity status. One-sample MR analysis showed an effect of depression genetic liability on asthma, ranging from beta = 0.36 ± 0.03 when considering a linear relationship to beta = 3.21 ± 0.31 when considering possible nonlinear relationships. Conversely, the effect of asthma genetic risk on depression was null after accounting for potential confounders. The gene-set analyses showed that asthma and depression polygenic risks share biological processes, molecular functions, and cellular components related to the immune system and the lung-brain axis. CONCLUSIONS: Genetic predisposition contributes to asthma-depression comorbidity through direct effects and shared pathogenic processes. These findings highlight the potential to develop targeted interventions to prevent and treat the co-occurrence of respiratory and neuropsychiatric disorders.

Comorbidity↗
PubMed2025

Bioavailable testosterone reduces the risk of lung squamous cell carcinoma: a comprehensive data study.

BACKGROUND: The association between testosterone and lung cancer remains unclear. This study investigates the relationship between testosterone levels and lung cancer risk, focusing on bioavailable testosterone levels (BTLs), total testosterone levels (TTLs), and sex hormone-binding globulin (SHBG) in relation to lung cancer subtypes. METHODS: We utilized bidirectional and multivariable Mendelian randomization (MR) analyses based on genome-wide association studies (GWAS) to assess causal links. To validate the findings clinically, immunohistochemical (IHC) staining for androgen receptor (AR) expression and survival analyses were conducted on a cohort of 90 patients with lung squamous cell carcinoma (LUSC). RESULTS: MR analysis demonstrated that higher BTLs were significantly associated with a reduced risk of LUSC (OR&#x2009;=&#x2009;0.365, P&#x2009;=&#x2009;0.001), while no significant associations were observed for TTLs or SHBG. Reverse MR analysis found no causal effect of lung cancer on testosterone levels. Multivariable MR confirmed BTLs as an independent protective factor. In the clinical cohort, AR expression was significantly associated with better prognosis, showing improved median progression-free survival (12.3 vs. 9.0 months, P&#x2009;=&#x2009;0.01) and median overall survival (35.3 vs. 29.4 months, P&#x2009;<&#x2009;0.01). Cox regression identified AR expression as an independent protective factor for patient outcomes. However, study limitations include potential residual confounding, ethnic heterogeneity between European GWAS data and Asian clinical cohorts, and the lack of direct experimental validation. CONCLUSIONS: Our findings suggest that higher BTLs may play a protective role against LUSC. BTLs and AR expression show potential as valuable biomarkers for the diagnosis and prognostic assessment of LUSC.

Humans↗
PubMed2025

The role of the brain-bone axis in skeletal degenerative diseases and psychiatric disorders, A genome-wide pleiotropic analysis.

INTRODUCTION: Skeletal degenerative diseases and psychiatric disorders often coexist clinically. However, the genetic correlations and underlying biological mechanisms between these two types of diseases remain unclear. OBJECTIVES: To investigate the genetic correlations between skeletal degenerative diseases and psychiatric disorders and to identify shared genomic loci, genes, and pathways. METHODS: This comprehensive genome-wide pleiotropic association study utilized summary statistics from publicly available genome-wide association data. Various statistical genetic correlation methods were employed, including LDSC, HDL, PLACO, Coloc, Hyprcoloc, and Mendelian randomization (MR) analysis, along with immune cell colocalization analysis. The study aimed to identify potential shared genetic factors among three skeletal degenerative diseases (osteoarthritis, intervertebral disc degeneration, and osteoporosis) and three psychiatric disorders (schizophrenia, anxiety disorder, and major depressive disorder). RESULTS: Analyses using LDSC, HDL, and Bonferroni corrections revealed significant genetic correlations between intervertebral disc degeneration (IVDD) and anxiety disorder (ANX); fractures, IVDD, and arthritis with major depressive disorder (MDD); and arthritis with schizophrenia (SCZ). Significant genetic correlations were also observed between VDD and ANX, fractures, IVDD, hip osteoarthritis (HipOA), knee osteoarthritis (KneeOA) and MDD, and KneeOA and SCZ. Pleiotropy analysis using PLACO, MAGMA, and multitrait colocalization Hyprcoloc identified 65 pleiotropic loci, 27 shared causal loci, and 9 shared risk loci involving immune cells related to both psychiatric and bone-related diseases. Additionally, tissue-specific enrichment analysis showed that genes mapped to these loci were enriched in brain, cardiovascular, pancreatic, and other tissues. The IVW method demonstrated that MDD increased the risk of IVDD and KneeOA, while IVDD increased the risk of ANX and MDD. Conversely, SCZ was associated with a reduced risk of KneeOA. Multiple sensitivity analyses further supported a positive causal effect of IVDD on MDD. CONCLUSION: These findings suggest significant genetic correlations between skeletal degenerative diseases and psychiatric disorders, highlighting multiple shared comorbid genes and key immune cell types. Importantly, the study supports the role of the brain-bone axis in the regulation of skeletal degenerative diseases and psychiatric disorders, which could provide valuable insights for potential therapeutic targets and interventions for these conditions.

Humans↗
PubMed2026

The causal relationships and potential pathways between birth weight and cardiovascular diseases: A human genomics study.

The causal relationships and potential pathways between birth weight (BW) and various cardiovascular diseases (CVDs) remain unclear, particularly when discriminating maternal and fetal contributions of BW to CVDs. Leveraging the genome-wide association studies (GWASs) of BW (N&#x2005;=&#x2005;321,223) and a range of CVDs (ncases&#x2005;=&#x2005;43,676-181,522), we performed a 2-sample Mendelian randomization (MR) analysis to estimate the causal effect of BW, fetal-specific BW, and maternal-specific BW on coronary artery disease (CAD), myocardial infarction (MI), heart failure (HF), atrial fibrillation (AF), and stroke. Furthermore, we applied a stepwise MR analysis approach to assess the potential involvement of childhood body mass index (CBMI) and age at menarche (AAM) in the causal pathways from BW to CVDs, while considering adult BMI. Finally, we performed colocalization analyses to justify the different biological mechanisms of maternal-specific and fetal-specific BW. The 2-sample MR analysis revealed that genetically predicted higher BW per standard deviation (SD) was associated with a decreased risk of CAD (odds ratio [OR]&#x2005;=&#x2005;0.804, 95% confidence interval [CI]: 0.731-0.883), MI (OR&#x2005;=&#x2005;0.720, 95% CI: 0.638-0.814), and stroke (OR&#x2005;=&#x2005;0.900, 95% CI: 0.823-0.985), but an increased risk of AF (OR&#x2005;=&#x2005;1.279, 95% CI: 1.160-1.410). Similar associations were observed for fetal-specific/maternal-specific BW. The stepwise MR analysis indicated that CBMI and AAM could serve as factors linking BW/fetal-specific BW and CVDs, albeit in different roles, by displaying an indirect causal effect through adult BMI. However, for maternal-specific BW, our results failed to support a causal effect on CBMI or AAM. Colocalization analyses supported the distinct biological mechanisms for maternal-specific and fetal-specific BW by showing different causal genes. The study suggested that both fetal genotype and intrauterine environmental exposure contribute to the causal associations. Additionally, AAM and CBMI may play a role in the pathways linking BW and CVDs, though the effect was only observed for fetal-specific BW.

Humans↗
PubMed2025

Causal relationships between antibody-mediated immune responses and acute pancreatitis: Evidence from a genetic study.

Certain specific antibody-mediated immune responses may be associated with acute pancreatitis (AP), but their causal relationship remains uncertain. Therefore, we used bidirectional two-sample Mendelian randomization (MR) to investigate their causal link and potential mediation by inflammatory cytokines. Data for this study were sourced from a large-scale Genome Wide Association Study (GWAS) communal data pool. To explore the causality between antibody-mediated immune responses and AP, we performed two-sample bidirectional MR analyses using 5 approaches: inverse-variance weighted (IVW), MR-Egger, weighted mode, weighted median, and simple mode. We also studied the potential mediating effect of 91 circulating inflammatory cytokines using a two-step MR method. Additionally, sensitivity analyses were conducted using MR-Egger intercept test and Cochran Q test to ensure the robustness of the outcomes. The results of forward MR analysis showed that anti-Epstein-Barr virus (anti-EBV) IgG seropositivity [OR&#x2005;=&#x2005;0.941; 95% CI, 0.893-0.992; P&#x2005;=&#x2005;.023] and human herpes virus (HHV) 6 IE1A antibody levels [OR&#x2005;=&#x2005;0.894; 95% CI, 0.816-0.981; P&#x2005;=&#x2005;.017] significantly reduced the risk of AP. The results of the reverse MR analysis revealed a negative correlation between AP and anti-EBV IgG seropositivity [OR&#x2005;=&#x2005;0.775; 95% CI, 0.605-0.992; P&#x2005;=&#x2005;.043]. Furthermore, none of the 91 circulating inflammatory cytokines could mediate the causal relationship between HHV-6 IE1A antibody levels and the risk of AP. The results of sensitivity analysis confirmed the robustness of these causalities. The current study suggests that HHV-6 IE1A antibody levels are a protective factor against AP, and there is a bidirectional causality between AP and anti-EBV IgG seropositivity. In addition, the mediation analysis results showed that the 91 circulating inflammatory cytokines could not serve as mediators between the 46 antibody-mediated immune responses and AP.

Humans↗
PubMed2026

Adolescent depression as a systemic multimorbidity catalyst: integrated genetic and metabolic pathway analysis.

BACKGROUND: Although adolescent depression has been linked to individual chronic conditions, its broader role in shaping multimorbidity risk remains understudied. METHODS: A total of 87,562 UK Biobank participants were included, of whom 18,851 had documented adolescent depression. Cox proportional hazards models were applied to evaluate associations between adolescent depression and 24 chronic diseases, followed by stratified analyses by sex and age. Two-sample Mendelian randomization (MR) was then conducted to infer causality for diseases showing significant associations. Genomic colocalization analyses were performed using relevant GWAS data to identify shared causal variants. Mediation analyses were performed to detect possible mediating factors, including the frailty index, KDM biological age acceleration, allostatic load and 30 circulating biomarkers. RESULTS: Adolescent depression was associated with elevated risk for 12 chronic diseases, with strongest associations for hypothyroidism (HR&#xa0;=&#xa0;1.29 [1.18-1.42]), diabetes (HR&#xa0;=&#xa0;1.25 [1.13-1.38]) and chronic obstructive pulmonary disease (COPD) (HR&#xa0;=&#xa0;1.74 [1.50-2.01]). Risks were notably higher among females and younger adults. MR confirmed likely causal relationships for hypothyroidism (OR&#xa0;=&#xa0;1.45 [1.03-2.05]), diabetes (OR&#xa0;=&#xa0;1.01 [1.01-1.02]) and COPD (OR&#xa0;=&#xa0;1.04 [1.02-1.06]). Genomic colocalization revealed a shared genetic signal at the CDSN/PSORS1C1 locus between adolescent depression and hypothyroidism. Mediation analyses revealed disease-specific pathways: creatinine for hypothyroidism, testosterone for diabetes, KDM biological ageing for COPD and frailty index across all three conditions. CONCLUSIONS: Adolescent depression confers systemic vulnerability through genetic and metabolic mechanisms, with amplified risks in females and individuals aged &#x2264;55&#xa0;years. These findings support early, integrated interventions to mitigate long-term multimorbidity.

Humans↗
PubMed2026

Causal Effects Between Neurodegenerative Diseases, Metabolites, and Brain Volume.

INTRODUCTION/OBJECTIVE: Neurodegenerative diseases such as Alzheimer's disease (AD), Lewy dody dementia (LBD), and Parkinson's disease (PD) are linked to changes in brain volume. However, causal evidence on how these diseases affect brain volume and whether metabolites mediate these causal effects remains limited. METHODS: We applied mediation Mendelian randomization analysis using GWAS summary statistics. The inverse variance-weighted method was used to assess causal effects and identify potential metabolite mediators. RESULTS: The MR analyses indicated that bilateral thalamus and putamen volumes (FDR < 0.05) had causal effects on PD. AD and LBD showed causal effects on bilateral thalamus and hippocampus (FDR < 0.01), with LBD specifically showing a causal effect on bilateral putamen (FDR < 0.05). Mediation analyses revealed that AD had a genetically predicted association with Nervonoy- L-carnitine and 1-linoleoyl-2-arachidonoyl-GPC (p-value = 0.04 and 0.01, respectively). Moreover, Nervonoy-L-carnitine was suggestively negatively associated with hippocampus volume (p-value = 0.03 and 0.02, respectively). 1-linoleoyl-2-arachidonoyl-GPC exhibited a negative genetically predicted association with hippocampus volume (p-value < 0.05). Additionally, LBD showed a negative genetically predicted association on the ratio of retinol to linoleoyl-arachidonoyl- glycerol (p-value = 0.02), and a positive genetically predicted association on Nervonoy-L-- carnitine (p-value < 0.05) and 1-linoleoyl-2-arachidonoyl-GPC (p-value = 0.03). DISCUSSION: These results suggest that AD and LBD affect brain regions through causal pathways. The involvement of specific metabolites highlights potential mechanisms linking neurodegeneration to brain volume. CONCLUSION: Nervonoylcarnitine and 1-linoleoyl-2-arachidonoyl-GPC may mediate the predicted effects of AD and LBD on hippocampal volumes, while the ratio of retinol to linoleoyl-arachidonoyl- glycerol mediates only LBD.

Humans↗
PubMed2026

NLCD: A method to discover nonlinear causal relations among genes.

Distinguishing correlation from causation is a fundamental challenge in many scientific fields, including biology, especially when interventions like randomized controlled trials are infeasible and only observational data are available. Methods based on statistical tests of conditional independence within the Mendelian Randomization framework can detect causality between two observed variables that are each associated with a third instrumental variable. However, these methods for detecting causal relationships between traits (e.g., two gene expression or clinical traits associated with a genetic variant, all observed in the same population) often assume a linear relationship, thereby hindering the discovery of causal gene networks from genomics data. We have developed NLCD, a method for NonLinear Causal Discovery from genomics data based on nonlinear regression modeling and conditional feature importance scoring. NLCD uses these techniques to extend the statistical tests in an existing linear causal discovery method called the Causal Inference Test (CIT). We benchmarked NLCD against current state-of-the-art methods: CIT, Findr, and MRPC. On simulated datasets, NLCD performs comparably to most methods in detecting linear relations (Average AUPRC (Area Under the Precision-Recall Curve) of NLCD&#x2009;=&#x2009;0.94, CIT&#x2009;=&#x2009;0.94, Findr&#x2009;=&#x2009;0.94, and MRPC&#x2009;=&#x2009;0.99), and outperforms them in detecting nonlinear (sine and sawtooth type) relations between two genes (Average AUPRC of NLCD&#x2009;=&#x2009;0.76, CIT&#x2009;=&#x2009;0.60, Findr&#x2009;=&#x2009;0.56, and MRPC&#x2009;=&#x2009;0.73). When tested on a nonlinear subset of a yeast genomic dataset to recover known causal relations involving transcription factors, NLCD and CIT performed comparable to each other and slightly better than Findr and MRPC (Average AUPRC of NLCD&#x2009;=&#x2009;0.82, CIT&#x2009;=&#x2009;0.81, Findr&#x2009;=&#x2009;0.71, and MRPC&#x2009;=&#x2009;0.54). On application to a human genomic dataset, NLCD revealed active causal gene pairs (IRF1 &#x2192; PSME1 and HLA-C &#x2192; HLA-T) in the muscle tissue, and clarified the promises and challenges in discovering causal gene networks in tissues under in vivo human settings.

Humans↗
PubMed2026

Artificial Intelligence-Driven Multi-Omics Analysis Reveals Hydroxytyrosol Targeting of the TXNIP-NLRP3 Inflammasome Axis in Traumatic Brain Injury.

Traumatic brain injury (TBI) induces secondary neuroinflammation driven by oxidative stress, inflammasome activation, and immune remodeling, yet specific mechanism-guided pharmacological interventions remain limited. This study established an artificial intelligence (AI)-integrated network pharmacology and multi-omics framework to evaluate whether hydroxytyrosol (HT), an olive-derived natural polyphenol, may regulate TBI-related neuroinflammatory targets centered on the TXNIP/NLRP3 inflammasome axis. Starting from the SMILES structure of HT, potential targets were predicted using PharmMapper, SwissTargetPrediction, and the Similarity Ensemble Approach and were standardized to UniProt identifiers. TBI-associated genes were integrated from GeneCards, DisGeNET, OMIM, and the Therapeutic Target Database. The overlapping target set was analyzed using STRING-based protein-protein interaction (PPI) networks, MCODE, CytoHubba, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Public GEO transcriptomic datasets (GSE123831 and GSE104687) were used for cross-platform expression validation, differential expression analysis, and exploratory CIBERSORT-based immune infiltration estimation. Random forest (RF), multilayer perceptron (MLP), graph convolutional network (GCN), graph attention network (GAT), SHAP/LIME explainability analysis, LASSO inflammatory-risk scoring, and two-sample Mendelian randomization (MR) were further applied for target prioritization, immune phenotype mapping, and genetic association analysis. Seventy-three overlapping HT-TBI targets were identified. PPI and topology analyses prioritized TXNIP, NLRP3, CASP1, MAPK1, and TP53 as key hubs enriched in inflammasome activation, oxidative stress, apoptosis, and NOD-like receptor signaling. TXNIP, NLRP3, and CASP1 were consistently upregulated in both TBI transcriptomic datasets. LM22-based immune deconvolution suggested increased pro-inflammatory immune signatures and a positive TXNIP-M1 macrophage association (r&#x202f;=&#x202f;0.63, p < 0.001), which should be interpreted as a transcriptome-derived hypothesis rather than validated murine immune-cell proportions. AI-based models consistently ranked TXNIP/NLRP3 as high-contribution features under internal validation, and removal of these targets reduced model performance. A five-gene inflammatory score achieved an internally evaluated AUC of 0.87, while two-sample MR supported positive genetic associations involving TXNIP expression, TBI risk, NLRP3 and IL-1&#x3b2; expression. Collectively, these findings prioritize the TXNIP/NLRP3/CASP1 module as a computationally supported candidate mechanism through which HT may influence oxidative stress-inflammasome-immune coupling in TBI. This study provides an interpretable drug-target-pathway-phenotype framework and identifies TXNIP, NLRP3, and CASP1 as priority nodes for future experimental validation.

Artificial Intelligence↗
PubMed2024

Identification of biomarkers and potential therapeutic targets for pancreatic cancer by proteomic analysis in two prospective cohorts.

Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with &#x223c;5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p&#xa0;<&#xa0;0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.

Humans↗
PubMed2026

Integrative multi-omics analyses suggest a candidate microbial metabolite-associated host gene network in ulcerative colitis.

Ulcerative colitis (UC) is associated with gut microbial dysbiosis, but the host molecular alterations potentially linked to microbially derived metabolites remain incompletely understood. We integrated Mendelian randomization (MR), microbial metabolite annotation, computational target prediction, colonic transcriptomics, network analysis, and machine learning. MiBioGen microbiome GWAS data were used as exposures and FinnGen Release 12 ULCERENTER as the outcome. Metabolites linked to MR-prioritized taxa were retrieved from GutMGene, and human targets were predicted using SwissTargetPrediction and SEA. UC-related genes were defined by integrating differential expression analysis and WGCNA and then intersected with predicted metabolite targets. MR prioritized one family and eight genera showing nominal genetically supported associations with UC, but none remained significant after Benjamini-Hochberg FDR correction. Three prioritized genera were linked to 15 microbe-metabolite records, corresponding to 13 unique metabolites; nine were retained for target prediction, yielding 277 unique predicted human targets. Transcriptomic analysis identified 1,530 DEGs and a 312-gene MEgrey60 module, with 273 overlapping genes, producing 1,569 unique UC-related genes. Their intersection with the 277 predicted targets yielded 47 candidate genes. Enrichment analyses highlighted mainly metabolic and lipid-related processes. Random Forest showed the highest mean AUC across the two independent external benchmarking cohorts, and SHAP prioritized EPHX1, HSD17B2, IGFBP5, and MMP10. IBDome analysis showed inflammation-associated expression differences in these genes. This study provides a genomics-informed, hypothesis-generating framework that prioritizes candidate microbe-metabolite-host relationships in UC for future experimental validation.

Humans↗
PubMed2025

Shared Genetic Architecture Between Atopic Dermatitis and Autoimmune Diseases.

Atopic dermatitis (AD) and autoimmune diseases exhibit epidemiological comorbidity, yet the shared genetic architecture remains incompletely understood. We investigated the genetic overlap between AD and three autoimmune disorders including inflammatory bowel disease (IBD), rheumatoid arthritis (RA), and vitiligo, leveraging genome-wide association data. Despite modest evidence for global genetic correlations, we found 113 independent pleiotropic loci shared among AD and autoimmune diseases, with 11 displaying a concordant effect across all 3 pairwise comparisons. Gene-set and tissue enrichment analyses evidenced the inflammatory background of pleiotropic associations. Multi-trait colocalization analysis prioritized 22 loci, linking the tissue-specific expression of DOK2, GPR132, RERE, RERE-AS1, SUOX, TNFRSF11A, and TRAF1 pleiotropic genes with AD risk. Mendelian randomization revealed no causal effect of genetic liability to AD on autoimmune diseases. Nevertheless, genetic liability to IBD increased AD risk, while vitiligo exhibited a protective effect post outlier correction. Our findings provide mechanistic insights into the multimorbidity of atopic dermatitis (AD) and autoimmune diseases, offering additional evidence for the pleiotropic genetic architecture of AD that contributes to systemic immune dysregulation across multiple organ systems.

Humans↗
PubMed2026

A genetic signal at 8q12.3 modulates GGT levels via the Runx1-CYP7B1 axis in female ethnic minorities from Guizhou.

Gamma-glutamyl transferase (GGT) regarded as a biomarker of liver dysfunction or excessive alcohol consumption; however, existing genome-wide association studies (GWAS) have been conducted predominantly in European populations and East Asian populations from Japan and the Taiwan region, with limited investigation in ethnic minorities from Guizhou Province. Previous genetic studies have demonstrated that Guizhou ethnic minorities share an East Asian genetic background while exhibiting specific genetic structures, a pattern that is also confirmed by our principal component analysis (PCA) results. We therefore performed a GWAS in this population and identified a genome-wide significant signal at 8q12.3 in female ethnic minorities from Guizhou. Fine-mapping and functional annotation analyses suggest that a regulatory pathway involving Runt-related transcription factor 1 (Runx1)-Cytochrome P450 family 7 subfamily B member 1 (CYP7B1)-cholesterol-reactive oxygen species (ROS)-glutathione (GSH) may contribute to the regulation of GGT levels. Mendelian randomization (MR) analyses further supported a causal relationship between GGT levels and autoimmune hepatitis (AIH). These findings uncover a genetic mechanism underlying GGT variation at 8q12.3 in female ethnic minorities from Guizhou, implicating a pathway linked to cholesterol metabolism and oxidative stress, and providing potential targets and insights for precision prevention and treatment of related diseases.

Female↗
PubMed2025

The relationship between vitamin D levels and depression: a genetically informed study.

BACKGROUND: Low vitamin D (vitD) levels are consistently associated with an increased risk of depression. However, the biological mechanisms underlying this relationship and potential shared genetic overlap remain elusive. METHODS: We investigated the genetic overlap and causal relationships between depression (N&#x2009;=&#x2009;589,356) and vitD levels (N&#x2009;=&#x2009;417,580) using genome-wide association study (GWAS) summary statistics. We performed genome-wide and local genetic correlation analyses, followed by quantification of polygenic overlap variants. Shared genetic loci were identified and mapped to genes, which were further analyzed through gene expression and lifespan brain expression trajectory analyses. Bidirectional causal relationships were examined using multiple Mendelian randomization approaches. RESULTS: We observed significant negative genetic correlations (rg = -0.079) and identified genetic overlap (N&#x2009;=&#x2009;410 variants). Genes mapped to the 13 shared loci showed opposing expression patterns. Tissue- and cell-specific functional enrichment analyses revealed significant signals related to brain development, with distinct patterns emerging between fetal development and adulthood. Shared genes (TRMT61A, ITIH4, RASGRP1, CTNND1, HERC1, IP6K1, FURIN ESR1, ZMYND and GRM5) exhibited notable expression variation in the brian throughout the lifespan, aligning with functional enrichment findings. CONCLUSIONS: Our findings elucidate the shared biological mechanisms underlying the relationship between vitD and depression, suggesting that vitD play an important role in the development of depression through altered early neurodevelopmental processes.

Humans↗
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&#x2009;=&#x2009;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↗