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PubMed2026

Identifying potential drug targets for physical and cognitive frailty: an integrative analysis of CHARLS cohort, mendelian randomization, and gene colocalization.

With the aging of the population, frailty has become a common syndrome that severely affects the quality of life of older adults. This study aims to analyze the correlation between cognition and frailty, physical activity and frailty, and elucidate the potential pharmacological targets of cognitive frailty and physical frailty.We conducted logistic regression analyses using data from the China Health and Retirement Longitudinal Study (CHARLS) to examine the associations between total cognition and frailty, physical activity and frailty. Furthermore, summary-data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (TSMR) were employed to explore potential pharmacological targets for frailty. Genes associated with physical frailty and cognitive frailty were identified, followed by analysis via colocalization analysis, phenome-wide association studies (PheWAS), and DsigDB drug prediction. Cross-sectional analysis of CHARLs revealed that total cognition(OR 0.93, 95% CI 0.92-0.95) and middle physical activity(OR 0.95, 95% CI 0.92-0.97) were negatively correlated with frailty. SMR identified 41 drug genes associated with frailty, and subsequent TSMR validation and co-localization analysis showed that 11 candidate genes exhibited strong colocalization (PP.H4 > 0.8). GRPEL 1, PABPC 4, and WBP 2NL were ultimately identified as potential drug targets associated with physical frailty, while LANCL1, LRPPRC, FADS1, and WBP2NL were identified as potential drug targets associated with cognitive frailty. Phenome-wide association analysis(PheWAS) did not reveal any significant associations between these genes and other phenotypes at the genome-wide significance threshold. Laudanosine, 25-hydroxycholesterol, and hexadecanal emerged as the top three candidate compounds for therapeutic intervention. We identified potential drug targets for physical frailty and cognitive frailty through comprehensive analysis and elucidated drugs associated with potentially relevant genetic markers, thereby laying the foundation for a deeper understanding of the mechanisms of frailty.

Humans↗

PubMed2026

Cross-tissue multi-omics integration highlights BPHL and mitochondrial targets in Alzheimer's disease.

BACKGROUND: Mitochondrial dysfunction is a hallmark of Alzheimer's disease (AD), yet specific molecular targets remain to be fully characterized. METHODS: A summary-data-based Mendelian randomization (SMR) framework integrated AD genome-wide association study (GWAS) statistics (39,918 cases) with blood DNA methylation quantitative trait loci (mQTL), gene expression (eQTL), and protein (pQTL) data for 1136 mitochondria-related genes. Associations were assessed using Bayesian colocalization and HEIDI testing. Tissue relevance was evaluated in four brain regions (hippocampus, amygdala, cortex, frontal cortex) using GTEx and external transcriptomic datasets. RESULTS: Screening identified eight candidates supported across blood mQTL and eQTL layers. Stepwise central nervous system (CNS) evaluation singled out biphenyl hydrolase-like (BPHL) as the consistent candidate. Higher genetically predicted BPHL expression was associated with reduced AD risk across the hippocampus (OR=0.920, 95% CI 0.873-0.970), amygdala (OR=0.925, 95%CI 0.880-0.973), cortex (OR=0.943, 95% CI 0.908-0.978), and frontal cortex (OR=0.938, 95%CI 0.901-0.976). These findings aligned with protein-protein interactions connecting BPHL to respiratory complexes and lower BPHL expression in independent AD brains. Functional enrichment converged on oxidative phosphorylation pathways. CONCLUSIONS: By integrating multi-omics data with tissue-specific validation, this study nominates BPHL as a consistent protective candidate in the brain. These findings provide genetic support for mitochondrial molecular perturbations in AD, offering insights for future validation.

Alzheimer Disease↗

PubMed2026

Integrated single-cell RNA sequencing and mendelian randomization analysis identifies causal immune-related driver genes in the heart failure inflammatory microenvironment.

BACKGROUND: Heart failure (HF) is a major global cause of cardiovascular death and disability. Chronic inflammation and immune dysregulation are critical in its development. The cardiac immune microenvironment, especially macrophages, drives HF progression, yet its molecular mechanisms and prognostic impact are not fully clear. This study aimed to identify causal immune-related driver genes in the HF inflammatory microenvironment. METHODS: We combined single-cell RNA sequencing (scRNA-seq) and Mendelian randomization (MR) to study how the inflammatory immune microenvironment affects HF risk. Using two public scRNA-seq datasets, we identified differentially expressed genes (DEGs) in HF heart tissues and selected 489 candidate genes. Causal relationships between these genes and HF were tested using expression quantitative trait loci (eQTL) data and HF genome-wide association study (GWAS) summary statistics. RESULTS: MR analysis showed that 65 genes were causally linked to HF risk. These genes were enriched in pathways related to cardiomyopathy, leukocyte migration, natural killer (NK) cell cytotoxicity, neutrophil extracellular traps, and NF-κB signaling. HF hearts displayed increased levels of macrophages, T cells, B cells, lymphoid cells, and mast cells, while neutrophils were reduced. CONCLUSIONS: Our integrated analysis reveals the central role of the cardiac inflammatory immune microenvironment in HF and identifies 65 key genes causally associated with HF susceptibility. These genes influence specific immune pathways and cell infiltration, shaping HF progression, and provide a basis for developing new biomarkers and immune-targeted therapies.

Heart failure (HF)↗

PubMed2026

Inflammatory cytokines mediate thoracic aortic aneurysm formation via plasma metabolites: A two-step Mendelian randomization and single cell sequencing-based investigation.

Thoracic aortic aneurysm (TAA) is a life-threatening condition characterized by pathological dilation of the aorta. While inflammatory responses have been implicated in TAA pathogenesis, the causal relationships remain elusive. This study aimed to elucidate potential causal associations between inflammatory cytokines, plasma metabolites, and TAA risk using Mendelian randomization (MR) analysis. We conducted bidirectional two-sample MR analysis utilizing genome-wide association study data from 91 inflammatory cytokines (n = 14,824), 1400 plasma metabolites (n = 8299), and TAA (n = 385,857). The inverse-variance weighted method served as the primary analytical approach, with comprehensive sensitivity analyses performed to assess pleiotropy and heterogeneity. Two-step MR analysis was employed to explore potential mediating roles of plasma metabolites. Single-cell sequencing analysis was utilized to detect cell type enrichment and elucidate cellular functions of identified cytokines. Additionally, we conducted an analysis to identify druggable proteins as potential therapeutic targets for TAA. MR analysis revealed that genetically-determined increases in C-X-C motif chemokine 10 (CXCL10) (odds ratios [OR] = 1.149, 95% confidence interval [CI]: 1.009-1.309, P = .037) and fibroblast growth factor 5 (OR = 1.101, 95% CI: 1.013-1.196, P = .024) were associated with elevated TAA risk. Conversely, C-C motif chemokine 20 (CCL20) (OR = 0.870, 95% CI: 0.759-0.996, P = .043) and CD40L receptor (CD40) (OR = 0.906, 95% CI: 0.827-0.992, P = .033) demonstrated inverse associations with TAA risk. Two-step MR analysis identified potential mediating metabolites: the phosphate to linoleoyl-arachidonoyl-glycerol ratio for CXCL10, thyroxine and X-24585 for FGF-5, and the creatine to carnitine ratio for CCL20. Single-cell sequencing analysis revealed enrichment of these cytokines in specific cell types and pathways relevant to TAA pathogenesis. Drug-gene interaction analysis identified CXCL10, CCL20, and CD40 as potential targets for treatment of TAA. This study provides robust genetic evidence supporting causal relationships between specific inflammatory cytokines and TAA risk, with plasma metabolites potentially mediating these effects. CXCL10 and FGF-5 were identified as potential risk factors, while CCL20 and CD40 may confer protective effects. These findings offer novel insights into TAA pathogenesis and suggest potential targets for intervention. Further research is warranted to elucidate the underlying mechanisms and validate these results across diverse populations.

Aortic Aneurysm, Thoracic↗

PubMed2026

Role of CD25hi CD45RA+ CD4 not Treg %T cell in mediating the effect of pyruvate fermentation to acetone on intrahepatic cholangiocarcinoma.

This study aimed to elucidate the potential correlation between gut microbiota and intrahepatic cholangiocarcinoma (ICC) by investigating their causal relationship, while also exploring the possible role of immune cells as mediators in this association. We first identified gut microbiota based on phylum, class, order, family, and genus level information. Using summary-level data from a Genome-Wide Association Study (GWAS), we performed a 2-sample Mendelian randomization (MR) analysis of ICC and gut microbiota. Furthermore, we used 2-step MR to quantify the proportion of the effect of immune cell-mediated gut microbiota on ICC. MR analysis identified pyruvate fermentation to acetone (PFA) as predicting ICC risk reduction. There was no strong evidence that genetically predicted ICC had an effect on PFA risk. Furthermore, the proportion of genetically predicted PFA mediated by CD25hi CD45RA+ CD4 not Treg %T cell (CCCTT) was 3% (95% CI: 0.93-5.03%). In conclusion, our study established a causal relationship between PFA and ICC. We observed that a minor fraction of this effect was mediated by CCCTT, while the majority of the impact exerted by PFA on ICC remains elusive. However, further investigations are warranted to elucidate the mechanisms underlying the influence of gut microbiota on ICC development.

Cholangiocarcinoma↗

PubMed2026

Mendelian Randomization Analysis of NETs-Associated Inflammatory Traits and Type 2 Diabetes and its Complications.

Neutrophil extracellular traps (NETs) -associated inflammatory traits play a significant role in type 2 diabetes mellitus (T2DM) and its complications. Notably, IL-6, a key inflammatory cytokine, is intricately linked to the formation of NETs and the pathogenesis of T2DM and its complications. This study aimed to explore the causal association between NETs-associated inflammatory traits and T2DM, as well as its complications, using a Mendelian Randomization (MR) approach. This study utilized a two-sample MR design with data from Genome-Wide Association Studies (GWAS), comprising a large European population-based meta-analysis for T2DM and its complications. The primary method of analysis was the inverse variance weighted (IVW) approach, complemented by MR-Egger regression, weighted median, and weighted mode methods. Sensitivity analyses included MR-Egger, MR-PRESSO, Cochran's Q, and leave-one-out methods to assess the robustness of the findings. The study indicated that genetically predicted levels of interleukin-6 (IL-6) were inversely associated with diabetic coronary artery disease (CAD) (OR = 0.8997, 95% CI: 0.8257-0.9803, P = 0.0158). Additionally, NETs showed significant associations with T2DM with renal complications (OR=0.97, 95% CI 0.9428-0.998, P = 0.0358) and T2DM with peripheral circulatory complications(OR = 1.0342, 95% CI 1.002-1.0673, P = 0.037). The significant IVW associations showed no evidence of heterogeneity or horizontal pleiotropy. This study suggests that genetically predicted NETs-associated inflammatory traits are associated with specific T2DM complications. Genetically predicted IL-6 was inversely associated with diabetic CAD, whereas NETs were associated with renal and peripheral circulatory complications in T2DM.

Diabetes Mellitus, Type 2↗

PubMed2026

Multistage Genetic, Transcriptomic, and Single-Cell Evidence Prioritizes MAP1LC3A among Ferroptosis-Related Genes in Glioblastoma.

Glioblastoma (GBM) remains a highly aggressive malignancy, and the contribution of ferroptosis-related genes to disease susceptibility remains incompletely understood. A genetically anchored, multistage framework was applied to prioritize ferroptosis-related genes associated with GBM. Among 483 genes curated from FerrDb V2, 315 had candidate cis-expression quantitative trait loci (cis-eQTLs) in eQTLGen, 250 retained at least three independent instruments after linkage disequilibrium clumping, and 226 yielded valid inverse-variance weighted (IVW) Mendelian randomization estimates using a GBM genome-wide association study comprising 6,183 cases and 18,169 controls. Thirty-four genes met the exploratory discovery criteria of P < 0.05 and a Benjamini-Hochberg false discovery rate (BH-FDR) < 0.20, with directionally concordant Bayesian weighted Mendelian randomization (BWMR) estimates. Replication-stage Mendelian randomization using GTEx V10 whole-blood cis-eQTLs supported four genes: ATG7, RPTOR, MAP1LC3A, and CHMP6. Evaluation across three independent tumor-control transcriptomic cohorts demonstrated that MAP1LC3A was consistently downregulated in tumor tissue and showed a significant random-effects pooled estimate (log₂ fold change, -1.273; 95% confidence interval, -1.625 to -0.920; false discovery rate = 0.016), whereas the other three genes lacked comparable cross-cohort statistical support. Single-cell virtual knockout analysis was subsequently performed in a patient-balanced subset of 2,400 malignant cells selected from 4,916 eligible cells across 20 adult IDH-wild-type GBM tumors. Across five independently seeded runs, 3, 15, 4, and 7 robust downstream genes were identified for ATG7, RPTOR, MAP1LC3A, and CHMP6, respectively. The resulting consensus sets comprised 17 unique genes, with RND3 shared across all four targets. Gene Ontology analysis indicated enrichment of cell-adhesion and cell-surface processes, whereas no KEGG or Reactome pathways remained significant after multiple-testing correction. Collectively, these findings prioritize MAP1LC3A for future experimental investigation while distinguishing genetic association, tumor-expression concordance, and computational perturbation from definitive evidence of causality or mechanism.

Humans↗

PubMed2023

Causal Associations of Sleep Apnea with Alzheimer's Disease and Cardiovascular Disease: a Bidirectional Mendelian Randomization Analysis.

BACKGROUND: Sleep apnea (SA) has been linked to an increased risk of dementia in numerous observational studies; whether this is driven by neurodegenerative, vascular or other mechanisms is not clear. We sought to examine the bidirectional causal relationships between SA, Alzheimer's disease (AD), coronary artery disease (CAD), and ischemic stroke using Mendelian randomization (MR). METHODS: Using summary statistics from four recent, large genome-wide association studies of SA (n=523,366), AD (n=64,437), CAD (n=1,165,690), and stroke (n=1,308,460), we conducted bidirectional two-sample MR analyses. Our primary analytic method was fixed-effects inverse variance weighted MR; diagnostics tests and sensitivity analyses were conducted to verify the robustness of the results. RESULTS: We identified a significant causal effect of SA on the risk of CAD (odds ratio (OR IVW ) =1.35 per log-odds increase in SA liability, 95% confidence interval (CI) =1.25-1.47) and stroke (OR IVW =1.13, 95% CI =1.01-1.25). These associations were somewhat attenuated after excluding single-nucleotide polymorphisms associated with body mass index (BMI) (OR IVW =1.26, 95% CI =1.15-1.39 for CAD risk; OR IVW =1.08, 95% CI =0.96-1.22 for stroke risk). SA was not causally associated with a higher risk of AD (OR IVW =1.14, 95% CI =0.91-1.43). We did not find causal effects of AD, CAD, or stroke on risk of SA. CONCLUSIONS: These results suggest that SA increased the risk of CAD, and the identified causal association with stroke risk may be confounded by BMI. Moreover, no causal effect of SA on AD risk was found. Future studies are warranted to investigate cardiovascular pathways between sleep disorders, including SA, and dementia.

Preprint↗

PubMed2026

Shared Genetic Basis, Biological Function and Causal Relationship Between Sleep Traits and Hypothyroidism: Evidence from a Comprehensive Genetic Analysis.

BACKGROUND: This research attempts to clarify whether there are any genetic similarities between sleep traits and hypothyroidism based on publicly accessible large-scale genomewide association studies. METHODS: The methodology included colocalization analysis, cross-phenotype association analysis, and linkage disequilibrium score regression analysis to find common genetic overlap. Through tissue function specificity and functional mapping, we were able to identify the shared genetic level. Genetic instrumental factors were used for causal inference in two-sample univariate and multivariable Mendelian randomization analyses. RESULTS: A hereditary correlation between hypothyroidism and napping during the day and getting up in the morning (rg= -0.0982, P= 0.0007; rg= -0.101, P= 0.0001). MAGI3, and HLA-DRB1 BX296568.1 may be potential targets for shared treatments. Colocalization and tissue-specific analysis demonstrated that the common genes and SNPs were identified in the thyroid, lung, brain, and lymphatic tissues. Functional analysis emphasized the importance of these common genes in processes like as protein transport, inflammatory response, and MHC class II protein synthesis. Furthermore, an association has been established between hypothyroidism and sleep duration (IVW, OR 1.5208; 95% CI 1.1142-2.0758, P=0.0082) and getting up in the morning (IVW, OR 1.8375; 95%CI: 1.4502-2.3284, P=4.73E-07). Furthermore, the reverse MR analysis revealed no causal connection between aberrant sleep traits and hypothyroidism. The enduring impact of insomnia on hypothyroidism persists despite controlling for alcohol consumption and smoking habits. CONCLUSION: Certain genetic correlations between sleep traits and hypothyroidism have been emphasized. These findings may elucidate the origin of comorbidity and have implications for future clinical trials.

Humans↗

PubMed2026

Identification of Critical Genes for Recurrent Aphthous Ulcer by Transcriptome Data Analysis and Mendelian Randomization.

PURPOSE: Recurrent aphthous ulcer (RAU) is a common oral mucosal disorder with a poorly understood etiology, significantly affecting patients' quality of life. This study aims to investigate critical genes linked to RAU and explore their biological mechanisms using transcriptomic data and Mendelian randomization (MR) analysis. MATERIALS AND METHODS: RAU-related gene expression data from the GEO database (GSE37265) were analyzed to identify differentially expressed genes (DEGs). A two-sample MR approach was used to assess the causal impact of expression quantitative trait loci (eQTL) on RAU. Critical genes were identified by intersecting DEGs with significant MR findings. GO and KEGG pathway enrichment analyses were performed, along with GSEA and immune cell infiltration analysis, to investigate the functions and mechanisms of these genes in RAU. RESULTS: A total of 184 differentially expressed genes (DEGs) were identified, while 339 RAU-associated genes were screened through MR analysis. Cross-validation further identified 7 critical genes. Among these, CCR1, ERP27, HCK, MICB, and SLC2A3 showed protective associations with RAU risk, whereas CD177 and IFITM1 were positively associated with increased risk. Enrichment analysis revealed that these genes are involved in specific biological processes, including cell migration, immune response, and metabolic regulation, which are closely linked to RAU pathogenesis. CONCLUSION: This systematic study comprehensively investigates the critical causative genes underlying RAU, emphasizing the intricate relationships between immune regulation and metabolic disturbances in its pathology. These findings lay a solid foundation for the development of novel biomarkers and may inform future research on targeted therapeutic strategies for RAU.

Stomatitis, Aphthous↗

PubMed2005

Insulin-like growth factor-I and risk of type 2 diabetes and coronary heart disease: molecular epidemiology.

Insulin-like growth factors (IGFs) play a fundamental role in somatic growth and cellular differentiation, metabolism and survival. Indeed, the processes linking nutrition, metabolism and growth are thought to involve a complex interrelation among insulin, growth hormone (GH), IGFs and their binding proteins (IGFBPs). However, accumulating data from both experimental and molecular epidemiological studies indicate that these growth factors may also be important in the pathophysiological processes underlying chronic disease, including type 2 diabetes mellitus, coronary heart disease and cancer. Experimental and observational studies suggest that higher levels of circulating IGF-I may increase risk of several cancers. By contrast, recent prospective epidemiological studies suggest that relatively higher IGF-I levels may reduce the risk of type 2 diabetes and coronary heart disease. However, these relatively small-scale observational studies are susceptible to chance, reverse causality and residual or unmeasured confounding. A 'Mendelian randomization' approach based on large-scale gene association and prospective observational studies might help determine the possible causal role of IGF-I and its binding proteins in the aetiology of type 2 diabetes, coronary heart disease and cancer.

Animals↗

PubMed2026

TL-HDMR: a transfer learning framework for advancing equitable causal inference reveals metabolic signatures of stroke across multiple ancestries.

The limited genetic diversity in genome-wide association studies (GWAS) poses a significant challenge to the generalizability and equity of biomedical discoveries. Most causal inferences, particularly from high-dimensional phenomes (e.g. metabolomics), are primarily based on European populations, and their applicability to other ancestries remains uncertain. Traditional multivariable Mendelian randomization (MVMR) methods further struggle in high-dimensional and correlated settings due to collinearity and model instability. To bridge this gap, we present a two-step transfer learning framework for high-dimensional MR (TL-HDMR), designed to enhance causal exposure detection in understudied populations. Our approach leverages the Minimax Concave Penalty for asymptotically unbiased estimation amidst exposure correlations. Crucially, we introduce two novel pre-transfer procedures-HDMR.TSD for sourcing beneficial data and HDMR.PRESSO for filtering pleiotropic instruments-to ensure robust knowledge transfer. Extensive simulations demonstrated TL-HDMR's superior performance in ROC curves and mean absolute error over alternative methods. When applied to identify causal metabolites for stroke across multi-ancestry cohorts (European, East Asian, South Asian, and African), TL-HDMR successfully pinpointed both shared and ethnic-specific causal biomarkers, showcasing its unique capability for equitable causal inference. This work provides a powerful statistical tool that not only addresses critical methodological challenges but also promotes inclusivity and fairness in human health research.

Humans↗

PubMed2025

Association between gynecological cancers and female infertility: insights from bidirectional Mendelian randomization analysis.

PURPOSE: In recent years, research interest in the potential link between female infertility (FI) and gynecological cancer (GC), including ovarian cancer (OC), endometrial cancer (EC), cervical cancer (CC), and breast cancer (BC), has grown, yet findings remain inconclusive. This study aims to explore the causal relationship between FI and GC using bidirectional two-sample Mendelian randomization (MR) analyses, thereby informing future strategies for FI and GC prevention. METHODS: We utilized SNPs identified from genome-wide association studies (GWAS) on FI and GC. The inverse variance weighted (IVW) method served as the primary approach to assess the causal association between FI and GC. Additionally, five other MR methods-Weighted median, Weighted mode, MR-Egger, Simple mode, and Robust-Adjusted Profile Score-were employed to enhance result robustness and credibility. RESULTS: In the forward MR analysis, our IVW results indicated no significant association between FI and GC (FI-BC: OR = 0.95, 95% CI: 0.83-1.09, P = 0.47, P-FDR = 0.775; FI-OC: OR = 1.01, 95% CI: 0.84-1.24, P = 0.789, P-FDR = 0.896; FI-CC: OR = 0.80, 95% CI: 0.61-1.06, P = 0.118, P-FDR = 0.775; FI-EC: OR = 1.07, 95% CI: 0.88-1.30, P = 0.490, P-FDR = 0.775).In the reverse MR analysis, we found a marginal association between BC and FI. However, after adjusting for multiple testing using the FDR method, no significant causal relationship was found between BC and FI, suggesting a marginal association (OR = 1.054, 95% CI: 1.001-1.108, P = 0.043, P-FDR = 0.331). For other cancers, no significant causal relationships were observed between OC, CC and EC with FI(OC-FI: OR = 1.043, 95% CI: 0.999-1.087, P = 0.051, P-FDR = 0.331;CC-FI: OR = 0.992, 95% CI: 0.956-1.028, P = 0.654, P-FDR = 0.836; EC-FI: OR = 1.006, 95% CI: 0.956-1.055, P = 0.809, P-FDR = 0.885). CONCLUSIONS: Our study found no significant causal relationship between FI and GC. However, a potential marginal association between BC and FI was observed. These findings underscore the need for further research to confirm this association and emphasize the importance of reproductive protection for young breast cancer patients to preserve fertility.

Humans↗

PubMed2025

A Causal Effect of Serum 25(OH)D Level on Appendicular Muscle Mass: Evidence From NHANES Data and Mendelian Randomization Analyses.

BACKGROUND: Low serum vitamin D status was reported to be associated with reduced muscle mass; however, it is inconclusive whether this relationship is causal. This study used data from the National Health and Nutrition Examination Survey (NHANES) and two-sample Mendelian randomization (MR) analyses to ascertain the causal relationship between serum 25-hydroxyvitamin D [25(OH)D] and appendicular muscle mass (AMM). METHODS: In the NHANES 2011-2018 dataset, 11 242 participants (5588 males and 5654 females) aged 18-59 years old were included, and multivariant linear regression was performed to assess the relationship between 25(OH)D and AMM measured by dual-energy X-ray absorptiometry. In two-sample MR analysis, 167 single nucleotide polymorphisms significantly associated with serum 25(OH)D at the genome-wide association level (p < 5 × 10-8) were applied as instrumental variables (IVs) to assess vitamin D effects on AMM in the UK Biobank (417 580 Europeans) using univariable and multivariable MR (MVMR) models. RESULTS: In the NHANES dataset, serum 25(OH)D concentrations were positively associated with AMM (β = 0.013, SE = 0.001, p < 0.001) in all participants, after adjustment for age, race, season of blood collection, education, income, body mass index and physical activity. In stratification analysis by sex, males (β = 0.024, SE = 0.002, p < 0.001) showed more pronounced positive associations than females (β = 0.003, SE = 0.002, p = 0.024). In univariable MR, genetically higher serum 25(OH)D levels were positively associated with AMM in all participants (β = 0.049, SE = 0.024, p = 0.039) and males (β = 0.057, SE = 0.025, p = 0.021), but only marginally significant in females (β = 0.043, SE = 0.025, p = 0.090) based on IVW models was noticed. No significant pleiotropy effects were detected for the IVs in the two-sample MR investigations. In MVMR analysis, a positive causal effect of 25(OH)D on AMM was observed in the total population (β = 0.116, SE = 0.051, p = 0.022), males (β = 0.111, SE = 0.053, p = 0.036) and females (β = 0.124, SE = 0.054, p = 0.021). CONCLUSIONS: Our results suggested a positive causal effect of serum 25(OH)D concentration on AMM; however, more researches are warranted to unveil the underlying biological mechanisms and evaluate the effects of vitamin D intervention on AMM.

Humans↗

PubMed2026

The reporting and handling of missing data in genetic epidemiological studies of mental health in childhood and adolescence: A systematic review.

BACKGROUND: Genetic epidemiological analyses of child and adolescent mental health often use data from prospective longitudinal cohorts. Missingness due to selective attrition is therefore an important potential source of bias in such analyses. Informatively reporting on missingness and taking appropriate steps to handle it in analyses can mitigate this potential bias. Here, we aim to systematically assess how researchers report and address missingness in genetic epidemiological studies of child and adolescent mental health-related outcomes using cohort data. METHODS: We systematically searched the Ovid Medline database for studies published between August 2012 and August 2025, reporting polygenic score, genome-wide association, or Mendelian randomization analyses, of data on children or adolescents participating in cohort studies. We extracted information from eligible studies based on criteria adapted from the strengthening and reporting of observational studies in epidemiology (STROBE) guidelines. RESULTS: A total of 133 eligible studies were included, of which 125 (93.98%) reported the number of complete cases in all waves, while 84 (63.16%) detailed the amount of missingness on all key variables. Most studies used complete case analysis, while 39 studies explicitly reported applying other methods to handle missingness, with multiple imputation (n = 20, 15.04%) being the most common, followed by full information maximum likelihood 10 (8.1%). Only 18 studies (13.53%) reported an assumed missing mechanism along with the method used to address missingness. Full reporting of both the extent and handling of missingness at the item level was rare, occurring in only 5 (3.76%) and 15 (11.28%) studies, respectively, among the 123 studies that used multi-item instruments. CONCLUSION: Best practice recommendations for reporting on missing data handling emphasize the importance of detailing the proportion of missingness, types of mechanisms underpinning missingness, and details of approaches used. Based on this review, these recommendations for proper reporting of missing data are rarely followed in full.

children and adolescents↗

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↗

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

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↗