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PubMed2025

From genetic causality to druggable targets: A multiomics framework identifies ZSCAN16 in gout pathogenesis.

ObjectiveGout is a prevalent form of inflammatory arthritis in which many patients respond suboptimally to current therapies. Drug development is hampered by a lack of genetically validated targets, leading to high clinical trial attrition. This study aimed to systematically identify and prioritize novel, druggable targets for gout via a multilayered genetic and functional genomics approach.MethodsWe performed two-sample Mendelian randomization (MR) using cis-expression quantitative trait locus (cis-eQTL) data and dual independent gout genome-wide association study (GWAS) cohorts (openGWAS and FinnGen). The candidate genes were subjected to a rigorous validation pipeline including Bayesian colocalization, phenome-wide association studies (PheWASs) to assess pleiotropy and on-target safety, and single-cell RNA sequencing (scRNA-seq) to delineate the cellular context. Molecular docking was used to evaluate the structural druggability of prioritized targets.ResultsMR analysis revealed 15 genes causally associated with gout. Colocalization analysis (PPH4 > 0.8) prioritized two targets: ZSCAN16 (risk-increasing, OR = 1.04, 95% CI [1.02-1.06]) and TRIM10 (protective, OR = 0.96, 95% CI [0.94-0.98]). Crucially, PheWAS revealed that ZSCAN16 is highly specific to gout, whereas TRIM10 exhibited extensive pleiotropy with hematological and cardiometabolic traits, indicating significant safety risks. Single-cell analysis provided orthogonal validation, demonstrating flare-specific upregulation of ZSCAN16 in cytotoxic T/NK cells. Molecular docking confirmed ZSCAN16 as a structurally druggable target, showing high-affinity binding with known compounds (e.g. digoxin, binding energy = -9.6 kcal/mol).ConclusionsOur study identifies ZSCAN16 as a high-potential, druggable therapeutic target for gout, highlighting its genetic influence on specific immune cell activities during acute flares. Conversely, TRIM10 was deprioritized owing to substantial pleiotropic liabilities and poor chemical tractability. These findings suggest that ZSCAN16 could play a crucial role in the pathogenesis of gout and may provide a valuable lead for future drug discovery efforts.

Humans↗

PubMed2026

Dissecting the shared genetic architecture between migraine subtypes and cardiovascular diseases: a multi-layered genomic analysis.

BACKGROUND: Epidemiological studies have linked migraine to an increased risk of cardiovascular disease (CVD); however, the shared genetic basis and putative causal relationships between migraine subtypes and cardiovascular traits remain poorly understood. METHODS: Leveraging large-scale GWAS summary statistics for migraine phenotypes (overall migraine, migraine with aura [MA], and migraine without aura [MO]) from FinnGen R12, along with seven cardiovascular diseases from publicly available consortia, we conducted a multi-layered genetic analysis. This integrative framework encompassed genetic correlation [linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL)], cross-trait meta-analysis (CPASSOC and PLACO), Bayesian colocalization, summary-data-based Mendelian randomization (SMR) using GTEx v8 eQTL data, and bidirectional two-sample Mendelian randomization (MR). RESULTS: Significant genetic correlations were identified between migraine and multiple cardiovascular traits, with hypertension and coronary artery disease (CAD) showing the most robust associations. MA exhibited broader genetic overlap with cardiovascular diseases than MO, including a notably stronger correlation with ischemic stroke, whereas MO demonstrated a stronger correlation with hypertension. Cross-trait meta-analysis identified 160 pleiotropic loci across 17 of 21 trait pairs. Colocalization analysis confirmed 32 loci harboring shared causal variants, mapped to 13 candidate genes, of which 7 (PHACTR1, LRP1, SOX7, ABO, FHOD3, MEI1, XKR6) were further validated by SMR as exhibiting tissue-specific regulatory effects. Among these, PHACTR1 displayed the broadest pleiotropic profile across migraine phenotypes and vascular diseases. After MR-PRESSO outlier removal, bidirectional MR identified 10 MR-supported associations, two of which (genetic liability to hypertension on overall migraine, and CAD on MA) survived Bonferroni correction, all free of detectable horizontal pleiotropy. Genetic liability to hypertension was associated with increased migraine risk (OR = 1.90, 95% CI 1.25-2.90, P = 2.64 × 10⁻³), atherosclerotic diseases showed subtype-specific effects (inverse for MO, positive for MA), and, in the reverse direction, migraine was associated with increased ischemic stroke risk. CONCLUSIONS: This study provides a comprehensive and systematic characterization of the shared genetic architecture between migraine subtypes and cardiovascular diseases. By identifying pleiotropic genes and bidirectional putative causal relationships with subtype-specific patterns, our findings carry implications for the development of targeted therapeutics and subtype-specific cardiovascular risk stratification.

Humans↗

PubMed2025

Education, socioeconomic status, leisure sedentary behaviors and female infertility: mendelian randomization study.

BACKGROUND: Previous studies have indicated that education, socioeconomic status, and leisure sedentary behavior may be associated with female infertility. However, it remains unclear whether these associations imply causal relationships. METHODS: Genetic variants from genome-wide association studies (GWAS) of education, socioeconomic status, and leisure sedentary behaviors were obtained from the UK Biobank and MRC-IEU database (Medical Research Council Integrative Epidemiology Unit), female infertility data was acquired from the FinnGen Biobank. Univariable and multivariable MR analyses were performed to explore the relationships between these traits and female infertility. RESULTS: The results of the univariate MR analysis indicated that age of full-time education had a protective effect on female infertility (odds ratio [OR] 0.471; 95% confidence interval [CI] 0.24 to 0.93; p = 0.03). Multivariable MR and reverse MR studies support the existence of a relationship between them. However, no causal correlation was found between other traits and female infertility. No significant heterogeneity or horizontal pleiotropy was detected, and the stability of the results was confirmed through sensitivity analysis and the leave-one-out test. CONCLUSIONS: A later age of completion of full-time education may be causally related to a reduced risk of female infertility, but no causality is established between other educational levels factors, socioeconomic status, or sedentary behaviors and infertility risk.

Humans↗

PubMed2024

Mendelian randomization analysis reveals higher whole body water mass may increase risk of bacterial infections.

BACKGROUND AND PURPOSE: The association of water loading with several infections remains unclear. Observational studies are hard to investigate definitively due to potential confounders. In this study, we employed Mendelian randomization (MR) analysis to assess the association between genetically predicted whole body water mass (BWM) and several infections. METHODS: BWM levels were predicted among 331,315 Europeans in UK Biobank using 418 SNPs associated with BWM. For outcomes, we used genome-wide association data from the UK Biobank and FinnGen consortium, including sepsis, pneumonia, intestinal infections, urinary tract infections (UTIs) and skin and soft tissue infections (SSTIs). Inverse-variance weighted MR analyses as well as a series of sensitivity analyses were conducted. RESULTS: Genetic prediction of BWM is associated with an increased risk of sepsis (OR 1.34; 95% CI 1.19 to 1.51; P = 1.57 × 10- 6), pneumonia (OR: 1.17; 95% CI 1.08 to 1.29; P = 3.53 × 10- 4), UTIs (OR: 1.26; 95% CI 1.16 to 1.37; P = 6.29 × 10- 8), and SSTIs (OR: 1.57; 95% CI 1.25 to 1.96; P = 7.35 × 10- 5). In the sepsis and pneumonia subgroup analyses, the relationship between BWM and infection was observed in bacterial but not in viral infections. Suggestive evidence suggests that BWM has an effect on viral intestinal infections (OR: 0.86; 95% CI 0.75 to 0.99; P = 0.03). There is limited evidence of an association between BWM levels and bacteria intestinal infections, and genitourinary tract infection (GUI) in pregnancy. In addition, MR analyses supported the risk of BWM for several edematous diseases. However, multivariable MR analysis shows that the associations of BWM with sepsis, pneumonia, UTIs and SSTIs remains unaffected when accounting for these traits. CONCLUSIONS: In this study, the causal relationship between BWM and infectious diseases was systematically investigated. Further prospective studies are necessary to validate these findings.

Humans↗

PubMed2025

Severe traumatic brain injury and risk for osteoporosis: a Mendelian randomization study.

BACKGROUND: The influence of nervous system activity on bone remodeling has been widely reported. Patients with traumatic brain injury (TBI) exhibit a high incidence of osteoporosis (OP). Nevertheless, the relationship between severe TBI (sTBI) and OP remains unclear. We performed Mendelian randomization (MR) analysis to assess the potential causal relationship between sTBI and OP. METHODS: Data on exposure and outcomes were acquired from genome-wide association studies (GWAS). Data on OP was obtained from UK Biobank (5,266 cases of OP and 331,893 controls). Data on sTBI was obtained from FinnGen Consortium (6,687 cases and 370,590 controls). Single nucleotide polymorphisms (SNPs) that underwent strict screening were regarded as instrumental variables. We used the inverse variance weighted (IVW), constrained maximum likelihood and model averaging (CML-MA), MR-Egger, and weighted median methods for causal effect estimation. To test the reliability of the results, sensitivity analysis was performed using Cochran's Q, leave-one-out, MR-Egger intercept, and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) tests. RESULTS: The IVW analysis indicates that sTBI and OP have a suggestive association (odds ratio [OR] = 1.004, 95% confidence interval [CI] = 1.001,1.007; p = 0.002), and no heterogeneity (Q = 11.536, p = 0.241) or directional pleiotropy was observed (egger_intercept = 7.368 × 10- 5, p = 0.870). The robustness of the results was validated using a leave-one-out sensitivity test. CONCLUSION: According to the MR analysis, sTBI and OP are likely suggestively related. This finding contributes to the prevention of OP in patients with sTBI and provides genetic evidence supporting the theory that the nervous system regulates bone remodeling.

Humans↗

PubMed2025

Causal association between non-steroidal anti-inflammatory drugs use and the risk of benign prostatic hyperplasia: a univariable and multivariable Mendelian randomization study.

BACKGROUND: The results of earlier observational research on the relationships between the usage of non-steroidal anti-inflammatory medicines (NSAIDs) and the risk of benign prostatic hyperplasia (BPH) have been inconsistent. METHODS: To assess these associations, we performed both univariable and multivariable Mendelian randomization (MR) studies. Instrumental variables (IVs) associated with exposures at the significance level (p < 5 × 10-6) were selected from a comprehensive meta-analysis conducted by the United Kingdom Biobank (UKB). Summary data for BPH were obtained from the FinnGen consortium, which comprised 30,066 cases and 119,297 controls. Sensitivity analyses were performed to evaluate heterogeneity and pleiotropy. RESULTS: We found evidence by univariable MR (UVMR) that genetically predicted NSAIDs use increased the risk of BPH (odds ratio [OR] per unit increase in log odds NSAIDs use: 1.164, 95% confidence interval [CI]: 1.041-1.302, p = 0.008). After controlling for inflammation in multivariable MR (MVMR), the link persisted (OR: 1.165, 95% CI: 1.049-1.293, p = 0.004). There were no indications of potential heterogeneity and pleiotropy in UVMR and MVMR analyses. CONCLUSION: The results of the MR estimates suggest that genetically predicted NSAIDs use may elevate the risk of BPH. This outcome prompts the imperative for deeper exploration into potential underlying mechanisms.

Humans↗

PubMed2025

Association of genetically proxied cancer-targeted drugs with cardiovascular diseases through Mendelian randomization analysis.

BACKGROUND: Cancer-targeted therapies are progressively pivotal in oncological care. Observational studies underscore the emergence of cancer therapy-related cardiovascular toxicity (CTR-CVT), impacting patient outcomes. We aimed to investigate the causal relationship between different types of cancer-targeted therapies and cardiovascular disease (CVD) outcomes through a two-sample Mendelian randomization (MR) study. METHODS: This genome-wide association study was conducted using a two-sample Mendelian randomization framework. Genetic instruments for drug target gene expression were extracted from the eQTLGen consortium (31684 individuals, 37 cohorts). Genome-wide association study (GWAS) summary statistics for 19 cardiovascular diseases were derived from the FinnGen database. Primary analysis was carried out using the summary-data-based MR (SMR) method, with sensitivity analysis for validation. Colocalization analysis identifies shared causal variants between exposure eQTLs and CVD-associated single-nucleotide polymorphisms (SNPs). RESULTS: Among the 39 drug target genes, 8 were identified with detectable cis-eQTLs and were subsequently validated through positive control analysis for further investigation. In the SMR and sensitivity analyses, genetically proxied VEGFA inhibition showed significantly strong association with stroke (odds ratio [OR] = 1.17, 95% confidence interval [CI] = 1.09-1.26, p = 1.33 × 10- 5). Additionally, the inhibition of FGFR1, FLT1, and MAP2K2 exhibited suggestive association with corresponding cardiovascular disease outcomes. Nevertheless, only VEGFA expression and stroke shared a causal variant (93.6%), whereas FGFR1, MAP2K2, and FLT1 did not share causal variants with corresponding cardiovascular diseases in the colocalization analysis. CONCLUSIONS: This genetic association study revealed evidence supporting the genetic association between the use of VEGFA inhibitors and increased stroke risk, highlighting the need for enhanced pharmacovigilance. These findings underscore the delicate balance between cardiovascular toxicity risk and the benefits of cancer-targeted therapy.

Humans↗

PubMed2026

Linking cortical structure and delirium in the elderly: insights from cohort study and shared genetic risk analysis.

BACKGROUND: This study aimed to assess the association between regional cortical changes measured via baseline magnetic resonance imaging (MRI) and the incidence of delirium. METHODS: Observational associations were assessed using a prospective cohort from the UK Biobank and an independent clinical cohort. The population-based study included participants aged 60 years or older who had undergone structural brain MRI since 2014. Regional cortical volume, mean thickness, and surface area were extracted based on the Desikan-Killiany cortical atlas. Delirium was defined using ICD-10 diagnostic codes. Additionally, preoperative brain MRI images from participants in another cohort were collected and automatically segmented using deep learning algorithms to obtain cortical measurements. Logistic analysis was performed to investigate the associations between cerebral cortical structure and delirium risk. Lastly, genome-wide association study data derived from the ENIGMA Consortium and FinnGen Biobank were utilized to conduct conditional/conjunctional false discovery rate (cond/conjFDR) analyses to identify shared genetic loci associated with cortical structures and delirium. RESULTS: This observational analysis included 31,890 participants from the UK Biobank and 152 participants from an independent cohort. In the UK Biobank cohort, decreased cortical thickness in the 17 regions was associated with a significantly increased risk of delirium. Similarly, a preoperative reduction in cortical volume in 7 regions was associated with an increased risk of delirium in the independent cohort. Besides, 100 single-nucleotide polymorphisms (SNPs) were identified as significantly associated with cortical structures when conditioned on delirium. Finally, colocalization analysis demonstrated that these pleiotropic risk loci modulated the expression of NT5C2, RGP1, CCDC25, TPM2, EEF1AKMT2, IQANK1 and LHPP in blood and brain tissues. CONCLUSION: Regional cortical atrophy is associated with an increased risk of delirium in the elderly. Brain MRI examinations may be beneficial for preoperative delirium risk assessment in elderly individuals undergoing elective surgery.

Humans↗

PubMed2024

Assessing the causal link between liver function and acute pancreatitis: A Mendelian randomisation study.

A correlation has been reported to exist between exposure factors (e.g. liver function) and acute pancreatitis. However, the specific causal relationship remains unclear. This study aimed to infer the causal relationship between liver function and acute pancreatitis using the Mendelian randomisation method. We employed summary data from a genome-wide association study involving individuals of European ancestry from the UK Biobank and FinnGen. Single-nucleotide polymorphisms (SCNPs), closely associated with liver function, served as instrumental variables. We used five regression models for causality assessment: MR-Egger regression, the random-effect inverse variance weighting method (IVW), the weighted median method (WME), the weighted model, and the simple model. We assessed the heterogeneity of the SNPs using Cochran's Q test. Multi-effect analysis was performed using the intercept term of the MR-Egger method and leave-one-out detection. Odds ratios (ORs) were used to evaluate the causal relationship between liver function and acute pancreatitis risk. A total of 641 SNPs were incorporated as instrumental variables. The MR-IVW method indicated a causal effect of gamma-glutamyltransferase (GGT) on acute pancreatitis (OR = 1.180, 95%CI [confidence interval]: 1.021-1.365, P = 0.025), suggesting that GGT may influence the incidence of acute pancreatitis. Conversely, the results for alkaline phosphatase (ALP) (OR = 0.997, 95%CI: 0.992-1.002, P = 0.197) and aspartate aminotransferase (AST) (OR = 0.939, 95%CI: 0.794-1.111, P = 0.464) did not show a causal effect on acute pancreatitis. Additionally, neither the intercept term nor the zero difference in the MR-Egger regression attained statistical significance (P = 0.257), and there were no observable gene effects. This study suggests that GGT levels are a potential risk factor for acute pancreatitis and may increase the associated risk. In contrast, ALP and AST levels did not affect the risk of acute pancreatitis.

Humans↗

PubMed2026

Integrated single-cell transcriptomics, Mendelian randomization, and machine learning identify CEBPZ as an immune-related biomarker in oral lichen planus.

BACKGROUND: Oral lichen planus (OLP) is a chronic, immune-mediated oral mucosal disease with complex pathophysiology and potential for malignant transformation. Understanding its molecular basis is critical for the development of precise diagnostic and therapeutic strategies. OBJECTIVES: We aimed to identify key immune-related biomarkers and characterize cellular dynamics in OLP, with a particular focus on the role of CEBPZ in disease pathogenesis. MATERIAL AND METHODS: We analyzed single-cell RNA sequencing (scRNA-seq) data from OLP lamina propria samples (GSE211630) to identify disease-specific T-cell subpopulations using high-dimensional weighted gene co-expression network analysis (hdWGCNA) for oxidative stress-related gene modules.-data-based Mendelian randomization (SMR) integrated FinnGen genome-wide association study (GWAS; 342,499 Europeans) data with Genotype-Tissue Expression (GTEx) expression quantitative trait loci (eQTL) data to identify causal genes. Machine learning (ML) models (least absolute shrinkage and selection operator (LASSO) and convolutional neural network (CNN)) were developed using bulk RNA-seq datasets (GSE52130 and GSE38616) for diagnostic purposes. RESULTS: We identified OLP-specific T-cell populations (clusters 0, 3, 5, 7, 13, and 15) with enhanced migration inhibition factor (MIF) pathway signaling toward B cells and monocytes. Two oxidative stress-associated modules contained hub genes, including CEBPZ. Summary-data-based Mendelian randomization analysis identified 231 OLP-associated genes, with CEBPZ uniquely intersecting LASSO-selected markers (odds ratio (OR) = 1.057, 95% confidence interval (95% CI) = 1.013-1.102, p = 0.010). Machine learning models achieved area under the curve (AUC) values ranging from 0.653 to 0.745, with the CNN model reaching a validation accuracy of 0.735. CEBPZ showed elevated expression in OLP T cells and correlated with enhanced MIF-(CD74+CXCR4) signaling. CONCLUSIONS: This integrative approach identifies CEBPZ as a pivotal biomarker linking genetic susceptibility, oxidative stress, and immune dysregulation in OLP. Our diagnostic models offer promising tools for OLP management.

CEBPZ↗

PubMed2026

Genetically Predicted Gene Expression and Circulating Metabolites Associated with Cervical High-Grade Squamous Intraepithelial Lesion: A Mendelian Randomization Study.

BACKGROUND: High-grade squamous intraepithelial lesion (HSIL) is a precancerous condition of the cervix. Identifying risk factors associated with HSIL and understanding their potential mechanisms may inform prevention strategies. This study aimed to investigate the associations of genetically predicted gene expression and circulating metabolites with HSIL risk using Mendelian randomization (MR). METHODS: We performed two-sample MR analysis to evaluate the associations of genetically predicted gene expression (eQTLGen consortium, N=31,684) and circulating metabolites (genome-wide association study [GWAS], N=8,299) with HSIL risk (FinnGen R12, N=293,218; 8,291 cases). Mediation analysis was conducted to explore whether metabolites might mediate the associations between genes and HSIL. Sensitivity analyses, including Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), leave-one-out, and colocalization, were performed to assess the robustness of the findings. All GWAS data used in this study were derived from European-ancestry populations. RESULTS: Eleven genes showed significant associations with HSIL after false discovery rate (FDR) correction (q<0.05), including VWA7, PAX8, GUSBP1, IKZF3, PAX8-AS1, NFKBIL1 (interpret with caution due to an influential single nucleotide polymorphism [SNP]), ERBB2, COL11A2, SKIV2L, TCF19, and PGAP3. Eleven circulating metabolites were also significantly associated with HSIL. Mediation analysis suggested that two phospholipid metabolites (GCST90200685 and GCST90200692) might mediate a small proportion of the total protective association of COL11A2 with HSIL (1.46% and 1.45%, respectively), indicating that the protective association of COL11A2 is largely independent of these circulating metabolites. Colocalization analysis showed strong evidence of shared causal variants for eight genes (PP.H4>0.98), while COL11A2 showed weak evidence of colocalization (PP.H4=1.58×10-15). Functional enrichment analysis indicated that COL11A2-related genes were enriched in extracellular matrix (ECM)-receptor interaction and PI3K-Akt signaling pathways. CONCLUSION: This MR study identified 11 genes and 11 circulating metabolites associated with HSIL risk. Among these, COL11A2 showed a protective association that appeared to be largely independent of circulating phospholipid metabolites, suggesting potential local mechanisms. These findings provide genetic and metabolic clues for future studies on HSIL etiology.

COL11A2↗

PubMed2026

Spatially Contextualized Integrative Genomics Highlights Neuronal and Glial Regulatory Programs in Low Back Pain.

PURPOSE: Low back pain (LBP) is a heterogeneous pain condition with a measurable genetic contribution, but the genes, brain cell types, and spatial tissue contexts through which inherited risk is expressed remain unclear. We aimed to define cell-type-specific and spatially contextualized genetic mechanisms underlying LBP. METHODS: FinnGen R12 LBP GWAS summary statistics (42,521 cases and 353,224 controls) were integrated with brain single-nuclei eQTL data across eight major brain cell classes. We evaluated genome-wide polygenic signal using LDSC, prioritized genes using MAGMA and PoPS, and performed brain cell-type-specific eQTL-anchored Mendelian randomization, primarily based on single-instrument Wald ratio estimates, followed by Bayesian colocalization. Spatial genetic mapping was conducted using gsMap in an E16.5 murine embryonic atlas and two adult human lumbar spinal cord Visium sections. Selected candidates were assessed by RT-qPCR in neuronal-like and astroglial-like inflammatory cell models. RESULTS: LDSC supported interpretable polygenic signal for LBP. MAGMA and PoPS showed partial gene-level convergence, with TCF4 and TMEFF2 supported by both approaches. Across 1641 tested gene-cell type exposures, significant eQTL-anchored MR associations were concentrated in excitatory neurons, oligodendrocytes, inhibitory neurons, and astrocytes. Integrated eQTL-anchored MR, colocalization, and gene-prioritization evidence highlighted CLEC18A, QPRT, and GMPPB as higher-priority non-MHC candidates with moderate, but not strong, colocalization support. gsMap localized LBP-associated enrichment to neuroaxis-related embryonic regions, including brain, spinal cord, sympathetic nerve, and dorsal root ganglion, and to neuronal-like niches in adult lumbar spinal cord. RT-qPCR showed model-dependent expression changes, with QPRT and LGI4 preferentially responsive in neuronal-like SH-SY5Y cells and GMPPB and DPYSL5 responsive in astroglial-like U251 cells. CONCLUSION: These findings support neuronal and glial regulatory programs as plausible contributors to LBP genetic susceptibility and highlight CLEC18A, QPRT, and GMPPB as higher-priority non-MHC candidates with moderate colocalization support. The results provide a spatially contextualized framework for candidate prioritization in LBP, while emphasizing the need for larger cell-type-specific eQTL resources and functional validation before therapeutic or mechanistic conclusions can be drawn.

Mendelian randomization↗

PubMed2026

The Association of Allergic Rhinitis with Chronic Adenotonsillar Diseases and Chronic Rhinosinusitis: A Mendelian Randomization Study.

INTRODUCTION: Allergic rhinitis (AR) has long been considered to be associated with chronic adenotonsillar disease (CATD). However, their causal relationship remains unclear. This study aims to investigate the causal relationship between AR and CATD and to examine the mediating role of chronic rhinosinusitis (CRS) in this association. METHODS: This study employed a two-sample Mendelian randomization (MR) design using genetic instrumental variable analysis. Data for allergic rhinitis (AR) were obtained from the MRC IEU OpenGWAS data infrastructure, data for chronic adenotonsillar disease (CATD) from the FinnGen biobank, and data for chronic rhinosinusitis (CRS) from the GWAS Catalog. Several MR methods were applied. In addition, a two-step MR approach was used to investigate the mediating role of CRS in the relationship between AR and CATD. RESULTS: MR analysis identified a positive correlation between AR and CATD. IVW and weighted median analyses showed significant causal effects (beta = 0.55, 95% CI: 0.26 to 0.84); p <0.001). No causal association was found between CATD and AR. AR and CRS showed a positive correlation (beta = 1.38, 95% CI: 0.78 to 1.98; p = 6.5 × 10-6). CRS had a beta value of 0.15 (95% CI: 0.06 to 0.24; p = 0.001) for CATD. CRS mediates 37.6% of the AR to CATD pathway (mediation effect = 0.20, 95% CI: 0.04 to 0.37; p = 0.013). DISCUSSION: These findings indicate that AR may contribute to CATD risk through CRS, highlighting the need for further research to explore underlying biological mechanisms and validate these findings. CONCLUSIONS: This study suggests a positive causal relationship between AR and CATD, with CRS acting as a mediator.

Mendelian Randomization Analysis↗

PubMed2026

Genetic Association Between Sleep Traits and Vertigo Risk: A Two-sample Bidirectional Mendelian Randomization Study.

BACKGROUND: Observational studies suggest the potential association between sleep traits and vertigo; however, causal evidence remains limited. OBJECTIVE: This study aimed to explore the relationship between genetically predicted sleep traits and vertigo with the Mendelian randomization (MR) method. METHODS: Instrumental variables for sleep traits (snoring, sleep duration, insomnia, daytime sleepiness, daytime napping, and chronotype) were adopted from genomewide association studies (GWAS) data of European ancestry from UK Biobank. The summary-level datasets of vertigo were retrieved from the GWAS of FinnGen. Inversevariance weighted (IVW) method was adopted as the main analysis. RESULTS: IVW analysis revealed a significant association between genetically predicted daytime napping (OR = 1.51, 95% CI =1.08-2.12, P = 0.016) and chronotype (OR = 1.13, 95% CI =1.01-1.26, P = 0.033), both of which were associated with an increased risk of vertigo. However, we did not find evidence for a causal effect of snoring, overall sleep duration, long sleep duration, short sleep duration, insomnia, and excessive daytime sleepiness on vertigo. No reverse causality was detected. CONCLUSION: Our findings suggest that abnormal sleep patterns may serve as risk factors for vertigo disorders and offer opportunities for the prevention and management of vertigo disorders.

Humans↗

PubMed2026

Gut Microbiota, Lipidome, and Metabolites Mediate Immune Dysregulation in Diabetic Microvascular Disease: A Two-sample Mendelian Randomization and Mediation Analysis.

INTRODUCTION: Diabetic microvascular disease (DMiVD) involves dysregulated immune cell function, but the precise pathogenic mechanisms remain unclear. MATERIALS AND METHODS: We conducted a two-sample Mendelian randomization (MR) study using comprehensive GWAS and FinnGen summary statistics, encompassing 731 immune cell phenotypes, 473 gut microbial taxa, 91 inflammatory proteins, 179 lipid types, 1,400 plasma metabolites, 20 micronutrients, and DMiVD cases. The analysis aimed to evaluate causal associations between these variables and DMiVD. We further explored potential mediating roles of gut microbiota, plasma lipidome, and metabolites using mediation analysis, with multiple sensitivity tests confirming the robustness of our findings. RESULTS: We identified 20 immune cell phenotypes, 33 gut microbial taxa, 31 lipid types, and 83 plasma metabolites with significant causal associations with DMiVD. Mediation analysis revealed that the risk effect of CD3+ resting Tregs on diabetic nephropathy was partly mediated by phosphatidylcholine (16:0_18:2) (10.7%). Additionally, the protective effect of CX3CR1 on monocytes against DMiVD was partly mediated by Unclassified Bacilli A (35%), Species CAG-177 sp003538135 (22.6%), and triacylglycerol (52:6) (25.5%). DISCUSSION: These findings advance understanding of DMiVD pathogenesis, highlighting that modulation of key metabolic pathways and immune regulatory nodes may represent promising therapeutic strategies. Further experimental studies are needed to validate these potential causal relationships. CONCLUSION: Using causal inference approaches, this study identifies immune cell-mediated mechanisms underlying DMiVD, involving gut microbiota, plasma lipids, and metabolites. The results suggest potential intervention targets for mechanistic studies and therapeutic development.

Mendelian Randomization Analysis↗

PubMed2024

Effect of inflammatory cytokines and plasma metabolome on OSA: a bidirectional two- sample Mendelian randomization study and mediation analysis.

BACKGROUND: Obstructive sleep apnea (OSA) is a common sleep disorder. Inflammatory factors and plasma metabolites are important in assessing its progression. However, the causal relationship between them and OSA remains unclear, hampering early clinical diagnosis and treatment decisions. METHODS: We conducted a large-scale study using data from the FinnGen database, with 43,901 cases and 366,484 controls for our discovery MR analysis. We employed 91 plasma proteins from 11 cohorts (totaling 14,824 participants of European descent) as instrumental variables (IVs). Additionally, we conducted a GWAS involving 13,818 cases and 463,035 controls to replicate the MR analysis. We primarily used the IVW method, supplemented by MR Egger, weighted median, simple mode, and weighted mode methods. Meta-analysis was used to synthesize MR findings, followed by tests for heterogeneity, pleiotropy, and sensitivity analysis (LOO). Reverse MR analysis was also performed to explore causal relationships. RESULTS: The meta-analysis showed a correlation between elevated Eotaxin levels and an increased risk of OSA (OR=1.050, 95% CI: 1.008-1.096; p < 0.05). Furthermore, we found that the increased risk of OSA could be attributed to reduced levels of X-11849 and X-24978 (decreases of 7.1% and 8.4%, respectively). Sensitivity analysis results supported the reliability of these findings. CONCLUSIONS: In this study, we uncovered a novel biomarker and identified two previously unknown metabolites strongly linked to OSA. These findings underscore the potential significance of inflammatory factors and metabolites in the genetic underpinnings of OSA development and prognosis.

Female↗

PubMed2026

Potential mitochondria-associated pathogenic genes in sepsis: a multi-omics Mendelian randomization study.

BACKGROUND: Mitochondrial dysfunction has been implicated in the pathophysiology of sepsis. However, human genetic evidence linking mitochondria-related genes to sepsis susceptibility remains limited. This study aimed to identify mitochondria-related genes associated with sepsis risk using a multi-omics Mendelian randomization framework. METHODS: Summary-data-based Mendelian randomization (SMR) was applied using sepsis genome-wide association study (GWAS) summary statistics from the UK Biobank and FinnGen databases. Expression, methylation, single-cell, and protein quantitative trait loci (QTLs) were used as genetic instruments. Colocalization analyses were conducted to evaluate whether SMR associations were driven by shared genetic variants. Expression of prioritized candidate genes was further examined in clinical septic samples, and correlations with disease severity (SOFA scores) were assessed. RESULTS: SMR analysis prioritized 13 mitochondria-related genes associated with sepsis risk. Immune cell-specific eQTL analysis suggested that genetically predicted SURF1 expression in memory B cells and naïve T cells was associated with sepsis risk. Differential expression of 12 candidate genes was confirmed in septic patients by qPCR, and PPOX expression showed a negative correlation with SOFA scores. Integration of mQTL and eQTL data supported a regulatory relationship between methylation at cg06661924 and AK4 expression. Increased genetically predicted AK4 expression was associated with higher sepsis risk (OR = 1.21, 95% CI 1.02-1.42). Protein-level analysis identified DUT as a potential sepsis-associated candidate, with consistent evidence across streptococcal and pneumococcal septicemia subtypes. Subtype analyses also suggested heterogeneous genetic signals across different sepsis subtypes. CONCLUSION: This study prioritized several mitochondria-related genes associated with sepsis susceptibility based on human genetic evidence. These findings provide candidate targets for further mechanistic and translational investigation.

Humans↗

PubMed2025

Exploring the causal relationship between plasma proteins and postherpetic neuralgia: a Mendelian randomization study.

BACKGROUND: The proteome represents a valuable resource for identifying therapeutic targets and clarifying disease mechanisms in neurological disorders. This study investigated potential causal relationships between plasma proteins and postherpetic neuralgia (PHN). METHODS: We conducted a two-sample Mendelian randomization (MR) analysis using genome-wide association study (GWAS) summary statistics from the Decode Genetics dataset (4,907 plasma proteins) and the FinnGen database (490 PHN cases and 435,371 controls). Instrumental variables (IVs) were selected based on relevance, independence, and exclusivity. Causal associations were assessed using inverse-variance weighted (IVW), MR-Egger regression, simple mode, weighted mode, and weighted median methods. Sensitivity analyses, including leave-one-out tests, evaluated result robustness, while colocalization analysis examined shared causal variants between traits. RESULTS: Eight plasma proteins showed significant associations with PHN (PFDR < 0.05). Higher levels of ATRN, PIANP, and CD48 correlated with increased PHN risk, whereas elevated KIR2DL5A, GPI, SEMG2, EIF4B, and HFE2 levels were associated with reduced risk. Sensitivity analyses supported these findings and excluded genetic pleiotropy as a major confounding factor. Colocalization analysis did not detect shared causal variants (PPH4 < 0.8). CONCLUSION: These results suggest a potential causal role for eight plasma proteins in PHN pathogenesis. While these proteins may serve as biomarkers or therapeutic candidates, further validation is required. This study advances understanding of PHN pathophysiology and supports future investigations into diagnostic and therapeutic strategies.

Mendelian randomization↗