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PubMed2026

Associations between granulysin and ovarian endometriosis: A 2-sample Mendelian randomization study.

Endometriosis (EMS) is a chronic inflammatory disease defined by the presence of endometrial-like tissue outside the uterine cavity. Ovarian EMS is considered the most prevalent disease phenotype. However, the causal relationship between granulysin and ovarian EMS remains unclear. We investigate the potential causal relationship between granulysin and ovarian EMS using a 2-sample Mendelian randomization analysis. Genome-wide association study data for granulysin and ovarian EMS were obtained from publicly available online databases. A 2-sample Mendelian randomization analysis was conducted using the inverse-variance weighted method. The causal effect was further validated through weighted median and MR-Egger regression analyses, and a leave-one-out sensitivity analysis was performed. The odds ratio and its 95% confidence interval were used to evaluate the causal relationship between granulysin and the risk of ovarian EMS. Our findings suggest a direct causal relationship between granulysin expression and ovarian EMS. The inverse-variance weighted analysis revealed that a 1-standard deviation increase in granulysin was associated with a 10.7% reduction in the risk of ovarian EMS (odd ratio = 0.892, 95% confidence interval: 0.824-0.966, P = .004). There may exist a negative causal relationship between granulysin expression and ovarian EMS.

Female↗
PubMed2025

Potential therapeutic targets for ovarian hyperstimulation syndrome revealed by proteome-wide mendelian randomization and colocalization analysis.

Ovarian hyperstimulation syndrome (OHSS) is a severe complication associated with assisted reproductive technologies, characterized by metabolic, immune and vascular disorders. Understanding the molecular mechanisms underlying OHSS could reveal potential therapeutic targets and improve patient outcomes. In this study, We aimed to utilize proteome-wide Mendelian randomization (MR) and colocalization analysis to identify plasma proteins associated with OHSS and evaluate their potential as therapeutic targets through druggability assessment. We employed proteome-wide MR analysis summary data-based Mendelian randomization (SMR) analysis and phenome-wide association study (PheWAS) analysis to establish causal relationships between plasma proteins and OHSS. Colocalization analysis confirmed overlaps between proteins and genetic signals associated with OHSS. Pathway and network analyses were conducted to explore biological functions and protein interactions, while drug-target databases were queried for potential therapeutic interventions. Our results showed that 4 key proteins, including Suprabasin (SBSN), SLAMF4 (CD244), Enolase 3 (ENO3) and Thioredoxin domain-containing protein 12 (TXNDC12) were identified as significant contributors to OHSS. Pathway enrichment and interaction analyses further supported their involvement in metabolic, immune and structural pathways related to OHSS. Drug availability for colocalized proteins reveled potential drug targets for ENO3 (2-deoxy-D-glucose), CD244 (lenalidomide) and TXNDC12 (Auranofin), while no potential drug targets were identified for SBSN. Over all, our study identified15 plasma proteins, including SBSN, CD244, ENO3, and TXNDC12, as key contributors to the risk of OHSS through MR and colocalization analysis. These proteins were involved in metabolic regulation, immune response and antioxidant pathways, highlighting potential therapeutic targets and suggesting new directions for treatment strategies.

Humans↗
PubMed2026

Immune Cell-Stratified Regulatory Contexts Associated With BMI-Related Multi-System Disease Risk: A Cell-Stratified Mendelian Randomization Study Using Single-Cell eQTL Data.

AIMS: Body mass index (BMI) is associated with multisystem disease risk, but the immune cell-specific regulatory contexts underlying BMI-related genetic associations with disease outcomes remain unclear. METHODS: We applied a cell-stratified Mendelian randomization framework integrating European-ancestry BMI GWAS data, GWAS datasets for 33 disease outcomes across five disease systems, single-cell cis-eQTL data from 28 peripheral blood immune cell types, and dynamic CD4+ T cell eQTL data. SuSiE-based colocalization was used to identify BMI-associated loci sharing causal variants with immune-cell gene expression. These variants were used as cell-stratified instruments for Mendelian randomization. RESULTS: Across 28 immune cell types, 1326 colocalized variants regulating 1426 genes were identified. In primary MR analyses, genetically predicted BMI showed Bonferroni-significant associations with 26 disease outcomes. Cell-stratified analyses identified 87 Bonferroni-significant associations across 17 disease outcomes. Cardiovascular diseases showed the broadest cell-stratified associations, followed by respiratory and metabolic diseases. CD4+ T cell regulatory contexts contributed one of the largest shares of prioritized associations, and BMI-related effects varied across CD4+ T cell activation states. Cross-disease prioritization highlighted recurrent immune feature genes, including TRAF3 and FGFR1. CONCLUSION: These findings prioritize CD4+ T cell regulatory contexts as potential immunogenetic links between BMI and multi-system disease risk, while requiring further validation in diverse populations and mechanistic models.

Humans↗
PubMed2026

Standard tea intake is causally associated with a reduced risk of wet age-related macular degeneration: a Mendelian randomization study.

Researchers have posited that increased consumption of tea and coffee may be associated with more favorable treatment outcomes in patients with age-related macular degeneration (AMD). However, there is no clear evidence regarding the causal associations. To delve deeper into this potential connection, scientists used a rigorous method known as Mendelian randomization (MR). This technique was used to explore the causal impact of tea and coffee consumption on the development or progression of AMD. With the aim of investigating the cause-and-effect relationship between 16 tea- and coffee-consuming subtypes and 3 AMD, we designed a two-sample MR study using comprehensive data from genome-wide association studies (GWAS). The major approach adopted was inverse variance weighting (IVW). Furthermore, we implemented complementary methods like the weighted median (WM), weighted mode, and MR-Egger to strengthen our findings. Sensitivity analyses, including MR-Egger, MR-PRESSO, leave-one-out, and Cochran's Q tests, were used to validate results, explore heterogeneity and pleiotropy, and pinpoint potential biases. Two hundred and sixty-eight instrumental variables were selected for MR analysis. The results showed that standard tea intake may be a protective factor for wet AMD [odds ratio (OR) = 0.7076, 95% confidence interval (CI) = 0.5776-0.8668, P = 8 × 10-4, PFDR = 0.0402]. Sensitivity analysis suggests that the results are robust. Our findings provide genetic evidence that standard tea intake is a protective factor against wet AMD, providing new insights into early risk stratification and prevention strategies for the disease.NEW & NOTEWORTHY This study investigates the potential causal relationship between tea and coffee consumption and age-related macular degeneration (AMD) using Mendelian randomization. Analyzing data from genome-wide association studies, we focused on 16 beverage subtypes and 3 AMD conditions. Our findings suggest that standard tea consumption may protect against wet AMD, with robust evidence supporting this link. The results offer new insights into risk stratification and prevention strategies for AMD, highlighting the importance of dietary factors in eye health.

Mendelian Randomization Analysis↗
PubMed2026

Plasma lipid species, immune cell traits, and gastric cancer risk: A Mendelian randomization study.

Plasma lipid composition has been linked to multiple cancers, yet its causal contribution to gastric cancer and the potential intermediary role of immune cells remain unclear. We aimed to clarify these relationships and identify specific lipid and immune cell traits that either protect against or promote gastric cancer. We performed a 2-sample, 2-step Mendelian randomization analysis using summary statistics from large genome-wide association studies of gastric cancer (1423 cases, 3,14,193 controls), plasma lipidomics (179 molecular species), and 731 immune cell phenotypes. Independent, genome-wide significant single-nucleotide variants served as instrumental variables. First, we estimated the causal effects of each plasma lipid on gastric cancer. Then, we explored the potential intermediary role of lipid-associated immune cell traits using a 2-step Mendelian randomization framework. Two lipids - phosphatidylethanolamine (18:0 0:0) and phosphatidylcholine (O-18:0 16:1) - were causally associated with a lower risk of gastric cancer. Three immune cell traits (CD8br and CD8dim %leukocyte, IgD on IgD+ CD38- and CD3 on CD28- CD8br) similarly showed protective effects. In contrast, phosphatidylcholine (O-16:1 18:2), triacylglycerol (49:1), triacylglycerol (56:3), and triacylglycerol (56:4) increased gastric cancer risk, as did immune traits such as TD DN (CD4-CD8-)AC, CD19 on memory B cell, CD28 on CD39+ activated Treg, CD45 on CD4+, CD127 on CD28+DN(CD4-CD8-) and CCR2 on CD14+CD16+ monocyte. Exploratory mediation analyses found no statistically significant evidence that immune cell traits mediated the effects of plasma lipids on gastric cancer risk. Specific phosphatidylethanolamines and phosphatidylcholines confer protection against gastric cancer, whereas several triacylglycerols increase risk. However, exploratory mediation analyses provided no statistically significant evidence that immune cell traits mediated these associations.

Humans↗
PubMed2025

The causal relationship between steroid hormones and risk of stroke: evidence from a two-sample Mendelian randomization study.

It is unclear how steroid hormones contribute to stroke, and conducting randomized controlled trials to obtain related evidence is challenging. Therefore, Mendelian randomization (MR) technique was employed in this study to examine this association. Through genome-wide association meta-analysis, the genetic variants of steroid hormones, including testosterone/17β-estradiol (T/E2) ratio, aldosterone, androstenedione, progesterone, and hydroxyprogesterone, were acquired as instrumental variables. Analysis was done on the impact of these steroid hormones on the risk of stroke subtypes. The T/E2 ratio was associated to an elevated risk of small vessel stroke (SVS) according to the inverse variance weighted approach which was the main MR analytic technique (OR, 1.23, 95% CI: 1.05-1.44, p = 0.009). These findings were solid since no heterogeneity nor horizontal pleiotropy were found. The causal association between T/E2 and SVS was also confirmed in the replication study (p = 0.009). Nevertheless, there was no proof that other steroid hormones increased the risk of stroke. According to this study, T/E2 ratio and SVS are causally related. However, strong evidence for the impact of other steroid hormones on stroke subtypes is still lacking. These findings may be beneficial for developing stroke prevention strategies from steroid hormones levels.

Mendelian Randomization Analysis↗
PubMed2025

Integrative analyses of mendelian randomization and bioinformatics reveal casual relationship and genetic links between COVID-19 and knee osteoarthritis.

BACKGROUND: Clinical and epidemiological analyses have found an association between coronavirus disease 2019 (COVID-19) and knee osteoarthritis (KOA). Infection with COVID-19 may increase the risk of developing KOA. OBJECTIVES: This study aimed to investigate the potential causal relationship between COVID-19 and KOA using Mendelian randomization (MR) and to explore the underlying mechanisms through a systematic bioinformatics approach. METHODS: Our investigation focused on exploring the potential causal relationship between COVID-19, acute upper respiratory tract infection (URTI) and KOA utilizing a bidirectional MR approach. Additionally, we conducted differential gene expression analysis using public datasets related to these three conditions. Subsequent analyses, including transcriptional regulation analysis, immune cell infiltration analysis, single-cell analysis, and druggability evaluation, were performed to explore potential mechanisms and prioritize therapeutic targets. RESULTS: The results indicate that COVID-19 has a one-way impact on KOA, while URTI does not play a causal role in this association. Ribosomal dysfunction may serve as an intermediate factor connecting COVID-19 with KOA. Specifically, COVID-19 has the potential to influence the metabolic processes of the extracellular matrix, potentially impacting the joint homeostasis. A specific group of genes (COL10A1, BGN, COL3A1, COMP, ACAN, THBS2, COL5A1, COL16A1, COL5A2) has been identified as a shared transcriptomic signature in response to KOA with COVID-19. Imatinib, Adiponectin, Myricetin, Tranexamic acid, and Chenodeoxycholic acid are potential drugs for the treatment of KOA patients with COVID-19. CONCLUSIONS: This study uniquely combines Mendelian randomization and bioinformatics tools to explore the possibility of a causal relationship and genetic association between COVID-19 and KOA. These findings are expected to provide novel perspectives on the underlying biological mechanisms that link COVID-19 and KOA.

Humans↗
PubMed2026

Immunological, Inflammatory, and Microbiota Determinants of Carpal Tunnel Syndrome: Evidence from Mendelian Randomization.

INTRODUCTION: Carpal Tunnel Syndrome (CTS) is a common peripheral neuropathy, and immune dysregulation and microbial dysbiosis are believed to play a role in its development. However, the cause-and-effect relationships have yet to be clarified. METHODS: Using publicly available Genome-Wide Association Study (GWAS), there are 731 immune cell phenotypes, 91 inflammatory proteins, 150 skin microbiota taxon, and 473 gut microbiota taxon based on two-sample Mendelian Randomization (MR) analysis to test whether there is a causal relationship between them and CTS. The results from the study were shown to have some degree of stability as demonstrated by various sensitivity analyses, which included running heterogeneity tests, performing MR -PRESSO, and running MR-Egger regressions. On the other hand, reverse MR was performed to verify the direction of the association. In addition, a two-step MR mediation analysis was conducted to explore whether there was a mediation effect of gut microbiota and skin microbiota, respectively, of immune and inflammatory traits on CTS. RESULTS: 22 Immune cell traits, 4 Inflammatory proteins, 18 gut microbiota taxa, and 3 skin microbiota taxa are causally associated with CTS. Reverse MR suggested feedback effects of CTS on select immune traits and gut microbiota. Mediation analysis revealed 4 gut microbiota taxa that substantially mediated immune/inflammatory effects upon CTS, with mediation rates as high as 44%; however, skin microbiota did not demonstrate any mediation. DISCUSSION: The immune dysregulation, inflammation, and the gut microbiota that cause CTS are all revealed through this research. Mendelian randomization analysis suggests that traits and inflammatory proteins of immune cells directly increase the risk of CTS, and certain types of gut microbes partially mediate these effects. Therefore, the results show a central role of the immune-gut axis in CTS pathogenesis, and suggest a systemic, rather than a local, immune-microbial interaction in disease development. CONCLUSION: We provided the first causal evidence that immune cells, inflammatory proteins, and CTS risk are causally associated with some specific taxa of gut microbiota. This contributes to a better understanding of the immune-microbiome interactions in the process of occurrence and development of CTS, and also provides theoretical support for precision prevention and treatment.

Humans↗
PubMed2026

Causal Associations and Potential Mediating Factors between Sarcopenia-Related Traits and Heart Failure Risk: A Mendelian Randomization Study.

INTRODUCTION: In this two-sample, two-step Mendelian randomization (MR) study, we aimed to elucidate the causal associations between sarcopenia-related characteristics and heart failure (HF) risk, and to identify the factors mediating these associations, with a particular focus on the mediating roles of obesity and sedentary habits. METHODS: Genetic instruments for appendicular lean mass (ALM), hand grip strength (HGS), walking pace (WP), and potential mediators were extracted from genome-wide association studies. Inverse-variance weighting (IVW) was used as the primary analytical method, supplemented by MR-Egger regression, weighted median, and weighted mode analyses. Sensitivity analyses including Cochran's Q test and MR-Egger intercept method were performed to assess heterogeneity and pleiotropy. Bidirectional MR was conducted to exclude reverse causation. RESULTS: IVW revealed that a faster genetically predicted WP was associated with lower HF risk (odds ratio [OR] 0.44, 95% confidence interval [CI] 0.33-0.60, p = 5.806 × 10-7). The mediation analysis indicated that body mass index (BMI) accounted for 32% of this effect, while time spent watching television accounted for 14%. Elevated ALM showed a slight but significant positive association with HF risk (OR 1.06, 95% CI 1.03-1.09, p = 5.437 × 10-4). However, multivariable MR adjusting for BMI completely attenuated this association (p = 0.693), suggesting ALM reflects overall body composition rather than isolated muscle mass. No significant associations were found between HGS and HF. Bidirectional MR showed no robust reverse effects. CONCLUSIONS: These findings suggest that genetically predicted increased WP exerts beneficial effects against HF, partially mediated by obesity and sedentary habits. Targeting weight management and anti-sedentary interventions may mitigate HF risk in individuals with sarcopenia-related characteristics.

Heart failure↗
PubMed2025

Alterations of gut microbiome in chronic rhinosinusitis: insights from a mendelian randomization study.

OBJECTIVE: Gut microbiome dysbiosis is associated with various diseases. Causal association between Chronic Rhinosinusitis (CRS) and gut microbiome is yet unknown. This study aimed to investigate the potential causal relationship between CRS and gut microbiome dysbiosis. METHODS: We used Genome-Wide Association Study (GWAS) data from FinnGen database for CRS. The Dutch Microbiome Project study provided data on gut microbiota species. A total of 334,182 individuals were included. Two-sample bidirectional Mendelian Randomization (MR) analysis was used to investigate causal relationship between CRS and gut microbiome. The main methods of evaluation were Inverse Variance Weighting (IVW), weighted median, weighted mode, and MR-Egger regression. Sensitivity analyses were performed to assess heterogeneity and pleiotropy. RESULTS: Forward MR analysis indicated CRS is potentially linked to decreased risk of Haemophilus parainfluenzae (OR = 0.79, 95% CI 0.66‒0.94, p = 0.009) and increased risk of Bilophila's (OR = 1.14, 95% CI 1.02-1.27, p = 0.023) within the gut. Reduced risks in gut microbiota-related pathways like UDP-N-acetyl-d-glucosamine biosynthesis I (OR = 0.85, 95% CI 0.77‒0.94, p = 0.002) and increased risk in pathway NAD biosynthesis I from aspartate (OR = 1.14, 95% CI 1.03-1.27, p = 0.010) were also linked to CRS. Reverse MR analyses, we obtained no positive results (p > 0.05/412). CONCLUSION: This study reveals CRS exerts a causal impact on shifts within the composition of the gut microbiome and also links to the changes of gut microbiota-related metabolic pathways. The risk of changes in gut microbiota should be of greater concern in patients with CRS than in the general population. LEVEL OF EVIDENCE: Mendelian Randomized (MR) studies are second only to randomized controlled trials in terms of the level of evidence.

Humans↗
PubMed2026

Genetic evidence that advanced COVID-19 accelerates longitudinal brain atrophy: A Mendelian randomization study.

Coronavirus disease 2019 (COVID-19) was reported to persist long-term in the brain and leave several long-term neurologic sequelae. However, the causal relationship between COVID-19 and brain aging is still unknown. The genome-wide association study (GWAS) data on COVID-19 phenotypes (susceptibility, hospitalization, and severity), involving a total of 5,779,391 participants, were collected from the COVID-19 Host Genetics Initiative. In addition, GWAS data on longitudinal changes in 15 brain structures, assessed via magnetic resonance imaging across the lifespan, were sourced from the ENIGMA Consortium and involved 15,640 participants. Two-sample Mendelian randomization was conducted to infer the causal relationship between COVID-19 and longitudinal brain changes. Multi-trait GWAS meta-analysis, colocalization, and fine-mapping analyses were performed to identify shared genetic etiologies. H3K27me3 ChIP-seq was used to evaluate the regulatory effect of colocalized loci. Two-step Mendelian randomization was applied to explore potential mediating mechanisms across multi-omics layers, including proteomics, metabolomics, and immunomics. Our results showed that COVID-19 hospitalization (β = -262.405, P = .041) and severity (β = -177.676, P = .049) were genetically associated with atrophied volume of total brain during longitudinal change. This suggests that individuals with advanced COVID-19 may be more susceptible to accelerated global brain aging. Caudate was genetically affected by all COVID-19 phenotypes. Seven variants were shared between advanced COVID-19 and global brain aging. rs117169628 was colocalized between advanced COVID-19 and global brain aging, and exerted an inhibitory effect on CDH15 expression, further strengthening the causality. Six metabolites, 1 protein, and 1 immune trait were identified as potential mediators. Our study indicates that advanced COVID-19 might be genetically associated with accelerated brain aging. Brain health should be paid more attention in long COVID-19.

Humans↗
PubMed2025

The relationship between major depression, attention-deficit hyperactivity disorder and coronary artery disease: A two-sample Mendelian randomization analysis.

Coronary artery disease (CAD) constitutes a principal cause of global morbidity and mortality. Studies imply a connection between mental health disorders, especially major depression (MD) and attention-deficit hyperactivity disorder (ADHD), and the risk of CAD. To investigate the causal influence of genetic susceptibility to MD and attention-deficit/hyperactivity disorder (ADHD) on the risk of CAD, summary-level data from genome-wide association studies involving individuals of European descent were utilized. This analysis identified 11 single-nucleotide polymorphisms (SNPs) associated with MD, 60 SNPs linked to ADHD, and 10 SNPs related to CAD as instrumental variables. The inverse variance weighted method was employed for causal estimation, complemented by sensitivity analyses using MR-Egger regression and the weighted median estimator. A positive causal relationship was identified between MD, attention-deficit/hyperactivity disorder (ADHD), and the risk of CAD [MD: Odds Ratio (OR): 42.66, 95% Confidence Interval (CI): 7.55-241.2; ADHD: OR: 1.055, 95% CI: 1.006-1.106]. No significant causal association was observed between obesity and ADHD. In the multivariable Mendelian randomization (MVMR) analysis, the causal effect of ADHD on CAD was found to be diminished (OR: 1.005, 95% CI: 0.998-1.020), while the impact of body mass index on CAD remained stable (OR: 1.557, 95% CI: 1.459-1.661). This Mendelian randomization study reveals the lack of a consistent association among MD, ADHD, and CAD, suggesting a causal relationship and bidirectional effects between ADHD and obesity.

Humans↗
PubMed2026

Comparing genome-wide significant and chemosensory variants as instruments for dietary patterns in Mendelian randomization.

BACKGROUND: Diet is a modifiable risk factor for cardiometabolic disease, yet establishing causality remains challenging. Mendelian randomization (MR) leverages genetic variants as instrumental variables (IVs) to enable causal inference. METHOD: Using two-sample MR, we assessed the causal effects of four principal component-derived dietary patterns (DPs)-Unhealthy, Healthy, Meat-based, Pescatarian-on cardiometabolic outcomes including body mass index, coronary artery disease, blood lipids, blood pressures, type 2 diabetes, fasting glucose and insulin, and glycated haemoglobin. Two sets of IVs were employed: conventional genome-wide significant variants associated with each DP, filtered for pleiotropy and directionality; and biologically informed variants in chemosensory receptor genes, given the role of taste and smell perception in food choice. RESULTS: Using conventional IVs, the Pescatarian DP was associated with reduced fasting insulin (βIVW = -0.10 pmol/L per SD increase in the Pescatarian DP score, 95% confidence interval -0.15, -0.04; P = 1.19 × 10-3), surviving multiple sensitivity analyses. Associations between the Unhealthy DP and elevated blood pressure and glycated haemoglobin should be interpreted cautiously; one of the two filtered IVs was strongly associated with caffeine intake, limiting the attribution of these findings to the DP itself. Chemosensory Receptor IVs yielded null findings, reflecting insufficient power. CONCLUSION: Evidence for causal effects of DPs on cardiometabolic traits was limited, with the strongest support for a protective effect of the Pescatarian DP on fasting insulin. Chemosensory IVs demonstrated limited utility for DPs, likely reflecting the heterogeneous and complex sensory profiles of overall diets. Future efforts should consider guideline-based dietary indices to facilitate interpretability and translation.

Humans↗
PubMed2025

Association of cancers with the occurrence and 28-day mortality of sepsis: a mendelian randomization and mediator analysis.

Observational studies have indicated an association between cancer and the occurrence of sepsis, with an increased risk of mortality in cancer-related sepsis. However, whether a causal relationship exists between the two remains unknown. Summary statistics of thirteen cancers from the largest available genome-wide association studies (GWAS) of GWAS catalog and FinnGen biobank were extracted for the MR analysis. GWAS data for sepsis and its 28-day mortality were obtained from MRC-IEU. Univariable, multivariable, and reverse MR analyses were employed to explore potential associations between cancers and sepsis and its 28-day mortality. Moreover, a two-step mediation MR analysis was performed to investigate independent positive causal relationships between cancers and sepsis and its 28-day mortality. In univariable Mendelian randomization (MR) analysis, significant causal relationships were found between genetically predicted lung cancer (OR = 1.17, 95% CI = 1.08-1.26, adjusted p = 0.001), squamous cell lung carcinoma (OR = 1.10, 95% CI = 1.02-1.18, adjusted p = 0.042), lung adenocarcinoma (OR = 1.12, 95% CI = 1.03-1.21, adjusted p = 0.032), small cell lung carcinoma (OR = 1.07, 95% CI = 1.02-1.12, adjusted p = 0.031), and sepsis. Subsequent multivariable MR analysis revealed that these three types of lung cancer were independently associated with the risk of sepsis. Additionally, a causal relationship was found between lung cancer and 28-day mortality from sepsis, while no causal link was observed between non-solid tumors and the onset or death of sepsis. Reverse MR analysis did not indicate a potential for sepsis to trigger the onset of cancers. Furthermore, TRAIL was found to have promotive effects on the occurrence and mortality of sepsis. Lung cancer causally correlates with increased sepsis occurrence and 28-day mortality, as evidenced by Mendelian Randomization analysis. Genetic predispositions enhance this risk, underscoring the potential of genetic profiling to guide early, precise sepsis interventions in these patients.

Humans↗
PubMed2026

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

BACKGROUND: Neutrophil extracellular traps (NETs) participate in thrombosis, inflammation, and cardiovascular remodeling, yet whether NET-related genes (NRGs) are associated with atrial fibrillation (AF) risk across multiple molecular layers remains unclear. This study used a multiomics Mendelian randomization framework to prioritize NRGs supported by methylation, expression, and protein quantitative trait loci (QTL) data. METHODS: Genome-wide significant cis instruments (P < 5 &#xd7; 10-8) were obtained for 90 methylation QTLs (mQTLs), 100 expression QTLs (eQTLs), and 38 protein QTLs (pQTLs) mapped to 137 literature- curated NRG entries. Summary-data-based Mendelian randomization (SMR) coupled with the heterogeneity in dependent instruments (HEIDI) test was applied using whole-blood mQTL data (n = 1,980), eQTLGen blood eQTL data (n = 31,684), and deCODE plasma pQTL data (n = 35,559). AF outcome data were obtained from a meta-analysis including 60,620 cases and 970,216 controls of European ancestry. RESULTS: At the methylation level, 21 CpG-feature associations across 13 genes remained significant after HEIDI filtering and false discovery rate (FDR) correction. Expression-level analysis identified eight significant gene-AF associations, whereas protein-level analysis identified seven significant features representing five unique proteins. Cross-omics integration prioritized C3, MAPK3, and STAT3 as Tier 1 genes, CTSC, LPAR3, and THBD as Tier 2 genes, and fourteen additional genes as Tier 3 candidates. C3 showed risk-increasing protein-level associations together with multiple significant CpG signals, whereas MAPK3 and STAT3 showed directionally protective expression/protein or methylation/protein patterns. DISCUSSION: The cross-omics convergence on C3, MAPK3, and STAT3 is consistent with complement activation, immune-fibrotic signaling, and cytokine-regulatory pathways implicated in AF biology, but the findings should be interpreted as genetic prioritization rather than definitive intervention-ready causality. CpG-level heterogeneity at the C3 locus and the blood/plasma origin of the QTL resources further support a cautious interpretation. Modest colocalization support and the unresolved possibility of pQTL sample overlap further support this cautious, hypothesis-generating interpretation. CONCLUSION: Multi-omics SMR prioritizes C3, MAPK3, and STAT3 as the most consistently supported NET-related genes associated with AF risk. These findings provide a framework for atrialtissue replication and mechanistic validation of NET-related pathways in AF.

Atrial fibrillation↗
PubMed2026

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&#xd7;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

Identification of putative causal associations between MicroRNAs and breast cancer via Mendelian randomization and bioinformatic analysis.

MicroRNAs (miRNAs) are implicated in breast cancer progression and prognosis. This study employed a Mendelian randomization (MR) framework to investigate causal relationships between plasma circulating miRNAs and breast cancer. miRNA expression quantitative trait loci were extracted from 2 independent cohorts. High-confidence miRNAs and their associated single-nucleotide polymorphisms were selected for 2-sample MR analyses using inverse-variance weighted and MR-Egger methods. Differential expression analysis and univariate Cox regression identified survival-associated genes in breast cancer, while enrichment analyses revealed pathways and biological processes linked to candidate targets. Pan-cancer analyses of miRNAs and targets were conducted via the ENCORI platform. Initial MR analyses in the discovery phase identified hsa-miR-100-5p, hsa-miR-125b-5p, and hsa-miR-339-5p as significantly associated with reduced breast cancer risk (P&#x2005;<&#x2005;.05), suggesting potential protective roles. A total of 1291 survival-associated differentially expressed genes were identified, with 39 overlapping targets implicated in miRNA-mediated breast cancer intervention. Enrichment analyses highlighted their involvement in cell cycle regulation and p53 signaling pathway. In the validation cohort, only hsa-miR-339-5p confirmed a protective effect on breast cancer risk, while hsa-miR-100-5p and hsa-miR-125b-5p did not reach significance. Pan-cancer profiling demonstrated aberrant miRNA expression across malignancies, prognostic relevance in multiple cancers, and significant negative correlations between miRNAs and target genes in breast tumors. Our findings provide novel insights into the causal roles of miRNAs in breast cancer pathogenesis and underscore their potential as noninvasive biomarkers and therapeutic targets. Future studies should prioritize functional validation and clinical translation of these miRNAs.

Humans↗
PubMed2024

The causal relationship between genetically predicted blood metabolites and idiopathic pulmonary fibrosis: A bidirectional two-sample Mendelian randomization study.

BACKGROUND: Numerous metabolomic studies have confirmed the pivotal role of metabolic abnormalities in the development of idiopathic pulmonary fibrosis (IPF). Nevertheless, there is a lack of evidence on the causal relationship between circulating metabolites and the risk of IPF. METHODS: The potential causality between 486 blood metabolites and IPF was determined through a bidirectional two-sample Mendelian randomization (TSMR) analysis. A genome-wide association study (GWAS) involving 7,824 participants was performed to analyze metabolite data, and a GWAS meta-analysis involving 6,257 IPF cases and 947,616 control European subjects was conducted to analyze IPF data. The TSMR analysis was performed primarily with the inverse variance weighted model, supplemented by weighted mode, MR-Egger regression, and weighted median estimators. A battery of sensitivity analyses was performed, including horizontal pleiotropy assessment, heterogeneity test, Steiger test, and leave-one-out analysis. Furthermore, replication analysis and meta-analysis were conducted with another GWAS dataset of IPF containing 4,125 IPF cases and 20,464 control subjects. Mediation analyses were used to identify the mediating role of confounders in the effect of metabolites on IPF. RESULTS: There were four metabolites associated with the elevated risk of IPF, namely glucose (odds ratio [OR] = 2.49, 95% confidence interval [95%CI] = 1.13-5.49, P = 0.024), urea (OR = 6.24, 95% CI = 1.77-22.02, P = 0.004), guanosine (OR = 1.57, 95%CI = 1.07-2.30, P = 0.021), and ADpSGEGDFXAEGGGVR (OR = 1.70, 95%CI = 1.00-2.88, P = 0.0496). Of note, the effect of guanosine on IPF was found to be mediated by gastroesophageal reflux disease. Reverse Mendelian randomization analysis displayed that IPF might slightly elevate guanosine levels in the blood. CONCLUSION: Conclusively, hyperglycemia may confer a promoting effect on IPF, highlighting that attention should be paid to the relationship between diabetes and IPF, not solely to the diagnosis of diabetes. Additionally, urea, guanosine, and ADpSGEGDFXAEGGGVR also facilitate the development of IPF. This study may provide a reference for analyzing the potential mechanism of IPF and carry implications for the prevention and treatment of IPF.

Humans↗