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Causal Relationship of Polyunsaturated Fatty Acids With Mental Disorders: A Systematic Review and Meta-analysis.

CONTEXT: Mental disorders (MDs) pose a important global health challenge, with a complex pathogenesis complicating treatment development. Nutritional interventions, particularly polyunsaturated fatty acids (PUFAs), have gained attention as potential therapeutic options. OBJECTIVE: This Mendelian randomization (MR) meta-analysis aimed to evaluate the potential causal relationship between PUFAs and MDs. DATA SOURCES: Genome-wide association study data were utilized to analyze the association between PUFAs (including omega-3, omega-3 percentage [omega-3%], omega-6, omega-6 percentage [omega-6%], and omega-6 to omega-3 ratio) and 12 major MDs. DATA EXTRACTION: Two-sample MR technology was used to assess the role of PUFAs in MDs. DATA ANALYSIS: The MR analysis revealed that genetically predicted omega-3 was causally linked to MDs, such as obsessive-compulsive disorder, bipolar disorder, schizophrenia, and major depressive disorder. Omega-3% exhibited protective effects against emotional personality disorder. Conversely, omega-6 was inversely correlated with attention-deficit/hyperactivity disorder risk, while a high omega-6 to omega-3 ratio was associated with an increased risk of depression and other mood disorders. CONCLUSION: High omega-3 levels and omega-3% may reduce the risk of MDs, whereas a high omega-6:omega-3 ratio may elevate the risk. These findings highlight the potential of PUFAs, particularly omega-3, in MD prevention and treatment, while underscoring the need for further research into the complex interactions between omega-3 and omega-6. The study provides a scientific foundation for future clinical trials and dietary intervention strategies. SYSTEMATIC REVIEW REGISTRATION: PROSPERO no. CRD42024598472.

Humans↗

'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?

Associations between modifiable exposures and disease seen in observational epidemiology are sometimes confounded and thus misleading, despite our best efforts to improve the design and analysis of studies. Mendelian randomization-the random assortment of genes from parents to offspring that occurs during gamete formation and conception-provides one method for assessing the causal nature of some environmental exposures. The association between a disease and a polymorphism that mimics the biological link between a proposed exposure and disease is not generally susceptible to the reverse causation or confounding that may distort interpretations of conventional observational studies. Several examples where the phenotypic effects of polymorphisms are well documented provide encouraging evidence of the explanatory power of Mendelian randomization and are described. The limitations of the approach include confounding by polymorphisms in linkage disequilibrium with the polymorphism under study, that polymorphisms may have several phenotypic effects associated with disease, the lack of suitable polymorphisms for studying modifiable exposures of interest, and canalization-the buffering of the effects of genetic variation during development. Nevertheless, Mendelian randomization provides new opportunities to test causality and demonstrates how investment in the human genome project may contribute to understanding and preventing the adverse effects on human health of modifiable exposures.

Animals↗

Alcohol, ALDH2, and esophageal cancer: a meta-analysis which illustrates the potentials and limitations of a Mendelian randomization approach.

Mendelian randomization, the use of common polymorphisms as surrogates for measuring exposure levels in epidemiologic studies, provides one method of assessing the causal nature of some environmental exposures. This can be illustrated by looking at the association between the ALDH2 polymorphism and esophageal cancer. Alcohol drinking is considered a risk factor for esophageal cancer, and exposure to high levels of acetaldehyde, the principal metabolite of alcohol, may be responsible for the increased cancer risk. The ability to metabolize acetaldehyde is encoded by the ALDH2 gene, which is polymorphic in some populations. The ALDH2*2 allele produces an inactive protein subunit, which is unable to metabolize acetaldehyde. An individual's genotype at this locus may influence their esophageal cancer risk through two mechanisms, first through influencing alcohol intake and second through influencing acetaldehyde levels. We have carried out a meta-analysis of studies looking at the ALDH2 genotype and esophageal cancer and found that risk was reduced among *2*2 homozygotes [odds ratio (OR), 0.36; 95% confidence interval (95% CI), 0.16-0.80] and increased among heterozygotes (OR, 3.19; 95% CI, 1.86-5.47) relative to *1*1 homozygotes. This provides strong evidence that alcohol intake increases the risk of esophageal cancer and individuals whose genotype results in markedly lower intake, because they have an adverse reaction to alcohol are thus protected. This meta-analysis also provides evidence that acetaldehyde plays a carcinogenic role in esophageal cancer. The two different processes operating as a result of the ALDH2 genotype have implications for the interpretation of studies using the Mendelian randomization paradigm.

Acetaldehyde↗

Causal relationship between white matter structural connectivity and epilepsy.

White matter structural connectivity has recently been linked to epilepsy pathogenesis, yet its causal role remains unclear. This study used Mendelian randomization (MR) to investigate the causal relationship between white matter structural connectivity and epilepsy. GWAS summary statistics for white matter structural connectivity were sourced from the UK Biobank, while epilepsy data were obtained from FinnGen R10 and the International League Against Epilepsy (ILAE). Our MR analysis revealed significant causal links between white matter structural connectivity and epilepsy risk. Increased connectivity between the right hemisphere visual and salience/ventral attention networks (RH Vis to RH Sal/VentAttn WMSC) was associated with higher epilepsy risk in FinnGen_R10_FE_STRICT (OR&#xa0;=&#xa0;2.25, 95&#xa0;% CI&#xa0;=&#xa0;1.43-3.56, p&#xa0;<&#xa0;0.01, FDR P&#xa0;=&#xa0;0.019). Conversely, increased connectivity between left and right hemisphere salience/ventral attention networks (LH Sal/VentAttn to RH Sal/VentAttn WMSC) was linked to reduced epilepsy risk in FinnGen_R10_GE_STRICT (OR&#xa0;=&#xa0;0.17, 95&#xa0;% CI&#xa0;=&#xa0;0.07-0.46, p&#xa0;<&#xa0;0.01, FDR P&#xa0;=&#xa0;0.033). A total of 15 nominally significant associations were identified across datasets. These findings suggest a causal relationship between white matter structural connectivity and epilepsy, offering insights into disease mechanisms and potential therapeutic targets.

Humans↗

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&#x2009;=&#x2009;1.90, 95% CI 1.25-2.90, P&#x2009;=&#x2009;2.64&#x2009;&#xd7;&#x2009;10&#x207b;&#xb3;), 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↗

Perirenal Adipose Tissue and Hypertension: Observational and Genetic Analyses.

BACKGROUND: Perirenal adipose tissue (PRAT) consists of white and brown adipocytes with good vascularization and dense innervation, which could influence the blood pressure. We aim to investigate the association of PRAT thickness with risks of overall and specific forms of hypertension. METHODS: We measured PRAT thickness in the UK Biobank and CONPASS (Chongqing Primary Aldosteronism Study). We prospectively examined the correlation between PRAT thickness and incident hypertension in the UK Biobank. We cross-sectionally explored associations between PRAT thickness and common forms of hypertension in CONPASS. Integrating data from GWAS (Genome-Wide Association Study), we investigated the potential causal relationship between PRAT and hypertension forms by 2-sample Mendelian randomization analyses. RESULTS: In the prospective analysis of the UK Biobank, participants whose PRAT thickness was &#x2265;46.1 mm showed a higher risk of developing hypertension than participants whose PRAT thickness was <16.4 mm (hazard ratio, 2.91 [95% CI, 1.97-4.32]). In the cross-sectional analysis of CONPASS, a 1 SD increment in PRAT thickness was associated with a 2.77-fold higher adjusted odds of low-renin essential hypertension and a 3.89-fold higher adjusted odds of idiopathic hyperaldosteronism. PRAT thickness was not significantly associated with other forms of hypertension, such as aldosterone-producing adenoma and obstructive sleep apnea. In 2-sample Mendelian randomization analyses, PRAT thickness was only significantly associated with a higher risk of idiopathic hyperaldosteronism (inverse variance weighted odds ratio, 1.33 [95% CI, 1.09-1.62]), with no evidence of significant heterogeneity or substantial directional pleiotropy. CONCLUSIONS: PRAT is causally associated with idiopathic hyperaldosteronism rather than essential hypertension and other forms of secondary hypertension.

Humans↗

Limits to causal inference based on Mendelian randomization: a comparison with randomized controlled trials.

"Mendelian randomization" refers to the random assortment of genes transferred from parent to offspring at the time of gamete formation. This process has been compared to a randomized controlled trial of genetic variants. This could greatly aid observational epidemiology by potentially allowing an unbiased estimate of the effects of gene products on disease outcomes. However, studies utilizing Mendelian randomization to estimate effects of gene products on outcomes should be interpreted with caution. In this paper, the authors discuss some of the challenges facing epidemiologists in the analysis and interpretation of Mendelian randomization studies, particularly those that become apparent when the analogy with randomized controlled trials is closely examined. The authors conclude that Mendelian randomization is a powerful addition to etiologic research tools. However, care must be taken, because drawing valid causal inferences from its application depends upon more extensive assumptions than are required in randomized controlled trials.

Causality↗

The causal effect of juvenile idiopathic arthritis on IgA nephropathy: A Mendelian randomization study.

IgA nephropathy (IgAN) has been documented in patients with various comorbidities. Previous observational studies showed an association between juvenile idiopathic arthritis (JIA) and IgAN. The aim of this study was to determine whether there is a causal effect of JIA on the risk of IgAN using a 2-sample Mendelian randomization (MR) approach. A 2-sample MR analysis was conducted to elucidate the potential causal relationship between JIA and IgAN. Summary-level data from genome-wide association studies in the European population were utilized, including IgAN (5556 cases and 21,178 controls) and JIA (3305 cases and 9196 controls). The inverse variance weighted method showed significant evidence of a positive causal relationship between genetically predicted JIA and IgAN. For each standard deviation increase in genetically predicted JIA, the risk of IgAN was found to be increased by 22% (odds ratio [OR]&#x2005;=&#x2005;1.22, 95% CI: 1.10-1.29, P&#x2005;=&#x2005;3.03&#x2005;&#xd7;&#x2005;10-4). Similar associations were observed with the weighted median (OR: 1.16, 95% CI: 1.05-1.29) and weighted mode methods (OR: 1.16 95% CI: 1.02-1.33), but not with the simple median (OR: 1.22, 95% CI: 0.99-1.50) and MR Egger method (OR: 1.21, 95% CI: 0.93-1.57). Reverse MR analysis found no inverse causal relationship between these 2 diseases. This study provides genetic evidence supporting a causal link between JIA and an increased risk of IgAN. In JIA patients, periodic evaluation of kidney function and proteinuria is warranted.

Humans↗

Investigating the causal role of smoking in gout: A triangulation approach combining NHANES data, genetic correlation, and Mendelian randomization.

The relationship between smoking and the development of gout is not well understood. To address this, we adopted a triangulation framework that integrates observational analysis, genetic correlation estimation, and two-sample Mendelian randomization (MR) to examine whether smoking confers a causal risk for gout. We first performed a cross-sectional analysis using information for 13,626 participants from the National Health and Nutrition Examination Survey between 2013 and 2018. The association of smoking with gout was subsequently assessed through logistic regression models. We next investigated the extent of shared genetic factors between smoking phenotypes and gout. We were able to demonstrate this using the linkage disequilibrium score regression applied to genome-wide association study data of European ancestry. Finally, to verify the causality of our relationship, we carried out a two-sample MR analysis. We selected the inverse-variance weighted (IVW) method and confirmed the consistency of using the IVW method with other statistical methods, including weighted median, weighted mode, and simple mode, as well as MR-Egger regression. We performed sensitivity analyses to investigate the heterogeneity of the hypothesis and stability of the data. Our findings based on National Health and Nutrition Examination Survey data reveal that there is a strong positive association between smoking and the risk of gout (odds ratio [OR]&#x2005;=&#x2005;1.94, 95% confidence interval [CI]&#x2005;=&#x2005;1.48-2.55, P&#x2005;<&#x2005;.001). This association persisted after confounding adjustments (OR&#x2005;=&#x2005;1.41, 95% CI&#x2005;=&#x2005;1.04-1.91, P&#x2005;=&#x2005;.027). In the subgroup analyses, former smokers and current smokers of 10 to 20 cigarettes per day had a substantially increased risk. Post-linkage disequilibrium score regression analysis revealed that the significantly positive genetic correlations of smoking initiation and lifetime smoking index with gout risk were both significantly positive. Additional evidence for causality is presented by MR. Genetic prediction of smoking initiation statistically increases gout risk (IVW OR&#x2005;=&#x2005;1.55, 95% CI&#x2005;=&#x2005;1.26-1.90, P&#x2005;=&#x2005;3.17&#x2005;&#xd7;&#x2005;10-5). A much stronger association is evident for lifetime smoking index (IVW OR&#x2005;=&#x2005;1.99, 95% CI&#x2005;=&#x2005;1.44-2.76, P&#x2005;=&#x2005;3.24&#x2005;&#xd7;&#x2005;10-5). These findings are the same with or without heterogeneity by sensitivity analysis. In light of our integrated analysis, smoking is a causative factor for gout. This suggests that public health interventions like anti-smoking campaigns might reduce gout incidence.

Humans↗

Integrative omics of the genetic basis for wheat WUE and drought resilience reveal the function of TaMYB7-A1.

Improving wheat&#xa0;drought resilience and water use efficiency (WUE) is critical for sustaining productivity under increasing water scarcity. Here, we integrate genome-wide association&#xa0;study (GWAS), expression quantitative trait locus (eQTL) mapping, population-transcriptome analysis, and summary-data-based mendelian randomization (SMR), followed by functional validation using indexed EMS mutants and transgenic lines, to systematically identify key WUE regulators. GWAS across water conditions in 228 accessions identifies 73 quantitative trait loci (QTLs) for WUE-traits. Transcriptome profiling of 110 diverse accessions reveals 28 drought-responsive modules. eQTL mapping uncovers 146,966 regulatory variants, including condition-specific hotspots associated with key drought-related pathways. Integrative analysis underscores 85 high-confidence candidate genes, notably TaMYB7-A1. Overexpression of TaMYB7-A1 enhances photosynthesis, WUE, root development, and grain yield under drought condition by activating TaPIP2;2-B1 (water transport), TaRD20-D1 (stomatal regulation), and TaABCB4-B1 (root growth), reflecting reduced water loss and improved physiological resilience. Our study presents a comprehensive regulatory map and robust targets for wheat drought adaptation and resilient cultivar breeding.

Triticum↗

Leisure television watching exerts a causal effect on gastroesophageal reflux disease: evidence from a two-step mendelian randomization study.

BACKGROUND: Previous studies have shown that physical activity (PA) and leisure sedentary behaviors (LSB, including leisure television watching) are linked to gastroesophageal reflux disease (GERD). However, the associations between PA/LSB and GERD remain controversial. In this study, we aimed to reveal whether these associations reflect causal relationships and reveal the potential mechanisms of these relationships using bidirectional and two-step Mendelian randomization (MR) analyses. METHODS: We obtained genome-wide association study (GWAS) summary statistics for PA/LSB, four common risk factors (including cigarettes smoked per day, alcoholic drinks per week, triglycerides, total cholesterol) and GERD from published GWASs. A bidirectional MR analysis was performed to identify causal relationships between PA/LSB and GERD. Then, a series of sensitivity analyses were performed to verify the robustness of the results. Finally, a mediation analysis via two-step MR was conducted to investigate any effects explained by common risk factors in these relationships. RESULTS: Genetically predicted per 1-SD increase in leisure time television watching significantly increased the risk of GERD in the bidirectional MR analysis (OR&#x2009;=&#x2009;1.33; 95% CI: 1.14-1.56; P&#x2009;=&#x2009;2.71&#x2009;&#xd7;&#x2009;10-&#x2009;4). Sensitivity analyses successfully verified the robustness of the causal relationship. Further mediation analysis showed that this effect was partly mediated by increasing cigarettes smoked per day, with mediated proportions of 18.37% (95% CI: 11.94-39.79%). CONCLUSION: Our findings revealed a causal relationship between leisure television watching and an increased risk of GERD, notably, the causal effect was partially mediated by cigarettes smoked per day. These findings may inform prevention and management strategies directed toward GERD.

Humans↗

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 &#xd7; 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↗

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

BACKGROUND: Sarcopenia severely affects the physical health of the elderly. Currently, there is no specific drug available for sarcopenia. This study aims to identify pathogenic proteins and druggable targets for sarcopenia through Mendelian randomization (MR)-based analytical framework. METHODS: A sequential stepwise screening method that includes two-sample MR, Steiger filtering test and colocalization (MRSC) was applied to identify causal proteins associated with sarcopenia-related traits. In the MR analyses, 4372 circulating proteins with valid instrumental variables (IVs) from eight proteomic genome-wide association studies were utilized as exposures, and nine sarcopenia-related traits were utilized as outcomes. IVs were classified into cis-protein quantitative trait loci (pQTLs) and trans-pQTLs based on their positions. We conducted cis-only MRSC analyses and cis&#x2009;+&#x2009;trans MRSC analyses using cis-pQTLs and cis&#x2009;+&#x2009;trans pQTLs as IVs, respectively. Post-MRSC analyses were conducted on the prioritized findings of MRSC, including annotation of protein-altering variants (PAVs), assessment of overlap between pQTLs and expression quantitative trait loci (eQTLs), protein-protein interaction (PPI) analysis, pathway enrichment analysis and annotation of drug targets. Utilizing data from the UK Biobank, we performed an observational study to explore the associations between baseline circulating protein levels and the longitudinal changes in nine sarcopenia-related traits. RESULTS: A total of 181 causal associations for 65 proteins were prioritized by the cis-only MRSC analyses and 227 associations for 91 proteins were prioritized by the cis&#x2009;+&#x2009;trans MRSC analyses. Among the prioritized proteins, the majority of them employed non-PAVs as IVs and most of their cis-pQTLs overlapped with corresponding eQTLs and exhibited consistent directionality, with only one trans-pQTL overlapping with an eQTL. The PPI network of cis-only MRSC-prioritized proteins (p&#x2009;=&#x2009;4.04&#x2009;&#xd7;&#x2009;10-4) and cis&#x2009;+&#x2009;trans MRSC-prioritized proteins (p&#x2009;=&#x2009;8.76&#x2009;&#xd7;&#x2009;10-5) showed significantly more interactions than expected. Reactome, KEGG and GO pathway enrichment analyses for cis-only MRSC-prioritized proteins identified 52, 12 and 79 enriched pathways, respectively (adjusted p&#x2009;<&#x2009;0.05). For proteins identified by cis&#x2009;+&#x2009;trans MRSC analyses, only 15 pathways were enriched through the GO pathway enrichment analyses. In the observational study, 197 circulating proteins were identified to be associated with one or more sarcopenia-related traits (p&#x2009;<&#x2009;0.05/2923). Among them, the significant associations of CTSB (negative association) and ASGR1 (positive association) with sarcopenia-related traits were observed to have consistent directional associations in both MR-based studies and observational studies. Drug target annotations suggested that 52 MRSC-prioritized proteins and 145 biomarkers are drug targets or druggable. CONCLUSIONS: This study identified 89 potential pathogenic proteins and 197 candidate biomarkers for sarcopenia, providing valuable clues for the development of therapeutic drugs for sarcopenia.

Humans↗

Mapping the Immune cell-specific gene regulatory network in bipolar disorder: A framework from scTWMR to exploratory drug-target annotation.

BACKGROUND: Although the involvement of the immune system in the genetic susceptibility of bipolar disorder (BD) is widely acknowledged, the causal relationship between gene expression in specific immune cell subtypes and BD requires systematic elucidation. METHODS: We implemented an analytical framework integrating single-cell transcriptome-wide Mendelian randomization (scTWMR) with colocalization analysis. This approach utilized cis-expression quantitative trait loci (cis-eQTLs) derived from 14 distinct immune cell types as instrumental variables to interrogate BD genome-wide association study (GWAS) summary statistics (comprising 41,917 cases and 371,549 controls). Subsequent investigations encompassed functional enrichment analysis, protein-protein interaction (PPI) network construction, phenome-wide association study (PheWAS), and performed an exploratory drug-target annotation. RESULTS: Our analysis identified 33 gene-immune cell associations. Colocalization analysis provided robust evidence (PPH4 > 90%) for shared causal variants implicating the MAD1L1, APOM, and NFKBIL1 loci. Significantly enriched biological pathways included cell cycle regulation, circadian rhythm entrainment, and neuroinflammation. The PPI network revealed a core regulatory module centered on histone-encoding and immune-related genes. Exploratory drug-target annotation nominated compounds for further investigation for compounds targeting APOM, TMEM258, and NFKBIL1. CONCLUSION: This study systematically delineates a genetically supported regulatory network of immune cell-specific gene expression in BD, predominantly implicating CD8&#x207a; effector T cells, plasma cells, and B cells. The findings corroborate established pathological pathways while uncovering novel cell type-specific therapeutic targets, thereby providing a genetic framework for prioritizing candidate targets for future investigation.

Bipolar disorder↗

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

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

Female↗

Endocrine-disrupting chemical-induced gene networks confer coronary heart disease risk revealed by causal inference and single-cell analyses.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are linked to coronary heart disease (CHD), but underlying mechanisms remain unclear. We aimed to identify EDC-related genes and evaluate their causal roles in CHD. METHODS: We curated EDC-related genes from a compound-gene interaction database and integrated them with CHD genome-wide association study (GWAS) summary statistics and tissue-specific expression quantitative trait loci (eQTL) data. Two-sample Mendelian randomization (MR) and Bayesian colocalization were applied to infer causality. Functional enrichment, single-cell RNA sequencing of human coronary arteries, and EDC-gene networks were further analyzed. RESULTS: After FDR correction, 39 genes were significantly associated with CHD risk via MR. Four genes-ZNF827, FCHO1, IPO9 (protective), and RPL13 (risk-increasing)-showed strong colocalization (PPH4&#x202f;>&#x202f;0.9). Pathway and single-cell analyses of coronary artery tissue indicated that vascular and immune pathways mediate these effects. An interaction network highlighted associations between specific EDCs and candidate genes implicated in CHD susceptibility. CONCLUSION: This integrative genomic study provides evidence that EDCs influence CHD susceptibility through distinct gene networks, revealing potential mechanisms and molecular targets for prevention and therapy.

Humans↗

Genetic association between epilepsy and gliomas: Insights from Mendelian randomization and single-cell transcriptomic analyses.

BACKGROUND: Seizures are prevalent in glioma patients, especially in those with low-grade gliomas. The interaction between gliomas and epilepsy involves complex biological mechanisms that are not fully understood. METHODS: We collected Genome-Wide Association Study data for epilepsy and gliomas, performed differential expression analysis, and conducted Gene Ontology (GO) enrichment analysis on the identified genes. Single-cell RNA sequencing data (scRNA-seq) from GSE221534 dataset in Gene Expression Omnibus (GEO) were used to analyze cell-cell interactions within glioma samples from patients with and without epilepsy. RESULTS: Mendelian Randomization (MR) analysis revealed significant associations between genetic variants related to epilepsy and glioma risk, suggesting a potential causal relationship, especially in astrocytomas. Differential expression analysis identified epilepsy-related genes that were significantly upregulated in astrocytoma tissues compared to normal brain tissues. GO enrichment analysis indicated that these genes are involved in critical biological processes such as neurogenesis and cellular signaling. The scRNA-seq analysis showed, compared to non-epileptic samples, glioma stem cells, microglia, and NK cells are increased in the core regions of astrocytomas in epileptic patients. Additionally, intercellular communication between tumor cells and other non-tumor cells is markedly enhanced in astrocytoma samples from epileptic patients. CONCLUSION: This study provides evidence of a genetic association between epilepsy and gliomas and elucidates the biological mechanisms through which epilepsy may influence glioma progression.

Humans↗

Mendel randomization confirmed gastroesophageal reflux disease may increase the risk of mental disorders.

BACKGROUND: The potential causal relationship between gastroesophageal reflux disease (GERD) and mental disorder was analyzed using the mendelian randomization (MR) method. METHODS: Data are derived from genome-wide association study (GWAS) summary data, using gastroesophageal reflux disease (GERD) as the exposure factor. Single nucleotide polymorphisms (SNPs) significantly associated with GERD were selected as instrumental variables (IVs), and mental disorders (bipolar disorder, major depression, Alzheimer's disease, anorexia nervosa, anxiety, and obsessive-compulsive disorder) were used as outcome variables. The inverse variance weighted (IVW) method is used as the main analysis method, and MR-Egger regression, weighted median (WM) method, simple mode and weighted mode are used as supplementary methods for Mendelian randomization (MR) analysis. Cochran's Q&#xa0;test and P&#xa0;value are used to quantify heterogeneity, MR-Egger regression was used to evaluate the multilevel effect test of SNPs, and leave-one-out method to determine whether there are potential SNPs, and to evaluate the stability of the results. Odds ratio (OR) and 95% confidence interval (CI) were used as effect indicators to evaluate whether there is a&#xa0;causal relationship between GERD and mental disorders. RESULTS: IVW demonstrated a&#xa0;causal relationship between GERD and bipolar disorder (OR&#x202f;=&#x2009;1.70, 95%CI&#x202f;=&#x2009;1.39-2.09, P&#x202f;<&#x2009;0.05) and anorexia nervosa (OR&#x202f;=&#x2009;0.71, 95%CI&#x202f;=&#x2009;0.52-0.99, P&#x202f;<&#x2009;0.05). Furthermore, there is a&#xa0;weak causal relationship between GERD and major depression (OR&#x202f;=&#x2009;1.01, 95%CI&#x202f;=&#x2009;1.01-1.02, P&#x202f;<&#x2009;0.05) and anxiety (OR&#x202f;=&#x2009;1.01, 95%CI&#x202f;=&#x2009;1.01-1.01, P&#x202f;<&#x2009;0.05). Similarly, there is no evidence of a&#xa0;causal relationship between GERD and Alzheimer's disease (OR&#x202f;=&#x2009;0.95, 95%CI&#x202f;=&#x2009;0.87-1.03, P&#x202f;>&#x2009;0.05) or obsessive-compulsive disorder (OR&#x202f;=&#x2009;0.95, 95%CI&#x202f;=&#x2009;0.67-1.36, P&#x202f;>&#x2009;0.05). Cochran's Q&#xa0;test for heterogeneity shows that there is no significant heterogeneity (P&#x202f;>&#x2009;0.05) for bipolar disorder, anxiety, and obsessive-compulsive disorder. However, major depression, Alzheimer's disease, and anorexia nervosa have some degree of heterogeneity (P&#x202f;<&#x2009;0.05). Horizontal pleiotropic analysis showed that the P&#xa0;values for six mental disorders (0.750, 0.296, 0.154, 0.798, 0.893, 0.451) were all greater than 0.05. Leave-one-out analysis and funnel plot showed that MR analysis results can be considered relatively stable. All F are >&#x2009;10, indicating no weak IVs bias. CONCLUSION: GERD can obviously increase the risk of bipolar disorder; the increased risk of anxiety disorder is very slight. There is no clear evidence to support the causal relationship between GERD and four other mental disorders, including major depression, Alzheimer's disease, anorexia nervosa, and obsessive-compulsive disorder.

Humans↗