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Results for “summary-based Mendelian randomization”

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Shared genetic architecture of obesity and gastroesophageal reflux disease.

Obesity is identified as a risk factor of gastroesophageal reflux disease (GERD). This study aims to elucidate the shared genetic architecture of obesity-related phenotypes and GERD. Based on the publicly available genome-wide association studies' datasets, this genome-wide pleiotropic association study was conducted with various genetic approaches (including linkage disequilibrium score regression, high-definition likelihood inference for genetic correlations, pleiotropic analysis under composite null hypothesis, Functional Mapping and Annotation, Bayesian colocalization, summary-based Mendelian randomization, and multi-marker analysis of genomic annotation analysis) sequentially to unravel the genetic associations from single-nucleotide polymorphism to gene levels, and to reveal the underlying shared genetic architecture between obesity-related phenotypes and GERD. This study discovered shared genetic mechanisms between GERD and several obesity-related phenotypes, including arm fat percentage (left), arm fat percentage (right), leg fat percentage (left), leg fat percentage (right), trunk fat percentage, waist-to-hip ratio, and body mass index. Significant genetic correlations were observed by linkage disequilibrium score regression and high-definition likelihood inference for genetic correlations, with multiple associated pleiotropic loci and their mapped genes identified by pleiotropic analysis under composite null hypothesis, Functional Mapping and Annotation, Bayesian colocalization, summary-based Mendelian randomization, and multi-marker analysis of genomic annotation analysis. Additionally, several brain tissues were identified to be linked to both obesity and GERD by multi-marker analysis of genomic annotation. This research provided strong evidence of genetic correlations and brought novel insights into the underlying genetic connections and shared genetic architectures of obesity and GERD.

Humans

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4 = 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4 = 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans

Integrative multi-omics quantitative trait loci prioritize CASP7 as a candidate protective gene for cataract.

Cataracts are the leading cause of vision loss worldwide. Despite surgery being the only effective treatment, its economic burden highlights the necessity of exploring the pathogenesis of cataracts. In this study, we analyzed 4 large-scale GWAS (genome-wide association study) datasets for cataracts and performed SMR analysis along with heterogeneity in dependent instruments (HEIDI) testing to explore the effects of methylation, expression, and protein QTLs on cataracts. We further validated shared genetic variants through COLOC analysis. Additionally, we searched datasets related to cataracts from the Gene Expression Omnibus (GEO) database for differentially expressed genes (DEGs) and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses. By integrating summary-based Mendelian randomization (SMR) results with bioinformatics findings, CASP7 showed a consistent protective-direction association with cataract risk (mQTL: OR [95% CI] = 0.959 [0.941-0.977], FDR-adjusted P = .039; eQTL: OR [95% CI] = 0.897 [0.860-0.937], FDR-adjusted P = .0046; pQTL: OR [95% CI] = 0.597 [0.483-0.738], FDR-adjusted P = .00083). GEO-based analyses provided transcriptomic support for CASP7 involvement in cataract-related lens biology. These findings prioritize CASP7 as a genetically supported candidate protective gene associated with cataract risk. Because this study is based on public summary-level and transcriptomic datasets, the results should be interpreted cautiously and require functional validation in human lens-relevant systems.

Quantitative Trait Loci

Maternal COVID-19 infection associated with offspring neurodevelopmental disorders.

Maternal COVID-19 infection increases the incidence of neurodevelopmental disorders (NDDs) in offspring, although the underlying mechanisms have not been elucidated. This study demonstrated that COVID-19 infection during pregnancy disrupted the balance of maternal and fetal immune environments, driving alterations in astrocytes, endothelial cells, and excitatory neurons. A risk score was established using 47 unique genes in the single-cell transcriptome of gestational mothers. The high risk score in CD4 proliferating T cell level served as an indicator for increased risk of offspring NDDs. Summary-based Mendelian randomization and phenome-wide association study analyses were conducted to identify the causal association of the transcriptional changes with the increased risk of offspring NDDs. Additionally, 10 drugs were identified as potential therapeutic candidates. Our findings support a model where the maternal COVID-19 infection changed the levels of CD4 proliferating T cells, leading to the alterations of astrocytes, endothelial cells, and excitatory neurons in offspring, contributing to the increased risk of NDDs in these individuals.

Humans

Genetic pleiotropy underlying obesity and autoimmune disorders: a large-scale cross-trait gwas analysis in European ancestry populations.

BACKGROUND: Obesity and autoimmune disorders represent a significant comorbidity burden, yet their shared genetic architecture is not fully understood. Elucidating the pleiotropic genetic basis underlying both conditions is crucial for unraveling the mechanisms driving their co-occurrence and advancing therapeutic strategies. METHODS: We conducted a large-scale cross-trait analysis integrating genome-wide association study (GWAS) summary data for obesity and 17 autoimmune diseases. Genetic correlations were assessed using LD score regression and high-definition likelihood. Cross-trait pleiotropic analysis was performed using Stratified Pleiotropic Locus Mapping (PLACO) to identify shared loci, followed by Bayesian colocalization to confirm shared causal variants. Gene-level and tissue-specific heritability analyses were conducted, and drug targets were prioritized via summary-based Mendelian randomization (SMR). Finally, immune co-localization and bidirectional Mendelian randomization were employed to elucidate immunological mechanisms and causal relationships. RESULTS: Our analysis identified eight autoimmune diseases with significant genetic correlations to obesity. We discovered 10,324 pleiotropic SNPs, which mapped to 52 independent risk loci, with nine loci confirmed as shared causal variants by colocalization. Gene-level analysis revealed 133 unique pleiotropic genes, including CLN3, SH2B1, and MMEL1, enriched in pathways of hematopoietic cell differentiation and immune homeostasis. Tissue-specific heritability was most prominent in the spleen, whole blood, and EBV-transformed lymphocytes. Immuno-co-localization implicated six IgD+ CD38- %B cell-related traits as key pathological conduits. Bidirectional Mendelian randomization established a causal role of obesity in hypothyroidism, psoriasis, and multiple sclerosis, while revealing an inverse causal association of type 1 diabetes with obesity risk. CONCLUSIONS: This study demonstrates a robust shared genetic foundation between obesity and multiple autoimmune diseases, pinpointing specific pleiotropic loci, genes, and immune cell subsets. Our findings provide a mechanistic framework for their comorbidity and highlight potential targets for therapeutic intervention.

Humans

Integrative cross-tissue transcriptome-wide association and metabolomic analysis reveals novel genetic risk loci for aortic aneurysm.

BACKGROUND: Aortic aneurysm (AA) is a life-threatening cardiovascular condition with a strong genetic component, however, its molecular mechanisms remain poorly understood. Although genome-wide association studies (GWAS) have identified numerous risk loci, most prior studies have investigated genetic and metabolic factors separately, leaving the causal pathways from genetic variants to disease largely unexplored. METHODS: We established an integrative framework combining cross-tissue transcriptome-wide association studies (TWAS) with metabolomic mediation analysis. First, we integrated GWAS data from FinnGen R12 with multi-tissue expression quantitative trait loci (eQTL) data from Genotype-Tissue Expression Project (GTEx) V8, then performed cross-tissue TWAS using the Unified Test for MOlecular SignaTures (UTMOST) and single-tissue validation with the Functional Summary-based Imputation (FUSION) to prioritize susceptibility genes. Second, we applied Mendelian randomization (MR), colocalization, and Fine-mapping Of CaUsal gene Sets (FOCUS) to assess causality and identify high-confidence genes. Third, we performed metabolite mediation analysis to uncover metabolic pathways linking genetic variants to disease risk. Finally, we validated key findings in mouse models of thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA) using Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction (RT-qPCR) and Western blotting. RESULTS: We identified multiple novel susceptibility genes for AA and its subtypes. Key genes included ADH family members (ADH1A, ADH1B, ADH4, ADH6) and ZNF827, which showed cross-subtype associations with strong colocalization evidence in vascular tissues. Metabolite mediation analysis revealed significant pathways involving N-acetylphenylalanine and methionine sulfoxide. Functional enrichment revealed distinct biological mechanisms: AA and AAA were primarily associated with metabolic pathways, whereas TAA-related genes were enriched in developmental and contractile processes. PheWAS indicated no significant off-target associations. Critically, experimental validation in mouse models confirmed significant upregulation of ZNF827 in TAA and ADH6 in AAA at both mRNA and protein levels, corroborating the genetic predictions. CONCLUSION: This integrated cross-omics analysis identifies novel genetic loci and, crucially, uncovers specific nutrient-related metabolic pathways that mediate genetic risk. These findings provide a mechanistic basis for future nutritional and metabolic intervention studies in AA and its subtypes.

MAGMA

Genetic and epigenetic underpinnings of biological aging: a multi-omics study integrating Mendelian randomization, spatial transcriptomics, and drug target discovery.

Inflammaging represents a hallmark of biological aging, yet the causal inflammatory mediators driving multi-dimensional epigenetic aging and their effector genes remain poorly characterized at the genetic level. We developed a four-tier analytical framework integrating causal screening, multi-omics effector gene mapping, spatial transcriptomics, and drug target evaluation. Two-sample Mendelian randomization (MR) of 91 circulating inflammatory proteins against six aging phenotypes identified IL-12B, IFNG, and IL-2 as the most robust pro-aging mediators with consistent effects across independent outcomes. Using multi-omics summary-based MR (SMR) as the core analytical engine, we integrated four-layer whole-blood molecular QTL resources eQTL (eQTLGen, n = 31,684), sQTL (GTEx, n = 755), pQTL (INTERVAL + SCALLOP, n = 34,232), and mQTL (McRae et al., n = 1,980) - with GWAS summary statistics for four epigenetic age acceleration measures. At a stringent threshold (P_SMR < 1&#xd7;10&#x207b;&#xb9;&#xb2;), seven high-confidence effector genes were identified: NHLRC1, TPMT, SELP, and RIPPLY3 for IEAA; ZNF373A and PLDN for HannumAA; and EDARADD for PhenoAA. The chromosome 6p21 NHLRC1-TPMT locus, overwhelmingly driven by methylation QTL signals (-log&#x2081;&#x2080;P = 26.06), emerged as the dominant genetic node of epigenetic aging. Spatial projection via gsMap onto a mouse E16.5 embryo atlas (121,767 cells) revealed preferential enrichment in smooth muscle and lung, with EDARADD showing marked specificity in mucosal epithelium. Cross-database drug target mining classified TPMT and SELP as repurposable known targets and NHLRC1 as a high-priority novel druggable candidate. This study provides multi-omics convergent causal evidence for inflammation-driven epigenetic aging and delivers genetically anchored targets for precision anti-aging intervention.

Aging

Association among blood pressure, antihypertensive drugs, and amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disease. The impacts of antihypertensive drugs and blood pressure (BP) on ALS are currently debatable. OBJECTIVE: To evaluate the causal relationship involving antihypertensive drugs, BP, and ALS through a Mendelian randomization (MR) analysis. METHODS: The causal relationship between BP and ALS was evaluated by a bidirectional two-sample MR analysis. Then, a sensitivity analysis was performed using a secondary BP genome-wide association study. The drug-target MR was employed to evaluate the impact of antihypertensive drugs on ALS. Furthermore, we used cis-expression quantitative trait loci (cis-eQTLs) data from brain tissue and blood to validate the positive results by a summary-based MR method. RESULTS: We found that an increment in systolic BP (SBP) could elevate the risk of ALS (inverse-variance weighted [IVW] odds ratio [OR]&#x2009;=&#x2009;1.003; 95% confidence interval [95%CI]: 1.001-1.006; per 10-mmHg increment) and ALS might be protected by angiotensin-converting enzyme inhibitors (ACEIs; OR&#x2009;=&#x2009;0.970; 95%CI: 0.956-0.984; p&#x2009;=&#x2009;1.96&#x2009;&#xd7;&#x2009;10-5; per 10-mmHg decrement). A causal relationship was not observed between diastolic BP and other antihypertensive drugs in ALS. CONCLUSION: In the present study, genetic support for elevated SBP serves as a risk factor for ALS. Besides, ACEIs hold promise as a candidate for ALS.

Humans