Skip to content
Open access

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

Aug 2026 · Frontiers in Nutrition · Vol 13 · 0 citations · 47 references
Medicine

TL;DR

An integrated cross-omics analysis identifies novel genetic loci and, crucially, uncovers specific nutrient-related metabolic pathways that mediate genetic risk in Aortic aneurysm and its subtypes.

Abstract

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.

Read PDF

Similar papers

Open access Aug 2026

Ancestry-specific TWAS refines type 2 diabetes GWAS loci in disease-relevant tissues

The findings demonstrate that integrating tissue-specific and ancestry-aware TWAS refines the identification of causal genes for T2D, with cross-ancestry replication supporting the robustness of these signals and cross-tissue analyses revealing context-specific effects.

I. Pagnuco, S. Eyre, M. Rattray et al. · 0 citations
Open access Jan 2026

From Germline Variants to Tumor Outcome: GWAS‐Based Functional Genomics Prioritizes Colorectal Cancer Susceptibility Genes and Links SMAD9 to Prognosis

Integrating statistical genetics, regulatory prediction, and locus‐directed experiments prioritized SMAD9, MAP3K2, FADS1, and ACTR1B as CRC susceptibility genes, and placed experimental bounds on the proposed MAP3K2 and ACTR1B mechanisms.

Chengguang Hu, Guang Yang, Han Xiong et al. · 0 citations
Open access Jul 2026

Genetic architecture shared between body shape phenotypes and preeclampsia-related diseases: a genome-wide cross-trait analysis.

This study indicates a genetic correlation and common risk genes, linking adiposity-related traits to PE-related diseases, and offers novel insights into the biological mechanisms underlying this comorbidity.

Yuping Shan, Hong Hu, Chong Liu et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.