Genomic structural equation modeling elucidates the shared genetic architecture of vascular ageing
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Updated: Nov 1, 2026

A Phenotyping Regimen for Genetically Modified Mice Used to Study Genes Implicated in Human Diseases of Aging
Published on: July 14, 2016
Yiming Liu1, You Ma2, Yiwei Liu3
1Department of Cardiology, First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Background:
Vascular ageing is a central driver of age-related cardiovascular morbidity and systemic ageing, encompassing arterial stiffening, hemodynamic alterations, subclinical atherosclerosis, and vascular calcification. The shared genetic architecture underlying these multidimensional phenotypes remains incompletely characterized.
Methods:
We applied genomic structural equation modeling (Genomic SEM) to GWAS summary statistics for five vascular-ageing traits in European-ancestry populations-arterial stiffness, pulse pressure, carotid artery thickness, coronary artery calcification, and carotid plaque. A common-factor model defined a latent vascular-ageing phenotype, followed by functional annotation, Bayesian fine-mapping, cross-tissue sCCA-TWAS with colocalization, pathway and cell-type enrichment, partitioned heritability, and polygenic risk score analyses.
Results:
The common-factor model showed good fit (CFI = 0.998; SRMR = 0.047). The resulting multivariate GWAS identified 372 independent lead SNPs across 249 genomic risk loci, including three loci newly implicated in vascular ageing. Bayesian fine-mapping prioritized 49 high-confidence causal SNPs, and transcriptomic prioritization (TWAS-FOCUS-colocalization) yielded 69 putative causal genes. Three-CDH13, FES, and CCN3-converged across MAGMA, fine-mapping, and TWAS evidence, implicating endothelial adhesion, vascular inflammation, and extracellular matrix remodeling. Enrichment analyses highlighted the senescence-associated secretory phenotype, circulatory system processes, and extracellular matrix organization, implicating fibroblast-stromal compartments, smooth muscle cells, endothelial cells, and monocytes/macrophages as candidate cellular substrates.
Conclusion:
This study provides the first multivariate genomic characterization of vascular ageing using Genomic SEM, uncovering loci newly implicated in vascular ageing, convergent putative causal genes, and cellular substrates that link vascular biology to systemic ageing and may inform precision prevention of age-related vascular disorders.
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