Evidence map›Paper›PMID 42449234›Full record

ArticleBMC cardiovascular disorders2026

Decoding the shared genetic architecture of atherosclerotic cardiovascular disease: a genomic structural equation modeling analysis.

Danfeng Zhong, Yaping Ye, Tingting Ye, Shishi Jin

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Article in BMC cardiovascular disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Danfeng ZhongDepartment of Medical Intensive Care Unit, School of Medicine, The First People's Hospital of Wenling (Taizhou University Affiliated Wenling Hospital), Taizhou University, Taizhou, Zhejiang, China.
Yaping YeDepartment of Medical Intensive Care Unit, School of Medicine, The First People's Hospital of Wenling (Taizhou University Affiliated Wenling Hospital), Taizhou University, Taizhou, Zhejiang, China.
Tingting YeDepartment of Cardiovascular Medicine, School of Medicine, The First People's Hospital of Wenling (Taizhou University Affiliated Wenling Hospital), Taizhou University, Taizhou, Zhejiang, China.
Shishi JinDepartment of Medical Intensive Care Unit, School of Medicine, The First People's Hospital of Wenling (Taizhou University Affiliated Wenling Hospital), Taizhou University, Taizhou, Zhejiang, China. sunshine0300@163.com.

Funding

Taizhou Science and Technology Program No.25ywb191The Medical Health Science and Technology Project of Zhejiang Provincial Health Commission 2025HY1489
6 · The paper itself

Abstract

backgroundAtherosclerotic cardiovascular disease (ASCVD) represents a broad spectrum of phenotypes with shared pathology. However, the joint genetic architecture across different vascular beds remains incompletely characterized.

methodsWe applied genomic structural equation modeling (Genomic SEM) to integrate GWAS summary statistics from six ASCVD-related traits: coronary artery disease, myocardial infarction, ischemic stroke, peripheral artery disease, carotid intima-media thickness, and intracranial aneurysm. Downstream analyses included multivariate GWAS, fine-mapping, TWAS with FOCUS, MAGMA, pathway enrichment, cell-type and functional annotation, gsMAP and polygenic risk score.

resultsA single latent common factor model demonstrated an excellent fit to the genetic covariance matrix (CFI = 0.9837, SRMR = 0.1448). The multivariate GWAS identified 839 genome-wide significant SNPs, delineating 85 independent lead loci, of which 67 were novel. Integration of TWAS and FOCUS prioritized 6 high-confidence putative effector genes, including CDKN2B, MIA3, and NBEAL1. Functional enrichment highlighted lipid remodeling and apolipoprotein binding as predominant pathways. Notably, heritability was significantly localized in endothelial cell lineages across multiple tissues. Spatial mapping further identified the lung and kidney as key developmental tissue contexts for ASCVD genetic risk.

conclusionOur study provides a unified genetic framework for ASCVD, demonstrating that its shared liability is anchored in lipid homeostasis and systemic endothelial dysfunction. These findings offer a foundational atlas for early genomic-based risk stratification and therapeutic targeting.

Indexed as

AtherosclerosisGenome-Wide Association StudyPolymorphism, Single NucleotideGenetic Predisposition to DiseaseGenetic Risk ScoreHeredityHumansLatent Class AnalysisMultifactorial InheritancePhenotypeRisk AssessmentRisk FactorsAtherosclerotic cardiovascular diseaseFine-mappingGenetic pleiotropyGenomic structural equation modelingTWAS

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.