Cited by 0Genetic Associations and EpidemiologyCardiovascular Disease and AdiposityAdipokines, Inflammation, and Metabolic Diseases

Regional Adipose Distribution Reveals Differential Genetic Risk Patterns for Cardiometabolic Diseases

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Wu, Qian, Yang, Fan, An, Qi, Liu, Ying, Tian, Hexian, Du, Yamin, Cai, Wenjie, Lei, Minghuan +9 more·2026·Journal of the American Heart Association

Abstract

Background: Cardiometabolic risk associated with obesity is increasingly recognized to be strongly influenced by the anatomical distribution and ectopic deposition of adipose tissue, yet the genetic mechanisms linking adipose depots to cardiometabolic diseases remain incompletely understood. Methods: Using large‐scale genome‐wide association summary statistics, we systematically characterized shared genetic architecture between 7 magnetic resonance imaging‐derived regional and ectopic adipose traits and 20 cardiometabolic diseases, including major cardiovascular outcomes and type 2 diabetes. Genetic overlap was assessed at genome‐wide, regional, and variant levels, followed by functional annotation, cell‐type enrichment, and phenotype enrichment analyses. Protein–protein interaction networks and molecular docking analyses were further applied to prioritize disease‐relevant genes and potential therapeutic compounds. Results: We identified widespread yet heterogeneous genetic overlap, including 109 adipose‐cardiometabolic diseases pairs with genome‐wide overlap, 92 pairs showing regional concordance across 423 genomic regions, and 146 pleiotropic loci supported by colocalization. Shared variants were enriched in regulatory elements and connected to pleiotropic genes involved in metabolic and inflammatory pathways, including insulin signaling, ion homeostasis, and cellular stress responses. Cell type enrichment analyses highlighted immune, endothelial, and metabolically active parenchymal cells as key contributing cell types. Network and docking analyses further prioritized cardiometabolic disease‐related genes such as MMP9 , PPARG , and TM6SF2 , along with candidate compounds exhibiting favorable binding properties. Conclusions: This study delineates differential genetic risk patterns linking adipose distribution to multiple cardiometabolic diseases and reveals interconnected metabolic, immune, and vascular mechanisms, providing a genetic framework for cardiometabolic and cardiovascular risk assessment and the prioritization of potential therapeutic targets.

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Crossref · 10.1161/jaha.126.049987

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Authors
Wu, Q., Yang, F., An, Q., Liu, Y., Tian, H., Du, Y., Cai, W., Lei, M., Xu, J., Deng, L., Zhai, Y., Zhang, Z., Wu, Y., Wang, H., Cheng, Y., Liu, F., & Li, D.
Affiliations
  • Tianjin Medical University General Hospital (CN)
  • Tianjin First Center Hospital (CN)
Corresponding author
  • Cheng, Yue
  • Liu, Feng
  • Li, Dong
Venue
Journal of the American Heart Association
Published
2026-10-20
Volume
15
Issue
20
Pages
e049987-e049987
ISSN
2047-9980 (ISSN-L)
OpenAlex
W7221322297
Cited by
0
References
102
FWCI
0.00
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • Journal of the American Heart Association (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Disease and Adiposity
  • Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
Keywords
ectopic adipose tissue, cardiometabolic disease, genetic overlap, pleiotropy, type 2 diabetes, cardiovascular disease, obesity, colocalization, cell type enrichment, MMP-9, PPARγ, TM6SF2, drug target prioritization, protein-protein interaction network, molecular docking
MeSH terms
Cardiometabolic Risk Factors, Adipose Tissue, Cardiovascular Diseases, Humans, Magnetic Resonance Imaging, Obesity, Phenotype, Risk Factors, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Adiposity, Body Fat Distribution, Genome-Wide Association Study, Genetic Pleiotropy

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