Genetic link between metabolic syndrome and coronary artery disease: Insights from genome-wide cross-trait analysis

Abstract

Metabolic syndromes (MeS), marked by central obesity, high blood pressure, abnormal cholesterol and blood sugar, are key cardiovascular disease (especially coronary artery disease, CAD) risk factors. Genetic studies show MeS-CAD genetic overlap, indicating shared biological pathways. We used Summary-data-based Mendelian Randomization (SMR), Bayesian colocalization (with large GWAS summary stats for MeS/CAD and cis-eQTL data from 3 tissues) and Transcriptome-Wide Association Study (TWAS). We also investigated the effects of gene knockout on mouse phenotypes. SMR found 886/737/192 shared genes in blood/brain cortex/liver; colocalization identified 11/13/5 shared causal genes in these tissues and 46 shared loci (e.g., CAMK1D, OR=1.11; AGPAT1, OR=1.13; FDR<0.05). Moreover, knocking out these genes in mice affected metabolism, adipose tissue, cardiovascular function, glucose homeostasis, and the fat/muscle balance. This study identified common regulatory genes between MeS and CAD, suggesting that targeted therapies or interventions could potentially address both conditions simultaneously, offering prospects for more integrated treatment strategies.

Keywords

Coronary artery disease / Diabetes / Obesity / Expression quantitative loci / Genetic correlation / Mendelian randomization / Co-localization

Author contributions

FX and JM conceived the study. PY conducted and performed data analysis. PY wrote the manuscript. QY and HZ prepared the figures. YZ, ZX, CY, FX, and JM reviewed the manuscript. All authors read and approved the final version of the manuscript for publication.

Ethics approval and consent to participate

All data used in this study were obtained from public databases and do not involve any ethical concerns. Clinical trial number: not applicable.

Consent for publication

All authors have agreed to publish.

Funding

This research was funded by Taishan Scholars Construction Engineering, National Natural Science Foundation of China (32170989), Major Basic Research Project of Shandong Provincial Natural Science Foundation (ZR2019ZD27), Key Research and Development Program of Shandong Province (2023CXPTO12), Natural Science Foundation of Shandong Province (ZR2021MH141, ZR2023MH373), Binzhou Medical University Research Start-up (50012305190).

Data availability

All the data involved in this study were obtained from public databases. This study code is available on GitHub (https://github.com/yi9099/genetic-link), and is free for academic and research purposes.

Declaration of Competing Interest

The authors declare no competing interests.

Appendix A. Supplementary material

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.gmg.2025.100092.

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