GlycA-gene interactions in cardiovascular-kidney-metabolic syndrome: evidence from genetic association.
7 affiliations
- 1Department of Pediatrics, The Third People's Hospital of Chengdu (Affiliated Hospital of Southwest Jiaotong University), College of Medicine, Southwest Jiaotong University, Chengdu, 610031, Sichuan, China.
- 2Department of Clinical Laboratory, The Affiliated Hospital of Southwest Medical University, Luzhou, China, Sichuan, 646099.
- 3Department of Pediatrics, The Third People's Hospital of Chengdu, Chengdu, 610031, Sichuan, China.
- 4School of Clinical Medicine, Southwest Medical University, Luzhou, 646099, Sichuan, China.
- 5Department of General Practice, The Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, 161006, Heilongjiang, China.
- 6Department of Pediatrics, The Third People's Hospital of Chengdu (Affiliated Hospital of Southwest Jiaotong University), College of Medicine, Southwest Jiaotong University, Chengdu, 610031, Sichuan, China. [email protected].
- 7Department of Cardiology, The Third People's Hospital of Chengdu (Affiliated Hospital of Southwest Jiaotong University), College of Medicine, Southwest Jiaotong University, Chengdu, 610031, Sichuan, China. [email protected].
Abstract
Objective
Cardiovascular-Kidney-metabolic (CKM) syndrome is a concept introduced by the American Heart Association, describing systemic diseases resulting from the pathophysiological interaction among obesity, stroke, type 2 diabetes, chronic kidney disease, and cardiovascular disease. Glycoprotein acetyls (GlycA) is a novel biomarker for systemic inflammation and cardiovascular risk. This study aims to uncover the shared genetic architecture between GlycA and CKM, identify common risk loci and key tissues, and clarify the mechanisms linking these conditions.Methods
Using summary data from large-scale GWAS studies, we evaluated both global and local genetic correlations between GlycA and various components of CKM. A cross-trait pleiotropic analysis was conducted to identify shared pleiotropic loci and related genes. FUSION was used to find susceptibility genes linked to GlycA and CKM. A comprehensive set of functional annotations and tissue-specific analyses was performed to uncover potential connections between these traits. Furthermore, a multi-trait colocalization method was utilized to explore the underlying mechanisms of the association between GlycA and CKM.Results
Our study revealed a close genetic correlation between GlycA and CKM. We identified 260 potential SNPs that were corrected using the Bonferroni method, of which 30 passed the colocalization test (PP.H4 > 0.70). Notably, locus 9q34.2 appeared in both GlycA-T2D and GlycA-HF trait pairs. By integrating post-GWAS methods, we identified 53 potentially drug targets (CMIP, DNAJC5G, FCGRT, etc.). FUSION analysis identified 23 shared susceptibility genes for GlycA and CKM (ZPR1, IL6R, PABPC4, etc.). Analysis of tissue enrichment at the SNP level revealed pleiotropic mechanisms associated with whole blood and liver. Gene-level analysis highlighted important roles of metabolic signaling pathways. Furthermore, multi-trait colocalization analysis suggested that rs1260326 and rs2925979 may play significant roles in the mechanistic link between GlycA and CKM.Conclusion
Our study confirmed a significant genetic association and shared genetic structure between GlycA and CKM, revealing potential mechanisms that may be involved.
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BibTeX
@article{yuan2026glycagene,
title = {{GlycA-gene interactions in cardiovascular-kidney-metabolic syndrome: evidence from genetic association.}},
author = {Mingyang Yuan and Suwen Cao and Xing Wan and Yuting Yang and Siyu Fan and Jiang Xie and Han Wang},
journal = {Diabetology \& metabolic syndrome},
year = {2026},
month = jul,
doi = {10.1186/s13098-026-02252-7},
url = {https://europepmc.org/article/MED/42902308},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - GlycA-gene interactions in cardiovascular-kidney-metabolic syndrome: evidence from genetic association.
AU - Mingyang Yuan
AU - Suwen Cao
AU - Xing Wan
AU - Yuting Yang
AU - Siyu Fan
AU - Jiang Xie
AU - Han Wang
PY - 2026
DA - 2026/07/01
JO - Diabetology & metabolic syndrome
DO - 10.1186/s13098-026-02252-7
UR - https://europepmc.org/article/MED/42902308
AB - Objective Cardiovascular-Kidney-metabolic (CKM) syndrome is a concept introduced by the American Heart Association, describing systemic diseases resulting from the pathophysiological interaction among obesity, stroke, type 2 diabetes, chronic kidney disease, and cardiovascular disease. Glycoprotein acetyls (GlycA) is a novel biomarker for systemic inflammation and cardiovascular risk. This study aims to uncover the shared genetic architecture between GlycA and CKM, identify common risk loci and key tissues, and clarify the mechanisms linking these conditions.Methods Using summary data from large-scale GWAS studies, we evaluated both global and local genetic correlations between GlycA and various components of CKM. A cross-trait pleiotropic analysis was conducted to identify shared pleiotropic loci and related genes. FUSION was used to find susceptibility genes linked to GlycA and CKM. A comprehensive set of functional annotations and tissue-specific analyses was performed to uncover potential connections between these traits. Furthermore, a multi-trait colocalization method was utilized to explore the underlying mechanisms of the association between GlycA and CKM.Results Our study revealed a close genetic correlation between GlycA and CKM. We identified 260 potential SNPs that were corrected using the Bonferroni method, of which 30 passed the colocalization test (PP.H4 > 0.70). Notably, locus 9q34.2 appeared in both GlycA-T2D and GlycA-HF trait pairs. By integrating post-GWAS methods, we identified 53 potentially drug targets (CMIP, DNAJC5G, FCGRT, etc.). FUSION analysis identified 23 shared susceptibility genes for GlycA and CKM (ZPR1, IL6R, PABPC4, etc.). Analysis of tissue enrichment at the SNP level revealed pleiotropic mechanisms associated with whole blood and liver. Gene-level analysis highlighted important roles of metabolic signaling pathways. Furthermore, multi-trait colocalization analysis suggested that rs1260326 and rs2925979 may play significant roles in the mechanistic link between GlycA and CKM.Conclusion Our study confirmed a significant genetic association and shared genetic structure between GlycA and CKM, revealing potential mechanisms that may be involved.
SN - 1758-5996
ER -