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RUNX1 and CCL3 in Diabetes Mellitus-Related Coronary Artery Disease: A Bioinformatics Analysis
Yi Zhong1,2, Guoyong Du1,2, Jie Liu1,2
1Department of Cardiology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People's Republic of China.
Insights
Cardiovascular complications in diabetes mellitus are linked to viral infection pathways. CCL3 may be a key regulator, and RUNX1 a key transcription factor in diabetes mellitus-associated coronary artery disease.
Area of Science:
- Genomics
- Bioinformatics
- Cardiovascular Research
Background:
- Cardiovascular complications are a leading cause of death in diabetes mellitus patients.
- The underlying mechanisms of these complications remain largely unknown.
Purpose of the Study:
- To investigate the molecular mechanisms of diabetes mellitus-associated coronary artery disease (DMCAD).
- To identify key regulators and transcription factors involved in DMCAD progression.
Main Methods:
- Weighted gene correlation network analysis (WGCNA) on gene expression profiles.
- Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) pathway enrichment analysis.
- Gene set enrichment analysis (GSEA), ClueGo, and regulatory network construction.
Main Results:
- Three gene modules associated with DMCAD progression were identified.
- Module genes are involved in interferon, viral infection, viral myocarditis, and chemokine signaling pathways.
- RUNX1 was identified as a potential transcription factor, and CCL3 as a key regulator in DMCAD.
Conclusions:
- Bioinformatic analysis suggests CCL3 is a key regulator in DMCAD.
- RUNX1 is identified as a key transcription factor in the development of DMCAD.
Background:
Cardiovascular complications are a major cause of death and disability in patients with diabetes mellitus, but how such complications arise is unclear.
Methods:
Weighted gene correlation network analysis (WGCNA) was performed on gene expression profiles from healthy controls, individuals with diabetes mellitus, and individuals with diabetes mellitus-associated coronary artery disease (DMCAD). Phenotypically related module genes were analyzed for enrichment in Gene Ontology (GO) terms and Kyoto Gene and Genome Encyclopedia (KEGG) pathways. Predicted biological functions were validated using gene set enrichment analysis (GSEA) and ClueGo analysis. Based on the TRRUST v2 database and hypergeometric tests, a global network was built to identify transcription factors (TFs) and downstream target genes potentially involved in DMCAD.
Results:
WGCNA identified three modules associated with progression from diabetes mellitus to DMCAD. The module genes were significantly involved in biological processes related to interferon and viral infection, while GSEA of DMCAD samples suggested involvement in viral myocarditis, chemokine signaling and phagosomes. RUNX1 was identified as a potential TF regulating these module genes. Analysis of the global regulatory network of TFs and their targets suggested that CCL3 may be a key regulator in DMCAD.
Conclusion:
We found bioinformatic evidence that CCL3 may be a key regulator and RUNX1 a key TF in DMCAD.
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