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Published on: January 28, 2020
STAT4 and COL1A2 are potential diagnostic biomarkers and therapeutic targets for heart failure comorbided with
Kai Huang1, Xinying Zhang2, Jiahao Duan1
1Department of Cardiology, The Third Affiliated Hospital of Soochow University, Changzhou 213003, China.
Insights
Heart failure (HF) and depression share underlying mechanisms. Bioinformatics analysis identified STAT4 and COL1A2 as key genes, offering potential therapeutic targets for this common comorbidity.
Area of Science:
- Biomedical Informatics
- Cardiovascular Research
- Psychiatric Genetics
Background:
- Heart failure (HF) and depression frequently co-occur, significantly impacting patient quality of life and societal costs.
- The precise biological mechanisms driving this comorbidity remain incompletely understood.
- Existing evidence suggests a strong link, necessitating further investigation into shared pathological pathways.
Purpose of the Study:
- To elucidate the molecular mechanisms underlying the comorbidity of heart failure and depression.
- To identify potential diagnostic biomarkers and therapeutic targets for co-occurring HF and depression.
- To leverage bioinformatics network analysis for uncovering shared genetic and pathway associations.
Main Methods:
- Downloaded Gene Expression Omnibus (GEO) datasets for HF and depression.
- Constructed co-expression networks using Weighted Gene Co-Expression Network Analysis (WGCNA).
- Performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis.
- Built a protein-protein interaction (PPI) network using the STRING database to identify hub genes.
- Validated hub gene expression in additional HF and depression datasets.
Main Results:
- Functional enrichment analysis implicated platelet activation, chemokine signaling, and focal adhesion pathways.
- Protein-protein interaction network analysis identified five key hub genes: STAT4, CD83, CX3CR1, COL1A2, and SH2D1B.
- Validation datasets confirmed the significant involvement of STAT4 and COL1A2 in the HF-depression comorbidity.
Conclusions:
- Identified five hub genes (STAT4, CD83, CX3CR1, COL1A2, SH2D1B) associated with HF and depression comorbidity.
- STAT4 and COL1A2 were highlighted as particularly crucial in the underlying mechanisms of this dual diagnosis.
- These findings suggest shared pathways that may serve as novel targets for future research into the pathogenesis and treatment of comorbid HF and depression.
Background:
Heart failure (HF) and depression are common disorders that markedly compromise quality of life and impose a great financial burden on the society. Although increasing evidence has supported the closely linkage between the two disorders, the comorbidity mechanisms remain to be fully illuminated. We performed a bioinformatics network analysis to understand potential diagnostic biomarkers and therapeutic targets for HF comorbided with depression.
Methods:
We downloaded the datasets of HF and depression from the Gene Expression Omnibus (GEO) database and constructed co-expression networks by Weighted Gene Co-Expression Network Analysis (WGCNA) to identify key modules. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the common genes existing in the HF and depression related modules. Then, we employed the STRING database to construct the protein-protein interaction (PPI) network and detected the hub genes in the network. Finally, we validated the expression difference of hub genes from additional datasets of HF and depression.
Results:
Functional enrichment analysis indicated that platelet activation, chemokine signaling and focal adhesion were probably involved in HF comorbided with depression. PPI network construction indicated that HF comorbided with depression is likely related to 5 hub genes, including STAT4, CD83, CX3CR1, COL1A2, and SH2D1B. In validated datasets, STAT4 and COL1A2 were especially involved in the comorbidity of HF and depression.
Conclusion:
Our work indicated a total of 5 hub genes including STAT4, CD83, CX3CR1, COL1A2, and SH2D1B, in which STAT4 and COL1A2 especially underlie the comorbidity mechanisms of HF and depression. These shared pathways might provide new targets for further mechanistic studies of the pathogenesis and treatment of HF and depression.
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