Systematic analysis of molecular mechanisms of heart failure through the pathway and network-based approach

Aims: The molecular networks and pathways involved in heart failure (HF) are still largely unknown. The present study aimed to systematically investigate the genes associated with HF, comprehensively explore their interactions and functions, and identify possible regulatory networks involved in HF. Main methods: The weighted gene coexpression network analysis (WGCNA), crosstalk analysis, and Pivot analysis were used to identify gene connections, interaction networks, and molecular regulatory mechanisms. Functional analysis and protein-protein interaction (PPI) were performed using DAVID and STRING databases. Gene set variation analysis (GSVA) and receiver operating characteristic (ROC) curve analysis were also performed to evaluate the relationship of the hub genes with HF. Key findings: A total of 5968 HF-related genes were obtained to construct the co-expression networks, and 18 relatively independent and closely linked modules were identified. Pivot analysis suggested that four transcription factors and five noncoding RNAs were involved in regulating the process of HF. The genes in the module with the highest positive correlation to HF was mainly enriched in cardiac remodeling and response to stress. Five upregulated hub genes (ASPN, FMOD, NT5E, LUM, and OGN) were identified and validated. Furthermore, the GSVA scores of the five hub genes for HF had a relatively high areas under the curve (AUC). Significance: The results of this study revealed specific molecular networks and their potential regulatory mechanisms involved in HF. These may provide new insight into understanding the mechanisms underlying HF and help to identify more effective therapeutic targets for HF.

Automated summary

This study identified 18 relatively independent and closely linked modules in the gene co-expression network associated with heart failure (HF). Pivot analysis revealed the involvement of four transcription factors and five noncoding RNAs in regulating HF. The upregulated hub genes ASPN, FMOD, NT5E, LUM, and OGN showed relatively high areas under the curve (AUC) in gene set variation analysis (GSVA) for HF. These results provide new insights into potential regulatory mechanisms in HF and may help in identifying effective therapeutic targets.