BMC Medical Genomics (Jul 2020)

Weighted correlation network bioinformatics uncovers a key molecular biosignature driving the left-sided heart failure

  • Jiamin Zhou,
  • Wei Zhang,
  • Chunying Wei,
  • Zhiliang Zhang,
  • Dasong Yi,
  • Xiaoping Peng,
  • Jingtian Peng,
  • Ran Yin,
  • Zeqi Zheng,
  • Hongmei Qi,
  • Yunfeng Wei,
  • Tong Wen

DOI
https://doi.org/10.1186/s12920-020-00750-9
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 13

Abstract

Read online

Abstract Background Left-sided heart failure (HF) is documented as a key prognostic factor in HF. However, the relative molecular mechanisms underlying left-sided HF is unknown. The purpose of this study is to unearth significant modules, pivotal genes and candidate regulatory components governing the progression of left-sided HF by bioinformatical analysis. Methods A total of 319 samples in GSE57345 dataset were used for weighted gene correlation network analysis (WGCNA). ClusterProfiler package in R was used to conduct functional enrichment for genes uncovered from the modules of interest. Regulatory networks of genes were built using Cytoscape while Enrichr database was used for identification of transcription factors (TFs). The MCODE plugin was used for identifying hub genes in the modules of interest and their validation was performed based on GSE1869 dataset. Results A total of six significant modules were identified. Notably, the blue module was confirmed as the most crucially associated with left-sided HF, ischemic heart disease (ISCH) and dilated cardiomyopathy (CMP). Functional enrichment conveyed that genes belonging to this module were mainly those driving the extracellular matrix-associated processes such as extracellular matrix structural constituent and collagen binding. A total of seven transcriptional factors, including Suppressor of Zeste 12 Protein Homolog (SUZ12) and nuclear factor erythroid 2 like 2 (NFE2L2), adrenergic receptor (AR), were identified as possible regulators of coexpression genes identified in the blue module. A total of three key genes (OGN, HTRA1 and MXRA5) were retained after validation of their prognostic value in left-sided HF. The results of functional enrichment confirmed that these key genes were primarily involved in response to transforming growth factor beta and extracellular matrix. Conclusion We uncovered a candidate gene signature correlated with HF, ISCH and CMP in the left ventricle, which may help provide better prognosis and therapeutic decisions and in HF, ISCH and CMP patients.

Keywords