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. 2021 Jul 4;21(1):329.
doi: 10.1186/s12872-021-02146-8.

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Vijayakrishna Kolur  1 , Basavaraj Vastrad  2 , Chanabasayya Vastrad  3 , Shivakumar Kotturshetti  4 , Anandkumar Tengli  5
Affiliations

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Vijayakrishna Kolur et al. BMC Cardiovasc Disord. .

Abstract

Introduction: Heart failure (HF) is a heterogeneous clinical syndrome and affects millions of people all over the world. HF occurs when the cardiac overload and injury, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental HF as well as to explore active drug molecules.

Methods: The expression profiling by high throughput sequencing of GSE141910 dataset was downloaded from the Gene Expression Omnibus (GEO) database, which contained 366 samples, including 200 heart failure samples and 166 non heart failure samples. The raw data was integrated to find differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. Gene ontology (GO) and REACTOME enrichment analyses were performed via ToppGene; protein-protein interaction (PPI) networks of the DEGs was constructed based on data from the HiPPIE interactome database; modules analysis was performed; target gene-miRNA regulatory network and target gene-TF regulatory network were constructed and analyzed; hub genes were validated; molecular docking studies was performed.

Results: A total of 881 DEGs, including 442 up regulated genes and 439 down regulated genes were observed. Most of the DEGs were significantly enriched in biological adhesion, extracellular matrix, signaling receptor binding, secretion, intrinsic component of plasma membrane, signaling receptor activity, extracellular matrix organization and neutrophil degranulation. The top hub genes ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 were identified from the PPI network. Module analysis revealed that HF was associated with adaptive immune system and neutrophil degranulation. The target genes, miRNAs and TFs were identified from the target gene-miRNA regulatory network and target gene-TF regulatory network. Furthermore, receiver operating characteristic (ROC) curve analysis and RT-PCR analysis revealed that ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 might serve as prognostic, diagnostic biomarkers and therapeutic target for HF. The predicted targets of these active molecules were then confirmed.

Conclusion: The current investigation identified a series of key genes and pathways that might be involved in the progression of HF, providing a new understanding of the underlying molecular mechanisms of HF.

Keywords: Differentially expressed genes; Enrichment analysis; Heart failure; Molecular docking; Prognosis.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Volcano plot of differentially expressed genes. Genes with a significant change of more than two-fold were selected. Green dot represented up regulated significant genes and red dot represented down regulated significant genes
Fig. 2
Fig. 2
Heat map of differentially expressed genes. Legend on the top left indicate log fold change of genes. (A1 – A200 = heart failure samples; B1 – B166 = non heart failure samples)
Fig. 3
Fig. 3
PPI network and the most significant modules of DEGs. A The PPI network of DEGs was constructed using Cytoscape. B The most significant module was obtained from PPI network with 4 nodes and 6 edges for up regulated genes. C The most significant module was obtained from PPI network with 6 nodes and 10 edges for down regulated genes. Up regulated genes are marked in green; down regulated genes are marked in red
Fig. 4
Fig. 4
Target gene—miRNA regulatory network between target genes. The light orange color diamond nodes represent the key miRNAs; up regulated genes are marked in green; down regulated genes are marked in red
Fig. 5
Fig. 5
Target gene—TF regulatory network between target genes. The sky blue color triangle nodes represent the key TFs; up regulated genes are marked in green; down regulated genes are marked in red
Fig. 6
Fig. 6
ROC curve analyses of hub genes. A ESR1, B PYHIN1, C PPP2R2B, D LCK, E TP63, F PCLAF, G CFTR, H TK1, I ECT2, J FKBP5
Fig. 7
Fig. 7
RT-PCR analyses of hub genes. A ESR1, B PYHIN1, C PPP2R2B, D LCK, E TP63, F PCLAF, G) CFTR H TK1, I ECT2, J FKBP5
Fig. 8
Fig. 8
Structures of designed molecules
Fig. 9
Fig. 9
Structure of active designed molecule of HIM11
Fig.10
Fig.10
3D binding of molecule HIM11 with 2HV7
Fig.11
Fig.11
2D binding of molecule HIM11 with 2HV7
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