Basic Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Cardiol. May 26, 2022; 14(5): 282-296
Published online May 26, 2022. doi: 10.4330/wjc.v14.i5.282
Bioinformatics prediction of potential mechanisms and biomarkers underlying dilated cardiomyopathy
Zhou Liu, Ying-Nan Song, Kai-Yuan Chen, Wei-Long Gao, Hong-Jin Chen, Gui-You Liang
Zhou Liu, Gui-You Liang, School of Basic Medical Sciences, Guizhou Medical University, Guiyang 550025, Guizhou Province, China
Zhou Liu, Ying-Nan Song, Kai-Yuan Chen, Wei-Long Gao, Hong-Jin Chen, Gui-You Liang, Translational Medicine Research Center, Guizhou Medical University, Guiyang 550025, Guizhou Province, China
Ying-Nan Song, Hong-Jin Chen, Gui-You Liang, Department of Cardiovascular Surgery, the Affiliated Hospital of Guizhou Medical University, Guiyang 510000, Guizhou Province, China
Author contributions: Liu Z and Song YN designed this study; Chen KY collected the relevant data; Liu Z analyzed the data; Liu Z and Gao WL drafted the manuscript; Chen HJ and Liang GY reviewed and supervised this manuscript; All authors approved the final version of the article.
Supported by National Nature Science Foundation of China, No. 81960051, No. 8217021743, and No. 82160060; Project of High–Level Innovative Talents of Guizhou Province, No. [2016]4034; and Construction Funding from Characteristic Key Laboratory of Guizhou Province, No. [2021]313.
Conflict-of-interest statement: The authors have no conflicts of interest to declare.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Gui-You Liang, MD, Professor, School of Basic Medical Sciences, Guizhou Medical University, Dangwu, Guian District, Guiyang 550025, Guizhou Province, China. guiyou515@163.com
Received: December 14, 2021
Peer-review started: December 14, 2021
First decision: January 25, 2022
Revised: February 19, 2022
Accepted: April 26, 2022
Article in press: April 26, 2022
Published online: May 26, 2022
ARTICLE HIGHLIGHTS
Research background

Dilated cardiomyopathy (DCM), a disease of the heart muscle, is one of the most common causes of heart failure. However, the original cause and pathogenesis in development of DCM are still remain elusive.

Research motivation

The early diagnosis and prognosis of DCM patients are unsatisfactory because of DCM main cause and pathogenesis are still unclear. Increasing DCM datasets were provided online but little was been explored. Bioinformatics could further investigate the DCM mechanism and biomarkers for improving the diagnostic and therapeutic efficiency.

Research objectives

This study investigated the candidate genes and pathways involved in DCM patients.

Research methods

Expression datasets were downloaded from the Gene Expression Omnibus database. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analyses investigated the key pathway in differentially expressed genes (DEGs) between the DCM patients and healthy individuals. Protein-protein interaction network identified the hub genes and modules in DCM. MicroRNA Database predicted the microRNAs which targeting the hub genes. CIBERSORT analyzed the immune- ell infiltration in DCM.

Research results

Ninety-seven DEGs mainly enriched in “response to growth factor,” “extracellular matrix,” and “extracellular matrix structural constituent.” Moreover, the top two pathways were “protein digestion and absorption” and “interleukin 17 signaling pathway.” Collagen type III alpha 1 chain (COL3A1) and COL1A2, whose were regulated by hsa-miR-5682 and hsa-miR-4500, mainly contributed to the pathogenesis of DCM. Compared with the control group, DCM patients had more infiltrated plasma cells and fewer infiltrated B memory cells, T follicular helper cells, and resting dendritic cells.

Research conclusions

DCM progression closely related to IL-17 signaling pathway and acute inflammatory response. COL1A2 and COL3A1 and their targeting miRNAs, hsa-miR-5682 and hsa-miR-4500, are the potential biomarkers of DCM.

Research perspectives

This study may provide valuable pathways and biomarkers for the diagnosis or treatment of DCM. Further studies should investigate the functions of the predicted genes and pathways.