Research Paper Advance Articles
Identification of differentially expressed genes to predict the risk of heart failure in older patients with hypertrophic cardiomyopathy
- 1 Department of Cardiology, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing 210000, China
- 2 Education Section, The Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing 210000, China
- 3 Department of Cardiology, The First Hospital of Nanchang, Nanchang 330000, China
Received: January 31, 2024 Accepted: May 29, 2024 Published: June 20, 2024
https://doi.org/10.18632/aging.205956How to Cite
Copyright: © 2024 Dong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Aim: Hypertrophic cardiomyopathy (HCM) is a common heart disease. Old people with HCM are at high risk of heart failure (HF). This study aimed to identify differentially expressed genes (DEGs) to evaluate the risk of HF in older patients with HCM.
Methods: GSE89714 and GSE116250 were downloaded from Gene Expression Omnibus (GEO) database, and DEGs were identified by using limma R package with P < 0.05 and logFC> 1 as cut off. Protein-protein interaction (PPI) network, Genome Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for the identified DEGs. NetworkAnalyst online tool was applied for Gene Set Enrichment Analysis (GSEA) analysis.
Results: We identified 124 overlap DEGs from the 2 datasets. PPI network showed that COL1A1, COL3A1, COL1A2, BGN, COL5A1, LUM, TGFB2, FMOD, ASPN, and COL14A1 were the top ten genes related to HCM and HF compared with control. Functional and pathway analyses showed that the overlap genes were mainly related to ECM-receptor interaction, ECM organization, Focal adhesion, PI3K-Akt signaling, TGF-beta signaling, and Platelet activation signaling and aggregation. Among the overlap genes, COL5A1 and LUM were significantly upregulated, while TGFB2, FMOD, ASPN, and COL14A1 were significantly downregulated in HF dataset compared with HCM dataset.
Conclusions: Bioinformatics-based analysis revealed potential genes associated with HCM and HF, which could be utilized to evaluate the risk of HF in older patients with HCM.