Potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis

Haiming Wang; Junjie Shao; Xuechun Lu; Min Jiang; Xin Li; Zifan Liu; Yunzhang Zhao; Jingjing Zhou; Lejian Lin; Lin Wang; Qiang Xu; Yundai Chen; Ran Zhang

doi:10.3389/fcvm.2022.893502

Potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis

Front Cardiovasc Med. 2022 Aug 26:9:893502. doi: 10.3389/fcvm.2022.893502. eCollection 2022.

Authors

Haiming Wang¹, Junjie Shao¹, Xuechun Lu², Min Jiang³, Xin Li⁴, Zifan Liu¹, Yunzhang Zhao¹, Jingjing Zhou¹, Lejian Lin¹, Lin Wang¹, Qiang Xu¹, Yundai Chen¹, Ran Zhang¹

Affiliations

¹ Department of Cardiovascular Medicine, Chinese PLA General Hospital and Chinese People's Liberation Army (PLA) Medical School, Beijing, China.
² Department of Hematology, The Second Medical Center of Chinese PLA General Hospital and Chinese People's Liberation Army (PLA) Medical School, Beijing, China.
³ Department of Respiratory and Critical Care, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
⁴ Department of Health Services, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.

Abstract

Background: Coronary heart disease (CHD) is the most common progressive disease that is difficult to diagnose and predict in the young asymptomatic period. Our study explored a mechanistic understanding of the genetic effects of premature CHD (PCHD) and provided potential biomarkers and treatment targets for further research through high throughput sequencing and integrated bioinformatics analysis.

Methods: High throughput sequencing was performed among recruited patients with PCHD and young healthy individuals, and CHD-related microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by using R software. Enrichment analysis and CIBERSORT were performed to explore the enriched pathways of DEGs and the characteristics of infiltrating immune cells. Hub genes identified by protein-protein interaction (PPI) networks were used to construct the competitive endogenous RNA (ceRNA) networks. Potential drugs were predicted by using the Drug Gene Interaction Database (DGIdb).

Results: A total of 35 DEGs were identified from the sequencing dataset and GEO database by the Venn Diagram. Enrichment analysis indicated that DEGs are mostly enriched in excessive immune activation pathways and signal transduction. CIBERSORT exhibited that resting memory CD4 T cells and neutrophils were more abundant, and M2 macrophages, CD8 T cells, and naïve CD4 T cells were relatively scarce in patients with PCHD. After the identification of 10 hub gens, three ceRNA networks of CD83, CXCL8, and NR4A2 were constructed by data retrieval and validation. In addition, CXCL8 might interact most with multiple chemical compounds mainly consisting of anti-inflammatory drugs.

Conclusions: The immune dysfunction mainly contributes to the pathogenesis of PCHD, and three ceRNA networks of CD83, CXCL8, and NR4A2 may be potential candidate biomarkers for early diagnosis and treatment targets of PCHD.

Keywords: high throughput sequencing; immune dysfunction; integrated bioinformatics analysis; potential biomarkers; premature coronary heart disease.