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

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 ta...

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Autores principales: Wang, Haiming, Shao, Junjie, Lu, Xuechun, Jiang, Min, Li, Xin, Liu, Zifan, Zhao, Yunzhang, Zhou, Jingjing, Lin, Lejian, Wang, Lin, Xu, Qiang, Chen, Yundai, Zhang, Ran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9458892/
https://www.ncbi.nlm.nih.gov/pubmed/36093144
http://dx.doi.org/10.3389/fcvm.2022.893502
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author Wang, Haiming
Shao, Junjie
Lu, Xuechun
Jiang, Min
Li, Xin
Liu, Zifan
Zhao, Yunzhang
Zhou, Jingjing
Lin, Lejian
Wang, Lin
Xu, Qiang
Chen, Yundai
Zhang, Ran
author_facet Wang, Haiming
Shao, Junjie
Lu, Xuechun
Jiang, Min
Li, Xin
Liu, Zifan
Zhao, Yunzhang
Zhou, Jingjing
Lin, Lejian
Wang, Lin
Xu, Qiang
Chen, Yundai
Zhang, Ran
author_sort Wang, Haiming
collection PubMed
description 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.
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spelling pubmed-94588922022-09-10 Potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis Wang, Haiming Shao, Junjie Lu, Xuechun Jiang, Min Li, Xin Liu, Zifan Zhao, Yunzhang Zhou, Jingjing Lin, Lejian Wang, Lin Xu, Qiang Chen, Yundai Zhang, Ran Front Cardiovasc Med Cardiovascular Medicine 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. Frontiers Media S.A. 2022-08-26 /pmc/articles/PMC9458892/ /pubmed/36093144 http://dx.doi.org/10.3389/fcvm.2022.893502 Text en Copyright © 2022 Wang, Shao, Lu, Jiang, Li, Liu, Zhao, Zhou, Lin, Wang, Xu, Chen and Zhang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cardiovascular Medicine
Wang, Haiming
Shao, Junjie
Lu, Xuechun
Jiang, Min
Li, Xin
Liu, Zifan
Zhao, Yunzhang
Zhou, Jingjing
Lin, Lejian
Wang, Lin
Xu, Qiang
Chen, Yundai
Zhang, Ran
Potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis
title Potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis
title_full Potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis
title_fullStr Potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis
title_full_unstemmed Potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis
title_short Potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis
title_sort potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9458892/
https://www.ncbi.nlm.nih.gov/pubmed/36093144
http://dx.doi.org/10.3389/fcvm.2022.893502
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