Bioinformatics Analysis Reveals Diagnostic Markers and Vital Pathways Involved in Acute Coronary Syndrome

Background. Acute coronary syndrome (ACS) has a high incidence and mortality rate. Early detection and intervention would provide clinical benefits. This study aimed to reveal hub genes, transcription factors (TFs), and microRNAs (miRNAs) that affect plaque stability and provide the possibility for...

Full description

Saved in:
Bibliographic Details
Main Authors: Mingshuang Li, Conglin Ren, Chenxia Wu, Xinyao Li, Xinyi Li, Wei Mao
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Cardiology Research and Practice
Online Access:http://dx.doi.org/10.1155/2020/3162581
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850217025244233728
author Mingshuang Li
Conglin Ren
Chenxia Wu
Xinyao Li
Xinyi Li
Wei Mao
author_facet Mingshuang Li
Conglin Ren
Chenxia Wu
Xinyao Li
Xinyi Li
Wei Mao
author_sort Mingshuang Li
collection DOAJ
description Background. Acute coronary syndrome (ACS) has a high incidence and mortality rate. Early detection and intervention would provide clinical benefits. This study aimed to reveal hub genes, transcription factors (TFs), and microRNAs (miRNAs) that affect plaque stability and provide the possibility for the early diagnosis and treatment of ACS. Methods. We obtained gene expression matrix GSE19339 for ACS patients and healthy subjects from public database. The differentially expressed genes (DEGs) were screened using Limma package in R software. The biological functions of DEGs were shown by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Protein-protein interaction (PPI) network was mapped in Cytoscape, followed by screening of hub genes based on the Molecular Complex Detection (MCODE) plug-in. Functional Enrichment analysis tool (FunRich) and Database for Annotation, Visualization and Integrated Discovery (DAVID) were used to predict miRNAs and TFs, respectively. Finally, GSE60993 expression matrix was chosen to plot receiver operating characteristic (ROC) curves with the aim of further assessing the reliability of our findings. Results. We obtained 176 DEGs and further identified 16 hub genes by MCODE. The results of functional enrichment analysis showed that DEGs mediated inflammatory response and immune-related pathways. Among the predicted miRNAs, hsa-miR-4770, hsa-miR-5195, and hsa-miR-6088 all possessed two target genes, which might be closely related to the development of ACS. Moreover, we identified 11 TFs regulating hub gene transcriptional processes. Finally, ROC curves confirmed three genes with high confidence (area under the curve > 0.9), including VEGFA, SPP1, and VCAM1. Conclusion. This study suggests that three genes (VEGFA, SPP1, and VCAM1) were involved in the molecular mechanisms of ACS pathogenesis and could serve as biomarkers of disease progression.
format Article
id doaj-art-2e097239ef024fc9bd51119d6a07799b
institution OA Journals
issn 2090-8016
2090-0597
language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Cardiology Research and Practice
spelling doaj-art-2e097239ef024fc9bd51119d6a07799b2025-08-20T02:08:09ZengWileyCardiology Research and Practice2090-80162090-05972020-01-01202010.1155/2020/31625813162581Bioinformatics Analysis Reveals Diagnostic Markers and Vital Pathways Involved in Acute Coronary SyndromeMingshuang Li0Conglin Ren1Chenxia Wu2Xinyao Li3Xinyi Li4Wei Mao5Department of Cardiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310002, ChinaThe Third Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310051, ChinaDepartment of Cardiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310002, ChinaDepartment of Cardiology, Zhejiang Hospital, Hangzhou, Zhejiang 310013, ChinaDepartment of Cardiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310002, ChinaDepartment of Cardiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310002, ChinaBackground. Acute coronary syndrome (ACS) has a high incidence and mortality rate. Early detection and intervention would provide clinical benefits. This study aimed to reveal hub genes, transcription factors (TFs), and microRNAs (miRNAs) that affect plaque stability and provide the possibility for the early diagnosis and treatment of ACS. Methods. We obtained gene expression matrix GSE19339 for ACS patients and healthy subjects from public database. The differentially expressed genes (DEGs) were screened using Limma package in R software. The biological functions of DEGs were shown by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Protein-protein interaction (PPI) network was mapped in Cytoscape, followed by screening of hub genes based on the Molecular Complex Detection (MCODE) plug-in. Functional Enrichment analysis tool (FunRich) and Database for Annotation, Visualization and Integrated Discovery (DAVID) were used to predict miRNAs and TFs, respectively. Finally, GSE60993 expression matrix was chosen to plot receiver operating characteristic (ROC) curves with the aim of further assessing the reliability of our findings. Results. We obtained 176 DEGs and further identified 16 hub genes by MCODE. The results of functional enrichment analysis showed that DEGs mediated inflammatory response and immune-related pathways. Among the predicted miRNAs, hsa-miR-4770, hsa-miR-5195, and hsa-miR-6088 all possessed two target genes, which might be closely related to the development of ACS. Moreover, we identified 11 TFs regulating hub gene transcriptional processes. Finally, ROC curves confirmed three genes with high confidence (area under the curve > 0.9), including VEGFA, SPP1, and VCAM1. Conclusion. This study suggests that three genes (VEGFA, SPP1, and VCAM1) were involved in the molecular mechanisms of ACS pathogenesis and could serve as biomarkers of disease progression.http://dx.doi.org/10.1155/2020/3162581
spellingShingle Mingshuang Li
Conglin Ren
Chenxia Wu
Xinyao Li
Xinyi Li
Wei Mao
Bioinformatics Analysis Reveals Diagnostic Markers and Vital Pathways Involved in Acute Coronary Syndrome
Cardiology Research and Practice
title Bioinformatics Analysis Reveals Diagnostic Markers and Vital Pathways Involved in Acute Coronary Syndrome
title_full Bioinformatics Analysis Reveals Diagnostic Markers and Vital Pathways Involved in Acute Coronary Syndrome
title_fullStr Bioinformatics Analysis Reveals Diagnostic Markers and Vital Pathways Involved in Acute Coronary Syndrome
title_full_unstemmed Bioinformatics Analysis Reveals Diagnostic Markers and Vital Pathways Involved in Acute Coronary Syndrome
title_short Bioinformatics Analysis Reveals Diagnostic Markers and Vital Pathways Involved in Acute Coronary Syndrome
title_sort bioinformatics analysis reveals diagnostic markers and vital pathways involved in acute coronary syndrome
url http://dx.doi.org/10.1155/2020/3162581
work_keys_str_mv AT mingshuangli bioinformaticsanalysisrevealsdiagnosticmarkersandvitalpathwaysinvolvedinacutecoronarysyndrome
AT conglinren bioinformaticsanalysisrevealsdiagnosticmarkersandvitalpathwaysinvolvedinacutecoronarysyndrome
AT chenxiawu bioinformaticsanalysisrevealsdiagnosticmarkersandvitalpathwaysinvolvedinacutecoronarysyndrome
AT xinyaoli bioinformaticsanalysisrevealsdiagnosticmarkersandvitalpathwaysinvolvedinacutecoronarysyndrome
AT xinyili bioinformaticsanalysisrevealsdiagnosticmarkersandvitalpathwaysinvolvedinacutecoronarysyndrome
AT weimao bioinformaticsanalysisrevealsdiagnosticmarkersandvitalpathwaysinvolvedinacutecoronarysyndrome