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Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction
Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases worldwide. Advances in genomics have provided new ideas for the development of novel molecular biomarkers of potential clinical value for AMI. METHODS: Based on microarray data from a public database, differential a...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046674/ https://www.ncbi.nlm.nih.gov/pubmed/35498008 http://dx.doi.org/10.3389/fcvm.2022.863248 |
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author | Tan, Xiaobing Dai, Qingli Sun, Huang Jiang, Wenqing Lu, Si Wang, Ruxian Lv, Meirong Sun, Xianfeng Lv, Naying Dai, Qingyuan |
author_facet | Tan, Xiaobing Dai, Qingli Sun, Huang Jiang, Wenqing Lu, Si Wang, Ruxian Lv, Meirong Sun, Xianfeng Lv, Naying Dai, Qingyuan |
author_sort | Tan, Xiaobing |
collection | PubMed |
description | Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases worldwide. Advances in genomics have provided new ideas for the development of novel molecular biomarkers of potential clinical value for AMI. METHODS: Based on microarray data from a public database, differential analysis and functional enrichment analysis were performed to identify aberrantly expressed genes in AMI and their potential functions. CIBERSORT was used for immune landscape analysis. We also obtained whole blood samples of 3 patients with AMI and performed second-generation sequencing (SGS) analysis. Weighted gene co-expression network analysis (WGCNA) and cross-tabulation analysis identified AMI-related key genes. Receiver operating characteristic (ROC) curves were used to assess the diagnostic power of key genes. Single-gene gene set enrichment analysis (GSEA) revealed the molecular mechanisms of diagnostic indicators. RESULTS: A total of 53 AMI-related DEGs from a public database were obtained and found to be involved in immune cell activation, immune response regulation, and cardiac developmental processes. CIBERSORT confirmed that the immune microenvironment was altered between AMI and normal samples. A total of 77 hub genes were identified by WGCNA, and 754 DEGs were obtained from own SGS data. Seven diagnostic indicators of AMI were obtained, namely GZMA, NKG7, TBX21, TGFBR3, SMAD7, KLRC4, and KLRD1. The single-gene GSEA suggested that the diagnostic indicators seemed to be closely implicated in cell cycle, immune response, cardiac developmental, and functional regulatory processes. CONCLUSION: The present study provides new diagnostic indicators for AMI and further confirms the feasibility of the results of genome-wide gene expression analysis. |
format | Online Article Text |
id | pubmed-9046674 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90466742022-04-29 Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction Tan, Xiaobing Dai, Qingli Sun, Huang Jiang, Wenqing Lu, Si Wang, Ruxian Lv, Meirong Sun, Xianfeng Lv, Naying Dai, Qingyuan Front Cardiovasc Med Cardiovascular Medicine Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases worldwide. Advances in genomics have provided new ideas for the development of novel molecular biomarkers of potential clinical value for AMI. METHODS: Based on microarray data from a public database, differential analysis and functional enrichment analysis were performed to identify aberrantly expressed genes in AMI and their potential functions. CIBERSORT was used for immune landscape analysis. We also obtained whole blood samples of 3 patients with AMI and performed second-generation sequencing (SGS) analysis. Weighted gene co-expression network analysis (WGCNA) and cross-tabulation analysis identified AMI-related key genes. Receiver operating characteristic (ROC) curves were used to assess the diagnostic power of key genes. Single-gene gene set enrichment analysis (GSEA) revealed the molecular mechanisms of diagnostic indicators. RESULTS: A total of 53 AMI-related DEGs from a public database were obtained and found to be involved in immune cell activation, immune response regulation, and cardiac developmental processes. CIBERSORT confirmed that the immune microenvironment was altered between AMI and normal samples. A total of 77 hub genes were identified by WGCNA, and 754 DEGs were obtained from own SGS data. Seven diagnostic indicators of AMI were obtained, namely GZMA, NKG7, TBX21, TGFBR3, SMAD7, KLRC4, and KLRD1. The single-gene GSEA suggested that the diagnostic indicators seemed to be closely implicated in cell cycle, immune response, cardiac developmental, and functional regulatory processes. CONCLUSION: The present study provides new diagnostic indicators for AMI and further confirms the feasibility of the results of genome-wide gene expression analysis. Frontiers Media S.A. 2022-04-14 /pmc/articles/PMC9046674/ /pubmed/35498008 http://dx.doi.org/10.3389/fcvm.2022.863248 Text en Copyright © 2022 Tan, Dai, Sun, Jiang, Lu, Wang, Lv, Sun, Lv and Dai. 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 Tan, Xiaobing Dai, Qingli Sun, Huang Jiang, Wenqing Lu, Si Wang, Ruxian Lv, Meirong Sun, Xianfeng Lv, Naying Dai, Qingyuan Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction |
title | Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction |
title_full | Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction |
title_fullStr | Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction |
title_full_unstemmed | Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction |
title_short | Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction |
title_sort | systematic bioinformatics analysis based on public and second-generation sequencing transcriptome data: a study on the diagnostic value and potential mechanisms of immune-related genes in acute myocardial infarction |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046674/ https://www.ncbi.nlm.nih.gov/pubmed/35498008 http://dx.doi.org/10.3389/fcvm.2022.863248 |
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