Cargando…

Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells

Myocardial infarction (MI) is a serious heart disease and a leading cause of mortality and morbidity worldwide. Although some molecules (genes, miRNAs and transcription factors (TFs)) associated with MI have been studied in a specific pathological context, their dynamic characteristics in gene expre...

Descripción completa

Detalles Bibliográficos
Autores principales: Shi, Hongbo, Zhang, Guangde, Wang, Jing, Wang, Zhenzhen, Liu, Xiaoxia, Cheng, Liang, Li, Weimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4930172/
https://www.ncbi.nlm.nih.gov/pubmed/27367417
http://dx.doi.org/10.1371/journal.pone.0158638
_version_ 1782440706341601280
author Shi, Hongbo
Zhang, Guangde
Wang, Jing
Wang, Zhenzhen
Liu, Xiaoxia
Cheng, Liang
Li, Weimin
author_facet Shi, Hongbo
Zhang, Guangde
Wang, Jing
Wang, Zhenzhen
Liu, Xiaoxia
Cheng, Liang
Li, Weimin
author_sort Shi, Hongbo
collection PubMed
description Myocardial infarction (MI) is a serious heart disease and a leading cause of mortality and morbidity worldwide. Although some molecules (genes, miRNAs and transcription factors (TFs)) associated with MI have been studied in a specific pathological context, their dynamic characteristics in gene expressions, biological functions and regulatory interactions in MI progression have not been fully elucidated to date. In the current study, we analyzed time-series RNA expression data from peripheral blood mononuclear cells. We observed that significantly differentially expressed genes were sharply up- or down-regulated in the acute phase of MI, and then changed slowly until the chronic phase. Biological functions involved at each stage of MI were identified. Additionally, dynamic miRNA–TF co-regulatory networks were constructed based on the significantly differentially expressed genes and miRNA–TF co-regulatory motifs, and the dynamic interplay of miRNAs, TFs and target genes were investigated. Finally, a new panel of candidate diagnostic biomarkers (STAT3 and ICAM1) was identified to have discriminatory capability for patients with or without MI, especially the patients with or without recurrent events. The results of the present study not only shed new light on the understanding underlying regulatory mechanisms involved in MI progression, but also contribute to the discovery of true diagnostic biomarkers for MI.
format Online
Article
Text
id pubmed-4930172
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-49301722016-07-18 Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells Shi, Hongbo Zhang, Guangde Wang, Jing Wang, Zhenzhen Liu, Xiaoxia Cheng, Liang Li, Weimin PLoS One Research Article Myocardial infarction (MI) is a serious heart disease and a leading cause of mortality and morbidity worldwide. Although some molecules (genes, miRNAs and transcription factors (TFs)) associated with MI have been studied in a specific pathological context, their dynamic characteristics in gene expressions, biological functions and regulatory interactions in MI progression have not been fully elucidated to date. In the current study, we analyzed time-series RNA expression data from peripheral blood mononuclear cells. We observed that significantly differentially expressed genes were sharply up- or down-regulated in the acute phase of MI, and then changed slowly until the chronic phase. Biological functions involved at each stage of MI were identified. Additionally, dynamic miRNA–TF co-regulatory networks were constructed based on the significantly differentially expressed genes and miRNA–TF co-regulatory motifs, and the dynamic interplay of miRNAs, TFs and target genes were investigated. Finally, a new panel of candidate diagnostic biomarkers (STAT3 and ICAM1) was identified to have discriminatory capability for patients with or without MI, especially the patients with or without recurrent events. The results of the present study not only shed new light on the understanding underlying regulatory mechanisms involved in MI progression, but also contribute to the discovery of true diagnostic biomarkers for MI. Public Library of Science 2016-07-01 /pmc/articles/PMC4930172/ /pubmed/27367417 http://dx.doi.org/10.1371/journal.pone.0158638 Text en © 2016 Shi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Shi, Hongbo
Zhang, Guangde
Wang, Jing
Wang, Zhenzhen
Liu, Xiaoxia
Cheng, Liang
Li, Weimin
Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells
title Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells
title_full Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells
title_fullStr Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells
title_full_unstemmed Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells
title_short Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells
title_sort studying dynamic features in myocardial infarction progression by integrating mirna-transcription factor co-regulatory networks and time-series rna expression data from peripheral blood mononuclear cells
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4930172/
https://www.ncbi.nlm.nih.gov/pubmed/27367417
http://dx.doi.org/10.1371/journal.pone.0158638
work_keys_str_mv AT shihongbo studyingdynamicfeaturesinmyocardialinfarctionprogressionbyintegratingmirnatranscriptionfactorcoregulatorynetworksandtimeseriesrnaexpressiondatafromperipheralbloodmononuclearcells
AT zhangguangde studyingdynamicfeaturesinmyocardialinfarctionprogressionbyintegratingmirnatranscriptionfactorcoregulatorynetworksandtimeseriesrnaexpressiondatafromperipheralbloodmononuclearcells
AT wangjing studyingdynamicfeaturesinmyocardialinfarctionprogressionbyintegratingmirnatranscriptionfactorcoregulatorynetworksandtimeseriesrnaexpressiondatafromperipheralbloodmononuclearcells
AT wangzhenzhen studyingdynamicfeaturesinmyocardialinfarctionprogressionbyintegratingmirnatranscriptionfactorcoregulatorynetworksandtimeseriesrnaexpressiondatafromperipheralbloodmononuclearcells
AT liuxiaoxia studyingdynamicfeaturesinmyocardialinfarctionprogressionbyintegratingmirnatranscriptionfactorcoregulatorynetworksandtimeseriesrnaexpressiondatafromperipheralbloodmononuclearcells
AT chengliang studyingdynamicfeaturesinmyocardialinfarctionprogressionbyintegratingmirnatranscriptionfactorcoregulatorynetworksandtimeseriesrnaexpressiondatafromperipheralbloodmononuclearcells
AT liweimin studyingdynamicfeaturesinmyocardialinfarctionprogressionbyintegratingmirnatranscriptionfactorcoregulatorynetworksandtimeseriesrnaexpressiondatafromperipheralbloodmononuclearcells