Literature DB >> 24704022

Bioinformatics analysis of time series gene expression in left ventricle (LV) with acute myocardial infarction (AMI).

Tong Zhang1, Li-Li Zhao2, Xue Cao1, Li-Chun Qi1, Guo-Qian Wei1, Jun-Yan Liu1, Shu-Jun Yan1, Jin-Gang Liu3, Xue-Qi Li4.   

Abstract

This study is to investigate the key genes and their possible function in acute myocardial infarction (AMI). The data of GSE4648 downloaded from the Gene Expression Omnibus (GEO) database include 6 time points (15 min, 60 min, 4h, 12h, 24h and 48 h) of 12 left ventricle (LV) samples, 12 surviving LV free wall (FW) samples, 12 inter-ventricular septum (IVS) samples after AMI operation and corresponding sham-operated samples. The data of each sample were analyzed with Affy and Bioconductor packages, and differentially expressed genes (DEGs) were screened out using BETR package with false discovery rate (FDR)<0.01. Then, functional enrichment analysis for DEGs was conducted with Database for Annotation, Visualization and Integrated Discovery (DAVID). Totally 194 DEGs were identified in LV, and only the gene tubulin beta 2a (Tubb2a) and natriuretic peptide B (Nppb) were respectively up-regulated in surviving FW tissue and IVS tissue. The biological process response to wounding and inflammatory response were significantly enriched, as well as leukocyte transendothelial migration pathway. Besides, the expression pattern analysis showed the DEGs mostly up-regulated at 4h after AMI, and these genes were mainly associated with immunity. Additionally, in transcriptional regulatory network, early growth response 1 (Egr1), activating transcription factor 3 (Atf3), Atf4, Myc and Fos were considered as the key transcription factors related to immune response. The key transcription factors and potential target genes might provide new information for the development of AMI, and leukocyte transendothelial migration pathway might play a vital role in AMI.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Acute myocardial infarction; Differentially expressed genes; Left ventricle; Time series; Transcription factor

Mesh:

Year:  2014        PMID: 24704022     DOI: 10.1016/j.gene.2014.04.002

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  12 in total

Review 1.  Molecular tissue changes in early myocardial ischemia: from pathophysiology to the identification of new diagnostic markers.

Authors:  Aleksandra Aljakna; Tony Fracasso; Sara Sabatasso
Journal:  Int J Legal Med       Date:  2018-01-23       Impact factor: 2.686

2.  The Long Noncoding RNA Landscape of the Ischemic Human Left Ventricle.

Authors:  Louis A Saddic; Martin I Sigurdsson; Tzuu-Wang Chang; Erica Mazaika; Mahyar Heydarpour; Stanton K Shernan; Christine E Seidman; Jon G Seidman; Sary F Aranki; Simon C Body; Jochen D Muehlschlegel
Journal:  Circ Cardiovasc Genet       Date:  2017-01

3.  MiRNA and TF co-regulatory network analysis for the pathology and recurrence of myocardial infarction.

Authors:  Ying Lin; Vusumuzi Leroy Sibanda; Hong-Mei Zhang; Hui Hu; Hui Liu; An-Yuan Guo
Journal:  Sci Rep       Date:  2015-04-13       Impact factor: 4.379

4.  Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics Analysis.

Authors:  Da-Qiu Chen; Xiang-Sheng Kong; Xue-Bin Shen; Mao-Zhi Huang; Jian-Ping Zheng; Jing Sun; Shang-Hua Xu
Journal:  Cardiovasc Ther       Date:  2019-08-01       Impact factor: 3.023

5.  PIK3R1, SPNB2, and CRYAB as Potential Biomarkers for Patients with Diabetes and Developing Acute Myocardial Infarction.

Authors:  Yue Zheng; Yuheng Lang; Zhenchang Qi; Wenqing Gao; Xiaomin Hu; Tong Li
Journal:  Int J Endocrinol       Date:  2021-11-30       Impact factor: 3.257

6.  KLRD1, FOSL2 and LILRB3 as potential biomarkers for plaques progression in acute myocardial infarction and stable coronary artery disease.

Authors:  Qiang Zhang; Yue Zheng; Meng Ning; Tong Li
Journal:  BMC Cardiovasc Disord       Date:  2021-07-16       Impact factor: 2.298

7.  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.

Authors:  Hongbo Shi; Guangde Zhang; Jing Wang; Zhenzhen Wang; Xiaoxia Liu; Liang Cheng; Weimin Li
Journal:  PLoS One       Date:  2016-07-01       Impact factor: 3.240

8.  Analysis of region specific gene expression patterns in the heart and systemic responses after experimental myocardial ischemia.

Authors:  Matthias Zimmermann; Lucian Beer; Robert Ullrich; Dominika Lukovic; Elisabeth Simader; Denise Traxler; Tanja Wagner; Lucas Nemec; Lukas Altenburger; Andreas Zuckermann; Mariann Gyöngyösi; Hendrik Jan Ankersmit; Michael Mildner
Journal:  Oncotarget       Date:  2017-05-17

9.  Hypoxic Stress Decreases c-Myc Protein Stability in Cardiac Progenitor Cells Inducing Quiescence and Compromising Their Proliferative and Vasculogenic Potential.

Authors:  Michael A Bellio; Mariana T Pinto; Victoria Florea; Paola A Barrios; Christy N Taylor; Ariel B Brown; Courtney Lamondin; Joshua M Hare; Ivonne H Schulman; Claudia O Rodrigues
Journal:  Sci Rep       Date:  2017-08-29       Impact factor: 4.379

10.  In Silico Analysis of Differential Gene Expression in Three Common Rat Models of Diastolic Dysfunction.

Authors:  Raffaele Altara; Fouad A Zouein; Rita Dias Brandão; Saeed N Bajestani; Alessandro Cataliotti; George W Booz
Journal:  Front Cardiovasc Med       Date:  2018-02-21
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.