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Bioinformatics method combined with logistic regression analysis reveal potentially important miRNAs in ischemic stroke.

Authors :
Zhiqiang Wei
Xingdi Qi
Yan Chen
Xiaoshuang Xia
Boyu Zheng
Xugang Sun
Guangming Zhang
Ling Wang
Qi Zhang
Chen Xu
Shihe Jiang
Xiulian Li
Bingxin Xie
Xiaohui Liao
Ai Zhu
Source :
Bioscience Reports; Aug2020, Vol. 40 Issue 8, p1-7, 7p
Publication Year :
2020

Abstract

Purpose: The present study aimed to investigate the comprehensive differential expression profile of microRNAs (miRNAs) by screening for miRNA expression in ischemic stroke and normal samples. Methods: Differentially expressed miRNA (DEM) analysis was conducted using limma R Bioconductor package. Target genes of DEMs were identified from TargetScanHuman and miRTarBase databases. Functional enrichment analysis of the target genes was performed using clusterProfiler R Bioconductor package. The miRNA-based ischemic stroke diagnostic signature was constructed via logistic regression analysis. Results: Compared with the normal cohort, a total of 14 DEMs, including 5 up-regulated miRNAs and 9 down-regulated miRNAs, were identified in ischemic stroke patients. These DEMs have 1600 regulatory targets. Using a logistic regression model, the top five miRNAs were screened for constructing an miRNA-based ischemic stroke diagnostic signature. Using the miRNA–mRNA interaction pairs, two target genes (specificity protein 1 (SP1) and Argonaute 1 (AGO1)) were speculated to be the primary genes of ischemic stroke. Discussion and conclusion: Here, several potential miRNAs biomarkers were identified and an miRNA-based diagnostic signature for ischemic stroke was established, which can be a valuable reference for future clinical researches. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01448463
Volume :
40
Issue :
8
Database :
Complementary Index
Journal :
Bioscience Reports
Publication Type :
Academic Journal
Accession number :
145538763
Full Text :
https://doi.org/10.1042/BSR20201154