小RNA
荟萃分析
计算生物学
基因表达谱
小桶
生物
生物信息学
纤维化
基因表达
医学
病理
基因
转录组
遗传学
作者
Alieh Gholaminejad,Hossein Abdul Tehrani,Mohammad Gholami Fesharaki
出处
期刊:Biomarkers
[Informa]
日期:2018-10-16
卷期号:23 (8): 713-724
被引量:30
标识
DOI:10.1080/1354750x.2018.1488275
摘要
The prognostic, diagnostic and therapeutic value of microRNA (miRNA) expression aberrations in renal fibrosis has been studied in recent years. However, the miRNA expression profiling efforts have led to inconsistent results between the studies. The aim of this study was to perform a meta-analysis on the renal fibrosis miRNA expression profiling studies to identify candidate diagnostic biomarkers. We performed comprehensive literature searches in several databases to identify miRNA expression studies of renal fibrosis in animal models and humans. The miRNAs expression data were extracted from 20 included studies, and both miRNA vote-counting strategy and Robust Rank Aggregation method were utilized to identify significant miRNA meta-signatures. The predicted and validated targets of miRNA meta-signature were obtained by using MultiMiR package in 11 databases. Then a gene set enrichment analysis (KEGG, PANTHER pathways and GO processes) were carried out with GeneCodis web tool to recognize pathways that are most strongly influenced by modified expressions of these miRNAs. We recognized in both meta-analysis approaches a significant miRNA meta-signature of five up-regulated (miR-142-3p, miR-223-3p, miR-21-5p, miR-142-5p and miR-214-3p) and two down-regulated (miR-29c-3p and miR-200a-3p) miRNAs. Enrichment analysis confirmed that miRNA meta-signature cooperatively target functionally related genes in signalling and developmental pathways in renal fibrosis. This meta-analysis identified seven highly significant and consistently dysregulated miRNAs from 20 datasets, as the focus of future investigations to discover their potential influence to renal fibrosis and their clinical utility as biomarkers and/or as therapeutic mediators against chronic kidney disease..
科研通智能强力驱动
Strongly Powered by AbleSci AI