A meta-analysis of microRNA expression profiling studies in heart failure

Abstract

Heart failure (HF) is a major consequence of many cardiovascular diseases with high rate of morbidity and mortality. Early diagnosis and prevention are hampered by the lack of informative biomarkers. The aim of this study was to perform a meta-analysis of the miRNA expression profiling studies in HF to identify novel candidate biomarkers or/and therapeutic targets. A comprehensive literature search of the PubMed for miRNA expression studies related to HF was carried out. The vote counting and robust rank aggregation meta-analysis methods were used to identify significant meta- signatures of HF-miRs. The targets of HF-miRs were identified, and network construction and gene set enrichment analysis (GSEA) were performed to identify the genes and cognitive pathways most affected by the dysregulation of the miRNAs. The literature search identified forty-five miRNA expression studies related to CHF. Shared meta-signature was identified for 3 up-regulated (miR-21, miR-214, and miR-27b) and 13 down-regulated (miR-133a, miR-29a, miR-29b, miR-451, miR-185, miR-133b, miR-30e, miR-30b, miR- 1, miR-150, miR- 486, miR-149, and miR-16-5p) miRNAs. Network properties showed miR-29a, miR- 21, miR-29b, miR-1, miR-16, miR- 133a, and miR-133b have the most degree centrality. GESA identified functionally related sets of genes in signaling and community pathways in HF that are the targets of HF-miRs. The miRNA expression meta-analysis identified sixteen highly significant HF-miRs that are differentially expressed in HF. Further validation in large patient cohorts is required to confirm the significance of these miRs as HF biomarkers and therapeutic targets.