Identification of candidate microRNA biomarkers in diabetic nephropathy: a meta-analysis of profiling studies

J Nephrol. 2018 Dec;31(6):813-831. doi: 10.1007/s40620-018-0511-5. Epub 2018 Jul 17.

Abstract

Aims: The aim was to perform a meta-analysis on the miRNA expression profiling studies in diabetic nephropathy (DN) to identify candidate diagnostic biomarkers.

Methods: A comprehensive literature search was done in several databases and 53 DN miRNA expression studies were selected. To identify significant DN-miR meta-signatures, two meta-analysis methods were employed: vote-counting strategy and the robust rank aggregation method. The targets of DN-miRs were obtained and a gene set enrichment analysis was carried out to identify the pathways most strongly affected by dysregulation of these miRNAs.

Results: We identified a significant miRNA meta-signature common to both meta-analysis approaches of three up-regulated (miR-21-5p, miR-146a-5p, miR-10a-5p) and two down-regulated (miR-25-3p and miR-26a-5p) miRNAs. Besides that, subgroup analyses divided and compared the differentially expressed miRNAs according to species (human and animal), types of diabetes (T1DN and T2DN) and tissue types (kidney, blood and urine). Enrichment analysis confirmed that DN-miRs supportively target functionally related genes in signaling and community pathways in DN.

Conclusion: Five highly significant and consistently dysregulated miRNAs were identified, and future studies should focus on discovering their potential effect on DN and their clinical value as DN biomarkers and therapeutic mediators.

Publication types

  • Meta-Analysis
  • Review

MeSH terms

  • Diabetic Nephropathies / diagnosis
  • Diabetic Nephropathies / genetics*
  • Diabetic Nephropathies / metabolism
  • Disease Progression
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation
  • Genetic Markers
  • Humans
  • MicroRNAs / genetics*
  • MicroRNAs / metabolism
  • Signal Transduction
  • Transcriptome*

Substances

  • Genetic Markers
  • MicroRNAs