Identification of novel microRNAs associated with type 2 diabetes by an integrative bioinformatic analysis

Abstract

To identify potential miRNAs involved in the development/progression of type 2 diabetes (T2D) we performed data screening and integration of microRNA (miRNA) and messenger RNA (mRNA) expression profiles available in public data repositories. We retrieved two independent sequencing datasets: GSE52314 (small RNA-Seq) and GSE50244 (RNA-Seq). Then, we identified Differentially Expressed Genes (DEGs) and Differentially Expressed miRNAs (DEMs) from non-diabetic (ND) vs. people with T2D. The integrative analysis of identified DEGs and DEMs revealed 303 interactions involving 33 miRNAs and 256 genes. Functional enrichment analysis showed these interactions could play a functional role in carbohydrate, lipid, and nucleotide impaired metabolism. Some interactions we identified could also be relevant at an early stage of T2D. We also performed a similar integration analysis using a single study from a rat model, including both RNA-Seq and small RNA-Seq in the same pancreatic tissue: CRA000791. Interestingly, in this analysis one identified miRNA was also identified in the integrative analysis in human transcriptome: hsa-miR-27a-5p. Moreover, functional enrichment analysis showed that the target genes are mainly enriched in biological processes and pathways related to lipid and nucleotide metabolism. The miRNAs and interactions we identified could be relevant to gene expression regulation in T2D. Although further validation is necessary for extensive use in clinics, they provide new and useful knowledge to develop potential novel strategies for early diagnosis, prevention, and treatment of T2D.