Background: Translational research on miRNAs develops reliable biomarkers for diagnosis and prognosis of renal diseases. Bioinformatic analyses and systems biology could drive the research for knowing new informative miRNA targets.
Objectives: This study proposes an approach to identify miRNA specific significant target genes, and single nucleotide polymorphisms (SNPs) associated with renal pathophysiology.
Methods: miRNAs were selected after removing duplicity, on the basis of techniques used, and disease spectrum width score. Target genes were predicted from different databases like miRWalk, miRTarBase, and DIANA-TarBase. SNPs were prioritized on the basis of target score and conserved energy score available in MirSNP database. miRNAs were characterized as “specific”, “strong”, “likely”, “unlikely”, and “irrelevant” biomarkers. PCR-SSP based genotyping was carried out to access the molecular profiling of hsa-miR-192 and TGF-β1 followed by quantitative real time PCR to analyze expression level of TGF-β1. The relative expression levels of mRNAs were analyzed by 2-ΔΔCt method.
Results: 170 renal associated miRNAs were found to be up-regulated, down-regulated or differentially expressed. Noticeably hsa-miR-192-3p expression was reported in nine diseases. 117 genes were associated with basic kidney diseases and end stage renal disease (ESRD). Threshold > 80% for 93 target genes was observed from mirSVR. Mutant genotypes for hsa-miR-192 (OR=4.64, p-value ≤ 0.0001) and its corresponding target gene TGF-β1 (OR = 0.70, p-value = 0.0351) showed susceptible association with ESRD. More so, patients possessing mutant allele of TGF-β1 showed elevated mRNA expression (Fold change = 9.83).
Conclusion: Study proposed a new approach to identify specific miRNA biomarkers for particular diseases with corresponding target genes and SNPs and also highlighted the importance of hsa-miR- 192 in renal diseases.