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
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.