Parkinson's disease (PD) is the second most common neurodegenerative disease, which still lacks a biomarker to aid in diagnosis and to differentiate diagnosis at the early stage of the disease. microRNAs (miRNAs) are small and evolutionary conserved non-coding RNAs that are involved in post-transcriptional gene regulation. Several miRNAs have been proposed as potential biomarkers in several diseases. In the present study, we screened miRNAs using a network vulnerability analysis, to evaluate their potential as PD biomarkers. We first extracted miRNAs that were differentially expressed between PD and healthy controls (HC) samples. Then we constructed the PD-specific miRNA-mRNA network and screened miRNA biomarkers using a new bioinformatics model. With this model, we identified miR-105-5p as a putative biomarker for PD. Moreover, we measured miR-105-5p levels in the plasma of patients with idiopathic PD (IPD) (n = 319), neurological disease controls (NDC, n = 305) and HC (n = 273) using reverse transcription real-time quantitative PCR (RT-qPCR). Our data clearly demonstrated that the plasma miR-105-5p level in IPD patients was significantly higher than those of HC (251%, p < 0.001) and NDC (347%, p < 0.001). There was no significant difference in miR-105-5p expression between IPD patients with or without anti-PD medications. Interestingly, we found that the plasma miR-105-5p expression level may be able to differentiate IPD from parkinsonian syndrome, essential tremor and other neurodegenerative diseases. We believe that a change in the plasma miR-105-5p level is a potential biomarker for IPD.
Keywords: bioinformatics model; biomarker; idiopathic Parkinson’s disease; microRNA-105-5p; network vulnerability analysis.