Circulating microRNAs as potential biomarkers for the diagnosis of Parkinson's disease: A meta-analysis

Abstract

Background and objective

Parkinson's disease (PD) is the one of the most common neurodegenerative diseases. Many investigators have confirmed the possibility of using circulating miRNAs to diagnose PD. However, the results were inconsistent. Therefore, the aim of this meta-analysis was to systematically evaluate the diagnostic accuracy of circulating miRNAs in the diagnosis of PD.

Methods

We carefully searched PubMed, Embase, Web of Science, Cochrane Library, Wanfang database and China National Knowledge Infrastructure for relevant studies (up to January 1, 2022) based on PRISMA statement. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), the diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated to test the diagnostic accuracy. Furthermore, subgroup analyses were performed to identify the potential sources of heterogeneity, and the Deeks’ funnel plot asymmetry test was used to evaluate the potential publication bias.

Results

Forty-four eligible studies from 16 articles (3298 PD patients and 2529 healthy controls) were included in the current meta-analysis. The pooled sensitivity was 0.79 (95% CI: 0.76–0.81), specificity was 0.82 (95% CI: 0.78–0.84), PLR was 4.3 (95% CI: 3.6–5.0), NLR was 0.26 (95% CI: 0.23–0.30), DOR was 16 (95% CI: 13–21), and AUC was 0.87 (95% CI: 0.84–0.90). Subgroup analysis suggested that miRNA cluster showed a better diagnostic accuracy than miRNA simple. Moreover, there was no significant publication bias.

Conclusions

Circulating miRNAs have great potential as novel non-invasive biomarkers for PD diagnosis.