MicroRNAs in Parkinson's disease: a systematic review and diagnostic accuracy meta-analysis

Abstract

Current clinical tests for Parkinson's disease (PD) provide insufficient diagnostic accuracy leading to an urgent need for improved diagnostic biomarkers. As microRNAs (miRNAs) are promising biomarkers of various diseases, including PD, this systematic review and meta-analysis aimed to assess the diagnostic accuracy of biofluid miRNAs in PD. All studies reporting data on miRNAs expression in PD patients compared to controls were included. Gene targets and significant pathways associated with miRNAs expressed in more than 3 biofluid studies with the same direction of change were analyzed using target prediction and enrichment analysis. A bivariate model was used to calculate sensitivity, specificity, likelihood ratios, and diagnostic odds ratio. While miR-24-3p and miR-214-3p were the most reported miRNA (7 each), miR-331-5p was found to be consistently up regulated in 4 different biofluids. Importantly, miR-19b-3p, miR-24-3p, miR-146a-5p, and miR-221-3p were reported in multiple studies without conflicting directions of change in serum and bioinformatic analysis found the targets of these miRNAs to be associated with pathways important in PD pathology. Of the 102 studies from the systematic review, 15 studies reported sensitivity and specificity data on combinations of miRNAs and were pooled for meta-analysis. Studies (17) reporting sensitivity and specificity data on single microRNA were pooled in a separate meta-analysis. Meta-analysis of the combinations of miRNAs (15 studies) showed that biofluid miRNAs can discriminate between PD patients and controls with good diagnostic accuracy (sensitivity = 0.82, 95% CI 0.76-0.87; specificity = 0.80, 95% CI 0.74-0.84; AUC = 0.87, 95% CI 0.83-0.89). However, we found multiple studies included more males with PD than any other group therefore possibly introducing a sex-related selection bias. Overall, our study captures key miRNAs which may represent a point of focus for future studies and the development of diagnostic panels whilst also highlighting the importance of appropriate study design to develop representative biomarker panels for the diagnosis of PD.

Figure 1

The PRISMA flow chart showing study identification and inclusion and exclusion criteria for all studies included in the systematic review and meta-analyses.

Figure 2

Bioinformatic analysis of key biofluid-derived microRNAs. Top enriched pathways (Fisher exact test p < 0.05) associated with (a) most consistent miRNA across biofluids, miR-331-5p (b) most reported miRNA, miR-24-3p and miR-214-3p and (c) miRNA reported without conflicting direction of change, miR-19b-3p, miR-24-3p, miR-146a-5p, and miR-221-3p and (d) Venn Diagram showing the target genes regulated by the key biofluid-derived microRNAs. Overlapping target genes: CCND2 (Cyclin D2), CDK6 (Cyclin Dependent Kinase 6), CDNKN1A (cyclin dependent kinase inhibitor 1A) and MDM2 (Mouse Double Minute 2).

Figure 3

Diagnostic accuracy indices for meta-analysis of the combinations of miRNAs. (a) sensitivity and specificity of biofluid-derived microRNAs with corresponding estimates for heterogeneity I2 tests (n = 15 studies). The sensitivity or specificity for each study is represented by the black circles in the grey square and the 95% confidence interval for each study is represented by the associated horizontal lines. (b) positive and negative likelihood ratios: PLR/NLR is represented by the black circles in the grey squares and the 95% confidence interval for each study is represented by the associated horizontal lines (c) diagnostic score and diagnostic odds ratio: the diagnostic score/DOR are represented by the black circles in the grey squares and the 95% confidence interval for each study is represented by the associated horizontal lines. The pooled estimate is represented by the diamonds with the horizontal edges of the diamonds reflecting the 95% confidence interval. The red dotted line represents the pooled average point estimate. The studies are ordered by biofluid type: Serum^–, Plasma^–, CSF^,, PBMC and Saliva. (d) Summary Receiver Operating Characteristic curve of biofluid-derived microRNAs in PD patients compared to controls (n = 15 studies). The red filled diamond represents the summary estimate of the test accuracy, and the dotted line denoting the 95% confidence region around this estimate. The circles represent each study involved in the meta-analysis: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15.

Figure 4

Model diagnostics to assess suitability and robustness of the bivariate model. Graphical representation of (a) goodness of fit (quantile plot of residual) (b) bivariate normality (Chi-squared probability plot of squared Mahalanobis distances), (c) influence analysis (spike plot using Cook’s distance; threshold = 4/n where n is the total number of data points;) and (d) outlier detection (scatter plot using standardized predicted random effects); yellow: = study outside the 95% boundaries and may be considered as an outlier. These analyses were conducted on biofluid-derived microRNAs from PD patients and controls (n = 15 studies). The circles represent each study involved in the meta-analysis: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 and 15.

Figure 5

Meta-regression analysis and subgroup analysis (a) Meta-regression analysis of study characteristics to identify potential sources of heterogeneity in sensitivity and specificity of biofluid-derived microRNAs from PD patients and controls. Sensitivity and specificity of each study characteristic is represented by the red dot with the corresponding horizontal line showing 95% confidence interval. Vertical line represents the average point estimate. *p < 0.05, **p < 0.01, ***p < 0.001. (b) Bar graph showing sex distribution of the groups studied in the systematic review: mean sample size and 95% CI for each group (blue = male, orange = female). The horizontal dotted gray bar represents the mean average sample size for the 4 groups. ***p ≤ 0.001 Dunn’s post hoc tests.