Background: Currently, depression is diagnosed on the basis of neuropsychological examinations and clinical symptoms, and there is no objective diagnostic method. Several studies have explored the application of microRNAs as potential biomarkers diagnostic for depression. This study aims to determine the diagnostic value of microRNAs for depression.
Methods: PubMed, Embase, the Cochrane Library, the Web of Science, Wanfang Database, SINOMED, China Science and Technology Journal Databaseand China National Knowledge Infrastructure were searched up to 11 January 2022. Stata (version 16.0) and RevMan (version 5.3) software were used for meta-analysis. The pooled sensitivity, pooled specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio (DOR) were calculated; the summary receiver operating characteristic (SROC) curve was plotted, and the area under the curve (AUC) was calculated. Moreover, meta-regression analyses were performed to determine the source of heterogeneity. Deeks' funnel plot test was used to assess publication bias.
Results: In total, 677 patients were enrolled, including 364 patients with depression and 313 healthy controls. Meta-analysis results showed that the pooled sensitivity, specificity, and DOR of microRNAs for the diagnosis of depression were 0.82 [95% confidence intervals(CI): 0.76, 0.87], 0.70 (95% CI: 0.62, 0.77), and 11 (95% CI: 6, 20), respectively, and the AUC of the SROC was 0.84 (95% CI: 0.80, 0.87).
Conclusions: MicroRNAs have high sensitivity and specificity in diagnosing depression and are potential diagnostic biomarkers for depression.
Registration number: PROSPERO CRD42022303616.
Keywords: Biomarker; Depression; Diagnostic value; Meta-analysis; microRNA.
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