The potential diagnostic accuracy of circulating microRNAs for Alzheimer's disease: A meta-analysis

Abstract

Background & objective

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease that seriously affects cognitive ability and has become a key public health problem. Many studies have identified the possibility of peripheral blood microRNA as effective non-invasive biomarkers for AD diagnosis, but the results are inconsistent. Therefore, we carried out this meta-analysis to evaluate the diagnostic accuracy of circulating microRNAs in the diagnosis of AD patients.

Methods

We performed a systematic literature search of the following databases: PubMed, EMBASE, Web of Science, Cochrane Library, Wanfang database and China National Knowledge Infrastructure, updated to March 15, 2021. A random effects model was used to pool the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the curve. Meta-regression and subgroup analysis were performed to explore the sources of heterogeneity, and Deeks’ funnel plot was used to assess whether there was publication bias.

Results

62 studies from 18 articles were included in this meta-analysis. The pooled sensitivity was 0.82 (95% CI: 0.78–0.85), specificity was 0.80 (95% CI: 0.76–0.83), PLR was 4. 1 (95% CI: 3.4–4.9), NLR was 0.23 (95% CI: 0.19–0.28), DOR was 18 (95% CI: 13–25) and AUC was 0.88 (95% CI: 0.84–0.90). Subgroup analysis shows that the microRNA clusters of plasma type performed a better diagnostic accuracy of AD patients. In addition, publication bias was not found.

Conclusions

Circulating microRNAs can be used as a promising non-invasive biomarker in AD diagnosis.