To identify dysregulated microRNAs in patients with ALS compared to controls.

ALS is a neurodegenerative disease characterized by degeneration of upper and lower motor neurons. The diagnosis is challenging and is delayed due to a lack of adequate tools. Currently, circulating microRNAs have evidence in their favor as diagnostic biomarkers in ALS.

We performed a systematic review and conducted a database search in PubMed, Embase, Scopus, and Web of Science until July 2021. We included articles about patients with ALS diagnosed by Revised El Escorial Criteria, who measure the expression of microRNA and compare it with controls. On the other hand, we excluded articles based on animal models, reviews, letters, and articles with no complete text. We used two independent reviewers for article selection, quality assessment, and data extraction. We used the BIOCROSS (biomarker-based cross-sectional studies) tool to assess the risk of bias. We conducted the bioinformatic analysis using the DIANA tools mirPath v.3.0 software.

We included 24 original articles and identified 23 microRNAs repeated twice or more times in the articles, showing consistency and significant expression in ALS patients compared to controls. From these 23 miRNAs, 10 were up-regulated (hsa-miR-338-3p, hsa-miR-100, hsa-miR-206, hsa-miR-133a/b, hsa-miR-31, hsa-miR-34c, hsa-miR-424, hsa-miR-36073p, and  hsa-miR-542-3p) and 13 were down-regulated (hsa-miR-451,  hsa-miR-638, hsa-miR-149, hsa-miR183, hsa-miR-3613-5p, hsa-miR-425-5p, hsa-miR-30c-5p, hsa-let-7a, hsa-miR-26b-5p, hsa-let-7f-5p, hsa-miR-409-3p, hsa-miR-148b-3p, and hsa-miR584-5p). Bioinformatic analysis suggests these microRNAs are involved with three genetic pathways: prion disease, fatty acid synthesis, and fatty acid metabolism.

The 23 microRNA we identified might be the beginning of a panel to diagnose ALS in its early stages. The genetic pathways shown in the bioinformatic analysis can provide clues to the pathophysiology of ALS. In addition, there is a need to conduct more studies regarding the potential of miRNAs as biomarkers; these studies should be standardized to avoid variability among them.