The Role of MicroRNA in Diagnosis of Huntington's Disease: A Systematic Review.

Huntington's disease (HD) is an autosomal dominant genetic neurodegenerative disorder with features of progressive motor, cognitive, and psychiatric dysfunction. Current diagnosis relies largely on clinical presentation and genetic testing but lacks sensitivity to early disease diagnosis or progression monitoring. MicroRNAs (miRNAs) are short non-coding RNA molecules that regulate gene expression post-transcriptionally. They are increasingly being investigated as potential diagnostic biomarkers, especially given their detectability in biofluids like plasma and cerebrospinal fluid. This review aimed to evaluate the clinical utility of miRNAs in HD, specifically defining their roles not as primary diagnostic screeners, but as dynamic biomarkers for predicting clinical conversion in premanifest individuals, tracking disease progression, and monitoring therapeutic responses. A comprehensive literature search was conducted in Medline, Embase, PubMed, Scopus, Cochrane, and ClinicalTrials.gov up to November 2024. Studies written in English including human subjects or HD models quantifying miRNA expression level for diagnostic purposes were included in this systematic review. Data was extracted onto a standard form and quality assessed with the MINORS and Cochrane tools. Thirty studies with 1889 participants were included. Dysregulated miRNAs that had been repeatedly identified in HD were miRNA-9, miRNA-124, miRNA-214, miRNA-146a, and miRNA-10b. Remarkably, Romano et al. have attained 88% sensitivity and 92% specificity for SNORD13 in plasma, and Chang et al. have achieved AUC > 0.90 for a multi-miRNA panel. While promising trends, high heterogeneity of methods and incomplete reporting of diagnostic metrics limited meta-analysis. miRNAs, particularly exosome-derived ones, possess great potential as minimally invasive biomarkers for HD diagnosis. However, while current evidence strongly supports this biomarker potential, immediate clinical implementation is not yet feasible. Future studies must resolve ongoing challenges in assay standardization, cross-cohort external validation, and integration with clinical and imaging data before clinical deployment can be realized.