Henderson, B. W.; Roberts, B. S.; Kolodziejczak, S.; Cohcran, M.; Myers, R. M.

Amyotrophic lateral sclerosis (ALS) is a devastating and fatal neurodegenerative disease with no current therapeutic to modify disease progression. Reliable biomarkers for ALS are essential for improving diagnosis and evaluating therapeutic efficacy. We combined small-RNA sequencing from a discovery cohort of ALS patients and healthy controls with sequencing data from a previously published ALS cohort to identify candidate biomarkers. Machine learning analysis identified hsa-miR-206 as a strong classifier of ALS status in both cohorts. This finding was validated in an independent ALS cohort using droplet digital PCR (ddPCR), confirming the biomarkers sensitivity and specificity in identifying ALS. Importantly, hsa-miR-206 also displayed high accuracy in differentiating ALS from Parkinsons disease. These results further validate hsa-miR-206 as a circulating small-RNA biomarker for ALS with potential utility in diagnosis and therapeutic monitoring. Further studies in larger, diverse cohorts will be needed to validate its clinical applicability.