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<jats:title>Abstract</jats:title> <jats:p>Objective biomarkers for the clinically heterogeneous adult-onset neurodegenerative disorder amyotrophic lateral sclerosis are crucial to facilitate assessing emerging therapeutics and improve the diagnostic pathway in what is a clinically heterogeneous syndrome. With non-coding RNA transcripts including microRNA, piwi-RNA and transfer RNA present in human biofluids, we sought to identify whether non-coding RNA in serum could be biomarkers for amyotrophic lateral sclerosis. Serum samples from our Oxford Study for Biomarkers in motor neurone disease/amyotrophic lateral sclerosis discovery cohort of amyotrophic lateral sclerosis patients (n = 48), disease mimics (n = 16) and age- and sex-matched healthy controls (n = 24) were profiled for non-coding RNA expression using RNA-sequencing, which showed a wide range of non-coding RNA to be dysregulated. We confirmed significant alterations with reverse transcription-quantitative PCR in the expression of hsa-miR-16-5p, hsa-miR-21-5p, hsa-miR-92a-3p, hsa-piR-33151, TRV-AAC4-1.1 and TRA-AGC6-1.1. Furthermore, hsa-miR-206, a previously identified amyotrophic lateral sclerosis biomarker, showed a binary-like pattern of expression in our samples. Using the expression of these non-coding RNA, we were able to discriminate amyotrophic lateral sclerosis samples from healthy controls in our discovery cohort using a random forest analysis with 93.7% accuracy with promise in predicting progression rate of patients. Importantly, cross-validation of this novel signature using a new geographically distinct cohort of samples from the United Kingdom and Germany with both amyotrophic lateral sclerosis and control samples (n = 156) yielded an accuracy of 73.9%. The high prediction accuracy of this non-coding RNA-based biomarker signature, even across heterogeneous cohorts, demonstrates the strength of our approach as a novel platform to identify and stratify amyotrophic lateral sclerosis patients.</jats:p>

Original publication

DOI

10.1093/braincomms/fcaa053

Type

Journal article

Journal

Brain Communications

Publisher

Oxford University Press (OUP)

Publication Date

01/01/2020

Volume

2