Identification of a potential non-coding RNA biomarker signature for amyotrophic lateral sclerosis

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 incl...

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Main Authors: Joilin, Greig (Author) , Gray, Elizabeth (Author) , Thompson, Alexander G. (Author) , Bobeva, Yoana (Author) , Talbot, Kevin (Author) , Weishaupt, Jochen H. (Author) , Ludolph, Albert C. (Author) , Malaspina, Andrea (Author) , Leigh, P. Nigel (Author) , Newbury, Sarah F. (Author) , Turner, Martin R. (Author) , Hafezparast, Majid (Author)
Format: Article (Journal)
Language:English
Published: June 17, 2020
In: Brain communications
Year: 2020, Volume: 2, Issue: 1, Pages: 1-14
ISSN:2632-1297
Online Access: Get full text
Author Notes:Greig Joilin, Elizabeth Gray, Alexander G. Thompson, Yoana Bobeva, Kevin Talbot, Jochen Weishaupt, Albert Ludolph, Andrea Malaspina, P. Nigel Leigh, Sarah F. Newbury, Martin R. Turner and Majid Hafezparast

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520 |a 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. 
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