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

ALS RNA-seq amyotrophic lateral sclerosis biomarker non-coding RNA

Journal

Brain communications
ISSN: 2632-1297
Titre abrégé: Brain Commun
Pays: England
ID NLM: 101755125

Informations de publication

Date de publication:
2020
Historique:
entrez: 3 7 2020
pubmed: 3 7 2020
medline: 3 7 2020
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 32613197
doi: 10.1093/braincomms/fcaa053
pmc: PMC7329382
mid: EMS86669
doi:

Types de publication

Journal Article

Langues

eng

Pagination

fcaa053

Subventions

Organisme : Motor Neurone Disease Association
ID : TURNER/OCT18/989-797
Pays : United Kingdom
Organisme : Motor Neurone Disease Association
ID : HAFEZPARAST/APR15/836-791
Pays : United Kingdom
Organisme : Motor Neurone Disease Association
ID : HAFEZPARAST/APR18/861-791
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/K01014X/1
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Motor Neurone Disease Association
ID : MALASPINA/APR13/817-791
Pays : United Kingdom

Déclaration de conflit d'intérêts

Competing Interests The authors report no competing interests.

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Auteurs

Greig Joilin (G)

School of Life Sciences, University of Sussex, Falmer, Brighton, UK.

Elizabeth Gray (E)

Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.

Alexander G Thompson (AG)

Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.

Yoana Bobeva (Y)

Centre for Neuroscience and Trauma, Blizard Institute, Queen Mary University of London, London, UK.

Kevin Talbot (K)

Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.

Jochen Weishaupt (J)

Department of Neurology, University of Ulm, Ulm, Germany.

Albert Ludolph (A)

Department of Neurology, University of Ulm, Ulm, Germany.

Andrea Malaspina (A)

Centre for Neuroscience and Trauma, Blizard Institute, Queen Mary University of London, London, UK.

P Nigel Leigh (PN)

Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK.

Sarah F Newbury (SF)

Department of Clinical and Experimental Medicine, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK.

Martin R Turner (MR)

Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.

Majid Hafezparast (M)

School of Life Sciences, University of Sussex, Falmer, Brighton, UK.

Classifications MeSH