Evidence map›Paper›PMID 32613197›Full record

ArticleBrain communications2020

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

Greig Joilin, Elizabeth Gray, Alexander G Thompson, Yoana Bobeva, Kevin Talbot, Jochen Weishaupt, Albert Ludolph, Andrea Malaspina, P Nigel Leigh, Sarah F Newbury and 2 more

Open access · goldAbstract read
In one paragraph

Article in Brain communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 2 pooled it
3.2field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 2 syntheses or guidelines pooled it, 58 citations in OpenAlex.

  1. Exploring dysregulated miRNAs in ALS: implications for disease pathogenesis and early diagnosis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 5 institutions in 2 countries.

Greig JoilinSchool of Life Sciences, University of Sussex, Falmer, Brighton, UK.ORCID 0000-0001-5827-6382
Elizabeth GrayNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Alexander G ThompsonNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0003-1063-3277
Yoana BobevaCentre for Neuroscience and Trauma, Blizard Institute, Queen Mary University of London, London, UK.
Kevin TalbotNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0001-5490-1697
Jochen WeishauptDepartment of Neurology, University of Ulm, Ulm, Germany.
Albert LudolphDepartment of Neurology, University of Ulm, Ulm, Germany.
Andrea MalaspinaCentre for Neuroscience and Trauma, Blizard Institute, Queen Mary University of London, London, UK.
P Nigel LeighDepartment of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK.
Sarah F NewburyDepartment of Clinical and Experimental Medicine, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK.ORCID 0000-0002-1863-3258
Martin R TurnerNuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Majid HafezparastSchool of Life Sciences, University of Sussex, Falmer, Brighton, UK.ORCID 0000-0002-5262-7150
University of Oxford · GBBrighton and Sussex Medical School · GBQueen Mary University of London · GBUniversität Ulm · DEUniversity of Sussex · GB

Funding

Motor Neurone Disease Association MALASPINA/APR13/817-791Wellcome Trust
6 · The paper itself

Abstract

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.

Indexed as

ALSamyotrophic lateral sclerosisbiomarkernon-coding RNARNA-seq

Identifiers

PMID32613197
PMCPMC7329382
OpenAlexW3015778291

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.