Evidence map›Paper›PMID 42509371›Full record

ArticleNature medicine2026

Longitudinal plasma proteomics predict phenoconversion to clinically manifest ALS.

Ximing Ran, Joanne Wuu, Zhaohui S Qin, Michael P McDermott, Johnathan Cooper-Knock, Yindi Li, Volkan Granit, Anne-Laure Grignon, Elizabeth Lin, Maria Catalina Fernandez and 6 more

Abstract read
In one paragraph

Article in Nature medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Ximing Ran *Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA.ORCID http://orcid.org/0009-0004-5414-1885
Joanne Wuu *Department of Neurology and ALS Center, University of Miami Miller School of Medicine, Miami, FL, USA.ORCID http://orcid.org/0009-0005-9643-9855
Zhaohui S QinDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA.ORCID http://orcid.org/0000-0002-1583-146X
Michael P McDermottDepartment of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Johnathan Cooper-KnockSheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0002-0873-8689
Yindi LiDepartment of Neurology and ALS Center, University of Miami Miller School of Medicine, Miami, FL, USA.
Volkan GranitDepartment of Neurology and ALS Center, University of Miami Miller School of Medicine, Miami, FL, USA.ORCID http://orcid.org/0000-0002-6519-7225
Anne-Laure GrignonDepartment of Neurology and ALS Center, University of Miami Miller School of Medicine, Miami, FL, USA.
Elizabeth LinDepartment of Neuromuscular Diseases, UCL Queen Square Motor Neuron Disease Center, UCL Queen Square Institute of Neurology, University College London, London, UK.ORCID http://orcid.org/0009-0007-7739-8714
Maria Catalina FernandezDepartment of Neurology and ALS Center, University of Miami Miller School of Medicine, Miami, FL, USA.ORCID http://orcid.org/0009-0001-0408-151X
Danielle ColatoDepartment of Neurology and ALS Center, University of Miami Miller School of Medicine, Miami, FL, USA.ORCID http://orcid.org/0009-0004-4068-1629
Nathan CarberryDepartment of Neurology and ALS Center, University of Miami Miller School of Medicine, Miami, FL, USA.
Christina M LillInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.ORCID http://orcid.org/0000-0002-2805-1307
Paolo PiazzaNuffield Department of Medicine, Centre for Human Genetics, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-3736-1841
Andrea MalaspinaDepartment of Neuromuscular Diseases, UCL Queen Square Motor Neuron Disease Center, UCL Queen Square Institute of Neurology, University College London, London, UK.ORCID http://orcid.org/0000-0002-8020-7567
Michael BenatarDepartment of Neurology and ALS Center, University of Miami Miller School of Medicine, Miami, FL, USA. mbenatar@med.miami.edu.ORCID http://orcid.org/0000-0003-4241-5135

Funding

Uncovering new genes and disease modifiers for ALS and related disordersU54NS092091 · NINDS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI Michael Benatar · 2014 to 2026
$19.8M
Pre-Symptomatic Familial ALS (Pre-fALS) Study - Prelude to a Treatment Trial; Administrative SupplementR01NS105479 · NINDS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI BENATAR, MICHAEL, WUU, JOANNE · 2018 to 2022
$3.0M
Amyotrophic Lateral Sclerosis Association (ALS Association) 2015, 16-TACL-242Muscular Dystrophy Association (Muscular Dystrophy Association Inc.) 4365, 172123NINDS NIH HHS R01 NS105479NINDS NIH HHS U54 NS092091U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01 NS105479U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01 NS105479, U54 NS092091
6 · The paper itself

Abstract

The study of pre-symptomatic amyotrophic lateral sclerosis (ALS) and the design of disease prevention trials are greatly hampered by our inability to predict which unaffected carriers of ALS-associated pathogenic variants will phenoconvert to clinically manifest disease and when. In this longitudinal Olink Explore, high-throughput, proteomic study, 516 serially collected plasma samples from 33 phenoconverters, 35 patients with ALS, 10 pre-symptomatic pathogenic variant carriers and 59 controls were included. Here we identified 92 proteins with concentrations that changed before phenoconversion; characterized the longitudinal trajectory of these proteins and identified a core panel of 19 proteins which, collectively, predicted phenoconversion over the 0.5-year to 5-year time horizons (crossvalidated areas under the curve 0.80-0.89) and yielded estimates of time to phenoconversion with a mean absolute error of 1.6 years. These findings were partially replicated in UK Biobank data, confirming pre-symptomatic increases in several proteins (for example, NEFL, EDA2R and CA3) and that a multi-protein panel outperformed NEFL alone in estimating time to phenoconversion. This work sheds light on the biology of pre-symptomatic ALS. Moreover, our identification of a panel of new susceptibility/risk biomarkers based on empirical longitudinal data furthers the ultimate goal of ALS prevention.

Indexed as

Amyotrophic Lateral SclerosisProteomicsAgedBiomarkersDisease ProgressionFemaleHumansLongitudinal StudiesMaleMiddle AgedBiomarkers

Identifiers

PMID42509371
PMCPMC13577924

What OpenQuestion holds

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Registered trials

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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.