Evidence map›Paper›PMID 42901869›Full record

ArticleJournal of cachexia, sarcopenia and muscle2026

Plasma Proteomic Signatures Predict Incident Amyotrophic Lateral Sclerosis: A Prospective Study Stratified by C9orf72 Expansion.

Wei-Ming Su, Qing-Qing Duan, Nan Zhang, Sheng-Yi He, Ru-Yin Liu, Xiang-Jin Wen, Xiao-Jing Gu, Yi Wang, Bei Cao, Yong-Ping Chen

Abstract read
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Wei-Ming SuDepartment of Neurology and Institute of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID https://orcid.org/0000-0001-7935-4159
Qing-Qing DuanDepartment of Neurology and Institute of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Nan ZhangDepartment of Neurology and Institute of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID https://orcid.org/0009-0005-9708-5999
Sheng-Yi HeDepartment of Neurology and Institute of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Ru-Yin LiuDepartment of Neurology and Institute of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Xiang-Jin WenDepartment of Neurology and Institute of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID https://orcid.org/0009-0005-6402-7821
Xiao-Jing GuMental Health Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Yi WangDepartment of Pathophysiology, West China College of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, Sichuan, China.
Bei CaoDepartment of Neurology and Institute of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID https://orcid.org/0009-0003-3857-7235
Yong-Ping ChenDepartment of Neurology and Institute of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID https://orcid.org/0000-0002-5603-4192

Funding

the 1·3·5 project for disciplines of excellence Clinical Research Fund, West China Hospital, Sichuan University 2023HXFH032the National Key Research and Development Program of China 2022YFC2703101the National Natural Science Fund of China 82371422the Science and Technology Bureau Fund of Sichuan Province 2026NSFSC0510
6 · The paper itself

Abstract

backgroundAmyotrophic lateral sclerosis (ALS) is a progressive and fatal neurological disorder for which reliable preclinical biomarkers to predict disease onset are currently lacking. Plasma proteomics offers a promising avenue for early detection. The identification of plasma proteins and pathways associated with incident ALS holds potential to improve early diagnosis, enable risk stratification and provide insights into disease mechanisms.

methodsEmploying the Olink Explore platform, we quantified 2920 plasma proteins within a prospective cohort of UK Biobank participants. Multivariate Cox proportional hazards regression was utilized to identify proteins associated with incident generalized ALS, C9-ALS (C9orf72-associated ALS) and non-C9-ALS. Enrichment analysis was conducted to delineate the biological pathways implicated by the identified proteins. Associations between plasma protein levels and the age at onset (AAO) of ALS were assessed via linear regression, while a multivariate Cox model was employed to evaluate the relationships between protein levels and ALS survival. We subsequently assessed potential causal relationships using Mendelian randomization (MR) and colocalization and analysed protein cross-sectional temporal patterns in ALS.

resultsIn this prospective cohort study, we followed 52 584 participants from the UK Biobank for a mean of 11.8 years. During this period, 291 (0.55%) incident cases of ALS were identified, among whom 34 individuals carried the C9orf72 hexanucleotide repeat expansion mutation. Nine proteins demonstrated associations with all-type ALS risk (FDR < 0.05): NEFL (HR: 2.897), CSRP3 (HR: 1.233), MYBPC1 (HR: 1.352), MEGF10 (HR: 1.744), MYOM3 (HR: 1.289) and THBS4 (HR: 1.570) were identified as risk factors, whereas EGFLAM (HR: 0.402), ITGAV (HR: 0.284) and CD248 (HR: 0.573) exhibited protective effects. NEFL (HR: 2.742) and three additional proteins were primarily associated with non-C9-ALS, while only NEFL (HR: 4.403) and COL5A1 (HR: 3.072) showed significant associations with C9-ALS. When combined with age and sex, these proteins yielded area under the curve (AUC) values exceeding 0.750 for predicting ALS at 3, 5 and 10 years. Furthermore, elevated NEFL levels were correlated with an earlier onset of non-C9-ALS and began to increase approximately 9.27 years prior to diagnosis, reaching a peak 1-2 years before clinical presentation in non-C9ALS cases via cross-sectional temporal analysis. Pathway analysis implicated muscle-related, extracellular matrix, energy metabolism and inflammatory pathways.

conclusionsThis investigation uncovers extensive alterations in plasma proteins associated with ALS risk, revealing potential novel biomarkers for both sporadic and C9orf72-linked forms of the disease. These results enhance our comprehension of early ALS pathogenesis and provide a foundation for subsequent biomarker identification and the development of targeted therapeutic strategies.

Indexed as

Amyotrophic Lateral SclerosisC9orf72 ProteinProteomicsAgedBiomarkersDNA Repeat ExpansionFemaleHumansIncidenceMaleMiddle AgedProspective StudiesBiomarkersC9orf72 ProteinC9orf72 protein, humanamyotrophic lateral sclerosisC9orf72NEFLplasma proteomicsrisk prediction

Identifiers

PMID42901869
PMCPMC13683052

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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.