Evidence map›Paper›PMID 40909834›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

Jan Homann, Roxanna Korologou-Linden, Vivian Viallon, Sarah Morgan, Valerija Dobricic, Laura Deecke, Julia P Schessner, Karl Smith-Byrne, Daniel Birtles, Yujia Zhao and 36 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

46 authors.

Jan HomannInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.
Roxanna Korologou-LindenAgeing and Epidemiology Unit (AGE), School of Public Health, Imperial College London, London, UK.
Vivian ViallonInternational Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, Lyon, France.
Sarah MorganCentre for Neuroscience, Surgery and Trauma, Blizard Institute, Queen Mary University of London, London, UK.
Valerija DobricicLübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany.
Laura DeeckeInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.
Julia P SchessnerDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
Karl Smith-ByrneCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID 0000-0002-1932-7463
Daniel BirtlesCentre for Neuroscience, Surgery and Trauma, Blizard Institute, Queen Mary University of London, London, UK.
Yujia ZhaoInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands.
Joanne WuuDepartment of Neurology and the ALS Center, University of Miami, Miami, FL, USA.
Fanny ArtaudUniversité Paris-Saclay, UVSQ, Inserm, Gustave Roussy, CESP, Villejuif, France.
Fatema HajizadahCentre for Neuroscience, Surgery and Trauma, Blizard Institute, Queen Mary University of London, London, UK.
Jose Maria HuertaDepartment of Epidemiology, Murcia Regional Health Council, Biomedical Research Institute of Murcia-IMIB, Murcia, Spain.
Olena OhleiInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.
Mikhail LebedevDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
P Martijn KolijnInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands.
Marcela GuevaraCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Ana Jimenez-ZabalaBiogipuzkoa Health Research Institute, San Sebastian, Gipuzkoa, Spain.
María José SánchezCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Camino Trobajo-SanmartínCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Sandra M Colorado-YoharDepartment of Epidemiology, Murcia Regional Health Council, Biomedical Research Institute of Murcia-IMIB, Murcia, Spain.
Sonia Alonso-MartínBiogipuzkoa Health Research Institute, San Sebastian, Gipuzkoa, Spain.
Dafina PetrovaCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Sabina SieriEpidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori Di Milano Via Venezian, Milan, Italy.
Klaus BergerInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.
Susan PetersInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands.
Nick WarehamMedical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK.
Rudolph KaaksDivision of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.ORCID 0000-0003-3751-3929
Ruth C TravisCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Roel C H VermeulenInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands.
Global Neurodegeneration Proteomics Consortium (GNPC)
Ioanna TzoulakiDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.ORCID 0000-0002-4275-9328
Alexis ElbazUniversité Paris-Saclay, UVSQ, Inserm, Gustave Roussy, CESP, Villejuif, France.ORCID 0000-0001-9724-5490
Matthias MannDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
Carlotta SacerdoteDepartment of Health Sciences, University of Eastern Piedmont, Novara, Italy.
Giovanna MasalaClinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy.
Verena KatzkeDivision of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.
Michael BenatarDepartment of Neurology and the ALS Center, University of Miami, Miami, FL, USA.
Lars BertramLübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany.ORCID 0000-0002-0108-124X
Lefkos MiddletonAgeing and Epidemiology Unit (AGE), School of Public Health, Imperial College London, London, UK.
Elio RiboliAgeing and Epidemiology Unit (AGE), School of Public Health, Imperial College London, London, UK.
Marc J GunterDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Pietro FerrariInternational Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, Lyon, France.
Oliver RobinsonAgeing and Epidemiology Unit (AGE), School of Public Health, Imperial College London, London, UK.
Christina M LillInstitute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.ORCID 0000-0002-2805-1307

Funding

Uncovering new genes and disease modifiers for ALS and related disordersU54NS092091 · NINDS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI Corey T McMillan · 2014 to 2026
$19.8M
NINDS NIH HHS U54 NS092091
6 · The paper itself

Abstract

Background: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. Methods: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). Findings: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson's and Alzheimer's disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. Interpretation: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention. Funding: Clinical Research in ALS and Related Disorders for Therapeutic Development (CreATe) Consortium, Cure Alzheimer's Fund, Michael J Fox Foundation, Interdisciplinary Centre for Clinical Research, University Münster.

Identifiers

PMID40909834
PMCPMC12407616

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