Evidence map›Paper›PMID 42698373›Full record

ArticleEuropean journal of neurology2026

Protein Biomarkers in Risk and Prognosis of Amyotrophic Lateral Sclerosis.

Lu Pan, Can Hou, Christina Seitz, Caroline Ingre, Åsa K Hedman, Jose Laffita, Trung Nghia Vu, Yudi Pawitan, Abbe Ullgren, Solmaz Yazdani and 14 more

Abstract read
In one paragraph

Article in European journal of neurology, 2026. 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

24 authors.

Lu PanInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0001-7467-6992
Can HouInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-6903-6007
Christina SeitzInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Caroline IngreDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0001-5327-7204
Åsa K HedmanDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Jose LaffitaDepartment of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0009-0000-6516-0185
Trung Nghia VuDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0001-7945-5750
Yudi PawitanDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0003-0324-7052
Abbe UllgrenDepartment of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
Solmaz YazdaniInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
John AnderssonInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0003-2799-6349
Emily E JoyceInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0001-9722-5596
Charilaos ChourpiliadisInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-4733-5698
Anikó LovikInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-6397-5011
Yan ChenDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Sebastian A LewandowskiDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-5935-0211
Oscar Fernandez-CapetilloGenomic Instability Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
Myriam BarzScience for Life Laboratory, Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-5012-4779
Kristin SamuelssonDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0003-3116-7578
Rayomand PressDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0001-7077-2530
Fredrik PiehlDepartment of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0001-8329-5219
Caroline GraffDepartment of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-9949-2951
Anders MälarstigDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0003-2608-1358
Fang FangInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-3310-6456

Funding

Åhlen Stiftelse 223077Bjorklunds fundBruno and Ilse Frick Foundation for Research on ALSFondation Thierry Latran FIB-ALSH2020 European Research Council MegaALS, 802091Hjärnfonden FO2022-0233Karolinska Institutet 2021-01276Konung Gustaf V:s och Drottning Victorias FrimurarestiftelseNeuro Sweden F2021-0116Swedish Research Council 2021-02605Swedish Research Council 2023-02428
6 · The paper itself

Abstract

backgroundPlasma and cerebrospinal fluid (CSF) protein biomarkers in amyotrophic lateral sclerosis (ALS) may provide insight into disease mechanisms and yield clinically useful biomarkers.

methodsOverall, 363 proteins in plasma and CSF from 198 patients with ALS and 125 matched controls were profiled using Olink assays. Associations with disease status, survival, and functional decline, as well as longitudinal biomarker stability across the disease course were assessed, together with network and enrichment analyses. ALS risk-associated biomarkers were externally validated in the UK Biobank (UKB).

resultsOverall, 125 proteins were significantly associated with at least one outcome (i.e., case status, risk, survival, or functional decline), and 21 were associated with three or more outcomes. NEFL was the most robust biomarker in plasma and CSF, alongside TNFRSF12A in plasma and CSF, EDA2R in plasma, and FABP4 in plasma and CSF. Most biomarkers remained stable longitudinally across the disease course. ALS risk-associated biomarkers were replicated in UKB, in which > 3000 plasma proteins were measured in 52,990 participants, including 298 with ALS. Network and enrichment analyses highlighted their roles in immune response and extracellular-matrix remodeling, and their enrichments in the brain and T-cell subsets. Construction of an ALS risk-prediction model achieved an ROC-AUC of 0.72 in the UKB validation cohort.

conclusionsThese findings suggest candidate protein biomarkers for ALS risk stratification, early detection, and clinical therapeutic monitoring.

Indexed as

Amyotrophic Lateral SclerosisBiomarkersAgedFemaleHumansMaleMiddle AgedPrognosisBiomarkersALSdiagnosisOlinkprognosisproteins

Identifiers

PMID42698373
PMCPMC13545642

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.