Protein Biomarkers in Risk and Prognosis of Amyotrophic Lateral Sclerosis.

Authors

Lu Pan, Can Hou, Christina Seitz, Caroline Ingre, Åsa K Hedman, Jose Laffita, Trung Nghia Vu, Yudi Pawitan, Abbe Ullgren, Solmaz Yazdani, John Andersson, Emily E Joyce, Charilaos Chourpiliadis, Anikó Lovik, Yan Chen, Sebastian A Lewandowski, Oscar Fernandez-Capetillo, Myriam Barz, Kristin Samuelsson, Rayomand Press, Fredrik Piehl, Caroline Graff, Anders Mälarstig, Fang Fang

Published in

European journal of neurology. Volume 33. Issue 9. Pages e70741.

Abstract

Plasma and cerebrospinal fluid (CSF) protein biomarkers in amyotrophic lateral sclerosis (ALS) may provide insight into disease mechanisms and yield clinically useful biomarkers.
Overall, 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).
Overall, 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.
These findings suggest candidate protein biomarkers for ALS risk stratification, early detection, and clinical therapeutic monitoring.

PMID:
42698373
Bibliographic data and abstract were imported from PubMed on 05 Sep 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.