Longitudinal plasma proteomics predict phenoconversion to clinically manifest ALS

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.

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Publication Details

Journal
Nature Medicine
Published
2026-07-27
DOI
https://doi.org/10.1038/s41591-026-04528-x
Primary Topic
Amyotrophic Lateral Sclerosis Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Longitudinal plasma proteomics predict phenoconversion to clinically manifest ALS

Christina M. Lill, Paolo Piazza, Joanne Wuu, Yindi Li et al.
Nature Medicine
Amyotrophic Lateral Sclerosis Research
article

Longitudinal plasma proteomics predict phenoconversion to clinically manifest ALS

Christina M. Lill, Paolo Piazza, Joanne Wuu, Yindi Li, Volkan Granit, Michael Benatar, Anne‐Laure Grignon, Maria Catalina Fernandez, Johnathan Cooper‐Knock, Zhaohui Qin, Andrea Malaspina, Danielle Colato, Ximing Ran, Elizabeth Lin, Nathan Carberry, Michael P. McDermott
article en

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.

Nature Medicine
Centre for Human Genetics (GB), University of Miami (US), Emory University (US), Queen Mary University of London (GB), University of Münster (DE), University of Oxford (GB), University College London (GB), Imperial College London (GB), University of Rochester (US), University of Sheffield (GB)
ALS Association, Muscular Dystrophy Association, National Institutes of Health
Good health and well-being
Openalex Percentile: Top 9%
Amyotrophic Lateral Sclerosis Research
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