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Predicting Phenoconversion to Clinically Manifest ALS: Results of a Large-Scale Proteomic Study
Ximing Ran1, Joanne Wuu2, Zhaohui S Qin1
1Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA.
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. We identified 81 proteins whose concentrations changed prior to phenoconversion; characterized the longitudinal trajectory of these proteins; and identified a core panel of 19 proteins that, collectively, predicted phenoconversion over the 0.5- to 5-year time horizons (areas under curve 0.80-0.89) and yielded estimates of time-to-phenoconversion with a mean absolute error of 1.6 years. These findings were replicated in UK Biobank data, confirming pre-symptomatic increases in several proteins (e.g. NEFL, EDA2R, 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 novel susceptibility/risk biomarkers based on empirical longitudinal data furthers the ultimate goal of ALS prevention.
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