Predicting Phenoconversion to Clinically Manifest ALS: Results of a Large-Scale Proteomic Study

Area of Science:

• Neuroscience
• Proteomics
• Biomarker Discovery

Background:

• Predicting phenoconversion in pre-symptomatic amyotrophic lateral sclerosis (ALS) carriers is challenging.
• Early detection and prevention trials for ALS are hindered by the inability to identify individuals at risk and the timing of disease onset.

Purpose of the Study:

• To identify proteomic biomarkers for predicting phenoconversion in pre-symptomatic ALS.
• To develop a predictive model for estimating the time-to-phenoconversion in individuals carrying ALS-associated pathogenic variants.

Main Methods:

• Longitudinal proteomic analysis of 516 plasma samples from controls, pre-symptomatic carriers, and ALS patients using Olink Explore.
• Statistical analysis to identify proteins changing before phenoconversion and develop a predictive panel.
• Replication of key findings using UK Biobank data.

Main Results:

• Identified 81 proteins with altered concentrations prior to phenoconversion.
• A core panel of 19 proteins predicted phenoconversion with high accuracy (AUC 0.80-0.89) and estimated time-to-phenoconversion (mean absolute error 1.6 years).
• Replication confirmed pre-symptomatic protein changes (e.g., NEFL, EDA2R, CA3) and the superiority of a multi-protein panel over single markers.

Conclusions:

• A novel 19-protein panel serves as a reliable biomarker for predicting ALS phenoconversion and estimating disease onset.
• These findings offer insights into pre-symptomatic ALS biology and advance the goal of disease prevention.
• The identified biomarkers can aid in designing future ALS prevention strategies and clinical trials.