Michael Benatar, MD, PhD, Department of Neurology and ALS Center, University of Miami Miller School of Medicine, discusses the use of plasma proteomics in predicting clinical manifestations of amyotrophic lateral sclerosis (ALS).
ALS is a rare motor neuron disease characterized by problems with muscle control and movement. Early symptoms may include muscle twitching, cramping, stiffness, or weakness, slurred speech, and/or difficulty chewing or swallowing. There are various types of ALS depending on symptoms, and sometimes, genetic cause. Most people with ALS have a sporadic form of ALS. It is believed that these cases are caused by an interaction between genetic and environmental factors. Familial ALS may be caused by genetic changes in any one of several genes and the pattern of inheritance varies depending on the gene involved.
A study published in Nature Medicine looked at longitudinal plasma proteomics to predict phenoconversion to clinically manifest ALS. The study was conducted in patients with pre-symptomatic ALS to predict which unaffected carriers of ALS-associated pathogenic variants will phenoconvert to clinically manifest disease and when, with the hopes of designing more effective disease prevention trials.
A total of 516 serially collected plasma samples from 33 phenoconverters, 35 patients with ALS, 10 pre-symptomatic pathogenic variant carriers, and 59 controls were included. 92 proteins were then identified with concentrations that changed before phenoconversion and the longitudinal trajectory of these proteins was characterized. A core panel of 19 proteins was identified which, collectively, predicted phenoconversion over the 0.5-year to 5-year time horizons and resulted in 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 (including NEFL, EDA2R and CA3) and that a multi-protein panel outperformed NEFL alone in estimating time to phenoconversion.
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