Months to years before symptoms of amyotrophic lateral sclerosis (ALS) appear, the levels of certain blood proteins can change dramatically. Researchers analyzed data from the long-term National Institutes of Health (NIH)-funded Presymptomatic Familial ALS (Pre-fALS) study to identify a lineup of key proteins that may predict the emergence of clinically apparent ALS. By predicting the onset of symptoms, researchers may be able to intervene with preventive treatments before the irreversible motor neuron damage that characterizes ALS begins.
In the past, if someone with an ALS-related genetic mutation had asked me when they would experience symptoms, I would have struggled to give a reasonable estimate. These biomarkers provide a more precise picture of timing, allowing us to estimate the time to onset of symptoms with an average margin of error of about 18 months. That’s something we can work on. ”
Michael Benatar, MD, Ph.D., senior author, professor of neurology and public health sciences, University of Miami
For nearly 20 years, the Pre-fALS study, led by Benatar and Joan Wu, Ph.D., a research associate professor of neurology and public health sciences at the University of Miami, has collected data and biological samples from people who are at significantly higher genetic risk for ALS but have not yet progressed to ALS or transformed. Although this cohort is unique in allowing testing for presymptomatic ALS, recent studies suggest that findings from pre-fALS are likely to be relevant to the broader population.
In 2017, an analysis of 10 Pre-fALS participants who developed symptoms showed that neurofilament light chain (NfL), a structural protein of neurons, surged in the blood in the months preceding the ALS phenotype.
As more study participants begin to show symptoms and signs of the disease, new opportunities are emerging to explore other presymptomatic ALS biomarkers.
Now, the researchers applied a high-throughput protein or proteomics analysis method called Olink to plasma samples taken from 137 study participants. Of these, 33 had clinical symptoms of ALS or frontotemporal dementia. Collecting data on the levels of more than 5,000 proteins, the research team identified 92 proteins whose levels vary from person to person before symptoms eventually appear.
The authors used machine learning techniques to test how different combinations of proteins could predict future risk of phenotypic conversion. They settled on 19 carefully selected panels, including NfL, that maximized forecast accuracy over a range of six months to five years. Using data from these 19 proteins, the researchers demonstrated that a predictive model could estimate a patient’s onset within two years of actually showing signs of the disease.
They also produced similar results using data from the UK Biobank. This data, although with some limitations, is more representative of the general population than the genetically predisposed Pre-fALS cohort.
“With the availability of preventive gene-targeted therapies, there is an especially urgent need for reliable biofluid-based signatures of impending disease in individuals with ALS risk genes,” said Amy Vanney Adams, Ph.D., acting director of the NIH National Institute of Neurological Disorders and Stroke (NINDS).
Tofersen, a drug approved for symptomatic ALS, is currently being evaluated as a preventive treatment for symptomatic ALS through ATLAS, a clinical trial designed by Benatar in partnership with Biogen. ATLAS will test whether the onset of ALS can be avoided or delayed by starting treatment just before symptoms appear.
“This is all thanks to the members of the career community who believe in our mission to prevent ALS and support and participate in our research. Being able to give something back has been one of the greatest privileges of my life,” Benatar said.
This research was supported by the NIH through NINDS grants R01NS105479 and U54NS092091.
sauce:
National Institutes of Health (NIH)
Reference magazines:
Ran, X, others. (2026). Longitudinal plasma proteomics predicts phenotypic transformation leading to clinical manifestations of ALS. natural medicine. DOI: 10.1038/s41591-026-04528-x. https://www.nature.com/articles/s41591-026-04528-x
