Johns Hopkins-led study identifies protein signature with 98% accuracy in distinguishing ALS patients from healthy individuals and those with other neurological diseases.
Researchers at Johns Hopkins University School of Medicine and the National Institutes of Health have developed a blood test that can detect amyotrophic lateral sclerosis (ALS) up to a decade before symptoms appear, with more than 98% accuracy in distinguishing patients with ALS from healthy individuals and those with other neurological diseases.
The study, published in Nature Medicine, analyzed nearly 3,000 neurological and skeletal muscle proteins in blood samples from over 600 participants using an advanced platform combined with machine learning to isolate a protein signature predictive of ALS.
“We see the light at the end of the tunnel here, and that target is an approved and available blood test for ALS,” says co-investigator Alexander Pantelyat, MD, associate professor of neurology at Johns Hopkins University School of Medicine and director of the Johns Hopkins Atypical Parkinsonism Center, in a release. “With a test that allows for earlier detection of ALS, we have opportunities to enroll people in observational studies, and by extension, offer promising disease-modifying—and hopefully disease-stopping—medications, before ALS becomes debilitating.”
Validation Across Multiple Cohorts
The research team confirmed the test’s accuracy across multiple independent groups, including a 23,000-participant cohort from the UK Biobank. Within this group, blood samples from 110 individuals—collected 10 to 15 years before they developed ALS—showed changes in the protein signature identified in the study.
The study examined both patients with active ALS and individuals who had donated blood samples years before developing the disease. Among pre-symptomatic individuals, researchers observed previously unknown changes in blood proteins before patients later developed symptoms. These protein shifts point to early dysfunction in skeletal muscle, nerve signaling and energy metabolism.
“We had always assumed that ALS was a rapid disease that starts 12 to 18 months before symptom onset,” says Pantelyat, in a release. “But when we look at our findings, we see this has been a process that goes on for a decade or so before the patient ever steps into the doctor’s office or clinic.”
Clinical Laboratory Implications
Currently, ALS diagnosis relies on neurological evaluations and the presence of symptoms, with no definitive diagnostic test available. By 2040, experts estimate that nearly 400,000 people worldwide will be living with ALS.
In every validation group, the model demonstrated strong ability to detect ALS while minimizing false positives caused by other neurological conditions like Parkinson’s disease or neuropathy. The study confirmed that these protein changes were not driven by inherited genetic mutations, meaning the blood-based signature could be applied broadly, even in patients with no family history of ALS.
“It’s crucial for patients and their families to be able to discern between ALS and other conditions for diagnostic clarity, prognostic understanding and eligibility to enroll into the appropriate clinical trials,” says Pantelyat, in a release.
Future Research and Development
Further research is underway to explore how this protein-based signature could help monitor ALS progression, evaluate treatment effectiveness in clinical trials and inform diagnostic tools for other neurodegenerative diseases. The research team has made their data publicly available to accelerate progress in ALS biomarker development.
The research was funded by the Intramural Research Program of the National Institutes of Health, the National Institute on Aging, the National Institute of Neurological Disorders and Stroke, the Division of Intramural Research of the National Institute of Allergy and Infectious Diseases, and Merck Sharp & Dohme Corporation, among other organizations.
Bryan Traynor, an additional researcher who conducted the study, and others have a patent pending (US Patent Application No 63/717,807)Â on diagnostic testing for ALS based on the proteomic panel.
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