Amytrophic lateral sclerosis: three proteins that may be first tools for confirming diagnosis, identified
Researchers from Mount Sinai School of Medicine have identified three proteins that are found in significantly lower concentration in the cerebral spinal fluid of patients with amytrophic lateral sclerosis ( ALS ) than in healthy individuals. These are the first biomarkers for this disease.
" Amytrophic lateral sclerosis is a very difficult disease to diagnose. To date, there is no one test or procedure to ultimately establish the diagnosis of amytrophic lateral sclerosis . It is through a clinical examination and series of diagnostic tests, often ruling out other diseases," website of the ALS Association.
Giulio Pasinetti, at Mount Sinai School of Medicine, and colleagues compared cerebral spinal fluid from patients diagnosed with amytrophic lateral sclerosis, patients with other neurological disorders, and healthy individuals. They found that fluid from patients with amytrophic lateral sclerosis had significantly lower concentrations of three proteins than either of the other groups. Evaluating the levels of these three proteins proved 95% accurate for diagnosing amytrophic lateral sclerosis.
The researchers found that the changes in concentration of these proteins were evident within 1.5 years of onset of symptoms. With current methods, the average time from onset of symptoms to diagnosis is two years. Testing for these protein concentrations may provide a means of early diagnosis, allowing patients to receive relief from symptoms years earlier.
" For the first time we have the possibility of developing a test that can definitively say whether or not a patient has amytrophic lateral sclerosis ," said Pasinetti. " Such a test would eliminate the need for patients to undergo months of diagnostic evaluation and remove the uncertainty that currently lingers with physicians and patients even after a diagnosis is made."
The study is published in the journal Neurology.
Source: The Mount Sinai Hospital / Mount Sinai School of Medicine, 2006
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