MG Metabolic Profile May be Used as Diagnostic, Prognostic Biomarker, Study Says
Scientists discovered that patients with myasthenia gravis have a unique metabolic profile that can be used to diagnose the disorder, but also to predict the course of the disease and possibly lead to personalized treatments.
The study, “Beyond the antibodies: serum metabolomic profiling of myasthenia gravis,” recently was published in the journal Metabolomics.
Myasthenia gravis (MG) is an autoimmune disease caused by the abnormal production of antibodies against proteins essential for muscle contraction. It often is associated with a series of debilitating symptoms, including muscle weakness, extreme fatigue, and sleep and mood disturbances.
Although some diagnostic biomarkers are already available to facilitate the identification of patients with MG, no robust prognostic biomarkers that allow physicians to estimate how the disease will progress and what is the best way to tackle it have ever been described.
“Therefore, new diagnostic approaches and biological markers are essential not only for improved diagnosis of the disease but for improved outcomes,” the researchers said.
In this study, researchers from the University of Alberta in Canada set out to investigate the potential of using patients’ serum metabolic profile as a diagnostic and prognostic biomarker of MG.
They collected blood samples from 46 MG patients, 23 patients with rheumatoid arthritis (RA, another autoimmune disease) and 49 healthy individuals (controls) who were followed at neuromuscular and rheumatology clinics affiliated with the University of Alberta Hospital.
They then removed blood cells from the samples in order to obtain serum, and used a technique called liquid chromatography-mass spectrometry (LC-MS) to simultaneously separate and analyze the properties of the different metabolites — byproducts of the body’s metabolism — found in the purified serum samples.
After identifying more than 10,000 different metabolites in serum samples from study participants, investigators found that MG patients had a unique metabolic profile composed of 12 specific metabolites that distinguished them not only from healthy individuals, but also from individuals with RA.
“This is really important because now we have a way to easily separate a patient with myasthenia gravis from someone with rheumatoid arthritis or another autoimmune disease,” Zaeem Siddiqi, a neurologist, member of the U of A’s Women’s and Children’s Health Research Institute and the Neuroscience and Mental Health Institute, and co-author of the study, said in a news release.
“What’s more, now we’re able to explore how those 12 metabolites change in mild, moderate, or severe cases so we can make this biomarker more robust and more effective for predicting the course of the disease and developing treatment plans,” Siddiqi said.
According to researchers, the discovery of these 12 MG-specific metabolites may open the door to implementation of the first personalized treatments for MG patients. This may be one of the biggest turning points in the treatment and management of MG seen in recent years.
“Finding the antibodies is good for diagnosis, but they do not tell us how the patient will react to a specific drug or which drug will be most effective,” Siddiqi said. “What we’re trying to do with this biomarker discovery is develop treatments specific to the needs of the patient, to have more precise management, and to be able to more accurately predict the effects of the treatments.”
According to the team, plans include studying these unique metabolites in MG patients at different stages to get a better picture of how they change over the course of the disorder.