Researchers have identified previously undetectable biomarkers that could help diagnose and direct the treatment of a rare autoimmune disease.
Autoimmune conditions are a class of disease in which a person's immune system produces antibodies to attack tissues in the body.
There are many types of autoimmune disease, and in a recent study, researchers focused specifically on myasthenia gravis (MG).
MG is a rare condition characterized by weakness and rapid fatigue of voluntary muscles. Symptoms often get worse after exertion.
MG is a chronic illness, and it can be debilitating and, in some cases, fatal. It affects between 14–40 people per 100,000 in the United States, and there is no known cure.
Treatment usually involves medications to increase levels of the organic chemical acetylcholine available to stimulate receptors and improve muscle strength, as well as drugs to suppress the immune system.
Historically, diagnosing MG has been difficult because symptoms often mimic those of other neurological conditions, such as stroke.
Now, a team of researchers — based at the University of Alberta, Edmonton, in Canada — has shown that MG can not only be detected, but its disease progression can be predicted by the presence of certain metabolic biomarkers in blood serum.
The researchers hope that their findings, which appear in the journal Metabolomics, will help clinicians diagnose this difficult-to-identify disease. Dr. Zaeem Siddiqi, a neurologist, and graduate student Derrick Blackmore, Ph.D., co-led the new research.
Why are biomarkers useful?
A biomarker is a small biological compound defined by its pathological significance in identifying certain diseases. Many diseases can be detected by the presence of biomarkers in blood serum, and these markers can help indicate the type of treatment that a person may respond best to.
"Biomarker discovery is an important step in individualized medicine," explains Dr. Siddiqi.
Currently, MG is diagnosed via the detection of acetylcholine receptor and anti-MuSK, or muscle-specific kinase, antibodies.
However, previous research has shown that these do not correlate with disease severity or clinical response. The identification of biomarkers to detect the severity of MG has remained elusive — until now.
The new study focused on three subject groups. The first consisted of 46 participants with MG, the second consisted of 23 participants with rheumatoid arthritis (a reference autoimmune disease), and the third comprised 49 healthy control participants.
The study was a two-control approach for metabolomics profiling. People with rheumatoid arthritis displayed physically identical symptoms to those with MG, and all participants were age- and gender-matched as closely as possible.
The researchers extracted serum from each person and analyzed its principal components. They then filtered the metabolites to remove those common to both disease cohorts, leaving just the unique markers, of which there were 12.
Metabolomics profiling helps detect MG
Metabolomics profiling is the study of chemical processes and molecules — including intermediates and byproducts — involved in metabolism, which is vital for cell and organism survival.
Changes in metabolomics can have disastrous consequences and often lead to disease. Metabolite markers offer the possibility of identifying specific problems in metabolism associated with specific conditions, such as MG.
The researchers found a clear distinction in metabolite markers among all three study cohorts. In addition, there was a clear separation between different stages of the disease, allowing for analysis of disease progression.
There was specific upregulation of short-chain keto acids in participants with MG, compared with controls. This included compounds such as α-ketobutyric acid, a key regulator of metabolic pathways.
The upregulation of α-ketobutyric acid suggests that there is enhanced metabolic activity in the cells of people with MG. The majority of metabolites that the researchers identified also have significant roles in energy production pathways.
Interestingly, researchers have also
Impaired glycolysis leads to reduced adenosine triphosphate synthesis, and in turn, this can result in cell death and degeneration, symptomatic of MG.
Strengths and limitations of the study
This study demonstrates a rapid identification of metabolites present in people who are showing symptoms of MG. This would give a huge advantage to clinicians treating the disease and allow for quicker diagnosis.
"Right now we don't have the ability to manage [MG] in a more specific way; we treat all patients the same," explains Dr. Siddiqi. But the new findings might change this.
"Now we have a unique fingerprint or map of metabolites that can easily separate healthy individuals from those with [MG] and a path to the discovery of more accurate and specific treatments."
Dr. Zaeem Siddiqi
"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," continues the researcher.
Although this study paves the way for more detailed analysis of the metabolic profile of MG, there are limitations to the work.
These include the fact that some of the cohort had previously been treated with drugs that could have altered their metabolic profile, and the participants were not required to fast before the study.
Both of these factors could have contributed to the identification of false positives. The analysis would also benefit from a much larger sampling pool. This would also help correlate work from previous studies.
Despite the limitations, it is clear that the results could benefit those currently living with MG or similar conditions.