Genetic Clue May Predict Multiple Sclerosis Severity
Biomarker May Have Potential to Help With Diagnosis, Treatment of Multiple Sclerosis
WebMD News Archive
Oct. 19, 2009 -- A newly identified biomarker may be linked to the severity of multiple sclerosis and may one day help with diagnosis and treatment of the often frustrating and unpredictable disease.
Multiple sclerosis is a disease of the brain and spinal cord that affects more than 400,000 Americans. MS is believed to be an autoimmune disease because the body’s immune system attacks the protective myelin sheath around nerve fibers. This results in problems with nerve messages being conducted to and from the brain.
In a new study published in Nature Immunology, researchers identified short RNA molecules, known as microRNAs, that were linked to multiple sclerosis symptoms in mice, depending on their level of activity or expression. The researchers found that when expression of the microRNA called miR-326 was silenced, MS severity in mice was mild. When the microRNA expression was increased, disease severity was severe.
The researchers note that microRNAs have been linked to regulation of autoimmunity in mouse studies, but details about the specific microRNAs involved in autoimmune disease are unclear.
Predicting Multiple Sclerosis Severity
Researcher Changsheng Du of the Shanghai Institute for Biological Sciences at the Chinese Academy of Sciences in Shanghai, China, and colleagues found that the microRNA called miR-326 is also associated with severity of multiple sclerosis in humans.
They found that miR-326 expression was much higher in the immune cells of MS patients compared to patients with a different neurological disease that affects myelin. The biomarker appears to correlate with the severity of multiple sclerosis by affecting the production of certain inflammatory proteins.
Researchers say learning how to manipulate these microRNA molecules in humans may help lead to better treatments for the disease. It may also serve as a marker to help diagnose the disease, monitor response to treatment, and predict prognosis.