Multiple sclerosis (MS) is the most widespread disabling neurological condition of young adults around the world. Anyone can develop MS at any age, but most people are diagnosed between the ages of 20 and 50. A new study helped identify a genetic marker that can help doctors better tailor treatment for patients with MS.
“With this study, we were able to identify something that can impact patients in a direct manner, which is really rewarding. Too often, things we find in research aren’t able to translate into improved care for patients, so it is exciting to see something here that may help MS patients,” said Mary Davis, an assistant BYU professor in the Department of Microbiology and Molecular Biology.
Davis earned a Ph.D. in human genetics from Vanderbilt University and got involved with the multiple sclerosis genetic research while working on her Ph.D. Davis and her team was performing a similar analysis using another MS drug (glatiramer acetate) when they were contacted by Dr. Bruce Carleton’s group. Davis and her team changed drug targets to interferon-beta to replicate their analysis.
Their goal is to identify genetic variants that can help clinicians tailor care for MS patients both through medication and lifestyle alterations. “It’s important that we be able to understand who might be most at risk so that we can intervene with an altered treatment plan or increased monitoring to prevent liver damage,” said Dr. Bruce Carleton, study co-author and Director of the Pharmaceutical Outcomes Programme at BC Children’s Hospital.
The National MS Society estimates that 2.3 million people currently live with MS globally. There are about 200 new cases diagnosed each week in the United States alone. Although there is no cure yet for MS, there are different types of treatment options that can help patients better cope with the condition.
“We are submitting grants to pay for additional phenotyping and genotyping of individuals in the EHR, so we can increase our sample size in this dataset. Using electronic health records (EHR) gives us access to long-term clinical data that is necessary for the MS research we perform. However, most of the data is unstructured, and EHR platforms vary drastically across institutions. This requires individualized extraction algorithms to identify phenotype data from the EHR, and makes it challenging to use our data extraction tools for EHRs at other institutions to increase the sample size,” said Davis.
To learn more about the genetic research please visit the BYU news website.
