Farren Briggs, PhD, ScM, was awarded $1.2 million over three years from the National Institute of Neurological Disorders and Stroke (NINDS) at the National Institutes of Health to identify biomarkers to improve the diagnoses of multiple sclerosis (MS), including the ability to monitor disease activity and progression.
Briggs, the principal investigator, will work in collaboration with colleagues at the Mayo Clinic and Duke University.
To address the challenges posed by initial misdiagnosis, Briggs and his colleagues will identify blood serum biomarkers that accurately classify people with MS, compared to unaffected individuals and those with other rare demyelinating and inflammatory diseases.
An important challenge in MS treatment is the absence of reliable biomarkers that signal the onset of relapse or changes in the disease’s progression. Another goal of this work is to identify biomarkers that can help monitor MS progression, which will contribute to improving clinical trials for new therapeutics.
This research is organized into the following Aims:
• Identify biochemical traits that discriminate MS from other central nervous system demyelinating disorders (CNSIDDs) and healthy controls. Supervised machine learning and classification models will identify a metabolic signature discriminating MS from other CNSIDDs and healthy controls (HCs) in two cohorts.
• Identify biochemical features of MS disease activity. Identify metabolic variation corresponding to disease activity by comparing immunomodulatory therapies (IMT) naïve/free patients within 2 years of diagnosis and with a recent relapse to those who have been in remission for ≥3 months and to HCs.
• Identify biochemical traits that discriminate progressive from relapsing MS. Supervised machine learning and classification models will identify metabolic patterns associated with MS progression.
• Identify metabolites that interact with HLA-DRB1*15:01 to increase MS risk.
At the completion of the research, Briggs and his team expect to have identified and characterized a serum-derived metabolomic signature that discriminates MS from other CNSIDDs and non-CNSIDD controls. They also expect to have identified novel serum markers of MS disease activity and progression, as well as putative metabolites that interact with HLA-DRB1*15:01 to modify risk.
These results will have an important positive impact by identifying serum-derived biochemical traits that could be used to improve diagnostic specificity in MS. There is also the promise of discerning novel molecular processes underlying MS, which will provide new opportunities for the development and evaluation of novel therapies.
This grant-funded research is slated to run for three years. This page will be updated as publications and presentations are developed about this work.
Grant number: NIH/NINDS: 1R01NS121928-01