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This study applies functional brain imaging techniques to identify neurobiological markers associated with fall risk in older adults with multiple sclerosis. The research aims to develop predictive models that could improve clinical assessment and prevention strategies for falls in this vulnerable population.
This study investigates structural brain differences in grey matter related to mobility function, comparing older adults with MS to those without the disease. The research uses neuroimaging to identify which brain regions correlate with physical mobility capacity in MS and healthy aging.
A multicenter prospective study measured serum neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) levels in 115 relapsing-remitting MS patients treated with ocrelizumab over one year to identify biomarkers predicting treatment response. Elevated baseline sNfL and sGFAP levels were associated with treatment failure due to ongoing inflammation, while most patients with progression without relapse showed low sNfL levels, suggesting these biomarkers may help predict which patients will achieve disease activity remission.
This prospective study compared serum pleiotrophin (PTN) levels in 168 MS patients across three disease subtypes (RRMS, PPMS, SPMS) against 41 healthy controls, finding significantly lower PTN levels in MS patients overall and in RRMS and SPMS subgroups. The findings suggest pleiotrophin may play a role in MS pathogenesis and could be investigated as a potential biomarker for certain disease phenotypes.
Multiple sclerosis is a chronic autoimmune disorder of the central nervous system characterized by demyelination, inflammation, and progressive neuronal loss, presenting with diverse neurological symptoms including vision problems, sensory changes, weakness, and cognitive decline. The disease exhibits distinct clinical courses—relapsing-remitting (70-80% of cases), primary progressive (15-20%), and secondary progressive forms—with symptom onset typically in young adulthood and variable progression timelines.