Abstract
INTRODUCTION: Multiple sclerosis (MS) is an immune-mediated neurological disorder that affects one million people in the USA. Up to 50% of patients with MS experience depression, yet the mechanisms of depression in MS remain underinvestigated. MS is characterised by white matter lesions, suggesting that brain network disruption may underlie depression symptoms. Studies of medically healthy participants with depression have described associations between white matter variability and depressive symptoms, but frequently exclude participants with medical comorbidities and thus cannot be extrapolated to people with intracranial diseases. The purpose of this current study is to investigate how brain network disruption underlies depression by learning from the example of MS. METHODS AND ANALYSIS: We will obtain structured clinical and cognitive assessments from 250 participants with MS and prospectively evaluate white matter disease burden as a predictor of depressive symptoms. White matter lesion burden will be quantified by identifying streamlines within white matter fascicles that intersect lesions along any portion of their trajectory, classifying these streamlines as injured, and calculating the total volume of injured streamlines to serve as the metric of disease burden. ETHICS AND DISSEMINATION: Ethics approval was obtained from The University of Pennsylvania Institutional Review Board (protocol #853883). The results of this study will be presented at scientific meetings and conferences and published in peer-reviewed journals.