Research Grants

Multiple sclerosis (MS) is an immune-mediated neurological disorder that affects one million people in the United States. Up to 50% of patients with MS experience anxiety, yet the mechanisms of anxiety in MS remain under-investigated. MS is characterized by white matter lesions, suggesting that brain network disruption may underly anxiety symptoms. Studies of medically healthy participants with anxiety have described associations between white matter variability and anxiety symptoms, but frequently exclude participants with medical comorbidities and thus cannot be extrapolated to people with intracranial diseases. Previous research using lesion network mapping, a technique for mapping heterogeneous gray matter lesions to neuropsychiatric symptoms, has demonstrated that strokes in gray matter associated with depression disrupt a reproducible depression network. However, such techniques have not been applied to white matter disease and anxiety in MS. The purpose of this current study is to investigate how brain network disruption underlies anxiety by learning from the example of MS. Specifically, I will 1) construct a white matter anxiety network and examine whether MS lesions preferentially impact fascicles in this network, and 2) delineate how anxiety in adults with MS is associated with white matter lesion location and burden in a clinical sample. Predictors of anxiety from white matter lesions could be used for treatment stratification in clinical trials using personalized biomarkers. In line with the goals of the BBRF, this innovative proposal will generate knowledge that would benefit public health by reducing the costs and burden of anxiety on society at large.

Multiple sclerosis (MS) is an immune-mediated neurological disorder that affects one million people in the United States. Up to 50% of patients with MS experience depression, yet the mechanisms of depression in MS remain under-investigated. MS is characterized by white matter lesions, suggesting that brain network disruption may underly 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. Previous research using lesion network mapping, a technique for mapping heterogeneous gray matter lesions to neuropsychiatric symptoms, has demonstrated that strokes in gray matter associated with depression disrupt

a reproducible depression network. However, such techniques have never been applied to white matter disease or MS. Studying white matter lesions associated with depression in MS may provide a way to understand both the pathophysiology of depression in MS and general network mechanisms of depression more broadly. The purpose of this current study is to investigate how brain network disruption underlies depression by learning from the example of multiple sclerosis.