Multi-scale, multi-modal imaging assessment of trajectories of cognitive impairment in Multiple Sclerosis

Cognitive impairment is highly prevalent in patients with multiple sclerosis (MS) and increases in severity with disease progression. Unfortunately, treatment options for MS-related cognitive impairment are limited in that they are not neurobiologically-based or personalized. Moreover, to date there are no approved pharmaceutical

treatments to manage chronic cognitive symptoms. Brain network studies using diffusion MRI (dMRI) to measure white matter structural connectivity (SC) and functional MRI (fMRI) to measure functional connectivity (FC) have identified specific networks related to cognitive impairment in MS. However, both increased and decreased FC

have been associated with lower cognitive performance, leading to unresolved questions regarding the response of brain networks to the pathology of MS. There is an urgent, unmet need to understand the directionality of this relationship, and mechanisms driving these brain activity changes, if we are to design neurobiologically-based

cognition-preserving therapies. Our overall objective is to utilize a multi-scale, multi-modal, longitudinal imaging approach to examine the association of cognitive function with both macroscopic and microscopic changes in brain function, anatomy, and neuronal integrity, and to create clinically applicable models that can identify

patients at risk for cognitive decline. We will utilize MRI to examine FC and SC brain networks (macroscopic) and [11C] Flumazenil (FMZ) positron emission tomography (PET) to measure concurrent receptor-level neuronal integrity (microscopic). We our hypotheses are based on a three-stage trajectory of cognitive decline in MS i)

early “adaptive” stage where increased FC is related to intact neuronal integrity and cognitive resilience, ii) middle “adaptive exhaustion” stage of cognitive decline wherein FC continues to increase but with decreasing efficacy due to loss of neuronal integrity and continued SC damage and, finally, iii) “decline” or network collapse stage

wherein all imaging markers decline with cognition. Here, we focus on the first two stages of the trajectory, as our aim is to identify mechanistic targets prior to overall decline. In Aim 1, we will examine the association between cognition and each imaging modality (and their changes) over 4-years in 66 people with MS and 30

controls. Our hypothesis is that larger FC/FMZ-PET binding potential and more intact SC/gray matter volume will be related to preserved cognition in the “adaptive” stage of cognitive decline, while higher FC and reduced SC/FMZ-PET and gray matter volume will be related to worse cognition in the “adaptive exhaustion” stage. In

Aim 2, we hypothesize multi-modal, multi-scale imaging will reveal i) positive correlations between neuronal integrity and FC and ii) negative correlations between neuronal integrity and SC in the “adaptive” stage; both of these relationships will reverse in the “adaptive exhaustion” stage. Lastly, in Aim 3, we will use MRI-based

measures of SC/FC/brain atrophy to identify patients at high risk for future cognitive decline and provide a clinically feasible tool for clinicians. The overall impact of this proposal is to create a clear path to develop and deliver personalized, effective therapies to prevent cognitive decline in people with MS.