Network analysis characterizes key associations between subjective fatigue and specific depressive symptoms in early relapsing-remitting multiple sclerosis.

Abstract

Fatigue is common and disabling in multiple sclerosis (MS), yet its mechanisms are poorly understood. In particular, overlap in measures of fatigue and depression complicates interpretation. We applied a multivariate network approach to quantify relationships between fatigue and other variables in early MS. Data were collected from patients with newly diagnosed immunotherapy-naïve relapsing-remitting MS at baseline and month 12 follow-up in FutureMS, a Scottish nationally representative cohort. Subjective fatigue was assessed by Fatigue Severity Scale. Detailed phenotyping included measures assessing each of physical disability, affective disorders, cognitive performance, sleep quality, and structural brain imaging. Network analysis was conducted to estimate partial correlations between variables. Baseline networks were compared between those with persistent and remitted fatigue at one-year follow up. Data from 322 participants at baseline, and 323 at month 12, were included. At baseline, 154 patients (47.8%) reported clinically significant fatigue. In the network analysis, fatigue severity showed strongest connections with depression, followed by Expanded Disability Status Scale. Conversely, fatigue severity was not linked to objective cognitive performance or brain imaging variables. Even after controlling for measurement of "tiredness" in our measure of depression, four specific depressive symptoms remained linked to fatigue. Results were consistent at baseline and month 12. Overall network strength was not significantly different between groups with persistent and remitted fatigue (4.89vs 2.90, p=0.11). Our findings support robust links between subjective fatigue and depression in early relapsing-remitting MS. Shared mechanisms between specific depressive symptoms and fatigue could be key targets of treatment and research in MS-related fatigue.