Associations of social network structure with cognition and amygdala volume in multiple sclerosis: An exploratory investigation

Abstract

Background:

Humans are inherently social, biologically programmed to connect with others. Social connections are known to impact mental and physical health.

Objective:

The aim of this study was to test whether social network structure is linked to cognition, mood, fatigue, and regional brain volumes in persons with multiple sclerosis (MS).

Methods:

A questionnaire quantifying individual-level social network structure (size, density, effective size, and constraint), a comprehensive battery of neuropsychological tests, and magnetic resonance imaging (MRI) was administered to 51 persons with relapsing–remitting MS. Linear regressions assessed associations of network variables to cognition, depression, fatigue, and structural brain volumes.

Results:

Higher network density and constraint, indicating stronger connections among network members, were associated with worse language functions. Conversely, larger network effective size, a measure of non-redundant network members, was associated with better language functions. No relationships of network structure to depression or fatigue were found. Larger network size was related to larger amygdala volume.

Conclusion:

Findings suggest that social network structure is linked to language function and amygdala volume in persons with MS. Patients with close-knit networks showed worse language function than those with open networks. Longitudinal studies with larger samples are warranted to evaluate potential causal links between social network structure and MS-related cognitive impairment.

Keywords

Multiple sclerosis social networks clinical outcome measures cognition magnetic resonance imaging amygdala

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