Objective: To investigate brain structural connectivity in relation to cognitive abilities andsystemic damage in systemic lupus erythematosus (SLE). Methods: Structural and diffusionMRI data were acquired from 47 patients with SLE. Brains were segmented into 85 corticaland subcortical regions and combined with whole brain tractography to generate structuralconnectomes using graph theory. Global cognitive abilities were assessed using a compositevariable g, derived from the first principal component of three common clinical screening testsof neurological function. SLE damage (LD) was measured using a composite of a validatedSLE damage score and disease duration. Relationships between network connectivity metrics,cognitive ability and systemic damage were investigated. Hub nodes were identified. Multiplelinear regression, adjusting for covariates, was employed to model the outcomes g and LD as afunction of network metrics. Results: The network measures of density (standardisedß ¼ 0.266, p ¼ 0.025) and strength (standardised ß ¼ 0.317, p ¼ 0.022) were independentlyrelated to cognitive abilities. Strength (standardised ß ¼ –0.330, p ¼ 0.048), mean shortestpath length (standardised ß ¼ 0.401, p ¼ 0.020), global efficiency (standardised ß ¼ –0.355,p ¼ 0.041) and clustering coefficient (standardised ß ¼ –0.378, p ¼ 0.030) were independentlyrelated to systemic damage. Network metrics were not related to current diseaseactivity. Conclusion: Better cognitive abilities and more SLE damage are related to braintopological network properties in this sample of SLE patients, even those without neuropsychiatricinvolvement and after correcting for important covariates. These data show thatconnectomics might be useful for understanding and monitoring cognitive function and whitematter damage in SLE.
- systemic lupus erythematosus