Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus

S. J. Wiseman, M. E. Bastin (Lead / Corresponding author), E. N. Amft, J. F. F Belch, S. H. Ralston, J. M. Wardlaw

Research output: Contribution to journalArticle

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Abstract

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.
Original languageEnglish
Pages (from-to)1329-1337
Number of pages9
JournalLupus
Volume27
Issue number8
Early online date3 May 2018
DOIs
Publication statusPublished - 1 Jul 2018

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Connectome
Aptitude
Systemic Lupus Erythematosus
Cognition
Brain
Cluster Analysis
Efficiency

Keywords

  • Connectome
  • systemic lupus erythematosus
  • cognition
  • MRI

Cite this

Wiseman, S. J., Bastin, M. E., Amft, E. N., Belch, J. F. F., Ralston, S. H., & Wardlaw, J. M. (2018). Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus. Lupus, 27(8), 1329-1337. https://doi.org/10.1177/0961203318772666
Wiseman, S. J. ; Bastin, M. E. ; Amft, E. N. ; Belch, J. F. F ; Ralston, S. H. ; Wardlaw, J. M. / Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus. In: Lupus. 2018 ; Vol. 27, No. 8. pp. 1329-1337.
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abstract = "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 (standardised{\ss} 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.",
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Wiseman, SJ, Bastin, ME, Amft, EN, Belch, JFF, Ralston, SH & Wardlaw, JM 2018, 'Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus', Lupus, vol. 27, no. 8, pp. 1329-1337. https://doi.org/10.1177/0961203318772666

Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus. / Wiseman, S. J.; Bastin, M. E. (Lead / Corresponding author); Amft, E. N.; Belch, J. F. F; Ralston, S. H.; Wardlaw, J. M.

In: Lupus, Vol. 27, No. 8, 01.07.2018, p. 1329-1337.

Research output: Contribution to journalArticle

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T1 - Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus

AU - Wiseman, S. J.

AU - Bastin, M. E.

AU - Amft, E. N.

AU - Belch, J. F. F

AU - Ralston, S. H.

AU - Wardlaw, J. M.

N1 - The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Lupus UK and the University of Edinburgh.

PY - 2018/7/1

Y1 - 2018/7/1

N2 - 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.

AB - 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.

KW - Connectome

KW - systemic lupus erythematosus

KW - cognition

KW - MRI

U2 - 10.1177/0961203318772666

DO - 10.1177/0961203318772666

M3 - Article

VL - 27

SP - 1329

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JO - Lupus

JF - Lupus

SN - 0961-2033

IS - 8

ER -