Gray matter networks and cognitive impairment in multiple sclerosis

Author(s)

Rimkus, Carolina M. ^{[1, 2]} ; Schoonheim, Menno M. ^[3] ; Steenwijk, Martijn D. ^{[3, 4]} ; Vrenken, Hugo ^[2] ; Eijlers, Anand J. C. ^[3] ; Killestein, Joep ^[4] ; Wattjes, Mike P. ^[2] ; Leite, Claudia C. ^[1] ; Barkhof, Frederik ^{[5, 2, 6]} ; Tijms, Betty M. ^{[7, 8]}

Affiliation

^[1] Univ Sao Paulo, Fac Med, Dept Radiol, Sao Paulo - Brazil

^[2] Vrije Univ Amsterdam Med Ctr, Amsterdam Neurosci, VUmc MS Ctr Amsterdam, Dept Radiol & Nucl Med, Amsterdam - Netherlands

^[3] Vrije Univ Amsterdam Med Ctr, Amsterdam Neurosci, VUmc MS Ctr Amsterdam, Dept Anat & Neurosci, Amsterdam - Netherlands

^[4] Vrije Univ Amsterdam Med Ctr, Amsterdam Neurosci, VUmc MS Ctr Amsterdam, Dept Neurol, Amsterdam - Netherlands

^[5] UCL, Inst Neurol, London - England

^[6] UCL, Inst Healthcare Engn, London - England

^[7] Vrije Univ Amsterdam Med Ctr, Amsterdam Neurosci, Alzheimer Ctr, POB 7057, NL-1007 MB Amsterdam - Netherlands

^[8] Vrije Univ Amsterdam Med Ctr, Amsterdam Neurosci, Dept Neurol, POB 7057, NL-1007 MB Amsterdam - Netherlands

• Document type: Journal article
• Source: MULTIPLE SCLEROSIS; v. 25, n. 3, p. 382-391, MAR 2019.
• Web of Science Citations: 4

Abstract

Background: Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS). Objective: To investigate whether single-subject gray matter network properties are related to impaired cognition in MS. Methods: We studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively normal and impaired subjects, and associated with performance on neuropsychological tests in six cognitive domains with regression models. Analyses were controlled for age, gender, whole-brain gray matter volumes, and education level. Results: Compared to MS subjects with normal cognition, MS subjects with cognitive impairment showed a more random network organization as indicated by lower lambda values (all p<0.05). Worse average cognition and executive function were associated with lower lambda values. Impaired information processing speed, working memory, and attention were associated with lower clustering values. Conclusion: Our findings indicate that MS subjects with a more randomly organized gray matter network show worse cognitive functioning, suggesting that single-subject gray matter graphs may capture neurological dysfunction due to MS. (AU)

• FAPESP's process: 14/23299-4 - Cortical graphs and brain disconnection in multiple sclerosis
• Grantee: Carolina de Medeiros Rimkus
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor