TY - JOUR
T1 - Exploring the core network of the structural covariance network in childhood absence epilepsy
AU - Eussen, Merel J.A.
AU - Jansen, Jacobus F.A.
AU - Voncken, Twan P.C.
AU - Debeij-Van Hall, Mariette H.J.A.
AU - Hendriksen, Jos G.M.
AU - Vermeulen, R. Jeroen
AU - Klinkenberg, Sylvia
AU - Backes, Walter H.
AU - Drenthen, Gerhard S.
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/12/1
Y1 - 2023/12/1
N2 - Childhood absence epilepsy (CAE) is a generalized pediatric epilepsy, which is generally considered to be a benign condition since most children become seizure-free before reaching adulthood. However, cognitive deficits and changes of brain morphological have been previously reported in CAE. These morphological changes, even if they might be very subtle, are not independent due to the underlying network structure and can be captured by the structural covariance network (SCN). In this study, SCNs were used to quantify the structural brain network for children with CAE as well as controls. Seventeen children with CAE (6-12y) and fifteen controls (6-12y) were included. To estimate the SCN, T1-weighted images were acquired and parcellated into 68 cortical regions. Graph measures characterizing the core network architecture, i.e. the assortativity and rich-club coefficient, were calculated for all individuals. Multivariable linear regression models, including age and sex as covariates, were used to assess differences between children with CAE and controls. Additionally, potential relations between the core network and cognitive performance was investigated. A lower assortativity (i.e. less efficiently organized core network organization) was found for children with CAE compared to controls. Moreover, better cognitive performance was found to relate to stronger assortative mixing pattern (i.e. more efficient core network structure). Rich-club coefficients did not differ between groups, nor relate to cognitions. The core network organization of the SCN in children with CAE tend to be less efficient organized compared to controls, and relates to cognitive performance, and therefore this study provides novel insights into the SCN organization in relation to CAE and cognition.
AB - Childhood absence epilepsy (CAE) is a generalized pediatric epilepsy, which is generally considered to be a benign condition since most children become seizure-free before reaching adulthood. However, cognitive deficits and changes of brain morphological have been previously reported in CAE. These morphological changes, even if they might be very subtle, are not independent due to the underlying network structure and can be captured by the structural covariance network (SCN). In this study, SCNs were used to quantify the structural brain network for children with CAE as well as controls. Seventeen children with CAE (6-12y) and fifteen controls (6-12y) were included. To estimate the SCN, T1-weighted images were acquired and parcellated into 68 cortical regions. Graph measures characterizing the core network architecture, i.e. the assortativity and rich-club coefficient, were calculated for all individuals. Multivariable linear regression models, including age and sex as covariates, were used to assess differences between children with CAE and controls. Additionally, potential relations between the core network and cognitive performance was investigated. A lower assortativity (i.e. less efficiently organized core network organization) was found for children with CAE compared to controls. Moreover, better cognitive performance was found to relate to stronger assortative mixing pattern (i.e. more efficient core network structure). Rich-club coefficients did not differ between groups, nor relate to cognitions. The core network organization of the SCN in children with CAE tend to be less efficient organized compared to controls, and relates to cognitive performance, and therefore this study provides novel insights into the SCN organization in relation to CAE and cognition.
KW - assortativity
KW - Childhood absence epilepsy
KW - Cognitive performance
KW - cortical thickness
KW - graph theory
KW - structural covariance network
U2 - 10.1016/j.heliyon.2023.e22657
DO - 10.1016/j.heliyon.2023.e22657
M3 - Article
SN - 2405-8440
VL - 9
JO - Heliyon
JF - Heliyon
IS - 12
M1 - e22657
ER -