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Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study

Larivière, S; Rodríguez-Cruces, R; Royer, J; Caligiuri, ME; Gambardella, A; Concha, L; Keller, SS; ... Bernhardt, BC; + view all (2020) Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study. Science Advances , 6 (47) , Article eabc6457. 10.1126/sciadv.abc6457. Green open access

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Abstract

Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1021 adults with epilepsy compared to 1564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy colocalized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Negative effects of age on atrophy further revealed a strong influence of connectome architecture in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided deeper insights into the macroscale features that shape the pathophysiology of common epilepsies.

Type: Article
Title: Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1126/sciadv.abc6457
Publisher version: https://doi.org/10.1126/sciadv.abc6457
Language: English
Additional information: This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. See: https://creativecommons.org/licenses/by-nc/4.0/
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Experimental Epilepsy
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10116033
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