Network-based atrophy modelling in the common epilepsies: a worldwide ENIGMA study

Abstract

Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional megaanalysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1,021 adults with epilepsy compared to 1,564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy co-localized 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. Indices of progressive atrophy further revealed a strong influence of connectome architecture on disease progression 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 novel insights into the macroscale features that shape the pathophysiology of common epilepsies.Larivière et al.Atrophy modelling in the common epilepsies | 4

The ENIGMA Toolbox: Cross-disorder integration and multiscale neural contextualization of multisite neuroimaging datasets

“…To exemplify the potential of macroscale network modeling, our toolbox provides detailed tutorials on how to relate ENIGMA-based surface maps to normative connectome properties derived from functional and diffusion MRI. Building on prior neurodegenerative 46,57 and psychiatric 70 research, as well as recent work from our group 22 , Toolbox users can build hub susceptibility models to assess the vulnerability of highly connected network hubs to disease-related effects. Given their role in integrative processing, as well as their high topological value and biological cost, hub regions have been hypothesized to be preferentially susceptible to diverse pathological perturbations 71,72 .…”

“…Moreover, disease epicenters do not necessarily represent hub regions, but may rather be connected to them (i.e., so-called 'feeder nodes', which directly link peripheral nodes to hubs). As in prior work 22 focal epilepsy are anchored to the connectivity profiles of mesiotemporal regions (SUPPLEMENTARY FIG. 5A-C).…”

“…Prior work studying network underpinnings of morphological abnormalities in neurodegenerative and psychiatric disorders has demonstrated that hubs (i.e., brain regions with many connections) typically show greater atrophy than locally-connected peripheral nodes 57,58 . Within the ENIGMA Epilepsy Working Group, we recently tested this hypothesis using data from 1,021 individuals with epilepsy and 1,564 healthy controls, and also showed that atrophy preferentially colocalized with highly interconnected hub regions in the common epilepsies 22 . A series of follow-up ENIGMA studies are currently underway to assess these network-level effects in other disorders.…”

“…To further investigate whether disease-related morphological abnormalities (e.g., atrophy) follow overarching principles of connectome organization, one can identify disease epicenters. Disease epicenters are regions whose functional and/or structural connectivity profile spatially resembles a given disease-related atrophy map 22,[44][45][46] . Hence, disease epicenters can be identified by spatially correlating every region's healthy functional and/or structural connectivity profiles to whole-brain atrophy patterns in a given disease.…”

“…We provide the ability to decode ENIGMA-type brain maps with respect to postmortem gene expression maps (from the Allen Human Brain Atlas 19 ), postmortem cytoarchitecture (from the BigBrain project 20 ), and structural as well as functional connectome properties (from the Human Connectome Project 21 ). We provide several start-to-finish tutorials to show how these workflows can offer neurobiological and system-level insights into how regional effects, for example disease-related atrophy patterns, co-vary with transcriptomic, microstructural, and macrolevel properties, similar to recently published ENIGMA studies 18,22 .…”