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

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.

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

“…e ., so-called ‘feeder nodes’, which directly link peripheral nodes to hubs). As in prior work 22 , this approach suggests that patterns of atrophy in left focal epilepsy are anchored to the connectivity profiles of mesiotemporal regions ( S upplementary F ig . 5A–C ).…”

“…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 .…”

“…As in prior work 22 , we selected a group of unrelated healthy adults ( n =207; 83 males, mean age±SD=28.73±3.73 years, range=22-36 years) from the HCP dataset 21 . HCP data were acquired on a Siemens Skyra 3T and included: ( i ) T1-weighted images (magnetization-prepared rapid gradient echo [MPRAGE] sequence, repetition time [TR]=2,400ms, echo time [TE]=2.14ms, field of view [FOV]=224×224 mm 2 , voxel size=0.7×0.7×0.7 mm, 256 slices), ( ii ) resting-state functional MRI (gradient-echo echo-planar imaging [EPI] sequence, TR=720 ms, TE=33.1 ms, FOV=208×180 mm 2 , voxel size=2 mm 3 , 72 slices), and ( iii ) diffusion MRI (spin-echo EPI sequence, TR=5,520 ms, TE=89.5ms, FOV=210×180, voxel size=1.25mm 3 , b -value=1,000/2,000/3,000 s/mm 2 , 270 diffusion directions, 18 b0 images).…”

“…We provide the ability to decode brain maps with respect to postmortem gene expression maps (based on microarray data from the Allen Human Brain Atlas 17 ), postmortem cytoarchitecture (using the von Economo-Koskinas classification of cortical cytoarchitecture and derivatives from the BigBrain dataset 18 ), and structural as well as functional connectome properties (from the Human Connectome Project 19 ). 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 16,20 .…”

Emerging Trends in Neuroimaging of Epilepsy

“…In this context, Open Science 47 collaborative efforts are expected to catalyze translation of advanced analytic methods. A leading example is the ENIGMA-Epilepsy consortium, 48 which has used meta- and mega-analyses to assess group-level morphology, 49 microstructure, and network models 50 of structural compromise across thousands of patients. Knowledge derived from these large-scale studies is expected to set the basis of novel, clinically applicable individualized disease biomarkers.…”