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. 2018 Jan 30;141(2):391–408. doi: 10.1093/brain/awx341

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Christopher D Whelan 1,2,✉, Andre Altmann 3, Juan A Botía 4, Neda Jahanshad 1, Derrek P Hibar 1, Julie Absil 5, Saud Alhusaini 2,6, Marina K M Alvim 7, Pia Auvinen 8,9, Emanuele Bartolini 10,11, Felipe P G Bergo 7, Tauana Bernardes 7, Karen Blackmon 12,13, Barbara Braga 7, Maria Eugenia Caligiuri 14, Anna Calvo 15, Sarah J Carr 16, Jian Chen 17, Shuai Chen 18,19, Andrea Cherubini 14, Philippe David 5, Martin Domin 20, Sonya Foley 21, Wendy França 7, Gerrit Haaker 22,23, Dmitry Isaev 1, Simon S Keller 24, Raviteja Kotikalapudi 25,26, Magdalena A Kowalczyk 27, Ruben Kuzniecky 12, Soenke Langner 20, Matteo Lenge 10, Kelly M Leyden 28,29, Min Liu 30, Richard Q Loi 28,29, Pascal Martin 25, Mario Mascalchi 31,32, Marcia E Morita 7, Jose C Pariente 15, Raul Rodríguez-Cruces 33, Christian Rummel 34, Taavi Saavalainen 9,35, Mira K Semmelroch 27, Mariasavina Severino 36, Rhys H Thomas 37,38, Manuela Tondelli 39, Domenico Tortora 36, Anna Elisabetta Vaudano 39, Lucy Vivash 40,41, Felix von Podewils 42, Jan Wagner 43,44, Bernd Weber 43,45, Yi Yao 46, Clarissa L Yasuda 7, Guohao Zhang 47, Nuria Bargalló 15,48, Benjamin Bender 26, Neda Bernasconi 30, Andrea Bernasconi 30, Boris C Bernhardt 30,49, Ingmar Blümcke 23, Chad Carlson 12,50, Gianpiero L Cavalleri 2,51, Fernando Cendes 7, Luis Concha 33, Norman Delanty 2,51,52, Chantal Depondt 53, Orrin Devinsky 12, Colin P Doherty 51,54, Niels K Focke 25,55, Antonio Gambardella 14,56, Renzo Guerrini 10,11, Khalid Hamandi 37,38, Graeme D Jackson 27,57, Reetta Kälviäinen 8,9, Peter Kochunov 58, Patrick Kwan 41, Angelo Labate 14,56, Carrie R McDonald 28,29, Stefano Meletti 39, Terence J O'Brien 41,59, Sebastien Ourselin 3, Mark P Richardson 16,60, Pasquale Striano 61, Thomas Thesen 12,13, Roland Wiest 34, Junsong Zhang 18,19, Annamaria Vezzani 62, Mina Ryten 4,63, Paul M Thompson 1, Sanjay M Sisodiya 64,65,✉
PMCID: PMC5837616  PMID: 29365066

Structural MRI abnormalities are inconsistently reported in epilepsy. In the largest neuroimaging study to date, Whelan et al. report robust structural alterations across and within epilepsy syndromes, including shared volume loss in the thalamus, and widespread cortical thickness differences. The resulting neuroanatomical map will guide prospective studies of disease progression.

Keywords: epilepsy, MRI, thalamus, precentral gyrus

Abstract

Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen’s d = −0.24 to −0.73; P < 1.49 × 10−4), and lower thickness in the precentral gyri bilaterally (d = −0.34 to −0.52; P < 4.31 × 10−6). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = −1.73 to −1.91, P < 1.4 × 10−19), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = −0.36 to −0.52; P < 1.49 × 10−4). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = −0.29 to −0.54; P < 1.49 × 10−4). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = −0.27 to −0.51; P < 1.49 × 10−4). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < −0.0018; P < 1.49 × 10−4). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.

Introduction

Epilepsy is a prevalent neurological disorder, comprising many different syndromes and conditions, affecting 0.6–1.5% of the population worldwide (Bell et al., 2014). Approximately one-third of affected individuals do not respond to antiepileptic drug therapy (French, 2007). Alternative treatment options may not be appropriate (Englot et al., 2011), and are not always effective (Téllez-Zenteno et al., 2005; Englot et al., 2011). The identification of shared biological disease pathways may help elucidate diagnostic and prognostic biomarkers and therapeutic targets, which, in turn, could help to optimize individual treatment (Pitkänen et al., 2016). However, disease biology remains unexplained for most cases—especially in commonly occurring epilepsies.

Epilepsy is a network disorder typically involving widespread structural alterations beyond the putative epileptic focus (Bernhardt et al., 2015; Vaughan et al., 2016). Hippocampal sclerosis is a common pathological substrate of mesial temporal lobe epilepsy (MTLE), but extrahippocampal abnormalities are also frequently observed in MTLE, notably in the thalamus (Keller and Roberts, 2008; Coan et al., 2014; Alvim et al., 2016) and neocortex (Keller and Roberts, 2008; Bernhardt et al., 2009b, 2010; Blanc et al., 2011; Labate et al., 2011; Vaughan et al., 2016). Neocortical abnormalities are also reported in idiopathic generalized epilepsies (IGE) (Bernhardt et al., 2009a), and many childhood syndromes (O’Muircheartaigh et al., 2011; Vollmar et al., 2011; Ronan et al., 2012; Overvliet et al., 2013). Thus, common epilepsies may be characterized by shared disturbances in distributed cortico-subcortical brain networks (Berg et al., 2010), but the pattern, consistency and cause of these disturbances, and how they relate to functional decline (Vlooswijk et al., 2010; Bernasconi, 2016; Nickels et al., 2016), are largely unknown.

Currently, we lack reliable data from large cross-sectional neuroimaging, brain tissue, or biomarker studies in the common epilepsies. Brain tissue is not available from large cohorts of patients: common forms of epilepsy are often unsuitable for surgical treatment, so biopsied tissues are simply unavailable in sufficient numbers for research into disease biology. Brain-wide post-mortem studies also require extensive effort for comprehensive analysis. MRI offers detailed information on brain structure, but MRI measures from groups of individuals with and without epilepsy are not always consistent. For example, MTLE is associated with hippocampal sclerosis in up to 70% of brain MRI scans (Blümcke et al., 2013). However, the effects of laterality, and the extent of extrahippocampal grey matter loss are inconsistently reported in studies of left versus right MTLE (Kemmotsu et al., 2011; Liu et al., 2016). Similarly, abnormalities of the basal ganglia, hippocampus, lateral ventricles, and neocortex have all been reported in IGE (Betting et al., 2006), but most alterations are non-specific, and visual inspection of clinical MRI in IGE is typically normal (Woermann et al., 1998). Genome-wide association studies (GWAS) have identified genetic variants associated with complex epilepsies by ‘lumping’ different epilepsy types together (International League Against Epilepsy Consortium on Complex Epilepsies, 2014), but MRI studies are typically of smaller scale, and have not widely explored whether distinct epilepsy syndromes share common structural abnormalities.

There are many sources of inconsistency in previously reported MRI findings. First, epileptic seizures and syndromes are diverse; classifications are often revised and contested (Berg et al., 2010; Scheffer et al., 2017). Second, most cross-sectional brain imaging studies are based on small samples (typically <50 cases), limiting the power to detect subtle group differences (Button et al., 2013). Third, variability in scanning protocols, image processing, and statistical analysis may affect the sensitivity of brain measures across studies.

The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium was formed to address these issues (Bearden and Thompson, 2017). ENIGMA is a global initiative, combining large samples with coordinated image processing, and integrating genomic and MRI data across hundreds of research centres worldwide. Prior ENIGMA studies have identified genetic variants associated with variations in brain structure (Stein et al., 2012; Hibar et al., 2015, 2017a; Adams et al., 2016), and have reliably characterized patterns of brain abnormalities in schizophrenia (van Erp et al., 2016), major depression (Schmaal et al., 2016), obsessive compulsive disorder (Boedhoe et al., 2017), attention deficit hyperactivity disorder (Hoogman et al., 2017), and many other brain illnesses (Thompson et al., 2017). Large-scale, collaborative initiatives such as ENIGMA may improve our understanding of epilepsy, helping clinicians make more informed decisions and provide personalized treatment strategies (Ben-Menachem, 2016). Thus, we formed the Epilepsy Working Group of ENIGMA (‘ENIGMA-Epilepsy’) to apply coordinated, well-powered studies of imaging and genetic data in epilepsy.

Here, in the largest analysis of structural brain abnormalities in epilepsy to date, we ranked effect sizes for 16 subcortical and 68 cortical brain regions in 2149 individuals with epilepsy and 1727 healthy controls, using harmonized image processing, quality control, and meta-analysis. First, we grouped all epilepsies together, to determine whether biologically distinct syndromes show robust, common structural deficits. Second, we assessed a well-characterized form of epilepsy: MTLE with hippocampal sclerosis, analysing patients with left- and right-sided hippocampal sclerosis as independent groups. Third, we examined another major set of epilepsy syndromes: IGE. Finally, we studied all remaining epilepsies as a combined subgroup, to understand the relative contributions of IGE, MTLE-L, MTLE-R, and all other syndromes on shared patterns of structural compromise. We tested how age at scan, age of onset, and epilepsy duration affected brain structural measures. Based on existing neuroimaging (Gotman et al., 2005; Bernhardt et al., 2009a; Liu et al., 2016), neurophysiological (Gotman et al., 2005), neuropathological (Thom et al., 2009), and genetic data (International League Against Epilepsy Consortium on Complex Epilepsies, 2014), we predicted that (i) biologically distinct epilepsy syndromes would exhibit shared patterns of structural abnormalities; (ii) MTLEs with left or right hippocampal sclerosis would show distinct patterns of hippocampal and extrahippocampal structural deficits; and (iii) IGEs would also display subcortical volume and cortical thickness differences, compared to healthy controls.

Materials and methods

Each centre received approval from their local institutional review board or ethics committee. Written informed consent was provided according to local requirements (Supplementary Table 1).

Experimental design

Participants

Twenty-four cross-sectional samples from 14 countries were included in the study, totalling 2149 people with epilepsy and 1727 research centre-matched healthy control subjects (Fig. 1 and Table 1). The locations, dates, and periods of participant recruitment are provided in Supplementary Table 1. An epilepsy specialist assessed seizure and syndrome classifications at each centre, using International League Against Epilepsy terminology (Berg et al., 2010). Participants were aged 18–55.

Figure 1.

Figure 1

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Study flowchart. ILAE = International League Against Epilepsy; MOU = memorandum of understanding.

Table 1.

ENIGMA - Epilepsy Working Group demographics, including age (in years), mean age at onset of epilepsy (in years), mean duration of illness (in years), sex, and case-control breakdown for participating sites

Site name Age controls (Mean ± SD) Age cases (Mean ± SD) Age of onset (Mean ± SD) Duration of illness (Mean ± years) Female controls Female cases Total controls Total cases MTLE-L cases MTLE-R cases IGE cases ‘Other’ cases Total n
Bern 32.5 ± 9.39 30.48 ± 10.13 - - 41 28 78 56 10 8 12 26 134
Bonn 40.11 ± 13.4 39.68 ± 13.4 16.86 ± 11.96 22.82 ± 14.18 40 60 77 108 71 37 0 0 185
BRI 34.73 ± 10.61 33.28 ± 10.59 17.9 ± 11.49 17.9 ± 12.93 49 46 112 79 10 13 18 38 191
Brussels 26.64 ± 4.34 33.79 ± 9.9 14.46 ± 10.13 19.02 ± 12.77 24 49 44 83 11 0 (4) 8 60 127
CUBRIC 28.04 ± 8.16 28.42 ± 8.06 13.56 ± 5.18 14.81 ± 9.91 34 34 48 48 0 0 44 0 (4) 96
EKUT_A 34.82 ± 11.38 33.58 ± 11.07 17.04 ± 11.09 16.84 ± 13.18 30 28 49 47 6 0 5 36 96
EKUT_B 35.33 ± 12.27 31.13 ± 10.74 17.32 ± 10.8 14.45 ± 11.14 9 18 18 24 0 0 16 8 42
EPICZ 30.48 ± 9.39 30.42 ± 10.13 - - 59 71 116 113 19 27 0 67 229
EPIGEN_3.0 34.75 ± 9.36 36.2 ± 9.97 17.03 ± 13.7 18.93 ± 10.88 30 37 70 60 8 5 0 47 130
EPIGEN_1.5 31.7 ± 9.24 37.46 ± 10.69 14.51 ± 11.8 22.68 ± 14.28 24 35 47 52 27 25 0 0 99
Florence 35.29 ± 8.48 28 ± 7.77 12.69 ± 8.02 14.27 ± 8.06 8 12 14 31 0 (1) 0 5 25 45
Greifswald 42.26 ± 14.97 26.23 ± 7.49 28.12 ± 17.86 14.13 ± 12.81 60 21 99 39 0 0 39 0 138
IDIBAPS-HCP 33.13 ± 5.99 36.77 ± 9.52 18.07 ± 11.72 17.64 ± 10.51 29 67 52 115 17 36 0 (3) 59 167
KCL_CNS 31.68 ± 8.4 33.2 ± 8.9 13.22 ± 8.2 20.67 ± 11.23 54 50 101 96 5 0 (4) 32 55 197
KCL_CRF 28.73 ± 8.29 31.47 ± 11.33 23.13 ± 7.55 8.33 ± 9.99 16 7 26 15 0 (3) 0 (2) 0 (4) 6 41
Kuopio 25.16 ± 1.55 33.35 ± 11.21 24 ± 13.22 9.35 ± 11.23 33 135 67 240 0 9 36 195 307
MNI 30.74 ± 7.38 32.53 ± 9.92 16.48 ± 9.72 16.05 ± 11.32 21 71 46 128 45 38 0 45 174
NYU 30.1 ± 10.36 33.23 ± 9.66 16.96 ± 11.27 16.43 ± 12.7 62 93 118 159 8 11 36 104 277
RMH 39.35 ± 20.26 38.08 ± 15.91 28.23 ± 17.98 10.18 ± 12.65 12 70 28 146 22 13 25 86 174
UCSD 36.89 ± 15.1 37.67 ± 11.79 19.32 ± 14.77 18.8 ± 15.36 16 22 37 43 14 8 0 21 80
UNAM 33.2 ± 12.29 31.47 ± 11.81 16.26 ± 11.33 15.03 ± 12.53 25 24 35 36 10 10 0 16 71
UNICAMP 34.39 ± 10.45 39.98 ± 10.25 12.07 ± 9.52 27.96 ± 12.54 249 183 398 291 107 84 40 60 689
UNIMORE 28.47 ± 5.25 28.36 ± 10.26 12.58 ± 8.13 14.34 ± 10.94 20 47 34 82 0 (3) 0 (2) 40 37 116
XMU 31.54 ± 6.99 28.79 ± 9.06 17.04 ± 12.2 11.76 ± 8.78 4 20 13 58 25 15 11 7 71
Combined 33.31 ± 9.91 34.36 ± 10.65 17.63 ± 11.47 17.42 ± 11.99 949 1228 1727 2149 415 339 367 1028 3876
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Also provided is the total number of MTLE cases with left hippocampal sclerosis, MTLE cases with right hippocampal sclerosis, IGE and all-other-epilepsies (‘other’) cases per site. Research centres with fewer than five participants for a given phenotype are marked as ‘0’ for that phenotype, with the original sample size noted in parentheses.

SD = standard deviation.

To test for shared and syndrome-specific structural alterations, analyses included one group combining all epilepsies (‘all-epilepsies’; n = 2149), and four stratified subgroups: (i) left MTLE with left hippocampal sclerosis (MTLE-L; n = 415); (ii) right MTLE with right hippocampal sclerosis (MTLE-R; n = 339); (iii) IGE (n = 367); and (iv) all other epilepsies (n = 1028). Supplementary Table 2 lists all syndromic diagnoses included in the aggregate ‘all-epilepsies’ group. For the MTLE subgroups, we included anyone with the typical electroclinical constellation (Berg et al., 2010), and a neuroradiologically-confirmed diagnosis of unilateral hippocampal sclerosis on clinical MRI. Participants were included in the IGE subgroup if they presented with tonic-clonic, absence or myoclonic seizures with generalized spike-wave discharges on EEG. Participants were included in the ‘all-other-epilepsies’ subgroup if they were diagnosed with non-lesional MTLE (43.3%), occipital (1.67%), frontal (8.78%), or parietal lobe epilepsy (0.84%), focal epilepsies not otherwise specified (37.03%), or another unclassified syndrome (8.37%; Supplementary Table 2). We excluded participants with a progressive disease (e.g. Rasmussen’s encephalitis), malformations of cortical development, tumours or previous neurosurgery.

MRI data collection and processing

Structural T1-weighted MRI brain scans were collected at the 24 participating centres. Scanning details are provided in Supplementary Table 3. T1-weighted images from cases and controls were analysed at each site using FreeSurfer 5.3.0, for automated analysis of brain structure (Fischl, 2012). Volumetric measures were extracted for 12 subcortical grey matter regions (six left and six right, including the amygdala, caudate, nucleus accumbens, pallidum, putamen, and thalamus), the left and right hippocampi, and the left and right lateral ventricles. Cortical thickness measures were extracted for 34 left-hemispheric grey matter regions, and 34 right-hemispheric grey matter regions (68 total; Supplementary Table 4). Visual inspections of subcortical and cortical segmentations were conducted following standardized ENIGMA protocols (http://enigma.usc.edu), used in prior genetic studies of brain structure (Stein et al., 2012; Hibar et al., 2015, 2017a; Adams et al., 2016), and large-scale case-control studies of neuropsychiatric illnesses (Schmaal et al., 2015, 2016; Hibar et al., 2016; van Erp et al., 2016; Boedhoe et al., 2017). Analysts were blind to participants’ diagnoses. Each analyst was instructed to execute a series of standardized bash scripts, identifying participants with volumetric or thickness measures greater or less than 1.5 times the interquartile range as outliers. Outlier data were then visually inspected, by overlaying the participant’s cortical segmentations on their whole-brain anatomical images. If the blinded local analyst judged any structure as inaccurately segmented, that structure was omitted from the analysis. The Supplementary material provides further information.

Statistical analysis

Participant demographics

All research centres tested for differences in age between individuals with epilepsy and controls using an unpaired, two-tailed t-test in the R statistics package (https://www.r-project.org). Each centre also tested for sex differences between individuals with epilepsy and controls using a chi-squared test in SPSS Statistics package (IBM Corp., Version 21.0).

Meta-analytical group comparisons

Each research centre tested for case-versus-control differences using multiple linear regressions (via the lm function implemented in R), where a binary indicator of diagnosis (0 = healthy control, 1 = person with epilepsy) was the predictor of interest, and the volume or thickness of a specified brain region was the outcome measure. We calculated effect size estimates across all brain regions using Cohen’s d, adjusting for age, sex and intracranial volume (ICV). ICV is a reliable, indirect measure of head size (Hansen et al., 2015), used as a covariate in other large-scale ENIGMA collaborations (Schmaal et al., 2015, 2016; Hibar et al., 2016; van Erp et al., 2016; Boedhoe et al., 2017). Cohen’s d effect sizes and regression beta coefficients were pooled across centres using a random-effects, restricted maximum likelihood method of meta-analysis via the R package, metafor (Viechtbauer, 2010). The Supplementary material provides additional details.

Meta-analytical regression with clinical variables

Each centre conducted a series of linear regressions, testing the association between subcortical volume or cortical thickness, and: (i) age at onset of epilepsy; and (ii) duration of epilepsy. All centres tested for interactions between diagnosis of epilepsy (including syndrome groups) and age at time of scan. Beta values representing the unstandardized slopes of each regression were extracted for each analysis. Sex and ICV were included as covariates in all secondary analyses.

Correction for multiple comparisons

We conducted four independent regressions (one case versus control regression, and three regressions with clinical variables) across 84 regions of interest, adjusting the statistical significance threshold to Pthresh < 1.49 × 10−4 to correct for 336 comparisons. To account for correlations between tests, we also applied a less conservative adjustment for false discovery rate (FDR), using the Benjamini and Hochberg method (Benjamini and Hochberg, 1995). For clarity, we report only P-values significant after stringent Bonferroni correction; FDR-adjusted P-values are summarized in the Supplementary material.

Power analyses

Across all regions of interest, we calculated the sample sizes necessary to achieve 80% power to detect case-control differences, given the observed effect sizes at each region of interest, based on two-tailed t-tests, using G*Power Version 3.1. For each region of interest, we also estimated N80: the total number of samples required, per group, to achieve 80% power to detect group differences using a t-test at the threshold of P < 0.05 (two-tailed).

Results

Participant demographics

The sample size-weighted mean age across all epilepsy samples was 34.4 (range: 26.2–40) years, and the weighted mean age of healthy controls was 33.3 (range: 25.2–42.3) years. The weighted mean age at onset of epilepsy and duration of epilepsy were 17.6 (range: 12.1–28.2) years and 17.4 (range: 8.3–28) years, respectively. Females comprised 57% of the total epilepsy sample (range: 34–75% by individual sample), and 53% of the controls (range: 31–71% by individual sample). Case-control differences in age were observed at 8 of 24 research centres, and case-control differences in sex were observed at 2 of 24 research centres (Supplementary Table 5); hence, age and sex were included as covariates in all group comparisons.

Volumetric findings

Compared to controls, the aggregate all-epilepsies group exhibited lower volumes in the left (d = −0.36; P = 1.31 × 10−6) and right thalamus (d = −0.37; P = 7.67 × 10−14), left (d = −0.35; P = 3.04 × 10−7) and right hippocampus (d = −0.34; P = 6.63 × 10−10), and the right pallidum (d = −0.32; P = 8.32 × 10−9). Conversely, the left (d = 0.29; P = 2.14 × 10−12) and right (d = 0.27; P = 3.73 × 10−15) lateral ventricles were enlarged across all epilepsies when compared to controls (Table 2 and Fig. 2A). A supplementary analysis of all-epilepsies, excluding individuals with hippocampal sclerosis or other lesions, revealed similar patterns of volume loss in the right thalamus and pallidum, and bilaterally enlarged ventricles; however, volume differences were not observed in the hippocampus (Supplementary Table 6).

Table 2.

Effect size differences between epilepsy cases and healthy controls (Cohen’s d) for the mean volume of subcortical structures, controlling for age, sex and intracranial volume

Structure Phenotype Cohen’s d SE Z score 95% CI P-value I2 N80 Number of controls Number of cases
Amygdala (LH) All-other-epilepsies 0.327 0.065 5.024 0.199–0.455 5.05 x 10−7 45.470 148 1448 998
Amygdala (RH) All-other-epilepsies 0.218 0.057 3.799 0.106–0.33 1.46 x 10−4 31.256 335 1422 989
Hippocampus (LH) MTLE-L −1.728 0.191 −9.056 −2.102 to −1.354 1.35 x 10−19 85.532 7 1412 410
All epilepsies −0.353 0.069 −5.121 −0.488 to −0.217 3.04 x 10−7 71.845 127 1707 2125
Hippocampus (RH) MTLE-R −1.906 0.15 −12.694 −2.2 to −1.611 6.36 x 10−37 72.476 6 1286 336
All epilepsies −0.336 0.054 −6.175 −0.443 to −0.229 6.63 x 10−10 54.801 141 1719 2129
Lateral ventricle (LH) MTLE-L 0.465 0.089 5.203 0.289–0.640 1.96 x 10−7 43.124 74 1417 414
MTLE-R 0.39 0.081 4.808 0.231–0.549 1.52 x 10−6 26.750 105 1291 338
All epilepsies 0.288 0.041 7.025 0.207–0.368 2.14 x 10−12 23.338 191 1722 2135
All-other-epilepsies 0.198 0.045 4.373 0.109–0.287 1.23 x 10−5 0.218 402 1452 996
Lateral ventricle (RH) MTLE-R 0.444 0.065 6.867 0.317−0.57 6.57 x 10−12 0.003 81 1292 338
MTLE-L 0.363 0.093 3.917 0.1814−0.544 8.95 x 10−5 47.227 121 1418 414
All epilepsies 0.268 0.034 7.864 0.2−0.334 3.73 x 10−15 0 220 1722 2137
All-other-epilepsies 0.212 0.046 4.581 0.122−0.303 4.62 x 10−6 3.528 350 1453 996
Pallidum (RH) MTLE-L −0.452 0.09 −5.009 −0.628 to −0.275 5.48 x 10−7 43.985 78 1406 414
MTLE-R −0.451 0.089 −5.071 −0.624 to −0.276 3.96 x 10−7 36.432 79 1278 332
All epilepsies −0.316 0.055 −5.762 −0.424 to −0.208 8.32 x 10−9 55.575 159 1710 2112
All-other-epilepsies −0.235 0.060 −3.942 −0.352 to −0.118 8.07 x 10−5 36.141 286 1440 976
Putamen (LH) MTLE-L −0.385 0.079 −4.878 −0.539 to −0.23 1.07 x 10−6 28.474 107 1352 410
Thalamus (LH) MTLE-L −0.843 0.126 −6.693 −1.089 to −0.595 2.19 x 10−11 70.462 24 1384 408
All epilepsies −0.358 0.074 −4.839 −0.503 to −0.213 1.31 x 10−6 75.649 124 1687 2104
Thalamus (RH) MTLE-R −0.727 0.103 −7.066 −0.928 to −0.525 1.60 x 10−12 51.499 31 1285 335
MTLE-L −0.462 0.117 −3.941 −0.691 to −0.232 8.12 x 10−5 67.376 75 1412 414
IGE −0.403 0.087 −4.633 −0.574 to −0.233 3.60 x 10−6 39.715 98 1210 363
All epilepsies −0.368 0.049 −7.476 −0.464 to −0.271 7.67 x 10−14 44.822 117 1716 2137
All-other-epilepsies −0.305 0.047 −6.502 −0.397 to −0.213 7.92 x 10−11 4.985 170 1446 998
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CI = confidence interval; LH = left hemisphere; RH = right hemisphere; SE = standard error; I2 = heterogeneity index; N80 = number of subjects required in each group to yield 80% power to detect significant group differences (P < 0.05, two-tailed). Uncorrected P-values are reported. Subcortical structures that failed to survive Bonferroni correction (P < 1.49 x 10−4) are not reported (see ‘Materials and methods’ section for statistical threshold determination). See Supplementary material for a full list of volume differences with adjustment for false discovery rate (FDR).

Figure 2.

Figure 2

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Subcortical volume findings. Cohen’s d effect size estimates for case-control differences in subcortical volume, across the (A) all-epilepsies, (B) mesial temporal lobe epilepsies with left hippocampal sclerosis (HS; MTLE-L), (C) mesial temporal lobe epilepsies with right hippocampal sclerosis (MTLE-R), (D) idiopathic generalized epilepsies (IGE), and (E) all-other-epilepsies groups. Cohen’s d effect sizes were extracted using multiple linear regressions, and pooled across research centres using random-effects meta-analysis. Subcortical structures with P-values < 1.49 × 10−4 are shown in heatmap colours; strength of heat map is determined by the size of the Cohen’s d (d < 0 = blue, d > 0 = yellow/red). Image generated using MATLAB, with annotations added using Adobe Photoshop. An interactive version of this figure is available online, via ‘ENIGMA-Viewer’: http://enigma-viewer.org/ENIGMA_epilepsy_subcortical.html. See Supplementary material for guidelines on how to use the interactive visualization.

The MTLE-L subgroup showed lower volumes in the left hippocampus (d = −1.73; P = 1.35 × 10−19), left (d = P = 2.19 × 10−11) and right thalamus (d = −0.46; P = 8.12 × 10−5), left putamen (d = −0.39; P = 1.07 × 10−6), and right pallidum (d = −0.45; P = 5.48 × 10−7). As in the overall group comparison, we observed larger left (d = 0.47; P = 1.96 × 10−7) and right lateral ventricles (d = 0.36; P = 8.95 × 10−5) in MTLE-L patients relative to controls (Table 2 and Fig. 2B).

The MTLE-R subgroup showed lower volumes across a number of regions in the right hemisphere only, including the hippocampus (d = −1.91; P = 6.36 × 10−37), thalamus (d = −0.73; P = 1.6 × 10−12), and pallidum (d = −0.45; P = 3.96 × 10−7), together with increased volumes of the left (d = 0.39; P = 1.52 × 10−6) and right lateral ventricles (d = 0.44; P = 6.57 × 10−12) compared to controls (Table 2 and Fig. 2C).

The IGE subgroup showed lower volumes in the right thalamus (d = −0.4; P = 3.6 × 10−6) compared to controls (Table 2 and Fig. 2D).

The all-other-epilepsies subgroup showed lower volumes in the right thalamus (d = −0.31; P = 7.9 × 10−11) and the right pallidum (d = −0.24; P = 8.1 × 10−5) compared to controls. The all-other-epilepsies subgroup also showed significant enlargements of the left (d = 0.33; P = 5.1 × 10−7) and right amygdala (d = 0.22; P = 1.46 × 10−4), and the left (d = 0.2; P = 1.2 × 10−5) and right lateral ventricles (d = 0.21; P = 4.62 × 10−6) compared to controls (Table 2 and Fig. 2E).

All volume differences can be visualized using the interactive ENIGMA-Viewer tool (Zhang et al., 2017), at http://enigma-viewer.org/ENIGMA_epilepsy_subcortical.html (Supplementary material). Volume differences significant after FDR adjustment can also be visualized at http://enigma-viewer.org/ENIGMA_epilepsy_subcortical_fdr.html (Supplementary Tables 26–30).

Cortical thickness findings

The all-epilepsies group showed reduced thickness of cortical grey matter across seven regions bilaterally, including the left (d = −0.38; P = 1.82 × 10−18) and right precentral gyri (d = −0.4; P = 8.85 × 10−20), left (d = −0.32; P = 2.11 × 10−15) and right caudal middle frontal gyri (d = −0.31; P = 2.09 × 10−9), left (d = −0.31; P = 2.05 × 10−6) and right paracentral gyri (d = −0.32; P = 2.19 × 10−9), left (d = −0.19; P = 1.29 × 10−4) and right pars triangularis (d = −0.2; P = 4.25 × 10−8), left (d = −0.28; P = 1.51 × 10−7) and right superior frontal gyri (d = −0.27; P = 4.49 × 10−6), left (d = −0.19; P = 1.05 × 10−5) and right transverse temporal gyri (d = −0.18; P = 2.81 × 10−5), and left (d = −0.23; P = 9.87 × 10−5) and right supramarginal gyri (d = −0.22; P = 5.24 × 10−5). The all-epilepsies group also showed unilaterally thinner right cuneus (d = −0.2; P = 9.68 × 10−8), right pars opercularis (d = −0.18; P = 6.48 × 10−7), right precuneus (d = −0.28; P = 2.7 × 10−5), and left entorhinal gyrus (d = −0.26; P = 2.04 × 10−5), compared to healthy controls (Table 3 and Fig. 3A). Supplementary analysis in a non-lesional epilepsy subgroup revealed a similar pattern of cortical thickness differences compared to controls, suggesting that the changes observed in our main analysis were not driven by the inclusion of patients with hippocampal sclerosis or other common lesions (Supplementary Table 7).

Table 3.

Effect size differences between epilepsy cases and healthy controls (Cohen’s d) for the mean thickness of cortical structures, controlling for age, sex and intracranial volume

Structure Phenotype Cohen’s d SE Z score 95% CI P-value I2 N80 Number of controls Number of cases
Caudal middle frontal gyrus (LH) MTLE-L −0.403 0.07 −5.789 −0.538 to −0.2663 7.07 x 10−9 13.807 98 1344 412
All epilepsies −0.319 0.04 −7.935 −0.397 to −0.24 2.11 x 10−15 17.112 156 1650 2061
All other epilepsies −0.291 0.045 −6.425 −0.38 to −0.202 1.32 x 10−10 0 197 1447 1000
Caudal middle frontal gyrus (RH) MTLE-L −0.441 0.087 −5.089 −0.611 to −0.271 3.61 x 10−7 39.444 82 1348 412
All epilepsies −0.307 0.051 −5.991 −0.407 to −0.206 2.09 x 10−9 46.443 168 1653 2059
All other epilepsies −0.212 0.045 −4.699 −0.301 to −0.124 2.62 x 10−6 0 350 1451 998
Cuneus (RH) All other epilepsies −0.234 0.045 −5.186 −0.323 to −0.146 2.15 x 10−7 0 288 1449 996
All epilepsies −0.204 0.038 −5.333 −0.279 to −0.129 9.68 x10−8 11.423 379 1651 2057
Entorhinal gyrus (LH) MTLE-L −0.445 0.072 −6.158 −0.5865 to −0.303 7.35 x 10−10 0 81 1102 303
All epilepsies −0.264 0.062 −4.261 −0.385 to −0.142 2.04 x 10−5 56.648 227 1402 1724
Fusiform gyrus (LH) MTLE-L −0.359 0.069 −5.183 −0.494 to −0.223 2.19 x 10−7 13.465 123 1339 412
Lateral occipital gyrus (RH) All other epilepsies −0.211 0.045 −4.659 −0.299 to −0.122 3.18 x 10−6 2.50 x 10−3 354 1450 997
Lingual gyrus (RH) All other epilepsies −0.180 0.045 −3.972 −0.268 to −0.091 7.12 x 10−5 1.25 x 10−2 491 1450 996
Paracentral gyrus (LH) MTLE-R −0.505 0.102 −4.944 −0.705 to −0.305 7.67 x 10−7 52.283 63 1292 338
MTLE-L −0.426 0.099 −4.313 −0.62 to −0.232 1.61 x 10−5 53.165 88 1344 412
All epilepsies −0.311 0.065 −4.748 −0.439 to −0.182 2.05 x 10−6 67.476 164 1650 2061
All other epilepsies −0.257 0.045 −5.680 −0.346 to −0.168 1.34 x 10−8 0 239 1447 1000
Paracentral gyrus (RH) MTLE-R −0.421 0.064 −6.538 −0.548 to −0.295 6.24 x 10−11 0.407 90 1296 338
MTLE-L −0.378 0.075 −5.021 −0.526 to −0.231 5.14 x 10−7 23.536 111 1348 412
All other epilepsies −0.351 0.045 −7.733 −0.44 to −0.262 1.05 x 10−14 3.43 x 10−3 129 1451 998
All epilepsies −0.315 0.053 −5.983 −0.418 to −0.212 2.19 x 10−9 49.261 160 1654 2059
Parahippocampal gyrus (LH) MTLE-L −0.3 0.073 −4.11 −0.444 to −0.1572 3.95 x 10−5 19.366 176 1335 410
Pars opercularis (RH) MTLE-R −0.271 0.071 −3.8 −0.411 to −0.131 1.45 x 10−4 12.105 215 1295 338
All epilepsies −0.177 0.036 −4.976 −0.247 to −0.107 6.48 x 10−7 2.624 503 1652 2059
Pars triangularis (LH) All epilepsies −0.192 0.05 −3.828 −0.2897 to −0.094 1.29 x 10−4 44.414 427 1650 2060
Pars triangularis (RH) MTLE-L −0.285 0.06 −4.738 −0.403 to −0.167 2.16 x 10−6 0 195 1346 412
All epilepsies −0.199 0.036 −5.48 −0.27 to −0.128 4.25 x 10−8 4.66 398 1652 2058
All other epilepsies −0.210 0.045 −4.650 −0.299 to −0.122 3.32 x 10−6 2.58 x 10−3 357 1449 998
Precentral gyrus (LH) MTLE-L −0.466 0.081 −5.755 −0.625 to −0.307 8.64 x 10−9 31.602 74 1339 412
MTLE-R −0.415 0.09 −4.596 −0.592 to −0.238 4.31 x 10−6 40.044 93 1287 338
All epilepsies −0.384 0.044 −8.768 −0.469 to −0.298 1.82 x 10−18 27.649 108 1645 2058
All other epilepsies −0.375 0.046 −8.237 −0.464 to −0.286 1.76 x 10−16 5.59 x 10−3 113 1442 997
IGE −0.342 0.071 −4.78 −0.482 to −0.201 1.75 x 10−6 0.003 136 1043 297
Precentral gyrus (RH) MTLE-R −0.52 0.086 −6.073 −0.687 to −0.352 1.25 x 10−9 33.288 60 1293 337
MTLE-L −0.492 0.078 −6.335 −0.6436 to −0.339 2.37 x 10−10 26.33 66 1345 412
All epilepsies −0.399 0.044 −9.102 −0.485 to −0.313 8.85 x 10−20 27.929 100 1649 2054
IGE −0.39 0.072 −5.442 −0.531 to −0.25 5.27 x 10−8 0.005 105 1044 295
All other epilepsies −0.348 0.045 −7.672 −0.437 to −0.259 1.70 x 10−14 0 131 1448 996
Precuneus (LH) MTLE-L −0.536 0.135 −3.965 −0.801 to −0.271 7.35 x 10−5 75.18 56 1343 412
All other epilepsies −0.178 0.047 −3.819 −0.27 to −0.087 1.34 x 10−4 4.474 497 1446 998
Precuneus (RH) MTLE-L −0.473 0.104 −4.558 −0.676 to −0.27 5.16 x 10−6 57.498 72 1348 412
All epilepsies −0.275 0.066 −4.197 −0.404 to −0.147 2.70 x 10−5 67.608 209 1654 2055
All other epilepsies −0.238 0.053 −4.471 −0.343 to −0.134 7.78 x 10−6 22.378 279 1451 994
Superior frontal gyrus (LH) MTLE-L −0.411 0.06 −6.804 −0.529 to −0.292 1.02 x 10−11 0 94 1343 412
All epilepsies −0.283 0.054 −5.251 −0.389 to −0.177 1.51 x 10−7 51.773 197 1649 2059
All other epilepsies −0.243 0.059 −4.138 −0.358 to −0.128 3.51 x 10−5 34.545 267 1446 999
Superior frontal gyrus (RH) MTLE-L −0.365 0.06 −6.051 −0.483 to −0.246 1.44 x 10−9 0 119 1345 412
All epilepsies −0.269 0.059 −4.588 −0.385 to −0.154 4.49 x 10−6 59.483 218 1650 2058
All other epilepsies −0.235 0.052 −4.489 −0.337 to −0.132 7.15 x 10−6 20.049 286 1448 997
Superior parietal gyrus (LH) All other epilepsies −0.224 0.045 −4.954 −0.313 to −0.136 7.27 x 10−7 0.001 314 1444 996
Superior parietal gyrus (RH) All other epilepsies −0.220 0.045 −4.864 −0.309 to −0.131 1.15 x 10−6 0.002 326 1450 997
Supramarginal gyrus (LH) All epilepsies −0.232 0.06 −3.894 −0.348 to −0.115 9.87 x 10−5 59.391 293 1606 1965
Supramarginal gyrus (RH) All epilepsies −0.223 0.055 −4.045 −0.331 to −0.115 5.24 x 10−5 52.895 317 1597 1971
All other epilepsies −0.206 0.047 −4.418 −0.297 to −0.115 9.95 x 10−6 0 371 1395 961
Temporal pole (LH) MTLE-L −0.315 0.068 −4.649 −0.447 to −0.182 3.33 x 10−6 10.901 160 1341 410
Transverse temporal gyrus (LH) MTLE-R −0.312 0.073 −4.249 −0.456 to −0.168 2.15 x 10−5 15.614 163 1289 338
All epilepsies −0.192 0.044 −4.406 −0.278 to −0.107 1.05 x 10−5 28.178 427 1647 2061
Transverse temporal gyrus (RH) All epilepsies −0.182 0.044 −4.188 −0.267 to −0.097 2.81 x 10−5 27.918 475 1654 2059
All other epilepsies −0.18 0.045 −3.982 −0.269 to −0.091 6.84 x 10−5 0.012 486 1451 998
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CI = confidence interval; LH = left hemisphere; RH = right hemisphere; SE = standard error; I2 = heterogeneity index; N80 = number of subjects required in each group to yield 80% power to detect significant group differences (P < 0.05, two-tailed). Uncorrected P-values are reported. Cortical regions that failed to survive Bonferroni correction (P < 1.49 x 10−4) are not reported (see ‘Materials and methods’ section for statistical threshold determination). See Supplementary material for a full list of cortical differences with adjustment for false discovery rate (FDR).

Figure 3.

Figure 3

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Cortical thickness findings. Cohen’s d effect size estimates for case-control differences in cortical thickness, across the (A) all-epilepsies, (B) mesial temporal lobe epilepsies with left hippocampal sclerosis (MTLE-L), (C) mesial temporal lobe epilepsies with right hippocampal sclerosis (MTLE-R), (D) idiopathic generalized epilepsies (IGE), and (E) all-other-epilepsies groups. Cohen’s d effect sizes were extracted using multiple linear regressions, and pooled across research centres using random-effects meta-analysis. Cortical structures with P-values < 1.49 × 10−4 are shown in heatmap colours; strength of heat map is determined by the size of the Cohen’s d (d < 0 = blue, d > 0 = yellow/red). Image generated using MATLAB with annotations added using Adobe Photoshop. An interactive version of this figure is available online, via ‘ENIGMA-Viewer’: http://enigma-viewer.org/ENIGMA_epilepsy_cortical.html. See Supplementary material for guidelines on how to use the interactive visualization. HS = hippocampal sclerosis.

The MTLE-L and MTLE-R subgroups showed distinct patterns of cortical thickness reductions when compared to healthy controls (Table 3, Fig. 3B and C). In MTLE-R, lower cortical thickness was reported across four motor regions, including the left (d = −0.51; P = 7.67 × 10−7) and right paracentral gyri (d = −0.42; P = 6.24 × 10−11), and the left (d = −0.42; P = 4.31 × 10−6) and right precentral gyri (d = −0.52; P = 1.25 × 10−9). The MTLE-R subgroup also showed thickness changes in the left transverse temporal gyrus (d = −0.31; P = 2.15 × 10−5), and right pars opercularis (d = −0.27; P = 1.45 × 10−4) (Table 3 and Fig. 3C). By contrast, in MTLE-L, lower thickness was observed across six regions of the motor cortex, including the left (d = −0.43; P = 1.61 × 10−5) and right paracentral gyri (d = −0.38; P = 5.14 × 10−7), left (d = −0.47; P = 8.64 × 10−9) and right precentral gyri (d = −0.49; P = 2.37 × 10−10), and left (d = −0.54; P = 7.35 × 10−5) and right precuneus (d = −0.47; P = 5.16 × 10−6). The MTLE-L group also showed thickness changes across five regions of the frontal cortex, including the left (d = −0.41; P = 1.02 × 10−11) and right superior frontal gyri (d = −0.37; P = 1.44 × 10−9), left (d = −0.4; P = 7.07 × 10−9) and right caudal middle frontal gyri (d = −0.44; P = 3.61 × 10−7), and the right pars triangularis (d = −0.29; P = 2.16 × 10−6). In MTLE-L, thickness alterations were also observed in four regions of the temporal cortex, including the left temporopolar cortex (d = −0.32; P = 3.33 × 10−6), left parahippocampal gyrus (d = −0.3; P = 3.95 × 10−5), left entorhinal gyrus (d = −0.45; P = 7.35 × 10−10), and left fusiform gyrus (d = −0.36; P = 2.19 × 10−7) (Table 3 and Fig. 3B).

The IGE subgroup showed reduced thickness in the left (d = −0.34; P = 1.75 × 10−6) and right precentral gyri (d = −0.39; P = 5.27 × 10−8), when compared to healthy controls (Table 3 and Fig. 3D).

The all-other-epilepsies subgroup showed lower thickness across six cortical regions bilaterally, including the left (d = −0.38; P = 1.76 × 10−16) and right precentral gyri (d = −0.35; P = 1.7 × 10−14), left (d = −0.26; P = 1.34 × 10−8) and right paracentral gyri (d = −0.35; P = 1.1 × 10−14), left (d = −0.29; P = 1.32 × 10−10) and right caudal middle frontal gyri (d = −0.21; P = 2.62 × 10−6), left (d = −0.22; P = 7.27 × 10−7) and right superior parietal gyri (d = −0.22; P = 1.15 × 10−6), left (d = −0.24; P = 3.51 × 10−5) and right superior frontal gyri (d = −0.23; P = 7.15 × 10−6), and the left (d = −0.18; P = 1.34 × 10−4) and right precuneus (d = −0.24; P = 7.78 × 10−6) compared to controls. The all-other-epilepsies group also showed unilaterally reduced thickness in six right hemispheric regions, including the cuneus (d = −0.23; P = 2.15 × 10−7), lateral occipital gyrus (d = −0.21; P = 3.18 × 10−6), pars triangularis (d = −0.21; P = 3.32 × 10−6), supramarginal gyrus (d = −0.21; P = 9.95 × 10−6), transverse temporal gyrus (d = −0.18; P = 6.84 × 10−5), and lingual gyrus (d = −0.18; P = 7.12 × 10−5), compared to controls (Table 3 and Fig. 3E).

An interactive 3D visualization of these results is available via the ENIGMA-Viewer tool (Zhang et al., 2017), at http://enigma-viewer.org/ENIGMA_epilepsy_cortical.html (Supplementary material). Cortical thickness differences significant after FDR adjustment can also be visualized at http://enigma-viewer.org/ENIGMA_epilepsy_cortical_fdr.html (Supplementary Tables 31–35).

Duration of illness, age at onset, and age-by-diagnosis effects on brain abnormalities

A secondary analysis identified significant associations between duration of epilepsy and several affected brain regions in the all-epilepsies, MTLE-R, and all-other-epilepsies groups. In the all-epilepsies group, duration of epilepsy negatively associated with volume measures in the left hippocampus (b = −8.32; P = 8.16 × 10−13), left (b = −13.58; P = 3.52 × 10−15), and right thalamus (b = −12.25; P = 1.58 × 10−13), and right pallidum (b = −2.67; P = 1.78 × 10−7), in addition to bilateral thickness measures in the left (b = −0.003; P = 2.99 × 10−11) and right pars triangularis (b = −0.002; P = 4.24 × 10−9), left (b = −0.003; P = 1.61 × 10−15) and right caudal middle frontal gyri (b = −0.003; P = 1.65 × 10−17), left (b = −0.003; P = 1.77 × 10−13) and right supramarginal gyri (b = −0.003; P = 2.58 × 10−19), left (b = −0.003; P = 5.84 × 10− 12) and right precentral gyri (b = −0.003; P = 2.54 × 10−24), left (b = −0.004; P = 1.94 × 10−12) and right superior frontal gyri (b = −0.003; P = 4.65 × 10−11), left (b = −0.004; P = 1.05 × 10−10) and right transverse temporal gyri (b = −0.003; P = 8.24 × 10−10), and left (b = −0.002; P = 5.22 × 10−6) and right paracentral gyri (b = −0.002; P = 5.63 × 10−6). Duration of epilepsy also negatively associated with unilateral thickness measures in the right precuneus (b = −0.003; P = 6.03 × 10−21), right pars opercularis (b = −0.003; P = 5.59 × 10−13), and right cuneus (b = −0.002; P = 1.1 × 10−9; Supplementary Table 8). In the MTLE-R subgroup, duration of epilepsy negatively associated with volume measures in the right hippocampus (b = −22.42; P = 1.1 × 10−7), and the right thalamus (b = −18.11; P = 1.84 × 10−5), and thickness measures in the left transverse temporal gyrus (b = −0.007; P = 8.39 × 10−5; Supplementary Table 8). In the all-other-epilepsies subgroup, duration of epilepsy negatively associated with bilateral thickness measures in the left (b = −0.003; P = 3.39 × 10−7) and right caudal middle frontal gyri (b = −0.003; P = 6.91 × 10−8), left (b = −0.003; P = 1.36 × 10−9) and right superior frontal gyri (b = −0.003; P = 3.16 × 10−7), and the left (b = −0.003; P = 3.17 × 10−5) and right precuneus (b = −0.003; P = 5.01 × 10−9), in addition to unilateral thickness measures in the right precentral gyrus (b = −0.004; P = 1.16 × 10−12), right cuneus (b = −0.003; P = 8.57 × 10−8), right pars triangularis (b = −0.003; P = 5.16 × 10−7), and right supramarginal gyrus (b = −0.003; P = 2.24 × 10−7). Duration of epilepsy also showed a positive association with the size of the left lateral ventricle in the all-other-epilepsies group (b = 13.6; P = 1.17 × 10−5).

In the all-epilepsies group, age at onset of epilepsy negatively associated with thickness measures in the left (b = −0.003; P = 2.66 × 10−15) and right superior frontal gyri (b = −0.003; P = 9.77 × 10−10), left (b = −0.003; P = 2.78 × 10−9) and right pars triangularis (b = −0.003; P = 6.51 × 10−7), right pars opercularis (b = −0.003; P = 5.4 × 10−14), left transverse temporal gyrus (b = −0.003; P = 1.03 × 10−8), and right cuneus (b = −0.001; P = 4.9 × 10−6). In the all-other-epilepsies subgroup, age at onset negatively correlated with thickness measures in the left (b = −0.003; P = 3.21 × 10−8) and right superior frontal gyri (b = −0.002; P = 1.18 × 10−4), left (b = −0.002; P = 8.42 × 10−6) and right precuneus (b = −0.002; P = 7.23 × 10−5), right pars triangularis (b = −0.003; P = 2.53 × 10−5), and right supramarginal gyrus (b = −0.002; P = 2.38 × 10−6). Age at onset also positively associated with the size of the right lateral ventricle in the all-other-epilepsies subgroup (b = 57.73; P = 1.62 × 10−7).

Age at onset negatively associated with other regional volumetric and thickness measures in the all-epilepsies, IGE, MTLE-L, MTLE-R, and all-other-epilepsies groups, but these associated areas showed no significant structural differences in the primary case-control analysis (Table 1 and Supplementary Table 8).

There were no interaction effects between age and syndromic diagnosis in the all-epilepsies, MTLE-L, MTLE-R, IGE, or all-other-epilepsies groups.

Power analyses for detection of case-control differences

In our sample of 2149 individuals with epilepsy and 1727 healthy controls, we had 80% power to detect Cohen’s d effect sizes as small as d = 0.091 at the standard alpha level of P < 0.05 (two-tailed), and 80% power to detect Cohen’s d effect sizes as small as d = 0.149 at the study’s stringent Bonferroni-corrected threshold of P < 1.49 × 10−4.

N80, the number of cases and controls required to achieve 80% power to detect group differences using a two-tailed t-test at P < 0.05, ranged from N80 = 6, to detect group effects in the right hippocampus in our MTLE-R group, to N80 = 503, to detect group effects in the right pars opercularis in our ‘all epilepsies’ group (Tables 2 and 3).

Discussion

In the largest coordinated neuroimaging study of epilepsy to date, we identified a series of quantitative imaging signatures—some shared across common epilepsy syndromes, and others characteristic of selected, specific epilepsy syndromes. Our sample of 2149 individuals with epilepsy and 1727 controls provided 80% power to detect differences as small as d = 0.091 (P < 0.05, two-tailed), allowing us to identify subtle, consistent brain abnormalities that are typically undetectable on visual inspection, or overlooked using smaller case-control designs. This international collaboration addresses prior inconsistencies in the field of epilepsy neuroimaging, providing a robust, in vivo map of structural aberrations, upon which future studies of disease mechanisms may expand.

In the first of five cross-sectional MRI analyses, we investigated a diverse aggregation of epilepsy syndromes, putative causes, and durations of disease. This all-epilepsies group exhibited shared, diffuse brain structural differences across several regions including the thalamus, pallidum, precentral, paracentral, and superior frontal cortices. With the exception of hippocampal volume and entorhinal thickness differences (Supplementary material), these structural alterations were not driven by any specific syndrome or dataset (Supplementary Figs 3 and 7). Our findings suggest a common neuroanatomical signature of epilepsy across a wide spectrum of disease types, complementing recent evidence for shared genetic susceptibility to a wide spectrum of epilepsies (International League Against Epilepsy Consortium on Complex Epilepsies, 2014). Some structural and genetic pathways may be shared across syndromes, despite the heterogeneity of epilepsy and seizure types. This shared MRI signature underpins the contemporary shift towards the study of epilepsies as network phenomena (Caciagli et al., 2014).

In MTLE, as expected, we observed hippocampal volume abnormalities ipsilateral to the patient’s side of seizure onset. Neither MTLE-L nor MTLE-R showed significant contralateral hippocampal volume reductions, confirming that sporadic, unilateral MTLE is not routinely underpinned by bilateral hippocampal damage (Blümcke et al., 2013). Both MTLE groups showed extrahippocampal abnormalities in the ipsilateral thalamus and pallidum, with widespread reductions in cortical thickness, supporting a growing body of literature indicating that MTLE, as an example of a specific disease constellation in the epilepsies, is also a network disease, extending beyond the mesial temporal regions (Keller et al., 2014; de Campos et al., 2016). Disruption of this network, notably in the thalamus (Keller et al., 2015; He et al., 2017) and thalamo-temporal white matter tracts (Keller et al., 2015, 2017), may be associated with postoperative seizure outcome in MTLE.

Patients with left and right MTLE showed distinct patterns of structural abnormalities when compared to controls, resolving conflicting findings from smaller studies, some reporting an equal distribution of structural differences (Liu et al., 2016), and others indicating more diffuse abnormalities, either in left MTLE (Keller et al., 2002, 2012; Bonilha et al., 2007; Kemmotsu et al., 2011; de Campos et al., 2016) or in right MTLE (Pail et al., 2009). The structural differences observed in the present study may reflect a younger age at onset of epilepsy in left MTLE, which occurred, on average, 1.2 years earlier than those with right MTLE (Supplementary Table 20). Independent, large-scale studies of MTLE patients have confirmed a significantly earlier age at onset in left, compared to right, MTLE (Blümcke et al., 2017). Duration-related effects were also observed in right, but not left, MTLE, pointing to possible biological distinctions between the two.

In IGE, a clinically and biologically distinct group of epilepsies typically associated with ‘normal’ MRI on clinical inspection (Woermann et al., 1998), we identified reduced volume of the right thalamus, and thinner precentral gyri in both hemispheres, supporting prior reports of structural (Bernhardt et al., 2009a), electroencephalographic, and functional (Gotman et al., 2005) abnormalities in IGE. These IGE cases were considered typical by reviewing neurologists, suggesting that this common type of epilepsy is also associated with quantifiable structural brain abnormalities.

The precentral gyri, site of the primary motor cortex, showed bilateral structural deficits across all epilepsy groups (all-epilepsies, IGE, MTLE-L, MTLE-R, and all-other-epilepsies), without detectable inter-cohort or between-disease heterogeneity (Supplementary Figs 3–12). Atrophy of the motor cortex has been linked to seizure frequency and duration of epilepsy in MTLE (Coan et al., 2014); here, we observed a negative correlation between precentral (and postcentral) grey matter thickness and duration of epilepsy in the aggregate all-epilepsies group.

The right thalamus also showed evidence of structural compromise across all epilepsy cohorts, re-emphasizing the importance of the thalamus as a major hub in the epilepsy network (He et al., 2017; Jobst and Cascino, 2017). Loss of feed-forward inhibition between the thalamus and its neocortical connections may be epileptogenic (Paz and Huguenard, 2015), and thalamocortical abnormalities have previously been reported in IGE (Gotman et al., 2005; Bernhardt et al., 2009a; O’Muircheartaigh et al., 2012) and MTLE (Mueller et al., 2010; Bernhardt et al., 2012). These findings support prior ‘system epilepsies’ hypotheses of pathophysiology (Avanzini et al., 2012), suggesting that a broad range of common epilepsies share vulnerability within a thalamocortical structural pathway involved in, and likely affected by, seizures (Liu et al., 2003; Bernhardt et al., 2013). Given this study’s cross-sectional design, we cannot determine if these are causative changes, consequences of recurrent seizures, prolonged drug treatment, or a combination of factors. The epilepsies, as a broad group, may involve progressive structural change (Caciagli et al., 2017), indicating the need for large-scale longitudinal studies.

A heterogeneous subgroup of individuals without confirmed diagnoses of IGE or MTLE with hippocampal sclerosis showed similar patterns of structural alterations to those observed in the aggregate all-epilepsies cohort. The findings included enlarged ventricles, smaller right pallidum and right thalamus, and reduced thickness across the motor and frontal cortices. Hippocampal abnormalities were not observed in this subgroup, suggesting that the patterns of reduced hippocampal grey matter observed in the aggregate group were driven by the inclusion of MTLEs with hippocampal sclerosis. Unlike the IGE, MTLE, and aggregate epilepsy cohorts, this subgroup also showed bilateral enlargement of the amygdala—a phenomenon previously reported in non-lesional localization-related epilepsies (Reyes et al., 2017) and non-lesional MTLEs (Takaya et al., 2012; Coan et al., 2013). Non-lesional MTLEs formed a large proportion of this ‘all-other-epilepsies’ cohort (43.3%; 445 individuals), but the subgroup included many other focal and unclassified syndromes, potentially obscuring specific biological interpretations. Future, sufficiently powered studies will stratify this cohort into finer-grained subtypes to delineate syndrome-specific effects.

Despite its international scale, our study has limitations. All results were derived from cross-sectional data: we cannot distinguish between historical acute damage and progressive abnormalities. We cannot disentangle the relative contributions of environmental and treatment-related factors, including antiepileptic medications, seizure types and frequencies, disease severity, language dominance, and other initial precipitating factors. On average, duration of epilepsy was at least 10 years; longitudinal investigations of new-onset and paediatric epilepsies will provide a more comprehensive understanding. Despite using standardized image processing protocols, quality control, and statistical techniques, some brain measures showed a wide distribution of effect sizes across research centres, which may reflect sample heterogeneity and differences in scanning protocols (Supplementary material).

We observed modest thickness differences across the majority of cortical regions; Cohen’s d effect sizes ranged from small to moderate (d = 0.2–0.5), with some very small effects (d < 0.2) noted in the right pars opercularis, bilateral pars triangularis, and bilateral transverse temporal gyri of the aggregate all-epilepsies group. Other large-scale ENIGMA studies have reported similarly modest (albeit less widespread) cortical abnormalities in psychiatric illnesses including major depression (Schmaal et al., 2016) and bipolar disorder (Hibar et al., 2017b). Although epilepsy is characterized by an enduring predisposition to generate abnormal excessive or synchronous neuronal activity in the brain (Fisher et al., 2014), our findings indicate that common epilepsies are associated with widespread, but relatively subtle, structural alterations of the neocortex. Replication in independent MRI cohorts, complemented by advanced imaging modalities and large-scale gene expression datasets, will help elucidate how these cortical abnormalities relate to underlying disease processes.

Overall, in the largest neuroimaging analysis of epilepsy to date, we demonstrate a pattern of robust brain structural abnormalities within and between syndromes. Specific functional interpretations cannot be inferred from grey matter differences, but lower volume and thickness measures may reflect tissue loss, supporting recent observations that the common epilepsies cannot always be considered benign (Gaitatzis et al., 2004; Bell et al., 2016; Devinsky et al., 2017). The study provides a macroscopic neuroanatomical map upon which neuropathological work, animal models, and further gene expression studies, can expand. Our consortium plans to investigate more specific neuroanatomical traits and epilepsy phenotypes, explore sophisticated shape and sulcal measures, and eventually conduct genome-wide association analysis of brain measures, to improve our understanding and treatment of the epilepsies.

Web resources

All image processing, quality assurance, and statistical analysis protocols for this study can be downloaded from the ENIGMA website, at: http://enigma.usc.edu/ongoing/enigma-epilepsy/enigma-epilepsy-protocols/.

Supplementary Material

Supplementary Tables and Figures
Click here for additional data file. (2.4MB, pdf)

Acknowledgements

We thank Dr Costin Leu, Dr Sinéad Kelly, Dr Michael Nagle, and Dr Craig Hyde for helpful discussions. The RCSI EPIGEN centre thanks Professor James F. Meaney, Dr Andrew J. Fagan, Dr Jason McMorrow and Dr Gerard Boyle for designing MR acquisition protocols and assisting in the acquisition of MRI data. The IDIBAPS-HCP centre thanks Dr Mar Carreño for providing clinical data. The NYU centre thanks Dr Heath Pardoe for designing MR acquisition protocols, and Xiuyuan Wang for conducting image quality inspection and analysis. The Bern centre thanks Prof. Kaspar Schindler, epilepsy surgery program PI, for providing clinical input, Dr Christian Weisstanner for supporting neuroradiological quality assessment, Dr. Andrea Seiler for collecting clinical information, and Dr Heinz Krestel for supporting data collection. The Tübingen centre thanks Dr Silke Klamer for recruitment of the EKUT_B cohort. The Brussels site thanks Dr Xavier De Tiège for making the control scans available. We thank the International League Against Epilepsy Consortium on Complex Epilepsies for advertising the ENIGMA-Epilepsy project amongst its members. New groups are welcome to join the consortium at http://enigma.usc.edu

Funding

This study was supported in part by a Center grant (U54 EB020403) from the National Institutes of Health as part of the 2014 Big Data to Knowledge (BD2K) Initiative. The work was partly undertaken at UCLH/UCL, which received a proportion of funding from the Department of Health's NIHR Biomedical Research Centres funding scheme. We are grateful to the Wolfson Trust and the Epilepsy Society for supporting the Epilepsy Society MRI scanner. The UNICAMP research centre was funded by FAPESP (São Paulo Research Foundation); Contract grant number: 2013/07559-3. The BRI at the Florey Institute of Neuroscience and Mental Health acknowledges funding from the National Health and Medical Research Council of Australia (NHMRC Project Grant 628952, Practitioner Fellowship 1060312). The UCSD research centre acknowledges support from the U.S. National Institute of Neurological Disorders and Stroke (NIH/NINDS, grant no. R01NS065838). The UNAM centre was funded by grants UNAM-DGAPA IB201712 and Conacyt 181508 RRC Graduate Fellowship Conacyt 329866. UNIMORE acknowledges funding from the Carismo Foundation (grant number: A.010@FCRMO RINT@MELFONINFO) and the Italian Ministry of Health, Emilia-Romagna Region (N. PRUA1GR-2013-00000120). Work conducted at Kuopio University Hospital was funded by Government Grant 5772810. Work at the University of Eastern Finland was funded by Vaajasalo Foundation and Saastamoinen Foundation. Funding sources for the King’s College London research centre include: National Institute for Health Research Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust; Medical Research Council (grants G0701310 and MR/K013998/1); Epilepsy Research UK. Work conducted at the University of Liverpool was funded by the UK Medical Research Council (grant MR/K023152/1). The Cardiff University centre acknowledges funding from Cardiff University Brain Research Imaging Centre, Cardiff and Vale University Health Board, Epilepsy Research UK and Health and Care Research Wales, Wales Government. Montreal Neurological Institute funding sources include the Canadian Institutes of Health Research (CIHR MOP-57840 and CIHR MOP-123520). Dr. Bernhardt acknowledges funding through NSERC Discovery, CIHR Foundation, SickKids New Investigator, and FRQS Junior 1. NYU funding includes: Finding a Cure for Epilepsy and Seizures (FACES); The Morris and Alma Schapiro Fund; Epilepsy Foundation. The Royal Melbourne Hospital group received funding from The Royal Melbourne Hospital Neurosciences Foundation. The Bern research centre was funded by Swiss National Science Foundation, grants no. 124089, 140332 and 320030-163398. The NYU School of Medicine site acknowledges support from Finding A Cure for Epilepsy and Seizures (FACES). Dr. Chen at the Ohio State University was partially sponsored by the National Science Foundation IIS-1302755, DBI-1260795, DBI-1062057, and CNS-1531491. At the Florence research centre, Dr. Blümcke and Dr. Haaker received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no: Health-Fs-602531-2013 (see DESIRE, http://epilepsydesireproject.eu/, for more information). The Xiamen University group was partly supported by the National Nature Science Foundation of China (No. 61772440), and the Open Project Program of the State Key Lab of CAD&CG (No. A1706). Dr Altmann holds an MRC eMedLab Medical Bioinformatics Career Development Fellowship. This work was partly supported by the Medical Research Council [grant number MR/L016311/1], and supported by the MRC through the MRC Sudden Death Brain Bank (C.S.) and by a Project Grant (G0901254 to J.H. and M.W.) and Training Fellowship (G0802462 to M.R.).

Supplementary material

Supplementary material is available at Brain online.

Glossary

Abbreviations

ENIGMA

Enhancing Neuro Imaging Genetics through Meta-Analysis

IGE

idiopathic generalized epilepsy

MTLE-L/R

mesial temporal lobe epilepsy with left/right hippocampal sclerosis

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