Search

Your search keyword '"Thomas, Rhys H"' showing total 541 results
Start Over Author "Thomas, Rhys H"
541 results on '"Thomas, Rhys H"'

1. Seizure Onset Zone Localisation Algorithms with Intracranial EEG: Evaluating Methodological Variations and Targeted Features

Author

Gascoigne, Sarah J., Vila-Vidal, Manel, Evans, Nathan, Da Silva, Anderson Brito, Thomas, Rhys H., Thornton, Christopher, Wilson, Kevin, Taylor, Peter N., Tauste, Adrià, and Wang, Yujiang

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

During clinical treatment for epilepsy, the area of the brain thought to be responsible for pathological activity - known as the Seizure Onset Zone (SOZ) - is identified. This is typically performed through visual assessment of EEG recordings; however, this is time consuming and prone to subjective inconsistency. Automated SOZ localisation algorithms provide objective identification of the SOZ by highlighting changes in signal features associated with seizure onset. In this work we investigate how methodological differences in such algorithms can result in different SOZ localisations. We analysed ictal intracranial EEG (icEEG) recordings in 16 subjects (100 seizures) with drug-resistant epilepsy from the SWEZ-ETHZ public database. Through our analysis, we identified a series of key methodological differences that must be considered when designing or selecting a SOZ localisation algorithm. These differences were demonstrated using three distinct algorithms that capture different, but complementary, seizure onset features: Imprint, Epileptogenicity Index (EI), and Low Entropy Map (LEM). We assessed methodological differences at each Decision Point, comparing the resultant SOZ localisations. Our independent application of all three algorithms to the same ictal icEEG dataset revealed low agreement between algorithms: 27-60% of seizure onsets were as minimally or non-overlapping (<25% overlap). Therefore, we investigated the effect of three key methodological differences (or Decision Points). Changes at each Decision Point were found to result in significantly different SOZ localisations (p<0.05). Our results demonstrate how seemingly small methodological changes can result in large differences in SOZ localisations. We propose that key Decision Points must be considered when using or designing a SOZ localisation algorithm.

Published
2024

2. Incomplete resection of the icEEG seizure onset zone is not associated with post-surgical outcomes

Author

Gascoigne, Sarah J., Evans, Nathan, Hall, Gerard, Kozma, Csaba, Panagiotopoulou, Mariella, Schroeder, Gabrielle M., Simpson, Callum, Thornton, Christopher, Turner, Frances, Woodhouse, Heather, Blickwedel, Jess, Chowdhury, Fahmida, Diehl, Beate, Duncan, John S., Faulder, Ryan, Thomas, Rhys H., Wilson, Kevin, Taylor, Peter N., and Wang, Yujiang

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

Delineation of seizure onset regions from EEG is important for effective surgical workup. However, it is unknown if their complete resection is required for seizure freedom, or in other words, if post-surgical seizure recurrence is due to incomplete removal of the seizure onset regions. Retrospective analysis of icEEG recordings from 63 subjects (735 seizures) identified seizure onset regions through visual inspection and algorithmic delineation. We analysed resection of onset regions and correlated this with post-surgical seizure control. Most subjects had over half of onset regions resected (70.7% and 60.5% of subjects for visual and algorithmic methods, respectively). In investigating spatial extent of onset or resection, and presence of diffuse onsets, we found no substantial evidence of association with post-surgical seizure control (all AUC<0.7, p>0.05). Seizure onset regions tends to be at least partially resected, however a less complete resection is not associated with worse post-surgical outcome. We conclude that seizure recurrence after epilepsy surgery is not necessarily a result of failing to completely resect the seizure onset zone, as defined by icEEG. Other network mechanisms must be involved, which are not limited to seizure onset regions alone.

Published
2023

3. Complementary structural and functional abnormalities to localise epileptogenic tissue

Author

Horsley, Jonathan J, Thomas, Rhys H, Chowdhury, Fahmida A, Diehl, Beate, McEvoy, Andrew W, Miserocchi, Anna, de Tisi, Jane, Vos, Sjoerd B, Walker, Matthew C, Winston, Gavin P, Duncan, John S, Wang, Yujiang, and Taylor, Peter N

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

When investigating suitability for surgery, people with drug-refractory focal epilepsy may have intracranial EEG (iEEG) electrodes implanted to localise seizure onset. Diffusion-weighted magnetic resonance imaging (dMRI) may be acquired to identify key white matter tracts for surgical avoidance. Here, we investigate whether structural connectivity abnormalities, inferred from dMRI, may be used in conjunction with functional iEEG abnormalities to aid localisation and resection of the epileptogenic zone (EZ), and improve surgical outcomes in epilepsy. We retrospectively investigated data from 43 patients with epilepsy who had surgery following iEEG. Twenty five patients (58%) were free from disabling seizures (ILAE 1 or 2) at one year. For all patients, T1-weighted and diffusion-weighted MRIs were acquired prior to iEEG implantation. Interictal iEEG functional, and dMRI structural connectivity abnormalities were quantified by comparison to a normative map and healthy controls respectively. First, we explored whether the resection of maximal (dMRI and iEEG) abnormalities related to improved surgical outcomes. Second, we investigated whether the modalities provided complementary information for improved prediction of surgical outcome. Third, we suggest how dMRI abnormalities may be useful to inform the placement of iEEG electrodes as part of the pre-surgical evaluation using a patient case study. Seizure freedom was 15 times more likely in those patients with resection of maximal dMRI and iEEG abnormalities (p=0.008). Both modalities were separately able to distinguish patient outcome groups and when combined, a decision tree correctly separated 36 out of 43 (84%) patients based on surgical outcome. Structural dMRI could be used in pre-surgical evaluations, particularly when localisation of the EZ is uncertain, to inform personalised iEEG implantation and resection., Comment: 5 figures

Published
2023

4. A library of quantitative markers of seizure severity

Author

Gascoigne, Sarah J., Waldmann, Leonard, Panagiotopoulou, Mariella, Chowdhury, Fahmida, Cronie, Alison, Diehl, Beate, Duncan, John S., Falconer, Jennifer, Guan, Yu, Leach, Veronica, Livingstone, Shona, Papasavvas, Christoforos, Faulder, Ryan, Blickwedel, Jess, Schroeder, Gabrielle M., Thomas, Rhys H., Wilson, Kevin, Taylor, Peter N., and Wang, Yujiang

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

Purpose: Understanding fluctuations of seizure severity within individuals is important for defining treatment outcomes and response to therapy, as well as developing novel treatments for epilepsy. Current methods for grading seizure severity rely on qualitative interpretations from patients and clinicians. Quantitative measures of seizure severity would complement existing approaches, for EEG monitoring, outcome monitoring, and seizure prediction. Therefore, we developed a library of quantitative electroencephalographic (EEG) markers that assess the spread and intensity of abnormal electrical activity during and after seizures. Methods: We analysed intracranial EEG (iEEG) recordings of 1056 seizures from 63 patients. For each seizure, we computed 16 markers of seizure severity that capture the signal magnitude, spread, duration, and post-ictal suppression of seizures. Results: Quantitative EEG markers of seizure severity distinguished focal vs. subclinical and focal vs. FTBTC seizures across patients. In individual patients, 71% had a moderate to large difference (ranksum r > 0.3) between focal and subclinical seizures in three or more markers. Circadian and longer-term changes in severity were found for 67% and 53% of patients, respectively. Conclusion: We demonstrate the feasibility of using quantitative iEEG markers to measure seizure severity. Our quantitative markers distinguish between seizure types and are therefore sensitive to established qualitative differences in seizure severity. Our results also suggest that seizure severity is modulated over different timescales. We envisage that our proposed seizure severity library will be expanded and updated in collaboration with the epilepsy research community to include more measures and modalities., Comment: 30 pages main text, 18 pages supplementary. Six main figures, two supplementary figures

Published
2022

5. Investigating the effect of polygenic background on epilepsy phenotype in ‘monogenic’ families

Author

Afawi, Zaid, Amrom, Dina, Andermann, Eva, Bautista, Jocelyn F., Bellows, Susannah T., Bluvstein, Judith, Cascino, Gregory D., Chung, Seo-Kyung, Cossette, Patrick, Curtis, Sarah W., Delanty, Norman, Devinsky, Orrin, Dlugos, Dennis, Epstein, Michael P., Freyer, Catharine, Gravel, Micheline, Harris, Rebekah V., Heinzen, Erin L., Henry, Olivia J., Kirsch, Heidi E., Knowlton, Robert C., Kossoff, Eric H., Loeb, Rebecca, Lowenstein, Daniel H., Marson, Anthony G., Mefford, Heather C., Motika, Paul V., O'Brien, Terence J., Ottman, Ruth, Paolicchi, Juliann M., Petrovski, Slave, Pickrell, William O., Rees, Mark I., Sadleir, Lynette G., Shih, Jerry J., Singh, Rani K., Smith, Michael C., Smith, Philip E.M., Thomas, Rhys H., Weisenberg, Judith, Widdess-Walsh, Peter, Winawer, Melodie R., Oliver, Karen L., Scheffer, Ingrid E., Ellis, Colin A., Grinton, Bronwyn E., Berkovic, Samuel F., and Bahlo, Melanie

Published
2024
Full Text
View/download PDF

6. Utilising accessible and reproducible neurological assessments in clinical studies: Insights from use of the Neurological Impairment Scale in the multi-centre COVID-CNS study

Author

Alam, Ali M., Webb, Glynn W., Collie, Ceryce, Mariathasan, Sashini, Huang, Yun, Hilton, Orla, Shil, Rajish, Dodd, Katherine C., Lilleker, James B., Smith, Craig J., Easton, Ava, Tamborska, Arina, Thomas, Rhys H., Davies, Nicholas W.S., Jenkins, Thomas M., Zandi, Michael, Benjamin, Laura, Ellul, Mark A., Solomon, Tom, Pollak, Thomas A., Nicholson, Tim, Breen, Gerome, van Wamelen, Daniel J., Wood, Nicholas W., and Michael, Benedict D.

Published
2024
Full Text
View/download PDF

7. Volumetric and structural connectivity abnormalities co-localise in TLE

Author

Horsley, Jonathan J., Schroeder, Gabrielle M., Thomas, Rhys H., de Tisi, Jane, Vos, Sjoerd B., Winston, Gavin P., Duncan, John S., Wang, Yujiang, and Taylor, Peter N.

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

Patients with temporal lobe epilepsy (TLE) exhibit both volumetric and structural connectivity abnormalities relative to healthy controls. How these abnormalities inter-relate and their mechanisms are unclear. We computed grey matter volumetric changes and white matter structural connectivity abnormalities in 144 patients with unilateral TLE and 96 healthy controls. Regional volumes were calculated using T1-weighted MRI, while structural connectivity was derived using white matter fibre tractography from diffusion-weighted MRI. For each regional volume and each connection strength, we calculated the effect size between patient and control groups in a group-level analysis. We then applied hierarchical regression to investigate the relationship between volumetric and structural connectivity abnormalities in individuals. Additionally, we quantified whether abnormalities co-localised within individual patients by computing Dice similarity scores. In TLE, white matter connectivity abnormalities were greater when joining two grey matter regions with abnormal volumes. Similarly, grey matter volumetric abnormalities were greater when joined by abnormal white matter connections. The extent of volumetric and connectivity abnormalities related to epilepsy duration, but co-localisation did not. Co-localisation was primarily driven by neighbouring abnormalities in the ipsilateral hemisphere. Overall, volumetric and structural connectivity abnormalities were related in TLE. Our results suggest that shared mechanisms may underlie changes in both volume and connectivity alterations in patients with TLE.

Published
2022

8. Event‐based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross‐sectional data

Author

Lopez, Seymour M, Aksman, Leon M, Oxtoby, Neil P, Vos, Sjoerd B, Rao, Jun, Kaestner, Erik, Alhusaini, Saud, Alvim, Marina, Bender, Benjamin, Bernasconi, Andrea, Bernasconi, Neda, Bernhardt, Boris, Bonilha, Leonardo, Caciagli, Lorenzo, Caldairou, Benoit, Caligiuri, Maria Eugenia, Calvet, Angels, Cendes, Fernando, Concha, Luis, Conde‐Blanco, Estefania, Davoodi‐Bojd, Esmaeil, de Bézenac, Christophe, Delanty, Norman, Desmond, Patricia M, Devinsky, Orrin, Domin, Martin, Duncan, John S, Focke, Niels K, Foley, Sonya, Fortunato, Francesco, Galovic, Marian, Gambardella, Antonio, Gleichgerrcht, Ezequiel, Guerrini, Renzo, Hamandi, Khalid, Ives‐Deliperi, Victoria, Jackson, Graeme D, Jahanshad, Neda, Keller, Simon S, Kochunov, Peter, Kotikalapudi, Raviteja, Kreilkamp, Barbara AK, Labate, Angelo, Larivière, Sara, Lenge, Matteo, Lui, Elaine, Malpas, Charles, Martin, Pascal, Mascalchi, Mario, Medland, Sarah E, Meletti, Stefano, Morita‐Sherman, Marcia E, Owen, Thomas W, Richardson, Mark, Riva, Antonella, Rüber, Theodor, Sinclair, Ben, Soltanian‐Zadeh, Hamid, Stein, Dan J, Striano, Pasquale, Taylor, Peter N, Thomopoulos, Sophia I, Thompson, Paul M, Tondelli, Manuela, Vaudano, Anna Elisabetta, Vivash, Lucy, Wang, Yujiang, Weber, Bernd, Whelan, Christopher D, Wiest, Roland, Winston, Gavin P, Yasuda, Clarissa Lin, McDonald, Carrie R, Alexander, Daniel C, Sisodiya, Sanjay M, Altmann, Andre, Bargalló, Núria, Bartolini, Emanuele, O’Brien, Terence J, and Thomas, Rhys H

Subjects
Brain Disorders, Epilepsy, Neurodegenerative, Neurosciences, Clinical Research, Biomedical Imaging, Aetiology, 2.1 Biological and endogenous factors, Neurological, Good Health and Well Being, Atrophy, Biomarkers, Cross-Sectional Studies, Epilepsy, Temporal Lobe, Hippocampus, Humans, Magnetic Resonance Imaging, Sclerosis, disease progression, duration of illness, event-based model, MTLE, patient staging, ENIGMA-Epilepsy Working Group, Clinical Sciences, Neurology & Neurosurgery
Abstract

ObjectiveRecent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features.MethodsWe extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers. Features with a moderate case-control effect size (Cohen d ≥ .5) were used to train an event-based model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance.ResultsIn MTLE-HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10-16 ), age at onset (ρ = -.18, p = 9.82 × 10-7 ), and ASM resistance (area under the curve = .59, p = .043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE-HS with mild or nondetectable abnormality on T1W MRI.SignificanceFrom cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features.

Published
2022

9. SLCO5A1 and synaptic assembly genes contribute to impulsivity in juvenile myoclonic epilepsy

Author

Roshandel, Delnaz, Sanders, Eric J., Shakeshaft, Amy, Panjwani, Naim, Lin, Fan, Collingwood, Amber, Hall, Anna, Keenan, Katherine, Deneubourg, Celine, Mirabella, Filippo, Topp, Simon, Zarubova, Jana, Thomas, Rhys H., Talvik, Inga, Syvertsen, Marte, Striano, Pasquale, Smith, Anna B., Selmer, Kaja K., Rubboli, Guido, Orsini, Alessandro, Ng, Ching Ching, Møller, Rikke S., Lim, Kheng Seang, Hamandi, Khalid, Greenberg, David A., Gesche, Joanna, Gardella, Elena, Fong, Choong Yi, Beier, Christoph P., Andrade, Danielle M., Jungbluth, Heinz, Richardson, Mark P., Pastore, Annalisa, Fanto, Manolis, Pal, Deb K., and Strug, Lisa J.

Published
2023
Full Text
View/download PDF

11. Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy

Author

Park, Bo-yong, Larivière, Sara, Rodríguez-Cruces, Raul, Royer, Jessica, Tavakol, Shahin, Wang, Yezhou, Caciagli, Lorenzo, Caligiuri, Maria Eugenia, Gambardella, Antonio, Concha, Luis, Keller, Simon S, Cendes, Fernando, Alvim, Marina KM, Yasuda, Clarissa, Bonilha, Leonardo, Gleichgerrcht, Ezequiel, Focke, Niels K, Kreilkamp, Barbara AK, Domin, Martin, von Podewils, Felix, Langner, Soenke, Rummel, Christian, Rebsamen, Michael, Wiest, Roland, Martin, Pascal, Kotikalapudi, Raviteja, Bender, Benjamin, O’Brien, Terence J, Law, Meng, Sinclair, Benjamin, Vivash, Lucy, Kwan, Patrick, Desmond, Patricia M, Malpas, Charles B, Lui, Elaine, Alhusaini, Saud, Doherty, Colin P, Cavalleri, Gianpiero L, Delanty, Norman, Kälviäinen, Reetta, Jackson, Graeme D, Kowalczyk, Magdalena, Mascalchi, Mario, Semmelroch, Mira, Thomas, Rhys H, Soltanian-Zadeh, Hamid, Davoodi-Bojd, Esmaeil, Zhang, Junsong, Lenge, Matteo, Guerrini, Renzo, Bartolini, Emanuele, Hamandi, Khalid, Foley, Sonya, Weber, Bernd, Depondt, Chantal, Absil, Julie, Carr, Sarah JA, Abela, Eugenio, Richardson, Mark P, Devinsky, Orrin, Severino, Mariasavina, Striano, Pasquale, Parodi, Costanza, Tortora, Domenico, Hatton, Sean N, Vos, Sjoerd B, Duncan, John S, Galovic, Marian, Whelan, Christopher D, Bargalló, Núria, Pariente, Jose, Conde-Blanco, Estefania, Vaudano, Anna Elisabetta, Tondelli, Manuela, Meletti, Stefano, Kong, Xiang‐Zhen, Francks, Clyde, Fisher, Simon E, Caldairou, Benoit, Ryten, Mina, Labate, Angelo, Sisodiya, Sanjay M, Thompson, Paul M, McDonald, Carrie R, Bernasconi, Andrea, Bernasconi, Neda, and Bernhardt, Boris C

Subjects
Epilepsy, Neurodegenerative, Clinical Research, Brain Disorders, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Atrophy, Connectome, Epilepsy, Temporal Lobe, Hippocampus, Humans, Magnetic Resonance Imaging, temporal lobe epilepsy, asymmetry, cortical thickness, multi-site, gradients, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.

Published
2022

12. Addressing ethnic disparities in neurological research in the United Kingdom: An example from the prospective multicentre COVID-19 Clinical Neuroscience Study

Author

van Wamelen, Daniel J., Rota, Silvia, Hartmann, Monika, Martin, Naomi H., Alam, Ali M., Thomas, Rhys H., Dodd, Katherine C., Jenkins, Thomas, Smith, Craig J., Zandi, Michael S., Easton, Ava, Carr, Georgina, Benjamin, Laura A., Lilleker, James B., Saucer, David, Coles, Alasdair J., Wood, Nicholas, Ray Chaudhuri, K., Breen, Gerome, and Michael, Benedict Daniel

Published
2024
Full Text
View/download PDF

14. The ENIGMA‐Epilepsy working group: Mapping disease from large data sets

Author

Sisodiya, Sanjay M, Whelan, Christopher D, Hatton, Sean N, Huynh, Khoa, Altmann, Andre, Ryten, Mina, Vezzani, Annamaria, Caligiuri, Maria Eugenia, Labate, Angelo, Gambardella, Antonio, Ives‐Deliperi, Victoria, Meletti, Stefano, Munsell, Brent C, Bonilha, Leonardo, Tondelli, Manuela, Rebsamen, Michael, Rummel, Christian, Vaudano, Anna Elisabetta, Wiest, Roland, Balachandra, Akshara R, Bargalló, Núria, Bartolini, Emanuele, Bernasconi, Andrea, Bernasconi, Neda, Bernhardt, Boris, Caldairou, Benoit, Carr, Sarah JA, Cavalleri, Gianpiero L, Cendes, Fernando, Concha, Luis, Desmond, Patricia M, Domin, Martin, Duncan, John S, Focke, Niels K, Guerrini, Renzo, Hamandi, Khalid, Jackson, Graeme D, Jahanshad, Neda, Kälviäinen, Reetta, Keller, Simon S, Kochunov, Peter, Kowalczyk, Magdalena A, Kreilkamp, Barbara AK, Kwan, Patrick, Lariviere, Sara, Lenge, Matteo, Lopez, Seymour M, Martin, Pascal, Mascalchi, Mario, Moreira, José CV, Morita‐Sherman, Marcia E, Pardoe, Heath R, Pariente, Jose C, Raviteja, Kotikalapudi, Rocha, Cristiane S, Rodríguez‐Cruces, Raúl, Seeck, Margitta, Semmelroch, Mira KHG, Sinclair, Benjamin, Soltanian‐Zadeh, Hamid, Stein, Dan J, Striano, Pasquale, Taylor, Peter N, Thomas, Rhys H, Thomopoulos, Sophia I, Velakoulis, Dennis, Vivash, Lucy, Weber, Bernd, Yasuda, Clarissa Lin, Zhang, Junsong, Thompson, Paul M, McDonald, Carrie R, Abela, Eugenio, Absil, Julie, Adams, Sophia, Alhusaini, Saud, Alvim, Marina, Balestrini, Simona, Bender, Benjamin, Bergo, Felipe, Bernardes, Tauana, Calvo, Anna, Carreno, Mar, Cherubini, Andrea, David, Philippe, Davoodi‐Bojd, Esmaeil, Delanty, Norman, Depondt, Chantal, Devinsky, Orrin, Doherty, Colin, França, Wendy Caroline, Franceschet, Leticia, Hibar, Derrek P, Ishikawa, Akari, Kaestner, Erik, Langner, Soenke, Liu, Min, Mirandola, Laura, Naylor, Jillian, and Nazem‐Zadeh, Mohammad‐reza

Subjects
Brain Disorders, Biomedical Imaging, Neurosciences, Epilepsy, Neurodegenerative, 2.1 Biological and endogenous factors, Aetiology, Neurological, covariance, deep learning, DTI, event-based modeling, gene expression, genetics, imaging, MRI, quantitative, rsfMRI, ENIGMA Consortium Epilepsy Working Group, Cognitive Sciences, Experimental Psychology
Abstract

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy.

Published
2022

15. Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression

Author

Larivière, Sara, Royer, Jessica, Rodríguez-Cruces, Raúl, Paquola, Casey, Caligiuri, Maria Eugenia, Gambardella, Antonio, Concha, Luis, Keller, Simon S, Cendes, Fernando, Yasuda, Clarissa L, Bonilha, Leonardo, Gleichgerrcht, Ezequiel, Focke, Niels K, Domin, Martin, von Podewills, Felix, Langner, Soenke, Rummel, Christian, Wiest, Roland, Martin, Pascal, Kotikalapudi, Raviteja, O’Brien, Terence J, Sinclair, Benjamin, Vivash, Lucy, Desmond, Patricia M, Lui, Elaine, Vaudano, Anna Elisabetta, Meletti, Stefano, Tondelli, Manuela, Alhusaini, Saud, Doherty, Colin P, Cavalleri, Gianpiero L, Delanty, Norman, Kälviäinen, Reetta, Jackson, Graeme D, Kowalczyk, Magdalena, Mascalchi, Mario, Semmelroch, Mira, Thomas, Rhys H, Soltanian-Zadeh, Hamid, Davoodi-Bojd, Esmaeil, Zhang, Junsong, Winston, Gavin P, Griffin, Aoife, Singh, Aditi, Tiwari, Vijay K, Kreilkamp, Barbara AK, Lenge, Matteo, Guerrini, Renzo, Hamandi, Khalid, Foley, Sonya, Rüber, Theodor, Weber, Bernd, Depondt, Chantal, Absil, Julie, Carr, Sarah JA, Abela, Eugenio, Richardson, Mark P, Devinsky, Orrin, Severino, Mariasavina, Striano, Pasquale, Tortora, Domenico, Kaestner, Erik, Hatton, Sean N, Vos, Sjoerd B, Caciagli, Lorenzo, Duncan, John S, Whelan, Christopher D, Thompson, Paul M, Sisodiya, Sanjay M, Bernasconi, Andrea, Labate, Angelo, McDonald, Carrie R, Bernasconi, Neda, and Bernhardt, Boris C

Subjects
Neurodegenerative, Genetics, Neurosciences, Brain Disorders, Epilepsy, Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Connectome, Epilepsy, Generalized, Epilepsy, Temporal Lobe, Gene Expression, Humans, Immunoglobulin E, Magnetic Resonance Imaging, Nerve Net
Abstract

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.

Published
2022

16. Fluctuations in EEG band power at subject-specific timescales over minutes to days explain changes in seizure evolutions

Author

Panagiotopoulou, Mariella, Papasavvas, Christoforos A, Schroeder, Gabrielle M, Thomas, Rhys H, Taylor, Peter N, and Wang, Yujiang

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

Epilepsy is recognised as a dynamic disease, where both seizure susceptibility and seizure characteristics themselves change over time. Specifically, we recently quantified the variable electrographic spatio-temporal seizure evolutions that exist within individual patients. This variability appears to follow subject-specific circadian, or longer, timescale modulations. It is therefore important to know whether continuously-recorded interictal iEEG features can capture signatures of these modulations over different timescales. In this work, we analyse continuous intracranial electroencephalographic (iEEG) recordings from video-telemetry units and find fluctuations in iEEG band power over timescales ranging from minutes up to twelve days. As expected and in agreement with previous studies, we find that all subjects show a circadian fluctuation in their iEEG band power. We additionally find other fluctuations of similar magnitude on subject-specific timescales. Importantly, we find that a combination of these fluctuations on different timescales can explain changes in seizure evolutions in most subjects above chance level. These results suggest that subject-specific fluctuations in iEEG band power over timescales of minutes to days may serve as markers of seizure modulating processes. We hope that future work can link these detected fluctuations to their biological driver(s). There is a critical need to better understand seizure modulating processes, as this will enable the development of novel treatment strategies that could minimise the seizure spread, duration, or severity and therefore the clinical impact of seizures.

Published
2020

19. Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study

Author

Gleichgerrcht, Ezequiel, Munsell, Brent C, Alhusaini, Saud, Alvim, Marina KM, Bargalló, Núria, Bender, Benjamin, Bernasconi, Andrea, Bernasconi, Neda, Bernhardt, Boris, Blackmon, Karen, Caligiuri, Maria Eugenia, Cendes, Fernando, Concha, Luis, Desmond, Patricia M, Devinsky, Orrin, Doherty, Colin P, Domin, Martin, Duncan, John S, Focke, Niels K, Gambardella, Antonio, Gong, Bo, Guerrini, Renzo, Hatton, Sean N, Kälviäinen, Reetta, Keller, Simon S, Kochunov, Peter, Kotikalapudi, Raviteja, Kreilkamp, Barbara AK, Labate, Angelo, Langner, Soenke, Larivière, Sara, Lenge, Matteo, Lui, Elaine, Martin, Pascal, Mascalchi, Mario, Meletti, Stefano, O'Brien, Terence J, Pardoe, Heath R, Pariente, Jose C, Rao, Jun Xian, Richardson, Mark P, Rodríguez-Cruces, Raúl, Rüber, Theodor, Sinclair, Ben, Soltanian-Zadeh, Hamid, Stein, Dan J, Striano, Pasquale, Taylor, Peter N, Thomas, Rhys H, Vaudano, Anna Elisabetta, Vivash, Lucy, von Podewills, Felix, Vos, Sjoerd B, Weber, Bernd, Yao, Yi, Yasuda, Clarissa Lin, Zhang, Junsong, Thompson, Paul M, Sisodiya, Sanjay M, McDonald, Carrie R, Bonilha, Leonardo, Group, ENIGMA-Epilepsy Working, Altmann, Andre, Depondt, Chantal, Galovic, Marian, Thomopoulos, Sophia I, and Wiest, Roland

Subjects
Biomedical Imaging, Neurodegenerative, Neurosciences, Brain Disorders, Prevention, Epilepsy, 2.1 Biological and endogenous factors, Aetiology, Neurological, Artificial Intelligence, Brain, Epilepsy, Temporal Lobe, Hippocampus, Humans, Magnetic Resonance Imaging, Sclerosis, Support Vector Machine, Temporal lobe epilepsy, Machine learning, Artificial inteligence, ENIGMA-Epilepsy Working Group
Abstract

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with ("lesional") and without ("non-lesional") radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68-75%) compared to models to lateralize the side of TLE (56-73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67-75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68-76%) than models that stratified non-lesional patients (53-62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care.

Published
2021

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

Author

Larivière, Sara, Rodríguez-Cruces, Raúl, Royer, Jessica, Caligiuri, Maria Eugenia, Gambardella, Antonio, Concha, Luis, Keller, Simon S, Cendes, Fernando, Yasuda, Clarissa, Bonilha, Leonardo, Gleichgerrcht, Ezequiel, Focke, Niels K, Domin, Martin, von Podewills, Felix, Langner, Soenke, Rummel, Christian, Wiest, Roland, Martin, Pascal, Kotikalapudi, Raviteja, O’Brien, Terence J, Sinclair, Benjamin, Vivash, Lucy, Desmond, Patricia M, Alhusaini, Saud, Doherty, Colin P, Cavalleri, Gianpiero L, Delanty, Norman, Kälviäinen, Reetta, Jackson, Graeme D, Kowalczyk, Magdalena, Mascalchi, Mario, Semmelroch, Mira, Thomas, Rhys H, Soltanian-Zadeh, Hamid, Davoodi-Bojd, Esmaeil, Zhang, Junsong, Lenge, Matteo, Guerrini, Renzo, Bartolini, Emanuele, Hamandi, Khalid, Foley, Sonya, Weber, Bernd, Depondt, Chantal, Absil, Julie, Carr, Sarah JA, Abela, Eugenio, Richardson, Mark P, Devinsky, Orrin, Severino, Mariasavina, Striano, Pasquale, Tortora, Domenico, Hatton, Sean N, Vos, Sjoerd B, Duncan, John S, Whelan, Christopher D, Thompson, Paul M, Sisodiya, Sanjay M, Bernasconi, Andrea, Labate, Angelo, McDonald, Carrie R, Bernasconi, Neda, and Bernhardt, Boris C

Subjects
Mental Health, Brain Disorders, Epilepsy, Clinical Research, Neurosciences, Neurodegenerative, Aetiology, 2.1 Biological and endogenous factors, Neurological
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.

Published
2020

21. Semantic Similarity Analysis Reveals Robust Gene-Disease Relationships in Developmental and Epileptic Encephalopathies

Author

Galer, Peter D, Ganesan, Shiva, Lewis-Smith, David, McKeown, Sarah E, Pendziwiat, Manuela, Helbig, Katherine L, Ellis, Colin A, Rademacher, Annika, Smith, Lacey, Poduri, Annapurna, Seiffert, Simone, von Spiczak, Sarah, Muhle, Hiltrud, van Baalen, Andreas, Group, NCEE Study, Investigators, EPGP, Consortium, EuroEPINOMICS-RES, Network, Genomics Research and Innovation, Thomas, Rhys H, Krause, Roland, Weber, Yvonne, and Helbig, Ingo

Subjects
Biological Sciences, Genetics, Neurodegenerative, Epilepsy, Prevention, Neurosciences, Brain Disorders, Pediatric, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Child, Preschool, Cohort Studies, Female, GABA Plasma Membrane Transport Proteins, Gene Expression, Gene Ontology, Humans, Male, Munc18 Proteins, Mutation, NAV1.1 Voltage-Gated Sodium Channel, Phenotype, Seizures, Semantics, Shab Potassium Channels, Spasms, Infantile, Speech Disorders, Terminology as Topic, Exome Sequencing, NCEE Study Group, EPGP Investigators, EuroEPINOMICS-RES Consortium, Genomics Research and Innovation Network, Human Phenotype Ontology, childhood epilepsies, computational phenotypes, developmental and epileptic encephalopathies, electronic medical records, neurogenetic disorders, whole-exome sequencing, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

More than 100 genetic etiologies have been identified in developmental and epileptic encephalopathies (DEEs), but correlating genetic findings with clinical features at scale has remained a hurdle because of a lack of frameworks for analyzing heterogenous clinical data. Here, we analyzed 31,742 Human Phenotype Ontology (HPO) terms in 846 individuals with existing whole-exome trio data and assessed associated clinical features and phenotypic relatedness by using HPO-based semantic similarity analysis for individuals with de novo variants in the same gene. Gene-specific phenotypic signatures included associations of SCN1A with "complex febrile seizures" (HP: 0011172; p = 2.1 × 10-5) and "focal clonic seizures" (HP: 0002266; p = 8.9 × 10-6), STXBP1 with "absent speech" (HP: 0001344; p = 1.3 × 10-11), and SLC6A1 with "EEG with generalized slow activity" (HP: 0010845; p = 0.018). Of 41 genes with de novo variants in two or more individuals, 11 genes showed significant phenotypic similarity, including SCN1A (n = 16, p < 0.0001), STXBP1 (n = 14, p = 0.0021), and KCNB1 (n = 6, p = 0.011). Including genetic and phenotypic data of control subjects increased phenotypic similarity for all genetic etiologies, whereas the probability of observing de novo variants decreased, emphasizing the conceptual differences between semantic similarity analysis and approaches based on the expected number of de novo events. We demonstrate that HPO-based phenotype analysis captures unique profiles for distinct genetic etiologies, reflecting the breadth of the phenotypic spectrum in genetic epilepsies. Semantic similarity can be used to generate statistical evidence for disease causation analogous to the traditional approach of primarily defining disease entities through similar clinical features.

Published
2020

22. White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study

Author

Hatton, Sean N, Huynh, Khoa H, Bonilha, Leonardo, Abela, Eugenio, Alhusaini, Saud, Altmann, Andre, Alvim, Marina KM, Balachandra, Akshara R, Bartolini, Emanuele, Bender, Benjamin, Bernasconi, Neda, Bernasconi, Andrea, Bernhardt, Boris, Bargallo, Núria, Caldairou, Benoit, Caligiuri, Maria E, Carr, Sarah JA, Cavalleri, Gianpiero L, Cendes, Fernando, Concha, Luis, Davoodi-bojd, Esmaeil, Desmond, Patricia M, Devinsky, Orrin, Doherty, Colin P, Domin, Martin, Duncan, John S, Focke, Niels K, Foley, Sonya F, Gambardella, Antonio, Gleichgerrcht, Ezequiel, Guerrini, Renzo, Hamandi, Khalid, Ishikawa, Akari, Keller, Simon S, Kochunov, Peter V, Kotikalapudi, Raviteja, Kreilkamp, Barbara AK, Kwan, Patrick, Labate, Angelo, Langner, Soenke, Lenge, Matteo, Liu, Min, Lui, Elaine, Martin, Pascal, Mascalchi, Mario, Moreira, José CV, Morita-Sherman, Marcia E, O’Brien, Terence J, Pardoe, Heath R, Pariente, José C, Ribeiro, Letícia F, Richardson, Mark P, Rocha, Cristiane S, Rodríguez-Cruces, Raúl, Rosenow, Felix, Severino, Mariasavina, Sinclair, Benjamin, Soltanian-Zadeh, Hamid, Striano, Pasquale, Taylor, Peter N, Thomas, Rhys H, Tortora, Domenico, Velakoulis, Dennis, Vezzani, Annamaria, Vivash, Lucy, von Podewils, Felix, Vos, Sjoerd B, Weber, Bernd, Winston, Gavin P, Yasuda, Clarissa L, Zhu, Alyssa H, Thompson, Paul M, Whelan, Christopher D, Jahanshad, Neda, Sisodiya, Sanjay M, and McDonald, Carrie R

Subjects
Genetics, Neurodegenerative, Epilepsy, Clinical Research, Brain Disorders, Neurosciences, Biomedical Imaging, Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Brain, Diffusion Magnetic Resonance Imaging, Epileptic Syndromes, Female, Humans, Image Interpretation, Computer-Assisted, Male, Middle Aged, White Matter, epilepsy, diffusion tensor imaging, multisite analysis, white matter, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P

Published
2020

23. Widening of the genetic and clinical spectrum of Lamb–Shaffer syndrome, a neurodevelopmental disorder due to SOX5 haploinsufficiency

Author

Zawerton, Ash, Mignot, Cyril, Sigafoos, Ashley, Blackburn, Patrick R, Haseeb, Abdul, McWalter, Kirsty, Ichikawa, Shoji, Nava, Caroline, Keren, Boris, Charles, Perrine, Marey, Isabelle, Tabet, Anne-Claude, Levy, Jonathan, Perrin, Laurence, Hartmann, Andreas, Lesca, Gaetan, Schluth-Bolard, Caroline, Monin, Pauline, Dupuis-Girod, Sophie, Guillen Sacoto, Maria J, Schnur, Rhonda E, Zhu, Zehua, Poisson, Alice, El Chehadeh, Salima, Alembik, Yves, Bruel, Ange-Line, Lehalle, Daphné, Nambot, Sophie, Moutton, Sébastien, Odent, Sylvie, Jaillard, Sylvie, Dubourg, Christèle, Hilhorst-Hofstee, Yvonne, Barbaro-Dieber, Tina, Ortega, Lucia, Bhoj, Elizabeth J, Masser-Frye, Diane, Bird, Lynne M, Lindstrom, Kristin, Ramsey, Keri M, Narayanan, Vinodh, Fassi, Emily, Willing, Marcia, Cole, Trevor, Salter, Claire G, Akilapa, Rhoda, Vandersteen, Anthony, Canham, Natalie, Rump, Patrick, Gerkes, Erica H, Klein Wassink-Ruiter, Jolien S, Bijlsma, Emilia, Hoffer, Mariëtte JV, Vargas, Marcelo, Wojcik, Antonina, Cherik, Florian, Francannet, Christine, Rosenfeld, Jill A, Machol, Keren, Scott, Daryl A, Bacino, Carlos A, Wang, Xia, Clark, Gary D, Bertoli, Marta, Zwolinski, Simon, Thomas, Rhys H, Akay, Ela, Chang, Richard C, Bressi, Rebekah, Sanchez Russo, Rossana, Srour, Myriam, Russell, Laura, Goyette, Anne-Marie E, Dupuis, Lucie, Mendoza-Londono, Roberto, Karimov, Catherine, Joseph, Maries, Nizon, Mathilde, Cogné, Benjamin, Kuechler, Alma, Piton, Amélie, Klee, Eric W, Lefebvre, Véronique, Clark, Karl J, and Depienne, Christel

Subjects
Intellectual and Developmental Disabilities (IDD), Pediatric, Genetics, Brain Disorders, Clinical Research, Rare Diseases, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Adolescent, Adult, Animals, Child, Child, Preschool, DNA-Binding Proteins, Female, Genetic Predisposition to Disease, Haploinsufficiency, Humans, Infant, Intellectual Disability, Language Development Disorders, Male, Mutation, Missense, Neurodevelopmental Disorders, Pedigree, Phenotype, SOXD Transcription Factors, Young Adult, autism, developmental delay, intellectual disability, epilepsy, missense variants, Deciphering Developmental DisorderStudy, missense variants., Clinical Sciences, Genetics & Heredity
Abstract

PurposeLamb-Shaffer syndrome (LAMSHF) is a neurodevelopmental disorder described in just over two dozen patients with heterozygous genetic alterations involving SOX5, a gene encoding a transcription factor regulating cell fate and differentiation in neurogenesis and other discrete developmental processes. The genetic alterations described so far are mainly microdeletions. The present study was aimed at increasing our understanding of LAMSHF, its clinical and genetic spectrum, and the pathophysiological mechanisms involved.MethodsClinical and genetic data were collected through GeneMatcher and clinical or genetic networks for 41 novel patients harboring various types ofSOX5 alterations. Functional consequences of selected substitutions were investigated.ResultsMicrodeletions and truncating variants occurred throughout SOX5. In contrast, most missense variants clustered in the pivotal SOX-specific high-mobility-group domain. The latter variants prevented SOX5 from binding DNA and promoting transactivation in vitro, whereas missense variants located outside the high-mobility-group domain did not. Clinical manifestations and severity varied among patients. No clear genotype-phenotype correlations were found, except that missense variants outside the high-mobility-group domain were generally better tolerated.ConclusionsThis study extends the clinical and genetic spectrum associated with LAMSHF and consolidates evidence that SOX5 haploinsufficiency leads to variable degrees of intellectual disability, language delay, and other clinical features.

Published
2020

25. Quantitative analysis of phenotypic elements augments traditional electroclinical classification of common familial epilepsies

Author

Abou‐Khalil, Bassel, Afawi, Zaid, Allen, Andrew S, Bautista, Jocelyn F, Bellows, Susannah T, Berkovic, Samuel F, Bluvstein, Judith, Burgess, Rosemary, Cascino, Gregory, Cossette, Patrick, Cristofaro, Sabrina, Crompton, Douglas E, Delanty, Norman, Devinsky, Orrin, Dlugos, Dennis, Ellis, Colin A, Epstein, Michael P, Fountain, Nathan B, Freyer, Catharine, Geller, Eric B, Glauser, Tracy, Glynn, Simon, Goldberg‐Stern, Hadassa, Goldstein, David B, Gravel, Micheline, Haas, Kevin, Haut, Sheryl, Heinzen, Erin L, Kirsch, Heidi E, Kivity, Sara, Knowlton, Robert, Korczyn, Amos D, Kossoff, Eric, Kuzniecky, Ruben, Loeb, Rebecca, Lowenstein, Daniel H, Marson, Anthony G, McCormack, Mark, McKenna, Kevin, Mefford, Heather C, Motika, Paul, Mullen, Saul A, J. O'Brien, Terence, Ottman, Ruth, Paolicchi, Juliann, Parent, Jack M, Paterson, Sarah, Petrou, Steven, Petrovski, Slavé, Owen Pickrell, William, Poduri, Annapurna, Rees, Mark I, Sadleir, Lynette G, Scheffer, Ingrid E, Shih, Jerry, Singh, Rani, Sirven, Joseph, Smith, Michael, Smith, Phil EM, Thio, Liu Lin, Thomas, Rhys H, Venkat, Anu, Vining, Eileen, Von Allmen, Gretchen, Weisenberg, Judith, Widdess‐Walsh, Peter, and Winawer, Melodie R

Subjects
Neurodegenerative, Neurosciences, Epilepsy, Clinical Research, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Neurological, Electroencephalography, Epileptic Syndromes, Female, Humans, Latent Class Analysis, Male, Pedigree, Phenotype, epilepsy, genetics, latent class analysis, phenotype, Epi4K Consortium, Clinical Sciences, Neurology & Neurosurgery
Abstract

ObjectiveClassification of epilepsy into types and subtypes is important for both clinical care and research into underlying disease mechanisms. A quantitative, data-driven approach may augment traditional electroclinical classification and shed new light on existing classification frameworks.MethodsWe used latent class analysis, a statistical method that assigns subjects into groups called latent classes based on phenotypic elements, to classify individuals with common familial epilepsies from the Epi4K Multiplex Families study. Phenotypic elements included seizure types, seizure symptoms, and other elements of the medical history. We compared class assignments to traditional electroclinical classifications and assessed familial aggregation of latent classes.ResultsA total of 1120 subjects with epilepsy were assigned to five latent classes. Classes 1 and 2 contained subjects with generalized epilepsy, largely reflecting the distinction between absence epilepsies and younger onset (class 1) versus myoclonic epilepsies and older onset (class 2). Classes 3 and 4 contained subjects with focal epilepsies, and in contrast to classes 1 and 2, these did not adhere as closely to clinically defined focal epilepsy subtypes. Class 5 contained nearly all subjects with febrile seizures plus or unknown epilepsy type, as well as a few subjects with generalized epilepsy and a few with focal epilepsy. Family concordance of latent classes was similar to or greater than concordance of clinically defined epilepsy types.SignificanceQuantitative classification of epilepsy has the potential to augment traditional electroclinical classification by (1) combining some syndromes into a single class, (2) splitting some syndromes into different classes, (3) helping to classify subjects who could not be classified clinically, and (4) defining the boundaries of clinically defined classifications. This approach can guide future research, including molecular genetic studies, by identifying homogeneous sets of individuals that may share underlying disease mechanisms.

Published
2019

26. Sex-specific disease modifiers in juvenile myoclonic epilepsy

Author

Shakeshaft, Amy, Panjwani, Naim, Collingwood, Amber, Crudgington, Holly, Hall, Anna, Andrade, Danielle M., Beier, Christoph P., Fong, Choong Yi, Gardella, Elena, Gesche, Joanna, Greenberg, David A., Hamandi, Khalid, Koht, Jeanette, Lim, Kheng Seang, Møller, Rikke S., Ng, Ching Ching, Orsini, Alessandro, Rees, Mark I., Rubboli, Guido, Selmer, Kaja K., Striano, Pasquale, Syvertsen, Marte, Thomas, Rhys H., Zarubova, Jana, Richardson, Mark P., Strug, Lisa J., and Pal, Deb K.

Published
2022
Full Text
View/download PDF

29. Incomplete resection of the intracranial electroencephalographic seizure onset zone is not associated with postsurgical outcomes.

Author

Gascoigne, Sarah J., Evans, Nathan, Hall, Gerard, Kozma, Csaba, Panagiotopoulou, Mariella, Schroeder, Gabrielle M., Simpson, Callum, Thornton, Christopher, Turner, Frances, Woodhouse, Heather, Blickwedel, Jess, Chowdhury, Fahmida A., Diehl, Beate, Duncan, John S., Faulder, Ryan, Thomas, Rhys H., Wilson, Kevin, Taylor, Peter N., and Wang, Yujiang

Subjects
RECEIVER operating characteristic curves, EPILEPSY surgery, SEIZURES (Medicine), ELECTROENCEPHALOGRAPHY, EPILEPSY
Abstract

Delineation of seizure onset regions using intracranial electroencephalography (icEEG) is vital in the surgical workup of drug‐resistant epilepsy cases. However, it is unknown whether the complete resection of these regions is necessary for seizure freedom, or whether postsurgical seizure recurrence can be attributed to the incomplete removal of seizure onset regions. To address this gap, we retrospectively analyzed icEEG recordings from 63 subjects, identifying seizure onset regions visually and algorithmically. We assessed onset region resection and correlated this with postsurgical seizure control. The majority of subjects had more than half of their onset regions resected (82.46% and 80.65% of subjects using visual and algorithmic methods, respectively). There was no association between the proportion of the seizure onset zone (SOZ) that was subsequently resected and better surgical outcomes (area under the receiver operating characteristic curve [AUC] <.7). Investigating the spatial extent of onset regions, we found no substantial evidence of an association with postsurgical seizure control (all AUC <.7). Although seizure onset regions are typically resected completely or in large part, incomplete resection is not associated with worse postsurgical outcomes. We conclude that postsurgical seizure recurrence cannot be attributed to an incomplete resection of the icEEG SOZ alone. Other network mechanisms beyond icEEG seizure onset likely contribute. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

30. A worldwide ENIGMA study on epilepsy-related gray and white matter compromise across the adult lifespan

Author

Chen, Judy, primary, Ngo, Alexander, additional, Rodríguez-Cruces, Raúl, additional, Royer, Jessica, additional, Caligiuri, Maria Eugenia, additional, Gambardella, Antonio, additional, Concha, Luis, additional, Keller, Simon S., additional, Cendes, Fernando, additional, Yasuda, Clarissa L., additional, Alvim, Marina K. M., additional, Bonilha, Leonardo, additional, Gleichgerrcht, Ezequiel, additional, Focke, Niels K., additional, Kreilkamp, Barbara, additional, Domin, Martin, additional, von Podewils, Felix, additional, Langner, Soenke, additional, Rummel, Christian, additional, Wiest, Roland, additional, Martin, Pascal, additional, Kotikalapudi, Raviteja, additional, Bender, Benjamin, additional, O’Brien, Terence J., additional, Sinclair, Benjamin, additional, Vivash, Lucy, additional, Kwan, Patrick, additional, Desmond, Patricia M., additional, Lui, Elaine, additional, Duma, Gian Marco, additional, Bonanni, Paolo, additional, Ballerini, Alice, additional, Vaudano, Anna Elisabetta, additional, Meletti, Stefano, additional, Tondelli, Manuela, additional, Alhusaini, Saud, additional, Doherty, Colin P., additional, Cavalleri, Gianpiero L., additional, Delanty, Norman, additional, Kälviäinen, Reetta, additional, Jackson, Graeme D., additional, Kowalczyk, Magdalena, additional, Mascalchi, Mario, additional, Semmelroch, Mira, additional, Thomas, Rhys H., additional, Soltanian-Zadeh, Hamid, additional, Davoodi-Bojd, Esmaeil, additional, Zhang, Junsong, additional, Lenge, Matteo, additional, Guerrini, Renzo, additional, Bartolini, Emanuele, additional, Hamandi, Khalid, additional, Foley, Sonya, additional, Rüber, Theodor, additional, Bauer, Tobias, additional, Weber, Bernd, additional, Caldairou, Benoit, additional, Depondt, Chantal, additional, Absil, Julie, additional, Carr, Sarah J. A., additional, Abela, Eugenio, additional, Richardson, Mark P., additional, Devinsky, Orrin, additional, Pardoe, Heath, additional, Severino, Mariasavina, additional, Striano, Pasquale, additional, Tortora, Domenico, additional, Kaestner, Erik, additional, Hatton, Sean N., additional, Arienzo, Donatello, additional, Vos, Sjoerd B., additional, Ryten, Mina, additional, Taylor, Peter N., additional, Duncan, John S., additional, Whelan, Christopher D., additional, Galovic, Marian, additional, Winston, Gavin P., additional, Thomopoulos, Sophia I., additional, Thompson, Paul M., additional, Sisodiya, Sanjay M., additional, Labate, Angelo, additional, McDonald, Carrie R., additional, Caciagli, Lorenzo, additional, Bernasconi, Neda, additional, Bernasconi, Andrea, additional, Larivière, Sara, additional, Schrader, Dewi, additional, and Bernhardt, Boris C., additional

Published
2024
Full Text
View/download PDF

31. Phenotypic analysis of 303 multiplex families with common epilepsies.

Author

Abou-Khalil, Bassel, Afawi, Zaid, Allen, Andrew S, Bautista, Jocelyn F, Bellows, Susannah T, Berkovic, Samuel F, Bluvstein, Judith, Burgess, Rosemary, Cascino, Gregory, Cops, Elisa J, Cossette, Patrick, Cristofaro, Sabrina, Crompton, Douglas E, Delanty, Norman, Devinsky, Orrin, Dlugos, Dennis, Epstein, Michael P, Fountain, Nathan B, Freyer, Catharine, Garry, Sarah I, Geller, Eric B, Glauser, Tracy, Glynn, Simon, Goldberg-Stern, Hadassa, Goldstein, David B, Gravel, Micheline, Haas, Kevin, Haut, Sheryl, Heinzen, Erin L, Kirsch, Heidi E, Kivity, Sara, Knowlton, Robert, Korczyn, Amos D, Kossoff, Eric, Kuzniecky, Ruben, Loeb, Rebecca, Lowenstein, Daniel H, Marson, Anthony G, McCormack, Mark, McKenna, Kevin, Mefford, Heather C, Motika, Paul, Mullen, Saul A, O'Brien, Terence J, Ottman, Ruth, Paolicchi, Juliann, Parent, Jack M, Paterson, Sarah, Petrovski, Slave, Pickrell, William Owen, Poduri, Annapurna, Rees, Mark I, Sadleir, Lynette G, Scheffer, Ingrid E, Shih, Jerry, Singh, Rani, Sirven, Joseph, Smith, Michael, Smith, Phil EM, Thio, Liu Lin, Thomas, Rhys H, Venkat, Anu, Vining, Eileen, Von Allmen, Gretchen, Weisenberg, Judith, Widdess-Walsh, Peter, and Winawer, Melodie R

Subjects
Genetics, Clinical Research, Brain Disorders, Pediatric, Neurosciences, Epilepsy, Neurodegenerative, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adolescent, Age of Onset, Child, Child, Preschool, Epilepsy, Generalized, Family Health, Female, Humans, Male, Pedigree, Phenotype, Sex Factors, Young Adult, epilepsy, multiplex families, phenotype, genetics, Epi4K Consortium, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Gene identification in epilepsy has mainly been limited to large families segregating genes of major effect and de novo mutations in epileptic encephalopathies. Many families that present with common non-acquired focal epilepsies and genetic generalized epilepsies remain unexplained. We assembled a cohort of 'genetically enriched' common epilepsies by collecting and phenotyping families containing multiple individuals with unprovoked seizures. We aimed to determine if specific clinical epilepsy features aggregate within families, and whether this segregation of phenotypes may constitute distinct 'familial syndromes' that could inform genomic analyses. Families with three or more individuals with unprovoked seizures were studied across multiple international centres. Affected individuals were phenotyped and classified according to specific electroclinical syndromes. Families were categorized based on syndromic groupings of affected family members, examined for pedigree structure and phenotypic patterns and, where possible, assigned specific familial epilepsy syndromes. A total of 303 families were assembled and analysed, comprising 1120 affected phenotyped individuals. Of the 303 families, 117 exclusively segregated generalized epilepsy, 62 focal epilepsy, and 22 were classified as genetic epilepsy with febrile seizures plus. Over one-third (102 families) were observed to have mixed epilepsy phenotypes: 78 had both generalized and focal epilepsy features within the same individual (n = 39), or within first or second degree relatives (n = 39). Among the genetic generalized epilepsy families, absence epilepsies were found to cluster within families independently of juvenile myoclonic epilepsy, and significantly more females were affected than males. Of the 62 familial focal epilepsy families, two previously undescribed familial focal syndrome patterns were evident: 15 families had posterior quadrant epilepsies, including seven with occipito-temporal localization and seven with temporo-parietal foci, and four families displayed familial focal epilepsy of childhood with multiple affected siblings that was suggestive of recessive inheritance. The findings suggest (i) specific patterns of syndromic familial aggregation occur, including newly recognized forms of familial focal epilepsy; (ii) although syndrome-specificity usually occurs in multiplex families, the one-third of families with features of both focal and generalized epilepsy is suggestive of shared genetic determinants; and (iii) patterns of features observed across families including pedigree structure, sex, and age of onset may hold clues for future gene identification. Such detailed phenotypic information will be invaluable in the conditioning and interpretation of forthcoming sequencing data to understand the genetic architecture and inter-relationships of the common epilepsy syndromes.

Published
2017

34. Therapeutic strategies during cenobamate treatment initiation: Delphi panel recommendations.

Author

Steinhoff, Bernhard J., Ben-Menachem, Elinor, Klein, Pavel, Peltola, Jukka, Schmitz, Bettina, Thomas, Rhys H., and Villanueva, Vicente

Subjects
ANTICONVULSANTS, SEIZURES diagnosis, TREATMENT of epilepsy, INTELLECTUAL disabilities, MEDICAL personnel
Abstract

The goal of epilepsy treatment is seizure freedom, typically with antiseizure medication (ASM). If patients fail to attain seizure control despite two trials of appropriately chosen ASMs at adequate doses, they are classified as having drug-resistant epilepsy (DRE). Adverse events (AEs) commonly occur in people with DRE because they are typically on ⩾2 ASMs, increasing the potential for drug–drug interactions. Early emerging AEs may impact adherence, decrease quality of life, and delay achieving optimal treatment dosages. Cenobamate is an oral ASM with a long half-life which has proven to be highly effective in clinical trials. An international Delphi panel of expert epileptologists experienced in the clinical use of cenobamate and other ASMs was convened to develop consensus best practices for managing patients during and after cenobamate titration, with consideration for its known pharmacokinetic and pharmacodynamic interactions, to allow patients to reach the most appropriate cenobamate dose while limiting tolerability issues. The modified Delphi process included one open-ended questionnaire and one virtual face-to-face meeting. Participants agreed that cenobamate can be prescribed for most patients experiencing focal-onset seizures. Patients initiating cenobamate therapy should have access to healthcare professionals as needed and their treatment response should be evaluated at the 100-mg dose. Patients with intellectual disabilities may need additional support to navigate the titration period. Proactive down-titration or withdrawal of sodium channel blockers (SCBs) is recommended when concomitant ASM regimens include ⩾2 SCBs. When applicable, maintaining a concomitant clobazam dose at ~5–10 mg may be beneficial. Patients taking oral contraceptives, newer oral anticoagulants, or HIV antiretroviral medications should be monitored for potential interactions. Because clinical evidence informing treatment decisions is limited, guidance regarding dose adjustments of non-ASM drugs was not developed beyond specific recommendations presented in the Summary of Product Characteristics. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

35. Neurological and neuropsychiatric complications of COVID-19 in 153 patients: a UK-wide surveillance study

Author

Allen, Claire, Archibald, Neil, Arkell, James, Arthur-Farraj, Peter, Baker, Mark, Ball, Harriet, Bradley-Barker, Verity, Brown, Zoe, Bruno, Stefania, Carey, Lois, Carswell, Christopher, Chakrabarti, Annie, Choulerton, James, Daher, Mazen, Davies, Ruth, Di Marco Barros, Rafael, Dima, Sofia, Dunley, Rachel, Dutta, Dipankar, Ellis, Richard, Everitt, Alex, Fady, Joseph, Fearon, Patricia, Fisniku, Leonora, Gbinigie, Ivie, Gemski, Alan, Gillies, Emma, Gkrania-Klotsas, Effrossyni, Grigg, Julie, Hamdalla, Hisham, Hubbett, Jack, Hunter, Neil, Huys, Anne-Catherine, Ihmoda, Ihmoda, Ispoglou, Sissi, Jha, Ashwani, Joussi, Ramzi, Kalladka, Dheeraj, Khalifeh, Hind, Kooij, Sander, Kumar, Guru, Kyaw, Sandar, Li, Lucia, Littleton, Edward, Macleod, Malcolm, Macleod, Mary Joan, Madigan, Barbara, Mahadasa, Vikram, Manoharan, Manonmani, Marigold, Richard, Marks, Isaac, Matthews, Paul, Mccormick, Michael, Mcinnes, Caroline, Metastasio, Antonio, Milburn-McNulty, Philip, Mitchell, Clinton, Mitchell, Duncan, Morgans, Clare, Morris, Huw, Morrow, Jasper, Mubarak Mohamed, Ahmed, Mulvenna, Paula, Murphy, Louis, Namushi, Robert, Newman, Edward, Phillips, Wendy, Pinto, Ashwin, Price, David Ashley, Proschel, Harald, Quinn, Terry, Ramsey, Deborah, Roffe, Christine, Ross Russell, Amy, Samarasekera, Neshika, Sawcer, Stephen, Sayed, Walee, Sekaran, Lakshmanan, Serra-Mestres, Jordi, Snowdon, Victoria, Strike, Gayle, Sun, James, Tang, Christina, Vrana, Mark, Wade, Ryckie, Wharton, Chris, Wiblin, Lou, Boubriak, Iryna, Herman, Katie, Plant, Gordon, Varatharaj, Aravinthan, Thomas, Naomi, Ellul, Mark A, Davies, Nicholas W S, Pollak, Thomas A, Tenorio, Elizabeth L, Sultan, Mustafa, Easton, Ava, Breen, Gerome, Zandi, Michael, Coles, Jonathan P, Manji, Hadi, Al-Shahi Salman, Rustam, Menon, David K, Nicholson, Timothy R, Benjamin, Laura A, Carson, Alan, Smith, Craig, Turner, Martin R, Solomon, Tom, Kneen, Rachel, Pett, Sarah L, Galea, Ian, Thomas, Rhys H, and Michael, Benedict D

Published
2020
Full Text
View/download PDF

39. The Human Phenotype Ontology in 2024: phenotypes around the world

Author

Gargano, Michael A, primary, Matentzoglu, Nicolas, additional, Coleman, Ben, additional, Addo-Lartey, Eunice B, additional, Anagnostopoulos, Anna V, additional, Anderton, Joel, additional, Avillach, Paul, additional, Bagley, Anita M, additional, Bakštein, Eduard, additional, Balhoff, James P, additional, Baynam, Gareth, additional, Bello, Susan M, additional, Berk, Michael, additional, Bertram, Holli, additional, Bishop, Somer, additional, Blau, Hannah, additional, Bodenstein, David F, additional, Botas, Pablo, additional, Boztug, Kaan, additional, Čady, Jolana, additional, Callahan, Tiffany J, additional, Cameron, Rhiannon, additional, Carbon, Seth J, additional, Castellanos, Francisco, additional, Caufield, J Harry, additional, Chan, Lauren E, additional, Chute, Christopher G, additional, Cruz-Rojo, Jaime, additional, Dahan-Oliel, Noémi, additional, Davids, Jon R, additional, de Dieuleveult, Maud, additional, de Souza, Vinicius, additional, de Vries, Bert B A, additional, de Vries, Esther, additional, DePaulo, J Raymond, additional, Derfalvi, Beata, additional, Dhombres, Ferdinand, additional, Diaz-Byrd, Claudia, additional, Dingemans, Alexander J M, additional, Donadille, Bruno, additional, Duyzend, Michael, additional, Elfeky, Reem, additional, Essaid, Shahim, additional, Fabrizzi, Carolina, additional, Fico, Giovanna, additional, Firth, Helen V, additional, Freudenberg-Hua, Yun, additional, Fullerton, Janice M, additional, Gabriel, Davera L, additional, Gilmour, Kimberly, additional, Giordano, Jessica, additional, Goes, Fernando S, additional, Moses, Rachel Gore, additional, Green, Ian, additional, Griese, Matthias, additional, Groza, Tudor, additional, Gu, Weihong, additional, Guthrie, Julia, additional, Gyori, Benjamin, additional, Hamosh, Ada, additional, Hanauer, Marc, additional, Hanušová, Kateřina, additional, He, Yongqun (Oliver), additional, Hegde, Harshad, additional, Helbig, Ingo, additional, Holasová, Kateřina, additional, Hoyt, Charles Tapley, additional, Huang, Shangzhi, additional, Hurwitz, Eric, additional, Jacobsen, Julius O B, additional, Jiang, Xiaofeng, additional, Joseph, Lisa, additional, Keramatian, Kamyar, additional, King, Bryan, additional, Knoflach, Katrin, additional, Koolen, David A, additional, Kraus, Megan L, additional, Kroll, Carlo, additional, Kusters, Maaike, additional, Ladewig, Markus S, additional, Lagorce, David, additional, Lai, Meng-Chuan, additional, Lapunzina, Pablo, additional, Laraway, Bryan, additional, Lewis-Smith, David, additional, Li, Xiarong, additional, Lucano, Caterina, additional, Majd, Marzieh, additional, Marazita, Mary L, additional, Martinez-Glez, Victor, additional, McHenry, Toby H, additional, McInnis, Melvin G, additional, McMurry, Julie A, additional, Mihulová, Michaela, additional, Millett, Caitlin E, additional, Mitchell, Philip B, additional, Moslerová, Veronika, additional, Narutomi, Kenji, additional, Nematollahi, Shahrzad, additional, Nevado, Julian, additional, Nierenberg, Andrew A, additional, Čajbiková, Nikola Novák, additional, Nurnberger, John I, additional, Ogishima, Soichi, additional, Olson, Daniel, additional, Ortiz, Abigail, additional, Pachajoa, Harry, additional, Perez de Nanclares, Guiomar, additional, Peters, Amy, additional, Putman, Tim, additional, Rapp, Christina K, additional, Rath, Ana, additional, Reese, Justin, additional, Rekerle, Lauren, additional, Roberts, Angharad M, additional, Roy, Suzy, additional, Sanders, Stephan J, additional, Schuetz, Catharina, additional, Schulte, Eva C, additional, Schulze, Thomas G, additional, Schwarz, Martin, additional, Scott, Katie, additional, Seelow, Dominik, additional, Seitz, Berthold, additional, Shen, Yiping, additional, Similuk, Morgan N, additional, Simon, Eric S, additional, Singh, Balwinder, additional, Smedley, Damian, additional, Smith, Cynthia L, additional, Smolinsky, Jake T, additional, Sperry, Sarah, additional, Stafford, Elizabeth, additional, Stefancsik, Ray, additional, Steinhaus, Robin, additional, Strawbridge, Rebecca, additional, Sundaramurthi, Jagadish Chandrabose, additional, Talapova, Polina, additional, Tenorio Castano, Jair A, additional, Tesner, Pavel, additional, Thomas, Rhys H, additional, Thurm, Audrey, additional, Turnovec, Marek, additional, van Gijn, Marielle E, additional, Vasilevsky, Nicole A, additional, Vlčková, Markéta, additional, Walden, Anita, additional, Wang, Kai, additional, Wapner, Ron, additional, Ware, James S, additional, Wiafe, Addo A, additional, Wiafe, Samuel A, additional, Wiggins, Lisa D, additional, Williams, Andrew E, additional, Wu, Chen, additional, Wyrwoll, Margot J, additional, Xiong, Hui, additional, Yalin, Nefize, additional, Yamamoto, Yasunori, additional, Yatham, Lakshmi N, additional, Yocum, Anastasia K, additional, Young, Allan H, additional, Yüksel, Zafer, additional, Zandi, Peter P, additional, Zankl, Andreas, additional, Zarante, Ignacio, additional, Zvolský, Miroslav, additional, Toro, Sabrina, additional, Carmody, Leigh C, additional, Harris, Nomi L, additional, Munoz-Torres, Monica C, additional, Danis, Daniel, additional, Mungall, Christopher J, additional, Köhler, Sebastian, additional, Haendel, Melissa A, additional, and Robinson, Peter N, additional

Published
2023
Full Text
View/download PDF

41. List of contributors

Author

Agrawal, Anurag, primary, Agrawal, Megha, additional, AlBanyan, Saleh, additional, Baranwal, Ajay Kumar, additional, Behr, Elijah R., additional, Bhatnagar, Deepak, additional, Bose, D., additional, Busi, María V., additional, Chakraborty, Samarpana, additional, Chitayat, David, additional, Craig, Donald P., additional, Das, Reena, additional, Davies, Dyfud Mark, additional, Doctor, Pezad, additional, Garofalidou, Tatiana, additional, Godbole, Koumudi, additional, Gogtay, N.J., additional, Gomez-Casati, Diego F., additional, Gupta, Anubhuti, additional, Haddad, Luciana Amaral, additional, Hamandi, Khalid, additional, Hegde, Shivaram, additional, Hodgson, Shirley V., additional, Kalhan, Atul, additional, Kirov, George, additional, Kleinendorst, Lotte, additional, Kumar, Dhavendra, additional, Lewis-Smith, David, additional, MacIver, Claire, additional, Mehra, Narinder Kumar, additional, Merchant, Rashid, additional, Morgan, Dafydd, additional, Munroe, Patricia B., additional, Ormerod, Julian O.M., additional, Pathan, Saad, additional, Peall, Kathryn J., additional, Ravi, R., additional, Rees, Elliott, additional, Schofield, Jonathan, additional, Shah, Parin, additional, Sharma, Gaurav, additional, Sharma, Prashant, additional, Sinajon, Pierre, additional, Singh, Indu, additional, Singh, Raghu Inder, additional, Soran, Handrean, additional, Stuart, Alan Graham, additional, Thatte, U.M., additional, Thomas, Naomi J.P., additional, Thomas, Rhys H., additional, Tully, IAN, additional, van Haelst, Mieke M., additional, Varaiya, Ami, additional, Yamada, Yoshiji, additional, and Zaidi, Abbas, additional

Published
2020
Full Text
View/download PDF

46. Neurologic phenotypes associated with COL4A1/2 mutations: Expanding the spectrum of disease

Author

Zagaglia, Sara, Selch, Christina, Nisevic, Jelena Radic, Mei, Davide, Michalak, Zuzanna, Hernandez-Hernandez, Laura, Krithika, S., Vezyroglou, Katharina, Varadkar, Sophia M., Pepler, Alexander, Biskup, Saskia, Leão, Miguel, Gärtner, Jutta, Merkenschlager, Andreas, Jaksch, Michaela, Møller, Rikke S., Gardella, Elena, Kristiansen, Britta Schlott, Hansen, Lars Kjærsgaard, Vari, Maria Stella, Helbig, Katherine L., Desai, Sonal, Smith-Hicks, Constance L., Hino-Fukuyo, Naomi, Talvik, Tiina, Laugesaar, Rael, Ilves, Pilvi, Õunap, Katrin, Körber, Ingrid, Hartlieb, Till, Kudernatsch, Manfred, Winkler, Peter, Schimmel, Mareike, Hasse, Anette, Knuf, Markus, Heinemeyer, Jan, Makowski, Christine, Ghedia, Sondhya, Subramanian, Gopinath M., Striano, Pasquale, Thomas, Rhys H., Micallef, Caroline, Thom, Maria, Werring, David J., Kluger, Gerhard Josef, Cross, J. Helen, Guerrini, Renzo, Balestrini, Simona, and Sisodiya, Sanjay M.

Published
2018
Full Text
View/download PDF

47. Clinical spectrum of STX1B-related epileptic disorders

Author

Wolking, Stefan, May, Patrick, Mei, Davide, Møller, Rikke S., Balestrini, Simona, Helbig, Katherine L., Altuzarra, Cecilia Desmettre, Chatron, Nicolas, Kaiwar, Charu, Stöhr, Katharina, Widdess-Walsh, Peter, Mendelsohn, Bryce A., Numis, Adam, Cilio, Maria R., Van Paesschen, Wim, Svendsen, Lene L., Oates, Stephanie, Hughes, Elaine, Goyal, Sushma, Brown, Kathleen, Sifuentes Saenz, Margarita, Dorn, Thomas, Muhle, Hiltrud, Pagnamenta, Alistair T., Vavoulis, Dimitris V., Knight, Samantha J.L., Taylor, Jenny C., Canevini, Maria Paola, Darra, Francesca, Gavrilova, Ralitza H., Powis, Zöe, Tang, Shan, Marquetand, Justus, Armstrong, Martin, McHale, Duncan, Klee, Eric W., Kluger, Gerhard J., Lowenstein, Daniel H., Weckhuysen, Sarah, Pal, Deb K., Helbig, Ingo, Guerrini, Renzo, Thomas, Rhys H., Rees, Mark I., Lesca, Gaetan, Sisodiya, Sanjay M., Weber, Yvonne G., Lal, Dennis, Marini, Carla, Lerche, Holger, and Schubert, Julian

Published
2019
Full Text
View/download PDF

48. A library of quantitative markers of seizure severity

Author

Gascoigne, Sarah J., primary, Waldmann, Leonard, additional, Schroeder, Gabrielle M., additional, Panagiotopoulou, Mariella, additional, Blickwedel, Jess, additional, Chowdhury, Fahmida, additional, Cronie, Alison, additional, Diehl, Beate, additional, Duncan, John S., additional, Falconer, Jennifer, additional, Faulder, Ryan, additional, Guan, Yu, additional, Leach, Veronica, additional, Livingstone, Shona, additional, Papasavvas, Christoforos, additional, Thomas, Rhys H., additional, Wilson, Kevin, additional, Taylor, Peter N., additional, and Wang, Yujiang, additional

Published
2023
Full Text
View/download PDF

50. The different clinical facets of SYN1-related neurodevelopmental disorders

Author

Parenti, Ilaria, primary, Leitão, Elsa, additional, Kuechler, Alma, additional, Villard, Laurent, additional, Goizet, Cyril, additional, Courdier, Cécile, additional, Bayat, Allan, additional, Rossi, Alessandra, additional, Julia, Sophie, additional, Bruel, Ange-Line, additional, Tran Mau-Them, Frédéric, additional, Nambot, Sophie, additional, Lehalle, Daphné, additional, Willems, Marjolaine, additional, Lespinasse, James, additional, Ghoumid, Jamal, additional, Caumes, Roseline, additional, Smol, Thomas, additional, El Chehadeh, Salima, additional, Schaefer, Elise, additional, Abi-Warde, Marie-Thérèse, additional, Keren, Boris, additional, Afenjar, Alexandra, additional, Tabet, Anne-Claude, additional, Levy, Jonathan, additional, Maruani, Anna, additional, Aledo-Serrano, Ángel, additional, Garming, Waltraud, additional, Milleret-Pignot, Clara, additional, Chassevent, Anna, additional, Koopmans, Marije, additional, Verbeek, Nienke E., additional, Person, Richard, additional, Belles, Rebecca, additional, Bellus, Gary, additional, Salbert, Bonnie A., additional, Kaiser, Frank J., additional, Mazzola, Laure, additional, Convers, Philippe, additional, Perrin, Laurine, additional, Piton, Amélie, additional, Wiegand, Gert, additional, Accogli, Andrea, additional, Brancati, Francesco, additional, Benfenati, Fabio, additional, Chatron, Nicolas, additional, Lewis-Smith, David, additional, Thomas, Rhys H., additional, Zara, Federico, additional, Striano, Pasquale, additional, Lesca, Gaetan, additional, and Depienne, Christel, additional

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results