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1,132 results on '"Devinsky O."'

1. Effects of ganaxolone on non-seizure outcomes in CDKL5 Deficiency Disorder: Double-blind placebo-controlled randomized trial.

Author: Downs, J, Jacoby, P, Specchio, N, Cross, H, Amin, S, Bahi-Buisson, N, Rajaraman, Rajsekar, Suter, B, Devinsky, O, Aimetti, A, Busse, G, Olson, H, Demarest, S, Benke, T, and Pestana-Knight, E
Subjects: Anti-Seizure medication, CDKL5 deficiency disorder, Epilepsy, Patient-reported outcomes, Humans, Female, Male, Double-Blind Method, Child, Child, Preschool, Adolescent, Quality of Life, Young Adult, Treatment Outcome, Epileptic Syndromes, Seizures, Pregnanolone, Spasms, Infantile
Abstract: CDKL5 deficiency disorder (CDD) is a rare developmental and epileptic encephalopathy. Ganaxolone, a neuroactive steroid, reduces the frequency of major motor seizures in children with CDD. This analysis explored the effect of ganaxolone on non-seizure outcomes. Children (2-19 years) with genetically confirmed CDD and ≥ 16 major motor seizures per month were enrolled in a double-blind randomized placebo-controlled trial. Ganaxolone or placebo was administered three times daily for 17 weeks. Behaviour was measured with the Anxiety, Depression and Mood Scale (ADAMS), daytime sleepiness with the Child Health Sleep Questionnaire, and quality of life with the Quality of Life Inventory-Disability (QI-Disability) scale. Scores were compared using ANOVA, adjusted for age, sex, number of anti-seizure mediations, baseline 28-day major motor seizure frequency, baseline developmental skills, and behaviour, sleep or quality of life scores. 101 children with CDD (39 clinical sites, 8 countries) were randomized. Median (IQR) age was 6 (3-10) years, 79.2 % were female, and 50 received ganaxolone. After 17 weeks of treatment, Manic/Hyperactive scores (mean difference 1.27, 95%CI -2.38,-0.16) and Compulsive Behaviour scores (mean difference 0.58, 95%CI -1.14,-0.01) were lower (improved) in the ganaxolone group compared with the placebo group. Daytime sleepiness scores were similar between groups. The total change in QOL score for children in the ganaxolone group was 2.6 points (95%CI -1.74,7.02) higher (improved) than in the placebo group but without statistical significance. Along with better seizure control, children who received ganaxolone had improved behavioural scores in select domains compared to placebo.
Published: 2024

2. Effects of ganaxolone on non-seizure outcomes in CDKL5 Deficiency Disorder: Double-blind placebo-controlled randomized trial

Author: Downs, J., Jacoby, P., Specchio, N., Cross, H., Amin, S., Bahi-Buisson, N., Rajaraman, R., Suter, B., Devinsky, O., Aimetti, A., Busse, G., Olson, H.E., Demarest, S., Benke, T.A., and Pestana-Knight, E.
Published: 2024
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3. Simulating human sleep spindle MEG and EEG from ion channel and circuit level dynamics

Author: Rosen, BQ, Krishnan, GP, Sanda, P, Komarov, M, Sejnowski, T, Rulkov, N, Ulbert, I, Eross, L, Madsen, J, Devinsky, O, Doyle, W, Fabo, D, Cash, S, Bazhenov, M, and Halgren, E
Subjects: Medical Physiology, Biomedical and Clinical Sciences, Sleep Research, Neurosciences, Biomedical Imaging, Behavioral and Social Science, Basic Behavioral and Social Science, Underpinning research, 1.1 Normal biological development and functioning, Neurological, Adolescent, Adult, Cerebral Cortex, Computer Simulation, Electroencephalography, Female, Humans, Ion Channels, Magnetic Resonance Imaging, Magnetoencephalography, Male, Models, Biological, Nerve Net, Sleep Stages, Thalamus, Young Adult, MEG, EEG, Forward model, Sleep, Spindle, Cortex, Human, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract: BackgroundAlthough they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain.MethodWe present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits. 32,652 cortical neurons were mapped onto the cortical surface reconstructed from subjects' MRI, interconnected based on geodesic distances, and scaled-up to current dipole densities based on laminar recordings in humans. MRIs were used to generate a quasi-static electromagnetic model enabling simulated cortical activity to be projected to the M/EEG sensors.ResultsThe simulated M/EEG spindles were similar in amplitude and topography to empirical examples in the same subjects. Simulated spindles with more core-dominant activity were more MEG weighted.Comparison with existing methodsPrevious models lacked either spindle-generating thalamic neural dynamics or whole head biophysical modeling; the framework presented here is the first to simultaneously capture these disparate scales.ConclusionsThis multiscale model provides a platform for the principled quantitative integration of existing information relevant to the generation of sleep spindles, and allows the implications of future findings to be explored. It provides a proof of principle for a methodological framework allowing large-scale integrative brain oscillations to be understood in terms of their underlying channels and synapses.
Published: 2019

4. Potential of cannabinoids as treatments for autism spectrum disorders

Author: Nezgovorova, V., Ferretti, C.J., Taylor, B.P., Shanahan, E., Uzunova, G., Hong, K., Devinsky, O., and Hollander, E.
Published: 2021
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5. An iPSC line (FINi003-A) from a male with late-onset developmental and epileptic encephalopathy caused by a heterozygous p.E1211K variant in the SCN2A gene encoding the voltage-gated sodium channel Nav1.2

Author: Ovchinnikov, DA, Jong, S, Cuddy, C, Dalby, K, Devinsky, O, Mullen, S, Maljevic, S, Petrou, S, Ovchinnikov, DA, Jong, S, Cuddy, C, Dalby, K, Devinsky, O, Mullen, S, Maljevic, S, and Petrou, S
Abstract: Many developmental and epileptic encephalopathies (DEEs) result from variants in cation channel genes. Using mRNA transfection, we generated and characterised an induced pluripotent stem cell (iPSC) line from the fibroblasts of a male late-onset DEE patient carrying a heterozygous missense variant (E1211K) in Nav1.2(SCN2A) protein. The iPSC line displays features characteristic of the human iPSCs, colony morphology and expression of pluripotency-associated marker genes, ability to produce derivatives of all three embryonic germ layers, and normal karyotype without SNP array-detectable abnormalities. We anticipate that this iPSC line will aid in the modelling and development of precision therapies for this debilitating condition.
Published: 2024

6. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author: Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J., Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, and Gorgolewski, Krzysztof J.
Abstract: The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.
Published: 2024

7. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author: Poldrack, R. A., Markiewicz, C. J., Appelhoff, S., Ashar, Y. K., Auer, T., Baillet, S., Bansal, S., Beltrachini, L., Bertazzoli, G., Bhogawar, S., Blair, R. W., Bortoletto, M., Boudreau, M., Brooks, T. L., Bénar, C. G., Calhoun, V. D., Castelli, F. M., Clement, P., Cohen, A. L., Cohen-Adad, J., Dambrosio, S., Delorme, A., Devinsky, O., Draschkow, D., Duff, E. P., Dupre, E., Earl, E., Esteban, O., Feingold, F. W., Flandin, G., Galassi, A., Gallitto, G., Ganz, M., Gholam, J., Ghosh, S. S., Giacomel, A., Gillman, A. G., Gleeson, P., Gramfort, A., Guay, S., Guidali, G., Halchenko, Y. O., Handwerker, D. A., Hardcastle, N., Herholz, P., Hermes, D., Honey, C. J., Innis, R. B., Ioanas, H.-I., Jahn, A., Karakuzu, A., Keator, D. B., Kiar, G., Kincses, B., Laird, A. R., Lau, J. C., Lazari, A., Legarreta, J. H., Li, A., Li, X., Love, B. C., Lu, H., Maumet, C., Mazzamuto, G., Meisler, S. L., Mikkelsen, M., Mutsaerts, H., Nichols, T. E., Nikolaidis, A., Nilsonne, G., Niso, G., Norgaard, M., Okell, T. W., Oostenveld, R., Ort, E., Park, P. J., Pawlik, M., Pernet, C. R., Pestilli, F., (0000-0002-3201-6002) Petr, J., Phillips, C., Poline, J.-B., Pollonini, L., Raamana, P. R., Ritter, P., Rizzo, G., Robbins, K. A., Rockhill, A. P., Rogers, C., Rokem, A., Rorden, C., Routier, A., Saborit-Torres, J. M., Salo, T., Schirner, M., Smith, R. E., Spisak, T., Sprenger, J., Swann, N. C., Szinte, M., Takerkart, S., Thirion, B., Thomas, A. G., Torabian, S., Varoquaux, G., Vaya, M. D. L. I., Voytek, B., Welzel, J., Wilson, M., Hollander, G., Vega, A., Gorgolewski, K. J., Poldrack, R. A., Markiewicz, C. J., Appelhoff, S., Ashar, Y. K., Auer, T., Baillet, S., Bansal, S., Beltrachini, L., Bertazzoli, G., Bhogawar, S., Blair, R. W., Bortoletto, M., Boudreau, M., Brooks, T. L., Bénar, C. G., Calhoun, V. D., Castelli, F. M., Clement, P., Cohen, A. L., Cohen-Adad, J., Dambrosio, S., Delorme, A., Devinsky, O., Draschkow, D., Duff, E. P., Dupre, E., Earl, E., Esteban, O., Feingold, F. W., Flandin, G., Galassi, A., Gallitto, G., Ganz, M., Gholam, J., Ghosh, S. S., Giacomel, A., Gillman, A. G., Gleeson, P., Gramfort, A., Guay, S., Guidali, G., Halchenko, Y. O., Handwerker, D. A., Hardcastle, N., Herholz, P., Hermes, D., Honey, C. J., Innis, R. B., Ioanas, H.-I., Jahn, A., Karakuzu, A., Keator, D. B., Kiar, G., Kincses, B., Laird, A. R., Lau, J. C., Lazari, A., Legarreta, J. H., Li, A., Li, X., Love, B. C., Lu, H., Maumet, C., Mazzamuto, G., Meisler, S. L., Mikkelsen, M., Mutsaerts, H., Nichols, T. E., Nikolaidis, A., Nilsonne, G., Niso, G., Norgaard, M., Okell, T. W., Oostenveld, R., Ort, E., Park, P. J., Pawlik, M., Pernet, C. R., Pestilli, F., (0000-0002-3201-6002) Petr, J., Phillips, C., Poline, J.-B., Pollonini, L., Raamana, P. R., Ritter, P., Rizzo, G., Robbins, K. A., Rockhill, A. P., Rogers, C., Rokem, A., Rorden, C., Routier, A., Saborit-Torres, J. M., Salo, T., Schirner, M., Smith, R. E., Spisak, T., Sprenger, J., Swann, N. C., Szinte, M., Takerkart, S., Thirion, B., Thomas, A. G., Torabian, S., Varoquaux, G., Vaya, M. D. L. I., Voytek, B., Welzel, J., Wilson, M., Hollander, G., Vega, A., and Gorgolewski, K. J.
Abstract: The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, and the mechanisms by which it has been extended. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.
Published: 2024

8. Early manifestations of renal disease in patients with tuberous sclerosis complex

Author: Malaga-Dieguez L, Spencer R, Pehrson LJ, Vento S, Menzer K, Devinsky O, and Trachtman H
Subjects: Tuberous sclerosis complex, TSC, chronic kidney disease, CKD, Hypertension, Proteinuria, eGFR., Diseases of the genitourinary system. Urology, RC870-923
Abstract: Laura Malaga-Dieguez,1 Robert Spencer,1 Laura J Pehrson,1 Suzanne Vento,1 Kimberly Menzer,2 Orrin Devinsky,2 Howard Trachtman1 1Division of Pediatric Nephrology, 2Department of Neurology, Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY, USA Objectives: Renal manifestations are the second most significant cause of morbidity and mortality in patients with tuberous sclerosis complex (TSC), and include renal cysts, angiomyolipomas, fat-poor lesions, and malignant tumors. These lesions begin in childhood and often lead to chronic kidney disease (CKD). Little is known on the incidence of early modifiable risk factors of CKD, such as proteinuria and hypertension, or subtle decreases in glomerular filtration rate that correspond to the early stages of CKD in children with TSC. The impact of genotype on these early manifestations of CKD has not been investigated. Design: Retrospective chart review of 84 children and young adults with TSC. Measurements: This study assessed the prevalence of hypertension, renal impairment, and proteinuria, as well as the genotype–phenotype correlations. Results: Children and young adults with TSC2 mutations had a significantly higher rate of renal lesions, hypertension (36% vs 14%), and decreased renal function than those with TSC1 mutations. Conclusion: On the basis of estimated glomerular filtration rate and blood pressure, our findings are consistent with the hypothesis that TSC2 mutations are associated with more severe early renal involvement in children. There is a compelling need for close collaboration of nephrologists and neurologists to provide care to pediatric patients with TSC to improve screening and management of early manifestations of renal disease. Keywords: tuberous sclerosis complex, chronic kidney disease, hypertension, proteinuria, estimated glomerular filtration rate
Published: 2017

9. GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

Author: Stevelink, R, Campbell, C, Chen, S, Abou-Khalil, B, Adesoji, OM, Afawi, Z, Amadori, E, Anderson, A, Anderson, J, Andrade, DM, Annesi, G, Auce, P, Avbersek, A, Bahlo, M, Baker, MD, Balagura, G, Balestrini, S, Barba, C, Barboza, K, Bartolomei, F, Bast, T, Baum, L, Baumgartner, T, Baykan, B, Bebek, N, Becker, AJ, Becker, F, Bennett, CA, Berghuis, B, Berkovic, SF, Beydoun, A, Bianchini, C, Bisulli, F, Blatt, I, Bobbili, DR, Borggraefe, I, Bosselmann, C, Braatz, V, Bradfield, JP, Brockmann, K, Brody, LC, Buono, RJ, Busch, RM, Caglayan, H, Campbell, E, Canafoglia, L, Canavati, C, Cascino, GD, Castellotti, B, Catarino, CB, Cavalleri, GL, Cerrato, F, Chassoux, F, Cherny, SS, Cheung, C-L, Chinthapalli, K, Chou, I-J, Chung, S-K, Churchhouse, C, Clark, PO, Cole, AJ, Compston, A, Coppola, A, Cosico, M, Cossette, P, Craig, JJ, Cusick, C, Daly, MJ, Davis, LK, de Haan, G-J, Delanty, N, Depondt, C, Derambure, P, Devinsky, O, Di Vito, L, Dlugos, DJ, Doccini, V, Doherty, CP, El-Naggar, H, Elger, CE, Ellis, CA, Eriksson, JG, Faucon, A, Feng, Y-CA, Ferguson, L, Ferraro, TN, Ferri, L, Feucht, M, Fitzgerald, M, Fonferko-Shadrach, B, Fortunato, F, Franceschetti, S, Franke, A, French, JA, Freri, E, Gagliardi, M, Gambardella, A, Geller, EB, Giangregorio, T, Gjerstad, L, Glauser, T, Goldberg, E, Goldman, A, Granata, T, Greenberg, DA, Guerrini, R, Gupta, N, Haas, KF, Hakonarson, H, Hallmann, K, Hassanin, E, Hegde, M, Heinzen, EL, Helbig, I, Hengsbach, C, Heyne, HO, Hirose, S, Hirsch, E, Hjalgrim, H, Howrigan, DP, Hucks, D, Hung, P-C, Iacomino, M, Imbach, LL, Inoue, Y, Ishii, A, Jamnadas-Khoda, J, Jehi, L, Johnson, MR, Kalviainen, R, Kamatani, Y, Kanaan, M, Kanai, M, Kantanen, A-M, Kara, B, Kariuki, SM, Kasperaviciute, D, Trenite, DK-N, Kato, M, Kegele, J, Kesim, Y, Khoueiry-Zgheib, N, King, C, Kirsch, HE, Klein, KM, Kluger, G, Knake, S, Knowlton, RC, Koeleman, BPC, Korczyn, AD, Koupparis, A, Kousiappa, I, Krause, R, Krenn, M, Krestel, H, Krey, I, Kunz, WS, Kurki, MI, Kurlemann, G, Kuzniecky, R, Kwan, P, Labate, A, Lacey, A, Lal, D, Landoulsi, Z, Lau, Y-L, Lauxmann, S, Leech, SL, Lehesjoki, A-E, Lemke, JR, Lerche, H, Lesca, G, Leu, C, Lewin, N, Lewis-Smith, D, Li, GH-Y, Li, QS, Licchetta, L, Lin, K-L, Lindhout, D, Linnankivi, T, Lopes-Cendes, I, Lowenstein, DH, Lui, CHT, Madia, F, Magnusson, S, Marson, AG, May, P, McGraw, CM, Mei, D, Mills, JL, Minardi, R, Mirza, N, Moller, RS, Molloy, AM, Montomoli, M, Mostacci, B, Muccioli, L, Muhle, H, Mueller-Schlueter, K, Najm, IM, Nasreddine, W, Neale, BM, Neubauer, B, Newton, CRJC, Noethen, MM, Nothnagel, M, Nuernberg, P, O'Brien, TJ, Okada, Y, Olafsson, E, Oliver, KL, Ozkara, C, Palotie, A, Pangilinan, F, Papacostas, SS, Parrini, E, Pato, CN, Pato, MT, Pendziwiat, M, Petrovski, S, Pickrell, WO, Pinsky, R, Pippucci, T, Poduri, A, Pondrelli, F, Powell, RHW, Privitera, M, Rademacher, A, Radtke, R, Ragona, F, Rau, S, Rees, MI, Regan, BM, Reif, PS, Rhelms, S, Riva, A, Rosenow, F, Ryvlin, P, Saarela, A, Sadleir, LG, Sander, JW, Sander, T, Scala, M, Scattergood, T, Schachter, SC, Schankin, CJ, Scheffer, IE, Schmitz, B, Schoch, S, Schubert-Bast, S, Schulze-Bonhage, A, Scudieri, P, Sham, P, Sheidley, BR, Shih, JJ, Sills, GJ, Sisodiya, SM, Smith, MC, Smith, PE, Sonsma, ACM, Speed, D, Sperling, MR, Stefansson, H, Stefansson, K, Steinhoff, BJ, Stephani, U, Stewart, WC, Stipa, C, Striano, P, Stroink, H, Strzelczyk, A, Surges, R, Suzuki, T, Tan, KM, Taneja, RS, Tanteles, GA, Tauboll, E, Thio, LL, Thomas, GN, Thomas, RH, Timonen, O, Tinuper, P, Todaro, M, Topaloglu, P, Tozzi, R, Tsai, M-H, Tumiene, B, Turkdogan, D, Unnsteinsdottir, U, Utkus, A, Vaidiswaran, P, Valton, L, van Baalen, A, Vetro, A, Vining, EPG, Visscher, F, von Brauchitsch, S, von Wrede, R, Wagner, RG, Weber, YG, Weckhuysen, S, Weisenberg, J, Weller, M, Widdess-Walsh, P, Wolff, M, Wolking, S, Wu, D, Yamakawa, K, Yang, W, Yapici, Z, Yucesan, E, Zagaglia, S, Zahnert, F, Zara, F, Zhou, W, Zimprich, F, Zsurka, G, Ali, QZ, Stevelink, R, Campbell, C, Chen, S, Abou-Khalil, B, Adesoji, OM, Afawi, Z, Amadori, E, Anderson, A, Anderson, J, Andrade, DM, Annesi, G, Auce, P, Avbersek, A, Bahlo, M, Baker, MD, Balagura, G, Balestrini, S, Barba, C, Barboza, K, Bartolomei, F, Bast, T, Baum, L, Baumgartner, T, Baykan, B, Bebek, N, Becker, AJ, Becker, F, Bennett, CA, Berghuis, B, Berkovic, SF, Beydoun, A, Bianchini, C, Bisulli, F, Blatt, I, Bobbili, DR, Borggraefe, I, Bosselmann, C, Braatz, V, Bradfield, JP, Brockmann, K, Brody, LC, Buono, RJ, Busch, RM, Caglayan, H, Campbell, E, Canafoglia, L, Canavati, C, Cascino, GD, Castellotti, B, Catarino, CB, Cavalleri, GL, Cerrato, F, Chassoux, F, Cherny, SS, Cheung, C-L, Chinthapalli, K, Chou, I-J, Chung, S-K, Churchhouse, C, Clark, PO, Cole, AJ, Compston, A, Coppola, A, Cosico, M, Cossette, P, Craig, JJ, Cusick, C, Daly, MJ, Davis, LK, de Haan, G-J, Delanty, N, Depondt, C, Derambure, P, Devinsky, O, Di Vito, L, Dlugos, DJ, Doccini, V, Doherty, CP, El-Naggar, H, Elger, CE, Ellis, CA, Eriksson, JG, Faucon, A, Feng, Y-CA, Ferguson, L, Ferraro, TN, Ferri, L, Feucht, M, Fitzgerald, M, Fonferko-Shadrach, B, Fortunato, F, Franceschetti, S, Franke, A, French, JA, Freri, E, Gagliardi, M, Gambardella, A, Geller, EB, Giangregorio, T, Gjerstad, L, Glauser, T, Goldberg, E, Goldman, A, Granata, T, Greenberg, DA, Guerrini, R, Gupta, N, Haas, KF, Hakonarson, H, Hallmann, K, Hassanin, E, Hegde, M, Heinzen, EL, Helbig, I, Hengsbach, C, Heyne, HO, Hirose, S, Hirsch, E, Hjalgrim, H, Howrigan, DP, Hucks, D, Hung, P-C, Iacomino, M, Imbach, LL, Inoue, Y, Ishii, A, Jamnadas-Khoda, J, Jehi, L, Johnson, MR, Kalviainen, R, Kamatani, Y, Kanaan, M, Kanai, M, Kantanen, A-M, Kara, B, Kariuki, SM, Kasperaviciute, D, Trenite, DK-N, Kato, M, Kegele, J, Kesim, Y, Khoueiry-Zgheib, N, King, C, Kirsch, HE, Klein, KM, Kluger, G, Knake, S, Knowlton, RC, Koeleman, BPC, Korczyn, AD, Koupparis, A, Kousiappa, I, Krause, R, Krenn, M, Krestel, H, Krey, I, Kunz, WS, Kurki, MI, Kurlemann, G, Kuzniecky, R, Kwan, P, Labate, A, Lacey, A, Lal, D, Landoulsi, Z, Lau, Y-L, Lauxmann, S, Leech, SL, Lehesjoki, A-E, Lemke, JR, Lerche, H, Lesca, G, Leu, C, Lewin, N, Lewis-Smith, D, Li, GH-Y, Li, QS, Licchetta, L, Lin, K-L, Lindhout, D, Linnankivi, T, Lopes-Cendes, I, Lowenstein, DH, Lui, CHT, Madia, F, Magnusson, S, Marson, AG, May, P, McGraw, CM, Mei, D, Mills, JL, Minardi, R, Mirza, N, Moller, RS, Molloy, AM, Montomoli, M, Mostacci, B, Muccioli, L, Muhle, H, Mueller-Schlueter, K, Najm, IM, Nasreddine, W, Neale, BM, Neubauer, B, Newton, CRJC, Noethen, MM, Nothnagel, M, Nuernberg, P, O'Brien, TJ, Okada, Y, Olafsson, E, Oliver, KL, Ozkara, C, Palotie, A, Pangilinan, F, Papacostas, SS, Parrini, E, Pato, CN, Pato, MT, Pendziwiat, M, Petrovski, S, Pickrell, WO, Pinsky, R, Pippucci, T, Poduri, A, Pondrelli, F, Powell, RHW, Privitera, M, Rademacher, A, Radtke, R, Ragona, F, Rau, S, Rees, MI, Regan, BM, Reif, PS, Rhelms, S, Riva, A, Rosenow, F, Ryvlin, P, Saarela, A, Sadleir, LG, Sander, JW, Sander, T, Scala, M, Scattergood, T, Schachter, SC, Schankin, CJ, Scheffer, IE, Schmitz, B, Schoch, S, Schubert-Bast, S, Schulze-Bonhage, A, Scudieri, P, Sham, P, Sheidley, BR, Shih, JJ, Sills, GJ, Sisodiya, SM, Smith, MC, Smith, PE, Sonsma, ACM, Speed, D, Sperling, MR, Stefansson, H, Stefansson, K, Steinhoff, BJ, Stephani, U, Stewart, WC, Stipa, C, Striano, P, Stroink, H, Strzelczyk, A, Surges, R, Suzuki, T, Tan, KM, Taneja, RS, Tanteles, GA, Tauboll, E, Thio, LL, Thomas, GN, Thomas, RH, Timonen, O, Tinuper, P, Todaro, M, Topaloglu, P, Tozzi, R, Tsai, M-H, Tumiene, B, Turkdogan, D, Unnsteinsdottir, U, Utkus, A, Vaidiswaran, P, Valton, L, van Baalen, A, Vetro, A, Vining, EPG, Visscher, F, von Brauchitsch, S, von Wrede, R, Wagner, RG, Weber, YG, Weckhuysen, S, Weisenberg, J, Weller, M, Widdess-Walsh, P, Wolff, M, Wolking, S, Wu, D, Yamakawa, K, Yang, W, Yapici, Z, Yucesan, E, Zagaglia, S, Zahnert, F, Zara, F, Zhou, W, Zimprich, F, Zsurka, G, and Ali, QZ
Abstract: Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment.
Published: 2023

10. POLR1A variants underlie phenotypic heterogeneity in craniofacial, neural, and cardiac anomalies.

Author: Smallwood, K, Watt, KEN, Ide, S, Baltrunaite, K, Brunswick, C, Inskeep, K, Capannari, C, Adam, MP, Begtrup, A, Bertola, DR, Demmer, L, Demo, E, Devinsky, O, Gallagher, ER, Guillen Sacoto, MJ, Jech, R, Keren, B, Kussmann, J, Ladda, R, Lansdon, LA, Lunke, S, Mardy, A, McWalters, K, Person, R, Raiti, L, Saitoh, N, Saunders, CJ, Schnur, R, Skorvanek, M, Sell, SL, Slavotinek, A, Sullivan, BR, Stark, Z, Symonds, JD, Wenger, T, Weber, S, Whalen, S, White, SM, Winkelmann, J, Zech, M, Zeidler, S, Maeshima, K, Stottmann, RW, Trainor, PA, Weaver, KN, Smallwood, K, Watt, KEN, Ide, S, Baltrunaite, K, Brunswick, C, Inskeep, K, Capannari, C, Adam, MP, Begtrup, A, Bertola, DR, Demmer, L, Demo, E, Devinsky, O, Gallagher, ER, Guillen Sacoto, MJ, Jech, R, Keren, B, Kussmann, J, Ladda, R, Lansdon, LA, Lunke, S, Mardy, A, McWalters, K, Person, R, Raiti, L, Saitoh, N, Saunders, CJ, Schnur, R, Skorvanek, M, Sell, SL, Slavotinek, A, Sullivan, BR, Stark, Z, Symonds, JD, Wenger, T, Weber, S, Whalen, S, White, SM, Winkelmann, J, Zech, M, Zeidler, S, Maeshima, K, Stottmann, RW, Trainor, PA, and Weaver, KN
Abstract: Heterozygous pathogenic variants in POLR1A, which encodes the largest subunit of RNA Polymerase I, were previously identified as the cause of acrofacial dysostosis, Cincinnati-type. The predominant phenotypes observed in the cohort of 3 individuals were craniofacial anomalies reminiscent of Treacher Collins syndrome. We subsequently identified 17 additional individuals with 12 unique heterozygous variants in POLR1A and observed numerous additional phenotypes including neurodevelopmental abnormalities and structural cardiac defects, in combination with highly prevalent craniofacial anomalies and variable limb defects. To understand the pathogenesis of this pleiotropy, we modeled an allelic series of POLR1A variants in vitro and in vivo. In vitro assessments demonstrate variable effects of individual pathogenic variants on ribosomal RNA synthesis and nucleolar morphology, which supports the possibility of variant-specific phenotypic effects in affected individuals. To further explore variant-specific effects in vivo, we used CRISPR-Cas9 gene editing to recapitulate two human variants in mice. Additionally, spatiotemporal requirements for Polr1a in developmental lineages contributing to congenital anomalies in affected individuals were examined via conditional mutagenesis in neural crest cells (face and heart), the second heart field (cardiac outflow tract and right ventricle), and forebrain precursors in mice. Consistent with its ubiquitous role in the essential function of ribosome biogenesis, we observed that loss of Polr1a in any of these lineages causes cell-autonomous apoptosis resulting in embryonic malformations. Altogether, our work greatly expands the phenotype of human POLR1A-related disorders and demonstrates variant-specific effects that provide insights into the underlying pathogenesis of ribosomopathies.
Published: 2023

11. Rare Genetic Variation and Outcome of Surgery for Mesial Temporal Lobe Epilepsy

Author: Perucca, P, Stanley, K, Harris, N, McIntosh, AM, Asadi-Pooya, AA, Mikati, MA, Andrade, DM, Dugan, P, Depondt, C, Choi, H, Heinzen, EL, Cavalleri, GL, Buono, RJ, Devinsky, O, Sperling, MR, Berkovic, SF, Delanty, N, Goldstein, DB, O'Brien, TJ, Perucca, P, Stanley, K, Harris, N, McIntosh, AM, Asadi-Pooya, AA, Mikati, MA, Andrade, DM, Dugan, P, Depondt, C, Choi, H, Heinzen, EL, Cavalleri, GL, Buono, RJ, Devinsky, O, Sperling, MR, Berkovic, SF, Delanty, N, Goldstein, DB, and O'Brien, TJ
Abstract: OBJECTIVE: Genetic factors have long been debated as a cause of failure of surgery for mesial temporal lobe epilepsy (MTLE). We investigated whether rare genetic variation influences seizure outcomes of MTLE surgery. METHODS: We performed an international, multicenter, whole exome sequencing study of patients who underwent surgery for drug-resistant, unilateral MTLE with normal magnetic resonance imaging (MRI) or MRI evidence of hippocampal sclerosis and ≥2-year postsurgical follow-up. Patients with either sustained seizure freedom (favorable outcome) or ongoing uncontrolled seizures since surgery (unfavorable outcome) were included. Exomes of controls without epilepsy were also included. Gene set burden analyses were carried out to identify genes with significant enrichment of rare deleterious variants in patients compared to controls. RESULTS: Nine centers from 3 continents contributed 206 patients operated for drug-resistant unilateral MTLE, of whom 196 (149 with favorable outcome and 47 with unfavorable outcome) were included after stringent quality control. Compared to 8,718 controls, MTLE cases carried a higher burden of ultrarare missense variants in constrained genes that are intolerant to loss-of-function (LoF) variants (odds ratio [OR] = 2.6, 95% confidence interval [CI] = 1.9-3.5, p = 1.3E-09) and in genes encoding voltage-gated cation channels (OR = 2.4, 95% CI = 1.4-3.8, p = 2.7E-04). Proportions of subjects with such variants were comparable between patients with favorable outcome and those with unfavorable outcome, with no significant between-group differences. INTERPRETATION: Rare variation contributes to the genetic architecture of MTLE, but does not appear to have a major role in failure of MTLE surgery. These findings can be incorporated into presurgical decision-making and counseling. ANN NEUROL 2022.
Published: 2023

12. Risk of sudden unexpected death in epilepsy (SUDEP) with lamotrigine and other sodium channel-modulating antiseizure medications

Author: Nightscales, R, Barnard, S, Laze, J, Chen, Z, Tao, G, Auvrez, C, Sivathamboo, S, Cook, MJ, Kwan, P, Friedman, D, Berkovic, SF, D'Souza, W, Perucca, P, Devinsky, O, O'Brien, TJ, Nightscales, R, Barnard, S, Laze, J, Chen, Z, Tao, G, Auvrez, C, Sivathamboo, S, Cook, MJ, Kwan, P, Friedman, D, Berkovic, SF, D'Souza, W, Perucca, P, Devinsky, O, and O'Brien, TJ
Abstract: OBJECTIVE: In vitro data prompted U.S Food and Drug Administration warnings that lamotrigine, a common sodium channel modulating anti-seizure medication (NaM-ASM), could increase the risk of sudden death in patients with structural or ischaemic cardiac disease, however, its implications for Sudden Unexpected Death in Epilepsy (SUDEP) are unclear. METHODS: This retrospective, nested case-control study identified 101 sudden unexpected death in epilepsy (SUDEP) cases and 199 living epilepsy controls from Epilepsy Monitoring Units (EMUs) in Australia and the USA. Differences in proportions of lamotrigine and NaM-ASM use were compared between cases and controls at the time of admission, and survival analyses from the time of admission up to 16 years were conducted. Multivariable logistic regression and survival analyses compared each ASM subgroup adjusting for SUDEP risk factors. RESULTS: Proportions of cases and controls prescribed lamotrigine (P = 0.166), one NaM-ASM (P = 0.80), or ≥2NaM-ASMs (P = 0.447) at EMU admission were not significantly different. Patients taking lamotrigine (adjusted hazard ratio [aHR] = 0.56; P = 0.054), one NaM-ASM (aHR = 0.8; P = 0.588) or ≥2 NaM-ASMs (aHR = 0.49; P = 0.139) at EMU admission were not at increased SUDEP risk up to 16 years following admission. Active tonic-clonic seizures at EMU admission associated with >2-fold SUDEP risk, irrespective of lamotrigine (aHR = 2.24; P = 0.031) or NaM-ASM use (aHR = 2.25; P = 0.029). Sensitivity analyses accounting for incomplete ASM data at follow-up suggest undetected changes to ASM use are unlikely to alter our results. SIGNIFICANCE: This study provides additional evidence that lamotrigine and other NaM-ASMs are unlikely to be associated with an increased long-term risk of SUDEP, up to 16 years post-EMU admission.
Published: 2023

13. Effect of Fenfluramine on Generalized Tonic–Clonic Seizures in Rare Epilepsy Syndromes: A Review of Published Studies.

Author: Cross, J. H., Devinsky, O., Gil-Nagel, A., Ceulemans, B., Lagae, L., Schoonjans, A.-S., Ryvlin, P., Nabbout, R., Haas, S., Lothe, A., and Polega, S.
Subjects: *EPILEPSY, *SEIZURES (Medicine), *FENFLURAMINE, *SYNDROMES, *PEOPLE with epilepsy, *SUDDEN death
Abstract: This article, published in Neuropediatrics, reviews the effectiveness of fenfluramine (FFA) in treating generalized tonic-clonic seizures (GTCS) or tonic-clonic seizures (TCS) in patients with rare epilepsy syndromes. The study included data from 13 studies, including randomized-controlled trials, observational studies, open-label studies, and a case series. The results showed that FFA led to a clinically significant reduction in GTCS or TCS frequency in patients with rare epilepsy syndromes. However, further research is needed to determine the impact of FFA on sudden unexpected death in epilepsy (SUDEP) in these patient populations. [Extracted from the article]
Published: 2023
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14. Impact of the COVID-19 pandemic on people with epilepsy: findings from the US arm of the COV-E study

Author: Dugan, P, Carroll, E, Thorpe, J, Jette, N, Agarwal, P, Ashby, S, Hanna, J, French, J, Devinsky, O, Sen, A, and Group, COVID-19 Epilepsy COV-E Study
Subjects: Neurology, Neurology (clinical)
Abstract: Objectives As part of the COVID-19 and Epilepsy (COV-E) global study, we aimed to understand the impact of COVID-19 on the medical care and well-being of people with epilepsy (PWE) in the United States, based on their perspectives and those of their caregivers. Methods Separate surveys designed for PWE and their caregivers were circulated from April 2020 to July 2021; modifications in March 2021 included a question about COVID-19 vaccination status. Results We received 788 responses, 71% from PWE (n = 559) and 29% (n = 229) from caregivers of persons with epilepsy. A third (n = 308) of respondents reported a change in their health or in the health of the person they care for. Twenty-seven percent (n = 210) reported issues related to worsening mental health. Of respondents taking ASMs (n = 769), 10% (n = 78) reported difficulty taking medications on time, mostly due to stress causing forgetfulness. Less than half of respondents received counseling on mental health and stress. Less than half of the PWE reported having discussions with their healthcare providers about sleep, ASMs, and potential side effects, while a larger proportion of caregivers (81%) reported having had discussions with their healthcare providers on the same topics. More PWE and caregivers reported that COVID-19-related measures caused adverse impact on their health in the post-vaccine period than during the pre-vaccine period, citing mental health issues as the primary reason. Significance Our findings indicate that the impact of the COVID-19 pandemic in the US on PWE is multifaceted. Apart from the increased risk of poor COVID-19 outcomes, the pandemic has also had negative effects on mental health and self-management. Healthcare providers must be vigilant for increased emotional distress in PWE during the pandemic and consider the importance of effective counseling to diminish risks related to exacerbated treatment gaps.
Published: 2023
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15. Immunoreactivity of muscarinic acetylcholine M2 and serotonin 5-HT2B receptors, norepinephrine transporter and kir channels in a model of epilepsy

Author: Akyuz, E, Doganyigit, Z, Paudel, Y, Koklu, B, Kaymak, E, Villa, C, Arulsamy, A, Shaikh, M, Devinsky, O, Akyuz E., Doganyigit Z., Paudel Y. N., Koklu B., Kaymak E., Villa C., Arulsamy A., Shaikh M. F., Devinsky O., Akyuz, E, Doganyigit, Z, Paudel, Y, Koklu, B, Kaymak, E, Villa, C, Arulsamy, A, Shaikh, M, Devinsky, O, Akyuz E., Doganyigit Z., Paudel Y. N., Koklu B., Kaymak E., Villa C., Arulsamy A., Shaikh M. F., and Devinsky O.
Abstract: Epilepsy is characterized by an imbalance in neurotransmitter activity; an increased excitatory to an inhibitory activity. Acetylcholine (ACh), serotonin, and norepinephrine (NE) may modulate neural activity via several mechanisms, mainly through its receptors/transporter activity and alterations in the extracellular potassium (K+) concentration via K+ ion channels. Seizures may disrupt the regulation of inwardly rectifying K+ (Kir) channels and alter the receptor/transporter activity. However, there are limited data present on the immunoreactivity pattern of these neurotransmitter receptors/transporters and K+ channels in chronic models of epilepsy, which therefore was the aim of this study. Changes in the immunoreactivity of epileptogenesis-related neurotransmitter receptors/transporters (M2, 5-HT2B, and NE transporter) as well as Kir channels (Kir3.1 and Kir6.2) were determined in the cortex, hippocampus and medulla of adultWistar rats by utilizing a Pentylenetetrazol (PTZ)-kindling chronic epilepsy model. Increased immunoreactivity of the NE transporter, M2, and 5-HT2B receptors was witnessed in the cortex and medulla. While the immunoreactivity of the 5-HT2B receptor was found increased in the cortex and medulla, it was decreased in the hippocampus, with no changes observed in the M2 receptor in this region. Kir3.1 and Kir6.2 staining showed increase immunoreactivity in the cerebral cortex, but channel contrasting findings in the hippocampus and medulla. Our results suggest that seizure kindling may result in significant changes in the neurotransmitter system which may contribute or propagate to future epileptogenesis, brain damage and potentially towards sudden unexpected death in epilepsy (SUDEP). Further studies on the pathogenic role of these changes in neurotransmitter receptors/transporters and K+ channel immunoreactivity may identify newer possible targets to treat seizures or prevent epilepsy-related comorbidities.
Published: 2021

16. Review: The past, present and future challenges in epilepsy‐related and sudden deaths and biobanking

Author: Thom, M., Boldrini, M., Bundock, E., Sheppard, M. N., and Devinsky, O.
Published: 2018
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17. Association of ultra-rare coding variants with genetic generalized epilepsy: A case–control whole exome sequencing study

Author: Koko, M, Motelow, JE, Stanley, KE, Bobbili, DR, Dhindsa, RS, May, P, Alldredge, BK, Allen, AS, Altmüller, J, Amrom, D, Andermann, E, Auce, P, Avbersek, A, Baulac, S, Bautista, JF, Becker, F, Bellows, Susannah, Berghuis, B, Berkovic, SF, Bluvstein, J, Boro, A, Bridgers, J, Burgess, R, Caglayan, H, Cascino, GD, Cavalleri, GL, Chung, SK, Cieuta-Walti, C, Cloutier, V, Consalvo, D, Cossette, P, Crumrine, P, Delanty, N, Depondt, C, Desbiens, R, Devinsky, O, Dlugos, D, Epstein, MP, Everett, K, Fiol, M, Fountain, NB, Francis, B, French, J, Freyer, C, Friedman, D, Gambardella, A, Geller, EB, Girard, S, Glauser, T, Glynn, S, Goldstein, DB, Gravel, M, Haas, K, Haut, SR, Heinzen, EL, Helbig, I, Hildebrand, MS, Johnson, MR, Jorgensen, A, Joshi, S, Kanner, A, Kirsch, HE, Klein, KM, Knowlton, RC, Koeleman, BPC, Kossoff, EH, Krause, R, Krenn, M, Kunz, WS, Kuzniecky, R, Langley, SR, LeGuern, E, Lehesjoki, AE, Lerche, H, Leu, C, Lortie, A, Lowenstein, DH, Marson, AG, Mebane, C, Mefford, HC, Meloche, C, Moreau, C, Motika, PV, Muhle, H, Møller, RS, Nabbout, R, Nguyen, DK, Nikanorova, M, Novotny, EJ, Nürnberg, P, Ottman, R, O’Brien, TJ, Paolicchi, JM, Parent, JM, Park, K, Peter, S, Petrou, S, Petrovski, S, Pickrell, WO, Poduri, A, Koko, M, Motelow, JE, Stanley, KE, Bobbili, DR, Dhindsa, RS, May, P, Alldredge, BK, Allen, AS, Altmüller, J, Amrom, D, Andermann, E, Auce, P, Avbersek, A, Baulac, S, Bautista, JF, Becker, F, Bellows, Susannah, Berghuis, B, Berkovic, SF, Bluvstein, J, Boro, A, Bridgers, J, Burgess, R, Caglayan, H, Cascino, GD, Cavalleri, GL, Chung, SK, Cieuta-Walti, C, Cloutier, V, Consalvo, D, Cossette, P, Crumrine, P, Delanty, N, Depondt, C, Desbiens, R, Devinsky, O, Dlugos, D, Epstein, MP, Everett, K, Fiol, M, Fountain, NB, Francis, B, French, J, Freyer, C, Friedman, D, Gambardella, A, Geller, EB, Girard, S, Glauser, T, Glynn, S, Goldstein, DB, Gravel, M, Haas, K, Haut, SR, Heinzen, EL, Helbig, I, Hildebrand, MS, Johnson, MR, Jorgensen, A, Joshi, S, Kanner, A, Kirsch, HE, Klein, KM, Knowlton, RC, Koeleman, BPC, Kossoff, EH, Krause, R, Krenn, M, Kunz, WS, Kuzniecky, R, Langley, SR, LeGuern, E, Lehesjoki, AE, Lerche, H, Leu, C, Lortie, A, Lowenstein, DH, Marson, AG, Mebane, C, Mefford, HC, Meloche, C, Moreau, C, Motika, PV, Muhle, H, Møller, RS, Nabbout, R, Nguyen, DK, Nikanorova, M, Novotny, EJ, Nürnberg, P, Ottman, R, O’Brien, TJ, Paolicchi, JM, Parent, JM, Park, K, Peter, S, Petrou, S, Petrovski, S, Pickrell, WO, and Poduri, A
Published: 2022

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

Author: Park, B.-y., Larivière, S., Rodríguez-Cruces, R., Royer, J., Tavakol, S., Wang, Y., Caciagli, L., Caligiuri, M.E., Gambardella, A., Concha, L., Keller, S.S., Cendes, F., Alvim, M.K.M., Yasuda, C., Bonilha, L., Gleichgerrcht, E., Focke, N.K., Kreilkamp, B.A.K., Domin, M., Podewils, F. von, Langner, S., Rummel, C., Rebsamen, M., Wiest, R., Martin, P., Kotikalapudi, R., Bender, B., O’Brien, T.J., Law, M., Sinclair, B., Vivash, L., Kwan, P., Desmond, P.M., Malpas, C.B., Lui, E., Alhusaini, S., Doherty, C.P., Cavalleri, G.L., Delanty, N., Kälviäinen, R., Jackson, G.D., Kowalczyk, M., Mascalchi, M., Semmelroch, M., Thomas, R.H., Soltanian-Zadeh, H., Davoodi-Bojd, E., Zhang, J., Lenge, M., Guerrini, R., Bartolini, E., Hamandi, K., Foley, S., Weber, B., Depondt, C., Absil, J., Carr, S.J.A., Abela, E., Richardson, M.P., Devinsky, O., Severino, M., Striano, P., Parodi, C., Tortora, D., Hatton, S.N., Vos, S.B., Duncan, J.S., Galovic, M., Whelan, C.D., Bargalló, N., Pariente, J., Conde-Blanco, E., Vaudano, A.E., Tondelli, M., Meletti, S., Kong, X.Z., Francks, C., Fisher, S.E., Caldairou, B., Ryten, M., Labate, A., Sisodiya, S.M., Thompson, P.M., McDonald, C.R., Bernasconi, A., Bernasconi, N., Bernhardt, B.C., Park, B.-y., Larivière, S., Rodríguez-Cruces, R., Royer, J., Tavakol, S., Wang, Y., Caciagli, L., Caligiuri, M.E., Gambardella, A., Concha, L., Keller, S.S., Cendes, F., Alvim, M.K.M., Yasuda, C., Bonilha, L., Gleichgerrcht, E., Focke, N.K., Kreilkamp, B.A.K., Domin, M., Podewils, F. von, Langner, S., Rummel, C., Rebsamen, M., Wiest, R., Martin, P., Kotikalapudi, R., Bender, B., O’Brien, T.J., Law, M., Sinclair, B., Vivash, L., Kwan, P., Desmond, P.M., Malpas, C.B., Lui, E., Alhusaini, S., Doherty, C.P., Cavalleri, G.L., Delanty, N., Kälviäinen, R., Jackson, G.D., Kowalczyk, M., Mascalchi, M., Semmelroch, M., Thomas, R.H., Soltanian-Zadeh, H., Davoodi-Bojd, E., Zhang, J., Lenge, M., Guerrini, R., Bartolini, E., Hamandi, K., Foley, S., Weber, B., Depondt, C., Absil, J., Carr, S.J.A., Abela, E., Richardson, M.P., Devinsky, O., Severino, M., Striano, P., Parodi, C., Tortora, D., Hatton, S.N., Vos, S.B., Duncan, J.S., Galovic, M., Whelan, C.D., Bargalló, N., Pariente, J., Conde-Blanco, E., Vaudano, A.E., Tondelli, M., Meletti, S., Kong, X.Z., Francks, C., Fisher, S.E., Caldairou, B., Ryten, M., Labate, A., Sisodiya, S.M., Thompson, P.M., McDonald, C.R., Bernasconi, A., Bernasconi, N., and Bernhardt, B.C.
Abstract: Contains fulltext : 252489.pdf (Publisher’s version ) (Open Access)
Published: 2022

19. Interictal EEG and ECG for SUDEP Risk Assessment: A Retrospective Multicenter Cohort Study

Author: Chen, ZS, Hsieh, A, Sun, G, Bergey, GK, Berkovic, SF, Perucca, P, D'Souza, W, Elder, CJ, Farooque, P, Johnson, EL, Barnard, S, Nightscales, R, Kwan, P, Moseley, B, O'Brien, TJ, Sivathamboo, S, Laze, J, Friedman, D, Devinsky, O, Chen, ZS, Hsieh, A, Sun, G, Bergey, GK, Berkovic, SF, Perucca, P, D'Souza, W, Elder, CJ, Farooque, P, Johnson, EL, Barnard, S, Nightscales, R, Kwan, P, Moseley, B, O'Brien, TJ, Sivathamboo, S, Laze, J, Friedman, D, and Devinsky, O
Abstract: OBJECTIVE: Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality. Although lots of effort has been made in identifying clinical risk factors for SUDEP in the literature, there are few validated methods to predict individual SUDEP risk. Prolonged postictal EEG suppression (PGES) is a potential SUDEP biomarker, but its occurrence is infrequent and requires epilepsy monitoring unit admission. We use machine learning methods to examine SUDEP risk using interictal EEG and ECG recordings from SUDEP cases and matched living epilepsy controls. METHODS: This multicenter, retrospective, cohort study examined interictal EEG and ECG recordings from 30 SUDEP cases and 58 age-matched living epilepsy patient controls. We trained machine learning models with interictal EEG and ECG features to predict the retrospective SUDEP risk for each patient. We assessed cross-validated classification accuracy and the area under the receiver operating characteristic (AUC) curve. RESULTS: The logistic regression (LR) classifier produced the overall best performance, outperforming the support vector machine (SVM), random forest (RF), and convolutional neural network (CNN). Among the 30 patients with SUDEP [14 females; mean age (SD), 31 (8.47) years] and 58 living epilepsy controls [26 females (43%); mean age (SD) 31 (8.5) years], the LR model achieved the median AUC of 0.77 [interquartile range (IQR), 0.73-0.80] in five-fold cross-validation using interictal alpha and low gamma power ratio of the EEG and heart rate variability (HRV) features extracted from the ECG. The LR model achieved the mean AUC of 0.79 in leave-one-center-out prediction. CONCLUSIONS: Our results support that machine learning-driven models may quantify SUDEP risk for epilepsy patients, future refinements in our model may help predict individualized SUDEP risk and help clinicians correlate predictive scores with the clinical data. Low-cost and noninvasive interictal biomarkers of SUDEP
Published: 2022

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

Author: Park, B-Y, Lariviere, S, Rodriguez-Cruces, R, Royer, J, Tavakol, S, Wang, Y, Caciagli, L, Caligiuri, ME, Gambardella, A, Concha, L, Keller, SS, Cendes, F, Alvim, MKM, Yasuda, C, Bonilha, L, Gleichgerrcht, E, Focke, NK, Kreilkamp, BAK, Domin, M, von Podewils, F, Langner, S, Rummel, C, Rebsamen, M, Wiest, R, Martin, P, Kotikalapudi, R, Bender, B, O'Brien, TJ, Law, M, Sinclair, B, Vivash, L, Kwan, P, Desmond, PM, Malpas, CB, Lui, E, Alhusaini, S, Doherty, CP, Cavalleri, GL, Delanty, N, Kalviainen, R, Jackson, GD, Kowalczyk, M, Mascalchi, M, Semmelroch, M, Thomas, RH, Soltanian-Zadeh, H, Davoodi-Bojd, E, Zhang, J, Lenge, M, Guerrini, R, Bartolini, E, Hamandi, K, Foley, S, Weber, B, Depondt, C, Absil, J, Carr, SJA, Abela, E, Richardson, MP, Devinsky, O, Severino, M, Striano, P, Parodi, C, Tortora, D, Hatton, SN, Vos, SB, Duncan, JS, Galovic, M, Whelan, CD, Bargallo, N, Pariente, J, Conde-Blanco, E, Vaudano, AE, Tondelli, M, Meletti, S, Kong, X-Z, Francks, C, Fisher, SE, Caldairou, B, Ryten, M, Labate, A, Sisodiya, SM, Thompson, PM, McDonald, CR, Bernasconi, A, Bernasconi, N, Bernhardt, BC, Park, B-Y, Lariviere, S, Rodriguez-Cruces, R, Royer, J, Tavakol, S, Wang, Y, Caciagli, L, Caligiuri, ME, Gambardella, A, Concha, L, Keller, SS, Cendes, F, Alvim, MKM, Yasuda, C, Bonilha, L, Gleichgerrcht, E, Focke, NK, Kreilkamp, BAK, Domin, M, von Podewils, F, Langner, S, Rummel, C, Rebsamen, M, Wiest, R, Martin, P, Kotikalapudi, R, Bender, B, O'Brien, TJ, Law, M, Sinclair, B, Vivash, L, Kwan, P, Desmond, PM, Malpas, CB, Lui, E, Alhusaini, S, Doherty, CP, Cavalleri, GL, Delanty, N, Kalviainen, R, Jackson, GD, Kowalczyk, M, Mascalchi, M, Semmelroch, M, Thomas, RH, Soltanian-Zadeh, H, Davoodi-Bojd, E, Zhang, J, Lenge, M, Guerrini, R, Bartolini, E, Hamandi, K, Foley, S, Weber, B, Depondt, C, Absil, J, Carr, SJA, Abela, E, Richardson, MP, Devinsky, O, Severino, M, Striano, P, Parodi, C, Tortora, D, Hatton, SN, Vos, SB, Duncan, JS, Galovic, M, Whelan, CD, Bargallo, N, Pariente, J, Conde-Blanco, E, Vaudano, AE, Tondelli, M, Meletti, S, Kong, X-Z, Francks, C, Fisher, SE, Caldairou, B, Ryten, M, Labate, A, Sisodiya, SM, Thompson, PM, McDonald, CR, Bernasconi, A, Bernasconi, N, and Bernhardt, BC
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 ou
Published: 2022

21. A systems-level analysis highlights microglial activation as a modifying factor in common epilepsies

Author: Altmann, A, Ryten, M, Di Nunzio, M, Ravizza, T, Tolomeo, D, Reynolds, RH, Somani, A, Bacigaluppi, M, Iori, V, Micotti, E, Di Sapia, R, Cerovic, M, Palma, E, Ruffolo, G, Botia, JA, Absil, J, Alhusaini, S, Alvim, MKM, Auvinen, P, Bargallo, N, Bartolini, E, Bender, B, Bergo, FPG, Bernardes, T, Bernasconi, A, Bernasconi, N, Bernhardt, BC, Blackmon, K, Braga, B, Caligiuri, ME, Calvo, A, Carlson, C, Carr, SJA, Cavalleri, GL, Cendes, F, Chen, J, Chen, S, Cherubini, A, Concha, L, David, P, Delanty, N, Depondt, C, Devinsky, O, Doherty, CP, Domin, M, Focke, NK, Foley, S, Franca, W, Gambardella, A, Guerrini, R, Hamandi, K, Hibar, DP, Isaev, D, Jackson, GD, Jahanshad, N, Kalviainen, R, Keller, SS, Kochunov, P, Kotikalapudi, R, Kowalczyk, MA, Kuzniecky, R, Kwan, P, Labate, A, Langner, S, Lenge, M, Liu, M, Martin, P, Mascalchi, M, Meletti, S, Morita-Sherman, ME, O'Brien, TJ, Pariente, JC, Richardson, MP, Rodriguez-Cruces, R, Rummel, C, Saavalainen, T, Semmelroch, MK, Severino, M, Striano, P, Thesen, T, Thomas, RH, Tondelli, M, Tortora, D, Vaudano, AE, Vivash, L, Podewils, F, Wagner, J, Weber, B, Wiest, R, Yasuda, CL, Zhang, G, Zhang, J, Leu, C, Avbersek, A, Thom, M, Whelan, CD, Thompson, P, McDonald, CR, Vezzani, A, Sisodiya, SM, Altmann, A, Ryten, M, Di Nunzio, M, Ravizza, T, Tolomeo, D, Reynolds, RH, Somani, A, Bacigaluppi, M, Iori, V, Micotti, E, Di Sapia, R, Cerovic, M, Palma, E, Ruffolo, G, Botia, JA, Absil, J, Alhusaini, S, Alvim, MKM, Auvinen, P, Bargallo, N, Bartolini, E, Bender, B, Bergo, FPG, Bernardes, T, Bernasconi, A, Bernasconi, N, Bernhardt, BC, Blackmon, K, Braga, B, Caligiuri, ME, Calvo, A, Carlson, C, Carr, SJA, Cavalleri, GL, Cendes, F, Chen, J, Chen, S, Cherubini, A, Concha, L, David, P, Delanty, N, Depondt, C, Devinsky, O, Doherty, CP, Domin, M, Focke, NK, Foley, S, Franca, W, Gambardella, A, Guerrini, R, Hamandi, K, Hibar, DP, Isaev, D, Jackson, GD, Jahanshad, N, Kalviainen, R, Keller, SS, Kochunov, P, Kotikalapudi, R, Kowalczyk, MA, Kuzniecky, R, Kwan, P, Labate, A, Langner, S, Lenge, M, Liu, M, Martin, P, Mascalchi, M, Meletti, S, Morita-Sherman, ME, O'Brien, TJ, Pariente, JC, Richardson, MP, Rodriguez-Cruces, R, Rummel, C, Saavalainen, T, Semmelroch, MK, Severino, M, Striano, P, Thesen, T, Thomas, RH, Tondelli, M, Tortora, D, Vaudano, AE, Vivash, L, Podewils, F, Wagner, J, Weber, B, Wiest, R, Yasuda, CL, Zhang, G, Zhang, J, Leu, C, Avbersek, A, Thom, M, Whelan, CD, Thompson, P, McDonald, CR, Vezzani, A, and Sisodiya, SM
Abstract: AIMS: The causes of distinct patterns of reduced cortical thickness in the common human epilepsies, detectable on neuroimaging and with important clinical consequences, are unknown. We investigated the underlying mechanisms of cortical thinning using a systems-level analysis. METHODS: Imaging-based cortical structural maps from a large-scale epilepsy neuroimaging study were overlaid with highly spatially resolved human brain gene expression data from the Allen Human Brain Atlas. Cell-type deconvolution, differential expression analysis and cell-type enrichment analyses were used to identify differences in cell-type distribution. These differences were followed up in post-mortem brain tissue from humans with epilepsy using Iba1 immunolabelling. Furthermore, to investigate a causal effect in cortical thinning, cell-type-specific depletion was used in a murine model of acquired epilepsy. RESULTS: We identified elevated fractions of microglia and endothelial cells in regions of reduced cortical thickness. Differentially expressed genes showed enrichment for microglial markers and, in particular, activated microglial states. Analysis of post-mortem brain tissue from humans with epilepsy confirmed excess activated microglia. In the murine model, transient depletion of activated microglia during the early phase of the disease development prevented cortical thinning and neuronal cell loss in the temporal cortex. Although the development of chronic seizures was unaffected, the epileptic mice with early depletion of activated microglia did not develop deficits in a non-spatial memory test seen in epileptic mice not depleted of microglia. CONCLUSIONS: These convergent data strongly implicate activated microglia in cortical thinning, representing a new dimension for concern and disease modification in the epilepsies, potentially distinct from seizure control.
Published: 2022

22. Genomic analysis of 'microphenotypes' in epilepsy

Author: Stanley, K, Hostyk, J, Tran, L, Amengual-Gual, M, Dugan, P, Clark, J, Choi, H, Tchapyjnikov, D, Perucca, P, Fernandes, C, Andrade, D, Devinsky, O, Cavalleri, GL, Depondt, C, Sen, A, O'Brien, T, Heinzen, E, Loddenkemper, T, Goldstein, DB, Mikati, MA, Delanty, N, Stanley, K, Hostyk, J, Tran, L, Amengual-Gual, M, Dugan, P, Clark, J, Choi, H, Tchapyjnikov, D, Perucca, P, Fernandes, C, Andrade, D, Devinsky, O, Cavalleri, GL, Depondt, C, Sen, A, O'Brien, T, Heinzen, E, Loddenkemper, T, Goldstein, DB, Mikati, MA, and Delanty, N
Abstract: Large international consortia examining the genomic architecture of the epilepsies focus on large diagnostic subgroupings such as "all focal epilepsy" and "all genetic generalized epilepsy". In addition, phenotypic data are generally entered into these large discovery databases in a unidirectional manner at one point in time only. However, there are many smaller phenotypic subgroupings in epilepsy, many of which may have unique genomic risk factors. Such a subgrouping or "microphenotype" may be defined as an uncommon or rare phenotype that is well recognized by epileptologists and the epilepsy community, and which may or may not be formally recognized within the International League Against Epilepsy classification system. Here we examine the genetic structure of a number of such microphenotypes and report in particular on two interesting clinical phenotypes, Jeavons syndrome and pediatric status epilepticus. Although no single gene reached exome-wide statistical significance to be associated with any of the diagnostic categories, we observe enrichment of rare damaging variants in established epilepsy genes among Landau-Kleffner patients (GRIN2A) and pediatric status epilepticus patients (MECP2, SCN1A, SCN2A, SCN8A).
Published: 2022

23. KCNQ2 R144 variants cause neurodevelopmental disability with language impairment and autistic features without neonatal seizures through a gain-of-function mechanism

Author: Miceli, F., Millevert, C., Soldovieri, M.V., Mosca, I., Ambrosino, P., Carotenuto, L., Schrader, D., Lee, H.K., Riviello, J., Hong, W., Risen, S., Emrick, L., Amin, H., Ville, D. Van De, Edery, P., Bellescize, J. de, Michaud, V., Van-Gils, J., Goizet, C., Willemsen, M.H., Kleefstra, T., Møller, R.S., Bayat, A., Devinsky, O., Sands, T., Korenke, G.C., Kluger, G., Mefford, H.C., Brilstra, E., Lesca, G., Milh, M., Cooper, E.C., Taglialatela, M., Weckhuysen, S., Miceli, F., Millevert, C., Soldovieri, M.V., Mosca, I., Ambrosino, P., Carotenuto, L., Schrader, D., Lee, H.K., Riviello, J., Hong, W., Risen, S., Emrick, L., Amin, H., Ville, D. Van De, Edery, P., Bellescize, J. de, Michaud, V., Van-Gils, J., Goizet, C., Willemsen, M.H., Kleefstra, T., Møller, R.S., Bayat, A., Devinsky, O., Sands, T., Korenke, G.C., Kluger, G., Mefford, H.C., Brilstra, E., Lesca, G., Milh, M., Cooper, E.C., Taglialatela, M., and Weckhuysen, S.
Abstract: Contains fulltext : 284811.pdf (Publisher’s version ) (Open Access), BACKGROUND: Prior studies have revealed remarkable phenotypic heterogeneity in KCNQ2-related disorders, correlated with effects on biophysical features of heterologously expressed channels. Here, we assessed phenotypes and functional properties associated with KCNQ2 missense variants R144W, R144Q, and R144G. We also explored in vitro blockade of channels carrying R144Q mutant subunits by amitriptyline. METHODS: Patients were identified using the RIKEE database and through clinical collaborators. Phenotypes were collected by a standardized questionnaire. Functional and pharmacological properties of variant subunits were analyzed by whole-cell patch-clamp recordings. FINDINGS: Detailed clinical information on fifteen patients (14 novel and 1 previously published) was analyzed. All patients had developmental delay with prominent language impairment. R144Q patients were more severely affected than R144W patients. Infantile to childhood onset epilepsy occurred in 40%, while 67% of sleep-EEGs showed sleep-activated epileptiform activity. Ten patients (67%) showed autistic features. Activation gating of homomeric Kv7.2 R144W/Q/G channels was left-shifted, suggesting gain-of-function effects. Amitriptyline blocked channels containing Kv7.2 and Kv7.2 R144Q subunits. INTERPRETATION: Patients carrying KCNQ2 R144 gain-of-function variants have developmental delay with prominent language impairment, autistic features, often accompanied by infantile- to childhood-onset epilepsy and EEG sleep-activated epileptiform activity. The absence of neonatal seizures is a robust and important clinical differentiator between KCNQ2 gain-of-function and loss-of-function variants. The Kv7.2/7.3 channel blocker amitriptyline might represent a targeted treatment. FUNDING: Supported by FWO, GSKE, KCNQ2-Cure, Jack Pribaz Foundation, European Joint Programme on Rare Disease 2020, the Italian Ministry for University and Research, the Italian Ministry of Health, the European Commission, the University
Published: 2022

24. Heterogeneous nuclear ribonucleoprotein U (HNRNPU) safeguards the developing mouse cortex

Author: Sapir, T, Kshirsagar, A, Gorelik, A, Olender, T, Porat, Z, Scheffer, IE, Goldstein, DB, Devinsky, O, Reiner, O, Sapir, T, Kshirsagar, A, Gorelik, A, Olender, T, Porat, Z, Scheffer, IE, Goldstein, DB, Devinsky, O, and Reiner, O
Abstract: HNRNPU encodes the heterogeneous nuclear ribonucleoprotein U, which participates in RNA splicing and chromatin organization. Microdeletions in the 1q44 locus encompassing HNRNPU and other genes and point mutations in HNRNPU cause brain disorders, including early-onset seizures and severe intellectual disability. We aimed to understand HNRNPU's roles in the developing brain. Our work revealed that HNRNPU loss of function leads to rapid cell death of both postmitotic neurons and neural progenitors, with an apparent higher sensitivity of the latter. Further, expression and alternative splicing of multiple genes involved in cell survival, cell motility, and synapse formation are affected following Hnrnpu's conditional truncation. Finally, we identified pharmaceutical and genetic agents that can partially reverse the loss of cortical structures in Hnrnpu mutated embryonic brains, ameliorate radial neuronal migration defects and rescue cultured neural progenitors' cell death.
Published: 2022

25. Germline variants in tumor suppressor FBXW7 lead to impaired ubiquitination and a neurodevelopmental syndrome

Author: Stephenson, SEM, Costain, G, Blok, LER, Silk, MA, Nguyen, TB, Dong, X, Alhuzaimi, DE, Dowling, JJ, Walker, S, Amburgey, K, Hayeems, RZ, Rodan, LH, Schwartz, MA, Picker, J, Lynch, SA, Gupta, A, Rasmussen, KJ, Schimmenti, LA, Klee, EW, Niu, Z, Agre, KE, Chilton, I, Chung, WK, Revah-Politi, A, Au, PYB, Griffith, C, Racobaldo, M, Raas-Rothschild, A, Ben Zeev, B, Barel, O, Moutton, S, Morice-Picard, F, Carmignac, V, Cornaton, J, Marle, N, Devinsky, O, Stimach, C, Wechsler, SB, Hainline, BE, Sapp, K, Willems, M, Bruel, A, Dias, K-R, Evans, C-A, Roscioli, T, Sachdev, R, Temple, SEL, Zhu, Y, Baker, JJ, Scheffer, IE, Gardiner, FJ, Schneider, AL, Muir, AM, Mefford, HC, Crunk, A, Heise, EM, Millan, F, Monaghan, KG, Person, R, Rhodes, L, Richards, S, Wentzensen, IM, Cogne, B, Isidor, B, Nizon, M, Vincent, M, Besnard, T, Piton, A, Marcelis, C, Kato, K, Koyama, N, Ogi, T, Goh, ES-Y, Richmond, C, Amor, DJ, Boyce, JO, Morgan, AT, Hildebrand, MS, Kaspi, A, Bahlo, M, Fridriksdottir, R, Katrinardottir, H, Sulem, P, Stefansson, K, Bjornsson, HT, Mandelstam, S, Morleo, M, Mariani, M, Scala, M, Accogli, A, Torella, A, Capra, V, Wallis, M, Jansen, S, Waisfisz, Q, de Haan, H, Sadedin, S, Lim, SC, White, SM, Ascher, DB, Schenck, A, Lockhart, PJ, Christodoulou, J, Tan, TY, Stephenson, SEM, Costain, G, Blok, LER, Silk, MA, Nguyen, TB, Dong, X, Alhuzaimi, DE, Dowling, JJ, Walker, S, Amburgey, K, Hayeems, RZ, Rodan, LH, Schwartz, MA, Picker, J, Lynch, SA, Gupta, A, Rasmussen, KJ, Schimmenti, LA, Klee, EW, Niu, Z, Agre, KE, Chilton, I, Chung, WK, Revah-Politi, A, Au, PYB, Griffith, C, Racobaldo, M, Raas-Rothschild, A, Ben Zeev, B, Barel, O, Moutton, S, Morice-Picard, F, Carmignac, V, Cornaton, J, Marle, N, Devinsky, O, Stimach, C, Wechsler, SB, Hainline, BE, Sapp, K, Willems, M, Bruel, A, Dias, K-R, Evans, C-A, Roscioli, T, Sachdev, R, Temple, SEL, Zhu, Y, Baker, JJ, Scheffer, IE, Gardiner, FJ, Schneider, AL, Muir, AM, Mefford, HC, Crunk, A, Heise, EM, Millan, F, Monaghan, KG, Person, R, Rhodes, L, Richards, S, Wentzensen, IM, Cogne, B, Isidor, B, Nizon, M, Vincent, M, Besnard, T, Piton, A, Marcelis, C, Kato, K, Koyama, N, Ogi, T, Goh, ES-Y, Richmond, C, Amor, DJ, Boyce, JO, Morgan, AT, Hildebrand, MS, Kaspi, A, Bahlo, M, Fridriksdottir, R, Katrinardottir, H, Sulem, P, Stefansson, K, Bjornsson, HT, Mandelstam, S, Morleo, M, Mariani, M, Scala, M, Accogli, A, Torella, A, Capra, V, Wallis, M, Jansen, S, Waisfisz, Q, de Haan, H, Sadedin, S, Lim, SC, White, SM, Ascher, DB, Schenck, A, Lockhart, PJ, Christodoulou, J, and Tan, TY
Abstract: Neurodevelopmental disorders are highly heterogenous conditions resulting from abnormalities of brain architecture and/or function. FBXW7 (F-box and WD-repeat-domain-containing 7), a recognized developmental regulator and tumor suppressor, has been shown to regulate cell-cycle progression and cell growth and survival by targeting substrates including CYCLIN E1/2 and NOTCH for degradation via the ubiquitin proteasome system. We used a genotype-first approach and global data-sharing platforms to identify 35 individuals harboring de novo and inherited FBXW7 germline monoallelic chromosomal deletions and nonsense, frameshift, splice-site, and missense variants associated with a neurodevelopmental syndrome. The FBXW7 neurodevelopmental syndrome is distinguished by global developmental delay, borderline to severe intellectual disability, hypotonia, and gastrointestinal issues. Brain imaging detailed variable underlying structural abnormalities affecting the cerebellum, corpus collosum, and white matter. A crystal-structure model of FBXW7 predicted that missense variants were clustered at the substrate-binding surface of the WD40 domain and that these might reduce FBXW7 substrate binding affinity. Expression of recombinant FBXW7 missense variants in cultured cells demonstrated impaired CYCLIN E1 and CYCLIN E2 turnover. Pan-neuronal knockdown of the Drosophila ortholog, archipelago, impaired learning and neuronal function. Collectively, the data presented herein provide compelling evidence of an F-Box protein-related, phenotypically variable neurodevelopmental disorder associated with monoallelic variants in FBXW7.
Published: 2022

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

Author: Lariviere, S, Royer, J, Rodriguez-Cruces, R, Paquola, C, Caligiuri, ME, Gambardella, A, Concha, L, Keller, SS, Cendes, F, Yasuda, CL, Bonilha, L, Gleichgerrcht, E, Focke, NK, Domin, M, von Podewills, F, Langner, S, Rummel, C, Wiest, R, Martin, P, Kotikalapudi, R, O'Brien, TJ, Sinclair, B, Vivash, L, Desmond, PM, Lui, E, Vaudano, AE, Meletti, S, Tondelli, M, Alhusaini, S, Doherty, CP, Cavalleri, GL, Delanty, N, Kalviainen, R, Jackson, GD, Kowalczyk, M, Mascalchi, M, Semmelroch, M, Thomas, RH, Soltanian-Zadeh, H, Davoodi-Bojd, E, Zhang, J, Winston, GP, Griffin, A, Singh, A, Tiwari, VK, Kreilkamp, BAK, Lenge, M, Guerrini, R, Hamandi, K, Foley, S, Ruber, T, Weber, B, Depondt, C, Absil, J, Carr, SJA, Abela, E, Richardson, MP, Devinsky, O, Severino, M, Striano, P, Tortora, D, Kaestner, E, Hatton, SN, Vos, SB, Caciagli, L, Duncan, JS, Whelan, CD, Thompson, PM, Sisodiya, SM, Bernasconi, A, Labate, A, McDonald, CR, Bernasconi, N, Bernhardt, BC, Lariviere, S, Royer, J, Rodriguez-Cruces, R, Paquola, C, Caligiuri, ME, Gambardella, A, Concha, L, Keller, SS, Cendes, F, Yasuda, CL, Bonilha, L, Gleichgerrcht, E, Focke, NK, Domin, M, von Podewills, F, Langner, S, Rummel, C, Wiest, R, Martin, P, Kotikalapudi, R, O'Brien, TJ, Sinclair, B, Vivash, L, Desmond, PM, Lui, E, Vaudano, AE, Meletti, S, Tondelli, M, Alhusaini, S, Doherty, CP, Cavalleri, GL, Delanty, N, Kalviainen, R, Jackson, GD, Kowalczyk, M, Mascalchi, M, Semmelroch, M, Thomas, RH, Soltanian-Zadeh, H, Davoodi-Bojd, E, Zhang, J, Winston, GP, Griffin, A, Singh, A, Tiwari, VK, Kreilkamp, BAK, Lenge, M, Guerrini, R, Hamandi, K, Foley, S, Ruber, T, Weber, B, Depondt, C, Absil, J, Carr, SJA, Abela, E, Richardson, MP, Devinsky, O, Severino, M, Striano, P, Tortora, D, Kaestner, E, Hatton, SN, Vos, SB, Caciagli, L, Duncan, JS, Whelan, CD, Thompson, PM, Sisodiya, SM, Bernasconi, A, Labate, A, McDonald, CR, Bernasconi, N, and Bernhardt, BC
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

27. Impact of the COVID-19 pandemic on people with epilepsy: findings from the US arm of the COV-E study.

Author: Dugan, P, Carroll, E, Thorpe, J, Jette, N, Agarwal, P, Ashby, S, Hanna, J, French, J, Devinsky, O, Sen, A, COVID-19 Epilepsy COV-E Study Group, Dugan, P, Carroll, E, Thorpe, J, Jette, N, Agarwal, P, Ashby, S, Hanna, J, French, J, Devinsky, O, Sen, A, and COVID-19 Epilepsy COV-E Study Group
Abstract: OBJECTIVES: As part of the COVID-19 and Epilepsy (COV-E) global study, we aimed to understand the impact of COVID-19 on the medical care and well-being of people with epilepsy (PWE) in the United States, based on their perspectives and those of their caregivers. METHODS: Separate surveys designed for PWE and their caregivers were circulated from April 2020 to July 2021; modifications in March 2021 included a question about COVID-19 vaccination status. RESULTS: We received 788 responses, 71% from PWE (n = 559) and 29% (n=229) from caregivers of persons with epilepsy. A third (n = 308) of respondents reported a change in their health or in the health of the person they care for. Twenty-seven percent (n = 210) reported issues related to worsening mental health. Of respondents taking ASMs (n = 769), 10% (n= 78) reported difficulty taking medications on time, mostly due to stress causing forgetfulness. Less than half of respondents received counseling on mental health and stress. Less than half of the PWE reported having discussions with their healthcare providers about sleep, ASMs and potential side effects, while a larger proportion of caregivers (81%) reported having had discussions with their healthcare providers on the same topics. More PWE and caregivers reported that COVID-19 related measures caused adverse impact on their health in the post-vaccine period than during the pre-vaccine period, citing mental health issues as the primary reason. SIGNIFICANCE: Our findings indicate that the impact of the COVID-19 pandemic in the US on PWE is multifaceted. Apart from the increased risk of poor COVID-19 outcomes, the pandemic has also had negative effects on mental health and self-management. Healthcare providers must be vigilant for increased emotional distress in PWE during the pandemic and consider the importance of effective counseling to diminish risks related to exacerbated treatment gaps.
Published: 2022

28. Serotonin receptor expression in hippocampus and temporal cortex of temporal lobe epilepsy patients by postictal generalized electroencephalographic suppression duration

Author: Leitner, DF, Devore, S, Laze, J, Friedman, D, Mills, JD, Liu, Y, Janitz, M, Anink, JJ, Baayen, JC, Idema, S, van Vliet, EA, Diehl, B, Scott, C, Thijs, R, Nei, M, Askenazi, M, Sivathamboo, S, O'Brien, T, Wisniewski, T, Thom, M, Aronica, E, Boldrini, M, Devinsky, O, Leitner, DF, Devore, S, Laze, J, Friedman, D, Mills, JD, Liu, Y, Janitz, M, Anink, JJ, Baayen, JC, Idema, S, van Vliet, EA, Diehl, B, Scott, C, Thijs, R, Nei, M, Askenazi, M, Sivathamboo, S, O'Brien, T, Wisniewski, T, Thom, M, Aronica, E, Boldrini, M, and Devinsky, O
Abstract: OBJECTIVE: Prolonged postictal generalized electroencephalographic suppression (PGES) is a potential biomarker for sudden unexpected death in epilepsy (SUDEP), which may be associated with dysfunctional autonomic responses and serotonin signaling. To better understand molecular mechanisms, PGES duration was correlated to 5HT1A and 5HT2A receptor protein expression and RNAseq from resected hippocampus and temporal cortex of temporal lobe epilepsy patients with seizures recorded in preoperative evaluation. METHODS: Analyses included 36 cases (age = 14-64 years, age at epilepsy onset = 0-51 years, epilepsy duration = 2-53 years, PGES duration = 0-93 s), with 13 cases in all hippocampal analyses. 5HT1A and 5HT2A protein was evaluated by Western blot and histologically in hippocampus (n = 16) and temporal cortex (n = 9). We correlated PGES duration to our previous RNAseq dataset for serotonin receptor expression and signaling pathways, as well as weighted gene correlation network analysis (WGCNA) to identify correlated gene clusters. RESULTS: In hippocampus, 5HT2A protein by Western blot positively correlated with PGES duration (p = .0024, R2 = .52), but 5HT1A did not (p = .87, R2 = .0020). In temporal cortex, 5HT1A and 5HT2A had lower expression and did not correlate with PGES duration. Histologically, PGES duration did not correlate with 5HT1A or 5HT2A expression in hippocampal CA4, dentate gyrus, or temporal cortex. RNAseq identified two serotonin receptors with expression that correlated with PGES duration in an exploratory analysis: HTR3B negatively correlated (p = .043, R2 = .26) and HTR4 positively correlated (p = .049, R2 = .25). WGCNA identified four modules correlated with PGES duration, including positive correlation with synaptic transcripts (p = .040, Pearson correlation r = .52), particularly potassium channels (KCNA4, KCNC4, KCNH1, KCNIP4, KCNJ3, KCNJ6, KCNK1). No modules were associated with serotonin receptor signaling. SIGNIFICANCE: Higher hippocamp
Published: 2022

29. Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

Author: Iemi, L., Gwilliams, L., Samaha, J., Auksztulewicz, R., Cycowicz, Y., King, J., Nikulin, V., Thesen, T., Doyle, W., Devinsky, O., Schroeder, C., Melloni, L., and Haegens, S.
Subjects: Adult, Male, Alpha, Drug Resistant Epilepsy, Oscillations, Excitability, Cognitive Neuroscience, 350 000 Brain Rhythms, Decoding, Brain, Neurosciences. Biological psychiatry. Neuropsychiatry, Electroencephalography, Prestimulus, Brain Waves, Discrimination, Psychological, Neurology, Auditory Perception, Reaction Time, Visual Perception, Humans, Female, Longitudinal Studies, Reaction times, Photic Stimulation, RC321-571
Abstract: The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Ongoing fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on intracranial electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.
Published: 2022

30. Association of ultra-rare coding variants with genetic generalized epilepsy: A case–control whole exome sequencing study

Author: Koko, M., Motelow, J. E., Stanley, K. E., Bobbili, D. R., Dhindsa, R. S., May, P., Alldredge, B. K., Allen, A. S., Altmuller, J., Amrom, D., Andermann, E., Auce, P., Avbersek, A., Baulac, S., Bautista, J. F., Becker, F., Bellows, S. T., Berghuis, B., Berkovic, S. F., Bluvstein, J., Boro, A., Bridgers, J., Burgess, R., Caglayan, H., Cascino, G. D., Cavalleri, G. L., Chung, S. -K., Cieuta-Walti, C., Cloutier, V., Consalvo, D., Cossette, P., Crumrine, P., Delanty, N., Depondt, C., Desbiens, R., Devinsky, O., Dlugos, D., Epstein, M. P., Everett, K., Fiol, M., Fountain, N. B., Francis, B., French, J., Freyer, C., Friedman, D., Gambardella, A., Geller, E. B., Girard, S., Glauser, T., Glynn, S., Goldstein, D. B., Gravel, M., Haas, K., Haut, S. R., Heinzen, E. L., Helbig, I., Hildebrand, M. S., Johnson, M. R., Jorgensen, A., Joshi, S., Kanner, A., Kirsch, H. E., Klein, K. M., Knowlton, R. C., Koeleman, B. P. C., Kossoff, E. H., Krause, R., Krenn, M., Kunz, W. S., Kuzniecky, R., Langley, S. R., Leguern, E., Lehesjoki, A. -E., Lerche, H., Leu, C., Lortie, A., Lowenstein, D. H., Marson, A. G., Mebane, C., Mefford, H. C., Meloche, C., Moreau, C., Motika, P. V., Muhle, H., Moller, R. S., Nabbout, R., Nguyen, D. K., Nikanorova, M., Novotny, E. J., Nurnberg, P., Ottman, R., O'Brien, T. J., Paolicchi, J. M., Parent, J. M., Park, K., Peter, S., Petrou, S., Petrovski, S., Pickrell, W. O., Poduri, A., Radtke, R. A., Rees, M. I., Regan, B. M., Ren, Z., Sadleir, L. G., Sander, J. W., Sander, T., Scheffer, I. E., Schubert, J., Shellhaas, R. A., Sherr, E. H., Shih, J. J., Shinnar, S., Sills, G. J., Singh, R. K., Siren, A., Sirven, J., Sisodiya, S. M., Smith, M. C., Sonsma, A. C. M., Striano, P., Sullivan, J., Thio, L. L., Thomas, R. H., Venkat, A., Vining, E. P. G., Von Allmen, G. K., Wang, Q., Weber, Y. G., Weckhuysen, S., Weisenberg, J. L., Widdess-Walsh, P., Winawer, M. R., Wolking, S., Zara, F., Zimprich, F., Canadian Epilepsy Network, Epi4K Consortium, Epilepsy Phenome/Genome Project, EpiPGX Consortium, EuroEPINOMICS-CoGIE Consortium, Department of Medical and Clinical Genetics, Medicum, Fonds National de la Recherche - FnR [sponsor], Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Peter, Sarah, Petrou, Steven, Petrovski, Slavé, Pickrell, William O., Poduri, Annapurna, Radtke, Rodney A., Rees, Mark I., Regan, Brigid M., Ren, Zhong, Sadleir, Lynette G., Alldredge, Brian K., Sander, Josemir W., Sander, Thomas, Scheffer, Ingrid E., Schubert, Julian, Shellhaas, Renée A., Sherr, Elliott H., Shih, Jerry J., Shinnar, Shlomo, Sills, Graeme J., Singh, Rani K., Allen, Andrew S., Siren, Auli, Sirven, Joseph, Sisodiya, Sanjay M., Smith, Michael C., Sonsma, Anja C. M., Striano, Pasquale, Sullivan, Joseph, Thio, Liu Lin, Thomas, Rhys H., Venkat, Anu, Altmüller, Janine, Vining, Eileen P. G., Von Allmen, Gretchen K., Wang, Quanli, Weber, Yvonne G., Weckhuysen, Sarah, Weisenberg, Judith L., Widdess-Walsh, Peter, Winawer, Melodie R., Wolking, Stefan, Zara, Federico, Amrom, Dina, Zimprich, Fritz, Andermann, Eva, Auce, Pauls, Avbersek, Andreja, Baulac, Stéphanie, Bautista, Jocelyn F., Becker, Felicitas, Bellows, Susannah T., Berghuis, Bianca, Berkovic, Samuel F., Bluvstein, Judith, Boro, Alex, Bridgers, Joshua, Burgess, Rosemary, Caglayan, Hande, Cascino, Gregory D., Cavalleri, Gianpiero L., Chung, Seo-Kyung, Cieuta-Walti, Cécile, Cloutier, Véronique, Consalvo, Damian, Cossette, Patrick, Crumrine, Patricia, Delanty, Norman, Depondt, Chantal, Desbiens, Richard, Devinsky, Orrin, Dlugos, Dennis, Epstein, Michael P., Everett, Kate, Fiol, Miguel, Fountain, Nathan B., Francis, Ben, French, Jacqueline, Freyer, Catharine, Friedman, Daniel, Gambardella, Antonio, Geller, Eric B., Girard, Simon, Glauser, Tracy, Glynn, Simon, Goldstein, David B., Gravel, Micheline, Haas, Kevin, Haut, Sheryl R., Heinzen, Erin L., Helbig, Ingo, Hildebrand, Michael S., Johnson, Michael R., Jorgensen, Andrea, Joshi, Sucheta, Kanner, Andres, Kirsch, Heidi E., Klein, Karl M., Knowlton, Robert C., Koeleman, Bobby P. C., Kossoff, Eric H., Krause, Roland, Krenn, Martin, Kunz, Wolfram S., Kuzniecky, Ruben, Langley, Sarah R., LeGuern, Eric, Lehesjoki, Anna-Elina, Lerche, Holger, Leu, Costin, Lortie, Anne, Lowenstein, Daniel H., Marson, Anthony G., Mebane, Caroline, Mefford, Heather C., Meloche, Caroline, Moreau, Claudia, Motika, Paul V., Muhle, Hiltrud, Møller, Rikke S., Nabbout, Rima, Nguyen, Dang K., Nikanorova, Marina, Novotny, Edward J., Nürnberg, Peter, Ottman, Ruth, O'Brien, Terence J., Paolicchi, Juliann M., Parent, Jack M., and Park, Kristen
Subjects: GABA receptors, Neurology [D14] [Human health sciences], Clinical Sciences, GABA(A) receptors, GABRG2, familial epilepsy, Article, Clinical Research, Receptors, Exome Sequencing, Genetics, 2.1 Biological and endogenous factors, Humans, GGE, Genetic Predisposition to Disease, sporadic epilepsy, EpiPGX Consortium, Aetiology, gamma-Aminobutyric Acid, GABAA receptors, Epi4K Consortium, Epilepsy, Neurology & Neurosurgery, Neurologie [D14] [Sciences de la santé humaine], Generalized, GABA-A, Prevention, Human Genome, Neurosciences, 1184 Genetics, developmental biology, physiology, 3112 Neurosciences, Receptors, GABA-A, EuroEPINOMICS-CoGIE Consortium, Neurology, Case-Control Studies, Epilepsy, Generalized, Canadian Epilepsy Network, Neurology (clinical), Genetics & genetic processes [F10] [Life sciences], 3111 Biomedicine, Human medicine, Génétique & processus génétiques [F10] [Sciences du vivant], Epilepsy Phenome/Genome Project
Abstract: ObjectiveWe aimed to identify genes associated with genetic generalized epilepsy (GGE) by combining large cohorts enriched with individuals with a positive family history. Secondarily, we set out to compare the association of genes independently with familial and sporadic GGE.MethodsWe performed a case-control whole exome sequencing study in unrelated individuals of European descent diagnosed with GGE (previously recruited and sequenced through multiple international collaborations) and ancestry-matched controls. The association of ultra-rare variants (URVs; in 18834 protein-coding genes) with epilepsy was examined in 1928 individuals with GGE (vs. 8578 controls), then separately in 945 individuals with familial GGE (vs. 8626 controls), and finally in 1005 individuals with sporadic GGE (vs. 8621 controls). We additionally examined the association of URVs with familial and sporadic GGE in two gene sets important for inhibitory signaling (19genes encoding γ-aminobutyric acid type A [GABAA ] receptors, 113genes representing the GABAergic pathway).ResultsGABRG2 was associated with GGE (p=1.8×10-5 ), approaching study-wide significance in familial GGE (p=3.0×10-6 ), whereas no gene approached a significant association with sporadic GGE. Deleterious URVs in the most intolerant subgenic regions in genes encoding GABAA receptors were associated with familial GGE (odds ratio [OR]=3.9, 95% confidence interval [CI]=1.9-7.8, false discovery rate [FDR]-adjusted p=.0024), whereas their association with sporadic GGE had marginally lower odds (OR=3.1, 95% CI=1.3-6.7, FDR-adjusted p=.022). URVs in GABAergic pathway genes were associated with familial GGE (OR=1.8, 95% CI=1.3-2.5, FDR-adjusted p=.0024) but not with sporadic GGE (OR=1.3, 95% CI=.9-1.9, FDR-adjusted p=.19).SignificanceURVs in GABRG2 are likely an important risk factor for familial GGE. The association of gene sets of GABAergic signaling with familial GGE is more prominent than with sporadic GGE.
Published: 2022
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31. Abnormalities of cortical thickness in postictal psychosis

Author: DuBois, J.M., Devinsky, O., Carlson, C., Kuzniecky, R., Quinn, B.T., Alper, K., Butler, T., Starner, K., Halgren, E., and Thesen, T.
Published: 2011
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32. Anatomic and Physiological Considerations in Pallidotomy for Parkinson’s Disease

Author: Dogali, M., Berić, A., Sterio, D., Eidelberg, D., Fazzini, E., Takikawa, S., Samelson, D. R., Devinsky, O., Kolodny, E. H., Meyerson, Björn A., editor, and Ostertag, Christoph, editor
Published: 1995
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33. Historical perspectives and definitions of the postictal state

Author: Widdess-Walsh, P. and Devinsky, O.
Published: 2010
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34. Seizure prediction and recall

Author: DuBois, J.M., Boylan, L.S., Shiyko, M., Barr, W.B., and Devinsky, O.
Published: 2010
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35. Brain and Cerebrospinal Fluid Quinolinic Acid Concentrations in Patients with Intractable Complex Partial Seizures

Author: Heyes, M. P., Wyler, A. R., Devinsky, O., Yergey, J. A., Markey, S. P., Nadi, N. S., Schwarcz, Robert, editor, Young, Simon N., editor, and Brown, Raymond R., editor
Published: 1991
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36. Impact of Fenfluramine on the Expected SUDEP Incidence Rate in Patients with Dravet Syndrome

Author: Pringsheim, M., additional, Cross, J. H., additional, Galer, B. S., additional, Gil-Nagel, A., additional, Devinsky, O., additional, Ceulemans, B., additional, Lagae, L., additional, Schoonjans, A. S., additional, Donner, E., additional, Wirrell, E., additional, and Gammaitoni, A. R., additional
Published: 2021
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37. Topographic Divergence of Atypical Cortical Asymmetry and Regional Atrophy Patterns in Temporal Lobe Epilepsy: A Worldwide ENIGMA Study

Author: Colin P. Doherty, Boris C. Bernhardt, Graeme D. Jackson, Mariasavina Severino, Christian Rummel, Charles B Malpas, Esmaeil Davoodi-Bojd, Gianpiero L. Cavalleri, Angelo Labate, Sean N. Hatton, Soenke Langner, Magdalena A. Kowalczyk, Domenico Tortora, Barbara A. K. Kreilkamp, Manuela Tondelli, Clarissa L. Yasuda, Clyde Francks, Sara Larivière, Jose C. Pariente, Norman Delanty, Terence J. O'Brien, J Duncan, Roland Wiest, Emanuele Bartolini, Lorenzo Caciagli, Pasquale Striano, Saud Alhusaini, Jessica Royer, Ezequiel Gleichgerrcht, Lucy Vivash, Conde E, Paul M. Thompson, Raúl Rodríguez-Cruces, Neda Bernasconi, Elaine Lui, Renzo Guerrini, Antonio Gambardella, Xiangzhen Kong, Simon E. Fisher, Matteo Lenge, Leonardo Bonilha, Bernd Weber, Patricia Desmond, von Podewils F, Luis Concha, Andrea Bernasconi, Mark P. Richardson, Christopher D. Whelan, Benjamin Bender, Bo-yong Park, Khalid Hamandi, Julie Absil, Eugenio Abela, Hamid Soltanian-Zadeh, Marina K. M. Alvim, Benjamin Sinclair, Núria Bargalló, Pascal Martin, Anna Elisabetta Vaudano, Jinwei Zhang, Martin Domin, Sarah J. A. Carr, Meletti S, Sanjay M. Sisodiya, Carrie R. McDonald, Niels K. Focke, Mira Semmelroch, Devinsky O, Maria Eugenia Caligiuri, Parodi C, Chantal Depondt, Marian Galovic, Reetta Kälviäinen, Shahin Tavakol, Simon S. Keller, Micheal Rebsamen, Fernando Cendes, Yezhou Wang, Mario Mascalchi, Meng Law, Rhys H. Thomas, Sjoerd B. Vos, Raviteja Kotikalapudi, and Sonya Foley
Subjects: 0303 health sciences, Neuropathology, Disease, Hippocampal formation, Grey matter, Biology, medicine.disease, Divergence, Temporal lobe, 03 medical and health sciences, Epilepsy, 0302 clinical medicine, medicine.anatomical_structure, Atrophy, medicine, Neuroscience, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract: Temporal lobe epilepsy (TLE), 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 pathology in TLE 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 multi-site ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 TLE patients and 1,418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in TLE, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity, 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 TLE-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 TLE and may inform future discovery and validation of complementary MRI biomarkers in TLE.
Published: 2021
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38. Spontaneous neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

Author: Vadim V. Nikulin, Jean-Rémi King, Laura Gwilliams, Ryszard Auksztulewicz, Lucia Melloni, Charles E. Schroeder, Luca Iemi, Thomas Thesen, Devinsky O, Saskia Haegens, Yael M. Cycowicz, Werner Doyle, and Jason Samaha
Subjects: Adaptive behavior, Electrophysiology, Rhythm, Sensory processing, medicine.medical_treatment, medicine, Alpha (ethology), Sensory system, Stimulus (physiology), Biology, Neuroscience, Sensory cue
Abstract: The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Spontaneous fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on invasive electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.
Published: 2021
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39. Imagined speech can be decoded from low- and cross-frequency features in perceptual space

Author: David Poeppel, Luc H. Arnal, Brian N. Pasley, Timothée Proix, Jaime Fernando Delgado Saa, Xing Tian, Anne-Lise Giraud, Pierre Mégevand, Robert T. Knight, Devinsky O, Andy Christen, Werner Doyle, and Stephanie Martin
Subjects: Speech production, Imagined speech, Dynamics (music), Computer science, Speech recognition, Perception, media_common.quotation_subject, Space (commercial competition), Decoding methods, media_common
Abstract: SummaryReconstructing intended speech from neural activity using brain-computer interfaces (BCIs) holds great promises for people with severe speech production deficits. While decoding overt speech has progressed, decoding imagined speech have met limited success, mainly because the associated neural signals are weak and variable hence difficult to decode by learning algorithms. Using three electrocorticography datasets totalizing 1444 electrodes from 13 patients who performed overt and imagined speech production tasks, and based on recent theories of speech neural processing, we extracted consistent and specific neural features usable for future BCIs, and assessed their performance to discriminate speech items in articulatory, phonetic, vocalic, and semantic representation spaces. While high-frequency activity provided the best signal for overt speech, both low- and higher-frequency power and local cross-frequency contributed to successful imagined speech decoding, in particular in phonetic and vocalic, i.e. perceptual, spaces. These findings demonstrate that low-frequency power and cross-frequency dynamics contain key information for imagined speech decoding, and that exploring perceptual spaces offers a promising avenue for future imagined speech BCIs.
Published: 2021
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40. Shared genetic basis between genetic generalized epilepsy and background electroencephalographic oscillations

Author: Stevelink, R, Luykx, JJ, Lin, BD, Leu, C, Lal, D, Smith, AW, Schijven, D, Carpay, JA, Rademaker, K, Baldez, RAR, Devinsky, O, Braun, KPJ, Jansen, FE, Smit, DJA, Koeleman, BPC, Stevelink, R, Luykx, JJ, Lin, BD, Leu, C, Lal, D, Smith, AW, Schijven, D, Carpay, JA, Rademaker, K, Baldez, RAR, Devinsky, O, Braun, KPJ, Jansen, FE, Smit, DJA, and Koeleman, BPC
Abstract: OBJECTIVE: Paroxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations. METHODS: Confounding factors, including the heterogeneous etiology of epilepsies and medication effects, hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a genome-wide association study (GWAS) on epilepsy (n = 12 803 people with epilepsy and 24 218 controls) with that from a GWAS on background EEG (n = 8425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta, and theta. We replicated our findings in an independent epilepsy replication dataset (n = 4851 people with epilepsy and 20 428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores, and Mendelian randomization analyses. RESULTS: Our analyses show strong genetic correlations of genetic generalized epilepsy (GGE) with background EEG oscillations, primarily in the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations. SIGNIFICANCE: Our results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic workup of epilepsy.
Published: 2021

41. Diverse genetic causes of polymicrogyria with epilepsy

Author: Allen, AS, Aggarwal, V, Berkovic, SF, Cossette, P, Delanty, N, Dlugos, D, Eichler, EE, Epstein, MP, Freyer, C, Goldstein, DB, Guerrini, R, Glauser, T, Heinzen, EL, Johnson, MR, Kuzniecky, R, Lowenstein, DH, Marson, AG, Mefford, HC, O'Brien, TJ, Ottman, R, Poduri, A, Petrou, S, Petrovski, S, Ruzzo, EK, Scheffer, IE, Sherr, EH, Abou-Khalil, B, Amrom, D, Andermann, E, Andermann, F, Bluvstein, J, Boro, A, Cascino, G, Consalvo, D, Crumrine, P, Devinsky, O, Fountain, N, Friedman, D, Geller, E, Glynn, S, Haas, K, Haut, S, Joshi, S, Kirsch, H, Knowlton, R, Kossoff, E, Motika, PV, Paolicchi, JM, Parent, JM, Shellhaas, RA, Shih, JJ, Shinnar, S, Singh, RK, Sperling, M, Smith, MC, Sullivan, J, Vining, EPG, Von Allmen, GK, Widdess-Walsh, P, Winawer, MR, Bautista, J, Fiol, M, Hayward, J, Helmers, S, Park, K, Sirven, J, Thio, LL, Venkat, A, Weisenberg, J, Kuperman, R, McGuire, S, Novotny, E, Sadleir, L, Allen, AS, Aggarwal, V, Berkovic, SF, Cossette, P, Delanty, N, Dlugos, D, Eichler, EE, Epstein, MP, Freyer, C, Goldstein, DB, Guerrini, R, Glauser, T, Heinzen, EL, Johnson, MR, Kuzniecky, R, Lowenstein, DH, Marson, AG, Mefford, HC, O'Brien, TJ, Ottman, R, Poduri, A, Petrou, S, Petrovski, S, Ruzzo, EK, Scheffer, IE, Sherr, EH, Abou-Khalil, B, Amrom, D, Andermann, E, Andermann, F, Bluvstein, J, Boro, A, Cascino, G, Consalvo, D, Crumrine, P, Devinsky, O, Fountain, N, Friedman, D, Geller, E, Glynn, S, Haas, K, Haut, S, Joshi, S, Kirsch, H, Knowlton, R, Kossoff, E, Motika, PV, Paolicchi, JM, Parent, JM, Shellhaas, RA, Shih, JJ, Shinnar, S, Singh, RK, Sperling, M, Smith, MC, Sullivan, J, Vining, EPG, Von Allmen, GK, Widdess-Walsh, P, Winawer, MR, Bautista, J, Fiol, M, Hayward, J, Helmers, S, Park, K, Sirven, J, Thio, LL, Venkat, A, Weisenberg, J, Kuperman, R, McGuire, S, Novotny, E, and Sadleir, L
Abstract: OBJECTIVE: We sought to identify novel genes and to establish the contribution of known genes in a large cohort of patients with nonsyndromic sporadic polymicrogyria and epilepsy. METHODS: We enrolled participants with polymicrogyria and their parents through the Epilepsy Phenome/Genome Project. We performed phenotyping and whole exome sequencing (WES), trio analysis, and gene-level collapsing analysis to identify de novo or inherited variants, including germline or mosaic (postzygotic) single nucleotide variants, small insertion-deletion (indel) variants, and copy number variants present in leukocyte-derived DNA. RESULTS: Across the cohort of 86 individuals with polymicrogyria and epilepsy, we identified seven with pathogenic or likely pathogenic variants in PIK3R2, including four germline and three mosaic variants. PIK3R2 was the only gene harboring more than expected de novo variants across the entire cohort, and likewise the only gene that passed the genome-wide threshold of significance in the gene-level rare variant collapsing analysis. Consistent with previous reports, the PIK3R2 phenotype consisted of bilateral polymicrogyria concentrated in the perisylvian region with macrocephaly. Beyond PIK3R2, we also identified one case each with likely causal de novo variants in CCND2 and DYNC1H1 and biallelic variants in WDR62, all genes previously associated with polymicrogyria. Candidate genetic explanations in this cohort included single nucleotide de novo variants in other epilepsy-associated and neurodevelopmental disease-associated genes (SCN2A in two individuals, GRIA3, CACNA1C) and a 597-kb deletion at 15q25, a neurodevelopmental disease susceptibility locus. SIGNIFICANCE: This study confirms germline and postzygotically acquired de novo variants in PIK3R2 as an important cause of bilateral perisylvian polymicrogyria, notably with macrocephaly. In total, trio-based WES identified a genetic diagnosis in 12% and a candidate diagnosis in 6% of our polymicrogyria
Published: 2021

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

Author: Gleichgerrcht, E, Munsell, BC, Alhusaini, S, Alvim, MKM, Bargallo, N, Bender, B, Bernasconi, A, Bernasconi, N, Bernhardt, B, Blackmon, K, Caligiuri, ME, Cendes, F, Concha, L, Desmond, PM, Devinsky, O, Doherty, CP, Domin, M, Duncan, JS, Focke, NK, Gambardella, A, Gong, B, Guerrini, R, Hatton, SN, Kalviainen, R, Keller, SS, Kochunov, P, Kotikalapudi, R, Kreilkamp, BAK, Labate, A, Langner, S, Lariviere, S, Lenge, M, Lui, E, Martin, P, Mascalchi, M, Meletti, S, O'Brien, TJ, Pardoe, HR, Pariente, JC, Rao, JX, Richardson, MP, Rodriguez-Cruces, R, Ruber, T, Sinclair, B, Soltanian-Zadeh, H, Stein, DJ, Striano, P, Taylor, PN, Thomas, RH, Vaudano, AE, Vivash, L, von Podewills, F, Vos, SB, Weber, B, Yao, Y, Yasuda, CL, Zhang, J, Thompson, PM, Sisodiya, SM, McDonald, CR, Bonilha, L, Gleichgerrcht, E, Munsell, BC, Alhusaini, S, Alvim, MKM, Bargallo, N, Bender, B, Bernasconi, A, Bernasconi, N, Bernhardt, B, Blackmon, K, Caligiuri, ME, Cendes, F, Concha, L, Desmond, PM, Devinsky, O, Doherty, CP, Domin, M, Duncan, JS, Focke, NK, Gambardella, A, Gong, B, Guerrini, R, Hatton, SN, Kalviainen, R, Keller, SS, Kochunov, P, Kotikalapudi, R, Kreilkamp, BAK, Labate, A, Langner, S, Lariviere, S, Lenge, M, Lui, E, Martin, P, Mascalchi, M, Meletti, S, O'Brien, TJ, Pardoe, HR, Pariente, JC, Rao, JX, Richardson, MP, Rodriguez-Cruces, R, Ruber, T, Sinclair, B, Soltanian-Zadeh, H, Stein, DJ, Striano, P, Taylor, PN, Thomas, RH, Vaudano, AE, Vivash, L, von Podewills, F, Vos, SB, Weber, B, Yao, Y, Yasuda, CL, Zhang, J, Thompson, PM, Sisodiya, SM, McDonald, CR, and Bonilha, L
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

43. Evaluating risk to people with epilepsy during the COVID-19 pandemic: Preliminary findings from the COV-E study

Author: Thorpe, J, Ashby, S, Hallab, A, Ding, D, Andraus, M, Dugan, P, Perucca, P, Costello, D, French, JA, O'Brien, TJ, Depondt, C, Andrade, DM, Sengupta, R, Delanty, N, Jette, N, Newton, CR, Brodie, MJ, Devinsky, O, Cross, JH, Sander, JW, Hanna, J, Sen, A, Thorpe, J, Ashby, S, Hallab, A, Ding, D, Andraus, M, Dugan, P, Perucca, P, Costello, D, French, JA, O'Brien, TJ, Depondt, C, Andrade, DM, Sengupta, R, Delanty, N, Jette, N, Newton, CR, Brodie, MJ, Devinsky, O, Cross, JH, Sander, JW, Hanna, J, and Sen, A
Abstract: The COVID-19 pandemic has caused global anguish unparalleled in recent times. As cases rise, increased pressure on health services, combined with severe disruption to people's everyday lives, can adversely affect individuals living with chronic illnesses, including people with epilepsy. Stressors related to disruption to healthcare, finances, mental well-being, relationships, schooling, physical activity, and increased isolation could increase seizures and impair epilepsy self-management. We aim to understand the impact that COVID-19 has had on the health and well-being of people with epilepsy focusing on exposure to increased risk of seizures, associated comorbidity, and mortality. We designed two online surveys with one addressing people with epilepsy directly and the second for caregivers to report on behalf of a person with epilepsy. The survey is ongoing and has yielded 463 UK-based responses by the end of September 2020. Forty percent of respondents reported health changes during the pandemic (n = 185). Respondents cited a change in seizures (19%, n = 88), mental health difficulties (34%, n = 161), and sleep disruption (26%, n = 121) as the main reasons. Thirteen percent found it difficult to take medication on time. A third had difficulty accessing medical services (n = 154), with 8% having had an appointment canceled (n = 39). Only a small proportion reported having had discussions about epilepsy-related risks, such as safety precautions (16%, n = 74); mental health (29%, n = 134); sleep (30%, n = 140); and Sudden Unexpected Death in Epilepsy (SUDEP; 15%, n = 69) in the previous 12 months. These findings suggest that people with epilepsy are currently experiencing health changes, coupled with inadequate access to services. Also, there seems to be a history of poor risk communication in the months preceding the pandemic. As the UK witnesses a second COVID-19 wave, those involved in healthcare delivery must ensure optimal care is provided for people with chron
Published: 2021

44. Add-on cannabidiol in patients with Dravet syndrome: Results of a long-term open-label extension trial

Author: Scheffer, IE, Halford, JJ, Miller, I, Nabbout, R, Sanchez-Carpintero, R, Shiloh-Malawsky, Y, Wong, M, Zolnowska, M, Checketts, D, Dunayevich, E, Devinsky, O, Scheffer, IE, Halford, JJ, Miller, I, Nabbout, R, Sanchez-Carpintero, R, Shiloh-Malawsky, Y, Wong, M, Zolnowska, M, Checketts, D, Dunayevich, E, and Devinsky, O
Abstract: OBJECTIVE: Add-on cannabidiol (CBD) reduced seizures associated with Dravet syndrome (DS) in two randomized, double-blind, placebo-controlled trials: GWPCARE1 Part B (NCT02091375) and GWPCARE2 (NCT02224703). Patients who completed GWPCARE1 Part A (NCT02091206) or Part B, or GWPCARE2, were enrolled in a long-term open-label extension trial, GWPCARE5 (NCT02224573). We present an interim analysis of the safety, efficacy, and patient-reported outcomes from GWPCARE5. METHODS: Patients received a pharmaceutical formulation of highly purified CBD in oral solution (100 mg/ml), titrated from 2.5 to 20 mg/kg/day over a 2-week period, added to their existing medications. Based on response and tolerance, CBD could be reduced or increased to 30 mg/kg/day. RESULTS: Of the 330 patients who completed the original randomized trials, 315 (95%) enrolled in this open-label extension. Median treatment duration was 444 days (range = 18-1535), with a mean modal dose of 22 mg/kg/day; patients received a median of three concomitant antiseizure medications. Adverse events (AEs) occurred in 97% patients (mild, 23%; moderate, 50%; severe, 25%). Commonly reported AEs were diarrhea (43%), pyrexia (39%), decreased appetite (31%), and somnolence (28%). Twenty-eight (9%) patients discontinued due to AEs. Sixty-nine (22%) patients had liver transaminase elevations >3 × upper limit of normal; 84% were on concomitant valproic acid. In patients from GWPCARE1 Part B and GWPCARE2, the median reduction from baseline in monthly seizure frequency assessed in 12-week periods up to Week 156 was 45%-74% for convulsive seizures and 49%-84% for total seizures. Across all visit windows, ≥83% patients/caregivers completing a Subject/Caregiver Global Impression of Change scale reported improvement in overall condition. SIGNIFICANCE: We show that long-term CBD treatment had an acceptable safety profile and led to sustained, clinically meaningful reductions in seizure frequency in patients with treatment-resistant DS
Published: 2021

45. Sub-genic intolerance, ClinVar, and the epilepsies: A whole-exome sequencing study of 29,165 individuals

Author: Motelow, JE, Povysil, G, Dhindsa, RS, Stanley, KE, Allen, AS, Feng, Y-CA, Howrigan, DP, Abbott, LE, Tashman, K, Cerrato, F, Cusick, C, Singh, T, Heyne, H, Byrnes, AE, Churchhouse, C, Watts, N, Solomonson, M, Lal, D, Gupta, N, Neale, BM, Cavalleri, GL, Cossette, P, Cotsapas, C, De Jonghe, P, Dixon-Salazar, T, Guerrini, R, Hakonarson, H, Heinzen, EL, Helbig, I, Kwan, P, Marson, AG, Petrovski, S, Kamalakaran, S, Sisodiya, SM, Stewart, R, Weckhuysen, S, Depondt, C, Dlugos, DJ, Scheffer, IE, Striano, P, Freyer, C, Krause, R, May, P, McKenna, K, Regan, BM, Bennett, CA, Leu, C, Leech, SL, O'Brien, TJ, Todaro, M, Stamberger, H, Andrade, DM, Ali, QZ, Sadoway, TR, Krestel, H, Schaller, A, Papacostas, SS, Kousiappa, I, Tanteles, GA, Christou, Y, Sterbova, K, Vlckova, M, Sedlackova, L, Lassuthova, P, Klein, KM, Rosenow, F, Reif, PS, Knake, S, Neubauer, BA, Zimprich, F, Feucht, M, Reinthaler, EM, Kunz, WS, Zsurka, G, Surges, R, Baumgartner, T, von Wrede, R, Pendziwiat, M, Muhle, H, Rademacher, A, van Baalen, A, von Spiczak, S, Stephani, U, Afawi, Z, Korczyn, AD, Kanaan, M, Canavati, C, Kurlemann, G, Muller-Schluter, K, Kluger, G, Haeusler, M, Blatt, I, Lemke, JR, Krey, I, Weber, YG, Wolking, S, Becker, F, Lauxmann, S, Bosselmann, C, Kegele, J, Hengsbach, C, Rau, S, Steinhoff, BJ, Schulze-Bonhage, A, Borggraefe, I, Schankin, CJ, Schubert-Bast, S, Schreiber, H, Mayer, T, Korinthenberg, R, Brockmann, K, Wolff, M, Dennig, D, Madeleyn, R, Kalviainen, R, Saarela, A, Timonen, O, Linnankivi, T, Lehesjoki, A-E, Rheims, S, Lesca, G, Ryvlin, P, Maillard, L, Valton, L, Derambure, P, Bartolomei, F, Hirsch, E, Michel, V, Chassoux, F, Rees, M, Chung, S-K, Pickrell, WO, Powell, R, Baker, MD, Fonferko-Shadrach, B, Lawthom, C, Anderson, J, Schneider, N, Balestrini, S, Zagaglia, S, Braatz, V, Johnson, MR, Auce, P, Sills, GJ, Baum, LW, Sham, PC, Cherny, SS, Lui, CHT, Delanty, N, Doherty, CP, Shukralla, A, El-Naggar, H, Widdess-Walsh, P, Barisi, N, Canafoglia, L, Franceschetti, S, Castellotti, B, Granata, T, Ragona, F, Zara, F, Iacomino, M, Riva, A, Madia, F, Vari, MS, Salpietro, V, Scala, M, Mancardi, MM, Nobili, L, Amadori, E, Giacomini, T, Bisulli, F, Pippucci, T, Licchetta, L, Minardi, R, Tinuper, P, Muccioli, L, Mostacci, B, Gambardella, A, Labate, A, Annesi, G, Manna, L, Gagliardi, M, Parrini, E, Mei, D, Vetro, A, Bianchini, C, Montomoli, M, Doccini, V, Barba, C, Hirose, S, Ishii, A, Suzuki, T, Inoue, Y, Yamakawa, K, Beydoun, A, Nasreddine, W, Zgheib, NK, Tumiene, B, Utkus, A, Sadleir, LG, King, C, Caglayan, SH, Arslan, M, Yapici, Z, Topaloglu, P, Kara, B, Yis, U, Turkdogan, D, Gundogdu-Eken, A, Bebek, N, Tsai, M-H, Ho, C-J, Lin, C-H, Lin, K-L, Chou, I-J, Poduri, A, Shiedley, BR, Shain, C, Noebels, JL, Goldman, A, Busch, RM, Jehi, L, Najm, IM, Ferguson, L, Khoury, J, Glauser, TA, Clark, PO, Buono, RJ, Ferraro, TN, Sperling, MR, Lo, W, Privitera, M, French, JA, Schachter, S, Kuzniecky, R, Devinsky, O, Hegde, M, Greenberg, DA, Ellis, CA, Goldberg, E, Helbig, KL, Cosico, M, Vaidiswaran, P, Fitch, E, Berkovic, SF, Lerche, H, Lowenstein, DH, Goldstein, DB, Motelow, JE, Povysil, G, Dhindsa, RS, Stanley, KE, Allen, AS, Feng, Y-CA, Howrigan, DP, Abbott, LE, Tashman, K, Cerrato, F, Cusick, C, Singh, T, Heyne, H, Byrnes, AE, Churchhouse, C, Watts, N, Solomonson, M, Lal, D, Gupta, N, Neale, BM, Cavalleri, GL, Cossette, P, Cotsapas, C, De Jonghe, P, Dixon-Salazar, T, Guerrini, R, Hakonarson, H, Heinzen, EL, Helbig, I, Kwan, P, Marson, AG, Petrovski, S, Kamalakaran, S, Sisodiya, SM, Stewart, R, Weckhuysen, S, Depondt, C, Dlugos, DJ, Scheffer, IE, Striano, P, Freyer, C, Krause, R, May, P, McKenna, K, Regan, BM, Bennett, CA, Leu, C, Leech, SL, O'Brien, TJ, Todaro, M, Stamberger, H, Andrade, DM, Ali, QZ, Sadoway, TR, Krestel, H, Schaller, A, Papacostas, SS, Kousiappa, I, Tanteles, GA, Christou, Y, Sterbova, K, Vlckova, M, Sedlackova, L, Lassuthova, P, Klein, KM, Rosenow, F, Reif, PS, Knake, S, Neubauer, BA, Zimprich, F, Feucht, M, Reinthaler, EM, Kunz, WS, Zsurka, G, Surges, R, Baumgartner, T, von Wrede, R, Pendziwiat, M, Muhle, H, Rademacher, A, van Baalen, A, von Spiczak, S, Stephani, U, Afawi, Z, Korczyn, AD, Kanaan, M, Canavati, C, Kurlemann, G, Muller-Schluter, K, Kluger, G, Haeusler, M, Blatt, I, Lemke, JR, Krey, I, Weber, YG, Wolking, S, Becker, F, Lauxmann, S, Bosselmann, C, Kegele, J, Hengsbach, C, Rau, S, Steinhoff, BJ, Schulze-Bonhage, A, Borggraefe, I, Schankin, CJ, Schubert-Bast, S, Schreiber, H, Mayer, T, Korinthenberg, R, Brockmann, K, Wolff, M, Dennig, D, Madeleyn, R, Kalviainen, R, Saarela, A, Timonen, O, Linnankivi, T, Lehesjoki, A-E, Rheims, S, Lesca, G, Ryvlin, P, Maillard, L, Valton, L, Derambure, P, Bartolomei, F, Hirsch, E, Michel, V, Chassoux, F, Rees, M, Chung, S-K, Pickrell, WO, Powell, R, Baker, MD, Fonferko-Shadrach, B, Lawthom, C, Anderson, J, Schneider, N, Balestrini, S, Zagaglia, S, Braatz, V, Johnson, MR, Auce, P, Sills, GJ, Baum, LW, Sham, PC, Cherny, SS, Lui, CHT, Delanty, N, Doherty, CP, Shukralla, A, El-Naggar, H, Widdess-Walsh, P, Barisi, N, Canafoglia, L, Franceschetti, S, Castellotti, B, Granata, T, Ragona, F, Zara, F, Iacomino, M, Riva, A, Madia, F, Vari, MS, Salpietro, V, Scala, M, Mancardi, MM, Nobili, L, Amadori, E, Giacomini, T, Bisulli, F, Pippucci, T, Licchetta, L, Minardi, R, Tinuper, P, Muccioli, L, Mostacci, B, Gambardella, A, Labate, A, Annesi, G, Manna, L, Gagliardi, M, Parrini, E, Mei, D, Vetro, A, Bianchini, C, Montomoli, M, Doccini, V, Barba, C, Hirose, S, Ishii, A, Suzuki, T, Inoue, Y, Yamakawa, K, Beydoun, A, Nasreddine, W, Zgheib, NK, Tumiene, B, Utkus, A, Sadleir, LG, King, C, Caglayan, SH, Arslan, M, Yapici, Z, Topaloglu, P, Kara, B, Yis, U, Turkdogan, D, Gundogdu-Eken, A, Bebek, N, Tsai, M-H, Ho, C-J, Lin, C-H, Lin, K-L, Chou, I-J, Poduri, A, Shiedley, BR, Shain, C, Noebels, JL, Goldman, A, Busch, RM, Jehi, L, Najm, IM, Ferguson, L, Khoury, J, Glauser, TA, Clark, PO, Buono, RJ, Ferraro, TN, Sperling, MR, Lo, W, Privitera, M, French, JA, Schachter, S, Kuzniecky, R, Devinsky, O, Hegde, M, Greenberg, DA, Ellis, CA, Goldberg, E, Helbig, KL, Cosico, M, Vaidiswaran, P, Fitch, E, Berkovic, SF, Lerche, H, Lowenstein, DH, and Goldstein, DB
Abstract: Both mild and severe epilepsies are influenced by variants in the same genes, yet an explanation for the resulting phenotypic variation is unknown. As part of the ongoing Epi25 Collaboration, we performed a whole-exome sequencing analysis of 13,487 epilepsy-affected individuals and 15,678 control individuals. While prior Epi25 studies focused on gene-based collapsing analyses, we asked how the pattern of variation within genes differs by epilepsy type. Specifically, we compared the genetic architectures of severe developmental and epileptic encephalopathies (DEEs) and two generally less severe epilepsies, genetic generalized epilepsy and non-acquired focal epilepsy (NAFE). Our gene-based rare variant collapsing analysis used geographic ancestry-based clustering that included broader ancestries than previously possible and revealed novel associations. Using the missense intolerance ratio (MTR), we found that variants in DEE-affected individuals are in significantly more intolerant genic sub-regions than those in NAFE-affected individuals. Only previously reported pathogenic variants absent in available genomic datasets showed a significant burden in epilepsy-affected individuals compared with control individuals, and the ultra-rare pathogenic variants associated with DEE were located in more intolerant genic sub-regions than variants associated with non-DEE epilepsies. MTR filtering improved the yield of ultra-rare pathogenic variants in affected individuals compared with control individuals. Finally, analysis of variants in genes without a disease association revealed a significant burden of loss-of-function variants in the genes most intolerant to such variation, indicating additional epilepsy-risk genes yet to be discovered. Taken together, our study suggests that genic and sub-genic intolerance are critical characteristics for interpreting the effects of variation in genes that influence epilepsy.
Published: 2021

46. Multiple Subpial Cortical Transections for the Control of Intractable Epilepsy in Exquisite Cortex

Author: Dogali, Michael, Devinsky, O., Luciano, D., Perrine, K., Beric, A., Meyerson, Björn A., editor, Broggi, Giovanni, editor, Martin-Rodriguez, Jose, editor, Ostertag, Christoph, editor, and Sindou, Marc, editor
Published: 1993
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47. Levetiracetam has no acute effects on brain γ-aminobutyric acid levels

Author: Kuzniecky, R., Pan, J., Burns, A., Devinsky, O., and Hetherington, H.
Published: 2008
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48. Polygenic burden in focal and generalized epilepsies

Author: Leu C., Stevelink R., Smith A. W., Goleva S. B., Kanai M., Ferguson L., Campbell C., Kamatani Y., Okada Y., Sisodiya S. M., Cavalleri G. L., Koeleman B. P. C., Lerche H., Jehi L., Davis L. K., Najm I. M., Palotie A., Daly M. J., Busch R. M., Lal D., Feng Y. -C. A., Howrigan D. P., Abbott L. E., Tashman K., Cerrato F., Churchhouse C., Gupta N., Neale B. M., Berkovic S. F., Goldstein D. B., Lowenstein D. H., Cossette P., Cotsapas C., De Jonghe P., Dixon-Salazar T., Guerrini R., Hakonarson H., Heinzen E. L., Helbig I., Kwan P., Marson A. G., Petrovski S., Kamalakaran S., Stewart R., Weckhuysen S., Depondt C., Dlugos D. J., Scheffer I. E., Striano P., Freyer C., Krause R., May P., McKenna K., Regan B. M., Bellows S. T., Bennett C. A., Johns E. M. C., Macdonald A., Shilling H., Burgess R., Weckhuysen D., Bahlo M., O'Brien T. J., Todaro M., Stamberger H., Andrade D. M., Sadoway T. R., Mo K., Krestel H., Gallati S., Papacostas S. S., Kousiappa I., Tanteles G. A., Sterbova K., Vlckova M., Sedlackova L., Lassuthova P., Klein K. M., Rosenow F., Reif P. S., Knake S., Kunz W. S., Zsurka G., Elger C. E., Bauer J., Rademacher M., Pendziwiat M., Muhle H., Rademacher A., Van Baalen A., Von Spiczak S., Stephani U., Afawi Z., Korczyn A. D., Kanaan M., Canavati C., Kurlemann G., Muller-Schluter K., Kluger G., Hausler M., Blatt I., Lemke J. R., Krey I., Weber Y. G., Wolking S., Becker F., Hengsbach C., Rau S., Maisch A. F., Steinhoff B. J., Schulze-Bonhage A., Schubert-Bast S., Schreiber H., Borggrafe I., Schankin C. J., Mayer T., Korinthenberg R., Brockmann K., Dennig D., Madeleyn R., Kalviainen R., Auvinen P., Saarela A., Linnankivi T., Lehesjoki A. -E., Rees M. I., Chung S. -K., Pickrell W. O., Powell R., Schneider N., Balestrini S., Zagaglia S., Braatz V., Johnson M. R., Auce P., Sills G. J., Baum L. W., Sham P. C., Cherny S. S., Lui C. H. T., Barisic N., Delanty N., Doherty C. P., Shukralla A., McCormack M., El-Naggar H., Canafoglia L., Franceschetti S., Castellotti B., Granata T., Zara F., Iacomino M., Madia F., Vari M. S., Mancardi M. M., Salpietro V., Bisulli F., Tinuper P., Licchetta L., Pippucci T., Stipa C., Muccioli L., Minardi R., Gambardella A., Labate A., Annesi G., Manna L., Gagliardi M., Parrini E., Mei D., Vetro A., Bianchini C., Montomoli M., Doccini V., Marini C., Suzuki T., Inoue Y., Yamakawa K., Birute T., Ruta M., Algirdas U., Ruta P., Jurgita G., Ruta S., Sadleir L. G., King C., Mountier E., Caglayan S. H., Arslan M., Yapici Z., Yis U., Topaloglu P., Kara B., Turkdogan D., Gundogdu-Eken A., Bebek N., Ugur-Iseri S., Baykan B., Salman B., Haryanyan G., Yucesan E., Kesim Y., Ozkara C., Sheidley B. R., Shain C., Poduri A., Buono R. J., Ferraro T. N., Sperling M. R., Lo W., Privitera M., French J. A., Schachter S., Kuzniecky R. I., Devinsky O., Hegde M., Khankhanian P., Helbig K. L., Ellis C. A., Spalletta G., Piras F., Gili T., Ciullo V., Leu C., Stevelink R., Smith A.W., Goleva S.B., Kanai M., Ferguson L., Campbell C., Kamatani Y., Okada Y., Sisodiya S.M., Cavalleri G.L., Koeleman B.P.C., Lerche H., Jehi L., Davis L.K., Najm I.M., Palotie A., Daly M.J., Busch R.M., Lal D., Feng Y.-C.A., Howrigan D.P., Abbott L.E., Tashman K., Cerrato F., Churchhouse C., Gupta N., Neale B.M., Berkovic S.F., Goldstein D.B., Lowenstein D.H., Cossette P., Cotsapas C., De Jonghe P., Dixon-Salazar T., Guerrini R., Hakonarson H., Heinzen E.L., Helbig I., Kwan P., Marson A.G., Petrovski S., Kamalakaran S., Stewart R., Weckhuysen S., Depondt C., Dlugos D.J., Scheffer I.E., Striano P., Freyer C., Krause R., May P., McKenna K., Regan B.M., Bellows S.T., Bennett C.A., Johns E.M.C., Macdonald A., Shilling H., Burgess R., Weckhuysen D., Bahlo M., O'Brien T.J., Todaro M., Stamberger H., Andrade D.M., Sadoway T.R., Mo K., Krestel H., Gallati S., Papacostas S.S., Kousiappa I., Tanteles G.A., Sterbova K., Vlckova M., Sedlackova L., Lassuthova P., Klein K.M., Rosenow F., Reif P.S., Knake S., Kunz W.S., Zsurka G., Elger C.E., Bauer J., Rademacher M., Pendziwiat M., Muhle H., Rademacher A., Van Baalen A., Von Spiczak S., Stephani U., Afawi Z., Korczyn A.D., Kanaan M., Canavati C., Kurlemann G., Muller-Schluter K., Kluger G., Hausler M., Blatt I., Lemke J.R., Krey I., Weber Y.G., Wolking S., Becker F., Hengsbach C., Rau S., Maisch A.F., Steinhoff B.J., Schulze-Bonhage A., Schubert-Bast S., Schreiber H., Borggrafe I., Schankin C.J., Mayer T., Korinthenberg R., Brockmann K., Dennig D., Madeleyn R., Kalviainen R., Auvinen P., Saarela A., Linnankivi T., Lehesjoki A.-E., Rees M.I., Chung S.-K., Pickrell W.O., Powell R., Schneider N., Balestrini S., Zagaglia S., Braatz V., Johnson M.R., Auce P., Sills G.J., Baum L.W., Sham P.C., Cherny S.S., Lui C.H.T., Barisic N., Delanty N., Doherty C.P., Shukralla A., McCormack M., El-Naggar H., Canafoglia L., Franceschetti S., Castellotti B., Granata T., Zara F., Iacomino M., Madia F., Vari M.S., Mancardi M.M., Salpietro V., Bisulli F., Tinuper P., Licchetta L., Pippucci T., Stipa C., Muccioli L., Minardi R., Gambardella A., Labate A., Annesi G., Manna L., Gagliardi M., Parrini E., Mei D., Vetro A., Bianchini C., Montomoli M., Doccini V., Marini C., Suzuki T., Inoue Y., Yamakawa K., Birute T., Ruta M., Algirdas U., Ruta P., Jurgita G., Ruta S., Sadleir L.G., King C., Mountier E., Caglayan S.H., Arslan M., Yapici Z., Yis U., Topaloglu P., Kara B., Turkdogan D., Gundogdu-Eken A., Bebek N., Ugur-Iseri S., Baykan B., Salman B., Haryanyan G., Yucesan E., Kesim Y., Ozkara C., Sheidley B.R., Shain C., Poduri A., Buono R.J., Ferraro T.N., Sperling M.R., Lo W., Privitera M., French J.A., Schachter S., Kuzniecky R.I., Devinsky O., Hegde M., Khankhanian P., Helbig K.L., Ellis C.A., Spalletta G., Piras F., Gili T., Ciullo V., Commission of the European Communities, Medical Research Council (MRC), Tumienė, Birutė, Mameniškienė, Rūta, Utkus, Algirdas, Praninskienė, Rūta, Grikinienė, Jurgita, Samaitienė-Aleknienė, Rūta, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, University of Helsinki, Helsinki Institute of Life Science HiLIFE, and Department of Medical and Clinical Genetics
Subjects: 0301 basic medicine, Male, Multifactorial Inheritance, Epi25 Consortium, Databases, Factual, FEATURES, Genome-wide association study, Epilepsies, 3124 Neurology and psychiatry, Cohort Studies, Epilepsy, 0302 clinical medicine, Cost of Illness, 1ST SEIZURE, HISTORY, genetics, POPULATION, 11 Medical and Health Sciences, education.field_of_study, medicine.diagnostic_test, SCORES, Single Nucleotide, Biobank, 3. Good health, 17 Psychology and Cognitive Sciences, Genetic generalized epilepsy, Epilepsy, Generalized, Female, Partial, Cohort study, Human, medicine.medical_specialty, Population, European Continental Ancestry Group, Clinical Neurology, BIOBANK, Polymorphism, Single Nucleotide, epilepsy, genetic generalized epilepsy, common variant risk, Databases, 03 medical and health sciences, Genetic, Internal medicine, medicine, Journal Article, Genetics, Humans, Genetic Predisposition to Disease, Polymorphism, GENOME-WIDE ASSOCIATION, Generalized epilepsy, education, SEIZURE RECURRENCE, Factual, METAANALYSIS, Genetic testing, Neurology & Neurosurgery, RISK PREDICTION, Generalized, business.industry, 3112 Neurosciences, Common variant risk, Genetic Variation, Original Articles, medicine.disease, Comorbidity, Cost of Illne, Epilepsies, Partial, Genome-Wide Association Study, 030104 developmental biology, Neurology (clinical), Cohort Studie, business, 030217 neurology & neurosurgery
Abstract: See Hansen and Møller (doi:10.1093/brain/awz318) for a scientific commentary on this article. Using polygenic risk scores from a genome-wide association study in generalized and focal epilepsy, Leu et al. reveal a significantly higher genetic burden for epilepsy in multiple cohorts of people with epilepsy compared to population controls. Quantification of common variant burden may be valuable for epilepsy prognosis and treatment., Rare genetic variants can cause epilepsy, and genetic testing has been widely adopted for severe, paediatric-onset epilepsies. The phenotypic consequences of common genetic risk burden for epilepsies and their potential future clinical applications have not yet been determined. Using polygenic risk scores (PRS) from a European-ancestry genome-wide association study in generalized and focal epilepsy, we quantified common genetic burden in patients with generalized epilepsy (GE-PRS) or focal epilepsy (FE-PRS) from two independent non-Finnish European cohorts (Epi25 Consortium, n = 5705; Cleveland Clinic Epilepsy Center, n = 620; both compared to 20 435 controls). One Finnish-ancestry population isolate (Finnish-ancestry Epi25, n = 449; compared to 1559 controls), two European-ancestry biobanks (UK Biobank, n = 383 656; Vanderbilt biorepository, n = 49 494), and one Japanese-ancestry biobank (BioBank Japan, n = 168 680) were used for additional replications. Across 8386 patients with epilepsy and 622 212 population controls, we found and replicated significantly higher GE-PRS in patients with generalized epilepsy of European-ancestry compared to patients with focal epilepsy (Epi25: P = 1.64×10−15; Cleveland: P = 2.85×10−4; Finnish-ancestry Epi25: P = 1.80×10−4) or population controls (Epi25: P = 2.35×10−70; Cleveland: P = 1.43×10−7; Finnish-ancestry Epi25: P = 3.11×10−4; UK Biobank and Vanderbilt biorepository meta-analysis: P = 7.99×10−4). FE-PRS were significantly higher in patients with focal epilepsy compared to controls in the non-Finnish, non-biobank cohorts (Epi25: P = 5.74×10−19; Cleveland: P = 1.69×10−6). European ancestry-derived PRS did not predict generalized epilepsy or focal epilepsy in Japanese-ancestry individuals. Finally, we observed a significant 4.6-fold and a 4.5-fold enrichment of patients with generalized epilepsy compared to controls in the top 0.5% highest GE-PRS of the two non-Finnish European cohorts (Epi25: P = 2.60×10−15; Cleveland: P = 1.39×10−2). We conclude that common variant risk associated with epilepsy is significantly enriched in multiple cohorts of patients with epilepsy compared to controls—in particular for generalized epilepsy. As sample sizes and PRS accuracy continue to increase with further common variant discovery, PRS could complement established clinical biomarkers and augment genetic testing for patient classification, comorbidity research, and potentially targeted treatment.
Published: 2019
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49. Epilepsy surgery in tuberous sclerosis complex: early predictive elements and outcome

Author: Teutonico, F., Mai, R., Devinsky, O., Lo Russo, G., Weiner, H. L., Borrelli, P., Balottin, U., and Veggiotti, P.
Published: 2008
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50. Multiscale integration organizes hierarchical computation in human auditory cortex

Author: Neil A. Feldstein, Catherine A. Schevon, Edward M. Merricks, Guy M. McKhann, Irobunda I, Nima Mesgarani, Laura Kathleen Long, Devinsky O, Werner Doyle, Adeen Flinker, and Sam V. Norman-Haignere
Subjects: Hierarchy (mathematics), Computer science, Computation, Speech recognition, Auditory cortex
Abstract: To derive meaning from sound, the brain must integrate information across tens (e.g. phonemes) to hundreds (e.g. words) of milliseconds, but the neural computations that enable multiscale integration remain unclear. Prior evidence suggests that human auditory cortex analyzes sound using both generic acoustic features (e.g. spectrotemporal modulation) and category-specific computations, but how these putatively distinct computations integrate temporal information is unknown. To answer this question, we developed a novel method to estimate neural integration periods and applied the method to intracranial recordings from human epilepsy patients. We show that integration periods increase three-fold as one ascends the auditory cortical hierarchy. Moreover, we find that electrodes with short integration periods (~50-150 ms) respond selectively to spectrotemporal modulations, while electrodes with long integration periods (~200-300 ms) show prominent selectivity for sound categories such as speech and music. These findings reveal how multiscale temporal analysis organizes hierarchical computation in human auditory cortex.
Published: 2020
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