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2. Brain language networks and cognitive outcomes in children with frontotemporal lobe epilepsy.

Author

Hüsser, Alejandra M., Vannasing, Phetsamone, Tremblay, Julie, Osterman, Bradley, Lortie, Anne, Diadori, Paola, Major, Philippe, Rossignol, Elsa, Roger, Kassandra, Fourdain, Solène, Provost, Sarah, Maalouf, Yara, Dang Khoa Nguyen, and Gallagher, Anne

Subjects
LARGE-scale brain networks, CEREBRAL dominance, FRONTAL lobe, TEMPORAL lobe epilepsy, EPILEPSY, NEAR infrared spectroscopy, NEUROPSYCHOLOGICAL tests, NEUROLINGUISTICS, NEUROPSYCHOLOGY
Abstract

Introduction: Pediatric frontal and temporal lobe epilepsies (FLE, TLE) have been associated with language impairments and structural and functional brain alterations. However, there is no clear consensus regarding the specific patterns of cerebral reorganization of language networks in these patients. The current study aims at characterizing the cerebral language networks in children with FLE or TLE, and the association between brain network characteristics and cognitive abilities. Methods: Twenty (20) children with FLE or TLE aged between 6 and 18 years and 29 age- and sex-matched healthy controls underwent a neuropsychological evaluation and a simultaneous functional near-infrared spectroscopy and electroencephalography (fNIRS-EEG) recording at rest and during a receptive language task. EEG was used to identify potential subclinical seizures in patients. We removed these time intervals from the fNIRS signal to investigate language brain networks and not epileptogenic networks. Functional connectivity matrices on fNIRS oxy-hemoglobin concentration changes were computed using cross-correlations between all channels. Results and discussion: Group comparisons of residual matrices (=individual task-based matrix minus individual resting-state matrix) revealed significantly reduced connectivity within the left and between hemispheres, increased connectivity within the right hemisphere and higher right hemispheric local efficiency for the epilepsy group compared to the control group. The epilepsy group had significantly lower cognitive performance in all domains compared to their healthy peers. Epilepsy patients' local network efficiency in the left hemisphere was negatively associated with the estimated IQ (p = 0.014), suggesting that brain reorganization in response to FLE and TLE does not allow for an optimal cognitive development. [ABSTRACT FROM AUTHOR]

Published
2023
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4. Pharmacogenetic testing in pediatric neurology: a pragmatic study evaluating clinician and patient perceptions

Author

Pépin, Marie-Anne, primary, Otis, Anne-Sophie, additional, Tremblay, Zoë, additional, Boulé, Marianne, additional, Lebel, Denis, additional, Major, Philippe, additional, Lortie, Anne, additional, Pinchefsky, Elana, additional, Rossignol, Elsa, additional, Carleton, Bruce, additional, Bussières, Jean-François, additional, and Métras, Marie-Élaine, additional

Published
2022
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6. Recognition of Psychogenic Versus Epileptic Seizures Based on Videos

Author

Birca, Veronica, Keezer, Mark R., Chamelian, Laury, Lortie, Anne, and Nguyen, Dang K.

Abstract

ABSTRACTObjective:Ictal semiology interpretation for differentiating psychogenic nonepileptic seizures (PNESs) and epileptic seizures (ESs) is important for the institution of appropriate treatment. Our objective was to assess the ability of different health care professionals (HCPs) or students to distinguish PNES from ES based on video-recorded seizure semiology.Methods:This study was designed following the Standards for Reporting of Diagnostic Accuracy Studies (STARD) guidelines. We showed in a random mix 36 videos of PNES or ES (18 each) and asked 558 participants to classify each seizure. The diagnostic accuracy of various groups of HCPs or students for PNES versus ES was assessed, as well as the effect of patient age and sex. Measures of diagnostic accuracy included sensitivity, specificity, and area under the curve (AUC).Results:The descending order of diagnostic accuracy (AUC) was the following (p ≤ 0.001): (1) neurologists and epileptologists; (2) neurology residents; (3) other specialists and nurses with experience in epilepsy; and (4) undergraduate medical students. Although there was a strong trend toward statistical difference, with AUC 95% confidence intervals (CIs) that were not overlapping, between epileptologists (95% CI 93, 97) compared to neurologists (95% CI 88, 91), and neurologists compared to electroencephalography technicians (95% CI 82, 87), multiple pairwise comparisons with the conservative Tukey–Kramer honest significant difference test revealed no statistical difference (p = 0.25 and 0.1, respectively). Patient age and sex did not have an effect on diagnostic accuracy in neurology specialists.Conclusion:Visual recognition of PNES by HCPs or students varies overall proportionately with the level of expertise in the field of neurology/epilepsy.

Published
2022
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7. 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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