Portal de Periódicos da CAPES

Heterogeneity of resting-state EEG features in juvenile myoclonic epilepsy and controls

2022; Oxford University Press; Volume: 4; Issue: 4 Linguagem: Inglês

10.1093/braincomms/fcac180

2632-1297

Amy Shakeshaft, Petroula Laiou, Eugenio Abela, Ioannis Stavropoulos, Mark P. Richardson, Deb K. Pal, Alessandro Orsini, Alice Howell, Alison Hyde, Alison McQueen, Almu Duran, Alok Gaurav, Amber Collingwood, Amy Kitching, Amy Shakeshaft, Anastasia Papathanasiou, Andrea Clough, Andrew Gribbin, Andrew Swain, Ann Needle, Anna Hall, Anna Smith, Anne Scott MacLeod, Asyah Chhibda, Beata Fonferko‐Shadrach, Bintou Camara, Boyanka Petrova, Carmel Stuart, Caroline Hamilton, Caroline Peacey, Carolyn Campbell, Catherine Cotter, Catherine Edwards, Catie Picton, Charlotte Busby, Charlotte Quamina, Charlotte Waite, Charlotte West, Ching Ching Ng, Christina Giavasi, Claire Backhouse, Claire Holliday, Claire Mewies, Coleen Thow, Dawn Egginton, Debbie Dickerson, Debbie Rice, Dee Mullan, Déirdre Daly, Dympna Mcaleer, Elena Gardella, Elma Stephen, Eve Irvine, Eve Sacre, Fan Lin, Gail Castle, Graham A. Mackay, Kheng Seang Lim, Hannah R. Cock, Heather Collier, Helen Cockerill, Helen Navarra, Hilda Mhandu, Holly Crudgington, Imogen Hayes, Ioannis Stavropoulos, Jacqueline Daglish, Jacqueline Smith, Jacqui Bartholomew, Janet Cotta, Javier Peña‐Ceballos, Jaya Natarajan, Jennifer Crooks, Jennifer M. Quirk, Jeremy D.P. Bland, J Sidebottom, Joanna Gesche, Joanne Glenton, Joanne Henry, John M. Davis, Julie Ball, Kaja Kristine Selmer, Karen Helton Rhodes, Kelly Holroyd, Kheng Seang Lim, Kirsty O’Brien, Laura Thrasyvoulou, Linetty Makawa, Lisa Charles, Mark P. Richardson, Liz Nelson, Lorna Walding, Louise Woodhead, Loveth Ehiorobo, Lynn D. Hawkins, Lynsey Adams, Margaret Connon, Marie Home, Mark D. Baker, Mark Mencias, Mark P. Richardson, M. Sargent, Marte Syvertsen, Matthew J. Milner, Mayeth Recto, Michael Chang, Michael O’Donoghue, Michael C. Young, Munni Ray, Naim Panjwani, Naveed Ghaus, Nikil Sudarsan, Nooria Said, William Owen Pickrell, Patrick Easton, Paul Frattaroli, Paul McAlinden, Rachel Harrison, Rachel Swingler, Rachel Wane, Rebecca Ramsay, Rikke S. Møller, R. J. S. McDowall, R. T. Clegg, Sal Uka, Sam White, Samantha Truscott, Sarah Francis, Sarah Tittensor, Sarah-Jane Sharman, Seo‐Kyung Chung, Shakeelah Patel, Shan Ellawela, Shanaz Begum, Sharon Kempson, Sonia Raj, Sophie Bayley, Stephen Warriner, Susan Kilroy, Susan MacFarlane, Thomas D. Brown, T Samakomva, Tonicha Nortcliffe, Verity Calder, Vicky Collins, Victoria A. Parker, Vivien Richmond, William Stern, Zena Haslam, Zuzana Šobíšková, Amit Agrawal, Amy B. Heagle, Andrea D. Praticò, Archana Desurkar, Arun Saraswatula, Bridget MacDonald, Choong Yi Fong, Christoph P. Beier, Danielle M. Andrade, Darwin Pauldhas, David A. Greenberg, David Deekollu, Deb K. Pal, Dina Jayachandran, Dora A. Lozsádi, Elizabeth Caruana Galizia, Fraser Scott, Guido Rubboli, Heather Angus‐Leppan, Inga Talvik, Inyan Takon, Jana Zárubová, Jeanette Koht, Julia Aram, Karen Lanyon, Kate Irwin, Khalid Hamandi, Lap Yeung, Lisa J. Strug, Mark I. Rees, Markus Reuber, Martin Kirkpatrick, Matthew D. Taylor, Melissa Maguire, Michalis Koutroumanidis, Muhammad Shamim Khan, Nick Moran, Pasquale Striano, Pronab Bala, Rahul Bharat, Rajesh K. Pandey, Rajiv Mohanraj, Rhys H. Thomas, Rosemary Belderbos, Sean Slaght, Shane Delamont, Shashikiran Sastry, Shyam Mariguddi, Siva Kumar, Sumant Kumar, Tahir Majeed, Uma Jegathasan, William Whitehouse,

Functional Brain Connectivity Studies

Abnormal EEG features are a hallmark of epilepsy, and abnormal frequency and network features are apparent in EEGs from people with idiopathic generalized epilepsy in both ictal and interictal states. Here, we characterize differences in the resting-state EEG of individuals with juvenile myoclonic epilepsy and assess factors influencing the heterogeneity of EEG features. We collected EEG data from 147 participants with juvenile myoclonic epilepsy through the Biology of Juvenile Myoclonic Epilepsy study. Ninety-five control EEGs were acquired from two independent studies [Chowdhury et al. (2014) and EU-AIMS Longitudinal European Autism Project]. We extracted frequency and functional network-based features from 10 to 20 s epochs of resting-state EEG, including relative power spectral density, peak alpha frequency, network topology measures and brain network ictogenicity: a computational measure of the propensity of networks to generate seizure dynamics. We tested for differences between epilepsy and control EEGs using univariate, multivariable and receiver operating curve analysis. In addition, we explored the heterogeneity of EEG features within and between cohorts by testing for associations with potentially influential factors such as age, sex, epoch length and time, as well as testing for associations with clinical phenotypes including anti-seizure medication, and seizure characteristics in the epilepsy cohort. P-values were corrected for multiple comparisons. Univariate analysis showed significant differences in power spectral density in delta (2-5 Hz) (P = 0.0007, hedges' g = 0.55) and low-alpha (6-9 Hz) (P = 2.9 × 10-8, g = 0.80) frequency bands, peak alpha frequency (P = 0.000007, g = 0.66), functional network mean degree (P = 0.0006, g = 0.48) and brain network ictogenicity (P = 0.00006, g = 0.56) between epilepsy and controls. Since age (P = 0.009) and epoch length (P = 1.7 × 10-8) differed between the two groups and were potential confounders, we controlled for these covariates in multivariable analysis where disparities in EEG features between epilepsy and controls remained. Receiver operating curve analysis showed low-alpha power spectral density was optimal at distinguishing epilepsy from controls, with an area under the curve of 0.72. Lower average normalized clustering coefficient and shorter average normalized path length were associated with poorer seizure control in epilepsy patients. To conclude, individuals with juvenile myoclonic epilepsy have increased power of neural oscillatory activity at low-alpha frequencies, and increased brain network ictogenicity compared with controls, supporting evidence from studies in other epilepsies with considerable external validity. In addition, the impact of confounders on different frequency-based and network-based EEG features observed in this study highlights the need for careful consideration and control of these factors in future EEG research in idiopathic generalized epilepsy particularly for their use as biomarkers.