Whole exome sequencing-based testing of adult epilepsy in a Polish population
, 23, 32, 2, 4, 3, 5
Abstract
Aim of the study. Genetic panel testing in paediatric and mixed adult and children populations has demonstrated clinical utility and provided a diagnostic yield of 18–40%. The data on adult epilepsies is limited. We aimed to investigate the diagnostic yield and analyse genetic diagnoses in whole exome sequenced adult patients with epilepsies in Poland.
Material and methods. We recruited 151 patients from 42 clinical centres across Poland. The patients had a diagnosis of epilepsy/ seizures, were 18 or older at the time of the genetic testing, and did not have a genetic diagnosis. All patients were tested with whole exome sequencing after an initial testing with a panel of 47 epilepsy-related genes.
Results. We reached a diagnostic yield when considering pathogenic/probably pathogenic variants according to ClinVar of 8.6% (n = 13) and 17% (n = 26) when applying the American College of Medical Genetics (ACMG) criteria. Most patients had a pathogenic/probably pathogenic variant in epilepsy-related genes (54%), followed by potential epilepsy-related genes (19%), and neurodevelopment-associated epilepsy genes (15%).
Conclusions. Our study shows that whole exome sequencing-based testing reaches a slightly higher diagnostic yield that the traditional 300 gene panel. Genes related to childhood onset neurodevelopmental disorders and epilepsy should be considered as well.
Clinical implications/future directions. Patients may have had a diagnosis related to a childhood syndrome, but due to limited diagnostic possibilities, it was not possible to diagnose them in childhood. We would consider testing adult patients with epilepsy with whole exome or genome sequencing (or if not possible with a panel) in cases of a diagnosis of epilepsy with no hints suggesting secondary epilepsy, and especially with clinical features indicating a genetic epilepsy diagnosis, such as neurodevelopmental delay and early onset of seizures.
Keywords: epilepsygeneticswhole exome sequencingPolish population
References
- Ministerstwo Zdrowia. Mapy dla 30 grup chorób . Available at: http://www mpz mz gov pl/mapy-dla-30grup-chorob. 2018(17.4.2019).
- McKnight D, Bristow SL, Truty RM, et al. Multigene Panel Testing in a Large Cohort of Adults With Epilepsy: Diagnostic Yield and Clinically Actionable Genetic Findings. Neurol Genet. 2022; 8(1): e650.
- Borlot F, de Almeida BI, Combe SL, et al. Clinical utility of multigene panel testing in adults with epilepsy and intellectual disability. Epilepsia. 2019; 60(8): 1661–1669.
- Johannesen KM, Nikanorova N, Marjanovic D, et al. Utility of genetic testing for therapeutic decision-making in adults with epilepsy. Epilepsia. 2020; 61(6): 1234–1239.
- Smith L, Malinowski J, Ceulemans S, et al. Genetic testing and counseling for the unexplained epilepsies: An evidence-based practice guideline of the National Society of Genetic Counselors. J Genet Couns. 2023; 32(2): 266–280.
- Stefanski A, Calle-López Y, Leu C, et al. Clinical sequencing yield in epilepsy, autism spectrum disorder, and intellectual disability: A systematic review and meta-analysis. Epilepsia. 2021; 62(1): 143–151.
- Rochtus A, Olson HE, Smith L, et al. Genetic diagnoses in epilepsy: The impact of dynamic exome analysis in a pediatric cohort. Epilepsia. 2020; 61(2): 249–258.
- Badura-Stronka M, Wołyńska K, Winczewska-Wiktor A, et al. Validation of targeted next-generation sequencing panels in a cohort of Polish patients with epilepsy: assessing variable performance across clinical endophenotypes and uncovering novel genetic variants. Front Neurol. 2023; 14: 1316933.
- Scheffer IE, Berkovic S, Capovilla G, et al. ILAE classification of the epilepsies: Position paper of the ILAE Commission for Classification and Terminology. Epilepsia. 2017; 58(4): 512–521.
- Wang J, Lin ZJ, Liu L, et al. Epilepsy-associated genes. Seizure. 2017; 44: 11–20.
- Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009; 25(14): 1754–1760.
- Tischler G, Leonard S. biobambam: tools for read pair collation based algorithms on BAM files. Source Code for Biology and Medicine. 2014; 9(1).
- McKenna A, Hanna M, Banks E, et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010; 20(9): 1297–1303.
- McLaren W, Gil L, Hunt SE, et al. The Ensembl Variant Effect Predictor. Genome Biol. 2016; 17(1): 122.
- Katsnelson A, Auton A, Brooks LD, et al. 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature. 2015; 526(7571): 68–71.
- Chen S, Francioli L, Goodrich J, et al. A genome-wide mutational constraint map quantified from variation in 76,156 human genomes. Nature . 2024; 625(7993): 92–100.
- Jaganathan K, Kyriazopoulou Panagiotopoulou S, McRae JF, et al. Predicting Splicing from Primary Sequence with Deep Learning. Cell. 2019; 176(3): 535–548.e24.
- Cardoza B, Clarke A, Wilcox J, et al. Epilepsy in Rett syndrome: association between phenotype and genotype, and implications for practice. Seizure. 2011; 20(8): 646–649.
- McEneaney LJ, Tee AR. Finding a cure for tuberous sclerosis complex: From genetics through to targeted drug therapies. Adv Genet. 2019; 103: 91–118.
- Krey I, Platzer K, Esterhuizen A, et al. Current practice in diagnostic genetic testing of the epilepsies. Epileptic Disord. 2022; 24(5): 765–786.
