Genetic Diagnosis and Personalized Medicine for Patients With Epilepsy

Background Epilepsy is a common neurological disorder. It affects 50 million people worldwide and has the highest incidence in pediatric age. According to the latest classification of the ILAE (International League against Epilepsy), epilepsies are divided into lesional (symptomatic) and non-lesional/genetic forms. Symptomatic causes of epilepsy may include scarring, tumors, strokes, and brain developmental disorders such as dysplasias. In approximately 30% of epilepsies a genetic cause of epilepsy can be hypothesized. Since the identification of the first epilepsy gene in 1995, over the next 25 years over 500 genes associated with epilepsy have been identified. The importance of many genes and many gene variants identified in many genes is not yet clear and the mutations identified in different genes require confirmation with functional studies and confirmation on larger series of patients. Furthermore, the genetic defect underlying many patients with epilepsy remains unknown to this day, despite a high level of gene sequencing effort. Molecular studies on these genes have demonstrated how pathogenic variants on these genes determine a protein dysfunction that can cause neuronal hyperexcitability and pathological synchronization of neuronal networks leading to epileptic seizures and brain dysfunction. A notable complication in the field of epilepsy genetics is represented by the fact that the concept of a gene/a disease is valid only in a few cases, as there is a high phenotypic and genotypic heterogeneity so that a gene can present different types of epilepsy even within the same family. This means that there is a complex multigenic and multifactorial genetic substrate for which the impact of a specific genetic variant is conditioned by variants of other genes. This concept is particularly valid for the most common epileptic forms such as idiopathic generalized epilepsies. The integration of genetic analysis with epileptological characterization in clinical practice is increasingly crucial in defining a clear molecular diagnosis in patients whose disease cause would otherwise remain unknown, and potentially allows avoiding other unnecessary diagnostic investigations. It is therefore expected that this will lead to optimizing clinical management and reducing overall costs over time. The genetic finding can constitute a useful biomarker for defining the outcome of the disease and for guiding clinical decisions such as the best choice of therapy. Despite the advantages, before starting the genetic testing process, patients and their family members should be informed about the ethical issues that may arise from genetic testing, the technical limitations, legal aspects and costs of genetic investigation. Aim of the study Characterization of patients with epilepsy recruited at the Hospital Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico in Milan (Italy) and analysis with exome NGS sequencing of patients with the highest probability of genetic diagnosis with exome (use of a probability score) Endpoints of study are the following: 1. Identification of the genetic cause of the forms of genetic epilepsies with the highest probability of molecular diagnosis with exome 2. Clinical-instrumental and epileptological characterization according to the ILAE classification of patients with epilepsy followed at the Fondazione IRCCS Ca' Granda Fondazione Ospedale Maggiore Policlinico 3. Correlation of clinical and instrumental parameters (in particular EEG and neuropsychological) of epilepsy recorded on the database with etiology, outcome and response to therapy

Study design Non-pharmacological (diagnostic) interventional, single-center, biological, observational, prospective Interventions 1. Collection of clinical and instrumental data of patients with epilepsy at first outpatient visit (time 0) and at one-year follow-up: age, gender, education, age of onset of seizures, new diagnosis/check-up, type of seizure according to the ILAE classification, type of epilepsy according to the ILAE classification, frequency of epileptic seizures, etiology, for cases with a genetic/probably genetic etiology application of an ad hoc score to determine the probability of a positive outcome for exome research, neurological objectivity, presence of comorbidities, parameters of EEG background activity, parameters relating to interictal EEG anomalies, parameters relating to critical EEG anomalies, magnetic resonance parameters, therapies used, effectiveness of therapies used, side effects of therapies, duration of therapy, dosages of therapy, neuropsychological and psychological outcome (score on standard tests/questionnaires administered according to age as required by the standard of care), functional outcome expressed with the modified Rankin scale; clinical and instrumental data will also be collected for sick or healthy parents of patients with epilepsy who will be identified for the exome analysis of the trio (proband + parents) during the recruitment phase (not at follow-up), while they will not be collected sensitive data relating to the parents of patients who did not undergo an exome (observational part of the study). 2. Qualitative evaluation of the EEG according to the ACNS guidelines and whenever possible through quantitative analysis of the EEG parameters at time 0 and at 1 year follow up. In the quantitative analysis, ad hoc algorithms will be used to extract the temporal and frequency domain characteristics of the EEG traces. 3. Sequencing and analysis of the exome of at least 30 patients and their natural parents (plus any other first-degree relatives affected by epilepsy or genetic condition related to epilepsy) for a total of at least 90 exomes. With the exception of WES sequencing, the other diagnostic-evaluative procedures are part of the normal clinical management of patients. Genotype-phenotype correlations The WES will be evaluated in relation to the clinical picture on the basis of a close collaboration between clinicians (neurologists), biologists, geneticists, bioinformatics involved in the project. The acquired data will also be used to define the risk of recurrence, prognosis, monitoring of complications and identification of possible targeted treatments.