The potential impact of genotype-driven precision medicine for children with epilepsy

Symonds, Joseph Daniel (2019) The potential impact of genotype-driven precision medicine for children with epilepsy. PhD thesis, University of Glasgow.

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Printed Thesis Information: https://eleanor.lib.gla.ac.uk/record=b3921242

Abstract

Introduction:

The development and application of next generation sequencing (NGS) technology has led to an exponential rise in the number of genes and genetic variants associated with epilepsy. The detection of highly penetrant and damaging variants in some patients can be sufficient to provide an adequate explanation for the entire disease process. Particularly high yields from such diagnostic genetic testing are observed in cohorts of children who present with early onset seizures. Obtaining a genetic diagnosis can be helpful to families in terms of informing further reproductive decisions, providing answers, and preventing further costly investigations. Evidence is emerging that certain anti-epileptic therapies may be more effective than others in specific genetic epilepsies.

Aim:

The aim of this thesis is to explore the potential for genetically-guided therapy for children with epilepsy. This will be primarily achieved through describing the epidemiology of the genetic epilepsies of childhood, and through researching the evidence-base for gene-specific therapy.

Methods:

This is a mixed methods study. In chapter 5 The epidemiology of early childhood genetic epilepsy is described using a prospective whole Scotland population based national cohort. This includes all children presenting under three years of age presenting with new onset epilepsy over a defined time period (May 2014 to May 2017, n =315). These children were tested on a panel of 104 epilepsy-associated genes. In chapter 6 the potential for Whole Genome Sequencing (WGS) to identify further genetic diagnoses in deeply-phenotyped families is then explored in a separate cohort of children presenting in the West of Scotland with severe or drug-resistant epilepsy (n = 79). In chapter 4, a systematic review approach is used to identify any epilepsy-associated genes for which evidence exists to support a specific therapeutic approach. The results from this review considered in both cohorts. Chapter 7 describes a new genetic epilepsy due to SMC1A truncation and explores the potential for specific therapy in this condition. Chapter 8 evaluates whether sub-analysis of genetic data within a randomised controlled trial can be harnessed to identify patients most likely to respond to therapy.

Key results:

Epilepsy affects 1 per 383 children before their third birthday. In 22% of these children a single-gene cause can be identified. For 80% per cent of single-gene diagnoses in this group of patients there is some evidence to support a specific therapeutic approach. Evidence is variable in quality and nature. Between 1 in 2,000 and 1 in 2,300 of all children born are likely to have a genetically determined epilepsy for which there is currently available some evidence for a specific treatment choice. The majority of currently achievable genetic diagnoses are concentrated in a small number of genes, with genetic diagnoses beyond the 20 most common being extremely individually rare. Evidence to support specific therapeutic approaches is generally lacking in these rarer genetic epilepsies, particularly in those not associated with ion channel dysfunction. A stronger evidence base is required, and to generate this this will demand wide collaboration, and rigorous study design, and open access to pharmacogenomic data.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Keywords: Epilepsy, genetic, child, precision.
Subjects: R Medicine > RJ Pediatrics
Colleges/Schools: College of Medical Veterinary and Life Sciences
Supervisor's Name: Zuberi, Professor Sameer M.
Date of Award: 2019
Depositing User: Dr Joseph Symonds
Unique ID: glathesis:2019-77899
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 29 Jan 2020 13:12
Last Modified: 17 Nov 2022 11:31
Thesis DOI: 10.5525/gla.thesis.77899
URI: https://theses.gla.ac.uk/id/eprint/77899
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