Biomarkers for treatment outcome in newly diagnosed epilepsy

• Main Author: Auce, P.
• Other Authors: Sills, G. J. ; Marson, A. G. M. ; Jorgensen, A. J.
• Published: University of Liverpool 2017
• Subjects: 616.85
• Online Access: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.722053

Introduction and aims Epilepsy is a common neurological condition and around 25% of patients are resistant to treatment with currently available drugs (Brodie et al., 2012). Currently there is only a limited ability to predict treatment outcome and no genome based biomarkers for treatment efficacy. The main aim for this thesis was to investigate clinical and genome based biomarkers for treatment response in newly diagnosed epilepsy as well as explore methodological aspects related to the assembly of a large scale international research cohort. Methods An EU-funded project entitled “Epilepsy Pharmacogenomics: delivering biomarkers for clinical use (EpiPGX)” was undertaken by a pan-European research consortium to explore genome-based biomarkers that could be used to individualize treatment of epilepsy. University of Liverpool led work on newly diagnosed epilepsy. Work presented in this thesis is solely based on this project. Cases with newly diagnosed epilepsy were either de-novo phenotyped or data was transferred from existing clinical databases. Analysis of clinical covariates using logistic and Cox regression, and a subsequent GWAS were performed. Methodological and data transfer quality aspects were assessed separately using descriptive statistics and Cohen's kappa and Lin’s coefficients. Results and Conclusion The following clinical factors were significantly associated with twelve month remission after application of first well tolerated antiepileptic drug: age at diagnosis, abnormal neurological examination, GTCs-only, epilepsy type, number of seizures before the treatment, MRI and EEG results. Heterogeneity of outcomes between cohorts, effect of mode of cases ascertainment was also demonstrated. Data quality assessment showed that simple variables can be robustly transferred between data bases whereas more complicated variables have a potential for introduction of bias. A GWAS was carried out on newly diagnosed cases with focal epilepsy and failed to identify any SNPs significantly associated with treatment outcome. Clinical factors associated with treatment outcome potentially can be useful in daily clinical practice when assessing patients with newly diagnosed epilepsy. Large scale multi-centre studies utilizing historical retrospective data are possible but prospective recruitment should be preferred. Sound methodology and quality assurance methods should be applied in future epilepsy pharmacogenetic research particularly involving large multi-centre cohorts.