Abstract

Genetic generalized epilepsies (GGE) are genetically determined, as their name implies and they are clinically characterized by generalized seizures involving both sides of the brain in the absence of detectable brain lesions or other known causes. GGEs are yet complex and are influenced by many different genetic and environmental factors. Methylation specific epigenetic marks are one of the players of the complex epileptogenesis scenario leading to GGE. In this study, we have set out to perform genome-wide methylation profiling to analyze GGE trios each consisting of an affected parent-offspring couple along with an unaffected parent. We have developed a novel scoring scheme within trios to categorize each locus analyzed as hypo or hypermethylated. This stringent approach classified differentially methylated genes in each trio and helped us to produce trio specific and pooled gene lists with inherited and aberrant methylation levels. In order to analyze the methylation differences from a boarder perspective, we performed enrichment analysis with these lists using the PANOGA software. This collective effort has led us to detect pathways associated with the GGE phenotype, including the neurotrophin signaling pathway. We have demonstrated a trio based approach to genome-wide DNA methylation analysis that identified individual and possibly minor changes in methylation marks that could be involved in epileptogenesis leading to GGE.

Highlights

  • We present pathway oriented genome-wide DNA methylation analyses related to 13 Genetic generalized epilepsies (GGE) trios which meet relevant quality control metrics (S1 Table)

  • We have focused on a novel enrichment analysis strategy by using a custom designed TbSSch for each CpG locus in individual trios

  • The relevant loci were mapped to associated genes and imputed with PANOGA protocol to analyze pathway specific variances

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Summary

Introduction

A trio based approach to genome-wide DNA methylation in epilepsy. OO, EE and SAUI had been fellows of TUBITAK-IntenC project

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