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Integrated Analysis of Genetic Variation, Gene Expression and Methylation Changes in Epilepsy

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Integrated Analysis of Genetic Variation, Gene Expression and Methylation Changes in Epilepsy

Table of Contents

Background

Epilepsy is a neurological disorder characterized by recurrent seizures caused by abnormal brain activity. While seizures are the hallmark of epilepsy, not all seizures are due to epilepsy. Idiopathic epilepsy presents only with seizures, while in symptomatic epilepsy, seizures are a sign of an underlying brain condition. Studies have shown that epileptic activity can result in significant behavioral and cognitive impairments. These cognitive and personality deficiencies are strongly linked to the duration and frequency of seizures, as well as earlier age of onset of epilepsy.

Genetic factors play a significant role in epilepsy with over 500 genes linked to the disorder. Several studies have identified specific gene mutations associated with different types of epilepsy. Epigenetic changes, such as DNA methylation, have also been found to play a role in epilepsy and several differentially methylated genes have been linked to specific types of epilepsy. Despite these findings, over 30% of epilepsy patients cannot effectively manage their seizures with medication.

Objectives

  • To analyse genetic variation and gene expression on temporal lobe epilepsy (TLE) transcriptopmic data
  • To investigate the methylation changes in TLE whole genome bisulphite sequence data

Methods

Variant calling and analysis of differentially expressed genes (DEGs) were carried out on two sets of temporal lobe epilepsy (TLE) transcriptomic data from. Bisulfite mapping, methylation calling, and differential methylation (DMR) analysis were also conducted on two sets of TLE whole genome bisulphite sequence (WGBS) data. For RNA-seq variant calling, the Haplotypecaller tools from GATK4 were utilized, and variant annotation was performed using ANNOVAR. Differential expression analysis was executed using DESeq2 in R, with annotation facilitated by the AnnotationDbi and org.Hs.eg.db packages. DMR analysis of bisulfite sequences was accomplished using the Bismark tool. Bisulphite mapping and methylation calling of the TLE WGBS data were carried out using Bismark tool, while DMRichR was used to perform differential methylation analysis.

Analysis workflow

Results

References

  • [Epileptic encephalopathies] - PubMed. (n.d.). Retrieved January 17, 2023, from https://pubmed.ncbi.nlm.nih.gov/28524219/
  • Benini, R., Roth, R., Khoja, Z., Avoli, M., & Wintermark, P. (2016). Does angiogenesis play a role in the establishment of mesial temporal lobe epilepsy? International Journal of Developmental Neuroscience, 49(1), 31–36.
  • Martins-Ferreira, R., Leal, B., Chaves, J., Li, T., Ciudad, L., Rangel, R., Santos, A., Martins da Silva, A., Pinho Costa, P., & Ballestar, E. (2022). Epilepsy progression is associated with cumulative DNA methylation changes in inflammatory genes. Progress in Neurobiology, 209. https://doi.org/10.1016/J.PNEUROBIO.2021.102207
  • Wang K, Li M, Hakonarson H. ANNOVAR: Functional annotation of genetic variants from next-generation sequencing data Nucleic Acids Research, 38:e164, 2010
  • Zhang, W., Wang, H., Liu, B., Jiang, M., Gu, Y., Yan, S., Han, X., Hou, A. Y., Tang, C., Jiang, Z., Shen, H., Na, M., & Lin, Z. (2021). Differential DNA Methylation Profiles in Patients with Temporal Lobe Epilepsy and Hippocampal Sclerosis ILAE Type I. Journal of Molecular Neuroscience, 71(9), 1951–1966. https://doi.org/10.1007/s12031-020-01780-9

Acknowledgment

The authors thank the National Institutes of Health (NIH) Office of Data Science Strategy (ODSS) for their immense support before and during the April 2024 Omics codeathon organised by the African Society for Bioinformatics and Computational Biology (ASBCB).

Team

Marion Nyaboke - MSc. Bioinformatics

Shamim Osata -MSc. Bioinformatics

Modibo K. Goita - MSc. Bioinformatics

George E. Kuodza - MD

Jonathan Kalami - BSc. Biochemistry

Ifeoluwa H. Ojelabi - MD

Awe Olaitan - African Society for Bioinformatics and Computational Biology, South Africa

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