Single-cell RNA-sequencing in epilepsy; discovery of cell-types, pathways, and drug targets
File(s)
Author(s)
Abouzeid, Maya
Type
Thesis
Abstract
Epilepsy is a complex neurological disorder, affecting millions of people worldwide. It is characterised by spontaneous seizures caused by hyperexcitability of neurones in the brain. There is a large unmet need for new epilepsy therapeutic strategies, with one in three patients experiencing uncontrolled seizures despite medication. This thesis explores the cellular and molecular landscape of epilepsy at a single-cell level using single-nucleus RNA sequencing, offering greater resolution to the diverse cell-types involved in epilepsy. Using tissue from three mouse models of epilepsy; Pilocarpine induced status epilepticus, Self-Sustaining status epilepticus, Focal Cortical Dysplasia, and two human epilepsies; Hippocampal Sclerosis, and Focal Cortical Dysplasia, this work aimed to identify converging signatures across multiple forms of epilepsy and brain regions.
Using an optimised bioinformatic pipeline, this work identified differentially expressed genes (DEGs) in epilepsy, providing insights into the transcriptional and epigenetic changes associated with the disease state. Functional enrichment analyses revealed pathways implicated in neuronal excitability and neuroinflammation, emphasizing the role of glial cells as well as neurons in epilepsy pathology.
These analyses were then integrated with epilepsy GWAS and rare-variant analyses, to associate epilepsy risk with these transcriptional changes. A convergent signature was identified in astrocytes across both monogenic and polygenic epilepsies in both mouse and human forms of epilepsy. Perturbation datasets were integrated with the DEGs to predict potential regulators of epilepsy that could be targeted for treatment. With a focus on drug repurposing, these targets were intersected with interaction databases to identify candidate drugs for the treatment of epilepsy, focusing on disease modification. We highlight predicted
2 targets with pre-approved molecules, some which have been previously shown to be effective in epilepsy. This work enhances our understanding of epilepsy at a single-cell level, highlights the heterogeneity of the disease, identifies associated pathways, and points to potential therapeutic targets.
Using an optimised bioinformatic pipeline, this work identified differentially expressed genes (DEGs) in epilepsy, providing insights into the transcriptional and epigenetic changes associated with the disease state. Functional enrichment analyses revealed pathways implicated in neuronal excitability and neuroinflammation, emphasizing the role of glial cells as well as neurons in epilepsy pathology.
These analyses were then integrated with epilepsy GWAS and rare-variant analyses, to associate epilepsy risk with these transcriptional changes. A convergent signature was identified in astrocytes across both monogenic and polygenic epilepsies in both mouse and human forms of epilepsy. Perturbation datasets were integrated with the DEGs to predict potential regulators of epilepsy that could be targeted for treatment. With a focus on drug repurposing, these targets were intersected with interaction databases to identify candidate drugs for the treatment of epilepsy, focusing on disease modification. We highlight predicted
2 targets with pre-approved molecules, some which have been previously shown to be effective in epilepsy. This work enhances our understanding of epilepsy at a single-cell level, highlights the heterogeneity of the disease, identifies associated pathways, and points to potential therapeutic targets.
Version
Open Access
Date Issued
2024-07-10
Date Awarded
01/10/2024
Advisor
Johnson, Michael
Srivastava, Prashant
Publisher Department
Department of Brain Sciences
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)