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Gene expression regulation in immune cell dysfunction in multiple sclerosis

Hrastelj, James ORCID: 2023. Gene expression regulation in immune cell dysfunction in multiple sclerosis. PhD Thesis, Cardiff University.
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Multiple sclerosis (MS) is an inflammatory disease of the central nervous system (CNS). Genome-wide association studies in MS have identified over 200 genetic risk variants, but most are non-coding. Non-coding genetic variants are known to control gene expression in specific cells and contexts, but the tissues whose functions are altered by the MS genetic risk variants are largely unknown. CSF CD4+ T-cells play a key role in CNS immune surveillance, but gene expression analysis of CNS CD4+ T-cells has been limited. Building on the clinical research infrastructure in Cardiff a method was developed that obtained RNA from low numbers of CD4+ T-cells from cerebrospinal fluid (CSF) from 111 of 135 consenting patients. Gene expression profiles of CSF CD4+ T-cells were compared with those of blood CD4+ T-cells from the same patients using RNA-seq. Thousands of differentially expressed genes were identified in controls as well as MS, highlighting many functional differences. Expression quantitative trait locus analysis revealed 93 genes with expression associated with a genetic variant (eGenes). 29 eGenes may be specific to CSF CD4+ T-cells. Summary data-based Mendelian randomisation revealed no genes reaching genome-wide significance for association with MS, but seven genes with nominal significance. This work has developed a technically challenging pipeline to further our understanding of CNS immune surveillance by CD4+ T-cells in health and in MS. Building on this study, future work could provide a more complete understanding of the genetic aetiology of MS and other neurological disorders by 1) exploring novel sensitive data analysis methods to identify eGenes and prioritise potentially causal genes, 2) expanding analysis to other cell types and activation states (freshly collected or derived from induced pluripotent stem cells), 3) performing multiplex analysis combining gene expression with chromatin accessibility studies and proteomics, 4) testing for association between gene expression and longitudinal clinical data.

Item Type: Thesis (PhD)
Date Type: Completion
Status: Unpublished
Schools: Medicine
Date of First Compliant Deposit: 8 February 2024
Last Modified: 08 Feb 2024 10:16

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