Chen, Zhongbo; (2023) Using functional genomics and transcriptomics to further the understanding of neurogenetic disorders. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

The last decade has seen significant improvements in the diagnosis of neurogenetic disorders. Despite this, the diagnostic yield for a genetic neurological condition remains low. One such archetypal neurogenetic disorder is hereditary ataxia, in which progressive incoordination from cerebellar dysfunction presents as the predominant symptom. Despite an increasing plethora of genes found to be associated with this heterogeneous condition, 75% of patients remain undiagnosed after whole genome sequencing (WGS). This thesis aims to leverage the improved granularity and precision of multi-omics data, initially through functional genomic annotation and then through post-mortem brain tissue transcriptomics, to inform our knowledge of the underlying genetic architecture of ataxia. In the first part, I have developed and validated a novel genomic annotation to identify and prioritise human-specific genes and transcripts of relevance to neurodegenerative diseases. This highlighted genes in which pathogenic variants are known to cause ataxia. In the second part, I have integrated this novel annotation with ∼300 other genic features from publicly available multi-omics data to capture information about each gene’s structure, variation, expression and protein products. I used this information to characterise ataxia genes, verifying the results using WGS data derived from 2,182 patients with ataxia enrolled in the 100,000 Genomes Project. These findings suggested that naturally occurring short tandem repeats within known ataxia genes could be candidate pathogenic loci in an unsolved cohort. In the last part, I have compared post-mortem cerebellar and frontal cortex tissue bulk RNA-sequencing data from 23 ataxia patients and 23 matched controls. I found distinct transcriptional alterations between cerebellar and frontal cortices and across different disease pathologies, and unexpected enrichment of immune-associated pathways in disease. These findings provide a map of transcriptomic changes in ataxia. Taken together, these results provide a novel integrated approach to understanding the underlying pathogenesis of hereditary ataxia, a key step for improving its diagnostic yield and the identification of disease-modifying treatments.

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