| Summary: | Huntington’s Disease (HD) is an incurable neurodegenerative disease caused by the CAG expansion in the Huntingtin gene. Although its genetic cause is well-defined, the mechanism leading to HD pathology is poorly understood. This work hypothesises that in silico drug repurposing (ISDR) through transcriptional signature matching can deliver mechanistic insights and identify repurposable therapeutics for HD. Herein, I performed a novel benchmarking of three signature-matching algorithms, by incorporating noise into gene expression data. I analysed bulk and single-nuclei RNA-seq from differentiated stem cell and post-mortem HD models to reveal large transcriptional variability across cell types and CAG lengths. I interrogated Connectivity Map using HD signatures to identify phenocopying or reversing compounds. Notably, epigenetic modulators displayed contrasting effects with the transcriptome of short and long HD CAG expansions, suggesting distinct mechanisms occurring across mutation lengths. Together, this thesis contributes evidence to suggest a two-stage mechanism in HD progression, demonstrating the applicability of ISDR towards HD.
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