Investigating the contribution of rare coding variants to schizophrenia

Chick, Sophie 2025. Investigating the contribution of rare coding variants to schizophrenia. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

Schizophrenia is a severe and disabling psychiatric disorder associated with positive symptoms (delusions and hallucinations), negative symptoms (loss of motivation and emotional expression), and cognitive symptoms (memory and attention deficits). Genetic factors make a substantial contribution to the liability of schizophrenia, including rare genetic variants with large effects on risk. To date, sequencing studies of rare variants have significantly implicated 32 genes in schizophrenia, whose functions contribute to our existing knowledge of the neurobiology of schizophrenia and provide insight into its molecular mechanisms. However, not all of these associations have been replicated in independent samples. Furthermore, it has been reported that the burden of rare variants which lies outside these genes in individuals with schizophrenia is consistent with additional genes that are yet to be discovered. In this thesis, I analyse a new schizophrenia case-control dataset to replicate existing rare variant gene discovery, and find that the majority of published genes are consistent with genuine association with schizophrenia. The exception to this is CACNA1G, where my results align with those of a previous replication study in suggesting that it does not represent a genuine risk gene. Through combining the new case-control sample with previously published data, I then undertake a meta-analysis which implicates two previously-associated genes at a greater level of statistical significance (STAG1 and ZNF136), and newly implicates six novel genes. In my final chapter, I perform a comparison of tools used to predict the pathogenicity of missense variants in rare variant association studies, and identify a best-performing combination of predictors, which when applied to the meta-analysis sample is able to implicate a further five novel schizophrenia risk genes. All together, these analyses implicate rare variant burden in 11 novel genes as risk factors in schizophrenia, and provide a number of insights into the biological mechanisms underlying schizophrenia.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Schools > Medicine
Date of First Compliant Deposit:	11 March 2026
Last Modified:	11 Mar 2026 14:24
URI:	https://orca.cardiff.ac.uk/id/eprint/185668

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