Investigation of new strategies for identifying causal mechanisms in schizophrenia taking bioinformatics approaches beyond genome-wide association studies

Hubert, John 2023. Investigation of new strategies for identifying causal mechanisms in schizophrenia taking bioinformatics approaches beyond genome-wide association studies. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

The goal of the research presented here is to provide support towards finding true precision medicine for patients with schizophrenia. In ideal circumstances, and as hinted towards already within oncology (Le Tourneau et al., 2015), this would be to obtain quantitative information from the patient, and use this information to identify an effective treatment option. As the heritability of the genetic liability towards schizophrenia is around 80%, genetic studies are an ideal base to build individualised treatment options. GWA studies have successfully discovered over 150 loci associated with schizophrenia and have confirmed that the condition is polygenic, i.e. each risk variant in an individual’s genome has a small effect size, but there are a large number of these variants which contribute to the pathogenesis of schizophrenia. The explanation of how these variants contribute to the biological processes that cause schizophrenia is however, unknown.PRSs provide a metric to measure the genetic liability to any individual disorder and capture a large component of the genetic risk towards schizophrenia. In addition, studies using schizophrenia PRS have found genetic overlap with other disorders. If the PRS was designed to focus on specific genes/pathways, it could give a clearer insight into the biological mechanisms that cause schizophrenia. However, there are many genetic, statistical and computation problems when using multiple PRS across multiple traits. Therefore, I present SurPRSe, a bioinformatics workflow to produce robust gene-set specific PRS that can be compared across multiple traits. I use this method to investigate the relationship between schizophrenia, subcortical brain volume sizes and cognition.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Medicine
Date of First Compliant Deposit:	13 April 2023
Last Modified:	13 Apr 2023 11:07
URI:	https://orca.cardiff.ac.uk/id/eprint/158017

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