Using functional genetics and epigenetics to dissect the molecular architecture of schizophrenia
Date: 20 April 2020
Thesis or dissertation
University of Exeter
PhD in Medical Studies
Schizophrenia is a severe neuropsychiatric disorder which is within the top ten causes of disability in the developed world. While we currently do not fully understand the aetiology of schizophrenia, a wealth of genetic, epigenetic, and epidemiological evidence suggests a neurodevelopmental origin, and that dysregulation of the immune ...
Schizophrenia is a severe neuropsychiatric disorder which is within the top ten causes of disability in the developed world. While we currently do not fully understand the aetiology of schizophrenia, a wealth of genetic, epigenetic, and epidemiological evidence suggests a neurodevelopmental origin, and that dysregulation of the immune system and infection can play a role in aetiology. This has been supported throughout the last decade and the “big data” revolution. Genetic and epigenetic data gathered through genome and epigenome wide association studies, have identified over 100 genetic risk loci for schizophrenia. Further to this there have been a number of epidemiological studies examining the effect of environmental risk factors to schizophrenia. However, many of these genetic, epigenetic, and environmental risk factors have no clear mechanism by which they cause disease. Many of these studies published present evidence for the “risk factor” involvement but fail to validate their findings in model systems, to establish how these risk factors cause disease. The main aim of this thesis was to develop functional assays and methods to validate genetic, epigenetic, and environmental risk factors in human cellular based models to elucidate how these risks can contribute to disease. From this work I have developed a protocol for knocking out risk genes, and have identified a role for the schizophrenia risk gene AS3MT in neuronal development. I have also developed several pipelines to validate epigenome wide association studies, and link how changes in DNA methylation can affect gene expression, at both the regional level and at individual genomic loci. And finally, I have examined what effect, if any, the active component of cannabis, which is an established environmental risk factor for schizophrenia, has on the DNA methylome, to understand how environmental risk can cause disease. In summary, the work presented in this thesis represents the movement from large scale (epi)genetic analysis and statistics to functional lab validation. This thesis contains several methods for the functional validation of identified (epi)genetic risk loci and risk factors for schizophrenia in a cellular model. From this we can now begin to explore how these changes in genetics, epigenetics, and environmental risk factors biologically link to the development and progression of schizophrenia and other neuropsychiatric disorders.
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