Methylomic and transcriptomic profiling of the schizophrenia brain

Schizophrenia is a severe psychiatric disorder that affects more than twenty-one million people worldwide, contributing significantly to the global burden of disease. A growing body of genetic, epigenetic and epidemiological evidence suggests that schizophrenia has its origins during neurodevelopment and that dysregulation of the immune system and infection may play a role in disease etiology. Twin and family studies have highlighted a considerable heritable component to schizophrenia; however the role of genetic variation in the etiology of the disorder is complex. In the majority of cases, susceptibility is attributed to the combined action of multiple common genetic risk variants of low penetrance. Improved understanding about the biology of the genome has led to increased interest in the role of non-sequence-based variation in the etiology of neurodevelopmental phenotypes, including schizophrenia. The notion that epigenetic processes and gene expression dysregulation are involved in the onset of schizophrenia is supported by recent studies of disease-discordant monozygotic twins, clinical sample cohorts, and post-mortem brain tissue. To date, however, studies characterizing schizophrenia-associated methylomic and transcriptomic variation in the brain have been limited by small sample number or the assessment of a single brain region. The main aim of this thesis was to undertake a comprehensive study of genomic variation across four brain regions in schizophrenia. The results provide further support for a neurodevelopmental origin to schizophrenia, as well as a role of the immune system on schizophrenia etiology. My analyses also suggest that epigenetic variation associated with polygenic burden for schizophrenia might play a role in the disease. In summary, the work presented in this thesis represents the first analysis of epigenetic and gene expression variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with etiological variation in complex disease.