Psychiatry - Theses
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ItemFunctional brain networks in schizophrenia: mapping connectivity and topology at early and late psychotic illness stages( 2017)Schizophrenia is a severe mental disorder that is characterised by symptoms including hallucinations, delusions and disorganized thought. The cause of schizophrenia remains unknown; however, it is thought that a combination of genetics, environment and altered neurobiology play a role in the emergence and perpetuation of the disorder. Accumulating evidence suggests that disrupted brain network connectivity may in part underlie the pathophysiology of psychosis, and that network connectivity is to some extent genetically determined and heritable. However, there is still much to be learned surrounding the nature of network abnormalities and how they differ in early versus late psychosis. Exploring the underlying neurobiology at discrete clinical stages of psychotic illness creates a framework to evaluate the biological factors that may be contributing to the progression from early psychosis, to more advanced chronic stages of the disorder. This thesis used resting-state functional magnetic resonance imaging (fMRI) to characterise network functional connectivity and topology in early and late psychosis, as well as in a group of unaffected family members (UFM) of individuals with schizophrenia. Resting-state fMRI is a well validated and sensitive tool for probing the intrinsic functional integrity of the brain. Specifically, this thesis used a data-driven approach to map the temporal coherence of fMRI time series (functional connectivity) across the whole brain. To complement the resting-state functional connectivity (rs-FC) analysis, this thesis used graph theory to explore functional network topology. Network topology describes that brains ability to maintain a balance between local processing speed and global integration of information. These methodological approaches were used to investigate network abnormalities in three groups relative to healthy controls; a first-episode psychosis (FEP) group, a treatment-resistant schizophrenia (TRS) group and a group of UFM. This thesis aimed to investigate 1) whether rs-FC and network topology was abnormal in the early FEP stage of schizophrenia relative to healthy controls at two time-points (baseline and at 12-months follow-up); 2) whether rs-FC and network topology was impaired in a chronic TRS group relative to healthy controls; 3) whether abnormal rs-FC and network topology was evident in a group of UFM, and whether any network measure could be characterised as a marker of risk or resilience to psychosis in UFM. Firstly, results showed no evidence of abnormal rs-FC or topology in FEP individuals relative to healthy controls at baseline, or at the 12-months follow-up. Further, longitudinal changes in network properties over a 12-month period did not significantly differ between FEP individuals and healthy controls. Secondly, this thesis found widespread reductions in rs-FC in the TRS group that predominantly involved temporal, occipital and frontal brain regions. The TRS group also showed reduced global network efficiency and increased local efficiency relative to controls. Thirdly, TRS and UFM shared frontal and occipital rs-FC deficits, representing a ‘risk’ endophenotype. Additional reductions in frontal and temporal rs-FC appeared to be associated with risk that precipitates psychosis in vulnerable individuals, or may be due to other illness-related effects, such as medication. Functional brain networks were more topologically resilient in UFM compared to TRS, which may protect UFM from psychosis onset despite familial liability. Together, the body of work presented in this thesis provides a number of novel and unique findings that serve to advance the current state of knowledge regarding the pathophysiology and heritability of psychosis. Specifically, the work demonstrated that the latest most severe stage of psychosis, TRS, is associated with widespread reduced rs-FC, and that milder, yet similar patterns of dysconnectivity were observed in UFM, implying a genetic root to some, but not all of the observed network abnormalities. Network topology differed relative to healthy controls in both UFM and TRS patients, suggesting that functional network architecture is also disturbed in late psychosis, and again, results suggest a genetic/shared environmental basis for this characteristic. Our finding of no significant difference in rs-FC or network topology in our FEP sample suggests that there is a differentiation between biological processes occurring in early and late psychosis with a subgroup of individuals’ rs-FC potentially being unaffected in the FEP stage.
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ItemPiecing the puzzle together: white, grey and PET imaging across the course of schizophrenia( 2018)Schizophrenia is a severe and debilitating brain disorder, marked by abnormalities in perception, mood and cognition. Despite copious evidence indicating that brain changes are involved in the pathophysiology of schizophrenia, well-replicated neuroimaging markers that track disease progression or reveal therapeutic targets have not been identified. This may be due to regional and unimodal approaches applied in previous neuroimaging studies of schizophrenia, providing limited context to interpret neuropathology; imbedded in a complex multimodal and dynamic system. Furthermore, as neuropathology could evolve over the course of schizophrenia, duration of illness or illness stage reflects a key source of heterogeneity across prior studies. While grey matter deficits are thought to be progressive, it remains unclear whether white matter abnormalities vary as a function of illness stage and whether these changes are regionally linked to structural grey matter loss in anatomically adjacent regions, thus pointing to related aetiological processes. Furthermore, the mechanisms underlying structural grey and white matter deficits remain unknown. Recent evidence points to elevated microglial activation - an inflammatory response in the central nervous system, which might cause secondary neuronal degeneration, decreased neurogenesis and synaptic dysfunction, and may thus underlie structural brain changes in schizophrenia. This thesis applies multimodal imaging to address gaps in our knowledge of brain changes in schizophrenia, through evaluating three primary questions: (i) Do white matter disruptions deteriorate as a function of illness stage over the course of schizophrenia? (ii) Are white matter deficits regionally linked to the well-characterised grey matter deficits in schizophrenia? (iii) Is elevated microglial activation evident and associated with structural brain changes in schizophrenia? Using diffusion-weighted magnetic resonance imaging data, we mapped whole-brain white matter circuitry in patients recently diagnosed with a first-episode psychosis and patients with chronic schizophrenia. We found that white matter pathology in recently diagnosed patients was confined to selective anterior callosal fibres within a more extensive network of white matter disruptions found in chronic illness. These findings may suggest a progressive trajectory of white matter pathology in schizophrenia. Secondly, we applied multimodal imaging techniques to reveal a strong and reproducible relationship between white and anatomically adjacent grey matter deficits in schizophrenia, a relationship that dynamically varied as a function of illness duration. Thirdly, we examined microglial activation, indexed using 11C-(R)-PK11195 positron emission tomography (PET) imaging, as a key mechanism hypothesised to underlie structural deficits in schizophrenia. In contrast to our hypothesis, we found no evidence of microglial activation or a relationship to brain changes in individuals across any stage of illness, including those at ultra-high risk of psychosis, recently diagnosed with a first-episode psychosis and patients with chronic schizophrenia. These findings highlight the need for whole-brain and multimodal approaches to expose patterns of neuropathology in schizophrenia for biomarker and therapeutic detection. Using a whole-brain perspective, our results implicate early grey and white matter abnormalities in schizophrenia, which dynamically evolve over the course of illness. An exciting possibility of these findings is that processes underlying such early deficits could be targeted therapeutically to delay or prevent illness progression or alternatively, as signatures for later illness chronicity.