Ranlund, SM;
(2016)
Biomarkers of brain function in psychosis and their genetic basis.
Doctoral thesis , UCL (University College London).
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Abstract
Psychotic disorders, including schizophrenia and bipolar disorder, are amongst the most severe and enduring mental illnesses. Recent research has identified several genetic variants associated with an increased risk of developing psychosis; however, it remains largely unknown how these lead to the illness. This is where endophenotypes – heritable traits associated with the illness and observed in unaffected family members of patients – could be valuable. Endophenotypes are linked to the genetic underpinnings of disorders, and can help elucidate the functional effects of genetic risk variants. This thesis investigates endophenotypes for psychosis, with the overall aim of identify such biological markers, as well as to examine the relationships between different endophenotypes and their associations with genetic risk for psychosis. A family design has been used throughout, including patients with psychosis, their unaffected first-degree relatives, as well as healthy controls. In chapter 1, I review the endophenotype approach and those markers proposed for psychosis genetic research. Chapters 2 and 3 investigate whether different neurophysiological measures are potential endophenotypes for psychosis. In chapter 2, resting state EEG was studied and it was shown that risk groups, including unaffected relatives and people with an at-risk mental state, presented no abnormalities. This suggests that – rather than endophenotypes – the low frequency electrophysiological abnormalities seen in chronic patients in this study might be related to illness progression or long-term medication effects, and be more useful as biomarkers in non-genetic research. In chapter 3, I used dynamic causal modelling to investigate effective connectivity – the influence that one neuronal system exerts over another – underlying the mismatch negativity evoked potential, a marker of pre-attentive auditory perception. Results indicate that, compared to controls, both patients and their relatives show abnormalities of the excitability of superficial pyramidal cells in prefrontal cortex. Hence, this appears to be linked to the genetic aetiology of psychosis, and constitutes a potential endophenotype. Chapters 4 and 5 investigate several pre-identified endophenotypes for psychosis: Electrophysiological (the P300 event related potential), cognitive (working memory, spatial visualisation, and verbal memory), and neuroanatomical (lateral ventricular volume). In chapter 4, the associations between these endophenotypes were examined. Results showed that the P300 amplitude and latency are independent measures; the former indexing attention and working memory and the latter possibly a correlate of basic speed of processing. Importantly, individuals with psychosis, their unaffected relatives, and healthy controls all showed similar patterns of associations between all pairs of endophenotypes, supporting the notion of a continuum of psychosis across the population. Lastly, in chapter 5, polygenic risk scores – a measure of the combined effect of a large number of common genetic risk variants – were used to investigate the relationships between genetic risk for schizophrenia and bipolar disorder, and the endophenotypes studied in the previous chapter. Results showed that higher polygenic score for schizophrenia nominally predicts poorer performance on a spatial visualisation task; providing some evidence that the two traits share genetic risk variants as hypothesised. No other associations approached significance, possibly due to insufficient statistical power. However, as discovery samples grow, the use of polygenic scores is promising. This thesis has thus contributed to the field of mental health research by investigating key electrophysiological, cognitive and imaging endophenotypes for psychosis, as well as their genetic influences. Well defined and reliably measured endophenotypes are valuable in mental health research by clarifying the functional effects of identified genetic risk factors, and by providing ways of identifying groups of people with similar abnormalities, both within and between current diagnostic categories.
Type: | Thesis (Doctoral) |
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Title: | Biomarkers of brain function in psychosis and their genetic basis |
Event: | University College London |
Open access status: | An open access version is available from UCL Discovery |
Language: | English |
Additional information: | Third party copyright material has been removed from ethesis. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences |
URI: | https://discovery.ucl.ac.uk/id/eprint/1493030 |



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