Investigating the Molecular Biology of Psychosis: Evidence and Implications for Pathophysiology, Prediction and Prevention

Background: Psychotic disorders such as schizophrenia are severe mental illnesses associated with significant burden for individuals and society. Investigation of the molecular pathophysiology of psychosis may inform prediction and prevention strategies. This thesis focuses on the potential roles of the complement system and polyunsaturated fatty acids (PUFAs).

Methods: Firstly, a systematic literature review and meta-analyses were performed to synthesise results of studies measuring peripheral complement system protein activities or concentrations in patients with schizophrenia compared to controls.

Secondly, plasma proteomic analyses were performed in two nested case-control studies. The first comprised a subsample of 133 clinical high-risk (CHR) for psychosis participants in the European Network of National Schizophrenia Networks studying Gene-Environment Interactions (EU-GEI) longitudinal study, of whom 49 (36.8%) developed psychosis. The second comprised a subsample of 121 participants in the Avon Longitudinal Study of Parents and Children (ALSPAC) who did not report psychotic experiences (PEs) at age 12 years, of whom 55 (45.4%) had PEs at age 18 years. Machine learning algorithms were used to predict transition to psychosis in EU-GEI and development of PEs in ALSPAC.

Thirdly, plasma PUFA measures were assessed using nuclear magnetic spectroscopy in samples provided by ALSPAC cohort participants at age 17 years and age 24 years. Cross-sectional and longitudinal associations with mental disorders (psychotic disorder, depressive disorder and generalised anxiety disorder [GAD]) were evaluated using logistic regression, adjusting for key confounders.

Results: There was little evidence of a consistent pattern of complement dysregulation in patients with schizophrenia relative to controls in the existing literature, although there was marked heterogeneity between studies.

In the EU-GEI subsample, a model based on baseline clinical and proteomic data demonstrated excellent performance for prediction of transition to psychosis (area under the receiver-operating characteristic curve [AUC] 0.95). Functional analysis of differentially expressed proteins implicated the complement and coagulation cascade. A model based on the 10 most predictive proteins accurately predicted transition status in training (AUC 0.99) and test data (AUC 0.92). In the ALSPAC subsample, a model using age 12 proteomic data predicted PEs at age 18 years with AUC 0.74.

Based on cohort-wide data in ALSPAC, at age 24 years the omega-6:omega-3 PUFA ratio was positively associated with psychotic disorder, depressive disorder and GAD, while docosahexaenoic acid (DHA) was inversely associated with psychotic disorder. In longitudinal analyses, there was evidence of an inverse association between DHA at age 17 years and incident psychotic disorder at age 24 years (adjusted odds ratio 0.44, 95% confidence interval 0.22 – 0.87) with little evidence for depressive disorder or GAD.

Conclusions: Complement system dysregulation is detectable prior to the development of early psychosis phenotypes. Proteomic biomarkers may augment individualised prediction of outcomes in the clinical high-risk subpopulation. In the general population, higher levels of DHA in adolescence may be associated with reduced odds of psychosis in early adulthood, suggesting a potentially preventative role. These findings have implications regarding the pathophysiology, prediction and prevention of psychotic disorders.