The association of jumping to conclusions and facial emotion recognition with genetic liability and outcome of psychosis

Introduction: Schizophrenia and other psychotic disorders are complex disorders with multifactorial aetiology encompassing genetic and environmental factors. The genetic architecture of these disorders involves many numerous loci implicated in conferring risk for developing the illness. Cognitive impairments are considered as important core features, serving as potential intermediate phenotypes for psychotic disorders. Cognitive biases including jumping to conclusions (JTC) and social cognition impairments such as difficulties in facial emotion recognition (FER) have been reported to be associated with psychosis, yet their link to shared genetic pathways with the disorder, and their contribution to psychotic outcome are still open questions. My thesis aimed to clarify the relation of these two biases with psychosis liability and with outcome. Methods: Data used in this Thesis come from two large-scale studies in which I participated: the multisite incidence and case-control EU-GEI study, and the Biological Phenotypes, Environment, Genes and Psychosis Outcome (GAP follow-up) study. To examine the presence of the JTC bias at first episode psychosis (FEP), taking into account the influence of general cognitive ability, I conducted a mediation analysis between case/control status, JTC, and IQ in a large sample of patients experiencing their FEP, and population controls. I then explored the associations of JTC with both psychosis and general cognition liability, estimating multiple linear regression models using calculated polygenic risk scores for schizophrenia (SZ PRS) and IQ (IQ PRS). Global and specific facial emotion recognition was analysed through fixed and random effects in repeated measures mixed models in the same large sample. Multiple linear regression models were used to investigate the association with FER and SZ PRS. In a London subsample in which I contributed to recruitment and assessment, I then tested both JTC and FER measured at FEP for multi-domain outcome prediction at, on average, 5-year-follow-up, based on estimated linear, ordinal, and multinomial logistic regression models. Finally, to test the stability of jumping to conclusions and facial emotion recognition over the years, intra-class correlations and repeated measures mixed models were performed. Results: The association between JTC and psychosis was shown to be fully mediated by IQ, and JTC was explained by the genetic underpinnings of IQ but not SZ PRS. Psychotic patients were more prone to display deficits in facial emotion recognition than controls, specifically in fear and anger recognition compared to happy or neutral faces. SZ PRS was associated with worse global facial emotion recognition and specifically with impairments in anger recognition. Neither JTC nor FER measured at FEP predicted any outcome domains at follow-up, although JTC showed a small effect on social outcome. Finally, an overall steady pattern of performance over time was detected for JTC and general facial emotion recognition in both patients and controls, with patients making hastier decisions and recognising fewer emotional faces than controls. Conclusions: My thesis contributed to clarifying the association of jumping to conclusions with psychotic disorders as mediated by general cognition; furthermore, JTC appeared not directly associated with common genetic risk variants for the disorder. However, this finding raised also the necessity of improved assessment for the JTC bias to reduce cognitive noise. On the other hand, findings on facial emotion recognition provided more evidence regarding impairment in global and emotion-specific recognition of emotional faces in the context of psychosis, corroborating previous findings from family studies; the results I obtained with polygenic risk score analysis suggested that facial emotion recognition - specifically negative emotions - could serve as intermediate phenotype for psychosis.