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Previous studies identified clusters of first-episode psychosis (FEP) patients based on cognition and premorbid adjustment. This study examined a range of socio-environmental risk factors associated with clusters of FEP, aiming a) to compare clusters of FEP and community controls using the Maudsley Environmental Risk Score for psychosis (ERS), a weighted sum of the following risks: paternal age, childhood adversities, cannabis use, and ethnic minority membership; b) to explore the putative differences in specific environmental risk factors in distinguishing within patient clusters and from controls.
Methods
A univariable general linear model (GLS) compared the ERS between 1,263 community controls and clusters derived from 802 FEP patients, namely, low (n = 223) and high-cognitive-functioning (n = 205), intermediate (n = 224) and deteriorating (n = 150), from the EU-GEI study. A multivariable GLS compared clusters and controls by different exposures included in the ERS.
Results
The ERS was higher in all clusters compared to controls, mostly in the deteriorating (β=2.8, 95% CI 2.3 3.4, η2 = 0.049) and the low-cognitive-functioning cluster (β=2.4, 95% CI 1.9 2.8, η2 = 0.049) and distinguished them from the cluster with high-cognitive-functioning. The deteriorating cluster had higher cannabis exposure (meandifference = 0.48, 95% CI 0.49 0.91) than the intermediate having identical IQ, and more people from an ethnic minority (meandifference = 0.77, 95% CI 0.24 1.29) compared to the high-cognitive-functioning cluster.
Conclusions
High exposure to environmental risk factors might result in cognitive impairment and lower-than-expected functioning in individuals at the onset of psychosis. Some patients’ trajectories involved risk factors that could be modified by tailored interventions.
The ‘jumping to conclusions’ (JTC) bias is associated with both psychosis and general cognition but their relationship is unclear. In this study, we set out to clarify the relationship between the JTC bias, IQ, psychosis and polygenic liability to schizophrenia and IQ.
Methods
A total of 817 first episode psychosis patients and 1294 population-based controls completed assessments of general intelligence (IQ), and JTC, and provided blood or saliva samples from which we extracted DNA and computed polygenic risk scores for IQ and schizophrenia.
Results
The estimated proportion of the total effect of case/control differences on JTC mediated by IQ was 79%. Schizophrenia polygenic risk score was non-significantly associated with a higher number of beads drawn (B = 0.47, 95% CI −0.21 to 1.16, p = 0.17); whereas IQ PRS (B = 0.51, 95% CI 0.25–0.76, p < 0.001) significantly predicted the number of beads drawn, and was thus associated with reduced JTC bias. The JTC was more strongly associated with the higher level of psychotic-like experiences (PLEs) in controls, including after controlling for IQ (B = −1.7, 95% CI −2.8 to −0.5, p = 0.006), but did not relate to delusions in patients.
Conclusions
Our findings suggest that the JTC reasoning bias in psychosis might not be a specific cognitive deficit but rather a manifestation or consequence, of general cognitive impairment. Whereas, in the general population, the JTC bias is related to PLEs, independent of IQ. The work has the potential to inform interventions targeting cognitive biases in early psychosis.
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