Season of birth and schizotypy in a sample of undergraduate students.

PURPOSE: In line with the psychotic continuum theory, the study of psychometric schizotypy in non-clinical samples has been proposed as a convenient yet powerful method for studying the etiology of psychosis. Based on this paradigm, several studies explored the association between season of birth (SoB) and schizotypy but led to inconsistent results. Building on the analysis of the previous studies, in the present study, we aimed to advance our understanding by improving the methodology (using a homogeneous group, eliminating unreliable respondents, taking into account potential confounders) and the reporting. METHODS: Subjects were recruited among undergraduate students from 3 Romanian Universities. To limit the potential influence of invalid response, we applied methods for detecting unreliable and/or biased questionnaires and excluded subjects with unreliable/ biased answers from the analyses. Schizotypal dimensions were measured using the Romanian translation of the 22-items Schizotypal Personality Questionnaire-Brief (SPQ-B). The association between schizotypy scores and season of birth was explored using linear regression. RESULTS: In a sample of 484 undergraduate students from Romania, we found that being born in late winter/early spring (February and March) was associated to higher total schizotypy score and disorganization. Furthermore, we found that restricting the sample to subjects born in an urban environment increased the strength of the association. CONCLUSION: This study is consistent with an association between SoB and the risk of psychotic disorders.

Cognitive performance at first episode of psychosis and the relationship with future treatment resistance: Evidence from an international prospective cohort study.

BACKGROUND: Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia, with recent research finding systematic biological differences between antipsychotic resistant and responsive patients. Our aim was to determine whether cognitive impairment at first episode significantly differs between future antipsychotic responders and resistant cases. METHODS: Analysis of data from seven international cohorts of first-episode psychosis (FEP) with cognitive data at baseline (N = 683) and follow-up data on antipsychotic treatment response: 605 treatment responsive and 78 treatment resistant cases. Cognitive measures were grouped into seven cognitive domains based on the pre-existing literature. We ran multiple imputation for missing data and used logistic regression to test for associations between cognitive performance at FEP and treatment resistant status at follow-up. RESULTS: On average patients who were future classified as treatment resistant reported poorer performance across most cognitive domains at baseline. Univariate logistic regressions showed that antipsychotic treatment resistance cases had significantly poorer IQ/general cognitive functioning at FEP (OR = 0.70, p = .003). These findings remained significant after adjusting for additional variables in multivariable analyses (OR = 0.76, p = .049). CONCLUSIONS: Although replication in larger studies is required, it appears that deficits in IQ/general cognitive functioning at first episode are associated with future treatment resistance. Cognitive variables may be able to provide further insight into neurodevelopmental factors associated with treatment resistance or act as early predictors of treatment resistance, which could allow prompt identification of refractory illness and timely interventions.

Clinical predictors of antipsychotic treatment resistance: Development and internal validation of a prognostic prediction model by the STRATA-G consortium.

INTRODUCTION: Our aim was to, firstly, identify characteristics at first-episode of psychosis that are associated with later antipsychotic treatment resistance (TR) and, secondly, to develop a parsimonious prediction model for TR. METHODS: We combined data from ten prospective, first-episode psychosis cohorts from across Europe and categorised patients as TR or non-treatment resistant (NTR) after a mean follow up of 4.18 years (s.d. = 3.20) for secondary data analysis. We identified a list of potential predictors from clinical and demographic data recorded at first-episode. These potential predictors were entered in two models: a multivariable logistic regression to identify which were independently associated with TR and a penalised logistic regression, which performed variable selection, to produce a parsimonious prediction model. This model was internally validated using a 5-fold, 50-repeat cross-validation optimism-correction. RESULTS: Our sample consisted of N = 2216 participants of which 385 (17 %) developed TR. Younger age of psychosis onset and fewer years in education were independently associated with increased odds of developing TR. The prediction model selected 7 out of 17 variables that, when combined, could quantify the risk of being TR better than chance. These included age of onset, years in education, gender, BMI, relationship status, alcohol use, and positive symptoms. The optimism-corrected area under the curve was 0.59 (accuracy = 64 %, sensitivity = 48 %, and specificity = 76 %). IMPLICATIONS: Our findings show that treatment resistance can be predicted, at first-episode of psychosis. Pending a model update and external validation, we demonstrate the potential value of prediction models for TR.

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia.

IMPORTANCE: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. OBJECTIVE: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. DESIGN, SETTING, AND PARTICIPANTS: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). MAIN OUTCOMES AND MEASURES: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. RESULTS: The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04). CONCLUSIONS AND RELEVANCE: In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.

The Independent Effects of Psychosocial Stressors on Subclinical Psychosis: Findings From the Multinational EU-GEI Study.

The influence of psychosocial stressors on psychosis risk has usually been studied in isolation and after the onset of the disorder, potentially ignoring important confounding relationships or the fact that some stressors that may be the consequence of the disorder rather than preexisting. The study of subclinical psychosis could help to address some of these issues. In this study, we investigated whether there was (i) an association between dimensions of subclinical psychosis and several psychosocial stressors including: childhood trauma, self-reported discrimination experiences, low social capital, and stressful life experiences, and (ii) any evidence of environment-environment (ExE) interactions between these factors. Data were drawn from the EUGEI study, in which healthy controls (N = 1497) and siblings of subjects with a psychotic disorder (N = 265) were included in six countries. The association between psychosocial stressors and subclinical psychosis dimensions (positive, negative and depressive dimension as measured by the Community Assessment of Psychic Experiences (CAPE) scale) and possible ExE interactions were assessed using linear regression models. After adjusting for sex, age, ethnicity, country, and control/sibling status, childhood trauma (ß for positive dimension: 0.13, negative: 0.49, depressive: 0.26) and stressful life events (positive: 0.08, negative: 0.16, depressive: 0.17) were associated with the three dimensions. Lower social capital was associated with the negative and depression dimensions (negative: 0.26, depressive: 0.13), and self-reported discrimination experiences with the positive dimension (0.06). Our findings are in favor of independent, cumulative and non-specific influences of social adversities in subclinical psychosis in non-clinical populations, without arguments for E × E interactions.

Characteristics associated with the risk of psychosis among immigrants and their descendants in France.

OBJECTIVE: To explore the sociodemographic characteristics that might explain the increased incidence of psychosis among immigrants and their descendants in France. METHODS: Data were collected for all subjects with first contact for psychosis aged between 18 and 64 years, in two catchment areas in the Paris region. Incidence rates (IR) and incidence rate ratios (IRR) were adjusted for gender and age. RESULTS: During 805,396 persons-year at risk, we identified 321 cases of first-episode psychosis, of which 129 were immigrants and 78 descendants of immigrants. We found that the geographic origin was associated with the risk of psychosis although generation has little impact. Sub-Saharan African immigrants and their descendants showed the highest risk (IRR = 3.1 and IRR = 2.9, respectively). We observed that living in deprived areas increased the incidence of psychosis (IRR = 1.3, 95CI%: 1.0-1.6), particularly among immigrants (IRR = 1.6; 95% CI: 1.1-2.5). Finally, our study showed that subjects having unstable housing (a proxy for "hard to count population") could inflate the incidence rates among immigrants. CONCLUSION: The current study shows that the increased risk of psychosis in groups with an immigration background in France is associated with their origin and highlights the importance of socioeconomic factors in modulating this risk.

Assessing cross-national invariance of the Community Assessment of Psychic Experiences (CAPE).

BACKGROUND: The Community Assessment of Psychic Experiences (CAPE) is a 42-item self-report questionnaire that has been developed and validated to measure the dimensions of psychosis in the general population. The CAPE has a three-factor structure with dimensions of positive, negative and depression. Assessing the cross-national equivalence of a questionnaire is an essential prerequisite before pooling data from different countries. In this study, our aim was to investigate the measurement invariance of the CAPE across different countries. METHODS: Data were drawn from the European Union Gene-Environment Interaction (EU-GEI) study. Participants (incident cases of psychotic disorder, controls and siblings of cases) were recruited in Brazil, France, Italy, the Netherlands, Spain and UK. To analyse the measurement invariance across these samples, we tested configural invariance (i.e. identical structures of the factors), metric invariance (i.e. equivalence of the factor loadings) and scalar invariance (i.e. equivalence of the thresholds) of the three CAPE dimensions using multigroup categorical confirmatory factor analysis methods. RESULTS: The configural invariance model fits well, providing evidence for identical factorial structure across countries. In comparison with the configural model invariance, the fit indices were very similar in the metric and scalar invariance models, indicating that factor loadings and thresholds did not differ across the six countries. CONCLUSION: We found that, across six countries, the CAPE showed equivalent factorial structure, factor loadings and thresholds. Thus, differences observed in scores between individuals from different countries should be considered as reflecting different levels of psychosis.

Relationship between incidence and prevalence in psychotic disorders: An incidence-prevalence-mortality model.

OBJECTIVES: Incidence-prevalence-mortality (IPM) models have been developped to estimate incidence or prevalence when one of these two measures is unavailable. We aimed to test the consistency of an IPM model of psychotic disorders on a recent incidence-prevalence couple dataset and to identify potential causes of inconsistency by applying the model to (a) the whole population, (b) female and male subgroups, (c) migrant subgroups, and (d) psychotic disorders with age at onset (AAO) between 18 and 24 (18-24 AAO). METHODS: We modelled prevalence (MP) using incidence data and the expected mortality and remission values. We then compared the MP to the observed prevalence (OP). RESULTS: In the whole population, the model significantly underestimated the prevalence (MP = 3.30, 95% CI [2.97, 3.66]; OP = 4.98, 95% CI [4.58, 5.41]). The results were similar for the two genders. In the migrants group, results were in the opposite direction, the model significantly overestimating the prevalence. Finally, in the 18-24 AAO subgroup, the model performed well, with OP and MP not significantly different. CONCLUSION: These results suggest that standard IPM models do not perform well for psychotic disorders and more complex models taking into account the heterogeneity of the sample (in terms of remission, mortality, population movements, etc.) need to be developed.

Spatial distribution of psychotic disorders in an urban area of France: an ecological study.

Previous analyses of neighbourhood variations of non-affective psychotic disorders (NAPD) have focused mainly on incidence. However, prevalence studies provide important insights on factors associated with disease evolution as well as for healthcare resource allocation. This study aimed to investigate the distribution of prevalent NAPD cases in an urban area in France. The number of cases in each neighbourhood was modelled as a function of potential confounders and ecological variables, namely: migrant density, economic deprivation and social fragmentation. This was modelled using statistical models of increasing complexity: frequentist models (using Poisson and negative binomial regressions), and several Bayesian models. For each model, assumptions validity were checked and compared as to how this fitted to the data, in order to test for possible spatial variation in prevalence. Data showed significant overdispersion (invalidating the Poisson regression model) and residual autocorrelation (suggesting the need to use Bayesian models). The best Bayesian model was Leroux's model (i.e. a model with both strong correlation between neighbouring areas and weaker correlation between areas further apart), with economic deprivation as an explanatory variable (OR = 1.13, 95% CI [1.02-1.25]). In comparison with frequentist methods, the Bayesian model showed a better fit. The number of cases showed non-random spatial distribution and was linked to economic deprivation.

Association between cannabis use and schizotypal dimensions--a meta-analysis of cross-sectional studies.

Cannabis consumption can cause abuse and dependence and increase risk of developing psychiatric and somatic disorders. Several literature reviews explored the link between cannabis consumption and schizophrenia but none summarized the rich literature on cannabis and psychometric schizotypy. The aim of our review is to synthesize data from studies that explored the association between cannabis consumption and schizoptypal dimensions. A systematic review of the literature and, when needed, contact with the authors, allowed us to gather data from 29 cross-sectional studies. We compared schizotypy scores between subjects that never used cannabis and subjects that used it at least once ("never vs. ever") and between current users and subjects that do not use cannabis currently ("current vs. other"). We conducted separate analyses for total schizotypy score and each of the three classical schizotypal dimensions (positive, negative, disorganized). For all eight comparisons, the cannabis group ("ever" or "current") had higher schizotypy scores. Differences were in the small or medium range and, with the exception of the negative score in the current vs. other comparison, statistically significant. Cannabis consumption is associated with increased schizotypal traits. More research, using different approaches (e.g. longitudinal studies) is needed to explore the cause of this association.

Exploring the relationships between tobacco smoking and schizophrenia in first-degree relatives.

Up to 90% of individuals with schizophrenia suffer from nicotine dependence. Both schizophrenia and nicotine consumption have strong genetic components, which may overlap. The relationship between schizophrenia and nicotine dependence remains unclear, due in part to confounding factors. Studies of the relationship between nicotine consumption and milder schizophrenia-related phenotypes, such as schizotypy, in first-degree relatives of individuals with schizophrenia could help to better understand the relationship between smoking and schizophrenia while avoiding such confounders. We assessed the proportion of smokers, their level of nicotine dependence and their level of schizotypy in a sample of 98 first-degree relatives of schizophrenic subjects and 110 healthy controls. Partial correlation analysis was used to assess the relationship between schizotypal dimensions and smoking dependence. The prevalence of smoking and nicotine dependence levels were higher in the relatives than in the healthy control group. We found no relationship between nicotine dependence and the magnitude of schizotypal features in either group. Our results support the hypothesis that the relationship between schizophrenia and smoking is largely mediated by common familial factors, which may be genetic.

Correlations between cognitive performances and psychotic or schizotypal dimensions.

OBJECTIVE: To test if specific correlations exist between cognitive measures and psychotic dimensions in schizophrenic subjects and if similar correlations, between cognition and schizotypal dimensions, are present in non-psychotic subjects. METHODS: We administered the same battery of cognitive tests (Source Monitoring, Verbal Fluency [VF] and Stroop tests) to schizophrenic subjects (N=54), their first-degree relatives (N=37) and controls (N=41). Scores of negative, positive and disorganisation dimensions were derived from the Signs and Symptoms of Psychotic Illness scale in schizophrenic subjects, and from the Schizotypal Personality Questionnaire in relatives and controls. RESULTS: In schizophrenic subjects, as hypothesised, the negative dimension correlated with performance on VF and disorganisation with performance in the Stroop test. The positive dimension did not correlate with any cognitive measure. With only one exception, the significant correlations observed in non-psychotic subjects did not match correlations seen in schizophrenic subjects. In non-psychotic subjects greater disorganisation was associated with more clustered words in VF suggesting that excessive automatic spreading of activation in semantic networks could underlie this dimension. CONCLUSION: As a whole, data lent partial support to our hypothesis of specific cognitive-clinical correlations in schizophrenic subjects but did not support the existence of similar correlations in non-psychotic subjects.