Do loneliness and social exclusion breed paranoia? An experience sampling investigation across the psychosis continuum.

The role of loneliness and social exclusion in the development of paranoia is largely unexplored. Negative affect may mediate potential associations between these factors. We investigated the temporal relationships of daily-life loneliness, felt social exclusion, negative affect, and paranoia across the psychosis continuum. Seventy-five participants, including 29 individuals with a diagnosis of non-affective psychosis, 20 first-degree relatives, and 26 controls used an Experience Sampling Method (ESM) app to capture the fluctuations in loneliness, feelings of social exclusion, paranoia, and negative affect across a 1-week period. Data were analysed with multilevel regression analyses. In all groups, loneliness and feelings of social exclusion were independent predictors of paranoia over time (b = 0.05,  < .001 and b = 0.04,  < .05, respectively). Negative affect predicted paranoia (b = 0.17,  < .001) and partially mediated the associations between loneliness, social exclusion, and paranoia. It also predicted loneliness (b = 0.15,  < .0001), but not social exclusion (b = 0.04,  = .21) over time. Paranoia predicted social exclusion over time, with more pronounced effects in controls (b = 0.43) than patients (b = 0.19; relatives: b = 0.17); but not loneliness (b = 0.08,  = .16). Paranoia and negative affect worsen in all groups following feelings of loneliness and social exclusion. This highlights the importance of a sense of belonging and being included for mental well-being. Loneliness, feeling socially excluded, and negative affect were independent predictors of paranoid thinking, suggesting they represent useful targets in its treatment. [Abstract copyright: © 2023 The Author(s).

Treated Incidence of Psychotic Disorders in the Multinational EU-GEI Study

Importance: Psychotic disorders contribute significantly to the global disease burden, yet the latest international incidence study of psychotic disorders was conducted in the 1980s. Objectives: To estimate the incidence of psychotic disorders using comparable methods across 17 catchment areas in 6 countries and to examine the variance between catchment areas by putative environmental risk factors. Design, Setting, and Participants: An international multisite incidence study (the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions) was conducted from May 1, 2010, to April 1, 2015, among 2774 individuals from England (2 catchment areas), France (3 catchment areas), Italy (3 catchment areas), the Netherlands (2 catchment areas), Spain (6 catchment areas), and Brazil (1 catchment area) with a first episode of nonorganic psychotic disorders (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10] codes F20-F33) confirmed by the Operational Criteria Checklist. Denominator populations were estimated using official national statistics. Exposures: Age, sex, and racial/ethnic minority status were treated as a priori confounders. Latitude, population density, percentage unemployment, owner-occupied housing, and single-person households were treated as catchment area-level exposures. Main Outcomes and Measures: Incidence of nonorganic psychotic disorders (ICD-10 codes F20-F33), nonaffective psychoses (ICD-10 codes F20-F29), and affective psychoses (ICD-10 codes F30-F33) confirmed by the Operational Criteria Checklist. Results: A total of 2774 patients (1196 women and 1578 men; median age, 30.5 years [interquartile range, 23.0-41.0 years]) with incident cases of psychotic disorders were identified during 12.9 million person-years at risk (crude incidence, 21.4 per 100 000 person-years; 95% CI, 19.4-23.4 per 100 000 person-years). A total of 2183 patients (78.7%) had nonaffective psychotic disorders. After direct standardization for age, sex, and racial/ethnic minority status, an 8-fold variation was seen in the incidence of all psychotic disorders, from 6.0 (95% CI, 3.5-8.6) per 100 000 person-years in Santiago, Spain, to 46.1 (95% CI, 37.3-55.0) per 100 000 person-years in Paris, France. Rates were elevated in racial/ethnic minority groups (incidence rate ratio, 1.6; 95% CI, 1.5-1.7), were highest for men 18 to 24 years of age, and were lower in catchment areas with more owner-occupied homes (incidence rate ratio, 0.8; 95% CI, 0.7-0.8). Similar patterns were observed for nonaffective psychoses; a lower incidence of affective psychoses was associated with higher area-level unemployment (incidence rate ratio, 0.3; 95% CI, 0.2-0.5). Conclusions and Relevance: This study confirmed marked heterogeneity in risk for psychotic disorders by person and place, including higher rates in younger men, racial/ethnic minorities, and areas characterized by a lower percentage of owner-occupied houses.The European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) Project is funded by grant agreement HEALTH-F2-2010-241909 (Project EU-GEI) from the European Community’s Seventh Framework Programme. The Brazilian study was funded by grant 2012/0417-0 from the São Paulo Research Foundation. Dr Kirkbride is funded by the Wellcome Trust and grant 101272/Z/13/Z from the Royal Society. Ms Jongsma and Dr Jones are funded by the National Institute of Health Research Collaboration of Leadership in Applied Health Research and Care East of England

The effects of recent stressful life events on outcomes in individuals at clinical high risk for psychosis:results from the longitudinal EU-GEI high-risk study

BACKGROUND: Recent stressful life events (SLE) are a risk factor for psychosis, but limited research has explored how SLEs affect individuals at clinical high risk (CHR) for psychosis. The current study investigated the longitudinal effects of SLEs on functioning and symptom severity in CHR individuals, where we hypothesized CHR would report more SLEs than healthy controls (HC), and SLEs would be associated with poorer outcomes.METHODS: The study used longitudinal data from the EU-GEI High Risk study. Data from 331 CHR participants were analyzed to examine the effects of SLEs on changes in functioning, positive and negative symptoms over a 2-year follow-up. We compared the prevalence of SLEs between CHR and HCs, and between CHR who did (CHR-T) and did not (CHR-NT) transition to psychosis.RESULTS: CHR reported 1.44 more SLEs than HC ( p &lt; 0.001), but there was no difference in SLEs between CHR-T and CHR-NT at baseline. Recent SLEs were associated with poorer functioning and more severe positive and negative symptoms in CHR individuals (all p &lt; 0.01) but did not reveal a significant interaction with time. CONCLUSIONS: CHR individuals who had experienced recent SLEs exhibited poorer functioning and more severe symptoms. However, as the interaction between SLEs and time was not significant, this suggests SLEs did not contribute to a worsening of symptoms and functioning over the study period. SLEs could be a key risk factor to becoming CHR for psychosis, however further work is required to inform when early intervention strategies mitigating against the effects of stress are most effective.</p

Age-Related Social Cognitive Performance in Individuals With Psychotic Disorders and Their First-Degree Relatives

Background Social cognitive impairment is a recognized feature of psychotic disorders. However, potential age-related differences in social cognitive impairment have rarely been studied. Study Design Data came from 905 individuals with a psychotic disorder, 966 unaffected siblings, and 544 never-psychotic controls aged 18–55 who participated in the Genetic Risk and Outcome of Psychosis (GROUP) study. Multilevel linear models were fitted to study group main effects and the interaction between group and age on emotion perception and processing (EPP; degraded facial affect recognition) and theory of mind (ToM; hinting task) performance. Age-related differences in the association between socio-demographic and clinical factors, and EPP and ToM were also explored. Study Results Across groups, EPP performance was associated with age (β = −0.02, z = −7.60, 95% CI: −0.02, −0.01, P < .001), with older participants performing worse than younger ones. A significant group-by-age interaction on ToM (X2(2) = 13.15, P = .001) indicated that older patients performed better than younger ones, while no age-related difference in performance was apparent among siblings and controls. In patients, the association between negative symptoms and ToM was stronger for younger than older patients (z = 2.16, P = .03). Conclusions The findings point to different age-related performance patterns on tests of 2 key social cognitive domains. ToM performance was better in older individuals, although this effect was only observed for patients. EPP was less accurate in older compared with younger individuals. These findings have implications with respect to when social cognitive training should be offered to patients

Age-at-migration, ethnicity and psychosis risk: Findings from the EU-GEI case-control study

Several studies have highlighted increased psychosis risk in migrant and minority ethnic populations. Migration before age 18 appears to increase risk, but further evidence is required. We investigated this issue in a European case-control study. We hypothesized that migration during two key socio-developmental periods, childhood and adolescence, would be most strongly associated with increased odds of psychosis, and that this would be more pronounced for racialised minorities. We used data from five countries in the EUropean network of national schizophrenia networks studying Gene-Environment Interactions [EU-GEI] study. We examined the association between migration in infancy (0–4 years), childhood (5–10 years), adolescence (11–17 years) or adulthood (18+ years) and first episode psychotic disorder. We fitted unadjusted and adjusted logistic regression models to estimate odds ratios [OR] and 95% confidence intervals [95%CI] for associations between age-at-migration and psychosis. In stratified models, we also examined whether these associations varied by ethnicity. The sample consisted of 937 cases and 1,195 controls. Migration at all ages, including infancy (OR: 2.03, 95%CI: 1.01–4.10), childhood (OR: 2.07, 95%CI: 1.04–4.14), adolescence (OR: 3.26, 95%CI: 1.89–5.63) and adulthood (OR: 1.71, 95%CI: 1.21–2.41), was associated with increased odds of psychosis compared with the white majority non-migrant group, after adjustment for all confounders except ethnoracial identity. After additional adjustment for ethnoracial identity, only migration during adolescence remained associated with psychosis (OR 1.94, 95%CI: 1.11–3.36). In stratified analyses, migration during adolescence was associated with increased odds of psychosis in Black (OR: 6.52, 95%CI: 3.00–14.20) and North African (OR: 16.43, 95%CI: 1.88–143.51) groups.Migration during adolescence increased psychosis risk, particularly in racially minoritised young people. This suggests that development of interventions for minoritised young migrants that alleviate stressors associated with migration and acculturation are warranted

Cognitive presentation at psychosis onset through premorbid deterioration and exposure to environmental risk factors

BACKGROUND: 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 Role of Social Deprivation and Cannabis Use in Explaining Variation in the Incidence of Psychotic Disorders: Findings From the EU-GEI Study

BACKGROUND AND HYPOTHESIS: Recent findings suggest the incidence of first-episode psychotic disorders (FEP) varies according to setting-level deprivation and cannabis use, but these factors have not been investigated together. We hypothesized deprivation would be more strongly associated with variation in FEP incidence than the prevalence of daily or high-potency cannabis use between settings. STUDY DESIGN: We used incidence data in people aged 18-64 years from 14 settings of the EU-GEI study. We estimated the prevalence of daily and high-potency cannabis use in controls as a proxy for usage in the population at-risk; multiple imputations by chained equations and poststratification weighting handled missing data and control representativeness, respectively. We modeled FEP incidence in random intercepts negative binomial regression models to investigate associations with the prevalence of cannabis use in controls, unemployment, and owner-occupancy in each setting, controlling for population density, age, sex, and migrant/ethnic group. STUDY RESULTS: Lower owner-occupancy was independently associated with increased FEP (adjusted incidence rate ratio [aIRR]: 0.76, 95% CI: 0.61-0.95) and non-affective psychosis incidence (aIRR: 0.68, 95% CI: 0.55-0.83), after multivariable adjustment. Prevalence of daily cannabis use in controls was associated with the incidence of affective psychoses (aIRR: 1.53, 95% CI: 1.02-2.31). We found no association between FEP incidence and unemployment or high-potency cannabis use prevalence. Sensitivity analyses supported these findings. CONCLUSIONS: Lower setting-level owner-occupancy and increased prevalence of daily cannabis use in controls independently contributed to setting-level variance in the incidence of different psychotic disorders. Public health interventions that reduce exposure to these harmful environmental factors could lower the population-level burden of psychotic disorders

The Role of Social Deprivation and Cannabis Use in Explaining Variation in the Incidence of Psychotic Disorders:Findings From the EU-GEI Study

Background and Hypothesis: Recent findings suggest the incidence of first-episode psychotic disorders (FEP) varies according to setting-level deprivation and cannabis use, but these factors have not been investigated together. We hypothesized deprivation would be more strongly associated with variation in FEP incidence than the prevalence of daily or high-potency cannabis use between settings. Study Design: We used incidence data in people aged 18-64 years from 14 settings of the EU-GEI study. We estimated the prevalence of daily and high-potency cannabis use in controls as a proxy for usage in the population at-risk; multiple imputations by chained equations and poststratification weighting handled missing data and control representativeness, respectively. We modeled FEP incidence in random intercepts negative binomial regression models to investigate associations with the prevalence of cannabis use in controls, unemployment, and owner-occupancy in each setting, controlling for population density, age, sex, and migrant/ethnic group. Study Results: Lower owner-occupancy was independently associated with increased FEP (adjusted incidence rate ratio [aIRR]: 0.76, 95% CI: 0.61-0.95) and non-affective psychosis incidence (aIRR: 0.68, 95% CI: 0.55-0.83), after multivariable adjustment. Prevalence of daily cannabis use in controls was associated with the incidence of affective psychoses (aIRR: 1.53, 95% CI: 1.02-2.31). We found no association between FEP incidence and unemployment or high-potency cannabis use prevalence. Sensitivity analyses supported these findings. Conclusions: Lower setting-level owner-occupancy and increased prevalence of daily cannabis use in controls independently contributed to setting-level variance in the incidence of different psychotic disorders. Public health interventions that reduce exposure to these harmful environmental factors could lower the population-level burden of psychotic disorders.</p

Use of multiple polygenic risk scores for distinguishing schizophrenia-spectrum disorder and affective psychosis categories in a first-episode sample; the EU-GEI study

Background: Schizophrenia (SZ), bipolar disorder (BD) and depression (D) run in families. This susceptibility is partly due to hundreds or thousands of common genetic variants, each conferring a fractional risk. The cumulative effects of the associated variants can be summarised as a polygenic risk score (PRS). Using data from the EUropean Network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) first episode case-control study, we aimed to test whether PRSs for three major psychiatric disorders (SZ, BD, D) and for intelligent quotient (IQ) as a neurodevelopmental proxy, can discriminate affective psychosis (AP) from schizophrenia-spectrum disorder (SSD). Methods: Participants (842 cases, 1284 controls) from 16 European EU-GEI sites were successfully genotyped following standard quality control procedures. The sample was stratified based on genomic ancestry and analyses were done only on the subsample representing the European population (573 cases, 1005 controls). Using PRS for SZ, BD, D, and IQ built from the latest available summary statistics, we performed simple or multinomial logistic regression models adjusted for 10 principal components for the different clinical comparisons. Results: In case-control comparisons PRS-SZ, PRS-BD and PRS-D distributed differentially across psychotic subcategories. In case-case comparisons, both PRS-SZ [odds ratio (OR) = 0.7, 95% confidence interval (CI) 0.54-0.92] and PRS-D (OR = 1.31, 95% CI 1.06-1.61) differentiated AP from SSD; and within AP categories, only PRS-SZ differentiated BD from psychotic depression (OR = 2.14, 95% CI 1.23-3.74). Conclusions: Combining PRS for severe psychiatric disorders in prediction models for psychosis phenotypes can increase discriminative ability and improve our understanding of these phenotypes. Our results point towards the potential usefulness of PRSs in specific populations such as high-risk or early psychosis phases

Development and Validation of Predictive Model for a Diagnosis of First Episode Psychosis Using the Multinational EU-GEI Case-control Study and Modern Statistical Learning Methods

Background and Hypothesis: It is argued that availability of diagnostic models will facilitate a more rapid identification of individuals who are at a higher risk of first episode psychosis (FEP). Therefore, we developed, evaluated, and validated a diagnostic risk estimation model to classify individual with FEP and controls across six countries. Study Design: We used data from a large multi-center study encompassing 2627 phenotypically well-defined participants (aged 18-64 years) recruited from six countries spanning 17 research sites, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions study. To build the diagnostic model and identify which of important factors for estimating an individual risk of FEP, we applied a binary logistic model with regularization by the least absolute shrinkage and selection operator. The model was validated employing the internal-external cross-validation approach. The model performance was assessed with the area under the receiver operating characteristic curve (AUROC), calibration, sensitivity, and specificity. Study Results: Having included preselected 22 predictor variables, the model was able to discriminate adults with FEP and controls with high accuracy across all six countries (rangesAUROC=0.84-0.86). Specificity (range=73.9-78.0%) and sensitivity (range=75.6-79.3%) were equally good, cumulatively indicating an excellent model accuracy; though, calibration slope for the diagnostic model showed a presence of some overfitting when applied specifically to participants from France, the UK, and The Netherlands. Conclusions: The new FEP model achieved a good discrimination and good calibration across six countries with different ethnic contributions supporting its robustness and good generalizability.</p