Climate change is one of the greatest threats to health that societies face and can adversely affect mental health. Given the current lack of a European consensus paper on the interplay between climate change and mental health, we signal a need for a pan-European position paper about this topic, written by stakeholders working in mental health care.

On behalf of the European Psychiatric Association (EPA), we give recommendations to make mental health care, research, and education more sustainable based on a narrative review of the literature.

Examples of sustainable mental healthcare comprise preventive strategies, interdisciplinary collaborations, evidence-based patient care, addressing social determinants of mental health, maintaining health services during extreme weather events, optimising use of resources, and sustainable facility management. In mental health research, sustainable strategies include investigating the impact of climate change on mental health, promoting research on climate change interventions, strengthening the evidence base for mental health-care recommendations, evaluating the allocation of research funding, and establishing evidence-based definitions and clinical approaches for emerging issues such as ‘eco-distress’. Regarding mental health education, planetary health, which refers to human health and how it is intertwined with ecosystems, may be integrated into educational courses.

The EPA is committed to combat climate change as the latter poses a threat to the future of mental health care. The current EPA position paper on climate change and mental health may be of interest to a diverse readership of stakeholders, including clinicians, researchers, educators, patients, and policymakers.

For most countries it is currently unknown to what degree concentrations of psychotropic drugs in surface water exceed environmental threshold concentrations (ETCs) [MOU1] for ecosystems and what risk mitigation could be applied. ETCs are defined as per-compound threshold concentrations above which detrimental effects on reproduction, growth, and mortality of aquatic organisms cannot be exclude

To quantify levels of antidepressants, antipsychotics, mood stabilizers, and benzodiazepines in surface water, investigate their sources and assess whether these levels exceed ETCs.

Cross-sectional analysis of measured and modeled data. Environmental levels were compared to ETCs to evaluate their risks for the aquatic environment. Finally, sources of psychotropic drugs were investigated.

All available Dutch water monitoring data from all regional and national monitoring campaigns of 2019, the last year before the COVID-19 pandemic.

Concentrations of aripiprazole, carbamazepine and its metabolites, clozapine, diazepam, (es)citalopram, fluoxetine, haloperidol, nortriptyline, olanzapine, oxazepam, temazepam, quetiapine, sertraline, valproic acid, and venlafaxine.

The main outcomes were measured and modeled concentrations of the aforementioned agents in surface water. As a secondary outcome, where possible, average risk quotients (RQs) were calculated by dividing the measured or modeled concentrations by the ETC. An RQ > 1 was interpreted as a risk to the environment.

Psychotropic drug samples (n=1201; 14-520 measurements per drug) showed the highest average concentrations for oxazepam (0.91 μg/L; RQ = 1.89) and carbamazepine (0.74 μg/L; RQ = 1.48), with individual measurements exceeding ETCs. For other drugs, measured concentrations did not reach the detection limit (amisulpride, (es)citalopram, quetiapine, and venlafaxine) or did not exceed the ETC (fluoxetine). Furthermore, households contributed most to psychotropics in surface water. Finally, psychotropics were cleared less efficiently from a wastewater treatment plant than other medications.

Psychotropic drugs are present in surface water, are primarily emitted by households, and may put organisms at risk. We signal a need to reduce concentrations of several psychotropic agents in the environment. Our findings set the stage for policies and research aimed at curtailing emissions of psychotropic drugs into the environment and highlight a need for responsible prescribing and waste measures.

None Declared

Predictors consistently associated with psychosis liability and course of illness in schizophrenia (SCZ) spectrum disorders (SSD), including the need for clozapine treatment, are lacking. Longitudinally ascertained medication use may empower studies examining associations between polygenic risk scores (PRSs) and pharmacotherapy choices.

To examine associations between PRS-SCZ loading and groups with different liabilities to SSD: individuals with SSD on clozapine, individuals with SSD on other antipsychotics, their parents and siblings, and unrelated healthy controls; and between PRS-SCZ and the likelihood of receiving a prescription of clozapine relative to other antipsychotics.

Six-year follow-up and cross-sectional observational cohort study.

Multi-center.

Individuals diagnosed with SSD using clozapine or other antipsychotics, their parents and siblings, and unrelated healthy controls.

PRS-SCZ.

We used multinomial logistic regression to examine possible differences between groups by computing risk ratios (RRs), i.e., ratios of the probability of pertaining to a particular group divided by the probability of healthy control status. We also computed PRS-informed odd ratios (ORs) for clozapine use relative to other antipsychotics.

PRSs-SCZ were generated for 2344 participants (mean age: 36.95 years; 42.4% female) remaining after quality control (557 individuals with SSD on clozapine, 350 individuals with SSD on other antipsychotics during six-year follow-up, 542 parents and 574 siblings of individuals with SSD, and 321 unrelated healthy controls). All RRs were significantly different from 1; RRs were highest for individuals with SSD on clozapine (RR=3.24 [95%CI 2.76-3.81], p=2.47x10-46), followed by individuals with SSD on other antipsychotics (RR=2.30 [95%CI 1.95-2.72], p=3.77x10-22), parents (RR=1.44 [95%CI 1.25-1.68], p=1.76x10-6), and siblings (RR=1.40 [95%CI 1.21-1.63], p=8.22x10-6). PRS-SCZ was positively associated with clozapine versus other antipsychotic use (OR=1.41 [95%CI 1.22-1.63], p=2.98x10-6), suggesting a higher likelihood of clozapine prescriptions in individuals with higher PRS-SCZ.

PRS-SCZ loading differs between groups of individuals with SSD, their relatives, and unrelated healthy controls, with clozapine users being at the far end of PRS-SCZ loading. Additionally, PRS-SCZ is associated with a higher likelihood of clozapine prescribing. Our findings may inform early intervention and prognostic studies into the value of PRS-SCZ for personalized antipsychotic treatment.

None Declared

There is an urgent need for sustainable thinking and practices in healthcare systems to meet the challenge of climate change (Charlesworth & Jamieson, 2019; Corvalan et al., 2020; Luykx & Voetterl, 2022; Madden et al., 2020). This need is accelerated by the recent energy crisis. According to an international NGO policy paper (Karliner et al., 2019) healthcare institutions are large energy consumers and major emitters. The (mental) health sectors of the Netherlands and Flanders, the northern part of Belgium, also greatly contribute to the global climate crisis. Both regions have per capita emissions (between the 0.50t and 1t) that fall just below the world’s healthcare top emitters.

To evaluate the state of sustainability in Dutch and Flemish mental health institutions (including psychiatric hospitals, rehabilitation centers, and community mental health centers) and assess whether certain differences can be found in the climate policies of these institutions between both regions.

Board members of mental health institutions were asked to complete a 20-item online survey in which concrete actions, objectives and ambitions in the field of sustainability were questioned. Frequencies and percentages were calculated for each question. For certain topics chi-squared tests were performed to test differences in sustainability issues addressed in the questionnaire between Dutch and Flemish mental healthcare institutions.

Survey response rates for Dutch and Flemish mental health institutions were 38% and 20%, respectively. Ninety-five percent and 38% of respectively the Dutch and Flemish institutions fully agreed that sustainability is a very important theme (χ2(1)=2,25, p=0,13). Key focus areas in both regions included sustainable energy transition (with half of the mental health institutions sourcing at least half of their energy via renewable energy resources and technologies) and recycling (almost 80% of the institutions). Statistically significant differences were found between both regions with regard to monitoring the environmental impact (Flanders 24% vs. The Netherlands 60%, χ2(1)=6,41, p=0,01) and fostering more sustainable commutes (Flanders 72% vs. The Netherlands 15%, χ2(1)=17,35, p<0,0001). The climate impact of medicines and food, as well as investments in sustainable projects, received little attention.

Although a substantial part of Dutch and Flemish mental health institutions consider sustainability (very) important, a systemic ‘transformation’ will be necessary to make them climate neutral, as tenets of practicing mental healthcare sustainably include more than sustainable energy transition and recycling (Monsell et al., 2021). Moreover, a lack of sufficient investment opportunities, partly due to a lack of financial resources, seems to be the main barrier for many mental healthcare institutions for quickly reaching sustainability goals.

None Declared

Research on the effectiveness of pharmacotherapies for schizophrenia and comorbid substance use disorder (SUD) is very sparse, and non-existent on the prevention of the development of SUDs in patients with schizophrenia.

To compare the real-world effectiveness of antipsychotics in schizophrenia in decreasing risk of developing an initial SUD, and psychiatric hospital admission and SUD-related hospital admission among patients with an SUD.

Two independent national cohorts including all persons diagnosed with schizophrenia (N = 45 476) were followed up for 22 (Finland: 1996–2017) and 11 (Sweden: 2006–2016) years. Risk of developing an SUD was calculated with between-individual models, and risks of psychiatric and SUD-related hospital admission were calculated with within-individual models, using Cox regression and adjusted hazard ratios (aHRs) for using versus not using certain antipsychotics.

For patients with schizophrenia without an SUD, clozapine use (Finland: aHR 0.20, 95% CI 0.16–0.24, P < 0.001; Sweden: aHR 0.35, 95% CI 0.24–0.50, P < 0.001) was associated with lowest risk of developing an initial SUD in both countries. Antipsychotic polytherapy was associated with second lowest risk (aHR 0.54, 95% CI 0.44–0.66) in Sweden, and third lowest risk (aHR 0.47, 95% CI 0.42–0.53) in Finland. Risk of relapse (psychiatric hospital admission and SUD-related hospital admission) were lowest for clozapine, antipsychotic polytherapy and long-acting injectables in both countries. Results were consistent across both countries.

Clozapine and antipsychotic polytherapy are most strongly associated with reduced risk of developing SUDs among patients with schizophrenia, and with lower relapse rates among patients with both diagnoses.

There is evidence for a polygenic contribution to psychosis. One targetable mechanism through which polygenic variation may impact on individuals and interact with the social environment is stress sensitization, characterized by elevated reactivity to minor stressors in daily life. The current study aimed to investigate whether stress reactivity is modified by polygenic risk score for schizophrenia (PRS) in cases with enduring non-affective psychotic disorder, first-degree relatives of cases, and controls.

We used the experience sampling method to assess minor stressors, negative affect, positive affect and psychotic experiences in 96 cases, 79 first-degree relatives, i.e. siblings, and 73 controls at wave 3 of the Dutch Genetic Risk and Outcome of Psychosis (GROUP) study. Genome-wide data were collected at baseline to calculate PRS.

We found that associations of momentary stress with psychotic experiences, but not with negative and positive affect, were modified by PRS and group (all pFWE<0.001). In contrast to our hypotheses, siblings with high PRS reported less intense psychotic experiences in response to momentary stress compared to siblings with low PRS. No differences in magnitude of these associations were observed in cases with high v. low level of PRS. By contrast, controls with high PRS showed more intense psychotic experiences in response to stress compared to those with low PRS.

This tentatively suggests that polygenic risk may operate in different ways than previously assumed and amplify reactivity to stress in unaffected individuals but operate as a resilience factor in relatives by attenuating their stress reactivity.

Previous studies into mental health service utilisation during the COVID-19 pandemic are limited to a few countries or specific type of service. In addition, data on changes in telepsychiatry are currently lacking.

We aimed to investigate whether the COVID-19 pandemic is associated with changes in mental health service utilisation, including telepsychiatry, and how these changes were distributed among patients with mental illness during the first COVID-19 outbreak.

This retrospective study obtained routinely assessed healthcare data from a large Dutch mental healthcare institute. Data from the second quarter of 2020 (the first COVID-19 outbreak period) were compared with the pre-pandemic period between January 2018 and March 2020. Time-series analyses were performed with the quasi-Poisson generalised linear model, to examine the effect of the COVID-19 lockdown and the overall trend of mental health service utilisation per communication modality and diagnostic category.

We analysed 204 808 care contacts of 28 038 patients. The overall number of care contacts in the second quarter of 2020 remained the same as in the previous 2 years, because the number of video consultations significantly increased (B = 2.17, P = 0.488 × 10−3) as the number of face-to-face out-patient contacts significantly decreased (B = −0.98, P = 0.011). This was true for all different diagnostic categories, although this change was less pronounced in patients with psychotic disorders.

Diminished face-to-face out-patient contacts were well-compensated by the substantial increase of video consultations during the first COVID-19 outbreak in The Netherlands. This increase was less pronounced for psychotic disorders. Further research should elucidate the need for disorder-specific digital mental healthcare delivery.

It has not yet been determined if the commonly reported cannabis–psychosis association is limited to individuals with pre-existing genetic risk for psychotic disorders.

We examined whether the relationship between polygenic risk score for schizophrenia (PRS-Sz) and psychotic-like experiences (PLEs), as measured by the Community Assessment of Psychic Experiences-42 (CAPE-42) questionnaire, is mediated or moderated by lifetime cannabis use at 16 years of age in 1740 of the individuals of the European IMAGEN cohort. Secondary analysis examined the relationships between lifetime cannabis use, PRS-Sz and the various sub-scales of the CAPE-42. Sensitivity analyses including covariates, including a PRS for cannabis use, were conducted and results were replicated using data from 1223 individuals in the Dutch Utrecht cannabis cohort.

PRS-Sz significantly predicted cannabis use (p = 0.027) and PLE (p = 0.004) in the IMAGEN cohort. In the full model, considering PRS-Sz and covariates, cannabis use was also significantly associated with PLE in IMAGEN (p = 0.007). Results remained consistent in the Utrecht cohort and through sensitivity analyses. Nevertheless, there was no evidence of a mediation or moderation effects.

These results suggest that cannabis use remains a risk factor for PLEs, over and above genetic vulnerability for schizophrenia. This research does not support the notion that the cannabis–psychosis link is limited to individuals who are genetically predisposed to psychosis and suggests a need for research focusing on cannabis-related processes in psychosis that cannot be explained by genetic vulnerability.

A transdiagnostic and contextual framework of ‘clinical characterization’, combining clinical, psychopathological, sociodemographic, etiological, and other personal contextual data, may add clinical value over and above categorical algorithm-based diagnosis.

Prediction of need for care and health care outcomes was examined prospectively as a function of the contextual clinical characterization diagnostic framework in a prospective general population cohort (n = 6646 at baseline), interviewed four times between 2007 and 2018 (NEMESIS-2). Measures of need, service use, and use of medication were predicted as a function of any of 13 DSM-IV diagnoses, both separately and in combination with clinical characterization across multiple domains: social circumstances/demographics, symptom dimensions, physical health, clinical/etiological factors, staging, and polygenic risk scores (PRS). Effect sizes were expressed as population attributable fractions.

Any prediction of DSM-diagnosis in relation to need and outcome in separate models was entirely reducible to components of contextual clinical characterization in joint models, particularly the component of transdiagnostic symptom dimensions (a simple score of the number of anxiety, depression, mania, and psychosis symptoms) and staging (subthreshold, incidence, persistence), and to a lesser degree clinical factors (early adversity, family history, suicidality, slowness at interview, neuroticism, and extraversion), and sociodemographic factors. Clinical characterization components in combination predicted more than any component in isolation. PRS did not meaningfully contribute to any clinical characterization model.

A transdiagnostic framework of contextual clinical characterization is of more value to patients than a categorical system of algorithmic ordering of psychopathology.

Schizophrenia is highly comorbid with substance use disorders (SUD), which may negatively impact the course of illness. However, large studies exploring the best lines of treatment for this combination are lacking.

We investigated what are the most effective antipsychotics for patients with schizophrenia in preventing the development of substance use disorders and preventing hospitalizations in patients already having substance use disorder.

We used two independent national cohort registries including all patient with schizophrenia aged under 46 years. Participants were followed during 22 (1996–2017, Finland) and 11 years (2006–2016, Sweden). We studied risk of rehospitalization, and risk of developing an SUD when using vs. not using antipsychotics, using Cox proportional hazards regression analysis models.

45,476 patients with schizophrenia were identified (30,860 in Finland; 14,616 in Sweden). For patients without SUD, clozapine and antipsychotic polytherapy were associated with the lowest risks of developing SUD in both countries. For patients with co-existing SUD, the risk of hospitalization was the lowest during clozapine, polytherapy and long-acting injectable use.

In patients with schizophrenia and comorbid SUD, antipsychotic medications were effective in preventing relapses. In those without an SUD, antipsychotic use was associated with a markedly reduced risk of developing an initial SUD. Clozapine and long-acting injectables should be considered treatments of choice in patients with schizophrenia and SUD, or at risk of developing co-morbid SUD.

ML: Genomi Solutions Ltd, DNE Ltd, Sunovion, Orion Pharma, Janssen-Cilag, Finnish Medical Foundation, Emil Aaltonen Foundation. HT, EMR, AT: Eli Lilly, Janssen–Cilag. JT: Eli Lilly, Janssen-Cilag, Lundbeck, Otsuka.

Schizophrenia is highly comorbid with substance use disorders (SUD) but large epidemiological cohorts exploring the prevalence and prognostic significance of SUD are lacking.

To investigate the prevalence of SUD in patients with schizophrenia in Finland and Sweden, and the effect of these co-occurring disorders on risks of psychiatric hospitalization and mortality.

45,476 individuals with schizophrenia from two independent national cohort studies, aged <46 years at cohort entry, were followed during 22 (1996-2017, Finland) and 11 years (2006-2016, Sweden). We first assessed SUD prevalence (excluding smoking). Then we performed Cox regression on risk of psychiatric hospitalization and mortality in patients with schizohrenia and SUD compared with those without SUD.

The prevalence of SUD in specialized healthcare ranged from 26% (Finland) to 31% (Sweden). Multiple drug use and alcohol use disorders were the most prevalent SUD, followed by cannabis use disorders. Any SUD comorbidity, and particularly multiple drug use and alcohol use, were associated with 50% to 100% increases in hospitalization and mortality compared to individuals without SUD. Elevated mortality risks were observed especially for deaths due to suicide and other external causes. All results were similar across countries.

Co-occurring SUD, and particularly alcohol and multiple drug use, are associated with high rates of hospitalization and mortality in patients with schizophrenia. Preventive interventions should prioritize detection and tailored treatments for these co-morbidities, which often remain underdiagnosed and untreated.

ML: Genomi Solutions Ltd, Nursie Health Ltd, Sunovion, Orion Pharma, Janssen-Cilag, Finnish Medical Foundation, Emil Aaltonen Foundation. HT, EMR, AT: Eli Lilly, Janssen–Cilag. JT: Eli Lilly, Janssen-Cilag, Lundbeck, Otsuka.

Alcohol consumption, smoking and mood disorders are leading contributors to the global burden of disease and are highly comorbid. Yet, their interrelationships have remained elusive. The aim of this study was to examine the multi-cross-sectional and longitudinal associations between (change in) smoking and alcohol use and (change in) number of depressive symptoms.

In this prospective, longitudinal study, 6646 adults from the general population were included with follow-up measurements after 3 and 6 years. Linear mixed-effects models were used to test multi-cross-sectional and longitudinal associations, with smoking behaviour, alcohol use and genetic risk scores for smoking and alcohol use as independent variables and depressive symptoms as dependent variables.

In the multi-cross-sectional analysis, smoking status and number of cigarettes per day were positively associated with depressive symptoms (p < 0.001). Moderate drinking was associated with less symptoms of depression compared to non-use (p = 0.011). Longitudinally, decreases in the numbers of cigarettes per day and alcoholic drinks per week as well as alcohol cessation were associated with a reduction of depressive symptoms (p = 0.001–0.028). Results of genetic risk score analyses aligned with these findings.

While cross-sectionally smoking and moderate alcohol use show opposing associations with depressive symptoms, decreases in smoking behaviour as well as alcohol consumption are associated with improvements in depressive symptoms over time. Although we cannot infer causality, these results open avenues to further investigate interventions targeting smoking and alcohol behaviours in people suffering from depressive symptoms.

Although attenuated psychotic symptoms in the psychosis clinical high-risk state (CHR-P) almost always occur in the context of a non-psychotic disorder (NPD), NPD is considered an undesired ‘comorbidity’ epiphenomenon rather than an integral part of CHR-P itself. Prospective work, however, indicates that much more of the clinical psychosis incidence is attributable to prior mood and drug use disorders than to psychosis clinical high-risk states per se. In order to examine this conundrum, we analysed to what degree the ‘risk’ in CHR-P is indexed by co-present NPD rather than attenuated psychosis per se.

We examined the incidence of early psychotic experiences (PE) with and without NPD (mood disorders, anxiety disorders, alcohol/drug use disorders), in a prospective general population cohort (n = 6123 at risk of incident PE at baseline). Four interview waves were conducted between 2007 and 2018 (NEMESIS-2). The incidence of PE, alone (PE-only) or with NPD (PE + NPD) was calculated, as were differential associations with schizophrenia polygenic risk score (PRS-Sz), environmental, demographical, clinical and cognitive factors.

The incidence of PE + NPD (0.37%) was lower than the incidence of PE-only (1.04%), representing around a third of the total yearly incidence of PE. Incident PE + NPD was, in comparison with PE-only, differentially characterised by poor functioning, environmental risks, PRS-Sz, positive family history, prescription of antipsychotic medication and (mental) health service use.

The risk in ‘clinical high risk’ states is mediated not by attenuated psychosis per se but specifically the combination of attenuated psychosis and NPD. CHR-P/APS research should be reconceptualised from a focus on attenuated psychotic symptoms with exclusion of non-psychotic DSM-disorders, as the ‘pure' representation of a supposedly homotypic psychosis risk state, towards a focus on poor-outcome NPDs, characterised by a degree of psychosis admixture, on the pathway to psychotic disorder outcomes.

A cumulative environmental exposure score for schizophrenia (exposome score for schizophrenia [ES-SCZ]) may provide potential utility for risk stratification and outcome prediction. Here, we investigated whether ES-SCZ was associated with functioning in patients with schizophrenia spectrum disorder, unaffected siblings, and healthy controls.

This cross-sectional sample consisted of 1,261 patients, 1,282 unaffected siblings, and 1,525 healthy controls. The Global Assessment of Functioning (GAF) scale was used to assess functioning. ES-SCZ was calculated based on our previously validated method. The association between ES-SCZ and the GAF dimensions (symptom and disability) was analyzed by applying regression models in each group (patients, siblings, and controls). Additional models included polygenic risk score for schizophrenia (PRS-SCZ) as a covariate.

ES-SCZ was associated with the GAF dimensions in patients (symptom: B = −1.53, p-value = 0.001; disability: B = −1.44, p-value = 0.001), siblings (symptom: B = −3.07, p-value < 0.001; disability: B = −2.52, p-value < 0.001), and healthy controls (symptom: B = −1.50, p-value < 0.001; disability: B = −1.31, p-value < 0.001). The results remained the same after adjusting for PRS-SCZ. The degree of associations of ES-SCZ with both symptom and disability dimensions were higher in unaffected siblings than in patients and controls. By analyzing an independent dataset (the Genetic Risk and Outcome of Psychosis study), we replicated the results observed in the patient group.

Our findings suggest that ES-SCZ shows promise for enhancing risk prediction and stratification in research practice. From a clinical perspective, ES-SCZ may aid in efforts of clinical characterization, operationalizing transdiagnostic clinical staging models, and personalizing clinical management.

Schizophrenia negatively affects quality of life (QoL). A handful of variables from small studies have been reported to influence QoL in patients with schizophrenia, but a study comprehensively dissecting the genetic and non-genetic contributing factors to QoL in these patients is currently lacking.

We adopted a hypothesis-generating approach to assess the phenotypic and genotypic determinants of QoL in schizophrenia.

The study population comprised 1119 patients with a psychotic disorder, 1979 relatives and 586 healthy controls. Using linear regression, we tested >100 independent demographic, cognitive and clinical phenotypes for their association with QoL in patients. We then performed genome-wide association analyses of QoL and examined the association between polygenic risk scores for schizophrenia, major depressive disorder and subjective well-being and QoL.

We found nine phenotypes to be significantly and independently associated with QoL in patients, the most significant ones being negative (β = −1.17; s.e. 0.05; P = 1 × 10–83; r2 = 38%), depressive (β = −1.07; s.e. 0.05; P = 2 × 10–79; r2 = 36%) and emotional distress (β = −0.09; s.e. 0.01; P = 4 × 10–59, r2 = 25%) symptoms. Schizophrenia and subjective well-being polygenic risk scores, using various P-value thresholds, were significantly and consistently associated with QoL (lowest association P-value = 6.8 × 10–6). Several sensitivity analyses confirmed the results.

Various clinical phenotypes of schizophrenia, as well as schizophrenia and subjective well-being polygenic risk scores, are associated with QoL in patients with schizophrenia and their relatives. These may be targeted by clinicians to more easily identify vulnerable patients with schizophrenia for further social and clinical interventions to improve their QoL.

Psychosis spectrum disorder has a complex pathoetiology characterised by interacting environmental and genetic vulnerabilities. The present study aims to investigate the role of gene–environment interaction using aggregate scores of genetic (polygenic risk score for schizophrenia (PRS-SCZ)) and environment liability for schizophrenia (exposome score for schizophrenia (ES-SCZ)) across the psychosis continuum.

The sample consisted of 1699 patients, 1753 unaffected siblings, and 1542 healthy comparison participants. The Structured Interview for Schizotypy-Revised (SIS-R) was administered to analyse scores of total, positive, and negative schizotypy in siblings and healthy comparison participants. The PRS-SCZ was trained using the Psychiatric Genomics Consortiums results and the ES-SCZ was calculated guided by the approach validated in a previous report in the current data set. Regression models were applied to test the independent and joint effects of PRS-SCZ and ES-SCZ (adjusted for age, sex, and ancestry using 10 principal components).

Both genetic and environmental vulnerability were associated with case-control status. Furthermore, there was evidence for additive interaction between binary modes of PRS-SCZ and ES-SCZ (above 75% of the control distribution) increasing the odds for schizophrenia spectrum diagnosis (relative excess risk due to interaction = 6.79, [95% confidential interval (CI) 3.32, 10.26], p < 0.001). Sensitivity analyses using continuous PRS-SCZ and ES-SCZ confirmed gene–environment interaction (relative excess risk due to interaction = 1.80 [95% CI 1.01, 3.32], p = 0.004). In siblings and healthy comparison participants, PRS-SCZ and ES-SCZ were associated with all SIS-R dimensions and evidence was found for an interaction between PRS-SCZ and ES-SCZ on the total (B = 0.006 [95% CI 0.003, 0.009], p < 0.001), positive (B = 0.006 [95% CI, 0.002, 0.009], p = 0.002), and negative (B = 0.006, [95% CI 0.004, 0.009], p < 0.001) schizotypy dimensions.

The interplay between exposome load and schizophrenia genetic liability contributing to psychosis across the spectrum of expression provide further empirical support to the notion of aetiological continuity underlying an extended psychosis phenotype.

There is evidence that environmental and genetic risk factors for schizophrenia spectrum disorders are transdiagnostic and mediated in part through a generic pathway of affective dysregulation.

We analysed to what degree the impact of schizophrenia polygenic risk (PRS-SZ) and childhood adversity (CA) on psychosis outcomes was contingent on co-presence of affective dysregulation, defined as significant depressive symptoms, in (i) NEMESIS-2 (n = 6646), a representative general population sample, interviewed four times over nine years and (ii) EUGEI (n = 4068) a sample of patients with schizophrenia spectrum disorder, the siblings of these patients and controls.

The impact of PRS-SZ on psychosis showed significant dependence on co-presence of affective dysregulation in NEMESIS-2 [relative excess risk due to interaction (RERI): 1.01, p = 0.037] and in EUGEI (RERI = 3.39, p = 0.048). This was particularly evident for delusional ideation (NEMESIS-2: RERI = 1.74, p = 0.003; EUGEI: RERI = 4.16, p = 0.019) and not for hallucinatory experiences (NEMESIS-2: RERI = 0.65, p = 0.284; EUGEI: −0.37, p = 0.547). A similar and stronger pattern of results was evident for CA (RERI delusions and hallucinations: NEMESIS-2: 3.02, p < 0.001; EUGEI: 6.44, p < 0.001; RERI delusional ideation: NEMESIS-2: 3.79, p < 0.001; EUGEI: 5.43, p = 0.001; RERI hallucinatory experiences: NEMESIS-2: 2.46, p < 0.001; EUGEI: 0.54, p = 0.465).

The results, and internal replication, suggest that the effects of known genetic and non-genetic risk factors for psychosis are mediated in part through an affective pathway, from which early states of delusional meaning may arise.