Dissecting the exposome linked to mental health outcomes can help identify potentially modifiable targets to improve mental well-being. However, the multiplicity of exposures and the complexity of mental health phenotypes pose a challenge that requires data-driven approaches.

Guided by our previous systematic approach, we conducted hypothesis-free exposome-wide analyses to identify factors associated with 7 psychiatric diagnostic domains and 19 symptom dimensions in 157,298 participants from the UK Biobank Mental Health Survey. After quality control, 294 environmental, lifestyle, behavioral, and economic variables were included. An Exposome-Wide Association Study was conducted per outcome in two equally split datasets. Variables associated with each outcome were then tested in a multivariable model.

Across all diagnostic domains and symptom dimensions, the top three exposures were childhood adversities and traumatic events. Cannabis use was associated with common psychiatric disorders (depressive, anxiety, psychotic, and bipolar manic disorders), with ORs ranging from 1.10 to 1.79 in the multivariable models. Additionally, differential associations were identified between specific outcomes—such as neurodevelopmental disorders, eating disorders, and self-harm behaviors—and exposures, including early life experiences (being adopted), lifestyle (time spent using computers), and dietary habits (vegetarian diet).

This comprehensive mapping of the exposome revealed that several factors, particularly in the domains of those previously well-studied were shared across mental health phenotypes, providing further support for transdiagnostic pathoetiology. Our findings also showed that distinct relations might exist. Continued exposome research through multimodal mechanistic studies guided by the transdiagnostic mental health framework is required to better inform public health policies.

Empirical evidence suggests that people use cannabis to ameliorate anxiety and depressive symptoms, yet cannabis also acutely worsens psychosis and affective symptoms. However, the temporal relationship between cannabis use, anxiety and depressive symptoms and psychotic experiences (PE) in longitudinal studies is unclear. This may be informed by examination of mutually mediating roles of cannabis, anxiety and depressive symptoms in the emergence of PE.

Data were derived from the second longitudinal Netherlands Mental Health Survey and Incidence Study. Mediation analysis was performed to examine the relationship between cannabis use, anxiety/depressive symptoms and PE, using KHB logit in STATA while adjusting for age, sex and education status.

Cannabis use was found to mediate the relationship between preceding anxiety, depressive symptoms and later PE incidence, but the indirect contribution of cannabis use was small (for anxiety: % of total effect attributable to cannabis use = 1.00%; for depression: % of total effect attributable to cannabis use = 1.4%). Interestingly, anxiety and depressive symptoms were found to mediate the relationship between preceding cannabis use and later PE incidence to a greater degree (% of total effect attributable to anxiety = 17%; % of total effect attributable to depression = 37%).

This first longitudinal cohort study examining the mediational relationship between cannabis use, anxiety/depressive symptoms and PE, shows that there is a bidirectional relationship between cannabis use, anxiety/depressive symptoms and PE. However, the contribution of anxiety/depressive symptoms as a mediator was greater than that of cannabis.

Evidence suggests that environmental factors not only increase psychosis liability but also influence the prognosis and outcomes of psychotic disorders. We investigated temporal and cross-sectional associations of a weighted score of cumulative environmental liability for schizophrenia – the exposome score for schizophrenia (ES-SCZ) – with functioning in first-episode psychosis (FEP).

Data were derived from the baseline and 1-month assessments of the Athens FEP Research Study that enrolled 225 individuals with FEP. The Global Assessment of Functioning (GAF) and the Personal and Social Performance Scale (PSP) were used to measure social, occupational, and psychological functioning. The ES-SCZ was calculated based on the previously validated method.

ES-SCZ was associated with the total scores of GAF and PSP at baseline and 1-month assessments. These findings remained significant when accounting for several associated alternative explanatory variables, including other environmental factors (obstetric complications, migration, ethnic minority), clinical characteristics (duration of untreated psychosis, symptom severity, previous antipsychotic use), and family history of psychosis, demonstrating that the association between ES-SCZ and functioning is over and above other risk factors and cannot be explained by symptom severity alone. Functioning improved from baseline to 1-month assessment, but no significant ES-SCZ-by-time interaction was found on functioning, indicating that functioning changes were not contingent on ES-SCZ.

Our findings suggest that rather than a predictor of functional improvement, ES-SCZ represents a stable severity indicator that captures poor functioning in early psychosis. Environmental risk loading for schizophrenia (ES-SCZ) can be beneficial for clinical characterization and incorporated into transdiagnostic staging models.

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.

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.

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.

Contemporary models of psychosis implicate the importance of affective dysregulation and cognitive factors (e.g. biases and schemas) in the development and maintenance of psychotic symptoms, but studies testing proposed mechanisms remain limited. This study, uniquely using a prospective design, investigated whether the jumping to conclusions (JTC) reasoning bias contributes to psychosis progression and persistence.

Data were derived from the second Netherlands Mental Health Survey and Incidence Study (NEMESIS-2). The Composite International Diagnostic Interview and an add-on instrument were used to assess affective dysregulation (i.e. depression, anxiety and mania) and psychotic experiences (PEs), respectively. The beads task was used to assess JTC bias. Time series analyses were conducted using data from T1 and T2 (N = 8666), excluding individuals who reported high psychosis levels at T0.

Although the prospective design resulted in low statistical power, the findings suggest that, compared to those without symptoms, individuals with lifetime affective dysregulation were more likely to progress from low/moderate psychosis levels (state of ‘aberrant salience’, one or two PEs) at T1 to high psychosis levels (‘frank psychosis’, three or more PEs or psychosis-related help-seeking behaviour) at T2 if the JTC bias was present [adj. relative risk ratio (RRR): 3.8, 95% confidence interval (CI) 0.8–18.6, p = 0.101]. Similarly, the JTC bias contributed to the persistence of high psychosis levels (adj. RRR: 12.7, 95% CI 0.7–239.6, p = 0.091).

We found some evidence that the JTC bias may contribute to psychosis progression and persistence in individuals with affective dysregulation. However, well-powered prospective studies are needed to replicate these findings.

First-degree relatives of patients with psychotic disorder have higher levels of polygenic risk (PRS) for schizophrenia and higher levels of intermediate phenotypes.

We conducted, using two different samples for discovery (n = 336 controls and 649 siblings of patients with psychotic disorder) and replication (n = 1208 controls and 1106 siblings), an analysis of association between PRS on the one hand and psychopathological and cognitive intermediate phenotypes of schizophrenia on the other in a sample at average genetic risk (healthy controls) and a sample at higher than average risk (healthy siblings of patients). Two subthreshold psychosis phenotypes, as well as a standardised measure of cognitive ability, based on a short version of the WAIS-III short form, were used. In addition, a measure of jumping to conclusion bias (replication sample only) was tested for association with PRS.

In both discovery and replication sample, evidence for an association between PRS and subthreshold psychosis phenotypes was observed in the relatives of patients, whereas in the controls no association was observed. Jumping to conclusion bias was similarly only associated with PRS in the sibling group. Cognitive ability was weakly negatively and non-significantly associated with PRS in both the sibling and the control group.

The degree of endophenotypic expression of schizophrenia polygenic risk depends on having a sibling with psychotic disorder, suggestive of underlying gene–environment interaction. Cognitive biases may better index genetic risk of disorder than traditional measures of neurocognition, which instead may reflect the population distribution of cognitive ability impacting the prognosis of psychotic disorder.

Evidence suggests that cannabis use, childhood adversity, and urbanicity, in interaction with proxy measures of genetic risk, may facilitate onset of psychosis in the sense of early affective dysregulation becoming ‘complicated’ by, first, attenuated psychosis and, eventually, full-blown psychotic symptoms.

Data were derived from three waves of the second Netherlands Mental Health Survey and Incidence Study (NEMESIS-2). The impact of environmental risk factors (cannabis use, childhood adversity, and urbanicity) was analyzed across severity levels of psychopathology defined by the degree to which affective dysregulation was ‘complicated’ by low-grade psychotic experiences (‘attenuated psychosis’ – moderately severe) and, overt psychotic symptoms leading to help-seeking (‘clinical psychosis’ – most severe). Familial and non-familial strata were defined based on family history of (mostly) affective disorder and used as a proxy for genetic risk in models of family history × environmental risk interaction.

In proxy gene–environment interaction analysis, childhood adversity and cannabis use, and to a lesser extent urbanicity, displayed greater-than-additive risk if there was also evidence of familial affective liability. In addition, the interaction contrast ratio grew progressively greater across severity levels of psychosis admixture (none, attenuated psychosis, clinical psychosis) complicating affective dysregulation.

Known environmental risks interact with familial evidence of affective liability in driving the level of psychosis admixture in states of early affective dysregulation in the general population, constituting an affective pathway to psychosis. There is interest in decomposing family history of affective liability into the environmental and genetic components that underlie the interactions as shown here.

The jumping to conclusions (JTC) reasoning bias and decreased working memory performance (WMP) are associated with psychosis, but associations with affective disturbances (i.e. depression, anxiety, mania) remain inconclusive. Recent findings also suggest a transdiagnostic phenotype of co-occurring affective disturbances and psychotic experiences (PEs). This study investigated whether JTC bias and decreased WMP are associated with co-occurring affective disturbances and PEs.

Data were derived from the second Netherlands Mental Health Survey and Incidence Study (NEMESIS-2). Trained interviewers administered the Composite International Diagnostic Interview (CIDI) at three time points in a general population sample (N = 4618). The beads and digit-span task were completed to assess JTC bias and WMP, respectively. CIDI was used to measure affective disturbances and an add-on instrument to measure PEs.

Compared to individuals with neither affective disturbances nor PEs, the JTC bias was more likely to occur in individuals with co-occurring affective disturbances and PEs [moderate psychosis (1–2 PEs): adjusted relative risk ratio (RRR) 1.17, 95% CI 0.98–1.41; and high psychosis (3 or more PEs or psychosis-related help-seeking behaviour): adjusted RRR 1.57, 95% CI 1.19–2.08], but not with affective disturbances and PEs alone, whereas decreased WMP was more likely in all groups. There was some evidence of a dose–response relationship, as JTC bias and decreased WMP were more likely in individuals with affective disturbances as the level of PEs increased or help-seeking behaviour was reported.

The findings suggest that JTC bias and decreased WMP may contribute to a transdiagnostic phenotype of co-occurring affective disturbances and PEs.