The clinical high-risk (CHR) state for psychosis demonstrates considerable clinical heterogeneity, presenting challenges for clinicians and researchers alike. Basic symptoms, to date, have largely been ignored in explorations of clinical profiles.

We examined clinical profiles by using a broader spectrum of CHR symptoms, including not only (attenuated) psychotic, but also basic symptoms.

Patients (N = 875) of specialised early intervention centres for psychosis in Germany and Switzerland were assessed with the Schizophrenia Proneness Instruments and the Structured Interview for Psychosis-Risk Syndromes. Latent class analysis was applied to CHR symptoms to identify clinical profiles. Additionally, demographics, other symptoms, current non-psychotic DSM-IV axis I disorders and neurocognitive variables were assessed to further describe and compare the profiles.

A three-class model was best fitting the data, whereby basic symptoms best differentiated between the profiles (η2 = 0.08–0.52). Class 1 had a low probability of CHR symptoms, the highest functioning and lowest other psychopathology, neurocognitive deficits and transition-to-psychosis rate. Class 2 had the highest probability of basic and (attenuated) positive symptoms (excluding hallucinations), lowest functioning, highest symptom load, most neurocognitive deficits and highest transition rate (55.1%). Class 3 was mostly characterised by attenuated hallucination, and was otherwise intermediate between the other two classes. Comorbidity rates were comparable across classes, with some class differences in diagnostic categories.

Our profiles based on basic and (attenuated) psychotic symptoms provide clinically useful entities by parsing out heterogeneity in clinical presentation. In future, they could guide class-specific intervention.

Computational models offer promising potential for personalised treatment of psychiatric diseases. For their clinical deployment, fairness must be evaluated alongside accuracy. Fairness requires predictive models to not unfairly disadvantage specific demographic groups. Failure to assess model fairness prior to use risks perpetuating healthcare inequalities. Despite its importance, empirical investigation of fairness in predictive models for psychiatry remains scarce.

To evaluate fairness in prediction models for development of psychosis and functional outcome.

Using data from the PRONIA study, we examined fairness in 13 published models for prediction of transition to psychosis (n = 11) and functional outcome (n = 2) in people at clinical high risk for psychosis or with recent-onset depression. Using accuracy equality, predictive parity, false-positive error rate balance and false-negative error rate balance, we evaluated relevant fairness aspects for the demographic attributes ‘gender’ and ‘educational attainment’ and compared them with the fairness of clinicians’ judgements.

Our findings indicate systematic bias towards assigning less favourable outcomes to individuals with lower educational attainment in both prediction models and clinicians’ judgements, resulting in higher false-positive rates in 7 of 11 models for transition to psychosis. Interestingly, the bias patterns observed in algorithmic predictions were not significantly more pronounced than those in clinicians’ predictions.

Educational bias was present in algorithmic and clinicians’ predictions, assuming more favourable outcomes for individuals with higher educational level (years of education). This bias might lead to increased stigma and psychosocial burden in patients with lower educational attainment and suboptimal psychosis prevention in those with higher educational attainment.

Neurocognitive deficits are a core feature of psychosis and depression. Despite commonalities in cognitive alterations, it remains unclear if and how the cognitive deficits in patients at clinical high risk for psychosis (CHR) and those with recent-onset psychosis (ROP) are distinct from those seen in recent-onset depression (ROD).

This study was carried out within the European project ‘Personalized Prognostic Tools for Early Psychosis Management’, and aimed to characterise the cognitive profiles of patients with psychosis or depression.

We examined cognitive profiles for patients with ROP (n = 105), patients with ROD (n = 123), patients at CHR (n = 116) and healthy controls (n = 372) across seven sites in five European countries. Confirmatory factor analysis identified four cognitive factors independent of gender, education and site: speed of processing, attention and working memory, verbal learning and spatial learning.

Patients with ROP performed worse than healthy controls in all four domains (P < 0.001), whereas performance of patients with ROD was not affected (P > 0.05). Patients at CHR performed worse than healthy controls in speed of processing (P = 0.001) and spatial learning (P = 0.003), but better than patients with ROP across all cognitive domains (all P ≤ 0.01). CHR and ROD groups did not significantly differ in any cognitive domain. These findings were independent of comorbid depressive symptoms, substance consumption and illness duration.

These results show that neurocognitive abilities are affected in CHR and ROP, whereas ROD seems spared. Although our findings may support the notion that those at CHR have a specific vulnerability to psychosis, future studies investigating broader transdiagnostic risk cohorts in longitudinal designs are needed.

Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression.

A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15–41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1–2 s.d. below or above HC, respectively) for each cognitive test.

Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP.

These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.

Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning.

We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample.

Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD).

Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD.

Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.

Psychosis expression in the general population may reflect a behavioral manifestation of the risk for psychotic disorder. It can be conceptualized as an interconnected system of psychotic and affective experiences; a so-called ‘symptom network’. Differences in demographics, as well as exposure to adversities and risk factors, may produce substantial heterogeneity in symptom networks, highlighting potential etiological divergence in psychosis risk.

To explore this idea in a data-driven way, we employed a novel recursive partitioning approach in the 2007 English National Survey of Psychiatric Morbidity (N = 7242). We sought to identify ‘network phenotypes’ by explaining heterogeneity in symptom networks through potential moderators, including age, sex, ethnicity, deprivation, childhood abuse, separation from parents, bullying, domestic violence, cannabis use, and alcohol.

Sex was the primary source of heterogeneity in symptom networks. Additional heterogeneity was explained by interpersonal trauma (childhood abuse and domestic violence) in women and domestic violence, cannabis use, ethnicity in men. Among women, especially those exposed to early interpersonal trauma, an affective loading within psychosis may have distinct relevance. Men, particularly those from minority ethnic groups, demonstrated a strong network connection between hallucinatory experiences and persecutory ideation.

Symptom networks of psychosis expression in the general population are highly heterogeneous. The structure of symptom networks seems to reflect distinct sex-related adversities, etiologies, and mechanisms of symptom-expression. Disentangling the complex interplay of sex, minority ethnic group status, and other risk factors may help optimize early intervention and prevention strategies in psychosis.

Childhood trauma (CT) is associated with an increased risk of mental health disorders; however, it is unknown whether this represents a diagnosis-specific risk factor for specific psychopathology mediated by structural brain changes. Our aim was to explore whether (i) a predictive CT pattern for transdiagnostic psychopathology exists, and whether (ii) CT can differentiate between distinct diagnosis-dependent psychopathology. Furthermore, we aimed to identify the association between CT, psychopathology and brain structure.

We used multivariate pattern analysis in data from 643 participants of the Personalised Prognostic Tools for Early Psychosis Management study (PRONIA), including healthy controls (HC), recent onset psychosis (ROP), recent onset depression (ROD), and patients clinically at high-risk for psychosis (CHR). Participants completed structured interviews and self-report measures including the Childhood Trauma Questionnaire, SCID diagnostic interview, BDI-II, PANSS, Schizophrenia Proneness Instrument, Structured Interview for Prodromal Symptoms and structural MRI, analyzed by voxel-based morphometry.

(i) Patients and HC could be distinguished by their CT pattern with a reasonable precision [balanced accuracy of 71.2% (sensitivity = 72.1%, specificity = 70.4%, p ≤ 0.001]. (ii) Subdomains ‘emotional neglect’ and ‘emotional abuse’ were most predictive for CHR and ROP, while in ROD ‘physical abuse’ and ‘sexual abuse’ were most important. The CT pattern was significantly associated with the severity of depressive symptoms in ROD, ROP, and CHR, as well as with the PANSS total and negative domain scores in the CHR patients. No associations between group-separating CT patterns and brain structure were found.

These results indicate that CT poses a transdiagnostic risk factor for mental health disorders, possibly related to depressive symptoms. While differences in the quality of CT exposure exist, diagnostic differentiation was not possible suggesting a multi-factorial pathogenesis.

Experiences of childhood trauma (CT) are associated with increased psychological vulnerability. Past research suggests that CT might alter stress processing with a subsequent negative impact on mental health. However, it is currently unclear how different domains of CT exert effects on specific subjective experiences of stress during adulthood.

In the present study, we used network analysis to explore the complex interplay between distinct domains of CT and perceived stress in a large, general-population sample of middle-aged adults (N = 1252). We used a data-driven community-detection algorithm to identify strongly connected subgroups of items within the network. To assess the replicability of the findings, we repeated the analyses in a second sample (N = 862). Combining data from both samples, we evaluated network differences between men (n = 955) and women (n = 1159).

Results indicate specific associations between distinct domains of CT and perceived stress. CT domains reflecting a dimension of deprivation, i.e. experiences of neglect, were associated exclusively to a stress network community representing low perceived self-efficacy. By contrast, CT associated with threat, i.e. experiences of abuse, was specifically related to a stress community reflecting perceived helplessness. Our results replicated with high accordance in the second sample. We found no difference in network structure between men and women, but overall a stronger connected network in women.

Our findings emphasize the unique role of distinct domains of CT in psychological stress processes in adulthood, implying opportunities for targeted interventions following distinct domains of CT.

Stimulant drugs can cause persistent changes in the brain. Imaging studies show that these changes are most apparent in dopamine transporter (DAT) or receptor availability within the striatum.

This work focuses on influences of stimulant use on dopaminergic function assessed using nuclear-medicine imaging (PET/SPECT). Included are 39 studies on 655 cocaine, amphetamine, methamphetamine or nicotine users, as well as 690 healthy controls. Metaanalyses were conducted separately for D2/D3 receptors and dopamine transporters of the entire striatum, its subregions caudate and putamen respectively.

Meta-analyses results regarding nicotine did not show significant effects between smokers and nonsmokers. In cocaine users there was a significant decrease in dopamine receptor availability in all regions. The striatal DAT availability was significantly increased in cocaine users. Methamphetamine users showed a significantly decreased dopamine receptor and transporter density in all regions. Significant results also indicate a lower transporter availability in all regions. Amphetamine users showed reduced DAT availability in the striatum, as well as in the sub regions.

This meta-analysis provides evidence that there are ongoing changes in the dopaminergic system associated with the use of stimulants. Especially the results of cocaine, methamphetamine and amphetamine use mainly showed a downregulation. In addition, this meta-analysis is the first to include nicotine. This subset of studies showed evidence for a decreased receptor and DAT availability but no significant results were found in the metaanalyses.

The hypothesis that cortical dopaminergic alterations underlie aspects of schizophrenia has been highly influential.

To bring together and evaluate the imaging evidence for dopaminergic alterations in cortical and other extrastriatal regions in schizophrenia.

Electronic databases were searched for in vivo molecular studies of extrastriatal dopaminergic function in schizophrenia. Twenty-three studies (278 patients and 265 controls) were identified. Clinicodemographic and imaging variables were extracted and effect sizes determined for the dopaminergic measures. There were sufficient data to permit meta-analyses for the temporal cortex, thalamus and substantia nigra but not for other regions.

The meta-analysis of dopamine D2/D3 receptor availability found summary effect sizes of d =–0.32 (95% CI −0.68 to 0.03) for the thalamus, d =–0.23 (95% CI −0.54 to 0.07) for the temporal cortex and d = 0.04 (95% CI −0.92 to 0.99) for the substantia nigra. Confidence intervals were wide and all included no difference between groups. Evidence for other measures/regions is limited because of the small number of studies and in some instances inconsistent findings, although significant differences were reported for D2/D3 receptors in the cingulate and uncus, for D1 receptors in the prefrontal cortex and for dopamine transporter availability in the thalamus.

There is a relative paucity of direct evidence for cortical dopaminergic alterations in schizophrenia, and findings are inconclusive. This is surprising given the wide influence of the hypothesis. Large, well-controlled studies in drug-naive patients are warranted to definitively test this hypothesis.