Jim van Os

Background: After remission from a first episode psychosis (FEP), international clinical guidelines recommend continuation of antipsychotic medication for at least 1 year, although many patients wish to reduce or discontinue medication due to side effects or long‐term health concerns. Evidence on the cost‐effectiveness of early dose reduction or discontinuation compared to continuation remains limited. Methods: A trial‐based cost‐utility analysis was conducted alongside the ongoing HAMLETT study, in which 347 remitted FEP participants were randomized to either early guided dose reduction or discontinuation or maintenance treatment for 1 year. Both healthcare and societal perspectives over a 24‐month time horizon were considered. Health outcomes were expressed as quality‐adjusted life years (QALYs) derived from the EQ‐5D‐5L questionnaire using Dutch valuation tariffs. Costs were estimated using patient reported healthcare utilization and administrative pharmacy data. Incremental costs and effects were analysed using seemingly unrelated regression with uncertainty assessed through nonparametric bootstrapping and multiple sensitivity analyses. Results: Early dose reduction or discontinuation was associated with lower quality‐adjusted life years and higher or comparable costs compared with maintenance treatment over the 2‐year analysis period. In the base‐case societal perspective analysis, incremental costs were €23,563 and incremental effects were −0.077 QALYs, resulting in an incremental net monetary benefit of ‐€27,430 at a willingness‐to‐pay threshold of €50,000 per QALY at 24 months. Results were consistent across several scenarios with only approximately 9% probability that early dose reduction or discontinuation was cost‐effective at the assumed willingness‐to‐pay threshold. However, a sex‐at‐birth subgroup analysis suggested a small and uncertain positive incremental net monetary benefit among female participants. Conclusion: Over a 24‐month period, early dose reduction or discontinuation of antipsychotic medication after remission from a FEP is unlikely to be cost‐effective compared with maintenance treatment from both healthcare and societal perspectives. Whether longer term functional improvements associated with early dose reduction translate into cost‐effective benefits remains uncertain and requires follow‐up. Trial Registration: EudraCT number: 2017‐002406‐12

Background: Although most individuals with schizophrenia do not show aggressive behavior, rates are higher than in the general population. Identifying the neurobiological correlates of aggression may inform prevention. Methods: We included 2260 individuals with schizophrenia spectrum disorders and 3058 healthy controls (HC) from 26 sites in the ENIGMA-Schizophrenia Working Group. The former were classified as showing at least moderate aggression (SZ+A; N = 231) or not (SZ−A; N = 2029) based on symptom rating scales. Structural covariance networks were constructed from cortical and subcortical volumes. We examined global and nodal network topology, as well as density within six large-scale brain networks and between each network and the rest of the brain. Metrics were summarized as the area under the curve (AUC) across a prespecified range of densities ( K = 0.10–0.25, Δ K = 0.01). Group differences were assessed using pairwise permutation tests with Benjamini–Hochberg correction for multiple comparisons. Results: Global and nodal network topology did not differ significantly between SZ+A and HC. Network–rest density of the salience network (SN) was higher in SZ+A than in HC, although this difference did not survive multiple-comparison correction (ΔAUC = 0.018, p _BH = .083). In exploratory subgroup analyses, higher SN network–rest density was observed only in SZ+A with high delusion severity (ΔAUC = 0.021, p = .007). By contrast, SZ−A demonstrated extensive alterations in global network topology compared with SZ+A and HC, alongside selective alterations in nodal topology and large-scale network density compared with HC. Results were broadly consistent across sensitivity analyses using alternative definitions of aggression and adjusting for current antipsychotic dose. Conclusions: SZ+A was characterized by fewer—not more—abnormalities in structural covariance network organization than SZ−A, which may reflect etiological heterogeneity. In SZ+A with high delusion severity, higher network–rest density of the SN may point to aberrant salience processing in aggressive behavior.

Background and aims: Polygenic risk scores (PRSs) for cannabis use disorder (CUD), major depressive disorder (MDD), insomnia and chronic pain, and early age at cannabis initiation might be linked to problematic cannabis use. We tested whether: (1) higher PRS for CUD, MDD, insomnia and chronic pain are associated with earlier initiation and problematic cannabis use; (2) age at cannabis initiation explains more variance in problematic use than any single PRS; and (3) PRSs moderate the association between early initiation and problematic cannabis use. Design: Observational study involving two cohorts: (1) the Avon Longitudinal Study of Parents and Children (ALSPAC) population‐based birth cohort and (2) for conceptual replication, the EUropean Gene–Environment Interaction (EU‐GEI) first‐episode psychosis case–control study. Setting: (1) United Kingdom; (2b) 16 population‐based catchment areas in Europe and 1 in Brazil, with FEP cases recruited from mental health services and controls from the general population of the same catchment areas. Participants: For ALSPAC, n = 8224 genotyped (51% male); subsamples with Cannabis Abuse Screening Test (CAST) at 17 years ( n = 895), 20y ( n = 1587), 24y ( n = 836) and frequency of use at 24y ( n = 2908). EU‐GEI: n = 776 [controls: mean age 37.2, standard deviation (SD) = 13.5; 47% male] and 491 FEP cases (mean age 31.5, SD = 11.2; 62.5% male). Measurements: Outcomes were self‐reported lifetime and frequency of cannabis use and CAST score (problematic use questionnaire). Predictors were PRSs for CUD, MDD, insomnia and chronic pain. Models were adjusted for sex, age and genetic principal components (ALSPAC), and additionally for site and case–control status (EU‐GEI). Results: In ALSPAC, CUD PRS was associated with CAST score at 20 [beta coefficient (β) = 0.04, False Discovery Rate‐corrected P ‐value (p _FDR ) = 0.03] and CAST at 24 years (β = 0.11, p _FDR = 0.005). MDD PRS was associated with CAST scores at 17y (β = 0.1, p _FDR = 0.002), 20y (β = 0.06, p _FDR = 0.01) and 24y (β = 0.09, p _FDR = 0.01). Pain PRS was associated with the CAST scores at 17y (β = 0.09, p _FDR = 0.002), 20y (β = 0.07, p _FDR < 0.001) and 24y (β = 0.09, p _FDR = 0.005). In EU‐GEI, CUD PRS (RRR = 1.82, p _FDR = 0.001) and pain PRS (RRR = 1.27, p _FDR = 0.007) were associated with weekly‐to‐daily use. The Relative Excess Risk due to Interaction RERI model showed evidence of additive interaction for CUD PRS, RERI = 2.4, P = 0.009, while MDD and schizophrenia PRS showed no evidence of additive interaction. Summary: Genetic liability, measured by polygenic risk scores, to cannabis use disorder, major depressive disorder, and chronic pain appears to be associated with heavier and more problematic cannabis use. Age at cannabis initiation explains more variance in problematic cannabis use than polygenic liability.

Most genetic variants associated with complex heritability phenotypes lie in non-coding regions and are thought to influence disease risk by regulating gene expression. However, most transcriptome-wide association approaches primarily model local ( cis ) genetic effects, leaving much of gene regulation unexplained. Here, we show that incorporating distal ( trans ) regulatory effects improves the prediction of gene expression and the identification of disease-associated genes. Using RNA sequencing data from six human post-mortem brain regions, we developed INGENE and MODULE, two models capturing the combined influence of candidate trans- acting variants within gene coexpression networks. Integrating these models with conventional cis -based predictors improved gene expression imputation (maximum likelihood estimation, α = 0.05) for 18,744 genes across regions. Applying this framework to Psychiatric Genomics Consortium wave 3 genotypes identified 766 genes associated with schizophrenia ( P _FDR < 0.01), including 641 not previously reported by transcriptome-wide analyses. These findings highlight the contribution of distal regulatory mechanisms and gene network interactions to schizophrenia risk.

This article explores how thinking in terms of neurodiversity can help clinicians take mental distress seriously without unnecessarily medicalizing normal variation. Rather than searching for a disorder label, the focus shifts to a profile of sensitivities and talents, always understood in relation to context. The article shows where the categorical DSM model falls short in everyday clinical practice, particularly due to comorbidity, heterogeneity, and a tendency to overlook strengths. As an alternative, a simple dimensional framework with seven developmental dimensions is presented. This framework provides clinicians with a practical language to work with patients, parents, schools, or employers in understanding where a person struggles and where they thrive. Two clinical vignettes illustrate how this approach can lead to more concrete contextual adaptations, less pressure to label, and a more cautious and goal-oriented use of medication. The core message is that neurodivergence is best understood as a dynamic state of dysregulation in a specific context rather than as a fixed identity trait.

Background: Recent proposals for revising the Diagnostic and Statistical Manual of Mental Disorders (DSM) aim to improve psychiatric diagnosis. While these efforts reflect substantial ambition, they continue to operate within assumptions embedded in the DSM’s underlying classificatory logic. This editorial examines whether such incremental revision is sufficient. Methods: We provide a critical analysis of the recently published DSM roadmap and accompanying subcommittee commentaries. Drawing on contemporary literature, we identify five structural blind spots in the current reform agenda: public mental health, scientific inference, lived experience, epistemic governance, and the function of diagnosis. Based on this analysis, we propose an alternative dialogical redesign for the DSM. Results: We argue that current revision considerations risk increasing complexity without resolving fundamental limitations in psychiatric classification. Specifically, our analysis highlights several areas that warrant further consideration, including the relationship between diagnostic expansion and societal conditions, the applicability of group-level scientific findings to individual care, the incorporation of experiential knowledge, participatory governance in revision processes, and the identity-related implications of diagnosis. In response, we propose redesigning the DSM as a hybrid dialogical system that retains coarse-grained classificatory categories for pragmatic purposes while shifting diagnostic practice toward contextual interpretation, collaborative meaning-making, relational understanding, and individualized care formulation. Conclusions: The challenges facing psychiatric diagnosis require more than incremental refinement. We therefore argue for a dialogical redesign of the DSM that better reflects the context-dependent, experiential, and relational nature of mental health conditions, positioning diagnosis as a starting point for collaborative inquiry.