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This study examined the association between infant developmental milestones and educational level at 31 years of age in the Northern Finland 1966 Birth Cohort (n = 12 058). Developmental data (age at standing, walking, speaking, and measures of bowel and bladder control) were gathered from children's welfare centres. Information on type of schooling at 14 years of age was reported by children and parents. School achievement at 16 years of age and educational level at 31 years were obtained from national registers. Those who reached infant developmental milestones sooner in their first year of life had significantly better (p < 0.05) mean scores in teacher ratings at 16 years, and at 31 years they were more likely to have achieved a better educational level than slower developers. The adjusted odds ratios for individuals who developed more slowly to remain at a basic educational level (7 to 16y) ranged significantly from 1.1 to 1.3. The possibility of advancing from secondary to tertiary level was 1.4 times greater in faster developers than in slow developers. In conclusion, those who develop faster during their first year of life tend to attain higher levels of education in adolescence and adulthood. [ABSTRACT FROM AUTHOR]

Objective: The default mode network (DMN) is active in the brain at rest and de-activated during cognitive tasks. Abnormal function in the DMN has been reported in people with schizophrenia but it is not known whether this applies also to people with a familial risk for psychosis (FR). We compared the activity of the DMN between FR participants and controls.Methods: We conducted a resting state functional MRI (R-fMRI) in 72 young adults without psychosis and with a history of psychosis in one or both parents (FR group) and 72 age matched controls without parental psychosis, and without current psychosis or a current prodromal syndrome. Both groups were drawn from the Northern Finland Birth Cohort 1986 (Oulu Brain and Mind study). Parental psychosis was established using the Finnish hospital discharge register. We pre-processed R-fMRI data using independent component analysis followed by a dual regression approach to assess differences between the groups. The FR vs. Control group differences were assessed using non-parametric permutation tests utilizing threshold-free cluster enhancement and correcting for multiple comparisons (p<0.05).Results: FR participants demonstrated significantly lower activity compared with controls in the posterior cingulate cortex, the central node of the DMN. The size of the region was 41 mm(3).Conclusion: The activity of the DMN differed between FR and control groups. This suggests that familial risk for psychotic disorders may be mediated through genetic effects on connectivity in the posterior cingulate cortex. [ABSTRACT FROM AUTHOR]

Delayed neuromotor development carries an increased risk of developing schizophrenia, and some authors have assumed that risk factors for schizophrenia such as delayed development are also prognostic indicators for patients with established illness. In those who do develop schizophrenia, it is not clear if these same early developmental markers influence the outcome of illness. Our aim was to examine the association between infant developmental milestones and a range of outcomes in patients with schizophrenia. Our sample was drawn from Northern Finland 1966 Birth Cohort and included 109 subjects for whom prospectively collected information on age of learning to stand, walk and talk was available and who had developed schizophrenia by the age 35 years. By utilizing national registers we examined outcomes related to service utilization, educational achievement, and occupational status. Age of illness onset was also analyzed. Based on the diagnostic interview, a subgroup of 59 cases was assessed in clinical examinations on functioning and quality of life. Contrary to a widespread assumption within the field of schizophrenia research, later attainment of developmental milestones was not associated with poor outcome. We conclude that risk factors for schizophrenia are not necessarily prognostic factors. [ABSTRACT FROM AUTHOR]

Introduction: Accurate detection of cardiometabolic risk in early psychosis is crucial to reducing somatic morbidity and mortality in people with psychotic disorders. We conducted an external validation of the psychosis metabolic risk calculator (PsyMetRiC), a cardiometabolic risk prediction tool developed in the UK and tailored for young people with psychosis. We compared the predictive accuracy and clinical usefulness of PsyMetRiC and a general population-based risk prediction tool for type 2 diabetes, the Finnish Diabetes Risk Score (FINDRISC)., Methods: We included first-episode psychosis and ultra-high-risk for psychosis patients without metabolic syndrome aged 18-35 years from the Helsinki Early Psychosis and Turku Early Psychosis Study cohorts. We tested two versions of PsyMetRiC: the full model including age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations, and the partial-model excluding biochemical predictors, and the simplified FINDRISC including BMI, sex, systolic blood pressure, and fasting glucose. Discrimination, calibration, and decision curve analyses were used to assess the predictive performance and clinical usefulness of both PsyMetRiC and FINDRISC. We performed a site-specific re-calibration of PsyMetRiC (PsyMetRiC-Fi)., Results: The study sample consisted of 278 individuals (all White European ethnicity, 58.6% male, mean age 24.8 years, 37.8% smoking, mean BMI 23.5). Discrimination was marginally better in the PsyMetRiC full model (C = 0.72, 95% CI, 0.59-0.82) compared with partial model (C = 0.70, 95% CI 0.59-0.80) or FINDRISC (C = 0.63, 95% CI 0.54-0.71). Calibration plots displayed evidence of minor miscalibration for PsyMetRiC, which corrected following recalibration. Miscalibration was more pronounced for FINDRISC. Decision curve analysis showed that PsyMetRiC offers likely clinical usefulness in improving cardiometabolic risk management in early psychosis compared with giving everyone or no one an intervention., Conclusion: PsyMetRiC has utility in predicting cardiometabolic risk in Finnish patients with early psychosis. It has better discriminatory accuracy and offers more accurate risk prediction compared to other available strategies., (© 2024 The Author(s). Acta Psychiatrica Scandinavica published by John Wiley & Sons Ltd.)

We used a probabilistic reversal learning task to examine prediction error-driven belief updating in three clinical groups with psychosis or psychosis-like symptoms. Study 1 compared people with at-risk mental state and first episode psychosis (FEP) to matched controls. Study 2 compared people diagnosed with treatment-resistant schizophrenia (TRS) to matched controls. The design replicated our previous work showing ketamine-related perturbations in how meta-level confidence maintained behavioural policy. We applied the same computational modelling analysis here, in order to compare the pharmacological model to three groups at different stages of psychosis. Accuracy was reduced in FEP, reflecting increased tendencies to shift strategy following probabilistic errors. The TRS group also showed a greater tendency to shift choice strategies though accuracy levels were not significantly reduced. Applying the previously-used computational modelling approach, we observed that only the TRS group showed altered confidence-based modulation of responding, previously observed under ketamine administration. Overall, our behavioural findings demonstrated resemblance between clinical groups (FEP and TRS) and ketamine in terms of a reduction in stabilisation of responding in a noisy environment. The computational analysis suggested that TRS, but not FEP, replicates ketamine effects but we consider the computational findings preliminary given limitations in performance of the model., (© 2024. The Author(s).)

Novel features derived from imaging and artificial intelligence systems are commonly coupled to construct computer-aided diagnosis (CAD) systems that are intended as clinical support tools or for investigation of complex biological patterns. This study used sulcal patterns from structural images of the brain as the basis for classifying patients with schizophrenia from unaffected controls. Statistical, machine learning and deep learning techniques were sequentially applied as a demonstration of how a CAD system might be comprehensively evaluated in the absence of prior empirical work or extant literature to guide development, and the availability of only small sample datasets. Sulcal features of the entire cerebral cortex were derived from 58 schizophrenia patients and 56 healthy controls. No similar CAD systems has been reported that uses sulcal features from the entire cortex. We considered all the stages in a CAD system workflow: preprocessing, feature selection and extraction, and classification. The explainable AI techniques Local Interpretable Model-agnostic Explanations and SHapley Additive exPlanations were applied to detect the relevance of features to classification. At each stage, alternatives were compared in terms of their performance in the context of a small sample. Differentiating sulcal patterns were located in temporal and precentral areas, as well as the collateral fissure. We also verified the benefits of applying dimensionality reduction techniques and validation methods, such as resubstitution with upper bound correction, to optimize performance., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Exposure to antipsychotics as well as certain first-episode illness characteristics have been associated with greater gray matter (GM) deficits in the early phase of schizophrenia. Whether the first-episode illness characteristics affect the long-term progression of the structural brain changes remain unexplored. We therefore assessed the role of first-episode illness characteristics and life-time antipsychotic use in relation to long-term structural brain GM changes in schizophrenia. Individuals with schizophrenia (SZ, n = 29) and non-psychotic controls (n = 61) from the Northern Finland Birth Cohort 1966 underwent structural MRI at the ages of 34 (baseline) and 43 (follow-up) years. At follow-up, the average duration of illness was 19.8 years. Voxel-based morphometry was used to assess the effects of predictors on longitudinal GM changes in schizophrenia-relevant brain areas. Younger age of onset (AoO), higher cumulative antipsychotic dose and severity of symptoms were associated with greater GM deficits in the SZ group at follow-up. None of the first-episode illness characteristics were associated with longitudinal GM changes during 9-year follow-up period. We conclude that a younger AoO and high life-time antipsychotic use may contribute to progression of structural brain changes in schizophrenia. Apart from AoO, other first-episode illness characteristics may not contribute to longitudinal GM changes in midlife., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: JL owns shares in Orion Pharma., (Copyright © 2024. Published by Elsevier B.V.)

Background: Early intervention in psychosis (EIP) services are nationally mandated in England to provide multidisciplinary care to people experiencing first-episode psychosis, which disproportionately affects deprived and ethnic minority youth. Quality of service provision varies by region, and people from historically underserved populations have unequal access. In other disease areas, including stroke and dementia, national digital registries coupled with clinical decision support systems (CDSSs) have revolutionized the delivery of equitable, evidence-based interventions to transform patient outcomes and reduce population-level disparities in care. Given psychosis is ranked the third most burdensome mental health condition by the World Health Organization, it is essential that we achieve the same parity of health improvements., Objective: This paper reports the protocol for the program development phase of this study, in which we aimed to co-design and produce an evidence-based, stakeholder-informed framework for the building, implementation, piloting, and evaluation of a national integrated digital registry and CDSS for psychosis, known as EPICare (Early Psychosis Informatics into Care)., Methods: We conducted 3 concurrent work packages, with reciprocal knowledge exchange between each. In work package 1, using a participatory co-design framework, key stakeholders (clinicians, academics, policy makers, and patient and public contributors) engaged in 4 workshops to review, refine, and identify a core set of essential and desirable measures and features of the EPICare registry and CDSS. Using a modified Delphi approach, we then developed a consensus of data priorities. In work package 2, we collaborated with National Health Service (NHS) informatics teams to identify relevant data currently captured in electronic health records, understand data retrieval methods, and design the software architecture and data model to inform future implementation. In work package 3, observations of stakeholder workshops and individual interviews with representative stakeholders (n=10) were subject to interpretative qualitative analysis, guided by normalization process theory, to identify factors likely to influence the adoption and implementation of EPICare into routine practice., Results: Stage 1 of the EPICare study took place between December 2021 and September 2022. The next steps include stage 2 building, piloting, implementation, and evaluation of EPICare in 5 demonstrator NHS Trusts serving underserved and diverse populations with substantial need for EIP care in England. If successful, this will be followed by stage 3, in which we will seek NHS adoption of EPICare for rollout to all EIP services in England., Conclusions: By establishing a multistakeholder network and engaging them in an iterative co-design process, we have identified essential and desirable elements of the EPICare registry and CDSS; proactively identified and minimized potential challenges and barriers to uptake and implementation; and addressed key questions related to informatics architecture, infrastructure, governance, and integration in diverse NHS Trusts, enabling us to proceed with the building, piloting, implementation, and evaluation of EPICare., International Registered Report Identifier (irrid): DERR1-10.2196/50177., (©Siân Lowri Griffiths, Graham K Murray, Yanakan Logeswaran, John Ainsworth, Sophie M Allan, Niyah Campbell, Richard J Drake, Mohammad Zia Ul Haq Katshu, Matthew Machin, Megan A Pope, Sarah A Sullivan, Justin Waring, Tumelo Bogatsu, Julie Kane, Tyler Weetman, Sonia Johnson, James B Kirkbride, Rachel Upthegrove. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 19.03.2024.)

Childhood-onset type 1 diabetes (T1D) is associated with substantial psychiatric morbidity in later life, but it remains unknown whether these associations are due to common underlying biological mechanisms or the impacts of living with the condition and its treatment. Here, using Czech national register data, we identified children with T1D aged ≤14 years between 1994 and 2007 and estimated the risk of psychiatric disorders up to 24 years later. We found that children diagnosed with T1D had an elevated risk of developing substance use, mood, anxiety and personality disorders, and behavioral syndromes. Conversely, we found that children with T1D had a lower risk of developing psychotic disorders. In Mendelian randomization analysis, we found an association with schizophrenia, which, however, did not persist following multiple testing adjustment. The combined observational and Mendelian randomization evidence suggests that T1D diagnosis in childhood predisposes to far-reaching, extensive psychiatric morbidity, which is unlikely to be explicable by common underlying biological mechanisms. The findings of this study highlight that monitoring and addressing the mental health needs of children with T1D is imperative, whereas glucose dysregulation and/or inflammation implicated in schizophrenia pathogenesis warrants future research., Competing Interests: Competing interestsThe authors declare no competing interests., (© The Author(s) 2024.)

Introduction: People with psychotic disorders commonly feature broad decision-making impairments that impact their functional outcomes. Specific associative/reinforcement learning problems have been demonstrated in persistent psychosis. But these phenotypes may differ in early psychosis, suggesting that aspects of cognition decline over time., Methods: The present proof-of-concept study examined goal-directed action and reversal learning in controls and those with early psychosis., Results: Equivalent performance was observed between groups during outcome-specific devaluation, and reversal learning at an 80:20 contingency (reward probability for high:low targets). But when the low target reward probability was increased (80:40) those with early psychosis altered their response to loss, whereas controls did not. Computational modelling confirmed that in early psychosis there was a change in punishment learning that increased the chance of staying with the same stimulus after a loss, multiple trials into the future. In early psychosis, the magnitude of this response was greatest in those with higher IQ and lower clinical severity scores., Conclusions: We show preliminary evidence that those with early psychosis present with a phenotype that includes altered responding to loss and hyper-adaptability in response to outcome changes. This may reflect a compensatory response to overcome the milieu of corticostriatal changes associated with psychotic disorders.

Our understanding of the genetics of the human cerebral cortex is limited both in terms of the diversity and the anatomical granularity of brain structural phenotypes. Here we conducted a genome-wide association meta-analysis of 13 structural and diffusion magnetic resonance imaging-derived cortical phenotypes, measured globally and at 180 bilaterally averaged regions in 36,663 individuals and identified 4,349 experiment-wide significant loci. These phenotypes include cortical thickness, surface area, gray matter volume, measures of folding, neurite density and water diffusion. We identified four genetic latent structures and causal relationships between surface area and some measures of cortical folding. These latent structures partly relate to different underlying gene expression trajectories during development and are enriched for different cell types. We also identified differential enrichment for neurodevelopmental and constrained genes and demonstrate that common genetic variants associated with cortical expansion are associated with cephalic disorders. Finally, we identified complex interphenotype and inter-regional genetic relationships among the 13 phenotypes, reflecting the developmental differences among them. Together, these analyses identify distinct genetic organizational principles of the cortex and their correlates with neurodevelopment., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: Several psychological symptoms in adolescence associate with later development of psychosis. However, it is unclear which symptoms specifically predict psychotic disorders rather than psychiatric disorders in general. We conducted a prospective study comparing how specific adolescent psychotic-like symptoms, predicted psychotic and non-psychotic hospital-treated psychiatric disorders in the population-based Northern Finland Birth Cohort 1986 (NFBC1986)., Methods: At age 15-16 years, 6632 members of the NFBC1986 completed the PROD-screen questionnaire. New hospital-treated mental disorders of the NFBC1986 participants were detected between age 17 and 30 years from the Finnish Care Register for Health Care. Multiple covariates were used in the analysis., Results: During the follow-up, 1.1% of the participants developed a psychotic and 3.2% a non-psychotic psychiatric disorder. Three symptoms were specifically associated with onset of psychosis compared to non-psychotic psychiatric disorders: 'Difficulty in controlling one's speech, behaviour or facial expression while communicating' (adjusted OR 4.00; 95% CI 1.66-9.92), 'Difficulties in understanding written text or heard speech' (OR 2.25; 1.12-4.51), and 'Difficulty or uncertainty in making contact with other people' (OR 2.20; 1.03-4.67). Of these, the first one remained statistically significant after Bonferroni correction for multiple comparisons., Conclusion: To our knowledge, this is the first general-population-based prospective study exploring psychiatric symptoms predicting the onset of hospital-treated first-episode psychosis in comparison to non-psychotic disorders. We found three symptoms related with difficulties in social interaction which predicted onset of psychosis. This is a novel finding and should be replicated., (© 2022 The Authors. Early Intervention in Psychiatry published by John Wiley & Sons Australia, Ltd.)

Psychotic symptoms occur in a majority of schizophrenia patients and in ~50% of all Parkinson's disease (PD) patients. Altered grey matter (GM) structure within several brain areas and networks may contribute to their pathogenesis. Little is known, however, about transdiagnostic similarities when psychotic symptoms occur in different disorders, such as in schizophrenia and PD. The present study investigated a large, multicenter sample containing 722 participants: 146 patients with first episode psychosis, FEP; 106 individuals in at-risk mental state for developing psychosis, ARMS; 145 healthy controls matching FEP and ARMS, Con-Psy; 92 PD patients with psychotic symptoms, PDP; 145 PD patients without psychotic symptoms, PDN; 88 healthy controls matching PDN and PDP, Con-PD. We applied source-based morphometry in association with receiver operating curves (ROC) analyses to identify common GM structural covariance networks (SCN) and investigated their accuracy in identifying the different patient groups. We assessed group-specific homogeneity and variability across the different networks and potential associations with clinical symptoms. SCN-extracted GM values differed significantly between FEP and Con-Psy, PDP and Con-PD, PDN and Con-PD, as well as PDN and PDP, indicating significant overall grey matter reductions in PD and early schizophrenia. ROC analyses showed that SCN-based classification algorithms allow good classification (AUC ~0.80) of FEP and Con-Psy, and fair performance (AUC ~0.72) when differentiating PDP from Con-PD. Importantly, the best performance was found in partly the same networks, including the thalamus. Alterations within selected SCNs may be related to the presence of psychotic symptoms in both early schizophrenia and PD psychosis, indicating some commonality of underlying mechanisms. Furthermore, results provide evidence that GM volume within specific SCNs may serve as a biomarker for identifying FEP and PDP., (© 2023. The Author(s).)

Functional impairments in cognition are frequently thought to be a feature of individuals with depression or anxiety. However, documented impairments are both broad and inconsistent, with little known about when they emerge, whether they are causes or effects of affective symptoms, or whether specific cognitive systems are implicated. Here, we show, in the adolescent ABCD cohort (N = 11,876), that attention dysregulation is a robust factor underlying wide-ranging cognitive task impairments seen in adolescents with moderate to severe anxiety or low mood. We stratified individuals high in DSM-oriented depression or anxiety symptomology, and low in attention deficit hyperactivity disorder (ADHD), as well as vice versa - demonstrating that those high in depression or anxiety dimensions but low in ADHD symptoms not only exhibited normal task performance across several commonly studied cognitive paradigms, but out-performed controls in several domains, as well as in those low in both dimensions. Similarly, we showed that there were no associations between psychopathological dimensions and performance on an extensive cognitive battery after controlling for attention dysregulation. Further, corroborating previous research, the co-occurrence of attention dysregulation was associated with a wide range of other adverse outcomes, psychopathological features, and executive functioning (EF) impairments. To assess how attention dysregulation relates to and generates diverse psychopathology, we performed confirmatory and exploratory network analysis with different analytic approaches using Gaussian Graphical Models and Directed Acyclic Graphs to examine interactions between ADHD, anxiety, low mood, oppositional defiant disorder (ODD), social relationships, and cognition. Confirmatory centrality analysis indicated that features of attention dysregulation were indeed central and robustly connected to a wide range of psychopathological traits across different categories, scales, and time points. Exploratory network analysis indicated potentially important bridging traits and socioenvironmental influences in the relationships between ADHD symptoms and mood/anxiety disorders. Trait perfectionism was uniquely associated with both better cognitive performance and broad psychopathological dimensions. This work suggests that attentional dysregulation may moderate the breadth of EF, fluid, and crystalized cognitive task outcomes seen in adolescents with anxiety and low mood, and may be central to disparate pathological features, and thus a target for attenuating wide-ranging negative developmental outcomes., (© 2023. The Author(s).)

Higher educational attainment is observationally associated with lower risk of Alzheimer's disease. However, the biological mechanisms underpinning this association remain unclear. The protective effect of education on Alzheimer's disease may be mediated via increased brain reserve. We used two-sample Mendelian randomization to explore putative causal relationships between educational attainment, structural brain reserve as proxied by MRI phenotypes and Alzheimer's disease. Summary statistics were obtained from genome-wide association studies of educational attainment (n = 1 131 881), late-onset Alzheimer's disease (35 274 cases, 59 163 controls) and 15 measures of grey or white matter macro- or micro-structure derived from structural or diffusion MRI (nmax = 33 211). We conducted univariable Mendelian randomization analyses to investigate bidirectional associations between (i) educational attainment and Alzheimer's disease; (ii) educational attainment and imaging-derived phenotypes; and (iii) imaging-derived phenotypes and Alzheimer's disease. Multivariable Mendelian randomization was used to assess whether brain structure phenotypes mediated the effect of education on Alzheimer's disease risk. Genetically proxied educational attainment was inversely associated with Alzheimer's disease (odds ratio per standard deviation increase in genetically predicted years of schooling = 0.70, 95% confidence interval 0.60, 0.80). There were positive associations between genetically predicted educational attainment and four cortical metrics (standard deviation units change in imaging phenotype per one standard deviation increase in genetically predicted years of schooling): surface area 0.30 (95% confidence interval 0.20, 0.40); volume 0.29 (95% confidence interval 0.20, 0.37); intrinsic curvature 0.18 (95% confidence interval 0.11, 0.25); local gyrification index 0.21 (95% confidence interval 0.11, 0.31)]; and inverse associations with cortical intracellular volume fraction [-0.09 (95% confidence interval -0.15, -0.03)] and white matter hyperintensities volume [-0.14 (95% confidence interval -0.23, -0.05)]. Genetically proxied levels of surface area, cortical volume and intrinsic curvature were positively associated with educational attainment [standard deviation units change in years of schooling per one standard deviation increase in respective genetically predicted imaging phenotype: 0.13 (95% confidence interval 0.10, 0.16); 0.15 (95% confidence interval 0.11, 0.19) and 0.12 (95% confidence interval 0.04, 0.19)]. We found no evidence of associations between genetically predicted imaging-derived phenotypes and Alzheimer's disease. The inverse association of genetically predicted educational attainment with Alzheimer's disease did not attenuate after adjusting for imaging-derived phenotypes in multivariable analyses. Our results provide support for a protective causal effect of educational attainment on Alzheimer's disease risk, as well as potential bidirectional causal relationships between education and brain macro- and micro-structure. However, we did not find evidence that these structural markers affect risk of Alzheimer's disease. The protective effect of education on Alzheimer's disease may be mediated via other measures of brain reserve not included in the present study, or by alternative mechanisms., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Introduction: Evidence suggests a potentially causal role of interleukin 6 (IL-6), a pleiotropic cytokine that generally promotes inflammation, in the pathogenesis of psychosis. However, no interventional studies in patients with psychosis, stratified using inflammatory markers, have been conducted to assess the therapeutic potential of targeting IL-6 in psychosis and to elucidate potential mechanism of effect. Tocilizumab is a humanised monoclonal antibody targeting the IL-6 receptor to inhibit IL-6 signalling, licensed in the UK for treatment of rheumatoid arthritis. The primary objective of this study is to test whether IL-6 contributes to the pathogenesis of first episode psychosis and to examine potential mechanisms by which IL-6 affects psychotic symptoms. A secondary objective is to examine characteristics of inflammation-associated psychosis., Methods and Analysis: A proof-of-concept study employing a randomised, parallel-group, double-blind, placebo-controlled design testing the effect of IL-6 inhibition on anhedonia in patients with psychosis. Approximately 60 participants with a diagnosis of schizophrenia and related psychotic disorders (ICD-10 codes F20, F22, F25, F28, F29) with evidence of low-grade inflammation (IL-6≥0.7 pg/mL) will receive either one intravenous infusion of tocilizumab (4.0 mg/kg; max 800 mg) or normal saline. Psychiatric measures and blood samples will be collected at baseline, 7, 14 and 28 days post infusion. Cognitive and neuroimaging data will be collected at baseline and 14 days post infusion. In addition, approximately 30 patients with psychosis without evidence of inflammation (IL-6<0.7 pg/mL) and 30 matched healthy controls will be recruited to complete identical baseline assessments to allow for comparison of the characteristic features of inflammation-associated psychosis., Ethics and Dissemination: The study is sponsored by the University of Bristol and has been approved by the Cambridge East Research Ethics Committee (reference: 22/EE/0010; IRAS project ID: 301682). Study findings will be published in peer-review journals. Findings will also be disseminated by scientific presentation and other means., Trial Registration Number: ISRCTN23256704., Competing Interests: Competing interests: NMB holds shares and is a Director of Celentyx, other authors have no conflicts of interest to report., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: To interact successfully with their environment, humans need to build a model to make sense of noisy and ambiguous inputs. An inaccurate model, as suggested to be the case for people with psychosis, disturbs optimal action selection. Recent computational models, such as active inference, have emphasized the importance of action selection, treating it as a key part of the inferential process. Based on an active inference framework, we sought to evaluate previous knowledge and belief precision in an action-based task, given that alterations in these parameters have been linked to the development of psychotic symptoms. We further sought to determine whether task performance and modelling parameters would be suitable for classification of patients and controls., Methods: Twenty-three individuals with an at-risk mental state, 26 patients with first-episode psychosis and 31 controls completed a probabilistic task in which action choice (go/no-go) was dissociated from outcome valence (gain or loss). We evaluated group differences in performance and active inference model parameters and performed receiver operating characteristic (ROC) analyses to assess group classification., Results: We found reduced overall performance in patients with psychosis. Active inference modelling revealed that patients showed increased forgetting, reduced confidence in policy selection and less optimal general choice behaviour, with poorer action-state associations. Importantly, ROC analysis showed fair-to-good classification performance for all groups, when combining modelling parameters and performance measures., Limitations: The sample size is moderate., Conclusion: Active inference modelling of this task provides further explanation for dysfunctional mechanisms underlying decision-making in psychosis and may be relevant for future research on the development of biomarkers for early identification of psychosis., Competing Interests: Competing interests: Franziska Knolle reports funding from the European Union’s Horizon 2020 fund. Joost Haarsma reports travel support from the American College of Neuropsychopharmacology. Paul Fletcher reports consulting fees from Ninja Theory. All competing interests are outside the submitted work., (© 2023 CMA Impact Inc. or its licensors.)

Around a quarter of people who experience a first episode of psychosis (FEP) will develop treatment-resistant schizophrenia (TRS), but there are currently no established clinically useful methods to predict this from baseline. We aimed to explore the predictive potential for clozapine use as a proxy for TRS of routinely collected, objective biomedical predictors at FEP onset, and to externally validate the model in a separate clinical sample of people with FEP. We developed and externally validated a forced-entry logistic regression risk prediction Model fOr cloZApine tReaTment, or MOZART, to predict up to 8-year risk of clozapine use from FEP using routinely recorded information including age, sex, ethnicity, triglycerides, alkaline phosphatase levels, and lymphocyte counts. We also produced a least-absolute shrinkage and selection operator (LASSO) based model, additionally including neutrophil count, smoking status, body mass index, and random glucose levels. The models were developed using data from two UK psychosis early intervention services (EIS) and externally validated in another UK EIS. Model performance was assessed via discrimination and calibration. We developed the models in 785 patients, and validated externally in 1,110 patients. Both models predicted clozapine use well at internal validation (MOZART: C 0.70; 95%CI 0.63,0.76; LASSO: 0.69; 95%CI 0.63,0.77). At external validation, discrimination performance reduced (MOZART: 0.63; 0.58,0.69; LASSO: 0.64; 0.58,0.69) but recovered after re-estimation of the lymphocyte predictor (C: 0.67; 0.62,0.73). Calibration plots showed good agreement between observed and predicted risk in the forced-entry model. We also present a decision-curve analysis and an online data visualisation tool. The use of routinely collected clinical information including blood-based biomarkers taken at FEP onset can help to predict the individual risk of clozapine use, and should be considered equally alongside other potentially useful information such as symptom scores in large-scale efforts to predict psychiatric outcomes.

Cognitive impairment in psychosis is one of the strongest predictors of functional decline. Problems with decision-making processes, such as goal-directed action and reversal learning, can reflect cortico-striatal dysfunction. The heterogenous symptoms and neurobiology observed in those with psychosis suggests that specific cognitive phenotypes may reflect differing causative mechanisms. As such, decision-making performance could identify subgroups of individuals with more severe cortico-striatal dysfunction and help to predict their functional decline. The present work evaluated the relationship between goal-directed action, reversal learning, and symptom profiles in those with psychosis. We assessed decision-making processes in healthy controls (N = 34) and those with persistent psychosis (N = 45), subclassifying subjects based on intact/impaired goal-directed action. Compared with healthy controls (<20%), a large proportion (58%) of those with persistent psychosis displayed impaired goal-directed action, predicting poor serial reversal learning performance. Computational approaches indicated that those with impaired goal-directed action had a decreased capacity to rapidly update their prior beliefs in the face of changing contingencies. Impaired decision-making also was associated with reduced levels of grandiosity and increased problems with abstract thinking. These findings suggest that prominent decision-making deficits, indicative of cortico-striatal dysfunction, are present in a large proportion of people with persistent psychosis. Moreover, these impairments would have significant functional implications in terms of planning and abstract thinking., (© 2022. The Author(s).)

Smoking, inflammation and depression commonly co-occur and may be mechanistically linked. However, key questions remain around the direction of association and the influence of residual confounding. We aimed to characterize the association between lifetime smoking and depression, as well as to assess the role that genetically-predicted C-reactive protein (CRP) level, (an archetypal generalized inflammatory marker) and/or IL-6 activity, as a potential explanation for this association. We performed inverse variance weighted Mendelian randomization (MR) analyses using recently published summary-level GWAS data for lifetime smoking index, CRP levels, and depression. A subset of inflammatory-related genetic variants from the lifetime smoking GWAS were also used to assess the potential inflammatory causal pathways between smoking and depression. The analysis indicated reciprocal relationships of lifetime smoking with depression (OR Smk-Dep  = 2.01, 95% CI 1.71-2.37, p < 0.001; OR Dep-Smk  = 1.09, 95% CI 1.06-1.13, p < 0.001), CRP levels and IL-6 activity (OR Smk-CRP  = 1.40, 95% CI 1.21-1.55, p < 0.001; OR CRP-Smk  = 1.03, 95% CI 1.02-1.05, p < 0.001, OR IL-6/CRP-Smk  = 1.06 (1.03-1.09), p < 0.001). These associations were also supported by the majority of the robust MR methods performed. We did not find evidence for a reciprocal relationship between CRP levels (using > 500 genetic instruments for CRP) and depression (OR CRP-Dep  = 1.01, 95% CI 0.99-1.04; OR Dep-CRP  = 1.03, 95% CI 0.99-1.07). We observed little variation in the IVW estimates between smoking and depression when we limited the genetic variants assessed to those related to measures of generalized inflammation, but we found evidence for an attenuation of the smoking-depression association in multivariable mendelian randomization when adjusting for IL-6 activity, suggesting that the IL-6 pathway may be at least in part responsible for the association of smoking and depression. Our study supports potential bidirectional causal associations between lifetime smoking and depression which may be at least in part explained by the IL-6 signalling pathway. The IL-6 pathway may represent a putative therapeutic target for smoking and to mitigate the effects of smoking on depression., (© 2022. The Author(s).)

Background and Hypothesis: Facial Emotion Recognition is a key domain of social cognition associated with psychotic disorders as a candidate intermediate phenotype. In this study, we set out to investigate global and specific facial emotion recognition deficits in first-episode psychosis, and whether polygenic liability to psychotic disorders is associated with facial emotion recognition., Study Design: 828 First Episode Psychosis (FEP) patients and 1308 population-based controls completed assessments of the Degraded Facial Affect Recognition Task (DFAR) and a subsample of 524 FEP and 899 controls provided blood or saliva samples from which we extracted DNA, performed genotyping and computed polygenic risk scores for schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MD)., Study Results: A worse ability to globally recognize facial emotion expressions was found in patients compared with controls [B= -1.5 (0.6), 95% CI -2.7 to -0.3], with evidence for stronger effects on negative emotions (fear [B = -3.3 (1.1), 95% CI -5.3 to -1.2] and anger [B = -2.3 (1.1), 95% CI -4.6 to -0.1]) than on happiness [B = 0.3 (0.7), 95% CI -1 to 1.7]. Pooling all participants, and controlling for confounds including case/control status, facial anger recognition was associated significantly with Schizophrenia Polygenic Risk Score (SZ PRS) [B = -3.5 (1.7), 95% CI -6.9 to -0.2]., Conclusions: Psychosis is associated with impaired recognition of fear and anger, and higher SZ PRS is associated with worse facial anger recognition. Our findings provide evidence that facial emotion recognition of anger might play a role as an intermediate phenotype for psychosis., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)

Background: Cardiometabolic dysfunction is common in young people with psychosis. Recently, the Psychosis Metabolic Risk Calculator (PsyMetRiC) was developed and externally validated in the UK, predicting up-to six-year risk of metabolic syndrome (MetS) from routinely collected data. The full-model includes age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations; the partial-model excludes biochemical predictors., Methods: To move toward a future internationally-useful tool, we externally validated PsyMetRiC in two independent European samples. We used data from the PsyMetab (Lausanne, Switzerland) and PAFIP (Cantabria, Spain) cohorts, including participants aged 16-35y without MetS at baseline who had 1-6y follow-up. Predictive performance was assessed primarily via discrimination (C-statistic), calibration (calibration plots), and decision curve analysis. Site-specific recalibration was considered., Findings: We included 1024 participants (PsyMetab n= 558, male=62%, outcome prevalence=19%, mean follow-up=2.48y; PAFIP n =466, male=65%, outcome prevalence=14%, mean follow-up=2.59y). Discrimination was better in the full- compared with partial-model (PsyMetab=full-model C=0.73, 95% C.I., 0.68-0.79, partial-model C=0.68, 95% C.I., 0.62-0.74; PAFIP=full-model C=0.72, 95% C.I., 0.66-0.78; partial-model C=0.66, 95% C.I., 0.60-0.71). As expected, calibration plots revealed varying degrees of miscalibration, which recovered following site-specific recalibration. PsyMetRiC showed net benefit in both new cohorts, more so after recalibration., Interpretation: The study provides evidence of PsyMetRiC's generalizability in Western Europe, although further local and international validation studies are required. In future, PsyMetRiC could help clinicians internationally to identify young people with psychosis who are at higher cardiometabolic risk, so interventions can be directed effectively to reduce long-term morbidity and mortality., Funding: NIHR Cambridge Biomedical Research Centre (BRC-1215-20014); The Wellcome Trust (201486/Z/16/Z); Swiss National Research Foundation (320030-120686, 324730- 144064, and 320030-173211); The Carlos III Health Institute (CM20/00015, FIS00/3095, PI020499, PI050427, and PI060507); IDIVAL (INT/A21/10 and INT/A20/04); The Andalusian Regional Government (A1-0055-2020 and A1-0005-2021); SENY Fundacion Research (2005-0308007); Fundacion Marques de Valdecilla (A/02/07, API07/011); Ministry of Economy and Competitiveness and the European Fund for Regional Development (SAF2016-76046-R and SAF2013-46292-R).For the Spanish and French translation of the abstract see Supplementary Materials section., Competing Interests: RU has in the past 3 years received honoraria for speaking events from Oktuska, Synovion and Vyalife; has participated as a Chair TSC for an NIHR-funded clinical trial on antipsychotic medication for treatment resistant depression, and as an Expert Member for an NIHR-funded clinical trial on psychological therapies for common mental disorders; is honorary general secretary for the British Association of Psychopharmacology and a Deputy Editor for British Journal of Psychiatry. PBJ is Chair of the MQ Mental Health Sciences Council and has participated in an advisory board for MSD on an unrelated mental health topic. FV received in the past 3 years honoraria for conferences or teaching CME courses from Forum für MedizinischeFortbildung and Sysmex Suisse AG. NA received in the past 3 years honoraria for a conference from Sysmex Suisse AG. SC received in the past 3 years honoraria for teaching CME courses from Forum pour la formation médicale, Barr Switzerland and for consultancy from the Swiss Health Observatory (Obsan) of the Swiss Federal Office of Public Health. CBE received in the past 3 years honoraria for conferences or teaching CME courses from Janssen-Cilag, Lundbeck, Otsuka, Sandoz, Servier, Sunovion, Sysmex Suisse AG, Takeda, Vifor-Pharma and Zeller. All other authors declare no potential conflicts of interest., (© 2022 The Author(s).)

Introduction: Glutamatergic dysfunction is implicated in the pathophysiology of schizophrenia. It is unclear whether glutamatergic dysfunction predicts response to treatment or if antipsychotic treatment influences glutamate levels. We investigated the effect of antipsychotic treatment on glutamatergic levels in the anterior cingulate cortex (ACC), and whether there is a relationship between baseline glutamatergic levels and clinical response after antipsychotic treatment in people with first episode psychosis (FEP)., Materials and Methods: The sample comprised 25 FEP patients; 22 completed magnetic resonance spectroscopy scans at both timepoints. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS)., Results: There was no significant change in glutamate [baseline 13.23 ± 2.33; follow-up 13.89 ± 1.74; t(21) = -1.158, p = 0.260], or Glx levels [baseline 19.64 ± 3.26; follow-up 19.66 ± 2.65; t(21) = -0.034, p = 0.973]. There was no significant association between glutamate or Glx levels at baseline and the change in PANSS positive (Glu r = 0.061, p = 0.777, Glx r = -0.152, p = 0.477), negative (Glu r = 0.144, p = 0.502, Glx r = 0.052, p = 0.811), general (Glu r = 0.110, p = 0.607, Glx r = -0.212, p = 0.320), or total scores (Glu r = 0.078, p = 0.719 Glx r = -0.155, p = 0.470)., Conclusion: These findings indicate that treatment response is unlikely to be associated with baseline glutamatergic metabolites prior to antipsychotic treatment, and there is no major effect of antipsychotic treatment on glutamatergic metabolites in the ACC., Competing Interests: OH was a part-time employee of H. Lundbeck A/S and has received investigator-initiated research funding from and/or participated in advisory/speaker meetings organised by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Heptares, Global Medical Education, Invicro, Jansenn, Lundbeck, Neurocrine, Otsuka, Sunovion, Rand, Recordati, Roche, and Viatris/Mylan. Neither OH or his family have holdings/a financial stake in any pharmaceutical company. OH has a patent for the use of dopaminergic imaging. RM has received honoraria for non-promotional talks for Janssen, Sunovian, Otsuka, Lundbeck. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zahid, McCutcheon, Borgan, Jauhar, Pepper, Nour, Rogdaki, Osugo, Murray, Hathway, Murray and Howes.)

Background: Studies report a strong impact of the COVID-19 pandemic and related stressors on the mental well-being of the general population. In this paper, we investigated whether COVID-19 related concerns and social adversity affected schizotypal traits, anxiety, and depression using structural equational modelling. In mediation analyses, we furthermore explored whether these associations were mediated by healthy (sleep and physical exercise) or unhealthy behaviours (drug and alcohol consumption, excessive media use)., Methods: We assessed schizotypy, depression, and anxiety as well as healthy and unhealthy behaviours and a wide range of sociodemographic scores using online surveys from residents of Germany and the United Kingdom over 1 year during the COVID-19 pandemic. Four independent samples were collected (April/May 2020: N=781, September/October 2020: N=498, January/February 2021: N=544, May 2021: N=486). The degree of schizotypy was measured using the Schizotypal Personality Questionnaire (SPQ), anxiety, and depression symptoms were surveyed with the Symptom Checklist (SCL-27), and healthy and unhealthy behaviours were assessed with the Coronavirus Health Impact Survey (CRISIS). Structural equation models were used to consider the influence of COVID-19 related concerns and social adversity on depressive and anxiety-related symptoms and schizotypal traits in relation to certain healthy (sleep and exercise) and unhealthy behaviours (alcohol and drug consumption, excessive media use)., Results: The results revealed that COVID-19 related life concerns were significantly associated with schizotypy in the September/October 2020 and May 2021 surveys, with anxiety in the September/October 2020, January/February 2021, and May 2021 surveys, and with depressive symptoms in all surveys. Social adversity significantly affected the expression of schizotypal traits and depressive and anxiety symptoms in all four surveys. Importantly, we found that excessive media consumption (>4 hr per day) fully mediated the relationship between COVID-19 related life concerns and schizotypal traits in the January/February 2021 survey. Furthermore, several of the surveys showed that excessive media consumption was associated with increased depressive and anxiety-related symptoms in people burdened by COVID-19 related life., Conclusions: The ongoing uncertainties of the pandemic and the restrictions on social life have a strong impact on mental well-being and especially the expression of schizotypal traits. The negative impact is further boosted by excessive media consumption, which is especially critical for people with high schizotypal traits., Funding: FK received funding from the European Union's Horizon 2020 (Grant number 754,462). SN received funding from the Cundill Centre for Child and Youth Depression at the Centre for Addiction and Mental Health, Toronto, Canada and the Wellcome Trust Institutional Strategic Support Fund from the University of Cambridge., Competing Interests: SD, LM, SN, GM, FK No competing interests declared, (© 2022, Daimer et al.)

Introduction: Neurocognitive models of hallucinations posit theories of misattribution and deficits in the monitoring of mental or perceptual phenomena but cannot yet account for the subjective experience of hallucinations across individuals and diagnostic categories. Arts-based research methods (ABRM) have potential for advancing research, as art depicts experiences which cognitive neuropsychiatry seeks to explain., Methods: To examine how incorporating ABRM may advance hallucination research and theories, we explore data on the lived experiences of hallucinations in psychiatric and neurological populations. We present a multiple case study of two empirical ABRM studies, which used participant-generated artwork and artist collaborations alongside interviews., Results: ABRM combined with interviews illustrated that hallucinations were infused with sensory features, characterised by embodiment, and situated within lived circumstances. These findings advance neurocognitive models of hallucinations by nuancing their multimodal nature, illustrating their embodied feelings, and exploring their content and themes. The process of generating artworks aided in disclosing difficult to discuss hallucinations, promoted participant self-reflection, and clarified multimodal details that may have been misconstrued through interview alone. ABRM were relevant and acceptable for participants and researchers., Conclusion: ABRM may contribute to the development of neurocognitive models of hallucinations by making hallucination experiences more visible, tangible, and accessible.

The processing of salient and rewarding stimuli is integral to engaging our attention, stimulating anticipation for future events, and driving goal-directed behaviors. Widespread impairments in these processes are observed in psychosis, which may be associated with worse functional outcomes or mechanistically linked to the development of symptoms. Here, we summarize the current knowledge of behavioral and functional neuroimaging in salience, prediction error, and reward. Although each is a specific process, they are situated in multiple feedback and feedforward systems integral to decision making and cognition more generally. We argue that the origin of salience and reward processing dysfunctions may be centered in the subcortex during the earliest stages of psychosis, with cortical abnormalities being initially more spared but becoming more prominent in established psychotic illness/schizophrenia. The neural circuits underpinning salience and reward processing may provide targets for delaying or preventing progressive behavioral and neurobiological decline., (© 2021 The Authors.)

Recent discovery of approximately 270 common genetic variants associated with schizophrenia has enabled polygenic risk scores (PRS) to be measured in the population. We hypothesized that normal variation in PRS would be associated with magnetic resonance imaging (MRI) phenotypes of brain morphometry and tissue composition. We used the largest extant genome-wide association dataset (N = 69,369 cases and N = 236,642 healthy controls) to measure PRS for schizophrenia in a large sample of adults from the UK Biobank (N max  = 29,878) who had multiple micro- and macrostructural MRI metrics measured at each of 180 cortical areas, seven subcortical structures, and 15 major white matter tracts. Linear mixed-effect models were used to investigate associations between PRS and brain structure at global and regional scales, controlled for multiple comparisons. Polygenic risk was significantly associated with reduced neurite density index (NDI) at global brain scale, at 149 cortical regions, five subcortical structures, and 14 white matter tracts. Other microstructural parameters, e.g., fractional anisotropy, that were correlated with NDI were also significantly associated with PRS. Genetic effects on multiple MRI phenotypes were co-located in temporal, cingulate, and prefrontal cortical areas, insula, and hippocampus. Post-hoc bidirectional Mendelian randomization analyses provided preliminary evidence in support of a causal relationship between (reduced) thalamic NDI and (increased) risk of schizophrenia. Risk-related reduction in NDI is plausibly indicative of reduced density of myelinated axons and dendritic arborization in large-scale cortico-subcortical networks. Cortical, subcortical, and white matter microstructure may be linked to the genetic mechanisms of schizophrenia., (© 2021. The Author(s).)

Objective: The COVID-19 pandemic has impacted community mental health, but the effect on psychiatric admissions is unknown. We investigated factors contributing to acute psychiatric admissions, and whether this changed during the first UK lockdown., Method: A retrospective case-note review study with an exploratory mixed-methods design to examine factors for psychiatric admissions following the first UK 2020 lockdown compared to the same time periods in 2019 and 2018., Results: Themes of psychopathology, risk, social stressors, community treatment issues, and physical health concerns were generated. The mean number of codes per case was 6.19 (s . d. = 2.43), with a mean number of categories per case of 3.73, (s. d. = 0.98). Changes in routines and isolation were common factors in the study year; accommodation and substance abuse were more prominent in the control year. Relationship stressors featured strongly in both groups. There were significantly more women (χ2(1, N = 98) = 20.80, p < 0.00001) and older adults (χ2(1, N = 98) = 8.61, p = 0.0033) in the study group than the control. Single people, compared to those in a relationship (χ2(1, N = 45 ) = 4.46, p = 0.035), and people with affective disorders compared to psychotic disorders ((χ2(1, N = 28 ) = 5.19, p = 0.023), were more likely to have a COVID-19 related admission factor., Conclusions: Early stages of the COVID-19 pandemic amplified pre-existing psychosocial vulnerabilities with a disproportionate psychiatric admissions impact on the mental health of women, older adults and those with affective disorders., Competing Interests: Competing interests: None., (© 2021 Giovanni Fioriti Editore s.r.l.)

Growing evidence supports that prenatal processes play an important role for cognitive ability in normal and clinical conditions. In this context, several neuroimaging studies searched for features in postnatal life that could serve as a proxy for earlier developmental events. A very interesting candidate is the sulcal, or sulco-gyral, patterns, macroscopic features of the cortex anatomy related to the fold topology-e.g., continuous vs. interrupted/broken fold, present vs. absent fold-or their spatial organization. Indeed, as opposed to quantitative features of the cortical sheet (e.g., thickness, surface area or curvature) taking decades to reach the levels measured in adult, the qualitative sulcal patterns are mainly determined before birth and stable across the lifespan. The sulcal patterns therefore offer a window on the fetal constraints on specific brain areas on cognitive abilities and clinical symptoms that manifest later in life. After a global review of the cerebral cortex sulcation, its mechanisms, its ontogenesis along with methodological issues on how to measure the sulcal patterns, we present a selection of studies illustrating that analysis of the sulcal patterns can provide information on prenatal dispositions to cognition (with a focus on cognitive control and academic abilities) and cognitive symptoms (with a focus on schizophrenia and bipolar disorders). Finally, perspectives of sulcal studies are discussed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Cachia, Borst, Jardri, Raznahan, Murray, Mangin and Plaze.)

Recent theories of cortical function construe the brain as performing hierarchical Bayesian inference. According to these theories, the precision of prediction errors plays a key role in learning and decision-making, is controlled by dopamine and contributes to the pathogenesis of psychosis. To test these hypotheses, we studied learning with variable outcome-precision in healthy individuals after dopaminergic modulation with a placebo, a dopamine receptor agonist bromocriptine or a dopamine receptor antagonist sulpiride (dopamine study n = 59) and in patients with early psychosis (psychosis study n = 74: 20 participants with first-episode psychosis, 30 healthy controls and 24 participants with at-risk mental state attenuated psychotic symptoms). Behavioural computational modelling indicated that precision weighting of prediction errors benefits learning in health and is impaired in psychosis. FMRI revealed coding of unsigned prediction errors, which signal surprise, relative to their precision in superior frontal cortex (replicated across studies, combined n = 133), which was perturbed by dopaminergic modulation, impaired in psychosis and associated with task performance and schizotypy (schizotypy correlation in 86 healthy volunteers). In contrast to our previous work, we did not observe significant precision-weighting of signed prediction errors, which signal valence, in the midbrain and ventral striatum in the healthy controls (or patients) in the psychosis study. We conclude that healthy people, but not patients with first-episode psychosis, take into account the precision of the environment when updating beliefs. Precision weighting of cortical prediction error signals is a key mechanism through which dopamine modulates inference and contributes to the pathogenesis of psychosis., (© 2020. The Author(s).)

Studies reported a strong impact on mental health during the first wave of the COVID-19 pandemic in March-June, 2020. In this study, we assessed the impact of the pandemic on mental health in general and on schizotypal traits in two independent general population samples of the United Kingdom (May sample N: 239, October sample N: 126; participation at both timepoints: 21) and in two independent general population samples of Germany (May sample N: 543, October sample N: 401; participation at both timepoints: 100) using online surveys. Whereas general psychological symptoms (global symptom index, GSI) and percentage of responders above clinical cut-off for further psychological investigation were higher in the May sample compared to the October sample, schizotypy scores (Schizotypal Personality Questionnaire) were higher in the October sample. We investigated potential associations, using general linear regression models (GLM). For schizotypy scores, we found that loneliness, use of drugs, and financial burden were more strongly corrected with schizotypy in the October compared to the May sample. We identified similar associations for GSI, as for schizotypy scores, in the May and October samples. We furthermore found that living in the United Kingdom was related to higher schizotypal scores or GSI. However, individual estimates of the GLM are highly comparable between the two countries. In conclusion, this study shows that while the general psychological impact is lower in the October than the May sample, potentially showing a normative response to an exceptional situation; schizotypy scores are higher at the second timepoint, which may be due to a stronger impact of estimates of loneliness, drug use, and financial burden. The ongoing, exceptional circumstances within this pandemic might increase the risk for developing psychosis in some individuals. The development of general psychological symptoms and schizotypy scores over time requires further attention and investigation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Daimer, Mihatsch, Ronan, Murray and Knolle.)

Age plays a crucial role in the performance of schizophrenia vs. controls (SZ-HC) neuroimaging-based machine learning (ML) models as the accuracy of identifying first-episode psychosis from controls is poor compared to chronic patients. Resolving whether this finding reflects longitudinal progression in a disorder-specific brain pattern or a systematic but non-disorder-specific deviation from a normal brain aging (BA) trajectory in schizophrenia would help the clinical translation of diagnostic ML models. We trained two ML models on structural MRI data: an SZ-HC model based on 70 schizophrenia patients and 74 controls and a BA model (based on 561 healthy individuals, age range = 66 years). We then investigated the two models' predictions in the naturalistic longitudinal Northern Finland Birth Cohort 1966 (NFBC1966) following 29 schizophrenia and 61 controls for nine years. The SZ-HC model's schizophrenia-specificity was further assessed by utilizing independent validation (62 schizophrenia, 95 controls) and depression samples (203 depression, 203 controls). We found better performance at the NFBC1966 follow-up (sensitivity = 75.9%, specificity = 83.6%) compared to the baseline (sensitivity = 58.6%, specificity = 86.9%). This finding resulted from progression in disorder-specific pattern expression in schizophrenia and was not explained by concomitant acceleration of brain aging. The disorder-specific pattern's progression reflected longitudinal changes in cognition, outcomes, and local brain changes, while BA captured treatment-related and global brain alterations. The SZ-HC model was also generalizable to independent schizophrenia validation samples but classified depression as control subjects. Our research underlines the importance of taking account of longitudinal progression in a disorder-specific pattern in schizophrenia when developing ML classifiers for different age groups.