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Special Issue: The ENIGMA Consortium: the first 10 years., Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes., European Community's Seventh Framework Programme, Grant/Award Numbers: 278948, 602450, 603016, 602805; US National Institute of Child Health and Human Development, Grant/Award Numbers: RO1HD050735, 1009064, 496682; QIMR Berghofer Medical Research Institute and the Centre for Advanced Imaging, University of Queensland; ICTSI NIH/NCRR, Grant/Award Number: RR025761; European Community's Horizon 2020 Programme, Grant/Award Numbers: 667302, 643051; Vici Innovation Program, Grant/Award Numbers: #91619115, 016-130-669; NWO Brain & Cognition Excellence Program, Grant/Award Number: 433-09-229; Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL); Spinozapremie, Grant/Award Number: NWO-56-464-14192; Biobanking and Biomolecular Resources Research Infrastructure, Grant/Award Numbers: 184.033.111, 184.021.007; Netherlands Organization for Health Research and Development (ZonMW), Grant/Award Numbers: 480-15-001/674, 024.001.003, 911-09-032, 056-32-010, 481-08-011, 016-115-035, 31160008, 400-07-080, 400-05-717, 451-04-034, 463-06-001, 480-04-004, 904-61-193, 912-10-020, 985-10-002, 904-61-090; NIMH, Grant/Award Number: R01 MH090553; Geestkracht programme of the Dutch Health Research Council, Grant/Award Number: 10-000-1001; FP7 Ideas: European Research Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/Award Numbers: NWO/SPI 56-464-14192, NWO-MagW 480-04-004, 433-09-220, NWO 51.02.062, NWO 51.02.061; National Center for Advancing Translational Sciences, National Institutes of Health, Grant/Award Number: UL1 TR000153; National Center for Research Resources; National Center for Research Resources at the National Institutes of Health, Grant/Award Numbers: NIH 1U24 RR025736-01, NIH 1U24 RR021992; NIH Institutes contributing to the Big Data to Knowledge; U.S. National Institutes of Health, Grant/Award Numbers: R01 CA101318, P30 AG10133, R01 AG19771; Medical Research Council, Grant/Award Numbers: U54EB020403, G0500092; National Institute of Mental Health, Grant/Award Numbers: R01MH117014, R01MH042191; Fundación Instituto de Investigación Marqués de Valdecilla, Grant/Award Numbers: API07/011, NCT02534363, NCT0235832; Instituto de Salud Carlos III, Grant/Award Numbers: PI14/00918, PI14/00639, PI060507, PI050427, PI020499; Swedish Research Council, Grant/Award Numbers: 523-2014-3467, 2017-00949, 521-2014-3487; South-Eastern Norway Health Authority; the Research Council of Norway, Grant/Award Number: 223273; South Eastern Norway Regional Health Authority, Grant/Award Numbers: 2017-112, 2019107; Icahn School of Medicine at Mount Sinai; Seventh Framework Programme (FP7/2007-2013), Grant/Award Number: 602450; National Institutes of Health, Grant/Award Numbers: R01 MH116147, R01 MH113619, R01 MH104284; South London and Maudsley NHS Foundation Trust; the National Institute for Health Research (NIHR)

SummaryPersonalised prediction of functional outcomes is a promising approach for targeted early intervention in psychiatry. However, generalisability and resource efficiency of such prognostic models represent challenges. In the PRONIA study (German Clinical Trials Register: DRKS00005042), we demonstrate excellent generalisability of prognostic models in individuals at clinical high-risk for psychosis or with recent-onset depression, and substantial contributions of detailed clinical phenotyping, particularly to the prediction of role functioning. These results indicate that it is possible that functioning prediction models based only on clinical data could be effectively applied in diverse healthcare settings, so that neuroimaging data may not be needed at early assessment stages.

Several meta-analyses of observational studies have addressed the association between risk and protective factors and cannabis/cocaine/opioid use disorders, but results are conflicting. No umbrella review has ever graded the credibility of this evidence (not significant/weak/suggestive/highly suggestive/convincing). We searched Pubmed-MEDLINE/PsycInfo, last search September 21, 2020. We assessed the quality of meta-analyses with the AMSTAR-2 tool. Out of 3,072 initial references, five were included, providing 19 associations between 12 putative risk/protective factors and cannabis/cocaine/opioid use disorders (cases: 4539; N = 1,118,872,721). While 84 % of the associations were statistically significant, none was convincing. One risk factor (smoking) had highly suggestive evidence for association with nonmedical use of prescription opioid medicines (OR = 3.07, 95 %CI:2.27 to 4.14). Convincing evidence emerged in sensitivity analyses on antisocial behavior and cannabis use disoder (OR 3.34, 95 %CI 2.53-4.41). Remaining associations had weak evidence. The quality of meta-analyses was rated as moderate in two (40 %), low in one (20 %), and critically low in two (40 %). Future research is needed to better profile risk/protective factors for cannabis/cocaine/opioid use disorders disorders informing preventive approaches.

Negative symptoms occur frequently in individuals at clinical high risk (CHR) for psychosis and contribute to functional impairments. The aim of this study was to predict negative symptom severity in CHR after 9 months. Predictive models either included baseline negative symptoms measured with the Structured Interview for Psychosis-Risk Syndromes (SIPS-N), whole-brain gyrification, or both to forecast negative symptoms of at least moderate severity in 94 CHR. We also conducted sequential risk stratification to stratify CHR into different risk groups based on the SIPS-N and gyrification model. Additionally, we assessed the models’ ability to predict functional outcomes in CHR and their transdiagnostic generalizability to predict negative symptoms in 96 patients with recent-onset psychosis (ROP) and 97 patients with recent-onset depression (ROD). Baseline SIPS-N and gyrification predicted moderate/severe negative symptoms with significant balanced accuracies of 68 and 62%, while the combined model achieved 73% accuracy. Sequential risk stratification stratified CHR into a high (83%), medium (40–64%), and low (19%) risk group regarding their risk of having moderate/severe negative symptoms at 9 months follow-up. The baseline SIPS-N model was also able to predict social (61%), but not role functioning (59%) at above-chance accuracies, whereas the gyrification model achieved significant accuracies in predicting both social (76%) and role (74%) functioning in CHR. Finally, only the baseline SIPS-N model showed transdiagnostic generalization to ROP (63%). This study delivers a multimodal prognostic model to identify those CHR with a clinically relevant negative symptom severity and functional impairments, potentially requiring further therapeutic consideration.

Background Early psychosis in first-episode psychosis (FEP) and clinical high-risk (CHR) individuals has been associated with alterations in mean regional measures of brain morphology. Examination of variability in brain morphology could assist in quantifying the degree of brain structural heterogeneity in clinical relative to healthy control (HC) samples. Methods Structural magnetic resonance imaging data were obtained from CHR (n = 71), FEP (n = 72), and HC individuals (n = 55). Regional brain variability in cortical thickness (CT), surface area (SA), and subcortical volume (SV) was assessed with the coefficient of variation (CV). Furthermore, the person-based similarity index (PBSI) was employed to quantify the similarity of CT, SA, and SV profile of each individual to others within the same diagnostic group. Normative modeling of the PBSI-CT, PBSI-SA, and PBSI-SV was used to identify CHR and FEP individuals whose scores deviated markedly from those of the healthy individuals. Results There was no effect of diagnosis on the CV for any regional measure (P > .38). CHR and FEP individuals differed significantly from the HC group in terms of PBSI-CT (P < .0001), PBSI-SA (P < .0001), and PBSI-SV (P = .01). In the clinical groups, normative modeling identified 32 (22%) individuals with deviant PBSI-CT, 12 (8.4%) with deviant PBSI-SA, and 21 (15%) with deviant PBSI-SV; differences of small effect size indicated that individuals with deviant PBSI scores had lower IQ and higher psychopathology. Conclusions Examination of brain structural variability in early psychosis indicated heterogeneity at the level of individual profiles and encourages further large-scale examination to identify individuals that deviate markedly from normative reference data.

Recent advances in machine learning (ML) promise far-reaching improvements across medical care, not least within psychiatry. While to date no psychiatric application of ML constitutes standard clinical practice, it seems crucial to get ahead of these developments and address their ethical challenges early on. Following a short general introduction concerning ML in psychiatry, we do so by focusing on schizophrenia as a paradigmatic case. Based on recent research employing ML to further the diagnosis, treatment, and prediction of schizophrenia, we discuss three hypothetical case studies of ML applications with view to their ethical dimensions. Throughout this discussion, we follow the principlist framework by Tom Beauchamp and James Childress to analyse potential problems in detail. In particular, we structure our analysis around their principles of beneficence, non-maleficence, respect for autonomy, and justice. We conclude with a call for cautious optimism concerning the implementation of ML in psychiatry if close attention is paid to the particular intricacies of psychiatric disorders and its success evaluated based on tangible clinical benefit for patients.

Background: Psychotic disorders are associated with high rates of comorbid substance use disorders. Use of cannabis rich in tetrahydrocannabinol (THC) is linked to an increased risk of psychosis, worsening of psychotic symptoms, and an adverse course of psychotic disorders. Previous studies suggest oral cannabidiol (CBD) as possible novel antipsychotic agent; however, no studies evaluated the effects of smoked CBD.Objective: The main aim of the study was to clarify the antipsychotic potential of CBD used as adjunctive therapy simulating a naturalistic setting. Our trial is the first study evaluating the effects of smoked CBD-cigarettes as adjunctive therapy for psychotic symptoms.Methods: A randomized, placebo-controlled open-label trial of cigarettes containing CBD-rich cannabis (THC < 1%) as adjunctive therapy to standard psychiatric treatment was conducted (ClinicalTrials.gov identifier NCT04700930). Primary outcomes were mean scores of Positive and Negative Syndrome Scale (PANSS), Brøset Violence Checklist, the Beck's Depression Inventory (BDI), the Subjective Well-Being Under Neuroleptics Scale short form (SWN-K), and antipsychotic medication equivalent doses. Outcomes were assessed after 4 weeks of acute treatment and long-term follow-up after discontinuation of CBD-cigarettes after 25 weeks. Participants were 31 acutely psychotic patients with tobacco use disorder and a mean age of 35.1 ± 10.58 years (71% male). Comorbid cannabis use was diagnosed in 51.6%.Results: A discontinuous multilevel model revealed no significant group differences for primary outcomes. After 4 weeks of acute treatment, mean PANSS and BDI decreased in both groups, while an increase of antipsychotic medication equivalent was observed in the placebo group.Conclusions: The presented findings might suggest an antipsychotic medication sparing effect of CBD-cigarettes as adjunctive treatment of acute psychosis. However, the low number of participants did not allow for further statistical analysis. Hence, a larger study sample and a more rigorous study design (blinding of the interventional product, fixed dosing regimen) may reveal different results.Clinical Trial Registration:ClinicalTrials.gov, identifier: NCT04700930

Background Stimulants such as methylphenidate and modafinil are frequently used as cognitive enhancers in healthy people, whereas 3,4-methylenedioxymethamphetamine (ecstasy) is proposed to enhance mood and empathy in healthy subjects. However, comparative data on the effects of methylphenidate and modafinil on negative emotions in healthy subjects have been partially missing. The aim of this study was to compare the acute effects of methylphenidate and modafinil on the neural correlates of fearful face processing using 3,4-methylenedioxymethamphetamine as a positive control. Methods Using a double-blind, within-subject, placebo-controlled, cross-over design, 60 mg methylphenidate, 600 mg modafinil, and 125 mg 3,4-methylenedioxymethamphetamine were administrated to 22 healthy subjects while performing an event-related fMRI task to assess brain activation in response to fearful faces. Negative mood states were assessed with the State-Trait Anxiety Inventory and subjective ratings. Results Relative to placebo, modafinil, but not methylphenidate or 3,4-methylenedioxymethamphetamine, increased brain activation within a limbic-cortical-striatal-pallidal-thalamic circuit during fearful face processing. Modafinil but not methylphenidate also increased amygdala responses to fearful faces compared with 3,4-methylenedioxymethamphetamine. Furthermore, activation in the middle and inferior frontal gyrus in response to fearful faces correlated positively with subjective feelings of fearfulness and depressiveness after modafinil administration. Conclusions Despite the cognitive enhancement effects of 600 mg modafinil in healthy people, potential adverse effects on emotion processing should be considered.

Background: This study explores the association of experienced dependency in psychotherapy as measured with the CDQ (Care Dependency Questionnaire) and treatment outcome in depression. Furthermore, the course of care dependency and differences in the CDQ scores depending on the received type of treatment, MCT (metacognitive therapy), or CBASP (cognitive behavioral analysis system of psychotherapy), were investigated.Methods: The study follows a prospective, parallel group observational design. Patients suffering from depression received an 8-week intensive day clinic program, which was either CBASP or MCT. The treatment decision was made by clinicians based on the presented symptomatology and with regard to the patients' preferences. The patients reported depressive symptoms with the QIDS-SR16 (Quick Inventory of Depressive Symptomatology) and levels of experienced care dependency with the German version of the CDQ on a weekly basis. Mixed-model analyses were run to account for the repeated-measures design.Results: One hundred patients were included in the analyses. Results indicate that higher levels of care dependency might predict a less favorable outcome of depressive symptomatology. Levels of care dependency as well as depressive symptoms decreased significantly over the course of treatment. There was no significant between-group difference in care dependency between the two treatment groups.Conclusion: The results suggest that care dependency might be associated with a worse treatment outcome in depressed patients. In general, care dependency seems to be a dynamic construct, as it is changing over time, while the levels of care dependency seem to be independent from the received type of treatment. Future research should continue investigating the mechanisms of care dependency in a randomized controlled design.Clinical Trial Registration:https://www.drks.de/drks_web/, identifier: DRKS00023779.

This paper aims to review data regarding two determinants of comorbidity between depression and obesity, i.e., the role of disturbed gut microbiome in their genesis and of diets in their treatment. Obesity and major depressive disorders (MDD) are highly comorbid, the “metabolic” (obese) subtype of MDD affects about one third of all individuals with MDD. There is an urgent need for better therapies strategies, which may include specific dietary measures. A diet low in carbohydrates (low-carb), effective in obesity, may be beneficial also in MDD. However, the underlying mechanisms have not yet been elucidated. Recent data suggest a key role of gut microbiota, neuroplasticity, and neuroinflammation in obesity and MDD. We will focus on the brain-derived neurotrophic factor (BDNF), and microglial fractalkine, a main modulator of neuroinflammation. BDNF and fractalkine may be involved in “metabolic” depression. Future studies may uncover specific pathophysiological pathways in affected patients towards more efficient causal therapies.

Itch is the commonest skin-related symptom, and sex differences are increasingly recognised as important determinants in stratified medicine, but only little is known about sex differences in itch. Questionnaire-based studies indicated that women perceive itch as more intensive and bothersome in comparison with men. However, data of studies using standardised itch models to objectify sex differences are scarce and inconsistent. To determine sex differences in intensity, skin flares and central processing of histaminergic itch, we compared 15 female and 15 male healthy subjects in a double-blinded, within-subject, placebo-controlled study using a histamine skin prick itch model (histamine 1% applied onto the volar forearm) and functional MRI. We found trends in higher mean itch intensity (0.58 VAS, CI 95% 0.004-1.19, P = .056) and maximum itch intensity (men 3.93 VAS ± 0.39 SD at 3 minutes, women 4.73 VAS ± 0.31 SD at 4 minutes, P = .073) in women paralleled by a trend in a stronger positive correlation between itch intensity and blood oxygen level-dependent (BOLD) activity in brain structures identified during itch in comparison with men (rs in women: .46, P = .08, rs in men: .07, P = .79). The erythema and wheal following histamine skin pricking were (non-significantly) larger in men, indicating that higher mean itch intensities on the right volar forearm in women may not be explained by more intense flares. The comparison of the activation patterns between the sexes revealed increased activity in men compared to women in the left middle temporal gyrus (temporooccipital part)/lateral occipital cortex. Thus, our findings indicate that histaminergic itch perception and central itch processing differ between the sexes under standardised conditions.

Zwangsmasnahmen haben negative Auswirkungen auf den Patienten und seine Behandlung. Ihre Anwendung stellt ein ethisches Dilemma dar, und sie sollten nur genutzt werden, wenn keine weniger einschneidenden Masnahmen zur Verfugung stehen. Geschlossene Turen in der Psychiatrie konnen ein Stationsklima fordern, das die Wahrscheinlichkeit fur Aggressionen und konsekutive Zwangsmasnahmen erhoht. Ziel der vorliegenden Arbeit ist es, die Haufigkeit von Zwangsmasnahmen wahrend der Implementation einer klinikweiten „open door policy“ zu untersuchen. In dieser Beobachtungsstudie uber sechs Jahre (2010–2015) untersuchten wir die Haufigkeit von Isolation und Zwangsmedikation anhand von 17.359 Fallen, die in der Klinik fur Erwachsene der Universitaren Psychiatrischen Kliniken Basel behandelt wurden. In diesem Zeitraum wurden sechs vormals dauerhaft geschlossen gefuhrte Stationen geoffnet. Die Haufigkeiten fur Isolation (von 8,2 % auf 3,5 %) und Zwangsmedikation (von 2,4 % auf 1,2 %) gingen innerhalb des Beobachtungszeitraums kontinuierlich und klinisch relevant zuruck. Unsere Ergebnisse unterstreichen das Potenzial, mithilfe einer offeneren Psychiatrie die Haufigkeit von Zwangsmasnahmen zu senken.

SUMMARYEarly detection and specialised early intervention for people at high risk for psychotic disorders have received growing attention in the past few decades, with the aim of delaying or preventing the outbreak of explicit psychotic symptoms and improving functional outcomes. This article summarises criteria for a diagnosis of high psychosis risk, the implications for such a diagnosis and recommendations for treatment.LEARNING OBJECTIVESAfter reading this article you will be able to: •recognise signs and symptoms indicating increased psychosis risk•understand uses and limitations of screening for high psychosis risk, and interpretation of results•recognise evidence-based treatment options for patients at clinical high risk for psychosis.DECLARATION OF INTERESTC.A. has received non-financial support from Sunovion and Lundbeck in the past 36 months.

The treatment of patients with schizophrenia and substance use disorder poses a challenge for clinicians. Continued use of cannabis and cocaine can exacerbate psychotic symptoms and worsen the course of disease. To date, no pharmacotherapy is available for patients with cannabis use disorder (CUD). Cannabidiol (CBD) and Δ9-tetrahydrocannabinol (THC) are the main active constituents in Cannabis sativa, with the latter being linked to an increased risk of psychosis. We describe a clinical case of a male patient diagnosed with schizophrenia, combined personality disorder, CUD and cocaine use disorder. Over the course of 8 years, he was hospitalized 30 times due to psychotic relapses and continued substance use. Consequently, CBD cigarettes with a low THC content (

Background Transition to psychosis is among the most adverse outcomes of clinical high-risk (CHR) syndromes encompassing ultra-high risk (UHR) and basic symptom states. Clinical risk calculators may facilitate an early and individualized interception of psychosis, but their real-world implementation requires thorough validation across diverse risk populations, including young patients with depressive syndromes. Methods We validated the previously described NAPLS-2 (North American Prodrome Longitudinal Study 2) calculator in 334 patients (26 with transition to psychosis) with CHR or recent-onset depression (ROD) drawn from the multisite European PRONIA (Personalised Prognostic Tools for Early Psychosis Management) study. Patients were categorized into three risk enrichment levels, ranging from UHR, over CHR, to a broad-risk population comprising patients with CHR or ROD (CHR|ROD). We assessed how risk enrichment and different predictive algorithms influenced prognostic performance using reciprocal external validation. Results After calibration, the NAPLS-2 model predicted psychosis with a balanced accuracy (BAC) (sensitivity, specificity) of 68% (73%, 63%) in the PRONIA-UHR cohort, 67% (74%, 60%) in the CHR cohort, and 70% (73%, 66%) in patients with CHR|ROD. Multiple model derivation in PRONIA–CHR|ROD and validation in NAPLS-2–UHR patients confirmed that broader risk definitions produced more accurate risk calculators (CHR|ROD-based vs. UHR-based performance: 67% [68%, 66%] vs. 58% [61%, 56%]). Support vector machines were superior in CHR|ROD (BAC = 71%), while ridge logistic regression and support vector machines performed similarly in CHR (BAC = 67%) and UHR cohorts (BAC = 65%). Attenuated psychotic symptoms predicted psychosis across risk levels, while younger age and reduced processing speed became increasingly relevant for broader risk cohorts. Conclusions Clinical-neurocognitive machine learning models operating in young patients with affective and CHR syndromes facilitate a more precise and generalizable prediction of psychosis. Future studies should investigate their therapeutic utility in large-scale clinical trials.

Caffeine elicits widespread effects in the central nervous system and is the most frequently consumed psychostimulant worldwide. First evidence indicates that, during daily intake, the elimination of caffeine may slow down and the primary metabolite, paraxanthine, may accumulate. The neural impact of such adaptions is virtually unexplored. In this report, we leveraged the data of a laboratory study with N= 20 participants and three within-subject conditions: caffeine (150 mg caffeine x 3/day x 10 days), placebo (150 mg mannitol x 3/day x 10 days), and withdrawal (caffeine x 9 days, afterwards placebo x 1 day). Using liquid chromatography–mass spectrometry coupled with tandem mass spectrometry, we determined the course of salivary caffeine and paraxanthine, measured regularly at day 10. We assessed grey matter (GM) intensity and cerebral blood flow (CBF) in the withdrawal condition as compared to their changes in caffeine in our previous report. The results indicate high remaining levels of paraxanthine and of caffeine carried overnight during daily intake, and the levels of paraxanthine remained higher than in placebo during withdrawal. After 36 h of withdrawal, the previously reported caffeine-induced GM reduction was partially mitigated, while CBF was elevated compared to placebo. Our findings unveil that conventional daily caffeine intake does not provide sufficient time to clear up psychoactive compounds and restore cerebral responses, even after 36 hours of abstinence. They also suggest investigating consequences of a paraxanthine accumulation during daily caffeine intake.

IMPORTANCE The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk.OBJECTIVE To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-).DESIGN, SETTING, AND PARTICIPANTS In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020.MAIN OUTCOMES AND MEASURES Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group).RESULTS Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with those in the CHR-PS+ group, age showed a stronger negative association with left fusiform CT measures (F = 9.8; P < .001; q < .001) and left paracentral CT measures (F = 5.9; P = .005; q = .02). Effect sizes representing lower CT associated with psychosis conversion resembled patterns of CT differences observed in ENIGMA studies of schizophrenia (rho = 0.35; 95% CI, 0.12 to 0.55; P = .004) and individuals with 22q11.2 microdeletion syndrome and a psychotic disorder diagnosis (rho = 0.43; 95% CI, 0.20 to 0.61; P = .001).CONCLUSIONS AND RELEVANCE This study provides evidence for widespread subtle, lower CT measures in individuals at CHR. The pattern of CT measure differences in those in the CHR-PS+ group was similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread disruptions in CT coupled with abnormal age associations in those at CHR may point to disruptions in postnatal brain developmental processes.Question How are brain morphometric features associated with later psychosis conversion in individuals at clinical high risk (CHR) for developing psychosis?Findings In this case-control study including 3169 participants, lower cortical thickness, but not cortical surface area or subcortical volume, was more pronounced in individuals at CHR in a manner highly consistent with thinner cortex in individuals with established psychosis. Regions that displayed lower cortical thickness in individuals at CHR who later developed a psychotic disorder additionally displayed abnormal associations with age.Meaning In this study, CHR status and later transition to psychosis was robustly associated with lower cortical thickness; abnormal age associations and specificity to cortical thickness may point to aberrant postnatal brain development in individuals at CHR, including pruning and myelination.This case-control study investigates baseline structural magnetic resonance imaging (MRI) differences between individuals at clinical high risk and healthy controls as well as between participants at clinical high risk who later developed a psychotic disorder and those who did not.

Background: Primary prevention has the potential to modify the course of depression, but the consistency and magnitude of this effect are currently undetermined. Methods: PRISMA and RIGHT compliant (PROSPERO:CRD42020179659) systematic meta-review, PubMed/Web of Science, up to June 2020. Meta-analyses of controlled interventions for the primary prevention of depressive symptoms [effect measures: standardized mean difference (SMD)] or depressive disorders [effect measure: relative risk (RR)] were carried out. Results were stratified by: (i) age range; (ii) target population (general and/or at-risk); (iii) intervention type. Quality (assessed with AMSTAR/AMSTAR-PLUS content) and credibility (graded as high/moderate/low) were assessed. USPSTF grading system was used for recommendations. Results: Forty-six meta-analyses (k=928 individual studies, n=286,429 individuals, mean age=22.4 years, 81.1% female) were included. Effect sizes were: SMD=0.08-0.53; for depressive symptoms; RR=0.90-0.28 for depressive disorders. Sensitivity analyses including only RCTs did not impact the findings. AMSTAR median=9 (IQR=8-9); AMSTAR-PLUS content median=4.25 (IQR=4-5). Credibility of the evidence was insufficient/low in 43 (93.5%) meta-analyses, moderate in two (4.3%), and high in one (2.2%): reduction of depressive symptoms using psychosocial interventions for young adults only, and a combination of psychological and educational interventions in primary care had moderate credibility; preventive administration of selective serotonin reuptake inhibitors (SSRIs) for depressive disorders in individuals with a stroke had high credibility. Limitations: Intervention heterogeneity and lack of long-term efficacy evaluation. Conclusions: Primary preventive interventions for depression might be effective. Among them, clinicians may offer SSRIs post-stroke to prevent depressive disorders, and psychosocial interventions for children/adolescents/young adults with risk factors or during the prenatal/perinatal period.

According to previous research, borderline personality disorder (BPD) is associated with high cost-of-illness. However, there is still a shortage of cost-of-illness-studies assessing costs from a broad societal perspective, including direct and indirect costs. Further, there are considerable differences in the results among the existing studies. In the present study, 167 German men and women seeking specialized outpatient treatment for BPD were included. We assessed societal cost-of-illness bottom-up through structured face-to-face interviews and encompassed a wide range of cost components. All costs were calculated for the 2015 price level. Cost-of-illness amounted to € 31,130 per patient and year preceding disorder-specific outpatient treatment. € 17,044 (54.8%) were direct costs that were mostly related to hospital treatment. Indirect costs amounted to € 14,086 (45.2%). Within indirect costs, costs related to work disability were the most crucial cost driver. The present study underlines the tremendous economic burden of BPD. According to the present study, both the direct and indirect costs are of significant importance for the societal costs associated with BPD. Besides the need for more disorder-specific treatment facilities for men and women with BPD, we assume that education and employment are topics that should be specifically targeted and individually supported at an early stage of treatment.Trial Registration: German Clinical Trial Registration, DRKS00011534, Date of Registration: 11/01/2017, retrospectively registered.

ImportanceBorderline personality disorder (BPD) is a severe mental disorder that is often inadequately treated.ObjectiveTo determine if adding a self-management intervention to care as usual (CAU) is effective and safe.DesignRandomised, controlled, rater-blind trial. Duration of treatment and assessments: 12 months.SettingSecondary care, recruited mainly via the internet.ParticipantsPatients with BPD and BPD Severity Index (BPDSI) of at least 15.InterventionsCAU by treating psychiatrist and/or psychotherapist alone or adjunctive use of an internet-based self-management intervention that is based on schema therapy (priovi).Main outcome measureOutcomes were assessed by trained raters. The primary outcome was change in BPDSI. The safety outcome was the number of serious adverse events (SAEs). The primary outcome time point was 12 months after randomisation.ResultsOf 383 participants assessed for eligibility, 204 were included (91.7% female, mean age: 32.4 years; 74% were in psychotherapy and 26% were in psychiatric treatment). The slope of BPDSI change did not differ significantly between groups from baseline to 12 months (F3,248= 1.857, p=0.14). At 12 months, the within-group effect sizes were d=1.38 (95% CI 1.07 to 1.68) for the intervention group and d=1.02 (95% CI 0.73 to 1.31) for the control group. The between-group effect size was d=0.27 (95% CI 0.00 to 0.55) in the intention-to-treat sample and d=0.39 (95% CI 0.09 to 0.68) for those who used the intervention for at least 3 hours (per-protocol sample). We found no significant differences in SAEs.ConclusionsWe have not found a significant effect in favour of the intervention. This might be due to the unexpectedly large effect in the group receiving CAU by a psychiatrist and/or psychotherapist alone.Trial registrationNCT03418142.

Negative symptoms such as anhedonia and apathy are among the most debilitating manifestations of schizophrenia (SZ). Imaging studies have linked these symptoms to morphometric abnormalities in 2 brain regions implicated in reward and motivation: the orbitofrontal cortex (OFC) and striatum. Higher negative symptoms are generally associated with reduced OFC thickness, while higher apathy specifically maps to reduced striatal volume. However, it remains unclear whether these tissue losses are a consequence of chronic illness and its treatment or an underlying phenotypic trait. Here, we use multicentre magnetic resonance imaging data to investigate orbitofrontal-striatal abnormalities across the SZ spectrum from healthy populations with high schizotypy to unmedicated and medicated first-episode psychosis (FEP), and patients with chronic SZ. Putamen, caudate, accumbens volume, and OFC thickness were estimated from T1-weighted images acquired in all 3 diagnostic groups and controls from 4 sites (n = 337). Results were first established in 1 discovery dataset and replicated in 3 independent samples. There was a negative correlation between apathy and putamen/accumbens volume only in healthy individuals with schizotypy; however, medicated patients exhibited larger putamen volume, which appears to be a consequence of antipsychotic medications. The negative association between reduced OFC thickness and total negative symptoms also appeared to vary along the SZ spectrum, being significant only in FEP patients. In schizotypy, there was increased OFC thickness relative to controls. Our findings suggest that negative symptoms are associated with a temporal continuum of orbitofrontal-striatal abnormalities that may predate the occurrence of SZ. Thicker OFC in schizotypy may represent either compensatory or pathological mechanisms prior to the disease onset.

Caffeine is commonly used to combat high sleep pressure on a daily basis. However, interference with sleep–wake regulation could disturb neural homeostasis and insufficient sleep could lead to alterations in human gray matter. Hence, in this double-blind, randomized, cross-over study, we examined the impact of 10-day caffeine (3 × 150 mg/day) on human gray matter volumes (GMVs) and cerebral blood flow (CBF) by fMRI MP-RAGE and arterial spin-labeling sequences in 20 habitual caffeine consumers, compared with 10-day placebo (3 × 150 mg/day). Sleep pressure was quantified by electroencephalographic slow-wave activity (SWA) in the previous nighttime sleep. Nonparametric voxel-based analyses revealed a significant reduction in GMV in the medial temporal lobe (mTL) after 10 days of caffeine intake compared with 10 days of placebo, voxel-wisely adjusted for CBF considering the decreased perfusion after caffeine intake compared with placebo. Larger GMV reductions were associated with higher individual concentrations of caffeine and paraxanthine. Sleep SWA was, however, neither different between conditions nor associated with caffeine-induced GMV reductions. Therefore, the data do not suggest a link between sleep depth during daily caffeine intake and changes in brain morphology. In conclusion, daily caffeine intake might induce neural plasticity in the mTL depending on individual metabolic processes.

Two decades of studies suggest that computerized cognitive training (CCT) has an effect on cognitive improvement and the restoration of brain activity. Nevertheless, individual response to CCT remains heterogenous, and the predictive potential of neuroimaging in gauging response to CCT remains unknown. We employed multivariate pattern analysis (MVPA) on whole-brain resting-state functional connectivity (rsFC) to (neuro)monitor clinical outcome defined as psychosis-likeness change after 10-hours of CCT in recent onset psychosis (ROP) patients. Additionally, we investigated if sensory processing (SP) change during CCT is associated with individual psychosis-likeness change and cognitive gains after CCT. 26 ROP patients were divided into maintainers and improvers based on their SP change during CCT. A support vector machine (SVM) classifier separating 56 healthy controls (HC) from 35 ROP patients using rsFC (balanced accuracy of 65.5%, P p

Schizophrenia has a prodromal phase of several years in most patients, making it possible to identify patients at clinical high risk (CHR) for developing the disorder. So far, these individuals are identified based on clinical criteria alone, and there is no reliable biomarker for predicting the transition to psychosis. It is well-established that reductions in brain volume, especially in the hippocampus, are associated with schizophrenia. Therefore, hippocampal volume may serve as a biomarker for psychosis. Several studies have already investigated hippocampal volume in CHR groups. Based on these studies, the present meta-analysis compares the baseline left and right hippocampal volume of CHR patients who developed a psychosis with that of CHR patients without such a transition. Our results show no statistically significant effect of the hippocampal volume on the transition risk for psychosis.

Machine learning classifications of first-episode psychosis (FEP) using neuroimaging have predominantly analyzed brain volumes. Some studies examined cortical thickness, but most of them have used parcellation approaches with data from single sites, which limits claims of generalizability. To address these limitations, we conducted a large-scale, multi-site analysis of cortical thickness comparing parcellations and vertex-wise approaches. By leveraging the multi-site nature of the study, we further investigated how different demographical and site-dependent variables affected predictions. Finally, we assessed relationships between predictions and clinical variables. 428 subjects (147 females, mean age 27.14) with FEP and 448 (230 females, mean age 27.06) healthy controls were enrolled in 8 centers by the ClassiFEP group. All subjects underwent a structural MRI and were clinically assessed. Cortical thickness parcellation (68 areas) and full cortical maps (20,484 vertices) were extracted. Linear Support Vector Machine was used for classification within a repeated nested cross-validation framework. Vertex-wise thickness maps outperformed parcellation-based methods with a balanced accuracy of 66.2% and an Area Under the Curve of 72%. By stratifying our sample for MRI scanner, we increased generalizability across sites. Temporal brain areas resulted as the most influential in the classification. The predictive decision scores significantly correlated with age at onset, duration of treatment, and positive symptoms. In conclusion, although far from the threshold of clinical relevance, temporal cortical thickness proved to classify between FEP subjects and healthy individuals. The assessment of site-dependent variables permitted an increase in the across-site generalizability, thus attempting to address an important machine learning limitation.

In community studies, both attenuated psychotic symptoms (APS) and basic symptoms (BS) were more frequent but less clinically relevant in children and adolescents compared to adults. In doing so, they displayed differential age thresholds that were around age 16 for APS, around age 18 for perceptive BS, and within the early twenties for cognitive BS. Only the age effect has previously been studied and replicated in clinical samples for APS. Thus, we examined the reported age effect on and age thresholds of 14 criteria-relevant BS in a patient sample at clinical-high risk of psychosis (N = 261, age 15–40 yrs.), recruited within the European multicenter PRONIA-study. BS and the BS criteria, “Cognitive Disturbances” (COGDIS) and “Cognitive-perceptive BS” (COPER), were assessed with the “Schizophrenia Proneness Instrument, Adult version” (SPI-A). Using logistic regressions, prevalence rates of perceptive and cognitive BS, and of COGDIS and COPER, as well as the impact of social and role functioning on the association between age and BS were studied in three age groups (15–18 years, 19–23 years, 24–40 years). Most patients (91.2%) reported any BS, 55.9% any perceptive and 87.4% any cognitive BS. Furthermore, 56.3% met COGDIS and 80.5% COPER. Not exhibiting the reported differential age thresholds, both perceptive and cognitive BS, and, at trend level only, COPER were less prevalent in the oldest age group (24–40 years); COGDIS was most frequent in the youngest group (15–18 years). Functional deficits did not better explain the association with age, particularly in perceptive BS and cognitive BS meeting the frequency requirement of BS criteria. Our findings broadly confirmed an age threshold in BS and, thus, the earlier assumed link between presence of BS and brain maturation processes. Yet, age thresholds of perceptive and cognitive BS did not differ. This lack of differential age thresholds might be due to more pronounced the brain abnormalities in this clinical sample compared to earlier community samples. These might have also shown in more frequently occurring and persistent BS that, however, also resulted from a sampling toward these, i.e., toward COGDIS. Future studies should address the neurobiological basis of CHR criteria in relation to age.

A 39-year-old female patient suffering from severe, treatment-resistant depression and other symptoms associated with a complex personality disorder was admitted to our open psychiatric ward for an experimental treatment with lysergic acid diethylamide (LSD). The substance was administered in repeated weekly and ascending doses. Curiously, there were no substantial acute subjective effects of the drug despite adequate dosing, which was also confirmed by plasma drug concentration monitoring. However, the patient showed rapid and significant improvement with most notable changes in depressed mood, emotional instability, loss of energy, and suicidal ideations. Additionally, the SCL-90 questionnaire indicated significant decreases in global severity and in various psychopathological subscales. Improvements persisted for ~7 days after each administration. Due to the severe course of the illness and the resistance to previous treatment it was decided to continue this experimental approach with weekly repeated doses of LSD. The patient will be observed closely with regard to somatic and mental side effects. Two features of this case are remarkable: Firstly, administration of LSD was associated with significant improvements in various symptoms of a condition usually difficult to treat. Secondly, symptom reductions occurred in the absence of acute drug effects. Therefore, the mechanism of action seemed to deviate from the concept that improvements after administration of drugs like LSD are due to experiences during the acute drug effects. This case might indicate that LSD can induce rapid but transient beneficial effects on several psychopathological symptoms. The time course of these improvements resembled antidepressant effects seen after administration of ketamine.

Clinical research has demonstrated the efficacy of injectable opioid treatment for long-term, treatment-refractory opioid-dependent patients. It has been hypothesized that compulsive drug use is particularly associated with neuroplasticity changes in the networks corresponding to withdrawal/negative affect and preoccupation/anticipation rather than binge/intoxication. However, as yet, no study has investigated the effect of long-term opioid treatment on key regions within these networks. Magnetic resonance imaging (MRI) was used to assess brain volumes changes during long-term (approximately 9 years) injectable opioid agonist treatment with diacetylmorphine (DAM) in 22 patients with opioid use disorder. Voxel-based morphometry was applied to detect volumetric changes within the networks of binge/intoxication (ventral/dorsal striatum, globus pallidus and thalamus), withdrawal/negative affect (amygdala and ventral striatum) and preoccupation/anticipation (hippocampus, orbitofrontal and anterior cingulate cortex). The relationships between significant volume changes and features of opioid use disorder were tested using Pearson correlation. Long-term opioid agonist treatment was associated with the enlargement of the right caudate nucleus, which was related to the duration of opioid use disorder. In contrast, reduced volume in the right amygdala, anterior cingulate cortex and orbitofrontal cortex were found that were related to opioid dose, onset of opioid consumption and state anxiety. These findings suggest that long-term opioid agonist treatment is related to structural changes in key brain regions underlying binge/intoxication, withdrawal/negative affect and preoccupation/anticipation, suggesting sustained interaction between these systems.

Altres ajuts: SRB: The Australian Schizophrenia Research Bank (ASRB) was supported by the National Health and Medical Research Council of Australia (NHMRC) (Enabling Grant, ID 386500), the Pratt Foundation, Ramsay Health Care, the Viertel Charitable Foundation and the Schizophrenia Research Institute. Chief Investigators for ASRB were Carr, V., Schall, U., Scott, R., Jablensky, A., Mowry, B., Michie, P., Catts, S., Henskens, F., Pantelis, C. We thank Loughland, C., the ASRB Manager, and acknowledge the help of Jason Bridge for ASRB database queries. CP was supported by NHMRC Senior Principal Research Fellowships (IDs: 628386 & 1105825); GC was supported by the Schizophrenia Research Institute utilizing infrastructure funding from the New South Wales Ministry of Health and New South Wales Ministry of Trade and Investment (Australia); JMF was supported by NHMRC project grant (1063960) and the Janette Mary O'Neil Research Fellowship; MJG was supported by NHMRC as an R.D. Wright Biomedical Career Development Fellow (1061875). MJC was supported by NHMRC Senior Research Fellowship (1121474). CASSI: CSW is funded by the NSW Ministry of Health, Office of Health and Medical Research. CSW is a recipient of a National Health and Medical Research Council (Australia) Principal Research Fellowship (PRF) (#1117079). CIAM: The CIAM study (FMH - PI) was supported by the University Research Committee, University of Cape Town and South African funding bodies National Research Foundation and Medical Research Council. COBRE: The COBRE dataset and investigators were supported by NIH grants R01EB006841 & P20GM103472, as well as NSF grant 1539067. JT (senior author) and VDC are supported by 5R01MH094524. JMS is supported by R01 AA021771 and P50 AA022534. EONCKS: This work was supported by a New Partnership for Africa's Development (NEPAD) grant through the Department of Science and Technology of South Africa, the Medical Research Council of South Africa (grant number 65174). ESO: The ESO study was funded by NPU I - LO1611 and Ministry of Health, Czech Republic - Conceptual Development of Research Organization 00023001 (IKEM). FIDMAG/Project: This work was supported by the Catalan Government and several grants from the Instituto de Salud Carlos III and co-funded by European Union (ERDF/ESF, 'Investing in your future'): Miguel Servet Research Contracts and Research Project Grants. FOR2107 Marburg: The FOR2107 Marburg study was funded by the German Research Foundation (DFG), Tilo Kircher (speaker FOR2107; DFG grant numbers KI588/14-1, KI588/14-2), Axel Krug (KR 3822/5-1, KR 3822/7-2), Igor Nenadic (NE 2254/1-2), Carsten Konrad (KO 4291/3-1). FOR2107 Muenster: The FOR2107 Muenster study was funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5-1 and DA1151/5-2 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). TH was supported by grants from the German Research Foundation (DFG grants HA7070/2-2, HA7070/3, HA7070/4). Frankfurt: MRI was performed at the Frankfurt Brain Imaging Center, supported by the German Research Council (DFG) and the German Ministry for Education and Research (BMBF; Brain Imaging Center Frankfurt/Main, DLR 01GO0203). GIPSI: This study was supported by Colciencias PRISMA-U.T. Huilong1 & Huilong2: This study was funded by the National Natural Science Foundation of China (81761128021; 31671145; 81401115; 81401133), Beijing Municipal Science and Technology Commission grant (Z141107002514016) and Beijing Natural Science Foundation(7162087, Beijing Municipal Administration of Hospitals Clinical medicine Development of special funding (XMLX201609; zylx201409). IGP: This study was funded by Project Grants from the Australian National Health and Medical Research Council of Australia (NHMRC; APP630471 and APP1081603), the Macquarie University's Australian Research Council Centre of Excellence in Cognition and its Disorders (CE110001021). Johns Hopkins: Supported by National Institutes of Health Grant Nos. MH-092443, MH-094268 (Silvio O. Conte Center), MH-105660, and MH-107730; foundation grants from Stanley, RUSK/S-R, and NARSAD/Brain and Behavior Research Foundation. Madrid: Supported by the Spanish Ministry of Science, Innovation and Universities, Instituto de Salud Carlos III, co-financed by ERDF Funds from the European Commission, "A way of making Europe", CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds and European Union Seventh Framework Program and H2020 Program; Fundación Familia Alonso, Fundación Alicia Koplowitz and Fundación Mutua Madrileña. MPRC1 & MPRC2: Support was received from NIH grants U01MH108148, 2R01EB015611, R01MH112180, R01DA027680, R01MH085646, P50MH103222 and T32MH067533, a State of Maryland contract (M00B6400091) and NSF grant (1620457). OLIN: The Olin study was supported by NIH grants R37MH43375 and R01MH074797. Oxford: The Oxford study MRC G0500092. SLF Rome: Support from the Italian Ministry of Health grants RC-12-13-14-15-16-17-18-19/A. RSCZ: RSCZ data collection was supported by RFBR 15-06-05758 grant. SCORE: This study was supported in part by grant 3232BO_119382 from the Swiss National Science Foundation. We thank the FePsy (Frueherkennung von Psychosen; early detection of psychosis) Study Group from the University of Basel, Department of Psychiatry, Switzerland, for the recruitment of the study participants. The FePsy Study was supported in part by grant No. SNF 3200-057216/1, ext./2, ext./3. Singapore: This study was supported by research grants from the National Healthcare Group, Singapore (SIG/05004; SIG/11003), and the Singapore Bioimaging Consortium (RP C-009/2006) research grants awarded to KS. SNUH: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (Grant no. 2013R1A2A1A03071089 and 2017M3C7A1029610). UCISZ: The UCISZ study was supported by the National Institutes of Mental Health grant number R21MH097196 to TGMvE. UCISZ data were processed by the UCI High Performance Computing cluster supported by Joseph Farran, Harry Mangalam, and Adam Brenner and the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant UL1 TR000153. UNIBA: The UNIBA study was supported by grant funding from the Italian Ministry of Health (PE-2011-02347951). UNIMAAS: The study was supported by Dutch Organization for Health Research and Development (ZonMw 91112002) and a personal grant to Thérèse van Amelsvoort (ZonMw-VIDI: 91712394). The data was collected in a clinical trial registered in the Dutch clinical trial registry under ID: NTR5094 (http://www.trialregister.nl). UPenn: This study was supported by the National Institute of Mental Health grants MH064045, MH 60722, MH019112, MH085096 (DHW), and R01MH112847 (RTS and TDS). Zurich: This study was supported by the Swiss National Science Foundation (105314_140351 to S.K.). Matthias Kirschner acknowledges support from the National Bank Fellowship (McGill University) and the Swiss National Foundation (P2SKP3_178175). Research reported in this publication was also supported by the following National Institutes of Health grants: U54 EB020403 to PMT, R01 MH116147, U24 RR21992, R21MH097196, and TR000153 to TGMvE, S10 OD023696 and R01EB015611 to PK, T32 AG058507and 5T32 MH073526 to CRKC, R01 MH117601 to NJ, ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403, ENIGMA Sex Differences R01MH116147, and ENIGMA-COINSTAC: Advanced World-wide Transdiagnostic Analysis of Valence System Brain Circuits R01MH121246. A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

Depression frequently occurs in first-episode psychosis (FEP) and predicts longer-term negative outcomes. It is possible that this depression is seen primarily in a distinct subgroup, which if identified could allow targeted treatments. We hypothesize that patients with recent-onset psychosis (ROP) and comorbid depression would be identifiable by symptoms and neuroanatomical features similar to those seen in recent-onset depression (ROD). Data were extracted from the multisite PRONIA study: 154 ROP patients (FEP within 3 months of treatment onset), of whom 83 were depressed (ROP+D) and 71 who were not depressed (ROP−D), 146 ROD patients, and 265 healthy controls (HC). Analyses included a (1) principal component analysis that established the similar symptom structure of depression in ROD and ROP+D, (2) supervised machine learning (ML) classification with repeated nested cross-validation based on depressive symptoms separating ROD vs ROP+D, which achieved a balanced accuracy (BAC) of 51%, and (3) neuroanatomical ML-based classification, using regions of interest generated from ROD subjects, which identified BAC of 50% (no better than chance) for separation of ROP+D vs ROP−D. We conclude that depression at a symptom level is broadly similar with or without psychosis status in recent-onset disorders; however, this is not driven by a separable depressed subgroup in FEP. Depression may be intrinsic to early stages of psychotic disorder, and thus treating depression could produce widespread benefit.

Delineating age-related cortical trajectories in healthy individuals is critical given the association of cortical thickness with cognition and behaviour. Previous research has shown that deriving robust estimates of age-related brain morphometric changes requires large-scale studies. In response, we conducted a large-scale analysis of cortical thickness in 17,075 individuals aged 3-90 years by pooling data through the Lifespan Working group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium. We used fractional polynomial (FP) regression to characterize age-related trajectories in cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma (LMS) method. Inter-individual variability was estimated using meta-analysis and one-way analysis of variance. Overall, cortical thickness peaked in childhood and had a steep decrease during the first 2-3 decades of life; thereafter, it showed a gradual monotonic decrease which was steeper in men than in women particularly in middle-life. Notable exceptions to this general pattern were entorhinal, temporopolar and anterior cingulate cortices. Inter-individual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results reconcile uncertainties about age-related trajectories of cortical thickness; the centile values provide estimates of normative variance in cortical thickness, and may assist in detecting abnormal deviations in cortical thickness, and associated behavioural, cognitive and clinical outcomes.

BackgroundA growing body of neuroimaging research has revealed a relationship between blunted activation of the ventral striatum (VS) and apathy in schizophrenia. In contrast, the association between reduced striatal volume and apathy is less well established, while the relationship between VS function and structure in patients with schizophrenia remains an open question. Here, we aimed to replicate previous structural findings in a larger independent sample and to investigate the relationship between VS hypoactivation and VS volume.MethodsWe included brain structural magnetic resonance imaging (MRI) data from 60 patients with schizophrenia (SZ) that had shown an association of VS hypoactivation with apathy during reward anticipation and 58 healthy controls (HC). To improve replicability, we applied analytical methods developed in two previously published studies: Voxel-based morphometry and the Multiple Automatically Generated Templates (MAGeT) algorithm. VS and dorsal striatum (DS) volume were correlated with apathy correcting for age, gender and total brain volume. Additionally, left VS activity was correlated with left VS volume.ResultsWe failed to replicate the association between apathy and reduced VS volume and did not find a correlation with DS volume. Functional and structural left VS measures exhibited a trend-level correlation (rs=0.248, p=0.067, r2=0.06).ConclusionsOur present data suggests that functional and structural striatal neuroimaging correlates of apathy can occur independently. Replication of previous findings may have been limited by other factors (medication, illness duration, age) potentially related to striatal volume changes in SZ. Finally, associations between reward-related VS function and structure should be further explored.

There are mixed reports on structural neuroimaging correlates of aggression in schizophrenia with weak evidence due to cohort overlaps and lack of replications. To our knowledge, no study examined volumetric neuroimaging correlates of aggression in early stages of psychosis. An agitated-aggressive syndrome is present in at-risk mental state (ARMS) and in first-episode psychosis (FEP) – it is unclear whether this syndrome is associated with structural brain abnormalities in early stages of psychosis. Using three-dimensional magnetic resonance imaging and a whole brain voxel-based morphometry approach, we examined 56 ARMS patients, 55 FEP patients and 25 healthy controls. We operationalized aggression using the Excited Component of the Brief Psychiatric Rating Scale (BPRS-EC) and dichotomized our patient group by median split into “BPRS-EC high” (n = 49) and “BPRS-EC low” groups (n = 62). The “BPRS-EC high” group had significantly smaller left lingual gyrus volume than HC. This finding was not present in the “BPRS-EC low” group. In addition, grey matter volume in the left lingual gyrus showed a negative linear correlation with BPRS-EC over all subjects (ρ = −0.318; p = 0.0001) and in the patient group (ρ = −0.202; p = 0.033). These findings provide first hints on structural brain abnormalities associated with an agitated-aggressive syndrome in ARMS and FEP patients.

AIMS Peripheral infusion of glucagon-like peptide-1 (GLP-1) can affect brain activity in areas involved in the regulation of appetite, including hypothalamic and reward-related brain regions. In contrast, the physiological role of endogenous GLP-1 in the central regulation of appetite has hardly been investigated. MATERIALS AND METHODS This was a randomized, cross-over trial that involved 12 healthy volunteers who received an intragastric (ig) glucose (gluc) load, with or without intravenous (iv) exendin9-39 (ex9-39; specific GLP-1 receptor antagonist). Functional magnetic resonance imaging was used to investigate the effect of endogenous GLP-1 on resting state functional connectivity (rsFC) between homeostatic and reward-related brain regions. Visual analogue scales were used to rate appetite-related sensations. Blood samples were collected for GI hormone measurements. RESULTS Administration of iv-ex9-39/ig-gluc induced a significantly higher rsFC, relative to ig-gluc administration, between the hypothalamus and the left lateral orbitofrontal cortex (OFC) as well as the left amygdala (P ≤ .001, respectively). Administration of iv-ex9-39/ig-gluc induced a significantly higher rsFC, relative to ig-gluc administration, between the right nucleus accumbens and the right lateral OFC (P < .001). Administration of iv-ex9-39/ig-gluc induced a significantly lower rsFC, relative to ig-gluc administration, between the midbrain and the right caudate nucleus (P = .001). Administration of ig-gluc significantly decreased prospective food consumption and increased sensations of fullness compared to pre-infusion baseline (P = .028 and P = .019, respectively); these effects were not present in the iv-ex9-39/ig-gluc condition. CONCLUSIONS This pilot trial provides preliminary experimental evidence that glucose-induced endogenous GLP-1 affects central regulation of appetite by modulating rsFC in homeostatic and reward-related brain regions in healthy lean male participants in a GLP-1 receptor-mediated fashion.

Marlon O Pflueger,1 Pasquale Calabrese,2 Erich Studerus,3 Ronan Zimmermann,4 Ute Gschwandtner,4 Stefan Borgwardt,5 Jacqueline Aston,3 Rolf-Dieter Stieglitz,6 Anita Riecher-Rössler3 1Department of Forensic Psychiatry, University of Basel Psychiatric Clinics, Basel, Switzerland; 2Division of Molecular andCognitive Neuroscience, University of Basel, Basel, Switzerland; 3Center for Gender Research and Early Detection, University of Basel Psychiatric Hospital, Basel, Switzerland; 4Department of Neurology and Neurosurgery, Hospital of the University of Basel, Basel, Switzerland; 5Department of Psychiatry (UPK), University of Basel, Basel, Switzerland; 6Division of Clinical Psychology and Psychiatry, University of Basel, Basel, Switzerland Background: Episodic memory encoding and working memory (WM) deficits are among the first cognitive signs and symptoms in the course of schizophrenia spectrum disorders. However, it is not clear whether the deficit pattern is generalized or specific in nature. We hypothesized that encoding deficits at an early stage of the disease might be due to the more fundamental WM deficits. Methods: We examined episodic memory encoding and WM by administering the California Verbal Learning Test, a 2-back task, and the Wisconsin Card Sorting Test in 90 first-episode psychosis (FE) patients and 116 individuals with an at-risk mental state for psychosis (ARMS) compared to 57 healthy subjects. Results: Learning progress, but not span of apprehension, was diminished to a similar extent in both the ARMS and the FE. We showed that this was due to WM impairment by applying a structural equation approach. Conclusion: Thus, we conclude that verbal memory encoding deficits are secondary to primary WM impairment in emerging psychosis. Keywords: at-risk mental state, first-episode psychosis, cognition, serial position effect, recency, semantic cluster ratio, 2-back task, rate of learning

BackgroundPsychiatric inpatient treatment is increasingly performed in settings with locked doors. However, locked wards have well-known disadvantages and are ethically problematic. In addition, recent data challenges the hypothesis that locked wards provide improved safety over open-door settings regarding suicide, absconding and aggression. Furthermore, there is evidence that the introduction of an open-door policy may lead to short-term reductions in involuntary measures. The aim of this study was to assess if the introduction of an open-door policy is associated with a long-term reduction of the frequency of seclusion and forced medication.MethodIn this 6-year, hospital-wide, longitudinal, observational study, we examined the frequency of seclusion and forced medication in 17,359 inpatient cases admitted to the Department of Adult Psychiatry, Universitäre Psychiatrische Kliniken (UPK) Basel, University of Basel, Switzerland. In an approach to enable a less restrictive policy, six previously closed psychiatric wards were permanently opened beginning from August 2011. During this process, a systematic change towards a more patient-centered and recovery-oriented care was applied. Statistical analysis consisted of generalized estimating equations (GEE) models.ResultsIn multivariate analyses controlling for potential confounders, the implementation of an open-door policy was associated with a continuous reduction of seclusion (from 8.2 to 3.5%; ηp2 = 0.82; odds ratio: 0.88) and forced medication (from 2.4 to 1.2%; ηp2 = 0.70; odds ratio: 0.90).ConclusionThis underlines the potential of the introduction of an open-door policy to attain a long-term reduction in involuntary measures.

Aggressive behavior and violence in psychiatric patients have often been quoted to justify more restrictive settings in psychiatric facilities. However, the effects of open vs. locked door policies on aggressive incidents remain unclear. This study had a naturalistic observational design and analyzed the occurrence of aggressive behavior as well as the use of seclusion or restraint in 21 German hospitals. The analysis included data from 1998 to 2012 and contained a total of n = 314,330 cases, either treated in one of 17 hospitals with (n = 68,135) or in one of 4 hospitals without an open door policy (n = 246,195). We also analyzed the data according to participants' stay on open, partially open, or locked wards. To compare hospital and ward types, we used generalized linear mixed-effects models on a propensity score matched subset (n = 126,268) and on the total dataset. The effect of open vs. locked door policy was non-significant in all analyses of aggressive behavior during treatment. Restraint or seclusion during treatment was less likely in hospitals with an open door policy. On open wards, any aggressive behavior and restraint or seclusion were less likely, whereas bodily harm was more likely than on closed wards. Hospitals with open door policies did not differ from hospitals with locked wards regarding different forms of aggression. Other restrictive interventions used to control aggression were significantly reduced in open settings. Open wards seem to have a positive effect on reducing aggression. Future research should focus on mental health care policies targeted at empowering treatment approaches, respecting the patient's autonomy and promoting reductions of institutional coercion.

HPA axis functioning plays an important role in the etiology of schizophrenia spectrum disorders (SSD). However, only few studies have examined HPA axis responsivity to psychosocial stress in SSD, and results are heterogeneous. Furthermore, childhood trauma is known to influence psychopathology and treatment outcome in SSD, but studies on the influence of childhood trauma on stress related HPA axis activity are missing. The purpose of this study was to investigate cortisol response to a psychosocial stress challenge in SSD patients, and to examine its association with severity of childhood trauma. The present study included 25 subacutely ill patients with a current episode of a chronic SSD and 25 healthy controls. Participants underwent the modified Trier Social Stress Test, and salivary cortisol levels were assessed. The childhood trauma questionnaire was used to assess severity of adverse life events. Overall, cortisol response was blunted in the patient group compared to the control group (p

Rationale 3,4-Methylenedioxymethamphetamine (MDMA) is used recreationally and investigated as an adjunct to psychotherapy. Methylphenidate and modafinil are psychostimulants that are used to treat attention-deficit/hyperactivity disorder and narcolepsy, respectively, but they are also misused as cognitive enhancers. Little is known about differences in the acute effects of equally cardiostimulant doses of these stimulant-type substances compared directly within the same subjects. Methods We investigated the acute autonomic, subjective, endocrine, and emotional effects of single doses of MDMA (125 mg), methylphenidate (60 mg), modafinil (600 mg), and placebo in a double-blind, cross-over study in 24 healthy participants. Acute drug effects were tested using psychometric scales, the Facial Emotion Recognition Task (FERT), and the Sexual Arousal and Desire Inventory (SADI). Results All active drugs produced comparable hemodynamic and adverse effects. MDMA produced greater increases in pupil dilation, subjective good drug effects, drug liking, happiness, trust, well-being, and alterations in consciousness than methylphenidate or modafinil. Only MDMA reduced subjective anxiety and impaired fear recognition and led to misclassifications of emotions as happy on the FERT. On the SADI, only MDMA produced sexual arousal-like effects. Only MDMA produced marked increases in cortisol, prolactin, and oxytocin. In contrast to MDMA, methylphenidate increased subjective anxiety, and methylphenidate and modafinil increased misclassifications of emotions as angry on the FERT. Modafinil had no significant subjective drug effects but significant sympathomimetic and adverse effects. Conclusions MDMA induced subjective, emotional, sexual, and endocrine effects that were clearly distinct from those of methylphenidate and modafinil at the doses used. Electronic supplementary material The online version of this article (doi:10.1007/s00213-017-4650-5) contains supplementary material, which is available to authorized users.

Aim: We aimed to determine the prognostic accuracy of the Basel Screening Instrument for Psychosis (BSIP) in terms of specificity, sensitivity, positive and negative predictive value by following up individuals that were initially not considered to be at increased risk of psychosis based on the BSIP. Moreover, clinical characteristics of these individuals were examined given the relative lack of such information in the literature. Methods: As part of the “Fruherkennung von Psychosen” (FePsy) study, 87 individuals were screened with the BSIP. Of these, 64 were classified at baseline as being in an at-risk mental state (ARMS+) for psychosis using the BSIP and followed up at regular time intervals for at least two years to determine a putative transition to psychosis. Twenty-three individuals were classified at baseline as not being in an at-risk mental state (ARMS–) using the BSIP and re-assessed after four years. Sensitivity, specificity, positive and negative predictive value of the BSIP were computed. Clinical characteristics of the ARMS– group were analysed descriptively. Results: During the follow-up period, none of the ARMS– individuals, but 21 of ARMS+ had developed psychosis. Sensitivity of the BSIP was 1.0, specificity was 0.35. The majority of ARMS– individuals showed depressive disorders or anxiety disorders and varying levels of functioning. Conclusions: The BSIP has good prognostic accuracy for detecting the prodromal phase of psychosis with an excellent sensitivity and a specificity similar to other risk instruments and the advantage of a relatively short duration. Depressive and anxiety symptoms commonly develop in ARMS– individuals.

Background Individuals at clinical high risk (CHR) of psychosis have an approximately 20% probability of developing psychosis within 2 years, as well as an associated risk of non-psychotic disorders and functional impairment. People with subclinical psychotic experiences (PEs) are also at risk of future psychotic and non-psychotic disorders and decreased functioning. It is difficult to accurately predict outcomes in individuals at risk of psychosis on the basis of symptoms alone. Biomarkers for accurate prediction of outcomes could inform the clinical management of this group. Methods We conducted two nested case-control studies. We employed discovery-based proteomic methods to analyse protein expression in baseline plasma samples in EU-GEI and age 12 plasma samples in ALSPAC using liquid chromatography mass spectrometry. Differential expression of quantified proteomic markers was determined by analyses of covariance (with false discovery rate of 5%) comparing expression levels for each marker between those who did not and did not develop psychosis in Study 1 (adjusting for age, gender, body mass index and years in education), and between those who did and did not develop PEs in Study 2 (adjusting for gender, body mass index and maternal social class). Support vector machine algorithms were used to develop models for prediction of transition vs. non-transition (as determined by the Comprehensive Assessment of At Risk Mental States) and poor vs. good functional outcome at 2 years in Study 1 (General Assessment of Functioning: Disability subscale score 60). Similar algorithms were used to develop a model for prediction of PEs vs. no PEs at age 18 in Study 2 (as determined by the Psychosis Like Symptoms Interview). Results In Study 1, 35 of 166 quantified proteins were significantly differentially expressed between CHR participants who did and did not develop psychosis. Functional enrichment analysis provided evidence for particular implication of the complement and coagulation cascade (false discovery rate-adjusted Fisher’s exact test p=2.23E-21). Using 65 clinical and 166 proteomic features a model demonstrated excellent performance for prediction of transition status (area under the receiver-operating curve [AUC] 0.96, positive predictive value [PPV] 83.0%, negative predictive value [NPV] 93.8%). A model based on the ten most predictive proteins accurately predicted transition status in training (AUC 0.96, PPV 87.5%, NPV 95.8%) and withheld data (AUC 0.92, PPV 88.9%, NPV 91.4%). A model using the same 65 clinical and 166 proteomic features predicted 2-year functional outcome with AUC 0.72 (PPV 67.6%, NPV 47.6%). In Study 2, 5 of 265 quantified proteins were significantly differentially expressed between participants who did and did not report PEs at age 18. A model using 265 proteomic features predicted PEs at age 18 with AUC 0.76 (PPV 69.1%, NPV 74.2%). Discussion With external validation, models incorporating proteomic data may contribute to improved prediction of clinical outcomes in individuals at risk of psychosis.

Background Evidence exists that cannabis consumption is associated with the development of psychosis. Further, continued cannabis use in individuals with recent onset psychosis (ROP) increases the risk for rehospitalization, high symptom severity and low general functioning. Clear inter-individual differences in the vulnerability to the harmful effects of the drug have been pointed out. These findings emphasize the importance of investigating the inter-individual variability in the role of cannabis use in ROP and to understand how cannabis use relates to subclinical conditions that predate the full-blown disease in clinical high-risk (CHR). Specific symptoms have been linked with continued cannabis consume, still research is lacking on how different factors contribute together to an elevated risk of cannabis relapse. Multivariate techniques have the capacity to extract complex patterns from high dimensional data and apply generalized rules to unseen cases. The aim of the study is therefore to assess the predictability of cannabis relapse in ROP and CHR by applying machine learning to clinical and environmental data. Methods All participants were recruited within the multi-site, longitudinal PRONIA study (www.pronia.eu). 112 individuals (58 ROP and 54 CHR) from 8 different European research centres reported lifetime cannabis consume at baseline and were abstinent for at least 4 weeks. We defined cannabis relapse as any cannabis consume between baseline and 9 months follow-up reported by the individual. To predict cannabis relapse, we trained a random forest algorithm implemented in the mlr package, R version 3.5.2. on 183 baseline variables including clinical symptoms, general functioning, demographics and consume patterns within a repeated-nested cross-validation framework. The data underwent pre-processing through pruning of non-informative variables and median-imputation for missing values. The number of trees was set to 500, while the number of nodes, sample fraction and mtry were optimized. All hyperparameters were tuned with the model-based optimization implemented in the mlrMBO R package. Results After 9 months 50 individuals (48 % ROP, 52 % CHR) have relapsed on cannabis use. Relapse was over all timepoints associated with more severe psychotic symptoms measured by PANSS positive and PANSS general (p Discussion Our results using a state-of-the-art machine learning approach suggest that the multivariate signature of baseline demographic and clinical data could predict follow up cannabis relapse above chance level in CHR and ROP. Our findings revealing that cannabis relapse is associated with more severe symptoms is in line with previous literature and emphasizes the need for targeted treatment towards abstinence from cannabis. The information of demographic and clinical patterns might be useful in order to specifically address therapeutic strategies in individuals at higher risk for relapse. This might include special programs for younger patients and taking into account the place of living, like urban areas. Further research is needed in order to validate our model in an independent sample.

Background: Health services research is of increasing importance in current psychiatry. Therefore, large datasets and aggregation of data generated by electronic routine documentation due to legal, financial, or administrative purposes play an important role. However, paper-based routine documentation is still of interest. It remains relevant in less developed health care systems, in emergency settings, and in long-term retrospective and historical studies. Whereas studies examining the reliability of electronic routine documentation support the application of routine data for research purposes, our knowledge regarding reliability of paper-based routine documentation is still very sparse.Methods: Basic documentation (BADO) was completed on paper forms and digitalized manually for all inpatients of the Department of Psychiatry and Psychotherapy, University Hospital Hamburg-Eppendorf, Germany, treated within the time period from 1998 to 2006. Four hundred twelve cases of first-episode psychosis patients were chosen for comparison with clinical data from paper-based patient files. The percentage of missing information, the percentage of correct classifications, sensitivity, and positive predictive value were calculated for all applicable variables.Results: In eight cases (1.9%), a BADO form was available, but was not filled in. In 37 cases (7.0%), the patient files were lost and could not be obtained from the centralized archive. Routine data were available for all other cases in 20 (58.8%) of the examined 34 variables, and the percentage of missing data for the remaining variables ranged between 0.3% and 22.9%, with only the variables education and suicidality during treatment having more than 5% missing data. In general, the overall rate of correct classifications was high, with a median percentage of 86.4% to 99.7% for the examined variables. Sensitivity was above 75% for eight and

Antidepressant fluoxetine (Flx) is the first therapeutic choice for the treatment of major depression (MD), however neuroanatomical spots of its action remain unclear. Immunohistochemical detection of c-Fos protein expression has been used for mapping activated neuronal circuits upon various stressors and drugs. We investigated the effect of 3 weeks of Flx treatment (15 mg/kg/day) on changes in neuronal activity, by mapping the number of c-Fos+ cells, in several brain subregions in adult male rats of control and following 3 weeks of chronic social isolation (CSIS), an animal model of depression. The aim was to identify brain subregions activated by vehicle or Flx treatment in both controls or simultaneously applied with CSIS. Flx prevented depressive- and anxiety-like behaviors in CSIS rats. In controls, Flx increased the number of c-Fos+ cells in the anterior/posterior piriform cortex (aPirCx, pPirCx), retrosplenial cortex dysgranular (RSD) and granular, c region (RSGc), dorsal hippocampal subregions (CA1d, CA2, CA3d, DGd), lateral habenula (LHB), paraventricular thalamic nucleus, posterior part (PVP) and lateral/basolateral complex of amygdala (LA/BL). CSIS-induced neuronal activation was observed in brain subregions implicated in mood and other mental disorders such as aPirCx, pPirCx, caudate putamen (CPu), acumbens nucleus shell (AcbSh), RSD, RSGc, DGd, PVP and LA/BL. Flx increased neuronal activation in both controls and CSIS rats in the CA1d, CA2, CA3d, PVP, LA/BL, while in striatum increased neuronal activation was observed only in CSIS. Our data identify activated CSIS-related brain subregions and/or Flx treatment, in which Flx increased c-Fos protein expression in CSIS rats.

Resting-state EEG microstates are brief (50–100 ms) periods, in which the spatial configuration of scalp global field power remains quasi-stable before rapidly shifting to another configuration. Changes in microstate parameters have been described in patients with psychotic disorders. These changes have also been observed in individuals with a clinical or genetic high risk, suggesting potential usefulness of EEG microstates as a biomarker for psychotic disorders. The present study aimed to investigate the potential of EEG microstates as biomarkers for psychotic disorders and future transition to psychosis in patients at ultra-high-risk (UHR). We used 19-channel clinical EEG recordings and orthogonal contrasts to compare temporal parameters of four normative microstate classes (A–D) between patients with first-episode psychosis (FEP; n = 29), UHR patients with (UHR-T; n = 20) and without (UHR-NT; n = 34) later transition to psychosis, and healthy controls (HC; n = 25). Microstate A was increased in patients (FEP & UHR-T & UHR-NT) compared to HC, suggesting an unspecific state biomarker of general psychopathology. Microstate B displayed a decrease in FEP compared to both UHR patient groups, and thus may represent a state biomarker specific to psychotic illness progression. Microstate D was significantly decreased in UHR-T compared to UHR-NT, suggesting its potential as a selective biomarker of future transition in UHR patients.