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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

Approximately 2% of adolescents and young adults display symptoms indicating a high risk for psychotic disorders. Apart from a risk of 20-35% of developing a psychotic disorder, these individuals show high rates of persisting mental health problems and functional impairment, even in the absence of a psychotic transition. Treatment in specialized centers can improve outcomes in these patients, but the need to provide timely access to care needs to be balanced against the risks of premature psychiatrization, stigmatization and unnecessary medication treatment. The transcantonal project PsyYoung aims to optimize early detection in young people, while at the same time minimizing unnecessary psychiatrization. This will be achieved through improved networking across the entire care chain and a stepped-care intervention approach.Près de 2 % des adolescents et jeunes adultes présentent des symptômes indiquant un risque élevé de développer une psychose. Outre ce risque se situant entre 20 et 35 %, ces individus présenteront des taux élevés d’autres troubles psychiques et déficits fonctionnels, même en l’absence de transition vers la psychose. Le traitement dans des centres spécialisés peut améliorer l’évolution de ces patients mais les besoins de fournir un accès rapide aux soins doivent être mis en perspective des risques de psychiatrisation prématurée, stigmatisation, et médication inutile. Le projet pluri-cantonal PsyYoung vise à optimiser la détection précoce pour les jeunes, tout en minimisant la psychiatrisation inutile. Ceci sera atteint en améliorant le réseautage de l’ensemble de la chaîne de soins et la mise en œuvre d’un modèle de soins par étapes.

Background: Interpersonal skills deficits and dysfunctional metacognitive beliefs have been implicated in the etiology and maintenance of depression. This study aimed to investigate the association between changes in these skills deficits and change in depressive symptoms over the course of treatment with Cognitive Behavioral Analysis System of Psychotherapy (CBASP) and Metacognitive Therapy (MCT).Methods: In this prospective, parallel group observational study, data was collected at baseline and after 8 weeks of an intensive day clinic psychotherapy program. Based on a shared decision between patients and clinicians, patients received either CBASP or MCT. Ninety patients were included in the analyses (CBASP: age M = 38.7, 40.5% female, MCT: age M = 44.7, 43.3% female). Interpersonal deficits were assessed with the short-form of the Luebeck Questionnaire for Recording Preoperational Thinking (LQPT-SF) and the Impact Message Inventory (IMI-R). Metacognitive beliefs were assessed with the Metacognition Questionnaire-30 (MCQ-30). The Quick Inventory of Depressive Symptomatology (QIDS-SR16) was utilized to assess depressive symptoms. A regression analysis was conducted to assess variables associated with outcome. ANCOVAs were utilized to investigate whether improvement in skills deficits is dependent on type of treatment received.Results: Improvements in preoperational thinking and increases in friendly-dominant behavior were associated with change in depressive symptoms. There was no association between reductions in dysfunctional metacognitive beliefs and a decrease in depressive symptoms. While both treatment groups showed significant improvements in interpersonal and metacognitive skills, there was no significant between-group difference in the change scores for either of these skills.Conclusion: Our findings suggest that changes in interpersonal skills seem to be of particular relevance in the treatment of depression. These results have to be replicated in a randomized-controlled design before firm conclusions can be drawn.

Acute caffeine intake can attenuate homeostatic sleep pressure and worsen sleep quality. Caffeine intake—particularly in high doses and close to bedtime—may also affect circadian-regulated rapid eye movement (REM) sleep promotion, an important determinant of subjective sleep quality. However, it is not known whether such changes persist under chronic caffeine consumption during daytime. Twenty male caffeine consumers (26.4 ± 4 years old, habitual caffeine intake 478.1 ± 102.8 mg/day) participated in a double-blind crossover study. Each volunteer completed a caffeine (3 × 150 mg caffeine daily for 10 days), a withdrawal (3 × 150 mg caffeine for 8 days then placebo), and a placebo condition. After 10 days of controlled intake and a fixed sleep-wake cycle, we recorded electroencephalography for 8 h starting 5 h after habitual bedtime (i.e., start on average at 04:22 h which is around the peak of circadian REM sleep promotion). A 60-min evening nap preceded each sleep episode and reduced high sleep pressure levels. While total sleep time and sleep architecture did not significantly differ between the three conditions, REM sleep latency was longer after daily caffeine intake compared with both placebo and withdrawal. Moreover, the accumulation of REM sleep proportion was delayed, and volunteers reported more difficulties with awakening after sleep and feeling more tired upon wake-up in the caffeine condition compared with placebo. Our data indicate that besides acute intake, also regular daytime caffeine intake affects REM sleep regulation in men, such that it delays circadian REM sleep promotion when compared with placebo. Moreover, the observed caffeine-induced deterioration in the quality of awakening may suggest a potential motive to reinstate caffeine intake after sleep.

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.

BackgroundPositive symptoms are a useful predictor of aggression in schizophrenia. Although a similar pattern of abnormal brain structures related to both positive symptoms and aggression has been reported, this observation has not yet been confirmed in a single sample.MethodTo study the association between positive symptoms and aggression in schizophrenia on a neurobiological level, a prospective meta-analytic approach was employed to analyze harmonized structural neuroimaging data from 10 research centers worldwide. We analyzed brain MRI scans from 902 individuals with a primary diagnosis of schizophrenia and 952 healthy controls.ResultsThe result identified a widespread cortical thickness reduction in schizophrenia compared to their controls. Two separate meta-regression analyses revealed that a common pattern of reduced cortical gray matter thickness within the left lateral temporal lobe and right midcingulate cortex was significantly associated with both positive symptoms and aggression.ConclusionThese findings suggested that positive symptoms such as formal thought disorder and auditory misperception, combined with cognitive impairments reflecting difficulties in deploying an adaptive control toward perceived threats, could escalate the likelihood of aggression in schizophrenia.

Lysergic acid diethylamide (LSD) is a classic psychedelic, 3,4-methylenedioxymethamphetamine (MDMA) is an empathogen, and d-amphetamine is a classic stimulant. All three substances are used recreationally. LSD and MDMA are being investigated as medications to assist psychotherapy, and d-amphetamine is used for the treatment of attention-deficit/hyperactivity disorder. All three substances induce distinct acute subjective effects. However, differences in acute responses to these prototypical psychoactive substances have not been characterized in a controlled study. We investigated the acute autonomic, subjective, and endocrine effects of single doses of LSD (0.1 mg), MDMA (125 mg), d-amphetamine (40 mg), and placebo in a randomized, double-blind, cross-over study in 28 healthy subjects. All of the substances produced comparable increases in hemodynamic effects, body temperature, and pupil size, indicating equivalent autonomic responses at the doses used. LSD and MDMA increased heart rate more than d-amphetamine, and d-amphetamine increased blood pressure more than LSD and MDMA. LSD induced significantly higher ratings on the 5 Dimensions of Altered States of Consciousness scale and Mystical Experience Questionnaire than MDMA and d-amphetamine. LSD also produced greater subjective drug effects, ego dissolution, introversion, emotional excitation, anxiety, and inactivity than MDMA and d-amphetamine. LSD also induced greater impairments in subjective ratings of concentration, sense of time, and speed of thinking compared with MDMA and d-amphetamine. MDMA produced greater ratings of good drug effects, liking, high, and ego dissolution compared with d-amphetamine. d-Amphetamine increased ratings of activity and concentration compared with LSD. MDMA but not LSD or d-amphetamine increased plasma concentrations of oxytocin. None of the substances altered plasma concentrations of brain-derived neurotrophic factor. These results indicate clearly distinct acute effects of LSD, MDMA, and d-amphetamine and may assist the dose-finding in substance-assisted psychotherapy research.

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 Despite the constant publication of new screening instruments for Internet use disorders (IUD), little is known about their content validity. This study aimed to identify potential mismatches between the items' intention and young adults' interpretation of these items when answering three screening instruments that are commonly used in research and clinical settings: The Compulsive Internet Use Scale (CIUS), the 10 Item-Internet Gaming Disorder Test (IGDT-10), and the Bergen Social Media Addiction Scale (BSMAS). Methods In total, 30 vocational students (50% female, age = 21.3; SD = 2.1) took part in individual think-aloud interviews. All participants were asked to report their thoughts while completing the CIUS. In addition, participants who reported online games (OG) as their main Internet activity (n = 11) answered the IGDT-10. Participants who reported social networks (SN) as their main Internet activity (n = 18) answered the BSMAS. One participant used OG and SN equally and completed both screening instruments. All interviews were audio-recorded, transcribed, and content-analysed. Results Overall, four potential sources for errors were identified: (1) High scorings were often not congruent with the underlying diagnostic criteria. In particular, such discrepancies were found in items aimed to assess dysfunctional emotional regulation strategies and cognitive involvement. (2) Some participants were uncertain which time frame or Internet activity should be considered in their answers. (3) Long and complex items led to the building of mean values or the choice of the middle answer category. (4) Some wordings were perceived to be outdated and difficult to understand. Discussion These findings might help to provide recommendations on how to improve screening instruments for IUD. Most important, items should more clearly distinguish between Internet use as a “normal” leisure activity and Internet use that leads to functional impairments in daily life.

Background Cognitive Behavioral Analysis System of Psychotherapy (CBASP) and Metacognitive Therapy (MCT) are effective for depression. CBASP might offer most benefit in patients reporting childhood emotional abuse (CEA). This needs to be confirmed in real-world settings and in comparisons with depression-specific psychotherapies. This study examines the moderating influence of CEA on the effectiveness of CBASP versus MCT. Methods In this observational study, we recruited patients treated with either CBASP or MCT in an intensive day treatment program for depression. CEA was assessed using the Childhood Trauma Questionnaire (CTQ). Patients reported symptoms weekly using the Quick Inventory of Depressive Symptoms (QIDS-SR). Mixed model analysis was run on the Intention to Treat dataset (ITT) using propensity matching to overcome baseline imbalances. Results A total of 141 patients were included in the analysis (MCT n = 78, CBASP n = 63). CEA moderated the treatment effect (time x CEA x treatment: β = 0.03, SE = 0.01, p = 0.014). Post-hoc analyses revealed that CBASP was more effective than MCT in patients without CEA (time x treatment: β = -0.01, SE = 0.007, p = .045). The difference between CBASP and MCT was not statistically significant for patients with CEA (β = 0.015, SE = 0.008, p = .11). Limitations Because of non-random treatment allocation the differences between CBASP and MCT can be due to unobserved baseline imbalances. Conclusions Our findings suggest that in patients reporting CEA, CBASP might not offer additional benefits above other depression-specific psychotherapies. Public Health Significance Statements This study shows that, on average, individuals with depression benefit equally from CBASP and MCT under the conditions of routine practice. Yet, CBASP was more effective than MCT for those without childhood emotional abuse. If childhood emotional abuse was present, CBASP and MCT were equally effective.

Neuroprotective effects of caffeine have been frequently reported in the context of disease and cognitive dysfunction as well as in epidemiological studies in humans. However, evidence on caffeine effects on neural and memory functions during daily intake in a healthy cognitive state remains scarce. This randomized double-blind placebo-controlled crossover study investigated working memory functions by N-back tasks and functional magnetic resonance imaging (fMRI) after daily caffeine intake compared to a placebo baseline and to acute caffeine withdrawal in 20 young healthy volunteers. Each volunteer was given 3 times 150 mg caffeine for 10 days in the daily caffeine condition, 3 times 150 mg mannitol for 10 days in the placebo condition, and 9-day caffeine plus 1-day mannitol in the acute withdrawal condition. During the 10th day, participants performed 4 N-back sessions (two loads each: 0- and 3-back) under controlled laboratory conditions. During the 4th session of N-Back (i.e. at 5.5 h, 36.5 h and > 10 days after the last caffeine intake in the caffeine, withdrawal, and placebo condition, respectively) we assessed blood-oxygen-level-dependent (BOLD) activity. During the entire 10th day, in 0-back tasks, we observed longer reaction times (RTs) in the withdrawal compared to the placebo (Cohen’s d = 0.7) and caffeine condition (Cohen’s d = 0.6), but no significant effects of conditions on error rates. In contrast, in 3-back tasks (controlled for 0-back), the RTs in the caffeine condition were longer compared to placebo (Cohen’s d = 0.6) and withdrawal (Cohen’s d = 0.5). Error rates were higher during both caffeine and withdrawal conditions compared to placebo (Cohen’s d of both contrasts = 0.4). Whole-brain analyses on fMRI data did not reveal significant condition-dependent differences in activities between task loads. Across task loads, however, we observed a reduced hippocampal activation (Cohen’s d = −1.3) during the caffeine condition compared to placebo, while no significant difference in brain activities between withdrawal and placebo conditions. Taken together, the worse working memory function and the hippocampal hypoactivation implicate a potential detrimental effect of daily caffeine intake on neurocognitive functions of healthy adults. Moreover, they echo the hippocampal volumetric reduction reported previously in the same volunteers. Lastly, acute withdrawal from daily caffeine intake impairs both low-order cognitive processes and working memory performance. Taking earlier studies on acute caffeine effects into account, our findings indicate that daily caffeine intake elicits a dynamic change in cerebral activities during the course of repeated consumption, with unknown consequences in the long run.

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.

Deregulation of synaptic function and neurotransmission has been linked with the development of major depression disorder (MDD). Tianeptine (Tian) has been used as antidepressant with anxiolytic properties and recently as a nootropic to improve cognitive performance, but its mechanism of action is unknown. We conducted a proteomic study on the hippocampal synaptosomal fractions of adult male Wistar rats exposed to chronic social isolation (CSIS, 6 weeks), an animal model of depression and after chronic Tian treatment in controls (nootropic effect) and CSIS-exposed rats (lasting 3 weeks of 6-week CSIS) (therapeutic effect). Increased expression of Syn1 and Camk2-related neurotransmission, vesicle transport and energy processes in Tian-treated controls were found. CSIS led to upregulation of proteins associated with actin cytoskeleton, signaling transduction and glucose metabolism. In CSIS rats, Tian up-regulated proteins involved in mitochondrial energy production, mitochondrial transport and dynamics, antioxidative defense and glutamate clearance, while attenuating the CSIS-increased glycolytic pathway and cytoskeleton organization proteins expression and decreased the expression of proteins involved in V-ATPase and vesicle endocytosis. Our overall findings revealed that synaptic vesicle dynamics, specifically exocytosis, and mitochondria-related energy processes might be key biological pathways modulated by the effective nootropic and antidepressant treatment with Tian and be a potential target for therapeutic efficacy of the stress-related mood disorders.

Although emerging evidence suggests that altered functional connectivity (FC) of large-scale neural networks is associated with disturbances in individuals at high-risk for psychosis, the findings are still far to be conclusive. We conducted a meta-analysis of seed-based resting-state functional magnetic resonance imaging studies that compared individuals at clinical high-risk for psychosis (CHR), first-degree relatives of patients with schizophrenia, or subjects who reported psychotic-like experiences with healthy controls. Twenty-nine studies met the inclusion criteria. The MetaNSUE method was used to analyze connectivity comparisons and symptom correlations. Our results showed a significant hypo-connectivity within the salience network (p = 0.012, uncorrected) in the sample of CHR individuals (n = 810). Additionally, we found a positive correlation between negative symptom severity and FC between the default mode network and both the salience network (p 0.001, r = 0.298) and the central executive network (p = 0.003, r = 0.23) in the CHR group. This meta-analysis lends support for the hypothesis that large-scale network dysfunctions represent a core neural deficit underlying psychosis development.

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.

Special Issue: The ENIGMA Consortium: the first 10 years.-- Karolinska Schizophrenia Project (KaSP)., Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3–90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns., National Institute of Mental Health, Grant/Award Numbers: MH104284, MH116147, R01MH113619, R01 MH090553, R01MH117014, R01MH042191; Karolinska Institutet; Stockholm County Council; Southern and Eastern Norway Regional Health Authority; German Centre for Cardiovascular Research; DZHK; Siemens Healthineers; University of Queensland; US National Institute of Child Health and Human Development, Grant/Award Number: RO1HD050735; Australian National Health and Medical Research Council; Eunice Kennedy Shriver National Institute of Child Health & Human Development; National Institute on Drug Abuse, Grant/Award Numbers: UL1 TR000153, 1 U24 RR025736-01, 1 U24 RR021992; Brain Injury Fund Research Grant Program; Indiana State Department of Health Spinal Cord; Parents Against Childhood Epilepsy; Epilepsy Therapy Project, Fight Against Childhood Epilepsy and Seizures; Epilepsy Foundation; American Epilepsy Society; Knut and Alice Wallenberg Foundation; European Community's Horizon 2020 Programme; Vici Innovation Program; NWO Brain & Cognition Excellence Program; Netherlands Organization for Scientific Research; Hersenstichting Nederland; Netherlands Organization for Health Research and Development; Geestkracht Programme of the Dutch Health Research Council, Grant/Award Number: 10-000-1001; Universiteit Utrecht; FP7 Ideas: European Research Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Center for Advancing Translational Sciences; National Institutes of Health; National Center for Research Resources; Consortium grant, Grant/Award Number: U54 EB020403; U.S. National Institutes of Health, Grant/Award Numbers: R01 CA101318, P30 AG10133, R01 AG19771; Medical Research Council, Grant/Award Number: G0500092; 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; the Research Council, Grant/Award Number: 223273; South Eastern Norway Regional Health Authority, Grant/Award Numbers: 2017-112, 2019107; Swedish Research Council; European Community's Seventh Framework Programme, Grant/Award Number: 602450; King's College London; South London and Maudsley NHS Foundation Trust; Biomedical Research Centre; National Institute for Health Research.

We constructed a novel design integrating the administration of a clinical self-assessment scale with simultaneous acquisition of functional Magnetic Resonance Imaging (fMRI), aiming at cross-validation between psychopathology evaluation and neuroimaging techniques. We hypothesized that areas demonstrating differential activation in two groups of patients (the first group exhibiting paranoid delusions in the context of paranoid schizophrenia&mdash, SCH&mdash, and second group with a depressive episode in the context of major depressive disorder or bipolar disorder&mdash, DEP) will have distinct connectivity patterns and structural differences. Fifty-one patients with SCH (n = 25) or DEP (n = 26) were scanned with three different MRI sequences: a structural and two functional sequences&mdash, resting-state and task-related fMRI (the stimuli represent items from a paranoid-depressive self-evaluation scale). While no significant differences were found in gray matter volumes, we were able to discriminate between the two clinical entities by identifying two significant clusters of activations in the SCH group&mdash, the left Precuneus (PreCu) extending to the left Posterior Cingulate Cortex (PCC) and the right Angular Gyrus (AG). Additionally, the effective connectivity of the middle frontal gyrus (MFG), a part of the Dorsolateral Prefrontal Cortex (DLPFC) to the Anterior Insula (AI), demonstrated a significant difference between the two groups with inhibitory connection demonstrated only in SCH. The observed activations of PreCu, PCC, and AG (involved in the Default Mode Network DMN) might be indirect evidence of the inhibitory connection from the DLPFC to AI, interfering with the balancing function of the insula as the dynamic switch in the DMN. The findings of our current study might suggest that the connectivity from DLPFC to the anterior insula can be interpreted as evidence for the presence of an aberrant network that leads to behavioral abnormalities, the manifestation of which depends on the direction of influence. The reduced effective connectivity from the AI to the DLPFC is manifested as depressive symptoms, and the inhibitory effect from the DLPFC to the AI is reflected in the paranoid symptoms of schizophrenia.

Highlights • Anhedonia is present in many different psychiatric disorders. • Anhedonia has been associated with abnormal reward-related striatal dopamine functioning. • This study tested whether transdiagnostic anhedonia expression mapped onto striatal volume. • Our findings suggest volumetric abnormalities in the putamen and cerebellum as a common neural substrate of anhedonia severity that cut across psychiatric entities., Anhedonia has been associated with abnormal reward-related striatal dopamine functioning in patients with different psychiatric disorders. Here, we tested whether anhedonia expression mapped onto striatal volume across several psychiatric diagnoses. T1-weighted images from 313 participants including 89 healthy controls (HC), 22 patients with opioid use disorder (OUD), 50 patients with major depressive disorder (MDD), 45 patients with borderline personality disorder (BPD), 49 patients with first-episode psychosis (FEP), 43 patients with cocaine use disorder (CUD) and 15 patients with schizophrenia (SZ) were included. Anhedonia was assessed with subscores of the Beck Depression Inventory (BDI) and/or the Scale for the Assessment of Negative Symptoms (SANS). Voxel-based morphometry (VBM) was conducted for identifying dimensional symptom-structure associations using region of interest (ROI, dorsal and ventral striatum) and whole-brain analyses, as well as for group comparisons of striatal volume. ROI analyses revealed significant negative relationships between putamen volume and BDI and SANS anhedonia scores across OUD, MDD, BPD, CUD and SZ patients (n = 175) and MDD, FEP and SZ patients (n = 114), respectively. Whole-brain VBM analyses confirmed these associations and further showed negative relationships between anhedonia severity and volume of the bilateral cerebellum. There were group differences in right accumbens volume, which however were not related to anhedonia expression across the different diagnoses. Our findings indicate volumetric abnormalities in the putamen and cerebellum as a common neural substrate of anhedonia severity that cut across psychiatric entities.

An early detection of emerging psychosis is decisive for the application of preventive interventions. Given that the predictive ability of clinical baseline assessment to prognosticate the onset of psychosis in high-risk individuals is limited, great expectations were raised after implementing neuroimaging techniques as state-of-the-art research methodologies to find brain markers for clinical utility in emerging psychosis. However, although a tremendous amount of effort has been invested, no reliable brain marker has yet been confirmed to predict the transition from the psychosis high-risk state to full-blown psychosis. This may be explained by the fact that previous investigations mainly focussed on changes in local regions rather than brain network dysfunctions. In line with most recent evidence indicating that psychosis may be best understood in terms of brain network dysfunctions, this chapter provides a brief overview of suitable analysis approaches and a selective overview of brain network findings in high-risk subjects for psychosis. Finally, we suggest necessary developments for future research to approach a brain network-driven stratification of individual risk propensity in people with an increased risk for psychosis.

Background Childhood maltreatment and difficulties in emotion regulation are common in patients with Borderline Personality Disorder (BPD) and Depressive Disorders (DD). Objective This study examines differences between patients with BPD and patients with DD, regarding childhood maltreatment and difficulties in emotion regulation as well as the mediating effect of different aspects of emotion regulation deficits on the association between childhood maltreatment and BPD-symptoms. Method A total of 305 participants, 177 with BPD and 128 with DD completed an assessment including the Childhood Trauma Questionnaire (CTQ), the Emotion Regulation Scale (DERS), the Brief Symptom Inventory (BSI), and the Structured Clinical Interview for DSM-IV (SCID). Data was analyzed using multiple analyses of variances and mediation analyses. Results Patients with BPD reported more childhood maltreatment and more difficulties in emotion regulation than patients with DD. When general symptom severity, age, and gender were included in the analysis as covariates only group differences regarding ‘impulse control difficulties’ (F(1,299) = 38.97, p < .001, ηp2 = .115), ‘limited access to emotion regulation strategies’ (F(1,299) = 4.66, p = .032, ηp2 = .015), and ‘lack of emotional clarity’ (F(1,299) = 9.38, p = .002, ηp2 = .030) remained statistically significant. A mediation analysis, including above-mentioned covariates, indicated an association between emotional abuse and BPD-symptoms, which was mediated by difficulties in emotion regulation (indirect effect B = .012, 95% CI [.001; .031], R2 = .429). Subscale analyses revealed ‘impulse control difficulties’ as the aspect of difficulties in emotion regulation that has the greatest impact on this association (B = .021, 95% CI [.003; .045]). Conclusions Patients with BPD display more childhood maltreatment and difficulties in emotion regulation than patients with DD. Difficulties in emotion regulation, especially difficulties in impulse control, seem to play an important role in the association between childhood emotional abuse and BPD-symptoms., HIGHLIGHTS Patients with BPD report more childhood maltreatment and more emotion regulation difficulties than patients with DD and difficulties in emotion regulation, specifically impulse control, play an important role in the association between childhood emotional abuse and BPD symptoms.

Logic-based approaches to AI have the advantage that their behavior can in principle be explained to a user. If, for instance, a Description Logic reasoner derives a consequence that triggers some action of the overall system, then one can explain such an entailment by presenting a proof of the consequence in an appropriate calculus. How comprehensible such a proof is depends not only on the employed calculus, but also on the properties of the particular proof, such as its overall size, its depth, the complexity of the employed sentences and proof steps, etc. For this reason, we want to determine the complexity of generating proofs that are below a certain threshold w.r.t. a given measure of proof quality. Rather than investigating this problem for a fixed proof calculus and a fixed measure, we aim for general results that hold for wide classes of calculi and measures. In previous work, we first restricted the attention to a setting where proof size is used to measure the quality of a proof. We then extended the approach to a more general setting, but important measures such as proof depth were not covered. In the present paper, we provide results for a class of measures called recursive, which yields lower complexities and also encompasses proof depth. In addition, we close some gaps left open in our previous work, thus providing a comprehensive picture of the complexity landscape.

This prognostic study evaluates whether psychosis transition can be predicted in patients with clinical high-risk syndromes or recent-onset depression by multimodal machine learning that optimally integrates clinical and neurocognitive data, structural magnetic resonance imaging, and polygenic risk scores for schizophrenia., Key Points Question Can a transition to psychosis be predicted in patients with clinical high-risk states or recent-onset depression by optimally integrating clinical, neurocognitive, neuroimaging, and genetic information with clinicians’ prognostic estimates? Findings In this prognostic study of 334 patients and 334 control individuals, machine learning models sequentially combining clinical and biological data with clinicians’ estimates correctly predicted disease transitions in 85.9% of cases across geographically distinct patient populations. The clinicians’ lack of prognostic sensitivity, as measured by a false-negative rate of 38.5%, was reduced to 15.4% by the sequential prognostic model. Meaning These findings suggest that an individualized prognostic workflow integrating artificial and human intelligence may facilitate the personalized prevention of psychosis in young patients with clinical high-risk syndromes or recent-onset depression., Importance Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to young patients with depressive syndromes remains unclear. Objectives To evaluate whether psychosis transition can be predicted in patients with CHR or recent-onset depression (ROD) using multimodal machine learning that optimally integrates clinical and neurocognitive data, structural magnetic resonance imaging (sMRI), and polygenic risk scores (PRS) for schizophrenia; to assess models’ geographic generalizability; to test and integrate clinicians’ predictions; and to maximize clinical utility by building a sequential prognostic system. Design, Setting, and Participants This multisite, longitudinal prognostic study performed in 7 academic early recognition services in 5 European countries followed up patients with CHR syndromes or ROD and healthy volunteers. The referred sample of 167 patients with CHR syndromes and 167 with ROD was recruited from February 1, 2014, to May 31, 2017, of whom 26 (23 with CHR syndromes and 3 with ROD) developed psychosis. Patients with 18-month follow-up (n = 246) were used for model training and leave-one-site-out cross-validation. The remaining 88 patients with nontransition served as the validation of model specificity. Three hundred thirty-four healthy volunteers provided a normative sample for prognostic signature evaluation. Three independent Swiss projects contributed a further 45 cases with psychosis transition and 600 with nontransition for the external validation of clinical-neurocognitive, sMRI-based, and combined models. Data were analyzed from January 1, 2019, to March 31, 2020. Main Outcomes and Measures Accuracy and generalizability of prognostic systems. Results A total of 668 individuals (334 patients and 334 controls) were included in the analysis (mean [SD] age, 25.1 [5.8] years; 354 [53.0%] female and 314 [47.0%] male). Clinicians attained a balanced accuracy of 73.2% by effectively ruling out (specificity, 84.9%) but ineffectively ruling in (sensitivity, 61.5%) psychosis transition. In contrast, algorithms showed high sensitivity (76.0%-88.0%) but low specificity (53.5%-66.8%). A cybernetic risk calculator combining all algorithmic and human components predicted psychosis with a balanced accuracy of 85.5% (sensitivity, 84.6%; specificity, 86.4%). In comparison, an optimal prognostic workflow produced a balanced accuracy of 85.9% (sensitivity, 84.6%; specificity, 87.3%) at a much lower diagnostic burden by sequentially integrating clinical-neurocognitive, expert-based, PRS-based, and sMRI-based risk estimates as needed for the given patient. Findings were supported by good external validation results. Conclusions and Relevance These findings suggest that psychosis transition can be predicted in a broader risk spectrum by sequentially integrating algorithms’ and clinicians’ risk estimates. For clinical translation, the proposed workflow should undergo large-scale international validation.

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.

Non-segmented MRI brain images are used for the identification of new Magnetic Resonance Imaging (MRI) biomarkers able to differentiate between schizophrenic patients (SCZ), major depressive patients (MD) and healthy controls (HC). Brain texture measures such as entropy and contrast, capturing the neighboring variation of MRI voxel intensities, were computed and fed into deep learning technique for group classification. Layer-wise relevance was applied for the localization of the classification results. Texture feature map of non-segmented brain MRI scans were extracted from 141 SCZ, 103 MD and 238 HC. The gray level co-occurrence matrix (GLCM) was calculated on a voxel-by-voxel basis in a cube of voxels. Deep learning tested if texture feature map could predict diagnostic group membership of three classes under a binary classification (SCZ vs. HC, MD vs. HC, SCZ vs. MD). The method was applied in a repeated nested cross-validation scheme and cross-validated feature selection. The regions with the highest relevance (positive/negative) are presented. The method was applied on non-segmented images reducing the computation complexity and the error associated with segmentation process.

Pattern classification aims to establish a new approach in personalized treatment. The scope is to tailor treatment on individual characteristics during all phases of care including prevention, diagnosis, treatment, and clinical outcome. In psychotic disorders, this need results from the fact that a third of patients with psychotic symptoms do not respond to antipsychotic treatment and are described as having treatment-resistant disorders. This, in addition to the high variability of treatment responses among patients, enhances the need of applying advanced classification algorithms to identify antipsychotic treatment patterns. This review comprehensively summarizes advancements and challenges of pattern classification in antipsychotic treatment response to date and aims to introduce clinicians and researchers to the challenges of including pattern classification into antipsychotic treatment decision algorithms.

Promotion of good mental health in young people is important. Our aim was to evaluate the consistency and magnitude of the efficacy of universal/selective interventions to promote good mental health. A systematic PRISMA/RIGHT-compliant meta-analysis (PROSPERO: CRD42018088708) search of Web of Science until 04/31/2019 identified original studies comparing the efficacy of universal/selective interventions for good mental health vs a control group, in samples with a mean age < 35 years. Meta-analytical random-effects model, heterogeneity statistics, assessment of publication bias, study quality and sensitivity analyses investigated the efficacy (Hedges' g = effect size, ES) of universal/selective interventions to promote 14 good mental health outcomes defined a-priori. 276 studies were included (total participants: 159,508, 79,142 interventions and 80,366 controls), mean age = 15.0 (SD = 7.4); female = 56.0%. There was a significant overall improvement in 10/13 good mental health outcome categories that could be meta-analysed: compared to controls, interventions significantly improved (in descending order of magnitude) mental health literacy (ES = 0.685, p < 0.001), emotions (ES = 0.541, p < 0.001), self-perceptions and values (ES = 0.49, p < 0.001), quality of life (ES = 0.457, p = 0.001), cognitive skills (ES = 0.428, p < 0.001), social skills (ES = 0.371, p < 0.001), physical health (ES = 0.285, p < 0.001), sexual health (ES = 0.257, p = 0.017), academic/occupational performance (ES = 0.211, p < 0.001) and attitude towards mental disorders (ES = 0.177, p = 0.006). Psychoeducation was the most effective intervention for promoting mental health literacy (ES = 0.774, p < 0.001) and cognitive skills (ES = 1.153, p = 0.03). Physical therapy, exercise and relaxation were more effective than psychoeducation and psychotherapy for promoting physical health (ES= 0.498, p

A potential pathophysiological mechanism of cognitive difficulties in schizophrenia is a dysregulated cholinergic system. Particularly, the cholinergic basal forebrain nuclei (BFCN), the source of cortical cholinergic innervation, support multiple cognitive functions, ranging from attention to decision-making. We hypothesized that BFCN structural integrity is altered in schizophrenia and associated with patients’ attentional deficits. We assessed gray matter (GM) integrity of cytoarchitectonically defined BFCN region-of-interest in 72 patients with schizophrenia and 73 healthy controls, matched for age and gender, from the COBRE open-source database, via structural magnetic resonance imaging (MRI)–based volumetry. MRI-derived measures of GM integrity (i.e., volumes) were linked with performance on a symbol coding task (SCT), a paper-pencil-based metric that assesses attention, by correlation and mediation analysis. To assess the replicability of findings, we repeated the analyses in an independent dataset comprising 26 patients with schizophrenia and 24 matched healthy controls. BFCN volumes were lower in patients (t(139)=2.51, p = 0.01) and significantly associated with impaired SCT performance (r = 0.31, p = 0.01). Furthermore, lower BFCN volumes mediated the group difference in SCT performance. When including global GM volumes, which were lower in patients, as covariates-of-no-interest, these findings disappeared, indicating that schizophrenia did not have a specific effect on BFCN relative to other regional volume changes. We replicated these findings in the independent cohort, e.g., BFCN volumes were lower in patients and mediated patients’ impaired SCT performance. Results demonstrate lower BFCN volumes in schizophrenia, which link with patients’ attentional deficits. Data suggest that a dysregulated cholinergic system might contribute to cognitive difficulties in schizophrenia via impaired BFCN., Open Access funding enabled and organized by Projekt DEAL.

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.

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.

Acute caffeine intake can attenuate homeostatic sleep pressure and worsen sleep quality. Besides, caffeine intake – particularly in high doses and close to bedtime – may also affect circadian-regulated REM sleep promotion, an important determinant of subjective sleep quality. However, it is not known whether such changes persist under chronic caffeine consumption during daytime. Twenty male caffeine consumers (26.4 ± 4 years old, habitual caffeine intake 478.1 ± 102.8 mg/day) participated in a double-blind crossover study. Each volunteer completed a caffeine (3 × 150 mg caffeine daily), a withdrawal (3 × 150 mg caffeine for eight days then placebo), and a placebo condition. After ten days of controlled intake and a fixed sleep-wake cycle, we recorded 8 h of electroencephalography starting 5 h after habitual bedtime (i.e., start on average at 04:22 am which is around the peak of circadian REM sleep promotion). A 60 min evening nap preceded each sleep episode and reduced high sleep pressure levels. While total sleep time and sleep architecture did not significantly differ between the three conditions, REM latency was longer after daily caffeine intake compared to both placebo and withdrawal. Moreover, the accumulation of REM sleep proportion was slower, and volunteers reported more difficulties at awakening after sleep and feeling more tired upon wake-up in the caffeine condition compared to placebo. Our data indicate that besides acute also regular daytime caffeine intake affects REM sleep regulation in men. We have evidence that regular caffeine intake during daytime weakens circadian sleep promotion when compared to placebo. Moreover, the observed caffeine-induced deterioration in the quality of awakening may suggest a potential motive to reinstate caffeine intake after sleep.

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).

Brainstem regions support vital bodily functions, yet their genetic architectures and involvement in common brain disorders remain understudied. Here, using imaging-genetics data from a discovery sample of 27,034 individuals, we identify 45 brainstem-associated genetic loci, including the first linked to midbrain, pons, and medulla oblongata volumes, and map them to 305 genes. In a replication sample of 7432 participants most of the loci show the same effect direction and are significant at a nominal threshold. We detect genetic overlap between brainstem volumes and eight psychiatric and neurological disorders. In additional clinical data from 5062 individuals with common brain disorders and 11,257 healthy controls, we observe differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson’s disease, supporting the relevance of brainstem regions and their genetic architectures in common brain disorders., The genetic architecture underlying brainstem regions and how this links to common brain disorders is not well understood. Here, the authors use MRI and GWAS data from 27,034 individuals to identify genetic and morphological brainstem features that influence common brain disorders.

Recent life events have been implicated in the onset and progression of psychosis. However, psychological processes that account for the association are yet to be fully understood. Using a network approach, we aimed to identify pathways linking recent life events and symptoms observed in psychosis. Based on previous literature, we hypothesized that general symptoms would mediate between recent life events and psychotic symptoms. We analyzed baseline data of patients at clinical high risk for psychosis and with recent-onset psychosis (n = 547) from the Personalised Prognostic Tools for Early Psychosis Management (PRONIA) study. In a network analysis, we modeled links between the burden of recent life events and all individual symptoms of the Positive and Negative Syndrome Scale before and after controlling for childhood trauma. To investigate the longitudinal associations between burden of recent life events and symptoms, we analyzed multiwave panel data from seven timepoints up to month 18. Corroborating our hypothesis, burden of recent life events was connected to positive and negative symptoms through general psychopathology, specifically depression, guilt feelings, anxiety and tension, even after controlling for childhood trauma. Longitudinal modeling indicated that on average, burden of recent life events preceded general psychopathology in the individual. In line with the theory of an affective pathway to psychosis, recent life events may lead to psychotic symptoms via heightened emotional distress. Life events may be one driving force of unspecific, general psychopathology described as characteristic of early phases of the psychosis spectrum, offering promising avenues for interventions.

Distress Tolerance Skills (DTS) are an important component of Dialectical Behavioral Therapy (DBT), a therapy method frequently used for treating patients with Borderline Personality Disorder (BPD). However, little is known about how DTS-training is experienced by individuals with BPD. The aim of this study was to explore BPD patients’ experiences with receiving DTS-training. Qualitative data were collected through semi-structured interviews with 24 individuals (87.5% females) with a primary diagnosis of BPD who received DTS-training in the context of 18 months of DBT treatment. Interview data were analyzed following the procedures of qualitative content analysis. Participants reported various effects of DTS including an immediate reduction of tension. Patients perceived DTS as a tool to cope with difficult interpersonal situations and emergencies and stated that this helped them to feel stable, safe and self-confident. Patients reported difficulties during the initial engagement, the learning process and the application of DTS as well as various facilitating factors. Implications of the findings for further research and for optimizing DTS-training in clinical practice are discussed.

A multitude of prediction models for a first psychotic episode in individuals at clinical high-risk (CHR) for psychosis have been proposed, but only rarely validated. We identified transition models based on clinical and neuropsychological data through a registered systematic literature search and evaluated their external validity in 173 CHRs from the Personalised Prognostic Tools for Early Psychosis Management (PRONIA) study. Discrimination performance was assessed with the area under the receiver operating characteristic curve (AUC), and compared to the prediction of clinical raters. External discrimination performance varied considerably across the 22 identified models (AUC 0.40-0.76), with two models showing good discrimination performance. None of the tested models significantly outperformed clinical raters (AUC = 0.75). Combining predictions of clinical raters and the best model descriptively improved discrimination performance (AUC = 0.84). Results show that personalized prediction of transition in CHR is potentially feasible on a global scale. For implementation in clinical practice, further rounds of external validation, impact studies, and development of an ethical framework is necessary.

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.