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Objective: To determine cannabinoid-levels in blood and driving-related ability after single (S1) and repetitive (S2) vapor inhalation of cannabis low in Δ9-tetrahydrocannabinol (THC), but high in cannabidiol (CBD). Methods: In a prospective, randomized, cross-over study at the Institute of Forensic Medicine Basel, healthy adults (NS1=27, NS2=20) vapor-inhaled two low-THC/CBD-rich products (both Outcomes: i) THC- and CBD-levels in whole blood, ii) assessment of driving-related ability.Results: Among 74 participants included, 27 (mean age ± SD, 28.9 ± 12.5 years) completed S1, and 20 (25.2 ± 4.0) completed S2. THC dropped below 1.5 µg/L after 1.5 h, but was detected up to 5 h. Pairwise comparison of driving-related ability revealed no significant differences between low-THC/CBD-rich products (P1, P2) and placebo (P1 - P2: β = 0.319 [95% CI, -1.731 to 2.368], p = 0.950; P1 - placebo: β = 0.854 [95% CI, -1.329 to 3.037], p = 0.724; P2 - placebo: β = 0.535 [95% CI, -1.632 to 2.702], p = 0.879).Conclusions: Detection of THC after consumption of low-THC/CBD-rich cannabis might have legal consequences for drivers. Regarding overall driving-related ability, no significant differences were observed between interventional products.Trial Registration: German Clinical Trials Register: DRKS00018836.

Background Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research.

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.

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.

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.

In schizophrenic psychoses, the normal sexual dimorphism of the brain has been shown to be disrupted or even reversed. Little is known, however, at what time point in emerging psychosis this occurs. We have therefore examined, if these alterations are already present in the at-risk mental state (ARMS) for psychosis and in first episode psychosis (FEP) patients.; Data from 65 ARMS (48 (73.8%) male; age=25.1±6.32) and 50 FEP (37 (74%) male; age=27±6.56) patients were compared to those of 70 healthy controls (HC; 27 (38.6%) male; age=26±4.97). Structural T1-weighted images were acquired using a 3 Tesla magnetic resonance imaging (MRI) scanner. Linear mixed effects models were used to investigate whether subcortical brain volumes are dependent on sex.; We found men to have larger total brain volumes (p

AIM Gender differences in the current symptomatology of patients with psychotic disorders have previously been described in the literature. However, it has not yet been investigated whether gender differences exist in the very first self-perceived signs or symptoms of illness onset. The aim of this study was to investigate this aspect in at-risk mental state (ARMS) and first-episode psychosis (FEP) patients. METHODS ARMS and FEP were recruited via the early detection of psychosis (FePsy) clinic Basel, Switzerland. The Basel Interview for Psychosis (BIP) was used to retrospectively assess the first 3 self-perceived signs and symptoms at illness onset. Differences between gender and patient groups on single item and symptom cluster levels were analysed using logistic regression models. RESULTS One-hundred-thirty six ARMS (91 men, 45 women) and 89 FEP patients (63 men, 26 women) could be recruited for this study. On a single item level, women more frequently reported "unusual anxiety, fears" and men (at a trend level) "social withdrawal" as being among their 3 first self-perceived symptoms, independent of diagnostic group. On the symptom cluster level, women more frequently reported "increased worrying/anxiety" and (sub-threshold) "hallucinations", independent of diagnostic group. Problems with "thinking, concentration" were reported more frequently by men in the ARMS group only. CONCLUSION Our results suggest that only few and relatively small gender differences exist in the first self-perceived signs and symptoms. While men initially mainly notice negative/cognitive symptoms, women first notice (sub-threshold) positive and affective symptoms.

Background Bullying as a specific subtype of adverse life events is a major risk factor for poor mental health. Although many questionnaires on bullying are available, so far none covers bullying retrospectively throughout school and working life. To close this gap, the Bullying Scale for Adults (BSA) was designed. Methods Based on data of 622 participants from five European countries collected in the prospective multicenter Personalized Prognostic Tools for Early Psychosis Management (PRONIA) study, we investigated whether the BSA is a reliable and valid measurement for bullying and whether there is a difference across different diagnostic groups of early mental disorders (recent onset depressive/ psychotic patients, patients at clinical high-risk of psychosis) and healthy controls. Results Bullying experiences were significantly less frequent in healthy controls than in patient groups, with no significant differences between the three clinical groups. The BSA exhibited a high item scale discrimination (r > .3) and very good internal consistency (Cronbach's α = .93). Four factors were identified: 1. Sexual harassment, 2. Emotional Abuse, 3. Physical Abuse, 4. Problems at school. The highly significant correlation between bullying, and childhood adversities and trauma (r = .645, p Discussion The BSA is the first validated questionnaire that, in retrospective, reliably records various aspects of bullying (incl. its consequences) not only throughout childhood but also working life. It can be used to assess bullying as a transdiagnostic risk factor of mental disorders in different mental disorders, esp. psychosis and depression.

Depressive symptoms in subjects at Clinical High Risk for Psychosis (CHR-P) or at first-episode psychosis (FEP) are often treated with antidepressants. Our cross-sectional study investigated whether brain morphology is altered by antidepressant medication. High-resolution T1-weighted structural MRI scans of 33 CHR-P and FEP subjects treated with antidepressants, 102 CHR-P and FEP individuals without antidepressant treatment and 55 controls, were automatically segmented using Freesurfer 6.0. Linear mixed-effects modelling was applied to assess the differences in subcortical volume, surface area and cortical thickness in treated, non-treated and healthy subjects, taking into account converted dosages of antidepressants. Increasing antidepressant dose was associated with larger volume of the pallidum and the putamen, and larger surface of the left inferior temporal gyrus. In a pilot subsample of separately studied subjects of known genomic risk loci, we found that in the right postcentral gyrus, the left paracentral lobule and the precentral gyrus antidepressant dose-associated surface increase depended on polygenic schizophrenia-related-risk score. As the reported regions are linked to the symptoms of psychosis, our findings reflect the possible beneficial effects of antidepressant treatment on an emerging psychosis.

Background:Few studies have followed up patients with a clinical high risk (CHR) for psychosis for more than 2–3 years. We aimed to investigate the rates and baseline predictors for remission from CHR and transition to psychosis over a follow-up period of up to 16 years. Additionally, we examined the clinical and functional long-term outcome of CHR patients who did not transition.Methods:We analyzed the long-term course of CHR patients that had been included in the longitudinal studies “Früherkennung von Psychosen” (FePsy) or “Bruderholz” (BHS). Those patients who had not transitioned to psychosis during the initial follow-up periods (2/5 years), were invited for additional follow-ups.Results:Originally, 255 CHR patients had been included. Of these, 47 had transitioned to psychosis during the initial follow-ups. Thus, 208 were contacted for the long-term follow-up, of which 72 (34.6%) participated. From the original sample of 255, 26%, 31%, 35%, and 38% were estimated to have transitioned after 3, 5, 10, and 16 years, respectively, and 51% had remitted from their high risk status at the latest follow-up. Better psychosocial functioning at baseline was associated with a higher rate of remission. Of the 72 CHR patients re-assessed at long-term follow-up, 60 had not transitioned, but only 28% of those were fully recovered clinically and functionally.Conclusions:Our study shows the need for follow-ups and clinical attention longer than the usual 2–3 years as there are several CHR patients with later transitions and only a minority of CHR those without transition fully recovers.

AIM Ultrahigh risk (UHR) criteria, consisting of brief limited intermittent psychotic symptoms (BLIPS), attenuated psychotic symptoms (APS) and genetic risk and deterioration (GRD) syndrome are the most widely used criteria for assessing the clinical high-risk state for psychosis (CHR-P). The Basel Screening Instrument for Psychosis (BSIP) includes a further risk category, the unspecific risk category (URC). However, little is known about the predictive power of this risk category compared to other risk categories. METHODS Two hundred CHR-P patients were detected as part of the Fruherkennung von Psychosen (FePsy) study using the BSIP. Transition to psychosis was assessed in regular intervals for up to 7 years. RESULTS Patients meeting only the URC criterion (n = 40) had a significantly lower risk of transition to psychosis than the UHR group (including BLIPS, APS and GRD) (HR 0.19 [0.05; 0.80] (P = 0.024). Furthermore, the URC only risk group had a lower transition risk than the APS without BLIPS group (P = 0.015) and a trendwise lower risk than the BLIPS group (P = 0.066). However, despite the lower transition risk in the URC only group, there were still two patients (5%) in this group with a later transition to psychosis. CONCLUSIONS The URC includes patients who have a lower risk of transition than those included by the UHR categories and thereby increases the sensitivity of the BSIP. This offers the possibility of a stratified intervention, with these subjects receiving low intensity follow-up and treatment.

Background:Gender differences in symptomatology in chronic schizophrenia and first episode psychosis patients have often been reported. However, little is known about gender differences in those at risk of psychotic disorders. This study investigated gender differences in symptomatology, drug use, comorbidity (i.e. substance use, affective and anxiety disorders) and global functioning in patients with an at-risk mental state (ARMS) for psychosis.Methods:The sample consisted of 336 ARMS patients (159 women) from the prodromal work package of the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI; 11 centers). Clinical symptoms, drug use, comorbidity and functioning were assessed at first presentation to an early detection center using structured interviews.Results:In unadjusted analyses, men were found to have significantly higher rates of negative symptoms and current cannabis use while women showed higher rates of general psychopathology and more often displayed comorbid affective and anxiety disorders. No gender differences were found for global functioning. The results generally did not change when corrected for possible cofounders (e.g. cannabis use). However, most differences did not withstand correction for multiple testing.Conclusions:Findings indicate that gender differences in symptomatology and comorbidity in ARMS are similar to those seen in overt psychosis and in healthy controls. However, observed differences are small and would only be reliably detected in studies with high statistical power. Moreover, such small effects would likely not be clinically meaningful.

Objectives: Brain-derived neurotrophic factor (BDNF) is involved in numerous cognitive processes. Since cognitive deficits are a core feature of psychotic disorders, the investigation of BDNF levels in psychosis and their correlation with cognition has received increased attention. However, there are no studies investigating BDNF levels in individuals with an at-risk mental state (ARMS) for psychosis. Hence, the aims of the present study were: (1) assessing peripheral BDNF levels across different (potential) stages of psychosis; (2) investigating their association with cognition. Methods: Plasma and serum BDNF levels and neuropsychological performance were assessed in 16 ARMS, six first-episode psychosis (FEP), and 11 chronic schizophrenia (CS) patients. Neuropsychological assessment covered intelligence, verbal memory, working memory, attention and executive functioning. Results: Both plasma and serum BDNF levels were highest in CS, intermediate in FEP and lowest in ARMS. Multiple regression analysis revealed a significant positive association of plasma BDNF levels with planning ability across all groups. Conclusions: The lower peripheral BDNF levels in ARMS compared to FEP and CS might point towards an important drop of this neurotrophin prior to the onset of frank psychosis. The associations of peripheral BDNF with planning-abilities match previous findings.

Grey matter (GM) volume alterations have been repeatedly demonstrated in patients with first episode psychosis (FEP). Some of these neuroanatomical abnormalities are already evident in the at-risk mental state (ARMS) for psychosis. Not only GM alterations but also neurocognitive impairments predate the onset of frank psychosis with verbal learning and memory (VLM) being among the most impaired domains. Yet, their interconnection with alterations in GM volumes remains ambiguous. Thus, we evaluated associations of different subcortical GM volumes in the medial temporal lobe with VLM performance in antipsychotic-naive ARMS and FEP patients. Data from 59 ARMS and 31 FEP patients, collected within the prospective Fruherkennung von Psychosen study, were analysed. Structural T1-weighted images were acquired using a 3 Tesla magnetic resonance imaging scanner. VLM was assessed using the California Verbal Learning Test and its factors Attention Span, Learning Efficiency, Delayed Memory and Inaccurate Memory. FEP patients showed significantly enlarged volumes of hippocampus, pallidum, putamen and thalamus compared to ARMS patients. A significant negative association between amygdala and pallidum volume and Attention Span was found in ARMS and FEP patients combined, which however did not withstand correction for multiple testing. Although we found significant between-group differences in subcortical volumes and VLM is among the most impaired cognitive domains in emerging psychosis, we could not demonstrate an association between low performance and subcortical GM volumes alterations in antipsychotic-naive patients. Hence, deficits in this domain do not appear to stem from alterations in subcortical structures.

Background Verbal learning and memory are impaired not only in patients with a first episode of psychosis (FEP) but also–to a lower extent–in those with an at-risk mental state for psychosis (ARMS). However, little is known about the specific nature of these impairments. Hence, we aimed to study learning and memory processes in ARMS and FEP patients by making use of structural equation modelling. Methods Verbal learning was assessed with the California Verbal Learning Test (CVLT) in 98 FEP patients, 126 ARMS patients and 68 healthy controls (HC) as part of the Basel early detection of psychosis (FePsy) study. The four-factorial CFA model of Donders was used to estimate test performance on latent variables of the CVLT and growth curve analysis was used to model the learning curve. The latter allows disentangling initial recall, which is strongly determined by attentional processes, from the learning rate. Results The CFA model revealed that ARMS and FEP patients were impaired in Attention Span, Learning Efficiency and Delayed Memory and that FEP patients were additionally impaired in Inaccurate Memory. Additionally, ARMS-NT, but not ARMS-T, performed significantly worse than HC on Learning Efficiency. The growth curve model indicated that FEP patients were impaired in both initial recall and learning rate and that ARMS patients were only impaired in the learning rate. Conclusions Since impairments were more pronounced in the learning rate than the initial recall, our results suggest that the lower scores in the CVLT reported in previous studies are more strongly driven by impairments in the rate of learning than by attentional processes.

Negative symptoms and neurocognitive performance have been reported to be negatively associated in patients with emerging psychosis. However, most previous studies focused on patients with frank psychosis and did not differentiate between subdomains of negative symptoms. Hence, we aimed to elucidate the specific relationship between negative symptoms and cognitive functioning in patients at clinical high risk (CHR) for psychosis. Data from 154 CHR patients collected within the prospective Fruherkennung von Psychosen (FePsy) study were analyzed. Negative symptoms were assessed with the Scale for the Assessment of Negative Symptoms (SANS) and cognitive functioning with an extensive neuropsychological test battery. Regression analyses revealed significant negative associations between negative symptoms and cognitive functioning, particularly in the domains of nonverbal intelligence and verbal fluency. When analyzing each negative symptom domain separately, alogia and asociality/anhedonia were significantly negatively associated with nonverbal intelligence and alogia additionally with verbal fluency. Overall, our results in CHR patients are similar to those reported in patients with frank psychosis. The strong negative association between verbal fluency and negative symptoms may be indicative of an overlap between these constructs. Verbal fluency might have a strong influence on the clinical impression of negative symptoms (particularly alogia) and vice versa.

Background Hyperprolactinemia is a known side effect of antipsychotics. In recent reports it has also been shown in antipsychotic-naive at-risk mental state (ARMS) and first-episode psychosis (FEP) patients. Prolactin is not only involved in reproduction and lactation, but is also synthesized in response to stress. As stress is thought to play an important role in the onset and relapse of schizophrenia, the aim of this study was to further elucidate the influence of prolactin in emerging psychosis. Methods The data analysed in this study were collected within the prospective Fruherkennung von Psychosen (FePsy) study. Blood sample collection took place under standardized conditions between 8 and 10 am after an overnight fast and 30 minutes of rest. All patients were antipsychotic-naive and did not take any prolactin influencing medication. Results Our sample consisted of 116 antipsychotic-naive ARMS and 49 FEP patients. Hyperprolactinemia was shown in 32% of ARMS and 35% of FEP patients. After correction for the normal biological variation between the sexes, we still found higher average prolactin levels in female than in male patients (β = 0.42; t = 2.47; p = 0.01) but no difference in prolactin levels between ARMS and FEP patients (β = − 0.05; t = − 0.30; p = 0.76). The survival analysis revealed no significant predictive value for prolactin levels to predict transition to psychosis. Conclusion Our findings support a possible role of prolactin in emerging psychosis and it could be speculated that stress, which can induce hyperprolactinemia, has a stronger effect on women than on men in emerging psychosis.

The brain-gut-axis is an interdependent system affecting neural functions and controlling our eating behaviour. In recent decades, neuroimaging techniques have facilitated its investigation. We systematically looked into functional and neurochemical brain imaging studies investigating how key molecules such as ghrelin, glucagon-like peptide-1 (GLP-1), peptide tyrosine-tyrosine (PYY), cholecystokinin (CCK), leptin, glucose and insulin influence the function of brain regions regulating appetite and satiety. Of the 349 studies published before July 2016 identified in the database search, 40 were included (27 on healthy and 13 on obese subjects). Our systematic review suggests that the plasma level of ghrelin, the gut hormone promoting appetite, is positively correlated with activation in the pre-frontal cortex (PFC), amygdala and insula and negatively correlated with activation in subcortical areas such as the hypothalamus. In contrast, the plasma levels of glucose, insulin, leptin, PYY, GLP-1 affect the same brain regions conversely. Our study integrates previous investigations of the gut-brain matrix during food-intake and homeostatic regulation and may be of use for future meta-analyses of brain-gut interactions.

Reduction in hippocampal volume is a hallmark of schizophrenia and already present in the clinical high-risk state. Nevertheless, other subcortical structures, such as the thalamus, amygdala and pallidum can differentiate schizophrenia patients from controls. We studied the role of hippocampal and subcortical structures in clinical high-risk individuals from two cohorts. High-resolution T1-weighted structural MRI brain scans of a total of 91 clinical high-risk individuals and 64 healthy controls were collected in two centers. The bilateral volume of the hippocampus, the thalamus, the caudate, the putamen, the pallidum, the amygdala, and the accumbens were automatically segmented using FSL-FIRST. A linear mixed-effects model and a prospective meta-analysis were applied to assess group-related volumetric differences. We report reduced hippocampal and thalamic volumes in clinical high-risk individuals compared to healthy controls. No volumetric alterations were detected for the caudate, the putamen, the pallidum, the amygdala, or the accumbens. Moreover, we found comparable medium effect sizes for group-related comparison of the thalamus in the two analytical methods. These findings underline the relevance of specific alterations in the hippocampal and subcortical volumes in the high-risk state. Further analyses may allow hippocampal and thalamic volumes to be used as biomarkers to predict psychosis.

IntroductionNegative symptoms and cognitive impairments are both present in patients with an at risk mental state (ARMS) for psychosis and negatively affect functioning and outcome. According to previous studies in patients with first-episode psychosis, negative symptoms are negatively associated with cognitive functioning while positive symptoms do not seem to be associated. Yet, little is known about the specific relationship of negative symptoms and cognitive functioning in ARMS patients.ObjectiveTo evaluate, the relationship between negative symptoms and cognitive functioning in ARMS patients.MethodsData of 154 ARMS patients were collected within the prospective Basel early detection of psychosis (FePsy) study. Negative symptoms were assessed with the SANS, positive psychotic symptoms with the BPRS, cognitive functioning with an extensive neuropsychological test battery. Multiple regressions were applied and results were controlled for age and gender.ResultsRegression analyses showed a significant, negative association between negative but not positive psychotic symptoms and cognitive functioning, showing the strongest association with verbal fluency (see Fig. 1). However, results mainly did not withstand correction for multiple testing.ConclusionsThe association found between verbal fluency and negative symptoms may be indicative of an overlap between those constructs. Finally, verbal fluency might have a strong influence on the clinical impression of negative symptoms, especially on alogia.Disclosure of interestThe authors have not supplied their declaration of competing interest.

IntroductionIn the growing research field of early psychosis detection in patients with an at risk mental state (ARMS), most studies focus on the transition to frank psychosis. However, the majority of ARMS patients do not go on to develop frank psychosis and reported transition rates are declining. Little is known about the long-term outcome of these non-transitioned patients (ARMS-NT).ObjectivesTo investigate in preliminary analyses the long-term outcome of ARMS-NT patients with respect to persistence of ARMS signs and symptoms and the rates of late psychotic transition.MethodsThe ongoing study “FePsy-BHS-NT” follows up ARMS-NT without transition during at least the first two years for up to 15 years after their initial assessment. ARMS status is ascertained with the Basel Screening Instrument for Psychosis (BSIP). ARMS remission is defined as the absence of attenuated psychotic symptoms or brief limited intermittent psychotic symptoms for at least 12 consecutive months.ResultsIn this preliminary sample of 51 ARMS-NT, the majority of patients (70.6%) have remitted from their at risk mental state, 13.7% remain at risk and 15.7% have made a late psychotic transition during the course of long-term follow up (median = 5.75, range 4–11 years after initial assessment).ConclusionsThe considerable rates of ARMS persistence and late psychotic transition indicate that longer follow-up durations than commonly recommended should be contemplated in ARMS patients. Potential predictors of favorable long-term clinical outcome, as well as psychosocial, neurocognitive and other outcomes of ARMS-NT patients will be further evaluated in the present study.Disclosure of interestThe authors have not supplied their declaration of competing interest.

IntroductionNon-psychotic axis I diagnoses are highly prevalent in at-risk mental state (ARMS) and first episode psychosis (FEP) patients, the most common being affective and anxiety disorders. Few studies have examined differences between ARMS and FEP patients or gender effects regarding such diagnoses.ObjectiveTo examine current and lifetime comorbidities in ARMS and FEP patients. Furthermore, to examine gender differences, and differences between patients with (ARMS-T) and without later transition to psychosis (ARMS-NT).MethodsThis study was part of the Früherkennung von Psychosen (FePsy) study. Current and lifetime axis I comorbidities were assessed using the Structured Clinical Interview for DSM-IV (SCID-I).ResultsOne hundred and thirty-two ARMS and 98 FEP patients were included. Current comorbidities were present in 53.1% of FEP and 64.4% of ARMS patients, the most common being affective, anxiety and substance use disorders. Current affective disorders were significantly more common in ARMS than FEP. Lifetime comorbidities were diagnosed in 58.2% of FEP and 69.7% of ARMS patients, with significantly more affective and anxiety disorders in ARMS than FEP. Male FEP patients had more current and lifetime substance use disorders (across all substances) compared to female FEP. No differences emerged between ARMS-T and ARMS-NT.ConclusionsAs expected ARMS patients have many comorbidities, while clearly diagnosed FEP have less comorbidities. There were few gender differences in axis I comorbidities. Moreover, no differences between ARMS-T and NT emerged, suggesting that axis I comorbidities do not improve prediction of transition. Nevertheless, the high comorbidity prevalence is relevant for global functioning and clinical treatment.Disclosure of interestThe authors have not supplied their declaration of competing interest.

IntroductionClinical, epidemiological and basic research studies have confirmed that estradiol can have protective effects in schizophrenic psychoses. At the same time many patients with schizophrenic psychoses – even antipsychotic naïve at-risk mental state (ARMS) patients show hyperprolactinemia and gonadal dysfunction with estrogen deficiency in women and possibly testosterone deficiency in men.AimTo investigate the relation between the stress hormone prolactin and the sex hormones estradiol in women and testosterone in men in emerging psychosis.MethodsForty-seven antipsychotic-naïve ARMS (38 men and 9 women) and 17 antipsychotic-naive first episode psychosis (FEP) (14 men and 3 women) patients were recruited via the Basel Früherkennung von Psychosen (FePsy) study. Blood was taken under standardized conditions between 8 and 10 am after an overnight fast and 30 minutes of rest. We performed a linear regression model to evaluate the association between prolactin and sex hormones including age and current antidepressant use as covariates.ResultsIn women, estradiol was negatively associated with prolactin (β = −1.28, P = 0.01) whereas in men there was a positive association of testosterone with prolactin (β = 0.52, P = 0.031).ConclusionThe often observed estrogen deficiency in women with psychosis could therefore be explained by the stress hormone prolactin suppressing the gonadal axis already in very early untreated stages of the emerging disease.In ARMS or FEP men prolactin does not seem to influence the gonadal axis in the same way as in women.Disclosure of interestThe authors have not supplied their declaration of competing interest.

IntroductionPatients with a first episode psychosis (FEP) have repeatedly been shown to have gray matter (GM) volume alterations. Some of these neuroanatomical abnormalities are already evident in the at-risk mental state (ARMS) for psychosis. Not only GM alterations but also neurocognitive impairments predate the onset of frank psychosis with verbal learning and memory (VLM) being among the most impaired domains. Yet, their interconnection with alterations in GM volumes remains ambiguous.ObjectiveTo evaluate associations of different subcortical GM volumes in the medial temporal lobe with VLM performance in ARMS and FEP patients.MethodsData were collected within the prospective Früherkennung von Psychosen (FePsy) study, which aims to improve the early detection of psychosis. VLM was assessed using the California Verbal Learning Test (CVLT) and its latent variables Attention Span (AS), Learning Efficiency (LE), Delayed Memory (DM) and Inaccurate Memory (IM). Structural images were acquired using a 3 Tesla magnetic resonance imaging scanner.ResultsData from 59 ARMS and 47 FEP patients were analysed. Structural equation models revealed significant associations between the amygdala and AS, LE and IM; thalamus and LE and IM; and the caudate, hippocampus and putamen with IM. However, none of these significant results withstood correction for multiple testing.ConclusionsAlthough VLM is among the most impaired cognitive domains in emerging psychosis, we could not find an association between low performance in this domain and reductions in subcortical GM volumes. Our results suggest that deficits in this domain may not stem from alterations in subcortical structures.Disclosure of interestThe authors have not supplied their declaration of competing interest.