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Psychosis risk prediction is one of the leading challenges in psychiatry. Previous investigations have suggested that plasma proteomic data may be useful in accurately predicting transition to psychosis in individuals at clinical high risk (CHR). We hypothesized that an a priori-specified proteomic prediction model would have strong predictive accuracy for psychosis risk and aimed to replicate longitudinal associations between plasma proteins and transition to psychosis. This study used plasma samples from participants in 3 CHR cohorts: the North American Prodrome Longitudinal Studies 2 and 3, and the NEURAPRO randomized control trial (total n  = 754). Plasma proteomic data were quantified using mass spectrometry. The primary outcome was transition to psychosis over the study follow-up period. Logistic regression models were internally validated, and optimism-corrected performance metrics derived with a bootstrap procedure. In the overall sample of CHR participants (age: 18.5, SD : 3.9; 51.9% male), 20.4% (n  = 154) developed psychosis within 4.4 years. The a priori-specified model showed poor risk-prediction accuracy for the development of psychosis (C -statistic: 0.51 [95% CI: 0.50, 0.59], calibration slope: 0.45). At a group level, Complement C8B, C4B, C5, and leucine-rich α-2 glycoprotein 1 (LRG1) were associated with transition to psychosis but did not surpass correction for multiple comparisons. This study did not confirm the findings from a previous proteomic prediction model of transition from CHR to psychosis. Certain complement proteins may be weakly associated with transition at a group level. Previous findings, derived from small samples, should be interpreted with caution. [ABSTRACT FROM AUTHOR]

Background and hypothesis Around 20% of people at clinical high risk (CHR) for psychosis later develop a psychotic disorder, but it is difficult to predict who this will be. We assessed the incidence of hearing speech (termed speech illusions [SIs]) in noise in CHR participants and examined whether this was associated with adverse clinical outcomes. Study design At baseline, 344 CHR participants and 67 healthy controls were presented with a computerized white noise task and asked whether they heard speech, and whether speech was neutral, affective, or whether they were uncertain about its valence. After 2 years, we assessed whether participants transitioned to psychosis, or remitted from the CHR state, and their functioning. Study results CHR participants had a lower sensitivity to the task. Logistic regression revealed that a bias towards hearing targets in stimuli was associated with remission status (OR = 0.21, P = 042). Conversely, hearing SIs with uncertain valence at baseline was associated with reduced likelihood of remission (OR = 7.72. P =.007). When we assessed only participants who did not take antipsychotic medication at baseline, the association between hearing SIs with uncertain valence at baseline and remission likelihood remained (OR = 7.61, P =.043) and this variable was additionally associated with a greater likelihood of transition to psychosis (OR = 5.34, P =.029). Conclusions In CHR individuals, a tendency to hear speech in noise, and uncertainty about the affective valence of this speech, is associated with adverse outcomes. This task could be used in a battery of cognitive markers to stratify CHR participants according to subsequent outcomes. [ABSTRACT FROM AUTHOR]

Background and hypothesis Although maintenance treatment with antipsychotics protects against psychotic relapse, high doses may hamper recovery. Therefore, dose reduction or discontinuation may be considered in patients with chronic schizophrenia. Here, we identified risk factors for psychotic relapse when doses are reduced. Study Design We systematically searched MEDLINE, EMBASE, and PsycINFO from January 1950 through January 2021 and reviewed randomized controlled trials (RCTs) that reported relapse rates after antipsychotic dose reduction or discontinuation in patients with chronic schizophrenia. We calculated relative risks (RRs) with 95% confidence intervals (CIs) per person-year and sought to identify potential risk factors for relapse. The study is registered with PROSPERO (CRD42017058296). Study Results Forty-seven RCTs (54 patient cohorts, 1746 person-years) were included. The RR for psychotic relapse with dose reduction/discontinuation versus maintenance treatment was 2.3 per person-year (95% CI: 1.9 to 2.8). The RR was higher with antipsychotic discontinuation, dose reduction to less than 3–5 mg haloperidol equivalent (HE), or relatively rapid dose reduction (<10 weeks). The RR was lower with long-acting injectable agents versus oral antipsychotic dose reduction. Other factors that increased the risk of psychotic relapse were younger age and short follow-up time. Conclusions Clinicians should take several risk factors for psychotic relapse into account when considering dose reduction in patients with chronic schizophrenia. Studies of a relatively fast reduction in antipsychotic dose support a minimum dose of 3–5 mg HE. However, if the dose is tapered more gradually, relapses related to medication withdrawal might be avoided, possibly enabling lower-end doses to be achieved. [ABSTRACT FROM AUTHOR]

Cluster studies identified a subgroup of patients with psychosis whose premorbid adjustment deteriorates before the onset, which may reflect variation in genetic influence. However, other studies reported a complex relationship between distinctive patterns of cannabis use and cognitive and premorbid impairment that is worthy of consideration. We examined whether: (1) premorbid social functioning (PSF) and premorbid academic functioning (PAF) in childhood and adolescence and current intellectual quotient (IQ) define different clusters in 802 first-episode of psychosis (FEP) patients; resulting clusters vary in (2) polygenic risk scores (PRSs) for schizophrenia (SCZ_PRS), bipolar disorder (BD_PRS), major depression (MD_PRS), and IQ (IQ_PRS), and (3) patterns of cannabis use, compared to 1,263 population-based controls. Four transdiagnostic clusters emerged (BIC = 2268.5): (1) high-cognitive-functioning (n  = 205), with the highest IQ (Mean = 106.1, 95% CI: 104.3, 107.9) and PAF, but low PSF. (2) Low-cognitive-functioning (n  = 223), with the lowest IQ (Mean = 73.9, 95% CI: 72.2, 75.7) and PAF, but normal PSF. (3) Intermediate (n  = 224) (Mean_IQ = 80.8, 95% CI: 79.1, 82.5) with low-improving PAF and PSF. 4) Deteriorating (n  = 150) (Mean_IQ = 80.6, 95% CI: 78.5, 82.7), with normal-deteriorating PAF and PSF. The PRSs explained 7.9% of between-group membership. FEP had higher SCZ_PRS than controls [ F (4,1319) = 20.4, P  < .001]. Among the clusters, the deteriorating group had lower SCZ_PRS and was likelier to have used high-potency cannabis daily. Patients with FEP clustered according to their premorbid and cognitive abilities. Pronounced premorbid deterioration was not typical of most FEP, including those more strongly predisposed to schizophrenia, but appeared in a cluster with a history of high-potency cannabis use. [ABSTRACT FROM AUTHOR]

Background and Hypothesis It is argued that availability of diagnostic models will facilitate a more rapid identification of individuals who are at a higher risk of first episode psychosis (FEP). Therefore, we developed, evaluated, and validated a diagnostic risk estimation model to classify individual with FEP and controls across six countries. Study Design We used data from a large multi-center study encompassing 2627 phenotypically well-defined participants (aged 18–64 years) recruited from six countries spanning 17 research sites, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions study. To build the diagnostic model and identify which of important factors for estimating an individual risk of FEP, we applied a binary logistic model with regularization by the least absolute shrinkage and selection operator. The model was validated employing the internal-external cross-validation approach. The model performance was assessed with the area under the receiver operating characteristic curve (AUROC), calibration, sensitivity, and specificity. Study Results Having included preselected 22 predictor variables, the model was able to discriminate adults with FEP and controls with high accuracy across all six countries (rangesAUROC = 0.84–0.86). Specificity (range = 73.9–78.0%) and sensitivity (range = 75.6–79.3%) were equally good, cumulatively indicating an excellent model accuracy; though, calibration slope for the diagnostic model showed a presence of some overfitting when applied specifically to participants from France, the UK, and The Netherlands. Conclusions The new FEP model achieved a good discrimination and good calibration across six countries with different ethnic contributions supporting its robustness and good generalizability. [ABSTRACT FROM AUTHOR]

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

Understanding longitudinal cognitive performance in individuals at ultra-high risk for psychosis (UHR) is important for informing theoretical models and treatment. A vital step in this endeavor is to determine whether there are UHR subgroups that have similar patterns of cognitive change over time. The aims were to: i) identify latent class trajectories of cognitive performance over 12-months in UHR individuals, ii) identify baseline demographic and clinical predictors of the resulting classes, and iii) determine whether trajectory classes were associated with transition to psychosis or functional outcomes. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia (BACS) at baseline, 6- and 12-months (N = 288). Using Growth Mixture Modeling, a single unimpaired improving trajectory class was observed for motor function, speed of processing, verbal fluency, and BACS composite. A two-class solution was observed for executive function and working memory, showing one unimpaired and a second impaired class. A three-class solution was found for verbal learning and memory: unimpaired, mildly impaired, and initially extremely impaired, but improved ("caught up") to the level of the mildly impaired. IQ, omega-3 index, and premorbid adjustment were associated with class membership, whereas clinical variables (symptoms, substance use), including transition to psychosis, were not. Working memory and verbal learning and memory trajectory class membership was associated with functioning outcomes. These findings suggest there is no short-term progressive cognitive decline in help-seeking UHR individuals, including those who transition to psychosis. Screening of cognitive performance may be useful for identifying UHR individuals who may benefit from targeted cognitive interventions. [ABSTRACT FROM AUTHOR]

Psychotic patients with a lifetime history of cannabis use generally show better cognitive functioning than other psychotic patients. Some authors suggest that cannabis-using patients may have been less cognitively impaired and less socially withdrawn in their premorbid life. Using a dataset comprising 948 patients with first-episode psychosis (FEP) and 1313 population controls across 6 countries, we examined the extent to which IQ and both early academic (Academic Factor [AF]) and social adjustment (Social Factor [SF]) are related to the lifetime frequency of cannabis use in both patients and controls. We expected a higher IQ and a better premorbid social adjustment in psychotic patients who had ever used cannabis compared to patients without any history of use. We did not expect such differences in controls. In both patients and controls, IQ was 3 points higher among occasional-users than in never-users (mean difference [Mdiff] = 2.9, 95% CI = [1.2, 4.7]). Both cases and control daily-users had lower AF compared to occasional (Mdiff = −0.3, 95% CI = [−0.5; −0.2]) and never-users (Mdiff = −0.4, 95% CI = [−0.6; −0.2]). Finally, patient occasional (Mdiff = 0.3, 95% CI = [0.1; 0.5]) and daily-users (Mdiff = 0.4, 95% CI = [0.2; 0.6]) had better SF than their never-using counterparts. This difference was not present in controls (F group*frequency(2, 2205) = 4.995, P =.007). Our findings suggest that the better premorbid social functioning of FEP with a history of cannabis use may have contributed to their likelihood to begin using cannabis, exposing them to its reported risk-increasing effects for Psychotic Disorders. [ABSTRACT FROM AUTHOR]

Background Individuals at clinical high risk (CHR) for psychosis have approximately a 25% chance of transitioning to psychosis in the first 2 years after first presentation to clinical services. A key aim in this field is to determine the risk of conversion for an individual meeting the criteria for CHR based on clinical, demographic and neuropsychological measures. An individualized risk calculator incorporating 8 risk factors based on these measures has recently been developed by the researchers from the North American Prodrome Longitudinal Study (NAPLS-2) and tested in their dataset of CHR participants. Methods We examined the risk factors from the NAPLS risk calculator in the EU-GEI (EU funded gene environment interaction) high risk study. The EU-GEI high risk study is a longitudinal multi-centre study including 9 sites in Europe, 1 site in Australia and 1 site in Brazil. At baseline, the study included 345 CHR individuals of which 65 later developed psychosis. The NAPLS risk calculator includes 8 risk factors and for each risk factor we attempted to harmonise the EU-GEI measures to the corresponding NAPLS measure. We used multivariate cox regression to determine the standardised hazard ratio for transition to psychosis for the 8 risk factors. To compare each of the NAPLS and EU-GEI hazard ratios we used a meta-analytical framework to calculate a combined hazard ratio and to examine heterogeneity between the effect sizes. Results In terms of the 8 risk factors, only the CAARMS unusual thought + non-bizarre ideas (corresponding to NAPLS SIPS P1+P2) was significantly associated with transition to psychosis, standardised hazard ratio = 1.51 (95%CI 1.01–2.23), p=0.046. Hazard ratios for the remaining risk factors varied from 0.73 to 1.41. The meta-analysis combining EU-GEI and NAPLS data did not indicate heterogeneity for any of the 8 measures, suggesting no systematic differences in the risk factors between the two studies. Discussion The test of the NAPLS risk factors in the independent EU-GEI high risk sample showed support for unusual thought content and non-bizarre ideas being predictive of later transition to psychosis. We were not able to replicate decline in functioning and lower scores in verbal learning memory as predictive of transition to psychosis as seen in the NAPLS study. However, our meta-analytical comparison showed no systematic differences in the hazard ratios for all 8 risk factors between both studies suggesting broad comparability between the samples. [ABSTRACT FROM AUTHOR]

Background The concept of a psychosis continuum implies that the same symptoms seen in patients with psychotic disorders can be measured in a healthy population. The assumption is that experiencing symptoms of psychosis such as delusions and hallucinations is not inevitably associated with the presence of the disorder. Surveys of unselected general population samples have consistently shown that a large number of individuals report experiences that strongly resemble the symptoms seen in psychotic patients. Only a fraction of these individuals met criteria for a clinical disorder such as schizophrenia. Alterations in the metabolic system in antipsychotic-naïve first-episode schizophrenia have been described, posing the question whether these metabolic markers are altered in persons with subclinical psychotic experiences as well. Methods We used cross-sectional data of 1890 participants of a prospective population-based cohort study, 'the Rotterdam Study (ERGO)'. The ages ranged from 45 to 54 years and the participants filled in a self-report questionnaire, 'The Community Assessment of Psychic Experience'. To assess subclinical psychotic symptoms, the frequency and distress ratings of the positive symptom dimension from this questionnaire were used. These items were offset against metabolic measured parameters. The metabolic parameters used were body-mass index (BMI; body weight in kg/m2), fasting glucose levels, low-density lipoproteins (LDL), high-density lipoproteins (HDL), triglycerides and cholesterol. Linear regression analyses were used with adjustment for age, gender, ethnicity, education level, employment status and marital status. The influences of psychopharmacology use, anxiety disorder, depressive symptoms and use of lipid reducing agents on the subclinical psychotic symptoms were analysed in sensitivity analyses. Results We observed a strong positive association between BMI and the frequency of subpsychotic symptoms, and also with the perceived distress of these subpsychotic symptoms. In participants with a BMI ≥ 30 we observed an even stronger association with the frequency score and distress rating of subpsychotic symptoms. In a restricted sample to non-lipid reducing agent users only, we observed that LDL is negatively associated with the frequency of subpsychotic symptoms and perceived distress of these subpsychotic symptoms. For HDL, we observed a negative association with only the frequency of subpsychotic symptoms. The other metabolic markers, total cholesterol, triglycerides and fasting glucose, did not show any significant associations with subpsychotic symptoms. The use of psychopharmaceuticals, the presence of an anxiety disorder or experiencing depressive symptoms did not alter our results. Discussion In this study of a large community sample we found that increased BMI and metabolic dysfunctions are associated with subclinical psychotic experiences. Our findings add to the evidence that psychotic phenomena are related to alterations in the metabolism and obesity even without antipsychotic medication use. Noticeably, this association seems also to hold for subclinical psychotic phenomena, present in the normal population. [ABSTRACT FROM AUTHOR]