Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach

Diagnostic heterogeneity within and across psychotic and affective disorders challenges accurate treatment selection, particularly in the early stages. Delineation of shared and distinct illness features at the phenotypic and brain levels may inform the development of more precise differential diagnostic tools. We aimed to identify prototypes of depression and psychosis to investigate their heterogeneity, with common, comorbid transdiagnostic symptoms. Analyzing clinical/neurocognitive and grey matter volume (GMV) data from the PRONIA database, we generated prototypic models of recent-onset depression (ROD) vs. recent-onset psychosis (ROP) by training support-vector machines to separate patients with ROD from patients with ROP, who were selected for absent comorbid features (pure groups). Then, models were applied to patients with comorbidity, ie, ROP with depressive symptoms (ROP+D) and ROD participants with sub-threshold psychosis-like features (ROD+P), to measure their positions within the affective-psychotic continuum. All models were independently validated in a replication sample. Comorbid patients were positioned between pure groups, with ROP+D patients being more frequently classified as ROD compared to pure ROP patients (clinical/neurocognitive model: χ2 = 14.874; P < .001; GMV model: χ2 = 4.933; P = .026). ROD+P patient classification did not differ from ROD (clinical/neurocognitive model: χ2 = 1.956; P = 0.162; GMV model: χ2 = 0.005; P = .943). Clinical/neurocognitive and neuroanatomical models demonstrated separability of prototypic depression from psychosis. The shift of comorbid patients toward the depression prototype, observed at the clinical and biological levels, suggests that psychosis with affective comorbidity aligns more strongly to depressive rather than psychotic disease processes. Future studies should assess how these quantitative measures of comorbidity predict outcomes and individual responses to stratified therapeutic interventions.

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and 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.

Development and Validation of a Nonremission Risk Prediction Model in First-Episode Psychosis: An Analysis of 2 Longitudinal Studies

Psychosis is a major mental illness with first onset in young adults. The prognosis is poor in around half of the people affected, and difficult to predict. The few tools available to predict prognosis have major weaknesses which limit their use in clinical practice. We aimed to develop and validate a risk prediction model of symptom nonremission in first-episode psychosis. Our development cohort consisted of 1027 patients with first-episode psychosis recruited between 2005 and 2010 from 14 early intervention services across the National Health Service in England. Our validation cohort consisted of 399 patients with first-episode psychosis recruited between 2006 and 2009 from a further 11 English early intervention services. The one-year nonremission rate was 52% and 54% in the development and validation cohorts, respectively. Multivariable logistic regression was used to develop a risk prediction model for nonremission, which was externally validated. The prediction model showed good discrimination C-statistic of 0.73 (0.71, 0.75) and adequate calibration with intercept alpha of 0.12 (0.02, 0.22) and slope beta of 0.98 (0.85, 1.11). Our model improved the net-benefit by 15% at a risk threshold of 50% compared to the strategy of treating all, equivalent to 15 more detected nonremitted first-episode psychosis individuals per 100 without incorrectly classifying remitted cases. Once prospectively validated, our first episode psychosis prediction model could help identify patients at increased risk of nonremission at initial clinical contact.

Research priorities for neuroimmunology: identifying the key research questions to be addressed by 2030

Neuroimmunology in the broadest sense is the study of interactions between the nervous and the immune systems. These interactions play important roles in health from supporting neural development, homeostasis and plasticity to modifying behaviour. Neuroimmunology is increasingly recognised as a field with the potential to deliver a significant positive impact on human health and treatment for neurological and psychiatric disorders. Yet, translation to the clinic is hindered by fundamental knowledge gaps on the underlying mechanisms of action or the optimal timing of an intervention, and a lack of appropriate tools to visualise and modulate both systems. Here we propose ten key disease-agnostic research questions that, if addressed, could lead to significant progress within neuroimmunology in the short to medium term. We also discuss four cross-cutting themes to be considered when addressing each question: i) bi-directionality of neuroimmune interactions; ii) the biological context in which the questions are addressed (e.g. health vs disease vs across the lifespan); iii) tools and technologies required to fully answer the questions; and iv) translation into the clinic. We acknowledge that these ten questions cannot represent the full breadth of gaps in our understanding; rather they focus on areas which, if addressed, may have the most broad and immediate impacts. By defining these neuroimmunology priorities, we hope to unite existing and future research teams, who can make meaningful progress through a collaborative and cross-disciplinary effort.

General psychopathology links burden of recent life events and psychotic symptoms in a network approach

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.

Traces of Trauma: A Multivariate Pattern Analysis of Childhood Trauma, Brain Structure, and Clinical Phenotypes

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.

Evidence in cortical folding patterns for prenatal predispositions to hallucinations in schizophrenia

All perception is a construction of the brain from sensory input. Our first perceptions begin during gestation, making fetal brain development fundamental to how we experience a diverse world. Hallucinations are percepts without origin in physical reality that occur in health and disease. Despite longstanding research on the brain structures supporting hallucinations and on perinatal contributions to the pathophysiology of schizophrenia, what links these two distinct lines of research remains unclear. Sulcal patterns derived from structural magnetic resonance (MR) images can provide a proxy in adulthood for early brain development. We studied two independent datasets of patients with schizophrenia who underwent clinical assessment and 3T MR imaging from the United Kingdom and Shanghai, China (n = 181 combined) and 63 healthy controls from Shanghai. Participants were stratified into those with (n = 79 UK; n = 22 Shanghai) and without (n = 43 UK; n = 37 Shanghai) hallucinations from the PANSS P3 scores for hallucinatory behaviour. We quantified the length, depth, and asymmetry indices of the paracingulate and superior temporal sulci (PCS, STS), which have previously been associated with hallucinations in schizophrenia, and constructed cortical folding covariance matrices organized by large-scale functional networks. In both ethnic groups, we demonstrated a significantly shorter left PCS in patients with hallucinations compared to those without, and to healthy controls. Reduced PCS length and STS depth corresponded to focal deviations in their geometry and to significantly increased covariance within and between areas of the salience and auditory networks. The discovery of neurodevelopmental alterations contributing to hallucinations establishes testable models for these enigmatic, sometimes highly distressing, perceptions and provides mechanistic insight into the pathological consequences of prenatal origins.

Blunted affect and suicide in schizophrenia: A systematic review

Individual negative symptoms have rarely been examined with regard to their relationship with suicide in schizophrenia, which continues to affect up to 13% of people with the disorder. Symptoms such as blunted affect, which can be an enduring hallmark of schizophrenia, may impact suicide through increasing isolation, leading to poor functional recovery and diminished quality of life. A systematic review following PRISMA guidelines and pre-registered on PROSPERO (CRD4219143373) was conducted; EMBASE, PsychInfo, and MedLine were searched until January 2020. Eight hundred and fifty-six articles were identified from the databases and 2 papers were identified from other resources. Twelve papers met inclusion criteria for the review. Nine out of twelve papers report a positive direct or indirect association between blunted affect and suicide in schizophrenia and three papers showed no association. The majority of included studies suggest that blunted affect may be indirectly related to suicide through risk factors such as emotional withdrawal, depressive symptoms, hopelessness, low self-esteem and negative evaluation. Future studies should include assessment of blunted affect as a potential mediator in the generation of suicidal behaviour in patients with such factors.

Prevalence of treatment resistance and clozapine use in early intervention services

BACKGROUND

Treatment resistance causes significant burden in psychosis. Clozapine is the only evidence-based pharmacologic intervention available for people with treatment-resistant schizophrenia; current guidelines recommend commencement after two unsuccessful trials of standard antipsychotics.

AIMS

This paper aims to explore the prevalence of treatment resistance and pathways to commencement of clozapine in UK early intervention in psychosis (EIP) services.

METHOD

Data were taken from the National Evaluation of the Development and Impact of Early Intervention Services study (N = 1027) and included demographics, medication history and psychosis symptoms measured by the Positive and Negative Syndrome Scale (PANSS) at baseline, 6 months and 12 months. Prescribing patterns and pathways to clozapine were examined. We adopted a strict criterion for treatment resistance, defined as persistent elevated positive symptoms (a PANSS positive score ≥16, equating to at least two items of at least moderate severity), across three time points.

RESULTS

A total of 143 (18.1%) participants met the definition of treatment resistance of having continuous positive symptoms over 12 months, despite treatment in EIP services. Sixty-one (7.7%) participants were treatment resistant and eligible for clozapine, having had two trials of standard antipsychotics; however, only 25 (2.4%) were prescribed clozapine over the 12-month study period. Treatment-resistant participants were more likely to be prescribed additional antipsychotic medication and polypharmacy, instead of clozapine.

CONCLUSIONS

Prevalent treatment resistance was observed in UK EIP services, but prescription of polypharmacy was much more common than clozapine. Significant delays in the commencement of clozapine may reflect a missed opportunity to promote recovery in this critical period.

Influences on the use of antidepressants in primary care: All England general practice-level analysis of demographic, practice-level and prescriber factors

INTRODUCTION

General practice (GP) antidepressants (ADs) prescribing in England has almost doubled in the past decade: how does location, GP characteristics, and prescribing selection influence antidepressant prescribing rate (ADPR) and growth.

METHODS

Stepwise multivariate regression analysis was applied to national public relevant data for each general practice to establish associations between these factors and ADPR. The regression coefficient was applied to the actual change in the number of different ADs and costs/dose to extrapolate the impact of these on growth.

RESULTS

In 2017-2018, 2.1 billion doses of antidepressant were prescribed into a population of 52 million people in 6,146 larger practices. In the model, location demographics accounted for 62% of the variation in ADPR: including practice size and health raised this to 71%, and local prescribing behaviour to 80%. Practices using more different drugs and lower-cost/dose had higher ADPR. Extrapolation showed that 40% of growth in ADPR could be attributed to the historic changes in these factors.

CONCLUSIONS

While practice location factors do impact on AD prescription rates, local long-term physical health condition prevalence and prescribing behaviours are almost as important. We hope that our findings can provide insights that are helpful to local clinical behaviour and medicines management.

Cardiometabolic risk prediction algorithms for young people with psychosis: a systematic review and exploratory analysis

OBJECTIVE

Cardiometabolic risk prediction algorithms are common in clinical practice. Young people with psychosis are at high risk for developing cardiometabolic disorders. We aimed to examine whether existing cardiometabolic risk prediction algorithms are suitable for young people with psychosis.

METHODS

We conducted a systematic review and narrative synthesis of studies reporting the development and validation of cardiometabolic risk prediction algorithms for general or psychiatric populations. Furthermore, we used data from 505 participants with or at risk of psychosis at age 18 years in the ALSPAC birth cohort, to explore the performance of three algorithms (QDiabetes, QRISK3 and PRIMROSE) highlighted as potentially suitable. We repeated analyses after artificially increasing participant age to the mean age of the original algorithm studies to examine the impact of age on predictive performance.

RESULTS

We screened 7820 results, including 110 studies. All algorithms were developed in relatively older participants, and most were at high risk of bias. Three studies (QDiabetes, QRISK3 and PRIMROSE) featured psychiatric predictors. Age was more strongly weighted than other risk factors in each algorithm. In our exploratory analysis, calibration plots for all three algorithms implied a consistent systematic underprediction of cardiometabolic risk in the younger sample. After increasing participant age, calibration plots were markedly improved.

CONCLUSION

Existing cardiometabolic risk prediction algorithms cannot be recommended for young people with or at risk of psychosis. Existing algorithms may underpredict risk in young people, even in the face of other high-risk features. Recalibration of existing algorithms or a new tailored algorithm for the population is required.

The management of depression following traumatic brain injury: A systematic review with meta-analysis

BACKGROUND

Traumatic brain injury (TBI) is prevalent. Declining mortality has led to increasing survivors with chronic sequalae, including depression. With a lack of guidelines, this review aims to provide a comprehensive, evidence-based summary of the management of depression following TBI.

METHODS

Systematic searches were conducted for quasi-experimental and randomized controlled trials (RCTs) assessing pharmacotherapy, psychological interventions, and transcranial magnetic stimulation (TMS). Databases searched CENTRAL, Medline, Embase, CINAHL, PsycINFO, Web of Science, and ProQuest dissertations. Data extraction and risk-of-bias tools were used. Where possible, outcomes were combined into meta-analyses.

RESULTS

2719 studies were identified. After abstract screening and full-text reading, 34 remained. Prophylactic sertraline significantly reduced the odds of depression (OR (odds ratio) = 0.31 [95%CI (confidence interval) = 0.12 to 0.82]). Meta-analysis of RCT's showed TMS to have the greatest reduction in depression severity (SMD (Standardized-Mean-Difference) = 2.43 [95%CI = 1.24 to 3.61]). Stimulants were the only treatment superior to control (SMD = -1.03 [95%CI = - 1.6 to -0.47]).

CONCLUSION

Methylphenidate was the most effective pharmacotherapy. Sertraline appears effective for prevention. The efficacy of psychological interventions is unclear. TMS as a combination therapy appears promising. Heterogeneity of study populations and dearth of evidence means results should be interpreted cautiously.

Effect of age on the relative efficacy of clozapine in schizophrenia

OBJECTIVE

Early treatment of schizophrenia improves outcomes. Clozapine appears to have unique benefit when other antipsychotic medication has failed. This systematic review and meta-analysis aims to assess clozapine's superiority over alternative antipsychotic medication and examine whether earlier use is associated with additional benefit.

METHOD

Systematic retrieval of blinded, randomized controlled trials comparing clozapine with alternative antipsychotics in adults with schizophrenia. The effect of mean age on relative clozapine response was examined using random effects meta-regression, and multiple linear regression on available patient data.

RESULTS

A total of 276 studies were retrieved. Thirty-four studies were included in the meta-analysis. Clozapine was significantly more effective than alternative antipsychotics in reducing psychotic symptoms and increasing response. However, meta-regression failed to show a more significant effect in younger patients (age on effect size (total psychotic symptoms) 0.00, P = 0.79 CI -0.03 to 0.03). Individual patient data were available for two studies, the larger of which showed a significant interaction between younger age and superiority of clozapine.

CONCLUSION

The results support clozapine's superiority over other antipsychotics. A convincing effect of age on this effect was not demonstrated, although this was suggested in one study. In view of the age of many of the included studies, and changes in reporting practice over time, new clozapine RCTs, which include age of illness onset as well as age at trial time, would be welcome in order to provide meta-analysable data for future use.

19 Pro-inflammatory cytokines and childhood trauma in young people with emerging mental health difficulties

Objectives/aims

Elevated levels of pro-inflammatory cytokines are associated with a range of mental illnesses, and also with childhood trauma.1–4 Evidence suggests that inflammation occurring as a result of childhood trauma could play a role in the pathogenesis of psychiatric disorders.5 6 However, previous research does not account for confounders, including psychotropic medication and illness duration, that may affect inflammation levels.7 The aim of this study was to investigate the relationship between childhood trauma exposure and levels of inflammation in young people with emerging mental health disorders with confounding factors removed.

Methods

10 patients, aged 16–25, with a range of psychiatric disorders and no history of psychotropic medication were recruited from Birmingham mental health services, along with 16 healthy controls. Childhood trauma exposure was assessed with the Childhood Trauma Questionnaire (CTQ), and blood samples were analysed for serum concentrations of pro- inflammatory cytokines IL-6 and IL-1β.

Results

There was no significant difference in serum cytokines between patients and healthy controls, or those with and without childhood trauma (p>0.05). Post-hoc sample size calculations estimated 197 patients with and 197 without childhood trauma would be needed to detect a significant 2 pg/ml difference in cytokine levels (80% power, 5% significance). There was a weak positive, but non-significant, correlation between both cytokines and CTQ score in the patient group (rS=0.1–0.3, p>0.05). Multiple linear regression of CTQ score, sex and BMI found that none of these variables significantly predicted cytokine concentration in our population.

Conclusions

There is preliminary evidence of an association between childhood trauma and inflammation in patients with mental illness, but due to small sample size no definitive conclusions can be drawn from this data. Future research with a larger sample size and longitudinal approach would be beneficial in establishing whether a relationship exists independent of confounders.

References

Goldsmith DR, Rapaport MH, Miller BJ. A meta-analysis of blood cytokine network alterations in psychiatric patients: comparisons between schizophrenia, bipolar disorder and depression. Mol Psychiatr. 2016; 21: 1696–1709.

Upthegrove R, Manzanares-Teson N, Barnes NM. Cytokine function in medication-naive first episode psychosis: a systematic review and meta-analysis. Schizophr. Res 2014; 155: 101–108.

Baumeister D, Akhtar R, Ciufolini S, Pariante CM, Mondelli V. Childhood trauma and adulthood inflammation: a meta-analysis of peripheral C-reactive protein, interleukin-6 and tumour necrosis factor-α. Mol Psychiatr 2016; 21: 642–649.

Danese A, Baldwin JR. Hidden wounds? Inflammatory links between childhood trauma and psychopathology. Annu Rev of Psychol 2017; 68: 517–544.

Upthegrove R, Barnes NM. The immune system and schizophrenia: an update for clinicians. BJPsych Adv 2014; 20: 83–91.

Miller AH, Maletic V, Raison CL. Inflammation and its discontents: the role of cytokines in the pathophysiology of major depression. Biol Psychiat 2009: 65; 732–741.

Danese A, Pariante CM, Caspi A, Taylor A, Poulton R. Childhood maltreatment predicts adult inflammation in a life-course study. P Natl Acad Sci USA 2007;104:1319–1324.

Exercise as a protective mechanism against the negative effects of oxidative stress in first-episode psychosis: a biomarker-led study

First-episode psychosis (FEP) is a psychiatric disorder, characterised by positive and negative symptoms, usually emerging during adolescence and early adulthood. FEP represents an early intervention opportunity for intervention in psychosis. Redox disturbance and subsequent oxidative stress have been linked to the pathophysiology of FEP. Exercise training can perturb oxidative stress and rebalance the antioxidant system and thus represents an intervention with the potential to interact with a mechanism of disease. The aim of this study was to assess the effect of exercise on markers of redox status in FEP. Twenty-two young men were recruited from Birmingham Early Intervention services and randomised to either a 12-week exercise programme or treatment as usual (control). Measures of blood and brain glutathione (GSH), markers of oxidative damage, inflammation, neuronal health, symptomology and habitual physical activity were assessed. Exercise training was protective against changes related to continued psychosis. Symptomatically, those in the exercise group showed reductions in positive and general psychopathology, and stable negative symptoms (compared to increased negative symptoms in the control group). Peripheral GSH was increased by 5.6% in the exercise group, compared to a significant decrease (24.4%) (p = 0.04) in the control group. Exercise attenuated negative changes in markers of neuronal function (brain-derived neurotrophic factor), lipid damage (thiobarbituric acid-reactive substances) and total antioxidant capacity. C-reactive protein and tumour necrosis factor-α also decreased in the exercise group, although protein and DNA oxidation were unchanged. Moderate-intensity exercise training has the ability to elicit changes in markers of oxidative stress and antioxidant concentration, with subsequent improvements in symptoms of psychosis.

The Psychopathology and Neuroanatomical Markers of Depression in Early Psychosis

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.

Role of magnetic resonance spectroscopy in cerebral glutathione quantification for youth mental health: A systematic review

AIM

Oxidative stress is strongly implicated in many psychiatric disorders, which has resulted in the development of new interventions to attempt to perturb this pathology. A great deal of attention has been paid to glutathione, which is the brain's dominant antioxidant and plays a fundamental role in removing free radicals and other reactive oxygen species. Measurement of glutathione concentration in the brain in vivo can provide information on redox status and potential for oxidative stress to develop. Glutathione might also represent a marker to assess treatment response.

METHODS

This paper systematically reviews studies that assess glutathione concentration (measured using magnetic resonance spectroscopy) in various mental health conditions.

RESULTS

There is limited evidence showing altered brain glutathione concentration in mental disorders; the best evidence suggests glutathione is decreased in depression, but is not altered in bipolar disorder. The review then outlines the various methodological options for acquiring glutathione data using spectroscopy.

CONCLUSIONS

Analysis of the minimum effect size measurable in existing studies indicates that increased number of participants is required to measure subtle but possibly important differences and move the field forward.

Depressive symptoms during first episode psychosis and functional outcome: A systematic review and meta-analysis

OBJECTIVES

First episode psychosis (FEP) is associated with functional decline. Existing evidence was synthesised to explore the influence of depressive symptoms during FEP on future social, occupational and global functioning.

METHODS

Medline, Embase, PsychINFO, Cochrane Library, Open Grey, NICE Evidence and Web of Science were searched from inception to May 2018. Longitudinal studies of FEP patients were included. Study quality was assessed using the Downs and Black instrument. Two meta-analyses were performed using random effect models. The first meta-analysis correlates depressive symptoms during FEP with follow-up Global Assessment of Functioning (GAF) scores. The second meta-analysis shows the odds of long-term functional remission if depressive symptoms are present during FEP.

RESULTS

4751 unique abstracts were found. 36 articles were included. The first meta-analysis included 7 studies (932 participants) and showed depressive symptoms during FEP were negatively correlated with follow-up GAF scores (r = -0.16, 95% CI: -0.24 to -0.09, p < 0.001). The second meta-analysis of 9 studies (2265 participants) showed weak evidence of an association between the presence of depressive symptoms in FEP and reduction in functional remission (OR = 0.87, 95% CI: 0.68 to 1.13, p = 0.294).

CONCLUSION

Depressive symptoms during FEP are associated with poorer long-term global functioning and may be associated with a reduced chance of achieving functional remission. Clinical trials are needed to identify efficacious management of depressive symptoms in early psychosis.

Insulin resistance and obesity, and their association with depression in relatively young people: findings from a large UK birth cohort

BACKGROUND

Depression frequently co-occurs with disorders of glucose and insulin homeostasis (DGIH) and obesity. Low-grade systemic inflammation and lifestyle factors in childhood may predispose to DGIH, obesity and depression. We aim to investigate the cross-sectional and longitudinal associations among DGIH, obesity and depression, and to examine the effect of demographics, lifestyle factors and antecedent low-grade inflammation on such associations in young people.

METHODS

Using the Avon Longitudinal Study of Parents and Children birth cohort, we used regression analyses to examine: (1) cross-sectional and (2) longitudinal associations between measures of DGIH [insulin resistance (IR); impaired glucose tolerance] and body mass index (BMI) at ages 9 and 18 years, and depression (depressive symptoms and depressive episode) at age 18 years and (3) whether sociodemographics, lifestyle factors or inflammation [interleukin-6 (IL-6) at age 9 years] confounded any such associations.

RESULTS

We included 3208 participants. At age 18 years, IR and BMI were positively associated with depression. These associations may be explained by sociodemographic and lifestyle factors. There were no longitudinal associations between DGIH/BMI and depression, and adjustment for IL-6 and C-reactive protein did not attenuate associations between IR/BMI and depression; however, the longitudinal analyses may have been underpowered.

CONCLUSIONS

Young people with depression show evidence of DGIH and raised BMI, which may be related to sociodemographic and lifestyle effects such as deprivation, smoking, ethnicity and gender. In future, studies with larger samples are required to confirm this. Preventative strategies for the poorer physical health outcomes associated with depression should focus on malleable lifestyle factors.

Designing a feasible exercise intervention in first-episode psychosis: Exercise quality, engagement and effect

First-episode psychosis (FEP) is the first presentation of a psychotic disorder that usually propagates during early adulthood. FEP represents an important early intervention point to attenuate the metabolic risks associated with psychosis and its treatment. Exercise has potential to improve metabolic and functional outcome, but engaging this population in regular exercise is typically difficult. Promoting enjoyment and attendance may improve participation. 22 men with FEP were randomised to a 12-week intervention of exercise training, or treatment as usual. Exercise was pre-standardised based on measures of heart rate to assess intensity. Symptoms of psychosis were assessed, alongside measures of quality of life, disability and habitual activity. The study observed 83% attendance at exercise sessions, with target intensity attained. There were clinically meaningful decreases in PANSS positive (17.31%) and general psychopathology (10.98%) scores and exercise was protective of negative score increase observed in the control group (13.89%). Assessment of disability declined after training (12.65%) compared with a 20.78% increase in controls. This study demonstrated that engagement of FEP patients in an intervention of high quality exercise was possible. Positive changes in psychopathology scores and disability show that the benefits of regular exercise are achievable with a potential positive impact on clinical presentation.

Basic Symptoms Are Associated With Age in Patients With a Clinical High-Risk State for Psychosis: Results From the PRONIA Study

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

Evidence-based guidelines for the pharmacological treatment of schizophrenia: Updated recommendations from the British Association for Psychopharmacology

These updated guidelines from the British Association for Psychopharmacology replace the original version published in 2011. They address the scope and targets of pharmacological treatment for schizophrenia. A consensus meeting was held in 2017, involving experts in schizophrenia and its treatment. They were asked to review key areas and consider the strength of the evidence on the risk-benefit balance of pharmacological interventions and the clinical implications, with an emphasis on meta-analyses, systematic reviews and randomised controlled trials where available, plus updates on current clinical practice. The guidelines cover the pharmacological management and treatment of schizophrenia across the various stages of the illness, including first-episode, relapse prevention, and illness that has proved refractory to standard treatment. It is hoped that the practice recommendations presented will support clinical decision making for practitioners, serve as a source of information for patients and carers, and inform quality improvement.

Instrumental rationality and suicide in schizophrenia: a case for rational suicide?

It is estimated that up to 7500 people develop schizophrenia each year in the UK. Schizophrenia has significant consequences, with 28% of the excess mortality in schizophrenia being attributed to suicide. Previous research suggests that suicide in schizophrenia may be more related to affective factors such as depression and hopelessness, rather than psychotic symptoms themselves. Considering suicide in schizophrenia within this framework enables us to develop a novel philosophical approach, in which suicide may not be related to loss of self-consciousness, thought processing dysfunctions or perception disturbances. The action of suicide may be due neither to persistent hallucinations nor other psychotic symptoms, such as delusional beliefs, but to other underexamined, perhaps rational reasons, such as extreme social isolation, severe depression or emotional withdrawal. This paper does not examine the moral character of suicide. Instead, it argues that we should conceive the action of suicide in schizophrenia as an act that is not necessarily irrational. People with schizophrenia might end their life based on reasons if suicide is the best means to achieve their ends. However, the paper does not support assisted suicide. It aims to provide a better understanding of the reasons why people take their own lives and suggests that understanding can inform effective interventions to reduce high rates of suicide.

A cross-sectional examination of the clinical significance of autistic traits in individuals experiencing a first episode of psychosis

Autism traits are found at elevated rates in individuals with schizophrenia spectrum disorders, however, there is a lack of evidence regarding potential clinical impact. The current research aimed to examine potential associations between autism traits and symptoms of psychosis, social and role functioning, and quality of life. 99 individuals experiencing a first episode of psychosis took part in a cross-sectional interview and self-report questionnaire which assessed current symptoms of psychosis, autism traits, functioning, and quality of life. Participants were found to have a high level of autism traits. Higher autism traits were associated with poorer quality of life, functioning, and current psychotic symptoms. Receiver operating characteristic curve (ROC) analyses indicated that optimal AQ cut-off scores to predict severity of psychosis symptoms, functioning, and quality of life were lower than those used to suggest likely autism-spectrum diagnosis. Results suggest that autism traits are associated with poorer clinical presentation in first-episode psychosis populations, even in those whose traits fall below potentially diagnostic thresholds for autism. Psychosis services should be prepared to adequately address the needs of individuals with higher autism traits.

Development and validation of multivariable prediction models of remission, recovery, and quality of life outcomes in people with first episode psychosis: a machine learning approach

BACKGROUND

Outcomes for people with first-episode psychosis are highly heterogeneous. Few reliable validated methods are available to predict the outcome for individual patients in the first clinical contact. In this study, we aimed to build multivariable prediction models of 1-year remission and recovery outcomes using baseline clinical variables in people with first-episode psychosis.

METHODS

In this machine learning approach, we applied supervised machine learning, using regularised regression and nested leave-one-site-out cross-validation, to baseline clinical data from the English Evaluating the Development and Impact of Early Intervention Services (EDEN) study (n=1027), to develop and internally validate prediction models at 1-year follow-up. We assessed four binary outcomes that were recorded at 1 year: symptom remission, social recovery, vocational recovery, and quality of life (QoL). We externally validated the prediction models by selecting from the top predictor variables identified in the internal validation models the variables shared with the external validation datasets comprised of two Scottish longitudinal cohort studies (n=162) and the OPUS trial, a randomised controlled trial of specialised assertive intervention versus standard treatment (n=578).

FINDINGS

The performance of prediction models was robust for the four 1-year outcomes of symptom remission (area under the receiver operating characteristic curve [AUC] 0·703, 95% CI 0·664-0·742), social recovery (0·731, 0·697-0·765), vocational recovery (0·736, 0·702-0·771), and QoL (0·704, 0·667-0·742; p<0·0001 for all outcomes), on internal validation. We externally validated the outcomes of symptom remission (AUC 0·680, 95% CI 0·587-0·773), vocational recovery (0·867, 0·805-0·930), and QoL (0·679, 0·522-0·836) in the Scottish datasets, and symptom remission (0·616, 0·553-0·679), social recovery (0·573, 0·504-0·643), vocational recovery (0·660, 0·610-0·710), and QoL (0·556, 0·481-0·631) in the OPUS dataset.

INTERPRETATION

In our machine learning analysis, we showed that prediction models can reliably and prospectively identify poor remission and recovery outcomes at 1 year for patients with first-episode psychosis using baseline clinical variables at first clinical contact.

FUNDING

Lundbeck Foundation.