Anhedonia as a potential transdiagnostic phenotype with immune-related changes in recent onset mental health disorders.

BACKGROUND: Chronic low-grade inflammation is observed across mental disorders and is associated with difficult-to-treat-symptoms of anhedonia and functional brain changes - reflecting a potential transdiagnostic dimension. Previous investigations have focused on distinct illness categories in those with enduring illness, with few exploring inflammatory changes. We sought to identify an inflammatory signal and associated brain function underlying anhedonia among young people with recent onset psychosis (ROP) and recent onset depression (ROD). METHOD: Resting-state functional magnetic resonance imaging, inflammatory markers, and anhedonia symptoms were collected from N=108 (M age=26.2[SD 6.2]years; Female =50) participants with ROP (n=53) and ROD (n=55) from the EU-FP7-funded PRONIA study. Time-series were extracted using the Schaefer atlas, defining 100 cortical regions of interest. Using advanced multimodal machine learning, an inflammatory marker model and functional connectivity model were developed to classify an anhedonic group, compared to a normal hedonic group. RESULTS: A repeated nested cross-validation model using inflammatory markers classified normal hedonic and anhedonic ROP/ROD groups with a balanced accuracy (BAC) of 63.9%, and an area under the curve (AUC) of 0.61. The functional connectivity model produced a BAC of 55.2% and an AUC of 0.57. Anhedonic group assignment was driven by higher levels of Interleukin-6, S100B, and Interleukin-1 receptor antagonist, and lower levels of Interferon gamma, in addition to connectivity within the precuneus and posterior cingulate. CONCLUSION: We identified a potential transdiagnostic anhedonic subtype that was accounted for by an inflammatory profile and functional connectivity. Results have implications for anhedonia as an emerging transdiagnostic target across emerging mental disorders.

Implementing and Evaluating a National Integrated Digital Registry and Clinical Decision Support System in Early Intervention in Psychosis Services (Early Psychosis Informatics Into Care): Co-Designed Protocol.

BACKGROUND: Early intervention in psychosis (EIP) services are nationally mandated in England to provide multidisciplinary care to people experiencing first-episode psychosis, which disproportionately affects deprived and ethnic minority youth. Quality of service provision varies by region, and people from historically underserved populations have unequal access. In other disease areas, including stroke and dementia, national digital registries coupled with clinical decision support systems (CDSSs) have revolutionized the delivery of equitable, evidence-based interventions to transform patient outcomes and reduce population-level disparities in care. Given psychosis is ranked the third most burdensome mental health condition by the World Health Organization, it is essential that we achieve the same parity of health improvements. OBJECTIVE: This paper reports the protocol for the program development phase of this study, in which we aimed to co-design and produce an evidence-based, stakeholder-informed framework for the building, implementation, piloting, and evaluation of a national integrated digital registry and CDSS for psychosis, known as EPICare (Early Psychosis Informatics into Care). METHODS: We conducted 3 concurrent work packages, with reciprocal knowledge exchange between each. In work package 1, using a participatory co-design framework, key stakeholders (clinicians, academics, policy makers, and patient and public contributors) engaged in 4 workshops to review, refine, and identify a core set of essential and desirable measures and features of the EPICare registry and CDSS. Using a modified Delphi approach, we then developed a consensus of data priorities. In work package 2, we collaborated with National Health Service (NHS) informatics teams to identify relevant data currently captured in electronic health records, understand data retrieval methods, and design the software architecture and data model to inform future implementation. In work package 3, observations of stakeholder workshops and individual interviews with representative stakeholders (n=10) were subject to interpretative qualitative analysis, guided by normalization process theory, to identify factors likely to influence the adoption and implementation of EPICare into routine practice. RESULTS: Stage 1 of the EPICare study took place between December 2021 and September 2022. The next steps include stage 2 building, piloting, implementation, and evaluation of EPICare in 5 demonstrator NHS Trusts serving underserved and diverse populations with substantial need for EIP care in England. If successful, this will be followed by stage 3, in which we will seek NHS adoption of EPICare for rollout to all EIP services in England. CONCLUSIONS: By establishing a multistakeholder network and engaging them in an iterative co-design process, we have identified essential and desirable elements of the EPICare registry and CDSS; proactively identified and minimized potential challenges and barriers to uptake and implementation; and addressed key questions related to informatics architecture, infrastructure, governance, and integration in diverse NHS Trusts, enabling us to proceed with the building, piloting, implementation, and evaluation of EPICare. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50177.

Experience-based Investigation and Co-design of Psychosis Centred Integrated Care Services for Ethnically Diverse People with Multimorbidity (CoPICS): study protocol.

INTRODUCTION: Ethnic minorities (also called racialised groups) are more likely to experience severe mental illness (SMI). People with SMI are more likely to experience multimorbidity (MM), making psychosis among racialised groups more likely to lead to MM, poor outcomes, disability and premature mortality. METHODS AND ANALYSIS: This National Institute for Health and Care Research-funded study (151887) seeks to use innovative participatory methods including photovoice and biographical narrative interviews in urban and rural areas of England to assemble experience data. These data will be subjected to polytextual thematic analysis, and alongside pictures and captions, will inform an experienced-based co-design of interventions, the implementation of which will be evaluated. There will be an economic analysis and a process evaluation of the implementation. ETHICS AND DISSEMINATION: This programme of work has received ethical (IRAS 322421; Newcastle North Tyneside Research Ethics Committee 23/NE/0143) and sponsor approval. The findings will be disseminated in galleries showing the creative work, as lay and academic summaries and infographics; as practice briefings for practitioners, commissioners and policy makers; peer-reviewed publications. TRIAL REGISTRATION NUMBER: https://www.researchregistry.com/browse-the-registry%23home/registrationdetails/649c08111c037d0027b17d17/.

Using Electronic Health Records to Facilitate Precision Psychiatry.

The use of clinical prediction models to produce individualized risk estimates can facilitate the implementation of precision psychiatry. As a source of data from large, clinically representative patient samples, electronic health records (EHRs) provide a platform to develop and validate clinical prediction models, as well as potentially implement them in routine clinical care. The current review describes promising use cases for the application of precision psychiatry to EHR data and considers their performance in terms of discrimination (ability to separate individuals with and without the outcome) and calibration (extent to which predicted risk estimates correspond to observed outcomes), as well as their potential clinical utility (weighing benefits and costs associated with the model compared to different approaches across different assumptions of the number needed to test). We review 4 externally validated clinical prediction models designed to predict psychosis onset, psychotic relapse, cardiometabolic morbidity, and suicide risk. We then discuss the prospects for clinically implementing these models and the potential added value of integrating data from evidence syntheses, standardized psychometric assessments, and biological data into EHRs. Clinical prediction models can utilize routinely collected EHR data in an innovative way, representing a unique opportunity to inform real-world clinical decision making. Combining data from other sources (e.g., meta-analyses) or enhancing EHR data with information from research studies (clinical and biomarker data) may enhance our abilities to improve the performance of clinical prediction models.

The social determinants of mental health and disorder: evidence, prevention and recommendations.

People exposed to more unfavourable social circumstances are more vulnerable to poor mental health over their life course, in ways that are often determined by structural factors which generate and perpetuate intergenerational cycles of disadvantage and poor health. Addressing these challenges is an imperative matter of social justice. In this paper we provide a roadmap to address the social determinants that cause mental ill health. Relying as far as possible on high-quality evidence, we first map out the literature that supports a causal link between social determinants and later mental health outcomes. Given the breadth of this topic, we focus on the most pervasive social determinants across the life course, and those that are common across major mental disorders. We draw primarily on the available evidence from the Global North, acknowledging that other global contexts will face both similar and unique sets of social determinants that will require equitable attention. Much of our evidence focuses on mental health in groups who are marginalized, and thus often exposed to a multitude of intersecting social risk factors. These groups include refugees, asylum seekers and displaced persons, as well as ethnoracial minoritized groups; lesbian, gay, bisexual, transgender and queer (LGBTQ+) groups; and those living in poverty. We then introduce a preventive framework for conceptualizing the link between social determinants and mental health and disorder, which can guide much needed primary prevention strategies capable of reducing inequalities and improving population mental health. Following this, we provide a review of the evidence concerning candidate preventive strategies to intervene on social determinants of mental health. These interventions fall broadly within the scope of universal, selected and indicated primary prevention strategies, but we also briefly review important secondary and tertiary strategies to promote recovery in those with existing mental disorders. Finally, we provide seven key recommendations, framed around social justice, which constitute a roadmap for action in research, policy and public health. Adoption of these recommendations would provide an opportunity to advance efforts to intervene on modifiable social determinants that affect population mental health.

Antidepressants for the prevention of depression following first-episode psychosis (ADEPP): study protocol for a multi-centre, double-blind, randomised controlled trial.

BACKGROUND: Depressive episodes are common after first-episode psychosis (FEP), affecting more than 40% of people, adding to individual burden, poor outcomes, and healthcare costs. If the risks of developing depression were lower, this could have a beneficial effect on morbidity and mortality, as well as improving outcomes. Sertraline is a selective serotonin reuptake inhibitor and a common first-line medication for the treatment of depression in adults. It has been shown to be safe when co-prescribed with antipsychotic medication, and there is evidence that it is an effective treatment for depression in established schizophrenia. We present a protocol for a multi-centre, double-blind, randomised, placebo-controlled clinical trial called ADEPP that aims to investigate the efficacy and cost-effectiveness of sertraline in preventing depression after FEP. METHODS: The recruitment target is 452 participants between the ages of 18 and 65 years who are within 12 months of treatment initiation for FEP. Having provided informed consent, participants will be randomised to receive either 50 mg of sertraline daily or matched placebo for 6 months, in addition to treatment as usual. The primary outcome measure will be a comparison of the number of new cases of depression between the treatment and placebo arms over the 6-month intervention phase. Secondary outcomes include suicidal behaviour, anxiety, rates of relapse, functional outcome, quality of life, and resource use. DISCUSSION: The ADEPP trial will test whether the addition of sertraline following FEP is a clinically useful, acceptable, and cost-effective way of improving outcomes following FEP. TRIAL REGISTRATION: ISRCTN12682719 registration date 24/11/2020.

Prevalence of cognitive impairments and strengths in the early course of psychosis and depression.

BACKGROUND: Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression. METHODS: A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15-41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1-2 s.d. below or above HC, respectively) for each cognitive test. RESULTS: Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP. CONCLUSIONS: These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.

Protocol for the Psychosis Immune Mechanism Stratified Medicine (PIMS) trial: a randomised double-blind placebo-controlled trial of single-dose tocilizumab in patients with psychosis.

INTRODUCTION: Evidence suggests a potentially causal role of interleukin 6 (IL-6), a pleiotropic cytokine that generally promotes inflammation, in the pathogenesis of psychosis. However, no interventional studies in patients with psychosis, stratified using inflammatory markers, have been conducted to assess the therapeutic potential of targeting IL-6 in psychosis and to elucidate potential mechanism of effect. Tocilizumab is a humanised monoclonal antibody targeting the IL-6 receptor to inhibit IL-6 signalling, licensed in the UK for treatment of rheumatoid arthritis. The primary objective of this study is to test whether IL-6 contributes to the pathogenesis of first episode psychosis and to examine potential mechanisms by which IL-6 affects psychotic symptoms. A secondary objective is to examine characteristics of inflammation-associated psychosis. METHODS AND ANALYSIS: A proof-of-concept study employing a randomised, parallel-group, double-blind, placebo-controlled design testing the effect of IL-6 inhibition on anhedonia in patients with psychosis. Approximately 60 participants with a diagnosis of schizophrenia and related psychotic disorders (ICD-10 codes F20, F22, F25, F28, F29) with evidence of low-grade inflammation (IL-6≥0.7 pg/mL) will receive either one intravenous infusion of tocilizumab (4.0 mg/kg; max 800 mg) or normal saline. Psychiatric measures and blood samples will be collected at baseline, 7, 14 and 28 days post infusion. Cognitive and neuroimaging data will be collected at baseline and 14 days post infusion. In addition, approximately 30 patients with psychosis without evidence of inflammation (IL-6<0.7 pg/mL) and 30 matched healthy controls will be recruited to complete identical baseline assessments to allow for comparison of the characteristic features of inflammation-associated psychosis. ETHICS AND DISSEMINATION: The study is sponsored by the University of Bristol and has been approved by the Cambridge East Research Ethics Committee (reference: 22/EE/0010; IRAS project ID: 301682). Study findings will be published in peer-review journals. Findings will also be disseminated by scientific presentation and other means. TRIAL REGISTRATION NUMBER: ISRCTN23256704.

Five-year illness trajectories across racial groups in the UK following a first episode psychosis.

PURPOSE: Psychosis disproportionally affects ethnic minority groups in high-income countries, yet evidence of disparities in outcomes following intensive early intervention service (EIS) for First Episode Psychosis (FEP) is less conclusive. We investigated 5-year clinical and social outcomes of young people with FEP from different racial groups following EIS care. METHOD: Data were analysed from the UK-wide NIHR SUPEREDEN study. The sample at baseline (n = 978) included White (n = 750), Black (n = 71), and Asian (n = 157) individuals, assessed during the 3 years of EIS, and up to 2 years post-discharge (n = 296; Black [n = 23]; Asian [n = 52] and White [n = 221]). Outcome trajectories were modelled for psychosis symptoms (positive, negative, and general), functioning, and depression, using linear mixed effect models (with random intercept and slopes), whilst controlling for social deprivation. Discharge service was also explored across racial groups, 2 years following EIS. RESULTS: Variation in linear growth over time was accounted for by racial group status for psychosis symptoms-positive (95% CI [0.679, 1.235]), negative (95% CI [0.315, 0.783]), and general (95% CI [1.961, 3.428])-as well as for functioning (95% CI [11.212, 17.677]) and depressive symptoms (95% CI [0.261, 0.648]). Social deprivation contributed to this variance. Black individuals experienced greater levels of deprivation (p < 0.001, 95% CI [0.187, 0.624]). Finally, there was a greater likelihood for Asian (OR = 3.04; 95% CI [2.050, 4.498]) and Black individuals (OR = 2.47; 95% CI [1.354, 4.520]) to remain in secondary care by follow-up. CONCLUSION: Findings suggest variations in long-term clinical and social outcomes following EIS across racial groups; social deprivation contributed to this variance. Black and Asian individuals appear to make less improvement in long-term recovery and are less likely to be discharged from mental health services. Replication is needed in large, complete data, to fully understand disparities and blind spots to care.

Rethinking Immunity and Cognition in Clinical High Risk for Psychosis.

It is well known that schizophrenia is associated with cognitive impairment, reduced cortical grey matter and increased circulating concentrations of inflammatory cytokines. However, the relationship between these findings is not clear. We outline the influential neuroinflammatory hypotheses that raised cytokines provoke a damaging immune response in microglia that results in reduced grey matter and associated cognitive performance. We investigated whether such an interaction might be detectable in the prodromal period as illness emerges from the Clinical High Risk for Psychosis (CHR-P). Meta-analyses suggest that compared with controls, impaired cognition and reduced grey matter are already present by the prodrome and that greater decrements are present in those who later develop symptoms. In contrast, the few cytokine studies report no abnormalities in CHR-P except that interleukin-6 (IL-6) levels were raised versus controls and to a greater extent in the future patients, in one study. We noted that cognitive impairment and less cortical grey matter are more severe in schizophrenia than in affective disorders, but that increased cytokine levels are similarly prevalent across disorders. We found no studies correlating cytokine levels with cognitive impairment in CHR-P but such correlations seem unlikely given the minimal relationship reported in a recent meta-analysis of the many cytokine-cognition studies in established illness. From this and other evidence, we conclude that neuroinflammation is not a core feature of schizophrenia nor a substrate for reduced grey matter volume or cognitive function. We draw attention instead to the emerging evidence that brain-resident immune cells and signalling molecules such as Tregs and IL-6, which are influenced by schizophrenia risk genes, regulate and are necessary for the development and function of neuron-glia interaction. We suggest that cognitive impairment in schizophrenia can be seen as a convergence of genetic and immune-neurodevelopmental dysregulation whereas raised cytokines are a consequence of impaired Tregs control of systemic inflammation.

Heterogeneity in treatment outcomes and incomplete recovery in first episode psychosis: does one size fit all?

The heterogeneity in recovery outcomes for individuals with First Episode Psychosis (FEP) calls for a strong evidence base to inform practice at an individual level. Between 19-89% of young people with FEP have an incomplete recovery despite gold-standard evidence-based treatments, suggesting current service models, which adopt a 'one-size fits all' approach, may not be addressing the needs of many young people with psychosis. The lack of consistent terminology to define key concepts such as recovery and treatment resistance, the multidimensional nature of these concepts, and common comorbid symptoms are some of the challenges faced by the field in delineating heterogeneity in recovery outcomes. The lack of robust markers for incomplete recovery also results in potential delay in delivering prompt, and effective treatments to individuals at greatest risk. There is a clear need to adopt a stratified approach to care where interventions are targeted at subgroups of patients, and ultimately at the individual level. Novel machine learning, using large, representative data from a range of modalities, may aid in the parsing of heterogeneity, and provide greater precision and sophistication in identifying those on a pathway to incomplete recovery.

Neurobiologically Based Stratification of Recent-Onset Depression and Psychosis: Identification of Two Distinct Transdiagnostic Phenotypes.

BACKGROUND: Identifying neurobiologically based transdiagnostic categories of depression and psychosis may elucidate heterogeneity and provide better candidates for predictive modeling. We aimed to identify clusters across patients with recent-onset depression (ROD) and recent-onset psychosis (ROP) based on structural neuroimaging data. We hypothesized that these transdiagnostic clusters would identify patients with poor outcome and allow more accurate prediction of symptomatic remission than traditional diagnostic structures. METHODS: HYDRA (Heterogeneity through Discriminant Analysis) was trained on whole-brain volumetric measures from 577 participants from the discovery sample of the multisite PRONIA study to identify neurobiologically driven clusters, which were then externally validated in the PRONIA replication sample (n = 404) and three datasets of chronic samples (Centre for Biomedical Research Excellence, n = 146; Mind Clinical Imaging Consortium, n = 202; Munich, n = 470). RESULTS: The optimal clustering solution was two transdiagnostic clusters (cluster 1: n = 153, 67 ROP, 86 ROD; cluster 2: n = 149, 88 ROP, 61 ROD; adjusted Rand index = 0.618). The two clusters contained both patients with ROP and patients with ROD. One cluster had widespread gray matter volume deficits and more positive, negative, and functional deficits (impaired cluster), and one cluster revealed a more preserved neuroanatomical signature and more core depressive symptomatology (preserved cluster). The clustering solution was internally and externally validated and assessed for clinical utility in predicting 9-month symptomatic remission, outperforming traditional diagnostic structures. CONCLUSIONS: We identified two transdiagnostic neuroanatomically informed clusters that are clinically and biologically distinct, challenging current diagnostic boundaries in recent-onset mental health disorders. These results may aid understanding of the etiology of poor outcome patients transdiagnostically and improve development of stratified treatments.

Inflammation and Brain Structure in Schizophrenia and Other Neuropsychiatric Disorders: A Mendelian Randomization Study.

Importance: Previous in vitro and postmortem research suggests that inflammation may lead to structural brain changes via activation of microglia and/or astrocytic dysfunction in a range of neuropsychiatric disorders. Objective: To investigate the relationship between inflammation and changes in brain structures in vivo and to explore a transcriptome-driven functional basis with relevance to mental illness. Design, Setting, and Participants: This study used multistage linked analyses, including mendelian randomization (MR), gene expression correlation, and connectivity analyses. A total of 20 688 participants in the UK Biobank, which includes clinical, genomic, and neuroimaging data, and 6 postmortem brains from neurotypical individuals in the Allen Human Brain Atlas (AHBA), including RNA microarray data. Data were extracted in February 2021 and analyzed between March and October 2021. Exposures: Genetic variants regulating levels and activity of circulating interleukin 1 (IL-1), IL-2, IL-6, C-reactive protein (CRP), and brain-derived neurotrophic factor (BDNF) were used as exposures in MR analyses. Main Outcomes and Measures: Brain imaging measures, including gray matter volume (GMV) and cortical thickness (CT), were used as outcomes. Associations were considered significant at a multiple testing-corrected threshold of P < 1.1 × 10-4. Differential gene expression in AHBA data was modeled in brain regions mapped to areas significant in MR analyses; genes were tested for biological and disease overrepresentation in annotation databases and for connectivity in protein-protein interaction networks. Results: Of 20 688 participants in the UK Biobank sample, 10 828 (52.3%) were female, and the mean (SD) age was 55.5 (7.5) years. In the UK Biobank sample, genetically predicted levels of IL-6 were associated with GMV in the middle temporal cortex (z score, 5.76; P = 8.39 × 10-9), inferior temporal (z score, 3.38; P = 7.20 × 10-5), fusiform (z score, 4.70; P = 2.60 × 10-7), and frontal (z score, -3.59; P = 3.30 × 10-5) cortex together with CT in the superior frontal region (z score, -5.11; P = 3.22 × 10-7). No significant associations were found for IL-1, IL-2, CRP, or BDNF after correction for multiple comparison. In the AHBA sample, 5 of 6 participants (83%) were male, and the mean (SD) age was 42.5 (13.4) years. Brain-wide coexpression analysis showed a highly interconnected network of genes preferentially expressed in the middle temporal gyrus (MTG), which further formed a highly connected protein-protein interaction network with IL-6 (enrichment test of expected vs observed network given the prevalence and degree of interactions in the STRING database: 43 nodes/30 edges observed vs 8 edges expected; mean node degree, 1.4; genome-wide significance, P = 4.54 × 10-9). MTG differentially expressed genes that were functionally enriched for biological processes in schizophrenia, autism spectrum disorder, and epilepsy. Conclusions and Relevance: In this study, genetically determined IL-6 was associated with brain structure and potentially affects areas implicated in developmental neuropsychiatric disorders, including schizophrenia and autism.

The clinical relevance of formal thought disorder in the early stages of psychosis: results from the PRONIA study.

BACKGROUND: Formal thought disorder (FTD) has been associated with more severe illness courses and functional deficits in patients with psychotic disorders. However, it remains unclear whether the presence of FTD characterises a specific subgroup of patients showing more prominent illness severity, neurocognitive and functional impairments. This study aimed to identify stable and generalizable FTD-subgroups of patients with recent-onset psychosis (ROP) by applying a comprehensive data-driven clustering approach and to test the validity of these subgroups by assessing associations between this FTD-related stratification, social and occupational functioning, and neurocognition. METHODS: 279 patients with ROP were recruited as part of the multi-site European PRONIA study (Personalised Prognostic Tools for Early Psychosis Management; www.pronia.eu). Five FTD-related symptoms (conceptual disorganization, poverty of content of speech, difficulty in abstract thinking, increased latency of response and poverty of speech) were assessed with Positive and Negative Symptom Scale (PANSS) and the Scale for the Assessment of Negative Symptoms (SANS). RESULTS: The results with two patient subgroups showing different levels of FTD were the most stable and generalizable clustering solution (predicted clustering strength value = 0.86). FTD-High subgroup had lower scores in social (pfdr < 0.001) and role (pfdr < 0.001) functioning, as well as worse neurocognitive performance in semantic (pfdr < 0.001) and phonological verbal fluency (pfdr < 0.001), short-term verbal memory (pfdr = 0.002) and abstract thinking (pfdr = 0.010), in comparison to FTD-Low group. CONCLUSIONS: Clustering techniques allowed us to identify patients with more pronounced FTD showing more severe deficits in functioning and neurocognition, thus suggesting that FTD may be a relevant marker of illness severity in the early psychosis pathway.

Recognition and management of depression in early psychosis.

AIMS AND METHOD: Depression in first-episode psychosis (FEP) is highly prevalent and associated with poor outcomes; it has become increasingly recognised and adopted in national and international guidelines for psychosis. Using a 26-item questionnaire, this study aimed to explore if this shift has led to greater recognition among UK psychiatrists, and more effective management of depression in FEP. RESULTS: Of the 297 respondents, 54.4% observed depression occurring in chronic psychosis, with the least number of respondents (17.7%) identifying depression occurring frequently during FEP. Although there was reasonable agreement in the use of antidepressants as a first-line treatment for depression (70% prescribing antidepressants), there was uncertainty around assessing depression and delineating from psychosis symptoms, and particularly negative symptoms. CLINICAL IMPLICATIONS: Evidence-based treatments for comorbid depression in psychosis will lead to clearer national guidelines, allowing for optimal management of depression in early psychosis, potentially leading to improved outcomes for these individuals.

Structure and stability of symptoms in first episode psychosis: a longitudinal network approach.

Early psychosis is characterised by heterogeneity in illness trajectories, where outcomes remain poor for many. Understanding psychosis symptoms and their relation to illness outcomes, from a novel network perspective, may help to delineate psychopathology within early psychosis and identify pivotal targets for intervention. Using network modelling in first episode psychosis (FEP), this study aimed to identify: (a) key central and bridge symptoms most influential in symptom networks, and (b) examine the structure and stability of the networks at baseline and 12-month follow-up. Data on 1027 participants with FEP were taken from the National EDEN longitudinal study and used to create regularised partial correlation networks using the 'EBICglasso' algorithm for positive, negative, and depressive symptoms at baseline and at 12-months. Centrality and bridge estimations were computed using a permutation-based network comparison test. Depression featured as a central symptom in both the baseline and 12-month networks. Conceptual disorganisation, stereotyped thinking, along with hallucinations and suspiciousness featured as key bridge symptoms across the networks. The network comparison test revealed that the strength and bridge centralities did not differ significantly between the two networks (C = 0.096153; p = 0.22297). However, the network structure and connectedness differed significantly from baseline to follow-up (M = 0.16405, p = <0.0001; S = 0.74536, p = 0.02), with several associations between psychosis and depressive items differing significantly by 12 months. Depressive symptoms, in addition to symptoms of thought disturbance (e.g. conceptual disorganisation and stereotyped thinking), may be examples of important, under-recognized treatment targets in early psychosis, which may have the potential to lead to global symptom improvements and better recovery.

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.

Improved social functioning following social recovery therapy in first episode psychosis: Do social cognition and neurocognition change following therapy, and do they predict treatment response?

There is a need to develop and refine psychosocial interventions to improve functioning in First Episode Psychosis (FEP). Social cognition and neurocognition are closely linked to functioning in psychosis; examinations of cognition pre- and post- psychosocial intervention may provide insights into the mechanisms of these interventions, and identify which individuals are most likely to benefit. METHOD: Cognition was assessed within a multi-site trial of Social Recovery Therapy (SRT) for individuals with FEP experiencing poor functioning (<30 h weekly structured activity). Fifty-nine participants were randomly allocated to the therapy group (SRT + Early intervention), and 64 were allocated to treatment as usual group (TAU - early intervention care). Social cognition and neurocognition were assessed at baseline and 9 months; assessors were blind to group allocation. It was hypothesized that social cognition would improve following therapy, and those with better social cognition prior to therapy would benefit the most from SRT. RESULTS: There was no significant impact of SRT on individual neurocognitive or social cognitive variables, however, joint models addressing patterns of missingness demonstrate improvement across a number of cognitive outcomes following SRT. Further, regression analyses showed those who had better social cognition at baseline were most likely to benefit from the therapy (ß = 0.350; 95% CI = 0.830 to 8.891; p = .019). CONCLUSION: It is not clear if SRT impacts on social cognitive or neurocognitive function, however, SRT may be beneficial in those with better social cognition at baseline.

Predictors of social and role outcomes in first episode psychosis: A prospective 12-month study of social cognition, neurocognition and symptoms.

BACKGROUND: Poor functioning is common in psychosis, with predictors of poor outcome including negative symptoms and deficits in neurocognition (NC) and social cognition (SC). The extent to which these variables contribute unique variance in social and role trajectories remains inconclusive. Identifying robust predictors of outcome will inform targeted interventions in early psychosis, where functional trajectories are being set. METHOD: Prospective 12-month follow-up study investigating the predictive values of NC and SC on social and role functioning in individuals with first-episode psychosis (FEP), within the context of clinical variables. 98 individuals with FEP (mean age = 24; male = 77) were assessed within the first year of diagnosis on functioning (social and role), cognition (SC and NC) and psychosis symptoms. RESULTS: Negative symptoms were the only significant predictor of 12-month social (χ2  = 9.59, P = .002, OR = 1.12) and role (χ2  = 10.86, P < .001, OR = 1.16) functioning in FEP. In exploratory analyses, negative symptoms mediated the relationship between baseline social knowledge and social functioning (Z = 1.92, P = .05; d = 0.56), and between baseline logical memory and role functioning (Z = 2.40, P = .02; d = 0.80) at 12-month follow-up. CONCLUSION: Although social and role trajectories in early psychosis appear somewhat distinct, negative symptoms were the best prognostic marker of social and role outcome in FEP, and mediated the relationship between SC and social outcome, and NC and role outcome; these relationships may be important when considering interventions to improve functional outcome in early psychosis.