Oxford Health NHS Foundation Trust

BACKGROUND: Major depressive disorder is one of the most common, burdensome, and costly psychiatric disorders worldwide in adults. Pharmacological and non-pharmacological treatments are available; however, because of inadequate resources, antidepressants are used more frequently than psychological interventions. Prescription of these agents should be informed by the best available evidence. Therefore, we aimed to update and expand our previous work to compare and rank antidepressants for the acute treatment of adults with unipolar major depressive disorder. METHODS: We did a systematic review and network meta-analysis. We searched Cochrane Central Register of Controlled Trials, CINAHL, Embase, LILACS database, MEDLINE, MEDLINE In-Process, PsycINFO, the websites of regulatory agencies, and international registers for published and unpublished, double-blind, randomised controlled trials from their inception to Jan 8, 2016. We included placebo-controlled and head-to-head trials of 21 antidepressants used for the acute treatment of adults (≥18 years old and of both sexes) with major depressive disorder diagnosed according to standard operationalised criteria. We excluded quasi-randomised trials and trials that were incomplete or included 20% or more of participants with bipolar disorder, psychotic depression, or treatment-resistant depression; or patients with a serious concomitant medical illness. We extracted data following a predefined hierarchy. In network meta-analysis, we used group-level data. We assessed the studies' risk of bias in accordance to the Cochrane Handbook for Systematic Reviews of Interventions, and certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation framework. Primary outcomes were efficacy (response rate) and acceptability (treatment discontinuations due to any cause). We estimated summary odds ratios (ORs) using pairwise and network meta-analysis with random effects. This study is registered with PROSPERO, number CRD42012002291. FINDINGS: We identified 28 552 citations and of these included 522 trials comprising 116 477 participants. In terms of efficacy, all antidepressants were more effective than placebo, with ORs ranging between 2·13 (95% credible interval [CrI] 1·89-2·41) for amitriptyline and 1·37 (1·16-1·63) for reboxetine. For acceptability, only agomelatine (OR 0·84, 95% CrI 0·72-0·97) and fluoxetine (0·88, 0·80-0·96) were associated with fewer dropouts than placebo, whereas clomipramine was worse than placebo (1·30, 1·01-1·68). When all trials were considered, differences in ORs between antidepressants ranged from 1·15 to 1·55 for efficacy and from 0·64 to 0·83 for acceptability, with wide CrIs on most of the comparative analyses. In head-to-head studies, agomelatine, amitriptyline, escitalopram, mirtazapine, paroxetine, venlafaxine, and vortioxetine were more effective than other antidepressants (range of ORs 1·19-1·96), whereas fluoxetine, fluvoxamine, reboxetine, and trazodone were the least efficacious drugs (0·51-0·84). For acceptability, agomelatine, citalopram, escitalopram, fluoxetine, sertraline, and vortioxetine were more tolerable than other antidepressants (range of ORs 0·43-0·77), whereas amitriptyline, clomipramine, duloxetine, fluvoxamine, reboxetine, trazodone, and venlafaxine had the highest dropout rates (1·30-2·32). 46 (9%) of 522 trials were rated as high risk of bias, 380 (73%) trials as moderate, and 96 (18%) as low; and the certainty of evidence was moderate to very low. INTERPRETATION: All antidepressants were more efficacious than placebo in adults with major depressive disorder. Smaller differences between active drugs were found when placebo-controlled trials were included in the analysis, whereas there was more variability in efficacy and acceptability in head-to-head trials. These results should serve evidence-based practice and inform patients, physicians, guideline developers, and policy makers on the relative merits of the different antidepressants. FUNDING: National Institute for Health Research Oxford Health Biomedical Research Centre and the Japan Society for the Promotion of Science.

, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

BACKGROUND: Neurological and psychiatric sequelae of COVID-19 have been reported, but more data are needed to adequately assess the effects of COVID-19 on brain health. We aimed to provide robust estimates of incidence rates and relative risks of neurological and psychiatric diagnoses in patients in the 6 months following a COVID-19 diagnosis. METHODS: For this retrospective cohort study and time-to-event analysis, we used data obtained from the TriNetX electronic health records network (with over 81 million patients). Our primary cohort comprised patients who had a COVID-19 diagnosis; one matched control cohort included patients diagnosed with influenza, and the other matched control cohort included patients diagnosed with any respiratory tract infection including influenza in the same period. Patients with a diagnosis of COVID-19 or a positive test for SARS-CoV-2 were excluded from the control cohorts. All cohorts included patients older than 10 years who had an index event on or after Jan 20, 2020, and who were still alive on Dec 13, 2020. We estimated the incidence of 14 neurological and psychiatric outcomes in the 6 months after a confirmed diagnosis of COVID-19: intracranial haemorrhage; ischaemic stroke; parkinsonism; Guillain-Barré syndrome; nerve, nerve root, and plexus disorders; myoneural junction and muscle disease; encephalitis; dementia; psychotic, mood, and anxiety disorders (grouped and separately); substance use disorder; and insomnia. Using a Cox model, we compared incidences with those in propensity score-matched cohorts of patients with influenza or other respiratory tract infections. We investigated how these estimates were affected by COVID-19 severity, as proxied by hospitalisation, intensive therapy unit (ITU) admission, and encephalopathy (delirium and related disorders). We assessed the robustness of the differences in outcomes between cohorts by repeating the analysis in different scenarios. To provide benchmarking for the incidence and risk of neurological and psychiatric sequelae, we compared our primary cohort with four cohorts of patients diagnosed in the same period with additional index events: skin infection, urolithiasis, fracture of a large bone, and pulmonary embolism. FINDINGS: Among 236 379 patients diagnosed with COVID-19, the estimated incidence of a neurological or psychiatric diagnosis in the following 6 months was 33·62% (95% CI 33·17-34·07), with 12·84% (12·36-13·33) receiving their first such diagnosis. For patients who had been admitted to an ITU, the estimated incidence of a diagnosis was 46·42% (44·78-48·09) and for a first diagnosis was 25·79% (23·50-28·25). Regarding individual diagnoses of the study outcomes, the whole COVID-19 cohort had estimated incidences of 0·56% (0·50-0·63) for intracranial haemorrhage, 2·10% (1·97-2·23) for ischaemic stroke, 0·11% (0·08-0·14) for parkinsonism, 0·67% (0·59-0·75) for dementia, 17·39% (17·04-17·74) for anxiety disorder, and 1·40% (1·30-1·51) for psychotic disorder, among others. In the group with ITU admission, estimated incidences were 2·66% (2·24-3·16) for intracranial haemorrhage, 6·92% (6·17-7·76) for ischaemic stroke, 0·26% (0·15-0·45) for parkinsonism, 1·74% (1·31-2·30) for dementia, 19·15% (17·90-20·48) for anxiety disorder, and 2·77% (2·31-3·33) for psychotic disorder. Most diagnostic categories were more common in patients who had COVID-19 than in those who had influenza (hazard ratio [HR] 1·44, 95% CI 1·40-1·47, for any diagnosis; 1·78, 1·68-1·89, for any first diagnosis) and those who had other respiratory tract infections (1·16, 1·14-1·17, for any diagnosis; 1·32, 1·27-1·36, for any first diagnosis). As with incidences, HRs were higher in patients who had more severe COVID-19 (eg, those admitted to ITU compared with those who were not: 1·58, 1·50-1·67, for any diagnosis; 2·87, 2·45-3·35, for any first diagnosis). Results were robust to various sensitivity analyses and benchmarking against the four additional index health events. INTERPRETATION: Our study provides evidence for substantial neurological and psychiatric morbidity in the 6 months after COVID-19 infection. Risks were greatest in, but not limited to, patients who had severe COVID-19. This information could help in service planning and identification of research priorities. Complementary study designs, including prospective cohorts, are needed to corroborate and explain these findings. FUNDING: National Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

BACKGROUND: Climate change has important implications for the health and futures of children and young people, yet they have little power to limit its harm, making them vulnerable to climate anxiety. This is the first large-scale investigation of climate anxiety in children and young people globally and its relationship with perceived government response. METHODS: We surveyed 10 000 children and young people (aged 16-25 years) in ten countries (Australia, Brazil, Finland, France, India, Nigeria, Philippines, Portugal, the UK, and the USA; 1000 participants per country). Invitations to complete the survey were sent via the platform Kantar between May 18 and June 7, 2021. Data were collected on participants' thoughts and feelings about climate change, and government responses to climate change. Descriptive statistics were calculated for each aspect of climate anxiety, and Pearson's correlation analysis was done to evaluate whether climate-related distress, functioning, and negative beliefs about climate change were linked to thoughts and feelings about government response. FINDINGS: Respondents across all countries were worried about climate change (59% were very or extremely worried and 84% were at least moderately worried). More than 50% reported each of the following emotions: sad, anxious, angry, powerless, helpless, and guilty. More than 45% of respondents said their feelings about climate change negatively affected their daily life and functioning, and many reported a high number of negative thoughts about climate change (eg, 75% said that they think the future is frightening and 83% said that they think people have failed to take care of the planet). Respondents rated governmental responses to climate change negatively and reported greater feelings of betrayal than of reassurance. Climate anxiety and distress were correlated with perceived inadequate government response and associated feelings of betrayal. INTERPRETATION: Climate anxiety and dissatisfaction with government responses are widespread in children and young people in countries across the world and impact their daily functioning. A perceived failure by governments to respond to the climate crisis is associated with increased distress. There is an urgent need for further research into the emotional impact of climate change on children and young people and for governments to validate their distress by taking urgent action on climate change. FUNDING: AVAAZ.

BACKGROUND: Schizophrenia is one of the most common, burdensome, and costly psychiatric disorders in adults worldwide. Antipsychotic drugs are its treatment of choice, but there is controversy about which agent should be used. We aimed to compare and rank antipsychotics by quantifying information from randomised controlled trials. METHODS: We did a network meta-analysis of placebo-controlled and head-to-head randomised controlled trials and compared 32 antipsychotics. We searched Embase, MEDLINE, PsycINFO, PubMed, BIOSIS, Cochrane Central Register of Controlled Trials (CENTRAL), WHO International Clinical Trials Registry Platform, and ClinicalTrials.gov from database inception to Jan 8, 2019. Two authors independently selected studies and extracted data. We included randomised controlled trials in adults with acute symptoms of schizophrenia or related disorders. We excluded studies in patients with treatment resistance, first episode, predominant negative or depressive symptoms, concomitant medical illnesses, and relapse-prevention studies. Our primary outcome was change in overall symptoms measured with standardised rating scales. We also extracted data for eight efficacy and eight safety outcomes. Differences in the findings of the studies were explored in metaregressions and sensitivity analyses. Effect size measures were standardised mean differences, mean differences, or risk ratios with 95% credible intervals (CrIs). Confidence in the evidence was assessed using CINeMA (Confidence in Network Meta-Analysis). The study protocol is registered with PROSPERO, number CRD42014014919. FINDINGS: We identified 54 417 citations and included 402 studies with data for 53 463 participants. Effect size estimates suggested all antipsychotics reduced overall symptoms more than placebo (although not statistically significant for six drugs), with standardised mean differences ranging from -0·89 (95% CrI -1·08 to -0·71) for clozapine to -0·03 (-0·59 to 0·52) for levomepromazine (40 815 participants). Standardised mean differences compared with placebo for reduction of positive symptoms (31 179 participants) varied from -0·69 (95% CrI -0·86 to -0·52) for amisulpride to -0·17 (-0·31 to -0·04) for brexpiprazole, for negative symptoms (32 015 participants) from -0·62 (-0·84 to -0·39; clozapine) to -0·10 (-0·45 to 0·25; flupentixol), for depressive symptoms (19 683 participants) from -0·90 (-1·36 to -0·44; sulpiride) to 0·04 (-0·39 to 0·47; flupentixol). Risk ratios compared with placebo for all-cause discontinuation (42 672 participants) ranged from 0·52 (0·12 to 0·95; clopenthixol) to 1·15 (0·36 to 1·47; pimozide), for sedation (30 770 participants) from 0·92 (0·17 to 2·03; pimozide) to 10·20 (4·72 to 29·41; zuclopenthixol), for use of antiparkinson medication (24 911 participants) from 0·46 (0·19 to 0·88; clozapine) to 6·14 (4·81 to 6·55; pimozide). Mean differences compared to placebo for weight gain (28 317 participants) ranged from -0·16 kg (-0·73 to 0·40; ziprasidone) to 3·21 kg (2·10 to 4·31; zotepine), for prolactin elevation (21 569 participants) from -77·05 ng/mL (-120·23 to -33·54; clozapine) to 48·51 ng/mL (43·52 to 53·51; paliperidone) and for QTc prolongation (15 467 participants) from -2·21 ms (-4·54 to 0·15; lurasidone) to 23·90 ms (20·56 to 27·33; sertindole). Conclusions for the primary outcome did not substantially change after adjusting for possible effect moderators or in sensitivity analyses (eg, when excluding placebo-controlled studies). The confidence in evidence was often low or very low. INTERPRETATION: There are some efficacy differences between antipsychotics, but most of them are gradual rather than discrete. Differences in side-effects are more marked. These findings will aid clinicians in balancing risks versus benefits of those drugs available in their countries. They should consider the importance of each outcome, the patients' medical problems, and preferences. FUNDING: German Ministry of Education and Research and National Institute for Health Research.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

BACKGROUND: Adverse mental health consequences of COVID-19, including anxiety and depression, have been widely predicted but not yet accurately measured. There are a range of physical health risk factors for COVID-19, but it is not known if there are also psychiatric risk factors. In this electronic health record network cohort study using data from 69 million individuals, 62 354 of whom had a diagnosis of COVID-19, we assessed whether a diagnosis of COVID-19 (compared with other health events) was associated with increased rates of subsequent psychiatric diagnoses, and whether patients with a history of psychiatric illness are at a higher risk of being diagnosed with COVID-19. METHODS: We used the TriNetX Analytics Network, a global federated network that captures anonymised data from electronic health records in 54 health-care organisations in the USA, totalling 69·8 million patients. TriNetX included 62 354 patients diagnosed with COVID-19 between Jan 20, and Aug 1, 2020. We created cohorts of patients who had been diagnosed with COVID-19 or a range of other health events. We used propensity score matching to control for confounding by risk factors for COVID-19 and for severity of illness. We measured the incidence of and hazard ratios (HRs) for psychiatric disorders, dementia, and insomnia, during the first 14 to 90 days after a diagnosis of COVID-19. FINDINGS: In patients with no previous psychiatric history, a diagnosis of COVID-19 was associated with increased incidence of a first psychiatric diagnosis in the following 14 to 90 days compared with six other health events (HR 2·1, 95% CI 1·8-2·5 vs influenza; 1·7, 1·5-1·9 vs other respiratory tract infections; 1·6, 1·4-1·9 vs skin infection; 1·6, 1·3-1·9 vs cholelithiasis; 2·2, 1·9-2·6 vs urolithiasis, and 2·1, 1·9-2·5 vs fracture of a large bone; all p<0·0001). The HR was greatest for anxiety disorders, insomnia, and dementia. We observed similar findings, although with smaller HRs, when relapses and new diagnoses were measured. The incidence of any psychiatric diagnosis in the 14 to 90 days after COVID-19 diagnosis was 18·1% (95% CI 17·6-18·6), including 5·8% (5·2-6·4) that were a first diagnosis. The incidence of a first diagnosis of dementia in the 14 to 90 days after COVID-19 diagnosis was 1·6% (95% CI 1·2-2·1) in people older than 65 years. A psychiatric diagnosis in the previous year was associated with a higher incidence of COVID-19 diagnosis (relative risk 1·65, 95% CI 1·59-1·71; p<0·0001). This risk was independent of known physical health risk factors for COVID-19, but we cannot exclude possible residual confounding by socioeconomic factors. INTERPRETATION: Survivors of COVID-19 appear to be at increased risk of psychiatric sequelae, and a psychiatric diagnosis might be an independent risk factor for COVID-19. Although preliminary, our findings have implications for clinical services, and prospective cohort studies are warranted. FUNDING: National Institute for Health Research.

Mental health problems are inseparable from the environment. With virtual reality (VR), computer-generated interactive environments, individuals can repeatedly experience their problematic situations and be taught, via evidence-based psychological treatments, how to overcome difficulties. VR is moving out of specialist laboratories. Our central aim was to describe the potential of VR in mental health, including a consideration of the first 20 years of applications. A systematic review of empirical studies was conducted. In all, 285 studies were identified, with 86 concerning assessment, 45 theory development, and 154 treatment. The main disorders researched were anxiety (n = 192), schizophrenia (n = 44), substance-related disorders (n = 22) and eating disorders (n = 18). There are pioneering early studies, but the methodological quality of studies was generally low. The gaps in meaningful applications to mental health are extensive. The most established finding is that VR exposure-based treatments can reduce anxiety disorders, but there are numerous research and treatment avenues of promise. VR was found to be a much-misused term, often applied to non-interactive and non-immersive technologies. We conclude that VR has the potential to transform the assessment, understanding and treatment of mental health problems. The treatment possibilities will only be realized if - with the user experience at the heart of design - the best immersive VR technology is combined with targeted translational interventions. The capability of VR to simulate reality could greatly increase access to psychological therapies, while treatment outcomes could be enhanced by the technology's ability to create new realities. VR may merit the level of attention given to neuroimaging.

BACKGROUND: The benefits and safety of medications for attention-deficit hyperactivity disorder (ADHD) remain controversial, and guidelines are inconsistent on which medications are preferred across different age groups. We aimed to estimate the comparative efficacy and tolerability of oral medications for ADHD in children, adolescents, and adults. METHODS: We did a literature search for published and unpublished double-blind randomised controlled trials comparing amphetamines (including lisdexamfetamine), atomoxetine, bupropion, clonidine, guanfacine, methylphenidate, and modafinil with each other or placebo. We systematically contacted study authors and drug manufacturers for additional information. Primary outcomes were efficacy (change in severity of ADHD core symptoms based on teachers' and clinicians' ratings) and tolerability (proportion of patients who dropped out of studies because of side-effects) at timepoints closest to 12 weeks, 26 weeks, and 52 weeks. We estimated summary odds ratios (ORs) and standardised mean differences (SMDs) using pairwise and network meta-analysis with random effects. We assessed the risk of bias of individual studies with the Cochrane risk of bias tool and confidence of estimates with the Grading of Recommendations Assessment, Development, and Evaluation approach for network meta-analyses. This study is registered with PROSPERO, number CRD42014008976. FINDINGS: 133 double-blind randomised controlled trials (81 in children and adolescents, 51 in adults, and one in both) were included. The analysis of efficacy closest to 12 weeks was based on 10 068 children and adolescents and 8131 adults; the analysis of tolerability was based on 11 018 children and adolescents and 5362 adults. The confidence of estimates varied from high or moderate (for some comparisons) to low or very low (for most indirect comparisons). For ADHD core symptoms rated by clinicians in children and adolescents closest to 12 weeks, all included drugs were superior to placebo (eg, SMD -1·02, 95% CI -1·19 to -0·85 for amphetamines, -0·78, -0·93 to -0·62 for methylphenidate, -0·56, -0·66 to -0·45 for atomoxetine). By contrast, for available comparisons based on teachers' ratings, only methylphenidate (SMD -0·82, 95% CI -1·16 to -0·48) and modafinil (-0·76, -1·15 to -0·37) were more efficacious than placebo. In adults (clinicians' ratings), amphetamines (SMD -0·79, 95% CI -0·99 to -0·58), methylphenidate (-0·49, -0·64 to -0·35), bupropion (-0·46, -0·85 to -0·07), and atomoxetine (-0·45, -0·58 to -0·32), but not modafinil (0·16, -0·28 to 0·59), were better than placebo. With respect to tolerability, amphetamines were inferior to placebo in both children and adolescents (odds ratio [OR] 2·30, 95% CI 1·36-3·89) and adults (3·26, 1·54-6·92); guanfacine was inferior to placebo in children and adolescents only (2·64, 1·20-5·81); and atomoxetine (2·33, 1·28-4·25), methylphenidate (2·39, 1·40-4·08), and modafinil (4·01, 1·42-11·33) were less well tolerated than placebo in adults only. In head-to-head comparisons, only differences in efficacy (clinicians' ratings) were found, favouring amphetamines over modafinil, atomoxetine, and methylphenidate in both children and adolescents (SMDs -0·46 to -0·24) and adults (-0·94 to -0·29). We did not find sufficient data for the 26-week and 52-week timepoints. INTERPRETATION: Our findings represent the most comprehensive available evidence base to inform patients, families, clinicians, guideline developers, and policymakers on the choice of ADHD medications across age groups. Taking into account both efficacy and safety, evidence from this meta-analysis supports methylphenidate in children and adolescents, and amphetamines in adults, as preferred first-choice medications for the short-term treatment of ADHD. New research should be funded urgently to assess long-term effects of these drugs. FUNDING: Stichting Eunethydis (European Network for Hyperkinetic Disorders), and the UK National Institute for Health Research Oxford Health Biomedical Research Centre.

BACKGROUND: There are well over a million homeless people in Western Europe and North America, but reliable estimates of the prevalence of major mental disorders among this population are lacking. We undertook a systematic review of surveys of such disorders in homeless people. METHODS AND FINDINGS: We searched for surveys of the prevalence of psychotic illness, major depression, alcohol and drug dependence, and personality disorder that were based on interviews of samples of unselected homeless people. We searched bibliographic indexes, scanned reference lists, and corresponded with authors. We explored potential sources of any observed heterogeneity in the estimates by meta-regression analysis, including geographical region, sample size, and diagnostic method. Twenty-nine eligible surveys provided estimates obtained from 5,684 homeless individuals from seven countries. Substantial heterogeneity was observed in prevalence estimates for mental disorders among the studies (all Cochran's chi(2) significant at p < 0.001 and all I(2) > 85%). The most common mental disorders were alcohol dependence, which ranged from 8.1% to 58.5%, and drug dependence, which ranged from 4.5% to 54.2%. For psychotic illness, the prevalence ranged from 2.8% to 42.3%, with similar findings for major depression. The prevalence of alcohol dependence was found to have increased over recent decades. CONCLUSIONS: Homeless people in Western countries are substantially more likely to have alcohol and drug dependence than the age-matched general population in those countries, and the prevalences of psychotic illnesses and personality disorders are higher. Models of psychiatric and social care that can best meet these mental health needs requires further investigation.

Early detection of vascular inflammation would allow deployment of targeted strategies for the prevention or treatment of multiple disease states. Because vascular inflammation is not detectable with commonly used imaging modalities, we hypothesized that phenotypic changes in perivascular adipose tissue (PVAT) induced by vascular inflammation could be quantified using a new computerized tomography (CT) angiography methodology. We show that inflamed human vessels release cytokines that prevent lipid accumulation in PVAT-derived preadipocytes in vitro, ex vivo, and in vivo. We developed a three-dimensional PVAT analysis method and studied CT images of human adipose tissue explants from 453 patients undergoing cardiac surgery, relating the ex vivo images with in vivo CT scan information on the biology of the explants. We developed an imaging metric, the CT fat attenuation index (FAI), that describes adipocyte lipid content and size. The FAI has excellent sensitivity and specificity for detecting tissue inflammation as assessed by tissue uptake of 18F-fluorodeoxyglucose in positron emission tomography. In a validation cohort of 273 subjects, the FAI gradient around human coronary arteries identified early subclinical coronary artery disease in vivo, as well as detected dynamic changes of PVAT in response to variations of vascular inflammation, and inflamed, vulnerable atherosclerotic plaques during acute coronary syndromes. Our study revealed that human vessels exert paracrine effects on the surrounding PVAT, affecting local intracellular lipid accumulation in preadipocytes, which can be monitored using a CT imaging approach. This methodology can be implemented in clinical practice to noninvasively detect plaque instability in the human coronary vasculature.

BACKGROUND: Antipsychotic treatment is associated with metabolic disturbance. However, the degree to which metabolic alterations occur in treatment with different antipsychotics is unclear. Predictors of metabolic dysregulation are poorly understood and the association between metabolic change and change in psychopathology is uncertain. We aimed to compare and rank antipsychotics on the basis of their metabolic side-effects, identify physiological and demographic predictors of antipsychotic-induced metabolic dysregulation, and investigate the relationship between change in psychotic symptoms and change in metabolic parameters with antipsychotic treatment. METHODS: We searched MEDLINE, EMBASE, and PsycINFO from inception until June 30, 2019. We included blinded, randomised controlled trials comparing 18 antipsychotics and placebo in acute treatment of schizophrenia. We did frequentist random-effects network meta-analyses to investigate treatment-induced changes in body weight, BMI, total cholesterol, LDL cholesterol, HDL cholesterol, triglyceride, and glucose concentrations. We did meta-regressions to examine relationships between metabolic change and age, sex, ethnicity, baseline weight, and baseline metabolic parameter level. We examined the association between metabolic change and psychopathology change by estimating the correlation between symptom severity change and metabolic parameter change. FINDINGS: (0·90 to 1·25) for olanzapine; for total-cholesterol from -0·09 mmol/L (-0·24 to 0·07) for cariprazine to 0·56 mmol/L (0·26-0·86) for clozapine; for LDL cholesterol from -0·13 mmol/L (-0.21 to -0·05) for cariprazine to 0·20 mmol/L (0·14 to 0·26) for olanzapine; for HDL cholesterol from 0·05 mmol/L (0·00 to 0·10) for brexpiprazole to -0·10 mmol/L (-0·33 to 0·14) for amisulpride; for triglycerides from -0·01 mmol/L (-0·10 to 0·08) for brexpiprazole to 0·98 mmol/L (0·48 to 1·49) for clozapine; for glucose from -0·29 mmol/L (-0·55 to -0·03) for lurasidone to 1·05 mmol/L (0·41 to 1·70) for clozapine. Greater increases in glucose were predicted by higher baseline weight (p=0·0015) and male sex (p=0·0082). Non-white ethnicity was associated with greater increases in total cholesterol (p=0·040) compared with white ethnicity. Improvements in symptom severity were associated with increases in weight (r=0·36, p=0·0021), BMI (r=0·84, p<0·0001), total-cholesterol (r=0·31, p=0·047), and LDL cholesterol (r=0·42, p=0·013), and decreases in HDL cholesterol (r=-0·35, p=0·035). INTERPRETATION: Marked differences exist between antipsychotics in terms of metabolic side-effects, with olanzapine and clozapine exhibiting the worst profiles and aripiprazole, brexpiprazole, cariprazine, lurasidone, and ziprasidone the most benign profiles. Increased baseline weight, male sex, and non-white ethnicity are predictors of susceptibility to antipsychotic-induced metabolic change, and improvements in psychopathology are associated with metabolic disturbance. Treatment guidelines should be updated to reflect our findings. However, the choice of antipsychotic should be made on an individual basis, considering the clinical circumstances and preferences of patients, carers, and clinicians. FUNDING: UK Medical Research Council, Wellcome Trust, National Institute for Health Research Oxford Health Biomedical Research Centre.

BACKGROUND: Long-COVID refers to a variety of symptoms affecting different organs reported by people following Coronavirus Disease 2019 (COVID-19) infection. To date, there have been no robust estimates of the incidence and co-occurrence of long-COVID features, their relationship to age, sex, or severity of infection, and the extent to which they are specific to COVID-19. The aim of this study is to address these issues. METHODS AND FINDINGS: We conducted a retrospective cohort study based on linked electronic health records (EHRs) data from 81 million patients including 273,618 COVID-19 survivors. The incidence and co-occurrence within 6 months and in the 3 to 6 months after COVID-19 diagnosis were calculated for 9 core features of long-COVID (breathing difficulties/breathlessness, fatigue/malaise, chest/throat pain, headache, abdominal symptoms, myalgia, other pain, cognitive symptoms, and anxiety/depression). Their co-occurrence network was also analyzed. Comparison with a propensity score-matched cohort of patients diagnosed with influenza during the same time period was achieved using Kaplan-Meier analysis and the Cox proportional hazard model. The incidence of atopic dermatitis was used as a negative control. Among COVID-19 survivors (mean [SD] age: 46.3 [19.8], 55.6% female), 57.00% had one or more long-COVID feature recorded during the whole 6-month period (i.e., including the acute phase), and 36.55% between 3 and 6 months. The incidence of each feature was: abnormal breathing (18.71% in the 1- to 180-day period; 7.94% in the 90- to180-day period), fatigue/malaise (12.82%; 5.87%), chest/throat pain (12.60%; 5.71%), headache (8.67%; 4.63%), other pain (11.60%; 7.19%), abdominal symptoms (15.58%; 8.29%), myalgia (3.24%; 1.54%), cognitive symptoms (7.88%; 3.95%), and anxiety/depression (22.82%; 15.49%). All 9 features were more frequently reported after COVID-19 than after influenza (with an overall excess incidence of 16.60% and hazard ratios between 1.44 and 2.04, all p < 0.001), co-occurred more commonly, and formed a more interconnected network. Significant differences in incidence and co-occurrence were associated with sex, age, and illness severity. Besides the limitations inherent to EHR data, limitations of this study include that (i) the findings do not generalize to patients who have had COVID-19 but were not diagnosed, nor to patients who do not seek or receive medical attention when experiencing symptoms of long-COVID; (ii) the findings say nothing about the persistence of the clinical features; and (iii) the difference between cohorts might be affected by one cohort seeking or receiving more medical attention for their symptoms. CONCLUSIONS: Long-COVID clinical features occurred and co-occurred frequently and showed some specificity to COVID-19, though they were also observed after influenza. Different long-COVID clinical profiles were observed based on demographics and illness severity.

Importance: Cannabis is the most commonly used drug of abuse by adolescents in the world. While the impact of adolescent cannabis use on the development of psychosis has been investigated in depth, little is known about the impact of cannabis use on mood and suicidality in young adulthood. Objective: To provide a summary estimate of the extent to which cannabis use during adolescence is associated with the risk of developing subsequent major depression, anxiety, and suicidal behavior. Data Sources: Medline, Embase, CINAHL, PsycInfo, and Proquest Dissertations and Theses were searched from inception to January 2017. Study Selection: Longitudinal and prospective studies, assessing cannabis use in adolescents younger than 18 years (at least 1 assessment point) and then ascertaining development of depression in young adulthood (age 18 to 32 years) were selected, and odds ratios (OR) adjusted for the presence of baseline depression and/or anxiety and/or suicidality were extracted. Data Extraction and Synthesis: Study quality was assessed using the Research Triangle Institute item bank on risk of bias and precision of observational studies. Two reviewers conducted all review stages independently. Selected data were pooled using random-effects meta-analysis. Main Outcomes and Measures: The studies assessing cannabis use and depression at different points from adolescence to young adulthood and reporting the corresponding OR were included. In the studies selected, depression was diagnosed according to the third or fourth editions of Diagnostic and Statistical Manual of Mental Disorders or by using scales with predetermined cutoff points. Results: After screening 3142 articles, 269 articles were selected for full-text review, 35 were selected for further review, and 11 studies comprising 23 317 individuals were included in the quantitative analysis. The OR of developing depression for cannabis users in young adulthood compared with nonusers was 1.37 (95% CI, 1.16-1.62; I2 = 0%). The pooled OR for anxiety was not statistically significant: 1.18 (95% CI, 0.84-1.67; I2 = 42%). The pooled OR for suicidal ideation was 1.50 (95% CI, 1.11-2.03; I2 = 0%), and for suicidal attempt was 3.46 (95% CI, 1.53-7.84, I2 = 61.3%). Conclusions and Relevance: Although individual-level risk remains moderate to low and results from this study should be confirmed in future adequately powered prospective studies, the high prevalence of adolescents consuming cannabis generates a large number of young people who could develop depression and suicidality attributable to cannabis. This is an important public health problem and concern, which should be properly addressed by health care policy.

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3–50, P < 2.14 × 10−6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-d-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach. Whole-exome sequencing identifies ten risk genes for schizophrenia implicated by rare protein-coding variants, a subset of which overlap with risk genes in other neurodevelopmental disorders.

Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen’s d=−0.293; P=1.71 × 10−21), left fusiform gyrus (d=−0.288; P=8.25 × 10−21) and left rostral middle frontal cortex (d=−0.276; P=2.99 × 10−19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.

Abstract Background Our aim was to estimate provisional willingness to receive a coronavirus 2019 (COVID-19) vaccine, identify predictive socio-demographic factors, and, principally, determine potential causes in order to guide information provision. Methods A non-probability online survey was conducted (24th September−17th October 2020) with 5,114 UK adults, quota sampled to match the population for age, gender, ethnicity, income, and region. The Oxford COVID-19 vaccine hesitancy scale assessed intent to take an approved vaccine. Structural equation modelling estimated explanatory factor relationships. Results 71.7% ( n =3,667) were willing to be vaccinated, 16.6% ( n =849) were very unsure, and 11.7% ( n =598) were strongly hesitant. An excellent model fit (RMSEA=0.05/CFI=0.97/TLI=0.97), explaining 86% of variance in hesitancy, was provided by beliefs about the collective importance, efficacy, side-effects, and speed of development of a COVID-19 vaccine. A second model, with reasonable fit (RMSEA=0.03/CFI=0.93/TLI=0.92), explaining 32% of variance, highlighted two higher-order explanatory factors: ‘excessive mistrust’ ( r =0.51), including conspiracy beliefs, negative views of doctors, and need for chaos, and ‘positive healthcare experiences’ ( r =−0.48), including supportive doctor interactions and good NHS care. Hesitancy was associated with younger age, female gender, lower income, and ethnicity, but socio-demographic information explained little variance (9.8%). Hesitancy was associated with lower adherence to social distancing guidelines. Conclusions COVID-19 vaccine hesitancy is relatively evenly spread across the population. Willingness to take a vaccine is closely bound to recognition of the collective importance. Vaccine public information that highlights prosocial benefits may be especially effective. Factors such as conspiracy beliefs that foster mistrust and erode social cohesion will lower vaccine up-take.

BACKGROUND: People with schizophrenia from families that express high levels of criticism, hostility, or over involvement, have more frequent relapses than people with similar problems from families that tend to be less expressive of emotions. Forms of psychosocial intervention, designed to reduce these levels of expressed emotions within families are now widely used. OBJECTIVES: To estimate the effects of family psychosocial interventions in community settings for people with schizophrenia or schizophrenia-like conditions compared to standard care. SEARCH STRATEGY: We updated previous searches by searching The Cochrane Schizophrenia Group's Register (November 2002 and June 2005), searched references of all new included studies for further trial citations, and contacted authors of trials. SELECTION CRITERIA: We selected randomised or quasi-randomised studies focusing primarily on families of people with schizophrenia or schizoaffective disorder that compared community-orientated family-based psychosocial intervention with standard care. DATA COLLECTION AND ANALYSIS: We independently extracted data and calculated fixed effects relative risk (RR), the 95% confidence intervals (CI) for binary data, and, where appropriate, the number needed to treat (NNT) on an intention-to-treat basis. For continuous data, we calculated weighted mean differences (WMD). MAIN RESULTS: This 2005-6 update adds data of 15 additional trials (1765 participants, 43% of the total 4124). Family intervention may decrease the frequency of relapse (n=857, 16 RCTs, RR 0.71 CI 0.6 to 0.8, NNT 8 CI 6 to 11), although some small but negative studies may not have been identified by the search. Family intervention may also reduce hospital admission (8 RCTs, n=481, RR 0.78 CI 0.6 to 1.0, NNT 8 CI 6 to 13)--and this finding is a change to the previous equivocal data reported in 2002. Family intervention may also encourage compliance with medication (n=369, 7 RCTs, RR 0.74 CI 0.6 to 0.9, NNT 7 CI 4 to 19) but does not obviously affect the tendency of individuals/families to drop out of care (n=481, 6 RCTs, RR 0.86 CI 0.5 to 1.4). It may improve general social impairment and the levels of expressed emotion within the family. We did not find data to suggest that family intervention either prevents or promotes suicide. AUTHORS' CONCLUSIONS: Clinicians, researchers, policy makers and recipients of care cannot be confident of the effects of family intervention from the findings of this review. Further data from already completed trials could greatly inform practice and more trials are justified as long as their participants, interventions and outcomes are applicable to routine care.

BACKGROUND: COVID-19 is associated with increased risks of neurological and psychiatric sequelae in the weeks and months thereafter. How long these risks remain, whether they affect children and adults similarly, and whether SARS-CoV-2 variants differ in their risk profiles remains unclear. METHODS: In this analysis of 2-year retrospective cohort studies, we extracted data from the TriNetX electronic health records network, an international network of de-identified data from health-care records of approximately 89 million patients collected from hospital, primary care, and specialist providers (mostly from the USA, but also from Australia, the UK, Spain, Bulgaria, India, Malaysia, and Taiwan). A cohort of patients of any age with COVID-19 diagnosed between Jan 20, 2020, and April 13, 2022, was identified and propensity-score matched (1:1) to a contemporaneous cohort of patients with any other respiratory infection. Matching was done on the basis of demographic factors, risk factors for COVID-19 and severe COVID-19 illness, and vaccination status. Analyses were stratified by age group (age <18 years [children], 18-64 years [adults], and ≥65 years [older adults]) and date of diagnosis. We assessed the risks of 14 neurological and psychiatric diagnoses after SARS-CoV-2 infection and compared these risks with the matched comparator cohort. The 2-year risk trajectories were represented by time-varying hazard ratios (HRs) and summarised using the 6-month constant HRs (representing the risks in the earlier phase of follow-up, which have not yet been well characterised in children), the risk horizon for each outcome (ie, the time at which the HR returns to 1), and the time to equal incidence in the two cohorts. We also estimated how many people died after a neurological or psychiatric diagnosis during follow-up in each age group. Finally, we compared matched cohorts of patients diagnosed with COVID-19 directly before and after the emergence of the alpha (B.1.1.7), delta (B.1.617.2), and omicron (B.1.1.529) variants. FINDINGS: We identified 1 487 712 patients with a recorded diagnosis of COVID-19 during the study period, of whom 1 284 437 (185 748 children, 856 588 adults, and 242 101 older adults; overall mean age 42·5 years [SD 21·9]; 741 806 [57·8%] were female and 542 192 [42·2%] were male) were adequately matched with an equal number of patients with another respiratory infection. The risk trajectories of outcomes after SARS-CoV-2 infection in the whole cohort differed substantially. While most outcomes had HRs significantly greater than 1 after 6 months (with the exception of encephalitis; Guillain-Barré syndrome; nerve, nerve root, and plexus disorder; and parkinsonism), their risk horizons and time to equal incidence varied greatly. Risks of the common psychiatric disorders returned to baseline after 1-2 months (mood disorders at 43 days, anxiety disorders at 58 days) and subsequently reached an equal overall incidence to the matched comparison group (mood disorders at 457 days, anxiety disorders at 417 days). By contrast, risks of cognitive deficit (known as brain fog), dementia, psychotic disorders, and epilepsy or seizures were still increased at the end of the 2-year follow-up period. Post-COVID-19 risk trajectories differed in children compared with adults: in the 6 months after SARS-CoV-2 infection, children were not at an increased risk of mood (HR 1·02 [95% CI 0·94-1·10) or anxiety (1·00 [0·94-1·06]) disorders, but did have an increased risk of cognitive deficit, insomnia, intracranial haemorrhage, ischaemic stroke, nerve, nerve root, and plexus disorders, psychotic disorders, and epilepsy or seizures (HRs ranging from 1·20 [1·09-1·33] to 2·16 [1·46-3·19]). Unlike adults, cognitive deficit in children had a finite risk horizon (75 days) and a finite time to equal incidence (491 days). A sizeable proportion of older adults who received a neurological or psychiatric diagnosis, in either cohort, subsequently died, especially those diagnosed with dementia or epilepsy or seizures. Risk profiles were similar just before versus just after the emergence of the alpha variant (n=47 675 in each cohort). Just after (vs just before) the emergence of the delta variant (n=44 835 in each cohort), increased risks of ischaemic stroke, epilepsy or seizures, cognitive deficit, insomnia, and anxiety disorders were observed, compounded by an increased death rate. With omicron (n=39 845 in each cohort), there was a lower death rate than just before emergence of the variant, but the risks of neurological and psychiatric outcomes remained similar. INTERPRETATION: This analysis of 2-year retrospective cohort studies of individuals diagnosed with COVID-19 showed that the increased incidence of mood and anxiety disorders was transient, with no overall excess of these diagnoses compared with other respiratory infections. In contrast, the increased risk of psychotic disorder, cognitive deficit, dementia, and epilepsy or seizures persisted throughout. The differing trajectories suggest a different pathogenesis for these outcomes. Children have a more benign overall profile of psychiatric risk than do adults and older adults, but their sustained higher risk of some diagnoses is of concern. The fact that neurological and psychiatric outcomes were similar during the delta and omicron waves indicates that the burden on the health-care system might continue even with variants that are less severe in other respects. Our findings are relevant to understanding individual-level and population-level risks of neurological and psychiatric disorders after SARS-CoV-2 infection and can help inform our responses to them. FUNDING: National Institute for Health and Care Research Oxford Health Biomedical Research Centre, The Wolfson Foundation, and MQ Mental Health Research.