Prevalence of multimorbidity in people with and without severe mental illness: a systematic review and meta-analysis.

BACKGROUND: People with severe mental illness, such as schizophrenia-spectrum disorder and bipolar disorder, face poorer health outcomes from multiple chronic illnesses. Physical multimorbidity, the coexistence of two or more chronic physical conditions, and psychiatric multimorbidity, the coexistence of three or more psychiatric disorders, are both emerging concepts useful in conceptualising disease burden. However, the prevalence of physical and psychiatric multimorbidity in this cohort is unknown. This study aimed to estimate the absolute prevalence of both physical and psychiatric multimorbidity in people with severe mental illness, and also compare the odds of physical multimorbidity prevalence against people without severe mental illness. METHODS: We searched CINAHL, EMBASE, PubMed, and PsycINFO from inception until Feb 15, 2024, for observational studies that measured multimorbidity prevalence. To be included, studies had to have an observational study design, be conducted in an adult population (mean age ≥18 years) diagnosed with either schizophrenia-spectrum disorder or bipolar disorder, and include a measurement of occurrence of either physical multimorbidity (≥2 physical health conditions) or psychiatric multimorbidity (≥3 psychiatric conditions total, including the severe mental illness). From control studies, a random-effects meta-analysis compared odds of physical multimorbidity between people with and without severe mental illness. Absolute prevalence of physical and psychiatric multimorbidity in people with severe mental illness was also calculated. Sensitivity and meta-regression analyses tested an array of demographic, diagnostic, and methodological variables. FINDINGS: From 11 144 citations we included 82 observational studies featuring 1 623 773 individuals with severe mental illness (specifically schizophrenia-spectrum disorder or bipolar disorder), of which 21 studies featured 13 235 882 control individuals without severe mental illness (descriptive data for the entire pooled cohorts were not available for numbers of males and females, age, and ethnicity). This study did not feature involvement of people with lived experience. The odds ratio (OR) of physical multimorbidity between people with and without severe mental illness was 2·40 (95% CI 1·57-3·65, k=11, p=0·0009). This ratio was higher in younger severe mental illness populations (mean age ≤40 years, OR 3·99, 95% CI 1·43-11·10) compared with older populations (mean age >40 years, OR 1·55, 95% CI 0·96-2·51; subgroup differences p=0·0013). For absolute prevalence, 25% of those with severe mental illness have physical multimorbidity (95% CI 0·19-0·32, k=29) and 14% have psychiatric multimorbidity (95% CI 0·08-0·23, k=21). INTERPRETATION: This is the first meta-analysis to estimate physical alongside psychiatric multimorbidity prevalence, showing that these are common in people with schizophrenia-spectrum disorder and bipolar disorder. The greater burden of physical multimorbidity in people with severe mental illness compared with those without is higher for younger cohorts, reflecting a need for earlier intervention. Our findings speak to the utility of multimorbidity for characterising the disease burden associated with severe mental illness, and the importance of facilitating integrated physical and mental health care. FUNDING: None.

Weight change following diagnosis with psychosis: a retrospective cohort study in Greater Manchester, UK.

INTRODUCTION: Weight gain in the months/years after diagnosis/treatment of severe enduring mental illness (SMI) is a major predictor of future diabetes, dysmetabolic profile and increased risk of cardiometabolic diseases. There is limited data on the longer-term profile of weight change in people with a history of SMI and how this may differ between individuals. We here report a retrospective study on weight change over the 5 years following an SMI diagnosis in Greater Manchester UK, an ethnically and culturally diverse community, with particular focus on comparing non-affective psychosis (NAP) vs affective psychosis (AP) diagnoses. METHODS: We undertook an anonymised search in the Greater Manchester Care Record (GMCR). We reviewed the health records of anyone who had been diagnosed for the first time with first episode psychosis, schizophrenia, schizoaffective disorder, delusional disorder (non-affective psychosis = NAP) or affective psychosis (AP). We analysed body mass index (BMI) change in the 5-year period following the first prescription of antipsychotic medication. All individuals had taken an antipsychotic agent for at least 3 months. The 5-year follow-up point was anywhere between 2003 and 2023. RESULTS: We identified 9125 people with the diagnoses above. NAP (n = 5618; 37.3% female) mean age 49.9 years; AP (n = 4131; 60.5% female) mean age 48.7 years. 27.0% of NAP were of non-White ethnicity vs 17.8% of AP individuals. A higher proportion of people diagnosed with NAP were in the highest quintile of social disadvantage 52.4% vs 39.5% for AP. There were no significant differences in baseline BMI profile. In a subsample with HbA1c data (n = 2103), mean HbA1c was higher in NAP at baseline (40.4 mmol/mol in NAP vs 36.7 mmol/mol for AP). At 5-year follow-up, there was similarity in both the overall % of individuals in the obese ≥ 30 kg/m2 category (39.8% NAP vs 39.7% AP), and % progressing from a normal healthy BMI transitioned to obese/overweight BMI (53.6% of NAP vs 55.6% with AP). 43.7% of those NAP with normal BMI remained at a healthy BMI vs 42.7% with AP. At 5-year follow-up for NAP, 83.1% of those with BMI ≥ 30 kg/m2 stayed in this category vs 81.5% of AP. CONCLUSION: The results of this real-world longitudinal cohort study suggest that the changes in BMI with treatment of non-affective psychosis vs bipolar disorder are not significantly different, while 43% maintain a healthy weight in the first 5 years following antipsychotic prescription.

Does Slow and Steady Win the Race? Rates of Antipsychotic Discontinuation, Antipsychotic Dose, and Risk of Psychotic Relapse.

BACKGROUND: Antipsychotics are recommended for prevention of relapse in schizophrenia. It is unclear whether increased risk of relapse following antipsychotic discontinuation is predominantly associated with an absolute magnitude of dose reduction or rate of antipsychotic reduction. Establishing the responsible mechanism is important because prolonged withdrawal schedules have been suggested to reduce risk of relapse. STUDY DESIGN: Individual patient data from antipsychotic discontinuation studies were obtained. We estimated the occupancy of receptors over time using half-lives and median effective dose ED50 values obtained from pharmacokinetic and receptor occupancy studies. Hazard ratios for relapse events were calculated using Cox proportional hazards models to assess the influence of formulation (oral, 1-monthly, and 3-monthly injections). The change in hazard ratio over time was estimated, and the effect of time-varying covariates was calculated, including rate of occupancy reduction and absolute receptor occupancy. STUDY RESULTS: Five studies including 1388 participants with schizophrenia were identified (k = 2: oral, k = 2: 1-monthly injection, k = 1: 3-monthly injection). Withdrawal of long-acting injectable medication did not lead to a lower hazard ratio compared with withdrawal of oral medication, and this included the period immediately following randomization. Hazard ratios were not associated with the rate of decline of receptor occupancy; however, they were associated with reduced absolute occupancy in trials of long-acting injections (P = .038). CONCLUSIONS: Antipsychotic discontinuation is associated with an increased risk of psychotic relapse, related to receptor occupancy. Although relapse does not appear to be related to the rate of discontinuation, gradual discontinuation strategies may allow for easier antipsychotic reinstatement in case of symptomatic worsening.

Antidepressant and antipsychotic side-effects and personalised prescribing: a systematic review and digital tool development.

BACKGROUND: Side-effects of psychiatric medication impair quality of life and functioning. Furthermore, they contribute to morbidity, mortality, stigma, and poor treatment concordance resulting in relapse of psychiatric illness. Guidelines recommend discussing side-effects with patients when making treatment decisions, but a synthesis of antidepressant and antipsychotic side-effects to guide this process is missing, and considering all side-effects is a complex, multidimensional process. We aimed to create comprehensive databases of antipsychotic and antidepressant side-effects, and a digital tool to support database navigation. METHODS: To create the databases, we did an umbrella review of Embase, PsycINFO, and MEDLINE from database inception to June 26, 2023. We included meta-analyses of randomised controlled trials examining antipsychotic monotherapy in the treatment of schizophrenia or antidepressant monotherapy in the treatment of major depressive disorder. We included meta-analyses in adults (aged ≥18 years) that assessed drugs with a common comparator. The search was complemented by a review of national and international guidelines and consensus statements for the treatment of major depressive disorder and schizophrenia in adults. Effect sizes for antipsychotic and antidepressant side-effects were extracted from meta-analyses examining the largest number of drugs. In cases of incomplete meta-analytic coverage, data were imputed on the basis of guideline-derived ordinal rankings or, if imputation was not possible, ordinal scores were extracted. Both meta-analytic and ordinal outcomes were normalised to provide values between 0 and 1. We then constructed a digital tool, the Psymatik Treatment Optimizer, to combine the side-effect databases with side-effect concerns of an individual user, to enable users to select side-effects of concern and the relative degree of concern for each side-effect. Concern weightings and the side-effect databases are synthesised via a multicriteria decision analysis method (technique for order of preference by similarity to ideal situation, or TOPSIS). FINDINGS: Of 3724 citations, 14 articles containing 68 meta-analyses of individual side-effects met inclusion criteria. After review of 19 guidelines, seven provided ordinal data. Antipsychotic data were extracted from five studies (11 meta-analyses, n=65 594 patients) and four guidelines, and antidepressant data were extracted from three guidelines. The resultant databases included data on 32 antipsychotics (14 side-effects) and 37 antidepressants (nine side-effects). The databases highlighted the clinical dilemma associated with balancing side-effects, with avoidance of one side-effect (eg, weight gain for antipsychotics) increasing the risk of others (eg, akathisia). To aid with this dilemma, the Psymatik Treatment Optimizer synthesises the side-effect databases with individual user-defined concern weights. After computing up to 5851 pairwise comparisons for antidepressants and 5142 pairwise comparisons for antipsychotics, Psymatik ranks treatments in order of preference for the individual user, with the output presented in a heatmap. INTERPRETATION: By facilitating collaborative, personalised, and evidence-based prescribing decisions, the side-effect databases and digital application supports care delivery that is consistent with international regulatory guidance for the treatment of schizophrenia and depression, and it therefore has promise for informing psychiatric practice and improving outcomes. FUNDING: National Institute for Health and Care Research, Maudsley Charity, Wellcome Trust, Medical Research Council.

Variability of glucose, insulin, and lipid disturbances in first-episode psychosis: a meta-analysis.

BACKGROUND: First-episode psychosis (FEP) is associated with metabolic alterations. However, it is not known if there is heterogeneity in these alterations beyond what might be expected due to normal individual differences, indicative of subgroups of patients at greater vulnerability to metabolic dysregulation. METHODS: We employed meta-analysis of variance, indexed using the coefficient of variation ratio (CVR), to compare variability of the following metabolic parameters in antipsychotic naïve FEP and controls: fasting glucose, glucose post-oral glucose tolerance test (OGTT), fasting insulin, insulin resistance, haemoglobin A1c (HbA1c), total-cholesterol, low-density lipoprotein (LDL)-cholesterol, high-density lipoprotein (HDL)-cholesterol, and triglycerides. Standardised mean difference in metabolic parameters between groups was also calculated; meta-regression analyses examined physiological/demographic/psychopathological moderators of metabolic change. RESULTS: Twenty-eight studies were analysed (1716 patients, 1893 controls). Variability of fasting glucose [CVR = 1.32; 95% confidence interval (CI) 1.12-1.55; p = 0.001], glucose post-OGTT (CVR = 1.43; 95% CI 1.10-1.87; p = 0.008), fasting insulin (CVR = 1.31; 95% CI 1.09-1.58; p = 0.01), insulin resistance (CVR = 1.34; 95% CI 1.12-1.60; p = 0.001), HbA1c (CVR = 1.18; 95% CI 1.06-1.27; p < 0.0001), total-cholesterol (CVR = 1.15; 95% CI 1.01-1.31; p = 0.03), LDL-cholesterol (CVR = 1.28; 95% CI 1.09-1.50; p = 0.002), and HDL-cholesterol (CVR = 1.15; 95% CI 1.00-1.31; p < 0.05), but not triglycerides, was greater in patients than controls. Mean glucose, glucose post-OGTT, fasting insulin, insulin resistance, and triglycerides were greater in patients; mean total-cholesterol and HDL-cholesterol were reduced in patients. Increased symptom severity and female sex were associated with worse metabolic outcomes. CONCLUSIONS: Patients with FEP present with greater variability in metabolic parameters relative to controls, consistent with a subgroup of patients with more severe metabolic changes compared to others. Understanding determinants of metabolic variability could help identify patients at-risk of developing metabolic syndrome. Female sex and severe psychopathology are associated with poorer metabolic outcomes, with implications for metabolic monitoring in clinical practice.

Data-Driven Taxonomy for Antipsychotic Medication: A New Classification System.

BACKGROUND: Globally, there are more than 25 licensed antipsychotic medications. Antipsychotics are commonly described as either typical or atypical, but this dichotomous classification does not reflect the diversity of their pharmacological and clinical profiles. There is a need for a data-driven antipsychotic classification scheme suitable for clinicians and researchers that maps onto both pharmacological and clinical effects. Receptor affinity provides one starting point for such a scheme. METHODS: We analyzed affinities of 27 antipsychotics for 42 receptors from 3325 in vitro receptor binding studies. We used a clustering algorithm to group antipsychotics based on receptor affinity. Using a machine learning model, we examined the ability of this grouping to predict antipsychotic-induced clinical effects quantified according to an umbrella review of clinical trial and treatment guideline data. RESULTS: Clustering resulted in 4 groups of antipsychotics. The predominant receptor affinity and clinical effect "fingerprints" of these 4 groups were defined as follows: group 1, muscarinic (M2-M5) receptor antagonism (cholinergic and metabolic side effects); group 2, dopamine (D2) partial agonism and adrenergic antagonism (overall low side-effect burden); group 3, serotonergic and dopaminergic antagonism (overall moderate side-effect burden); and group 4, dopaminergic antagonism (extrapyramidal side effects and hyperprolactinemia). Groups 1 and 4 were more efficacious than groups 2 and 3. The classification was shown to predict out-of-sample clinical effects of individual drugs. CONCLUSIONS: A receptor affinity-based grouping not only reflects compound pharmacology but also detects meaningful clinical differences. This approach has the potential to benefit both patients and researchers by guiding treatment and informing drug development.

Prolactin and morning cortisol concentrations in antipsychotic naïve first episode psychosis: A systematic review and meta-analysis.

IMPORTANCE: Alterations in prolactin and cortisol levels have been reported in antipsychotic naïve patients with first episode psychosis (FEP). However, it has been studied in very small samples, and inter-group variability has never been studied before. OBJECTIVE: To provide estimates of standardized mean differences (SMD) and inter-group variability for prolactin, cortisol awakening response (CAR) and morning cortisol concentrations in antipsychotic naïve FEP (AN-FEP) patients and healthy controls (HC). DATA SOURCES: BIOSIS, KCI, MEDLINE, Russian Science Citation Index, SciELO, Cochrane, PsycINFO, Web of Science were searched from inception to February 28, 2022. STUDY SELECTION: Peer-reviewed cohort studies that reported on prolactin or cortisol blood concentrations in AN- FEP patients and HC were included. DATA EXTRACTION AND SYNTHESIS: Study characteristics, means and standard deviations (SD) were extracted from each article. Inter group differences in magnitude of effect were estimated using Hedges g. Inter-group variability was estimated with the coefficient of variation ratio (CVR). In both cases estimates were pooled using random-effects meta-analysis. Differences by study-level characteristics were estimated using meta-regression. PRISMA guideline was followed (No. CRD42022303555). MAIN OUTCOMES AND MEASURES: Prolactin, CAR and morning cortisol blood concentrations in AN-FEP group in relation to HC group. RESULTS: Fourteen studies for prolactin (N = 761 for AN-FEP group, N = 687 for HC group) and twelve studies for morning cortisol (N = 434 for AN-FEP group, N = 528 for HC group) were included. No studies were found in CAR in AN-FEP patients. Mean SMD for prolactin blood concentration was 0.88 (95% CI 0.57, 1.20) for male and 0.56 (95% CI 0.26, 0.87) for female. As a group, AN-FEP presented greater inter-group variability for prolactin levels than HC (CVR=1.28, 95% CI 1.02, 1.62). SMD for morning cortisol concentrations was non-significant: 0.34 (95% CI -0.01, 0.69) and no inter-group variability significant differences were detected: CVR= 1.05 (95% CI 0.91, 1.20). Meta-regression analyses for age and quality were non-significant. Funnel plots did not suggest a publication bias. CONCLUSIONS AND RELEVANCE: Increased prolactin levels were found in AN-FEP patients. A greater inter-group variability in the AN-FEP group suggests the existence of patient subgroups with different prolactin levels. No significant abnormalities were found in morning cortisol levels. Further research is needed to clarify whether prolactin concentrations could be used as an illness biomarker.

Effect of polygenic risk for schizophrenia on cardiac structure and function: a UK Biobank observational study.

BACKGROUND: Cardiovascular disease is a major cause of excess mortality in people with schizophrenia. Several factors are responsible, including lifestyle and metabolic effects of antipsychotics. However, variations in cardiac structure and function are seen in people with schizophrenia in the absence of cardiovascular disease risk factors and after accounting for lifestyle and medication. Therefore, we aimed to explore whether shared genetic causes contribute to these cardiac variations. METHODS: For this observational study, we used data from the UK Biobank and included White British or Irish individuals without diagnosed schizophrenia with variable polygenic risk scores for the condition. To test the association between polygenic risk score for schizophrenia and cardiac phenotype, we used principal component analysis and regression. Robust regression was then used to explore the association between the polygenic risk score for schizophrenia and individual cardiac phenotypes. We repeated analyses with fibro-inflammatory pathway-specific polygenic risk scores for schizophrenia. Last, we investigated genome-wide sharing of common variants between schizophrenia and cardiac phenotypes using linkage disequilibrium score regression. The primary outcome was principal component regression. FINDINGS: Of 33 353 individuals recruited, 32 279 participants had complete cardiac MRI data and were included in the analysis, of whom 16 625 (51·5%) were female and 15 654 (48·5%) were male. 1074 participants were excluded on the basis of incomplete cardiac MRI data (for all phenotypes). A model regressing polygenic risk scores for schizophrenia onto the first five cardiac principal components of the principal components analysis was significant (F=5·09; p=0·00012). Principal component 1 captured a pattern of increased cardiac volumes, increased absolute peak diastolic strain rates, and reduced ejection fractions; polygenic risk scores for schizophrenia and principal component 1 were negatively associated (ß=-0·01 [SE 0·003]; p=0·017). Similar to the principal component analysis results, for individual cardiac phenotypes, we observed negative associations between polygenic risk scores for schizophrenia and indexed right ventricular end-systolic volume (ß=-0·14 [0·04]; p=0·0013, pFDR=0·015), indexed right ventricular end-diastolic volume (ß=-0·17 [0·08]); p=0·025; pFDR=0·082), and absolute longitudinal peak diastolic strain rates (ß=-0·01 [0·003]; p=0·0024, pFDR=0·015), and a positive association between polygenic risk scores for schizophrenia and right ventricular ejection fraction (ß=0·09 [0·03]; p=0·0041, pFDR=0·015). Models examining the transforming growth factor-ß (TGF-ß)-specific and acute inflammation-specific polygenic risk scores for schizophrenia found significant associations with the first five principal components (F=2·62, p=0·022; F=2·54, p=0·026). Using linkage disequilibrium score regression, we observed genetic overlap with schizophrenia for right ventricular end-systolic volume and right ventricular ejection fraction (p=0·0090, p=0·0077). INTERPRETATION: High polygenic risk scores for schizophrenia are associated with decreased cardiac volumes, increased ejection fractions, and decreased absolute peak diastolic strain rates. TGF-ß and inflammatory pathways might be implicated, and there is evidence of genetic overlap for some cardiac phenotypes. Reduced absolute peak diastolic strain rates indicate increased myocardial stiffness and diastolic dysfunction, which increases risk of cardiac disease. Thus, genetic risk for schizophrenia is associated with cardiac structural changes that can worsen cardiac outcomes. Further work is required to determine whether these associations are specific to schizophrenia or are also seen in other psychiatric conditions. FUNDING: National Institute for Health Research, Maudsley Charity, Wellcome Trust, Medical Research Council, Academy of Medical Sciences, Edmond J Safra Foundation, British Heart Foundation.

Brain glucose metabolism in schizophrenia: a systematic review and meta-analysis of 18FDG-PET studies in schizophrenia.

BACKGROUND: Impaired brain metabolism may be central to schizophrenia pathophysiology, but the magnitude and consistency of metabolic dysfunction is unknown. METHODS: We searched MEDLINE, PsychINFO and EMBASE between 01/01/1980 and 13/05/2021 for studies comparing regional brain glucose metabolism using 18FDG-PET, in schizophrenia/first-episode psychosis v. controls. Effect sizes (Hedges g) were pooled using a random-effects model. Primary measures were regional absolute and relative CMRGlu in frontal, temporal, parietal and occipital lobes, basal ganglia and thalamus. RESULTS: Thirty-six studies (1335 subjects) were included. Frontal absolute glucose metabolism (Hedge's g = -0.74 ± 0.54, p = 0.01; I2 = 67%) and metabolism relative to whole brain (g = -0.44 ± 0.34, p = 0.01; I2 = 55%) were lower in schizophrenia v. controls with moderate heterogeneity. Absolute frontal metabolism was lower in chronic (g = -1.18 ± 0.73) v. first-episode patients (g = -0.09 ± 0.88) and controls. Medicated patients showed frontal hypometabolism relative to controls (-1.04 ± 0.26) while metabolism in drug-free patients did not differ significantly from controls. There were no differences in parietal, temporal or occipital lobe or thalamic metabolism in schizophrenia v. controls. Excluding outliers, absolute basal ganglia metabolism was lower in schizophrenia v. controls (-0.25 ± 0.24, p = 0.049; I2 = 5%). Studies identified reporting voxel-based morphometry measures of absolute 18FDG uptake (eight studies) were also analysed using signed differential mapping analysis, finding lower 18FDG uptake in the left anterior cingulate gyrus (Z = -4.143; p = 0.007) and the left inferior orbital frontal gyrus (Z = -4.239; p = 0.02) in schizophrenia. CONCLUSIONS: We report evidence for hypometabolism with large effect sizes in the frontal cortex in schizophrenia without consistent evidence for alterations in other brain regions. Our findings support the hypothesis of hypofrontality in schizophrenia.

The association between N-methyl-d-aspartate receptor availability and glutamate levels: A multi-modal PET-MR brain imaging study in first-episode psychosis and healthy controls.

BACKGROUND: Evidence from post-mortem studies and in vivo imaging studies suggests there may be reduced N-methyl-d-aspartate receptor (NMDAR) levels in the hippocampus in patients with schizophrenia. Other studies have reported increased glutamate in striatum in schizophrenia patients. It has been hypothesised that NMDAR hypofunction leads to the disinhibition of glutamatergic signalling; however, this has not been tested in vivo. METHODS: In this study, we investigated the relationship between hippocampal NMDAR and striatal glutamate using simultaneous positron emission tomography-magnetic resonance (PET-MR) imaging. We recruited 40 volunteers to this cross-sectional study; 21 patients with schizophrenia, all in their first episode of illness, and 19 healthy controls. We measured hippocampal NMDAR availability using the PET ligand [18F]GE179. This was indexed relative to whole brain as the distribution volume ratio (DVR). Striatal glutamatergic indices (glutamate and Glx) were acquired simultaneously, using combined PET-MR proton magnetic resonance spectroscopy (1H-MRS). RESULTS: A total of 33 individuals (15 healthy controls, 18 patients) were included in the analyses (mean (SD) age of controls, 27.31 (4.68) years; mean (SD) age of patients, 24.75 (4.33), 27 male and 6 female). We found an inverse relationship between hippocampal DVR and striatal glutamate levels in people with first-episode psychosis (rho = -0.74, p < 0.001) but not in healthy controls (rho = -0.22, p = 0.44). CONCLUSION: This study show that lower relative NMDAR availability in the hippocampus may drive increased striatal glutamate levels in patients with schizophrenia. Further work is required to determine whether these findings may yield new targets for drug development in schizophrenia.

Reappraising the variability of effects of antipsychotic medication in schizophrenia: a meta-analysis.

It is common experience for practising psychiatrists that individuals with schizophrenia vary markedly in their symptomatic response to antipsychotic medication. What is not clear, however, is whether this variation reflects variability of medication-specific effects (also called "treatment effect heterogeneity"), as opposed to variability of non-specific effects such as natural symptom fluctuation or placebo response. Previous meta-analyses found no evidence of treatment effect heterogeneity, suggesting that a "one size fits all" approach may be appropriate and that efforts at developing personalized treatment strategies for schizophrenia are unlikely to succeed. Recent advances indicate, however, that earlier approaches may have been unable to accurately quantify treatment effect heterogeneity due to their neglect of a key parameter: the correlation between placebo response and medication-specific effects. In the present paper, we address this shortcoming by using individual patient data and study-level data to estimate that correlation and quantitatively characterize antipsychotic treatment effect heterogeneity in schizophrenia. Individual patient data (on 384 individuals who were administered antipsychotic treatment and 88 who received placebo) were obtained from the Yale University Open Data Access (YODA) database. Study-level data were obtained from a meta-analysis of 66 clinical trials including 17,202 patients. Both individual patient and study-level analyses yielded a negative correlation between placebo response and treatment effect for the total score on the Positive and Negative Syndrome Scale (PANSS) (ρ=-0.32, p=0.002 and ρ=-0.39, p<0.001, respectively). Using the most conservative of these estimates, a meta-analysis of treatment effect heterogeneity provided evidence of a marked variability in antipsychotic-specific effects between individuals with schizophrenia, with the top quartile of patients experiencing beneficial treatment effects of 17.7 points or more on the PANSS total score, while the bottom quartile presented a detrimental effect of treatment relative to placebo. This evidence of clinically meaningful treatment effect heterogeneity suggests that efforts to personalize antipsychotic treatment of schizophrenia have potential for success.

Real-world clinical and cost-effectiveness of community clozapine initiation: mirror cohort study.

BACKGROUND: Clozapine is the only drug licensed for treatment-resistant schizophrenia (TRS) but the real-world clinical and cost-effectiveness of community initiation of clozapine is unclear. AIMS: The aim was to assess the feasibility and cost-effectiveness of community initiation of clozapine. METHOD: This was a naturalistic study of community patients recommended for clozapine treatment. RESULTS: Of 158 patients recommended for clozapine treatment, 88 (56%) patients agreed to clozapine initiation and, of these, 58 (66%) were successfully established on clozapine. The success rate for community initiation was 65.4%; which was not significantly different from that for in-patient initiation (58.82%, χ2(1,88) = 0.47, P = 0.49). Following clozapine initiation, there was a significant reduction in median out-patient visits over 1 year (from 24.00 (interquartile range (IQR) = 14.00-41.00) to 13.00 visits (IQR = 5.00-24.00), P < 0.001), and 2 years (from 47.50 visits (IQR = 24.75-71.00) to 22.00 (IQR = 11.00-42.00), P < 0.001), and a 74.71% decrease in psychiatric hospital bed days (z = -2.50, P = 0.01). Service-use costs decreased (1 year: -£963/patient (P < 0.001); 2 years: -£1598.10/patient (P < 0.001). Subanalyses for community-only initiation also showed significant cost reductions (1 year: -£827.40/patient (P < 0.001); 2 year: -£1668.50/patient (P < 0.001) relative to costs prior to starting clozapine. Relative to before initiation, symptom severity was improved in patients taking clozapine at discharge (median Positive and Negative Syndrome Scale total score: initial visit: 80 (IQR = 71.00-104.00); discharge visit 50.5 (IQR = 44.75-75.00), P < 0.001) and at 2 year follow-up (Health of Nation Outcome Scales total score median initial visit: 13.00 (IQR = 9.00-15.00); 2 year follow-up: 8.00 (IQR = 3.00-13.00), P = 0.023). CONCLUSIONS: These findings indicate that community initiation of clozapine is feasible and is associated with significant reductions in costs, service use and symptom severity.

Half a century of research on antipsychotics and schizophrenia: A scientometric study of hotspots, nodes, bursts, and trends.

Changes over 50 years of research on antipsychotics in schizophrenia have occurred. A scientometric synthesis of such changes over time and a measure of researchers' networks and scientific productivity is currently lacking. We searched Web of Science Core Collection from inception until November 5, 2021, using the appropriate key. Our primary objective was to conduct systematic mapping with CiteSpace to show how clusters of keywords have evolved over time and obtain clusters' structure and credibility. Our secondary objective was to measure research network performance (countries, institutions, and authors) using CiteSpace, VOSviewer, and Bibliometrix. We included 32,240 studies published between 1955 and 2021. The co-cited reference network identified 25 clusters with a well-structured network (Q=0.8166) and highly credible clustering (S=0.91). The main trends of research were: 1) antipsychotic efficacy; 2) cognition in schizophrenia; 3) side effects of antipsychotics. Last five years research trends were: 'ultra-resistance schizophrenia' (S=0.925), 'efficacy/dose-response' (S=0.775), 'evidence-synthesis' (S=0.737), 'real-world effectiveness' (S=0.794), 'cannabidiol' (S=0.989), and 'gut microbiome' (S=0.842). These results can inform funding agencies and research groups' future directions.

Treatment resistance in psychiatry: state of the art and new directions.

Treatment resistance affects 20-60% of patients with psychiatric disorders; and is associated with increased healthcare burden and costs up to ten-fold higher relative to patients in general. Whilst there has been a recent increase in the proportion of psychiatric research focussing on treatment resistance (R2 = 0.71, p < 0.0001), in absolute terms this is less than 1% of the total output and grossly out of proportion to its prevalence and impact. Here, we provide an overview of treatment resistance, considering its conceptualisation, assessment, epidemiology, impact, and common neurobiological models. We also review new treatments in development and future directions. We identify 23 consensus guidelines on its definition, covering schizophrenia, major depressive disorder, bipolar affective disorder, and obsessive compulsive disorder (OCD). This shows three core components to its definition, but also identifies heterogeneity and lack of criteria for a number of disorders, including panic disorder, post-traumatic stress disorder, and substance dependence. We provide a reporting check-list to aid comparisons across studies. We consider the concept of pseudo-resistance, linked to poor adherence or other factors, and provide an algorithm for the clinical assessment of treatment resistance. We identify nine drugs and a number of non-pharmacological approaches being developed for treatment resistance across schizophrenia, major depressive disorder, bipolar affective disorder, and OCD. Key outstanding issues for treatment resistance include heterogeneity and absence of consensus criteria, poor understanding of neurobiology, under-investment, and lack of treatments. We make recommendations to address these issues, including harmonisation of definitions, and research into the mechanisms and novel interventions to enable targeted and personalised therapeutic approaches.

Adipose tissue dysfunction, inflammation, and insulin resistance: alternative pathways to cardiac remodelling in schizophrenia. A multimodal, case-control study.

Cardiovascular diseases are the leading cause of death in schizophrenia. Patients with schizophrenia show evidence of concentric cardiac remodelling (CCR), defined as an increase in left-ventricular mass over end-diastolic volumes. CCR is a predictor of cardiac disease, but the molecular pathways leading to this in schizophrenia are unknown. We aimed to explore the relevance of hypertensive and non-hypertensive pathways to CCR and their potential molecular underpinnings in schizophrenia. In this multimodal case-control study, we collected cardiac and whole-body fat magnetic resonance imaging (MRI), clinical measures, and blood levels of several cardiometabolic biomarkers known to potentially cause CCR from individuals with schizophrenia, alongside healthy controls (HCs) matched for age, sex, ethnicity, and body surface area. Of the 50 participants, 34 (68%) were male. Participants with schizophrenia showed increases in cardiac concentricity (d = 0.71, 95% CI: 0.12, 1.30; p = 0.01), indicative of CCR, but showed no differences in overall content or regional distribution of adipose tissue compared to HCs. Despite the cardiac changes, participants with schizophrenia did not demonstrate activation of the hypertensive CCR pathway; however, they showed evidence of adipose dysfunction: adiponectin was reduced (d = -0.69, 95% CI: -1.28, -0.10; p = 0.02), with evidence of activation of downstream pathways, including hypertriglyceridemia, elevated C-reactive protein, fasting glucose, and alkaline phosphatase. In conclusion, people with schizophrenia showed adipose tissue dysfunction compared to body mass-matched HCs. The presence of non-hypertensive CCR and a dysmetabolic phenotype may contribute to excess cardiovascular risk in schizophrenia. If our results are confirmed, acting on this pathway could reduce cardiovascular risk and resultant life-years lost in people with schizophrenia.

Increased rates of respiratory disease in schizophrenia: A systematic review and meta-analysis including 619,214 individuals with schizophrenia and 52,159,551 controls.

INTRODUCTION: Despite respiratory disease being a major cause of excess mortality in people with schizophrenia, the prevalence of respiratory conditions in this population is poorly defined. A systematic review and meta-analysis were conducted to establish the prevalence and association of respiratory diseases in people with schizophrenia. MATERIAL AND METHODS: Major electronic databases were searched from inception to 27 April 2020 for articles reporting respiratory disease (asthma, chronic obstructive pulmonary disease [COPD], pneumonia, and tuberculosis) in people with schizophrenia and, where possible, a control group. A random-effects meta-analysis was conducted. The study was registered with PROSPERO (CRD42018115137). RESULTS: Of 1569 citations, 21 studies consisting of 619,214 individuals with schizophrenia and 52,159,551 controls were included in the meta-analysis. Compared to the general population, people with schizophrenia had significantly higher rates of COPD (odds ratio [OR]: 1.82, 95% CI: 1.28-2.57), asthma (OR: 1.70, 95% CI: 1.02-2.83), and pneumonia (OR: 2.62, 95% CI: 1.10-6.23). In people with schizophrenia, the prevalence of COPD was 7.7% (95% CI: 4.0-14.4), asthma 7.5% (95% CI: 4.9-11.3), pneumonia 10.3% (95% CI 5.4-18.6), and tuberculosis 0.3% (95% CI 0.1 -0.8). After adjusting for publication bias, the prevalence of COPD increased to 19.9% (95% CI: 9.6-36.7). DISCUSSION: All respiratory diseases examined were significantly more prevalent in people with schizophrenia compared with the general population. Future studies should focus on improving the prevention and management of respiratory disease in this group to reduce associated excess mortality.

N-methyl-D-aspartate receptor availability in first-episode psychosis: a PET-MR brain imaging study.

N-methyl-D-aspartate receptor (NMDAR) hypofunction is hypothesised to underlie psychosis but this has not been tested early in illness. To address this, we studied 40 volunteers (21 patients with first-episode psychosis and 19 matched healthy controls) using PET imaging with an NMDAR selective ligand, [18F]GE-179, that binds to the ketamine binding site to index its distribution volume ratio (DVR) and volume of distribution (VT). Hippocampal DVR, but not VT, was significantly lower in patients relative to controls (p = 0.02, Cohen's d = 0.81; p = 0.15, Cohen's d = 0.49), and negatively associated with total (rho = -0.47, p = 0.04), depressive (rho = -0.67, p = 0.002), and general symptom severity (rho = -0.74, p < 0.001). Exploratory analyses found no significant differences in other brain regions (anterior cingulate cortex, thalamus, striatum and temporal cortex). These findings are consistent with the NMDAR hypofunction hypothesis and identify the hippocampus as a key locus for relative NMDAR hypofunction, although further studies should test specificity and causality.

Psychophysiological stress-reactivity in clinical and non-clinical voice-hearers.

BACKGROUND: Psychosis is associated with dysregulation of psychophysiological stress-reactivity, including in subjective, autonomic nervous system (ANS) and hypothalamic-pituitary-adrenal (HPA) parameters. AIMS: This study investigated whether dysregulated psychophysiological stress-reactivity is specifically associated with auditory verbal hallucinations (AVHs) or psychosis more generally by comparing voice-hearers with and without a need for care. METHOD: Clinical (n = 20) and non-clinical voice-hearers (n = 23), as well as a healthy control group with no voices (n = 23), were compared on HPA and ANS responses, and subjective reactivity, to a psychophysiological stress paradigm, the socially evaluative cold pressor test. RESULTS: Measures of HPA function in both clinical and non-clinical voice-hearers diverged from non-voice-hearing controls. Clinical participants showed a blunted peak response compared to both non-clinical groups (p = 0.02), whilst non-clinical voice-hearers showed, at trend-level, reduced cortisol levels during stress exposure compared to both clinical voice-hearers (p = 0.07) and healthy controls (p = 0.07), who unexpectedly did not differ from each other (p = 0.97). Clinical participants showed greater subjective stress levels than both non-clinical groups (p < 0.001), as well as greater anticipatory stress (p = 0.001) and less recovery. There were no differences between groups on parameters of the ANS (all p > 0.05). CONCLUSIONS: Dysregulated psychophysiological stress-function is present in clinical voice-hearers, and partially discriminates them from non-clinical voice-hearers. Overall, the present findings identified specific potential psychophysiological markers of risk and resilience in auditory verbal hallucinations and need for care.