Predicting treatment resistance from first-episode psychosis using routinely collected clinical information.

Around a quarter of people who experience a first episode of psychosis (FEP) will develop treatment-resistant schizophrenia (TRS), but there are currently no established clinically useful methods to predict this from baseline. We aimed to explore the predictive potential for clozapine use as a proxy for TRS of routinely collected, objective biomedical predictors at FEP onset, and to externally validate the model in a separate clinical sample of people with FEP. We developed and externally validated a forced-entry logistic regression risk prediction Model fOr cloZApine tReaTment, or MOZART, to predict up to 8-year risk of clozapine use from FEP using routinely recorded information including age, sex, ethnicity, triglycerides, alkaline phosphatase levels, and lymphocyte counts. We also produced a least-absolute shrinkage and selection operator (LASSO) based model, additionally including neutrophil count, smoking status, body mass index, and random glucose levels. The models were developed using data from two UK psychosis early intervention services (EIS) and externally validated in another UK EIS. Model performance was assessed via discrimination and calibration. We developed the models in 785 patients, and validated externally in 1,110 patients. Both models predicted clozapine use well at internal validation (MOZART: C 0.70; 95%CI 0.63,0.76; LASSO: 0.69; 95%CI 0.63,0.77). At external validation, discrimination performance reduced (MOZART: 0.63; 0.58,0.69; LASSO: 0.64; 0.58,0.69) but recovered after re-estimation of the lymphocyte predictor (C: 0.67; 0.62,0.73). Calibration plots showed good agreement between observed and predicted risk in the forced-entry model. We also present a decision-curve analysis and an online data visualisation tool. The use of routinely collected clinical information including blood-based biomarkers taken at FEP onset can help to predict the individual risk of clozapine use, and should be considered equally alongside other potentially useful information such as symptom scores in large-scale efforts to predict psychiatric outcomes.

The psychosis metabolic risk calculator (PsyMetRiC) for young people with psychosis: International external validation and site-specific recalibration in two independent European samples.

Background: Cardiometabolic dysfunction is common in young people with psychosis. Recently, the Psychosis Metabolic Risk Calculator (PsyMetRiC) was developed and externally validated in the UK, predicting up-to six-year risk of metabolic syndrome (MetS) from routinely collected data. The full-model includes age, sex, ethnicity, body-mass index, smoking status, prescription of metabolically-active antipsychotic medication, high-density lipoprotein, and triglyceride concentrations; the partial-model excludes biochemical predictors. Methods: To move toward a future internationally-useful tool, we externally validated PsyMetRiC in two independent European samples. We used data from the PsyMetab (Lausanne, Switzerland) and PAFIP (Cantabria, Spain) cohorts, including participants aged 16-35y without MetS at baseline who had 1-6y follow-up. Predictive performance was assessed primarily via discrimination (C-statistic), calibration (calibration plots), and decision curve analysis. Site-specific recalibration was considered. Findings: We included 1024 participants (PsyMetab n=558, male=62%, outcome prevalence=19%, mean follow-up=2.48y; PAFIP n=466, male=65%, outcome prevalence=14%, mean follow-up=2.59y). Discrimination was better in the full- compared with partial-model (PsyMetab=full-model C=0.73, 95% C.I., 0.68-0.79, partial-model C=0.68, 95% C.I., 0.62-0.74; PAFIP=full-model C=0.72, 95% C.I., 0.66-0.78; partial-model C=0.66, 95% C.I., 0.60-0.71). As expected, calibration plots revealed varying degrees of miscalibration, which recovered following site-specific recalibration. PsyMetRiC showed net benefit in both new cohorts, more so after recalibration. Interpretation: The study provides evidence of PsyMetRiC's generalizability in Western Europe, although further local and international validation studies are required. In future, PsyMetRiC could help clinicians internationally to identify young people with psychosis who are at higher cardiometabolic risk, so interventions can be directed effectively to reduce long-term morbidity and mortality. Funding: NIHR Cambridge Biomedical Research Centre (BRC-1215-20014); The Wellcome Trust (201486/Z/16/Z); Swiss National Research Foundation (320030-120686, 324730- 144064, and 320030-173211); The Carlos III Health Institute (CM20/00015, FIS00/3095, PI020499, PI050427, and PI060507); IDIVAL (INT/A21/10 and INT/A20/04); The Andalusian Regional Government (A1-0055-2020 and A1-0005-2021); SENY Fundacion Research (2005-0308007); Fundacion Marques de Valdecilla (A/02/07, API07/011); Ministry of Economy and Competitiveness and the European Fund for Regional Development (SAF2016-76046-R and SAF2013-46292-R).For the Spanish and French translation of the abstract see Supplementary Materials section.

Peripheral levels of C-reactive protein, tumor necrosis factor-α, interleukin-6, and interleukin-1ß across the mood spectrum in bipolar disorder: A meta-analysis of mean differences and variability.

IMPORTANCE: It is unclear whether differences exist in the magnitude and variability of pro-inflammatory mediators in the different phases of bipolar disorder (BD) and among subjects with BD, as compared to healthy controls. OBJECTIVE: To run a comparative meta-analysis of C-Reactive Protein (CRP), IL-1, IL-6, TNF-α in BD vs healthy controls, measuring mean and variability effects on all subjects. Sensitivity analyses include disease activity. DATA SOURCES: Systematic review of observational studies in PubMed and PsycInfo up to February 2nd, 2020. STUDY SELECTION: Case-control studies reporting inflammatory mediators' levels in BD and controls. DATA EXTRACTION AND SYNTHESIS: Summary distribution measures of circulating CRP, IL-1ß, IL-6, TNF-α in participants with BD and control groups were extracted. Random-effects multivariate meta-analyses were conducted based on individual study/mediator effect sizes (Hedge's g). MAIN OUTCOMES AND MEASURES: Co-primary outcomes were inflammatory mediators' levels (Hedge's g) and variability (coefficient of variance ratio (CVR)) differences between participants with BD across the mood spectrum and controls. RESULTS: Out of the initial 729 papers, 72 were assessed and then excluded after full-text review, and ultimately 53 studies were included in the systematic review, while 49 were included in the meta-analysis. The mean age was 36.96 (SD: 9.29) years, and the mean female percentage was 56.31 (SD: 16.61). CRP (g = 0.70, 95% CI 0.31-1.09, k = 37, BD = 2,215 vs HC = 3,750), IL-6 (g = 0.81, 95% CI 0.46-1.16, k = 45, BD = 1,956 vs HC = 4,106), TNF-α (g = 0.49, 95% CI 0.19-0.78, k = 49, BD = 2,231 vs HC = 3,017) were elevated in subjects with BD vs HC, but not IL-1ß (g = -0.28, 95% CI -0.68-0.12, k = 4, BD = 87 vs HC = 66). When considering euthymic, depressive, and manic episodes separately, CRP and TNF-α were elevated in both depressive and manic episodes, but not in euthymia, while IL-6 remained elevated regardless of the disease state. No difference in CVR emerged for CRP, IL-1ß, and TNF-α, while a lower CVR was observed for IL-6. When considering disease phases, CVR was higher in BD than in HCs for CRP during depressive episodes, lower for IL-6 during euthymia, and higher during manic episodes for CRP, IL-6, and TNF-α. Sensitivity analyses after excluding outliers identified with funnel plot visual inspection, low-quality studies, and considering only studies matched per body mass index confirmed the main results. Meta-regression showed that age (IL-6, TNF-α), gender (CRP), duration of illness (CRP) moderated elevated individual inflammatory levels. CONCLUSIONS AND RELEVANCE: Peripheral pro-inflammatory marker elevations were confirmed in BD. CRP and TNF-α could represent state markers, as they were only elevated during mood episodes, while IL-6 appeared to be a trait marker for BD. Increased variability of specific inflammatory mediators in specific disease active states suggests that a subset of subjects with BD may exhibit elevated inflammation as part of a manic or depressive episode.

Development and external validation of the Psychosis Metabolic Risk Calculator (PsyMetRiC): a cardiometabolic risk prediction algorithm for young people with psychosis.

BACKGROUND: Young people with psychosis are at high risk of developing cardiometabolic disorders; however, there is no suitable cardiometabolic risk prediction algorithm for this group. We aimed to develop and externally validate a cardiometabolic risk prediction algorithm for young people with psychosis. METHODS: We developed the Psychosis Metabolic Risk Calculator (PsyMetRiC) to predict up to 6-year risk of incident metabolic syndrome in young people (aged 16-35 years) with psychosis from commonly recorded information at baseline. We developed two PsyMetRiC versions using the forced entry method: a full model (including age, sex, ethnicity, body-mass index, smoking status, prescription of a metabolically active antipsychotic medication, HDL concentration, and triglyceride concentration) and a partial model excluding biochemical results. PsyMetRiC was developed using data from two UK psychosis early intervention services (Jan 1, 2013, to Nov 4, 2020) and externally validated in another UK early intervention service (Jan 1, 2012, to June 3, 2020). A sensitivity analysis was done in UK birth cohort participants (aged 18 years) who were at risk of developing psychosis. Algorithm performance was assessed primarily via discrimination (C statistic) and calibration (calibration plots). We did a decision curve analysis and produced an online data-visualisation app. FINDINGS: 651 patients were included in the development samples, 510 in the validation sample, and 505 in the sensitivity analysis sample. PsyMetRiC performed well at internal (full model: C 0·80, 95% CI 0·74-0·86; partial model: 0·79, 0·73-0·84) and external validation (full model: 0·75, 0·69-0·80; and partial model: 0·74, 0·67-0·79). Calibration of the full model was good, but there was evidence of slight miscalibration of the partial model. At a cutoff score of 0·18, in the full model PsyMetRiC improved net benefit by 7·95% (sensitivity 75%, 95% CI 66-82; specificity 74%, 71-78), equivalent to detecting an additional 47% of metabolic syndrome cases. INTERPRETATION: We have developed an age-appropriate algorithm to predict the risk of incident metabolic syndrome, a precursor of cardiometabolic morbidity and mortality, in young people with psychosis. PsyMetRiC has the potential to become a valuable resource for early intervention service clinicians and could enable personalised, informed health-care decisions regarding choice of antipsychotic medication and lifestyle interventions. FUNDING: National Institute for Health Research and Wellcome Trust.

Longitudinal association between CRP levels and risk of psychosis: a meta-analysis of population-based cohort studies.

Meta-analyses of cross-sectional studies suggest that patients with psychosis have higher circulating levels of C-reactive protein (CRP) compared with healthy controls; however, cause and effect is unclear. We examined the prospective association between CRP levels and subsequent risk of developing a psychotic disorder by conducting a systematic review and meta-analysis of population-based cohort studies. Databases were searched for prospective studies of CRP and psychosis. We obtained unpublished results, including adjustment for age, sex, body mass index, smoking, alcohol use, and socioeconomic status and suspected infection (CRP > 10 mg/L). Based on random effect meta-analysis of 89,792 participants (494 incident cases of psychosis at follow-up), the pooled odds ratio (OR) for psychosis for participants with high (>3 mg/L), as compared to low (≤3 mg/L) CRP levels at baseline was 1.50 (95% confidence interval [CI], 1.09-2.07). Evidence for this association remained after adjusting for potential confounders (adjusted OR [aOR] = 1.31; 95% CI, 1.03-1.66). After excluding participants with suspected infection, the OR for psychosis was 1.36 (95% CI, 1.06-1.74), but the association attenuated after controlling for confounders (aOR = 1.23; 95% CI, 0.95-1.60). Using CRP as a continuous variable, the pooled OR for psychosis per standard deviation increase in log(CRP) was 1.11 (95% CI, 0.93-1.34), and this association further attenuated after controlling for confounders (aOR = 1.07; 95% CI, 0.90-1.27) and excluding participants with suspected infection (aOR = 1.07; 95% CI, 0.92-1.24). There was no association using CRP as a categorical variable (low, medium or high). While we provide some evidence of a longitudinal association between high CRP (>3 mg/L) and psychosis, larger studies are required to enable definitive conclusions.

Inflammatory markers in depression: A meta-analysis of mean differences and variability in 5,166 patients and 5,083 controls.

IMPORTANCE: The magnitude and variability of cytokine alterations in depression are not clear. OBJECTIVE: To perform an up to date meta-analysis of mean differences of immune markers in depression, and to quantify and test for evidence of heterogeneity in immune markers in depression by conducting a meta-analysis of variability to ascertain whether only a sub-group of patients with depression show evidence of inflammation. DATA SOURCES: Studies that reported immune marker levels in peripheral blood in patients with depression and matched healthy controls in the MEDLINE database from inception to August 29th 2018 were examined. STUDY SELECTION: Case-control studies that reported immune marker levels in peripheral blood in patients with depression and healthy controls were selected. DATA EXTRACTION AND SYNTHESIS: Means and variances (SDs) were extracted for each measure to calculate effect sizes, which were combined using multivariate meta-analysis. MAIN OUTCOMES AND MEASURES: Hedges g was used to quantify mean differences. Relative variability of immune marker measurements in patients compared with control groups as indexed by the coefficient of variation ratio (CVR). RESULTS: A total of 107 studies that reported measurements from 5,166 patients with depression and 5,083 controls were included in the analyses. Levels of CRP (g = 0.71; 95%CI: 0.50-0.92; p < 0.0001); IL-3 (g = 0.60; 95%CI: 0.31-0.89; p < 0.0001); IL-6 (g = 0.61; 95%CI: 0.39-0.82; p < 0.0001); IL-12 (g = 1.18; 95%CI: 0.74-1.62; p < 0.0001); IL-18 (g = 1.97; 95%CI: 1.00-2.95; p < 0.0001); sIL-2R (g = 0.71; 95%CI: 0.44-0.98; p < 0.0001); and TNFα (g = 0.54; 95%CI: 0.32-0.76; p < 0.0001) were significantly higher in patients with depression. These findings were robust to a range of potential confounds and moderators. Mean-scaled variability, measured as CVR, was significantly lower in patients with depression for CRP (CVR = 0.85; 95%CI: 0.75-0.98; p = 0.02); IL-12 (CVR = 0.61; 95%CI: 0.46-0.80; p < 0.01); and sIL-2R (CVR = 0.85; 95%CI: 0.73-0.99; p = 0.04), while it was unchanged for IL-3, IL-6, IL-18, and TNF α. CONCLUSIONS AND RELEVANCE: Depression is confirmed as a pro-inflammatory state. Some of the inflammatory markers elevated in depression, including CRP and IL-12, show reduced variability in patients with depression, therefore supporting greater homogeneity in terms of an inflammatory phenotype in depression. Some inflammatory marker elevations in depression do not appear due to an inflamed sub-group, but rather to a right shift of the immune marker distribution.

Cardiac structure and function in schizophrenia: cardiac magnetic resonance imaging study.

BACKGROUND: Heart disease is the leading cause of death in schizophrenia. However, there has been little research directly examining cardiac function in schizophrenia. AIMS: To investigate cardiac structure and function in individuals with schizophrenia using cardiac magnetic resonance imaging (CMR) after excluding medical and metabolic comorbidity. METHOD: In total, 80 participants underwent CMR to determine biventricular volumes and function and measures of blood pressure, physical activity and glycated haemoglobin levels. Individuals with schizophrenia ('patients') and controls were matched for age, gender, ethnicity and body surface area. RESULTS: Patients had significantly smaller indexed left ventricular (LV) end-diastolic volume (effect size d = -0.82, P = 0.001), LV end-systolic volume (d = -0.58, P = 0.02), LV stroke volume (d = -0.85, P = 0.001), right ventricular (RV) end-diastolic volume (d = -0.79, P = 0.002), RV end-systolic volume (d = -0.58, P = 0.02), and RV stroke volume (d = -0.87, P = 0.001) but unaltered ejection fractions relative to controls. LV concentricity (d = 0.73, P = 0.003) and septal thickness (d = 1.13, P < 0.001) were significantly larger in the patients. Mean concentricity in patients was above the reference range. The findings were largely unchanged after adjusting for smoking and/or exercise levels and were independent of medication dose and duration. CONCLUSIONS: Individuals with schizophrenia show evidence of concentric cardiac remodelling compared with healthy controls of a similar age, gender, ethnicity, body surface area and blood pressure, and independent of smoking and activity levels. This could be contributing to the excess cardiovascular mortality observed in schizophrenia. Future studies should investigate the contribution of antipsychotic medication to these changes.

Cardiac structure and function in patients with schizophrenia taking antipsychotic drugs: an MRI study.

Cardiovascular disease (CVD) is a major cause of excess mortality in schizophrenia. Preclinical evidence shows antipsychotics can cause myocardial fibrosis and myocardial inflammation in murine models, but it is not known if this is the case in patients. We therefore set out to determine if there is evidence of cardiac fibrosis and/or inflammation using cardiac MRI in medicated patients with schizophrenia compared with matched healthy controls. Thirty-one participants (14 patients and 17 controls) underwent cardiac MRI assessing myocardial markers of fibrosis/inflammation, indexed by native myocardial T1 time, and cardiac structure (left ventricular (LV) mass) and function (left/right ventricular end-diastolic and end-systolic volumes, stroke volumes, and ejection fractions). Participants were physically fit, and matched for age, gender, smoking, blood pressure, BMI, HbA1c, ethnicity, and physical activity. Compared with controls, native myocardial T1 was significantly longer in patients with schizophrenia (effect size, d = 0.89; p = 0.02). Patients had significantly lower LV mass, and lower left/right ventricular end-diastolic and stroke volumes (effect sizes, d = 0.86-1.08; all p-values < 0.05). There were no significant differences in left/right end-systolic volumes and ejection fractions between groups (p > 0.05). These results suggest an early diffuse fibro-inflammatory myocardial process in patients that is independent of established CVD-risk factors and could contribute to the excess cardiovascular mortality associated with schizophrenia. Future studies are required to determine if this is due to antipsychotic treatment or is intrinsic to schizophrenia.

A Meta-analysis of Immune Parameters, Variability, and Assessment of Modal Distribution in Psychosis and Test of the Immune Subgroup Hypothesis.

Immune parameters are elevated in psychosis, but it is unclear whether alterations are homogenous across patients or heterogeneity exists, consistent with the hypothesis that immune alterations are specific to a subgroup of patients. To address this, we examine whether antipsychotic-naïve first-episode psychosis patients exhibit greater variability in blood cytokines, C-reactive protein, and white cell counts compared with controls, and if group mean differences persist after adjusting for skewed data and potential confounds. Databases were searched for studies reporting levels of peripheral immune parameters. Means and variances were extracted and analyzed using multivariate meta-analysis of mean and variability of differences. Outcomes were (1) variability in patients relative to controls, indexed by variability ratio (VR) and coefficient of variation ratio (CVR); (2) mean differences indexed by Hedges g; (3) Modal distribution of raw immune parameter data using Hartigan's unimodality dip test. Thirty-five studies reporting on 1263 patients and 1470 controls were included. Variability of interleukin-6 (IL6) (VR = 0.19), tumor necrosis factor-α (TNFα) (VR = 0.36), interleukin-1ß (VR = 0.35), interleukin-4 (VR = 0.55), and interleukin-8 (VR = 0.28) was reduced in patients. Results persisted for IL6 and IL8 after mean-scaling. Ninety-four percent and one hundred percent of raw data were unimodally distributed in psychosis and controls, respectively. Mean levels of IL6 (g = 0.62), TNFα (g = 0.56), interferon-γ (IFNγ) (g = 0.32), transforming growth factor-ß (g = 0.53), and interleukin-17 (IL17) (g = 0.48) were elevated in psychosis. Sensitivity analyses indicated this is unlikely explained by confounders for IL6, IFNγ, and IL17. These findings show elevated cytokines in psychosis after accounting for confounds, and that the hypothesis of an immune subgroup is not supported by the variability or modal distribution.