Association of symptom severity and cerebrospinal fluid alterations in recent onset psychosis in schizophrenia-spectrum disorders - An individual patient data meta-analysis.

Neuroinflammation and blood-cerebrospinal fluid barrier (BCB) disruption could be key elements in schizophrenia-spectrum disorders(SSDs) etiology and symptom modulation. We present the largest two-stage individual patient data (IPD) meta-analysis, investigating the association of BCB disruption and cerebrospinal fluid (CSF) alterations with symptom severity in first-episode psychosis (FEP) and recent onset psychotic disorder (ROP) individuals, with a focus on sex-related differences. Data was collected from PubMed and EMBASE databases. FEP, ROP and high-risk syndromes for psychosis IPD were included if routine basic CSF-diagnostics were reported. Risk of bias of the included studies was evaluated. Random-effects meta-analyses and mixed-effects linear regression models were employed to assess the impact of BCB alterations on symptom severity. Published (6 studies) and unpublished IPD from n = 531 individuals was included in the analyses. CSF was altered in 38.8 % of individuals. No significant differences in symptom severity were found between individuals with and without CSF alterations (SMD = -0.17, 95 %CI -0.55-0.22, p = 0.341). However, males with elevated CSF/serum albumin ratios or any CSF alteration had significantly higher positive symptom scores than those without alterations (SMD = 0.34, 95 %CI 0.05-0.64, p = 0.037 and SMD = 0.29, 95 %CI 0.17-0.41p = 0.005, respectively). Mixed-effects and simple regression models showed no association (p > 0.1) between CSF parameters and symptomatic outcomes. No interaction between sex and CSF parameters was found (p > 0.1). BCB disruption appears highly prevalent in early psychosis and could be involved in positive symptoms severity in males, indicating potential difficult-to-treat states. This work highlights the need for considering BCB breakdownand sex-related differences in SSDs clinical trials and treatment strategies.

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.

Associations between child maltreatment and hospital admissions for alcohol and other substance use-related disorders up to 40 years of age: Results from the Childhood Adversity and Lifetime Morbidity study.

BACKGROUND AND AIMS: Evidence on the associations between child maltreatment (CM), alcohol use disorders (AUDs) and other substance use disorders (SUDs) comes largely from retrospective studies. These rely on self-reported data, which may be impacted by recall bias. Using prospective CM reports to statutory agencies, we measured associations between CM notifications and inpatient admissions for AUDs and SUDs up to 40 years of age. DESIGN, SETTING AND PARTICIPANTS: Observational study linking administrative health data from Queensland, Australia to prospective birth cohort data comprising both agency-reported and substantiated notifications of CM. MEASUREMENTS: Outcomes were inpatient admissions for AUDs and SUDs based on ICD-10-Australian modification (AM)-coded primary diagnoses. Unadjusted and adjusted logistic regression analyses were undertaken. FINDINGS: Ten per cent (n = 609) of the cohort had a history of agency-reported or substantiated CM notifications before age 15. These individuals had higher adjusted odds of being admitted for AUDs and SUDs. For AUDs, the adjusted odds of inpatient admission were 2.86 [95% confidence interval (CI) = 1.73-4.74] greater where there was any previous agency-reported CM and 3.38 (95% CI = 1.94-5.89) greater where there was any previous substantiated CM. For SUDs, the adjusted odds of inpatient admission were 3.34 (95% CI = 2.42-4.61) greater where there was any previous agency-reported CM and 2.98 (95% CI = 2.04-4.36) greater where there was any previous substantiated CM. CONCLUSIONS: People with a history of child maltreatment appear to have significantly higher odds of inpatient admissions for alcohol use disorders and other substance use disorders up to 40 years of age compared to people with no history of child maltreatment.

Admissions for psychosis following agency-notified child maltreatment at 40-year-follow-up: Results from the Childhood Adversity and Lifetime Morbidity (CALM) cohort.

There is substantial evidence of an association between self-reported child maltreatment (CM) and subsequent psychosis in retrospective data. Such findings may be affected by recall bias. Prospective studies of notifications to statutory agencies address recall bias but are less common and subject to attrition bias. These studies may therefore be underpowered to detect significant associations for some CM types such as sexual abuse. This study therefore linked administrative health data to a large birth cohort that included notifications to child protection agencies. We assessed psychiatric outcomes of CM as measured by inpatient admissions for non-affective psychoses (ICD10 codes F20-F29) to both public and private hospitals in Brisbane, Australia. Follow-up was up to 40 years old. There were 6087 cohort participants whose data could be linked to the administrative health data. Of these, 10.1 % had been the subject of a CM notification. Seventy-two participants (1.2 %) had been admitted for non-affective psychosis by 40-year follow-up. On adjusted analysis, all notified and substantiated types of CM were associated with admissions for non-affective psychosis. This included neglect, physical, sexual or emotional abuse, as well as notifications for multiple CM types. For instance, there was a 2.72-fold increase in admissions following any agency notification (95 % CI = 1.53-4.85). All maltreatment types therefore show a significant association with subsequent admissions for psychosis up to the age of 40. Screening for CM in individuals who present with psychosis is, therefore, indicated, as well as greater awareness that survivors of CM may be at higher risk of developing psychotic symptoms.

Response rates to sequential trials of antipsychotic medications according to algorithms or treatment guidelines in psychotic disorders. A systematic review and meta-analysis.

BACKGROUND: There is a relative lack of research evaluating the outcomes when treatment guidelines or algorithms for psychotic disorders are followed. This systematic review and meta-analysis determined the response rates to antipsychotic medications at different stages of these algorithms and whether these response rates differ in first episode cohorts. METHODS: Data sources: A systematic search strategy was conducted across four databases PubMed, EMBASE, PsycINFO (Ovid) and CINAHL. Studies that had sequential trials of different antipsychotic medications were included. A meta-analysis of proportions was performed using random effects models and sub-group analysis in first episode psychosis studies. RESULTS: Of the 4078 unique articles screened, fourteen articles, from nine unique studies, were eligible and included 2522 participants. The proportion who experienced a response to any antipsychotic in the first stage of an algorithm was 0.53 (95 % C.I.:0.38,0.68) and this decreased to 0.26 (95 % C.I.:0.15,0.39) in the second stage. When clozapine was used in the third stage, the proportion that achieved a response was 0.43 (95 % C.I. 0.19, 0.69) compared to 0.26 (95 % C.I.:0.05,0.54) if a different antipsychotic was used. Four studies included 907 participants with a first episode of psychosis and the proportions that achieved a response were: 1st stage: 0.63 (95 % C.I.: 0.45, 0.79); 2nd stage: 0.34 (95 % C.I.:0.16,0.55); clozapine 3rd stage: 0.45 (95 % C.I.:0.0,0.97), different antipsychotic 3rd stage: 0.15 (95 % C.I.,0.01,0.37). DISCUSSION: These findings support the recommendation to have a trial of clozapine after two other antipsychotic medications have been found to be ineffective.

Inflammatory cerebrospinal fluid markers in schizophrenia spectrum disorders: A systematic review and meta-analysis of 69 studies with 5710 participants.

BACKGROUND: There is increasing evidence of immune dysregulation and neuroinflammation occurring in schizophrenia. The aim of this study is to combine studies on routine CSF parameters, as well as cytokines and inflammatory proteins, in individuals with schizophrenia spectrum disorders. METHODS: CSF parameters were summated and inverse variance meta-analyses using a random effects model were performed comparing mean difference or odds ratios. Between study heterogeneity was assessed using the I2 statistic. Quality assessment and sensitivity analyses were performed. RESULTS: There were 69 studies of 5710 participants, including 3180 individuals with schizophrenia spectrum disorders. Averaged CSF parameters were within normal limits, however, between 3.1 % and 23.5 % of individual cases with schizophrenia spectrum disorders had an abnormal CSF result: Protein (abnormal in 23.5 % cases), albumin (in 18.5 %), presence of oligoclonal bands (in 9.3 %), white blood cell count (in 3.6 %), and IgG levels (3.1 %). Meta-analysis of 55 studies with non-psychiatric controls demonstrated a significant increase in CSF total protein (MD: 3.50, CI: 0.12-6.87), albumin ratio (MD: 0.55, CI: 0.02-0.09), white cell count (MD: 0.25, CI: 0.05-0.46), IL-6 (SMD: 0.53, CI: 0.29 to 0.77) and IL-8 (SMD: 0.56, CI: 0.11 to 1.01). Sensitivity analysis did not alter findings. CONCLUSION: Abnormal CSF parameters, cytokines and inflammatory proteins were found in a significant proportion of individuals with schizophrenia spectrum disorders. This may indicate alterations to blood brain barrier function and permeability, CSF flow dynamics or neuroinflammation. Further research is needed to explore these potential mechanisms.

Associations of the Gut Microbiome With Treatment Resistance in Schizophrenia.

Importance: There is growing interest in the role of gut microbiome composition in schizophrenia. However, lifestyle factors are often neglected, and few studies have investigated microbiome composition in treatment-resistant schizophrenia. Objective: To explore associations between the gut microbiome and schizophrenia diagnosis, treatment resistance, clozapine response, and treatment-related adverse effects while adjusting for demographic and lifestyle factors. Design, Setting, and Participants: In this case-control study of adults aged 20 to 63 years, stool samples and data on demographic characteristics, lifestyle, and medication use were collected and gut microbiome measures obtained using shotgun metagenomics. Participants with a schizophrenia diagnosis were referred through psychiatric inpatient units and outpatient clinics. Data were collected for 4 distinct groups: control individuals without a psychiatric diagnosis (past or present), individuals with treatment-responsive schizophrenia taking nonclozapine antipsychotic medications, clozapine-responsive individuals with treatment-resistant schizophrenia, and clozapine-nonresponsive individuals with treatment-resistant schizophrenia. Participants were recruited between November 2020 and November 2021. Control individuals were recruited in parallel through posters and online advertisements and matched for age, sex, and body mass index (BMI) to the individuals with schizophrenia. Participants were excluded if taking antibiotics in the past 2 months, if unable to communicate in English or otherwise follow study instructions, were pregnant or planning to become pregnant, or had any concomitant disease or condition making them unsuited to the study per investigator assessment. Data were analyzed from January 2022 to March 2023. Main Outcomes and Measures: Omics relationship matrices, α and ß diversity, and relative abundance of microbiome features. Results: Data were collected for 97 individuals (71 [74%] male; mean [SD] age, 40.4 [10.3] years; mean [SD] BMI, 32.8 [7.4], calculated as weight in kilograms divided by height in meters squared). Significant microbiome associations with schizophrenia were observed at multiple taxonomic and functional levels (eg, common species: b2, 30%; SE, 13%; adjusted P = .002) and treatment resistance (eg, common species: b2, 27%; SE, 16%; adjusted P = .03). In contrast, limited evidence was found for microbiome associations with clozapine response, constipation, or metabolic syndrome. Significantly decreased microbial richness was found in individuals with schizophrenia compared to control individuals (t95 = 4.25; P < .001; mean [SD] for control individuals, 151.8 [32.31]; mean [SD] for individuals with schizophrenia, 117.00 [36.2]; 95% CI, 18.6-51.0), which remained significant after a covariate and multiple comparison correction. However, limited evidence was found for differences in ß diversity (weighted UniFrac) for schizophrenia diagnosis (permutational multivariate analysis of variance [PERMANOVA]: R2, 0.03; P = .02), treatment resistance (R2, 0.02; P = .18), or clozapine response (R2, 0.04; P = .08). Multiple differentially abundant bacterial species (19) and metabolic pathways (162) were found in individuals with schizophrenia, which were primarily associated with treatment resistance and clozapine exposure. Conclusions and Relevance: The findings in this study are consistent with the idea that clozapine induces alterations to gut microbiome composition, although the possibility that preexisting microbiome differences contribute to treatment resistance cannot be ruled out. These findings suggest that prior reports of microbiome alterations in individuals with chronic schizophrenia may be due to medication or lifestyle factors and that future studies should incorporate these variables in their design and interpretation.

Evaluating the epidemiology of clozapine-associated neutropenia among people on clozapine across Australia and Aotearoa New Zealand: a retrospective cohort study.

BACKGROUND: Clozapine is associated with the risk of serious neutropenia. However, this risk might decrease over time, meaning that indefinite absolute neutrophil count (ANC) monitoring could be unnecessary. We aimed to determine the epidemiology and timing of clozapine-associated neutropenia outcomes, to investigate variables that might contribute to the odds of neutropenia, and to determine risk of competing neutropenic events during clozapine treatment. METHODS: We performed a retrospective analysis of the Australian and New Zealand Viatris Pharmacovigilance system (one of two monitoring databases for these two countries) between June 6, 1990, and Oct 25, 2022. Patients were excluded from analysis if they commenced clozapine before 1990, did not have a haematology test within 2 weeks of commencement date, or had no follow-up. We measured minor neutropenia (ANC 1·0-1·5 × 109 per L) and serious neutropenia (ANC <1·0 × 109 per L) leading to cessation of clozapine within 6 weeks of the neutropenic event. We determined the rates of minor and serious neutropenia and calculated odds ratios (ORs) for the likelihood of neutropenia leading to cessation. For serious neutropenia leading to cessation, we used time-to-event to calculate rolling weekly averages and to perform competing risk analysis of outcomes using Cox proportional hazards models and a Fine-Gray subdistribution hazards regression model. For the subset of data where information on previous clozapine use was available, we did an analysis for participants who did and did not have previous clozapine exposure. FINDINGS: We included 26 630 people, with 2·6 million ANC values. Within the total cohort, 17 585 people (66%) were male, 9025 (33·9%) female, and 20 (0·1%) other gender, and the mean age was 36·1 years (SD 13·7). We did not have data on race or ethnicity. Of the 26 630 people taking clozapine, 1146 (4·3%) had minor neutropenia, 313 (1·2%) had serious neutropenia leading to cessation, and 223 (0·8%) had serious neutropenia unrelated to clozapine without cessation. In people with no previous exposure to clozapine (n=15 973), the cumulative incidence of serious neutropenia leading to cessation was 0·9% at 18 weeks and 1·4% at 2 years; the weekly incidence rate for serious neutropenia leading to cessation peaked at 9 weeks (0·128%) and fell to a rolling average weekly incidence of 0·001% by 2 years. For minor neutropenia, the cumulative incidence was 1·7% at 18 weeks and 3·5% at 2 years; the weekly incidence rate peaked at 9 weeks (0·218%) and fell to a stable rolling average of 0·01%. The median time to a serious neutropenic event leading to cessation was 17 weeks (IQR 9·96-102). Previous clozapine exposure reduced the risk of serious neutropenia leading to cessation (OR 0·19, 95% CI 0·12-0·31; p <0·0001). INTERPRETATION: Most serious neutropenia leading to clozapine cessation occurs within 18 weeks of treatment and becomes negligible after 2 years. Weekly haematological monitoring after the first 18 weeks could be safely reduced to once every 4 weeks and ceased after 2 years unless clinically indicated. Clozapine retrial after interruption with 2 cumulative years of unremarkable testing might not require further haematological monitoring. A serious neutropenia ANC threshold of ≤1·0 × 109 per L could be used in more jurisdictions. FUNDING: None.

Making meaning of multimorbidity and severe mental illness: A viewpoint.

People living with severe mental illness, such as schizophrenia and bipolar affective disorder, frequently experience poorer physical health compared to those without mental illness. This issue has hitherto been approached through the disease-centred construct of comorbidity, where subsequent conditions are viewed as secondary to an 'index condition'. In contrast, this Viewpoint sets out to explain why multimorbidity, a patient-centred concept that instead refers to the coexistence of multiple chronic illnesses, is a more versatile and robust framework for tackling the issue of poor physical health in people with severe mental illness. In establishing this argument, this Viewpoint has sought to address three key areas. First, this article will discuss the epidemiology of both physical and psychiatric multimorbidity, with respect to how they manifest at greater frequency and at younger ages in people with severe mental illness. Second, the profound consequences of this multimorbidity burden will be explored, with respect to the 'three D's' of death (premature mortality), disability (functional impacts) and deficit (health-economic impacts). Finally, the utility of multimorbidity as a framework will be illustrated through a proposal for a three-dimensional multimorbidity construct composed of (1) quantity, (2) severity and (3) duration of an individual's chronic illnesses. Consequently, this Viewpoint aims to capture why it is necessary for modern psychiatry to grasp the concept of multimorbidity to facilitate holistic healthcare for people living with severe mental illness.

Comprehensive dissection of prevalence rates, sex differences, and blood level-dependencies of clozapine-associated adverse drug reactions.

Clozapine is often underused due to concerns about adverse drug reactions (ADRs) but studies into their prevalences are inconclusive. We therefore comprehensively examined prevalences of clozapine-associated ADRs in individuals with schizophrenia and demographic and clinical factors associated with their occurrence. Data from a multi-center study (n = 698 participants) were collected. The mean number of ADRs during clozapine treatment was 4.8, with 2.4 % of participants reporting no ADRs. The most common ADRs were hypersalivation (74.6 %), weight gain (69.3 %), and increased sleep necessity (65.9 %), all of which were more common in younger participants. Participants with lower BMI prior to treatment were more likely to experience significant weight gain (>10 %). Constipation occurred more frequently with higher clozapine blood levels and doses. There were no differences in ADR prevalence rates between participants receiving clozapine monotherapy and polytherapy. These findings emphasize the high prevalence of clozapine-associated ADRs and highlight several demographic and clinical factors contributing to their occurrence. By understanding these factors, clinicians can better anticipate and manage clozapine-associated ADRs, leading to improved treatment outcomes and patient well-being.

Prevalence of frailty in severe mental illness: findings from the UK Biobank.

BACKGROUND: Severe mental illness (SMI) is associated with significant morbidity. Frailty combines biological ageing, comorbidity and psychosocial factors and can predict adverse health outcomes. Emerging evidence indicates that frailty is higher in individuals with SMI than in the general population, although studies have been limited by sample size. AIMS: To describe the prevalence of frailty in people with SMI in a large cohort using three different frailty measures and examine the impact of demographic and sociodemographic variables. METHOD: The UK Biobank survey data, which included individuals aged 37-73 years from England, Scotland and Wales from 2006 to 2010, with linked in-patient hospital episodes, were utilised. The prevalence of frailty in individuals with and without SMI was assessed through three frailty measures: frailty index, physical frailty phenotype (PFP) and Hospital Frailty Risk Score (HFRS). Stratified analysis and dichotomous logistic regression were conducted. RESULTS: A frailty index could be calculated for 99.5% of the 502 412 UK Biobank participants and demonstrated greater prevalence of frailty in women and an increase with age. The prevalence of frailty for those with SMI was 3.19% (95% CI 3.0-3.4), 4.2% (95% CI 3.8-4.7) and 18% (95% CI 15-23) using the frailty index, PFP and HFRS respectively. The prevalence ratio was between 3 and 18 times higher than in those without SMI. CONCLUSIONS: As a measure, frailty captures the known increase in morbidity associated with SMI and may potentially allow for earlier identification of those who will benefit from targeted interventions.

Pharmacological interventions for antipsychotic-related sialorrhea: a systematic review and network meta-analysis of randomized trials.

Antipsychotic-induced sialorrhea carries a significant burden, but evidence-based treatment guidance is incomplete, warranting network meta-analysis (NMA) of pharmacological interventions for antipsychotic-related sialorrhea. PubMed Central/PsycInfo/Cochrane Central database/Clinicaltrials.gov/WHO-ICTRP and the Chinese Electronic Journal Database (Qikan.cqvip.com) were searched for published/unpublished RCTs of antipsychotic-induced sialorrhea (any definition) in adults, up to 06/12/2023. We assessed global/local inconsistencies, publication bias, risk of bias (RoB2), and confidence in the evidence, conducting subgroup/sensitivity analyses. Co-primary efficacy outcomes were changes in saliva production (standardized mean difference/SMD) and study-defined response (risk ratios/RRs). The acceptability outcome was all-cause discontinuation (RR). Primary nodes were molecules; the mechanism of action (MoA) was secondary. Thirty-four RCTs entered a systematic review, 33 NMA (n = 1958). All interventions were for clozapine-induced sialorrhea in subjects with mental disorders. Regarding individual agents and response, metoclopramide (RR = 3.11, 95% C.I. = 1.39-6.98), cyproheptadine, (RR = 2.76, 95% C.I. = 2.00-3.82), sulpiride (RR = 2.49, 95% C.I. = 1.65-3.77), propantheline (RR = 2.39, 95% C.I. = 1.97-2.90), diphenhydramine (RR = 2.32, 95% C.I. = 1.88-2.86), benzhexol (RR = 2.32, 95% C.I. = 1.59-3.38), doxepin (RR = 2.30, 95% C.I. = 1.85-2.88), amisulpride (RR = 2.23, 95% C.I. = 1.30-3.81), chlorpheniramine (RR = 2.20, 95% C.I. = 1.67-2.89), amitriptyline (RR = 2.09, 95% C.I. = 1.34-3.26), atropine, (RR = 2.03, 95% C.I. = 1.22-3.38), and astemizole, (RR = 1.70, 95% C.I. = 1.28-2.26) outperformed placebo, but not glycopyrrolate or ipratropium. Across secondary nodes (k = 28, n = 1821), antimuscarinics (RR = 2.26, 95% C.I. = 1.91-2.68), benzamides (RR = 2.23, 95% C.I. = 1.75-3.10), TCAs (RR = 2.23, 95% C.I. = 1.83-2.72), and antihistamines (RR = 2.18, 95% C.I. = 1.83-2.59) outperformed placebo. In head-to-head comparisons, astemizole and ipratropium were outperformed by several interventions. All secondary nodes, except benzamides, outperformed the placebo on the continuous efficacy outcome. For nocturnal sialorrhea, neither benzamides nor atropine outperformed the placebo. Active interventions did not differ significantly from placebo regarding constipation or sleepiness/drowsiness. Low-confidence findings prompt caution in the interpretation of the results. Considering primary nodes' co-primary efficacy outcomes and head-to-head comparisons, efficacy for sialorrhea is most consistent for the following agents, decreasing from metoclopramide through cyproheptadine, sulpiride, propantheline, diphenhydramine, benzhexol, doxepin, amisulpride, chlorpheniramine, to amitriptyline, and atropine (the latter not for nocturnal sialorrhea). Shared decision-making with the patient should guide treatment decisions regarding clozapine-related sialorrhea.

Preliminary results from the Australian Genetics of Bipolar Disorder Study: A nation-wide cohort.

OBJECTIVE: The Australian Genetics of Bipolar Disorder Study is a nation-wide cohort of adults living with bipolar disorder. The study aims to detect the relationships between genetic risk, symptom severity, and the lifetime prevalence of bipolar disorder, treatment response and medication side effects, and patterns and costs of health care usage. METHODS: A total of 6682 participants (68.3% female; aged 44.8 ± 13.6 years [range = 18-90]) were recruited in three waves: a nation-wide media campaign, a mail-out based on prescriptions for lithium carbonate and through the Australian Genetics of Depression Study. Participants completed a self-report questionnaire. A total of 4706 (70%) participants provided a saliva sample and were genotyped and 5506 (82%) consented to record linkage of their Pharmaceutical and Medicare Benefits Schedule data. RESULTS: Most participants were living with bipolar I disorder (n = 4068) while 1622 participants were living with bipolar II disorder and 992 with sub-threshold bipolar disorder. The mean age of bipolar disorder diagnosis was 32.7 ± 11.6 years but was younger in bipolar I (p = 2.0E-26) and females (p = 5.7E-23). Excluding depression with onset prior to bipolar disorder diagnosis, 64.5% of participants reported one or more co-occurring psychiatric disorders: most commonly generalised anxiety disorder (43.5%) and posttraumatic stress disorder (20.7%). Adverse drug reactions were common and resulted in discontinuation rates ranging from 33.4% for lithium to 63.0% for carbamazepine. CONCLUSION: Our findings highlight the high rate of comorbidities and adverse drug reactions among adults living with bipolar disorder in the general Australian population. Future genomic analyses focus on identifying genetic variants influencing pharmacotherapy treatment response and side effects.

Comorbidity between major depressive disorder and physical diseases: a comprehensive review of epidemiology, mechanisms and management.

Populations with common physical diseases - such as cardiovascular diseases, cancer and neurodegenerative disorders - experience substantially higher rates of major depressive disorder (MDD) than the general population. On the other hand, people living with MDD have a greater risk for many physical diseases. This high level of comorbidity is associated with worse outcomes, reduced adherence to treatment, increased mortality, and greater health care utilization and costs. Comorbidity can also result in a range of clinical challenges, such as a more complicated therapeutic alliance, issues pertaining to adaptive health behaviors, drug-drug interactions and adverse events induced by medications used for physical and mental disorders. Potential explanations for the high prevalence of the above comorbidity involve shared genetic and biological pathways. These latter include inflammation, the gut microbiome, mitochondrial function and energy metabolism, hypothalamic-pituitary-adrenal axis dysregulation, and brain structure and function. Furthermore, MDD and physical diseases have in common several antecedents related to social factors (e.g., socioeconomic status), lifestyle variables (e.g., physical activity, diet, sleep), and stressful live events (e.g., childhood trauma). Pharmacotherapies and psychotherapies are effective treatments for comorbid MDD, and the introduction of lifestyle interventions as well as collaborative care models and digital technologies provide promising strategies for improving management. This paper aims to provide a detailed overview of the epidemiology of the comorbidity of MDD and specific physical diseases, including prevalence and bidirectional risk; of shared biological pathways potentially implicated in the pathogenesis of MDD and common physical diseases; of socio-environmental factors that serve as both shared risk and protective factors; and of management of MDD and physical diseases, including prevention and treatment. We conclude with future directions and emerging research related to optimal care of people with comorbid MDD and physical diseases.

Reversal learning in those with early psychosis features contingency-dependent changes in loss response and learning.

INTRODUCTION: People with psychotic disorders commonly feature broad decision-making impairments that impact their functional outcomes. Specific associative/reinforcement learning problems have been demonstrated in persistent psychosis. But these phenotypes may differ in early psychosis, suggesting that aspects of cognition decline over time. METHODS: The present proof-of-concept study examined goal-directed action and reversal learning in controls and those with early psychosis. RESULTS: Equivalent performance was observed between groups during outcome-specific devaluation, and reversal learning at an 80:20 contingency (reward probability for high:low targets). But when the low target reward probability was increased (80:40) those with early psychosis altered their response to loss, whereas controls did not. Computational modelling confirmed that in early psychosis there was a change in punishment learning that increased the chance of staying with the same stimulus after a loss, multiple trials into the future. In early psychosis, the magnitude of this response was greatest in those with higher IQ and lower clinical severity scores. CONCLUSIONS: We show preliminary evidence that those with early psychosis present with a phenotype that includes altered responding to loss and hyper-adaptability in response to outcome changes. This may reflect a compensatory response to overcome the milieu of corticostriatal changes associated with psychotic disorders.

An international research agenda for clozapine-resistant schizophrenia.

Treatment-resistant symptoms occur in about a third of patients with schizophrenia and are associated with a substantial reduction in their quality of life. The development of new treatment options for clozapine-resistant schizophrenia constitutes a crucial, unmet need in psychiatry. Additionally, an overview of past and possible future research avenues to optimise the early detection, diagnosis, and management of clozapine-resistant schizophrenia is unavailable. In this Health Policy, we discuss the ongoing challenges associated with clozapine-resistant schizophrenia faced by patients and health-care providers worldwide to improve the understanding of this condition. We then revisit several clozapine guidelines, the diagnostic tests and treatment options for clozapine-resistant schizophrenia, and currently applied research approaches in clozapine-resistant schizophrenia. We also suggest methodologies and targets for future research, divided into innovative nosology-oriented field trials (eg, examining dimensional symptom staging), translational approaches (eg, genetics), epidemiological research (eg, real-world studies), and interventional studies (eg, non-traditional trial designs incorporating lived experiences and caregivers' perspectives). Finally, we note that low-income and middle-income countries are under-represented in studies on clozapine-resistant schizophrenia and propose an agenda to guide multinational research on the cause and treatment of clozapine-resistant schizophrenia. We hope that this research agenda will empower better global representation of patients living with clozapine-resistant schizophrenia and ultimately improve their functional outcomes and quality of life.

Gone Too Soon: priorities for action to prevent premature mortality associated with mental illness and mental distress.

Globally, too many people die prematurely from suicide and the physical comorbidities associated with mental illness and mental distress. The purpose of this Review is to mobilise the translation of evidence into prioritised actions that reduce this inequity. The mental health research charity, MQ Mental Health Research, convened an international panel that used roadmapping methods and review evidence to identify key factors, mechanisms, and solutions for premature mortality across the social-ecological system. We identified 12 key overarching risk factors and mechanisms, with more commonalities than differences across the suicide and physical comorbidities domains. We also identified 18 actionable solutions across three organising principles: the integration of mental and physical health care; the prioritisation of prevention while strengthening treatment; and the optimisation of intervention synergies across social-ecological levels and the intervention cycle. These solutions included accessible, integrated high-quality primary care; early life, workplace, and community-based interventions co-designed by the people they should serve; decriminalisation of suicide and restriction of access to lethal means; stigma reduction; reduction of income, gender, and racial inequality; and increased investment. The time to act is now, to rebuild health-care systems, leverage changes in funding landscapes, and address the effects of stigma, discrimination, marginalisation, gender violence, and victimisation.