Metabolic syndrome after childhood trauma: a 9-year longitudinal analysis.

BACKGROUND: Childhood trauma (CT) has been cross-sectionally associated with metabolic syndrome (MetS), a group of biological risk factors for cardiometabolic disease. Longitudinal studies, while rare, would clarify the development of cardiometabolic dysregulations over time. Therefore, we longitudinally investigated the association of CT with the 9-year course of MetS components. METHODS: Participants (N = 2958) from the Netherlands Study of Depression and Anxiety were assessed four times across 9 years. The CT interview retrospectively assessed childhood emotional neglect and physical, emotional, and sexual abuse. Metabolic outcomes encompassed continuous MetS components (waist circumference, triglycerides, high-density lipoprotein [HDL] cholesterol, blood pressure [BP], and glucose) and count of clinically elevated MetS components. Mixed-effects models estimated sociodemographic- and lifestyle-adjusted longitudinal associations of CT with metabolic outcomes over time. Time interactions evaluated change in these associations. RESULTS: CT was reported by 49% of participants. CT was consistently associated with increased waist (b = 0.32, s.e. = 0.10, p = 0.001), glucose (b = 0.02, s.e. = 0.01, p < 0.001), and count of MetS components (b = 0.04, s.e. = 0.01, p < 0.001); and decreased HDL cholesterol (b = -0.01, s.e.<0.01, p = .020) and systolic BP (b = -0.33, s.e. = 0.13, p = 0.010). These associations were mainly driven by severe CT and unaffected by lifestyle. Only systolic BP showed a CT-by-time interaction, where CT was associated with lower systolic BP initially and with higher systolic BP at the last follow-up. CONCLUSIONS: Over time, adults with CT have overall persistent poorer metabolic outcomes than their non-maltreated peers. Individuals with CT have an increased risk for cardiometabolic disease and may benefit from monitoring and early interventions targeting metabolism.

Variability and magnitude of brain glutamate levels in schizophrenia: a meta and mega-analysis.

Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan's unimodality dip test). MEDLINE and EMBASE databases were searched from inception to September 2022 for proton magnetic resonance spectroscopy (1H-MRS) studies reporting glutamate, glutamine or Glx in schizophrenia. 123 studies reporting on 8256 patients and 7532 controls were included. Compared with controls, patients demonstrated greater variability in glutamatergic metabolites in the medial frontal cortex (MFC, glutamate: CVR = 0.15, p < 0.001; glutamine: CVR = 0.15, p = 0.003; Glx: CVR = 0.11, p = 0.002), dorsolateral prefrontal cortex (glutamine: CVR = 0.14, p = 0.05; Glx: CVR = 0.25, p < 0.001) and thalamus (glutamate: CVR = 0.16, p = 0.008; Glx: CVR = 0.19, p = 0.008). Studies in younger, more symptomatic patients were associated with greater variability in the basal ganglia (BG glutamate with age: z = -0.03, p = 0.003, symptoms: z = 0.007, p = 0.02) and temporal lobe (glutamate with age: z = -0.03, p = 0.02), while studies with older, more symptomatic patients associated with greater variability in MFC (glutamate with age: z = 0.01, p = 0.02, glutamine with symptoms: z = 0.01, p = 0.02). For individual patient data, most studies showed a unimodal distribution of glutamatergic metabolites. Meta-analysis of mean differences found lower MFC glutamate (g = -0.15, p = 0.03), higher thalamic glutamine (g = 0.53, p < 0.001) and higher BG Glx in patients relative to controls (g = 0.28, p < 0.001). Proportion of males was negatively associated with MFC glutamate (z = -0.02, p < 0.001) and frontal white matter Glx (z = -0.03, p = 0.02) in patients relative to controls. Patient PANSS total score was positively associated with glutamate SMD in BG (z = 0.01, p = 0.01) and temporal lobe (z = 0.05, p = 0.008). Further research into the mechanisms underlying greater glutamatergic metabolite variability in schizophrenia and their clinical consequences may inform the identification of patient subgroups for future treatment strategies.

Sleep disorders in a naturalistic cohort of Dutch psychiatric outpatients: prevalence rates and associations with psychopathology symptom severity and well-being.

Sleep problems are very common in individuals with a mental disorder. Given the abundant evidence indicating the negative impact of disturbed sleep on mental health outcome, insight into the prevalence of all types of sleep disorders in specific mental disorders and neurodevelopmental conditions is of practical importance. Therefore, we estimated the prevalence of six types of sleep disorders with the Holland Sleep Disorders Questionnaire in an overall mental health sample (n = 1082) and separately for different mental and neurodevelopmental conditions. Furthermore, associations between specific sleep disorders, psychopathology and well-being were studied. The impact of the total number of sleep disorders on these associations was examined. Overall, 46.2% of all participants scored above the cut-off for having a sleep disorder. Specifically, 26.8% scored on insomnia, 12.1% on sleep breathing disorders, 9.7% on hypersomnia, 13.7% on circadian rhythm sleep-wake disorders, 11.2% on parasomnia, and 17.9% on sleep-related movement disorders. Most sleep disorders were associated with greater severity of psychopathology and lower well-being. These associations got stronger with an increasing number of sleep disorders. Our study revealed higher suspected prevalence of most sleep disorders in a mental disorder sample compared to the general population. Moreover, the presence of sleep disorder(s) was strongly associated with symptom severity and reduced well-being. These findings extend the notion that early detection and treatment of sleep disorders in mental health populations is essential for psychiatric outcome.

Association of CYP2D6 and CYP2C19 metabolizer status with switching and discontinuing antidepressant drugs: an exploratory study.

BACKGROUND: Tailoring antidepressant drugs (AD) to patients' genetic drug-metabolism profile is promising. However, literature regarding associations of ADs' treatment effect and/or side effects with drug metabolizing genes CYP2D6 and CYP2C19 has yielded inconsistent results. Therefore, our aim was to longitudinally investigate associations between CYP2D6 (poor, intermediate, and normal) and CYP2C19 (poor, intermediate, normal, and ultrarapid) metabolizer-status, and switching/discontinuing of ADs. Next, we investigated whether the number of perceived side effects differed between metabolizer statuses. METHODS: Data came from the multi-site naturalistic longitudinal cohort Netherlands Study of Depression and Anxiety (NESDA). We selected depression- and/or anxiety patients, who used AD at some point in the course of the 9 years follow-up period (n = 928). Medication use was followed to assess patterns of AD switching/discontinuation over time. CYP2D6 and CYP2C19 alleles were derived using genome-wide data of the NESDA samples and haplotype data from the PharmGKB database. Logistic regression analyses were conducted to investigate the association of metabolizer status with switching/discontinuing ADs. Mann-Whitney U-tests were conducted to compare the number of patient-perceived side effects between metabolizer statuses. RESULTS: No significant associations were observed of CYP metabolizer status with switching/discontinuing ADs, nor with the number of perceived side effects. CONCLUSIONS: We found no evidence for associations between CYP metabolizer statuses and switching/discontinuing AD, nor with side effects of ADs, suggesting that metabolizer status only plays a limited role in switching/discontinuing ADs. Additional studies with larger numbers of PM and UM patients are needed to further determine the potential added value of pharmacogenetics to guide pharmacotherapy.

Shaping tomorrow's support: baseline clinical characteristics predict later social functioning and quality of life in schizophrenia spectrum disorder.

PURPOSE: We aimed to explore the multidimensional nature of social inclusion (mSI) among patients diagnosed with schizophrenia spectrum disorder (SSD), and to identify the predictors of 3-year mSI and the mSI prediction using traditional and data-driven approaches. METHODS: We used the baseline and 3-year follow-up data of 1119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) cohort in the Netherlands. The outcome mSI was defined as clusters derived from combined analyses of thirteen subscales from the Social Functioning Scale and the brief version of World Health Organization Quality of Life questionnaires through K-means clustering. Prediction models were built through multinomial logistic regression (ModelMLR) and random forest (ModelRF), internally validated via bootstrapping and compared by accuracy and the discriminability of mSI subgroups. RESULTS: We identified five mSI subgroups: "very low (social functioning)/very low (quality of life)" (8.58%), "low/low" (12.87%), "high/low" (49.24%), "medium/high" (18.05%), and "high/high" (11.26%). The mSI was robustly predicted by a genetic predisposition for SSD, premorbid adjustment, positive, negative, and depressive symptoms, number of met needs, and baseline satisfaction with the environment and social life. The ModelRF (61.61% [54.90%, 68.01%]; P =0.013) was cautiously considered outperform the ModelMLR (59.16% [55.75%, 62.58%]; P =0.994). CONCLUSION: We introduced and distinguished meaningful subgroups of mSI, which were modestly predictable from baseline clinical characteristics. A possibility for early prediction of mSI at the clinical stage may unlock the potential for faster and more impactful social support that is specifically tailored to the unique characteristics of the mSI subgroup to which a given patient belongs.

Cardiovascular risk assessment methods yield unequal risk predictions: a large cross-sectional study in psychiatric secondary care outpatients.

BACKGROUND: Patients with a mental illness are more likely to develop, and die from, cardiovascular diseases (CVD), necessitating optimal CVD-risk (CVR)-assessment to enable early detection and treatment. Whereas psychiatrists use the metabolic syndrome (MetS)-concept to estimate CVR, GPs use absolute risk-models. Additionally, two PRIMROSE-models have been specifically designed for patients with severe mental illness. We aimed to assess the agreement in risk-outcomes between these CVR-methods. METHODS: To compare risk-outcomes across the various CVR-methods, we used somatic information of psychiatric outpatients from the PHAMOUS-, and MOPHAR-database, aged 40-70 years, free of past or current CVD and diabetes. We investigated: (1) the degree-of-agreement between categorical assessments (i.e. MetS-status vs. binary risk-categories); (2) non-parametric correlations between the number of MetS-criteria and absolute risks; and (3) strength-of-agreement between absolute risks. RESULTS: Seven thousand twenty-nine measurements of 3509 PHAMOUS-patients, and 748 measurements of 748 MOPHAR-patients, were included. There was systematic disagreement between the categorical CVR-assessments (all p < 0.036). Only MetS-status versus binary Framingham-assessment had a fair strength-of-agreement (κ = 0.23-0.28). The number of MetS-criteria and Framingham-scores, as well as MetS-criteria and PRIMROSE lipid-scores, showed a moderate-strong correlation (τ = 0.25-0.34). Finally, only the continuous PRIMROSE desk and lipid-outcomes showed moderate strength-of-agreement (ρ = 0.91). CONCLUSIONS: The varying methods for CVR-assessment yield unequal risk predictions, and, consequently, carry the risk of significant disparities regarding treatment initiation in psychiatric patients. Considering the significantly increased health-risks in psychiatric patients, CVR-models should be recalibrated to the psychiatric population from adolescence onwards, and uniformly implemented by health care providers. TRIAL REGISTRATION: The MOPHAR research has been prospectively registered with the Netherlands Trial Register on 19th of November 2014 (NL4779).

Pharmacological treatment for psychotic depression.

BACKGROUND: Evidence is limited regarding the most effective pharmacological treatment for psychotic depression: monotherapy with an antidepressant, monotherapy with an antipsychotic, another treatment (e.g. mifepristone), or combination of an antidepressant plus an antipsychotic. This is an update of a review first published in 2005 and last updated in 2015. OBJECTIVES: 1. To compare the clinical efficacy of pharmacological treatments for patients with an acute psychotic depression: antidepressant monotherapy, antipsychotic monotherapy, mifepristone monotherapy, and the combination of an antidepressant plus an antipsychotic versus placebo and/or each other. 2. To assess whether differences in response to treatment in the current episode are related to non-response to prior treatment. SEARCH METHODS: A search of the Cochrane Central Register of Controlled Trials (CENTRAL), in the Cochrane Library; the Cochrane Common Mental Disorders Controlled Trials Register (CCMDCTR); Ovid MEDLINE (1950-); Embase (1974-); and PsycINFO (1960-) was conducted on 21 February 2020. Reference lists of all included studies and related reviews were screened and key study authors contacted. SELECTION CRITERIA: All randomised controlled trials (RCTs) that included participants with acute major depression with psychotic features, as well as RCTs consisting of participants with acute major depression with or without psychotic features, that reported separately on the subgroup of participants with psychotic features. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed risk of bias in the included studies, according to criteria from the Cochrane Handbook for Systematic Reviews of Interventions. Data were entered into RevMan 5.1. We used intention-to-treat data. Primary outcomes were clinical response for efficacy and overall dropout rate for harm/tolerance. Secondary outcome were remission of depression, change from baseline severity score, quality of life, and dropout rate due to adverse effects. For dichotomous efficacy outcomes (i.e. response and overall dropout), risk ratios (RRs) with 95% confidence intervals (CIs) were calculated.  Regarding the primary outcome of harm, only overall dropout rates were available for all studies. If the study did not report any of the response criteria as defined above, remission as defined here could be used as an alternative. For continuously distributed outcomes, it was not possible to extract data from the RCTs.  MAIN RESULTS: The search identified 3947 abstracts, but only 12 RCTs with a total of 929 participants could be included in the review. Because of clinical heterogeneity, few meta-analyses were possible. The main outcome was reduction in severity (response) of depression, not of psychosis. For depression response, we found no evidence of a difference between antidepressant and placebo (RR 8.40, 95% CI 0.50 to 142.27; participants = 27, studies = 1; very low-certainty evidence) or between antipsychotic and placebo (RR 1.13, 95% CI 0.74 to 1.73; participants = 201, studies = 2; very low-certainty evidence). Furthermore, we found no evidence of a difference in overall dropouts with antidepressant (RR 1.24, 95% CI 0.34 to 4.51; participants = 27, studies = 1; very low-certainty evidence) or antipsychotic monotherapy (RR 0.79, 95% CI 0.57 to 1.08; participants = 201, studies = 2; very low-certainty evidence). No evidence suggests a difference in depression response (RR 2.09, 95% CI 0.64 to 6.82; participants = 36, studies = 1; very low-certainty evidence) or overall dropouts (RR 1.79, 95% CI 0.18 to 18.02; participants = 36, studies = 1; very low-certainty evidence) between antidepressant and antipsychotic. For depression response, low- to very low-certainty evidence suggests that the combination of an antidepressant plus an antipsychotic may be more effective than antipsychotic monotherapy (RR 1.83, 95% CI 1.40 to 2.38; participants = 447, studies = 4), more effective than antidepressant monotherapy (RR 1.42, 95% CI 1.11 to 1.80; participants = 245, studies = 5), and more effective than placebo (RR 1.86, 95% CI 1.23 to 2.82; participants = 148, studies = 2). Very low-certainty evidence suggests no difference in overall dropouts between the combination of an antidepressant plus an antipsychotic versus antipsychotic monotherapy (RR 0.79, 95% CI 0.63 to 1.01; participants = 447, studies = 4), antidepressant monotherapy (RR 0.91, 95% CI 0.55 to 1.50; participants = 245, studies = 5), or placebo alone (RR 0.75, 95% CI 0.48 to 1.18; participants = 148, studies = 2). No study measured change in depression severity from baseline, quality of life, or dropouts due to adverse events. We found no RCTs with mifepristone that fulfilled our inclusion criteria. Risk of bias is considerable: we noted differences between studies with regards to diagnosis, uncertainties around randomisation and allocation concealment, treatment interventions (pharmacological differences between various antidepressants and antipsychotics), and outcome criteria. AUTHORS' CONCLUSIONS: Psychotic depression is heavily under-studied, limiting confidence in the conclusions drawn. Some evidence indicates that combination therapy with an antidepressant plus an antipsychotic is more effective than either treatment alone or placebo. Evidence is limited for treatment with an antidepressant alone or with an antipsychotic alone. Evidence for efficacy of mifepristone is lacking.

The development and evaluation of a computerized decision aid for the treatment of psychotic disorders.

BACKGROUND: Routinely monitoring of symptoms and medical needs can improve the diagnostics and treatment of medical problems, including psychiatric. However, several studies show that few clinicians use Routine Outcome Monitoring (ROM) in their daily work. We describe the development and first evaluation of a ROM based computerized clinical decision aid, Treatment-E-Assist (TREAT) for the treatment of psychotic disorders. The goal is to generate personalized treatment recommendations, based on international guidelines combined with outcomes of mental and physical health acquired through ROM. We present a pilot study aimed to assess the feasibility of this computerized clinical decision aid in daily clinical practice by evaluating clinicians' experiences with the system. METHODS: Clinical decision algorithms were developed based on international schizophrenia treatment guidelines and the input of multidisciplinary expert panels from multiple psychiatric institutes. Yearly obtained diagnostic (ROM) information of patients was presented to treating clinicians combined with treatment suggestions generated by the algorithms of TREAT. In this pilot study 6 clinicians and 16 patients of Lentis Psychiatric Institute used the application. Clinicians were interviewed and asked to fill out self-report questionnaires evaluating their opinions about ROM and the effectiveness of TREAT. RESULTS: Six clinicians and 16 patients with psychotic disorders participated in the pilot study. The clinicians were psychiatrists, physicians and nurse-practitioners which all worked at least 8 years in mental health care of which at least 3 years treating patients with psychotic illnesses. All Clinicians found TREAT easy to use and would like to continue using the application. They reported that TREAT offered support in using diagnostic ROM information when drafting the treatment plans, by creating more awareness of current treatment options. CONCLUSION: This article presents a pilot study on the implementation of a computerized clinical decision aid linking routine outcome monitoring to clinical guidelines in order to generate personalized treatment advice. TREAT was found to be feasible for daily clinical practice and effective based on this first evaluation by clinicians. However, adjustments have to be made to the system and algorithms of the application. The ultimate goal is to provide appropriate evidence based care for patients with severe mental illnesses.

Brain network dysregulation, emotion, and complaints after mild traumatic brain injury.

OBJECTIVES: To assess the role of brain networks in emotion regulation and post-traumatic complaints in the sub-acute phase after non-complicated mild traumatic brain injury (mTBI). EXPERIMENTAL DESIGN: Fifty-four patients with mTBI (34 with and 20 without complaints) and 20 healthy controls (group-matched for age, sex, education, and handedness) were included. Resting-state fMRI was performed at four weeks post-injury. Static and dynamic functional connectivity were studied within and between the default mode, executive (frontoparietal and bilateral frontal network), and salience network. The hospital anxiety and depression scale (HADS) was used to measure anxiety (HADS-A) and depression (HADS-D). PRINCIPAL OBSERVATIONS: Regarding within-network functional connectivity, none of the selected brain networks were different between groups. Regarding between-network interactions, patients with complaints exhibited lower functional connectivity between the bilateral frontal and salience network compared to patients without complaints. In the total patient group, higher HADS-D scores were related to lower functional connectivity between the bilateral frontal network and both the right frontoparietal and salience network, and to higher connectivity between the right frontoparietal and salience network. Furthermore, whereas higher HADS-D scores were associated with lower connectivity within the parietal midline areas of the bilateral frontal network, higher HADS-A scores were related to lower connectivity within medial prefrontal areas of the bilateral frontal network. CONCLUSIONS: Functional interactions of the executive and salience networks were related to emotion regulation and complaints after mTBI, with a key role for the bilateral frontal network. These findings may have implications for future studies on the effect of psychological interventions.

Do routine outcome monitoring results translate to clinical practice? A cross-sectional study in patients with a psychotic disorder.

BACKGROUND: The use of Routine Outcome Monitoring (ROM) in mental health care has increased widely during the past decade. Little is known, however, on the implementation and applicability of ROM outcome in daily clinical practice. In the Netherlands, an extensive ROM-protocol for patients with psychotic disorders has been implemented over the last years (ROM-Phamous). The current study investigated to what extent ROM results translate to daily clinical practice. Therefore, we investigated whether clinical problems as identified with ROM were detected and used in the treatment of patients with psychotic disorders. METHODS: Out of the ROM database of 2010 (n = 1040), a random sample of 100 patients diagnosed with a psychotic disorder was drawn. ROM-data used in this study included a physical examination, laboratory tests, interviews and self-report questionnaires. Based on these data, the prevalence of positive and negative symptoms, psychosocial problems and cardiovascular risk factors was determined. Next, we investigated whether these problems, as identified with ROM, were reflected in the treatment plans of patients, as an indication of the use of ROM in clinical practice. RESULTS: The sample consisted of 63 males and 37 females. The mean age was 44 and the mean duration of illness was 17.7 years. The prevalence of positive and negative symptoms, psychosocial problems and cardiovascular risk factors ranged from 11 to 86 %. In the majority of cases, problems as identified with ROM were not reflected in the treatment plans of patients. CONCLUSIONS: We found a substantial discrepancy between the ROM measurements and the treatment plans, i.e. low rates of detection of symptoms, psychosocial problems and cardiovascular risk factors in the treatment plans, even though these problems were identified with ROM. The opposite occurred as well, where problems were reflected in the treatment plans but not identified with ROM. Thus, ROM and daily clinical practice appear to be two separate processes, whereas ideally they should be integrated. Strong efforts should be made to integrate ROM and consequent treatment activities. Such integration may help to provide patients with adequate and customized care and simultaneously minimize under- and over-treatment.

High persistence and low treatment rates of metabolic syndrome in patients with mood and anxiety disorders: A naturalistic follow-up study.

BACKGROUND: Patients with affective and anxiety disorders are at risk of metabolic syndrome (MetS) and, consequently, cardiovascular disease and premature death. In this study, the course and treatment of MetS was investigated using longitudinal data from a naturalistic sample of affective- and anxiety-disordered outpatients (Monitoring Outcome of psychiatric PHARmacotherapy [MOPHAR]). METHODS: Demographics, clinical characteristics, medication use, and MetS components were obtained for n = 2098 patients at baseline and, in a FU-subsample of n = 507 patients, after a median follow-up (FU) of 11 months. Furthermore, pharmacological treatment rates of MetS were investigated at baseline and FU. Finally, demographic and clinical determinants of change in MetS (component) scores were investigated. RESULTS: At baseline, 34.6 % of n = 2098 patients had MetS, 41.4 % of whom received treatment. Of patients with persisting MetS, 46.1 % received treatment for one (or more) MetS component(s) at baseline, and 56.6 % received treatment at FU. Treatment rates of solely elevated blood pressure and reduced HDL-cholesterol did significantly, but modestly, improve. Higher age, male sex, smoking behavior, low education, diabetes, and depressive versus anxiety disorder were predictors of worse outcome at FU on at least one MetS component. LIMITATIONS: We did not have data on lifestyle interventions as a form of treatment, which might partly have explained the observed low pharmacotherapeutic treatment rates. CONCLUSION: MetS (components) show high persistence rates in affective- and anxiety-disordered patients, and are, despite adequate monitoring, undertreated over time. This indicates that adherence and implementation of monitoring protocols should be crucially improved in psychiatric outpatients in secondary care.

Effects of right prefrontal theta-burst transcranial magnetic stimulation or transcranial direct current stimulation on apathy in patients with schizophrenia: A multicenter RCT.

Apathy is a core negative symptom associated with an unfavorable functional outcome. Noninvasive brain stimulation has shown promise in the treatment of schizophrenia but has not been tested specifically for apathy. We conducted a randomized controlled trial of intermittent theta-burst (iTBS) transcranial magnetic stimulation and transcranial direct current stimulation (tDCS) targeted at the right dorsolateral prefrontal cortex (DLPFC) in patients diagnosed with a psychotic disorder suffering from apathy. The study was a multicenter, randomized, placebo-controlled, and rater-blinded trial. Patients (N = 88) were randomized into active iTBS, active tDCS, sham iTBS or sham tDCS treatment, daily for two weeks (excluding weekends). Effects were measured post-treatment and at four week and ten week follow-up. Primary outcome was apathy severity (Apathy Evaluation Scale, clinician-rated). Additional measures included assessment of negative symptoms, depression, anhedonia and quality of life. No significant difference in improvement of apathy or negative symptoms was observed for real versus sham treatment with either iTBS or tDCS, though all groups improved to a small extent. We conclude that two weeks of brain stimulation over the right DLPFC with either iTBS or tDCS is not effective for improving apathy or negative symptoms. Longer and more intensive protocols may yield different results.

The Progress and Pitfalls of Pharmacogenetics-Based Precision Medicine in Schizophrenia Spectrum Disorders: A Systematic Review and Meta-Analysis.

The inadequate efficacy and adverse effects of antipsychotics severely affect the recovery of patients with schizophrenia spectrum disorders (SSD). We report the evidence for associations between pharmacogenetic (PGx) variants and antipsychotics outcomes, including antipsychotic response, antipsychotic-induced weight/BMI gain, metabolic syndrome, antipsychotic-related prolactin levels, antipsychotic-induced tardive dyskinesia (TD), clozapine-induced agranulocytosis (CLA), and drug concentration level (pharmacokinetics) in SSD patients. Through an in-depth systematic search in 2010-2022, we identified 501 records. We included 29 meta-analyses constituting pooled data from 298 original studies over 69 PGx variants across 39 genes, 4 metabolizing phenotypes of CYP2D9, and 3 of CYP2C19. We observed weak unadjusted nominal significant (p < 0.05) additive effects of PGx variants of DRD1, DRD2, DRD3, HTR1A, HTR2A, HTR3A, and COMT (10 variants) on antipsychotic response; DRD2, HTR2C, BDNF, ADRA2A, ADRB3, GNB3, INSIG2, LEP, MC4R, and SNAP25 (14 variants) on weight gain; HTR2C (one variant) on metabolic syndrome; DRD2 (one variant) on prolactin levels; COMT and BDNF (two variants) on TD; HLA-DRB1 (one variant) on CLA; CYP2D6 (four phenotypes) and CYP2C19 (two phenotypes) on antipsychotics plasma levels. In the future, well-designed longitudinal naturalistic multi-center PGx studies are needed to validate the effectiveness of PGx variants in antipsychotic outcomes before establishing any reproducible PGx passport in clinical practice.

Effects of an eating club for people with a psychotic disorder on personal recovery: Results of a randomized controlled trial.

BACKGROUND AND OBJECTIVES: Many people with a psychotic disorder are coping with severe psychosocial limitations related to their illness. The current randomized controlled trial (RCT) investigates the effects of an eating club intervention (HospitalitY (HY)) aimed to improve personal and societal recovery. METHODS: In 15 biweekly sessions participants received individual home-based skill training and guided peer support sessions in groups of three participants from a trained nurse. A multi-center RCT was conducted (intended sample size: n = 84; n = 7 per block) in patients with a diagnosis of schizophrenia spectrum receiving community treatment. HospitalitY was compared to a Waiting List Control (WLC) condition at three time points (baseline, end-of-treatment (8 months) and follow-up (12 months)) using personal recovery as primary outcome and loneliness, social support, self-stigma, self-esteem, social skills, (social) functioning, independency competence, and psychopathology as secondary outcomes. Outcomes were evaluated with a mixed modeling statistical procedure. RESULTS: The HY-intervention had no significant effects on personal recovery or secondary outcomes. More attendance was associated with higher scores on social functioning. LIMITATIONS: With N = 43 participants included, power was insufficient. Seven HY-groups were started, from which three discontinued before the sixth meeting, one HY group stopped due the start of the COVID-19 pandemic. CONCLUSIONS: Despite a promising pilot study on feasibility, the current RCT did not show any effects of the HY intervention. A mixed qualitative-quantitative research methods might be more appropriate for researching the HospitalitY-intervention to investigate what social and cognitive processes are at play in this peer guided social intervention.

Deep Clinical Phenotyping of Schizophrenia Spectrum Disorders Using Data-Driven Methods: Marching towards Precision Psychiatry.

Heterogeneity is the main challenge in the traditional classification of mental disorders, including schizophrenia spectrum disorders (SSD). This can be partly attributed to the absence of objective diagnostic criteria and the multidimensional nature of symptoms and their associated factors. This article provides an overview of findings from the Genetic Risk and Outcome of Psychosis (GROUP) cohort study on the deep clinical phenotyping of schizophrenia spectrum disorders targeting positive and negative symptoms, cognitive impairments and psychosocial functioning. Three to four latent subtypes of positive and negative symptoms were identified in patients, siblings and controls, whereas four to six latent cognitive subtypes were identified. Five latent subtypes of psychosocial function-multidimensional social inclusion and premorbid adjustment-were also identified in patients. We discovered that the identified subtypes had mixed profiles and exhibited stable, deteriorating, relapsing and ameliorating longitudinal courses over time. Baseline positive and negative symptoms, premorbid adjustment, psychotic-like experiences, health-related quality of life and PRSSCZ were found to be the strong predictors of the identified subtypes. Our findings are comprehensive, novel and of clinical interest for precisely identifying high-risk population groups, patients with good or poor disease prognosis and the selection of optimal intervention, ultimately fostering precision psychiatry by tackling diagnostic and treatment selection challenges pertaining to heterogeneity.

Association of clinical symptoms and cardiometabolic dysregulations in patients with schizophrenia spectrum disorders.

BACKGROUND: Patients with schizophrenia spectrum disorders (SSD) have a shortened life expectancy related to cardiovascular diseases. We investigated the association of cognitive, positive, and negative symptoms with cardiometabolic dysregulations in SSD patients. METHODS: Overall, 1,119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) study were included. Cognitive function, positive and negative symptoms were assessed at baseline, 3-year, and 6-year. Cardiometabolic biomarkers were measured at 3-year follow-up. We used linear and multinomial logistic regression models to test the association between cardiometabolic biomarkers and clinical trajectories and performed mediation analyzes, while adjusting for clinical and demographic confounders. RESULTS: Cognitive performance was inversely associated with increased body mass index (mean difference [ß], ßhigh = -1.24, 95% CI = -2.28 to 0.20, P = 0.02) and systolic blood pressure (ßmild = 2.74, 95% CI = 0.11 to 5.37, P = 0.04). The severity of positive symptoms was associated with increased glycated hemoglobin (HbA1c) levels (ßlow = -2.01, 95% CI = -3.21 to -0.82, P = 0.001). Increased diastolic blood pressure (ORhigh-decreased = 1.04, 95% CI = 1.01 to 1.08, P = 0.02; ORhigh-increased = 1.04, 95% CI = 1.00 to 1.08, P = 0.048) and decreased high-density lipoprotein (OR high-increased = 6.25, 95% CI = 1.81 to 21.59, P = 0.004) were associated with more severe negative symptoms. Increased HbA1c (ORmoderate = 1.05, 95% CI = 1.01 to 1.10, P = 0.024; ORhigh = 1.08, 95% CI = 1.02 to 1.14, P = 0.006) was associated with more severe positive symptoms. These associations were not mediated by antipsychotics. CONCLUSIONS: We showed an association between cardiometabolic dysregulations and clinical and cognitive symptoms in SSD patients. The observed associations underscore the need for early identification of patients at risk of cardiometabolic outcomes.

Understanding Lifelong Factors and Prediction Models of Social Functioning After Psychosis Onset Using the Large-Scale GROUP Cohort Study.

BACKGROUND AND HYPOTHESIS: Current rates of poor social functioning (SF) in people with psychosis history reach 80% worldwide. We aimed to identify a core set of lifelong predictors and build prediction models of SF after psychosis onset. STUDY DESIGN: We utilized data of 1119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) longitudinal Dutch cohort. First, we applied group-based trajectory modeling to identify premorbid adjustment trajectories. We further investigated the association between the premorbid adjustment trajectories, six-year-long cognitive deficits, positive, and negative symptoms trajectories, and SF at 3-year and 6-year follow-ups. Next, we checked associations between demographics, clinical, and environmental factors measured at the baseline and SF at follow-up. Finally, we built and internally validated 2 predictive models of SF. STUDY RESULTS: We found all trajectories were significantly associated with SF (P < .01), explaining up to 16% of SF variation (R2 0.15 for 3- and 0.16 for 6-year follow-up). Demographics (sex, ethnicity, age, education), clinical parameters (genetic predisposition, illness duration, psychotic episodes, cannabis use), and environment (childhood trauma, number of moves, marriage, employment, urbanicity, unmet needs of social support) were also significantly associated with SF. After validation, final prediction models explained a variance up to 27% (95% CI: 0.23, 0.30) at 3-year and 26% (95% CI: 0.22, 0.31) at 6-year follow-up. CONCLUSIONS: We found a core set of lifelong predictors of SF. Yet, the performance of our prediction models was moderate.

The impact of frontal lesions after mild to moderate traumatic brain injury on frontal network measures.

To investigate the impact of frontal macro-structural lesions on intrinsic network measures, we examined brain network function during resting-state fMRI in patients with frontal lesions in the subacute phase after mild to moderate traumatic brain injury. Additionally, network function was related to neuropsychological performances. 17 patients with frontal lesions, identified on admission CT after mild to moderate trauma, were compared to 30 traumatic brain injury patients without frontal lesions and 20 healthy controls. Three months post-injury, we acquired fMRI scans and neuropsychological assessments (measuring frontal executive functions and information processing speed). Using independent component analysis, the activity of and connectivity between network components (largely located in the prefrontal cortex) and relations with neuropsychological measures were examined and compared across groups. The analysis yielded five predominantly frontal components: anterior and posterior part of the default mode network, left and right frontoparietal network and salience network. No significant differences concerning fMRI measures were found across groups. However, the frontal lesions group performed significantly worse on neuropsychological tests than the other two groups. Additionally, the frontal lesions group showed a significant positive association of stronger default mode network-salience network connectivity with better executive performances. Our findings suggest that, on fMRI level, frontal network measures are not largely affected by frontal lesions following a mild to moderate traumatic brain injury. Yet, patients with damage to the frontal structures did show poorer executive abilities which might to some degree be related to altered frontal network connectivity between the default mode network and salience network.

Pharmacogenetics of Long-Term Outcomes of Schizophrenia Spectrum Disorders: The Functional Role of CYP2D6 and CYP2C19.

Schizophrenia spectrum disorders (SSD) are complex mental disorders, and while treatment with antipsychotics is important, many patients do not respond or develop serious side effects. Genetic variation has been shown to play a considerable role in determining an individual's response to antipsychotic medication. However, previous pharmacogenetic (PGx) studies have been limited by small sample sizes, lack of consensus regarding relevant genetic variants, and cross-sectional designs. The current study aimed to investigate the association between PGx variants and long-term clinical outcomes in 691 patients of European ancestry with SSD. Using evidence from the literature on candidate genes involved in antipsychotic pharmacodynamics, we created a polygenic risk score (PRS) to investigate its association with clinical outcomes. We also created PRS using core variants of psychotropic drug metabolism enzymes CYP2D6 and CYP2C19. Furthermore, the CYP2D6 and CYP2C19 functional activity scores were calculated to determine the relationship between metabolism and clinical outcomes. We found no association for PGx PRSs and clinical outcomes; however, an association was found with CYP2D6 activity scores by the traditional method. Higher CYP2D6 metabolism was associated with high positive and high cognitive impairment groups relative to low symptom severity groups. These findings highlight the need to test PGx efficacy with different symptom domains. More evidence is needed before pharmacogenetic variation can contribute to personalized treatment plans.

Six-year trajectories and associated factors of positive and negative symptoms in schizophrenia patients, siblings, and controls: Genetic Risk and Outcome of Psychosis (GROUP) study.

Positive and negative symptoms are prominent but heterogeneous characteristics of schizophrenia spectrum disorder (SSD). Within the framework of the Genetic Risk and Outcome of Psychosis (GROUP) longitudinal cohort study, we aimed to distinguish and identify the genetic and non-genetics predictors of homogenous subgroups of the long-term course of positive and negative symptoms in SSD patients (n = 1119) and their unaffected siblings (n = 1059) in comparison to controls (n = 586). Data were collected at baseline, and after 3- and 6-year follow-ups. Group-based trajectory modeling was applied to identify latent subgroups using positive and negative symptoms or schizotypy scores. A multinomial random-effects logistic regression model was used to identify predictors of latent subgroups. Patients had decreasing, increasing, and relapsing symptoms course. Unaffected siblings and healthy controls had three to four subgroups characterized by stable, decreasing, or increasing schizotypy. PRSSCZ did not predict the latent subgroups. Baseline symptoms severity in patients, premorbid adjustment, depressive symptoms, and quality of life in siblings predicted long-term trajectories while were nonsignificant in controls. In conclusion, up to four homogenous latent subgroups of symptom course can be distinguished within patients, siblings, and controls, while non-genetic factors are the main factors associated with the latent subgroups.