A Deep Learning-Derived Transdiagnostic Signature Indexing Hypoarousal and Impulse Control: Implications for Treatment Prediction in Psychiatric Disorders.

BACKGROUND: Psychiatric disorders are traditionally classified within diagnostic categories, but this approach has limitations. Research Domain Criteria (RDoC) constitute a research classification system for psychiatric disorders based on dimensions within domains that cut across these psychiatric diagnoses. The overall aim of RDoC is to better understand mental illness in terms of dysfunction in fundamental neurobiological and behavioral systems, leading to better diagnosis, prevention and treatment. METHODS: A unique electroencephalographic (EEG) feature, referred to as spindling excessive beta (SEB), has been studied in relation to impulse control and sleep, as part of the arousal/regulatory systems RDoC domain. Here, we study EEG frontal beta activity as a potential transdiagnostic biomarker capable of diagnosing and predicting impulse control and sleep problems. RESULTS: We show in the first dataset (n=3279) that the probability of having SEB, classified by a deep learning algorithm, is associated with poor sleep maintenance and low daytime impulse control. Furthermore, in two additional, independent datasets (iSPOT-A, n=336; iSPOT-D, n=1008), we revealed that conventional frontocentral beta power and/or SEB probability, referred to as Brainmarker-III, is associated with a diagnosis of attention deficit hyperactivity disorder (ADHD), with remission to methylphenidate in children with ADHD in a sex-specific manner, and with remission to antidepressant medication in adults with a major depressive disorder in a drug-specific manner. CONCLUSION: Our results demonstrate the value of the RDoC approach in psychiatry research for the discovery of biomarkers with diagnostic and treatment prediction capacities.

Electroconvulsive Therapy Versus Aripiprazole Addition to Clozapine in Patients with Clozapine-Resistant Symptoms (EMECLO): A Protocol of a Single-Blind, Multicenter, Randomized-Controlled Feasibility Trial.

BACKGROUND: Currently, guidance on the most effective treatment for patients with clozapine-resistant schizophrenia-spectrum disorders (SSD) is lacking. While augmentation strategies to clozapine with aripiprazole and electroconvulsive therapy (ECT) have been demonstrated to be effective in patients with clozapine-resistant schizophrenia spectrum disorders (CRS), head-to-head comparisons between these addition strategies are unavailable. We therefore aim to examine the feasibility of a larger randomized, single-blind trial comparing the effectiveness, cost-effectiveness, and safety of aripiprazole addition vs. ECT addition in CRS. METHODS: In this multi-center, randomized, single-blind feasibility study, the feasibility of recruiting 20 participants with CRS who will be randomized to either aripiprazole or bilateral ECT addition will be assessed. The main endpoint is the number of patients willing to be randomized. The number of screened individuals and reasons to decline participation will be recorded. Effects will be estimated for the benefit of the foreseen larger trial. To that end, differences between both arms in symptom severity will be assessed using blinded video assessments. In addition, tolerability (e. g., cognitive functioning), safety, quality of life, recovery, and all-cause discontinuation will be compared. The follow-up period is 16 weeks, after which non-responders will be given the option to switch to the other treatment. DISCUSSION: Strengths of this feasibility trial include maintaining blinding with video assessment, a possibility to switch groups in case of non-response, and a broad set of outcome measures. Identification of factors contributing to non-participation and drop-out will generate valuable information on trial feasibility and may enhance recruitment strategies in a follow-up RCT. TRIAL REGISTRATION: The study has been approved by the Medical Research Ethics Committee of the Amsterdam University Medical Center, location AMC, and was registered on 1 May 2022 in the EU Clinical Trials Register (EudraCT) under the trial name 'EMECLO' (2021-006333-19).

Epigenome-wide association studies identify novel DNA methylation sites associated with PTSD: A meta-analysis of 23 military and civilian cohorts.

Background: The occurrence of post-traumatic stress disorder (PTSD) following a traumatic event is associated with biological differences that can represent the susceptibility to PTSD, the impact of trauma, or the sequelae of PTSD itself. These effects include differences in DNA methylation (DNAm), an important form of epigenetic gene regulation, at multiple CpG loci across the genome. Moreover, these effects can be shared or specific to both central and peripheral tissues. Here, we aim to identify blood DNAm differences associated with PTSD and characterize the underlying biological mechanisms by examining the extent to which they mirror associations across multiple brain regions. Methods: As the Psychiatric Genomics Consortium (PGC) PTSD Epigenetics Workgroup, we conducted the largest cross-sectional meta-analysis of epigenome-wide association studies (EWASs) of PTSD to date, involving 5077 participants (2156 PTSD cases and 2921 trauma-exposed controls) from 23 civilian and military studies. PTSD diagnosis assessments were harmonized following the standardized guidelines established by the PGC-PTSD Workgroup. DNAm was assayed from blood using either Illumina HumanMethylation450 or MethylationEPIC (850K) BeadChips. A common QC pipeline was applied. Within each cohort, DNA methylation was regressed on PTSD, sex (if applicable), age, blood cell proportions, and ancestry. An inverse variance-weighted meta-analysis was performed. We conducted replication analyses in tissue from multiple brain regions, neuronal nuclei, and a cellular model of prolonged stress. Results: We identified 11 CpG sites associated with PTSD in the overall meta-analysis (1.44e-09 < p < 5.30e-08), as well as 14 associated in analyses of specific strata (military vs civilian cohort, sex, and ancestry), including CpGs in AHRR and CDC42BPB. Many of these loci exhibit blood-brain correlation in methylation levels and cross-tissue associations with PTSD in multiple brain regions. Methylation at most CpGs correlated with their annotated gene expression levels. Conclusions: This study identifies 11 PTSD-associated CpGs, also leverages data from postmortem brain samples, GWAS, and genome-wide expression data to interpret the biology underlying these associations and prioritize genes whose regulation differs in those with PTSD.

Dopamine D2 receptor antagonism of antipsychotics and the risk of death due to choking.

The risk of fatal choking for people with schizophrenia and associations with antipsychotic medication are largely unknown. Therefore, we calculated the choking-related standardized mortality ratio for schizophrenia relative to the general population (SMRchoking). We also computed adjusted hazard ratios (aHR) of choking-related mortality for antipsychotics in a nationwide cohort of patients with schizophrenia (N = 59,916). SMRchoking was 20.5 (95 % confidence interval (CI)=17.1-23.9). The aHR was 1.74 (95 %CI=1.19-2.55) for strong dopamine 2-antagonists. For other antipsychotics, CIs included 1. Importantly, aHRs were particularly high for high dose categories of strong dopamine D2 receptor (D2R) antagonists. In conclusion, a schizophrenia diagnosis is associated with a 20-fold risk of death due to choking. This risk is elevated during use of strong D2R antagonist antipsychotics, particularly when prescribed in high dosages.

Pneumonia Risk, Antipsychotic Dosing, and Anticholinergic Burden in Schizophrenia.

Importance: Antipsychotic drugs (particularly clozapine) have been associated with pneumonia in observational studies. Despite studies of the associations between antipsychotic use and incident pneumonia, it remains unclear to what degree antipsychotic use is associated with increased risk of pneumonia, whether dose-response associations exist, and what agents are specifically associated with incident pneumonia. Objective: To estimate pneumonia risk associated with specific antipsychotics and examine whether polytherapy, dosing, and receptor binding properties are associated with pneumonia in patients with schizophrenia. Design, Setting, and Participants: This cohort study identified patients with schizophrenia or schizoaffective disorder (hereafter, schizophrenia) aged 16 years or older from nationwide Finnish registers from 1972 to 2014. Data on diagnoses, inpatient care, and specialized outpatient care were obtained from the Hospital Discharge Register. Information on outpatient medication dispensing was obtained from the Prescription Register. Study follow-up was from 1996 to 2017. Data were analyzed from November 4, 2022, to December 5, 2023. Exposures: Use of specific antipsychotic monotherapies; antipsychotics modeled by dosage as low (<0.6 of the World Health Organization defined daily dose [DDD] per day), medium (0.6 to <1.1 DDDs per day), or high dose (≥1.1 DDDs per day); antipsychotic polypharmacy; and antipsychotics categorized according to their anticholinergic burden as low, medium, and high. Main Outcomes and Measures: The primary outcome was hospitalization for incident pneumonia. Pneumonia risk was analyzed using adjusted, within-individual Cox proportional hazards regression models, with no antipsychotic use as the reference. Results: The study included 61 889 persons with schizophrenia (mean [SD] age, 46.2 [16.0] years; 31 104 men [50.3%]). During 22 years of follow-up, 8917 patients (14.4%) had 1 or more hospitalizations for pneumonia and 1137 (12.8%) died within 30 days of admission. Compared with no antipsychotic use, any antipsychotic use overall was not associated with pneumonia (adjusted hazard ratio [AHR], 1.12; 95% CI, 0.99-1.26). Monotherapy use was associated with increased pneumonia risk compared with no antipsychotic use (AHR, 1.15 [95% CI, 1.02-1.30]; P = .03) in a dose-dependent manner, but polytherapy use was not. When categorized by anticholinergic burden, only the use of antipsychotics with a high anticholinergic burden was associated with pneumonia (AHR, 1.26 [95% CI, 1.10-1.45]; P < .001). Of specific drugs, high-dose quetiapine (AHR, 1.78 [95% CI, 1.22-2.60]; P = .003), high- and medium-dose clozapine (AHR, 1.44 [95% CI, 1.22-1.71]; P < .001 and AHR, 1.43 [95% CI, 1.18-1.74]; P < .001, respectively), and high-dose olanzapine (AHR, 1.29 [95% CI, 1.05-1.58]; P = .02) were associated with increased pneumonia risk. Conclusions and Relevance: Results of this cohort study suggest that in patients with schizophrenia, antipsychotic agents associated with pneumonia include not only clozapine (at dosages ≥180 mg/d) but also quetiapine (≥440 mg/d) and olanzapine (≥11 mg/d). Moreover, monotherapy antipsychotics and antipsychotics with high anticholinergic burden are associated with increased pneumonia risk in a dose-dependent manner. These findings call for prevention strategies aimed at patients with schizophrenia requiring high-risk antipsychotics.

Climate change and mental health: Position paper of the European Psychiatric Association.

BACKGROUND: Climate change is one of the greatest threats to health that societies face and can adversely affect mental health. Given the current lack of a European consensus paper on the interplay between climate change and mental health, we signal a need for a pan-European position paper about this topic, written by stakeholders working in mental health care. METHODS: On behalf of the European Psychiatric Association (EPA), we give recommendations to make mental health care, research, and education more sustainable based on a narrative review of the literature. RESULTS: Examples of sustainable mental healthcare comprise preventive strategies, interdisciplinary collaborations, evidence-based patient care, addressing social determinants of mental health, maintaining health services during extreme weather events, optimising use of resources, and sustainable facility management. In mental health research, sustainable strategies include investigating the impact of climate change on mental health, promoting research on climate change interventions, strengthening the evidence base for mental health-care recommendations, evaluating the allocation of research funding, and establishing evidence-based definitions and clinical approaches for emerging issues such as 'eco-distress'. Regarding mental health education, planetary health, which refers to human health and how it is intertwined with ecosystems, may be integrated into educational courses. CONCLUSIONS: The EPA is committed to combat climate change as the latter poses a threat to the future of mental health care. The current EPA position paper on climate change and mental health may be of interest to a diverse readership of stakeholders, including clinicians, researchers, educators, patients, and policymakers.

Genome-wide association study identifies 30 obsessive-compulsive disorder associated loci.

Obsessive-compulsive disorder (OCD) affects ~1% of the population and exhibits a high SNP-heritability, yet previous genome-wide association studies (GWAS) have provided limited information on the genetic etiology and underlying biological mechanisms of the disorder. We conducted a GWAS meta-analysis combining 53,660 OCD cases and 2,044,417 controls from 28 European-ancestry cohorts revealing 30 independent genome-wide significant SNPs and a SNP-based heritability of 6.7%. Separate GWAS for clinical, biobank, comorbid, and self-report sub-groups found no evidence of sample ascertainment impacting our results. Functional and positional QTL gene-based approaches identified 249 significant candidate risk genes for OCD, of which 25 were identified as putatively causal, highlighting WDR6, DALRD3, CTNND1 and genes in the MHC region. Tissue and single-cell enrichment analyses highlighted hippocampal and cortical excitatory neurons, along with D1- and D2-type dopamine receptor-containing medium spiny neurons, as playing a role in OCD risk. OCD displayed significant genetic correlations with 65 out of 112 examined phenotypes. Notably, it showed positive genetic correlations with all included psychiatric phenotypes, in particular anxiety, depression, anorexia nervosa, and Tourette syndrome, and negative correlations with a subset of the included autoimmune disorders, educational attainment, and body mass index.. This study marks a significant step toward unraveling its genetic landscape and advances understanding of OCD genetics, providing a foundation for future interventions to address this debilitating disorder.

A review on side effect management of second-generation antipsychotics to treat schizophrenia: a drug safety perspective.

INTRODUCTION: Effective side effects management present a challenge in antipsychotic treatment with second-generation antipsychotics (SGAs). In recent years, most of the commonly used SGAs, except for clozapine, have been shown to differ only slightly in their effectiveness, but considerably regarding perceived side effects, safety profiles, and compatibility to preexisting medical conditions. AREAS COVERED: The current state of available evidence on side-effect management in SGA treatment of patients with schizophrenia spectrum disorders (SSD) is reviewed. In addition, current guideline recommendations are summarized, highlighting evidence gaps. EXPERT OPINION: SGA safety and side effects needs to be considered in treatment planning. Shared decision-making assistants (SDMA) can support patients, practitioners and relatives to orient their decisions toward avoiding side effects relevant to patients' adherence. Alongside general measures like psychosocial and psychotherapeutic care, switching to better tolerated SGAs can be considered a relatively safe strategy. By contrast, novel meta-analytical evidence emphasizes that dose reduction of SGAs can statistically increase the risk of relapse and other unfavorable outcomes. Further, depending on the type and severity of SGA-related side effects, specific treatments can be used to alleviate induced side effects (e.g. add-on metformin to reduce weight-gain). Finally, discontinuation should be reserved for acute emergencies.

The ethics of polygenic scores in psychiatry: minefield or opportunity for patient-centered psychiatry?

Recent advancements in psychiatric genetics have sparked a lively debate on the opportunities and pitfalls of incorporating polygenic scores into clinical practice. Yet, several ethical concerns have been raised, casting doubt on whether further development and implementation of polygenic scores would be compatible with providing ethically responsible care. While these ethical issues warrant thoughtful consideration, it is equally important to recognize the unresolved need for guidance on heritability among patients and their families. Increasing the availability of genetic counseling services in psychiatry should be regarded as a first step toward meeting these needs. As a next step, future integration of novel genetic tools such as polygenic scores into genetic counseling may be a promising way to improve psychiatric counseling practice. By embedding the exploration of polygenic psychiatry into the supporting environment of genetic counseling, some of the previously identified ethical pitfalls may be prevented, and opportunities to bolster patient empowerment can be seized upon. To ensure an ethically responsible approach to psychiatric genetics, active collaboration with patients and their relatives is essential, accompanied by educational efforts to facilitate informed discussions between psychiatrists and patients.

Discontinuation of psychotropic medication: a synthesis of evidence across medication classes.

Pharmacotherapy is an effective treatment modality across psychiatric disorders. Nevertheless, many patients discontinue their medication at some point. Evidence-based guidance for patients, clinicians, and policymakers on rational discontinuation strategies is vital to enable the best, personalized treatment for any given patient. Nonetheless, there is a scarcity of guidelines on discontinuation strategies. In this perspective, we therefore summarize and critically appraise the evidence on discontinuation of six major psychotropic medication classes: antidepressants, antipsychotics, benzodiazepines, mood stabilizers, opioids, and stimulants. For each medication class, a wide range of topics pertaining to each of the following questions are discussed: (1) Who can discontinue (e.g., what are risk factors for relapse?); (2) When to discontinue (e.g., after 1 year or several years of antidepressant use?); and (3) How to discontinue (e.g., what's the efficacy of dose reduction compared to full cessation and interventions to mitigate relapse risk?). We thus highlight how comparing the evidence across medication classes can identify knowledge gaps, which may pave the way for more integrated research on discontinuation.

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

Background: Incorporating genomic data into risk prediction has become an increasingly useful approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. Methods: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. Results: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p-0.003), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. Conclusion: Results, especially those from the eMRS, reinforce earlier findings that methylation and trauma are interconnected and can be leveraged to increase the correct classification of those with vs. without PTSD. Moreover, our models can potentially be a valuable tool in predicting the future risk of developing PTSD. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting the condition and, relatedly, improve their performance in independent cohorts.

Efficacy and effectiveness of antipsychotics in schizophrenia: network meta-analyses combining evidence from randomised controlled trials and real-world data.

BACKGROUND: There is debate about the generalisability of results from randomised clinical trials (RCTs) to real-world settings. Studying outcomes of treatments for schizophrenia can shed light on this issue and inform treatment guidelines. We therefore compared the efficacy and effectiveness of antipsychotics for relapse prevention in schizophrenia and estimated overall treatment effects using all available RCT and real-world evidence. METHODS: We conducted network meta-analyses using individual participant data from Swedish and Finnish national registries and aggregate data from RCTs. The target population was adults (age >18 and <65 years) with schizophrenia and schizoaffective disorder with stabilised symptoms. We analysed each registry separately to obtain hazard ratios (HRs) and 95% CIs for relapse within 6 months post-antipsychotic initiation as our main outcome. Interventions studied were antipsychotics, no antipsychotic use, and placebo. We compared HRs versus a reference drug (oral haloperidol) between registries, and between registry individuals who would be eligible and ineligible for RCTs, using the ratio of HRs. We synthesised evidence using network meta-analysis and compared results from our network meta-analysis of real-world data with our network meta-analysis of RCT data, including oral versus long-acting injectable (LAI) formulations. Finally, we conducted a joint real-world and RCT network meta-analysis. FINDINGS: We included 90 469 individuals from the Swedish and Finnish registries (mean age 45·9 [SD 14·6] years; 43 025 [47·5%] women and 47 467 [52·5%] men, ethnicity data unavailable) and 10 091 individuals from 30 RCTs (mean age 39·6 years [SD 11·7]; 3724 [36·9%] women and 6367 [63·1%] men, 6022 White [59·7%]). We found good agreement in effectiveness of antipsychotics between Swedish and Finnish registries (HR ratio 0·97, 95% CI 0·88-1·08). Drug effectiveness versus no antipsychotic was larger in RCT-eligible than RCT-ineligible individuals (HR ratio 1·40 [1·24-1·59]). Efficacy versus placebo in RCTs was larger than effectiveness versus no antipsychotic in real-world (HR ratio 2·58 [2·02-3·30]). We found no evidence of differences between effectiveness and efficacy for between-drug comparisons (HR ratio vs oral haloperidol 1·17 [0·83-1·65], where HR ratio >1 means superior effectiveness in real-world to RCTs), except for LAI versus oral comparisons (HR ratio 0·73 [0·53-0·99], indicating superior effectiveness in real-world data relative to RCTs). The real-world network meta-analysis showed clozapine was most effective, followed by olanzapine LAI. The RCT network meta-analysis exhibited heterogeneity and inconsistency. The joint real-world and RCT network meta-analysis identified olanzapine as the most efficacious antipsychotic amongst those present in both RCTs and the real world registries. INTERPRETATION: LAI antipsychotics perform slightly better in the real world than according to RCTs. Otherwise, RCT evidence was in line with real-world evidence for most between-drug comparisons, but RCTs might overestimate effectiveness of antipsychotics observed in routine care settings. Our results further the understanding of the generalisability of RCT findings to clinical practice and can inform preferential prescribing guidelines. FUNDING: None.

Vaccination and clozapine use: a systematic review and an analysis of the VAERS database.

In the context of COVID-19 concerns related to the potential interactions between clozapine and vaccination arose. With the ultimate goal of deriving recommendations for clinical practice, we systematically reviewed the current evidence regarding altered vaccine effectiveness in clozapine-treated patients and safety aspects of vaccination, such as haematological changes and the impact of vaccines on clozapine blood levels, in clozapine-treated patients. A systematic PRISMA-conform literature search of four databases (PubMed, PsycINFO, EMBASE and Cochrane Library) complemented by a case-by-case analysis of the Vaccine Adverse Event Reporting System (VAERS) database was performed. We then systematically appraised the joint evidence and tried to derive recommendations for clinical practice. 14 records were included in this analysis. These records consisted of 5 original articles and 9 case reports. Among the original articles, two studies provided data on the association between clozapine use and antibody responses to vaccination, both indicating that clozapine use in schizophrenia may be associated with reduced levels of immunoglobulins. Additionally, three studies examined vaccine safety in clozapine-treated patients, with no clinically significant adverse effects directly attributable to the interplay between vaccinations and clozapine. VAERS Analysis encompassed 137 reports and showed no consistent evidence of an increased risk for clozapine blood level increases or adverse events. We found no evidence indicating that clozapine impairs the effectiveness of vaccines. Moreover, no serious safety concerns seem to apply when patients on clozapine are receiving vaccines. However, it is crucial to acknowledge that data on the interaction between clozapine and vaccines remain limited.

Polygenetic risk scores and phenotypic constellations of obsessive-compulsive disorder in clozapine-treated schizophrenia.

Obsessive-compulsive symptoms (OCS) are frequently observed in individuals with schizophrenia (SCZ) treated with clozapine (CLZ). This study aimed to analyze prevalence of OCS and obsessive-compulsive disorder (OCD) in this subgroup and find possible correlations with different phenotypes. Additionally, this is the first study to examine polygenetic risk scores (PRS) in individuals with SCZ and OCS. A multicenter cohort of 91 individuals with SCZ who were treated with CLZ was recruited and clinically and genetically assessed. Symptom severity was examined using the Positive and Negative Symptom Scale (PANSS), Clinical Global Impression Scale (CGI), the Calgary Depression Scale for Schizophrenia (CDSS), Global Assessment of Functioning Scale (GAF) and Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). Participants were divided into subgroups based on phenotypic OCS or OCD using Y-BOCS scores. Genomic-wide data were generated, and PRS analyses were performed to evaluate the association between either phenotypic OCD or OCS severity and genotype-predicted predisposition for OCD, SCZ, cross-disorder, and CLZ/norclozapine (NorCLZ) ratio, CLZ metabolism and NorCLZ metabolism. OCS and OCD were frequent comorbidities in our sample of CLZ-treated SCZ individuals, with a prevalence of 39.6% and 27.5%, respectively. Furthermore, the Y-BOCS total score correlated positively with the duration of CLZ treatment in years (r = 0.28; p = 0.008) and the PANSS general psychopathology subscale score (r = 0.23; p = 0.028). A significant correlation was found between OCD occurrence and PRS for CLZ metabolism. We found no correlation between OCS severity and PRS for CLZ metabolism. We found no correlation for either OCD or OCS and PRS for OCD, cross-disorder, SCZ, CLZ/NorCLZ ratio or NorCLZ metabolism. Our study was able to replicate previous findings on clinical characteristics of CLZ-treated SCZ individuals. OCS is a frequent comorbidity in this cohort and is correlated with CLZ treatment duration in years and PANSS general psychopathology subscale score. We found a correlation between OCD and PRS for CLZ metabolism, which should be interpreted as incidental for now. Future research is necessary to replicate significant findings and to assess possible genetic predisposition of CLZ-treated individuals with SCZ to OCS/OCD. Limitations attributed to the small sample size or the inclusion of subjects on co-medication must be considered. If the association between OCD and PRS for CLZ metabolism can be replicated, it should be further evaluated if CYP1A2 alteration, respectively lower CLZ plasma level, is relevant for OCD development.

A posterior-alpha ageing network is differentially associated with antidepressant effects of venlafaxine and rTMS.

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder, but chances for remission largely decrease with each failed treatment attempt. It is therefore desirable to assign a given patient to the most promising individual treatment option as early as possible. We used a polygenic score (PGS) informed electroencephalography (EEG) data-driven approach to identify potential predictors for MDD treatment outcome. Post-hoc we conducted exploratory analyses in order to understand the results in depth. First, an EEG independent component analysis produced 54 functional brain networks in a large heterogeneous cohort of psychiatric patients (n = 4,045; 5-84 yrs.). Next, the network that was associated to PGS for antidepressant-response (PRS-AR) in an independent sample (n = 722) was selected: an age-related posterior alpha network that explained >60 % of EEG variance, and was highly stable over recording time. Translational analyses were performed in two other independent datasets to examine if the network was predictive of psychopharmacotherapy (n = 535) and/or repetitive transcranial magnetic stimulation (rTMS) and concomitant psychotherapy (PT; n = 186) outcome. The network predicted remission to venlafaxine (p = 0.015), resulting in a normalized positive predicted value (nPPV) of 138 %, and rTMS + PT - but in opposite direction for women (p = 0.002) relative to men (p = 0.018) - yielding a nPPV of 131 %. Blinded out-of-sample validations for venlafaxine (n = 29) and rTMS + PT (n = 36) confirmed the findings for venlafaxine, while results for rTMS + PT could not be replicated. These data suggest the existence of a relatively stable EEG posterior alpha aging network related to PGS-AR that has potential as MDD treatment predictor.

Challenges, unmet needs and future directions - a critical evaluation of the clinical trial landscape in schizophrenia research.

INTRODUCTION: Developing novel antipsychotic mechanisms of action and repurposing established compounds for the treatment of schizophrenia is of utmost importance to improve relevant symptom domains and to improve the risk/benefit ratio of antipsychotic compounds. Novel trial design concepts, pathophysiology-based targeted treatment approaches, or even the return to old values may improve schizophrenia outcomes in the future. AREAS COVERED: In this review of the clinical trial landscape in schizophrenia, we present an overview of the challenges and gaps in current clinical trials and elaborate on potential solutions to improve the outcomes of people with schizophrenia. EXPERT OPINION: The classic parallel group design may limit substantial advantages in drug approval or repurposing. Collaborative approaches between regulatory authorities, industry, academia, and funding agencies are needed to overcome barriers in clinical schizophrenia research to allow for meaningful outcome improvements for the patients.

Gene-environment interaction study on the polygenic risk score for neuroticism, childhood adversity, and parental bonding.

The present study examines whether neuroticism is predicted by genetic vulnerability, summarized as polygenic risk score for neuroticism (PRSN), in interaction with bullying, parental bonding, and childhood adversity. Data were derived from a general population adolescent and young adult twin cohort. The final sample consisted of 202 monozygotic and 436 dizygotic twins and 319 twin pairs. The Short Eysenck Personality questionnaire was used to measure neuroticism. PRSN was trained on the results from the Genetics of Personality Consortium (GPC) and United Kingdom Biobank (UKB) cohorts, yielding two different PRSN. Multilevel mixed-effects models were used to analyze the main and interacting associations of PRSN, childhood adversity, bullying, and parental bonding style with neuroticism. We found no evidence of gene-environment correlation. PRSN thresholds of .005 and .2 were chosen, based on GPC and UKB datasets, respectively. After correction for confounders, all the individual variables were associated with the expression of neuroticism: both PRSN from GPC and UKB, childhood adversity, maternal bonding, paternal bonding, and bullying in primary school and secondary school. However, the results indicated no evidence for gene-environment interaction in this cohort. These results suggest that genetic vulnerability on the one hand and negative life events (childhood adversity and bullying) and positive life events (optimal parental bonding) on the other represent noninteracting pathways to neuroticism.

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.

Associations between psychotropic drugs and rsEEG connectivity and network characteristics: a cross-sectional study in hospital-admitted psychiatric patients.

Introduction: Resting-state EEG (rsEEG) characteristics, such as functional connectivity and network topology, are studied as potential biomarkers in psychiatric research. However, the presence of psychopharmacological treatment in study participants poses a potential confounding factor in biomarker research. To address this concern, our study aims to explore the impact of both single and multi-class psychotropic treatments on aforementioned rsEEG characteristics in a psychiatric population. Methods: RsEEG was analyzed in a real-world cross-sectional sample of 900 hospital-admitted psychiatric patients. Patients were clustered into eight psychopharmacological groups: unmedicated, single-class treatment with antipsychotics (AP), antidepressants (AD) or benzodiazepines (BDZ), and multi-class combinations of these treatments. To assess the associations between psychotropic treatments and the macroscale rsEEG characteristics mentioned above, we employed a general linear model with post-hoc tests. Additionally, Spearman's rank correlation analyses were performed to explore potential dosage effects. Results: Compared to unmedicated patients, single-class use of AD was associated with lower functional connectivity in the delta band, while AP was associated with lower functional connectivity in both the delta and alpha bands. Single-class use of BDZ was associated with widespread rsEEG differences, including lower functional connectivity across frequency bands and a different network topology within the beta band relative to unmedicated patients. All of the multi-class groups showed associations with functional connectivity or topology measures, but effects were most pronounced for concomitant use of all three classes of psychotropics. Differences were not only observed in comparison with unmedicated patients, but were also evident in comparisons between single-class, multi-class, and single/multi-class groups. Importantly, multi-class associations with rsEEG characteristics were found even in the absence of single-class associations, suggesting potential cumulative or interaction effects of different classes of psychotropics. Dosage correlations were only found for antipsychotics. Conclusion: Our exploratory, cross-sectional study suggests small but significant associations between single and multi-class use of antidepressants, antipsychotics and benzodiazepines and macroscale rsEEG functional connectivity and network topology characteristics. These findings highlight the importance of considering the effects of specific psychotropics, as well as their interactions, when investigating rsEEG biomarkers in a medicated psychiatric population.