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The increasing availability of biobanks is changing the way individuals are identified for genomic research. This study assesses the validity of a self-reported clinical diagnosis of schizophrenia. The study included 1744 clinically-ascertained participants with schizophrenia or schizoaffective disorder depressed-type (SA-D) diagnosed by self-report and/or research interview and 1453 UK Biobank participants with self-reported and/or medical record diagnosis of schizophrenia or SA-D. Unaffected controls included a total of 501,837 participants. We assessed the positive predictive values (PPV) of self-reported clinical diagnoses against research interview and medical record diagnoses. Polygenic risk scores (PRS) and phenotypes relating to demographics, education and employment were compared across diagnostic groups. The variance explained (r 2 ) in schizophrenia PRS for each diagnostic group was compared to samples in the Psychiatric Genomics Consortium (PGC). In the clinically-ascertained participants, the PPV of self-reported schizophrenia for a research diagnosis of schizophrenia was 0.70, which increased to 0.81 after expanding the research diagnosis to schizophrenia or SA-D. In UK Biobank, the PPV of self-reported schizophrenia for a medical record diagnosis was 0.74. Compared to participants who self-reported, participants with a clinically-ascertained research diagnosis were younger and more likely to have a high school qualification. Participants with a medical record diagnosis in UK Biobank were less likely to be employed or have a high school qualification than those who self-reported. Schizophrenia PRS did not differ between participants that had a diagnosis from self-report, research diagnosis or medical records. Polygenic liability r 2 , for all diagnosis definitions, fell within the distribution of PGC schizophrenia cohorts. Self-reported measures of schizophrenia are justified in genomic research to maximise sample size and reduce the burden of in-depth interviews on participants, although within sample validation of diagnoses is recommended., (© 2024. The Author(s).)

Background: Positive, negative and disorganised psychotic symptom dimensions are associated with clinical and developmental variables, but differing definitions complicate interpretation. Additionally, some variables have had little investigation., Aims: To investigate associations of psychotic symptom dimensions with clinical and developmental variables, and familial aggregation of symptom dimensions, in multiple samples employing the same definitions., Method: We investigated associations between lifetime symptom dimensions and clinical and developmental variables in two twin and two general psychosis samples. Dimension symptom scores and most other variables were from the Operational Criteria Checklist. We used logistic regression in generalised linear mixed models for combined sample analysis ( n = 875 probands). We also investigated correlations of dimensions within monozygotic (MZ) twin pairs concordant for psychosis ( n = 96 pairs)., Results: Higher symptom scores on all three dimensions were associated with poor premorbid social adjustment, never marrying/cohabiting and earlier age at onset, and with a chronic course, most strongly for the negative dimension. The positive dimension was also associated with Black and minority ethnicity and lifetime cannabis use; the negative dimension with male gender; and the disorganised dimension with gradual onset, lower premorbid IQ and substantial within twin-pair correlation. In secondary analysis, disorganised symptoms in MZ twin probands were associated with lower premorbid IQ in their co-twins., Conclusions: These results confirm associations that dimensions share in common and strengthen the evidence for distinct associations of co-occurring positive symptoms with ethnic minority status, negative symptoms with male gender and disorganised symptoms with substantial familial influences, which may overlap with influences on premorbid IQ.

Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders., (Copyright © 2024 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

The missense SNP NC_000004.12:g.102267552C>T (SLC39A8.p.(Ala391Thr), rs13107325) in SLC39A8 , which encodes a zinc transporter, has been linked to schizophrenia and is the likely causal variant for one of the genome-wide association loci associated with the disorder. We tested whether the schizophrenia-risk allele at p.(Ala391Thr) was associated with schizophrenia-related phenotypes, including positive, negative, and disorganised symptoms, cognitive ability, educational attainment, and age of psychosis onset, within three schizophrenia cohorts (combined N=1,232) and, with equivalent phenotypes, in a sample of population controls (UK Biobank, N=355,069). We used regression analyses controlling for age, sex, and population stratification. Within the schizophrenia cohorts, after correction for multiple testing, p.(Ala391Thr) was not significantly associated with any schizophrenia-related phenotypes. In the unaffected participants from the UK Biobank, the schizophrenia-risk allele at p.(Ala391Thr) was associated with significantly poorer cognitive ability and fluid intelligence, a lower probability of obtaining GCSEs or a degree-level qualification, and fewer years in education. There was no association between p.(Ala391Thr) and self-reported psychotic experiences in this cohort. The schizophrenia-risk allele was associated with poorer cognitive ability, but not psychotic experiences, in a volunteer sample drawn from of the general population. To determine whether p.(Ala391Thr) is associated with cognitive phenotypes in people with schizophrenia, and to understand the role of p.(Ala391Thr) in the aetiology of cognitive impairment in schizophrenia, larger independent samples are required.

Background: The ganglionic eminences (GE) are fetal-specific structures that give rise to gamma-aminobutyric acid (GABA)- and acetylcholine-releasing neurons of the forebrain. Given the evidence for GABAergic, cholinergic, and neurodevelopmental disturbances in schizophrenia, we tested the potential involvement of GE neuron development in mediating genetic risk for the condition., Study Design: We combined data from a recent large-scale genome-wide association study of schizophrenia with single-cell RNA sequencing data from the human GE to test the enrichment of schizophrenia risk variation in genes with high expression specificity for developing GE cell populations. We additionally performed the single nuclei Assay for Transposase-Accessible Chromatin with Sequencing (snATAC-Seq) to map potential regulatory genomic regions operating in individual cell populations of the human GE, using these to test for enrichment of schizophrenia common genetic variant liability and to functionally annotate non-coding variants-associated with the disorder., Study Results: Schizophrenia common variant liability was enriched in genes with high expression specificity for developing neuron populations that are predicted to form dopamine D1 and D2 receptor-expressing GABAergic medium spiny neurons of the striatum, cortical somatostatin-positive GABAergic interneurons, calretinin-positive GABAergic neurons, and cholinergic neurons. Consistent with these findings, schizophrenia genetic risk was concentrated in predicted regulatory genomic sequence mapped in developing neuronal populations of the GE., Conclusions: Our study implicates prenatal development of specific populations of GABAergic and cholinergic neurons in later susceptibility to schizophrenia, and provides a map of predicted regulatory genomic elements operating in cells of the GE., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)

Importance: Large-scale biobanks provide important opportunities for mental health research, but selection biases raise questions regarding the comparability of individuals with those in clinical research settings., Objective: To compare the genetic liability to psychiatric disorders in individuals with schizophrenia in the UK Biobank with individuals in the Psychiatric Genomics Consortium (PGC) and to compare genetic liability and phenotypic features with participants recruited from clinical settings., Design, Setting, and Participants: This cross-sectional study included participants from the population-based UK Biobank and schizophrenia samples recruited from clinical settings (CLOZUK, CardiffCOGS, Cardiff F-Series, and Cardiff Affected Sib-Pairs). Data were collected between January 1993 and July 2021. Data analysis was conducted between July 2021 and June 2023., Main Outcomes and Measures: A genome-wide association study of UK Biobank schizophrenia case-control status was conducted, and the results were compared with those from the PGC via genetic correlations. To test for differences with the clinical samples, polygenic risk scores (PRS) were calculated for schizophrenia, bipolar disorder, depression, and intelligence using PRS-CS. PRS and phenotypic comparisons were conducted using pairwise logistic regressions. The proportions of individuals with copy number variants associated with schizophrenia were compared using Firth logistic regression., Results: The sample of 517 375 participants included 1438 UK Biobank participants with schizophrenia (550 [38.2%] female; mean [SD] age, 54.7 [8.3] years), 499 475 UK Biobank controls (271 884 [54.4%] female; mean [SD] age, 56.5 [8.1] years), and 4 schizophrenia research samples (4758 [28.9%] female; mean [SD] age, 38.2 [21.0] years). Liability to schizophrenia in UK Biobank was highly correlated with the latest genome-wide association study from the PGC (genetic correlation, 0.98; SE, 0.18) and showed the expected patterns of correlations with other psychiatric disorders. The schizophrenia PRS explained 6.8% of the variance in liability for schizophrenia case status in UK Biobank. UK Biobank participants with schizophrenia had significantly lower schizophrenia PRS than 3 of the clinically ascertained samples and significantly lower rates of schizophrenia-associated copy number variants than the CLOZUK sample. UK Biobank participants with schizophrenia had higher educational attainment and employment rates than the clinically ascertained schizophrenia samples, lower rates of smoking, and a later age of onset of psychosis., Conclusions and Relevance: Individuals with schizophrenia in the UK Biobank, and likely other volunteer-based biobanks, represent those less severely affected. Their inclusion in wider studies should enhance the representation of the full spectrum of illness severity.

Mental health and neurodevelopmental disorders are highly heritable and can affect morbidity and mortality. A large, growing body of evidence has implicated both common and rare variation in the risk of these disorders. Testing for rare variants, such as copy number variants, has been available in clinical practice for some time in the context of developmental disorders. However, until recently, individuals with mental health and neurodevelopmental disorders in the UK have not tended to access genetic counselling and testing. Here, we describe the development of the All Wales Psychiatric Genomics Service, a collaborative effort between psychiatric and clinical genetics services and the first of its kind in the UK. We provide an overview of the structure and function of the service, our referral criteria, a summary of the 40 referrals we have received to date and our future plans., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Recent research has highlighted the role of complement genes in shaping the microstructure of the brain during early development, and in contributing to common allele risk for Schizophrenia. We hypothesised that common risk variants for schizophrenia within complement genes will associate with structural changes in white matter microstructure within tracts innervating the frontal lobe. Results showed that risk alleles within the complement gene set, but also intergenic alleles, significantly predict axonal density in white matter tracts connecting frontal cortex with parietal, temporal and occipital cortices. Specifically, risk alleles within the Major Histocompatibility Complex region in chromosome 6 appeared to drive these associations. No significant associations were found for the orientation dispersion index. These results suggest that changes in axonal packing - but not in axonal coherence - determined by common risk alleles within the MHC genomic region - including variants related to the Complement system - appear as a potential neurobiological mechanism for schizophrenia., (© 2024. The Author(s).)

Clozapine is the only licensed medication for treatment-resistant schizophrenia (TRS). Few predictors for variation in response to clozapine have been identified, but clozapine metabolism is known to influence therapeutic response and adverse side effects. Here, we expand on genome-wide studies of clozapine metabolism, previously focused on common genetic variation, by analysing whole-exome sequencing data from 2062 individuals with schizophrenia taking clozapine in the UK. We investigated whether rare genomic variation in genes and gene sets involved in the clozapine metabolism pathway influences plasma concentrations of clozapine metabolites, assessed through the longitudinal analysis of 6585 pharmacokinetic assays. We observed a statistically significant association between the burden of rare damaging coding variants (MAF ≤ 1 %) in gene sets broadly related to drug pharmacokinetics and lower clozapine (β = -0.054, SE = 0.019, P-value = 0.005) concentrations in plasma. We estimate that the effects in clozapine plasma concentrations of a single damaging allele in this gene set are akin to reducing the clozapine dose by about 35 mg/day. The gene-based analysis identified rare variants in CYP1A2, which encodes the enzyme responsible for converting clozapine to norclozapine, as having the strongest effects of any gene on clozapine metabolism (β = 0.324, SE = 0.124, P = 0.009). Our findings support the hypothesis that rare genetic variants in known drug-metabolising enzymes and transporters can markedly influence clozapine plasma concentrations; these results suggest that pharmacogenomic efforts trying to predict clozapine metabolism and personalise drug therapy could benefit from the inclusion of rare damaging variants in pharmacogenes beyond those already identified and catalogued as PGx star alleles., Competing Interests: Declaration of competing interest AK is a full-time employee of Magna Laboratories Ltd. MH and JJ are full-time employees of Leyden Delta B.V. MJO, MCOD, and JTRW are supported by a collaborative research grant from Takeda Pharmaceuticals Ltd. for a project unrelated to the work presented here. ER, AFP, MJO, MCOD, and JTRW also reported receiving grants from Akrivia Health for a project unrelated to this submission. Takeda and Akrivia played no part in this study's conception, design, implementation, or interpretation., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objectives: People with bipolar disorder who also report binge eating have increased psychopathology and greater impairment than those without binge eating. Whether this co-occurrence is related to binge eating as a symptom or presents differently across full-syndrome eating disorders with binge eating is unclear., Methods: We first compared networks of 13 lifetime mania symptoms in 34,226 participants from the United Kingdom's National Institute for Health and Care Research BioResource with (n = 12,104) and without (n = 22,122) lifetime binge eating. Second, in the subsample with binge eating, we compared networks of mania symptoms in participants with lifetime anorexia nervosa binge-eating/purging (n = 825), bulimia nervosa (n = 3737), and binge-eating disorder (n = 3648)., Results: People with binge eating endorsed every mania symptom significantly more often than those without binge eating. Within the subsample, people with bulimia nervosa most often had the highest endorsement rate of each mania symptom. We found significant differences in network parameter statistics, including network structure (M = 0.25, p = 0.001) and global strength (S = 1.84, p = 0.002) when comparing the binge eating with no binge-eating participants. However, network structure differences were sensitive to reductions in sample size and the greater density of the latter network was explained by the large proportion of participants (34%) without mania symptoms. The structure of the anorexia nervosa binge-eating/purging network differed from the bulimia nervosa network (M = 0.66, p = 0.001), but the result was unstable., Conclusions: Our results suggest that the presence and structure of mania symptoms may be more associated with binge eating as a symptom rather than any specific binge-type eating disorder. Further research with larger sample sizes is required to confirm our findings., (© 2023 The Authors. Bipolar Disorders published by John Wiley & Sons Ltd.)

Clozapine is effective at reducing symptoms of treatment-resistant schizophrenia, but it can also induce several adverse outcomes including neutropenia and agranulocytosis. We used linear mixed-effect models and structural equation modelling to determine whether pharmacokinetic and genetic variables influence absolute neutrophil count in a longitudinal UK-based sample of clozapine users not currently experiencing neutropenia (N = 811). Increased daily clozapine dose was associated with elevated neutrophil count, amounting to a 133 cells/mm 3 rise per standard deviation increase in clozapine dose. One-third of the total effect of clozapine dose was mediated by plasma clozapine and norclozapine levels, which themselves demonstrated opposing, independent associations with absolute neutrophil count. Finally, CYP1A2 pharmacogenomic activity score was associated with absolute neutrophil count, supporting lower neutrophil levels in CYP1A2 poor metabolisers during clozapine use. This information may facilitate identifying at-risk patients and then introducing preventative interventions or individualised pharmacovigilance procedures to help mitigate these adverse haematological reactions., (© 2023. Springer Nature Limited.)

Background: Depressive episodes are common after first-episode psychosis (FEP), affecting more than 40% of people, adding to individual burden, poor outcomes, and healthcare costs. If the risks of developing depression were lower, this could have a beneficial effect on morbidity and mortality, as well as improving outcomes. Sertraline is a selective serotonin reuptake inhibitor and a common first-line medication for the treatment of depression in adults. It has been shown to be safe when co-prescribed with antipsychotic medication, and there is evidence that it is an effective treatment for depression in established schizophrenia. We present a protocol for a multi-centre, double-blind, randomised, placebo-controlled clinical trial called ADEPP that aims to investigate the efficacy and cost-effectiveness of sertraline in preventing depression after FEP., Methods: The recruitment target is 452 participants between the ages of 18 and 65 years who are within 12 months of treatment initiation for FEP. Having provided informed consent, participants will be randomised to receive either 50 mg of sertraline daily or matched placebo for 6 months, in addition to treatment as usual. The primary outcome measure will be a comparison of the number of new cases of depression between the treatment and placebo arms over the 6-month intervention phase. Secondary outcomes include suicidal behaviour, anxiety, rates of relapse, functional outcome, quality of life, and resource use., Discussion: The ADEPP trial will test whether the addition of sertraline following FEP is a clinically useful, acceptable, and cost-effective way of improving outcomes following FEP., Trial Registration: ISRCTN12682719 registration date 24/11/2020., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Objective: In 2008, the UK entered a period of economic recession followed by sustained austerity measures. We investigate changes in inequalities by area deprivation and urbanicity in incidence of severe mental illness (SMI, including schizophrenia-related disorders and bipolar disorder) between 2000 and 2017., Methods: We analysed 4.4 million individuals from primary and secondary care routinely collected datasets (2000-2017) in Wales and estimated the incidence of SMI by deprivation and urbanicity measured by the Welsh Index of Multiple Deprivation (WIMD) and urban/rural indicator respectively. Using linear modelling and joinpoint regression approaches, we examined time trends of the incidence and incidence rate ratios (IRR) of SMI by the WIMD and urban/rural indicator adjusted for available confounders., Results: We observed a turning point of time trends of incidence of SMI at 2008/2009 where slope changes of time trends were significantly increasing. IRRs by deprivation/urbanicity remained stable or significantly decreased over the study period except for those with bipolar disorder sourced from secondary care settings, with increasing trend of IRRs (increase in IRR by deprivation after 2010: 1.6 % per year, 95 % CI: 1.0 %-2.2 %; increase in IRR by urbanicity 1.0 % per year, 95 % CI: 0.6 %-1.3 %)., Conclusions: There was an association between recession/austerity and an increase in the incidence of SMI over time. There were variations in the effects of deprivation/urbanicity on incidence of SMI associated with short- and long-term socioeconomic change. These findings may support targeted interventions and social protection systems to reduce incidence of SMI., Competing Interests: Declaration of competing interest None declared., (Copyright © 2023. Published by Elsevier B.V.)

Dysfunction of glutamate neurotransmission has been implicated in the pathophysiology of schizophrenia and may be particularly relevant in severe, treatment-resistant symptoms. The underlying mechanism may involve hypofunction of the NMDA receptor. We investigated whether schizophrenia-related pathway polygenic scores, composed of genetic variants within NMDA receptor encoding genes, are associated with cortical glutamate in schizophrenia. Anterior cingulate cortex (ACC) glutamate was measured in 70 participants across 4 research sites using Proton Magnetic Resonance Spectroscopy ( 1 H-MRS). Two NMDA receptor gene sets were sourced from the Molecular Signatories Database and NMDA receptor pathway polygenic scores were constructed using PRSet. The NMDA receptor pathway polygenic scores were weighted by single nucleotide polymorphism (SNP) associations with treatment-resistant schizophrenia, and associations with ACC glutamate were tested. We then tested whether NMDA receptor pathway polygenic scores with SNPs weighted by associations with non-treatment-resistant schizophrenia were associated with ACC glutamate. A higher NMDA receptor complex pathway polygenic score was significantly associated with lower ACC glutamate (β = -0.25, 95 % CI = -0.49, -0.02, competitive p = 0.03). When SNPs were weighted by associations with non-treatment-resistant schizophrenia, there was no association between the NMDA receptor complex pathway polygenic score and ACC glutamate (β = 0.05, 95 % CI = -0.18, 0.27, competitive p = 0.79). These results provide initial evidence of an association between common genetic variation implicated in NMDA receptor function and ACC glutamate levels in schizophrenia. This association was specific to when the NMDA receptor complex pathway polygenic score was weighted by SNP associations with treatment-resistant schizophrenia., Competing Interests: Declaration of competing interest JTW is an investigator on a grant from Takeda Pharmaceuticals Ltd. to Cardiff University, for a project unrelated to the work presented here. SES is employed on this grant. GJB receives honoraria for teaching from GE Healthcare. All other authors have no conflicts of interest to disclose., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Psychiatric disorders are associated with cognitive impairment. We have developed a web-based, 9-task cognitive battery to measure the core domains affected in people with psychiatric disorders. To date, this assessment has been used to collect data on a clinical sample of participants with psychiatric disorders., Objective: The aims of this study were (1) to establish a briefer version of the battery (called the Cardiff Online Cognitive Assessment [CONCA]) that can give a valid measure of cognitive ability ("g") and (2) to collect normative data and demonstrate CONCA's application in a health population sample., Methods: Based on 6 criteria and data from our previous study, we selected 5 out of the original 9 tasks to include in CONCA. These included 3 core tasks that were sufficient to derive a measure of "g" and 2 optional tasks. Participants from a web-based national cohort study (HealthWise Wales) were invited to complete CONCA. Completion rates, sample characteristics, performance distributions, and associations between cognitive performance and demographic characteristics and mental health measures were examined., Results: A total of 3679 participants completed at least one CONCA task, of which 3135 completed all 3 core CONCA tasks. Performance on CONCA was associated with age (B=-0.05, SE 0.002; P<.001), device (tablet computer: B=-0.26, SE 0.05; P<.001; smartphone: B=-0.46, SE 0.05; P<.001), education (degree: B=1.68, SE 0.14; P<.001), depression symptoms (B=-0.04, SE 0.01; P<.001), and anxiety symptoms (B=-0.04, SE 0.01; P<.001)., Conclusions: CONCA provides a valid measure of "g," which can be derived using as few as 3 tasks that take no more than 15 minutes. Performance on CONCA showed associations with demographic characteristics in the expected direction and was associated with current depression and anxiety symptoms. The effect of device on cognitive performance is an important consideration for research using web-based assessments., (©Amy Joanne Lynham, Ian R Jones, James T R Walters. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.09.2023.)

There has been substantial progress in understanding the genetics of schizophrenia over the past 15 years. This has revealed a highly polygenic condition with the majority of the currently explained heritability coming from common alleles of small effect but with additional contributions from rare copy number and coding variants. Many specific genes and loci have been implicated that provide a firm basis upon which mechanistic research can proceed. These point to disturbances in neuronal, and particularly synaptic, functions that are not confined to a small number of brain regions and circuits. Genetic findings have also revealed the nature of schizophrenia's close relationship to other conditions, particularly bipolar disorder and childhood neurodevelopmental disorders, and provided an explanation for how common risk alleles persist in the population in the face of reduced fecundity. Current genomic approaches only potentially explain around 40% of heritability, but only a small proportion of this is attributable to robustly identified loci. The extreme polygenicity poses challenges for understanding biological mechanisms. The high degree of pleiotropy points to the need for more transdiagnostic research and the shortcomings of current diagnostic criteria as means of delineating biologically distinct strata. It also poses challenges for inferring causality in observational and experimental studies in both humans and model systems. Finally, the Eurocentric bias of genomic studies needs to be rectified to maximise benefits and ensure these are felt across diverse communities. Further advances are likely to come through the application of new and emerging technologies, such as whole-genome and long-read sequencing, to large and diverse samples. Substantive progress in biological understanding will require parallel advances in functional genomics and proteomics applied to the brain across developmental stages. For these efforts to succeed in identifying disease mechanisms and defining novel strata they will need to be combined with sufficiently granular phenotypic data., (© 2023. The Author(s).)

Background: Schizophrenia (SCZ) is caused by an interplay of polygenic risk and environmental factors, which may alter regulators of gene expression leading to pathogenic misexpression of SCZ risk genes. The CPEB family of RNA-binding proteins (CPEB1-4) regulates translation of target RNAs (approximately 40% of overall genes). We previously identified CPEB4 as a key dysregulated translational regulator in autism spectrum disorder (ASD) because its neuronal-specific microexon (exon 4) is mis-spliced in ASD brains, causing underexpression of numerous ASD risk genes. The genetic factors and pathogenic mechanisms shared between SCZ and ASD led us to hypothesize CPEB4 mis-splicing in SCZ leading to underexpression of multiple SCZ-related genes., Methods: We performed MAGMA-enrichment analysis on Psychiatric Genomics Consortium genome-wide association study data and analyzed RNA sequencing data from the PsychENCODE Consortium. Reverse transcriptase polymerase chain reaction and Western blot were performed on postmortem brain tissue, and the presence/absence of antipsychotics was assessed through toxicological analysis. Finally, mice with mild overexpression of exon 4-lacking CPEB4 (CPEB4Δ4) were generated and analyzed biochemically and behaviorally., Results: First, we found enrichment of SCZ-associated genes for CPEB4-binder transcripts. We also found decreased usage of CPEB4 microexon in SCZ probands, which was correlated with decreased protein levels of CPEB4-target SCZ-associated genes only in antipsychotic-free individuals. Interestingly, differentially expressed genes fit those reported for SCZ, specifically in the SCZ probands with decreased CPEB4-microexon inclusion. Finally, we demonstrated that mice with mild overexpression of CPEB4Δ4 showed decreased protein levels of CPEB4-target SCZ genes and SCZ-linked behaviors., Conclusions: We identified aberrant CPEB4 splicing and downstream misexpression of SCZ risk genes as a novel etiological mechanism in SCZ., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Current definitions and clinical heterogeneity in bipolar disorder are major concerns as they obstruct aetiological research and impede drug development. Therefore, stratification of bipolar disorder is a high priority. To inform stratification, our analysis aimed to examine the patterns and relationships between polygenic liability for bipolar disorder, major depressive disorder (MDD), and schizophrenia with multidimensional symptom representations of bipolar disorder., Methods: In this analysis, data from the UK Bipolar Disorder Research Network (BDRN) were assessed with the Operational Checklist for Psychotic Disorders. Individuals with bipolar disorder as defined in DSM-IV, of European ancestry (self-reported), aged 18 years or older at time of interview, living in the UK, and registered with the BDRN were eligible for inclusion. Psychopathological variables obtained via interview by trained research psychologists or psychiatrists and psychiatric case notes were used to identify statistically distinct symptom dimensions, calibrated with exploratory factor analysis and validated with confirmatory factor analysis (CFA). CFA was extended to include three polygenic risk scores (PRSs) indexing liability for bipolar disorder, MDD, and schizophrenia in a multiple indicator multiple cause (MIMIC) structural equation model to estimate PRS relationships with symptom dimensions., Findings: Of 4198 individuals potentially eligible for inclusion, 4148 (2804 [67·6%] female individuals and 1344 [32·4%] male individuals) with a mean age at interview of 45 years (SD 12·03) were available for analysis. Three reliable dimensions (mania, depression, and psychosis) were identified. The MIMIC model fitted the data well (root mean square error of approximation 0·021, 90% CI 0·019-0·023; comparative fit index 0·99) and suggests statistically distinct symptom dimensions also have distinct polygenic profiles. The PRS for MDD was strongly associated with the depression dimension (standardised β 0·125, 95% CI 0·080-0·171) and the PRS for schizophrenia was strongly associated with the psychosis dimension (0·108, 0·082-0·175). For the mania dimension, the PRS for bipolar disorder was weakly associated (0·050, 0·002-0·097)., Interpretation: Our findings support the hypothesis that genetic heterogeneity underpins clinical heterogeneity, suggesting that different symptom dimensions within bipolar disorder have partly distinct causes. Furthermore, our results suggest that a specific symptom dimension has a similar cause regardless of the primary psychiatric diagnosis, supporting the use of symptom dimensions in precision psychiatry., Funding: Wellcome Trust and UK Medical Research Council., Competing Interests: Declaration of interests We declare no competing interests., (Crown Copyright © 2023 Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.)

Background: The Genetic Links to Anxiety and Depression (GLAD) Study is a large cohort of individuals with lifetime anxiety and/or depression, designed to facilitate re-contact of participants for mental health research. At the start of the pandemic, participants from three cohorts, including the GLAD Study, were invited to join the COVID-19 Psychiatry and Neurological Genetics (COPING) study to monitor mental and neurological health. However, previous research suggests that participation in longitudinal studies follows a systematic, rather than random, process, which can ultimately bias results. Therefore, this study assessed participation biases following the re-contact of GLAD Study participants., Methods: In April 2020, all current GLAD Study participants (N = 36,770) were invited to the COPING study. Using logistic regression, we investigated whether sociodemographic, mental, and physical health characteristics were associated with participation in the COPING baseline survey (aim one). Subsequently, we used a zero-inflated negative binomial regression to examine whether these factors were also related to participation in the COPING follow-up surveys (aim two)., Results: For aim one, older age, female gender identity, non-binary or self-defined gender identities, having one or more physical health disorders, and providing a saliva kit for the GLAD Study were associated with an increased odds of completing the COPING baseline survey. In contrast, lower educational attainment, Asian or Asian British ethnic identity, Black or Black British ethnic identity, higher alcohol consumption at the GLAD sign-up survey, and current or ex-smoking were associated with a reduced odds. For aim two, older age, female gender, and saliva kit provision were associated with greater COPING follow-up survey completion. Lower educational attainment, higher alcohol consumption at the GLAD Study sign-up, ex-smoking, and self-reported attention deficit hyperactivity disorder had negative relationships., Conclusions: Participation biases surrounding sociodemographic and physical health characteristics were particularly evident when re-contacting the GLAD Study volunteers. Factors associated with participation may vary depending on study design. Researchers should examine the barriers and mechanisms underlying participation bias in order to combat these issues and address recruitment biases in future studies., (© 2023. The Author(s).)

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)-present in some but not all cells-remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e-4), with recurrent somatic deletions of exons 1-5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis -regulatory elements upon 5' deletions in NRXN1 . We also observed recurrent intragenic deletions of ABCB11 , encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk., Competing Interests: The authors declare no competing interests., (© 2023 The Author(s).)

Glutamate and increased inflammation have been separately implicated in the pathophysiology of schizophrenia and the extent of clinical response to antipsychotic treatment. Despite the mechanistic links between pro-inflammatory and glutamatergic pathways, the relationships between peripheral inflammatory markers and brain glutamate in schizophrenia have not yet been investigated. In this study, we tested the hypothesis that peripheral levels of pro-inflammatory cytokines would be positively associated with brain glutamate levels in schizophrenia. Secondary analyses determined whether this relationship differed according to antipsychotic treatment response. The sample consisted of 79 patients with schizophrenia, of whom 40 were rated as antipsychotic responders and 39 as antipsychotic non-responders. Brain glutamate levels were assessed in the anterior cingulate cortex (ACC) and caudate using proton magnetic resonance spectroscopy ( 1 H-MRS) and blood samples were collected for cytokine assay on the same study visit (IL-6, IL-8, IL-10, TNF- α and IFN-γ). Across the whole patient sample, there was a positive relationship between interferon-gamma (IFN-γ) and caudate glutamate levels (r = 0.31, p = 0.02). In the antipsychotic non-responsive group only, there was a positive relationship between interleukin-8 (IL-8) and caudate glutamate (r = 0.46, p = 0.01). These findings provide evidence to link specific peripheral inflammatory markers and caudate glutamate in schizophrenia and may suggest that this relationship is most marked in patients who show a poor response to antipsychotic treatment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Impaired cognition in schizophrenia is associated with worse functional outcomes. While genetic factors are known to contribute to variation in cognition in schizophrenia, few rare coding variants with strong effects have been identified, and the relative effects from de novo, inherited and non-transmitted alleles are unknown. We used array and exome sequencing data from 656 proband-parent trios to examine the contribution of common and rare variants to school performance, and by implication cognitive function, in schizophrenia. Parental transmission of common alleles contributing to higher educational attainment (p value = 0.00015; OR = 2.63) and intelligence (p value = 0.00009; OR = 2.80), but not to schizophrenia, were associated with higher proband school performance. No significant effects were seen for non-transmitted parental common alleles. Probands with lower school performance were enriched for damaging de novo coding variants in genes associated with developmental disorders (DD) (p value = 0.00026; OR = 11.6). Damaging, ultra-rare coding variants in DD genes that were transmitted or non-transmitted from parents, had no effects on school performance. Among probands with lower school performance, those with damaging de novo coding variants in DD genes had a higher rate of comorbid mild intellectual disability (p value = 0.0002; OR = 15.6). Overall, we provide evidence for rare and common genetic contributions to school performance in schizophrenia. The strong effects for damaging de novo coding variants in DD genes provide further evidence that cognitive impairment in schizophrenia has a shared aetiology with developmental disorders. Furthermore, we report no evidence in this sample that non-transmitted parental common alleles for cognitive traits contributed to school performance in schizophrenia via indirect effects on the environment., (© 2023. The Author(s).)

Background: Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia, with recent research finding systematic biological differences between antipsychotic resistant and responsive patients. Our aim was to determine whether cognitive impairment at first episode significantly differs between future antipsychotic responders and resistant cases., Methods: Analysis of data from seven international cohorts of first-episode psychosis (FEP) with cognitive data at baseline (N = 683) and follow-up data on antipsychotic treatment response: 605 treatment responsive and 78 treatment resistant cases. Cognitive measures were grouped into seven cognitive domains based on the pre-existing literature. We ran multiple imputation for missing data and used logistic regression to test for associations between cognitive performance at FEP and treatment resistant status at follow-up., Results: On average patients who were future classified as treatment resistant reported poorer performance across most cognitive domains at baseline. Univariate logistic regressions showed that antipsychotic treatment resistance cases had significantly poorer IQ/general cognitive functioning at FEP (OR = 0.70, p = .003). These findings remained significant after adjusting for additional variables in multivariable analyses (OR = 0.76, p = .049)., Conclusions: Although replication in larger studies is required, it appears that deficits in IQ/general cognitive functioning at first episode are associated with future treatment resistance. Cognitive variables may be able to provide further insight into neurodevelopmental factors associated with treatment resistance or act as early predictors of treatment resistance, which could allow prompt identification of refractory illness and timely interventions., Competing Interests: Declaration of competing interest J.T.R.W. is an investigator on a grant from Takeda Pharmaceuticals Ltd. to Cardiff University, for a project unrelated to the work presented here. S.E.S. is employed on this grant. M.D.F. has received a fee for educational seminars from Lundbeck and Janssen. O.A.A. is a consultant to HealthLytix and has received speakers honorarium from Lundbeck and Sunovion. T.R.E.B. has been a member of an advisory board for Gedeon Richter. B.C.F. has received honoraria for participation as a consultant and/or as a speaker at educational events from ADAMED, Mylan, Angelini, Janssen Johnson & Johnson, Lundbeck, and Otsuka Pharmaceuticals. R.M.M. has received payments for non-promotional lectures from Janssen, Otsuka, Sunovian, and Lundbeck. J.H.M. has received research funding from H Lundbeck., (Copyright © 2023. Published by Elsevier B.V.)

Background: The antipsychotic, clozapine, is the only licensed drug against the treatment-resistant symptoms that affect 20-30% of people with schizophrenia. Clozapine is markedly underprescribed, partly because of concerns about its narrow therapeutic range and adverse drug reaction profile. Both concerns are linked to drug metabolism, which varies across populations globally and is partly genetically determined. Our study aimed to use a cross-ancestry genome-wide association study (GWAS) design to investigate variations in clozapine metabolism within and between genetically inferred ancestral backgrounds, to discover genomic associations to clozapine plasma concentrations, and to assess the effects of pharmacogenomic predictors across different ancestries., Methods: In this GWAS, we analysed data from the UK Zaponex Treatment Access System clozapine monitoring service as part of the CLOZUK study. We included all available individuals with clozapine pharmacokinetic assays requested by their clinicians. We excluded people younger than 18 years, or whose records contained clerical errors, or with blood drawn 6-24 h after dose, a clozapine or norclozapine concentration less than 50 ng/mL, a clozapine concentration of more than 2000 ng/mL, a clozapine-to-norclozapine ratio outside of the 0·5-3·0 interval, or a clozapine dose of more than 900 mg/day. Using genomic information, we identified five biogeographical ancestries: European, sub-Saharan African, north African, southwest Asian, and east Asian. We did pharmacokinetic modelling, a GWAS, and a polygenic risk score association analysis using longitudinal regression analysis with three primary outcome variables: two metabolite plasma concentrations (clozapine and norclozapine) and the clozapine-to-norclozapine ratio., Findings: 19 096 pharmacokinetic assays were available for 4760 individuals in the CLOZUK study. After data quality control, 4495 individuals (3268 [72·7%] male and 1227 [27·3%] female; mean age 42·19 years [range 18-85]) linked to 16 068 assays were included in this study. We found a faster average clozapine metabolism in people of sub-Saharan African ancestry than in those of European ancestry. By contrast, individuals with east Asian or southwest Asian ancestry were more likely to be slow clozapine metabolisers than those with European ancestry. Eight pharmacogenomic loci were identified in the GWAS, seven with significant effects in non-European groups. Polygenic scores generated from these loci were associated with clozapine outcome variables in the whole sample and within individual ancestries; the maximum variance explained was 7·26% for the metabolic ratio., Interpretation: Longitudinal cross-ancestry GWAS can discover pharmacogenomic markers of clozapine metabolism that, individually or as polygenic scores, have consistent effects across ancestries. Our findings suggest that ancestral differences in clozapine metabolism could be considered for optimising clozapine prescription protocols for diverse populations., Funding: UK Academy of Medical Sciences, UK Medical Research Council, and European Commission., Competing Interests: Declaration of interests AK is a full-time employee of Magna Laboratories. MH and JJ are full-time employees of Leyden Delta. MJO, MCOD, and JTRW are supported by a collaborative research grant from Takeda Pharmaceuticals outside the submitted work. All other authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders., Methods: We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific., Results: We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues ( p = 0.001)., Conclusions: Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.

Background: Anxiety and depressive disorders often co-occur and the order of their emergence may be associated with different clinical outcomes. However, minimal research has been conducted on anxiety-anxiety comorbidity. This study examined factors associated with anxiety comorbidity and anxiety-MDD temporal sequence., Methods: Online, self-report data were collected from the UK-based GLAD and COPING NBR cohorts (N = 38,775). Logistic regression analyses compared differences in sociodemographic, trauma, and clinical factors between single anxiety, anxiety-anxiety comorbidity, anxiety-MDD (major depressive disorder) comorbidity, and MDD-only. Additionally, anxiety-first and MDD-first anxiety-MDD were compared. Differences in familial risk were assessed in those participants with self-reported family history or genotype data., Results: Anxiety-anxiety and anxiety-MDD had higher rates of self-reported anxiety or depressive disorder diagnoses, younger age of onset, and higher recurrence than single anxiety. Anxiety-MDD displayed greater clinical severity/complexity than MDD only. Anxiety-anxiety had more severe current anxiety symptoms, less severe current depressive symptoms, and reduced likelihood of self-reporting an anxiety/depressive disorder diagnosis than anxiety-MDD. Anxiety-first anxiety-MDD had a younger age of onset, more severe anxiety symptoms, and less likelihood of self-reporting a diagnosis than MDD-first. Minimal differences in familial risk were found., Limitations: Self-report, retrospective measures may introduce recall bias. The familial risk analyses were likely underpowered., Conclusions: Anxiety-anxiety comorbidity displayed a similarly severe and complex profile of symptoms as anxiety-MDD but distinct features. For anxiety-MDD, first-onset anxiety had an earlier age of onset and greater severity than MDD-first. Anxiety disorders and comorbidity warrant further investigation and attention in research and practice., Competing Interests: Conflict of interest Prof Breen has received honoraria, research or conference grants and consulting fees from Illumina, Otsuka, and COMPASS Pathfinder Ltd. Prof Hotopf is principal investigator of the RADAR-CNS consortium, an IMI public private partnership, and as such receives research funding from Janssen, UCB, Biogen, Lundbeck and MSD. Prof McIntosh has received research support from Eli Lilly, Janssen, and the Sackler Foundation, and has also received speaker fees from Illumina and Janssen. Prof Walters has received grant funding from Takeda for work unrelated to the GLAD Study. The remaining authors have nothing to disclose., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood., Aims: Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research., Method: As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant., Results: We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation., Conclusions: DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.

Background: Treatment-resistant schizophrenia affects approximately 30% of individuals with the disorder. Clozapine is the medication of choice in treatment-resistant schizophrenia, but optimizing administration and dose titration is complex. The identification of factors influencing clozapine prescription and response, including genetics, is of interest in a precision psychiatry framework., Methods: We used linear regression models accounting for demographic, pharmacological, and clinical covariates to determine whether a polygenic risk score (PRS) for schizophrenia would be associated with the highest dose recorded during clozapine treatment. Analyses were performed across 2 independent multiancestry samples of individuals from a UK patient monitoring system, CLOZUK2 (n = 3133) and CLOZUK3 (n = 909), and a European sample from a Norwegian therapeutic drug monitoring service (n = 417). In a secondary analysis merging both UK cohorts, logistic regression models were used to estimate the relationship between schizophrenia PRSs and clozapine doses classified as low, standard, or high., Results: After controlling for relevant covariates, the schizophrenia PRS was correlated with the highest clozapine dose on record for each individual across all samples: CLOZUK2 (β = 12.22, SE = 3.78, p = .001), CLOZUK3 (β = 12.73, SE = 5.99, p = .034), and the Norwegian cohort (β = 46.45, SE = 18.83, p = .014). In a secondary analysis, the schizophrenia PRS was associated with taking clozapine doses >600 mg/day (odds ratio = 1.279, p = .006)., Conclusions: The schizophrenia PRS was associated with the highest clozapine dose prescribed for an individual in records from 3 independent samples, suggesting that the genetic liability for schizophrenia might index factors associated with therapeutic decisions in cohorts of patients with treatment-resistant schizophrenia., (Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Polygenic risk prediction remains an important aim of genetic association studies. Currently, the predictive power of schizophrenia polygenic risk scores (PRSs) is not large enough to allow highly accurate discrimination between cases and controls and thus is not adequate for clinical integration. Since PRSs are rarely used to reveal biological functions or to validate candidate pathways, to fill this gap, we investigated whether their predictive ability could be improved by building genome-wide (GW-PRSs) and pathway-specific PRSs, using distance- or expression quantitative trait loci (eQTLs)- based mapping between genetic variants and genes. We focused on five pathways (glutamate, oxidative stress, GABA/interneurons, neuroimmune/neuroinflammation and myelin) which belong to a critical hub of schizophrenia pathophysiology, centred on redox dysregulation/oxidative stress. Analyses were first performed in the Lausanne Treatment and Early Intervention in Psychosis Program (TIPP) study (n = 340, cases/controls: 208/132), a sample of first-episode of psychosis patients and matched controls, and then validated in an independent study, the epidemiological and longitudinal intervention program of First-Episode Psychosis in Cantabria (PAFIP) (n = 352, 224/128). Our results highlighted two main findings. First, GW-PRSs for schizophrenia were significantly associated with early psychosis status. Second, oxidative stress was the only significantly associated pathway that showed an enrichment in both the TIPP (p = 0.03) and PAFIP samples (p = 0.002), and exclusively when gene-variant linking was done using eQTLs. The results suggest that the predictive accuracy of polygenic risk scores could be improved with the inclusion of information from functional annotations, and through a focus on specific pathways, emphasizing the need to build and study functionally informed risk scores., (© 2022. The Author(s).)

Introduction: Our aim was to, firstly, identify characteristics at first-episode of psychosis that are associated with later antipsychotic treatment resistance (TR) and, secondly, to develop a parsimonious prediction model for TR., Methods: We combined data from ten prospective, first-episode psychosis cohorts from across Europe and categorised patients as TR or non-treatment resistant (NTR) after a mean follow up of 4.18 years (s.d. = 3.20) for secondary data analysis. We identified a list of potential predictors from clinical and demographic data recorded at first-episode. These potential predictors were entered in two models: a multivariable logistic regression to identify which were independently associated with TR and a penalised logistic regression, which performed variable selection, to produce a parsimonious prediction model. This model was internally validated using a 5-fold, 50-repeat cross-validation optimism-correction., Results: Our sample consisted of N = 2216 participants of which 385 (17 %) developed TR. Younger age of psychosis onset and fewer years in education were independently associated with increased odds of developing TR. The prediction model selected 7 out of 17 variables that, when combined, could quantify the risk of being TR better than chance. These included age of onset, years in education, gender, BMI, relationship status, alcohol use, and positive symptoms. The optimism-corrected area under the curve was 0.59 (accuracy = 64 %, sensitivity = 48 %, and specificity = 76 %)., Implications: Our findings show that treatment resistance can be predicted, at first-episode of psychosis. Pending a model update and external validation, we demonstrate the potential value of prediction models for TR., Competing Interests: Declaration of competing interest The Authors declare no Competing Non-Financial Interests but the following Competing Financial Interests: J.T.R.W. is an investigator on a grant from Takeda Pharmaceuticals Ltd. to Cardiff University, for a project unrelated to the work presented here. S.E.S. is employed on this grant. M.D.F. has received a fee for educational seminars from Lundbeck and Janssen. O.A.A. is a consultant to HealthLytix and has received speakers honorarium from Lundbeck and Sunovion. T.R.E.B. has been a member of an advisory board for Gedeon Richter. C.B.E. received honoraria for conferences from Forum pour la formation médicale, Janssen-Cilag, Lundbeck, Otsuka, Sandoz, Servier, Sunovion, Sysmex Suisse AG, Takeda, Vifor-Pharma, and Zeller in the past 3 years. B.C.F. has received honoraria for participation as a consultant and/or as a speaker at educational events from ADAMED, Mylan, Angelini, Janssen Johnson & Johnson, Lundbeck, and Otsuka Pharmaceuticals. R.M.M. has received payments for non-promotional lectures from Janssen, Otsuka, Sunovian, and Lundbeck. J.H.M. has received research funding from H Lundbeck., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Progress towards stratified care for anxiety and depression will require the identification of new predictors. We collected data on retrospectively self-reported therapeutic outcomes in adults who received psychological therapy in the UK in the past ten years. We aimed to replicate factors associated with traditional treatment outcome measures from the literature., Methods: Participants were from the Genetic Links to Anxiety and Depression (GLAD) Study, a UK-based volunteer cohort study. We investigated associations between retrospectively self-reported outcomes following therapy, on a five-point scale (global rating of change; GRC) and a range of sociodemographic, clinical and therapy-related factors, using ordinal logistic regression models (n = 2890)., Results: Four factors were associated with therapy outcomes (adjusted odds ratios, OR). One sociodemographic factor, having university-level education, was associated with favourable outcomes (OR = 1.37, 95%CI: 1.18, 1.59). Two clinical factors, greater number of reported episodes of illness (OR = 0.95, 95%CI: 0.92, 0.97) and higher levels of personality disorder symptoms (OR = 0.89, 95%CI: 0.87, 0.91), were associated with less favourable outcomes. Finally, reported regular use of additional therapeutic activities was associated with favourable outcomes (OR = 1.39, 95%CI: 1.19, 1.63). There were no statistically significant differences between fully adjusted multivariable and unadjusted univariable odds ratios., Conclusion: Therapy outcome data can be collected quickly and inexpensively using retrospectively self-reported measures in large observational cohorts. Retrospectively self-reported therapy outcomes were associated with four factors previously reported in the literature. Similar data collected in larger observational cohorts may enable detection of novel associations with therapy outcomes, to generate new hypotheses, which can be followed up in prospective studies., (© 2022. The Author(s).)

Importance: Impaired cognitive function in schizophrenia is associated with poor functional outcomes, but the role of rare coding variants is unclear., Objective: To determine whether ultrarare constrained variants (URCVs) are associated with cognition in patients with schizophrenia., Design, Setting, and Participants: Linear regression was used to perform a within-case genetic association study of URCVs and current cognition and premorbid cognitive ability. A multivariable linear regression analysis of the outcomes associated with URCVs, schizophrenia polygenic risk score, polygenic risk score for intelligence and schizophrenia associated copy number variants on cognitive ability was performed. Exome sequencing data from 802 participants with schizophrenia were assessed for current cognition using the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery and for estimated premorbid IQ using the National Adult Reading Test. Individuals were recruited from clinical and voluntary mental health services in the UK. Those with a diagnosis of intellectual disability or a neurological disorder known to affect cognition were excluded. Data collection occurred between 2007 and 2015. Data were analyzed between April 2020 and March 2022., Main Outcomes and Measures: Association between URCVs, current cognition, and current cognition adjusted for premorbid IQ., Results: Of the 802 participants, 499 (62%) were men and 303 (38%) were women; mean (SD) age at interview was 43.36 (11.87) years. Ultrarare constrained variants (n = 400) were associated with lower current cognition scores (β = -0.18; SE = 0.07; P = .005). In the univariable analysis, premorbid IQ was associated with URCVs (β = -0.12; SE = 0.05; P = .02) and partly attenuated the association with current cognition (β = -0.09; SE = 0.05; P = .08). Multivariable analysis showed that measured genetic factors combined accounted for 6.2% of variance in current cognition, 10.3% of variance in premorbid IQ, and supported outcomes of URCVs associated with current cognition independent of premorbid IQ (β = -0.10; SE = 0.05; P = .03)., Conclusions and Relevance: The findings of this study suggest that URCVs contribute to variance in cognitive function in schizophrenia, with partly independent associations before and after onset of the disorder. Although the estimated effect sizes were small, future studies may show that the effect sizes will be greater with better annotation of pathogenic variants. Genomic data may contribute to identifying those at particularly high risk of cognitive impairment in whom early remedial or preventive measures can be implemented.

Background and Hypothesis: Schizophrenia has been robustly associated with multiple genetic and environmental risk factors. Childhood adversity is one of the most widely replicated environmental risk factors for schizophrenia, but it is unclear if schizophrenia genetic risk alleles contribute to this association., Study Design: In this systematic review and meta-analysis, we assessed the evidence for gene-environment correlation (genes influence likelihood of environmental exposure) between schizophrenia polygenic risk score (PRS) and reported childhood adversity. We also assessed the evidence for a gene-environment interaction (genes influence sensitivity to environmental exposure) in relation to the outcome of schizophrenia and/or psychosis. This study was registered on PROSPERO (CRD42020182812). Following PRISMA guidelines, a search for relevant literature was conducted using Cochrane, MEDLINE, PsycINFO, Web of Science, and Scopus databases until February 2022. All studies that examined the association between schizophrenia PRS and childhood adversity were included., Study Results: Seventeen of 650 identified studies met the inclusion criteria and were assessed against the Newcastle-Ottawa Scale for quality. The meta-analysis found evidence for gene-environment correlation between schizophrenia PRS and childhood adversity (r = .02; 95% CI = 0.01, 0.03; P = .001), but the effect was small and therefore likely to explain only a small proportion of the association between childhood adversity and psychosis. The 4 studies that investigated a gene-environment interaction between schizophrenia PRS and childhood adversity in increasing risk of psychosis reported inconsistent results., Conclusions: These findings suggest that a gene-environment correlation could explain a small proportion of the relationship between reported childhood adversity and psychosis., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)

Machine learning (ML) holds promise for precision psychiatry, but its predictive performance is unclear. We assessed whether ML provided added value over logistic regression for prediction of schizophrenia, and compared models built using polygenic risk scores (PRS) or clinical/demographic factors. LASSO and ridge-penalised logistic regression, support vector machines (SVM), random forests, boosting, neural networks and stacked models were trained to predict schizophrenia, using PRS for schizophrenia (PRS SZ ), sex, parental depression, educational attainment, winter birth, handedness and number of siblings as predictors. Models were evaluated for discrimination using area under the receiver operator characteristic curve (AUROC) and relative importance of predictors using permutation feature importance (PFI). In a secondary analysis, fitted models were tested for association with schizophrenia-related traits which had not been used in model development. Following learning curve analysis, 738 cases and 3690 randomly sampled controls were selected from the UK Biobank. ML models combining all predictors showed the highest discrimination (linear SVM, AUROC = 0.71), but did not significantly outperform logistic regression. AUROC was robust over 100 random resamples of controls. PFI identified PRS SZ as the most important predictor. Highest variance in fitted models was explained by schizophrenia-related traits including fluid intelligence (most associated: linear SVM), digit symbol substitution (RBF SVM), BMI (XGBoost), smoking status (XGBoost) and deprivation (linear SVM). In conclusion, ML approaches did not provide substantial added value for prediction of schizophrenia over logistic regression, as indexed by AUROC; however, risk scores derived with different ML approaches differ with respect to association with schizophrenia-related traits., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The D2 dopamine receptor (D2R) is the primary site of the therapeutic action of antipsychotics and is involved in essential brain functions relevant to schizophrenia, such as attention, memory, motivation, and emotion processing. Moreover, the gene coding for D2R (DRD2) has been associated with schizophrenia at a genome-wide level. Recent studies have shown that a polygenic co-expression index (PCI) predicting the brain-specific expression of a network of genes co-expressed with DRD2 was associated with response to antipsychotics, brain function during working memory in patients with schizophrenia, and with the modulation of prefrontal cortex activity after pharmacological stimulation of D2 receptors. We aimed to investigate the relationship between the DRD2 gene network and in vivo striatal dopaminergic function, which is a phenotype robustly associated with psychosis and schizophrenia. To this aim, a sample of 92 healthy subjects underwent 18 F-DOPA PET and was genotyped for genetic variations indexing the co-expression of the DRD2-related genetic network in order to calculate the PCI for each subject. The PCI was significantly associated with whole striatal dopamine synthesis capacity (p = 0.038). Exploratory analyses on the striatal subdivisions revealed a numerically larger effect size of the PCI on dopamine function for the associative striatum, although this was not significantly different than effects in other sub-divisions. These results are in line with a possible relationship between the DRD2-related co-expression network and schizophrenia and extend it by identifying a potential mechanism involving the regulation of dopamine synthesis. Future studies are needed to clarify the molecular mechanisms implicated in this relationship., (© 2022. The Author(s).)

Impaired cognition is associated with lower quality of life and poor outcomes in schizophrenia. Brain glutamate may contribute to both clinical outcomes and cognition, but these relationships are not well-understood. We studied a multicentre cohort of 85 participants with non-affective psychosis using proton magnetic resonance spectroscopy. Glutamate neurometabolites were measured in the anterior cingulate cortex (ACC). Cognition was assessed using the Brief Assessment for Cognition in Schizophrenia (BACS). Patients were categorised as antipsychotic responders or non-responders based on treatment history and current symptom severity. Inverted U-shaped associations between glutamate or Glx (glutamate + glutamine) with BACS subscale and total scores were examined with regression analyses. We then tested for an interaction effect of the antipsychotic response group on the relationship between glutamate and cognition. ACC glutamate and Glx had a positive linear association with verbal memory after adjusting for age, sex and chlorpromazine equivalent dose (glutamate, β = 3.73, 95% CI = 1.26-6.20, P = 0.004; Glx, β = 3.38, 95% CI = 0.84-5.91, P = 0.01). This association did not differ between good and poor antipsychotic response groups. ACC glutamate was also positively associated with total BACS score (β = 3.12, 95% CI = 0.01-6.23, P = 0.046), but this was not significant after controlling for antipsychotic dose. Lower glutamatergic metabolites in the ACC were associated with worse verbal memory, and this relationship was independent of antipsychotic response. Further research on relationships between glutamate and cognition in antipsychotic responsive and non-responsive illness could aid the stratification of patient groups for targeted treatment interventions., (© 2022. The Author(s).)

We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from genome-wide association studies (GWASs) of BD, however, are not significantly enriched for ultra-rare PTVs. Combining gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (odds ratio (OR) = 7.06, P = 2.83 × 10 -9 ). At the protein level, AKAP-11 interacts with GSK3B, the hypothesized target of lithium, a primary treatment for BD. Our results lend support to BD's polygenicity, demonstrating a role for rare coding variation as a significant risk factor in BD etiology., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Clozapine is the most effective antipsychotic for patients with treatment-resistant schizophrenia. However, response is highly variable and possible genetic underpinnings of this variability remain unknown. Here, we performed polygenic risk score (PRS) analyses to estimate the amount of variance in symptom severity among clozapine-treated patients explained by PRSs (R2) and examined the association between symptom severity and genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activity. Genome-wide association (GWA) analyses were performed to explore loci associated with symptom severity. A multicenter cohort of 804 patients (after quality control N = 684) with schizophrenia spectrum disorder treated with clozapine were cross-sectionally assessed using the Positive and Negative Syndrome Scale and/or the Clinical Global Impression-Severity (CGI-S) scale. GWA and PRS regression analyses were conducted. Genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activities were calculated. Schizophrenia-PRS was most significantly and positively associated with low symptom severity (p = 1.03 × 10 -3 ; R2 = 1.85). Cross-disorder-PRS was also positively associated with lower CGI-S score (p = 0.01; R2 = 0.81). Compared to the lowest tertile, patients in the highest schizophrenia-PRS tertile had 1.94 times (p = 6.84×10 -4 ) increased probability of low symptom severity. Higher genotype-predicted CYP2C19 enzyme activity was independently associated with lower symptom severity (p = 8.44×10 -3 ). While no locus surpassed the genome-wide significance threshold, rs1923778 within NFIB showed a suggestive association (p = 3.78×10 -7 ) with symptom severity. We show that high schizophrenia-PRS and genotype-predicted CYP2C19 enzyme activity are independently associated with lower symptom severity among individuals treated with clozapine. Our findings open avenues for future pharmacogenomic projects investigating the potential of PRS and genotype-predicted CYP-activity in schizophrenia., (© 2022. The Author(s).)

Interest in the cerebellum is expanding given evidence of its contributions to cognition and emotion, and dysfunction in various psychopathologies. However, research into its genetic architecture and shared influences with liability for mental disorders is lacking. We conducted a genome-wide association study (GWAS) of total cerebellar volume and underlying cerebellar lobe volumes in 33,265 UK-Biobank participants. Total cerebellar volume was heritable (h 2 SNP  = 50.6%), showing moderate genetic homogeneity across lobes (h 2 SNP from 35.4% to 57.1%; mean genetic correlation between lobes r g  ≈ 0.44). We identified 33 GWAS signals associated with total cerebellar volume, of which 6 are known to alter protein-coding gene structure, while a further five mapped to genomic regions known to alter cerebellar tissue gene expression. Use of summary data-based Mendelian randomisation further prioritised genes whose change in expression appears to mediate the SNP-trait association. In total, we highlight 21 unique genes of greatest interest for follow-up analyses. Using LD-regression, we report significant genetic correlations between total cerebellar volume and brainstem, pallidum and thalamus volumes. While the same approach did not result in significant correlations with psychiatric phenotypes, we report enrichment of schizophrenia, bipolar disorder and autism spectrum disorder associated signals within total cerebellar GWAS results via conditional and conjunctional-FDR analysis. Via these methods and GWAS catalogue, we identify which of our cerebellar genomic regions also associate with psychiatric traits. Our results provide important insights into the common allele architecture of cerebellar volume and its overlap with other brain volumes and psychiatric phenotypes., (© 2022. The Author(s).)

Schizophrenia has a heritability of 60-80% 1 , much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Importance: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts., Objective: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples., Design, Setting, and Participants: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G])., Main Outcomes and Measures: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition., Results: The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04)., Conclusions and Relevance: In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.

Background: Cognitive impairments are features of many psychiatric disorders and affect functioning. A barrier to cognitive research on psychiatric disorders is the lack of large cross-disorder data sets. However, the collection of cognitive data can be logistically challenging and expensive. Web-based collection may be an alternative; however, little is known about who does and does not complete web-based cognitive assessments for psychiatric research., Objective: The aims of this study are to develop a web-based cognitive battery for use in psychiatric research, validate the battery against the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery, and compare the characteristics of the participants who chose to take part with those of the individuals who did not participate., Methods: Tasks were developed by The Many Brains Project and selected to measure the domains specified by the MATRICS initiative. We undertook a cross-validation study of 65 participants with schizophrenia, bipolar disorder, depression, or no history of psychiatric disorders to compare the web-based tasks with the MATRICS Consensus Cognitive Battery. Following validation, we invited participants from 2 large ongoing genetic studies, which recruited participants with psychiatric disorders to complete the battery and evaluated the demographic and clinical characteristics of those who took part., Results: Correlations between web-based and MATRICS tasks ranged between 0.26 and 0.73. Of the 961 participants, 887 (92.3%) completed at least one web-based task, and 644 (67%) completed all tasks, indicating adequate completion rates. Predictors of web-based participation included being female (odds ratio [OR] 1.3, 95% CI 1.07-1.58), ethnicity other than White European (OR 0.66, 95% CI 0.46-0.96), higher levels of education (OR 1.19, 95% CI 1.11-1.29), diagnosis of an eating disorder (OR 2.17, 95% CI 1.17-4) or depression and anxiety (OR 5.12, 95% CI 3.38-7.83), and absence of a diagnosis of schizophrenia (OR 0.59, 95% CI 0.35-0.94). Lower performance on the battery was associated with poorer functioning (B=-1.76, SE 0.26; P<.001)., Conclusions: Our findings offer valuable insights into the advantages and disadvantages of testing cognitive function remotely for mental health research., (©Amy Joanne Lynham, Ian R Jones, James T R Walters. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.02.2022.)

Background: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders., Methods: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors., Results: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged., Conclusions: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders., (Copyright © 2021 Society of Biological Psychiatry. All rights reserved.)