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Key Points: Question: How do individuals with a diagnosis of schizophrenia recruited in a large volunteer-based research resource (UK Biobank) differ from those in the Psychiatric Genomics Consortium (PGC) or those recruited from clinical settings? Findings: In this cross-sectional study including more than 517 000 individuals, liability to schizophrenia in the UK Biobank had a high genetic correlation with the PGC. Compared with 4 clinically ascertained schizophrenia samples, UK Biobank participants with schizophrenia had significantly lower schizophrenia genetic liability as indexed by polygenic risk score, lower rates of copy number variants, and fewer phenotypic features of poor outcome. Meaning: In this study, individuals with schizophrenia in the UK Biobank had features of less severe illness, which indicates that registries such as the UK Biobank can help to capture the full range of heterogeneity in schizophrenia research. This cross-sectional study compares genetic liability to psychiatric disorders in individuals with schizophrenia in the UK Biobank with individuals in the Psychiatric Genomics Consortium and compares genetic liability and phenotypic features with participants recruited from clinical settings. 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. [ABSTRACT FROM AUTHOR]

Background: Psychotic symptoms and self-rated schizotypal phenomena have similar dimensional structures. Additionally, dissociative phenomena have conceptual links with psychosis/schizotypy and all of these phenotypes are associated with adverse life events (ALEs). The relationships between these factors among individuals with psychotic disorders are not well established and were investigated in this study. Method: 76 participants with any psychotic disorder were recruited from mental health services in West Yorkshire, UK. Lifetime psychotic and affective symptoms were assessed by research interviews and case record review. The self-rated Schizotypal Personality Questionnaire (SPQ) with additional questions regarding inappropriate affect, Dissociative Experiences Scale (DES), and questionnaires regarding cumulative adverse life events in childhood (CLEQ) and in the year before clinical onset (BLEQ) were also administered. Relationships between factors were assessed using Spearman correlations and linear regression analysis. Results: Correlations with relevant psychotic symptoms ranged from ~0.3 for some positive and negative SPQ subdomains to ~0 for disorganised subdomains. In contrast, SPQ and DES were highly correlated (~0.7). In univariate analysis, ALEs were associated with depression, DES, and positive and disorganised SPQ subdomains. In multivariable analysis, ALEs in childhood and before onset were independently associated with the SPQ Unusual perceptual experiences subdomain. Conclusion: Among individuals with psychotic disorders, neither SPQ nor DES questionnaire responses are likely to be useful proxies for psychotic symptoms. However, particularly questionnaire-based unusual perceptual experiences may be useful when assessing the range of phenomena associated with adverse life events. [ABSTRACT FROM AUTHOR]

Background: Presently, there is limited guidance on the maximal dosing of psychosis drugs that is based on effectiveness rather than safety or toxicity. Current maximum dosing recommendations may far exceed the necessary degree of dopamine D2 receptor blockade required to treat psychosis. This may lead to excess harm through cognitive impairment and side effects. Aims: This analysis aimed to establish guidance for prescribers by optimally dosing drugs for psychosis based on efficacy and benefit. Methods: We used data from two dose–response meta-analyses and reviewed seven of the most prescribed drugs for psychosis in the UK. Where data were not available, we used appropriate comparison techniques based on D2 receptor occupancy to extrapolate our recommendations. Results: We found that the likely threshold dose for achieving remission of psychotic symptoms was often significantly below the currently licensed dose for these drugs. We therefore recommend that clinicians are cautious about exceeding our recommended doses. Individual factors, however, should be accounted for. We outline potentially relevant factors including age, ethnicity, sex, smoking status and pharmacogenetics. Additionally, we recommend therapeutic drug monitoring as a tool to determine individual pharmacokinetic variation. Conclusions: In summary, we propose a new set of maximum target doses for psychosis drugs based on efficacy. Further research through randomised controlled trials should be undertaken to evaluate the effect of reducing doses from current licensing maximums or from doses that are above our recommendations. However, dose reductions should be implemented in a manner that accounts for and reduces the effects of drug withdrawal. [ABSTRACT FROM AUTHOR]

Importance: Schizophrenia is a clinically heterogeneous disorder. It is currently unclear how variability in symptom dimensions and cognitive ability is associated with genetic liability for schizophrenia.Objective: To determine whether phenotypic dimensions within schizophrenia are associated with genetic liability to schizophrenia, other neuropsychiatric disorders, and intelligence.Design, Setting, and Participants: In a genetic association study, 3 cross-sectional samples of 1220 individuals with a diagnosis of schizophrenia were recruited from community, inpatient, and voluntary sector mental health services across the UK. Confirmatory factor analysis was used to create phenotypic dimensions from lifetime ratings of the Scale for the Assessment of Positive Symptoms, Scale for the Assessment of Negative Symptoms, and the MATRICS Consensus Cognitive Battery. Analyses of polygenic risk scores (PRSs) were used to assess whether genetic liability to schizophrenia, other neuropsychiatric disorders, and intelligence were associated with these phenotypic dimensions. Data collection for the cross-sectional studies occurred between 1993 and 2016. Data analysis for this study occurred between January 2019 and March 2021.Main Outcomes and Measures: Outcome measures included phenotypic dimensions defined from confirmatory factor analysis relating to positive symptoms, negative symptoms of diminished expressivity, negative symptoms of motivation and pleasure, disorganized symptoms, and current cognitive ability. Exposure measures included PRSs for schizophrenia, bipolar disorder, major depression, attention-deficit/hyperactivity disorder, autism spectrum disorder, and intelligence.Results: Of the 1220 study participants, 817 were men (67.0%). Participants' mean (SD) age at interview was 43.10 (12.74) years. Schizophrenia PRS was associated with increased disorganized symptom dimension scores in both a 5-factor model (β = 0.14; 95% CI, 0.07-0.22; P = 2.80 × 10-4) and a 3-factor model across all samples (β = 0.10; 95% CI, 0.05-0.15; P = 2.80 × 10-4). Current cognitive ability was associated with genetic liability to schizophrenia (β = -0.11; 95% CI, -0.19 to -0.04; P = 1.63 × 10-3) and intelligence (β = 0.23; 95% CI, 0.16-0.30; P = 1.52 × 10-10). After controlling for estimated premorbid IQ, current cognitive performance was associated with schizophrenia PRS (β = -0.08; 95% CI, -0.14 to -0.02; P = 8.50 × 10-3) but not intelligence PRS.Conclusions and Relevance: The findings of this study suggest that genetic liability for schizophrenia is associated with higher disorganized dimension scores but not other symptom dimensions. Cognitive performance in schizophrenia appears to reflect distinct contributions from genetic liabilities to both intelligence and schizophrenia. [ABSTRACT FROM AUTHOR]

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.)