Exploration of first onsets of mania, schizophrenia spectrum disorders and major depressive disorder in perimenopause.

Although the relationship between perimenopause and changes in mood has been well established, knowledge of risk of a broad spectrum of psychiatric disorders associated with reproductive aging is limited. Here we investigate whether the perimenopause (that is, the years around the final menstrual period (FMP)) is associated with increased risk of developing psychiatric disorders compared with the late reproductive stage. Information on menopausal timing and psychiatric history was obtained from nurse-administered interviews and online questionnaires from 128,294 female participants within UK Biobank. Incidence rates of psychiatric disorders during the perimenopause (4 years surrounding the FMP) were compared with the reference premenopausal period (6-10 years before the FMP). The rates were calculated for major depressive disorder (MDD), mania, schizophrenia spectrum disorders and other diagnoses. Overall, of 128,294 participants, 753 (0.59%) reported their first onset of a psychiatric disorder during the late reproductive stage (incidence rate 1.53 per 1,000 person-years) and 1,133 (0.88%) during the perimenopause (incidence rate 2.33 per 1,000 person-years). Compared with the reference reproductive period, incidence rates of psychiatric disorders significantly increased during the perimenopause (incidence rate ratio (RR) of 1.52, 95% confidence interval (CI) 1.39-1.67) and decreased back down to that observed in the premenopausal period in the postmenopause (RR of 1.09 (95% CI 0.98-1.21)). The effect was primarily driven by increased incidence rates of MDD, with an incidence RR of 1.30 (95% CI 1.16-1.45). However, the largest effect size at perimenopause was observed for mania (RR of 2.12 (95% CI 1.30-3.52)). No association was found between perimenopause and incidence rates of schizophrenia spectrum disorders (RR of 0.95 (95% CI 0.48-1.88)). In conclusion, perimenopause was associated with an increased risk of developing MDD and mania. No association was found between perimenopause and first onsets of schizophrenia spectrum disorders.

SLC39A8.p.(Ala391Thr) is associated with poorer cognitive ability: a cross-sectional study of schizophrenia and the general UK population.

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.

Associations of psychotic symptom dimensions with clinical and developmental variables in twin and general clinical samples.

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.

Assessing the validity of a self-reported clinical diagnosis of schizophrenia.

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 (r2) 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 r2, 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.

Severe psychiatric disorders are associated with increased risk of dementia.

BACKGROUND: Individuals with psychiatric disorders have an increased risk of developing dementia. Most cross-sectional studies suffer from selection bias, underdiagnosis and poor population representation, while there is only limited evidence from longitudinal studies on the role of anxiety, bipolar and psychotic disorders. Electronic health records (EHRs) permit large cohorts to be followed across the lifespan and include a wide range of diagnostic information. OBJECTIVE: To assess the association between four groups of psychiatric disorders (schizophrenia, bipolar disorder/mania, depression and anxiety) with dementia in two large population-based samples with EHR. METHODS: Using EHR on nearly 1 million adult individuals in Wales, and from 228 937 UK Biobank participants, we studied the relationships between schizophrenia, mania/bipolar disorder, depression, anxiety and subsequent risk of dementia. FINDINGS: In Secure Anonymised Information Linkage, there was a steep increase in the incidence of a first diagnosis of psychiatric disorder in the years prior to the diagnosis of dementia, reaching a peak in the year prior to dementia diagnosis for all psychiatric diagnoses. Psychiatric disorders, except anxiety, were highly significantly associated with a subsequent diagnosis of dementia: HRs=2.87, 2.80, 1.63 for schizophrenia, mania/bipolar disorder and depression, respectively. A similar pattern was found in the UK Biobank (HRs=4.46, 3.65, 2.39, respectively) and anxiety was also associated with dementia (HR=1.34). Increased risk of dementia was observed for all ages at onset of psychiatric diagnoses when these were divided into 10-year bins. CONCLUSIONS: Psychiatric disorders are associated with an increased risk of subsequent dementia, with a greater risk of more severe disorders. CLINICAL IMPLICATIONS: A late onset of psychiatric disorders should alert clinicians of possible incipient dementia.

Common risk alleles for schizophrenia within the major histocompatibility complex predict white matter microstructure.

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.

Genetic and Phenotypic Features of Schizophrenia in the UK Biobank.

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.

Assessing the validity of a self-reported clinical diagnosis of schizophrenia.

Background: Diagnoses in psychiatric research can be derived from various sources. This study assesses the validity of a self-reported clinical diagnosis of schizophrenia. Methods: The study included 3,029 clinically ascertained participants with schizophrenia or psychotic disorders diagnosed by self-report and/or research interview and 1,453 UK Biobank participants with self-report and/or medical record diagnosis of schizophrenia or schizoaffective disorder depressed-type (SA-D). We assessed positive predictive values (PPV) of self-reported clinical diagnoses against research interview and medical record diagnoses. We compared polygenic risk scores (PRS) and phenotypes across diagnostic groups, and compared the variance explained by schizophrenia PRS to samples in the Psychiatric Genomics Consortium (PGC). Results: In the clinically ascertained sample, the PPV of self-reported schizophrenia to a research diagnosis of schizophrenia was 0.70, which increased to 0.81 when benchmarked against schizophrenia or SA-D. In UK Biobank, the PPV of self-reported schizophrenia to a medical record diagnosis was 0.74. Compared to self-report participants, those with a research diagnosis were younger and more likely to have a high school qualification (clinically ascertained sample) and those with a medical record diagnosis were less likely to be employed or have a high school qualification (UK Biobank). Schizophrenia PRS did not differ between participants that had a diagnosis from self-report, research diagnosis or medical record diagnosis. Polygenic liability r2, for all diagnosis definitions, fell within the distribution of PGC schizophrenia cohorts. Conclusions: Self-report measures of schizophrenia are justified in research to maximise sample size and representativeness, although within sample validation of diagnoses is recommended.

Mediation and longitudinal analysis to interpret the association between clozapine pharmacokinetics, pharmacogenomics, and absolute neutrophil count.

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/mm3 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.

Genomic findings in schizophrenia and their implications.

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.

Copy Number Variants Increasing Risk for Schizophrenia: Shared and Distinct Effects on Brain Morphometry and Cognitive Performance.

Background: Copy number variations (CNVs) conferring risk for mental disorders are associated with brain changes and cognitive deficits. However, whether these effects are shared or distinct across CNVs remains untested. Here we compared the effects on brain morphometry and cognitive performance across CNVs with shared psychiatric liability. Methods: Unaffected and unrelated participants of White British and Irish ancestry were drawn from the UK Biobank. After quality control, we retained 31,941 participants not carrying any damaging CNVs and 202 participants carrying one CNV increasing risk for schizophrenia. Using regression analyses, we tested the association between brain morphometry and cognitive performance with CNV carrying status and compared these effect sizes across CNVs using z test for the equality of regression coefficients. Equation modeling was used to examine the mediation of brain phenotypes on the association between CNVs and cognitive performance. Results: We detected different patterns of association between CNVs and brain morphometry and cognitive abilities. Comparing across CNVs, 1q21.1 deletion showed the strongest association with surface area in frontal lobe (ß = -1.03, p = 4 × 10-8; ß = -0.81, p = .00001) and performance in digit memory (ß = -1.58, p = .00003), while 1q21.1 duplication showed the strongest association with volume of the putamen (ß = -0.70, p = .0004) and reaction time (ß = -1.14, p = .000002). We also showed that even when 2 CNVs were associated with performance in the same cognitive ability, these associations were mediated by different brain changes. Conclusions: Despite sharing similar psychiatric liability, the CNVs under study appeared to have different effects on brain morphometry and on performance in cognitive abilities, suggesting the existence of distinctive neurobiological pathways into the same clinical phenotypes.

Early neutrophil trajectory following clozapine may predict clozapine response - Results from an observational study using electronic health records.

BACKGROUND: Clozapine has unique effectiveness in treatment-resistant schizophrenia and is known to cause immunological side-effects. A transient spike in neutrophils commonly occurs in the first weeks of clozapine therapy. There is contradictory evidence in the literature as to whether neutrophil changes with clozapine are linked to treatment response. AIMS: The current study aims to further examine the neutrophil changes in response to clozapine and explore any association between neutrophil trajectory and treatment response. METHODS: A retrospective cohort study of patients undergoing their first treatment with clozapine and continuing for at least 2 years identified 425 patients (69% male/31% female). Neutrophil counts at baseline, 3 weeks and 1 month were obtained predominantly by linkage with data from the clozapine monitoring service. Clinical Global Impression- Severity (CGI-S) was rated from case notes at the time of clozapine initiation and at 2 years. Latent class growth analysis (LCGA) was performed to define distinct trajectories of neutrophil changes during the first month of treatment. Logistic regression was then conducted to investigate for association between the trajectory of neutrophil count changes in month 1 and clinical response at 2 years as well as between baseline neutrophil count and response. RESULTS: Of the original cohort, 397 (93%) patients had useable neutrophil data during the first 6 weeks of clozapine treatment. LCGA revealed significant differences in neutrophil trajectories with a three-class model being the most parsimonious. The classes had similar trajectory profiles but differed primarily on overall neutrophil count: with low, high-normal and high neutrophil classes, comprising 52%, 40% and 8% of the sample respectively. Membership of the high-normal group was associated with significantly increased odds of a positive response to clozapine, as compared to the low neutrophil group [Odds ratio (OR) = 2.10, p-value = 0.002; 95% confidence interval (95% CI) = 1.31-3.36]. Baseline neutrophil count was a predictor of response to clozapine at 2 years, with counts of ≥5 × 109/l significantly associated with positive response (OR = 1.60, p-value = 0.03; 95% CI = 1.03-2.49). CONCLUSIONS: Our data are consistent with the hypothesis that patients with low-level inflammation, reflected in a high-normal neutrophil count, are more likely to respond to clozapine, raising the possibility that clozapine exerts its superior efficacy via immune mechanisms.

Genomic Stratification of Clozapine Prescription Patterns Using Schizophrenia Polygenic Scores.

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 (ß = 12.22, SE = 3.78, p = .001), CLOZUK3 (ß = 12.73, SE = 5.99, p = .034), and the Norwegian cohort (ß = 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.

Ultrarare Coding Variants and Cognitive Function in Schizophrenia.

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 (ß = -0.18; SE = 0.07; P = .005). In the univariable analysis, premorbid IQ was associated with URCVs (ß = -0.12; SE = 0.05; P = .02) and partly attenuated the association with current cognition (ß = -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 (ß = -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.

Schizophrenia Polygenic Risk and Experiences of Childhood Adversity: A Systematic Review and Meta-analysis.

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.

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia.

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.

Transcriptional programs regulating neuronal differentiation are disrupted in DLG2 knockout human embryonic stem cells and enriched for schizophrenia and related disorders risk variants.

Coordinated programs of gene expression drive brain development. It is unclear which transcriptional programs, in which cell-types, are affected in neuropsychiatric disorders such as schizophrenia. Here we integrate human genetics with transcriptomic data from differentiation of human embryonic stem cells into cortical excitatory neurons. We identify transcriptional programs expressed during early neurogenesis in vitro and in human foetal cortex that are down-regulated in DLG2-/- lines. Down-regulation impacted neuronal differentiation and maturation, impairing migration, morphology and action potential generation. Genetic variation in these programs is associated with neuropsychiatric disorders and cognitive function, with associated variants predominantly concentrated in loss-of-function intolerant genes. Neurogenic programs also overlap schizophrenia GWAS enrichment previously identified in mature excitatory neurons, suggesting that pathways active during prenatal cortical development may also be associated with mature neuronal dysfunction. Our data from human embryonic stem cells, when combined with analysis of available foetal cortical gene expression data, de novo rare variants and GWAS statistics for neuropsychiatric disorders and cognition, reveal a convergence on transcriptional programs regulating excitatory cortical neurogenesis.

Lack of Support for the Genes by Early Environment Interaction Hypothesis in the Pathogenesis of Schizophrenia.

Ursini et al reported recently that the liability of schizophrenia explained by a polygenic risk score (PRS) derived from the variants most associated with schizophrenia was increased 5-fold in individuals who experienced complications during pregnancy or birth. Follow-up gene expression analysis showed that the genes mapping to the most associated genetic variants are highly expressed in placental tissues. If confirmed, these findings will have major implications in our understanding of the joint effect of genes and environment in the pathogenesis of schizophrenia. We examined the interplay between PRS and obstetric complications (OCs) in 5 independent samples (effective N = 2110). OCs were assessed with the full or modified Lewis-Murray scale, or with birth weight < 2.5 kg as a proxy. In a large cohort we tested whether the pathways from placenta-relevant variants in the original report were associated with case-control status. Unlike in the original study, we did not find significant effect of PRS on the presence of OCs in cases, nor a substantial difference in the association of PRS with case-control status in samples stratified by the presence of OCs. Furthermore, none of the PRS by OCs interactions were significant, nor were any of the biological pathways, examined in the Swedish cohort. Our study could not support the hypothesis of a mediating effect of placenta biology in the pathway from genes to schizophrenia. Methodology differences, in particular the different scales measuring OCs, as well as power constraints for interaction analyses in both studies, may explain this discrepancy.

Associations Between Schizophrenia Polygenic Liability, Symptom Dimensions, and Cognitive Ability in Schizophrenia.

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 (ß = 0.14; 95% CI, 0.07-0.22; P = 2.80 × 10-4) and a 3-factor model across all samples (ß = 0.10; 95% CI, 0.05-0.15; P = 2.80 × 10-4). Current cognitive ability was associated with genetic liability to schizophrenia (ß = -0.11; 95% CI, -0.19 to -0.04; P = 1.63 × 10-3) and intelligence (ß = 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 (ß = -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.