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Emotional disorders are common in childhood, and their prevalence sharply increases during adolescence. The Strengths and Difficulties Questionnaire (SDQ) is widely used for screening emotional and behavioural difficulties in children and young people, but little is known about the accuracy of the emotional subscale (SDQ-E) in detecting emotional disorders, and whether this changes over development. Such knowledge is important in determining whether symptom changes across age are due to developmental or measurement differences. This study assessed the validity of the SDQ-E and two individual items (low mood and general worry) in differentiating between cases and non-cases of Major Depressive Disorder (MDD), Generalised Anxiety Disorder (GAD), and other anxiety disorders across ages 7, 10, 13, 15, and 25 years in a UK population cohort. Analyses showed moderate accuracy of the subscale in discriminating cases of MDD (AUC=0.67-0.85), and high accuracy for discriminating cases of GAD (AUC=0.80-0.93) and any anxiety disorder (AUC=0.74-0.83) compared to non-cases. The SDQ-E performed well across ages and sex, and generally performed better than the two individual items. Together our findings validate the SDQ-E as a screen for emotional disorders during childhood, adolescence, and early adulthood, and as a tool for longitudinal research on depression and anxiety disorders.

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.

There is controversy about the status of schizoaffective disorder depressive-type (SA-D), particularly whether it should be considered a form of schizophrenia or a distinct disorder. We aimed to determine whether individuals with SA-D differ from individuals with schizophrenia in terms of demographic, premorbid and lifetime clinical characteristics, and genetic liability to schizophrenia, depression and bipolar disorder. Participants were from the CardiffCOGS sample and met ICD-10 criteria for schizophrenia (n=713) or SA-D (n=151). Two samples, Cardiff Affected-sib (n=354) and Cardiff F-series (n=524), were used for replication. For all samples, phenotypic data were ascertained through structured interview, review of medical records, and an ICD-10 diagnosis made by trained researchers. Univariable and multivariable logistic regression models were used to compare individuals with schizophrenia and SA-D for demographic and clinical characteristics, and polygenic risk scores (PRS). In the CardiffCOGS, SA-D, compared to schizophrenia, was associated with female sex, childhood abuse, history of alcohol dependence, higher functioning Global Assessment Scale (GAS) score in worst episode of psychosis, lower functioning GAS score in worst episode of depression, and reduced lifetime severity of disorganised symptoms. Individuals with SA-D had higher depression PRS compared to those with schizophrenia. PRS for schizophrenia and bipolar disorder did not significantly differ between SA-D and schizophrenia. Compared to individuals with schizophrenia, individuals with SA-D had higher rates of environmental and genetic risk factors for depression and a similar genetic liability to schizophrenia. These findings are consistent with SA-D being a sub-type of schizophrenia resulting from elevated liability to both schizophrenia and depression.Key words: Polygenic risk score; depression; psychosis; diagnosis; phenotypes

Levels of activity are often affected in psychiatric disorders and can be core symptoms of illness. Advances in technology now allow the accurate assessment of activity levels but it remains unclear whether alterations in activity arise from shared risk factors for developing psychiatric disorders, such as genetics, or are better explained as consequences of the disorders and their associated factors. We aimed to examine objectively-measured physical activity in individuals with psychiatric disorders, and assess the role of genetic liability for psychiatric disorders on physical activity. Accelerometer data were available on 95,529 UK Biobank participants, including measures of overall mean activity and minutes per day of moderate activity, walking, sedentary activity, and sleep. Linear regressions measured associations between psychiatric diagnosis and activity levels, and polygenic risk scores (PRS) for psychiatric disorders and activity levels. Genetic correlations were calculated between psychiatric disorders and different types of activity. Having a diagnosis of schizophrenia, bipolar disorder, depression, or autism spectrum disorders (ASD) was associated with reduced overall activity compared to unaffected controls. In individuals without a psychiatric disorder, reduced overall activity levels were associated with PRS for schizophrenia, depression, and ASD. ADHD PRS was associated with increased overall activity. Genetic correlations were consistent with PRS findings. Variation in physical activity is an important feature across psychiatric disorders. Whilst levels of activity are associated with genetic liability to psychiatric disorders to a very limited extent, the substantial differences in activity levels in those with psychiatric disorders most likely arise as a consequences of disorder-related factors.

Genome-wide association studies (GWAS) have proved to be a powerful approach for gene discovery in schizophrenia; their findings have important implications not just for our understanding of the genetic architecture of the disorder, but for the potential applications of personalised medicine through improved classification and targeted interventions. In this article we review the current status of the GWAS literature in schizophrenia including functional annotation methods and polygenic risk scoring, as well as the directions and challenges of future research. We consider recent findings in East Asian populations and the advancements from trans-ancestry analysis, as well as the insights gained from research looking across psychiatric disorders.

Key Points Question Are phenotypic dimensions in schizophrenia associated with genetic liability to schizophrenia, other neuropsychiatric disorders, and intelligence? Findings In this cross-sectional genetic association study of 1220 individuals with schizophrenia, analyses indicated that higher levels of disorganized symptoms, but not other symptom dimensions, and lower levels of current cognitive ability were significantly associated with schizophrenia polygenic risk scores. Current cognitive ability was also associated with intelligence polygenic risk scores. Meaning The findings of this study suggest that variation in disorganized symptoms and cognitive ability in schizophrenia are markers of schizophrenia common genetic liability; cognitive performance in schizophrenia may reflect distinct contributions from genetic liabilities to both intelligence and 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 (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., This genetic association study examines the associations between phenotypic dimensions in schizophrenia and genetic liability to schizophrenia, other neuropsychiatric disorders, and intelligence in patients with schizophrenia.

Background Schizoaffective disorder depressed type (SAD) has been considered a distinct diagnostic entity since 1987, yet it is rarely recognised in clinical and research settings as it is considered analogous to schizophrenia with comorbid depression. However, these assumptions are often based on anecdotal evidence, as little research has attempted to examine differences between the two disorders. We aimed to establish the validity of SAD as a diagnosis, by investigating phenotypic and genotypic differences between schizophrenia and SAD. Methods Participants were from the Cardiff Cognition study and included if they met ICD-10 criteria for schizophrenia (n=713) or SAD (n=151). Diagnosis was determined via consensus assessment by trained researchers using lifetime symptom data from the SCAN interview alongside patient medical records. Polygenic risk scores were derived for schizophrenia and major depressive disorder using PRSice. Logistic regressions were used to measure the association between diagnosis and lifetime clinical characteristics across five categories: demographics, premorbid functioning, illness progression, psychosis, and depression. Sex and age at interview were included as covariates. Logistic regressions were used to measure the association between diagnosis and polygenic risk scores for schizophrenia and depression at a threshold of p Results Compared to schizophrenia, SAD was significantly associated with female sex (OR= 3.19, 95% CI= 2.23 - 4.59, p=5.0x10-9), lower global assessment score in worst episode of depression (OR= 0.47, 95% CI= 0.37 – 0.59, p=5.0x10-9), higher global assessment score in worst episode of psychosis (OR= 1.44, 95% CI= 1.20 – 1.72, p= 6.8x10-4), a greater likelihood of an admission for depression (OR= 2.24, 95% CI= 1.48 – 3.40, p= 1.2x10-3), greater alcohol abuse or dependence (OR= 2.12, 95% CI= 1.41 – 3.20, p= 2.3x10-3), longer duration of depression (OR= 1.46, 95% CI= 1.19 - 1.84, p= 3.5x10-3), experiencing childhood abuse (OR= 2.07, 95% CI = 1.35 – 3.17, p= 3.9x10-3), a reduced likelihood of an involuntary admission for psychosis (OR= 0.40, 95% CI= 0.22 – 0.75, p= 0.01), depression onset occurring prior to psychosis onset (OR= 2.40, 95% CI= 1.37 – 4.43, p= 0.01), having a higher number of children (OR= 1.34, 95% CI= 1.08 – 1.67, p= 0.03), and better cognitive functioning (OR= 1.20, 95% CI= 1.04 – 1.40, p= 0.05). Depression polygenic risk score was higher in participants with SAD (OR= 1.33, 95% CI= 1.06 – 1.66, R2= 0.015, p= 0.01); schizophrenia polygenic risk score was not associated with diagnosis (OR= 0.94, 95% CI= 0.75 – 1.17, R2= 0.001, p= 0.58). Secondary analyses were conducted to investigate sex-specific effects. A significant difference in schizophrenia polygenic risk was observed between males and females, which indicated that males with SAD have lower schizophrenia polygenic risk scores than females with SAD (OR= 0.46, 95% CI= 0.28 – 0.74, R2= 0.143, p=1.5x10-3). Sex-specific effects were not observed for depression PRS or phenotypes. Discussion Our results indicate a number of differences between individuals with schizophrenia and SAD. Primarily, the results demonstrate a greater burden of depression in those with SAD, both phenotypically and genotypically. Our results also suggest that the genetic contribution to SAD may differ between males and females. The findings indicate that schizophrenia research, particularly genetic research, needs to consider the impacts of sex-specific effects and comorbid depression before combining patient samples for analysis.

BackgroundAround 30% of individuals with schizophrenia remain symptomatic and significantly impaired despite antipsychotic treatment and are considered to be treatment resistant. Clinicians are currently unable to predict which patients are at higher risk of treatment resistance.AimsTo determine whether genetic liability for schizophrenia and/or clinical characteristics measurable at illness onset can prospectively indicate a higher risk of treatment-resistant psychosis (TRP).MethodIn 1070 individuals with schizophrenia or related psychotic disorders, schizophrenia polygenic risk scores (PRS) and large copy number variations (CNVs) were assessed for enrichment in TRP. Regression and machine-learning approaches were used to investigate the association of phenotypes related to demographics, family history, premorbid factors and illness onset with TRP.ResultsYounger age at onset (odds ratio 0.94,P= 7.79 × 10−13) and poor premorbid social adjustment (odds ratio 1.64,P= 2.41 × 10−4) increased risk of TRP in univariate regression analyses. These factors remained associated in multivariate regression analyses, which also found lower premorbid IQ (odds ratio 0.98,P= 7.76 × 10−3), younger father's age at birth (odds ratio 0.97,P= 0.015) and cannabis use (odds ratio 1.60,P= 0.025) increased the risk of TRP. Machine-learning approaches found age at onset to be the most important predictor and also identified premorbid IQ and poor social adjustment as predictors of TRP, mirroring findings from regression analyses. Genetic liability for schizophrenia was not associated with TRP.ConclusionsPeople with an earlier age at onset of psychosis and poor premorbid functioning are more likely to be treatment resistant. The genetic architecture of susceptibility to schizophrenia may be distinct from that of treatment outcomes.