Hannah J. Jones

Phenotypic manifestation of genetic risk for schizophrenia during adolescence in the general population

IMPORTANCE Schizophrenia is a highly heritable, polygenic condition characterized by a relatively diverse phenotype and frequent comorbid conditions, such as anxiety and depression. At present, limited evidence explains how genetic risk for schizophrenia is manifest in the general population. OBJECTIVE To investigate the extent to which genetic risk for schizophrenia is associated with different phenotypes during adolescence in a population-based birth cohort. DESIGN, SETTING, AND PARTICIPANTS This cohort study used data from the Avon Longitudinal Study of Parents and Children (ALSPAC). Of 14,062 children in the birth cohort, genetic data were available for 9912 adolescents. Data were collected periodically from September 6, 1990, and collection is ongoing. Data were analyzed from March 4 to August 13, 2015. EXPOSURES Polygenic risk scores (PRSs) for schizophrenia generated for individuals in the ALSPAC cohort using results of the second Psychiatric Genomics Consortium Schizophrenia genome-wide association study as a training set. MAIN OUTCOMES AND MEASURES Logistic regression was used to assess associations between the schizophrenia PRS and (1) psychotic experiences (Psychosis-Like Symptom Interview at 12 and 18 years of age), (2) negative symptoms (Community Assessment of Psychic Experiences at 16.5 years of age), (3) depressive disorder (Development and Well-Being Assessment at 15.5 years of age), and (4) anxiety disorder (Development and Well-Being Assessment at 15.5 years of age) in adolescence. RESULTS Of the 8230 ALSPAC participants whose genetic data passed quality control checks (51.2% male, 48.8% female), 3676 to 5444 participated in assessments from 12 to 18 years of age. The PRSs created using single-nucleotide polymorphisms with a training-set P ≤ .05 threshold were associated with negative symptoms (odds ratio [OR] per SD increase in PRS, 1.21; 95% CI, 1.08-1.36; R(2) = 0.007) and anxiety disorder (OR per SD increase in PRS, 1.17; 95% CI, 1.06- 1.29; R(2) = 0.005). No evidence was found of an association between schizophrenia PRS and psychotic experiences (OR per SD increase in PRS, 1.08; 95% CI, 0.98-1.19; R(2) = 0.001) or depressive disorder (OR per SD increase in PRS, 1.02; 95% CI, 0.91-1.13; R(2) = 0.00005). Results were mostly consistent across different training-set P value thresholds and using different cutoffs and measures of the psychopathological outcomes. CONCLUSIONS AND RELEVANCE This study demonstrates polygenic overlaps between common genetic polymorphisms associated with schizophrenia and negative symptoms and anxiety disorder but not with psychotic experiences or depression. Because the genetic risk for schizophrenia appears to be manifest as anxiety and negative symptoms during adolescence, a greater focus on these phenotypes rather than on psychotic experiences might be required for prediction of transition in at-risk samples.

Assessing causality in associations between cannabis use and schizophrenia risk: a two-sample Mendelian randomization study

Background Observational associations between cannabis and schizophrenia are well documented, but ascertaining causation is more challenging. We used Mendelian randomization (MR), utilizing publicly available data as a method for ascertaining causation from observational data. Method We performed bi-directional two-sample MR using summary-level genome-wide data from the International Cannabis Consortium (ICC) and the Psychiatric Genomics Consortium (PGC2). Single nucleotide polymorphisms (SNPs) associated with cannabis initiation (p < 10−5) and schizophrenia (p < 5 × 10−8) were combined using an inverse-variance-weighted fixed-effects approach. We also used height and education genome-wide association study data, representing negative and positive control analyses. Results There was some evidence consistent with a causal effect of cannabis initiation on risk of schizophrenia [odds ratio (OR) 1.04 per doubling odds of cannabis initiation, 95% confidence interval (CI) 1.01–1.07, p = 0.019]. There was strong evidence consistent with a causal effect of schizophrenia risk on likelihood of cannabis initiation (OR 1.10 per doubling of the odds of schizophrenia, 95% CI 1.05–1.14, p = 2.64 × 10−5). Findings were as predicted for the negative control (height: OR 1.00, 95% CI 0.99–1.01, p = 0.90) but weaker than predicted for the positive control (years in education: OR 0.99, 95% CI 0.97–1.00, p = 0.066) analyses. Conclusions Our results provide some that cannabis initiation increases the risk of schizophrenia, although the size of the causal estimate is small. We find stronger evidence that schizophrenia risk predicts cannabis initiation, possibly as genetic instruments for schizophrenia are stronger than for cannabis initiation.

Investigating causality in associations between smoking initiation and schizophrenia using Mendelian randomization

Smoking is strongly associated with schizophrenia. Although it has been widely assumed that this reflects self-medication, recent studies suggest that smoking may be a risk factor for schizophrenia. We performed two-sample bi-directional Mendelian randomization using summary level genomewide association data from the Tobacco And Genetics Consortium and Psychiatric Genomics Consortium. Variants associated with smoking initiation and schizophrenia were combined using an inverse-variance weighted fixed-effects approach. We found evidence consistent with a causal effect of smoking initiation on schizophrenia risk (OR 1.73, 95% CI 1.30–2.25, p < 0.001). However, after relaxing the p-value threshold to include variants from more than one gene and minimize the potential impact of pleiotropy, the association was attenuated (OR 1.03, 95% CI 0.97–1.09, p = 0.32). There was little evidence in support of a causal effect of schizophrenia on smoking initiation (OR 1.01, 95% CI 0.98–1.04, p = 0.32). MR Egger regression sensitivity analysis indicated no evidence for pleiotropy in the effect of schizophrenia on smoking initiation (intercept OR 1.01, 95% CI 0.99–1.02, p = 0.49). Our findings provide little evidence of a causal association between smoking initiation and schizophrenia, in either direction. However, we cannot rule out a causal effect of smoking on schizophrenia related to heavier, lifetime exposure, rather than initiation.

Association of Autistic Traits With Depression From Childhood to Age 18 Years

Importance Population-based studies following trajectories of depression in autism spectrum disorders (ASD) from childhood into early adulthood are rare. The role of genetic confounding and of potential environmental intermediaries, such as bullying, in any associations is unclear. Objectives To compare trajectories of depressive symptoms from ages 10 to 18 years for children with or without ASD and autistic traits, to assess associations between ASD and autistic traits and an International Statistical Classification of Diseases, 10th Revision (ICD-10) depression diagnosis at age 18 years, and to explore the importance of genetic confounding and bullying. Design, Setting, and Participants Longitudinal study of participants in the Avon Longitudinal Study of Parents and Children birth cohort in Bristol, United Kingdom, followed up through age 18 years. Data analysis was conducted from January to November 2017. Main Outcomes and Measures Depressive symptoms were assessed using the Short Mood and Feelings Questionnaire (SMFQ) at 6 time points between ages 10 and 18 years. An ICD-10 depression diagnosis at age 18 years was established using the Clinical Interview Schedule–Revised. Exposures were ASD diagnosis and 4 dichotomized autistic traits (social communication, coherence, repetitive behavior, and sociability). An autism polygenic risk score was derived using the Psychiatric Genomics Consortium autism discovery genome-wide association study summary data. Bullying was assessed at ages 8, 10, and 13 years. Results The maximum sample with complete data was 6091 for the trajectory analysis (48.8% male) and 3168 for analysis of depression diagnosis at age 18 years (44.4% male). Children with ASD and autistic traits had higher average SMFQ depressive symptom scores than the general population at age 10 years (eg, for social communication 5.55 [95% CI, 5.16-5.95] vs 3.73 [95% CI, 3.61-3.85], for ASD 7.31 [95% CI, 6.22-8.40] vs 3.94 [95% CI, 3.83-4.05], remaining elevated in an upward trajectory until age 18 years (eg, for social communication 7.65 [95% CI, 6.92-8.37] vs 6.50 [95% CI, 6.29-6.71], for ASD 7.66 [95% CI, 5.96-9.35] vs 6.62 [95% CI, 6.43-6.81]). Social communication impairments were associated with depression at age 18 years (adjusted relative risk, 1.68; 95% CI, 1.05-2.70), and bullying explained a substantial proportion of this risk. There was no evidence of confounding by the autism polygenic risk score. Analysis in larger samples using multiple imputation led to similar but more precise results. Conclusions and Relevance Children with ASD and ASD traits have higher depressive symptom scores than the general population by age 10 years, which persist to age 18 years, particularly in the context of bullying. Social communication impairments are an important autistic trait in relation to depression. Bullying, as an environmental intermediary, could be a target for interventions.

Causal effects of lifetime smoking on risk for depression and schizophrenia: Evidence from a Mendelian randomisation study

Smoking prevalence is higher amongst individuals with schizophrenia and depression, compared to the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS). We conducted a GWAS of lifetime smoking behaviour (capturing smoking duration, heaviness and cessation) in a sample of 463,003 individuals from the UK Biobank, and validated the findings via MR analyses of positive control outcomes (e.g., lung cancer). Further MR analyses provided evidence that smoking is a causal risk factor for both schizophrenia and depression. We also found some evidence that genetic liability for both depression and schizophrenia cause increased lifetime smoking. These findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking. The genetic variants we identify for lifetime smoking have the potential to be used in further MR studies.

Longitudinal serological measures of common infection in the Avon Longitudinal Study of Parents and Children cohort

Antibodies against pathogens provide information on exposure to infectious agents and are meaningful measures of past and present infection. Antibodies were measured in the plasma of children that are the offspring in a population-based birth cohort, the Avon Longitudinal Study of Parents and Children (ALSPAC). Plasma was collected during clinics at age 5, 7, 11 and 15 years. The antigens examined include: fungal ( Saccharomyces cerevisiae); protozoan ( Toxoplasma gondii and surface antigen 1 of T. gondii); herpes viruses (cytomegalovirus, Epstein-Barr virus, herpes simplex virus type 1); common colds (influenza virus subtypes H1N1 and H3N2); other antigens (measles); animal (feline herpes virus, Theiler’s virus); bacteria ( Helicobacter pylori); dietary antigens (bovine casein alpha protein, bovine casein beta protein). Alongside the depth of data available within the ALSPAC cohort, this longitudinal resource will enable the investigation of the association between infections and a wide variety of outcomes.

Investigating the genetic architecture of general and specific psychopathology in adolescence

Whilst associations between polygenic risk scores (PRSs) for schizophrenia and various phenotypic outcomes have been reported, an understanding of developmental pathways can only be gained by modelling comorbidity across psychopathology. We examine how genetic risk for schizophrenia relates to adolescent psychosis-related and internalizing psychopathology using a latent modelling approach, and compare this to genetic risk for other psychiatric disorders, to gain a more comprehensive understanding of the developmental pathways at this age. PRSs for schizophrenia, major depressive disorder, neuroticism and bipolar disorder were generated for individuals in the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. Multivariate linear regression was used to examine the relationships of these PRSs with psychopathology factors modelled within (i) a correlated factors structure and (ii) a bifactor structure. The schizophrenia PRS was associated with an increase in factors describing psychotic experiences, negative dimension, depression and anxiety, but, when modelling a general psychopathology factor based on these measures, specific effects above this persisted only for the negative dimension. Similar factor relationships were observed for the neuroticism PRS, with a (weak) specific effect only for anxiety once modelling general psychopathology. Psychopathology during adolescence can be described by a general psychopathology construct that captures common variance as well as by specific constructs capturing remaining non-shared variance. Schizophrenia risk genetic variants identified through genome-wide association studies mainly index negative rather than positive symptom psychopathology during adolescence. This has potentially important implications both for research and risk prediction in high-risk samples.

S139. INVESTIGATING THE GENETIC ARCHITECTURE OF GENERAL AND SPECIFIC PSYCHOPATHOLOGY IN ADOLESCENCE USING SCHIZOPHRENIA POLYGENIC SCORES

Abstract Background Whilst associations between polygenic risk scores (PRSs) for schizophrenia and various phenotypic outcomes have been reported, an understanding of developmental pathways can only be gained by modelling comorbidity across psychopathology, something no studies have done to date. We examine how genetic risk for schizophrenia relates to a broad range of adolescent psychopathology using a latent modelling approach, and compare this to genetic risk for other psychiatric disorders, to gain a more comprehensive understanding of development pathways at this age. Methods PRSs for schizophrenia, major depressive disorder, neuroticism and bipolar disorder were generated for individuals in the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. Multivariate linear regression was used to examine relationships of these PRSs with psychopathology factors modelled within i) a correlated factors structure, and ii) a bifactor structure. Results The schizophrenia PRS was associated with an increase in factors describing psychotic experiences, negative dimension, depression, and anxiety, but once modelling a general psychopathology factor specific effects above this persisted only for the negative dimension. Similar factor relationships were observed for the neuroticism PRS, with a (weak) specific effect only for anxiety once modelling general psychopathology. Discussion Psychopathology during adolescence can be described by a general psychopathology construct that captures common variance as well as by specific constructs capturing remaining non-shared variance. Schizophrenia risk genetic variants identified through genome-wide association studies mainly index negative rather than positive symptom psychopathology during adolescence. This has potentially important implications both for research and risk prediction in high-risk samples.

T128. THE ASSOCIATION BETWEEN GENETIC RISK FOR SCHIZOPHRENIA AND PATTERNS OF CIGARETTE AND CANNABIS USE IN ADOLESCENCE

Abstract Background Schizophrenia is associated with a higher prevalence of cannabis use and cigarette use. However, it is unknown to what extent these associations are due to a shared genetic aetiology. We therefore aim to examine how schizophrenia genetic risk associates with patterns of cigarette and cannabis use in adolescence. Methods We analysed repeated measures of cigarette and cannabis use during adolescence in a sample of 5,300 individuals in the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort who had at least 3 measures of cigarette and cannabis use between ages 14–19 years. Cigarette and cannabis use data were summarised using longitudinal latent class analysis to identify longitudinal classes of substance use, and associations between polygenic scores for schizophrenia and resulting classes were assessed. Results The schizophrenia polygenic score based on single nucleotide polymorphisms (SNPs) meeting a discovery sample threshold of p ≤ 0.05 was associated with late onset cannabis use as compared to non-use (OR = 1.20; 95% CI = 1.05, 1.37) but not with early onset or cigarette only use latent classes. This association persisted after excluding the CHRNA5-CHRNA3-CHRNB4 nicotinic receptor gene cluster (OR = 1.25; 95% CI = 1.08, 1.44), a locus which has previously been found to strongly associate with schizophrenia. Discussion This study found that genetic risk of schizophrenia (as captured by polygenic scores) is associated with late-onset cannabis use but not with other smoking phenotypes in adolescence in ALSPAC. Possible explanations for these results are that schizophrenia and cannabis use have a shared genetic aetiology or that biological risk of schizophrenia leads to cannabis use through secondary mechanisms. These secondary mechanisms may include stress of childhood behavioural problems occurring as a result of biological processes underling schizophrenia. Future analyses involving mediation models may shed some light on factors influencing patterns of substance use in individuals with a high genetic liability for schizophrenia.

F138. INVESTIGATING A CAUSAL ASSOCIATION BETWEEN NEUROTICISM AND SCHIZOPHRENIA USING TWO-SAMPLE MENDELIAN RANDOMIZATION

Abstract Background Anxiety is a prominent feature of schizophrenia, present in the prodromal phase of the illness. There is strong evidence that the personality trait neuroticism, an underlying factor strongly associated with anxiety, is genetically correlated with schizophrenia, implying that neuroticism and schizophrenia share genetic risk factors in common. However, a genetic correlation may also suggest a possible role of neuroticism in the pathogenesis of schizophrenia. We therefore performed a Mendelian randomization (MR) analysis using publicly available data to investigate the potential casual association between neuroticism and schizophrenia. Methods We performed bi-directional two-sample MR between neuroticism and schizophrenia using the most recent publically available summary-level genome-wide data. Single nucleotide polymorphisms (SNPs) associated with neuroticism (p ≤ 1e-5) and schizophrenia (p ≤ 5e-8) were combined using an inverse-variance-weighted (IVW) multiplicative random effects approach. Impact of potential MR assumption violations were explored using weighted median, weighted mode and MR Egger methods. All analyses were performed using the TwoSampleMR R package. Results The IVW MR method provided strong evidence of a casual effect of genetically instrumented neuroticism on risk of schizophrenia (p < 0.001). This causal association was also evident when using the median weighted approach (p = 0.004) but evidence was weaker when using the weighted mode (p = 0.719) and MR Egger approaches (p = 0.439). The MR Egger intercept provided weak evidence of presence of horizontal pleiotropy (p = 0.067), however, the I2GX statistic indicated potential violation of the no measurement error MR assumption. There was also evidence of a causal effect of schizophrenia on neuroticism (IVW p = 0.001, weighted median p = 0.017, weighted mode p = 0.018) however, again, the I2GX statistic indicated potential violation of the no measurement error MR assumption. Discussion Assuming certain MR assumptions are met, our results provide evidence of a bi-directional causal association between neuroticism and schizophrenia suggesting a genetic overlap rather than a uni-directional casual association, however, the impact of feedback loops between exposure and outcome cannot be addressed. Although there was evidence of horizontal pleiotropy between neuroticism and schizophrenia, evidence of violation of the no measurement error indicates that the MR Egger results should be interpreted with caution.