250 words). Background. 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).Methods. We conducted a GWAS of lifetime smoking behaviour (capturing smoking duration, heaviness and cessation) in a sample of 462,690 individuals from the UK Biobank, and validated the findings via two-sample MR analyses of positive control outcomes (e.g., lung cancer). Having established the validity of our instrument, we used bi-directional twosample Mendelian randomisation to explore its effects on schizophrenia and depression.Outcomes. There was strong evidence to suggest smoking is a causal risk factor for both schizophrenia (OR = 2.27, 95% CI = 1.67 -3.08, P < 0.001) and depression (OR = 1.99, 95% CI = 1.71 -2.32, P < 0.001). We also found some evidence that genetic risk for both schizophrenia and depression cause increased lifetime smoking (β = 0.022, 95% CI = 0.005 -0.038, P = 0.009; β = 0.091, 95% CI = 0.027 -0.155, P = 0.005).Interpretation. These findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking, providing further evidence for the detrimental consequences of smoking for mental health.Evidence before this study: The association between smoking and mental health (especially schizophrenia and depression) is often assumed to be the result of selfmedication (for example, to alleviate symptoms). However, more recent evidence has suggested that smoking might also be a risk factor for schizophrenia and depression. This alternative direction of effect is supported by meta-analyses and previous prospective observational evidence using related individuals to control for genetic and environmental confounding. However, observational evidence cannot completely account for confounding or the possibility of reverse causation. One way to get around these problems is Mendelian randomisation (MR). Previous MR studies of smoking and mental health have not shown an effect of smoking on depression and are inconclusive for the effects of smoking on schizophrenia. However, these studies have only looked at individual aspects of smoking behaviour and some studies required stratifying participants into smokers and non-smokers, reducing power. Added value of this study:We have developed a novel genetic instrument for lifetime smoking exposure which can be used within a two-sample MR framework, using publiclyavailable GWAS summary statistics. We were therefore able to test the bi-directional association between smoking with schizophrenia and depression to see if the effects are causal. We found strong evidence to suggest that smoking is a causal risk factor for both schizophrenia and depression. There was some evidence to suggest that risk of schizophrenia and depression increases lifetime smoking (consistent with the selfmedication hypothesis) but t...

Background Smoking and e-cigarette use are strongly associated, but it is currently unclear whether this association is causal, or due to shared factors that influence both behaviours such as a shared genetic liability. The aim of this study was to investigate whether polygenic risk scores (PRS) for smoking initiation are associated with ever use of e-cigarettes. Methods PRS of smoking initiation were calculated for young adults (aged 23 to 26 years) of European ancestry in the Avon Longitudinal Study of Parents and Children using the GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN) summary statistics. Five thresholds ranging from 5 × 10-8 to 0.5 were used to calculate five PRS for each individual. Using logistic regression, we investigated the association between smoking initiation PRS and both self-reported smoking initiation and self-reported e-cigarette use, as well as a number of negative control outcomes (socioeconomic position at birth, externalising disorders in childhood and risk-taking in young adulthood). Results We observed positive associations of similar magnitude between smoking initiation PRS and both smoking initiation (OR = 1.29, 95% CI 1.19 to 1.39) and ever e-cigarette use (OR = 1.24, 95% CI 1.14 to 1.34) by the age of 24 years. At lower p-value thresholds, we observed an association between smoking initiation PRS and ever e-cigarette use among never smokers. We also found evidence of associations between smoking initiation PRS and some negative control outcomes, particularly when less stringent p-value thresholds were used but also at the strictest threshold (e.g., gambling, number of sexual partners, conduct disorder at 7 years, and parental socioeconomic position at birth). Conclusions Our results indicate that there may be a shared genetic aetiology between smoking and e-cigarette use, and also with socioeconomic position, externalising disorders in childhood, and risky behaviour more generally. Taken together, this indicates that there may be a common genetic vulnerability to both smoking and e-cigarette use, which may reflect a broad risk-taking phenotype.

Background: Psychosis-like experiences (PLEs) are common and associated with mental health problems and poorer cognitive function. There is limited longitudinal research examining associations between cognition and PLEs in early adulthood. Aims: We investigated the association of PLEs with different domains of cognitive function, using cross-sectional and longitudinal observational, and Mendelian randomisation (MR) analyses. Method: Participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) completed tasks of working memory at age 18 and 24, and tasks of response inhibition and facial emotion recognition at age 24. Semi-structured interviews at age 18 and 24 established presence of PLEs (none vs. suspected/definite). Cross-sectional and prospective regression analysis tested associations between PLEs and cognition (N=3,087 imputed sample). MR examined causal pathways between schizophrenia liability and cognition. Results: The fully adjusted models indicated that PLEs were associated with poorer working memory performance (cross-sectional analyses: b=-0.18, 95% CI -0.27 to -0.08, p<0.001; prospective analyses: b=-0.18, 95% CI -0.31 to -0.06, p<0.01). A similar pattern of results was found for PLEs and response inhibition (cross-sectional analyses: b=7.29, 95% CI 0.96 to 13.62, p=0.02; prospective analyses: b=10.29, 95% CI 1.78 to 18.97, p=0.02). We did not find evidence to suggest an association between PLEs and facial emotion recognition. MR analyses were underpowered and did not support observational results. Conclusions: In young adults, PLEs are associated with poorer concurrent and future working memory and response inhibition. Better powered genetically informed studies are needed to determine if these associations are causal.