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Background: Various vitamins and minerals have been implicated in the aetiology of depression. Objective: To estimate the effects of micronutrient exposures on major depressive disorder (MDD) and recurrent depression (rMDD) using Mendelian randomisation (MR), a method using genetic data to estimate causal effects given certain assumptions. Methods: We undertook a comprehensive bidirectional MR study of multiple micronutrient exposures on MDD and rMDD. Summary statistics were obtained from the Psychiatric Genomics Consortium (PGC) genome-wide association studies (GWASs) of MDD (cases = 116,209; controls = 314,566) and rMDD (cases = 17,451; controls = 62,482). Results: None of the micronutrients with available genetic instruments were strongly associated with MDD or rMDD using traditional MR methods. However, using methods to increase analytical power by accounting for genetically correlated variants (e.g., cIVW) highlighted five micronutrients with possible causal effects. Point estimates for rMDD were the largest magnitude, with three micronutrients suggestive of a protective effect: serum iron (ORcIVW 0.90 per SD increase; 95% CI 0.85–0.95; p = 0.0003); erythrocyte copper (ORcIVW 0.97; 95% CI 0.95–0.99; p = 0.0004); and 25(OH) vitamin D (ORcIVW 0.81; 0.66–0.99; p = 0.04). Apparent adverse effects of increased selenium on the risk of MDD (ORcIVW 1.03; 95% CI 1.02–1.05; p = 0.0003) and rMDD (ORcIVW 1.08; 95% CI 1.00–1.08; p = 0.06), and serum magnesium on rMDD (ORcIVW 1.21; 1.01–1.44; p = 0.04); were less consistent between methods and may be driven by pleiotropy. Conclusions: Our results suggest weak evidence for a protective effect of iron, copper and 25(OH)D on major depressive outcomes, with mixed evidence for selenium and magnesium. There was no evidence to support a causal effect of any other micronutrients on MDD or rMDD, although genetic instruments were lacking, with insufficient power to detect small but important effects. Future micronutrient supplementation trials should ensure ample statistical power given modest causal effect estimates and consider potential risks of supplementation, as some micronutrient effect estimates suggested potential harm in excess. [ABSTRACT FROM AUTHOR]

Background Smokers report poorer sleep than nonsmokers and sleep quality deteriorates further during cessation, increasing risk of smoking relapse. Better understanding of the relationship between sleep and relapse-related outcomes could inform novel approaches to smoking cessation support. The aim of this study was to investigate same-day associations of self-reported sleep quality and fatigue severity with factors associated with successful cessation and cessation beliefs, among regular smokers. Methods This cross-sectional observational study (n = 412) collected self-reported sleep quality, fatigue severity, and factors associated with successful cessation and cessation beliefs among regular smokers via an online survey (60% male). Results There was evidence of an association between sleep quality (SQ) and reduced 24-hour (β = −0.12, p =.05) and lifetime (β = −0.09, p =.04) abstinence self-efficacy. In addition, poorer SQ and higher fatigue severity (FS) were associated with increased smoking urges (SQ: β = 0.27, p <.001; FS: β = 0.32, p <.001), increased barriers to cessation (SQ: β = 0.19, p <.001; FS: β = 0.32, p <.001), and increased perceived risks to cessation (SQ: β = 0.18, p <.001; FS: β = 0.26, p <.001). Fatigue severity was weakly associated with increased perceived benefits to cessation (β = 0.12, p =.017). Conclusions Self-reported sleep quality and fatigue severity were associated with multiple factors associated with successful cessation and cessation beliefs. Further research is needed to extend these findings by using different methods to identify the temporal direction of associations and causality. Implications This study is the first to examine associations between sleep quality, fatigue severity, and factors associated with successful cessation and cessation beliefs. Findings show that both sleep quality and fatigue severity are associated with multiple factors associated with successful cessation and could be modifiable targets for future smoking cessation interventions. Furthermore, our data suggest that fatigue severity has an independent effect on multiple factors associated with successful cessation when accounting for sleep quality. This indicates that fatigue, independent of sleep quality, could be an important factor in a quit attempt. [ABSTRACT FROM AUTHOR]

Introduction Although observational data suggest a relationship between headache and smoking, there remain questions about causality. Smoking may increase headache risk, individuals may smoke to alleviate headaches, or smoking and headache may share common risk factors. Mendelian randomization (MR) is a method that uses genetic variants as instruments for making causal inferences about an exposure and an outcome. Aims and Methods First, we conducted logistic regression of observational data in UK Biobank assessing the association between smoking behaviors (smoking status, cigarettes per day amongst daily smokers, and lifetime smoking score) on the risk of self-reported headache (in the last month and for more than 3 months). Second, we used genetic instruments for smoking behaviors and headache (identified in independent genome-wide association studies [GWAS]) to perform bidirectional MR analysis. Results Observationally, there is a weak association between smoking behavior and experiencing headache, with increased cigarettes per day associated with increased headache risk. In the MR analysis, genetic liability to smoking initiation and lifetime smoking increased odds of headache in the last month but not odds of headaches lasting more than 3 months. In the opposite direction, there was weak evidence for higher genetic liability to headaches decreasing the chance of quitting. Conclusions There was weak evidence for a partially bidirectional causal relationship between smoking behaviors and headache in the last month. Given this relationship is distinct from smoking heaviness, it suggests headache and smoking may share common risk factors such as personality traits. Implications Using MR, this study addresses the uncertainty regarding the observed relationship between headache and smoking. There was evidence for weak causal effects of smoking initiation and lifetime smoking (but not smoking heaviness) on likelihood of experiencing headache in the last month, but not over a prolonged period of more than 3 months. Those with higher genetic liability to headaches were also less likely to successfully stop smoking. This partially bidirectional causal relationship distinct from smoking heaviness suggests that observed associations are unlikely due to biological effects of tobacco smoke exposure and may be explained by shared personality traits. [ABSTRACT FROM AUTHOR]

Postpartum depression (PPD) is a common subtype of major depressive disorder (MDD) that is more heritable, yet is understudied in psychiatric genetics. The authors conducted meta-analyses of genome-wide association studies (GWASs) to investigate the genetic architecture of PPD. Meta-analyses were conducted on 18 cohorts of European ancestry (17,339 PPD cases and 53,426 controls), one cohort of East Asian ancestry (975 cases and 3,780 controls), and one cohort of African ancestry (456 cases and 1,255 controls), totaling 18,770 PPD cases and 58,461 controls. Post-GWAS analyses included 1) single-nucleotide polymorphism (SNP)–based heritability (), 2) genetic correlations between PPD and other phenotypes, and 3) enrichment of the PPD GWAS findings in 27 human tissues and 265 cell types from the mouse central and peripheral nervous system. No SNP achieved genome-wide significance in the European or the trans-ancestry meta-analyses. The of PPD was 0.14 (SE=0.02). Significant genetic correlations were estimated for PPD with MDD, bipolar disorder, anxiety disorders, posttraumatic stress disorder, insomnia, age at menarche, and polycystic ovary syndrome. Cell-type enrichment analyses implicate inhibitory neurons in the thalamus and cholinergic neurons within septal nuclei of the hypothalamus, a pattern that differs from MDD. While more samples are needed to reach genome-wide levels of significance, the results presented confirm PPD as a polygenic and heritable phenotype. There is also evidence that despite a high correlation with MDD, PPD may have unique genetic components. Cell enrichment results suggest GABAergic neurons, which converge on a common mechanism with the only medication approved by the U.S. Food and Drug Administration for PPD (brexanolone). [ABSTRACT FROM AUTHOR]

Background Smoking prevalence is higher among individuals with schizophrenia or depression, and previous work has suggested this relationship is causal. However, this may be due to dynastic effects, for example reflecting maternal smoking during pregnancy rather than a direct effect of smoking. We used a proxy gene-by-environment Mendelian randomization approach to investigate whether there is a causal effect of maternal heaviness of smoking during pregnancy on offspring mental health. Methods Analyses were performed in the UK Biobank cohort. Individuals with data on smoking status, maternal smoking during pregnancy, a diagnosis of schizophrenia or depression, and genetic data were included. We used participants' genotype (rs16969968 in the CHRNA5 gene) as a proxy for their mothers' genotype. Analyses were stratified on participants' own smoking status in order to estimate the effect of maternal smoking heaviness during pregnancy independently of offspring smoking. Results The effect of maternal smoking on offspring schizophrenia was in opposing directions when stratifying on offspring smoking status. Among offspring of never smokers, each additional risk allele for maternal smoking heaviness appeared to have a protective effect [odds ratio (OR)   =   0.77, 95% confidence interval (CI) 0.62 to 0.95, P =  0.015], whereas among ever smokers the effect of maternal smoking was in the reverse direction (OR = 1.23, 95% CI 1.05 to 1.45, P =  0.011, P interaction   <0.001). There was no clear evidence of an association between maternal smoking heaviness and offspring depression. Conclusions These findings do not provide clear evidence of an effect of maternal smoking during pregnancy on offspring schizophrenia or depression, which implies that any causal effect of smoking on schizophrenia or depression is direct. [ABSTRACT FROM AUTHOR]

Objective: To use genome-wide association study (GWAS) by subtraction, a method for deriving novel GWASs from existing summary statistics, to derive genome-wide summary statistics for paternal smoking. Result: A GWAS by subtraction was implemented using a weighted linear model that defined the child-genotype paternal-phenotype association as the child-genotype child-phenotype association minus the child-genotype maternal-phenotype association. We first use the laws of inherence to derive the weighted linear model. We then implemented the linear model to create a GWAS of paternal smoking by subtracting the summary statistics from a GWAS of maternal smoking from the summary statistics of a GWAS of the index individual's smoking. We used a Monte-Carlo simulation to validate the model and showed that this approach performed similarly in terms of bias to performing a traditional GWAS of paternal smoking. Finally, we validated the summary statistics in a Mendelian randomisation analysis by demonstrating an association of genetically predicted paternal smoking with paternal lung cancer and emphysema. [ABSTRACT FROM AUTHOR]

Background Mendelian randomization (MR) is a form of instrumental variable analysis used to investigate causality using observational data. Another important, although less frequently applied, use of this technique is to investigate confounding due to reverse causality. Methods We used a form of reverse MR and data from UK Biobank in a proof-of-principle study to investigate confounding due to reverse causation. Here we focus on the association between alcohol consumption (exposure) and outcomes including educational attainment, and physical and mental health. First, we examined the observational relationship between alcohol consumption and these outcomes. Allele scores were then derived for educational attainment, and physical and mental health, and the association with alcohol consumption (as the outcome) was explored. Sample sizes ranged from 114 941–336 473 in observational analyses and 142 093–336 818 in genetic analyses. Results Conventional observational analyses indicated associations between alcohol consumption and a number of outcomes (e.g. neuroticism, body mass index, educational attainment). Analyses using allele scores suggested evidence of reverse causation for several of these relationships (in particular physical health and educational attainment). Conclusion Allele scores allow us to investigate reverse causation in observational studies. Our findings suggest that observed associations implying beneficial effects of alcohol consumption may be due to confounding by reverse causation in many cases. [ABSTRACT FROM AUTHOR]

Background: Observational research implies a negative effect of having children on wellbeing. Objectives: To provide Mendelian randomisation evidence of the effect of having children on parental wellbeing. Design: Two-sample Mendelian randomisation. Setting: Non-clinical European ancestry participants. Participants: We used the UK Biobank (460,654 male and female European ancestry participants) as a source of genotype-exposure associations, the Social Science Genetics Consortia (SSGAC) (298,420 male and female European ancestry participants), and the Within-Family Consortia (effective sample of 22,656 male and female European ancestry participants) as sources of genotype-outcome associations. Interventions: The lifetime effect of an increase in the genetic liability to having children. Primary and secondary outcome measures: The primary analysis was an inverse variance weighed analysis of subjective wellbeing measured in the 2016 SSGAC Genome Wide Association Study (GWAS). Secondary outcomes included pleiotropy robust estimators applied in the SSGAC and an analysis using the Within-Family consortia GWAS. Results: We did not find strong evidence of a negative (standard deviation) change in wellbeing (β = 0.153 (95% CI: −0.210 to 0.516) per child parented. Secondary outcomes were generally slightly deflated (e.g., −0.049 [95% CI: −0.533 to 0.435] for the Within-Family Consortia and 0.090 [95% CI: −0.167 to 0.347] for weighted median), implying the presence of some residual confounding and pleiotropy. Conclusions: Contrary to the existing literature, our results are not compatible with a measurable negative effect of number of children on the average wellbeing of a parent over their life course. However, we were unable to explore non-linearities, interactions, or time-varying effects. [ABSTRACT FROM AUTHOR]

Mental health has worsened, and substance use has increased for some people during the coronavirus (COVID-19) pandemic. Some cross-sectional studies suggest that higher COVID-19 risk perceptions are related to poorer mental health and greater risk behaviours (e.g. substance use). However, longitudinal and genetic data are needed to help to reduce the likelihood of reverse causality. We used cross-sectional, longitudinal, and polygenic risk score (PRS; for anxiety, depression, wellbeing) data from the Avon Longitudinal Study of Parents and Children (ALSPAC). We examined cross-sectional and prospective longitudinal associations between COVID-19 risk perceptions (i.e. cognitive, affective, self, other, and a combined 'holistic' measure) and mental health (i.e. anxiety, depression), wellbeing, and risk behaviours. Pandemic (April–July 2020) and pre-pandemic (2003–2017) data (ns = 233–5,115) were included. Higher COVID-19 risk perceptions (holistic) were associated with anxiety (OR 2.78, 95% confidence interval [CI] 2.20 to 3.52), depression (OR 1.65, 95% CI 1.24 to 2.18), low wellbeing (OR 1.76, 95% CI 1.45 to 2.13), and increased alcohol use (OR 1.46, 95% CI 1.24 to 1.72). Higher COVID-19 risk perceptions were also associated with self-isolating given a suspected COVID-19 infection (OR 1.74, 95% CI 1.13 to 2.68), and less face-to-face contact (OR 0.83, 95% CI 0.70 to 0.98) and physical contact (OR 0.83, 95% CI 0.68 to 1.00). Pre-pandemic anxiety (OR 1.64, 95% CI 1.29 to 2.09) and low wellbeing (OR 1.41, 95% CI 1.15 to 1.74) were associated with higher COVID-19 risk perceptions. The depression PRS (b 0.21, 95% CI 0.02 to 0.40) and wellbeing PRS (b − 0.29, 95% CI −0.48 to −0.09) were associated with higher and lower COVID-19 risk perceptions, respectively. Poorer mental health and wellbeing are associated with higher COVID-19 risk perceptions, and longitudinal and genetic data suggest that they may play a causal role in COVID-19 risk perceptions. [ABSTRACT FROM AUTHOR]

Background and aims: Several studies have indicated an association between maternal prenatal substance use and offspring externalizing disorders; however, it is uncertain whether this relationship is causal. We conducted a systematic review to determine: (1) if the literature supports a causal role of maternal prenatal substance use on offspring externalizing disorders diagnosis and (2) whether these associations differ across externalizing disorders. Methods: We searched Web of Science, Embase, PsycINFO and Medline databases. Risk of bias assessment was conducted using the Newcastle–Ottawa Scale (NOS), and where possible meta‐analysis was conducted for studies classed as low risk of bias. We included studies of any design that examined prenatal smoking, alcohol or caffeine use. Studies in non‐English language, fetal alcohol syndrome and comorbid autism spectrum disorders were excluded. Participants in the included studies were mothers and their offspring. Measurements included prenatal smoking, alcohol or caffeine use as an exposure, and diagnosis of attention‐deficit hyperactivity disorder (ADHD), conduct disorder (CD) and oppositional defiant disorder (ODD) in offspring as an outcome. Results: We included 63 studies, 46 of which investigated smoking and ADHD. All studies were narratively synthesized, and seven studies on smoking and ADHD were meta‐analysed. The largest meta‐analysis based on genetically sensitive design included 1 011 546 participants and did not find evidence for an association [odds ratio (OR)1–9 cigarettes = 0.90, 95% confidence interval (CI) = 0.83–1.11; OR > 10 cigarettes = 1.04, 95% CI = 0.79–1.36). Studies on alcohol exposure in all the outcomes reported inconsistent findings and no strong conclusions on causality can be made. Studies on caffeine exposure were mainly limited to ADHD and these studies do not support a causal effect. Conclusions: There appears to be no clear evidence to support a causal relationship between maternal prenatal smoking and offspring attention‐deficit hyperactivity disorder. Findings with alcohol and caffeine exposures and conduct disorder and oppositional–defiant disorder need more research, using more genetically sensitive designs. [ABSTRACT FROM AUTHOR]

Background: Observational studies have found associations between smoking and both poorer cognitive ability and lower educational attainment; however, evaluating causality is challenging. We used two complementary methods to explore this. Methods: We conducted observational analyses of up to 12 004 participants in a cohort study (Study One) and Mendelian randomisation (MR) analyses using summary and cohort data (Study Two). Outcome measures were cognitive ability at age 15 and educational attainment at age 16 (Study One), and educational attainment and fluid intelligence (Study Two). Results: Study One: heaviness of smoking at age 15 was associated with lower cognitive ability at age 15 and lower educational attainment at age 16. Adjustment for potential confounders partially attenuated findings (e.g. fully adjusted cognitive ability β −0.736, 95% CI −1.238 to −0.233, p = 0.004; fully adjusted educational attainment β −1.254, 95% CI −1.597 to −0.911, p < 0.001). Study Two: MR indicated that both smoking initiation and lifetime smoking predict lower educational attainment (e.g. smoking initiation to educational attainment inverse-variance weighted MR β −0.197, 95% CI −0.223 to −0.171, p = 1.78 × 10−49). Educational attainment results were robust to sensitivity analyses, while analyses of general cognitive ability were less so. Conclusion: We find some evidence of a causal effect of smoking on lower educational attainment, but not cognitive ability. Triangulation of evidence across observational and MR methods is a strength, but the genetic variants associated with smoking initiation may be pleiotropic, suggesting caution in interpreting these results. The nature of this pleiotropy warrants further study. [ABSTRACT FROM AUTHOR]

Background: Polygenic risk scores (PRSs) operationalize genetic propensity toward a particular mental disorder and hold promise as early predictors of psychopathology, but before a PRS can be used clinically, explanatory power must be increased and the specificity for a psychiatric domain established. To enable early detection, it is crucial to study these psychometric properties in childhood. We examined whether PRSs associate more with general or with specific psychopathology in school‐aged children. Additionally, we tested whether psychiatric PRSs can be combined into a multi‐PRS score for improved performance. Methods: We computed 16 PRSs based on GWASs of psychiatric phenotypes, but also neuroticism and cognitive ability, in mostly adult populations. Study participants were 9,247 school‐aged children from three population‐based cohorts of the DREAM‐BIG consortium: ALSPAC (UK), The Generation R Study (Netherlands), and MAVAN (Canada). We associated each PRS with general and specific psychopathology factors, derived from a bifactor model based on self‐report and parental, teacher, and observer reports. After fitting each PRS in separate models, we also tested a multi‐PRS model, in which all PRSs are entered simultaneously as predictors of the general psychopathology factor. Results: Seven PRSs were associated with the general psychopathology factor after multiple testing adjustment, two with specific externalizing and five with specific internalizing psychopathology. PRSs predicted general psychopathology independently of each other, with the exception of depression and depressive symptom PRSs. Most PRSs associated with a specific psychopathology domain, were also associated with general child psychopathology. Conclusions: The results suggest that PRSs based on current GWASs of psychiatric phenotypes tend to be associated with general psychopathology, or both general and specific psychiatric domains, but not with one specific psychopathology domain only. Furthermore, PRSs can be combined to improve predictive ability. PRS users should therefore be conscious of nonspecificity and consider using multiple PRSs simultaneously, when predicting psychiatric disorders. [ABSTRACT FROM AUTHOR]

Background and aims: Studies have indicated that maternal prenatal substance use may be associated with offspring attention deficit hyperactivity disorder (ADHD) via intrauterine effects. We measured associations between prenatal smoking, alcohol and caffeine consumption with childhood ADHD symptoms accounting for shared familial factors. Design First, we used a negative control design comparing maternal and paternal substance use. Three models were used for negative control analyses: unadjusted (without confounders), adjusted (including confounders) and mutually adjusted (including confounders and partner's substance use). The results were meta‐analysed across the cohorts. Secondly, we used polygenic risk scores (PRS) as proxies for exposures. Maternal PRS for smoking, alcohol and coffee consumption were regressed against ADHD symptoms. We triangulated the results across the two approaches to infer causality. Setting: We used data from three longitudinal pregnancy cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) in the United Kingdom, Generation R study (GenR) in the Netherlands and Norwegian Mother, Father and Child Cohort study (MoBa) in Norway. Participants: Phenotype data available for children were: NALSPAC = 5455–7751; NGENR = 1537–3119; NMOBA = 28 053–42 206. Genotype data available for mothers was: NALSPAC = 7074; NMOBA = 14 583. Measurements A measure of offspring ADHD symptoms at age 7–8 years was derived by dichotomizing scores from questionnaires and parental self‐reported prenatal substance use was measured at the second pregnancy trimester. Findings The pooled estimate for maternal prenatal substance use showed an association with total ADHD symptoms [odds ratio (OR)SMOKING = 1.11, 95% confidence interval (CI) = 1.00–1.23; ORALCOHOL = 1.27, 95% CI = 1.08–1.49; ORCAFFEINE = 1.05, 95% CI = 1.00–1.11], while not for fathers (ORSMOKING = 1.03, 95% CI = 0.95–1.13; ORALCOHOL = 0.83, 95% CI = 0.47–1.48; ORCAFFEINE = 1.02, 95% CI = 0.97–1.07). However, maternal associations did not persist in sensitivity analyses (substance use before pregnancy, adjustment for maternal ADHD symptoms in MoBa). The PRS analyses were inconclusive for an association in ALSPAC or MoBa. Conclusions: There appears to be no causal intrauterine effect of maternal prenatal substance use on offspring attention deficit hyperactivity disorder symptoms. [ABSTRACT FROM AUTHOR]

Analysis of secondary data sources (such as cohort studies, survey data, and administrative records) has the potential to provide answers to science and society's most pressing questions. However, researcher biases can lead to questionable research practices in secondary data analysis, which can distort the evidence base. While pre-registration can help to protect against researcher biases, it presents challenges for secondary data analysis. In this article, we describe these challenges and propose novel solutions and alternative approaches. Proposed solutions include approaches to (1) address bias linked to prior knowledge of the data, (2) enable pre-registration of non-hypothesis-driven research, (3) help ensure that pre-registered analyses will be appropriate for the data, and (4) address difficulties arising from reduced analytic flexibility in pre-registration. For each solution, we provide guidance on implementation for researchers and data guardians. The adoption of these practices can help to protect against researcher bias in secondary data analysis, to improve the robustness of research based on existing data. [ABSTRACT FROM AUTHOR]

Background: Conflicting evidence has emerged regarding the relevance of smoking on risk of COVID-19 and its severity.Methods: We undertook large-scale observational and Mendelian randomisation (MR) analyses using UK Biobank. Most recent smoking status was determined from primary care records (70.8%) and UK Biobank questionnaire data (29.2%). COVID-19 outcomes were derived from Public Health England SARS-CoV-2 testing data, hospital admissions data, and death certificates (until 18 August 2020). Logistic regression was used to estimate associations between smoking status and confirmed SARS-CoV-2 infection, COVID-19-related hospitalisation, and COVID-19-related death. Inverse variance-weighted MR analyses using established genetic instruments for smoking initiation and smoking heaviness were undertaken (reported per SD increase).Results: There were 421 469 eligible participants, 1649 confirmed infections, 968 COVID-19-related hospitalisations and 444 COVID-19-related deaths. Compared with never-smokers, current smokers had higher risks of hospitalisation (OR 1.80, 95% CI 1.26 to 2.29) and mortality (smoking 1-9/day: OR 2.14, 95% CI 0.87 to 5.24; 10-19/day: OR 5.91, 95% CI 3.66 to 9.54; 20+/day: OR 6.11, 95% CI 3.59 to 10.42). In MR analyses of 281 105 White British participants, genetically predicted propensity to initiate smoking was associated with higher risks of infection (OR 1.45, 95% CI 1.10 to 1.91) and hospitalisation (OR 1.60, 95% CI 1.13 to 2.27). Genetically predicted higher number of cigarettes smoked per day was associated with higher risks of all outcomes (infection OR 2.51, 95% CI 1.20 to 5.24; hospitalisation OR 5.08, 95% CI 2.04 to 12.66; and death OR 10.02, 95% CI 2.53 to 39.72).Interpretation: Congruent results from two analytical approaches support a causal effect of smoking on risk of severe COVID-19. [ABSTRACT FROM AUTHOR]

Background and aims: Previous studies suggest an association between maternal tobacco and caffeine consumption during and outside of pregnancy and offspring mental health. We aimed to separate effects of the maternal environment (intrauterine or postnatal) from pleiotropic genetic effects. Design Secondary analysis of a longitudinal study. We (i) validated smoking and caffeine genetic risk scores (GRS) derived from published genome‐wide association study (GWAS) for use during pregnancy, (ii) compared estimated effects of maternal and offspring GRS on childhood mental health outcomes and (iii) tested associations between maternal and offspring GRS on their respective outcomes. Setting: We used data from a longitudinal birth cohort study from England, the Avon Longitudinal Study of Parents and Children (ALSPAC). Participants: Our sample included 7921 mothers and 7964 offspring. Measurements Mental health and non‐mental health phenotypes were derived from questionnaires and clinical assessments: 79 maternal phenotypes assessed during and outside of pregnancy and 71 offspring phenotypes assessed in childhood (<10 years) and adolescence (11–18 years). Findings The maternal smoking and caffeine GRS were associated with maternal smoking and caffeine consumption during pregnancy (2nd trimester: Psmoking = 3.0 × 10−7, Pcaffeine = 3.28 × 10−5). Both the maternal and offspring smoking GRS showed evidence of association with reduced childhood anxiety symptoms (βmaternal = −0.033; βoffspring = −0.031) and increased conduct disorder symptoms (βmaternal = 0.024; βoffspring = 0.030), after correcting for multiple testing. Finally, the maternal and offspring smoking GRS were associated with phenotypes related to sensation seeking behaviours in mothers and adolescence (e.g. increased symptoms of externalising disorders, extraversion and monotony avoidance). The caffeine GRS showed weaker evidence for associations with mental health outcomes. Conclusions: We did not find strong evidence that maternal smoking and caffeine genetic risk scores have a causal effect on offspring mental health outcomes. Our results confirm that the smoking genetic risk scores also captures liability for sensation seeking personality traits. [ABSTRACT FROM AUTHOR]

Background: Observational studies have reported an association between allergic disease and mental health, but a causal relationship has not been established. Here, we use Mendelian randomization (MR) to investigate a possible causal relationship between atopic disease and mental health phenotypes. Methods: The observational relationship between allergic disease and mental health was investigated in UK Biobank. The direction of causality was investigated with bidirectional two‐sample MR using summary‐level data from published genome‐wide association studies. A genetic instrument was derived from associated variants for a broad allergic disease phenotype to test for causal relationships with various mental health outcomes. We also investigated whether these relationships were specific to atopic dermatitis (AD), asthma or hayfever. Given the multiple testing burden, we applied a Bonferroni correction to use an individual test p‐value threshold of.0016 (32 tests). Results: We found strong evidence of an observational association between the broad allergic disease phenotype and depression (ORself‐report=1.45, 95% CI: 1.41–1.50, p = 3.6 × 10−130), anxiety (OR=1.25, 95% CI: 1.18–1.33, p = 6.5 × 10−13), bipolar disorder (ORself‐report=1.29, 95% CI: 1.12–1.47, p = 2.8 × 10−4) and neuroticism (β = 0.38, 95% CI: 0.36–0.41, p = 6.8 × 10−166). Similar associations were found between asthma, AD, hayfever individually with the mental health phenotypes, although the associations between AD and hayfever with bipolar disorder were weaker. There was little evidence of causality in either direction (all p‐values>.02). Conclusion: Using MR, we were unable to replicate most of the phenotypic associations between allergic disease and mental health. Any causal effects we detected were considerably attenuated compared with the phenotypic association. This suggests that most comorbidity observed clinically is unlikely to be causal. [ABSTRACT FROM AUTHOR]

Background: Studies investigating the effects of prenatal alcohol exposure on childhood attention‐deficit hyperactivity disorder (ADHD) symptoms using conventional observational designs have reported inconsistent findings, which may be affected by unmeasured confounding and maternal and fetal ability to metabolize alcohol. We used genetic variants from the alcohol metabolizing genes, alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), as proxies for fetal alcohol exposure to investigate their association with risk of offspring ADHD symptoms around age 7–8 years. Methods: We used data from 3 longitudinal pregnancy cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC), Generation R study (GenR), and the Norwegian Mother, Father and Child Cohort study (MoBa). Genetic risk scores (GRS) for alcohol use and metabolism using 36 single nucleotide polymorphisms (SNPs) from ADH and ALDH genes were calculated for mothers (NALSPAC = 8196; NMOBA = 13,614), fathers (NMOBA = 13,935), and offspring (NALSPAC=8,237; NMOBA=14,112; NGENR=2,661). Associations between maternal GRS and offspring risk of ADHD symptoms were tested in the full sample to avoid collider bias. Offspring GRS analyses were stratified by maternal drinking status. Results: The pooled estimate in maternal GRS analyses adjusted for offspring GRS in ALSPAC and MoBa was OR = 0.99, 95%CI 0.97–1.02. The pooled estimate in offspring GRS analyses stratified by maternal drinking status across all the cohorts was as follows: ORDRINKING = 0.98, 95% CI 0.94–1.02; ORNO DRINKING = 0.99, 95% CI 0.97–1.02. These findings remained similar after accounting for maternal genotype data in ALSPAC and maternal and paternal genotype data in MoBa. Conclusions: We did not find evidence for a causal effect of fetal alcohol exposure on risk of ADHD symptoms in offspring. The results may be affected by limited power to detect small effects and outcome assessment. [ABSTRACT FROM AUTHOR]

Background: There is a wealth of literature on the observed association between childhood trauma and psychotic illness. However, the relationship between childhood trauma and psychosis is complex and could be explained, in part, by gene–environment correlation. Methods: The association between schizophrenia polygenic scores (PGS) and experiencing childhood trauma was investigated using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Norwegian Mother, Father and Child Cohort Study (MoBa). Schizophrenia PGS were derived in each cohort for children, mothers, and fathers where genetic data were available. Measures of trauma exposure were derived based on data collected throughout childhood and adolescence (0–17 years; ALSPAC) and at age 8 years (MoBa). Results: Within ALSPAC, we found a positive association between schizophrenia PGS and exposure to trauma across childhood and adolescence; effect sizes were consistent for both child or maternal PGS. We found evidence of an association between the schizophrenia PGS and the majority of trauma subtypes investigated, with the exception of bullying. These results were comparable with those of MoBa. Within ALSPAC, genetic liability to a range of additional psychiatric traits was also associated with a greater trauma exposure. Conclusions: Results from two international birth cohorts indicate that genetic liability for a range of psychiatric traits is associated with experiencing childhood trauma. Genome-wide association study of psychiatric phenotypes may also reflect risk factors for these phenotypes. Our findings also suggest that youth at higher genetic risk might require greater resources/support to ensure they grow-up in a healthy environment. [ABSTRACT FROM AUTHOR]

Background: There is increasing evidence that smoking is a risk factor for severe mental illness, including bipolar disorder. Conversely, patients with bipolar disorder might smoke more (often) as a result of the psychiatric disorder.Aims: We conducted a bidirectional Mendelian randomisation (MR) study to investigate the direction and evidence for a causal nature of the relationship between smoking and bipolar disorder.Method: We used publicly available summary statistics from genome-wide association studies on bipolar disorder, smoking initiation, smoking heaviness, smoking cessation and lifetime smoking (i.e. a compound measure of heaviness, duration and cessation). We applied analytical methods with different, orthogonal assumptions to triangulate results, including inverse-variance weighted (IVW), MR-Egger, MR-Egger SIMEX, weighted-median, weighted-mode and Steiger-filtered analyses.Results: Across different methods of MR, consistent evidence was found for a positive effect of smoking on the odds of bipolar disorder (smoking initiation ORIVW = 1.46, 95% CI 1.28-1.66, P = 1.44 × 10-8, lifetime smoking ORIVW = 1.72, 95% CI 1.29-2.28, P = 1.8 × 10-4). The MR analyses of the effect of liability to bipolar disorder on smoking provided no clear evidence of a strong causal effect (smoking heaviness betaIVW = 0.028, 95% CI 0.003-0.053, P = 2.9 × 10-2).Conclusions: These findings suggest that smoking initiation and lifetime smoking are likely to be a causal risk factor for developing bipolar disorder. We found some evidence that liability to bipolar disorder increased smoking heaviness. Given that smoking is a modifiable risk factor, these findings further support investment into smoking prevention and treatment in order to reduce mental health problems in future generations. [ABSTRACT FROM AUTHOR]

Background: Smoking prevalence is higher amongst individuals with schizophrenia and depression compared with 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 two-sample MR to explore the bi-directional effects of smoking on schizophrenia and depression. For smoking behaviour, we used (1) smoking initiation GWAS from the GSCAN consortium and (2) we conducted our own GWAS of lifetime smoking behaviour (which captures smoking duration, heaviness and cessation) in a sample of 462690 individuals from the UK Biobank. We validated this instrument using positive control outcomes (e.g. lung cancer). For schizophrenia and depression we used GWAS from the PGC consortium. Results: There was strong evidence to suggest smoking is a risk factor for both schizophrenia (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.67–3.08, p < 0.001) and depression (OR 1.99, 95% CI 1.71–2.32, p < 0.001). Results were consistent across both lifetime smoking and smoking initiation. We found some evidence that genetic liability to depression increases smoking (β = 0.091, 95% CI 0.027–0.155, p = 0.005) but evidence was mixed for schizophrenia (β = 0.022, 95% CI 0.005–0.038, p = 0.009) with very weak evidence for an effect on smoking initiation. Conclusions: 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 on mental health. [ABSTRACT FROM AUTHOR]

There is substantial variation in the timing of significant reproductive life events such as menarche and first sexual intercourse. Life history theory explains this variation as an adaptive response to an individual's environment and it is important to examine how traits within life history strategies affect each other. Here we applied Mendelian randomization (MR) methods to investigate whether there is a causal effect of variation in age at menarche and age at first sexual intercourse (markers or results of exposure to early life adversity) on outcomes related to reproduction, education and risky behaviour in UK Biobank (N = 114 883–181 255). Our results suggest that earlier age at menarche affects some traits that characterize life history strategies including earlier age at first and last birth, decreased educational attainment, and decreased age at leaving education (for example, we found evidence for a 0.26 year decrease in age at first birth per year decrease in age at menarche, 95% confidence interval: -0.34 to -0.17; p < 0.001). We find no clear evidence of effects of age at menarche on other outcomes, such as risk taking behaviour. Age at first sexual intercourse was also related to many life history outcomes, although there was evidence of horizontal pleiotropy which violates an assumption of MR and we therefore cannot infer causality from this analysis. Taken together, these results highlight how MR can be applied to test predictions of life history theory and to better understand determinants of health and social behaviour. [ABSTRACT FROM AUTHOR]

Cultural effects can influence the results of causal genetic analyses, such as Mendelian randomisation, but the potential influences of culture on genotype–phenotype associations are not currently well understood. Different genetic variants could be associated with different phenotypes in different populations, or culture could confound or influence the direction of the association between genotypes and phenotypes in different populations. [ABSTRACT FROM AUTHOR]

Background: Despite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop tailored smoking interventions that could lead to both improved uptake and efficacy. Methods: Recent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to individual-level data from UK Biobank to investigate the link between smoking and personality. We first estimate genetic overlap between traits using LD score regression and then use bidirectional Mendelian randomisation methods to unpick the nature of this relationship. Results: We found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion. We found some evidence that personality traits are causally linked to certain smoking phenotypes: among current smokers each additional neuroticism risk allele was associated with smoking an additional 0.07 cigarettes per day (95% CI 0.02–0.12, p = 0.009), and each additional extraversion effect allele was associated with an elevated odds of smoking initiation (OR 1.015, 95% CI 1.01–1.02, p = 9.6 × 10−7). Conclusion: We found some evidence for specific causal pathways from personality to smoking phenotypes, and weaker evidence of an association from smoking initiation to personality. These findings could be used to inform future smoking interventions or to tailor existing schemes. [ABSTRACT FROM AUTHOR]

Objective: To assess the effects of n-3 polyunsaturated fatty acids (n-3PUFAs; also known as ω-3 fatty acids) compared with comparator for major depressive disorder (MDD) in adults. Design: Systematic review and meta-analyses. Data sources: The Cochrane Depression, Anxiety and Neurosis Review Group's Specialised Registers (CCDANCTR) and International Trial Registries searched to May 2015. CINAHL searched to September 2013. Trial selection: Inclusion criteria: a randomised controlled trial (RCT); that provided n-3PUFAs as an intervention; used a comparator; measured depressive symptomology as an outcome; and was conducted in adults with MDD. Outcomes: Primary outcomes were depressive symptomology and adverse events. Results: 20 trials encompassing 26 relevant studies were found. For n-3PUFAs versus placebo, n-3PUFA supplementation resulted in a small-to-modest benefit for depressive symptomology: SMD=-0.32 (95% CI -0.52 to -0.12; 25 studies, 1373 participants, very low-quality evidence), but this effect is unlikely to be clinically meaningful, is very imprecise and, based on funnel plot inspection, sensitivity analyses and comparison with large well-conducted trials, is likely to be biased. Considerable evidence of heterogeneity between studies was also found, and was not explained by subgroup or sensitivity analyses. Numbers of individuals experiencing adverse events were similar in intervention and placebo groups (OR=1.24, 95% CI 0.95 to 1.62; 19 studies, 1207 participants; very low-quality evidence). For n-3PUFAs versus antidepressants, no differences were found between treatments in depressive symptomology (MD=-0.70 (95% CI -5.88 to 4.48); 1 study, 40 participants, very low-quality evidence). Conclusions: At present, we do not have sufficient evidence to determine the effects of n-3PUFAs as a treatment for MDD. Further research in the form of adequately powered RCTs is needed. [ABSTRACT FROM AUTHOR]

Objective: To assess the effects of n-3 polyunsaturated fatty acids (n-3PUFAs; also known as ω-3 fatty acids) compared with comparator for major depressive disorder (MDD) in adults. Design: Systematic review and meta-analyses. Data sources: The Cochrane Depression, Anxiety and Neurosis Review Group's Specialised Registers (CCDANCTR) and International Trial Registries searched to May 2015. CINAHL searched to September 2013. Trial selection: Inclusion criteria: a randomised controlled trial (RCT); that provided n-3PUFAs as an intervention; used a comparator; measured depressive symptomology as an outcome; and was conducted in adults with MDD. Outcomes: Primary outcomes were depressive symptomology and adverse events. Results: 20 trials encompassing 26 relevant studies were found. For n-3PUFAs versus placebo, n-3PUFA supplementation resulted in a small-to-modest benefit for depressive symptomology: SMD=-0.32 (95% CI -0.52 to -0.12; 25 studies, 1373 participants, very low-quality evidence), but this effect is unlikely to be clinically meaningful, is very imprecise and, based on funnel plot inspection, sensitivity analyses and comparison with large well-conducted trials, is likely to be biased. Considerable evidence of heterogeneity between studies was also found, and was not explained by subgroup or sensitivity analyses. Numbers of individuals experiencing adverse events were similar in intervention and placebo groups (OR=1.24, 95% CI 0.95 to 1.62; 19 studies, 1207 participants; very low-quality evidence). For n-3PUFAs versus antidepressants, no differences were found between treatments in depressive symptomology (MD=-0.70 (95% CI -5.88 to 4.48); 1 study, 40 participants, very low-quality evidence). Conclusions: At present, we do not have sufficient evidence to determine the effects of n-3PUFAs as a treatment for MDD. Further research in the form of adequately powered RCTs is needed. [ABSTRACT FROM AUTHOR]

Background: Evidence from observational studies suggests an association between anxiety disorders and anorexia nervosa (AN), but causal inference is complicated by the potential for confounding in these studies. We triangulate evidence across a longitudinal study and a Mendelian randomization (MR) study, to evaluate whether there is support for anxiety disorder phenotypes exerting a causal effect on AN risk. Methods: Study One assessed longitudinal associations of childhood worry and anxiety disorders with lifetime AN in the Avon Longitudinal Study of Parents and Children cohort. Study Two used two-sample MR to evaluate: causal effects of worry, and genetic liability to anxiety disorders, on AN risk; causal effects of genetic liability to AN on anxiety outcomes; and the causal influence of worry on anxiety disorder development. The independence of effects of worry, relative to depressed affect, on AN and anxiety disorder outcomes, was explored using multivariable MR. Analyses were completed using summary statistics from recent genome-wide association studies. Results: Study One did not support an association between worry and subsequent AN, but there was strong evidence for anxiety disorders predicting increased risk of AN. Study Two outcomes supported worry causally increasing AN risk, but did not support a causal effect of anxiety disorders on AN development, or of AN on anxiety disorders/worry. Findings also indicated that worry causally influences anxiety disorder development. Multivariable analysis estimates suggested the influence of worry on both AN and anxiety disorders was independent of depressed affect. Conclusions: Overall our results provide mixed evidence regarding the causal role of anxiety exposures in AN aetiology. The inconsistency between outcomes of Studies One and Two may be explained by limitations surrounding worry assessment in Study One, confounding of the anxiety disorder and AN association in observational research, and low power in MR analyses probing causal effects of genetic liability to anxiety disorders. The evidence for worry acting as a causal risk factor for anxiety disorders and AN supports targeting worry for prevention of both outcomes. Further research should clarify how a tendency to worry translates into AN risk, and whether anxiety disorder pathology exerts any causal effect on AN. [ABSTRACT FROM AUTHOR]