Associations between self-reported sleep quality, fatigue severity, factors associated with successful cessation, and cessation beliefs among regular smokers.

BACKGROUND: Smokers report poorer sleep than non-smokers 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 24hr (ß = -0.12, p = 0.05) and lifetime (ß = -0.09, p = 0.04) abstinence self-efficacy. In addition, poorer SQ and higher fatigue severity (FS) were associated with increased smoking urges (SQ: ß = 0.27, p < .001; FS: ß = 0.32, p < .001), increased barriers to cessation (SQ: ß = 0.19, p < .001; FS: ß = 0.32, p < .001), and increased perceived risks to cessation (SQ: ß = 0.18, p < .001; FS: ß = 0.26, p < .001). Fatigue severity was weakly associated with increased perceived benefits to cessation (ß = 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.

Meta-Analyses of Genome-Wide Association Studies for Postpartum Depression.

OBJECTIVE: 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. METHOD: 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 ([Formula: see text]), 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. RESULTS: No SNP achieved genome-wide significance in the European or the trans-ancestry meta-analyses. The [Formula: see text] 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. CONCLUSIONS: 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).

Exploring the bidirectional causal pathways between smoking behaviours and headache: A Mendelian randomisation study.

INTRODUCTION: Although observational data suggests 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 randomisation (MR) is a method that uses genetic variants as instruments for making causal inferences about an exposure and an outcome. METHODS: First, we conducted logistic regression of observational data in UK Biobank assessing the association between smoking behaviours (smoking status, cigarettes per day amongst daily smokers and lifetime smoking score) on risk of self-reported headache (in the last month and for more than 3 months). Second, we used genetic instruments for smoking behaviours and headache (identified in independent genome-wide association studies) to perform bidirectional MR analysis. RESULTS: Observationally, there is a weak association between smoking behaviour 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 three months. In the opposite direction there was weak evidence for higher genetic liability to headaches decreasing the chance of quitting. CONCLUSION: There was weak evidence for a partially bidirectional causal relationship between smoking behaviours 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 Mendelian Randomisation, 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 three months. Those at higher genetic liability for 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.

Deriving GWAS summary estimates for paternal smoking in UK biobank: a GWAS by subtraction.

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.

Proxy gene-by-environment Mendelian randomization study of the association between cigarette smoking during pregnancy and offspring mental health.

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, Pinteraction <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.

Exploring the Lifetime Effect of Children on Wellbeing Using Two-Sample Mendelian Randomisation.

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 (ß = 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.

Do environmental effects indexed by parental genetic variation influence common psychiatric symptoms in childhood?

Parental genes may indirectly influence offspring psychiatric outcomes through the environment that parents create for their children. These indirect genetic effects, also known as genetic nurture, could explain individual differences in common internalising and externalising psychiatric symptoms during childhood. Advanced statistical genetic methods leverage data from families to estimate the overall contribution of parental genetic nurture effects. This study included up to 10,499 children, 5990 mother-child pairs, and 6,222 father-child pairs from the Norwegian Mother Father and Child Study. Genome-based restricted maximum likelihood (GREML) models were applied using software packages GCTA and M-GCTA to estimate variance in maternally reported depressive, disruptive, and attention-deficit hyperactivity disorder (ADHD) symptoms in 8-year-olds that was explained by direct offspring genetic effects and maternal or paternal genetic nurture. There was no strong evidence of genetic nurture in this sample, although a suggestive paternal genetic nurture effect on offspring depressive symptoms (variance explained (V) = 0.098, standard error (SE) = 0.057) and a suggestive maternal genetic nurture effect on ADHD symptoms (V = 0.084, SE = 0.058) was observed. The results indicate that parental genetic nurture effects could be of some relevance in explaining individual differences in childhood psychiatric symptoms. However, robustly estimating their contribution is a challenge for researchers given the current paucity of large-scale samples of genotyped families with information on childhood psychiatric outcomes.

Association between inflammation and cognition: Triangulation of evidence using a population-based cohort and Mendelian randomization analyses.

BACKGROUND: Inflammation is associated with cognitive functioning and dementia in older adults, but whether inflammation is related to cognitive functioning in youth and whether these associations are causal remains unclear. METHODS: In a population-based cohort (Avon Longitudinal Study of Parents and Children; ALSPAC), we investigated cross-sectional associations of inflammatory markers (C-reactive protein [CRP], Interleukin-6 [IL-6] and Glycoprotein acetyls [GlycA]) with measures of cold (working memory, response inhibition) and hot (emotion recognition) cognition at age 24 (N = 3,305 in multiple imputation models). Furthermore, we conducted one-sample and two-sample bidirectional Mendelian randomization (MR) analyses to examine potential causal effects of genetically-proxied inflammatory markers (CRP, GlycA, IL-6, IL-6 receptor, soluble IL-6 receptor) on cognitive measures (above) and on general cognitive ability. RESULTS: In the ALSPAC cohort, there was limited evidence of an association between standardised inflammatory markers and standardised cognitive measures at age 24 after adjusting for potential confounders (N = 3,305; beta range, -0.02 [95 % confidence interval (CI) -0.06 to 0.02, p = 0.27] to 0.02 [95 % CI -0.02 to 0.05, p = 0.33]). Similarly, we found limited evidence of potential effects of 1-unit increase in genetically-proxied inflammatory markers on standardised working memory, emotion recognition or response inhibition in one-sample MR using ALSPAC data (beta range, -0.73 [95 % CI -2.47 to 1.01, p = 0.41] to 0.21 [95 % CI -1.42 to 1.84, p = 0.80]; or on standardised general cognitive ability in two-sample MR using the latest Genome-Wide Association Study (GWAS) datasets (inverse-variance weighted beta range, -0.02 [95 % CI -0.05 to 0.01, p = 0.12] to 0.03 [95 % CI -0.01 to 0.07, p = 0.19]). CONCLUSIONS: Our MR findings do not provide strong evidence of a potential causal effect of inflammatory markers (CRP, IL-6, IL-6 receptor, GlycA) on the cognitive functions examined here. Given the large confidence intervals in the one-sample MR, larger GWAS of specific cognitive measures are needed to enable well-powered MR analyses to investigate whether inflammation causally influences specific cognitive domains.

Maternal postnatal depressive symptoms and offspring emotional and behavioral development at age 7 years in a U.K. birth cohort: The role of paternal involvement.

There is considerable variability in developmental outcomes of children whose mothers experience depression. Few longitudinal studies have examined contributions of paternal involvement in the association between maternal postnatal depression (PND) and offspring development. We examined pathways from maternal PND at 8 weeks (Edinburgh Postnatal Depression Scale; total score) to offspring emotional and behavioral development at 7 years (Strengths and Difficulties Questionnaire; total score) through behavioral, affective, and cognitive dimensions of paternal involvement in a U.K.-based birth cohort (Avon Longitudinal Study of Parents and Children; n = 3,434). Analyses were adjusted for baseline confounders and paternal PND (Edinburgh Postnatal Depression Scale; total score) as an intermediate confounder. Maternal PND was strongly associated with offspring development, but this association was not mediated by the combination of all indirect pathways through various dimensions of paternal involvement. Only father-child conflict emerged as a risk factor for adverse offspring development and as a mediator in the association between maternal PND and offspring development (albeit the effect size was small). If found causal, interventions that reduce father-child conflict may reduce the risk of adverse development in offspring of mothers with PND. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A genetically informed Registered Report on adverse childhood experiences and mental health.

Children who experience adversities have an elevated risk of mental health problems. However, the extent to which adverse childhood experiences (ACEs) cause mental health problems remains unclear, as previous associations may partly reflect genetic confounding. In this Registered Report, we used DNA from 11,407 children from the United Kingdom and the United States to investigate gene-environment correlations and genetic confounding of the associations between ACEs and mental health. Regarding gene-environment correlations, children with higher polygenic scores for mental health problems had a small increase in odds of ACEs. Regarding genetic confounding, elevated risk of mental health problems in children exposed to ACEs was at least partially due to pre-existing genetic risk. However, some ACEs (such as childhood maltreatment and parental mental illness) remained associated with mental health problems independent of genetic confounding. These findings suggest that interventions addressing heritable psychiatric vulnerabilities in children exposed to ACEs may help reduce their risk of mental health problems.

Using allele scores to identify confounding by reverse causation: studies of alcohol consumption as an exemplar.

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.

Is there a causal relationship between executive function and liability to mental health and substance use? A Mendelian randomization approach.

Poorer performance in tasks testing executive function (EF) is associated with a range of psychopathologies such as schizophrenia, major depressive disorder (MDD) and anxiety, as well as smoking and alcohol consumption. We used two-sample bidirectional Mendelian randomization to examine whether these may reflect causal relationships and the direction of causation. We used genome-wide association study summary data (N = 17 310 to 848 460) for a common EF factor score (cEF), schizophrenia, MDD, anxiety, smoking initiation, alcohol consumption, alcohol dependence and cannabis use disorder (CUD). We found evidence of increased cEF on reduced schizophrenia liability (OR = 0.10; CI: 0.05 to 0.19; p-value = 3.43 × 10-12), MDD liability (OR = 0.52; CI: 0.38 to 0.72; p-value = 5.23 × 10-05), drinks per week (ß = -0.06; CI: -0.10 to -0.02; p-value = 0.003) and CUD liability (OR = 0.27; CI: 0.12 to 0.61; p-value = 1.58 × 10-03). We also found evidence of increased schizophrenia liability (ß = -0.04; CI: -0.04 to -0.03; p-value = 3.25 × 10-27) and smoking initiation on decreased cEF (ß = -0.06; CI: -0.09 to -0.03; p-value = 6.11 × 10-05). Our results indicate potential causal relationships between cEF and mental health and substance use. Further studies are required to improve our understanding of the underlying mechanisms of these effects, but our results suggest that EF may be a promising intervention target for mental health and substance use.

Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis.

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10-10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). Polygenic risk score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg = 0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg = 0.54), cognitive ability (intelligence rg = -0.40), educational attainment (years of schooling rg = -0.46) and reproductive traits (age at first birth rg = -0.58, father's age at death rg = -0.54). Our findings provide a starting point toward identifying critical biosocial risk mechanisms for the development of ASB.

Culture and causal inference: The impact of cultural differences on the generalisability of findings from Mendelian randomisation studies.

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.

Genome-wide Association Meta-analysis of Childhood and Adolescent Internalizing Symptoms.

OBJECTIVE: To investigate the genetic architecture of internalizing symptoms in childhood and adolescence. METHOD: In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument. RESULTS: The meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. CONCLUSION: Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

Prenatal smoking, alcohol and caffeine exposure and offspring externalizing disorders: a systematic review and meta-analysis.

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.

Protecting against researcher bias in secondary data analysis: challenges and potential solutions.

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.

Associations between COVID-19 Risk Perceptions and Mental Health, Wellbeing, and Risk Behaviours.

Background: 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. Methods: 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. Results: 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. Conclusions: 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.

Does smoking cause lower educational attainment and general cognitive ability? Triangulation of causal evidence using multiple study designs.

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 ß -0.736, 95% CI -1.238 to -0.233, p = 0.004; fully adjusted educational attainment ß -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 ß -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.