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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., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

Obese adults are often reported to have smaller brain volumes than their non-obese peers. Whether this represents evidence of accelerations in obesity-driven atrophy or is instead a legacy of developmental differences established earlier in the lifespan remains unclear. This study aimed to investigate whether early-life differences in adiposity explain differences in numerous adult brain traits commonly attributed to mid-life obesity. We utilised a two-sample lifecourse Mendelian randomization study in 37,501 adults recruited to UK Biobank (UKB) imaging centers from 2014, with secondary analyses in 6,996 children assessed in the Adolescent Brain Cognitive Development Study (ABCD) recruited from 2018. Exposures were genetic variants for childhood (266 variants) and adult (470 variants) adiposity derived from a GWAS of 407,741 UKB participants. Primary outcomes were adult total brain volume; grey matter volume, thickness, and surface area; white matter volume and hyperintensities; and hippocampus, amygdala, and thalamus volumes at mean age 55 in UKB. Secondary outcomes were equivalent childhood measures collected at mean age 10 in ABCD. In UKB, individuals who were genetically-predicted to have had higher levels of adiposity in childhood were found to have multiple smaller adult brain volumes relative to intracranial volume (e.g. z-score difference in normalised brain volume per category increase in adiposity [95%CI] = -0.20 [-0.28, -0.12]; p = 4 × 10-6). These effect sizes remained essentially unchanged after accounting for birthweight or current adult obesity in multivariable models, whereas most observed adult effects attenuated towards null (e.g. adult z-score [95%CI] for total volume = 0.06 [-0.05,0.17]; p = 0.3). Observational analyses in ABCD showed a similar pattern of changes already present in those with a high BMI by age 10 (z-score [95%CI] = -0.10 [-0.13, -0.07]; p = 8 × 10-13), with follow-up genetic risk score analyses providing some evidence for a causal effect already at this early age. Sensitivity analyses revealed that many of these effects were likely due to the persistence of larger head sizes established in those who gained excess weight in childhood (childhood z-score [95%CI] for intracranial volume = 0.14 [0.05,0.23]; p = 0.002), rather than smaller brain sizes per se. Our data suggest that persistence of early-life developmental differences across the lifecourse may underlie numerous neuroimaging traits commonly attributed to obesity-related atrophy in later life., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Introduction: Knowledge of the impact of smoking on healthcare costs is important for establishing the external effects of smoking and for evaluating policies intended to modify this behavior. Conventional analysis of this association is difficult because of omitted variable bias, reverse causality, and measurement error., Methods: We approached these challenges using a Mendelian Randomization study design; genetic variants associated with smoking behaviors were used in instrumental variables models with inpatient hospital costs (calculated from electronic health records) as the outcome. We undertook genome wide association studies to identify genetic variants associated with smoking initiation and a composite smoking index (reflecting cumulative health impacts of smoking) on up to 300,045 individuals (mean age: 57 years at baseline, range 39 to 72 years) in the UK Biobank. We followed individuals up for a mean of six years., Results: Genetic liability to initiate smoking (ever versus never smoking) was estimated to increase mean per-patient annual inpatient hospital costs by £477 (95% confidence interval (CI): £187 to £766). A one-unit change in genetic liability to the composite smoking index (range: 0-4.0) increased inpatient hospital costs by £204 (95% CI: £105 to £303) per unit increase in this index. There was some evidence that the composite smoking index causal models violated the instrumental variable assumptions, and all Mendelian Randomization models were estimated with considerable uncertainty. Models conditioning on risk tolerance were not robust to weak instrument bias., Conclusions: Our findings have implications for the potential cost-effectiveness of smoking interventions., Implications: We report the first Mendelian Randomization analysis of the causal effect of smoking on healthcare costs. Using two distinct smoking phenotypes, we identified substantial impacts of smoking on inpatient hospital costs, although the causal models were associated with considerable uncertainty. These results could be used alongside other evidence on the impact of smoking to evaluate the cost-effectiveness of anti-smoking interventions and to understand the scale of externalities associated with this behaviour., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

Background: On average, educated people are healthier, wealthier and have higher life expectancy than those with less education. Numerous studies have attempted to determine whether education causes differences in later health outcomes or whether another factor ultimately causes differences in education and subsequent outcomes. Previous studies have used a range of natural experiments to provide causal evidence. Here we compare two natural experiments: a policy reform, raising the school leaving age in the UK in 1972; and Mendelian randomization., Methods: We used data from 334 974 participants of the UK Biobank, sampled between 2006 and 2010. We estimated the effect of an additional year of education on 25 outcomes, including mortality, measures of morbidity and health, ageing and income, using multivariable adjustment, the policy reform and Mendelian randomization. We used a range of sensitivity analyses and specification tests to assess the plausibility of each method's assumptions., Results: The three different estimates of the effects of educational attainment were largely consistent in direction for diabetes, stroke and heart attack, mortality, smoking, income, grip strength, height, body mass index (BMI), intelligence, alcohol consumption and sedentary behaviour. However, there was evidence that education reduced rates of moderate exercise and increased alcohol consumption. Our sensitivity analyses suggest that confounding by genotypic or phenotypic confounders or specific forms of pleiotropy are unlikely to explain our results., Conclusions: Previous studies have suggested that the differences in outcomes associated with education may be due to confounding. However, the two independent sources of exogenous variation we exploit largely imply consistent causal effects of education on outcomes later in life., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: The relevance of folic acid for stroke prevention in low-folate populations such as in China is uncertain. Genetic studies of the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism, which increases plasma homocysteine (tHcy) levels, could clarify the causal relevance of elevated tHcy levels for stroke, ischaemic heart disease (IHD) and other diseases in populations without folic acid fortification., Methods: In the prospective China Kadoorie Biobank, 156 253 participants were genotyped for MTHFR and 12 240 developed a stroke during the 12-year follow-up. Logistic regression was used to estimate region-specific odds ratios (ORs) for total stroke and stroke types, IHD and other diseases comparing TT genotype for MTHFR C677T (two thymine alleles at position 677 of MTHFR C677T polymorphism) vs CC (two cytosine alleles) after adjustment for age and sex, and these were combined using inverse-variance weighting., Results: Overall, 21% of participants had TT genotypes, but this varied from 5% to 41% across the 10 study regions. Individuals with TT genotypes had 13% (adjusted OR 1.13, 95% CI 1.09-1.17) higher risks of any stroke [with a 2-fold stronger association with intracerebral haemorrhage (1.24, 1.17-1.32) than for ischaemic stroke (1.11, 1.07-1.15)] than the reference CC genotype. In contrast, MTHFR C677T was unrelated to risk of IHD or any other non-vascular diseases, including cancer, diabetes and chronic obstructive lung disease., Conclusions: In Chinese adults, the MTHFR C677T polymorphism was associated with higher risks of stroke. The findings warrant corroboration by further trials of folic acid and implementation of mandatory folic acid fortification programmes for stroke prevention in low-folate populations., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Previous Mendelian randomization (MR) studies using population samples (population MR) have provided evidence for beneficial effects of educational attainment on health outcomes in adulthood. However, estimates from these studies may have been susceptible to bias from population stratification, assortative mating and indirect genetic effects due to unadjusted parental genotypes. MR using genetic association estimates derived from within-sibship models (within-sibship MR) can avoid these potential biases because genetic differences between siblings are due to random segregation at meiosis., Methods: Applying both population and within-sibship MR, we estimated the effects of genetic liability to educational attainment on body mass index (BMI), cigarette smoking, systolic blood pressure (SBP) and all-cause mortality. MR analyses used individual-level data on 72 932 siblings from UK Biobank and the Norwegian HUNT study, and summary-level data from a within-sibship Genome-wide Association Study including >140 000 individuals., Results: Both population and within-sibship MR estimates provided evidence that educational attainment decreased BMI, cigarette smoking and SBP. Genetic variant-outcome associations attenuated in the within-sibship model, but genetic variant-educational attainment associations also attenuated to a similar extent. Thus, within-sibship and population MR estimates were largely consistent. The within-sibship MR estimate of education on mortality was imprecise but consistent with a putative effect., Conclusions: These results provide evidence of beneficial individual-level effects of education (or liability to education) on adulthood health, independently of potential demographic and family-level confounders., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Epidemiological Association.)

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., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background/objectives: Different genetic variants are associated with larger body size in childhood vs adulthood. Whether and when these variants predominantly influence adiposity are unknown. We examined how genetic variants influence total body fat and total lean mass trajectories., Methods: Data were from the Avon Longitudinal Study of Parents and Children birth cohort (N = 6926). Sex-specific genetic risk scores (GRS) for childhood and adulthood body size were generated, and dual-energy X-ray absorptiometry scans measured body fat and lean mass six times between the ages of 9 and 25 years. Multilevel linear spline models examined associations of GRS with fat and lean mass trajectories., Results: In males, the sex-specific childhood and adulthood GRS were associated with similar differences in fat mass from 9 to 18 years; 8.3% [95% confidence interval (CI) 5.1, 11.6] and 7.5% (95% CI 4.3, 10.8) higher fat mass at 18 years per standard deviation (SD) higher childhood and adulthood GRS, respectively. In males, the sex-combined childhood GRS had stronger effects at ages 9 to 15 than the sex-combined adulthood GRS. In females, associations for the sex-specific childhood GRS were almost 2-fold stronger than the adulthood GRS from 9 to 18 years: 10.5% (95% CI 8.5, 12.4) higher fat mass at 9 years per SD higher childhood GRS compared with 5.1% (95% CI 3.2, 6.9) per-SD higher adulthood GRS. In females, the sex-combined GRS had similar effects, with slightly larger effect estimates. Lean mass effect sizes were much smaller., Conclusions: Genetic variants for body size are more strongly associated with adiposity than with lean mass. Sex-combined childhood variants are more strongly associated with increased adiposity until early adulthood. This may inform future studies that use genetics to investigate the causes and impact of adiposity at different life stages., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Genetic factors influence the risk of fatty liver disease (FLD) in adults. The aim of this study was to test if, and when, genetic risk factors known to affect FLD in adults begin to exert their deleterious effects during childhood, adolescence and early adulthood., Methods: We included up to 4018 British children and adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Three genetic variants known to associate robustly with FLD in adults (PNPLA3 rs738409, TM6SF2 rs58542926 and HSD17B13 rs72613567) were tested for association with plasma levels of alanine transaminase (ALT) and aspartate transaminase (AST) during childhood (mean age: 9.9 years), early adolescence (15.5 years), late adolescence (17.8 years), and early adulthood (24.5 years). We also tested the associations of a 17-variant score and whole-genome polygenic risk scores (PRS) derived from associations in adults with plasma ALT and AST at the same four time points. Associations with elastography-derived liver steatosis and fibrosis were tested in early adulthood., Results: Genetic risk factors for FLD (individually, combined into a 3-variant score, a 17-variant score and as a genome-wide PRS), were associated with higher liver enzymes, beginning in childhood and throughout adolescence and early adulthood. The ALT-increasing effects of the genetic risk variants became larger with increasing age. The ALT-PRS was associated with liver steatosis in early adulthood. No genetic associations with fibrosis were observed., Conclusions: Genetic factors that promote FLD in adults associate with elevated liver enzymes already during childhood, and their effects get amplified with increasing age., (© The Author(s) 2023; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Epigenetic clocks are increasingly being used as a tool to assess the impact of a wide variety of phenotypes and exposures on healthy ageing, with a recent focus on social determinants of health. However, little attention has been paid to the sociodemographic characteristics of participants on whom these clocks have been based. Participant characteristics are important because sociodemographic and socioeconomic factors are known to be associated with both DNA methylation variation and healthy ageing. It is also well known that machine learning algorithms have the potential to exacerbate health inequities through the use of unrepresentative samples - prediction models may underperform in social groups that were poorly represented in the training data used to construct the model. To address this gap in the literature, we conducted a review of the sociodemographic characteristics of the participants whose data were used to construct 13 commonly used epigenetic clocks. We found that although some of the epigenetic clocks were created utilizing data provided by individuals from different ages, sexes/genders, and racialized groups, sociodemographic characteristics are generally poorly reported. Reported information is limited by inadequate conceptualization of the social dimensions and exposure implications of gender and racialized inequality, and socioeconomic data are infrequently reported. It is important for future work to ensure clear reporting of tangible data on the sociodemographic and socioeconomic characteristics of all the participants in the study to ensure that other researchers can make informed judgements about the appropriateness of the model for their study population., Competing Interests: The authors declare no conflict of interest., (© The Author(s) 2023. Published by Oxford University Press.)

Motivated by our conduct of a literature review on social exposures and accelerated aging as measured by a growing number of epigenetic "clocks" (which estimate age via DNA methylation (DNAm) patterns), we report on 3 different approaches in the epidemiologic literature-1 incorrect and 2 correct-on the treatment of age in these and other studies using other common exposures (i.e., body mass index and alcohol consumption). Among the 50 empirical articles reviewed, the majority (n = 29; 58%) used the incorrect method of analyzing accelerated aging detrended for age as the outcome and did not control for age as a covariate. By contrast, only 42% used correct methods, which are either to analyze accelerated aging detrended for age as the outcome and control for age as a covariate (n = 16; 32%) or to analyze raw DNAm age as the outcome and control for age as a covariate (n = 5; 10%). In accord with prior demonstrations of bias introduced by use of the incorrect approach, we provide simulation analyses and additional empirical analyses to illustrate how the incorrect method can lead to bias towards the null, and we discuss implications for extant research and recommendations for best practices., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journalpermissions@oup.com.)

Background: An increasing proportion of people have a body mass index (BMI) classified as overweight or obese and published studies disagree whether this will be beneficial or detrimental to health. We applied and evaluated two intergenerational instrumental variable methods to estimate the average causal effect of BMI on mortality in a cohort with many deaths: the parents of UK Biobank participants., Methods: In Cox regression models, parental BMI was instrumented by offspring BMI using an 'offspring as instrument' (OAI) estimation and by offspring BMI-related genetic variants in a 'proxy-genotype Mendelian randomization' (PGMR) estimation., Results: Complete-case analyses were performed in parents of 233 361 UK Biobank participants with full phenotypic, genotypic and covariate data. The PGMR method suggested that higher BMI increased mortality with hazard ratios per kg/m2 of 1.02 (95% CI: 1.01, 1.04) for mothers and 1.04 (95% CI: 1.02, 1.05) for fathers. The OAI method gave considerably higher estimates, which varied according to the parent-offspring pairing between 1.08 (95% CI: 1.06, 1.10; mother-son) and 1.23 (95% CI: 1.16, 1.29; father-daughter)., Conclusion: Both methods supported a causal role of higher BMI increasing mortality, although caution is required regarding the immediate causal interpretation of these exact values. Evidence of instrument invalidity from measured covariates was limited for the OAI method and minimal for the PGMR method. The methods are complementary for interrogating the average putative causal effects because the biases are expected to differ between them., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Traditionally, heritability has been estimated using family-based methods such as twin studies. Advancements in molecular genomics have facilitated the development of methods that use large samples of (unrelated or related) genotyped individuals. Here, we provide an overview of common methods applied in genetic epidemiology to estimate heritability, i.e. the proportion of phenotypic variation explained by genetic variation. We provide a guide to key genetic concepts required to understand heritability estimation methods from family-based designs (twin and family studies), genomic designs based on unrelated individuals [linkage disequilibrium score regression, genomic relatedness restricted maximum-likelihood (GREML) estimation] and family-based genomic designs (sibling regression, GREML-kinship, trio-genome-wide complex trait analysis, maternal-genome-wide complex trait analysis, relatedness disequilibrium regression). We describe how heritability is estimated for each method and the assumptions underlying its estimation, and discuss the implications when these assumptions are not met. We further discuss the benefits and limitations of estimating heritability within samples of unrelated individuals compared with samples of related individuals. Overall, this article is intended to help the reader determine the circumstances when each method would be appropriate and why., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors., Methods: We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set., Results: We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls., Conclusions: In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats)., Competing Interests: None declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Research studies based on tractography have revealed a prominent reduction of asymmetry in some key white-matter tracts in schizophrenia (SCZ). However, we know little about the influence of common genetic risk factors for SCZ on the efficiency of routing on structural brain networks (SBNs). Here, we use a novel recall-by-genotype approach, where we sample young adults from a population-based cohort (ALSPAC:N genotyped = 8,365) based on their burden of common SCZ risk alleles as defined by polygenic risk score (PRS). We compared 181 individuals at extremes of low (N = 91) or high (N = 90) SCZ-PRS under a robust diffusion MRI-based graph theoretical SBN framework. We applied a semi-metric analysis revealing higher SMR values for the high SCZ-PRS group compared with the low SCZ-PRS group in the left hemisphere. Furthermore, a hemispheric asymmetry index showed a higher leftward preponderance of indirect connections for the high SCZ-PRS group compared with the low SCZ-PRS group (PFDR < 0.05). These findings might indicate less efficient structural connectivity in the higher genetic risk group. This is the first study in a population-based sample that reveals differences in the efficiency of SBNs associated with common genetic risk variants for SCZ., (© The Author(s) 2022. Published by Oxford University Press.)

Background: The use of Mendelian randomization (MR) in epidemiology has increased considerably in recent years, with a subsequent increase in systematic reviews of MR studies. We conducted a systematic review of tools designed for assessing risk of bias and/or quality of evidence in MR studies and a review of systematic reviews of MR studies., Methods: We systematically searched MEDLINE, Embase, the Web of Science, preprints servers and Google Scholar for articles containing tools for assessing, conducting and/or reporting MR studies. We also searched for systematic reviews and protocols of systematic reviews of MR studies. From eligible articles we collected data on tool characteristics and content, as well as details of narrative description of bias assessment., Results: Our searches retrieved 2464 records to screen, from which 14 tools, 35 systematic reviews and 38 protocols were included in our review. Seven tools were designed for assessing risk of bias/quality of evidence in MR studies and evaluation of their content revealed that all seven tools addressed the three core assumptions of instrumental variable analysis, violation of which can potentially introduce bias in MR analysis estimates., Conclusion: We present an overview of tools and methods to assess risk of bias/quality of evidence in MR analysis. Issues commonly addressed relate to the three standard assumptions of instrumental variables analyses, the choice of genetic instrument(s) and features of the population(s) from which the data are collected (particularly in two-sample MR), in addition to more traditional non-MR-specific epidemiological biases. The identified tools should be tested and validated for general use before recommendations can be made on their widespread use. Our findings should raise awareness about the importance of bias related to MR analysis and provide information that is useful for assessment of MR studies in the context of systematic reviews., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Non-random selection of analytic subsamples could introduce selection bias in observational studies. We explored the potential presence and impact of selection in studies of SARS-CoV-2 infection and COVID-19 prognosis., Methods: We tested the association of a broad range of characteristics with selection into COVID-19 analytic subsamples in the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank (UKB). We then conducted empirical analyses and simulations to explore the potential presence, direction and magnitude of bias due to this selection (relative to our defined UK-based adult target populations) when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19., Results: In both cohorts, a broad range of characteristics was related to selection, sometimes in opposite directions (e.g. more-educated people were more likely to have data on SARS-CoV-2 infection in ALSPAC, but less likely in UKB). Higher BMI was associated with higher odds of SARS-CoV-2 infection and death-with-COVID-19. We found non-negligible bias in many simulated scenarios., Conclusions: Analyses using COVID-19 self-reported or national registry data may be biased due to selection. The magnitude and direction of this bias depend on the outcome definition, the true effect of the risk factor and the assumed selection mechanism; these are likely to differ between studies with different target populations. Bias due to sample selection is a key concern in COVID-19 research based on national registry data, especially as countries end free mass testing. The framework we have used can be applied by other researchers assessing the extent to which their results may be biased for their research question of interest., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Two-sample Mendelian randomization (2SMR) is an increasingly popular epidemiological method that uses genetic variants as instruments for making causal inferences. Clear reporting of methods employed in such studies is important for evaluating their underlying quality. However, the quality of methodological reporting of 2SMR studies is currently unclear. We aimed to assess the reporting quality of studies that used MR-Base, one of the most popular platforms for implementing 2SMR analysis., Methods: We created a bespoke reporting checklist to evaluate reporting quality of 2SMR studies. We then searched Web of Science Core Collection, PsycInfo, MEDLINE, EMBASE and Google Scholar citations of the MR-Base descriptor paper to identify published MR studies that used MR-Base for any component of the MR analysis. Study screening and data extraction were performed by at least two independent reviewers., Results: In the primary analysis, 87 studies were included. Reporting quality was generally poor across studies, with a mean of 53% (SD = 14%) of items reported in each study. Many items required for evaluating the validity of key assumptions made in MR were poorly reported: only 44% of studies provided sufficient details for assessing if the genetic variant associates with the exposure ('relevance' assumption), 31% for assessing if there are any variant-outcome confounders ('independence' assumption), 89% for the assessing if the variant causes the outcome independently of the exposure ('exclusion restriction' assumption) and 32% for assumptions of falsification tests. We did not find evidence of a change in reporting quality over time or a difference in reporting quality between studies that used MR-Base and a random sample of MR studies that did not use this platform., Conclusions: The quality of reporting of two-sample Mendelian randomization studies in our sample was generally poor. Journals and researchers should consider using the STROBE-MR guidelines to improve reporting quality., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Mendelian randomization (MR) is a powerful tool through which the causal effects of modifiable exposures on outcomes can be estimated from observational data. Most exposures vary throughout the life course, but MR is commonly applied to one measurement of an exposure (e.g. weight measured once between ages 40 and 60 years). It has been argued that MR provides biased causal effect estimates when applied to one measure of an exposure that varies over time., Methods: We propose an approach that emphasizes the liability that causes the entire exposure trajectory. We demonstrate this approach using simulations and an applied example., Results: We show that rather than estimating the direct or total causal effect of changing the exposure value at a given time, MR estimates the causal effect of changing the underlying liability for the exposure, scaled to the effect of the liability on the exposure at that time. As such, results from MR conducted at different time points are expected to differ (unless the effect of the liability on exposure is constant over time), as we illustrate by estimating the effect of body mass index measured at different ages on systolic blood pressure., Conclusion: Univariable MR results should not be interpreted as time-point-specific direct or total causal effects, but as the effect of changing the liability for the exposure. Estimates of how the effects of a genetic variant on an exposure vary over time, together with biological knowledge that provides evidence regarding likely effective exposure periods, are required to interpret time-point-specific causal effects., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

It is unclear if body weight in early life affects cancer risk independently of adult body weight. To investigate this question for 6 obesity-related cancers, we performed univariable and multivariable analyses using 1) Mendelian randomization (MR) analysis and 2) longitudinal analyses in prospective cohorts. Both the MR and longitudinal analyses indicated that larger early life body size was associated with higher risk of endometrial (odds ratioMR = 1.61, 95% confidence interval = 1.23 to 2.11) and kidney (odds ratioMR = 1.40, 95% confidence interval = 1.09 to 1.80) cancer. These associations were attenuated after accounting for adult body size in both the MR and cohort analyses. Early life body mass index (BMI) was not consistently associated with the other investigated cancers. The lack of clear independent risk associations suggests that early life BMI influences endometrial and kidney cancer risk mainly through pathways that are common with adult BMI., (© World Health Organization, 2022. All rights reserved. The World Health Organization has granted the Publisher permission for the reproduction of this article.)

Objective: Conventional scoring methods for radiographic hip OA (rHOA) are subjective and show inconsistent relationships with clinical outcomes. To provide a more objective rHOA scoring method, we aimed to develop a semi-automated classifier based on DXA images and confirm its relationships with clinical outcomes., Methods: Hip DXAs in UK Biobank (UKB) were marked up for osteophyte area from which acetabular, superior and inferior femoral head osteophyte grades were derived. Joint space narrowing (JSN) grade was obtained automatically from minimum joint space width (mJSW) measures. Clinical outcomes related to rHOA comprised hip pain, hospital diagnosed OA (HES OA) and total hip replacement. Logistic regression and Cox proportional hazard modelling were used to examine associations between overall rHOA grade (0-4; derived from combining osteophyte and JSN grades) and the clinical outcomes., Results: A toal of 40 340 individuals were included in the study (mean age 63.7), of whom 81.2% had no evidence of rHOA, while 18.8% had grade ≥1 rHOA. Grade ≥1 osteophytes at each location and JSN were associated with hip pain, HES OA and total hip replacement. Associations with all three clinical outcomes increased progressively according to rHOA grade, with grade 4 rHOA and total hip replacement showing the strongest association [57.70 (38.08-87.44)]., Conclusions: Our novel semi-automated tool provides a useful means for classifying rHOA on hip DXAs, given its strong and progressive relationships with clinical outcomes. These findings suggest DXA scanning can be used to classify rHOA in large DXA-based cohort studies supporting further research, with the future potential for population-based screening., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Background: The prevalence of atrial fibrillation (AF) is increasing with an aging worldwide population, yet a comprehensive understanding of its causes and consequences remains limited. We aim to assess the causes and consequences of AF via a bidirectional Mendelian randomization (MR) analysis., Methods: We used publicly available genome-wide association study (GWAS) summary data, centralized and harmonized by an open GWAS database. We assessed the genetically predicted effects of 5048 exposures on risk of AF, and the genetically predicted effects of genetic liability to AF, on 10 308 outcomes via two-sample MR analysis. Multivariable MR analysis was further conducted to explore the comparative roles of identified risk factors., Results: MR analysis suggested that 55 out of 5048 exposure traits, including four proteins, play a causal role in AF (P <1e-5 allowing for multiple comparisons). Multivariable analysis suggested that higher body mass index, height and systolic blood pressure as well as genetic liability to coronary artery diseases independently cause AF. Three out of the four proteins (DUSP13, TNFSF12 and IL6R) had a drug prioritizing score for atrial fibrillation of 0.26, 0.38 and 0.88, respectively (values closer to 1 indicating stronger evidence of the protein as a potential drug target). Genetic liability to AF was linked to a higher risk of cardio-embolic ischaemic stroke., Conclusions: Our results suggest body mass index, height, systolic blood pressure and genetic liability to coronary artery disease are independent causal risk factors for AF. Several proteins, including DUSP13, IL-6R and TNFSF12, may have therapeutic potential for AF., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Mendelian randomization has been previously used to estimate the effects of binary and ordinal categorical exposures-e.g. Type 2 diabetes or educational attainment defined by qualification-on outcomes. Binary and categorical phenotypes can be modelled in terms of liability-an underlying latent continuous variable with liability thresholds separating individuals into categories. Genetic variants influence an individual's categorical exposure via their effects on liability, thus Mendelian-randomization analyses with categorical exposures will capture effects of liability that act independently of exposure category., Methods and Results: We discuss how groups in which the categorical exposure is invariant can be used to detect liability effects acting independently of exposure category. For example, associations between an adult educational-attainment polygenic score (PGS) and body mass index measured before the minimum school leaving age (e.g. age 10 years), cannot indicate the effects of years in full-time education on this outcome. Using UK Biobank data, we show that a higher educational-attainment PGS is strongly associated with lower smoking initiation and higher odds of glasses use at age 15 years. These associations were replicated in sibling models. An orthogonal approach using the raising of the school leaving age (ROSLA) policy change found that individuals who chose to remain in education to age 16 years before the reform likely had higher liability to educational attainment than those who were compelled to remain in education to age 16 years after the reform, and had higher income, lower pack-years of smoking, higher odds of glasses use and lower deprivation in adulthood. These results suggest that liability to educational attainment is associated with health and social outcomes independently of years in full-time education., Conclusions: Mendelian-randomization studies with non-continuous exposures should be interpreted in terms of liability, which may affect the outcome via changes in exposure category and/or independently., (© The Author(s) 2021. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Understanding the interplay between educational attainment and genetic predictors of cardiovascular risk may improve our understanding of the aetiology of educational inequalities in cardiovascular disease., Methods: In up to 320 120 UK Biobank participants of White British ancestry (mean age = 57 years, female 54%), we created polygenic scores for nine cardiovascular risk factors or diseases: alcohol consumption, body mass index, low-density lipoprotein cholesterol, lifetime smoking behaviour, systolic blood pressure, atrial fibrillation, coronary heart disease, type 2 diabetes and stroke. We estimated whether educational attainment modified genetic susceptibility to these risk factors and diseases., Results: On the additive scale, higher educational attainment reduced genetic susceptibility to higher body mass index, smoking, atrial fibrillation and type 2 diabetes, but increased genetic susceptibility to higher LDL-C and higher systolic blood pressure. On the multiplicative scale, there was evidence that higher educational attainment increased genetic susceptibility to atrial fibrillation and coronary heart disease, but little evidence of effect modification was found for all other traits considered., Conclusions: Educational attainment modifies the genetic susceptibility to some cardiovascular risk factors and diseases. The direction of this effect was mixed across traits considered and differences in associations between the effect of the polygenic score across strata of educational attainment was uniformly small. Therefore, any effect modification by education of genetic susceptibility to cardiovascular risk factors or diseases is unlikely to substantially explain the development of inequalities in cardiovascular risk., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Trajectories of attention-deficit hyperactivity disorder (ADHD) traits spanning early childhood to mid-life have not been described in general populations across different geographical contexts. Population trajectories are crucial to better understanding typical developmental patterns., Methods: We combined repeated assessments of ADHD traits from five population-based cohorts, spanning ages 3 to 45 years. We used two measures: (i) the Strengths and Difficulties Questionnaire (SDQ) hyperactive-inattentive subscale (175 831 observations, 29 519 individuals); and (ii) scores from DSM-referenced scales (118 144 observations, 28 685 individuals). Multilevel linear spline models allowed for non-linear change over time and differences between cohorts and raters (parent/teacher/self)., Results: Patterns of age-related change differed by measure, cohort and country: overall, SDQ scores decreased with age, most rapidly declining before age 8 years (-0.157, 95% CI: -0.170, -0.144 per year). The pattern was generally consistent using DSM scores, although with greater between-cohort variation. DSM scores decreased most rapidly between ages 14 and 17 years (-1.32%, 95% CI: -1.471, -1.170 per year). Average scores were consistently lower for females than males (SDQ: -0.818, 95% CI: -0.856, -0.780; DSM: -4.934%, 95% CI: -5.378, -4.489). This sex difference decreased over age for both measures, due to an overall steeper decrease for males., Conclusions: ADHD trait scores declined from childhood to mid-life, with marked variation between cohorts. Our results highlight the importance of taking a developmental perspective when considering typical population traits. When interpreting changes in clinical cohorts, it is important to consider the pattern of expected change within the general population, which is influenced by cultural context and measurement., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

The burden of cancer from a clinical, societal, and economic viewpoint continues to increase in all parts of the world, along with much debate regarding how to confront this. Projected increases in cancer indicate a 50% increase in the number of cases over the next 2 decades, with the greatest proportional increase in low- and medium-income settings. In contrast to the historic high cancer burden due to viral and bacterial infections in these regions, future increases are expected to be due to cancers linked to westernization including breast, colorectum, lung, and prostate cancer. Identifying the reasons underlying these increases will be paramount to informing prevention efforts. Evidence from epidemiological and laboratory studies conducted in high-income countries over the last 70 years has led to the conclusion that approximately 40% of the cancer burden is explained by known risk factors-the 2 most important being tobacco and obesity in that order-raising the question of what is driving the rest of the cancer burden. International cancer statistics continue to show that approximately 80% of the cancer burden in high-income countries could be preventable in principle, implying that there are important environmental or lifestyle risk factors for cancer that have not yet been discovered. Emerging genomic evidence from population and experimental studies points to an important role for nonmutagenic promoters in driving cancer incidence rates. New research strategies and infrastructures that combine population-based and laboratory research at a global level are required to break this deadlock., (© The Author(s) 2021. Published by Oxford University Press.)

Background: This study was to systematically test whether previously reported risk factors for chronic kidney disease (CKD) are causally related to CKD in European and East Asian ancestries using Mendelian randomization., Methods: A total of 45 risk factors with genetic data in European ancestry and 17 risk factors in East Asian participants were identified as exposures from PubMed. We defined the CKD by clinical diagnosis or by estimated glomerular filtration rate of <60 ml/min/1.73 m2. Ultimately, 51 672 CKD cases and 958 102 controls of European ancestry from CKDGen, UK Biobank and HUNT, and 13 093 CKD cases and 238 118 controls of East Asian ancestry from Biobank Japan, China Kadoorie Biobank and Japan-Kidney-Biobank/ToMMo were included., Results: Eight risk factors showed reliable evidence of causal effects on CKD in Europeans, including genetically predicted body mass index (BMI), hypertension, systolic blood pressure, high-density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein(a), type 2 diabetes (T2D) and nephrolithiasis. In East Asians, BMI, T2D and nephrolithiasis showed evidence of causality on CKD. In two independent replication analyses, we observed that increased hypertension risk showed reliable evidence of a causal effect on increasing CKD risk in Europeans but in contrast showed a null effect in East Asians. Although liability to T2D showed consistent effects on CKD, the effects of glycaemic phenotypes on CKD were weak. Non-linear Mendelian randomization indicated a threshold relationship between genetically predicted BMI and CKD, with increased risk at BMI of >25 kg/m2., Conclusions: Eight cardiometabolic risk factors showed causal effects on CKD in Europeans and three of them showed causality in East Asians, providing insights into the design of future interventions to reduce the burden of CKD., (© The Author(s) 2021. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: The association patterns of attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) with educational attainment (EA) are complex; children with ADHD and ASD are at risk of poor academic outcomes, and parental EA has been associated with risk of ADHD/ASD in the offspring. Little is known on the causal links between ADHD, ASD, EA and the potential contribution of cognitive ability., Methods: Using the latest genome-wide association studies (GWAS) summary data on ADHD, ASD and EA, we applied two-sample Mendelian randomization (MR) to assess the effects of genetic liability to ADHD and ASD on EA. Reverse direction analyses were additionally performed. Multivariable MR was performed to estimate any effects independent of cognitive ability., Results: Genetic liability to ADHD had a negative effect on EA, independently of cognitive ability (MVMRIVW: -1.7 months of education per doubling of genetic liability to ADHD; 95% CI: -2.8 to -0.7), whereas genetic liability to ASD a positive effect (MVMRIVW: 30 days per doubling of the genetic liability to ASD; 95% CI: 2 to 53). Reverse direction analyses suggested that genetic liability to higher EA had an effect on lower risk of ADHD, independently of cognitive ability (MVMRIVWOR: 0.33 per SD increase; 95% CI: 0.26 to 0.43) and increased risk of ASD (MRIVWOR: 1.51 per SD increase; 95% CI: 1.29 to 1.77), which was partly explained by cognitive ability (MVMRIVWOR per SD increase: 1.24; 95%CI: 0.96 to 1.60)., Conclusions: Genetic liability to ADHD and ASD is likely to affect educational attainment, independently of underlying cognitive ability., (© The Author(s) 2021. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Individuals who are obese in childhood have an elevated risk of disease in adulthood. However, whether childhood adiposity directly impacts intermediate markers of this risk, independently of adult adiposity, is unclear. In this study, we have simultaneously evaluated the effects of childhood and adulthood body size on 123 systemic molecular biomarkers representing multiple metabolic pathways., Methods: Two-sample Mendelian randomization (MR) was conducted to estimate the causal effect of childhood body size on a total of 123 nuclear magnetic resonance-based metabolic markers using summary genome-wide association study (GWAS) data from up to 24 925 adults. Multivariable MR was then applied to evaluate the direct effects of childhood body size on these metabolic markers whilst accounting for adult body size. Further MR analyses were undertaken to estimate the potential mediating effects of these circulating metabolites on the risk of coronary artery disease (CAD) in adulthood using a sample of 60 801 cases and 123 504 controls., Results: Univariable analyses provided evidence that childhood body size has an effect on 42 of the 123 metabolic markers assessed (based on P < 4.07 × 10-4). However, the majority of these effects (35/42) substantially attenuated when accounting for adult body size using multivariable MR. We found little evidence that the biomarkers that were potentially influenced directly by childhood body size (leucine, isoleucine and tyrosine) mediate this effect onto adult disease risk. Very-low-density lipoprotein markers provided the strongest evidence of mediating the long-term effect of adiposity on CAD risk., Conclusions: Our findings suggest that childhood adiposity predominantly exerts its detrimental effect on adult systemic metabolism along a pathway that involves adulthood body size., (© The Author(s) 2021. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: The causal nature of the observed associations between serum lipids and apolipoproteins and kidney function are unclear., Methods: Using two-sample and multivariable Mendelian randomization (MR), we examined the causal effects of serum lipids and apolipoproteins on kidney function, indicated by the glomerular-filtration rate estimated using creatinine (eGFRcrea) or cystatin C (eGFRcys) and the urinary albumin-to-creatinine ratio (UACR). We obtained lipid- and apolipoprotein-associated genetic variants from the Global Lipids Genetics Consortium (n = 331 368) and UK Biobank (n = 441 016), respectively, and kidney-function markers from the Trøndelag Health Study (HUNT; n = 69 736) and UK Biobank (n = 464 207). The reverse causal direction was examined using variants associated with kidney-function markers selected from recent genome-wide association studies., Results: There were no strong associations between genetically predicted lipid and apolipoprotein levels with kidney-function markers. Some, but inconsistent, evidence suggested a weak association of higher genetically predicted atherogenic lipid levels [indicated by low-density lipoprotein cholesterol (LDL-C), triglycerides and apolipoprotein B] with increased eGFR and UACR. For high-density lipoprotein cholesterol (HDL-C), results differed between eGFRcrea and eGFRcys, but neither analysis suggested substantial effects. We found no clear evidence of a reverse causal effect of eGFR on lipid or apolipoprotein traits, but higher UACR was associated with higher LDL-C, triglyceride and apolipoprotein B levels., Conclusion: Our MR estimates suggest that serum lipid and apolipoprotein levels do not cause substantial changes in kidney function. A possible weak effect of higher atherogenic lipids on increased eGFR and UACR warrants further investigation. Processes leading to higher UACR may lead to more atherogenic lipid levels., (© The Author(s) 2021. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Two-sample Mendelian randomization (MR) allows the use of freely accessible summary association results from genome-wide association studies (GWAS) to estimate causal effects of modifiable exposures on outcomes. Some GWAS adjust for heritable covariables in an attempt to estimate direct effects of genetic variants on the trait of interest. One, both or neither of the exposure GWAS and outcome GWAS may have been adjusted for covariables., Methods: We performed a simulation study comprising different scenarios that could motivate covariable adjustment in a GWAS and analysed real data to assess the influence of using covariable-adjusted summary association results in two-sample MR., Results: In the absence of residual confounding between exposure and covariable, between exposure and outcome, and between covariable and outcome, using covariable-adjusted summary associations for two-sample MR eliminated bias due to horizontal pleiotropy. However, covariable adjustment led to bias in the presence of residual confounding (especially between the covariable and the outcome), even in the absence of horizontal pleiotropy (when the genetic variants would be valid instruments without covariable adjustment). In an analysis using real data from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and UK Biobank, the causal effect estimate of waist circumference on blood pressure changed direction upon adjustment of waist circumference for body mass index., Conclusions: Our findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. When that is not possible, careful consideration of the causal relationships underlying the data (including potentially unmeasured confounders) is required to direct sensitivity analyses and interpret results with appropriate caution., (© The Author(s) 2021. Published by Oxford University Press on behalf of the International Epidemiological Association.)

A key assumption of Mendelian randomization (MR) analysis is that there is no association between the genetic variants used as instruments and the outcome other than through the exposure of interest. One way in which this assumption can be violated is through population stratification, which can introduce confounding of the relationship between the genetic variants and the outcome and so induce an association between them. Negative control outcomes are increasingly used to detect unobserved confounding in observational epidemiological studies. Here we consider the use of negative control outcomes in MR studies to detect confounding of the genetic variants and the exposure or outcome. As a negative control outcome in an MR study, we propose the use of phenotypes which are determined before the exposure and outcome but which are likely to be subject to the same confounding as the exposure or outcome of interest. We illustrate our method with a two-sample MR analysis of a preselected set of exposures on self-reported tanning ability and hair colour. Our results show that, of the 33 exposures considered, genome-wide association studies (GWAS) of adiposity and education-related traits are likely to be subject to population stratification that is not controlled for through adjustment, and so any MR study including these traits may be subject to bias that cannot be identified through standard pleiotropy robust methods. Negative control outcomes should therefore be used regularly in MR studies to detect potential population stratification in the data used., (© The Author(s) 2021. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: It is established that Alzheimer's disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD., Methods: We used the largest published genome-wide association studies of self-reported and accelerometer-measured sleep traits (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness), and AD. Mendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters on AD risk., Results: Overall, there was little evidence to support a causal effect of sleep traits on AD risk. There was some suggestive evidence that self-reported daytime napping was associated with lower AD risk [odds ratio (OR): 0.70, 95% confidence interval (CI): 0.50-0.99). Some other sleep traits (accelerometer-measured 'eveningness' and sleep duration, and self-reported daytime sleepiness) had ORs of a similar magnitude to daytime napping, but were less precisely estimated., Conclusions: Overall, we found very limited evidence to support a causal effect of sleep traits on AD risk. Our findings provide tentative evidence that daytime napping may reduce AD risk. Given that this is the first MR study of multiple self-report and objective sleep traits on AD risk, findings should be replicated using independent samples when such data become available., (© The Author(s) 2020. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Genetic liability for schizophrenia is associated with psychopathology in early life. It is not clear if these associations are time dependent during childhood, nor if they are specific across different forms of psychopathology. Using genotype and questionnaire data on children (N = 15 105) from the Norwegian Mother, Father and Child Cohort Study, we used schizophrenia polygenic risk scores to test developmental stability in associations with measures of emotional and behavioral problems between 18 months and 5 years, and domain specificity in associations with symptoms of depression, anxiety, conduct problems, oppositionality, inattention, and hyperactivity at 8 years. We then sought to identify symptom profiles-across development and domains-associated with schizophrenia polygenic liability. We found evidence for developmental stability in associations between schizophrenia polygenic risk scores and emotional and behavioral problems, with the latter being mediated specifically via the rate of change in symptoms (β slope = 0.032; 95% CI: 0.007-0.057). At age 8, associations were better explained by a model of symptom-specific polygenic effects rather than effects mediated via a general psychopathology factor or by domain-specific factors. Overall, individuals with higher schizophrenia polygenic risk scores were more likely (OR = 1.310 [95% CIs: 1.122-1.528]) to have a profile of increasing behavioral and emotional symptoms in early childhood, followed by elevated symptoms of conduct disorder, oppositionality, hyperactivity, and inattention by age 8. Schizophrenia-associated alleles are linked to specific patterns of early-life psychopathology. The associations are small, but findings of this nature can help us better understand the developmental emergence of schizophrenia., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Attention-deficit/hyperactivity disorder (ADHD) is associated with a broad range of physical health problems. Using different research designs to test whether ADHD has a causal role in these associations is important because comorbid health problems increase the serious social and economic impacts of ADHD. We used 2-sample Mendelian randomization (MR) to infer causal relationships between ADHD and previously implicated physical health conditions. Different MR methods were used to test the robustness and plausibility of our findings. Consistent findings underwent bidirectional and multivariable MR. We found evidence of ADHD having a causal effect on childhood obesity (odds ratio = 1.29, 95% confidence interval: 1.02, 1.63) and coronary artery disease (odds ratio = 1.11, 95% confidence interval: 1.03, 1.19) with consistent results across MR approaches. There was additional MR evidence for a bidirectional relationship between ADHD and childhood obesity. The relationship with coronary artery disease attenuated when controlling for childhood obesity. There was little evidence for inferring a causal effect on other cardiometabolic, autoimmune, allergic, and neurological diseases. Our findings strengthen the argument for effective treatment of children with ADHD, and suggest that clinicians who manage ADHD need to be aware of the risk of childhood obesity to reduce future risks of coronary artery disease., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)

Background: Systematic reviews of prenatal alcohol exposure effects generally only include conventional observational studies. However, estimates from such studies are prone to confounding and other biases., Objectives: To systematically review the evidence on the effects of prenatal alcohol exposure from randomized controlled trials (RCTs) and observational designs using alternative analytical approaches to improve causal inference., Search Strategy: Medline, Embase, Web of Science, PsychINFO from inception to 21 June 2018. Manual searches of reference lists of retrieved papers., Selection Criteria: RCTs of interventions to stop/reduce drinking in pregnancy and observational studies using alternative analytical methods (quasi-experimental studies e.g. Mendelian randomization and natural experiments, negative control comparisons) to determine the causal effects of prenatal alcohol exposure on pregnancy and longer-term offspring outcomes in human studies., Data Collection and Analysis: One reviewer extracted data and another checked extracted data. Risk of bias was assessed using customized risk of bias tools. A narrative synthesis of findings was carried out and a meta-analysis for one outcome., Main Results: Twenty-three studies were included, representing five types of study design, including 1 RCT, 9 Mendelian randomization and 7 natural experiment studies, and reporting on over 30 outcomes. One study design-outcome combination included enough independent results to meta-analyse. Based on evidence from several studies, we found a likely causal detrimental role of prenatal alcohol exposure on cognitive outcomes, and weaker evidence for a role in low birthweight., Conclusion: None of the included studies was judged to be at low risk of bias in all domains, results should therefore be interpreted with caution., Systematic Review Registration: This study is registered with PROSPERO, registration number CRD42015015941., (© The Author(s) 2020. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Individuals with obesity have higher concentrations of very low-density lipoprotein (VLDL) cholesterol and increased risk of myocardial infarction. We hypothesized that VLDL cholesterol explains a fraction of the excess myocardial infarction risk in individuals with obesity., Methods: We included 29 010 individuals free of myocardial infarction at baseline, nested within 109 751 individuals from the Copenhagen General Population Study. During 10 years of follow-up, 2306 individuals developed myocardial infarction. Cholesterol content in large and small VLDLs, in intermediate-density lipoprotein (IDL), and in LDL was measured directly with nuclear magnetic resonance spectroscopy., Results: Median concentrations of cholesterol in large and small VLDLs were 0.12 mmol/L (interquartile range [IQR], 0.07-0.20 mmol/L; 4.5 mg/dL [IQR, 2.6-6.9 mg/dL]) and 0.6 mmol/L (IQR, 0.5-0.8 mmol/L; 25 mg/dL [IQR, 20-30 mg/dL]) in individuals with obesity vs 0.06 mmol/L (IQR, 0.03-0.1 mmol/L; 2.2 mg/dL [IQR, 1.1-3.8 mg/dL]), and 0.5 mmol/L (IQR, 0.4-0.6 mmol/L; 20 mg/dL (IQR, 16-25 mg/dL]) in individuals with normal weight; in contrast, concentrations of IDL and LDL cholesterol were similar across body mass index (BMI) categories. Cholesterol in large and small VLDLs combined explained 40% (95% CI, 27%-53%) of the excess risk of myocardial infarction associated with higher BMI. In contrast, IDL and LDL cholesterol did not explain excess risk of myocardial infarction, whereas systolic blood pressure explained 17% (11%-23%) and diabetes mellitus explained 8.6% (3.2%-14%)., Conclusions: VLDL cholesterol explains a large fraction of excess myocardial infarction risk in individuals with obesity. These novel findings support a focus on cholesterol in VLDL for prevention of myocardial infarction and atherosclerotic cardiovascular disease in individuals with obesity., (© American Association for Clinical Chemistry 2021. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Previous studies have found that children born with a non-syndromic orofacial cleft have lower-than-average educational attainment. Differences could be due to a genetic predisposition to low intelligence and academic performance, factors arising due to the cleft phenotype (such as social stigmatization, impaired speech/language development) or confounding by the prenatal environment. A clearer understanding of this mechanism will inform interventions to improve educational attainment in individuals born with a cleft, which could substantially improve their quality of life. We assessed evidence for the hypothesis that common variant genetic liability to non-syndromic cleft lip with or without cleft palate (nsCL/P) influences educational attainment., Methods: We performed a genome-wide association study (GWAS) meta-analysis of nsCL/P with 1692 nsCL/P cases and 4259 parental and unrelated controls. Using GWAS summary statistics, we performed Linkage Disequilibrium (LD)-score regression to estimate the genetic correlation between nsCL/P, educational attainment (GWAS n = 766 345) and intelligence (GWAS n = 257 828). We used two-sample Mendelian randomization to evaluate the causal effects of genetic liability to nsCL/P on educational attainment and intelligence., Results: There was limited evidence for shared genetic aetiology or causal relationships between nsCL/P and educational attainment [genetic correlation (rg) -0.05, 95% confidence interval (CI) -0.12 to 0.01, P 0.13; MR estimate (βMR) -0.002, 95% CI -0.009 to 0.006, P 0.679) or intelligence (rg -0.04, 95% CI -0.13 to 0.04, P 0.34; βMR -0.009, 95% CI -0.02 to 0.002, P 0.11)., Conclusions: Common variants are unlikely to predispose individuals born with nsCL/P to low educational attainment or intelligence. This is an important first step towards understanding the aetiology of low educational attainment in this group., (© The Author(s) 2020. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Objectives: To examine whether educational attainment and intelligence have causal effects on risk of Alzheimer's disease (AD), independently of each other., Design: Two-sample univariable and multivariable Mendelian randomization (MR) to estimate the causal effects of education on intelligence and vice versa, and the total and independent causal effects of both education and intelligence on AD risk., Participants: 17 008 AD cases and 37 154 controls from the International Genomics of Alzheimer's Project (IGAP) consortium., Main Outcome Measure: Odds ratio (OR) of AD per standardized deviation increase in years of schooling (SD = 3.6 years) and intelligence (SD = 15 points on intelligence test)., Results: There was strong evidence of a causal, bidirectional relationship between intelligence and educational attainment, with the magnitude of effect being similar in both directions [OR for intelligence on education = 0.51 SD units, 95% confidence interval (CI): 0.49, 0.54; OR for education on intelligence = 0.57 SD units, 95% CI: 0.48, 0.66]. Similar overall effects were observed for both educational attainment and intelligence on AD risk in the univariable MR analysis; with each SD increase in years of schooling and intelligence, odds of AD were, on average, 37% (95% CI: 23-49%) and 35% (95% CI: 25-43%) lower, respectively. There was little evidence from the multivariable MR analysis that educational attainment affected AD risk once intelligence was taken into account (OR = 1.15, 95% CI: 0.68-1.93), but intelligence affected AD risk independently of educational attainment to a similar magnitude observed in the univariate analysis (OR = 0.69, 95% CI: 0.44-0.88)., Conclusions: There is robust evidence for an independent, causal effect of intelligence in lowering AD risk. The causal effect of educational attainment on AD risk is likely to be mediated by intelligence., (© The Author(s) 2020. Published by Oxford University Press on behalf of the International Epidemiological Association.)