International Journal of Epidemiology

BackgroundMendelian randomisation (MR) uses germline genetic variation as a natural experiment to investigate causal relations between traits. MR is robust to non-differential random measurement error in exposures or outcomes. However, the effect of differential measurement error, and non-differential measurement error on the variant selection process, remains unclear. MethodsWe use Monte-Carlo simulations and an applied example to explore the effect of differential measurement error on MR esti...

BackgroundMendelian Randomization (MR) is a widely used tool to infer causal relationships. Yet, little research has been conducted on the elucidation of environment specific causal effects, despite mounting evidence for the relevance of causal effect modifying environmental variables. MethodsTo investigate potential modifications of causal effects, we extended two-stage-least-squares MR to investigate interaction effects (2SLS-I). We first tested 2SLS-I in a wide range of realistic simulation ...

ObjectivesTo investigate which levels of educational attainment affect health. DesignMultivariable Mendelian randomization study (MVMR). SettingUK Biobank. ParticipantsEuropean ancestry participants born in England. Exposure Educationalattainment was defined as leaving school before age 18, leaving school after 18, or getting a university degree. Randomly allocated genetic variants were used as instruments for these traits. Main outcome measuresBody mass index (BMI), smoking initiation, and...

BackgroundNon-random selection into analytic subsamples could introduce selection bias in observational studies of SARS-CoV-2 infection and COVID-19 severity (e.g. including only those have had a COVID-19 PCR test). We explored the potential presence and impact of selection in such studies using data from self-report questionnaires and national registries. MethodsUsing pre-pandemic data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (mean age=27.6 (standard deviation [SD]=0.5...

BackgroundMendelian randomisation (MR) is a method of causal inference that uses genetic variation as an instrumental variable (IV) to account for confounding. While the number of MR articles published each year is rapidly rising (partly due to large cohort studies such as the UK Biobank making it easier to conduct MR), it is not currently known whether these studies are appropriately conducted and reported in enough detail for other researchers to accurately replicate and interpret them. Metho...

Socio-economic status of participants in many public health, epidemiological, and genome-wide association studies is an important trait of interest. It is often used in these studies as a measure of direct interest or as a covariate. The Africa Wits INDEPTH Partnership for Genomic and Environmental Research (AWI-Gen) explores genomic and environmental factors in non-communicable diseases, particularly cardio-metabolic disease. In Phase I of AWI-Gen, approximately 12,000 participants were recruit...

ObjectivesTo estimate the shape of the causal relationship between body mass index (BMI) and mortality risk in a Mendelian randomization framework. DesignMendelian randomization analyses of two prospective population-based cohorts. SettingIndividuals of European ancestries living in Norway or the United Kingdom. Participants56,150 participants from the Trondelag Health Study (HUNT) in Norway and 366,385 participants from UK Biobank recruited by postal invitation. OutcomesAll-cause mortality ...

IntroductionGenetic associations for variants identified through genome-wide association studies (GWAS) tend to be overestimated in the original discovery dataset; as if the association was underestimated, the variant may not have been detected. This bias, known as winners curse, can affect Mendelian randomization estimates, but its severity and potential impact is unclear. MethodsWe performed an empirical investigation to assess the potential bias from winners curse in practice. We considered ...

BackgroundOur aim is to produce guidance on exploring and mitigating possible bias when genetic instrumental variables (IVs) associate with traits other than the exposure of interest in Mendelian randomization (MR) studies. MethodsWe use causal diagrams to illustrate scenarios that could result in IVs being related to (non-exposure) traits. We recommend that MR studies explore possible IV-non-exposure associations across a much wider range of traits than is usually the case. Where associations ...

BackgroundEarly-life growth adversity is important to later-life health, but precision assessment in adulthood is challenging. We evaluated whether the difference between attained and genotype-predicted adult height ("height-GaP") would associate with prospectively ascertained early-life growth adversity and later-life all-cause and cardiovascular mortality. MethodsData were first analyzed from the Avon Longitudinal Study of Parents and Children (ALSPAC) and UKBiobank. Genotype-predicted height...

Mendelian randomization may give biased causal estimates if the instrument affects the outcome not solely via the exposure of interest (violating the exclusion restriction assumption). We demonstrate use of a global randomization test as a falsification test for the exclusion restriction assumption. Using simulations, we explored the statistical power of the randomization test to detect an association between a genetic instrument and a covariate set due to a) selection bias or b) horizontal plei...

ImportanceObservationally, greater pre-pregnancy maternal and paternal body mass index (BMI) are associated with a poorer offspring adult cardiovascular risk factor profile, but it is unclear whether this is due to family-level confounding or causal developmental mechanisms. ObjectiveWe aimed to test the causal effect of maternal and paternal BMI on offspring cardiovascular risk factors in adulthood, accounting for the genetic correlation between parents and offspring. DesignTwo-sample interge...

BackgroundStructural barriers to testing may introduce selection bias in COVID-19 research. We explore whether changes to testing and lockdown restrictions introduce time-specific selection bias into analyses of socioeconomic position (SEP) and SARS-CoV-2 infection. MethodsUsing UK Biobank (N = 420 231; 55 % female; mean age = 56{middle dot}3 [SD=8{middle dot}01]) we estimated the association between SEP and i) being tested for SARS-CoV-2 infection versus not being tested ii) testing positive f...

BackgroundStructured life course modelling approaches (SLCMA) have been developed to understand how exposures across the lifespan relate to later health, but have primarily been restricted to single exposures. As multiple exposures can jointly impact health, here we: i) demonstrate how to extend SLCMA to include exposure interactions; ii) conduct a simulation study investigating the performance of these methods; and iii) apply these methods to explore associations of access to green space, and i...

BackgroundObservational studies have consistently found educational inequalities in cardiovascular disease risk. Mendelian randomisation analyses have suggested a direct causal effect of education, however estimates may be biased by demography or dynastic effects. This study aimed to estimate the effects of educational attainment on cardiovascular disease risk and serum lipid concentrations before and after accounting for family structure. MethodsThis study included 28 448 siblings from the Tro...

Preliminary reports suggest that the Coronavirus Disease 2019 (COVIDa^19) pandemic has led to disproportionate morbidity and mortality among historically disadvantaged populations. The extent to which these disparities are related to socioeconomic versus biologic factors is largely unknown. We investigate the racial and socioeconomic associations of COVIDa^19 hospitalization among 418,794 participants of the UK Biobank, of whom 549 (0.13%) had been hospitalized. Both black participants (odds rat...

Estimates from conventional Mendelian randomization (MR) analyses can be biased when the genetic variants proposed as instruments vary over age in their relationship with the exposure. For four exposures commonly studied using MR, we assessed the degree to which their relationship with genetic variants commonly used as instruments varies by age using flexible, spline-based models in UK Biobank data. Using these models, we then estimated how biased MR estimates would be due to age-varying relatio...

BackgroundMeasurement error in exposures and confounders can bias exposure-outcome associations but is rarely considered. Our aim was to assess measurement error between repeat measures of all continuous variables in UK Biobank, and explore approaches to mitigate its impact on exposure-outcome associations. MethodsIntraclass correlation coefficients (ICC) were calculated for all continuous variables with repeat measures. Regression calibration was used to correct for measurement error in both e...

BackgroundEstimation of the average causal effect using instrumental variable (IV) analyses requires homogeneity of instrument-exposure and/or exposure-outcome relationships. Previous research explored the validity of homogeneity assumptions by testing IV-exposure interaction effects using a set of effect modifiers. However, this approach requires that modifiers are known and measured but evidence for interaction may also be observed through IV association with exposure variance without knowledg...

BackgroundThe most socioeconomically deprived individuals remain at the greatest risk of cardiovascular disease. Differences in risk adjusted use of statins between educational groups may contribute to these inequalities. We explore whether people with lower levels of educational attainment are less likely to take statins for a given level of cardiovascular risk. Methods and findingsUsing data from a large prospective cohort study, UK Biobank, we calculated a QRISK3 cardiovascular risk score fo...