Tempus et Locus: a tool for extracting precisely dated viral sequences from GenBank, and its application to the phylogenetics of primate erythroparvovirus 1 (B19V)

The presence of data in the collection_date field of a GenBank sequence record is of great assistance in the use of that sequence for Bayesian phylogenetics using tip-dating. We present Tempus et Locus (TeL), a tool for extracting such sequences from a GenBank-formatted sequence database. TeL shows that 60% of viral sequences in GenBank have collection date fields, but that this varies considerably between species. Primate erythroparvovirus 1 (human parvovirus B19 or B19V) has only 40% of its sequences dated, of which only 112 are of more than 4 kb. 100 of these are from B19V sub-genotype 1a and were collected from a mere 6 studies conducted in 5 countries between 2002 and 2013. Nevertheless, Bayesian phylogenetic analysis of this limited set gives a date for the common ancestor of sub-genotype 1a in 1990 (95% HPD 1981-1996) which is in reasonable agreement with estimates of previous studies where collection dates have been assembled by more laborious methods of literature search and direct enquiries to sequence submitters. We conclude that although collection dates should become standard for all future GenBank submissions of virus sequences, accurate dating of ancestors is possible with even a small number of sequences if sampling information is high quality

The impact of education inequality on rheumatoid arthritis risk is mediated by smoking and body mass index: mendelian randomization study

Objective To estimate the causal relationship between educational attainment—as a proxy for socioeconomic inequality—and risk of RA, and quantify the roles of smoking and BMI as potential mediators. Methods Using the largest genome-wide association studies (GWAS), we performed a two‐sample Mendelian randomization (MR) study of genetically predicted educational attainment (instrumented using 1265 variants from 766 345 individuals) and RA (14 361 cases, 43 923 controls). We used two-step MR to quantify the proportion of education’s effect on RA mediated by smoking exposure (as a composite index capturing duration, heaviness and cessation, using 124 variants from 462 690 individuals) and BMI (517 variants, 681 275 individuals), and multivariable MR to estimate proportion mediated by both factors combined. Results Each S.D. increase in educational attainment (4.2 years of schooling) was protective of RA (odds ratio 0.37; 95% CI: 0.31, 0.44). Higher educational attainment was also protective for smoking exposure (β = −0.25 S.D.; 95% CI: −0.26, −0.23) and BMI [β = −0.27 S.D. (∼1.3 kg/m2); 95% CI: −0.31, −0.24]. Smoking mediated 24% (95% CI: 13%, 35%) and BMI 17% (95% CI: 11%, 23%) of the total effect of education on RA. Combined, the two risk factors explained 47% (95% CI: 11%, 82%) of the total effect. Conclusion Higher educational attainment has a protective effect on RA risk. Interventions to reduce smoking and excess adiposity at a population level may reduce this risk, but a large proportion of education’s effect on RA remains unexplained. Further research into other risk factors that act as potentially modifiable mediators are required

Educational attainment as a modifier for the effect of polygenic scores for cardiovascular risk factors:cross-sectional and prospective analysis of UK Biobank

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

Separating the direct effects of traits on atherosclerotic cardiovascular disease from those mediated by type 2 diabetes

AIMS/HYPOTHESIS: Type 2 diabetes and atherosclerotic CVD share many risk factors. This study aimed to systematically assess a broad range of continuous traits to separate their direct effects on coronary and peripheral artery disease from those mediated by type 2 diabetes. METHODS: Our main analysis was a two-step Mendelian randomisation for mediation to quantify the extent to which the associations observed between continuous traits and liability to atherosclerotic CVD were mediated by liability to type 2 diabetes. To support this analysis, we performed several univariate Mendelian randomisation analyses to examine the associations between our continuous traits, liability to type 2 diabetes and liability to atherosclerotic CVD. RESULTS: Eight traits were eligible for the two-step Mendelian randomisation with liability to coronary artery disease as the outcome and we found similar direct and total effects in most cases. Exceptions included fasting insulin and hip circumference where the proportion mediated by liability to type 2 diabetes was estimated as 56% and 52%, respectively. Six traits were eligible for the analysis with liability to peripheral artery disease as the outcome. Again, we found limited evidence to support mediation by liability to type 2 diabetes for all traits apart from fasting insulin (proportion mediated: 70%). CONCLUSIONS/INTERPRETATION: Most traits were found to affect liability to atherosclerotic CVD independently of their relationship with liability to type 2 diabetes. These traits are therefore important for understanding atherosclerotic CVD risk regardless of an individual’s liability to type 2 diabetes. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00125-022-05653-1

Mendelian randomisation for mediation analysis: current methods and challenges for implementation

Mediation analysis seeks to explain the pathway(s) through which an exposure affects an outcome. Traditional, non-instrumental variable methods for mediation analysis experience a number of methodological difficulties, including bias due to confounding between an exposure, mediator and outcome and measurement error. Mendelian randomisation (MR) can be used to improve causal inference for mediation analysis. We describe two approaches that can be used for estimating mediation analysis with MR: multivariable MR (MVMR) and two-step MR. We outline the approaches and provide code to demonstrate how they can be used in mediation analysis. We review issues that can affect analyses, including confounding, measurement error, weak instrument bias, interactions between exposures and mediators and analysis of multiple mediators. Description of the methods is supplemented by simulated and real data examples. Although MR relies on large sample sizes and strong assumptions, such as having strong instruments and no horizontally pleiotropic pathways, our simulations demonstrate that these methods are unaffected by confounders of the exposure or mediator and the outcome and non-differential measurement error of the exposure or mediator. Both MVMR and two-step MR can be implemented in both individual-level MR and summary data MR. MR mediation methods require different assumptions to be made, compared with non-instrumental variable mediation methods. Where these assumptions are more plausible, MR can be used to improve causal inference in mediation analysis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10654-021-00757-1

Developmental transitions in body color in chacma baboon infants: Implications to estimate age and developmental pace

International audienc