Partial Identification of the Average Causal Effect in Multiple Study Populations: The Challenge of Combining Mendelian Randomization Studies.

Background: Researchers often use random-effects or fixed-effects meta-analysis to combine findings from multiple study populations. However, the causal interpretation of these models is not always clear, and they do not easily translate to settings where bounds, rather than point estimates, are computed.

Methods: If bounds on an average causal effect of interest in a well-defined population are computed in multiple study populations under specified identifiability assumptions, then under those assumptions the average causal effect would lie within all study-specific bounds and thus the intersection of the study-specific bounds.

Association of Assisted Reproductive Technology With Offspring Growth and Adiposity From Infancy to Early Adulthood.

Importance: People conceived using assisted reproductive technology (ART) make up an increasing proportion of the world's population.

Objective: To investigate the association of ART conception with offspring growth and adiposity from infancy to early adulthood in a large multicohort study.

Design, Setting, And Participants: This cohort study used a prespecified coordinated analysis across 26 European, Asia-Pacific, and North American population-based cohort studies that included people born between 1984 and 2018, with mean ages at assessment of growth and adiposity outcomes from 0.

Estimation of causal effects of a time-varying exposure at multiple time points through multivariable mendelian randomization.

Mendelian Randomisation (MR) is a powerful tool in epidemiology that can be used to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilising genetic variants as instrumental variables (IVs) for the exposure. The effect estimates obtained from MR studies are often interpreted as the lifetime effect of the exposure in question. However, the causal effects of some exposures are thought to vary throughout an individual's lifetime with periods during which an exposure has a greater effect on a particular outcome.

Interpretation of Mendelian randomization using a single measure of an exposure that varies over time.

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.

Effects of general and central adiposity on circulating lipoprotein, lipid, and metabolite levels in UK Biobank: A multivariable Mendelian randomization study.

Background: The direct effects of general adiposity (body mass index (BMI)) and central adiposity (waist-to-hip-ratio (WHR)) on circulating lipoproteins, lipids, and metabolites are unknown.

Methods: We used new metabolic data from UK Biobank (=109,532, a five-fold higher N over previous studies). EDTA-plasma was used to quantify 249 traits with nuclear-magnetic-resonance spectroscopy including subclass-specific lipoprotein concentrations and lipid content, plus pre-glycemic and inflammatory metabolites.

Individual-, family- and school-based interventions to prevent multiple risk behaviours relating to alcohol, tobacco and drug use in young people aged 8-25 years: a systematic review and meta-analysis.

Background: Engagement in multiple substance use risk behaviours such as tobacco smoking, alcohol and drug use during adolescence can result in adverse health and social outcomes. The impact of interventions that address multiple substance use risk behaviours, and the differential impact of universal versus targeted approaches, is unclear given findings from systematic reviews have been mixed. Our objective was to assess effects of interventions targeting multiple substance use behaviours in adolescents.

Exploring and mitigating potential bias when genetic instrumental variables are associated with multiple non-exposure traits in Mendelian randomization.

With the increasing size and number of genome-wide association studies, individual single nucleotide polymorphisms are increasingly found to associate with multiple traits. Many different mechanisms could result in proposed genetic IVs for an exposure of interest being associated with multiple non-exposure traits, some of which could bias MR results. We describe and illustrate, through causal diagrams, a range of scenarios that could result in proposed IVs being related to non-exposure traits in MR studies.

A multivariant recall-by-genotype study of the metabolomic signature of BMI.

Objective: This study estimated the effect of BMI on circulating metabolites in young adults using a recall-by-genotype study design.

Methods: A recall-by-genotype study was implemented in the Avon Longitudinal Study of Parents and Children. Samples from 756 participants were selected for untargeted metabolomics analysis based on low versus high genetic liability for higher BMI defined by a genetic risk score (GRS).

Puberty Timing and Sex-Specific Trajectories of Systolic Blood Pressure: a Prospective Cohort Study.

Background: Sex differences in systolic blood pressure (SBP) emerge during adolescence but the role of puberty is not well understood. We examined sex-specific changes in SBP preceding and following puberty and examined the impact of puberty timing on SBP trajectories in females and males.

Methods: Trajectories of SBP before and after puberty and by timing of puberty in females and males in a contemporary birth cohort study were analyzed.

Objective measures of reward sensitivity and motivation in people with high low anhedonia.

Background: Anhedonia - a diminished interest or pleasure in activities - is a core self-reported symptom of depression which is poorly understood and often resistant to conventional antidepressants. This symptom may occur due to dysfunction in one or more sub-components of reward processing: motivation, consummatory experience and/or learning. However, the precise impairments remain elusive.

Metabolomic Identification of a Novel, Externally Validated Predictive Test for Gestational Diabetes Mellitus.

Context: Undiagnosed gestational diabetes mellitus (GDM) is a major preventable cause of stillbirth. In the United Kingdom, women are selected for diagnostic testing for GDM based on risk factors, including body mass index (BMI) > 30 kg/m2.

Objective: To improve the prediction of GDM using metabolomics.

Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies.

Background: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories.

Pre-pregnancy lifestyle characteristics and risk of miscarriage: the Australian Longitudinal Study on Women's Health.

Background: Previous studies of lifestyle characteristics and risk of miscarriage have mostly been retrospective and failed to account for induced abortions. We examine whether pre-pregnancy body-mass index, alcohol intake and smoking influence the risk of miscarriage after accounting for induced abortions.

Methods: We conducted a prospective cohort study of 9213 women with 26,594 pregnancies participating in the Australian Longitudinal Study on Women's Health.

LongITools: Dynamic longitudinal exposome trajectories in cardiovascular and metabolic noncommunicable diseases.

The current epidemics of cardiovascular and metabolic noncommunicable diseases have emerged alongside dramatic modifications in lifestyle and living environments. These correspond to changes in our "modern" postwar societies globally characterized by rural-to-urban migration, modernization of agricultural practices, and transportation, climate change, and aging. Evidence suggests that these changes are related to each other, although the social and biological mechanisms as well as their interactions have yet to be uncovered.

Associations of early-life pet ownership with asthma and allergic sensitization: A meta-analysis of more than 77,000 children from the EU Child Cohort Network.

Background: Studies examining associations of early-life cat and dog ownership with childhood asthma have reported inconsistent results. Several factors could explain these inconsistencies, including type of pet, timing, and degree of exposure.

Objective: Our aim was to study associations of early-life cat and dog ownership with asthma in school-aged children, including the role of type (cat vs dog), timing (never, prenatal, or early childhood), and degree of ownership (number of pets owned), and the role of allergic sensitization.

The reproducibility debate is an opportunity, not a crisis.

There are many factors that contribute to the reproducibility and replicability of scientific research. There is a need to understand the research ecosystem, and improvements will require combined efforts across all parts of this ecosystem. National structures can play an important role in coordinating these efforts, working collaboratively with researchers, institutions, funders, publishers, learned societies and other sectoral organisations, and providing a monitoring and reporting function.

metaboprep: an R package for preanalysis data description and processing.

Motivation: Metabolomics is an increasingly common part of health research and there is need for preanalytical data processing. Researchers typically need to characterize the data and to exclude errors within the context of the intended analysis. Whilst some preprocessing steps are common, there is currently a lack of standardization and reporting transparency for these procedures.

A framework for research into continental ancestry groups of the UK Biobank.

Background: The UK Biobank is a large prospective cohort, based in the UK, that has deep phenotypic and genomic data on roughly a half a million individuals. Included in this resource are data on approximately 78,000 individuals with "non-white British ancestry." While most epidemiology studies have focused predominantly on populations of European ancestry, there is an opportunity to contribute to the study of health and disease for a broader segment of the population by making use of the UK Biobank's "non-white British ancestry" samples.

Disease consequences of higher adiposity uncoupled from its adverse metabolic effects using Mendelian randomisation.

Background: Some individuals living with obesity may be relatively metabolically healthy, whilst others suffer from multiple conditions that may be linked to adverse metabolic effects or other factors. The extent to which the adverse metabolic component of obesity contributes to disease compared to the non-metabolic components is often uncertain. We aimed to use Mendelian randomisation (MR) and specific genetic variants to separately test the causal roles of higher adiposity with and without its adverse metabolic effects on diseases.

Higher body mass index raises immature platelet count: potential contribution to obesity-related thrombosis.

Higher body mass index (BMI) is a risk factor for thrombosis. Platelets are essential for hemostasis but contribute to thrombosis when activated pathologically. We hypothesized that higher BMI leads to changes in platelet characteristics, thereby increasing thrombotic risk.

Stigmatising views towards individuals with eating disorders: trends and associations from 1998 to 2008 using a repeated cross-sectional design.

Background: Eating disorders are stigmatised. Little is known about whether stigma has decreased over time and which groups hold more stigmatising beliefs.

Aims: To explore whether stigma towards eating disorders has changed between 1998 and 2008 and whether it varies by sociodemographic characteristics.

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

Analysis of secondary data sources (such as cohort studies, survey data, and administrative records) has the potential to provide answers to science and society's most pressing questions. However, researcher biases can lead to questionable research practices in secondary data analysis, which can distort the evidence base. While pre-registration can help to protect against researcher biases, it presents challenges for secondary data analysis.