Causal Effects of Body Mass Index on Airflow Obstruction and Forced Mid-Expiratory Flow: A Mendelian Randomization Study Taking Interactions and Age-Specific Instruments Into Consideration Toward a Life Course Perspective

A data-adaptive method for investigating effect heterogeneity with high-dimensional covariates in Mendelian randomization

BACKGROUND

Mendelian randomization is a popular method for causal inference with observational data that uses genetic variants as instrumental variables. Similarly to a randomized trial, a standard Mendelian randomization analysis estimates the population-averaged effect of an exposure on an outcome. Dividing the population into subgroups can reveal effect heterogeneity to inform who would most benefit from intervention on the exposure. However, as covariates are measured post-"randomization", naive stratification typically induces collider bias in stratum-specific estimates.

METHOD

We extend a previously proposed stratification method (the "doubly-ranked method") to form strata based on a single covariate, and introduce a data-adaptive random forest method to calculate stratum-specific estimates that are robust to collider bias based on a high-dimensional covariate set. We also propose measures based on the Q statistic to assess heterogeneity between stratum-specific estimates (to understand whether estimates are more variable than expected due to chance alone) and variable importance (to identify the key drivers of effect heterogeneity).

RESULT

We show that the effect of body mass index (BMI) on lung function is heterogeneous, depending most strongly on hip circumference and weight. While for most individuals, the predicted effect of increasing BMI on lung function is negative, it is positive for some individuals and strongly negative for others.

CONCLUSION

Our data-adaptive approach allows for the exploration of effect heterogeneity in the relationship between an exposure and an outcome within a Mendelian randomization framework. This can yield valuable insights into disease aetiology and help identify specific groups of individuals who would derive the greatest benefit from targeted interventions on the exposure.

Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: A systematic literature review

Diseases diagnosed in adulthood may have antecedents throughout (including prenatal) life. Gaining a better understanding of how exposures at different stages in the lifecourse influence health outcomes is key to elucidating the potential benefits of disease prevention strategies. Mendelian randomisation (MR) is increasingly used to estimate causal effects of exposures across the lifecourse on later life outcomes. This systematic literature review explores MR methods used to perform lifecourse investigations and reviews previous work that has utilised MR to elucidate the effects of factors acting at different stages of the lifecourse. We conducted searches in PubMed, Embase, Medline and MedRXiv databases. Thirteen methodological studies were identified. Four studies focused on the impact of time-varying exposures in the interpretation of "standard" MR techniques, five presented methods for repeat measures of the same exposure, and four described methodological approaches to handling multigenerational exposures. A further 127 studies presented the results of an applied research question. Over half of these estimated effects in a single generation and were largely confined to the exploration of questions regarding body composition. The remaining mostly estimated maternal effects. There is a growing body of research focused on the development and application of MR methods to address lifecourse research questions. The underlying assumptions require careful consideration and the interpretation of results rely on select conditions. Whilst we do not advocate for a particular strategy, we encourage practitioners to make informed decisions on how to approach a research question in this field with a solid understanding of the limitations present and how these may be affected by the research question, modelling approach, instrument selection, and data availability.

Physiological association of the breakpoint with the duration of hyperventilation

OBJECTIVES

To determine the relationship of body mass index (BMI) with breath-holding time (BHT) as well as that of BHT with the duration of hyperventilation (DOH) in young healthy adults.

METHODS

An observational study was performed at Shalamar Medical and Dental College, Lahore, Pakistan, between May 2021 and June 2022. Healthy first-year Bachelor of Medicine, Bachelor of Surgery students aged 18-22 years, with a normal BMI were included. Spirometric measurements were taken through a spirometer pod connected to a pneumotachometer (model: Power Lab 26T). Body mass index was calculated as the weight (kg) to height (m2) ratio. Pearson correlation, linear regression, and t tests were applied using SPSS.

RESULTS

A total of 101 subjects participated, comprising of 44 men and 57 women. A weak negative association was found between BMI and BHT in all subjects (r= -0.08, p=0.34), in men (r= -0.24, p=0.11), and in women (r= -0.092, p=0.497). Furthermore, a strong association was observed between BHT and DOH in all subjects (r=0.64, p=0.000), in men (r=0.604, p=0.000), and in women (r=0.518, p=0.000). Moreover, a nonsignificant weak inverse linear regression was found between the BMI and BHT of all subjects (β= -0.087, p=0.38), of men (β= -0.241, p=0.11), and of women (β= -0.092, p=0.49). Lastly, a significantly strong positive regression was observed between the BHT and DOH of all subjects (β=0.637, p=0.000), of men (β=0.604, p=0.000), and of women (β=0.518, p=0.000).

CONCLUSION

No association was found between BMI and BHT. A strong positive association was observed between BHT and DOH in all healthy young people.

Pathogenesis of chronic obstructive pulmonary disease: understanding the contributions of gene-environment interactions across the lifespan

The traditional view of chronic obstructive pulmonary disease (COPD) as a self-inflicted disease caused by tobacco smoking in genetically susceptible individuals has been challenged by recent research findings. COPD can instead be understood as the potential end result of the accumulation of gene-environment interactions encountered by an individual over the life course. Integration of a time axis in pathogenic models of COPD is necessary because the biological responses to and clinical consequences of different exposures might vary according to both the age of an individual at which a given gene-environment interaction occurs and the cumulative history of previous gene-environment interactions. Future research should aim to understand the effects of dynamic interactions between genes (G) and the environment (E) by integrating information from basic omics (eg, genomics, epigenomics, proteomics) and clinical omics (eg, phenomics, physiomics, radiomics) with exposures (the exposome) over time (T)-an approach that we refer to as GETomics. In the context of this approach, we argue that COPD should be viewed not as a single disease, but as a clinical syndrome characterised by a recognisable pattern of chronic symptoms and structural or functional impairments due to gene-environment interactions across the lifespan that influence normal lung development and ageing.