Body mass index and all cause mortality in HUNT and UK Biobank studies: linear and non-linear mendelian randomisation analyses

Abstract

Objective To investigate the shape of the causal relation between body mass index (BMI) and mortality. Design Linear and non-linear mendelian randomisation analyses. Setting Nord-Trøndelag Health (HUNT) Study (Norway) and UK Biobank (United Kingdom). Participants Middle to early late aged participants of European descent: 56 150 from the HUNT Study and 366 385 from UK Biobank. Main outcome measures All cause and cause specific (cardiovascular, cancer, and non-cardiovascular non-cancer) mortality. Results 12 015 and 10 344 participants died during a median of 18.5 and 7.0 years of follow-up in the HUNT Study and UK Biobank, respectively. Linear mendelian randomisation analyses indicated an overall positive association between genetically predicted BMI and the risk of all cause mortality. An increase of 1 unit in genetically predicted BMI led to a 5% (95% confidence interval 1% to 8%) higher risk of mortality in overweight participants (BMI 25.0-29.9) and a 9% (4% to 14%) higher risk of mortality in obese participants (BMI ≥30.0) but a 34% (16% to 48%) lower risk in underweight (BMI <18.5) and a 14% (−1% to 27%) lower risk in low normal weight participants (BMI 18.5-19.9). Non-linear mendelian randomisation indicated a J shaped relation between genetically predicted BMI and the risk of all cause mortality, with the lowest risk at a BMI of around 22-25 for the overall sample. Subgroup analyses by smoking status, however, suggested an always-increasing relation of BMI with mortality in never smokers and a J shaped relation in ever smokers. Conclusions The previously observed J shaped relation between BMI and risk of all cause mortality appears to have a causal basis, but subgroup analyses by smoking status revealed that the BMI-mortality relation is likely comprised of at least two distinct curves, rather than one J shaped relation. An increased risk of mortality for being underweight was only evident in ever smokers.

Dapagliflozin Add-On Therapy Improves Body Composition and Metabolic Parameters in Overweight Type 2 Diabetic Patients: A Pilot Study

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Non-random sampling leads to biased estimates of transcriptome association

“…Our analysis is based on publicly available dbGaP Accession phs00424.v7.p2 data (https://www.gtexportal.org/ home/datasets). The GTEx cohort is composed of n = 752 post-mortem donors aged 20 Statistical approach. Data are simulated according to a composite model of association given by…”

“…A focus of this case study is the distribution of body mass index (BMI), a well-characterized quantitative trait with established heritability [13][14][15] and also a known marker for multiple complex diseases and all cause mortality, e.g. [16][17][18][19][20] . Herein, BMI is used both as a surrogate measure of dissimilarly between cohorts and the primary phenotype under investigation.…”

Understanding the relation between BMI and mortality

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“…Sun and colleagues use mendelian randomisation to estimate more accurately the shape of the causal relation between BMI and mortality 2. Mendelian randomisation aims to combine genetic predictions of the exposure (BMI) and of the outcome (death), to estimate the causal effect of the exposure on the outcome.…”