Using genome-wide data to examine the association between Body Mass Index (BMI) and sleep

Publication type

Conference Paper


Victoria Garfield

Publication date


Observational evidence
suggests that there is a possible bidirectional association between
obesity and sleep. An important limitation of observational analysis is
the ability to infer causation and overcome reverse causality. Mendelian
Randomization (MR) is a technique, which seeks to overcome this hurdle
by using genetic variants identified from the Genome Wide Association
Study (GWAS) literature as instruments for the exposure of interest and
test whether there is a causal association with the outcome of interest.
Here we implement the MR method to examine whether body mass index
(BMI) is causally associated with sleep duration using pooled data from a
number of studies, including the English Longitudinal Study of Ageing
(ELSA), the Avon Longitudinal Study of Parents and Children and
Understanding Society. Observational analyses using linear regression
confirms an association such that there is a negative relationship
between BMI and sleep duration: b=-0.010 (95% CI= -0.019 – -0.005),
N=4639, in ELSA, b=-0.010 (95% CI=-0.015 – -0.005), N=14981, in
Understanding Society, after adjustment for a wide range of covariates.
We will examine whether the observation of BMI and poor sleep
duration is causal by employing Mendelian Randomization using a genetic
score for BMI created from 92 single-nucleotide polymorphisms recently
identified in GWAS publications. Results from the Mendelian
Randomization will be presented.


Medicine, Science And Technology, Health, Biology and Genetics