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Controlling for baseline telomere length biases estimates of the rate of telomere attrition

Lookup NU author(s): Professor Melissa BatesonORCiD, Professor Daniel Nettle

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. Longitudinal studies have sought to establish whether environmental exposures such as smoking accelerate the attrition of individuals’ telomeres over time. These studies typically control for baseline telomere length (TL) by including it as a covariate in statistical models. However, baseline TL also differs between smokers and non-smokers, and telomere attrition is spuriously linked to baseline TL via measurement error and regression to the mean. Using simulated datasets, we show that controlling for baseline TL overestimates the true effect of smoking on telomere attrition. This bias increases with increasing telomere measurement error and increasing difference in baseline TL between smokers and non-smokers. Using a meta-analysis of longitudinal datasets, we show that as predicted, the estimated difference in telomere attrition between smokers and non-smokers is greater when statistical models control for baseline TL than when they do not, and the size of the discrepancy is positively correlated with measurement error. The bias we describe is not specific to smoking and also applies to other exposures. We conclude that to avoid invalid inference, models of telomere attrition should not control for baseline TL by including it as a covariate. Many claims of accelerated telomere attrition in individuals exposed to adversity need to be re-assessed.


Publication metadata

Author(s): Bateson M, Eisenberg DTA, Nettle D

Publication type: Article

Publication status: Published

Journal: Royal Society Open Science

Year: 2019

Volume: 6

Issue: 10

Online publication date: 30/10/2019

Acceptance date: 28/09/2019

Date deposited: 19/11/2019

ISSN (electronic): 2054-5703

Publisher: Royal Society Publishing

URL: https://doi.org/10.1098/rsos.190937

DOI: 10.1098/rsos.190937


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Funding

Funder referenceFunder name
AdG 666669
BCS-1519110
NC/K000802/1

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