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Smoking does not accelerate leucocyte telomere attrition: a meta-analysis of 18 longitudinal cohorts.

Melissa BatesonAbraham AvivLaila BendixAthanase BenetosYoav Ben-ShlomoStig E BojesenCyrus CooperRachel CooperIan J DearySara HäggSarah E HarrisJeremy D KarkFlorian KronenbergDiana KuhCarlos LabatCarmen M Martin-RuizCraig MeyerBørge G NordestgaardBrenda W J H PenninxGillian V PepperDóra RévészM Abdullah SaidJohn M StarrHolly SyddallWilliam Murray ThomsonPim van der HarstMary WhooleyThomas von ZglinickiPeter WilleitYiqiang ZhanDaniel Nettle
Published in: Royal Society open science (2019)
Smoking is associated with shorter leucocyte telomere length (LTL), a biomarker of increased morbidity and reduced longevity. This association is widely interpreted as evidence that smoking causes accelerated LTL attrition in adulthood, but the evidence for this is inconsistent. We analysed the association between smoking and LTL dynamics in 18 longitudinal cohorts. The dataset included data from 12 579 adults (4678 current smokers and 7901 non-smokers) over a mean follow-up interval of 8.6 years. Meta-analysis confirmed a cross-sectional difference in LTL between smokers and non-smokers, with mean LTL 84.61 bp shorter in smokers (95% CI: 22.62 to 146.61). However, LTL attrition was only 0.51 bp yr-1 faster in smokers than in non-smokers (95% CI: -2.09 to 1.08), a difference that equates to only 1.32% of the estimated age-related loss of 38.33 bp yr-1. Assuming a linear effect of smoking, 167 years of smoking would be required to generate the observed cross-sectional difference in LTL. Therefore, the difference in LTL between smokers and non-smokers is extremely unlikely to be explained by a linear, causal effect of smoking. Selective adoption, whereby individuals with short telomeres are more likely to start smoking, needs to be considered as a more plausible explanation for the observed pattern of telomere dynamics.
Keyphrases
  • smoking cessation
  • cross sectional
  • systematic review
  • randomized controlled trial
  • deep learning
  • artificial intelligence