Abstract
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 years. Meta-analysis confirmed a cross-sectional difference in LTL between smokers and non-smokers, with mean LTL 84.61 bp shorter in smokers (9.5%, CI: 22.02 to 140.01). 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 he 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 obseived pattern of telomere dynamics.
Original language | English |
---|---|
Article number | 190420 |
Number of pages | 16 |
Journal | Royal Society Open Science |
Volume | 6 |
Issue number | 6 |
DOIs | |
Publication status | Published - Jun 2019 |
Keywords
- biological age
- telomere length
- telomere attrition
- smoking
- longitudinal
- CIGARETTE-SMOKING
- OXIDATIVE STRESS
- LENGTH DYNAMICS
- LIFE
- DETERMINANTS
- EXPERIENCES
- CHILDHOOD
- MORTALITY
- INCREASE
- SMOKERS
Access to Document
- 10.1098/rsos.190420Licence: CC BY
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In: Royal Society Open Science, Vol. 6, No. 6, 190420, 06.2019.
Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Smoking does not accelerate leucocyte telomere attrition
T2 - a meta-analysis of 18 longitudinal cohorts
AU - Bateson, Melissa
AU - Aviv, Abraham
AU - Bendix, Laila
AU - Benetos, Athanase
AU - Ben-Shlomo, Yoav
AU - Bojesen, Stig E.
AU - Cooper, Cyrus
AU - Cooper, Rachel
AU - Deary, Ian J.
AU - Hagg, Sara
AU - Harris, Sarah E.
AU - Kark, Jeremy D.
AU - Kronenberg, Florian
AU - Kuh, Diana
AU - Labat, Carlos
AU - Martin-Ruiz, Carmen M.
AU - Meyer, Craig
AU - Nordestgaard, Borge G.
AU - Penninx, Brenda W. J. H.
AU - Pepper, Gillian V.
AU - Revesz, Dora
AU - Said, M. Abdullah
AU - Starr, John M.
AU - Syddall, Holly
AU - Thomson, William Murray
AU - van der Harst, Pim
AU - Whooley, Mary
AU - von Zglinicki, Thomas
AU - Willeit, Peter
AU - Zhan, Yiqiang
AU - Nettle, Daniel
N1 - Funding Information: Funding. Cohorts acknowledge the following sources of funding: LBC1921, CCS, HAS and NSHD—New Dynamics of Ageing via the HALCyon cross-cohort collaborative programme (RES-353-25-0001); LBC1921—UK Biotechnology and Biological Sciences Research Council (BBSRC), The Royal Society, and The Chief Scientist Office of the Scottish Government, Lifelong Health and Wellbeing Initiative (MR/K026992/1); LBC1936—Age UK (Disconnected Mind Project); NSHD—UK Medical Research Council; JLRCS—US-Israel Binational Science Foundation, the Israel Science Foundation and the National Institutes of Health (AG030678 and AG201320); DMHDS—US National Institute on Aging (AG032282) and the UK Medical Research Council (MR/K00381X and MR/P005918); NESDA—The Netherlands Organisation for Health Research and Development (10-000-1002), VU University Medical Center, GGZ inGeest, Leiden University Medical Center, Leiden University, GGZ Rivierduinen, University Medical Center Groningen, University of Groningen, Lentis, GGZ Friesland, GGZ Drenthe, Rob Giel Onderzoekscentrum. The authors additionally acknowledge the following sources of funding: M.B.—National Centre for the Replacement Refinement and Reduction of Animals in Research (NC/ K000802/1); D.N. and G.V.P.—European Research Council (AdG 666669); A.A.—National Institutes of Health (R01HL116446, R01HD071180, R01HL13840); S.H. and Y.Z.—Karolinska Institutet Delfinansiering, the Swedish Research Council (2015-03255), the Loo & Hans Osterman Foundation, the Foundation for Geriatric Diseases, the Magnus Bergwall Foundation, the Erik Rönnberg award for aging studies and the Strategic Research Program in Epidemiology at Karolinska Institutet; C.C. and H.S.—UK Medical Research Council and University of Southampton; T.v.Z.—UK Medical Research Council (G0601333); I.J.D., J.M.S. and S.E.H.—Centre for Cognitive Ageing and Cognitive Epidemiology, which is funded by the Medical Research Council and the Biotechnology and Biological Sciences Research Council (MR/K026992/1). Acknowledgements. We are grateful to all of the people who took part in the study, either as participants, or as part of the research teams responsible for the 18 cohorts analysed. We thank Jimmy Zeng who computed summary statistics for DMHDS. We also thank Maya B. Mathur and Idan Shalev who provided thoughtful reviewers’ comments that substantially improved the paper. Funding Information: Cohorts acknowledge the following sources of funding: LBC1921, CCS, HAS and NSHD-New Dynamics of Ageing via the HALCyon cross-cohort collaborative programme (RES-353-25-0001); LBC1921-UK Biotechnology and Biological Sciences Research Council (BBSRC), The Royal Society, and The Chief Scientist Office of the Scottish Government, Lifelong Health and Wellbeing Initiative (MR/K026992/1); LBC1936-Age UK (Disconnected Mind Project); NSHD-UK Medical Research Council; JLRCS-US-Israel Binational Science Foundation, the Israel Science Foundation and the National Institutes of Health (AG030678 and AG201320); DMHDS-US National Institute on Aging (AG032282) and the UK Medical Research Council (MR/K00381X and MR/P005918); NESDA-The Netherlands Organisation for Health Research and Development (10-000-1002), VU University Medical Center, GGZ inGeest, Leiden University Medical Center, Leiden University, GGZ Rivierduinen, University Medical Center Groningen, University of Groningen, Lentis, GGZ Friesland, GGZ Drenthe, Rob Giel Onderzoekscentrum. The authors additionally acknowledge the following sources of funding: M.B.-National Centre for the Replacement Refinement and Reduction of Animals in Research (NC/ K000802/1); D.N. and G.V.P.-European Research Council (AdG 666669); A.A.-National Institutes of Health (R01HL116446, R01HD071180, R01HL13840); S.H. and Y.Z.-Karolinska Institutet Delfinansiering, the Swedish Research Council (2015-03255), the Loo & Hans Osterman Foundation, the Foundation for Geriatric Diseases, the Magnus Bergwall Foundation, the Erik Rönnberg award for aging studies and the Strategic Research Program in Epidemiology at Karolinska Institutet; C.C. and H.S.-UK Medical Research Council and University of Southampton; T.v.Z.-UK Medical Research Council (G0601333); I.J.D., J.M.S. and S.E.H.-Centre for Cognitive Ageing and Cognitive Epidemiology, which is funded by the Medical Research Council and the Biotechnology and Biological Sciences Research Council (MR/K026992/1). Publisher Copyright: © 2019 The Authors.
PY - 2019/6
Y1 - 2019/6
N2 - 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 years. Meta-analysis confirmed a cross-sectional difference in LTL between smokers and non-smokers, with mean LTL 84.61 bp shorter in smokers (9.5%, CI: 22.02 to 140.01). 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 he 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 obseived pattern of telomere dynamics.
AB - 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 years. Meta-analysis confirmed a cross-sectional difference in LTL between smokers and non-smokers, with mean LTL 84.61 bp shorter in smokers (9.5%, CI: 22.02 to 140.01). 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 he 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 obseived pattern of telomere dynamics.
KW - biological age
KW - telomere length
KW - telomere attrition
KW - smoking
KW - longitudinal
KW - CIGARETTE-SMOKING
KW - OXIDATIVE STRESS
KW - LENGTH DYNAMICS
KW - LIFE
KW - DETERMINANTS
KW - EXPERIENCES
KW - CHILDHOOD
KW - MORTALITY
KW - INCREASE
KW - SMOKERS
U2 - 10.1098/rsos.190420
DO - 10.1098/rsos.190420
M3 - Article
C2 - 31312500
SN - 2054-5703
VL - 6
JO - Royal Society Open Science
JF - Royal Society Open Science
IS - 6
M1 - 190420
ER -