Man-Kit Lei1,2, Steven R H Beach1,3, Meeshanthini V Dogan4, Robert A Philibert4,5. 1. Center for Family Research, University of Georgia, Athens, Georgia. 2. Department of Sociology, University of Georgia, Athens, Georgia. 3. Department of Psychology, University of Georgia, Athens, Georgia. 4. Department of Psychiatry, University of Iowa, Iowa City, Iowa. 5. Behavioral Diagnostics, Iowa City, Iowa.
Abstract
BACKGROUND AND OBJECTIVES: Smoking is known to increase biological age. However, whether this process is reversible through smoking cessation is not known. In this pilot study, we attempt to determine whether smoking cessation reduces biological age. METHODS: We conducted regression analyses of methylation data from 22 subjects, as they entered and exited inpatient substance use treatment, to determine change in biological age, as indicated by the deviation of their methylomic age from chronological age across two time points. RESULTS: We found that, as compared to those subjects who did not stop smoking, subjects who significantly decreased their smoking consumption over a 1 month time period exhibited a marked reduction in methylomic age. CONCLUSION: The rapid and substantial reversal of accelerated aging associated with successful smoking cessation suggests that it can reverse well-known smoking effects on methylomic aging. This preliminary finding can be readily examined in other, larger data sets, and if replicated, this observation may provide smokers with yet another good reason to quit smoking. SCIENTIFIC SIGNIFICANCE: Successful smoking cessation makes patients appear biologically younger than they were at baseline, and to do so quite rapidly. In today's youth driven society, our observations may serve as a powerful impetus for some to quit smoking. (Am J Addict 2017;26:129-135).
BACKGROUND AND OBJECTIVES: Smoking is known to increase biological age. However, whether this process is reversible through smoking cessation is not known. In this pilot study, we attempt to determine whether smoking cessation reduces biological age. METHODS: We conducted regression analyses of methylation data from 22 subjects, as they entered and exited inpatient substance use treatment, to determine change in biological age, as indicated by the deviation of their methylomic age from chronological age across two time points. RESULTS: We found that, as compared to those subjects who did not stop smoking, subjects who significantly decreased their smoking consumption over a 1 month time period exhibited a marked reduction in methylomic age. CONCLUSION: The rapid and substantial reversal of accelerated aging associated with successful smoking cessation suggests that it can reverse well-known smoking effects on methylomic aging. This preliminary finding can be readily examined in other, larger data sets, and if replicated, this observation may provide smokers with yet another good reason to quit smoking. SCIENTIFIC SIGNIFICANCE: Successful smoking cessation makes patients appear biologically younger than they were at baseline, and to do so quite rapidly. In today's youth driven society, our observations may serve as a powerful impetus for some to quit smoking. (Am J Addict 2017;26:129-135).
Authors: Thomas Thom; Nancy Haase; Wayne Rosamond; Virginia J Howard; John Rumsfeld; Teri Manolio; Zhi-Jie Zheng; Katherine Flegal; Christopher O'Donnell; Steven Kittner; Donald Lloyd-Jones; David C Goff; Yuling Hong; Robert Adams; Gary Friday; Karen Furie; Philip Gorelick; Brett Kissela; John Marler; James Meigs; Veronique Roger; Stephen Sidney; Paul Sorlie; Julia Steinberger; Sylvia Wasserthiel-Smoller; Matthew Wilson; Philip Wolf Journal: Circulation Date: 2006-01-11 Impact factor: 29.690
Authors: Natalie S Shenker; Silvia Polidoro; Karin van Veldhoven; Carlotta Sacerdote; Fulvio Ricceri; Mark A Birrell; Maria G Belvisi; Robert Brown; Paolo Vineis; James M Flanagan Journal: Hum Mol Genet Date: 2012-11-21 Impact factor: 6.150
Authors: Hannah R Elliott; Therese Tillin; Wendy L McArdle; Karen Ho; Aparna Duggirala; Tim M Frayling; George Davey Smith; Alun D Hughes; Nish Chaturvedi; Caroline L Relton Journal: Clin Epigenetics Date: 2014-02-03 Impact factor: 6.551
Authors: Sonja Zeilinger; Brigitte Kühnel; Norman Klopp; Hansjörg Baurecht; Anja Kleinschmidt; Christian Gieger; Stephan Weidinger; Eva Lattka; Jerzy Adamski; Annette Peters; Konstantin Strauch; Melanie Waldenberger; Thomas Illig Journal: PLoS One Date: 2013-05-17 Impact factor: 3.240
Authors: Meeshanthini V Dogan; Bridget Shields; Carolyn Cutrona; Long Gao; Frederick X Gibbons; Ronald Simons; Martha Monick; Gene H Brody; Kai Tan; Steven R H Beach; Robert A Philibert Journal: BMC Genomics Date: 2014-02-22 Impact factor: 3.969
Authors: Steve Horvath; Yafeng Zhang; Peter Langfelder; René S Kahn; Marco P M Boks; Kristel van Eijk; Leonard H van den Berg; Roel A Ophoff Journal: Genome Biol Date: 2012-10-03 Impact factor: 13.583
Authors: Monika Lopuszanska-Dawid; Halina Kołodziej; Anna Lipowicz; Alicja Szklarska Journal: Int J Environ Res Public Health Date: 2022-04-21 Impact factor: 4.614
Authors: Eric T Klopack; Judith E Carroll; Steve W Cole; Teresa E Seeman; Eileen M Crimmins Journal: Clin Epigenetics Date: 2022-05-28 Impact factor: 7.259
Authors: Adiv A Johnson; Bradley W English; Maxim N Shokhirev; David A Sinclair; Trinna L Cuellar Journal: Aging Cell Date: 2022-07-02 Impact factor: 11.005
Authors: Polina Mamoshina; Kirill Kochetov; Franco Cortese; Anna Kovalchuk; Alexander Aliper; Evgeny Putin; Morten Scheibye-Knudsen; Charles R Cantor; Neil M Skjodt; Olga Kovalchuk; Alex Zhavoronkov Journal: Sci Rep Date: 2019-01-15 Impact factor: 4.379
Authors: Man-Kit Lei; Frederick X Gibbons; Ronald L Simons; Robert A Philibert; Steven R H Beach Journal: Genes (Basel) Date: 2020-03-14 Impact factor: 4.096