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Epigenome Wide Associations of Smoking Behavior in the Health and Retirement Study

DNA methylation (DNAm) is an increasingly popular biomarker of health and aging outcomes. Smoking behaviors have a significant and well documented correlation with methylation signatures within the epigenome and are important confounding variables to account for in epigenome-wide association studies...

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Autores principales: Fisher, Jonah, Mitchell, Colter, Meier, Helen, Crimmins, Eileen, Thyagarajan, Bharat, Faul, Jessica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8681306/
http://dx.doi.org/10.1093/geroni/igab046.2509
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author Fisher, Jonah
Mitchell, Colter
Meier, Helen
Crimmins, Eileen
Thyagarajan, Bharat
Faul, Jessica
author_facet Fisher, Jonah
Mitchell, Colter
Meier, Helen
Crimmins, Eileen
Thyagarajan, Bharat
Faul, Jessica
author_sort Fisher, Jonah
collection PubMed
description DNA methylation (DNAm) is an increasingly popular biomarker of health and aging outcomes. Smoking behaviors have a significant and well documented correlation with methylation signatures within the epigenome and are important confounding variables to account for in epigenome-wide association studies (EWAS). However, the common classification of individuals as ‘current’, ‘former’, and ‘never’ smokers may miss crucial DNAm patterns associated with other smoking behaviors such as duration, intensity, and frequency of cigarette smoking, resulting in an underestimation of the contribution of smoking behaviors to DNAm and potentially biasing EWAS results. We investigated associations between multiple smoking behavioral phenotypes (smoking pack years, smoking duration, smoking start age, and smoking end age) and single site DNAm using linear regressions adjusting for age, sex, race/ethnicity, education, and cell-type proportions in a subsample of individuals who participated in the HRS 2016 Venous Blood Study (N=1,775). DNAm was measured using the Infinium Methylation EPIC BeadChip. All 4 phenotypes had significant associations (FDR < 0.05) with many methylation sites (packyears=6859, smoking duration=6572, start age=11374, quit age=773). There was not much overlap in DNAm sites between the full set of models with only 6 overlapping between all 4. However, the phenotypes packyears and smoking duration showed large overlap (N=3782). Results suggest additional smoking phenotypes beyond current/former/never smoker classification should be included in EWAS analyses to appropriately account for the influence of smoking behaviors on DNAm.
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spelling pubmed-86813062021-12-17 Epigenome Wide Associations of Smoking Behavior in the Health and Retirement Study Fisher, Jonah Mitchell, Colter Meier, Helen Crimmins, Eileen Thyagarajan, Bharat Faul, Jessica Innov Aging Abstracts DNA methylation (DNAm) is an increasingly popular biomarker of health and aging outcomes. Smoking behaviors have a significant and well documented correlation with methylation signatures within the epigenome and are important confounding variables to account for in epigenome-wide association studies (EWAS). However, the common classification of individuals as ‘current’, ‘former’, and ‘never’ smokers may miss crucial DNAm patterns associated with other smoking behaviors such as duration, intensity, and frequency of cigarette smoking, resulting in an underestimation of the contribution of smoking behaviors to DNAm and potentially biasing EWAS results. We investigated associations between multiple smoking behavioral phenotypes (smoking pack years, smoking duration, smoking start age, and smoking end age) and single site DNAm using linear regressions adjusting for age, sex, race/ethnicity, education, and cell-type proportions in a subsample of individuals who participated in the HRS 2016 Venous Blood Study (N=1,775). DNAm was measured using the Infinium Methylation EPIC BeadChip. All 4 phenotypes had significant associations (FDR < 0.05) with many methylation sites (packyears=6859, smoking duration=6572, start age=11374, quit age=773). There was not much overlap in DNAm sites between the full set of models with only 6 overlapping between all 4. However, the phenotypes packyears and smoking duration showed large overlap (N=3782). Results suggest additional smoking phenotypes beyond current/former/never smoker classification should be included in EWAS analyses to appropriately account for the influence of smoking behaviors on DNAm. Oxford University Press 2021-12-17 /pmc/articles/PMC8681306/ http://dx.doi.org/10.1093/geroni/igab046.2509 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstracts
Fisher, Jonah
Mitchell, Colter
Meier, Helen
Crimmins, Eileen
Thyagarajan, Bharat
Faul, Jessica
Epigenome Wide Associations of Smoking Behavior in the Health and Retirement Study
title Epigenome Wide Associations of Smoking Behavior in the Health and Retirement Study
title_full Epigenome Wide Associations of Smoking Behavior in the Health and Retirement Study
title_fullStr Epigenome Wide Associations of Smoking Behavior in the Health and Retirement Study
title_full_unstemmed Epigenome Wide Associations of Smoking Behavior in the Health and Retirement Study
title_short Epigenome Wide Associations of Smoking Behavior in the Health and Retirement Study
title_sort epigenome wide associations of smoking behavior in the health and retirement study
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8681306/
http://dx.doi.org/10.1093/geroni/igab046.2509
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