Blood DNA methylation signatures of lifestyle exposures: tobacco and alcohol consumption.

Autor: Chamberlain JD; Department of Epidemiology and Health Systems (DESS), University Center for General Medicine and Public Health (Unisanté), Route de la Corniche 10, 1010, Lausanne, Switzerland. jonviea.chamberlain@unisante.ch., Nusslé S; Genknowme, Epalinges, Switzerland., Chapatte L; Genknowme, Epalinges, Switzerland., Kinnaer C; Genknowme, Epalinges, Switzerland., Petrovic D; Department of Epidemiology and Health Systems (DESS), University Center for General Medicine and Public Health (Unisanté), Route de la Corniche 10, 1010, Lausanne, Switzerland., Pradervand S; Vital-IT Group, Swiss Institute of Bioinformatics, Lausanne, Switzerland.; Genomic Technologies Facility, University of Lausanne, Lausanne, Switzerland., Bochud M; Department of Epidemiology and Health Systems (DESS), University Center for General Medicine and Public Health (Unisanté), Route de la Corniche 10, 1010, Lausanne, Switzerland., Harris SE; Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK., Corley J; Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK., Cox SR; Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK., Gonseth Nusslé S; Department of Epidemiology and Health Systems (DESS), University Center for General Medicine and Public Health (Unisanté), Route de la Corniche 10, 1010, Lausanne, Switzerland.; Genknowme, Epalinges, Switzerland.
Jazyk: angličtina
Zdroj: Clinical epigenetics [Clin Epigenetics] 2022 Nov 28; Vol. 14 (1), pp. 155. Date of Electronic Publication: 2022 Nov 28.
DOI: 10.1186/s13148-022-01376-7
Abstrakt: Background: Smoking and alcohol consumption may compromise health by way of epigenetic modifications. Epigenetic signatures of alcohol and tobacco consumption could provide insights into the reversibility of phenotypic changes incurred with differing levels of lifestyle exposures. This study describes and validates two novel epigenetic signatures of tobacco (EpiTob) and alcohol (EpiAlc) consumption and investigates their association with disease outcomes.
Methods: The epigenetic signatures, EpiTob and EpiAlc, were developed using data from the Swiss Kidney Project on Genes in Hypertension (SKIPOGH) (N = 689). Epigenetic and phenotypic data available from the 1921 (N = 550) and 1936 (N = 1091) Lothian Birth Cohort (LBC) studies, and two publicly available datasets on GEO Accession (GSE50660, N = 464; and GSE110043, N = 94) were used to validate the signatures. A multivariable logistic regression model, adjusting for age and sex, was used to assess the association between self-reported tobacco or alcohol consumption and the respective epigenetic signature, as well as to estimate the association between CVD and epigenetic signatures. A Cox proportional hazard model was used to estimate the risk of mortality in association with the EpiTob and EpiAlc signatures.
Results: The EpiTob signature was positively associated with self-reported tobacco consumption for current or never smokers with explained variance ranging from 0.49 (LBC1921) to 0.72 (LBC1936) (pseudo-R 2 ). In the SKIPOGH, LBC1921 and LBC1936 cohorts, the epigenetic signature for alcohol consumption explained limited variance in association with self-reported alcohol status [i.e., non-drinker, moderate drinker, and heavy drinker] (pseudo-R 2  = 0.05, 0.03 and 0.03, respectively), although this improved considerably when measuring self-reported alcohol consumption with standardized units consumed per week (SKIPOGH R 2  = 0.21; LBC1921 R 2  = 0.31; LBC1936 R 2  = 0.41). Both signatures were associated with history of CVD in SKIPOGH and LBC1936, but not in LBC1921. The EpiTob signature was associated with increased risk of all-cause and lung-cancer specific mortality in the 1936 and 1921 LBC cohorts.
Conclusions: This study found the EpiTob and EpiAlc signatures to be well-correlated with self-reported exposure status and associated with long-term health outcomes. Epigenetic signatures of lifestyle exposures may reduce measurement issues and biases and could aid in risk stratification for informing early-stage targeted interventions.
(© 2022. The Author(s).)
Databáze: MEDLINE
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