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Tobacco smoking leads to extensive genome-wide changes in DNA methylation.

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TLDR
The results of this study confirm the broad effect of tobacco smoking on the human organism, but also show that quitting tobacco smoking presumably allows regaining the DNA methylation state of never smokers.
Abstract
Environmental factors such as tobacco smoking may have long-lasting effects on DNA methylation patterns, which might lead to changes in gene expression and in a broader context to the development or progression of various diseases. We conducted an epigenome-wide association study (EWAs) comparing current, former and never smokers from 1793 participants of the population-based KORA F4 panel, with replication in 479 participants from the KORA F3 panel, carried out by the 450K BeadChip with genomic DNA obtained from whole blood. We observed wide-spread differences in the degree of site-specific methylation (with p-values ranging from 9.31E-08 to 2.54E-182) as a function of tobacco smoking in each of the 22 autosomes, with the percent of variance explained by smoking ranging from 1.31 to 41.02. Depending on cessation time and pack-years, methylation levels in former smokers were found to be close to the ones seen in never smokers. In addition, methylation-specific protein binding patterns were observed for cg05575921 within AHRR, which had the highest level of detectable changes in DNA methylation associated with tobacco smoking (-24.40% methylation; p = 2.54E-182), suggesting a regulatory role for gene expression. The results of our study confirm the broad effect of tobacco smoking on the human organism, but also show that quitting tobacco smoking presumably allows regaining the DNA methylation state of never smokers.

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References
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Journal ArticleDOI

Projections of Global Mortality and Burden of Disease from 2002 to 2030

TL;DR: These projections represent a set of three visions of the future for population health, based on certain explicit assumptions, which enable us to appreciate better the implications for health and health policy of currently observed trends, and the likely impact of fairly certain future trends.
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lumi: a pipeline for processing Illumina microarray

TL;DR: The lumi package as discussed by the authors is a Bioconductor package designed to process the Illumina microarray data, which includes data input, quality control, variance stabilization, normalization and gene annotation portions.
Journal ArticleDOI

Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis

TL;DR: The Beta-value has a more intuitive biological interpretation, but the M-value is more statistically valid for the differential analysis of methylation levels, and is recommended for conducting differential methylation analysis and including the beta-value statistics when reporting the results to investigators.
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