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Abstract
DNA methylation offers an objective method to assess the impact of smoking. In this work, we conduct a Bayesian EWAS of smoking pack years (n = 17,865, ~850k sites, Illumina EPIC array) and extend it by analysing whole genome data of smokers and non-smokers from Generation Scotland (n = 46, ~4–21 million sites via TWIST and Oxford Nanopore sequencing). We develop mCigarette, an epigenetic biomarker of smoking, and test it in two British cohorts. Results of brain- and blood-based EWAS (nbrain=14, nblood = 882, >450k sites, Illumina arrays) reveal several loci with near-perfect discrimination of smoking status, but which do not overlap across tissues. Furthermore, we perform a GWAS of epigenetic smoking, identifying several smoking-related loci. Overall, we improve smoking-related biomarker accuracy and enhance the understanding of the effects of smoking by integrating DNA methylation data from multiple tissues and cohorts.
Original language | English |
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Article number | 3210 |
Number of pages | 13 |
Journal | Nature Communications |
Volume | 16 |
Issue number | 1 |
DOIs | |
Publication status | Published - 4 Apr 2025 |
Bibliographical note
Publisher Copyright:© The Author(s) 2025.
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8074 (C18281/A29019) ICEP2 - Programme Award: Towards improved casual evidence and enhanced prediction of cancer risk and survival
Martin, R. M. (Principal Investigator)
1/10/20 → 30/09/25
Project: Research