A blood- and brain-based EWAS of smoking

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 (n<sub>brain</sub>=14, n<sub>blood</sub> = 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.

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Publication Details

Journal
Nature Communications
Published
2025-04-04
DOI
https://doi.org/10.1038/s41467-025-58357-6
Citations
9
Primary Topic
Smoking Behavior and Cessation
Type
article
Field-Weighted Citation Impact
10.48

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article

A blood- and brain-based EWAS of smoking

Lee Murphy, Jackie F. Price, Paul Yousefi, Archie Campbell et al.
9 citations
Nature Communications
Smoking Behavior and Cessation
10.48
article

A blood- and brain-based EWAS of smoking

Lee Murphy, Jackie F. Price, Paul Yousefi, Archie Campbell, Kathryn L. Evans, Sarah E. Harris, Daniel L. McCartney, Matthew Suderman, Aleksandra D. Chybowska, Robert F. Hillary, Richard C. Clark, Riccardo E. Marioni, Simon R. Cox, Louise MacGillivray, Elena Bernabeu, Janie Corley, Tara L. Spires‐Jones
article en
9 citations

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 (n<sub>brain</sub>=14, n<sub>blood</sub> = 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.

Nature CommunicationsVol. 16(1)
NHS Lothian (GB), Western General Hospital (GB), University Hospitals Bristol NHS Foundation Trust (GB), Edinburgh Cancer Research (GB), University of Bristol (GB), UK Dementia Research Institute (GB), Medical Research Council (GB), University of Edinburgh (GB)
John Templeton Foundation, National Alliance for Research on Schizophrenia and Depression, Wellcome Trust, Scottish Government, Royal College of Physicians of Edinburgh, Alzheimer's Society, Cancer Research UK, National Institute for Health and Care Research, Scottish Funding Council, Age UK, University of Edinburgh, University of Bristol, University of Queensland, Centre for Cognitive Ageing and Cognitive Epidemiology, Directorate for Biological Sciences, Chief Scientist Office, Scottish Government Health and Social Care Directorate, Medical Research Council, Biotechnology and Biological Sciences Research Council, Economic and Social Research Council
Openalex Percentile: Top 2%
Smoking Behavior and Cessation
10.48
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