A blood- and brain-based EWAS of smoking

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

doi:10.1038/s41467-025-58357-6

A blood- and brain-based EWAS of smoking

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

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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
Article number	3210
Journal	Nature Communications
Volume	16
Issue number	1
DOIs	https://doi.org/10.1038/s41467-025-58357-6 https://doi.org/10.1038/s41467-025-58357-6
Publication status	Published - 4 Apr 2025

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A blood and brain based EWAS of smokingFinal published version, 1.87 MBLicence: Creative Commons: Attribution (CC-BY)

https://www.nature.com/articles/s41467-025-58357-6

3 Active
6 Finished

The Lothian Birth Cohort 1936 Waves 6 and 7
Cox, S. (Principal Investigator), Bastin, M. (Co-investigator), Munoz Maniega, S. (Co-investigator), Shenkin, S. (Co-investigator) & Wardlaw, J. (Co-investigator)
BBSRC
1/04/22 → 28/02/26
Project: Research
Exploiting genomic approaches to identify the environmental basis of depression
McIntosh, A. (Principal Investigator)
Wellcome Trust (Rcl)
1/06/21 → 31/05/26
Project: Research
Factors of biological ageing: does it all go together when it goes?
Cox, S. (Principal Investigator)
Wellcome Trust (Rcl)
1/05/21 → 30/04/26
Project: Research

Genetics Core, Edinburgh Clinical Research Facility
Murphy, L. (Manager), Fawkes, A. (Other), Hafezi, K. (Other), Clark, R. (Other), MacCallum, A. (Other), Aitken, E. (Other) & Macgillivray, L. (Other)
Deanery of Clinical Sciences
Facility/equipment: Facility

Cite this

Chybowska, A. D., Bernabeu, E., Yousefi, P., Suderman, M., Hillary, R. F., Clark, R., MacGillivray, L., Murphy, L., Harris, S. E., Corley, J., Campbell, A., Spires-Jones, T. L., McCartney, D. L., Cox, S. R., Price, J. F., Evans, K. L., & Marioni, R. E. (2025). A blood- and brain-based EWAS of smoking. Nature Communications, 16(1), Article 3210 . https://doi.org/10.1038/s41467-025-58357-6, https://doi.org/10.1038/s41467-025-58357-6

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title = "A blood- and brain-based EWAS of smoking",

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.",

author = "Chybowska, {Aleksandra D.} and Elena Bernabeu and Paul Yousefi and Matthew Suderman and Hillary, {Robert F.} and Richard Clark and Louise MacGillivray and Lee Murphy and Harris, {Sarah E.} and Janie Corley and Archie Campbell and Spires-Jones, {Tara L.} and McCartney, {Daniel L.} and Cox, {Simon R.} and Price, {Jackie F.} and Evans, {Kathryn L.} and Marioni, {Riccardo E.}",

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doi = "10.1038/s41467-025-58357-6",

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Chybowska, AD, Bernabeu, E, Yousefi, P, Suderman, M, Hillary, RF , Clark, R , MacGillivray, L , Murphy, L , Harris, SE , Corley, J , Campbell, A , Spires-Jones, TL , McCartney, DL , Cox, SR , Price, JF , Evans, KL & Marioni, RE 2025, 'A blood- and brain-based EWAS of smoking', Nature Communications, vol. 16, no. 1, 3210 . https://doi.org/10.1038/s41467-025-58357-6, https://doi.org/10.1038/s41467-025-58357-6

TY - JOUR

T1 - A blood- and brain-based EWAS of smoking

AU - Chybowska, Aleksandra D.

AU - Bernabeu, Elena

AU - Yousefi, Paul

AU - Suderman, Matthew

AU - Hillary, Robert F.

AU - Clark, Richard

AU - MacGillivray, Louise

AU - Murphy, Lee

AU - Harris, Sarah E.

AU - Corley, Janie

AU - Campbell, Archie

AU - Spires-Jones, Tara L.

AU - McCartney, Daniel L.

AU - Cox, Simon R.

AU - Price, Jackie F.

AU - Evans, Kathryn L.

AU - Marioni, Riccardo E.

PY - 2025/4/4

Y1 - 2025/4/4

N2 - 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.

AB - 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.

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DO - 10.1038/s41467-025-58357-6

M3 - Article

SN - 2041-1723

VL - 16

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 3210

ER -

A blood- and brain-based EWAS of smoking

Abstract

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Projects

The Lothian Birth Cohort 1936 Waves 6 and 7

Exploiting genomic approaches to identify the environmental basis of depression

Factors of biological ageing: does it all go together when it goes?

Equipment

Genetics Core, Edinburgh Clinical Research Facility

Cite this