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Maas, S.C.E.* ; Vidaki, A.* ; Wilson, R. ; Teumer, A.* ; Liu, F.* ; van Meurs, J.B.J.* ; Uitterlinden, A.G.* ; Boomsma, D.I.* ; de Geus, E.J.C.* ; Willemsen, G.* ; van Dongen, J.* ; van der Kallen, C.J.H.* ; Slagboom, P.E.* ; Beekman, M.* ; van Heemst, D.* ; van den Berg, L.H.* ; Duijts, L.* ; Jaddoe, V.W.V.* ; Ladwig, K.-H. ; Kunze, S. ; Peters, A. ; Ikram, M.A.* ; Grabe, H.J.* ; Felix, J.F.* ; Waldenberger, M. ; Franco, O.H.* ; Ghanbari, M.* ; Kayser, M.*

Validated inference of smoking habits from blood with a finite DNA methylation marker set.

Eur. J. Epidemiol. 34, 1055-1074 (2019)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Inferring a person's smoking habit and history from blood is relevant for complementing or replacing self-reports in epidemiological and public health research, and for forensic applications. However, a finite DNA methylation marker set and a validated statistical model based on a large dataset are not yet available. Employing 14 epigenome-wide association studies for marker discovery, and using data from six population-based cohorts (N = 3764) for model building, we identified 13 CpGs most suitable for inferring smoking versus non-smoking status from blood with a cumulative Area Under the Curve (AUC) of 0.901. Internal fivefold cross-validation yielded an average AUC of 0.897 +/- 0.137, while external model validation in an independent population-based cohort (N = 1608) achieved an AUC of 0.911. These 13 CpGs also provided accurate inference of current (average AUC(crossvalidation) 0.925 +/- 0.021, AUC(externalvalidation)0.914), former (0.766 +/- 0.023, 0.699) and never smoking (0.830 +/- 0.019, 0.781) status, allowed inferring pack-years in current smokers (10 pack-years 0.800 +/- 0.068, 0.796; 15 pack-years 0.767 +/- 0.102, 0.752) and inferring smoking cessation time in former smokers (5 years 0.774 +/- 0.024, 0.760; 10 years 0.766 +/- 0.033, 0.764; 15 years 0.767 +/- 0.020, 0.754). Model application to children revealed highly accurate inference of the true non- smoking status (6 years of age: accuracy 0.994, N = 355; 10 years: 0.994, N = 309), suggesting prenatal and passive smoking exposure having no impact on model applications in adults. The finite set of DNA methylation markers allow accurate inference of smoking habit, with comparable accuracy as plasma cotinine use, and smoking history from blood, which we envision becoming useful in epidemiology and public health research, and in medical and forensic applications.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Epigenetics ; Dna Methylation ; Smoking Inference ; Epidemiology ; Forensics; Epigenome-wide Association; Self-reported Smoking; Cigarette-smoking; Maternal Smoking; Tobacco-smoking; Exposure; Cotinine; Biomarker; Newborns; Hypomethylation
Sprache englisch
Veröffentlichungsjahr 2019
HGF-Berichtsjahr 2019
ISSN (print) / ISBN 0393-2990
e-ISSN 1573-7284
Zeitschrift European Journal of Epidemiology
Quellenangaben Band: 34, Heft: 11, Seiten: 1055-1074 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Van Godewijckstraat 30, 3311 Gz Dordrecht, Netherlands
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Epidemiology (EPI)
POF Topic(s) 30202 - Environmental Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-504091-001
G-504000-003
G-504000-010
DOI 10.1007/s10654-019-00555-w
WOS ID WOS:000514858700006
Scopus ID 85071837008
PubMed ID 31494793
Erfassungsdatum 2019-10-01
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