Dataset Information

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

ABSTRACT: 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 AUCcrossvalidation 0.925?±?0.021, AUCexternalvalidation0.914), 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.

SUBMITTER: Maas SCE

PROVIDER: S-EPMC6861351 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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

Maas Silvana C E SCE Vidaki Athina A Wilson Rory R Teumer Alexander A Liu Fan F van Meurs Joyce B J JBJ Uitterlinden André G AG Boomsma Dorret I DI de Geus Eco J C EJC Willemsen Gonneke G van Dongen Jenny J van der Kallen Carla J H CJH Slagboom P Eline PE Beekman Marian M van Heemst Diana D van den Berg Leonard H LH Duijts Liesbeth L Jaddoe Vincent W V VWV Ladwig Karl-Heinz KH Kunze Sonja S Peters Annette A Ikram M Arfan MA Grabe Hans J HJ Felix Janine F JF Waldenberger Melanie M Franco Oscar H OH Ghanbari Mohsen M Kayser Manfred M

European journal of epidemiology 20190907 11

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 suit ...[more]

PMID: 31494793

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Project description:BACKGROUND: The immense diagnostic potential of human plasma has prompted great interest and effort in cataloging its contents, exemplified by the Human Proteome Organization (HUPO) Plasma Proteome Project (PPP) pilot project. Due to challenges in obtaining a reliable blood plasma protein list, HUPO later re-analysed their own original dataset with a more stringent statistical treatment that resulted in a much reduced list of high confidence (at least 95%) proteins compared with their original findings. In order to facilitate the discovery of novel biomarkers in the future and to realize the full diagnostic potential of blood plasma, we feel that there is still a need for an ultra-high confidence reference list (at least 99% confidence) of blood plasma proteins. METHODS: To address the complexity and dynamic protein concentration range of the plasma proteome, we employed a linear ion-trap-Fourier transform (LTQ-FT) and a linear ion trap-Orbitrap (LTQ-Orbitrap) for mass spectrometry (MS) analysis. Both instruments allow the measurement of peptide masses in the low ppm range. Furthermore, we employed a statistical score that allows database peptide identification searching using the products of two consecutive stages of tandem mass spectrometry (MS3). The combination of MS3 with very high mass accuracy in the parent peptide allows peptide identification with orders of magnitude more confidence than that typically achieved. RESULTS: Herein we established a high confidence set of 697 blood plasma proteins and achieved a high 'average sequence coverage' of more than 14 peptides per protein and a median of 6 peptides per protein. All proteins annotated as belonging to the immunoglobulin family as well as all hypothetical proteins whose peptides completely matched immunoglobulin sequences were excluded from this protein list. We also compared the results of using two high-end MS instruments as well as the use of various peptide and protein separation approaches. Furthermore, we characterized the plasma proteins using cellular localization information, as well as comparing our list of proteins to data from other sources, including the HUPO PPP dataset. CONCLUSION: Superior instrumentation combined with rigorous validation criteria gave rise to a set of 697 plasma proteins in which we have very high confidence, demonstrated by an exceptionally low false peptide identification rate of 0.29%.

Project description:BACKGROUND:Lung cancer is the leading cause of cancer-related death. While cigarette smoking is the primary cause of this malignancy, risk differs across racial/ethnic groups. For the same number of cigarettes smoked, Native Hawaiians compared to whites are at greater risk and Japanese Americans are at lower risk of developing lung cancer. DNA methylation of specific CpG sites (e.g., in AHRR and F2RL3) is the most common blood epigenetic modification associated with smoking status. However, the influence of internal smoking dose, measured by urinary nicotine equivalents (NE), on DNA methylation in current smokers has not been investigated, nor has a study evaluated whether for the same smoking dose, circulating leukocyte DNA methylation patterns differ by race. METHODS:We conducted an epigenome-wide association study (EWAS) of NE in 612 smokers from three racial/ethnic groups: whites (n = 204), Native Hawaiians (n = 205), and Japanese Americans (n = 203). Genome-wide DNA methylation profiling of blood leukocyte DNA was measured using the Illumina 450K BeadChip array. Average ? value, the ratio of signal from a methylated probe relative to the sum of the methylated and unmethylated probes at that CpG, was the dependent variables in linear regression models adjusting for age, sex, race (for pan-ethnic analysis), and estimated cell-type distribution. RESULTS:We found that NE was significantly associated with six differentially methylated CpG sites (Bonferroni corrected p < 1.48 × 10-7): four in or near the FOXK2, PBX1, FNDC7, and FUBP3 genes and two in non-annotated genetic regions. Higher levels of NE were associated with increasing methylation beta-valuesin all six sites. For all six CpG sites, the association was only observed in Native Hawaiians, suggesting that the influence of smoking dose on DNA methylation patterns is heterogeneous across race/ethnicity (p interactions < 8.8 × 10-8). We found two additional CpG sites associated with NE in only Native Hawaiians. CONCLUSIONS:In conclusion, internal smoking dose was associated with increased DNA methylation in circulating leukocytes at specific sites in Native Hawaiian smokers but not in white or Japanese American smokers.

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Project description:Background:Smoking has been reported to be associated with peripheral blood DNA methylation, but the causal aspects of the association have rarely been investigated. We aimed to investigate the association and underlying causation between smoking and blood methylation. Methods:The methylation profile of DNA from the peripheral blood, collected as dried blood spots stored on Guthrie cards, was measured for 479 Australian women including 66 monozygotic twin pairs, 66 dizygotic twin pairs, and 215 sisters of twins from 130 twin families using the Infinium HumanMethylation450K BeadChip array. Linear regression was used to estimate associations between methylation at ~?410,000 cytosine-guanine dinucleotides (CpGs) and smoking status. A regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess putative causation. Results:At a 5% false discovery rate, 39 CpGs located at 27 loci, including previously reported AHRR, F2RL3, 2q37.1 and 6p21.33, were found to be differentially methylated across never, former and current smokers. For all 39 CpG sites, current smokers had the lowest methylation level. Our study provides the first replication for two previously reported CpG sites, cg06226150 (SLC2A4RG) and cg21733098 (12q24.32). From the ICE FALCON analysis with smoking status as the predictor and methylation score as the outcome, a woman's methylation score was associated with her co-twin's smoking status, and the association attenuated towards the null conditioning on her own smoking status, consistent with smoking status causing changes in methylation. To the contrary, using methylation score as the predictor and smoking status as the outcome, a woman's smoking status was not associated with her co-twin's methylation score, consistent with changes in methylation not causing smoking status. Conclusions:For middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with smoking. Our study suggests that smoking has a causal effect on peripheral blood DNA methylation, but not vice versa.

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

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

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