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Smoking-associated DNA methylation markers predict lung cancer incidence

BACKGROUND: Newly established blood DNA methylation markers that are strongly associated with smoking might open new avenues for lung cancer (LC) screening. We aimed to assess the performance of the top hits from previous epigenome-wide association studies in prediction of LC incidence. In a prospec...

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Autores principales: Zhang, Yan, Elgizouli, Magdeldin, Schöttker, Ben, Holleczek, Bernd, Nieters, Alexandra, Brenner, Hermann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5123284/
https://www.ncbi.nlm.nih.gov/pubmed/27924164
http://dx.doi.org/10.1186/s13148-016-0292-4
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author Zhang, Yan
Elgizouli, Magdeldin
Schöttker, Ben
Holleczek, Bernd
Nieters, Alexandra
Brenner, Hermann
author_facet Zhang, Yan
Elgizouli, Magdeldin
Schöttker, Ben
Holleczek, Bernd
Nieters, Alexandra
Brenner, Hermann
author_sort Zhang, Yan
collection PubMed
description BACKGROUND: Newly established blood DNA methylation markers that are strongly associated with smoking might open new avenues for lung cancer (LC) screening. We aimed to assess the performance of the top hits from previous epigenome-wide association studies in prediction of LC incidence. In a prospective nested case-control study, DNA methylation at AHRR (cg05575921), 6p21.33 (cg06126421), and F2RL3 (cg03636183) were measured by pyrosequencing in baseline whole blood samples of 143 incident LC cases identified during 11 years of follow-up and 457 age- and sex-matched controls without diagnosis of LC until the end of follow-up. The individual and joint associations of the 3 markers with LC risk were estimated by logistic regression, adjusted for potential confounders including smoking status and cigarette pack-years. The predictive performance was evaluated for both the individual markers and their combinations derived from multiple algorithms. RESULTS: Pronounced demethylation of all 3 markers was observed at baseline among cases compared to controls. Risk of developing LC increased with decreasing DNA methylation levels, with adjusted ORs (95% CI) of 15.86 (4.18–60.17), 8.12 (2.69–4.48), and 10.55 (3.44–32.31), respectively, for participants in the lowest quartile of AHRR, 6p21.33, and F2RL3 compared to participants in the highest 2 quartiles of each site among controls. The individual 3 markers exhibited similar accuracy in predicting LC incidence, with AUCs ranging from 0.79 to 0.81. Combination of the 3 markers did not improve the predictive performance (AUC = 0.80). The individual markers or their combination outperformed self-reported smoking exposure particularly in light smokers. No variation in risk prediction was identified with respect to age, follow-up time, and histological subtypes. CONCLUSIONS: AHRR, 6p21.33, and F2RL3 methylation in blood DNA are predictive for LC development, which might be useful for identification of risk groups for further specific screening, such as CT examination. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13148-016-0292-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-51232842016-12-06 Smoking-associated DNA methylation markers predict lung cancer incidence Zhang, Yan Elgizouli, Magdeldin Schöttker, Ben Holleczek, Bernd Nieters, Alexandra Brenner, Hermann Clin Epigenetics Research BACKGROUND: Newly established blood DNA methylation markers that are strongly associated with smoking might open new avenues for lung cancer (LC) screening. We aimed to assess the performance of the top hits from previous epigenome-wide association studies in prediction of LC incidence. In a prospective nested case-control study, DNA methylation at AHRR (cg05575921), 6p21.33 (cg06126421), and F2RL3 (cg03636183) were measured by pyrosequencing in baseline whole blood samples of 143 incident LC cases identified during 11 years of follow-up and 457 age- and sex-matched controls without diagnosis of LC until the end of follow-up. The individual and joint associations of the 3 markers with LC risk were estimated by logistic regression, adjusted for potential confounders including smoking status and cigarette pack-years. The predictive performance was evaluated for both the individual markers and their combinations derived from multiple algorithms. RESULTS: Pronounced demethylation of all 3 markers was observed at baseline among cases compared to controls. Risk of developing LC increased with decreasing DNA methylation levels, with adjusted ORs (95% CI) of 15.86 (4.18–60.17), 8.12 (2.69–4.48), and 10.55 (3.44–32.31), respectively, for participants in the lowest quartile of AHRR, 6p21.33, and F2RL3 compared to participants in the highest 2 quartiles of each site among controls. The individual 3 markers exhibited similar accuracy in predicting LC incidence, with AUCs ranging from 0.79 to 0.81. Combination of the 3 markers did not improve the predictive performance (AUC = 0.80). The individual markers or their combination outperformed self-reported smoking exposure particularly in light smokers. No variation in risk prediction was identified with respect to age, follow-up time, and histological subtypes. CONCLUSIONS: AHRR, 6p21.33, and F2RL3 methylation in blood DNA are predictive for LC development, which might be useful for identification of risk groups for further specific screening, such as CT examination. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13148-016-0292-4) contains supplementary material, which is available to authorized users. BioMed Central 2016-11-25 /pmc/articles/PMC5123284/ /pubmed/27924164 http://dx.doi.org/10.1186/s13148-016-0292-4 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zhang, Yan
Elgizouli, Magdeldin
Schöttker, Ben
Holleczek, Bernd
Nieters, Alexandra
Brenner, Hermann
Smoking-associated DNA methylation markers predict lung cancer incidence
title Smoking-associated DNA methylation markers predict lung cancer incidence
title_full Smoking-associated DNA methylation markers predict lung cancer incidence
title_fullStr Smoking-associated DNA methylation markers predict lung cancer incidence
title_full_unstemmed Smoking-associated DNA methylation markers predict lung cancer incidence
title_short Smoking-associated DNA methylation markers predict lung cancer incidence
title_sort smoking-associated dna methylation markers predict lung cancer incidence
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5123284/
https://www.ncbi.nlm.nih.gov/pubmed/27924164
http://dx.doi.org/10.1186/s13148-016-0292-4
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