Epigenetic mechanisms of lung carcinogenesis involve differentially methylated CpG sites beyond those associated with smoking
Petrovic, Dusan; Bodinier, Barbara; Dagnino, Sonia; Whitaker, Matthew; Karimi, Maryam; Campanella, Gianluca; Haugdahl Nøst, Therese; Polidoro, Silvia; Palli, Domenico; Krogh, Vittorio; Tumino, Rosario; Sacerdote, Carlotta; Panico, Salvatore; Lund, Eiliv; Dugué, Pierre Antoine; Giles, Graham G.; Severi, Gianluca; Southey, Melissa; Vineis, Paolo; Stringhini, Silvia; Bochud, Murielle; Sandanger, Torkjel M.; Vermeulen, Roel C.H.; Guida, Florence; Chadeau-Hyam, Marc
(2022) European Journal of Epidemiology, volume 37, pp. 629 - 640
(Article)
Abstract
Smoking-related epigenetic changes have been linked to lung cancer, but the contribution of epigenetic alterations unrelated to smoking remains unclear. We sought for a sparse set of CpG sites predicting lung cancer and explored the role of smoking in these associations. We analysed CpGs in relation to lung cancer in
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participants from two nested case–control studies, using (LASSO)-penalised regression. We accounted for the effects of smoking using known smoking-related CpGs, and through conditional-independence network. We identified 29 CpGs (8 smoking-related, 21 smoking-unrelated) associated with lung cancer. Models additionally adjusted for Comprehensive Smoking Index-(CSI) selected 1 smoking-related and 49 smoking-unrelated CpGs. Selected CpGs yielded excellent discriminatory performances, outperforming information provided by CSI only. Of the 8 selected smoking-related CpGs, two captured lung cancer-relevant effects of smoking that were missed by CSI. Further, the 50 CpGs identified in the CSI-adjusted model complementarily explained lung cancer risk. These markers may provide further insight into lung cancer carcinogenesis and help improving early identification of high-risk patients.
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Keywords: DNA methylation, Lung cancer, Partial correlation network, Smoking, Variable selection, Epidemiology
ISSN: 0393-2990
Publisher: Springer Netherlands
Note: Funding Information: This work was supported by Cancer Research UK Population Research Committee ‘Mechanomics’ project Grant (Grant #22184 to MC-H). The NOWAC post-genome cohort study was funded by the ERC advanced Grant; Transcriptomics in Cancer Epidemiology (ERC-2008-AdG-232997). MC-H, FG, KS-B, THN, MJ, and TS acknowledge support from the Research Council of Norway (Id-Lung project FRIPRO 262111 to TS). MC-H, RV, acknowledge support from the H2020-EXPANSE project (Horizon 2020 Grant No 874627 to RV). SD acknowledges support to Horizon 2020 Marie Skłodowska-Curie fellowship EXACT Identifying biomarkers of EXposure leading to Lung Cancer with AdduCTomics (Grant # 708392 to SD). DP was supported by a Grant from the Swiss National Science Foundation (SNSF DocMobility Grant P1LAP3_178061). BB received a PhD studentship from the MRC Centre for Environment and Health. Publisher Copyright: © 2022, The Author(s).
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