Methylation scores for smoking, alcohol consumption, and body mass index and risk of seven types of cancer

Author:

Dugué Pierre-AntoineORCID,Yu Chenglong,Hodge Allison M,Wong Ee Ming,Joo JiHoon E,Jung Chol-Hee,Schmidt Daniel,Makalic Enes,Buchanan Daniel DORCID,Severi Gianluca,English Dallas R,Hopper John L,Milne Roger L,Giles Graham G,Southey Melissa C

Abstract

ABSTRACTMethylation marks of exposure to health risk factors may be useful markers of cancer risk as they might better capture current and past exposures than questionnaires, and reflect different individual responses to exposure. We used data from seven case-control studies nested within the Melbourne Collaborative Cohort Study of blood DNA methylation and risk of colorectal, gastric, kidney, lung, prostate and urothelial cancer, and B-cell lymphoma (N cases=3,123). Methylation scores (MS) for smoking, body mass index (BMI), and alcohol consumption were calculated based on published data as weighted averages of methylation values. Rate ratios (RR) and 95% confidence intervals for association with cancer risk were estimated using conditional logistic regression and expressed per standard deviation increase of the MS, with and without adjustment for health-related confounders. The contribution of MS to discriminate cases from controls was evaluated using the area under the curve (AUC). After confounder adjustment, we observed: large associations (RR∼1.5-1.7) with lung cancer risk for smoking MS; moderate associations (RR∼1.2-1.3) with urothelial cancer risk for smoking MS and with mature B-cell neoplasm risk for BMI and alcohol MS; moderate to small associations (RR∼1.1-1.2) for BMI and alcohol MS with several cancer types and cancer overall. Generally small AUC increases were observed after inclusion of several MS in the same model (colorectal, gastric, kidney, urothelial cancers: +3%; lung cancer: +7%; B-cell neoplasms: +8%). Methylation scores for smoking, BMI, and alcohol consumption show independent associations with cancer risk, and may provide some improvements in risk prediction.

Publisher

Cold Spring Harbor Laboratory

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