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

Author:

Dugué Pierre‐Antoine123ORCID,Yu Chenglong1,Hodge Allison M.23ORCID,Wong Ee Ming14,Joo JiHoon E.5,Jung Chol‐Hee6,Schmidt Daniel37,Makalic Enes3,Buchanan Daniel D.568ORCID,Severi Gianluca9ORCID,English Dallas R.23ORCID,Hopper John L.3,Milne Roger L.123,Giles Graham G.123,Southey Melissa C.124ORCID

Affiliation:

1. Precision Medicine, School of Clinical Sciences at Monash Health Monash University Clayton Victoria Australia

2. Cancer Epidemiology Division Cancer Council Victoria Melbourne Victoria Australia

3. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health The University of Melbourne Parkville Victoria Australia

4. Department of Clinical Pathology, Melbourne Medical School The University of Melbourne Parkville Victoria Australia

5. Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School The University of Melbourne Parkville Victoria Australia

6. Melbourne Bioinformatics University of Melbourne Parkville Victoria Australia

7. Department of Data Science and AI, Faculty of IT Monash University Clayton Victoria Australia

8. Genomic Medicine and Family Cancer Clinic Royal Melbourne Hospital Parkville Victoria Australia

9. Centre de Recherche en Epidémiologie et Santé des Populations (CESP, Inserm U1018) Facultés de Médecine Universités Paris‐Saclay, UVSQ, Gustave Roussy Villejuif France

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 = 3123). 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 SD 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

Wiley

Subject

Cancer Research,Oncology

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