1. Smoking Methylation Marks for Prediction of Urothelial Cancer Risk
- Author
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Damien M Bolton, Theodore M. Brasky, Maree Brinkman, Melissa C. Southey, Julie K. Bassett, Roger L. Milne, Ee Ming Wong, Jihoon E. Joo, Parveen Bhatti, Aladdin H. Shadyab, Chenglong Yu, Dallas R. English, Pierre Antoine Dugué, Kristina M. Jordahl, Graham G. Giles, John L. Hopper, Enes Makalic, Lesley Tinker, Daniel F. Schmidt, and Anthony Longano
- Subjects
Oncology ,medicine.medical_specialty ,education.field_of_study ,Epidemiology ,business.industry ,Population ,Confounding ,Area under the curve ,Odds ratio ,Methylation ,Internal medicine ,Cohort ,DNA methylation ,medicine ,education ,business ,Cohort study - Abstract
Background: Self-reported information may not accurately capture smoking exposure. We aimed to evaluate whether smoking-associated DNA methylation markers improve urothelial cell carcinoma (UCC) risk prediction. Methods: Conditional logistic regression was used to assess associations between blood-based methylation and UCC risk using two matched case–control samples: 404 pairs from the Melbourne Collaborative Cohort Study (MCCS) and 440 pairs from the Women's Health Initiative (WHI) cohort. Results were pooled using fixed-effects meta-analysis. We developed methylation-based predictors of UCC and evaluated their prediction accuracy on two replication data sets using the area under the curve (AUC). Results: The meta-analysis identified associations (P < 4.7 × 10−5) for 29 of 1,061 smoking-associated methylation sites, but these were substantially attenuated after adjustment for self-reported smoking. Nominally significant associations (P < 0.05) were found for 387 (36%) and 86 (8%) of smoking-associated markers without/with adjustment for self-reported smoking, respectively, with same direction of association as with smoking for 387 (100%) and 79 (92%) markers. A Lasso-based predictor was associated with UCC risk in one replication data set in MCCS [N = 134; odds ratio per SD (OR) = 1.37; 95% CI, 1.00–1.90] after confounder adjustment; AUC = 0.66, compared with AUC = 0.64 without methylation information. Limited evidence of replication was found in the second testing data set in WHI (N = 440; OR = 1.09; 95% CI, 0.91–1.30). Conclusions: Combination of smoking-associated methylation marks may provide some improvement to UCC risk prediction. Our findings need further evaluation using larger data sets. Impact: DNA methylation may be associated with UCC risk beyond traditional smoking assessment and could contribute to some improvements in stratification of UCC risk in the general population.
- Published
- 2021
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