Year: 2021
Type: article
Study design: Observational 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, N =404 pairs from the Melbourne Collaborative Cohort Study (MCCS) and N =440 pairs from the Women’s Health Initiative (WHI) cohort, respectively. Results were pooled using fixed-effects meta-analysis. We developed methylation-based predictors of UCC and evaluated their prediction accuracy on two replication datasets 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 dataset 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 dataset 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 datasets. 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.
Authors: Chenglong Yu, Kristina M. Jordahl, Julie K. Bassett, Jihoon Eric Joo, Ee Ming Wong, Maree Brinkman, Daniel Schmidt, Damien Bolton, Enes Makalic, Theodore M. Brasky, Aladdin H. Shadyab, Lesley Tinker, Anthony Longano, John L. Hopper, Dallas R. English, Roger L. Milne, Parveen Bhatti, Melissa C. Southey, Graham G. Giles, Pierre-Antoine Dugué
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Funders: U.S. Department of Health and Human Services, Women's Health Initiative, Brigham and Women's Hospital, Ohio State University, Wake Forest University, University of Pittsburgh, University of Nevada, Reno, MedStar Health Research Institute, National Institutes of Health, University at Buffalo, Medical Research Council, National Health and Medical Research Council, Cancer Council Victoria, National Heart, Lung, and Blood Institute
Awards: G1094733267, G1211708387, G2271866160, G2325632269, G3729156826, G3827278403, G4122490874, G4499735890, G554960330, G571830633, G5777902738, Methylation and the risk of urothelial cell cancer, G6238440229, G6374953548, Epidemiology of Chronic Disease, Health Interventions and DNA Studies, G6894818919, G7159829730, G7348868804, G7400227903, G7821233859, G796413602, G8123808567, G8566225511, Risk and prognostic factors for breast cancer of different immunohistochemical subtypes, G8615730155, G8836210513, Increasing precision in epidemiological exposure assessment by integrating genetic and epigenetic data
OpenAlex ID: W3199925472