Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228?951 Women of European Descent
| Autor: | Joe Dennis, Xiao-Ou Shu, Thilo Dörk, Yaohua Yang, Wei Zheng, Susan L. Neuhausen, Peter Kraft, Georgia Chenevix-Trench, Qin Wang, Paul D.P. Pharoah, Kyriaki Michailidou, Jirong Long, Douglas F. Easton, Manjeet K. Bolla, Irene L. Andrulis, Daniele Campa, Manuela Gago-Dominguez, Jacques Simard, Xiang Shu, Håkan Olsson, Xingyi Guo, Bingshan Li, Antoinette Hollestelle, Qiuyin Cai, Hermann Brenner, Fei Ye, Lang Wu, Artitaya Lophatananon, Dale P. Sandler, Jose E. Castelao, Kenneth Muir |
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| Přispěvatelé: | Medical Oncology |
| Rok vydání: | 2020 |
| Předmět: |
Oncology
Risk Cancer Research medicine.medical_specialty Genome-wide association study Breast Neoplasms Polymorphism Single Nucleotide White People Transcriptome 03 medical and health sciences 0302 clinical medicine Breast cancer SDG 3 - Good Health and Well-being Predictive Value of Tests Internal medicine Biomarkers Tumor Medicine Humans Genetic Predisposition to Disease European Continental Ancestry Group/genetics Gene 030304 developmental biology 0303 health sciences Models Statistical Models Genetic business.industry Breast Neoplasms/epidemiology Case-control study Articles DNA Methylation medicine.disease 3. Good health CpG site 030220 oncology & carcinogenesis Case-Control Studies DNA methylation Medical genetics CpG Islands Female Biomarkers Tumor/genetics business Genome-Wide Association Study |
| Zdroj: | Journal of the National Cancer Institute, 112, 295-304. Oxford University Press J Natl Cancer Inst Yang, Y, Wu, L, Shu, X-O, Cai, Q, Shu, X, Li, B, Guo, X, Ye, F, Michailidou, K, Bolla, M K, Wang, Q, Dennis, J, Andrulis, I L, Brenner, H, Chenevix-Trench, G, Campa, D, Castelao, J E, Gago-Dominguez, M, Dörk, T, Hollestelle, A, Lophatananon, A, Muir, K, Neuhausen, S L, Olsson, H, Sandler, D P, Simard, J, Kraft, P, Pharoah, P D P, Easton, D F, Zheng, W & Long, J 2020, ' Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk : Data From 228 951 Women of European Descent ', Journal of the National Cancer Institute, vol. 112, no. 3, pp. 295-304 . https://doi.org/10.1093/jnci/djz109 JNCI: Journal of the National Cancer Institute |
| ISSN: | 0027-8874 |
| DOI: | 10.1093/jnci/djz109 |
| Popis: | Background DNA methylation plays a critical role in breast cancer development. Previous studies have identified DNA methylation marks in white blood cells as promising biomarkers for breast cancer. However, these studies were limited by low statistical power and potential biases. Using a new methodology, we investigated DNA methylation marks for their associations with breast cancer risk. Methods Statistical models were built to predict levels of DNA methylation marks using genetic data and DNA methylation data from HumanMethylation450 BeadChip from the Framingham Heart Study (n = 1595). The prediction models were validated using data from the Women’s Health Initiative (n = 883). We applied these models to genomewide association study (GWAS) data of 122 977 breast cancer patients and 105 974 controls to evaluate if the genetically predicted DNA methylation levels at CpG sites (CpGs) are associated with breast cancer risk. All statistical tests were two-sided. Results Of the 62 938 CpG sites CpGs investigated, statistically significant associations with breast cancer risk were observed for 450 CpGs at a Bonferroni-corrected threshold of P less than 7.94 × 10–7, including 45 CpGs residing in 18 genomic regions, that have not previously been associated with breast cancer risk. Of the remaining 405 CpGs located within 500 kilobase flaking regions of 70 GWAS-identified breast cancer risk variants, the associations for 11 CpGs were independent of GWAS-identified variants. Integrative analyses of genetic, DNA methylation, and gene expression data found that 38 CpGs may affect breast cancer risk through regulating expression of 21 genes. Conclusion Our new methodology can identify novel DNA methylation biomarkers for breast cancer risk and can be applied to other diseases. |
| Databáze: | OpenAIRE |
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