4.7 Article

Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk

期刊

MOLECULAR ONCOLOGY
卷 14, 期 1, 页码 42-53

出版社

WILEY
DOI: 10.1002/1878-0261.12594

关键词

breast cancer; DNA methylation; environmental risk; genetic risk; risk prediction model; SNPs

类别

资金

  1. China Scholarship Council [201606260041]
  2. Baden-Wurttemberg State Ministry of Science, Research and Arts (Stuttgart, Germany)
  3. Federal Ministry of Education and Research (Berlin, Germany)
  4. Saarland State Ministry for Social Affairs, Health, Women and Family Affairs (Saarbrucken, Germany)
  5. Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany)

向作者/读者索取更多资源

DNA methylation patterns in the blood, genetic risk scores (GRSs), and environmental risk factors can potentially improve breast cancer (BC) risk prediction. We assessed the individual and joint predictive performance of methylation, GRS, and environmental risk factors for BC incidence in a prospective cohort study. In a cohort of 5462 women aged 50-75 from Germany, 101 BC cases were identified during 14 years of follow-up and were compared to 263 BC-free controls in a nested case-control design. Three previously suggested methylation risk scores (MRSs) based on methylation of 423, 248, and 131 cytosine-phosphate-guanine (CpG) loci, and a GRS based on the risk alleles from 269 recently identified single nucleotide polymorphisms were constructed. Additionally, multiple previously proposed environmental risk scores (ERSs) were built based on environmental variables. Areas under the receiver operating characteristic curves (AUCs) were estimated for evaluating BC risk prediction performance. MRS and ERS showed limited accuracy in predicting BC incidence, with AUCs ranging from 0.52 to 0.56 and from 0.52 to 0.59, respectively. The GRS predicted BC incidence with a higher accuracy (AUC = 0.61). Adjusted odds ratios per standard deviation increase (95% confidence interval) were 1.07 (0.84-1.36) and 1.40 (1.09-1.80) for the best performing MRS and ERS, respectively, and 1.48 (1.16-1.90) for the GRS. A full risk model combining the MRS, GRS, and ERS predicted BC incidence with the highest accuracy (AUC = 0.64) and might be useful for identifying high-risk populations for BC screening.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据