首页> 外文期刊>Journal of the National Cancer Institute >Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228 951 Women of European Descent
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Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228 951 Women of European Descent

机译:基因预测的DNA甲基化生物标志物和乳腺癌风险水平:来自228个951妇女欧洲血统的数据

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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 (GpGs) 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 x 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.
机译:背景:DNA甲基化在乳腺癌发育中起着关键作用。以前的研究已经确定了白细胞中的DNA甲基化标记作为乳腺癌的有希望的生物标志物。然而,这些研究受到低统计功率和潜在偏差的限制。使用新方法,我们研究了与乳腺癌风险的关联的DNA甲基化标记。方法:建立统计模型以预测来自来自Framingham心脏研究的人甲基化450珠芯片的遗传数据和DNA甲基化数据预测DNA甲基化标记的水平(n = 1595)。使用来自女性健康计划的数据(n = 883)验证预测模型。我们将这些模型应用于122977名乳腺癌患者的Genomewide Association(GWAS)数据,105 974次对照组,以评估CPG位点(GPGs)的转基因DNA甲基化水平与乳腺癌风险有关。所有统计测试都是双面的。结果:在62个938个CPG地点Cpgs调查的CPG中,在PNFERRONI校正的阈值下观察到450个CPG的统计上显着的关联,包括较低的7.94×10〜-7,其中包括45个基因组区域中的45个CPGS,即以前没有与乳腺癌风险有关。在剩余的405个CPG中,位于70 gwas鉴定的乳腺癌风险变体的500千碱基碎屑区域内,11个CPG的关联与GWAS鉴定的变体无关。遗传,DNA甲基化和基因表达数据的整合分析发现,通过调节21基因的表达,38个CPG可能会影响乳腺癌风险。结论:我们的新方法可以识别乳腺癌风险的新型DNA甲基化生物标志物,可应用于其他疾病。

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