Objective: To investigate the potential application values of screening on breast cancer, using the single-nucleotide polymorphisms (SNPs) that were identified from the genome- wide association studies (GWASs). Methods: Two million Chinese women aged 35-69 years were simulated, based on both age distributions, age-specific incidence rates of breast cancer and the distribution of known risk factors, in 2013. Twenty-three SNPs identified from GWAS were further simulated. Both genetic-related risks explained by each SNPs and the improvement on the risks under reclassification, were used to select SNPs for the prediction on breast cancer among the targeted high-risk population. Further analyses were conducted to investigate the following items as: improvements on detection rates of breast cancer among the high-risk populations, areas under the curve (AUC) and the odds ratio (OR) among women at high risk. Results: A total of 12 SNPs were eligible for targeting the high-risk population of breast cancer. When high-risk populations were defined as women whose predicted risks were higher than the 95(th) predicted risk of the whole population, the detection rate (146.99/100 000) among high-risked women predicted by 12 SNPs would be significantly lower than 177.46/100 000, which was predicted by the known risk factors (P<0.001), among the high-risked women. Among those women at high risk, the detection rate (229.00/100 000) predicted by integrating known risk factors and 12 SNPs was significantly higher than that predicted by known risk factors (P<0.001). Also, the AUC increased from 64.4% to 67.8% (P<0.001), and the OR of increased from 3.32 to 4.33, predicted by integrating known risk factors and 12 SNPs, for women at high risk on breast cancer. Conclusion: Targeted SNPs that were identified from genome- wide association studies could be used to improve the detection rates as well as the overall accuracy of risk prediction so as to identify the potential high-risk women on breast cancer before carrying on the screening program.
目的： 探索全基因组关联研究（GWAS）发现的单核苷酸多态性位点（SNP）在乳腺癌筛查中的潜在应用价值。 方法： 基于我国女性2013年的年龄构成、年龄别的乳腺癌发病率，以及明确的乳腺癌传统危险因素分布情况，对中国200万35~69岁女性人群进行模拟。进一步模拟GWAS发现的23个与我国女性乳腺癌风险相关的SNP位点的分布情况。依据SNP的遗传风险解释程度及风险再分类准确性的改善程度，初筛出可用于预测乳腺癌高危人群的目标SNP，并进一步探索目标SNP对乳腺癌检出率、乳腺癌风险预测曲线下面积（AUC）、高危人群中乳腺癌发病风险的影响。 结果： 共发现12个SNP可用于预测乳腺癌高危人群。如果将预测风险位于P(95)及更高风险的人群定义为高危人群，并在此类人群中进行筛查，采用目标SNP预测的高危人群中的乳腺癌检出率（146.99/10万）明显低于采用传统危险因素预测的高危人群中的乳腺癌检出率（177.46/10万）（P<0.001）。在传统危险因素基础上，加上目标SNP进行高危人群预测，高危人群中乳腺癌检出率（229.00/10万）提高29.0%（P<0.001）。同时乳腺癌风险预测的AUC从64.4%上升至67.8%（P<0.001），高危人群中乳腺癌发病风险OR值从3.32上升至4.33。 结论： GWAS筛选出的目标SNP可提高乳腺癌检出率、乳腺癌总体风险预测准确性，并有助于在乳腺癌筛查前发现潜在的乳腺癌高危人群。.
Keywords: Breast neoplasms; Genome-wide association study; Single-nucleotide polymorphism.