Application values of genome-wide association studies in screening for breast cancer
10.3760/cma.j.issn.0254-6450.2019.06.021
- VernacularTitle: 全基因组关联研究在乳腺癌筛查中的应用价值初探
- Author:
Yubei HUANG
1
;
Fengju SONG
;
Kexin CHEN
Author Information
1. Department of Epidemiology and Biostatistics, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin Medical University Cancer Hospital, Tianjin 300060, China
- Publication Type:Journal Article
- Keywords:
Breast neoplasms;
Genome-wide association study;
Single-nucleotide polymorphism
- From:
Chinese Journal of Epidemiology
2019;40(6):713-718
- CountryChina
- Language:Chinese
-
Abstract:
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 95th 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.
