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Breast Cancer Research
Published in: Breast Cancer Research 1/2013

Open Access 01-02-2012 | Research article

Breast cancer risk assessment with five independent genetic variants and two risk factors in Chinese women

Authors: Juncheng Dai, Zhibin Hu, Yue Jiang, Hao Shen, Jing Dong, Hongxia Ma, Hongbing Shen

Published in: Breast Cancer Research | Issue 1/2013

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Abstract

Introduction

Recently, several genome-wide association studies (GWAS) have identified novel single nucleotide polymorphisms (SNPs) associated with breast cancer risk. However, most of the studies were conducted among Caucasians and only one from Chinese.

Methods

In the current study, we first tested whether 15 SNPs identified by previous GWAS were also breast cancer marker SNPs in this Chinese population. Then, we grouped the marker SNPs, and modeled them with clinical risk factors, to see the usage of these factors in breast cancer risk assessment. Two methods (risk factors counting and odds ratio (OR) weighted risk scoring) were used to evaluate the cumulative effects of the five significant SNPs and two clinical risk factors (age at menarche and age at first live birth).

Results

Five SNPs located at 2q35, 3p24, 6q22, 6q25 and 10q26 were consistently associated with breast cancer risk in both testing set (878 cases and 900 controls) and validation set (914 cases and 967 controls) samples. Overall, all of the five SNPs contributed to breast cancer susceptibility in a dominant genetic model (2q35, rs13387042: adjusted OR = 1.26, P = 0.006; 3q24.1, rs2307032: adjusted OR = 1.24, P = 0.005; 6q22.33, rs2180341: adjusted OR = 1.22, P = 0.006; 6q25.1, rs2046210: adjusted OR = 1.51, P = 2.40 × 10-8; 10q26.13, rs2981582: adjusted OR = 1.31, P = 1.96 × 10-4). Risk score analyses (area under the curve (AUC): 0.649, 95% confidence interval (CI): 0.631 to 0.667; sensitivity = 62.60%, specificity = 57.05%) presented better discrimination than that by risk factors counting (AUC: 0.637, 95% CI: 0.619 to 0.655; sensitivity = 62.16%, specificity = 60.03%) (P < 0.0001). Absolute risk was then calculated by the modified Gail model and an AUC of 0.658 (95% CI = 0.640 to 0.676) (sensitivity = 61.98%, specificity = 60.26%) was obtained for the combination of five marker SNPs, age at menarche and age at first live birth.

Conclusions

This study shows that five GWAS identified variants were also consistently validated in this Chinese population and combining these genetic variants with other risk factors can improve the risk predictive ability of breast cancer. However, more breast cancer associated risk variants should be incorporated to optimize the risk assessment.
Appendix
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Metadata
Title
Breast cancer risk assessment with five independent genetic variants and two risk factors in Chinese women
Authors
Juncheng Dai
Zhibin Hu
Yue Jiang
Hao Shen
Jing Dong
Hongxia Ma
Hongbing Shen
Publication date
01-02-2012
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2013
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/bcr3101

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