Breast cancer is the most common malignancy among women in many parts of the world. Genetic factors play an important role in the etiology of breast cancer. However, to date, only a few breast cancer susceptibility genes have been identified, and they explain only a very small fraction of breast cancer cases in the general population. A large number of candidate-gene studies have been conducted over the past 10 years. These studies, however, are clearly inadequate to fully uncover the genetic basis of breast cancer. With recent significant advances in high-throughput genotyping technologies, it has become feasible to conduct genome-wide association (GWA) studies to systematically evaluate genetic risk factors for breast cancer. The multi-phase GWA study proposed in this application will be built upon the resources established in two large, on-going studies funded by NCI, the Shanghai Breast Cancer Study (R01 CA64277) a population-based case-control study, and the Shanghai Women's Health Study (RO1 CA70867) a population-based prospective cohort study. Approximately 8,000 breast cancer cases and controls will be included in this proposed study. In the first phase of the study, we will conduct a GWA scan in 1,000 cases and 1,000 controls using the Illumina HumanHap550 BeadChip. We will then select the 10,600 most promising SNPs for a validation study in an independent sample of 1500 cases and 1500 controls. All promising SNPs will be further validated using data from 1000 cases and 2000 controls selected from the prospective Shanghai Women's Health Study. The parent projects of this newly-proposed study have been exceptionally well-conducted with a strong methodology. The feasibility and utility of the proposed study have been clearly demonstrated in our pilot study. The study is unique and has many unique features that facilitate a rigorous evaluation of breast cancer genetic factors. The results from the study will be valuable in identifying high risk women for primary and secondary prevention of breast cancer.
Genetic factors and gene-environment interaction are believed to cause most breast cancers, yet only a small number of cases are explained by genetic factors identified thus far. The large epidemiologic study we propose will comprehensively evaluate genetic markers in relation to breast cancer risk. This study will generate valuable results for the identification of high-risk women for the primary and secondary prevention of breast cancer.
|Spracklen, Cassandra N; Chen, Peng; Kim, Young Jin et al. (2017) Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels. Hum Mol Genet 26:1770-1784|
|Shi, Jiajun; Zhang, Ben; Choi, Ji-Yeob et al. (2016) Age at menarche and age at natural menopause in East Asian women: a genome-wide association study. Age (Dordr) 38:513-523|
|Imamura, Minako; Takahashi, Atsushi; Yamauchi, Toshimasa et al. (2016) Genome-wide association studies in the Japanese population identify seven novel loci for type 2 diabetes. Nat Commun 7:10531|
|Zeng, Chenjie; Matsuda, Koichi; Jia, Wei-Hua et al. (2016) Identification of Susceptibility Loci and Genes for Colorectal Cancer Risk. Gastroenterology 150:1633-1645|
|Han, Mi-Ryung; Long, Jirong; Choi, Ji-Yeob et al. (2016) Genome-wide association study in East Asians identifies two novel breast cancer susceptibility loci. Hum Mol Genet 25:3361-3371|
|Wen, Wanqing; Shu, Xiao-Ou; Guo, Xingyi et al. (2016) Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry. Breast Cancer Res 18:124|
|Hwang, Joo-Yeon; Sim, Xueling; Wu, Ying et al. (2015) Genome-wide association meta-analysis identifies novel variants associated with fasting plasma glucose in East Asians. Diabetes 64:291-8|
|He, Meian; Xu, Min; Zhang, Ben et al. (2015) Meta-analysis of genome-wide association studies of adult height in East Asians identifies 17 novel loci. Hum Mol Genet 24:1791-800|
|Villegas, Raquel; Williams, Scott M; Gao, Yu-Tang et al. (2014) Genetic variation in the peroxisome proliferator-activated receptor (PPAR) and peroxisome proliferator-activated receptor gamma co-activator 1 (PGC1) gene families and type 2 diabetes. Ann Hum Genet 78:23-32|
|Qi, Qibin; Kilpeläinen, Tuomas O; Downer, Mary K et al. (2014) FTO genetic variants, dietary intake and body mass index: insights from 177,330 individuals. Hum Mol Genet 23:6961-72|
Showing the most recent 10 out of 56 publications