This study is identifying and sending a letter of invitation to many motivated women with breast cancer and their parents, and can effectively combine their data with the DNA and environmental data now being collected from their unaffected sisters. The study gains enormous operational efficiency advantages, by taking advantage of the infrastructure that is already in place and functioning smoothly for the Sister Study (Dale Sandler, PI). Based on the first 10,000 Sister Study enrollees, more than 20% have an eligible sister and 80% of those have one or both parents living. Mail-back saliva kits will provide DNA from cases and parents. We will collect clinical data and attempt to validate the diagnoses for all 1,600 cases. Follow-up of these cases (through the Sister Study) will also allow us to identify environmental, clinical, and genetic factors that influence health after treatment. We plan to genotype 1,536 markers on some 150 candidate genes, including some expected to be related to risk and others expected to be related to prognosis. In addition, archived DNA will provide a resource for future tests of not-yet-known candidates identified in recently-published and ongoing genome-wide association studies. Case-parent analyses of gene variants are protected against bias due to confounding by genetic heritage, and also permit detection of both maternally-mediated genetic effects and parent-of-origin (imprinting) effects. In the proposed study, the participating affected sisters will complete a computer-assisted telephone interview like the one their sister will have completed, providing information about personal exposures, reproductive history, and past occupational exposures. Environmental effects will be identifiable through a paired comparison of affected and unaffected sisters. Gene-by-exposure interactions will be assessed with novel statistical methods. In summary, the proposed study leverages off the ongoing Sister Study to build a cost-effective, powerful, and statistically independent study of young-onset breast cancer. Findings related to combined effects of genetic variants and environmental factors can be replicated later in the Sister Study. This year we continued to develop the materials required, secured IRB approval for the study, and negotiated the contract required to be awarded foundation funding ($1.7M) to carry it out, through the Susan G. Komen for the Cure foundation. Interview staff was trained and software developed for the computer-assisted telephone interview. A new CATI interview had to be developed related to the breast cancer diagnosis. We have now put the study into the field, with assistance from the EB support services contract. Initial response to our letters of invitation mailed to the first 431 Sister Study participants has been encouraging, though it is too early to estimate the response rate.
| O'Brien, Katie M; Sandler, Dale P; Xu, Zongli et al. (2018) Vitamin D, DNA methylation, and breast cancer. Breast Cancer Res 20:70 |
| Wu, Lang; Shi, Wei; Long, Jirong et al. (2018) A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer. Nat Genet 50:968-978 |
| Kleeberger, Cynthia; Shore, David; Gunter, Elaine et al. (2018) The Effects of Long-term Storage on Commonly Measured Serum Analyte Levels. Epidemiology 29:448-452 |
| White, Mary C; Soman, Ashwini; Weinberg, Clarice R et al. (2018) Factors associated with breast MRI use among women with a family history of breast cancer. Breast J 24:764-771 |
| O'Brien, Katie M; Sandler, Dale P; Shi, Min et al. (2018) Genome-Wide Association Study of Serum 25-Hydroxyvitamin D in US Women. Front Genet 9:67 |
| O'Brien, Katie M; Sandler, Dale P; Kinyamu, H Karimi et al. (2017) Single-Nucleotide Polymorphisms in Vitamin D-Related Genes May Modify Vitamin D-Breast Cancer Associations. Cancer Epidemiol Biomarkers Prev 26:1761-1771 |
| O'Brien, Katie M; Whelan, Denis R; Sandler, Dale P et al. (2017) Predictors and long-term health outcomes of eating disorders. PLoS One 12:e0181104 |
| Park, Yong-Moon Mark; White, Alexandra J; Nichols, Hazel B et al. (2017) The association between metabolic health, obesity phenotype and the risk of breast cancer. Int J Cancer 140:2657-2666 |
| Michailidou, Kyriaki (see original citation for additional authors) (2017) Association analysis identifies 65 new breast cancer risk loci. Nature 551:92-94 |
| Park, Yong-Moon Mark; O'Brien, Katie M; Zhao, Shanshan et al. (2017) Gestational diabetes mellitus may be associated with increased risk of breast cancer. Br J Cancer 116:960-963 |
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