This Komen-funded study has recruited women with young-onset breast cancer and, when available, their parents. We will combine their data with the DNA and environmental data now being collected from their unaffected sisters (who previously joined the Sister Study) and saliva-based DNA collected from their parents. We will use a nuclear-family-based approach to study genetic and environmental factors involved in young-onset breast cancer. 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). We are almost done with collecting clinical data and validating the diagnoses for all these young-onset 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. 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 are each completing a computer-assisted telephone interview like the one their sister completed for the Sister Study, 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. We have now recruited a total of 1,597 breast cancer cases, with 1,312 being fully enrolled. We have also enrolled 1,351 of their parents, and have saliva samples from them. This work was accomplished with assistance from the EB support services contract. We have hired a postdoc, Chunyuan Fei, who is writing papers based on the case-control sibling sets. This should provide good power for case-control analyses of environmental factors and other life experiences related to risk. Genotyping based on the available DNA is being deferred to provide time for recruitment of the parents into the study, and time to find funding to enable those studies. We have submitted two grant applications (one to the Department of Defense and one to Susan G. Komen for the Cure) in hopes of securing funding that would permit a full genome-wide study of these young-onset families.
| 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; 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 |
| 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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