We developed a web application that incorporates GWAS data, functional predictions, and LD information from multiple ethnic groups to select the most promising SNP candidates for association studies. We designed and implemented a set of SNP selection pipelines that allow an investigator to specify genes or linkage regions and select SNPs based on GWAS results, linkage disequilibrium (LD) and predicted functional characteristics of both coding and non-coding SNPs. We incorporated a variety of functional predictions including effects of protein structure, gene regulation, splicing, and miRNA binding. In doing so, we not only considered whether a SNP was in a putative functional region, but also considered whether alternative alleles of a SNP were likely to have differential effects on function. We also allowed user-assigned weights for different functional categories of SNPs so that an investigator may tailor SNP selection (e.g. toward SNPs that effect miRNA binding), depending on their area of interest. Using this tool we created a panel of 1,536 SNPs which we used to genotype an initial set of 935 African American (AA) and European American (EA) men with prostate cancer and compare them to publicly available population genotype data on 723 SNPs from Illumina iControlDB. This panel included 32 SNPs previously identified as being associated with prostate cancer risk in Genome Wide Association Studies (GWAS) of prostate cancer in men of European descent, along with 35 flanking SNPs. Of the 32 GWAS SNPs, 13 were significant at P <0.05 in EA and 4 in AA. Three of 35 flanking SNPs, all from chromosome 8q, reached study-wide significance (p <3.510-5);two in AA and one in EA. Among the remaining 656 SNPs, two were associated with CaP (p <3.510-5), on in EA (OR = 1.43 ) and one in AA (OR = 1.48). Both SNPs are located in intergenic regions. For the 32 GWAS SNPs, Receiver Operator Curve (ROC) plots yielded Area Under Curve (AUC) estimates too low for clinical use (EA AUC= 0.60 and AA AUC= 0.56). This study confirms a large proportion of CaP associated regions implicated by European-based GWAS and provides evidence that some regions may be important in AA CaP risk. Despite the identification of a large panel of GWAS replicated SNPs for CaP, this panel is not appropriate for clinical screening. A manuscript describing this study has been submitted for publication. We have now extended our genotyping efforts to increase the total number of men genotyped to more than 2000 and are now beginning analysis of this data in order to investigate whether inherited polymorphisms affect severity of disease. In addition we are currently genotyping al 1000 AA men using a large panel of Ancestry Informative Markers in order to do admixture mapping of prostate cancer. We have participated in two large bladder cancer consortia efforts directed at understanding the genetic determinants of this disease. One effort, combining our genotype data with that of other investigators was directed at evaluating polymorphisms in DNA repair genes and is currently in press. The second, a GWAS study, our laboratory genotyped cases and controls from our existing bladder cancer study as part of the validation phase of the study and this work is also in press.
| O'Brien, Katie M; Sandler, Dale P; Xu, Zongli et al. (2018) Vitamin D, DNA methylation, and breast cancer. Breast Cancer Res 20:70 |
| Herceg, Zdenko; Ghantous, Akram; Wild, Christopher P et al. (2018) Roadmap for investigating epigenome deregulation and environmental origins of cancer. Int J Cancer 142:874-882 |
| 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 |
| 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 |
| Wilson, L E; Harlid, S; Xu, Z et al. (2017) An epigenome-wide study of body mass index and DNA methylation in blood using participants from the Sister Study cohort. Int J Obes (Lond) 41:194-199 |
| Michailidou, Kyriaki (see original citation for additional authors) (2017) Association analysis identifies 65 new breast cancer risk loci. Nature 551:92-94 |
| Sandler, Dale P; Hodgson, M Elizabeth; Deming-Halverson, Sandra L et al. (2017) The Sister Study Cohort: Baseline Methods and Participant Characteristics. Environ Health Perspect 125:127003 |
| Amos, Christopher I; Dennis, Joe; Wang, Zhaoming et al. (2017) The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers. Cancer Epidemiol Biomarkers Prev 26:126-135 |
| Milne, Roger L (see original citation for additional authors) (2017) Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer. Nat Genet 49:1767-1778 |
Showing the most recent 10 out of 50 publications
