Genome Wide Association Study: Variants Influencing Steroid Hormone Levels

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DESCRIPTION (provided by applicant): There is substantial evidence that circulating sex steroid hormone levels are influenced by genetic factors. Sex steroid hormones, such as estradiol and testosterone, are implicated in the development of many diseases, including breast cancer. Recent advances in genotyping technology have reduced genotyping costs, allowing for the development of genotyping platforms capable of performing genome wide association scans. The Cancer Genetic Markers of Susceptibility (CGEMS) project has been initiated to perform a genome wide association study to detect single nucleotide polymorphisms (SNPs) which predispose for breast cancer, using the Illumina HumanHap500 bead chip. The Nurses' Health Study (NHS) is part of this collaborative effort, providing DNA from 2300 women (1150 women diagnosed with invasive breast cancer after menopause, and 1150 age-matched women not diagnosed with breast cancer). Levels of estradiol, testosterone, and SHBG have been assayed in plasma collected prospectively from women who were postmenopausal at blood collection, not having recently taken hormone replacement therapy. Approximately 430 cases and 415 controls within the samples genotyped in the CGEMS project fit these criteria, and have estradiol, testosterone, and SHBG levels available. These same plasma hormone levels have been assayed on a second control sample for each case, as well as the control subjects for women diagnosed with in situ carcinoma, however these control subjects (n~1100) have not been genotyped as part of the CGEMS project. The objective of this work is to describe polymorphisms that are associated with plasma sex steroid hormone levels. This will be accomplished in an initial screen of the 550,000 SNPs genotyped in the CGEMS project for associations with hormone levels using analysis of covariance. A subset of these SNPs will then be genotyped in the additional control samples, and joint analyses of the initial and second stages will provide strong evidence for association between SNP loci and plasma hormone levels. As hypothesis generating secondary analysis, we will also examine copy number variants (CNVs) for association with steroid hormone levels. By using genotype data collected in the CGEMS project, and sex steroid hormone levels assayed previously in the NHS, this work will provide a unique, cost effective, and powerful genome wide association study to describe polymorphisms which predict sex steroid hormone levels. The genotyping data collected in the current study will be combined with already available sex steroid hormone data to provide well powered joint analyses of the SNPs most strongly associated with sex steroid hormone levels from this two stage genome wide association scan. Therefore, polymorphisms found to be associated with sex steroid hormone levels in this joint analysis will provide very likely candidates for further study with respect to their influence on sex steroid hormone levels, which are well recognized predictors of many diseases, including breast cancer.