This page provides study documentation for BA1. For description of the specimen results, see
Specimen Results Description (open to public). Data sets of the specimen results are included in the existing WHI datasets located on the
WHI Data on this site (sign in and a completed Data Distribution Agreement are required; see details on the Data site).
Investigator Names and Contact Information
Michael F. Seldin, MD, PhD
The proposed studies will examine whether a proportion of variation in specific health measurements and outcomes in the Women’s Health Initiative (WHI) can be explained by genetic variation attributable to ancestry. Our study will distinguish ethnicity-outcome relationships due to ancestrally determined genetic variation differ from associations due to other (non-genetic) correlates of ethnicity, such as socioeconomic status. Characterization of study subjects using a panel of ancestrally informative markers (AIMs) is a novel feature of the proposed study and includes the use of an informative marker set of SNPs for examining European substructure in the “White” subset of subjects. For the two admixed populations in WHI (Black and Hispanic) the study will focus on several discrete disease measurements including breast cancer, CHD, stroke, and hip fractures and the quantitative measurement of bone mineral density. For bone mineral density the studies also includes an admixture mapping study to identify specific chromosomal regions that can explain ancestry linkage. For the White population the study will focus on signs and measurements of osteoporosis by examining subjects with hip fractures, and the quantitative trait, bone mineral density. In this aspect of the study we will also examine response to interventional strategies within WHI.
Some of the publications related to this ancillary study are: 964, 1185, 1253, 1315.
For a complete, up-to-date list of WHI papers related to this ancillary study, please use the searchable
Bibliography section of this website. To search for papers by study number, access the
Simple Search, and enter the study number in the “Related Studies” field.