To provide a resource for assessing continental ancestry in a wide variety of genetic studies we identified, validated and characterized a set of 128 ancestry informative markers (AIMs). The markers were chosen for informativeness, genome-wide distribution, and genotype reproducibility on two platforms (TaqMan® assays and Illumina arrays). We analyzed genotyping data from 825 subjects with diverse ancestry, including European, East Asian, Amerindian, African, South Asian, Mexican, and Puerto Rican. A comprehensive set of 128 AIMs and subsets as small as 24 AIMs are shown to be useful tools for ascertaining the origin of subjects from particular continents, and to correct for population stratification in admixed population sample sets. Our findings provide general guidelines for the application of specific AIM subsets as a resource for wide application. We conclude that investigators can use TaqMan assays for the selected AIMs as a simple and cost efficient tool to control for differences in continental ancestry when conducting association studies in ethnically diverse populations.

Endometrial cancer is the most commonly diagnosed cancer of the female reproductive tract in developed countries. Through genome-wide association studies (GWAS), we have previously identified eight risk loci for endometrial cancer. Here, we present an expanded meta-analysis of 12,906 endometrial cancer cases and 108,979 controls (including new genotype data for 5624 cases) and identify nine novel genome-wide significant loci, including a locus on 12q24.12 previously identified by meta-GWAS of endometrial and colorectal cancer. At five loci, expression quantitative trait locus (eQTL) analyses identify candidate causal genes; risk alleles at two of these loci associate with decreased expression of genes, which encode negative regulators of oncogenic signal transduction proteins (SH2B3 (12q24.12) and NF1 (17q11.2)). In summary, this study has doubled the number of known endometrial cancer risk loci and revealed candidate causal genes for future study.

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants (CCVs) in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium, and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Importance: Obesity is associated with increased risk of breast cancer, including the estrogen receptor (ER)-positive subtype in postmenopausal women. It is unknown whether excess adiposity is associated with increased risk in women with a normal body mass index (BMI). Objective: To investigate the association between body fat and breast cancer risk in normal BMI women. Design: This secondary analysis of the Women’s Health Initiative (WHI) cohort was restricted to participants with BMI 18.5 to <25.0 kg/m2. Setting: Women ages 50 to 79 years were enrolled from 1993 to 1998. Body fat was measured by dual energy X-ray absorptiometry (DXA) at 3 designated centers. Participants: 3,460 postmenopausal women with normal BMI who had DXA measures were included. At a median follow-up of 16 years, 182 incident breast cancers had been ascertained; 146 were ER-positive. Main Outcomes and Measures: DXA-derived body fat levels were measured at baseline and years 1, 3, 6, and 9. Information on demographic data, medical history, and lifestyle factors was collected at baseline. Invasive breast cancers were confirmed via central review of medical records by physician adjudicators. Blood analytes were measured in subsets of participants. Results: Multivariable-adjusted hazard ratios (HRs) for risk of invasive breast cancer were 1.89 (95% CI 1.21 to 2.95) and 1.88 (95% CI 1.18 to 2.98) in the uppermost versus lowest quartiles of whole body fat and trunk fat mass, respectively. The corresponding adjusted HRs for ER-positive breast cancer were 2.21 (95% CI 1.23 to 3.67) and 1.98 (95% CI 1.18 to 3.31), respectively. Similar positive associations were observed when accounting for serial DXA measurements in time-dependent covariate analyses for ER-positive breast cancer. Circulating insulin, C-reactive protein, interleukin-6, leptin and triglycerides were higher, while HDL-cholesterol and sex hormone binding globulin were lower in the uppermost versus lowest quartiles of trunk fat mass. Conclusions and Relevance: In normal BMI postmenopausal women, relatively high body fat was associated with elevated risk of invasive breast cancer and altered levels of circulating metabolic and inflammatory factors. Normal BMI categorization may be an inadequate proxy for the risk of breast cancer in postmenopausal women.

Background: Case-control genetic studies of complex human diseases can be confounded by population stratification. This issue can be addressed using panels of ancestry informative markers (AIMs) that can provide substantial population substructure information. Previously, we described a panel of 128 SNP AIMs that were designed as a tool for ascertaining the origins of subjects from Europe, Sub-Saharan Africa, Americas, and East Asia.