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.

In the E + P trial, the higher breast cancer risk seen during intervention was followed by a substantial drop in risk in the early postintervention phase, but a higher breast cancer risk remained during the late postintervention follow-up. In the estrogen alone trial, the lower breast cancer risk seen during intervention was sustained in the early postintervention phase but was not evident during the late postintervention follow-up.

BackgroundAtrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with increased risk of stroke and death. Obesity is an independent risk factor for AF, but modifiers of this risk are not well known. We studied the roles of obesity, physical activity, and their interaction in conferring risk of incident AF.Methods and ResultsThe Women's Health Initiative (WHI) Observational Study was a prospective observational study of 93 676 postmenopausal women followed for an average of 11.5 years. Incident AF was identified using WHI‐ascertained hospitalization records and diagnostic codes from Medicare claims. A multivariate Cox's hazard regression model adjusted for demographic and clinical risk factors was used to evaluate the interaction between obesity and physical activity and its association with incident AF. After exclusion of women with prevalent AF, incomplete data, or underweight body mass index (BMI), 9792 of the remaining 81 317 women developed AF. Women were, on average, 63.4 years old, 7.8% were African American, and 3.6% were Hispanic. Increased BMI (hazard ratio [HR], 1.12 per 5‐kg/m2 increase; 95% confidence interval [CI], 1.10 to 1.14) and reduced physical activity (>9 vs. 0 metabolic equivalent task hours per week; HR, 0.90; 95% CI, 0.85 to 0.96) were independently associated with higher rates of AF after multivariate adjustment. Higher levels of physical activity reduced the AF risk conferred by obesity (interaction P=0.033).ConclusionsGreater physical activity is associated with lower rates of incident AF and modifies the association between obesity and incident AF.

Purpose Distress and reduced quality of life (QOL) are common among people with cancer. No study has compared these variables after breast cancer diagnosis to pre-cancer diagnosis levels. Methods Data on women with breast cancer 50 years of age or older (n=6949) were analyzed from the Women's Health Initiative (1993-2013). Health-related QOL (physical function, mental health) was measured using Rand-36. Depressive symptoms were measured with the 6-item Center for Epidemiologic Studies Depression. Assessments occurred before and after the cancer diagnosis. Hierarchical linear modeling compared pre-cancer QOL and depressive symptoms to levels post-diagnosis and tested whether pre-cancer physical activity, stressful life events, sleep disturbance, and pain predicted post-diagnosis outcomes. Results Compared with pre-cancer levels, depressive symptoms increased (20.0% increase at 0-6 months, 12.9% increase at 6-12 months), while physical function (−3.882 points at 0-6 months, −3.545 at 6-12 months) and mental health decreased (−2.899 points at 0-6 months, −1.672 at 6-12 months) in the first year after diagnosis (p's<.01). Depressive symptoms returned to pre-cancer levels after 10 years but QOL remained significantly lower. At more than 10 years post-diagnosis, physical function was 2.379 points lower than pre-cancer levels (p<0.01) while mental health was 1.922 points lower (p<0.01). All pre-cancer predictors were associated with all outcomes. Pain predicted uniquely greater decreases in physical function post-diagnosis. Conclusions Depressive symptoms increased and QOL decreased following breast cancer diagnosis compared with pre-cancer levels, particularly in the first year. Implications for Cancer Survivors QOL may remain lower for years after breast cancer diagnosis, though decreases are small.