Supplementary data for the materials and methods section.

CCR Translation for This Article from Intrinsic Breast Tumor Subtypes, Race, and Long-Term Survival in the Carolina Breast Cancer Study

Supplementary Tables 1-8 from Smoking and Selected DNA Repair Gene Polymorphisms in Controls: Systematic Review and Meta-Analysis

To determine whether associations between estrogen pathway-related single nucleotide polymorphisms (SNPs) and breast cancer risk differ by molecular subtype, we evaluated associations between SNPs in cytochrome P450 family 19 subfamily A polypeptide 1 (CYP19A1), estrogen receptor (ESR1), 3-beta hydroxysteroid dehydrogenase type I (HSD3B1), 17-beta hydroxysteroid dehydrogenase type II (HSD17B2), progesterone receptor (PGR), and sex hormone-binding globulin (SHBG) and breast cancer risk in a case–control study in North Carolina.

AURKA is a putative low‐penetrance tumor susceptibility gene due to its prominent role in cell cycle regulation and centrosomal function. Germline variation in AURKA was evaluated for association with breast cancer and intrinsic breast cancer subtypes in the Carolina Breast Cancer Study (CBCS), a population‐based case‐control study of African Americans (AA) and Caucasians (Cau). Tag and candidate single nucleotide polymorphisms (SNPs) on AURKA were genotyped in 1946 cases and 1747 controls. In race‐stratified analyses adjusted for age and African ancestry, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate SNP associations with breast cancer. In a race‐combined analysis with similar adjustment, these associations were also examined by intrinsic breast cancer subtype. Using dominant models, most AURKA SNPs demonstrated no association with breast cancer in the race‐stratified analyses. Among AA, rs6092309 showed an inverse association with breast cancer (OR = 0.69, 95% CI = 0.53–0.90). In the race‐combined analyses, rs6099128 had reduced ORs for luminal A (OR = 0.76, 95% CI = 0.60–0.95) and basal‐like breast cancer (OR = 0.54, 95% CI = 0.37–0.80). Rs6092309 showed a similar pattern of association with each subtype. Three SNPs (rs6014711, rs911162, rs1047972) had positive associations with basal‐like breast cancer, and ORs reduced or close to 1.00 for other subtypes. Our results suggest inverse associations between some AURKA SNPs and overall breast cancer in AA. We found differential associations by specific subtypes and by race. Replication of these findings in larger AA populations would allow more powerful race‐stratified subtype analyses. © 2014 Wiley Periodicals, Inc.

Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious.

Cytochrome b 5 (encoded by CYB5A) and NADH cytochrome b 5 reductase (encoded by CYB5R3) detoxify aromatic and heterocyclic amine mammary carcinogens found in cigarette smoke. We hypothesized that CYB5A and CYB5R3 polymorphisms would be associated with breast cancer risk in women.

Genome-wide association studies have identified 73 breast cancer risk variants mainly in European populations. Given considerable differences in linkage disequilibrium structure between populations of European and African ancestry, the known risk variants may not be informative for risk in African ancestry populations. In a previous fine-mapping investigation of 19 breast cancer loci, we were able to identify SNPs in four regions that better captured risk associations in African American women. In this study of breast cancer in African American women (3016 cases, 2745 controls), we tested an additional 54 novel breast cancer risk variants. Thirty-eight variants (70%) were found to have an association with breast cancer in the same direction as previously reported, with eight (15%) replicating at P < 0.05. Through fine-mapping, in three regions (1q32, 3p24, 10q25), we identified variants that better captured associations with overall breast cancer or estrogen receptor positive disease. We also observed suggestive associations with variants (at P < 5 × 10(-6)) in three separate regions (6q25, 14q13, 22q12) that may represent novel risk variants. Directional consistency of association observed for ∼65-70% of currently known genetic variants for breast cancer in women of African ancestry implies a shared functional common variant at most loci. To validate and enhance the spectrum of alleles that define associations at the known breast cancer risk loci, as well as genome-wide, will require even larger collaborative efforts in women of African ancestry.

Age at menopause marks the end of a woman's reproductive life and its timing associates with risks for cancer, cardiovascular and bone disorders. GWAS and candidate gene studies conducted in women of European ancestry have identified 27 loci associated with age at menopause. The relevance of these loci to women of African ancestry has not been previously studied. We therefore sought to uncover additional menopause loci and investigate the relevance of European menopause loci by performing a GWAS meta-analysis in 6510 women with African ancestry derived from 11 studies across the USA. We did not identify any additional loci significantly associated with age at menopause in African Americans. We replicated the associations between six loci and age at menopause (P-value < 0.05): AMHR2, RHBLD2, PRIM1, HK3/UMC1, BRSK1/TMEM150B and MCM8. In addition, associations of 14 loci are directionally consistent with previous reports. We provide evidence that genetic variants influencing reproductive traits identified in European populations are also important in women of African ancestry residing in USA.

We scanned through the genomes of 29,141 African Americans, searching for loci where the average proportion of African ancestry deviates significantly from the genome-wide average. We failed to find any genome-wide significant deviations, and conclude that any selection in African Americans since admixture is sufficiently weak that it falls below the threshold of our power to detect it using a large sample size. These results stand in contrast to the findings of a recent study of selection in African Americans. That study, which had 15 times fewer samples, reported six loci with significant deviations. We show that the discrepancy is likely due to insufficient correction for multiple hypothesis testing in the previous study. The same study reported 14 loci that showed greater population differentiation between African Americans and Nigerian Yoruba than would be expected in the absence of natural selection. Four such loci were previously shown to be genome-wide significant and likely to be affected by selection, but we show that most of the 10 additional loci are likely to be false positives. Additionally, the most parsimonious explanation for the loci that have significant evidence of unusual differentiation in frequency between Nigerians and Africans Americans is selection in Africa prior to their forced migration to the Americas.

Central obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values<5.0 × 10(-6) were followed-up (stage 2) in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA) WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24×10(-8) for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10(-8) for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5 × 10(-8); RREB1: p = 5.7 × 10(-8)). Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region) in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02). In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept that there are fat distribution loci that are independent of generalized adiposity.

AbstractBackground: Gene expression analyses indicate that breast cancer is a heterogeneous disease with at least five immunohistologic subtypes. Despite growing evidence that these subtypes are etiologically and prognostically distinct, few studies have investigated whether they have divergent genetic risk factors. To help fill in this gap in our understanding, we examined associations between breast cancer subtypes and previously established susceptibility loci among white and African-American women in the Carolina Breast Cancer Study.Methods: We used Bayesian polytomous logistic regression to estimate ORs and 95% posterior intervals for the association between each of 78 single nucleotide polymorphisms (SNP) and five breast cancer subtypes. Subtypes were defined using five immunohistochemical markers: estrogen receptors (ER), progesterone receptors (PR), human epidermal growth factor receptors 1 and 2 (HER1/2), and cytokeratin (CK) 5/6.Results: Several SNPs in TNRC9/TOX3 were associated with luminal A (ER/PR+, HER2−) or basal-like breast cancer (ER−, PR−, HER2−, HER1, or CK 5/6+), and one SNP (rs3104746) was associated with both. SNPs in FGFR2 were associated with luminal A, luminal B (ER/PR+, HER2+), or HER2+/ER− disease, but none were associated with basal-like disease. We also observed subtype differences in the effects of SNPs in 2q35, 4p, TLR1, MAP3K1, ESR1, CDKN2A/B, ANKRD16, and ZM1Z1.Conclusion and Impact: We found evidence that genetic risk factors for breast cancer vary by subtype and further clarified the role of several key susceptibility genes. Cancer Epidemiol Biomarkers Prev; 23(1); 84–97. ©2013 AACR.

African-American (AA) women have earlier menarche on average than women of European ancestry (EA), and earlier menarche is a risk factor for obesity and type 2 diabetes among other chronic diseases. Identification of common genetic variants associated with age at menarche has a potential value in pointing to the genetic pathways underlying chronic disease risk, yet comprehensive genome-wide studies of age at menarche are lacking for AA women. In this study, we tested the genome-wide association of self-reported age at menarche with common single-nucleotide polymorphisms (SNPs) in a total of 18 089 AA women in 15 studies using an additive genetic linear regression model, adjusting for year of birth and population stratification, followed by inverse-variance weighted meta-analysis (Stage 1). Top meta-analysis results were then tested in an independent sample of 2850 women (Stage 2). First, while no SNP passed the pre-specified P < 5 × 10(-8) threshold for significance in Stage 1, suggestive associations were found for variants near FLRT2 and PIK3R1, and conditional analysis identified two independent SNPs (rs339978 and rs980000) in or near RORA, strengthening the support for this suggestive locus identified in EA women. Secondly, an investigation of SNPs in 42 previously identified menarche loci in EA women demonstrated that 25 (60%) of them contained variants significantly associated with menarche in AA women. The findings provide the first evidence of cross-ethnic generalization of menarche loci identified to date, and suggest a number of novel biological links to menarche timing in AA women.

Genome-wide association studies (GWAS) in diverse populations are needed to reveal variants that are more common and/or limited to defined populations. We conducted a GWAS of breast cancer in women of African ancestry, with genotyping of >1,000,000 SNPs in 3,153 African American cases and 2,831 controls, and replication testing of the top 66 associations in an additional 3,607 breast cancer cases and 11,330 controls of African ancestry. Two of the 66 SNPs replicated (p < 0.05) in stage 2, which reached statistical significance levels of 10−6 and 10−5 in the stage 1 and 2 combined analysis (rs4322600 at chromosome 14q31: OR = 1.18, p = 4.3 × 10−6; rs10510333 at chromosome 3p26: OR = 1.15, p = 1.5 × 10−5). These suggestive risk loci have not been identified in previous GWAS in other populations and will need to be examined in additional samples. Identification of novel risk variants for breast cancer in women of African ancestry will demand testing of a substantially larger set of markers from stage 1 in a larger replication sample.

Genome-wide association studies (GWAS) simultaneously investigating hundreds of thousands of single nucleotide polymorphisms (SNP) have become a powerful tool in the investigation of new disease susceptibility loci. Haplotypes are sometimes thought to be superior to SNPs and are promising in genetic association analyses. The application of genome-wide haplotype analysis, however, is hindered by the complexity of haplotypes themselves and sophistication in computation. We systematically analyzed the haplotype effects for breast cancer risk among 5,761 African American women (3,016 cases and 2,745 controls) using a sliding window approach on the genome-wide scale. Three regions on chromosomes 1, 4 and 18 exhibited moderate haplotype effects. Furthermore, among 21 breast cancer susceptibility loci previously established in European populations, 10p15 and 14q24 are likely to harbor novel haplotype effects. We also proposed a heuristic of determining the significance level and the effective number of independent tests by the permutation analysis on chromosome 22 data. It suggests that the effective number was approximately half of the total (7,794 out of 15,645), thus the half number could serve as a quick reference to evaluating genome-wide significance if a similar sliding window approach of haplotype analysis is adopted in similar populations using similar genotype density.