Abstract
African American women with breast cancer present more commonly with aggressive tumors that do not express the estrogen receptor (ER) and progesterone receptor (PR) compared with European American women. Whether this disparity is the result of inherited factors has not been established. We performed an admixture-based genome-wide scan to search for risk alleles for breast cancer that are highly differentiated in frequency between African American and European American women and may contribute to specific breast cancer phenotypes, such as ER negative (ER−) disease. African American women with invasive breast cancer (n=1,484) were pooled from 6 population-based studies and typed at ~1,500 ancestry informative markers (AIMs). We investigated global genetic ancestry and performed a whole genome admixture scan searching for breast cancer predisposing loci in association with disease phenotypes. We found a significant difference in ancestry between ER+PR+ and ER−PR− women, with higher European ancestry among ER+PR+ individuals, after controlling for possible confounders (OR for a 0 to 1 change in European ancestry proportion=2.84, 95% CI: 1.13–7.14, p=0.026). Women with localized tumors had higher European ancestry than women with non-localized tumors (OR=2.65, CI: 1.11–6.35, p=0.029). No genome-wide statistically significant associations were observed between European or African ancestry at any specific locus and breast cancer, or in analyses stratified by ER/PR status, stage or grade. In summary, in African American women genetic ancestry is associated with ER/PR status and disease stage. However, we found little evidence that genetic ancestry at any one region contributes significantly to breast cancer risk or hormone receptor status.
Keywords: African Americans, breast cancer, admixture mapping, hormone receptor status, genetic ancestry
Introduction
Breast cancer incidence and mortality varies widely among women of different population groups in the U.S. African American women have lower age-adjusted incidence of breast cancer compared with European Americans (1). However, breast cancer incidence is higher in African Americans who are 35 years of age or younger (2). African American women are also diagnosed, on average, with later stage of disease, larger tumors, and are more likely to present with lymph node metastases at the time of diagnosis (2, 3). Thus, despite the lower lifetime incidence of breast cancer among African American women compared to European American women, their breast cancer mortality rate is higher (4–6), particularly among younger women (7).
The expression of steroid hormone receptors (estrogen and progesterone receptors) in breast cancer tumors also varies substantially by population. African American women are diagnosed more frequently with estrogen receptor negative (ER−) and progesterone receptor negative (PR−) breast cancer compared with European American women (5, 7–9). In the Women’s Health Initiative, 32% of breast cancers among postmenopausal African American women were ER− with poor/anaplastic grade in comparison to only 10% among European American women, a difference which remained after adjustment for multiple potentially confounding factors, including differential access to health care (10). Given the greater incidence of hormone receptor negative, high-grade disease among African Americans, we hypothesized that there may be one or more genetic variants with increased frequency in populations of African origin, which predispose women to this more aggressive form of breast cancer.
Admixture mapping is a powerful approach for identifying genetic variants for common phenotypes that have large allele frequency differences between ancestral populations (11–14). Admixed populations are defined as populations in which two or more ancestral groups have been mixing over several generations. Recently admixed populations show extended linkage disequilibrium (LD) between markers that have a large difference in allele frequency between ancestral populations and are, therefore, informative about ancestry (ancestry informative markers or “AIMs”) (13, 15). The principle of admixture mapping is to identify regions of the genome with greater estimated ancestry from one of the ancestral populations than the chromosomal average in individuals from an admixed group. These regions may highlight candidate risk loci that are associated with complex phenotypes. We have previously utilized this approach to identify risk variants for prostate cancer at 8q24 that are common in African American men and contribute to their increased disease incidence (16).
Here we performed an admixture-based genome-wide scan in 1,484 African American women with invasive breast cancer pooled from 6 population-based studies. Samples were typed at ~1,500 AIMs to search for loci that might harbor predisposing variants for breast cancer, and more specifically, loci that may contribute to specific breast cancer phenotypes, such as ER− disease, a trait which is more common in African American women.
Materials and Methods
Samples
This analysis includes samples from 6 population-based breast cancer studies described in brief below.
The Multiethnic Cohort Study (MEC)
The MEC is a prospective cohort that includes over 215,000 individuals from Hawaii and California (primarily Los Angeles) that was assembled between 1993 and 1996 (17, 18). The cohort is comprised predominantly of African Americans, Native Hawaiians, Japanese, Latinos and European Americans. Beginning in 1994, blood samples were collected from incident breast cancer cases identified by cohort linkage to Surveillance, Epidemiology and End Results (SEER) registries, as well as a random sample of MEC participants to serve as controls for genetic analyses. The present study includes 423 invasive African American breast cancer cases from the MEC aged 45–82 years at diagnosis.
The Los Angeles component of the Women’s Contraceptive and Reproductive Experiences Study (CARE): a population-based case control study, included African American and Caucasian women with invasive breast cancer and control subjects, aged 35 to 64 years (19). Incident cases diagnosed between 1994 and 1998 were identified by the Los Angeles SEER registry. This study contributed 384 invasive African American breast cancer cases to the scan.
The Learning the Influence of Family and the Environment Study (LIFE)
The LIFE study included invasive African American breast cancer cases from Los Angeles county aged 20 to 49 years (20). Incident cases diagnosed between 2000 and 2003 were identified from the Los Angeles SEER registry. In the current study we used DNA samples obtained from 140 invasive cases.
The Womens’ Circle of Health Study (WCHS) includes African American women, 20 to 65 years of age, newly diagnosed with a first primary, histologically confirmed breast cancer. Cases were identified from major metropolitan hospitals in New York City serving a large minority population, and from the 8 counties in New Jersey bordering the Hudson River. The present study includes 194 invasive breast cancer cases.
The San Francisco Bay Area Breast Cancer Study (SFBABCS), is a population-based case-control study of breast cancer in Hispanic, African-American and non-Hispanic white women (21, 22). Incident cases of invasive breast cancer aged 35–79 years were identified through the Greater Bay Area Cancer Registry. The present analysis includes 191 African American breast cancer cases diagnosed between 1997 and 1999.
Northern California site of the Breast Cancer Family Registry (BCFR)
The BCFR is an international collaboration of six academic and research institutions, established in 1995 with support from the US National Cancer Institute to serve as a resource for genetic studies of breast cancer (23). The California site enrolled newly diagnosed breast cancer cases aged <65 years that were identified through the Greater Bay Area Cancer Registry. The present study includes 314 unrelated African American breast cancer cases diagnosed between 1995 and 2003.
Genotyping
Invasive breast cancer cases in these six studies (1,646) were genotyped for 2 AIM panels using the Illumina GoldenGate assay (Each panel consisting of 1,536 AIMs). The WCHS, SFBABCS, and BCFR samples (set 1, n=699) were genotyped at UCSF with a phase 2 panel, which was first published by Reich et al. 2007 (24). From this panel, 196 markers were dropped because of failure and replaced with 196 additional markers (Phase 2 panel version b) (Supplementary Table 1, 196 new SNPs are highlighted). A set of markers was selected based on allele frequency differences in West Africans from London and Europeans from CEPH and they were scored by the Illumina snp_score, which predicts how well the markers will genotyped. Fst and delta values (two measures of allele frequency difference between populations) were calculated for the markers. A total of 196 evenly spaced markers with the top scores for the Ilumina snp-score and with the highest Fst (>0.4) and delta values (>0.6) were selected to include in the new Phase 2 panel version b. The MEC, CARE and LIFE studies (set 2, n=947) were genotyped at the USC Genomics Core Laboratory with a phase 3 AIM panel1.
We genotyped the 1,646 samples for a total of 2,427 AIMs. For each set, we removed samples and SNPs that did not pass our quality control (QC) criteria. We removed samples with missing histology (set 1, n=88; set 2, n=0) and those with low call rates (defined as <85%) or that showed genotypes that are not consistent with the expectation based on the estimated global European ancestry (25) (set 1, n=13; set 2, n=56). We removed 5 samples because of overlap between studies. Overall, we removed 106 samples from set 1 and 56 samples from set 2. We also removed 187 AIMs that either had low call rates (<85%) or did not pass the different filters we applied to the data before analysis, which include a test of plausibility of parental allele frequencies, a measure of Hardy-Weinberg equilibrium with special attention to excess heterozygosity, and a linkage disequilibrium test (25). For QC, 8 duplicate pairs were analyzed in set1, and 8 duplicate pairs plus 8 CEU HapMap trios were analyzed in set 2. The overall QC concordance rate was >99.9% for both SNP panels. The final data-set consisted of 1,484 invasive breast cancer cases (593 from set 1 and 891 from set 2) and 2,240 AIMs, with 645 SNPs overlapping between the two sets. The final average number of AIMs per individual used in the analysis was 1,370.
Data analysis
Ancestry estimation
We used the ANCESTRYMAP software (26) as the central engine of the analysis. ANCESTRYMAP calculates the percentage of ancestry for each individual in the study. These estimates are reported in Supplementary Table 2 along with the standard deviations.
Association between global ancestry and tumor characteristics
We tested the association between proportion of global individual European ancestry (values range from 0 to 1) and ER, ER/PR status, stage (localized vs. non-localized (nonlocalized tumors includes those with regional extension only, regional nodes only, regional extension and nodes and remote)) and grade (1&2 vs. 3) using logistic regression models run with the STATA statistical package. Reported ORs refer to the difference in risk associated with a change in European ancestry proportion from 0 to 1. Age at diagnosis and study were included in the basic models as covariates. The adjusted models also included the following covariates: age at first full term pregnancy and number of full term pregnancies (0=no pregnancies, 1=1 or 2 children at age less than 21, 2= 1 or 2 children at age 21 or older, 3= 3 or more children at age less than 21, and 4= 3 or more children at age 21 or older -categorical), age at menarche (1=less or equal to 12, 2=13–14, 3=15 or more -categorical), body mass index (BMI) (continuous), family history of breast cancer in first degree relative (0=no, 1=yes -categorical), hormone replacement therapy (HRT) and menopausal status (0=pre-menopausal and no current HRT, 1=post-menopausal and no current HRT, 2=post-menopausal and current HRT -categorical).
Association between locus specific ancestry and breast cancer or tumor characteristics
The LOD score for association is defined as the log of the likelihood ratio of the data under a disease locus model vs. a no disease locus model. The ANCESTRYMAP software uses Bayesian statistics and thus requires specification of a prior distribution on risk models before carrying out the analysis. We carried out the analysis assuming a prior distribution for ancestry risk that tested both for loci associated with increased risk due to European ancestry, and increased risk due to African ancestry. For all phenotypes (all cases, ER status, ER/PR combined status, ER/grade combined status, ER/age combined status, stage (localized vs. non-localized), we ran a prior distribution considering equally likely models of 0.5, 0.6, 0.7, 0.8, 1.3, 1.5, 1.7 and 2.0-fold increased risk for European ancestry. The ANCESTRYMAP program calculates a log-factor for association at equally spaced points in the genome. A local score of 5, for example, means that the data at that locus are 105=100,000 times more likely under an appropriately weighted average of the disease models, than under the null model. We followed the criteria used by Deo et al. (24) of a high threshold of >5 to be considered genome-wide significant. The frequencies of the typed SNPs in the ancestral populations were estimated based on data from European Americans and West African controls from previous studies (16, 24, 27).
Construction of exclusion map
To obtain credible intervals for increased risk due to African or European ancestry across the genome, we modified the procedure described elsewhere (24). ANCESTRYMAP was run for each of the three case definitions (ER+ only, ER− only, all cases) using 85 independent disease risk models (0.30, 0.32, 0.34, 0.36 …, 1.94, 1.96 and 1.98-fold increased risk due to one European allele). We evaluated LOD scores at equally spaced points across the genome and searched for the maximum likelihood risk model at each of these points. This allowed computation of the 99.99% credible intervals for increased risk due to African (or European) ancestry by a likelihood ratio test, with the interval including all risk models for which the log-base-10 of the likelihood of the disease model was within 3.275 of the maximum. Assuming 500 independent loci in the genome, these correspond to 95% genome-wide credible intervals by the Sidak correction for multiple hypothesis testing.
Results
Descriptive and tumor characteristics for cases in each of the 6 studies as well as for the combined sample of 1,484 women are summarized in Table 1. The mean age at diagnosis of all cases was 54 years (range 22–83). The average percentage of European ancestry over all cases was 23% (range 1–98) and was relatively homogeneous among studies. The Women’s Circle of Health Study (WCHS) had the lowest average percentage of European ancestry (19%) and the Multiethnic Cohort study (MEC) had the highest (25%). We observed 31% of individuals with ER− tumors, 53% with ER+ tumors and 16% with missing status. ER− tumors were over-represented among younger cases as noted in the Learning the Influence of Family and the Environment study (LIFE) (42%) and the Los Angeles component of the Women’s Contraceptive and Reproductive Experiences study (CARE) (35%), which is consistent with previous reports (28–30). Regarding tumor stage, 53% of the individuals had localized tumors, 34% were nonlocalized and 13% had missing data. In the LIFE and CARE studies, which included higher proportions of younger cases, only about 50% of the tumors were localized. For tumor grade, we observed a similar pattern, with a smaller proportion of lower grade tumors (1&2) in the two studies that targeted younger women compared to the other studies. Percent European ancestry was significantly higher among individuals with hormone receptor-positive tumors compared with hormone receptor-negative tumors and women with localized disease compared to women with non-localized disease (Tables 1 and 2). We also observed a significantly higher percent European ancestry in women who were never pregnant compared to women who had one or more full term pregnancies (Table 1).
Table 1.
Sample and tumor characteristics for 1,484 African American women with breast cancer4
| SFBABCS | BCFR | CARE | LIFE | MEC | WCHS | Total | EA % (SD) | P2 | |
|---|---|---|---|---|---|---|---|---|---|
| N | 185 | 304 | 372 | 110 | 409 | 104 | 1484 | 23(15) | |
| Age mean (SD) | 55.2(11.7) | 50.4(9.3) | 48.8(7.9) | 42.3(5.3) | 65.8(9.0) | 50.0(9.5) | 54.2(11.9) | ||
| BMI mean kg/m2 (SD) | 30.4(5.9) | 30.3(6.7) | 27.6(6.1) | 29.0(6.9) | 29.1(6.1) | 30.4(6.8) | 29.2(6.4) | ||
| FHBC1 | |||||||||
| Percent with FHBC | 15 | 31 | 11 | 15 | 20 | 17 | 19 | 24(17) | 0.57 |
| Percent without FHBC | 85 | 69 | 84 | 79 | 72 | 83 | 77 | 23(15) | |
| Age first full term preg. | |||||||||
| Percent no pregnancies | 22 | 25 | 13 | 25 | 15 | 8 | 18 | 25(17) | 0.035 |
| Percent <20 | 41 | 37 | 47 | 41 | 37 | 43 | 41 | 22(14) | |
| Percent 20–30 | 29 | 34 | 33 | 27 | 38 | 30 | 33 | 24(16) | |
| Percent >30 | 8 | 4 | 7 | 6 | 6 | 11 | 6 | 20(14) | |
| Age menarche | |||||||||
| Percent <=12 | 52 | 47 | 57 | 54 | 51 | 47 | 52 | 23(16) | 0.18 |
| Percent 13–14 | 33 | 39 | 33 | 37 | 37 | 40 | 36 | 23(15) | |
| Percent 15 or more | 14 | 12 | 10 | 9 | 10 | 13 | 11 | 23(16) | |
| Number of full term preg. | |||||||||
| Percent 0 | 22 | 23 | 13 | 24 | 15 | 8 | 17 | 25(17) | <0.01 |
| Percent 1–2 | 37 | 44 | 47 | 41 | 38 | 51 | 42 | 23(15) | |
| Percent 3–5 | 33 | 29 | 34 | 31 | 35 | 27 | 32 | 23(15) | |
| Percent 6 or more | 8 | 3 | 6 | 3 | 8 | 7 | 6 | 18(11) | |
| HRT/menopause status | |||||||||
| Percent pre-no HRT | 31 | 58 | 47 | 81 | 11 | 35 | 39 | 23(15) | 0.13 |
| Percent post-no HRT | 45 | 23 | 23 | 16 | 61 | 32 | 36 | 23(16) | |
| Percent post-yes HRT | 16 | 9 | 14 | 2 | 16 | 0 | 12 | 25(15) | |
| Percent estimated EA (SD) | 22(15) | 23(15) | 23(15) | 23(15) | 25(16) | 19(18) | 23(15) | <0.013 | |
| ER status, n(%) | |||||||||
| ER+ | 96(52) | 158(52) | 192(52) | 45(41) | 237(58) | 57(55) | 785(53) | 24(16) | 0.04 |
| ER− | 52(28) | 92(30) | 131(35) | 46(42) | 94(23) | 41(39) | 456(31) | 22(14) | |
| PR status, n(%) | |||||||||
| PR+ | 86(46) | 144(47) | 153(41) | 42(38) | 168(41) | 45(43) | 638(43) | 24(16) | <0.01 |
| PR− | 61(33) | 104(34) | 121(33) | 44(40) | 111(27) | 53(51) | 494(33) | 22(14) | |
| ER/PR status, n(%) | |||||||||
| ER+PR+ | 78(42) | 131(43) | 128(34) | 38(35) | 152(37) | 45(43) | 572(39) | 24(17) | <0.01 |
| ER−PR− | 44(24) | 78(26) | 92(25) | 43(39) | 77(19) | 41(39) | 375(25) | 22(14) | |
| ER+PR− | 17(9) | 26(9) | 28(8) | 1(1) | 34(8) | 12(12) | 118(8) | 21(14) | |
| ER−PR+ | 8(4) | 13(4) | 23(6) | 3(3) | 15(4) | 0(0) | 62(4) | 24(12) | |
| Stage, n(%) | |||||||||
| Localized | 118(64) | 143(47) | 186(50) | 58(53) | 281(69) | 0(0) | 786(53) | 25(16) | <0.01 |
| Non-localized | 61(33) | 85(28) | 183(49) | 50(45) | 124(30) | 0(0) | 503(34) | 22(14) | |
| Grade, n(%) | |||||||||
| 1 | 20(11) | 34(11) | 42(11) | 8(7) | 67(16) | 12(11) | 183(12) | 24(15) | 0.27 |
| 2 | 63(34) | 81(27) | 98(26) | 32(29) | 132(32) | 34(33) | 440(30) | 24(16) | |
| 3 | 71(38) | 121(40) | 194(53) | 61(56) | 143(36) | 51(49) | 641(43) | 23(15) |
SFBABCS: San Francisco Bay Area Breast Cancer Study; BCFR: Breast Cancer Family Registry; CARE: Contraceptive and Reproductive Experiences study; LIFE: Learning the Influence of Family and the Environment study; MEC: The Multiethnic Cohort study; WCHS: Women’s Circle of Health Study; HR: Hormone Receptor; EA: European Ancestry; FHBC: family history of breast cancer.
In first degree relatives
P value of ANOVA (variables are unadjusted), evaluating if there is a significant difference in percent European ancestry between different groups within variables. European genetic ancestry was log-transformed to approximate normality.
P value for the comparison of European genetic ancestry between studies.
Percents within the table do not add up to 100 because of missing data.
For this particular test that compared mean genetic ancestry for the different age groups at first full-term pregnancy we restricted the analysis to women who had at least one full-term pregnancy.
Table 2.
Association between tumor characteristics and proportion of global European genetic ancestry (values of European ancestry range from 0 to 1)
| Odds Ratio | 95% CI | P | |
|---|---|---|---|
| ER+ vs. ER− status (n=1241)1,2 | 2.35 | 1.06–5.20 | 0.034 |
| ER+ vs. ER− status adjusted3 | 2.06 | 0.90–4.71 | 0.087 |
| ER+PR+ vs. ER−PR− status (n=947)2 | 4.73 | 1.56–14.33 | 0.006 |
| ER+PR+ vs. ER−PR− status adjusted3 | 2.84 | 1.13–7.14 | 0.026 |
| Stage (Localized vs. Non-Localized, n=1289)2 | 2.89 | 1.22–6.81 | 0.015 |
| Stage adjusted4 | 2.65 | 1.11–6.35 | 0.029 |
| Grade (1&2 vs. 3, n=1264)2 | 1.60 | 0.77–3.32 | 0.205 |
| Grade adjusted4 | 1.21 | 0.48–3.08 | 0.687 |
ER+ coded as 1 and ER− coded as 0
Adjusted for age and study
Adjusted for number of full term pregnancies, age at first full term pregnancy, hormone replacement therapy use, menopausal status, BMI, age, study, age at menarche and family history of breast cancer
Adjusted for number of full term pregnancies, age at first full term pregnancy, hormone replacement therapy use, menopausal status, BMI, age, study, age at menarche, family history of breast cancer and estrogen receptor status
Compared to women with ER− tumors, women with ER+ tumors had higher European ancestry (OR=2.35, 95% CI: 1.06–5.20) (Table 2). This trend was observed both in cases with localized and non-localized tumors (localized: OR=1.60, p=0.39, n=641; nonlocalized: OR=2.08, p=0.30, n=429). For ER+PR+ (vs. ER−PR−) tumors the association between European ancestry and positive receptor status became stronger (OR=4.73, 95% CI: 1.56–14.33). We adjusted the models to include factors that have been found to correlate with hormone receptor status (i.e., number of full term pregnancies, age at first full term pregnancy, hormone replacement therapy, menopausal status, age at menarche, body mass index and family history of breast cancer). In the adjusted model, ER status alone was no longer significantly associated with ancestry (OR=2.06, 95% CI: 0.90–4.71). The ER+PR+ vs. ER−PR− analysis showed a significant ancestry effect. The OR of the unadjusted model was 4.73 (95% CI: 1.56–14.33, p<0.01). After we adjusted for potential confounders the effect of ancestry was reduced but remained statistically significant (OR=2.84, 95% CI: 1.13–7.14, p=0.026). Among the factors included in the adjusted model, number of full term pregnancies had the strongest effect, with nulliparous women being more likely to have ER+PR+ tumors compared to women who have one or more children (OR for being ER+PR+ if woman has one or more children: 0.40, 95% CI: 0.26–0.60, p<0.01). We observed an association between European ancestry and disease stage (localized vs. non-localized), with higher European ancestry among women with localized tumors (multivariate adjusted OR=2.65, 95% CI: 1.11–6.35) compared to women with non-localized disease. We did not find a significant relationship between tumor grade and European ancestry (Table 2).
Admixture mapping does not show significant or suggestive results either for breast cancer risk or for tumor characteristics
We next conducted a series of genome-wide admixture scans evaluating a number of breast cancer phenotypes (as described in Materials and Methods) among 1,484 African American women with breast cancer and 1,370 ancestry informative markers per subject, on average. The data were analyzed using an affected-only statistic, which calculates the likelihood of association based on an estimate of the ancestry at a particular location relative to the overall average ancestry of the individual’s genome.
No genome wide statistically significant association was observed between European or African ancestry and breast cancer at any specific locus (Table 3). The largest LOD score genome-wide was 2.9 (we set a threshold of >5 for significance (24)) on chromosome X and 2.4 on chromosome 10 (in both cases the African allele was associated with increased risk).
Table 3.
Admixture mapping whole genome scan LOD scores for 1484 African American women with breast cancer
| Cases | ER+ | ER− | ER+PR+ | ER−PR− | ER+(g 1&2) | ER− (g 3) | ER+PR+ (g 1&2) | ER−PR− (g 3) | RA | |
|---|---|---|---|---|---|---|---|---|---|---|
| N | 1484 | 785 | 456 | 572 | 375 | 462 | 334 | 331 | 286 | |
| Ch 3p24 | 0.73 | 2.86 | 0.15 | 2.18 | 0.1 | 1.35 | 0.23 | 0.89 | −0.12 | A |
| Ch 5p15 | 0.43 | 0.95 | 1.02 | 0.72 | 1.5 | 1.37 | 1.24 | 0.84 | 1.65 | A |
| Ch 10q26 | 2.39 | 2.41 | 1.86 | 1.56 | 1.06 | 0.83 | 1.11 | 1.09 | 1.15 | A |
| Ch 18q21 | −0.77 | 1.38 | −0.34 | 2.22 | −0.33 | 0.34 | 0.22 | 1.29 | −0.19 | E |
| Ch Xp22 | 2.94 | 2.57 | 0.73 | 1.66 | 0.89 | 0.93 | 1.69 | 1.54 | 0.54 | A |
RA: Risk allele; A: African; E: European; g: grade.
The best LOD scores, or scores higher than 2, for the different admixture mapping whole genome scans are in bold. Results are presented only for chromosomes that included the highest scores in a particular scan.
A series of analyses looking at hormone receptor status and at hormone receptor status and grade combined (Table 3) were not significant. Stratifying the analyses by age did not significantly alter the results. Case-case analyses were performed comparing women with tumors that were hormone receptor negative to those with hormone receptor positive tumors as well as women with localized tumors vs. non-localized tumors. The differences in locus specific ancestry were not significant.
Analysis of known breast cancer risk loci
We also searched for ancestry associations within regions that have previously been reported to be associated with breast cancer risk in other populations. Four genome-wide scans have been reported to date; all of them have been conducted in populations of European or Asian ancestry. The different regions that were found to be associated with risk were 4p14, 6q22, 7q22, 10q26, 5q11, 16q12, 11p15, 8q24, 2p24, 5p12, and 2q35 (31–36). Many of these regions have also been more strongly associated with ER+ status in Europeans (37). We found a weak deviation towards higher African ancestry within the 10q26 region compared to the rest of the chromosome; this region includes the FGFR2 gene. The FGFR2 gene has been repeatedly identified as a breast cancer susceptibility locus by genome wide association studies (31, 33–35) and has also recently been fine mapped to identify specific variants (38).
Exclusion map
We prepared an exclusion map for the three case definitions with the largest sample sizes: all cases, ER+ and ER− cases. At least 98% of the genome can be excluded as having a European effect on risk of 1.4 or more, and at least 96% can be excluded as having an African effect on risk of 1.5 or more (Table 4). The power of the ER status analysis is less than that for all cases, because of the smaller sample size. In the case of ER− disease, we can exclude 87% of the genome as having an increased risk of 1.8 or higher due to African ancestry and 92% as having an increased risk of 1.7 or higher due to European ancestry. In the case of ER+ disease, we can exclude 89% of the genome as having an increased risk of 1.6 or higher associated with African ancestry and 92% as having an increased risk of 1.5 or higher associated with European ancestry (Table 4).
Table 4.
Proportion of genome excluded as contributing to differential risk for all affected individuals and for ER positive and ER negative phenotypes, comparing African and European ancestries
| African2 | Percent of genome excluded3 | European2 | Percent of genome excluded3 | ||||
|---|---|---|---|---|---|---|---|
| ER+ | ER− | All | ER+ | ER− | All | ||
| 1.01 | 0.01 | 0.01 | 0.01 | 1.0 | 0.01 | 0.01 | 0.01 |
| 1.1 | 1 | 0.01 | 2 | 1.1 | 3 | 0.2 | 5 |
| 1.2 | 8 | 1 | 28 | 1.2 | 13 | 3 | 32 |
| 1.3 | 31 | 9 | 64 | 1.3 | 39 | 11 | 73 |
| 1.4 | 57 | 26 | 85 | 1.4 | 70 | 28 | 98 |
| 1.5 | 78 | 48 | 96 | 1.5 | 92 | 55 | 100 |
| 1.6 | 89 | 66 | 99 | 1.6 | 98 | 79 | 100 |
| 1.7 | 95 | 78 | 100 | 1.7 | 100 | 92 | 100 |
| 1.8 | 98 | 87 | 100 | 1.8 | 100 | 99 | 100 |
| 1.9 | 100 | 92 | 100 | 1.9 | 100 | 100 | 100 |
| 2.0 | 100 | 95 | 100 | 2.0 | 100 | 100 | 100 |
| 2.1 | 100 | 97 | 100 | 2.1 | 100 | 100 | 100 |
| 2.2 | 100 | 99 | 100 | 2.2 | 100 | 100 | 100 |
| 2.3 | 100 | 99 | 100 | 2.3 | 100 | 100 | 100 |
| 2.4 | 100 | 100 | 100 | 2.4 | 100 | 100 | 100 |
The percentage of the genome where the null hypothesis (relative risk due to ancestry = 1) is excluded is about 0.01% for all scenarios, as expected using a P<0.0001 significance cutoff, which is the corrected 5% cutoff for genome wide significance (assuming 500 independent loci).
Factor by which African (European) ancestry increases risk at this locus compared with European (African) ancestry
Percent of genome excluded as having this risk or more at P<0.05 genome wide
Discussion
The present study represents the first genome-wide admixture scan conducted in African American women with breast cancer. In this study, we did not find an association between breast cancer risk and African or European ancestry at any specific loci among all cases or within subtypes of breast cancer, at genome-wide levels of significance. We did detect European ancestry to be over-represented among women with ER+ tumors. However, adjustment for known breast cancer risk factors could explain this association. A significant association remained for ER+PR+ tumors following adjustment, which could be due to misclassification of these risk factors, or, other risk factors which we did not consider (e.g., alcohol consumption) or that we do not know about that do correlate with ancestry and influence tumor characteristics. At the same time, it is possible that this association is due to genetic risk factors that correlate with ancestry. We observed that nulliparity was associated with both ER+PR+ disease as well as European ancestry. The association between number of full term pregnancies and hormone receptors status has been reported before in African Americans and white women (29) and our data replicates these results. The association between nulliparity and ER+PR+ disease could be the result of an underlying biological mechanism or could be due to the correlation between this risk factor and other known or unknown risk factors that we did not account for. The association between European ancestry and nulliparity was also significant (p=0.01) but could not completely explain the association that we observed between ancestry and ER/PR status. We also detected European ancestry to be significantly over-represented among women with localized tumors compared to women with non-localized tumors (2.65, 95% CI: 1.11–6.35, p=0.029). This association could not be explained by the known breast cancer risk factors.
The exclusion map shows that for the analysis of the ER− cases we had reasonable power to detect an increased risk due to an African allele of 1.8 and above and an increased risk due to a European allele of 1.6 and above. Therefore, the fact that our scan did not detect any significant signal does not discard the possibility that ancestry effects of 1.7 or lower are present. The observed association between ancestry and ER/PR status supports this possibility and suggests that further analyses are needed with adequate power to detect ancestry effects on risk of 1.7 or less.
We detected a non-significant deviation towards higher African ancestry on chromosome 10q26 compared to the chromosomal average. This region includes the FGFR2 gene and a common variant that is associated with increased risk of breast cancer in Asian and European populations (33, 34, 38). A recently published study investigated FGFR2 variants in African Americans, Asians and Europeans in order to search for causative variants and to evaluate if the same variants were associated with risk of breast cancer in the different racial/ethnic groups (38). Based on association results and an analysis of DNase I hypersensitive sites looking at chromatin accessibility the conclusion was reached that two variants, rs2981578 and rs10736303, are the most likely to be causal variants. The frequency of these two variants is different in African populations compared to Europeans or Asians. The frequency of the risk allele for the variant rs2981578 is 0.93 in the HapMap African sample and 0.46 in the HapMap Europeans. A similar difference is observed for the rs10736303, with the risk allele having a frequency of 0.92 in Africans and 0.60 in Europeans2. The increase in African ancestry that we observed in the admixture mapping analysis within the 10q26 region could potentially be explained by the higher frequency of causal risk alleles in this region which are likely to be more common in African than European populations.
There was no apparent deviation from the average chromosomal ancestry for any other region of the genome previously reported to have a risk variant. Different studies have reported associations between variants in the FGFR2 gene and breast cancer risk, with per-allele ORs that vary between 1.20 and 1.30 (33, 34, 38–40). The reported ORs for the FGFR2 gene are among the higher reported ORs compared to those of other risk variants discovered though whole genome association studies (~1.25 compared to less than 1.20 (39)). Adding to this, the candidate variants within the FGFR2 gene show a large allele frequency difference between Europeans and Africans. Therefore, it is likely that we did not observe any other ancestry deviations because of lack of power (We had power above 80% to detect risk variants with an allele effect of 1.5 or larger. If the allele effect was ~1.2, then the allele frequency difference between the ancestral populations needed to be larger than 0.7 to achieve a power above 40%).
One limitation of this study is the sample size. Although the study included over 1,400 women, ER−PR− cases are still a minority of cases, even among African Americans, and thus, we had limited power to assess associations for the different breast cancer phenotypes.
Her2 status was not available for the majority of cases since most of the cases in the different studies were recruited at a time when Her2 status was not routinely assayed for clinical testing. Therefore, we were unable to analyze ER−PR−Her2- negative breast cancer cases (i.e., “triple-negatives”), an aggressive subset of tumors that has been estimated to be more common in African Americans than in European Americans (28–30, 41). Much larger studies in African populations, with available tumor specimen resources for tumor phenotyping, will be needed to evaluate the genetic contribution to the various breast cancer subtypes.
Information about ER and PR status, grade and stage, comes from pathology reports or from the cancer registry, depending on the study. Therefore, it is likely that there were differences in how the tumors were classified. This potential misclassification could have contributed to the negative results observed. However, the frequency of the different tumor characteristics in the 6 studies are similar and when they differ they do it in the expected direction given the age distribution of the women in the studies. This suggests that misclassification might not be a serious problem for these data, though caution must be taken in the interpretation of the results. Future studies involving centralized tumor marker data collection will be necessary to avoid the potential effect of misclassification in genetic epidemiology studies with multiple data sources.
The AIMs selected to infer genetic ancestry are assumed to have homogenous frequency within the African continent. Given that African Americans are likely to have a mixed ancestry from different regions of Western Africa (42) which might not shared the same allele frequencies for the markers used in the present study, results must be interpreted with caution.
The clinical implications of the differences in tumor presentation of African American women with breast cancer compared to European American patients are substantial. Although the overall incidence of breast cancer is lower in African American women, the mortality rate is higher in African American women than in European American women (43). This may be in part due to higher rates of ER− disease, since hormonal treatment, either with selective estrogen receptor modifiers (tamoxifen or raloxifene) or with aromatase inhibitors, is highly effective for ER+ disease only (44). Furthermore, ER− disease often occurs in younger women who have never had screening because they are younger than the standard screening age and because screening with mammography is less sensitive among younger women (45). The high rates of ER− disease among African Americans may also have implications for breast cancer prevention. Tamoxifen and raloxifene have been shown to prevent ER+ breast cancer in primary prevention studies and some have advocated that the medications be used in high risk women (44, 46). In addition, aromatase inhibitors may also be useful in prevention of breast cancer (47). However, there is no clear preventive strategy for ER− breast cancers. Identifying the causal factors that explain the difference in incidence of hormone receptor negative tumors between European American and African American women should be a high priority.
The present admixture mapping scan in 1,484 African American women with breast cancer suggests that the difference in breast cancer risk between Europeans and African Americans is unlikely to be due to an effect of a European or African allele on risk larger than 1.7. It also excludes an effect on risk for ER+ status larger than 1.9 and for ER− status larger than 2.4. Global ancestry association results, however, show a positive association of European ancestry with stage of disease, and with ER+PR+ disease. These associations could result from population differences in non-genetic risk factors or from the effect of multiple genetic variants each with a relatively moderate contribution to the ancestry related risk difference
Supplementary Material
Acknowledgments
Grant Support: Postdoctoral fellowship from the Prevent Cancer Foundation (L. Fejerman). The Multiethnic Cohort Study was supported by National Cancer Institute (NCI) grants CA63464 and CA54281. Komen foundation investigator initiated grant KG080165 (E. Ziv). The Womens’ Circle of Health Study is supported by grants: NCI R01 CA100598, DAMD17-01-1-0334. The San Francisco Bay Area Breast Cancer Study was funded by grants from the National Cancer Institute (R01 CA63446 and R01 CA77305) and the United States Army Medical Research Program (DAMD17-96-6071) (E.M. John). Richard and Susan Smith Family Foundation, Chestnut Hill, MA (M. Freedman). Burroughs Wellcome Career Development Award in the biomedical Sciences (D. Reich). The Los Angeles Component of the Women’s Contraceptive and Reproductive Experiences (CARE) Study was supported by a contract from the National Institute of Child Health and Human Development (N01-HD-3-3175) (L. Bernstein). The Breast Cancer Family Registry (BCFR) is funded by the National Cancer Institute, National Institutes of Health under RFA-CA-06-503 and through cooperative agreements with members of the Breast Cancer Family Registry and Principal Investigators. The registry contributing data to this analysis was supported by U01 CA69417 (Northern California Cancer Center). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the BCFR, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR.
Notes: We want to thank Loreall Pooler, David Wong, and David Van Den Berg for their laboratory assistance and Dr. Kristine Monroe and Hank Huang for their technical support. We also want to thank the study participants.
Footnotes
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