Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach.

Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.

Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women.

Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P < 0.05 from African ancestry GWAS meta-analysis (9241 cases and 10193 controls), then meta-analyze with European ancestry GWAS data (122977 cases and 105974 controls) from the Breast Cancer Association Consortium. The approach identifies four loci for overall breast cancer risk [1p13.3, 5q31.1, 15q24 (two independent signals), and 15q26.3] and two loci for estrogen receptor-negative disease (1q41 and 7q11.23) at genome-wide significance. Four of the index single nucleotide polymorphisms (SNPs) lie within introns of genes (KCNK2, C5orf56, SCAMP2, and SIN3A) and the other index SNPs are located close to GSTM4, AMPD2, CASTOR2, and RP11-168G16.2. Here we present risk loci with consistent direction of associations in African and European descendants. The study suggests that replication across multiple ancestry populations can help improve the understanding of breast cancer genetics and identify causal variants.

The COronavirus Pandemic Epidemiology (COPE) Consortium: A Call to Action.

The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19) pandemic presents challenges to the real-time collection of population-scale data to inform near-term public health needs as well as future investigations. We established the COronavirus Pandemic Epidemiology (COPE) consortium to address this unprecedented crisis on behalf of the epidemiology research community. As a central component of this initiative, we have developed a COVID Symptom Study (previously known as the COVID Symptom Tracker) mobile application as a common data collection tool for epidemiologic cohort studies with active study participants. This mobile application collects information on risk factors, daily symptoms, and outcomes through a user-friendly interface that minimizes participant burden. Combined with our efforts within the general population, data collected from nearly 3 million participants in the United States and United Kingdom are being used to address critical needs in the emergency response, including identifying potential hot spots of disease and clinically actionable risk factors. The linkage of symptom data collected in the app with information and biospecimens already collected in epidemiology cohorts will position us to address key questions related to diet, lifestyle, environmental, and socioeconomic factors on susceptibility to COVID-19, clinical outcomes related to infection, and long-term physical, mental health, and financial sequalae. We call upon additional epidemiology cohorts to join this collective effort to strengthen our impact on the current health crisis and generate a new model for a collaborative and nimble research infrastructure that will lead to more rapid translation of our work for the betterment of public health.

PHIP - a novel candidate breast cancer susceptibility locus on 6q14.1.

Most non-BRCA1/2 breast cancer families have no identified genetic cause. We used linkage and haplotype analyses in familial and sporadic breast cancer cases to identify a susceptibility locus on chromosome 6q. Two independent genome-wide linkage analysis studies suggested a 3 Mb locus on chromosome 6q and two unrelated Swedish families with a LOD >2 together seemed to share a haplotype in 6q14.1. We hypothesized that this region harbored a rare high-risk founder allele contributing to breast cancer in these two families. Sequencing of DNA and RNA from the two families did not detect any pathogenic mutations. Finally, 29 SNPs in the region were analyzed in 44,214 cases and 43,532 controls from BCAC, and the original haplotypes in the two families were suggested as low-risk alleles for European and Swedish women specifically. There was also some support for one additional independent moderate-risk allele in Swedish familial samples. The results were consistent with our previous findings in familial breast cancer and supported a breast cancer susceptibility locus at 6q14.1 around the PHIP gene.

Validity of self-reported breast cancer characteristics in a nationwide cohort of women with a family history of breast cancer.

BACKGROUND: Women may have incomplete understanding of a breast cancer diagnosis, leading to inaccurate reporting in epidemiological studies. However, it is not feasible to obtain consent for medical records from all women participating in a study. Therefore, it is important to determine how well self-reported breast cancer characteristics correspond with what is found in medical records, but few studies have evaluated agreement of self-reported breast cancer characteristics with abstracted medical records. METHODS: We calculated the positive predictive value (PPV) of self-reports compared to medical records and explored whether participant characteristics may have influenced reporting accuracy. We analyzed data from 2518 reported breast cancer cases from the Sister Study, a large nationwide cohort of women with a family history of breast cancer. RESULTS: Medical records or pathology reports were obtained for 2066 of 2518 (82%) women who reported incident breast cancer. Breast cancer was confirmed for over 99% (n = 2054) of women with medical records. Confirmation rates were high for invasive, ductal, hormone receptor positive, and HER2 negative breast cancers, with little variation by race/ethnicity or age. Self-reported in situ breast cancer had a lower PPV (64.2%), with medical records showing invasive breast cancer instead, especially for older and Hispanic women. Hormone receptor (ER and PR) negative and HER2 positive self-reports had lower PPVs (83.0%, 71.6%, and 66.1% respectively). Hispanic women and women ages 65 or older at diagnosis were less able to accurately report breast cancer stage, excluding stage I. CONCLUSIONS: Accuracy of reporting overall breast cancer and common subtypes is high. Despite having a family history of breast cancer and voluntarily enrolling in a study evaluating breast cancer risk factors, participants may have greater difficulty distinguishing between in situ and invasive breast cancer and may less accurately report other less common subtypes. Discrepancies may reflect women's poor understanding of information conveyed by health care providers or lack of consistent terminology used to describe subtypes.

The Sister Study Cohort: Baseline Methods and Participant Characteristics.

BACKGROUND: The Sister Study was designed to address gaps in the study of environment and breast cancer by taking advantage of more frequent breast cancer diagnoses among women with a sister history of breast cancer and the presumed enrichment of shared environmental and genetic exposures. OBJECTIVE: The Sister Study sought a large cohort of women never diagnosed with breast cancer but who had a sister (full or half) diagnosed with breast cancer. METHODS: A multifaceted national effort employed novel strategies to recruit a diverse cohort, and collected biological and environmental samples and extensive data on potential breast cancer risk factors. RESULTS: The Sister Study enrolled 50,884 U.S. and Puerto Rican women 35-74y of age (median 56 y). Although the majority were non-Hispanic white, well educated, and economically well off, substantial numbers of harder-to-recruit women also enrolled (race/ethnicity other than non-Hispanic white: 16%; no college degree: 35%; household income <$50,000: 26%). Although all had a biologic sister with breast cancer, 16.5% had average or lower risk of breast cancer according to the Breast Cancer Risk Assessment Tool (Gail score). Most were postmenopausal (66%), parous with a first full-term pregnancy <30y of age (79%), never-smokers (56%) with body mass indexes (BMIs) of <29.9 kg/m2 (70%). Few (5%) reported any cancer prior to enrollment. CONCLUSIONS: The Sister Study is a unique cohort designed to efficiently study environmental and genetic risk factors for breast cancer. Extensive exposure data over the life-course and baseline specimens provide important opportunities for studying breast cancer and other health outcomes in women. Collaborations are welcome. https://doi.org/10.1289/EHP1923.

Use of nonsteroidal anti-inflammatory drugs and reduced breast cancer risk among overweight women.

Chronic inflammation is associated with increased risk of multiple cancers, including breast cancer. Adipose tissues produce proinflammatory cytokines, and obesity is a risk factor for postmenopausal breast cancer. We evaluated the association of regular use of nonsteroidal anti-inflammatory drugs (NSAIDs) with breast cancer risk, overall and by body mass index (BMI) and tumor subtypes defined by estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 status. We conducted a population-based, case-control study involving 5,078 women aged 25-75 years who were recruited primarily from the Nashville metropolitan area of Tennessee. Multivariate unconditional logistic regression models were used to estimate odds ratios and 95 % confidence intervals for breast cancer risk after adjusting for multiple potential confounding factors. Regular use of any NSAID was associated with significantly reduced breast cancer risk (OR 0.78; 95 % CI 0.69-0.89). This association was observed for regular use of baby aspirin only (OR 0.82, 95 % CI 0.69-0.99), other NSAIDs only (OR 0.81, 95 % CI 0.69-0.95), and both baby aspirin and other NSAIDs (OR 0.52, 95 % CI 0.40-0.69). These significant inverse associations were found among overweight women (BMI ≥25 kg/m(2)) overall and by subtypes of breast cancer, but not among women with BMI <25 kg/m(2) (P for interaction = 0.023). Regular use of NSAIDs was inversely associated with breast cancer risk, particularly among overweight women. Overweight women may benefit more from the protective effects of NSAID use than normal-weight women.

Associations of hormone-related factors with breast cancer risk according to hormone receptor status among white and African American women.

BACKGROUND: Causes of racial disparities in breast cancer incidence and mortality between white and African American women remain unclear. This study evaluated associations of menstrual and reproductive factors with breast cancer risk by race and cancer subtypes. PATIENTS AND METHODS: Included in the study were 1866 breast cancer cases and 2306 controls recruited in the Nashville Breast Health Study, a population-based case-control study. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: African American women were more likely to have estrogen receptor-negative (ER(-)), progesterone receptor-negative (PR(-)), and triple-negative (ER(-)PR(-)HER2(-)) breast cancer than white women. Age at menarche (≥ 14 years) and multiparity (≥ 3 live births) were inversely associated with ER(+) tumors only, whereas late age at first live birth (> 30 years) and nulliparity were associated with elevated risk; such associations were predominantly seen in white women (OR = 0.70, 95% CI = 0.55-0.88; OR = 0.72, 95% CI = 0.56-0.92; OR = 1.42, 95% CI = 1.13-1.79; OR = 1.32, 95% CI = 1.06-1.63, respectively). Age at menopause between 47 and 51 years was associated with elevated risk of ER(-) tumors in both white and African American women. Among women who had natural menopause, positive association between ever-use of hormone replacement therapy and breast cancer risk was seen in white women only (OR = 1.39, 95% CI = 1.03-1.87). CONCLUSION: This study suggests that certain hormone-related factors are differentially associated with risk of breast cancer subtypes, and these associations also differ by race.

Interactions of hormone replacement therapy, body weight, and bilateral oophorectomy in breast cancer risk.

PURPOSE: To examine potential modifying effects of body weight and bilateral oophorectomy on the association of hormone replacement therapy (HRT) with risk of breast cancer, overall and by subtypes according to status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (Her2) among postmenopausal women. EXPERIMENTAL DESIGN: This analysis included 2,510 postmenopausal white women recruited in the Nashville Breast Health Study, a population-based case-control study of breast cancer. Multivariable logistic regression was used to estimate ORs and 95% confidence intervals (CI) for associations between HRT use and risk of breast cancer overall and by subtypes, adjusted for age and education. RESULTS: Among women with natural menopause and body mass index (BMI) < 25 kg/m(2), ever-use of HRT was associated with increased breast cancer risk (OR, 1.95; 95% CI, 1.32-2.88). Risk was elevated with duration of HRT use (P for trend = 0.002). Similar association patterns were found for ER(+), ER(+)PR(+), and luminal A cancer subtypes but not ER(-), ER(-)PR(-), and triple-negative cancer. In contrast, ever-HRT use in overweight women (BMI ≥ 25 kg/m(2)) showed no association with risk of breast cancer overall or by subtypes; interaction tests for modifying effect of BMI were statistically significant. Ever-HRT use was associated with decreased breast cancer risk (OR, 0.70; 95% CI, 0.38-1.31) among women with prior bilateral oophorectomy but elevated risk (OR, 1.45; 95% CI, 0.92-2.29) among those with hysterectomy without bilateral oophorectomy (P for interaction = 0.057). Similar associations were seen for virtually all breast cancer subtypes, although interaction tests were statistically significant for ER(+) and luminal A only. CONCLUSION: Body weight and bilateral oophorectomy modify associations between HRT use and breast cancer risk, especially the risk of hormone receptor-positive tumors.

A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry.

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.

Local breast cancer spatial patterning: a tool for community health resource allocation to address local disparities in breast cancer mortality.

Despite available demographic data on the factors that contribute to breast cancer mortality in large population datasets, local patterns are often overlooked. Such local information could provide a valuable metric by which regional community health resources can be allocated to reduce breast cancer mortality. We used national and statewide datasets to assess geographical distribution of breast cancer mortality rates and known risk factors influencing breast cancer mortality in middle Tennessee. Each county in middle Tennessee, and each ZIP code within metropolitan Davidson County, was scored for risk factor prevalence and assigned quartile scores that were used as a metric to identify geographic areas of need. While breast cancer mortality often correlated with age and incidence, geographic areas were identified in which breast cancer mortality rates did not correlate with age and incidence, but correlated with additional risk factors, such as mammography screening and socioeconomic status. Geographical variability in specific risk factors was evident, demonstrating the utility of this approach to identify local areas of risk. This method revealed local patterns in breast cancer mortality that might otherwise be overlooked in a more broadly based analysis. Our data suggest that understanding the geographic distribution of breast cancer mortality, and the distribution of risk factors that contribute to breast cancer mortality, will not only identify communities with the greatest need of support, but will identify the types of resources that would provide the most benefit to reduce breast cancer mortality in the community.