scholarly journals Polygenic Risk Scores for Prediction of Breast Cancer Risk in Women of African Ancestry: a Cross-Ancestry Approach

2021 ◽  
Author(s):  
Guimin Gao ◽  
Fangyuan Zhao ◽  
Thomas Ahearn ◽  
Kathryn L. Lunetta ◽  
Melissa A. Troester ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
African Ancestry ◽  
Penalized Regression ◽  
European Ancestry ◽  
Risk Scores ◽  
Training Set ◽  
Polygenic Risk ◽  
Validation Set

Polygenic risk scores (PRSs) are useful to predict breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remain relatively low. We aim to develop optimal PRSs for prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in women of African ancestry. The AA dataset comprised 9,235 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. Genetic variants were selected by forward stepwise logistic regression or lasso penalized regression in the training set and the corresponding PRSs were evaluated in the validation set. To improve accuracy, we also developed joint PRSs that combined 1) the best PRSs built in the AA training dataset, 2) a previously-developed 313-variant PRS in women of European ancestry, and 3) PRSs using variants that were discovered in previous GWASs in women of European and African ancestry and were nominally significant the training set. For overall breast cancer, the odd ratio (OR) per standard deviation of the joint PRS in the validation set was 1.39 (95%CI: 1.31-1.46) with area under receiver operating characteristic curve (AUC) of 0.590. Compared to women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 2.03-fold increased risk (95%CI: 1.68-2.44). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.609 and 0.597, respectively. The proposed PRS can improve prediction of breast cancer risk in women of African ancestry.

scholarly journals Generalizability of Polygenic Risk Scores for Breast Cancer in the Multiethnic eMERGE Study

2020 ◽  
Author(s):  
Cong Liu ◽  
Nur Zeinomar ◽  
Wendy K Chung ◽  
Krzysztof Kiryluk ◽  
Ali G Ghravi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
African Ancestry ◽  
European Ancestry ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Emerge Network ◽  
Increase Odds Ratio ◽  
Breast Cancer Family History

Background: The majority of polygenic risk scores (PRS) for breast cancer have been developed and validated using cohorts of European ancestry (EA). Less is known about the generalizability of these PRS in other ancestral groups. Methods: The Electronic Medical Records and Genomics (eMERGE) network cohort dataset was used to evaluate the performance of seven previously developed PRS (three EA-based PRSs, and four non-EA based PRSs) in three major ancestral groups. Each PRS was separately evaluated in EA (cases: 3939; controls: 28840), African ancestry (AA) (cases: 121; controls: 1173) and self-reported LatinX ancestry (LA) (cases: 92; controls: 1363) women. We assessed the association between breast cancer risk and each PRS, adjusting forage, study site, breast cancer family history, and first three ancestry informative principal components. Results: EA-based PRSs were significantly associated with breast cancer risk in EA women per one SD increase (odds ratio [OR]=1.45, 95% confidence interval [CI]=1.40-1.51), and LA women (OR=1.41, 95% CI=1.13-1.77), but not AA women (OR=1.13, 95% CI=0.92-1.40). There was no statistically significant association for the non-EA PRSs in all ancestry groups, including an LA-based PRS and an AA-based PRS. Conclusion: We evaluated EA-derived PRS for estimating breast cancer risk using the eMERGE dataset and found they generalized well in LA women but not in AA women. For non-EA based PRSs, we did not replicate previously reported associations for the respective ancestries in the eMERGE cohort. Our results highlight the need to improve representation of diverse population groups, particularly AA women, in research cohorts.

Impact of Personalized Genetic Breast Cancer Risk Estimation With Polygenic Risk Scores on Preventive Endocrine Therapy Intention and Uptake

2020 ◽  
pp. canprevres.0154.2020
Author(s):  
Julian O. Kim ◽  
Daniel J. Schaid ◽  
Celine M. Vachon ◽  
Andrew Cooke ◽  
Fergus J. Couch ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Endocrine Therapy ◽  
Risk Estimation ◽  
Risk Scores ◽  
Polygenic Risk

scholarly journals Prospective Evaluation of a Breast Cancer Risk Model Integrating Classical Risk Factors and Polygenic Risk in 15 Cohorts from Six Countries

2019 ◽  
Author(s):  
Amber N Wilcox ◽  
Parichoy Pal Choudhury ◽  
Chi Gao ◽  
Anika Hüsing ◽  
Mikael Eriksson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Cancer Prevention ◽  
Risk Model ◽  
European Ancestry ◽  
Polygenic Risk ◽  
The Us ◽  
Prospective Cohorts

ABSTRACTPURPOSERisk-stratified breast cancer prevention requires accurate identification of women at sufficiently different levels of risk. We conducted a comprehensive evaluation of a model integrating classical risk factors and a recently developed 313-variant polygenic risk score (PRS) to predict breast cancer risk.METHODSFifteen prospective cohorts from six countries with 237,632 women (7,529 incident breast cancer patients) of European ancestry aged 19-75 years at baseline were included. Calibration of five-year risk was assessed by comparing predicted and observed proportions of cases overall and within risk categories. Risk stratification for women of European ancestry aged 50-70 years in those countries was evaluated by the proportion of women and future breast cancer cases crossing clinically-relevant risk thresholds.RESULTSThe model integrating classical risk factors and PRS accurately predicted five-year risk. For women younger than 50 years, median (range) expected-to-observed ratio across the cohorts was 0.94 (0.72 to 1.01) overall and 0.9 (0.7 to 1.4) at the highest risk decile. For women 50 years or older, these ratios were 1.04 (0.73 to 1.31) and 1.2 (0.7 to 1.6), respectively. The proportion of women in the general population identified above the 3% five-year risk threshold (used for recommending risk-reducing medications in the US) ranged from 7.0% in Germany (∼841,000 of 12 million) to 17.7% in the US (∼5.3 of 30 million). At this threshold, 14.7% of US women were re-classified by the addition of PRS to classical risk factors, identifying 12.2% additional future breast cancer cases.CONCLUSIONEvaluation across multiple prospective cohorts demonstrates that integrating a 313-SNP PRS into a risk model substantially improves its ability to stratify women of European ancestry for applying current breast cancer prevention guidelines.

scholarly journals Polygenic risk scores for prediction of breast cancer risk in Asian populations

2021 ◽  
Author(s):  
Weang-Kee Ho ◽  
Mei-Chee Tai ◽  
Joe Dennis ◽  
Xiang Shu ◽  
Jingmei Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Asian Populations

Investigation of Triple-Negative Breast Cancer Risk Alleles in An International African-Enriched Cohort

2020 ◽  
Author(s):  
Rachel Martini ◽  
Yalei Chen ◽  
Brittany Jenkins ◽  
Isra Elhussin ◽  
Esther Cheng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Therapeutic Potential ◽  
African Ancestry ◽  
Case Series ◽  
European Ancestry ◽  
Risk Alleles

Abstract Large-scale efforts to identify breast cancer risk alleles have historically taken place among women on European ancestry, with recent efforts to validate these alleles or identify risk alleles applicable to women of African descent. We investigated the effect of previously reported breast cancer and triple-negative breast cancer (TNBC) risk alleles in our African enriched International Center for the Study of Breast Cancer Subtypes (ICSBCS) cohort. Using case-control and nested case-series approaches, we report that the Duffy-null allele (rs2814778) is associated with TNBC risk (OR = 3.814, p = 0.001), specifically among AA individuals, after adjusting for self-indicated race and west African ancestry (OR = 3.368, p = 0.007). We have also validated the protective effect of the minor allele of the ANKLE1 missense variant rs2363956 among AA for TNBC (OR = 0.4204, p = 0.005). We have shown that differential prevalence of the protective allele may reflect a polymorphic function of ANKLE1 in TNBC breast cancer outcomes. These AA specific risk alleles present opportunities for future studies of therapeutic potential that address race-specific differences in BC and TNBC risk and disease outcome.

scholarly journals Variants of estrogen-related genes and breast cancer risk in European and African American women

2014 ◽  
Vol 21 (6) ◽  
pp. 853-864 ◽  
Author(s):  
Lei Quan ◽  
Chi-Chen Hong ◽  
Gary Zirpoli ◽  
Michelle R Roberts ◽  
Thaer Khoury ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
African American Women ◽  
African Ancestry ◽  
European Ancestry ◽  
Health Study ◽  
Nucleotide Polymorphisms ◽  
Estrogen Exposure ◽  
Estrogen Synthesis

It has been observed previously that compared with women of European ancestry (EA), those of African ancestry (AA) are more likely to develop estrogen receptor (ER)-negative breast cancer, although the mechanisms have not been elucidated. We tested the associations between breast cancer risk and a targeted set of 20 genes known to be involved in estrogen synthesis, metabolism, and response and potential gene–environment interactions using data and samples from 1307 EA (658 cases) and 1365 AA (621 cases) participants from the Women’s Circle of Health Study (WCHS). Multivariable logistic regression found evidence of associations with single-nucleotide polymorphisms (SNPs) in theESR1gene in EA women (rs1801132, odds ratio (OR)=1.47, 95% CI=1.20–1.80,P=0.0002; rs2046210, OR=1.24, 95% CI=1.04–1.47,P=0.02; and rs3020314, OR=1.43, 95% CI=1.19–1.70,P=0.00009), but not in AA women. The only other gene associated with breast cancer risk wasCYP1A2in AA women (rs2470893, OR=1.42, 95% CI=1.00–2.02,P=0.05), but not in EA women. When stratified by ER status,ESR1rs1801132, rs2046210, and rs3020314 showed stronger associations in ER-positive than in ER-negative breast cancer in only EA women. Associations with theESR1SNPs in EA women also appeared to be stronger with longer endogenous estrogen exposure or hormonal replacement therapy use. Our results indicate that there may be differential genetic influences on breast cancer risk in EA compared with AA women and that these differences may be modified by tumor subtype and estrogen exposures. Future studies with a larger sample size may determine the full contribution of estrogen-related genes to racial/ethnic differences in breast cancer.

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