Polygenic Risk Prediction of Breast Cancer for Women of African Descent

非洲裔女性乳腺癌的多基因风险预测

• 批准号: 10748724
• 负责人: Dezheng Huo
• 金额: $ 51.53万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-19 至 2028-07-01
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10748724
• 关键词: Address; African; African American; African American population; African ancestry; Age; Asian; Asian ancestry; Asian population; Assessment tool; Breast Cancer Detection; Breast Cancer Genetics; Breast Cancer Model; Breast Cancer Risk Factor; Case/Control Studies; Clinical; Cohort Studies; Complex; Data; Data Pooling; Data Set; Development; Elasticity; Epidemiology; Estrogen Receptors; Estrogen receptor negative; Estrogen receptor positive; Ethnic Population; European ancestry; Family history of; Funding; Gene Frequency; Genes; Genetic; Genetic Counseling; Genetic Diseases; Incidence; Individual; Investigation; Knowledge; Lasso; Left; Life Style; Linkage Disequilibrium; Mammographic screening; Maps; Methods; Modeling; Mutation; Noise; Outcome; Penetrance; Performance; Population; Predisposition; Prevention; Public Domains; Quantitative Trait Loci; RNA Splicing; Race; Racial Equity; Reproductive History; Risk; Risk Assessment; Risk Factors; Sample Size; Scoring Method; Signal Transduction; Statistical Methods; Susceptibility Gene; Target Populations; Testing; Training; Translating; Variant; Veterans; Woman; access disparities; ancestry analysis; black women; cancer subtypes; causal variant; clinical practice; cohort; early onset; genetic predictors; genetic variant; genome wide association study; genome-wide; genome-wide analysis; genomic locus; high risk; improved; innovation; malignant breast neoplasm; mortality; multi-ethnic; non-genetic; novel; polygenic risk score; precision medicine; racial disparity; racial population; risk prediction; risk prediction model; risk stratification; risk variant; screening; statistics; tool; transcriptome; transcriptome sequencing; transcriptomics; translational impact; triple-negative invasive breast carcinoma

PROJECT ABSTRACT African Americans have the highest breast cancer mortality rate, highest incidence rate of early-onset breast cancer, and highest incidence rate of triple-negative breast cancer in the U.S. More than 220 susceptibility loci for breast cancer have been identified by genome-wide association studies (GWAS), mainly in population of European ancestry. Polygenic risk scores (PRS), which aggregate common genetic variants identified by GWAS, have been developed to predict genetic risk of breast cancer for European ancestry women and used in clinical practice, but the PRS for African American women has suboptimal accuracy. Therefore, we propose a comprehensive analytical study that leverages several types of existing genetic datasets for breast cancer available to us and in public domains to address three specific aims. First, we aim to conduct cross-ancestry fine-mapping analysis to identify a credible set of causal variants in 237 breast cancer susceptibility loci. Then we will develop parsimonious and robust PRS from the credible set of variants. We have compiled and harmonized genetic data from breast cancer GWASs in women of African ancestry, including 18,034 cases and 22,104 controls, and leverage the association results from European ancestry (>133,000 cases and >291,000 controls) and Asian (>22,000 cases and >22,000 controls) populations. Second, we aim to develop precise PRS using genome-wide data with several novel cross-ancestry statistical methods. We will develop PRS models for overall breast cancer and its subtypes (estrogen receptor positive and negative, and triple-negative breast cancer). Then we will validate the models generated in aims 1-2 in independent datasets (>14,000 cases and >82,000 controls) from case-control studies, ongoing cohort studies, and an ongoing risk-adaptive breast cancer screening trial. Third, we will integrate the best performed PRS with existing risk prediction models that are based on non-genetic risk factors. The resulting absolute risk models have a good potential to translate knowledge from GWAS to inform the practice of genetic counseling, breast cancer screening and prevention for African Americans. It has good potential to advance racial equity in breast cancer.

项目摘要 非裔美国人乳腺癌死亡率最高，早发发病率最高 三阴性乳腺癌的发病率在美国最高，超过220 乳腺癌的易感基因座已经通过全基因组关联研究（GWAS）确定，主要是 欧洲血统的人口。多基因风险评分（PRS），汇总常见的遗传变异 GWAS鉴定的，已经被开发用于预测欧洲血统乳腺癌的遗传风险 女性和临床实践中使用，但非裔美国女性的PRS具有次优的准确性。 因此，我们提出了一个全面的分析研究，利用现有的几种类型的遗传 乳腺癌的数据集提供给我们和公共领域，以解决三个具体目标。首先，我们的目标是 进行跨祖先精细映射分析，以确定237例乳腺癌患者中一组可信的因果变异， 癌症易感基因座然后，我们将开发简约和强大的PRS从可靠的变量集。 我们已经汇编和协调了非洲血统妇女乳腺癌GWAS的遗传数据， 包括18，034例病例和22，104例对照，并利用来自欧洲血统的关联结果 （> 133，000例和> 291，000对照）和亚洲（> 22，000例和> 22，000对照）人群。 第二，我们的目标是使用全基因组数据开发精确的PRS，其中包括几个新的跨祖先统计数据。 方法.我们将为整体乳腺癌及其亚型（雌激素受体阳性）开发PRS模型 阴性和三阴性乳腺癌）。然后我们将在中验证目标1-2中生成的模型 来自病例对照研究、正在进行的队列研究、 以及一项正在进行的风险适应性乳腺癌筛查试验。第三，我们将整合表现最佳的生产者责任计划， 与现有的基于非遗传风险因素的风险预测模型相结合。由此产生的绝对风险 模型有很好的潜力将GWAS的知识转化为遗传咨询的实践， 非裔美国人的乳腺癌筛查和预防。它具有促进种族平等的良好潜力， 乳腺癌

项目成果

Germline variants and somatic mutation signatures of breast cancer across populations of African and European ancestry in the US and Nigeria.

美国和尼日利亚非洲和欧洲血统人群乳腺癌的种系变异和体细胞突变特征。

• DOI: 10.1002/ijc.32498
• 发表时间: 2019
• 期刊: International journal of cancer
• 影响因子: 6.4
• 作者: Wang,Shengfeng;Pitt,JasonJ;Zheng,Yonglan;Yoshimatsu,ToshioF;Gao,Guimin;Sanni,Ayodele;Oluwasola,Olayiwola;Ajani,Mustapha;Fitzgerald,Dominic;Odetunde,Abayomi;Khramtsova,Galina;Hurley,Ian;Popoola,Abiodun;Falusi,Adeyinka;Ogundira
• 通讯作者: Ogundira

Validation of the Nigerian Breast Cancer Study Model for Predicting Individual Breast Cancer Risk in Cameroon and Uganda.

• DOI: 10.1158/1055-9965.epi-22-0869
• 发表时间: 2023-01-09
• 期刊: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology

Whole-genome analysis of Nigerian patients with breast cancer reveals ethnic-driven somatic evolution and distinct genomic subtypes.

• DOI: 10.1038/s41467-021-27079-w
• 发表时间: 2021-11-26
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Ansari-Pour N;Zheng Y;Yoshimatsu TF;Sanni A;Ajani M;Reynier JB;Tapinos A;Pitt JJ;Dentro S;Woodard A;Rajagopal PS;Fitzgerald D;Gruber AJ;Odetunde A;Popoola A;Falusi AG;Babalola CP;Ogundiran T;Ibrahim N;Barretina J;Van Loo P;Chen M;White KP;Ojengbede O;Obafunwa J;Huo D;Wedge DC;Olopade OI
• 通讯作者: Olopade OI

An enhancer variant associated with breast cancer susceptibility in Black women regulates TNFSF10 expression and antitumor immunity in triple-negative breast cancer.

• DOI: 10.1093/hmg/ddac168
• 发表时间: 2023-01-01
• 期刊: Human molecular genetics
• 影响因子: 3.5

Benign breast disease and breast cancer risk in African women: A case-control study.

非洲女性的良性乳腺疾病和乳腺癌风险：病例对照研究。

• DOI: 10.21203/rs.3.rs-3301977/v1
• 发表时间: 2023
• 期刊: Research square
• 作者: Omoleye,OlasubomiJ;Freeman,JincongQ;Oluwasanu,Mojisola;Adeniji-Sofoluwe,Adenike;Woodard,AnnaE;Aribisala,BenjaminS;Adejumo,PriscaO;Ntekim,Atara;Makumbi,Timothy;Ndom,Paul;Ajayi,IkeOluwapoO;Olopade,OlufunmilayoI;Huo,Dezheng
• 通讯作者: Huo,Dezheng