Investigate interactive roles of environmental, behavioral and genetic factors on racial disparities in breast cancer outcomes

项目摘要： 健康差距广泛存在于乳腺癌的结果（发病率，生存率和生活质量）。当 与白色女性相比，非裔美国女性的乳腺癌复发率和死亡率更高， 癌症虽然发病率较低。众所周知，社区和个人层面 风险因素在乳腺癌预后中起着重要作用。在我们以前的研究中，我们开发了一种 中介分析方法，以确定有助于三阴性乳腺癌健康差异的新生物标志物 癌症（TNBC）。我们还开发了一种新的多层次中介分析方法，允许纵向 对居住环境和个人风险因素的评估，共同用于确定 种族和健康结果之间的机械联系。通过包括个人和环境的措施， 我们的方法能够解释健康结果中存在的差异。在这个项目中，我们的目标是 利用All of Us项目收集的综合数据库调查观察到的种族差异 乳腺癌的预后使用新的多级中介分析方法，我们将识别可修改的 这些因素可以解释在乳腺癌结果中观察到的种族差异。风险因素是 考虑的措施包括环境（例如污染测量）和个人水平（例如， 吸烟行为和基因表达）。这些信息将帮助护理人员设计精准医疗， 决策者评价旨在改善治疗和减少健康差距的干预措施。我们有 将我们的方法实现为R包（mlma），为研究社区提供开放访问 用于执行多级中介分析的软件。我们计划进一步开发用于交互式Web的API 软件的实现，使所有的研究人员可以使用的方法，而无需编程的要求。

Project Summary: Health disparities exist widely in the breast cancer outcomes (incidence, survival, and quality-of-life). When compared with white women, African American women have higher recurrence and death rates from breast cancer although they have a lower incidence rate. It is well established that both community and individual level risk factors play important roles in breast cancer outcomes. In our previous studies, we have developed a mediation analysis method to identify new biomarkers that contribute to health disparities in triple-negative breast cancer (TNBC). We also developed a new multilevel mediation analysis method that allows for longitudinal assessments of both residential environments and individual risk factors to be jointly utilized in determining the mechanistic link between race and health outcomes. By including measures of individual and environmental factors, our methods are capable of explaining existing disparities in health outcomes.In this project, we aim to utilize the comprehensive database collected by the All of Us project to investigate the observed racial disparities in breast cancer outcomes. Using the novel multilevel mediation analysis method, we will identify modifiable factors that can explain the racial disparities observed in breast cancer outcomes. The risk factors to be considered include measures at both the environmental (e.g. pollution measurements) and individual levels (e.g., smoking behavior and gene expressions). The information will help caregivers design precision medicine and policymakers evaluate interventions that aim at improving treatment and reducing health disparities. We have implemented our method as an R package (mlma) to provide the research community with open access to software for performing multilevel mediation analysis. We plan to further develop an API for an interactive web implementation of the software so that all researchers can use the method without the programming requirement.