Methods for Mendelian randomization and mediation analysis using integrative genetic and genomic data for breast cancer

项目总结 张浩宇博士是一名统计学家，他的最终职业目标是纳入先进的因果推理 将技术转化为遗传学和生物学研究，以便在流行病学和生物科学领域取得有影响力的进展 临床决策。他提出的研究将开发强大的因果推理方法，以 确定导致乳腺癌风险的因果风险因素和潜在的遗传途径。 候选人：张博士，哈佛大学生物统计学系博士后 公共卫生部(HSPH)。他在约翰·霍普金斯大学获得了生物统计学博士学位。他之前的作品 在乳腺癌全基因组关联研究中，专注于识别遗传关联和 构建多基因风险已经为他进行拟议的研究做好了准备。拟议的职业发展 计划将以他之前的训练为基础，制定三个训练目标，以增强成为一名 独立调查员：1)获取并应用尖端的因果推理方法，以适用于 基因数据集；2)获得分子生物学和癌症方面的知识；3)培养领导力和专业性 具备进行多学科分析的技能。 导师/环境：张博士组建了一个强大的导师委员会，与 拟议研究所需领域的专业知识。所有的导师都承诺与他在一个 定期参加咨询会议，每六年监督一次培训和研究进展 月份。作为一家机构，HSPH致力于帮助年轻的研究人员。张博士将有权访问 专业和职业发展资源，包括专业发展课程、写作和 论文和拨款申请的编辑支持等。 研究：乳腺癌的风险因素包括生殖和生活事件(统称为经典风险 因素)和遗传因素；然而，将这些风险因素与 乳腺癌目前还不清楚。为了解决这两个问题，他将开发一种强大而强大的方法来 孟德尔随机分析估计经典危险因素与乳腺癌之间的因果关系 风险(目标1)。他还将开发一种因果调解方法，将函数注释数据集集成到 确定乳腺癌风险的潜在途径(目标2)。在目标3中，他将应用这两个标准 在目标1和目标2中开发的方法和新方法关于最大的乳腺癌数据集 多民族融合工程。这项提案的结果将提供先进的统计工具，以 确定因果关系，阐明潜在的遗传途径，并指导个性化的发展 治疗和预防策略。该提案还将为他提供所需的培训和研究 经验成为一项具有偶然推断和乳腺癌专业知识的独立研究。

Project summary Haoyu Zhang, PhD is a statistician whose ultimate career goal is incorporating advanced causal inference techniques into genetics and biological research in order to make impactful advances in epidemiological and clinical decision-making. The research he proposes will develop powerful causal inference approaches to identify causal risk factors and underlying genetic pathways leading to the risk of breast cancer. Candidate: Dr. Zhang is a postdoctoral fellow in the Department of Biostatistics at Harvard T.H. Chan School of Public Health (HSPH). He completed a Ph.D. in Biostatistics at Johns Hopkins University. His previous work in breast cancer genome-wide association studies (GWAS) focusing on identifying genetic associations and building polygenic risk has prepared him to conduct the proposed research. The proposed career development plan will build upon his previous training with three training goals to enhance trajectory toward becoming an independent investigator: 1) acquire and apply cutting edge causal inference methodologies to apply on large genetic datasets; 2) gain knowledge in molecular biology and cancer; 3) develop leadership and professional skills to conduct multidisciplinary analysis. Mentors/Environment: Dr. Zhang has assembled a strong mentoring committee with complementary expertise in the required fields for the proposed research. All the mentors have committed to meet with him in a regular basis and participate the advisory meeting to oversight his training and research progress every six months. As an institution, HSPH is committed to help young researchers. Dr. Zhang will have access to professional and career development resources, which include professional development courses, writing and editing support for papers and grant applications, etc. Research: Risk factors for the breast cancer include reproductive and life events (collectively classic risk factors) and genetic factors; however, the causal associations and pathways linking these risk factors with breast cancer are unclear. To solve these two issues, He will develop a robust and powerful approach for Mendelian randomization analysis to estimate the causal effects between classic risk factors and breast cancer risk (Aim 1). He will also develop a causal mediation approach integrating functional annotation datasets to identify the underlying pathways for breast cancer risk (Aim 2). In Aim 3, he will apply both the standard approaches and novel approaches developed in Aim 1 and 2 on the largest breast cancer GWAS dataset from the multi-ethnic Confluence Project. The results of this proposal will provide advanced statistical tools to identify causal effect, elucidate the underlying genetic pathways and guide developments of personalized therapeutics and prevention strategies. The proposal will also provide him the required training and research experience to become an independent research with casual inference and breast cancer expertise.