Improving Prediction of Asthma-related Outcomes with Genetic Ancestry-informed Lung Function Equations

利用遗传祖先信息的肺功能方程改善哮喘相关结果的预测

• 批准号: 10723861
• 负责人: Jonathan Witonsky
• 金额: $ 17.4万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10723861
• 关键词: Affect; Algorithms; Area; Asthma; Black American; Black race; Bone Marrow Transplantation; California; Caring; Characteristics; Child; Childhood; Clinical; Clinical Investigator; Clinical Research; Data; Detection; Development; Development Plans; Diagnosis; Disease; Disparity; Educational workshop; Environmental Risk Factor; Equation; Equity; Ethnic Origin; Ethnic Population; Faculty; Foundations; Funding; Future; Genetic; Genetic Determinism; Genetic Variation; Goals; Health Disparities Research; Hispanic; Hospitals; Hypersensitivity; Immunology; Individual; Knowledge; Latino; Latino Population; Letters; Lung diseases; Measurement; Measures; Mediation; Medical; Mentors; Methods; Modeling; National Center for Advancing Translational Sciences; Neighborhoods; Outcome; Participant; Patient Self-Report; Performance; Population; Precision Health; Predictive Analytics; Prognosis; Prospective Studies; Prospective cohort; Public Health; Questionnaires; Race; Recontacts; Research; Research Design; Research Support; San Francisco; Scholars Program; Severities; Socioeconomic Status; Structure; Symptoms; Testing; Training; Translational Research; Universities; Variant; analytical method; biomedical facility; career development; cohort; ethnic bias; experience; genetic epidemiology; genomic data; genomic locus; improved; innovation; interest; lung basal segment; meetings; member; multi-ethnic; novel; pediatric department; programs; prospective; pulmonary function; racial bias; racial discrimination; racial population; research and development; research facility; social; social determinants; social epidemiology; social factors

PROJECT SUMMARY Lung function measurements are routinely compared to racial/ethnic norms, biasing interpretation and perpetuating asthma disparities. The race/ethnicity-based lung function reference equations used to calculate these norms do not account for genetic ancestry—the genetic origin of one’s population, which can explain over 15% of lung function variation within a racial/ethnic group. Consequently, race/ethnicity-based equations misestimate lung function, often resulting in delayed disease detection and inadequate treatment, especially among populations disproportionately affected by asthma. Dr. Witonsky (candidate) derived equations that use genetic ancestry instead of race/ethnicity to more accurately predict lung function. While genetic ancestry- informed equations appear to remove racial/ethnic bias from lung function measurement, establishing their clinical utility and equity requires evidence that they better predict asthma-related outcomes. In addition, further research is needed to disentangle the social and genetic determinants of genetic ancestry differences in lung function. The proposed mentored research will address these knowledge gaps using data from existing and new cohorts of Black and Hispanic/Latino individuals with and without asthma via three specific aims: (1) to evaluate genetic ancestry-informed, race/ethnicity-based, and “one size fits all” lung function equations for predicting asthma-related outcomes, (2) to quantify the proportion of genetic ancestry differences in lung function that is explained by social exposures, and (3) to quantify the proportion of genetic ancestry differences in lung function that is explained by known lung function-associated genetic loci. In support of this research and Dr. Witonsky’s goal of becoming an independent clinical investigator, this K23 proposal includes formal training with experts in the areas of asthma translational and clinical research (Dr. Prescott Woodruff, primary mentor); advanced statistical and predictive analytic methods (Dr. Stephen Shiboski, co-mentor); social epidemiology and health disparities research (Dr. Luísa Borrell, co-mentor); genetic epidemiology (Dr. Elad Ziv, co-mentor); and statistical genetics (Dr. Noah Zaitlen, advisor). In addition, professional development planning will involve structured meetings with Dr. Woodruff and a leader within Dr. Witonsky’s Division of Pediatric Allergy, Immunology, and Bone Marrow Transplant (Dr. Morna Dorsey, advisor). As a faculty member in the Department of Pediatrics at the University of California, San Francisco, Dr. Witonsky will have access to world-class biomedical and research facilities, workshops and seminars, and an NCATS-funded K Scholars Program. Completion of the proposed research and career development activities in this application will inform the development of an R01 proposal and enable Dr. Witonsky to develop an innovative research program applying computational precision health methods that integrate clinical, social, and genomic data to reduce asthma disparities.

项目摘要 通常将肺功能测量与种族/种族规范，偏见解释和 永久性哮喘分布。用于计算的基于种族/种族的肺功能参考方程 这些规范不能解释遗传血统 - 一个人口的遗传来源，可以解释 种族/族裔中肺功能变化的15％。因此，基于种族/种族的方程式 错误的肺功能，通常导致疾病检测延迟和治疗不足，尤其是 在受哮喘影响不成比例的人群中。 Witonsky博士（候选人）派生的方程式 遗传血统，而不是种族/种族，以更准确地预测肺功能。而遗传血统 - 知情方程式似乎从肺功能测量中消除了种族/种族偏见，建立了他们的 临床效用和公平性需要证据表明它们更好地预测了与哮喘相关的结果。另外，进一步 需要进行研究以消除肺部遗传血统差异的社会和遗传决定因素 功能。拟议的讨论研究将使用现有和新的数据来解决这些知识差距 黑色和西班牙裔/拉丁美洲人的同类人群，有和没有哮喘的三个特定目标：（1）评估 遗传血统，基于种族/种族的基于种族/种族，“一个尺寸适合所有”肺功能方程 与哮喘相关的结果，（2）量化肺功能遗传血统差异的比例 用社会暴露解释，（3）量化肺功能遗传祖先差异的比例 这是通过已知的肺功能相关遗传基因座来解释的。支持这项研究和Witonsky博士的 成为独立临床研究者的目标，该K23提案包括与专家的正规培训 哮喘转化和临床研究的领域（Prescott Woodruff博士，主要导师）；先进的 统计和预测分析方法（Stephen Shiboski博士，联合学）；社会流行病学与健康 差异研究（LuísaBorrell博士，联合学者）；遗传流行病学（Elad Ziv博士，同事）；和统计 遗传学（Noah Zaitlen博士，顾问）。此外，专业发展计划将涉及结构化 与Witonsky博士的儿科过敏，免疫学和 骨髓移植（Morna Dorsey博士，顾问）。作为儿科系的教职员工 加利福尼亚大学旧金山，维顿斯基博士将获得世界一流的生物医学和研究 设施，讲习班和半小伙子以及NCATS资助的K学者计划。拟议的完成 本应用程序中的研究和职业发展活动将为R01提案的开发提供信息 并使Witonsky博士能够制定一项应用计算精度健康的创新研究计划 整合临床，社会和基因组数据以减少哮喘分布的方法。