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.

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.