Genetic and social determinants of pharmacological health outcomes in ancestrally diverse populations

祖先不同人群药理健康结果的遗传和社会决定因素

• 批准号: 10578117
• 负责人: Akinyemi Oni-Orisan
• 金额: $ 61.67万
• 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: 2023-07-01 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10578117
• 关键词: Address; Adverse drug event; African American population; All of Us Research Program; American; Appointment; Biological; Biology; Biomedical Research; Black race; Characteristics; Clinical; Clinical Pharmacology; Communities; Country; Data; Data Set; Descriptor; Disease; Disease susceptibility; Dose; East Asian; Electronic Health Record; Ensure; Environment; Epigenetic Process; Equity; Ethnic Origin; Ethnic Population; European; Exclusion; Failure; Foundations; Future; Gene Expression; Genes; Genetic; Genetic Determinism; Genetic Polymorphism; Goals; Harm Reduction; Health; Healthcare; Heritability; Individual; Infrastructure; Institution; Knowledge; Label; Latino; Latino Population; Life Style; Link; Mexican Americans; Minority Groups; Molecular Genetics; Outcome; Participant; Patients; Pattern; Pharmaceutical Preparations; Pharmacogenetics; Pharmacogenomics; Pharmacotherapy; Phenotype; Population; Population Heterogeneity; Proxy; Puerto Rican; Quantitative Trait Loci; Race; Recommendation; Reporting; Research; Resources; Source; South Asian; Therapeutic; Traction; Underrepresented Populations; United States; United States Food and Drug Administration; United States National Institutes of Health; Variant; Work; Writing; admixture mapping; biobank; cardiovascular disorder epidemiology; care outcomes; clinical practice; cohort; demographics; diverse data; drug efficacy; efficacy outcomes; ethnic difference; ethnic minority; genetic variant; genome sequencing; genome wide association study; genome-wide; genome-wide analysis; health care disparity; improved; insight; medication compliance; medication safety; multidisciplinary; non-genetic; novel; pharmacologic; predicting response; predictive modeling; prevent; racial difference; racial minority; racial population; response; safety outcomes; side effect; social determinants; social factors; social health determinants; sociodemographics; study population; tool; transcriptome; whole genome

PROJECT SUMMARY/ABSTRACT Pharmacogenomics has the potential to dramatically improve health care outcomes, but is currently failing on diversity among its research participants. As a consequence, we do not fully understand all of the factors influencing pharmacogical response in underrepresented populations, including those that contribute to racial/ethnic differences in drug efficacy and safety as reported by Food and Drug Administration (FDA) drug labels. For example, the clinical validity of genetic variants that are common in research participants from historically-excluded populations (e.g., lower proportions of European genetic ancestry), but rare in wellrepresented study populations remains unknown. In addition, gene expression studies have already provided insight into the underlying biology of disease susceptibility for numerous conditions beyond what genome wide association study (GWAS) results alone have discovered, but have not been fully applied to studies of pharmacogenomic discovery. Furthermore, social determinants of health may impact pharmacological drug response from a biological standpoint even after taking into account the effects of these factors on drug adherence, access, and utilization (e.g. social determinants of epigenetics). Addressing this gap in knowledge has the potential to prevent future healthcare disparities that may be exacerbated as the infrastructure to support clinical pharmacogenomics continues to gain traction across health institutions nationwide. Furthermore, elucidation of the genetic and nongenetic contributors to differences in drug response across race/ethnicity will obviate the use of this population descriptor as a proxy for these factors. Pharmacogenomic studies using large, diverse datasets are necessary to ensure that advances in this field benefit individuals equitably. Our primary goal in this project is to identify genetic and social determinants of pharmacological drug response among racial/ethnic minorities. To accomplish this goal, we will leverage data from the Kaiser Permanente Research Biobank (KPRB) and the National Institutes of Health (NIH) All Of Us research program, which are two of the largest electronic health record-linked biobanks in the United States. These cohorts are ideal for the proposed studies because they are large (>400,000 participants each), diverse (>25% racial/ethnic minorities), linked to genome-wide genetic data, and capture social determinants of health. In Aim 1, we will evaluate the relative contribution of genetic ancestry versus social factors on race/ethnicity- based differences in drug efficacy and safety. In Aim 2, we will identify genome-wide polymorphisms predictive of drug effects in historically-excluded populations from large pharmacogenetics studies. In Aim 3, we will use ancestry-specific gene expression results to identify genetic determinants of drug response. The aims will be carried out by an established multidisciplinary team of experts in clinical pharmacology, cardiovascular epidemiology, and molecular genetics. These findings from the current study will help to inform clinical decisions impacting communities historically-excluded from biomedical research.

项目摘要/摘要 药物基因组学有可能极大地改善医疗保健结果，但目前正在失败 其研究参与者之间的多样性。因此，我们并不完全了解所有的因素 在代表性不足的人群中影响药理学反应，包括那些有助于 根据食品和药物管理局(FDA)药物的报告，药物疗效和安全性的种族/民族差异 标签。例如，研究参与者中常见的基因变异的临床有效性 历史上被排除在外的人群(例如，较低比例的欧洲遗传祖先)，但在 代表性很好的研究人群仍然未知。此外，基因表达研究已经提供了 对多种疾病易感性的潜在生物学的洞察超出了基因组范围 联合研究(GWAS)的结果已经发现，但还没有完全应用于 药物基因组学发现。此外，健康的社会决定因素可能会影响药理药物 即使在考虑了这些因素对药物的影响后，也要从生物学的角度做出反应 坚持、获取和利用(例如，表观遗传学的社会决定因素)。解决这一知识鸿沟 有可能防止未来的医疗差距，作为支持的基础设施，这种差距可能会加剧 临床药物基因组学继续在全国卫生机构中获得吸引力。此外， 阐明导致不同种族/民族药物反应差异的遗传和非遗传因素将 避免使用此总体描述符作为这些因素的代理。药物基因组学研究使用大型， 多样化的数据集是必要的，以确保这一领域的进步公平地惠及个人。 我们在这个项目中的主要目标是确定药物反应的遗传和社会决定因素 在种族/民族少数群体中。为了实现这个目标，我们将利用来自Kaiser Permanente的数据 研究生物库(KPRB)和美国国立卫生研究院(NIH)都是我们的研究计划，这是两个 美国最大的与健康记录相关的电子生物库。这些群体非常适合于 拟议的研究，因为它们规模庞大(每个参与者400,000人)，多样化(25%的种族/少数民族)， 与全基因组遗传数据相关联，并捕捉健康的社会决定因素。 在目标1中，我们将评估遗传血统与社会因素对种族/民族的相对贡献- 基于药物疗效和安全性的差异。在目标2中，我们将识别可预测的全基因组多态 从大型药物遗传学研究中了解历史上被排除在外的人群的药物效应。在目标3中，我们将使用 祖先特异性基因表达结果识别药物反应的遗传决定因素。目标将是 由临床药理学、心血管领域的专家组成的多学科专家团队进行 流行病学和分子遗传学。这些来自当前研究的发现将有助于指导临床决策。 影响历史上被排除在生物医学研究之外的社区。