Leveraging the Microbiome, Local Admixture, and Machine Learning to Optimize Anticoagulant Pharmacogenomics in Medically Underserved Patients

利用微生物组、局部混合物和机器学习来优化医疗服务不足的患者的抗凝药物基因组学

• 批准号: 10656719
• 负责人: Jason Hansen Karnes
• 金额: $ 10.68万
• 依托单位: UNIVERSITY OF ARIZONA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-12 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10656719
• 关键词: Admixture; Adverse drug event; Adverse event; Affect; African American; African American population; Algorithms; Anticoagulants; Asian; Award; CYP2C9 gene; Cardiovascular Diseases; Characteristics; Clinical; Clinical Research; Complex; DNA; Data; Dose; Drug Prescriptions; Drug Receptors; Electronic Health Record; Enzymes; Epigenetic Process; Ethnic group; European; Fostering; Frequencies; Funding; Gene Frequency; Generations; Genes; Genetic; Genome; Genomics; Genotype; Guidelines; Haplotypes; Hispanic; Individual; Investigation; Latino; Latino Population; Machine Learning; Medical Research; Minority Groups; Mission; Native American Ancestry; Outcome; Participant; Patient Self-Report; Patients; Pattern; Performance; Pharmaceutical Preparations; Pharmacogenetics; Pharmacogenomics; Pharmacologic Substance; Pharmacotherapy; Population; Population Heterogeneity; Public Health; Race; Research; Research Project Grants; Safety; Source; Testing; Therapeutic; Toxic effect; Translating; United States; United States National Institutes of Health; Variant; Warfarin; Work; clinically relevant; cohort; disparity elimination; disparity reduction; drug efficacy; ethnic diversity; genetic association; genome wide association study; genomic data; improved; medically underserved; medication safety; microbiome; novel; racial and ethnic; racial disparity; response; social health determinants; trait; treatment disparity

ABSTRACT Currently available pharmacogenomic (PGx) algorithms have critical limitations, including a lack of generalizability to non-white populations. Under-representation in clinical studies, the propensity to cause adverse events, and a lack of consideration of admixed populations in clinical PGx guidelines are all factors that contribute to limited utility of PGx algorithms in diverse populations. Thus, our originally awarded proposal focused on improving warfarin stable dose prediction, as it continues to remain one of the most prescribed drugs in the United States and a leading cause of adverse drug events particularly in underserved patients such as African Americans (AAs) and Latinos. Preliminary results from this proposal demonstrate that generation of local ancestry (LA) estimates enables inclusion of admixed populations and improves power in genetic association studies on diverse and admixed populations. Thus, we seek to expand upon our original proposal to perform more inclusive pharmacogenetic studies by generating LA estimates in the large, racially/ethnically diverse AllofUs cohort. We will investigate the relationships between LA and PGx variants and showcase the utility of LA estimates and the AllofUs cohort by identifying novel PGx variants associated with warfarin stable dose. Our overarching hypothesis is that LA can be used to enable genomic association analyses that are more inclusive of admixed and diverse cohorts and to uncover novel findings that were previously overlooked in ancestrally European populations. We will pursue two Specific Aims (SAs) to test this hypothesis: (SA1) Characterize LA for major pharmacogenes and its correlation with global ancestry and PGx variants in diverse populations from AllofUs and; (SA2) Leverage LA to identify novel PGx variants related to warfarin stable dose in admixed AllofUs participants. In SA1, We will estimate LA using RFMix from genome array and sequencing data in the AllofUs Controlled Tier. We will test if LA at clinically relevant pharmacogenes correlates with patient-level global ancestry and presence of clinically relevant pharmacogenomic variants. In SA2, we will incorporate LA estimates from SA1 into genome-wide association analyses for warfarin stable dose using Tractor while controlling for clinical characteristics and clinically relevant PGx variants in admixed individuals from AllofUs, including Hispanic, AA, and multi-race individuals. The outcomes of this work will provide a framework for LA investigation with other PGx drug-gene pairs and enable the identification of novel PGx variants that affect drug response in medically underserved, diverse populations. This research has the potential to identify new sources of variability in warfarin dose, improve the safety and efficacy of warfarin treatment, and reduce disparities in PGx research for medically underserved patients.

摘要 目前可用的药物基因组学（PGx）算法具有严重的局限性，包括缺乏 对非白人群体的普遍适用性。在临床研究中代表性不足，倾向于导致 不良事件，以及临床PGx指南中缺乏对混合人群的考虑，都是 导致PGx算法在不同人群中的效用有限。因此，我们最初的提案 专注于改善华法林稳定剂量预测，因为它仍然是最常用的处方药之一 在美国，这是药物不良事件的主要原因，特别是在服务不足的患者中， 非裔美国人（AAs）和拉丁美洲人。该提案的初步结果表明， 祖先（LA）估计能够纳入混合人群，并提高遗传关联的能力 对不同和混合人群的研究。因此，我们寻求扩大我们原来的建议， 通过在大型、种族/人种多样性研究中生成LA估计值， Allofus队列。我们将研究LA和PGx变体之间的关系，并展示LA的实用性。 通过鉴定与华法林稳定剂量相关的新型PGx变体，评估和AllofUs队列。我们 总体假设是，LA可以用于实现更具包容性的基因组关联分析 混合和多样化的队列，并发现新的发现，以前被忽视的祖先 欧洲人口。我们将采用两个特定目标（SA）来检验这一假设：（SA 1）表征LA 主要药物基因及其与全球血统和PGx变体的相关性， AllofUs和;（SA 2）利用LA在混合AllofUs中识别与华法林稳定剂量相关的新型PGx变体 参与者在SA 1中，我们将使用来自基因组阵列的RFMix和AllofUs中的测序数据来估计LA 控制层。我们将检测临床相关药物基因组的LA是否与患者水平的总体 血统和存在临床相关药物基因组学变体。在SA 2中，我们将合并LA估计值 从SA 1到使用Tractor进行华法林稳定剂量的全基因组关联分析，同时控制 来自AllofUs的混合个体的临床特征和临床相关PGx变体，包括 西班牙裔，AA，和多种族的人。这项工作的成果将为LA调查提供一个框架 与其他PGx药物-基因对，并能够鉴定新的PGx变体， 医疗条件差，人口多样这项研究有可能确定新的变异来源 华法林剂量，提高华法林治疗的安全性和有效性，并减少PGx研究的差异 为医疗服务不足的病人提供服务。

项目成果

Differential drug response in pulmonary arterial hypertension: The potential for precision medicine.

• DOI: 10.1002/pul2.12304
• 发表时间: 2023-10
• 期刊: PULMONARY CIRCULATION
• 影响因子: 2.6
• 作者: Miller, Elise;Sampson, Chinwuwanuju Ugo-Obi;Desai, Ankit A.;Karnes, Jason H.
• 通讯作者: Karnes, Jason H.

Laboratory and demographic predictors of functional assay positive status in suspected heparin-induced thrombocytopenia: A multicenter retrospective cohort study.

疑似肝素诱导的血小板减少症功能测定阳性状态的实验室和人口预测因素：一项多中心回顾性队列研究。

• DOI: 10.1016/j.thromres.2023.07.011
• 发表时间: 2023
• 期刊: Thrombosis research
• 影响因子: 7.5
• 作者: Giles,JasonB;Rollin,Jerome;Martinez,KianaL;Selleng,Kathleen;Thiele,Thomas;Pouplard,Claire;Sheppard,Jo-AnnI;Heddle,NancyM;Phillips,ElizabethJ;Roden,DanM;Gruel,Yves;Warkentin,TheodoreE;Greinacher,Andreas;Karnes,JasonH
• 通讯作者: Karnes,JasonH

Genome-wide association study of platelet factor 4/heparin antibodies in heparin-induced thrombocytopenia.

• DOI: 10.1182/bloodadvances.2022007673
• 发表时间: 2022-07-26
• 期刊: BLOOD ADVANCES
• 影响因子: 7.5
• 作者: Giles, Jason B.;Steiner, Heidi E.;Rollin, Jerome;Shaffer, Christian M.;Momozawa, Yukihide;Mushiroda, Taisei;Inai, Chihiro;Selleng, Kathleen;Thiele, Thomas;Pouplard, Claire;Heddle, Nancy M.;Kubo, Michiaki;Miller, Elise C.;Martinez, Kiana L.;Phillips, Elizabeth J.;Warkentin, Theodore E.;Gruel, Yves;Greinacher, Andreas;Roden, Dan M.;Karnes, Jason H.
• 通讯作者: Karnes, Jason H.

Bringing pharmacomicrobiomics to the clinic through well-designed studies.

• DOI: 10.1111/cts.13381
• 发表时间: 2022-10
• 期刊: Clinical and translational science

Role of the gut microbiome in cardiovascular drug response: The potential for clinical application.

• DOI: 10.1002/phar.2650
• 发表时间: 2022-02
• 期刊: Pharmacotherapy
• 影响因子: 4.1