Addressing the Racial Disparity of Angiotensin Inhibitor Benefit in HFrEF Hospitalizations: Distinguishing Genomic and Social Factors

项目总结/摘要 心力衰竭（HF）影响约620万美国人，是美国住院的主要原因之一。 心力衰竭（HHF）住院治疗占HF费用的80%，因为83%的HF患者住院治疗 至少一次，43%至少四次。大约30%的HF患者在住院一年内死亡。 随着时间的推移，黑人HF患者的住院率高于白色HF患者。 血管紧张素抑制剂可预防HHF。虽然这些药物对射血减少的患者最有效 在HFrEF分数（HFrEF）中，HHF患者仍然很高，表明个体之间的药物反应不同。种族 似乎是血管紧张素抑制剂反应的一个关键因素，因为白色HF患者经历了44%的 这些药物降低了HHF的风险，而在黑人HF患者中未观察到这种效果。虽然这 对血管紧张素抑制剂的反应性差异尚未完全了解，这些药物是指南- 推荐用于所有HFrEF患者。考虑到日益增加的频率、成本和严重后果， 迫切需要了解血管紧张素受体相关的种族差异的潜在因素， 减少HFrEF住院治疗。种族是社会和基因组变量的复杂结构，两者兼而有之 可能在种族差异中起了作用。我们的中心假设是社会变量更好地解释了这种种族差异。 差距因此，总的目标是了解自我认定的种族，基因组学， HFrEF住院治疗中血管紧张素II相关减少的种族差异的社会变量。 药物基因组学（PGx）研究通常依赖于自我确定的种族，而不是基因组祖先， 导致HF治疗结果差异的遗传变异不一致。目标1克服了这一点 亨利福特心力衰竭中HFrEF患者（N=575例黑人，N=547例白色）的多样化队列的局限性 PGx登记（HFPGR），全基因组数据，允许祖先量化和访问电子 医疗记录许多调查HHF种族差异的研究已经过时， 获得可能影响HHF的护理。目标2克服了这一限制， 患者具有相似的医疗保健服务和质量的数据集。社会影响研究 健康决定因素（SDoH）对HHF的研究发现，特定社会变量的累积增加与 HHF风险增加，但未调查药物特异性社会变量。Aim 3克服了这一点 通过使用自我确定的种族、基因组祖先和社会变量测试相互作用的限制 特别是与HFrEF住院治疗中血管紧张素抑制剂获益相关。总体方法是分析 现有的临床和基因组学数据集（HFPGR），以HHF为主要结局。这项研究是可行的 通过利用现有的数据集，我的赞助商的专业知识，密歇根大学的资源， 亨利福特卫生系统，并建立了方法。在完成这个项目，我将学习批判性研究 在PGx和社会服务的技能，这将准备我更先进的，博士后培训。

Project Summary / Abstract Heart failure (HF) affects ~6.2 million Americans and is one of the leading causes of hospitalization in the U.S. Hospitalizations for heart failure (HHF) account for 80% of HF costs since 83% of HF patients are hospitalized at least once and 43% at least four times. About 30% of HF patients die within one year of being hospitalized. Black HF patients experience higher hospitalization rates over time compared to White HF patients. Angiotensin Inhibitors prevent HHF. Although these drugs are most effective in patients with reduced ejection fraction (HFrEF), HHF patients remain high, suggesting that drug response differs between individuals. Race seems to be a critical factor in angiotensin inhibitor response because White HF patients experienced a 44% reduction in the risk of HHF on these drugs, while this effect was not seen in Black HF patients. Although this difference in responsiveness to angiotensin inhibitors is not yet fully understood, these drugs are guideline- recommended for all HFrEF patients. Given the increasing frequency, costs, and grave outcomes, there is a critical need to understand the factors underlying racial disparity in the angiotensin inhibitor-associated reduction of HFrEF hospitalizations. Race is a complex construct of social and genomic variables, and both may play a role in this racial disparity. Our central hypothesis is social variables better explain this racial disparity. Therefore, the overall objective is to understand the effects of self-identified race, genomics, and social variables in the racial disparity of angiotensin inhibitor-associated reductions in HFrEF hospitalizations. Pharmacogenomic (PGx) studies often rely on self-identified race instead of genomic ancestry, and findings of genetic variants responsible for differences in HF treatment outcomes are inconsistent. Aim 1 overcomes this limitation with a diverse cohort of HFrEF patients (N=575 Black, N=547 White) in the Henry Ford Heart Failure PGx registry (HFPGR) with whole-genome data, allowing for ancestral quantification and access to electronic medical records. Many studies investigating racial disparities in HHF are outdated, given current knowledge on access to care that can influence HHF. Aim 2 overcomes this limitation with access to a more contemporary dataset where patients have similar health care access and quality. Studies investigating the effects of social determinants of health (SDoH) on HHF found cumulative increases of specific social variables were associated with an increased risk of HHF but did not investigate drug-specific social variables. Aim 3 overcomes this limitation by testing for interactions using self-identified race, genomic ancestry, and social variables specifically related to angiotensin inhibitor benefit in HFrEF hospitalizations. The overall approach is to analyze an existing clinical and genomics dataset (HFPGR) with HHF as the primary outcome. This research is feasible by leveraging an existing dataset, the expertise of my sponsors, resources at the University of Michigan and Henry Ford Health System, and established methods. In completing this project, I will learn critical research skills in PGx and social services that will prepare me for more advanced, post-doctoral training.