Elucidating hereditary transthyretin-mediated heart failure risk using machine learning, polygenic risk and recall by genotype approaches in African ancestry individuals

项目摘要/摘要 转甲状腺素(TTR)基因突变可导致异常淀粉样纤维沉积在 心肌，导致遗传性转甲状腺素淀粉样心肌病(hATTR-CM)并导致心脏 失败了。针对hATTR-CM的靶向治疗最近被开发出来，并被证明可以提高死亡率 和住院治疗。 最近，我们领导了一项研究(《美国医学会杂志》，2019年12月)，该研究表明，TTR V122I突变，通常在种族/少数民族中观察到(4%在非裔美国人(AA)中，1%在 拉美裔美国人(HAS)，心力衰竭的风险增加两倍。尽管有这种强烈的影响，但只有11% 患有心力衰竭的V122I携带者中，hATTR-CM得到了适当的诊断，这表明 对该病的漏诊和误诊。我们进一步展示了潜在的临床证据 年轻、无症状V122I携带者的超声心动图异常，提示可出现早期体征 早在疾病发作之前就开始了。 我们建议通过解决目标目标所需的知识差距来扩展我们先前的工作 以充分发挥其潜力的疗法。这些包括：了解V122I的不完全外显； 在基因分型不常见的大型医疗保健系统中识别V122I携带者；以及了解 亚临床疾病负担。在目标1中，我们将研究多基因风险得分之间的相互作用，这些得分是 由数百万个影响很小的单核苷酸变体和V122I组成，V122I是一个单基因突变，具有 在6,609例AA和9,006例心力衰竭患者中，结合临床危险因素分析，单一的强效应 生物群生物库中有5833个氨基酸，宾夕法尼亚医学生物库(PMBB)中有5833个氨基酸。在目标2中，我们将应用 机器学习工具以多模式电子健康记录(EHR)数据识别~8中的V122I携带者 来自西奈山电子健康记录(EHR)数据库的100万名患者。在《目标3》中，我们将 评估淀粉样蛋白沉积对年轻无症状患者心脏结构/功能特征的亚临床影响 V122I携带者召回V122I携带者进行成像评估，包括研究级超声心动图， 心脏磁共振和氚核素扫描。 这项提议是创新的，因为我们利用了两个不同祖先的大型生物库，这些生物库来自 学术卫生系统(西奈山的Biome和宾夕法尼亚大学的PMBB)，以及 采用前沿方法，包括多种族多基因风险评分和机器学习方法 关于多模式电子病历数据。我们进一步提出了基于基因分型的患者回忆，并进行了深入的 使用全面的心脏成像扫描进行表型鉴定。 这项提议有可能实现精准医学在种族/民族中治疗心力衰竭的潜力 通过向临床护理、人口管理、风险分层和临床试验提供信息，为少数群体提供信息。

PROJECT SUMMARY / ABSTRACT Mutations in the Transthyretin (TTR) gene can lead to deposition of abnormal amyloid fibrils in the myocardium, resulting in hereditary transthyretin amyloid cardiomyopathy (hATTR-CM) and leading to heart failure. Targeted therapies for hATTR-CM have recently been developed and have shown to improve mortality and hospitalization. Recently, we led a study (Journal of American Medical Association, Dec 2019) that showed that the TTR V122I mutation, commonly observed in racial/ethnic minorities (4% in African Americans (AAs) and 1% in Hispanic Americans (HAs)), confers two-fold increased risk of heart failure. Despite this strong effect, only 11% of V122I carriers with heart failure were appropriately diagnosed with hATTR-CM, suggesting marked underdiagnosis and mis-diagnosis of the disease. We further showed subclinical evidence of echocardiographic derangements in young, asymptomatic V122I carriers, suggesting early signs can occur well before onset of disease. We propose to extend our prior work by addressing knowledge gaps which are necessary for targeted therapies to attain their full potential. These include: understanding the incomplete penetrance of V122I; identifying V122I carriers in large health care systems where genotyping is not common; and understanding subclinical disease burden. In Aim 1, we will examine the interplay between a polygenic risk score, which are comprised of millions of single nucleotide variants with small effects, and V122I, a monogenic mutation with a single strong effect, analyzed in conjunction with clinical risk factors on heart failure in in 6,609 AAs and 9,006 HAs in the BioMe biobank and 5,833 AAs in the Penn Medicine Biobank (PMBB). In Aim 2, we will apply machine learning tools to multi-modal electronic health record (EHR) data to identify V122I carriers in ~8 million patients from an electronic health record (EHR) data repository at Mount Sinai. In Aim 3, we will evaluate subclinical effects of amyloid deposition on cardiac structural/functional traits in young, asymptomatic V122I carriers by recalling V122I carriers for imaging evaluation including research-grade echocardiograms, cardiac magnetic resonance and technetium nuclear scanning. The proposal is innovative because we are utilizing two large diverse ancestry EHR-linked biobanks from academic health systems (BioMe at Mount Sinai, and PMBB at University of Pennsylvania), along with adopting cutting-edge methods including multi-ethnic polygenic risk scores, and machine learning approaches on multi-modal EHR data. We further propose patient recall based on genotypes and perform deep phenotyping using comprehensive heart imaging scans. This proposal has the potential to realize the potential of precision medicine for heart failure in racial/ethnic minorities by informing clinical care, population management, risk stratification and clinical trials.