Uncovering early signals of hereditary TTR amyloidosis in minority populations at high genetic risk

项目摘要 诊断患有遗传性TTR淀粉样变性（hATTR）的患者的奥德赛通常持续数年，因为 症状和体征是非特异性的。与此同时，患者可能会发展为晚期心脏病（心脏 淀粉样变性）和神经疾病（多发性神经病）。一种影响非洲人的常见致病性TTR变异体 美国（4%）和西班牙裔/拉丁裔（1%）患者，V142 I，心脏淀粉样变性的风险特别高， 但诊断延误使这些群体处于护理的边缘。现在有新的疗法可以延缓 hATTR进展;然而，它们不能逆转疾病。因此，诊断是必要的。 hATTR在尽可能早的阶段，当这些疗法可能是最有益的。由于黄金 hATTR相关心脏淀粉样变性的非侵入性诊断标准，核血管造影，包括 暴露于电离辐射和无症状患者的敏感性是未知的，广泛的筛查， 这种方法还不合理。传统的表型优先研究已经确定了非心脏红旗体征， 这些症状预示着未来的心脏病，但hATTR的完整表型谱和自然史 还不太清楚，特别是在高遗传风险的个体中。迄今为止，大量不同的个体群体 致病性TTR变异体（TTR+）尚未被广泛研究，以了解全方位的临床 hATTR的特点我们提出了一个基因型优先的研究，主要是非洲裔美国人和西班牙裔/拉丁裔 来自纽约市与电子健康记录（EHR）相关的BioMe生物库的TTR+个体。一是 使用EHR进行回顾性深度表型分析，以表征范围并制定心脏事件的时间轴 和非心脏的hATTR的功能，并估计年龄依赖性转移率。我们将执行一个强大的 与其他生物库合作进行的全表型关联研究，以确定相关的新健康特征 V142I在TTR+个体中发现的临床特征将累积为表型风险 评分，以帮助确定在卫生系统中的hATTR风险的患者。此外，我们将进行前瞻性的 研究旨在为心脏成像监测的最佳模式和时间提供指导， 高风险TTR+个体在成年期。我们将从BioMe招募100名TTR+人员， 使用金标准和尖端实验成像方法进行心脏成像研究。通过这些 努力，我们将描绘一个时间轴的预期系统和心脏成像签名独特的， hATTR的高遗传风险。这些结果将使临床医生能够在其 因此，患者可以最大限度地从治疗中受益。我们认为，虽然hATTR目前严重 虽然在美国少数民族患者中诊断不足，但事实上，通过发现有先见之明的 体征和症状，实施基于EHR的表型风险评分和适时的心脏成像。 这些方法将根除hATTR高风险患者的护理差异。

PROJECT SUMMARY The odyssey to a diagnosis for patients with hereditary TTR amyloidosis (hATTR) often lasts years because the signs and symptoms are non-specific. Meanwhile, patients can progress to advanced heart disease (cardiac amyloidosis) and nerve disease (polyneuropathy). A common pathogenic TTR variant impacting African American (4%) and Hispanic/Latino (1%) patients, V142I, confers particularly high risk for cardiac amyloidosis, but diagnostic delays keep these groups at the margins of care. Novel therapies are now available to delay hATTR progression; however, they cannot reverse the disease. For this reason, it is imperative to diagnose hATTR at the earliest possible stages, when these therapies are likely to be most beneficial. Because the gold standard for non-invasive diagnosis of hATTR-related cardiac amyloidosis, nuclear scintigraphy, involves exposure to ionizing radiation and the sensitivity in asymptomatic patients is unknown, widespread screening by this method is not yet justified. Traditional phenotype-first studies have identified non-cardiac red flag signs and symptoms that herald future heart disease, but the complete phenotypic spectrum and natural history of hATTR are not well understood, particularly in individuals at high genetic risk. To date, large diverse cohorts of individuals with pathogenic TTR variants (TTR+) have not been extensively studied to understand the full range of clinical features of hATTR. We propose a genotype-first study of predominantly African American and Hispanic/Latino TTR+ individuals from the electronic health record (EHR)-linked BioMe Biobank in New York City. First, we will perform retrospective deep phenotyping using EHRs to characterize the scope and develop a timeline of cardiac and non-cardiac features of hATTR, and estimate age-dependent penetrance. We will perform a well-powered phenome-wide association study, in collaboration with other biobanks, to identify novel health traits associated with V142I. Clinical characteristics found to be enriched in TTR+ individuals will be accrued into a phenotype risk score to help identify patients at risk for hATTR in health systems. In addition, we will conduct a prospective study to generate evidence informing guidelines for optimal mode and timing of cardiac imaging surveillance in high-risk TTR+ individuals across adulthood. We will recruit 100 TTR+ individuals from BioMe into a multimodal cardiac imaging study using gold standard and cutting-edge experimental imaging approaches. Through these endeavors, we will delineate a timeline of anticipatory systemic and cardiac imaging signatures unique to individuals at high genetic risk for hATTR. The results will empower clinicians to recognize the disease at its earliest stages so patients may maximally benefit from therapy. We posit that although hATTR is currently grossly underdiagnosed in U.S. minority patients, it is in fact amenable to earlier detection through discovery of prescient signs and symptoms, implementation of EHR-based phenotype risk scores and well-timed cardiac imaging. These approaches will uproot disparities in the care of diverse patients at high risk for hATTR.