Epigenetic Age Measures to Predict COVID-19 Symptom Progression and Severity

项目总结 新冠肺炎感染致死和/或严重并发症的风险与年龄有关 依附的。美国疾病控制与预防中心的数据显示，那些85岁及以上的人预测了死亡率 这是50岁以下人群的100倍，目前，每10人中就有8人死于新冠肺炎 在美国，65岁或以上的成年人。虽然这个年龄段背后的确切病因 差异是未知的，有证据表明，脆弱性可能是由于 老化过程的功能。脆弱性增加的模式进一步证明了这一点 在既有老龄化疾病的人中-心血管疾病，糖尿病，慢性阻塞性肺病， 慢性肾脏疾病，肝脏疾病--这表明，不仅仅是年龄决定了 风险，更确切地说，是生物年龄。 近年来，我们团队帮助开发了一些最强大的生物标记物， 也就是表观遗传时钟。这些测量方法根据DNA估计样本中的生物年龄 基因组中成百上千个CpG位点的甲基化水平。不仅表观遗传学 在不同的组织和细胞类型中，时钟随着年龄的变化而变化，但表观遗传年龄和 实际年龄也被证明可以预测死亡风险和重大慢性病的发病率， 包括那些似乎是新冠肺炎的主要风险因素。然而，为了实现这些目标 在临床或普通人群中评估新冠肺炎风险的信息性措施，1) 需要重新优化它们，以捕捉新冠肺炎特有的生物衰老方面 2)需要在技术上取得进步，以确保更低的成本和更快的 扭亏为盈。 该提案旨在建立我们团队的多学科优势，以开发和验证 有针对性的、实验室开发的、易于获得的测试，以预测新冠肺炎症状和死亡风险。 如果成功，这项测试将有广泛的应用--从通知分类和治疗 在诊所的决策，到指导社会和政治决策，当涉及到解除“呆在家里”时 某些人的订单。

PROJECT SUMMARY The risk of fatality and/or severe complications due to COVID-19 infection is strongly age dependent. Data from the CDC suggests that those ages 85 and older have predicted mortality rates that is 100-fold higher than for those under the age of 50 and currently, 8 out of 10 COVID-19 deaths in the United States were in adults age 65 or older. While the exact etiology underlying this age disparity is unknown, evidence suggests that vulnerability may be due to changes that occur as a function of the aging process. This is further evidenced by the pattern of increased vulnerability among persons with pre-existing diseases of aging—cardiovascular disease, diabetes, COPD, chronic kidney disease, liver disease—suggesting that it isn't just chronological age that determines risk, but rather, biological age. In recent years, our group has helped develop some of the most robust biomarkers available, namely the epigenetic clocks. These measures estimate biological age in a sample based on DNA methylation levels at hundreds to thousands of CpG sites across the genome. Not only do epigenetic clocks track with age in diverse tissues and cell types, but discrepancies between epigenetic age and actual age have also been shown to predict risk of mortality and incidence of major chronic disease, including those which appear to be major risk factors for COVID-19. However, in order for these measures to be informative for assessing COVID-19 risk clinically, or in the general population, 1) they need to be re-optimized to capture the aspects of biological aging specific to COVID-19 susceptibility, and 2) advances in technology need to be made to ensure lower costs and rapid turnaround. This proposal aims to build on our team's multidisciplinary strengths to develop and validate a targeted, lab-developed, readily-available test to predict COVID-19 symptomology and mortality risk. If successful, this test will have widespread applications—from informing triage and treatment decisions in the clinic, to guiding social and pollical decisions when it comes to lifting “stay-at-home” orders for certain individuals.