Endogenous retrovirus analyses in myalgic encephalomyelitis

项目摘要/摘要 肌痛性脑脊髓炎(ME)是一种致残性和复杂性疾病，在美国有100-250万患者 各州。肌萎缩侧索硬化症患者的生活质量较低，四分之一的患者卧床或呆在家里。我的研究还不够深入 资金不足，而且没有现有的诊断测试、FDA批准的治疗或治愈ME。原因何在 对我来说都是未知的。肌萎缩侧索硬化症患者免疫反应增强，炎症增强。 内源性逆转录病毒(ERV)是由古老的逆转录病毒感染和整合到 人类基因组。ERV(n≈400,000)通常保持沉默；然而，一些ERV可以转录 重新启动。激活的ERV类似于病毒RNA，因此可以触发免疫反应和慢性 发炎有可能导致我。与我们的合作者一起，我们收集了最大的深度 对ME患者的表型较深的数据集进行测序。我们最近开发了一套生物信息学 这些工具使我们能够对全基因组范围的个体ERV进行基因分型，并将个体ERV的高表达 精确度。对于这个R21应用程序，我们建议使用这些最先进的工具来分析现有的和新的 深度测序数据，以解决两个具体目标。目标1：识别不同的ERV，其表达为 使用RNA测序数据与ME关联。这些分析将首次量化转录组- 单独广泛表达的ERV；并允许识别激活的不同ERV和ERV基因 和我有关。目的2：利用全基因组技术鉴定与脑炎相关的ERV变异株 基因组测序数据。这些分析将产生全基因组范围内不同的ERV基因类型，并且，第一次 时间，允许识别与ME相关的单个ERV和相关基因。在完成这些任务后 两个目的，我们将知道ERV和ME是否在转录和/或基因组水平上联系在一起。 阐明ERV是ME的危险因素可能会导致ME治疗的突破，例如重新调整用途 现有FDA批准的抗逆转录病毒药物，可能逆转ERV效应。

Project Summary/Abstract Myalgic encephalomyelitis (ME) is a disabling and complex disease with 1-2.5 million patients in the United States. ME patients have low quality of life and one in four are bed- or house-bound. ME is under-studied and under-funded, and there are no existing diagnostic tests, FDA-approved treatments or cure for ME. The causes of ME are unknown. ME patients exhibit elevated immune responses and enhanced inflammation. Endogenous retroviruses (ERVs) result from the fixation of ancient retroviral infections and integrations into the human genome. ERVs (n≈400,000) typically remain silenced; however, some ERVs can be transcriptionally reactivated. Activated ERVs resemble viral RNA and can therefore trigger immune responses and chronic inflammation, potentially leading to ME. Together with our collaborators, we have collected the largest deep sequencing data sets with deep phenotypes from ME patients. We recently developed a set of bioinformatics tools that allow us to genotype genome-wide individual ERVs and quantify individual ERV expression with high accuracy. With this R21 application, we propose to use these state-of-the-art tools to analyze existing and new deep sequencing data to address two Specific Aims. Aim 1: Identify distinct ERVs whose expression is associated with ME using RNA-Sequencing data. These analyses will, for the first time, quantify transcriptome- wide expressed ERVs individually; and allow for identification of activated distinct ERVs and ERV genes associated with ME. Aim 2: Identify ERV variants whose genotypes are associated with ME using whole- genome sequencing data. These analyses will produce genome-wide distinct ERV genotypes, and, for the first time, allow for identification of ME-associated individual ERVs and related genes. Upon completion of these two Aims, we will know whether ERVs and ME are linked at the transcriptomic and/or genomic level. Elucidating ERVs as risk factors in ME may lead to breakthroughs in ME treatment, such as repurposing existing FDA-approved anti-retroviral drugs which may reverse ERV effects.