Endogenous retrovirus analyses in myalgic encephalomyelitis

肌痛性脑脊髓炎的内源性逆转录病毒分析

• 批准号: 10330602
• 负责人: Dawei Li
• 金额: --
• 依托单位: FLORIDA ATLANTIC UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-19 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10330602
• 关键词: Address; Anti-Inflammatory Agents; Anti-Retroviral Agents; Beds; Chronic; Chronic Fatigue Syndrome; Complex; Data; Data Set; Diagnostic tests; Disease; Endogenous Retroviruses; Exhibits; FDA approved; Funding; Genes; Genetic Transcription; Genomics; Genotype; Human Genome; Immune response; Individual; Infection; Inflammation; Lead; Link; Molecular; Patients; Pharmaceutical Preparations; Phenotype; Quality of life; Risk Factors; Role; Time; United States; Variant; bioinformatics tool; deep sequencing; disabling disease; genome sequencing; genome-wide; innovation; sample fixation; tool; transcriptome; transcriptome sequencing; transcriptomics; viral RNA; whole genome

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.

项目概要/摘要 肌痛性脑脊髓炎 (ME) 是一种致残且复杂的疾病，在美国有 1-250 万名患者 国家。 ME 患者的生活质量低下，四分之一的患者卧床或居家生活。 ME 的研究还不够充分 资金不足，并且没有现有的诊断测试、FDA 批准的治疗方法或治愈 ME 的方法。原因 ME 的未知数。 ME 患者表现出免疫反应升高和炎症增强。 内源性逆转录病毒（ERV）是由古代逆转录病毒感染的固定和整合产生的。 人类基因组。 ERV（n≈400,000）通常保持沉默；然而，一些 ERV 可以转录 重新激活。激活的 ERV 类似于病毒 RNA，因此可以触发免疫反应和慢性 炎症，可能导致 ME。我们与我们的合作者一起收集了最大的深度 对来自 ME 患者的具有深层表型的数据集进行测序。我们最近开发了一套生物信息学 使我们能够对全基因组个体 ERV 进行基因分型并以高通量定量个体 ERV 表达的工具 准确性。通过这个 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 深度测序数据以实现两个具体目标。目标 1：识别不同的 ERV，其表达为 使用 RNA 测序数据与 ME 相关联。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 与我相关。目标 2：使用整体识别其基因型与 ME 相关的 ERV 变体 基因组测序数据。这些分析将产生全基因组不同的 ERV 基因型，并且首次 时间，允许识别 ME 相关的个体 ERV 和相关基因。完成这些后 两个目标，我们将知道 ERV 和 ME 是否在转录组和/或基因组水平上相关。 阐明 ERV 作为 ME 的危险因素可能会带来 ME 治疗的突破，例如重新利用 FDA 批准的现有抗逆转录病毒药物可能会逆转 ERV 效应。