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.

项目摘要/摘要 肌电脑脊髓炎（ME）是一种残疾而复杂的疾病，统一患者有1-250万患者 国家。我的患者的生活质量较低，四分之一的人是床或家庭的。我研究不足， 资金不足，没有现有的诊断测试，FDA批准的治疗方法或治疗我。原因 我中的未知。我的患者表现出升高的免疫血液和炎症增强。 内源性逆转录病毒（ERV）是由古代逆转录病毒感染和整合固定在 人基因组。 ERV（N≈400,000）通常保持沉默；但是，某些ERV可以在转录上进行 重新激活。活化的ERV类似于病毒RNA，因此可以触发免疫反应和慢性 炎症，可能导致我。与我们的合作者一起，我们收集了最大的深度 用我患者的深层表型对数据集进行测序。我们最近开发了一套生物信息学 使我们能够基因组全基因组单独的ERV并用高量化单个ERV表达的工具 准确性。使用此R21应用程序，我们建议使用这些最先进的工具来分析现有和新的 深入测序数据以解决两个具体目标。目标1：确定表达的不同ERV 与我使用RNA序列数据相关联。这些分析将首次量化转录组 - 单独表达ERV；并允许鉴定活化的不同ERV和ERV基因 与我相关。 AIM 2：识别使用整体与我相关的基因型与我相关的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，并且是第一个 时间，允许鉴定与ME相关的单个ERV和相关基因。这些完成后 两个目标，我们将知道ERV和我是否在转录组和/或基因组水平上有联系。 将ERV阐明为我的危险因素可能会导致我的治疗突破，例如重新利用 现有的FDA批准的抗逆转录病毒药物可能会逆转ERV。