Viral and immune-mediated CNS pathology during SARS-CoV-2 infection

SARS-CoV-2 感染期间病毒和免疫介导的中枢神经系统病理学

• 批准号: 10554829
• 负责人: Charles S Dela Cruz
• 金额: $ 123.54万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-24 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10554829
• 关键词: 2019-nCoV; Acute; Affect; Animal Model; Animals; Antibodies; Antigens; Appearance; Applications Grants; Arrhythmia; Autoantibodies; Autoimmune Process; Autoimmune Responses; Autoimmunity; Biological; Biological Markers; COVID-19; COVID-19 pathogenesis; COVID-19 patient; Cardiomyopathies; Cessation of life; Chronic; Classification; Clinical; Confusion; Convalescence; Cross-Sectional Studies; Data; Development; Diagnosis; Diagnostic; Disease; Disease Outcome; Dizziness; Etiology; Fatigue; Foundations; Genetic Predisposition to Disease; Goals; Headache; Human; Immune; Immune System Diseases; Immune response; Immunophenotyping; Impairment; Infection; Inflammatory; International; Investigation; Lead; Link; Long COVID; Longitudinal Studies; Machine Learning; Mediating; Memory Loss; Mus; Myalgia; Neurologic; Neurologic Symptoms; Neurological Models; Organ; Parents; Pathogenesis; Pathology; Pathway interactions; Patient Recruitments; Patient Transfer; Patients; Plasma; Play; Post-Acute Sequelae of SARS-CoV-2 Infection; Prevention; Psyche structure; Publishing; Quality of life; Recovery; Reporting; Research; Research Design; Role; SARS-CoV-2 infection; Sampling; Severities; Site; Sleeplessness; Symptoms; Technology; Therapeutic Intervention; Translating; Viral; Virus; Virus Diseases; Work; associated symptom; body system; brain fog; cohort; common symptom; comparison group; coronavirus disease; cytokine; extracellular; immune function; immunopathology; innovation; insight; machine learning algorithm; machine learning model; mouse model; nervous system disorder; patient population; persistent symptom; post SARS-CoV-2 infection; programs; respiratory; response; therapeutic candidate; therapeutic target; tool

Supplement Project Summary Since its appearance in late 2019, SARS-CoV-2 has spread globally and resulted in 5.5 million deaths in 24 months. Our group’s published work has demonstrated that the pathogenesis of COVID-19 is characterized by overlapping TH1, TH2, and TH17 responses and the presence of diverse, disease-modifying autoantibodies (AAB). The extent of recovery following acute SARS-CoV-2 infection is varied, with 14-35% of patients reporting persistent or new symptoms during convalescence, collectively termed as post-acute sequelae of COVID-19 (PASC or “Long COVID”). While PASC affects multiple organs, a prominent feature of PASC includes neurological symptoms including unremitting fatigue, myalgia, insomnia, mental slowing, and confusion (‘Neuro- PASC’). Although persistent symptoms are common following other severe viral infections, PASC patients demonstrate significant and unique elevations in sequelae even when matched against comparator groups. In the parent R01 proposal, we outlined our goals to investigate the encephalitic potential of SARS-CoV-2 (Aim 1), to evaluate effects of CNS, respiratory and combination SARS-CoV-2 infection on disease outcomes in mouse models (Aim 2), and to determine the CNS responses in COVID-19 patients with neurological symptoms (Aim 3). The supplement extends these studies to investigation of post-acute neurologic sequelae of COVID. To this end, we have collated ~500 PASC patient plasma and sera samples from 4 separate, multisite cohorts to identify AABs that correlate with neuro-PASC (Suppl. Aim 1.1), study longitudinal AAB responses in a well-defined cohort of patients with or without neuro-PASC for which we have extensive data from their acute COVID infection (Suppl. Aim 1.2) and to use machine learning approaches to identify biomarkers of neuro-PASC (Suppl. Aim 1.3). In addition, while the original grant proposal uses SARS-CoV-2 infection to model neurological diseases as a result of direct virus infection in mice, this supplement takes an orthogonal approach to understand 1) how AAB that correlate with neurological symptoms in patients contribute to neurological symptoms of PASC through development of an AAB-transfer mouse model for neuro-PASC (Suppl. Aim 2.1), and 2) probe how SARS-CoV- 2 infection synergizes with host genetic predispositions towards autoimmunity to develop AAB that lead to neuro- PASC (Suppl. Aim 2.2). The proposed research is hypothesis-driven, innovative, highly interdisciplinary, and has a strong potential to inform the diagnosis, prevention, mitigation, and treatment of PASC through elucidating the pathogenesis of post-acute sequelae and the identification of associated mechanistic pathways.

补充项目摘要 自2019年底出现以来，SARS-CoV-2已在全球蔓延，并在24个国家造成550万人死亡。 个月我们小组发表的工作表明，COVID-19的发病机制的特点是： 重叠的TH 1、TH 2和TH 17应答以及存在多种疾病修饰自身抗体 （AAB）。急性SARS-CoV-2感染后的恢复程度各不相同，14-35%的患者报告 恢复期持续或新发症状，统称为COVID-19急性期后后遗症 (PASC或“长期COVID”）。虽然PASC影响多个器官，但PASC的一个突出特征包括 神经系统症状，包括持续疲劳、肌痛、失眠、智力迟钝和意识模糊（“神经系统- PASC“）。虽然持续的症状是常见的其他严重病毒感染，PASC患者 即使与对照组匹配，也显示后遗症显著且独特的升高。在 在R 01提案中，我们概述了我们的目标，即研究SARS-CoV-2的脑炎潜力（目标1）， 评价中枢神经系统、呼吸道和组合SARS-CoV-2感染对小鼠疾病结局的影响 模型（目的2），并确定具有神经系统症状的COVID-19患者的CNS反应（目的 3）。该补充将这些研究扩展到COVID急性后神经系统后遗症的研究。本 最后，我们整理了来自4个独立的多地点队列的约500例PASC患者血浆和血清样本，以确定 与神经-PASC相关的AAB（补充目的1.1），在明确定义的队列中研究纵向AAB反应 有或没有神经PASC的患者，我们有大量的急性COVID感染数据 （Suppl. Aim 1.2）和使用机器学习方法来鉴定神经PASC的生物标志物（Suppl. Aim 1.2）。 1.3）。此外，虽然最初的拨款提案使用SARS-CoV-2感染来模拟神经系统疾病， 直接病毒感染小鼠的结果，这种补充需要一个正交的方法来了解1）如何 与患者神经系统症状相关的AAB通过以下途径导致PASC的神经系统症状： 开发神经PASC的AAB-转移小鼠模型（Suppl.Aim2.1），和2）探索SARS-CoV- 2感染协同宿主遗传倾向对自身免疫发展AAB，导致神经， PASC（补充目标2.2）。拟议的研究是假设驱动的，创新的，高度跨学科的， 通过阐明PASC的诊断、预防、缓解和治疗， 急性后遗症的发病机制和相关机制途径的鉴定。