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在全球范围内传播，并在24中导致550万人死亡 月份。我们小组发表的工作表明，Covid-19的发病机理的特征是 重叠的Th1，Th2和Th17反应以及潜水员的存在，疾病改良的自身抗体 （AAB）。急性SARS-COV-2感染后的恢复程度各不相同，有14-35％的患者报告 康复期间的持续或新症状，统称为Covid-19的急性后遗症 （PASC或“长卷”）。尽管PASC影响多个器官，但PASC的重要特征包括 神经系统症状，包括疲劳，肌痛，失眠，精神放缓和混乱（'neuro-- PASC’）。尽管在其他严重病毒感染后，持续的症状很常见，但PASC患者很常见 即使与比较器组相匹配，也表现出后遗症的显着和独特的海拔。在 父母R01提案，我们概述了我们的目标，以调查SARS-COV-2的脑潜力（AIM 1）， 评估CNS，呼吸道和SARS-COV-2联合感染对小鼠疾病预后的影响 模型（AIM 2），并确定COVID-19患有神经系统症状的患者的CNS反应（AIM 3）。该补充剂将这些研究扩展到了急性后神经系统后遗症的研究。对此 结束，我们从4个单独的多站点同类群体中整理了约500名PASC患者血浆和血清样品 与Neuro-PASC相关的AABS（Suppl。AIM1.1），研究纵向AAB响应在明确定义的队列中 有或没有神经PASC的患者，我们从其急性共同感染中获得了广泛的数据 （Suppl。Aim1.2）并使用机器学习方法来识别Neuro-PASC的生物标志物（Suppl。AimAim 1.3）。此外，虽然原始赠款提案使用SARS-COV-2感染来对神经系统疾病进行建模 小鼠直接病毒感染的结果，该补充剂采用正交方法来理解1） 与患者中神经系统症状相关的AAB会导致PASC的神经系统症状 开发用于神经PASC的AAB-转移小鼠模型（Suppl。AIM2.1），以及2）探测如何SARS-COV- 2感染与宿主遗传易免免疫的宿主遗传倾向相结合，从而开发出导致神经的AAB PASC（补充AIM 2.2）。拟议的研究是由假设驱动的，创新的，高度跨学科的，并且具有 通过阐明PASC的诊断，预防，缓解和治疗的强大潜力 急性后遗症的发病机理和相关机械途径的鉴定。