Center for Circadian Rhythms and Alcohol-Induced Tissue Damage

摘要 2019冠状病毒病（COVID-19）大流行导致前所未有的发病率和死亡率。 年龄、肥胖和合并症等风险因素影响SARS-CoV-2感染率和COVID-1严重程度 19例导致医院ICU入院和死亡。其他风险因素，促进过度免疫和 必须存在对病毒的炎症反应，导致严重疾病或死亡。其中一个风险因素可能 这是因为：（1）酒精是美国最常用的药物。(2)患者 患有酒精使用障碍（AUD）的肺炎住院患者发生急性 呼吸窘迫综合征（ARDS）（COVID-19死亡的主要原因）比非AUD患者;以及 (3)酒精会对免疫系统的功能产生负面影响，并导致对免疫系统的不适当反应。 病原体（严重COVID-19和ARDS的主要机制）;以及（4）酒精破坏肠道 微生物组（生态失调）和肠和肺屏障，这两者都可以进一步促进炎症， 导致ARDS。因此，我们假设酒精滥用是一个独立的风险因素， 通过促进过度和失调的免疫，增加COVID-19的发病率和严重程度， 对SARS-CoV-2的炎症反应。我们将利用我们在拉什的COVID-19数据和生物储存库 大学医学中心（RUMC）已经测试了超过22，000名患者（68%为少数民族）， 病人检测呈阳性，超过1000人住院，超过600人病危。目前，所有抵达RUMC的患者 使用AUDIT进行酒精筛查。我们的COVID-19生物储存库储存了鼻咽拭子， 血清/血浆和外周血单核细胞（PBMC）。我们将致力于实现以下具体目标： 目的1：确定酒精使用或滥用是否会增加COVID-19的严重程度并阐明相互作用 其他风险因素。在这项横断面研究中，我们将使用机器学习分类器来确定 酒精使用/滥用增加与更严重的临床表现和更差的COVID-19相关 健康结果（12，000例RUMC，6000例COVID-19+患者）。目标2.确定酒精使用的影响 和滥用对COVID-19病程的影响以及COVID-19对酒精消费的影响。在这 纵向研究，我们将对6000名COVID-19阳性患者的酒精使用情况进行纵向分析 确定：（2a）酒精使用/滥用是否与COVID-19相关的恢复较慢有关 症状目标3。确定酒精滥用是否会导致过度的免疫炎症反应 SARS-CoV-2感染和COVID-19患者的更多器官功能障碍，并探讨 机制等在这一机制目标中，我们将比较不同疾病严重程度的COVID-19患者， 确定酒精滥用是否与：（3a）改变免疫/炎症反应有关。(3b)打乱 肠道屏障完整性。我们将使用机器学习和其他先进的信息学方法， 研究这些目标，以发现酒精与COVID-19相互作用的新机制， COVID-19的治疗靶点。

ABSTRACT The coronavirus disease 2019 (COVID-19) pandemic has resulted in unprecedented morbidity and mortality. Risk factors like age, obesity, and comorbidity impact the rate of SARS-CoV-2 infection and severity of COVID- 19 leading to hospital ICU admission and death. Additional risk factors that promote exaggerated immune and inflammatory response to the virus leading to severe disease or death must exist. One such risk factor could be alcohol consumption because: (1) Alcohol is the most frequently used drug in the United States. (2) Patients hospitalized for pneumonia who have an alcohol use disorder (AUD) are at greater risk for developing Acute Respiratory Distress Syndrome (ARDS) (the primary cause of death in COVID-19) than non-AUD patients; and (3) Alcohol negatively impacts function of the immune system and results in an inappropriate response to pathogens (a primary mechanism of severe COVID-19 and ARDS); and (4) Alcohol disrupts the intestinal microbiome (dysbiosis) and intestinal and lung barriers which can both further promote inflammation and contribute to ARDS. Accordingly, we hypothesize that alcohol misuse is an independent risk factor that increases the incidence and severity of COVID-19 by promoting exaggerated and dysregulated immune- inflammatory responses to SARS-CoV-2. We will leverage our COVID-19 data and biorepository at Rush University Medical Center (RUMC), which has tested over 22,000 patients (68% minority) with over 6000 patients testing positive, over 1000 hospitalized, over 600 critically ill. Currently, all patients arriving at RUMC are screened for alcohol use with AUDIT. Our COVID-19 biorepository has banked nasopharyngeal swabs, serum/plasma, and peripheral blood mononuclear cells (PBMC). We will address the following Specific Aims: Aim 1: Determine if alcohol use or misuse increases severity of COVID-19 and elucidate interactions with other risk factors. In this cross sectional study, we will use a machine learning classifier to determine if increased alcohol use/misuse are associated with more severe clinical presentation and poorer COVID-19 health outcomes (in 12,000 RUMC, 6000 COVID-19+) patients. Aim 2. Determine the impact of alcohol use and misuse on COVID-19 disease course and the impact of COVID-19 on alcohol consumption. In this longitudinal study, we will conduct longitudinal analysis of alcohol use in 6000 patients positive for COVID-19 to determine: (2a) if alcohol use/misuse is associated with slower recovery from COVID-19-associated symptoms. Aim 3. Determine if alcohol misuse results in exaggerated immune-inflammatory response to SARS-CoV-2 infection and more organ dysfunction in COVID-19 patients and explore the mechanisms. In this mechanistic Aim, we will compare COVID-19 patients with different disease severity to determine if alcohol misuse is associated with: (3a) altered immune/inflammatory response. (3b) disrupted intestinal barrier integrity. We will use machine learning and other advanced informatics approaches to investigate these Aims to discover new mechanisms for alcohol-COVID-19 interactions for prevention and therapeutic targets for COVID-19.