Alcohol Misuse: An Independent Risk Factor that Increases the Incidence and Severity of COVID-19

摘要 冠状病毒病2019年(新冠肺炎)大流行导致前所未有的发病率和死亡率。 年龄、肥胖和共病等危险因素影响SARS-CoV-2的感染率和COVID的严重程度。 19日导致医院ICU入院和死亡。其他促进免疫力和免疫力增强的风险因素 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是 饮酒是因为：(1)酒精是美国最常用的毒品。(2)病人 因肺炎住院的人有酒精使用障碍(AUD)，患急性肺炎的风险更高 呼吸窘迫综合征(新冠肺炎的主要死亡原因)高于非呼吸窘迫综合征患者；以及 (3)酒精对免疫系统的功能产生负面影响，并导致对 病原体(严重新冠肺炎和急性呼吸窘迫综合征的主要机制)；以及(4)酒精扰乱肠道 微生物群(微生物失调)和肠道和肺屏障，这两个都可以进一步促进炎症和 为急性呼吸窘迫综合征做出贡献。因此，我们假设酒精滥用是一个独立的风险因素 通过促进过度和调节失调的免疫-增加新冠肺炎的发病率和严重性- 对SARS-CoV-2的炎症反应。我们将利用我们在拉什的新冠肺炎数据和生物存储库 大学医学中心(RUMC)，已经测试了超过22,000名患者(68%的少数族裔)，超过6000名 检测呈阳性的患者，超过1000人住院，超过600人危重。目前，所有抵达RUMC的患者 通过审计对酒精使用情况进行筛查。我们的新冠肺炎生物库已经储存了鼻咽拭子， 血清/血浆和外周血单核细胞(PBMC)。我们将解决以下具体目标： 目标1：确定饮酒或误用是否会增加新冠肺炎的严重程度并阐明相互作用 与其他风险因素有关。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/误用增加与更严重的临床表现和更差的新冠肺炎相关 健康结果(12,000名RUMC，6,000名新冠肺炎+)患者。目标2.确定饮酒的影响 以及滥用对新冠肺炎病程的影响以及新冠肺炎对饮酒的影响。在这 纵向研究，对6,000例新冠肺炎阳性患者的饮酒情况进行纵向分析 确定：(2A)酒精使用/滥用是否与新冠肺炎相关的康复速度较慢有关 症状。目的3.确定酒精滥用是否会导致过度的免疫-炎症反应 新冠肺炎患者严重急性呼吸综合征冠状病毒感染及多脏器功能障碍 机械装置。在这个机械目标中，我们将比较不同疾病严重程度的新冠肺炎患者 确定酒精滥用是否与：(3A)免疫/炎症反应改变有关。(3B)中断 肠道屏障的完整性。我们将使用机器学习和其他先进的信息学方法来 调查这些目的是为了发现酒精-新冠肺炎相互作用的新机制，以预防和 新冠肺炎的治疗靶点。

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.