The COVID-19 epidemic of 2019–20 is due to the novel coronavirus SARS-CoV-2. Following first case description in December, 2019 this virus has infected over 10 million individuals and resulted in at least 500,000 deaths world-wide. The virus is undergoing rapid mutation, with two major clades of sequence variants emerging. This study sought to determine whether SARS-CoV-2 sequence variants are associated with differing outcomes among COVID-19 patients in a single medical system. Whole genome SARS-CoV-2 RNA sequence was obtained from isolates collected from patients registered in the University of Washington Medicine health system between March 1 and April 15, 2020. Demographic and baseline clinical characteristics of patients and their outcome data including their hospitalization and death were collected. Statistical and machine learning models were applied to determine if viral genetic variants were associated with specific outcomes of hospitalization or death. Full length SARS-CoV-2 sequence was obtained 190 subjects with clinical outcome data. 35 (18.4%) were hospitalized and 14 (7.4%) died from complications of infection. A total of 289 single nucleotide variants were identified. Clustering methods demonstrated two major viral clades, which could be readily distinguished by 12 polymorphisms in 5 genes. A trend toward higher rates of hospitalization of patients with Clade 2 infections was observed (p = 0.06, Fisher’s exact). Machine learning models utilizing patient demographics and co-morbidities achieved area-under-the-curve (AUC) values of 0.93 for predicting hospitalization. Addition of viral clade or sequence information did not significantly improve models for outcome prediction. In summary, SARS-CoV-2 shows substantial sequence diversity in a community-based sample. Two dominant clades of virus are in circulation. Among patients sufficiently ill to warrant testing for virus, no significant difference in outcomes of hospitalization or death could be discerned between clades in this sample. Major risk factors for hospitalization and death for either major clade of virus include patient age and comorbid conditions.

2019-20 年的 COVID-19 流行是由新型冠状病毒 SARS-CoV-2 引起的。自 2019 年 12 月出现首例病例以来，该病毒已感染超过 1000 万人，并导致全球至少 50 万人死亡。该病毒正在经历快速突变，出现了两个主要的序列变异分支。本研究旨在确定 SARS-CoV-2 序列变异是否与单一医疗系统中的 COVID-19 患者的不同结果相关。全基因组 SARS-CoV-2 RNA 序列是从 2020 年 3 月 1 日至 4 月 15 日期间从华盛顿大学医学卫生系统注册的患者收集的分离株获得的。患者的人口统计学和基线临床特征及其结果数据，包括住院和死亡被收集。应用统计和机器学习模型来确定病毒遗传变异是否与住院或死亡的特定结果相关。获得了 190 名受试者的全长 SARS-CoV-2 序列以及临床结果数据。35 人（18.4%）住院，14 人（7.4%）死于感染并发症。总共鉴定出 289 个单核苷酸变异。聚类方法证明了两个主要的病毒进化枝，可以通过 5 个基因的 12 个多态性轻松区分。观察到进化枝 2 感染患者的住院率呈较高趋势（p  = 0.06，Fisher 精确值）。利用患者人口统计数据和合并症的机器学习模型在预测住院治疗方面实现了 0.93 的曲线下面积 (AUC) 值。添加病毒进化枝或序列信息并没有显着改善结果预测模型。总之，SARS-CoV-2 在社区样本中显示出显着的序列多样性。病毒的两个主要分支正在传播。在病情严重到需要进行病毒检测的患者中，该样本中的进化枝之间的住院或死亡结果没有显着差异。任一主要病毒分支住院和死亡的主要危险因素包括患者年龄和合并症。