Table_1_How concerning is a SARS-CoV-2 variant of concern? Computational predictions and the variants labeling system.xlsx

In this study, we evaluated the use of a predictive computational approach for SARS-CoV-2 genetic variations analysis in improving the current variant labeling system. First, we reviewed the basis of the system developed by the World Health Organization (WHO) for the labeling of SARS-CoV-2 genetic variants and the derivative adapted by the United States Centers for Disease Control and Prevention (CDC). Both labeling systems are based on the virus’ major attributes. However, we found that the labeling criteria of the SARS-CoV-2 variants derived from these attributes are not accurately defined and are used differently by the two agencies. Consequently, discrepancies exist between the labels given by WHO and the CDC to the same variants. Our observations suggest that giving the variant of concern (VOC) label to a new variant is premature and might not be appropriate. Therefore, we used a comparative computational approach to predict the effects of the mutations on the virus structure and functions of five VOCs. By linking these data to the criteria used by WHO/CDC for variant labeling, we ascertained that a predictive computational comparative approach of the genetic variations is a good way for rapid and more accurate labeling of SARS-CoV-2 variants. We propose to label all emergent variants, variant under monitoring or variant being monitored (VUM/VBM), and to carry out computational predictive studies with thorough comparison to existing variants, upon which more appropriate and informative labels can be attributed. Furthermore, harmonization of the variant labeling system would be globally beneficial to communicate about and fight the COVID-19 pandemic.

本研究评估了一种预测性计算方法在新型冠状病毒（SARS-CoV-2）基因变异分析中的应用效果，以优化当前的变异株命名体系。首先，本研究梳理了世界卫生组织（World Health Organization, WHO）制定的SARS-CoV-2基因变异株命名体系，以及美国疾病控制与预防中心（United States Centers for Disease Control and Prevention, CDC）据此改编的命名体系的核心依据。两类命名体系均以病毒的关键特征为基础，但研究发现，基于上述特征制定的SARS-CoV-2变异株命名标准界定模糊，且两家机构的执行方式存在差异，导致二者对同一变异株的命名结果存在不一致。观察结果表明，过早将新变异株归类为关切变异株（Variant of Concern, VOC）可能并不恰当。为此，本研究采用对比计算方法，预测了5株VOC的突变对病毒结构与功能的影响。通过将上述数据与WHO与CDC的变异株命名标准相结合，本研究证实：针对基因变异开展预测性计算对比分析，是实现SARS-CoV-2变异株快速且更精准命名的有效手段。本研究建议，对所有新发变异株、监测中变异株（Variant under Monitoring / Variant being Monitored, VUM/VBM）进行命名，并开展计算预测研究，与现有变异株进行全面比对后，再赋予其更为恰当且信息充分的命名。此外，统一全球变异株命名体系，将有助于全球范围内的新冠疫情（COVID-19 pandemic）信息传播与疫情防控工作。