AUTHOR=Zhang Bicheng , Zhou Xiaoyang , Zhu Chengliang , Song Yuxiao , Feng Fan , Qiu Yanru , Feng Jia , Jia Qingzhu , Song Qibin , Zhu Bo , Wang Jun TITLE=Immune Phenotyping Based on the Neutrophil-to-Lymphocyte Ratio and IgG Level Predicts Disease Severity and Outcome for Patients With COVID-19 JOURNAL=Frontiers in Molecular Biosciences VOLUME=Volume 7 - 2020 YEAR=2020 URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2020.00157 DOI=10.3389/fmolb.2020.00157 ISSN=2296-889X ABSTRACT=Introduction: A recently emerging respiratory disease named coronavirus disease 2019 (COVID-19) has quickly spread across the world. This disease is initiated by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and uncontrolled cytokine storm, but it remains unknown as to whether a robust antibody response is related to clinical deterioration and poor outcome in COVID-19 patients. Methods: Anti-SARS-CoV-2 IgG and IgM antibodies were determined by chemiluminescence analysis (CLIA) in COVID-19 patients at a single center in Wuhan. Median IgG and IgM levels in acute and convalescent-phase sera (within 35 days) for all included patients were calculated and compared between severe and nonsevere patients. Immune response phenotyping based on the late IgG levels and neutrophil-to-lymphocyte ratio (NLR) was characterized to stratified patients into different disease severities and outcomes. Results: A total of 222 patients were included in this study. IgG was first detected on day 4 of illness, and its peak levels occurred in the fourth week. Severe cases were more frequently found in patients with high IgG levels, compared to those with low IgG levels (51.8% versus 32.3%; p=0.008). Severity rates for patients with NLRhiIgGhi, NLRhiIgGlo, NLRloIgGhi, and NLRloIgGlo phenotype were 72.3%, 48.5%, 33.3%, and 15.6%, respectively (p<0.0001). Furthermore, severe patients with NLRhiIgGhi, NLRhiIgGlo had higher proinflammatory cytokines levels including IL-2, IL-6 and IL-10, and decreased CD4+ T cell count compared to those with NLRloIgGlo phenotype (p<0.05). Recovery rates for severe patients with NLRhiIgGhi, NLRhiIgGlo, NLRloIgGhi, and NLRloIgGlo phenotype were 58.8% (20/34), 68.8% (11/16), 80.0% (4/5), and 100% (12/12), respectively (p=0.0592). Dead cases only occurred in NLRhiIgGhi and NLRhiIgGlo phenotypes. Conclusions: COVID-19 severity is associated with increased IgG response, and an immune response phenotyping based on the late IgG response and NLR could act as a simple complementary tool to discriminate between severe and nonsevere COVID-19 patients, and further predict their clinical outcome.