Humoral Immunity against SARS-CoV-2 and the Impact on COVID-19 Pathogenesis

• Published in: Molecules and cells Vol. 44; no. 6; pp. 392 - 400
• Main Authors: Lee, Eunjin, Oh, Ji Eun
• Format: Journal Article
• Language: English
• Published: United States Korean Society for Molecular and Cellular Biology 01.06.2021; 한국분자세포생물학회
• Subjects: Antibodies, Neutralizing - biosynthesis; Antibodies, Neutralizing - therapeutic use; Antibodies, Viral - biosynthesis; Antibody-Dependent Enhancement; Autoantibodies - biosynthesis; B-Lymphocytes - immunology; B-Lymphocytes - virology; COVID-19 - immunology; COVID-19 - mortality; COVID-19 - virology; COVID-19 Drug Treatment; Host-Pathogen Interactions - immunology; Humans; Immunity, Humoral - drug effects; Immunoglobulin A - biosynthesis; Immunoglobulin Class Switching; Immunoglobulin G - biosynthesis; Immunoglobulin M - biosynthesis; Immunologic Memory; Minireview; SARS-CoV-2 - immunology; SARS-CoV-2 - pathogenicity; Severity of Illness Index; Survival Analysis; 생물학; COVID-19; SARS-CoV-2 variants; neutralizing antibody; SARS-CoV-2; humoral immunity
• ISSN: 1016-8478; 0219-1032
• DOI: 10.14348/molcells.2021.0075

It has been more than a year since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first emerged. Many studies have provided insights into the various aspects of the immune response in coronavirus disease 2019 (COVID-19). Especially for antibody treatment and vaccine development, humoral immunity to SARS-CoV-2 has been studied extensively, though there is still much that is unknown and controversial. Here, we introduce key discoveries on the humoral immune responses in COVID-19, including the immune dynamics of antibody responses and correlations with disease severity, neutralizing antibodies and their cross-reactivity, how long the antibody and memory B-cell responses last, aberrant autoreactive antibodies generated in COVID-19 patients, and the efficacy of currently available therapeutic antibodies and vaccines against circulating SARS-CoV-2 variants, and highlight gaps in the current knowledge.