Profiling Early Humoral Response to Diagnose Novel Coronavirus Disease (COVID-19)

Abstract

Background The emergence of coronavirus disease 2019 (COVID-19) is a major healthcare threat. The current method of detection involves a quantitative polymerase chain reaction (qPCR)–based technique, which identifies the viral nucleic acids when present in sufficient quantity. False-negative results can be achieved and failure to quarantine the infected patient would be a major setback in containing the viral transmission. We aim to describe the time kinetics of various antibodies produced against the 2019 novel coronavirus (SARS-CoV-2) and evaluate the potential of antibody testing to diagnose COVID-19. Methods The host humoral response against SARS-CoV-2, including IgA, IgM, and IgG response, was examined by using an ELISA-based assay on the recombinant viral nucleocapsid protein. 208 plasma samples were collected from 82 confirmed and 58 probable cases (qPCR negative but with typical manifestation). The diagnostic value of IgM was evaluated in this cohort. Results The median duration of IgM and IgA antibody detection was 5 (IQR, 3–6) days, while IgG was detected 14 (IQR, 10–18) days after symptom onset, with a positive rate of 85.4%, 92.7%, and 77.9%, respectively. In confirmed and probable cases, the positive rates of IgM antibodies were 75.6% and 93.1%, respectively. The detection efficiency by IgM ELISA is higher than that of qPCR after 5.5 days of symptom onset. The positive detection rate is significantly increased (98.6%) when combining IgM ELISA assay with PCR for each patient compared with a single qPCR test (51.9%). Conclusions The humoral response to SARS-CoV-2 can aid in the diagnosis of COVID-19, including subclinical cases.

Diagnostic Testing for Severe Acute Respiratory Syndrome–Related Coronavirus 2

“…Serologic tests that identify antibodies (such as IgA, IgM, and IgG) to SARS-CoV-2 from clinical specimens (such as blood or saliva), such as enzyme-linked immunosorbent assays, may be less complex than molecular tests and have the potential to be used for diagnosis in certain situations (46). However, their utility for diagnosing acute infections is probably limited around the time of symptom onset, when viral shedding and transmission risk seem to be highest (32).…”

“…However, their utility for diagnosing acute infections is probably limited around the time of symptom onset, when viral shedding and transmission risk seem to be highest (32). Antibody responses to infection take days to weeks to be reliably (46). Negative results would not exclude SARS-CoV-2 infection, particularly among those with recent exposure to the virus.…”

Comparative computational analysis of SARS-CoV-2 nucleocapsid protein epitopes in taxonomically related coronaviruses

“…Nucleocapsid protein is a 50 KDa protein commonly involved in the replication, transcription and packaging of the viral genome, other than hindering the reproductive cycle of the host cell [11]. Also, NC is the most abundant protein in coronaviruses, is highly immunogenic and its amino acid sequence is normally conserved, making of this protein a suitable candidate target for both vaccine formulations and diagnostic assays [12,13]. Previous studies on SARS-CoV reported NC protein epitopes as capable of eliciting a massive production of antibodies in infected subjects while its prevalence was significantly reduced in convalescent patients, suggesting such epitopes as candidates for the design of diagnostic tools.…”

Large-scale implementation of pooled RNA-extraction and RT-PCR for SARS-CoV-2 detection

“…Several attempts to address this challenge have already been suggested, that can be categorized into three major approaches. The first approach is to replace PCR based methods by other direct diagnostic methods such as Loopmediated Isothermal Amplification (LAMP) [1][2][3] and CRISPR based diagnostic tools [4][5][6], the second approach involves serological surveys [7][8][9][10], and the third approach involves the improvement of the PCR methods capacity by optimization and automation (e.g. [11][12][13]) or by reducing the required number of tests via pooling samples together, known as group testing.…”