Characterization of antibody response to SARS-CoV-2 Orf8 from three waves of COVID-19 outbreak in Thailand.
Jeeraphong ThanongsaksrikulPaskorn SritipsukhoPotjanee SrimanoteOnruedee KhantisitthipornWipawadee SianglumUayporn PinitchaiYong PoovorawanPublished in: PloS one (2024)
A dynamic of virus adaptation and a mass vaccination campaign could significantly reduce the severity of clinical manifestations of COVID-19 and transmission. Hence, COVID-19 may become an endemic disease globally. Moreover, mass infection as the COVID-19 pandemic progressed affected the serology of the patients as a result of virus mutation and vaccination. Therefore, a need exists to acquire accurate serological testing to monitor the emergence of new outbreaks of COVID-19 to promptly prevent and control the disease spreading. In this study, the anti-Orf8 antibodies among samples collected in Thailand's first, fourth, and fifth waves of COVID-19 outbreaks compared with pre-epidemic sera were determined by indirect ELISA. The diagnostic sensitivity and specificity of the anti-Orf8 IgG ELISA for COVID-19 samples from the first, fourth, and fifth waves of outbreaks was found to be 100% compared with pre-epidemic sera. However, the diagnostic sensitivity and specificity of the anti-Orf8 IgG ELISA for a larger number of patient samples and controls from the fifth wave of outbreaks which were collected on day 7 and 14 after an RT-PCR positive result were 58.79 and 58.44% and 89.19 and 58.44%, respectively. Our data indicated that some of the controls might have antibodies from natural past infections. Our study highlighted the potential utility of anti-Orf8 IgG antibody testing for seroprevalence surveys but still warrants further investigations.
Keyphrases
- sars cov
- coronavirus disease
- respiratory syndrome coronavirus
- end stage renal disease
- chronic kidney disease
- newly diagnosed
- ejection fraction
- mass spectrometry
- case report
- risk assessment
- cross sectional
- peritoneal dialysis
- deep learning
- machine learning
- electronic health record
- human health
- monoclonal antibody
- data analysis