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Deprecated: Implicit conversion from float 286.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 J+Virol+Methods 2021 ; 287 (ä): 113996 Nephropedia Template TP
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Anti-SARS-CoV-2 IgG antibody response among Indian COVID-19 patients using beta-propiolactone-inactivated, whole virus-based indirect ELISA #MMPMID33126149
J Virol Methods 2021[Jan]; 287 (ä): 113996 PMID33126149show ga
BACKGROUND: Coronavirus disease 2019 (COVID-19) pandemic caused by infection with severe acute respiratory syndrome - coronavirus-2 (SARS-CoV-2) continues to affect many countries and large populations. Serologic assays for antibody detection aid patient diagnosis and seroepidemiologic investigations. METHODS: An indirect IgG ELISA was developed indigenously using beta-propiolactone (BPL) inactivated SARS-CoV-2. This assay was used for screening 200 healthy donor sera collected prior to COVID-19 emergence (2017-2019), 185 serum/plasma samples of confirmed COVID-19 patients (n?=?137) and 57 samples of viral RNA positive asymptomatic contacts (n?=?51). The IgG response was studied in relation to duration and severity of illness. RESULTS: The ELISA demonstrated 97 % specificity and IgG detection in >50 %, 80 %, 93.8 % and 100 % of the patients respectively during the first, second, third and fourth week of illness. IgG detection rate was higher in patients with severe disease (SD, 90.9 %) than those with mild disease (MD, 68.8 %) during the second week of illness (P?=?0.027). IgG seropositivity among asymptomatic contacts was 64.7 %. IgG ELISA absorbance values were higher in SD than MD patients during the first 2 weeks of illness (P?0.05). No significant difference was observed between the absorbance values of asymptomatic subjects and MD patients (P?=?0.94). CONCLUSION: The BPL inactivated virus-based ELISA could detect IgG antibodies early and in a significant proportion of COVID-19 patients suggesting its potential utility as a supplement to the currently used viral RNA detection tests in patient diagnosis and contact screening algorithms.