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Validation of the GSP ® /DELFIA ® Anti-SARS-CoV-2 IgG Kit Using Dried Blood Samples for High-Throughput Serosurveillance and Standardized Quantitative Measurement of Anti-Spike S1 IgG Antibody Responses Post-Vaccination.

Ilaria CicaliniPiero Del BoccioMirco ZucchelliClaudia RossiLuca NataleGianmaria DemattiaDomenico De BellisVerena DamianiMaria Lucia TommoliniErika PizzinatoAlberto FriscoSara VerrocchioInes BucciLiborio StuppiaVincenzo De LaurenziDamiana Pieragostino
Published in: Vaccines (2022)
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a major global public health crisis. In response, researchers and pharmaceutical companies worked together for the rapid development of vaccines to reduce the morbidity and mortality associated with viral infection. Monitoring host immunity following virus infection and/or vaccination is essential to guide vaccination intervention policy. Humoral immune response to vaccination can be assessed with serologic testing, and indeed, many serological immunoassays are now in use. However, these many different assays make the standardization of test results difficult. Moreover, most published serological tests require venous blood sampling, which makes testing large numbers of people complex and costly. Here, we validate the GSP ® /DELFIA ® Anti-SARS-CoV-2 IgG kit using dried blood samples for high-throughput serosurveillance using standard quantitative measurements of anti-spike S1 IgG antibody concentrations. We then apply our validated assay to compare post-vaccination anti-SARS-CoV-2 S1 IgG levels from subjects who received a double dose of the AZD1222 vaccine with those vaccinated with a heterologous strategy, demonstrating how this assay is suitable for large-scale screening to achieve a clearer population immune picture.
Keyphrases
  • sars cov
  • respiratory syndrome coronavirus
  • high throughput
  • public health
  • coronavirus disease
  • randomized controlled trial
  • immune response
  • single cell
  • high resolution
  • mass spectrometry
  • sensitive detection