| Literature DB >> 34954658 |
Lorenzo Azzi1, Daniela Dalla Gasperina2, Giovanni Veronesi3, Mariam Shallak4, Giuseppe Ietto2, Domenico Iovino2, Andreina Baj2, Francesco Gianfagna5, Vittorio Maurino2, Daniele Focosi6, Fabrizio Maggi2, Marco Mario Ferrario3, Francesco Dentali2, Giulio Carcano2, Angelo Tagliabue2, Lorenzo Stefano Maffioli7, Roberto Sergio Accolla4, Greta Forlani4.
Abstract
BACKGROUND: Although the BNT162b2 COVID-19 vaccine is known to induce IgG neutralizing antibodies in serum protecting against COVID-19, it has not been studied in detail whether it could generate specific immunity at mucosal sites, which represent the primary route of entry of SARS-CoV-2.Entities:
Keywords: BNT162b2 mRNA vaccine; COVID-19; IgA; SARS-CoV-2; Saliva
Mesh:
Substances:
Year: 2021 PMID: 34954658 PMCID: PMC8718969 DOI: 10.1016/j.ebiom.2021.103788
Source DB: PubMed Journal: EBioMedicine ISSN: 2352-3964 Impact factor: 8.143
Figure 1Distribution of serum (panels A and B) and salivary (panels C and D) IgG and IgA, at different times, for all the recruited individuals and according to previous SARS-CoV-2 status at T0. In each group, the horizontal line represents the sample median, while the vertical line the interquartile range.
Time trends for IgG and IgA antibodies in both serum and saliva, overall sample and by previous SARS-CoV-2 exposure.
| Variable, time | All subjects (n=60) | No previous SARS-CoV-2 (SN; n=50) | Previous SARS-CoV-2 (SP; n=10) | p-value | p-value | |||
|---|---|---|---|---|---|---|---|---|
| Mean | Δ (IC 95%) | Mean | Δ (IC 95%) | Mean | Δ (IC 95%) | |||
| Serum IgG (ng/ml)a | ||||||||
| T0 | 0.04 | - | 0.01 | - | 3.7 | - | 0.005 | 0.45 |
| T1 | 432.1 | 432.1 (219.3; 644.8) | 255.6 | 255.6 (112.0; 399.2) | 5962.2 | 5958.5 (-956.4; 12873.4) | 0.11 | |
| T2 | 20373.65 | 20373.6 (11486.0; 29261.2) | 17341.4 | 17341.4 (10262.7; 24420.1) | 45603.0 | 45599.3 (14787.7; 76410.8) | 0.08 | |
| Serum IgA (ng/ml)a | ||||||||
| T0 | 0.02 | - | 0.01 | - | 0.1 | - | <0.0001 | 0.24 |
| T1 | 1.71 | 1.7 (0.01; 3.4) | 1.10 | 1.1 (-0.1; 2.3) | 16.1 | 16 (-22.2; 54.1) | 0.44 | |
| T2 | 49.59 | 49.6 (21.1; 78.0) | 61.6 | 61.6 (29.5; 93.7) | 16.7 | 16.6 (-21.6; 54.9) | 0.08 | |
| Salivary IgG (ng/ml)a | ||||||||
| T0 | 0.02 | - | 0.02 | - | 0.03 | - | 0.04 | <0.0001 |
| T1 | 0.07 | 0.1 (0; 0.1) | 0.04 | 0.02 (-0.01; 0.06) | 1.08 | 1.1 (-1.2; 3.3) | 0.36 | |
| T2 | 10.8 | 10.8 (6.8; 14.8) | 9.8 | 9.7 (4.1; 15.4) | 18.1 | 18.1 (-7.2; 43.3) | 0.53 | |
| Salivary IgA, (ng/ml)a | ||||||||
| T0 | 0.02 | - | 0.02 | - | 0.02 | - | 0.22 | 0.06 |
| T1 | 0.05 | 0.02 (0.01; 0.05) | 0.04 | 0.02 (-0.01; 0.05) | 0.06 | 0.04 (-0.02; 0.11) | 0.59 | |
| T2 | 0.07 | 0.05 (0.02; 0.08) | 0.06 | 0.04 (0.01; 0.07) | 0.16 | 0.14 (-0.05; 0.32) | 0.29 | |
a: Change in geometric mean concentration, modelled through a log-linear regression model for repeated measures, with unstructured variance-covariance matrix and adjusting for baseline.
1: Geometric mean concentration
2: p-value testing homogeneity of trends between subjects with and without previous SARS-CoV-2 infection.
3: p-value testing homogeneity of geometric mean values in IgG and IgA between subjects with and without previous SARS-CoV-2 infection, at each time.
Figure 2Scatter-plot for salivary and serum IgG (panel A) and IgA (panel B) at different times according to previous SARS-CoV-2 status at T0.
Figure 3ROC curve for serum and salivary IgG to identify individuals with CLIA above 15 (A) and 90 (B) AU/ml
Figure 4Scatter-plot for salivary IgG and IgA among individuals with positive salivary NAb (n=15) at T2, according to previous SARS-CoV-2 status at T0.