Systemic and mucosal IgA responses are variably induced in response to SARS-CoV-2 mRNA vaccination and are associated with protection against subsequent infection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although SARS-CoV-2 infects the upper respiratory tract, we know little about the amount, type, and kinetics of antibodies (Ab) generated in the oral cavity in response to COVID-19 vaccination. We collected serum and saliva samples from participants receiving two doses of mRNA COVID-19 vaccines and measured the level of anti-SARS-CoV-2 Ab. We detected anti-Spike and anti-Receptor Binding Domain (RBD) IgG and IgA, as well as anti-Spike/RBD associated secretory component in the saliva of most participants after dose 1. Administration of a second dose of mRNA boosted the IgG but not the IgA response, with only 30% of participants remaining positive for IgA at this timepoint. At 6 months post-dose 2, these participants exhibited diminished anti-Spike/RBD IgG levels, although secretory component-associated anti-Spike Ab were more stable. Examining two prospective cohorts we found that participants who experienced breakthrough infections with SARS-CoV-2 variants had lower levels of vaccine-induced serum anti-Spike/RBD IgA at 2-4 weeks post-dose 2 compared to participants who did not experience an infection, whereas IgG levels were comparable between groups. These data suggest that COVID-19 vaccines that elicit a durable IgA response may have utility in preventing infection. Our study finds that a local secretory component-associated IgA response is induced by COVID-19 mRNA vaccination that persists in some, but not all participants. The serum and saliva IgA response modestly correlate at 2-4 weeks post-dose 2. Of note, levels of anti-Spike serum IgA (but not IgG) at this timepoint are lower in participants who subsequently become infected with SARS-CoV-2. As new surges of SARS-CoV-2 variants arise, developing COVID-19 booster shots that provoke high levels of IgA has the potential to reduce person-to-person transmission.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it