P-2052. Pre-existing Humoral Immunity to Seasonal Coronaviruses and Effect on SARS-CoV-2 Antibody Responses on SARS-CoV-2 Vaccination and Infection
Bibliographic record
Abstract
Abstract Background High homology and potential cross-reactive immune responses between SARS-CoV-2 and seasonal human coronaviruses (HCoVs) have been described by several studies. However, the role of pre-existing immunity to HCoVs in the outcome of SARS-CoV-2 infection and vaccination is still unclear. Anti-spike IgG titers against human coronavirus (HCoV)-229E, -HKU1, -NL63, and -OC43 by age of participants N=1,675 serum samples were collected from participants aged 2 to 95 years (median 44). anti-spike IgG titers against HCoV-229E, -HKU1, -NL63, and -OC43 were quantified by electrochemiluminescent immunoassay. Each dot represents the anti-HCoV spike IgG titer and age of the participant. Methods Pediatric and adult participants were enrolled. We collected demographic data and vaccination status, as well as serum samples at a single time point between August 2020 and August 2023. Anti-spike IgG titers against SARS-CoV-2 and HCoV-229E, -HKU1, -NL63, and -OC43 were quantified by electrochemiluminescent immunoassay. SARS-CoV-2 infection status was determined by the presence of anti-SARS-CoV-2 nucleocapsid antibodies. Correlations were assessed by two-sided Spearman rank-correlation tests. Correlations between SARS-CoV-2 and hCoV-229E, -HKU1, -NL63, and -OC43 spike IgG titers among SARS-CoV-2 unvaccinated participants To evaluate the effect of immunity against HCoVs on SARS-CoV-2 infection, correlations between SARS-CoV-2 and HCoV-229E, -HKU1, -NL63, and -OC43 spike IgG titers among SARS-CoV-2 unvaccinated participants are shown (N=380). Each dot represents individual participants. Solid and dotted lines respectively indicate linear regression and 95% confidence interval. Correlations were assessed by two-sided Spearman rank-correlation tests. Results Sera were collected from N=1,675 participants of which 5.7% were ≤10 years (age range: 2-95 yrs, median: 44 yrs). HCoV titers rapidly increased in early childhood and the majority of adults had immunity against HCoVs. We first analyzed N=380 sera from SARS-CoV-2 unvaccinated participants. SARS-CoV-2 titers positively correlated with HCoV-OC43, -HKU1, and -NL63 titers. Furthermore, HCoV-OC43 titers were significantly higher in participants post-SARS-CoV-2 infection, determined by the presence of SARS-CoV-2 nucleocapsid antibodies, as compared to non-infected participants (geometric mean, 49,256 vs 29,613; P< 0.01). Next, to evaluate the correlation between HCoV immunity and SARS-CoV-2 titers on vaccination, sera from N=1,059 SARS-CoV-2 non-infected participants were analyzed. Notably, positive correlations between SARS-CoV-2 and HCoV-OC43, and -HKU1 anti-spike IgG titers were demonstrated (r=0.43 and 0.27; both P< 0.0001). Although higher numbers of SARS-CoV-2 vaccinations were associated with more SARS-CoV-2 antibodies, HCoV-OC43 titers did not show a correlation. Correlations between SARS-CoV-2 and hCoV-229E, -HKU1, -NL63, and -OC43 spike IgG titers among SARS-CoV-2 non-infected participants To evaluate the effect of immunity against HCoVs on SARS-CoV-2 vaccination, correlations between SARS-CoV-2 and HCoV-229E, -HKU1, -NL63, and -OC43 spike IgG titers among SARS-CoV-2 non-infected participants, determined by the absence of SARS-CoV-2 nucleocapsid antibodies, are shown (N=1,059). Each dot represents individual participants. Solid and dotted lines respectively indicate linear regression and 95% confidence intervals. Correlations were assessed by two-sided Spearman rank-correlation tests. Conclusion HCoVs immunity was acquired in early childhood. HCoV-OC43 titers were higher in SARS-CoV-2 infected participants compared to non-infected. In SARS-CoV-2 non-infected participants, positive correlations were seen between SARS-CoV-2 and HCoV-OC43 and -HKU1 titers. Our data indicates that immunity against HCoVs may enhance SARS-CoV-2 immune responses on infection and vaccination. Anti-spike IgG titers against SARS-CoV-2 and HCoVs by numbers of previous SARS-CoV-2 vaccines SARS-CoV-2 and HCoV-229E, -HKU1, -NL63, and -OC43 spike IgG titers among SARS-CoV-2 non-infected participants, determined by the absence of SARS-CoV-2 nucleocapsid antibodies, are shown by numbers of previous SARS-CoV-2 vaccination (N=780). Geometric mean titers are listed. Data were analyzed by Kruskal–Wallis test. ** P<0.01. Disclosures Julia Upton, MD, ALK Abello: Advisor/Consultant|ALK Abello: Grant/Research Support|Bausch Health: Advisor/Consultant|DBV Technologies: Grant/Research Support|Pfizer: Advisor/Consultant|Pharming: Advisor/Consultant|Regeneron: Grant/Research Support|Sanofi: Grant/Research Support
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".