Associations of HLA Polymorphisms with Anti-SARS-CoV-2 Spike and Neutralizing Antibody Titers in Japanese Rheumatoid Arthritis Patients Vaccinated with BNT162b2
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes Coronavirus Disease 2019. Anti-SARS-CoV-2 spike (S) and neutralizing antibodies (Abs) are measured to evaluate the efficacy of vaccines. Human leukocyte antigen (HLA) may be associated with vaccine efficacy. Here, we investigated the association of HLA polymorphisms with the production of anti-SARS-CoV-2 S or neutralizing Abs in vaccinated rheumatoid arthritis (RA) patients in Japan. Genotyping of DRB1 and DQB1 was conducted in 87 Japanese RA patients vaccinated with BNT162b2. Associations of allele or haplotype carrier frequencies with anti-SARS-CoV-2 S or neutralizing Abs were examined. DRB1*12:01 was significantly positively associated with the production of S Ab (p = 0.0225, odds ratio [OR] 6.08, 95% confidence interval [CI] 1.32–28.03). The DQB1*03:01 allele carrier frequency tended to be higher in high responders of S Ab. Allele carrier frequencies of DRB1*15:01 (p = 0.0102, OR 9.26, 95% CI 1.65–52.01) and DQB1*06:02 (p = 0.0373, OR 7.00, 95% CI 1.18–41.36) were higher in responders of neutralizing Ab. Haplotype and two-locus analyses of DRB1 and DQB1 suggested that DRB1 alleles were the primary drivers of these associations. Logistic regression analysis showed associations of these alleles independent of clinical characteristics. Independent associations were found between HLA alleles and anti-SARS-CoV-2 Ab production by vaccinated RA patients.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".