HLA-DRB1 Amino Acid Positions and Residues Associated with Antibody-positive Rheumatoid Arthritis in Black South Africans
Bibliographic record
Abstract
OBJECTIVE: To investigate the association of specific amino acid positions, residues, and haplotypes of HLA-DRB1 in black South Africans with autoantibody-positive rheumatoid arthritis (RA). METHODS: genotyping was performed in 266 black South Africans with autoantibody-positive RA and 362 ethnically and geographically matched controls. The alleles were converted to specific amino acid residues at polymorphic sites for downstream analyses. Logistic regression models were used to test whether variability at site, specific amino acid residues, and haplotypes (constructed from positions 11, 71, and 74) were associated with RA. RESULTS: , respectively) showed the strongest association with RA. Univariate analyses of individual amino acid residues showed valine at position 11 (OR 5.1, 95% CI 3.7-7.0) and histidine at position 13 (OR 6.1, 95% CI 4.2-8.6) conferred the highest risk. The valine containing haplotypes of position 11, 71, 74, V_K_A conferred the most risk (OR 4.52, 95% CI 2.68-7.61) and conversely the haplotype with serine at this position, S_K_R, conferred the most protection (OR 0.83, 95% CI 0.61-1.15). CONCLUSION: Autoantibody-positive RA in black South Africans is associated with histidine at position 13 and valine at position 11 of HLA-DRB1, and haplotypes with valine at position 11 conferred the highest risk; conversely, serine at position 11 conveyed protection.
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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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".