Lack of Association of C-C Chemokine Receptor 5 Δ32 Deletion Status with Rheumatoid Arthritis, Systemic Lupus Erythematosus, Lupus Nephritis, and Disease Severity
Bibliographic record
Abstract
OBJECTIVE: C-C chemokine receptor 5 (CCR5) plays an important role in inflammation. A 32 base-pair (Δ32) deletion in the CCR5 gene leads to a nonfunctional receptor. This deletion has been reported to have a protective effect on the development and progression of several autoimmune diseases. We investigated whether the Δ32 deletion is associated with disease susceptibility in a population of patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and lupus nephritis (LN); and whether it is associated with disease severity. METHODS: DNA samples from 405 RA patients, 97 SLE patients, 113 LN patients, and 431 healthy controls were genotyped for the CCR5 Δ32 deletion. Differences in genotype frequencies were tested between patients and controls. Association of genotypes with disease severity was analyzed. RESULTS: Genotype frequencies of each group were in Hardy-Weinberg equilibrium. The genotype frequencies of patients did not differ significantly from controls (CCR5/Δ32, Δ32/Δ32: RA 18.3% and 1.2%, respectively; SLE 17.5% and 2.1%; LN 13.3% and 1.8%; controls 20.0% and 2.8%). However, there was a trend for lower Δ32 deletion allele frequency in LN patients compared to controls (p = 0.08). There was no significant association between the CCR5 status and disease severity in RA, SLE, or LN. CONCLUSION: Although an association with LN cannot be excluded, the CCR5 Δ32 deletion does not seem to be a disease susceptibility genotype for RA, SLE, or LN. No significant effect of the Δ32 deletion on disease severity was demonstrated.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".