Next generation sequencing reveals HLA and KIR susceptibility alleles for rheumatoid arthritis
Bibliographic record
Abstract
Abstract Previous associations of KIR with rheumatoid arthritis (RA) have been reported in some but not all populations studied, possibly due to limited genotyping in some studies, and gene content homogeneity in some populations. In this study, HLA and KIR typing was carried out, including KIR haplotype and allele typing, using state of the art sequencing methodologies in a re-examination of the association of these gene families with RA in a Japanese cohort. An additional cohort of pollen allergy patients was examined in an effort to distinguish common genetic elements in a phenotype functionally reciprocal to RA. DNAs from 116 RA patients, 167 pollen allergy patients, and 185 healthy controls were examined for KIR haplotype, allele type and HLA class I and II allele types using next generation sequencing (NGS). Association analysis was carried out with healthy controls classified into two groups, positive and negative for allergen specific IgE antibodies, including a pollen allergy group for comparison with RA. Significant results were observed with allele types KIR2DS4*007 and KIR3DL1*00501, which strongly associated with disease, while KIR 3DL1*001 and 3DL1*02901 associated with a protective phenotype. These findings were significant when compared with the IgE positive control group while the IgE-negative group did not demonstrate significance. Given that KIR3DL1 is an inhibitory receptor and the KIR3DL1*00501 allele has been reported as a low expression allele, these findings are consistent with a model of weak suppression of NK cytotoxic activity as a contributing factor in RA. Further support for this model was observed from the reciprocity of the genetic associations between RA and pollen allergy.
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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 | 0.001 |
| 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) | 0.001 | 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".