Cutting Edge: Heterozygote Advantage in Autoimmune Disease: Hierarchy of Protection/Susceptibility Conferred by HLA and Killer Ig-Like Receptor Combinations in Psoriatic Arthritis
Bibliographic record
Abstract
Functionally relevant combinations of HLA and killer Ig-like receptor (KIR) genotypes influence resistance to several diseases in humans. Analysis of genetic data from such studies is challenging because it involves multiple linked and unlinked loci that exert their influence in an epistatic manner. We previously reported that subjects with certain activating receptors were susceptible to developing psoriatic arthritis (PsA), an effect that was strongest when HLA ligands for corresponding homologous inhibitory receptors were missing. In this study, we present a novel model in which susceptibility to PsA is determined by the overall balance of activating and inhibitory composite KIR-HLA genotypes. This model fits our knowledge of clonal NK cell expression of KIR and regulation of NK cell activity better than does the previous model, as reflected in a robust trend for increasing susceptibility to PsA with more activating genotypes. These data emphasize the remarkable influence of KIR/HLA combinations on this disease.
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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 | 0.001 |
| 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 | 0.001 | 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".