MHC-I-opathy: A Unified Concept for the Etiology of Several Major Histocompatibility Complex–Associated Conditions Including Psoriasis and Psoriatic Arthritis
Bibliographic record
Abstract
At the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2024 annual meeting, Drs. Dennis McGonagle and Wilson Liao discussed "MHC-I-opathies," a class of immune-mediated diseases genetically associated with major histocompatibility complex class I (MHC-I) and class I peptide processing. MHC-I-opathies demonstrate epistatic interactions, genetic associations, and immunopathology that are distinct from classic B cell and autoantibody-driven autoimmune diseases. Investigations into the pathomechanisms of MHC-I-opathies have revealed a blend of tissue-specific innate immunity and CD8 T cell responses. Several functional pathomechanisms by which MHC-I molecules increase psoriasis (PsO) susceptibility were presented by McGonagle and Liao, and there were multiple associations within the HLA-C locus. Antigen presentation to T cells, HLA regulation of natural killer cells and CD8 T cells through killer immunoglobulin-like receptors, and HLA regulation of dendritic cells through leukocyte immunoglobulin-like receptors were discussed. Interestingly, MHC-I associations are not only linked to excessive inflammation in MHC-I-opathies but also to the spontaneous suppression of infection (eg, HIV-1 elite controllers). This striking prominence of MHC-I in PsO and antiviral immunity provides insight into why autoimmune alleles are maintained in the human genome and how protective antiviral pathways may be linked to aberrant activation of MHC-I-opathies. Outside of spinal inflammation in HLA-B27-positive axial psoriatic arthritis (PsA), the basis for MHC-I genetics in PsA remains less clear and is at least partly linked to greater PsA heterogeneity. Understanding the contribution of MHC-I in PsO and PsA may have important implications for therapy development.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".