The Role of Autoimmunity-Related Gene <i>CLEC16A</i> in the B Cell Receptor–Mediated HLA Class II Pathway
Bibliographic record
Abstract
Abstract C-type lectin CLEC16A is located next to CIITA, the master transcription factor of HLA class II (HLA-II), at a susceptibility locus for several autoimmune diseases, including multiple sclerosis (MS). We previously found that CLEC16A promotes the biogenesis of HLA-II peptide-loading compartments (MIICs) in myeloid cells. Given the emerging role of B cells as APCs in these diseases, in this study, we addressed whether and how CLEC16A is involved in the BCR-dependent HLA-II pathway. CLEC16A was coexpressed with surface class II–associated invariant chain peptides (CLIP) in human EBV-positive and not EBV-negative B cell lines. Stable knockdown of CLEC16A in EBV-positive Raji B cells resulted in an upregulation of surface HLA-DR and CD74 (invariant chain), whereas CLIP was slightly but significantly reduced. In addition, IgM-mediated Salmonella uptake was decreased, and MIICs were less clustered in CLEC16A-silenced Raji cells, implying that CLEC16A controls both HLA-DR/CD74 and BCR/Ag processing in MIICs. In primary B cells, CLEC16A was only induced under CLIP-stimulating conditions in vitro and was predominantly expressed in CLIPhigh naive populations. Finally, CLIP-loaded HLA-DR molecules were abnormally enriched, and coregulation with CLEC16A was abolished in blood B cells of patients who rapidly develop MS. These findings demonstrate that CLEC16A participates in the BCR-dependent HLA-II pathway in human B cells and that this regulation is impaired during MS disease onset. The abundance of CLIP already on naive B cells of MS patients may point to a chronically induced stage and a new mechanism underlying B cell–mediated autoimmune diseases such as MS.
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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 | 0.000 |
| 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 | 0.001 |
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".