CXCL10 Is Critical for the Progression and Maintenance of Depigmentation in a Mouse Model of Vitiligo
Bibliographic record
Abstract
Vitiligo is an autoimmune disease of the skin that results in disfiguring white spots. There are no U.S. Food and Drug Administration-approved treatments for vitiligo, and most off-label treatments yield unsatisfactory results. Vitiligo patients have increased numbers of autoreactive, melanocyte-specific CD8(+) T cells in the skin and blood, which are directly responsible for melanocyte destruction. We report that gene expression in lesional skin from vitiligo patients revealed an interferon-γ (IFN-γ)-specific signature, including the chemokine CXCL10. CXCL10 was elevated in both vitiligo patient skin and serum, and CXCR3, its receptor, was expressed on pathogenic T cells. To address the function of CXCL10 in vitiligo, we used a mouse model of disease that also exhibited an IFN-γ-specific gene signature, expression of CXCL10 in the skin, and up-regulation of CXCR3 on antigen-specific T cells. Mice that received Cxcr3(-/-) T cells developed minimal depigmentation, as did mice lacking Cxcl10 or treated with CXCL10-neutralizing antibody. CXCL9 promoted autoreactive T cell global recruitment to the skin but not effector function, whereas CXCL10 was required for effector function and localization within the skin. Surprisingly, CXCL10 neutralization in mice with established, widespread depigmentation induces reversal of disease, evidenced by repigmentation. These data identify a critical role for CXCL10 in both the progression and maintenance of vitiligo and thereby support inhibiting CXCL10 as a targeted treatment strategy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".