Integrated Multi-Omics Profiling Reveals That Highly Pyroptotic MDMs Contribute to Psoriasis Progression Through CXCL16
Bibliographic record
Abstract
Background: Psoriasis, an inflammatory skin disorder, involves pyroptosis—a pro-inflammatory cell death process. However, cell-specific pyroptosis dynamics and immune microenvironment interactions remain unclear. Objective: To investigate cell-type-specific pyroptosis patterns in psoriasis and their immunoregulatory mechanisms. Methods: We integrated 21 transcriptomic datasets (from 2007 to 2020) obtained from the GEO database and two single-cell RNA sequencing datasets to quantify pyroptotic activity using Gene Set Variation Analysis and AUCell algorithms. Immune cell infiltration profiles were evaluated via CIBERSORT, while cell-cell communication networks were analyzed by CellChat. In vitro and in vivo experiments were performed to validate key findings. Results: Our analysis revealed that psoriasis patients exhibited significantly elevated levels of pyroptosis compared to healthy controls, with pyroptotic activity reflecting treatment responses. Notably, monocyte-derived macrophages (MDMs) in psoriatic lesions displayed markedly heightened pyroptotic activity. In vitro experiments confirmed that MDMs derived from psoriasis patients overexpressed pyroptosis-related molecules (Caspase 1 and Caspase 4) as well as pro-inflammatory cytokines (TNFα, IL6, IL1β) when compared to healthy controls. Furthermore, these cells showed increased expression of CXCL16, which might potentially activate Th17 cells through CXCR6 signaling, thereby driving skin inflammation. Inhibition of monocyte migration in an imiquimod-induced psoriasiform dermatitis model significantly alleviated skin inflammation and reduced the proportion of M1 macrophages and Th17 cells in lesional skin. Conclusions: This study revealed that MDMs in psoriatic lesions exhibited a hyperactive pyroptotic state, which contributed to disease progression through CXCL16-mediated remodeling of the immune microenvironment. These findings highlight pyroptosis as a potential therapeutic target for psoriasis.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".