An IL10–PDGFB–STAM2 Axis in Peripheral CD1c+ cDC2 Cells Links JAK-STAT Signaling to Myeloid Immune Infiltration in Uveitis: Evidence from Mendelian Randomization, Multi-Omics, and In Vitro Validation

Background and objective: Uveitis is a group of immune-mediated inflammatory diseases of the eye and remains one of the leading causes of preventable visual loss in working-age adults, with relapsing and treatment-refractory phenotypes closely tied to disturbed peripheral myeloid immune homeostasis. Conventional type 2 dendritic cells (CD1c+ cDC2) sit at the junction between JAK-STAT cytokine signaling and antigen presentation, yet systematic work that quantifies this axis into a reproducible, falsifiable, and explicitly evidence-graded candidate set remains scarce. The present study therefore set out to decode the molecular pattern of the JAK-STAT axis in peripheral blood CD1c+ cDC2 cells from patients with uveitis and, while explicitly annotating the strength of each layer of evidence, to prioritize a candidate-target panel that can guide subsequent wet-laboratory work. Methods: With GEO dataset GSE194060 (28 uveitis and 14 healthy-control samples of sorted CD1c+ cDC2 cells) as the discovery cohort and the 168 genes of KEGG hsa04630 (JAK-STAT signaling) as a fixed molecular axis, we deployed an end-to-end pipeline: differential expression and three-way intersection (expression layer) → cis-instrument inverse-variance weighted (IVW) Mendelian randomization with FinnGen R12 iridocyclitis as the outcome (genetic-association layer) → consensus clustering and immune-microenvironment profiling → candidate locking by the intersection of LASSO, random forest, and SVM-RFE (machine-learning layer) → multi-cohort single-gene diagnostic modeling of STAM2 → aqueous-humor single-cell atlas and cell-cell communication → myeloid pseudotime and computational perturbation → qPCR, DrugReflector active-learning virtual screening, and molecular docking. Each layer was reported against its prespecified thresholds; the primary DrugReflector signature was evaluated by 200 sample-level bootstrap resamples, Mendelian randomization by leave-one-out analysis, and the remaining layers by the sensitivity analyses prespecified for each layer. Results: At the expression level, 3,301 nominally differential genes, the 168 JAK-STAT axis genes, and 3,872 uveitis-associated genes converged on an 18-gene intersection that included IL10 and PDGFB. At the genetic-association level, IVW analysis identified 20 genes at nominal significance (p< 0.05), 8 of which passed Benjamini-Hochberg FDR (q< 0.05); IL10 (q= 0.1246), STAM2 (q= 0.1246), and PDGFB (q= 0.1573) reached nominal significance only, without passing FDR correction, and are reported as nominal associations. The intersection of the three machine-learning algorithms converged on the three transcripts IL10 / PDGFB / STAM2. A STAM2 single-gene diagnostic model reached an AUC of 0.7883 in the training cohort and 0.8056 and 0.8000 in two independent myeloid/monocyte cohorts (a same-study audit cohort yielded 0.6288 and is used for sensitivity analysis only). The aqueous-humor single-cell atlas resolved 37,664 cells, 18 clusters, and 20 cell types; STAM2 myeloid pseudotime identified four differentiation states; and computational perturbation placed STAM2 among the most sensitive nodes (|Z|=5.17). DrugReflector active learning identified a single compound, BRD-K11973162 (probability 0.1591), exceeding the prespecified reversal-probability threshold of 0.10 among 9,597 compounds. In the LPS-stimulated THP-1 myeloid inflammation model, qPCR showed significant up-regulation of all three candidates relative to unstimulated controls (IL10, 1.5365-fold, p=3.17×10⁻³; PDGFB, 1.6592-fold, p=4.76×10⁻⁵; STAM2, 1.8220-fold, p=1.95×10⁻⁵; n=3 per group, n=3+3 total). Conclusion: In uveitis peripheral CD1c+ cDC2 cells, this study delineates a JAK-STAT-centered IL10–PDGFB–STAM2 candidate panel defined by an integrated chain of expression, genetic-association, machine-learning, single-cell, and in vitro evidence, and proposes BRD-K11973162 as the sole computationally prioritized candidate compound under the prespecified reversal-probability threshold. The computational and single-cell results are computational inferences; qPCR provides experimental support at the level of relative mRNA expression in LPS-stimulated THP-1 cells and does not address protein levels, cellular function, or clinical diagnostic performance. The candidate panel and its causal direction still require confirmation in prospective multicenter cohorts and functional experiments.