Deep learning-based integrative single-cell transcriptomic analysis of vitiligo
5 affiliations
- 1Department of Dermatology and Venereology, People’s Hospital of Xinjiang Uygur Autonomous Region
- 2Xinjiang Clinical Research Center for Dermatology and Venereology
- 3Xinjiang Key Laboratory of Dermatology Research
- 4Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences
- 5Graduate School of Xinjiang Medical University
Abstract
Introduction: Vitiligo is an immune-mediated depigmentation disorder in which interferon-γ signalling and autoreactive CD8+ T cells are central, but the cross-cohort cellular ecosystem and donor-level disease signature remain incompletely resolved.
Methods: We conducted a retrospective analysis of three public skin single-cell RNA-sequencing datasets comprising 35 donors and 93,287 post-quality-control cells. We combined donor-aware cell-composition and pseudobulk analyses with a deep attention multiple-instance learning model, and reserved a separate balanced patient -control cohort for independent evaluation.
Results: Eleven major cell populations were identified. The donor-level classifier achieved 0.914 accuracy and an area under the receiver operating characteristic curve of 0.990 in donor-stratified five-fold cross-validation. After Benjamini -Hochberg correction across 11 cell types, vitiligo lesions showed macrophage expansion and depletion of fibroblasts, endothelial cells, and mast cells (all q = 0.029). Integrated ranking prioritised an interferon-γ/CXCL9 -CXCL10 programme, while CD8+ T cells displayed Trm-associated and cytotoxic-effector transcriptional states. An eight-feature signature trained only in the primary discovery cohort achieved an area under the curve of 0.944 (95% CI, 0.778 -1.000) and accuracy of 0.750 (95% CI, 0.468 -0.911) in a small independent cohort of six healthy controls and six patients with vitiligo; exact label permutation supported discrimination ( p = 0.003). A directional omnibus test across ten prespecified validation measures supported panel-level concordance ( p = 0.023), although no individual measure remained significant after multiple-testing correction.
Discussion: These findings provide preliminary external support for a multivariable signal connecting an expanded macrophage compartment, interferon-associated chemokine signalling, and Trm-like CD8+ T-cell states.
Related
- Multi-Model Machine Learning Consensus Identifies a Dual-Interferon Gene Signature in Ischemic Stroke: An Integrative Single-Cell Transcriptomic Analysis
- Genetic Insights into the Potential Causal Role of LIPA and LTA4H in Vitiligo: A Single-Cell Integrative Analysis.
- Integrative single-cell and bulk transcriptomic analysis identify R-loop-associated gene signatures driving immune-inflammatory networks in acute pancreatitis
- Integrative genotype-environment association and single-cell transcriptomic analyses identify candidate mechanisms of environmental adaptation in pigs.
- Integrative single-cell and bulk transcriptomic analysis identifies monocyte/macrophage senescence-associated candidate genes in pulmonary arterial hypertension
BibTeX
@article{xiang2026deep,
title = {{Deep learning-based integrative single-cell transcriptomic analysis of vitiligo}},
author = {Fang Xiang and Yuan Ding and Jingzhan Zhang and Shirong Yu and Xiangyue Zhang and Hongjuan Wang and Yun Qiu and Hengchuang Yin and Xiaojing Kang},
journal = {Frontiers in Immunology},
year = {2026},
month = nov,
doi = {10.3389/fimmu.2026.1962144},
url = {https://www.frontiersin.org/articles/10.3389/fimmu.2026.1962144/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Deep learning-based integrative single-cell transcriptomic analysis of vitiligo
AU - Fang Xiang
AU - Yuan Ding
AU - Jingzhan Zhang
AU - Shirong Yu
AU - Xiangyue Zhang
AU - Hongjuan Wang
AU - Yun Qiu
AU - Hengchuang Yin
AU - Xiaojing Kang
PY - 2026
DA - 2026/11/03
JO - Frontiers in Immunology
DO - 10.3389/fimmu.2026.1962144
UR - https://www.frontiersin.org/articles/10.3389/fimmu.2026.1962144/full
AB - Introduction: Vitiligo is an immune-mediated depigmentation disorder in which interferon-γ signalling and autoreactive CD8+ T cells are central, but the cross-cohort cellular ecosystem and donor-level disease signature remain incompletely resolved. Methods: We conducted a retrospective analysis of three public skin single-cell RNA-sequencing datasets comprising 35 donors and 93,287 post-quality-control cells. We combined donor-aware cell-composition and pseudobulk analyses with a deep attention multiple-instance learning model, and reserved a separate balanced patient -control cohort for independent evaluation. Results: Eleven major cell populations were identified. The donor-level classifier achieved 0.914 accuracy and an area under the receiver operating characteristic curve of 0.990 in donor-stratified five-fold cross-validation. After Benjamini -Hochberg correction across 11 cell types, vitiligo lesions showed macrophage expansion and depletion of fibroblasts, endothelial cells, and mast cells (all q = 0.029). Integrated ranking prioritised an interferon-γ/CXCL9 -CXCL10 programme, while CD8+ T cells displayed Trm-associated and cytotoxic-effector transcriptional states. An eight-feature signature trained only in the primary discovery cohort achieved an area under the curve of 0.944 (95% CI, 0.778 -1.000) and accuracy of 0.750 (95% CI, 0.468 -0.911) in a small independent cohort of six healthy controls and six patients with vitiligo; exact label permutation supported discrimination ( p = 0.003). A directional omnibus test across ten prespecified validation measures supported panel-level concordance ( p = 0.023), although no individual measure remained significant after multiple-testing correction. Discussion: These findings provide preliminary external support for a multivariable signal connecting an expanded macrophage compartment, interferon-associated chemokine signalling, and Trm-like CD8+ T-cell states.
SN - 1664-3224
ER -