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Multimodal analyses of vitiligo skin idenitfy tissue characteristics of stable disease
Jessica Shiu, … , Mihaela Balu, Anand K. Ganesan
Jessica Shiu, … , Mihaela Balu, Anand K. Ganesan
Published June 2, 2022
Citation Information: JCI Insight. 2022;7(13):e154585. https://doi.org/10.1172/jci.insight.154585.
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Research Article Dermatology

Multimodal analyses of vitiligo skin idenitfy tissue characteristics of stable disease

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Abstract

Vitiligo is an autoimmune skin disease characterized by the destruction of melanocytes by autoreactive CD8+ T cells. Melanocyte destruction in active vitiligo is mediated by CD8+ T cells, but the persistence of white patches in stable disease is poorly understood. The interaction between immune cells, melanocytes, and keratinocytes in situ in human skin has been difficult to study due to the lack of proper tools. We combine noninvasive multiphoton microscopy (MPM) imaging and single-cell RNA-Seq (scRNA-Seq) to identify subpopulations of keratinocytes in stable vitiligo patients. We show that, compared with nonlesional skin, some keratinocyte subpopulations are enriched in lesional vitiligo skin and shift their energy utilization toward oxidative phosphorylation. Systematic investigation of cell-to-cell communication networks show that this small population of keratinocyte secrete CXCL9 and CXCL10 to potentially drive vitiligo persistence. Pseudotemporal dynamics analyses predict an alternative differentiation trajectory that generates this new population of keratinocytes in vitiligo skin. Further MPM imaging of patients undergoing punch grafting treatment showed that keratinocytes favoring oxidative phosphorylation persist in nonresponders but normalize in responders. In summary, we couple advanced imaging with transcriptomics and bioinformatics to discover cell-to-cell communication networks and keratinocyte cell states that can perpetuate inflammation and prevent repigmentation.

Authors

Jessica Shiu, Lihua Zhang, Griffin Lentsch, Jessica L. Flesher, Suoqin Jin, Christopher Polleys, Seong Jin Jo, Craig Mizzoni, Pezhman Mobasher, Jasmine Kwan, Francisca Rius-Diaz, Bruce J. Tromberg, Irene Georgakoudi, Qing Nie, Mihaela Balu, Anand K. Ganesan

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Figure 5

Stress keratinocytes have altered energy utilization and shift toward oxidative phosphorylation.

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Stress keratinocytes have altered energy utilization and shift toward ox...
(A) Violin plots of signature scores of OxPhos, glycolysis, WNT signaling, IFN-γ, IFN-α, and inflammatory response across nonlesional skin, lesional skin, and stress keratinocytes. The 2-sided Wilcoxon rank-sum test was used to evaluate whether there are significant differences in the computed signature scores. (B) Enrichment analysis of 21 metabolic pathways in stress keratinocytes versus other keratinocytes. Each dot represents 1 pathway. The x axis represents the differential gene signature scores of each metabolic pathway between stress keratinocytes and other keratinocytes. The y axis represents the Pearson’s correlation of gene signature scores between each metabolic pathway and stress response. Gene signature scores of stress response were computed based on the marker genes of stress keratinocytes. Colors represent the P values from 2-sided Wilcoxon rank-sum tests of each gene signature score between stress keratinocyte and other keratinocytes. (C) The number of differentially expressed OxPhos- and glycolysis-related genes in stress keratinocytes versus other keratinocytes. (D) Heatmap showing the average expression of top 18 differentially expressed OxPhos-related genes between stress keratinocytes and other keratinocytes. The top green bars represent the difference in the proportion of expressed cells between stress keratinocytes and other keratinocytes. (E) RNAscope demonstrating Krt6A and Krt10 in situ hybridization in patient-matched lesional and nonlesional punch grafting tissue. DAPI (cyan) was used to stain nuclei and second harmonic generation (blue) demonstrating location of collagen.

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