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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 8

Pseudotemporal dynamics reveal transition dynamics of stress keratinocytes.

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Pseudotemporal dynamics reveal transition dynamics of stress keratinocyt...
(A) Projection of keratinocytes onto the PHATE space revealed the potential lineage relationships between different keratinocyte subpopulations in nonlesional (NL, left panel) and lesional (LS, right panel) skin. Cells were colored by the annotated cell identity. (B) The inferred pseudotemporal trajectories of all cells using Monocle 3. Cells were colored by the inferred pseudotime. Pseudotemporal trajectory analysis revealed 2 potential transitional paths, as indicated by Path 1 and Path 2. (C) Pseudotemporal dynamics of all pseudotime-dependent genes along the Path 1 and Path 2. Each row (i.e., gene) is normalized to its peak value along the pseudotime. These genes were clustered into 5 groups with the average expression patterns (middle) and representative genes (right). Solid and dashed lines indicate the average expression of a particular gene group in Path 1 and Path 2, respectively. The number of genes in each gene group is indicated in parenthesis. (D) Enriched biological processes of the 5 gene groups in C.

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ISSN 2379-3708

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