Classification of human chronic inflammatory skin disease based on single-cell immune profiling

Abstract

Inflammatory conditions represent the largest class of chronic skin disease, but the molecular dysregulation underlying many individual cases remains unclear. Single-cell RNA sequencing (scRNA-seq) has increased precision in dissecting the complex mixture of immune and stromal cell perturbations in inflammatory skin disease states. We single-cell–profiled CD45 + immune cell transcriptomes from skin samples of 31 patients (7 atopic dermatitis, 8 psoriasis vulgaris, 2 lichen planus (LP), 1 bullous pemphigoid (BP), 6 clinical/histopathologically indeterminate rashes, and 7 healthy controls). Our data revealed active proliferative expansion of the T reg and Trm components and universal T cell exhaustion in human rashes, with a relative attenuation of antigen-presenting cells. Skin-resident memory T cells showed the greatest transcriptional dysregulation in both atopic dermatitis and psoriasis, whereas atopic dermatitis also demonstrated recurrent abnormalities in ILC and CD8 + cytotoxic lymphocytes. Transcript signatures differentiating these rash types included genes previously implicated in T helper cell (T H 2)/T H 17 diatheses, segregated in unbiased functional networks, and accurately identified disease class in untrained validation data sets. These gene signatures were able to classify clinicopathologically ambiguous rashes with diagnoses consistent with therapeutic response. Thus, we have defined major classes of human inflammatory skin disease at the molecular level and described a quantitative method to classify indeterminate instances of pathologic inflammation. To make this approach accessible to the scientific community, we created a proof-of-principle web interface (RashX), where scientists and clinicians can visualize their patient-level rash scRNA-seq–derived data in the context of our T H 2/T H 17 transcriptional framework.

Defining Patient-Level Molecular Heterogeneity in Psoriasis Vulgaris Based on Single-Cell Transcriptomics

“…We focused on 7 normal and 8 psoriasis samples from the Liu et al. study ( 8 ) ( Supplementary Table 1 ). Diagnoses were based on clinical evaluation by a board-certified dermatologist and confirmed by formal histopathological reading.…”

“…We obtained 20 cell types based on previously described unsupervised clustering approaches ( 8 ). Robust representation of each sample was observed ( Supplementary Data 1 ).…”

“…Patient recruitment and methods are detailed in our companion publication ( 8 ). Briefly, written informed consent was procured from donors providing both normal and psoriatic lesional skin under protocols approved by the University of California, San Francisco Institutional Review Board.…”

“…CD45 + Immune Cell Isolation, Single-Cell RNA-seq and CITE-Seq Profiling, and Data Processing Details of skin biopsy sample processing, CD45 + immune cell isolation, 10X Genomics 3' scRNA-seq and CITE-seq library preparation, and data analysis are further described in a recent prior publication (8). Briefly, we initially performed highresolution clustering and eliminated populations corresponding to non-immune and low quality cells (mitochondrial genes percentage <20%, 100 < nFeatures < 6000).…”

“…To formally deconstruct discrete levels of molecular heterogeneity underlying cutaneous psoriatic inflammation, we analyzed data from a recent study profiling 8 psoriasis samples and 7 normal controls using single-cell RNAseq (scRNA-seq) and CITE-seq based on the 10X Genomics Chromium platform ( 8 ). We intended to develop and test approaches to scRNA-seq datasets profiling chronic inflammatory disease that could be practically and widely applied as similar datasets become published.…”