Dataset Information

Single cell RNA-seq of psoriatic skin identifies pathogenic Tc17 subsets and reveals distinctions between CD8+ T cells in autoimmunity and cancer

ABSTRACT: Psoriasis is an inflammatory, IL-17-driven skin disease in which autoantigen-induced CD8+ T cells have been identified as pathogenic drivers. In this study, we used single-cell RNA-seq to identify 11 transcriptionally diverse CD8+ T cell subsets in psoriatic and healthy skin. Among several inflammatory subsets enriched in psoriatic skin, we observed two Tc17 subsets that were metabolically divergent, developmentally related, and expressed CXCL13, which we found to be a biomarker of psoriasis severity. Despite high co-inhibitory receptor expression in the Tc17 clusters, a comparison of these cells with melanoma-infiltrating CD8+ T cells revealed upregulated cytokine, cytolytic, and metabolic transcriptional activity in the psoriatic cells that differed from an exhaustion program. Our findings provide a high-resolution view of cutaneous CD8+ T cells in psoriasis and healthy skin and shed light on their functional distinctions within the chronic pathologies of autoimmunity and cancer.

ORGANISM(S): Homo sapiens

PROVIDER: GSE146264 | GEO | 2021/01/05

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Background: Plaque psoriasis is a chronic autoimmune disorder characterized by the development of red scaly plaques. To date psoriasis lesional skin transcriptome has been extensively studied, whereas only few proteomic studies of psoriatic skin are available. Aim: The aim of this study was to compare protein expression patterns of lesional and normally looking skin of psoriasis patients with skin of the healthy volunteers, reveal differentially expressed proteins and identify changes in cell metabolism caused by the disease. Methods: Skin samples of normally looking and lesional skin donated by psoriasis patients (n = 5) and samples of healthy skin donated by volunteers (n = 5) were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). After protein identification and data processing, the set of differentially expressed proteins was subjected to protein ontology analysis to characterize changes in biological processes, cell components and molecular functions in the patients' skin compared to skin of the healthy volunteers. Results: The performed analysis identified 405 and 59 differentially expressed proteins in lesional and normally looking psoriatic skin compared to healthy control. We discovered decreased expression of KNG1, APOE, HRG, THBS1 and PLG in normally looking skin of the patients. Presumably, these changes were needed to protect the epidermis from spontaneous activation of kallikrein-kinin system and delay the following development of inflammatory response. In lesional skin, we identified several large groups of proteins with coordinated expression. Mainly, these proteins were involved in different aspects of protein and RNA metabolism, namely ATP synthesis and consumption; intracellular trafficking of membrane-bound vesicles, pre-RNA processing, translation, chaperoning and degradation in proteasomes/immunoproteasomes. Conclusion: Our findings explain the molecular basis of metabolic changes caused by disease in skin lesions, such as faster cell turnover and higher metabolic rate. They also indicate on downregulation of kallikrein-kinin system in normally looking skin of the patients that would be needed to delay exacerbation of the disease.

Project description:Background: Psoriasis is a T cell-mediated chronic autoimmune/inflammatory disease. While some patients experience disease limited to the skin (skin psoriasis), others develop joint involvement (psoriatic arthritis; PsA). In the absence of disease- and/or outcome-specific biomarkers, and as arthritis can precede skin manifestations, diagnostic and therapeutic delays are common and contribute to disease burden and damage accrual. Objective: Altered epigenetic marks, including DNA methylation, contribute to effector T cell phenotypes and altered cytokine expression in autoimmune/inflammatory diseases. This project aimed at the identification of disease-/outcome-specific DNA methylation signatures in CD8+ T cells from patients with psoriasis and PsA as compared to heathy controls. Method: Peripheral blood CD8+ T cells from 9 healthy controls, 10 psoriasis and 7 PsA patients were collected to analyze DNA methylation marks using Illumina Human Methylation EPIC BeadChips (>850,000 CpGs per sample). Bioinformatic analysis was performed using R (minfi, limma, ChAMP and DMRcate packages). Results: DNA methylation profiles in CD8+ T cells differentiate healthy controls from psoriasis patients (397 Differentially Methylated Positions (DMPs); 9 Differentially Methylated Regions (DMRs) when ≥CpGs per DMR were considered; 2 DMRs for ≥10 CpGs). Furthermore, patients with skin psoriasis can be discriminated from PsA patients (1861 DMPs, 20 DMRs (≥5 CpGs per region), 4 DMRs (≥10 CpGs per region)). Gene ontology (GO) analyses considering genes with ≥1 DMP in their promoter delivered methylation defects in skin psoriasis and PsA primarily affecting the BMP signaling pathway and endopeptidase regulator activity, respectively. GO analysis of genes associated with DMRs between skin psoriasis and PsA demonstrated an enrichment of GABAergic neuron and cortex neuron development pathways. Treatment with cytokine blockers associated with DNA methylation changes (2372 DMPs; 1907 DMPs within promoters, 7 DMRs (≥5CpG per regions)) affecting transforming growth factor beta receptor and transmembrane receptor protein serine/threonine kinase signaling pathways. Lastly, a methylation score including TNF and IL-17 pathway associated DMPs inverse correlates with skin disease activity scores (PASI). Conclusion: Patients with skin psoriasis exhibit DNA methylation patterns in CD8+ T cells that allow differentiation from PsA patients and healthy individuals, and reflect clinical activity of skin disease. Thus, DNA methylation profiling promises potential as diagnostic and prognostic tool to be used for molecular patient stratification towards individualized treatment. This project aimed at the identification of disease-/outcome-specific DNA methylation signatures in CD8+ T cells from patients with psoriasis and PsA as compared to heathy controls.

Dataset Information

Single cell RNA-seq of psoriatic skin identifies pathogenic Tc17 subsets and reveals distinctions between CD8+ T cells in autoimmunity and cancer

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure