RNA-sequencing of mouse Lang+ and Lang- migratory dendritic cells (DC) under 2 pathogenic conditions of atopic dermatitis
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ABSTRACT: Comparison of mouse Lang+ and Lang- migratory dendritic cells (DC) under 2 pathogenic conditions of atopic dermatitis (MC903-treated and OVA treated)
Project description:Although several mouse models of exogenous-agent–induced atopic dermatitis (AD) are currently available, the lack of certainty regarding their similarity with human AD has limited their scientific value. Thus, comprehensive evaluation of the characteristics of mouse models and their similarity with human AD is essential. The DNFB plus OVA model showed the highest disease severity, while the OVA model showed the lowest severity. The MC903 and MC903 plus OVA models showed high expression of T-helper(Th)2- and Th17-related genes; the DNFB and DNFB plus OVA models showed upregulation of Th1-, Th2-, and Th17-related genes; while the S. aureus inoculation model showed more enhanced Th1 and Th17 immune responses. In contrast to the other models, the OVA-induced model showed the lowest expression levels of inflammation-related genes, while the MC903 model shared the largest overlap with human AD profiles. Each AD mouse model exhibited different characteristics. The MC903 model was the best to recapitulate most features of human AD among these exogenous-agent–induced AD models.
Project description:Atopic dermatitis was induced on dorsal skin of 7-10 week-old C57BL/6 female mice by bi- or tri-daily MC903 treatment. On day 8, viable mouse eosinophils (CD45+F4/80+SiglecF+) were sorted from skin regions of healthy or vehicle/treated atopic dermatitis or femur/tibia-derived bone marrow by FACS. Samples were paired within individual mice (4 mice each). RNA from 500 cells were isolated and profile for transcriptome by sequencing.
Project description:mRNA array analysis of total RNA from primary kertinocytes from three healthy controls, three atopic dermatitis patients and three psoriasis patients was carried out
Project description:Clinical overlaps between psoriasis and atopic dermatitis are sometimes undiscernible, and there is no consensus whether to treat the overlap phenotype as psoriasis or atopic dermatitis. We enrolled patients diagnosed with either psoriasis or atopic dermatitis, and clinically re-stratified them into classic psoriasis, classic atopic dermatitis, and the overlap phenotype between psoriasis and atopic dermatitis. We compared gene expression profiles of lesional and nonlesional skin biopsy tissues between the three comparison groups. Global mRNA expression and T-cell subset cytokine expression in the skin of the overlap phenotype were consistent with the profiles of psoriasis and different from the profiles of atopic dermatitis. Unsupervised k-means clustering indicated that the best number of distinct clusters for the total population of the three comparison groups was two, and the two clusters of psoriasis and atopic dermatitis were differentiated by gene expression. Our study suggests that clinical overlap phenotype between psoriasis and atopic dermatitis has dominant molecular features of psoriasis, and genomic biomarkers can differentiate psoriasis and atopic dermatitis at molecular levels in patients with a spectrum of psoriasis and atopic dermatitis.
Project description:To identify the molecular mechanisms responsible for enhanced atopic dermatitis (AD) pathogenesis upon Ets1 deficiency in CD4+ T cells, we compared transcriptome profile between CD4+ T cells from littermate control (LMC) and Ets1ΔdLck mice at the peak of AD progression by performing RNA-seq.
Project description:Characteization host-microbiome interactions in patients with allergic (model: atopic dermatitis) and autoimmune (model: psoriasis) diseases by integration of microarray transcriptome data with 16S microbial profiling. 6mm punch biopsies were collected from the skin of atopic dermatitis and psoriasis patients alongside healthy volunteers, and subjected to analysis using Affymetrix Human Gene ST 2.1 arrays.
Project description:Atopic dermatitis is increasing worldwide, correlating with air pollutions. Various organic components of pollutants activate transcription factor AhR (aryl-hydrocarbon receptor). We have established AhR-CA mice, whose keratinocytes express constitutive-active AhR, and these mice developed atopic dermatitis-like frequent scratching and allergic inflammation. In this study we performed ChIP-seq analyses and identified keratinocyte-specific AhR target genes, including inflammatory cytokines Tslp and IL33, and neurotrophic factor Artemin. While AhR-CA mice exhibited epidermal hyperinnervation and alloknesis leading to hypersensitivity to pruritus, blockade of Artemin alleviated these phenotypes. AhR-CA mice showed scratching-induced barrier insufficiency and enhanced sensitization to epicutaneously-applied antigens, recapitulating human atopic dermatitis. Consistently, AhR activation and Artemin expression was detected in the epidermis of atopic dermatitis patients and keratinocytes exposed to air pollutants. Thus, AhR in keratinocytes senses the environmental stimuli and responds to them through moderating inflammation. We propose a mechanism in which air pollution induces atopic dermatitis through AhR activation.
Project description:Atopic dermatitis (AD) is the most prevalent chronic inflammatory skin disease in children characterized by dermatitis and pruritus. MicroRNAs (miRNAs) have been shown as great potential biomarkers for disease fingerprints to predict prognostics. We aimed to identify miRNA signature from serum and urine for the prognosis of AD patient by genome-wide miRNA profiling analysis. Serum from 8 children with AD and 8 healthy children were collected