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:To investigate whether DDX5 is involved in the development of atopic dermatitis, we performed gene expression profiling analysis using data obtained from RNA-seq of ear skins from Ddx5f/f and K14Ddx5f/f atopic dermatitis mice
Project description:Purpose: provide evidence that RNA-seq can add information to transcriptome profiling already discovered by other technologies for atopic dermatitis Methods: mRNA profiles of 20 atopic dermatitis were analyzed to compare lesional and non-lesional skin, then transcriptomes found by reads were compared to Microarray and RT-PCR Results:RNA-seq provided complementary genes to AD transcriptome IL-36 and TREM-1 Conclusions: Our study represents the first analysis of lesional AD tissue by RNA-seq and comparison to microarray and RT-PCR
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: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: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:Purpose: To determine the transcriptional differences between lesional skin and nonlesional skin from patients with atopic dermatitis Methods: Skin biopsies of lesional and non-lesional sites on atopic dermatitis patients were obtained and stored in RNA Later. Ribosomal RNA was removed and cDNA was generated with the SMARTer kit (CloneTech) with 10 ng of total RNA per sample. Samples were sequenced to an average depth of 34 million 1x50 reads on a HiSeq3000 (Illumina). Reads were aligned to Ensembl release 76 using STAR, gene counts were determined with Subread:featureCount, and sequence performance was assessed with RSeQC.
