Project description:We identified zinc-alpha-2-glycoprotein (ZAG), a 41-kDa adipokine that regulates body weight, lipid, and mobilization, as a novel biomarker for AD. ZAG levels were consistently decreased in sera, T cells, and skin in human AD patients compared with healthy controls. We used microarrays to obtain the change of signaling molecules by topical treatment of recombinant ZAG using atopic dermatitis induced mouse model.
Project description:The study demonstrates the effects of dietary grape powder against atopic dermatitis in 2,4-dinitrofluorobenzene-induced atopic dermatitis in NC/NgaTndCrlj mice. To uncover molecular mechanism(s) of biological responses of grape powder, dorsal skin samples from normal control (noAD), atopic dermatitis control (ctlAD) and 5% grape powder (5GP) prevention groups were analyzed using gel-free quantitative global proteomics analysis at the School of Pharmacy Analytical Instrumentation Facility, University of Wisconsin–Madison. Briefly, sample proteins (20 micrograms) were digested with 1 microgram sequencing grade trypsin and analyzed by nano-LC/MS/MS. The data were searched against the Swiss-Prot mouse proteome database using the Sequest HT search engine in the Proteome Discoverer 1.4 software, and data were aligned using the ChromAlign algorithm. Quantitation of peptides was performed on processed data using SIEVE 2.1 (ThermoFisher Scientific).
Project description:Atopic dermatitis (AD) is a common pruritic dermatitis with macroscopically nonlesional skin that is often abnormal. Therefore, we used high-density oligonucleotide arrays to identify cutaneous gene transcription changes associated with early AD inflammation as potential disease control targets. Skin biopsy specimens analyzed included normal skin from five healthy nonatopic adults and both minimally lesional skin and nearby or contralateral nonlesional skin from six adult AD patients. Keywords: disease state analysis
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.
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: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:To gain a deeper understanding of the atopic dermatitis (AD) skin transcriptome and the effects of systemic treatment with dupilumab and cyclosporine, we conducted a gene expression study of AD using mRNA-Seq data generated from lesional and non-lesional skin biopsies collected from patients included in the TREATgermany registry. We are able to provide deep characterisation of AD skin transcriptomic signatures by using an assortment of bioinformatic approaches such as differential expression, co-expression network and pathway enrichment analysis.
Project description:We analyzed m6A modifications in skin lesions of patients with psoriasis or atopic dermatitis (AD). The results of this study will help to gain insight into the molecular basis of m6A modification in inflammatory skin diseases such as psoriasis or atopic dermatitis.