Skin transcriptome of non-communicable inflammatory skin diseases
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE154200 | GEO | 2024/06/20
REPOSITORIES: GEO
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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.
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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.
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