MicroRNA-sequencing Analysis of Plasma-derived Exosomes Provides Novel Insights into the Disease Mechanism of Childhood Atopic Dermatitis
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ABSTRACT: To investigate the expression pattern of exosomal miRNAs in pediatric atopic dermatitis patients, we performed miRNA-Seq of plasmal exosome from 5 patients and 5 healthy controls. We identify 40 differentially expressed exosomal miRNAs (DEPEMs) and found their target genes were involved in multiple functions and pathways associated with AD through GO and KEGG pathway analysis.
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
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. Urine from 3 children with AD and 3 healthy children were collected
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: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.
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.
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: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.