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Multiple Transcriptome Data Analysis Reveals Biologically Relevant Atopic Dermatitis Signature Genes and Pathways.

ABSTRACT: Several studies have identified genes that are differentially expressed in atopic dermatitis (AD) compared to normal skin. However, there is also considerable variation in the list of differentially expressed genes (DEGs) reported by different groups and the exact cause of AD is still not fully understood. Using a rank-based approach, we analyzed gene expression data from five different microarray studies, comprising a total of 127 samples and more than 250,000 transcripts. A total of 89 AD gene expression signatures '89ADGES', including FLG gene, were identified to show dysregulation consistently across these studies. Using a Support Vector Machine, we showed that the '89ADGES' discriminates AD from normal skin with 98% predictive accuracy. Functional annotation of these genes implicated their roles in immune responses (e.g., betadefensin, microseminoprotein), keratinocyte differentiation/epidermal development (e.g., FLG, CORIN, AQP, LOR, KRT16), inflammation (e.g., IL37, IL27RA, CCL18) and lipid metabolism (e.g., AKR1B10, FAD7, FAR2). Subsequently, we validated a subset of signature genes using quantitative PCR in a mouse model. Using a bioinformatic approach, we identified keratinocyte pathway over-represented (P = <0.0006) among the 89 signature genes. Keratinocytes are known to play a major role in barrier function due to their location in the epidermis. Our result suggests that besides immune- mediated pathway, skin barrier pathways such as the keratinocyte differentiation pathway play a key role in AD pathogenesis. A better understanding of the role of keratinocytes in AD will be important for developing novel "barrier therapy" for this disease.

SUBMITTER: Ghosh D

PROVIDER: S-EPMC4696650 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Multiple Transcriptome Data Analysis Reveals Biologically Relevant Atopic Dermatitis Signature Genes and Pathways.

Ghosh Debajyoti D Ding Lili L Sivaprasad Umasundari U Geh Esmond E Biagini Myers Jocelyn J Bernstein Jonathan A JA Khurana Hershey Gurjit K GK Mersha Tesfaye B TB

PloS one 20151230 12

Several studies have identified genes that are differentially expressed in atopic dermatitis (AD) compared to normal skin. However, there is also considerable variation in the list of differentially expressed genes (DEGs) reported by different groups and the exact cause of AD is still not fully understood. Using a rank-based approach, we analyzed gene expression data from five different microarray studies, comprising a total of 127 samples and more than 250,000 transcripts. A total of 89 AD gene ...[more]

PMID: 26717000

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Project description:BACKGROUND: DNA microarray technology has had a great impact on muscle research and microarray gene expression data has been widely used to identify gene signatures characteristic of the studied conditions. With the rapid accumulation of muscle microarray data, it is of great interest to understand how to compare and combine data across multiple studies. Meta-analysis of transcriptome data is a valuable method to achieve it. It enables to highlight conserved gene signatures between multiple independent studies. However, using it is made difficult by the diversity of the available data: different microarray platforms, different gene nomenclature, different species studied, etc. DESCRIPTION: We have developed a system tool dedicated to muscle transcriptome data. This system comprises a collection of microarray data as well as a query tool. This latter allows the user to extract similar clusters of co-expressed genes from the database, using an input gene list. Common and relevant gene signatures can thus be searched more easily. The dedicated database consists in a large compendium of public data (more than 500 data sets) related to muscle (skeletal and heart). These studies included seven different animal species from invertebrates (Drosophila melanogaster, Caenorhabditis elegans) and vertebrates (Homo sapiens, Mus musculus, Rattus norvegicus, Canis familiaris, Gallus gallus). After a renormalization step, clusters of co-expressed genes were identified in each dataset. The lists of co-expressed genes were annotated using a unified re-annotation procedure. These gene lists were compared to find significant overlaps between studies. CONCLUSIONS: Applied to this large compendium of data sets, meta-analyses demonstrated that conserved patterns between species could be identified. Focusing on a specific pathology (Duchenne Muscular Dystrophy) we validated results across independent studies and revealed robust biomarkers and new pathways of interest. The meta-analyses performed with MADMuscle show the usefulness of this approach. Our method can be applied to all public transcriptome data.

Project description:ImportanceDisease models for atopic dermatitis (AD) have primarily focused on understanding underlying environmental, immunologic, and genetic etiologies. However, the role of metabolic mechanisms in AD remains understudied.ObjectiveTo investigate the circulating blood metabolomic and cytokine profile of AD as compared to healthy control patients.DesignThis study collected plasma from 20 atopic dermatitis with moderate-to-severe itch (score of ≥5 on the itch Numeric Rating Scale and IGA score ≥3) and 24 healthy control patients. Mass-spectrometry based metabolite data were compared between AD and healthy controls. Unsupervised and supervised machine learning algorithms and univariate analysis analyzed metabolic concentrations. Metabolite enrichment and pathway analyses were performed on metabolites with significant fold change between AD and healthy control patients. To investigate the correlation between metabolites levels and cytokines, Spearman's rank correlation coefficients were calculated between metabolites and cytokines.SettingPatients were recruited from the Johns Hopkins Itch Center and dermatology outpatient clinics in the Johns Hopkins Outpatient Center.ParticipantsThe study included 20 atopic dermatitis patients and 24 healthy control patients.Main outcomes and measuresFold changes of metabolites in AD vs healthy control plasma.ResultsIn patients with AD, amino acids isoleucine, tyrosine, threonine, tryptophan, valine, methionine, and phenylalanine, the amino acid derivatives creatinine, indole-3-acrylic acid, acetyl-L-carnitine, L-carnitine, 2-hydroxycinnamic acid, N-acetylaspartic acid, and the fatty amide oleamide had greater than 2-fold decrease (all P-values<0.0001) compared to healthy controls. Enriched metabolites were involved in branched-chain amino acid (valine, leucine, and isoleucine) degradation, catecholamine biosynthesis, thyroid hormone synthesis, threonine metabolism, and branched and long-chain fatty acid metabolism. Dysregulated metabolites in AD were positively correlated cytokines TARC and MCP-4 and negatively correlated with IL-1a and CCL20.Conclusions and relevanceOur study characterized novel dysregulated circulating plasma metabolites and metabolic pathways that may be involved in the pathogenesis of AD. These metabolic pathways serve as potential future biomarkers and therapeutic targets in the treatment of AD.

Project description:BackgroundEczema vaccinatum (EV), a disseminated viral skin infection, is a life-threatening complication of vaccinia virus (VV) inoculation in patients with atopic dermatitis (AD) and is thought to be associated with a defective innate immune response. However, the precise mechanism or mechanisms and key factor or factors of EV are unknown.ObjectiveGiven that patients with psoriasis, another inflammatory skin disorder, are not susceptible to EV, we compared the global transcriptional response of skin to VV in healthy subjects, patients with psoriasis, and patients with AD, focusing on AD-specific genes. We hypothesized that differences in the transcriptional response to VV between patients with AD and patients with psoriasis or healthy subjects would identify a defective pathway or pathways that might be associated with the development of EV.MethodsGene expression profiling of sham-treated and VV-treated unaffected skin explants from patients with AD (n = 12), patients with psoriasis (n = 12), or healthy subjects (n = 13) were generated with U133_Plus2 (54,613 probe sets) GeneChips and analyzed with the GCOS_1.4/SAM_2.1/MAPPFinder_2.0 pipeline.ResultsSixty-seven genes were significantly affected by VV in AD skin but not in psoriatic and healthy skin. Genes associated with defense response, response to wounding, and immune response were the most affected by VV in AD skin. All genes in these ontologies were downregulated, including the innate immunity genes leukotriene B(4) receptor (LTB4R), orosomucoid 1 (ORM1), coagulation factor II (thrombin) receptor (F2R), complement component 9 (C9), and LPS-binding protein (LBP). These findings were confirmed by means of real-time PCR and validated by means of PubMatrix analysis. ORM1, Toll-like receptor 4 (TLR4), and NLR family pyrin domain containing 1 (NLRP1) genes were also linked to AD severity.ConclusionThis study identified groups of innate immunity genes that are associated with the aberrant response of AD skin to VV and represent potential targets for EV pathogenesis.

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Multiple Transcriptome Data Analysis Reveals Biologically Relevant Atopic Dermatitis Signature Genes and Pathways.

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Multiple Transcriptome Data Analysis Reveals Biologically Relevant Atopic Dermatitis Signature Genes and Pathways.

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