Dataset Information

Integrative Analysis of lncRNAs, miRNAs, and mRNA-Associated ceRNA Network in an Atopic Dermatitis Recurrence Model.

ABSTRACT: Atopic dermatitis (AD) is a prevalent inflammatory skin disease characterized by its chronic nature and relapse. Ample evidence suggests that non-coding RNAs play a major role in AD pathogenesis. However, the mechanism remains unknown, particularly in AD recurrence. Dynamic morphological and cytokine changes were measured throughout the whole course of an FITC-induced AD recurrence murine model. Microarray assay and integrative analysis were performed to comprehensively explore long non-coding RNA (lncRNA), messenger RNA (mRNA), and microRNA (miRNA) networks. Our results showed that an AD recurrence model was established. Overall, 5766 lncRNAs, 4025 mRNAs, and 202 miRNAs changed after elicitation, whereas, 419 lncRNAs, 349 mRNAs, and more notably, only 23 miRNAs, were dysregulated in the remission phase. Gene ontology (GO) and KEGG pathway enrichment analyses were used to investigate the potential functions of the dysregulated genes. The altered regulation of seven miRNAs and seven lncRNAs were validated in different stages of the model. The competing endogenous RNA (ceRNA) network inferred that lncRNA humanlincRNA0490+ could compete for miR-155-5p binding, through which it might affect Pki? expression. Altogether, our findings have provided a novel perspective on the potential roles of non-coding RNAs in AD, and suggest that specific non-coding RNAs could be new therapeutic targets against AD recurrence.

SUBMITTER: Wang X

PROVIDER: S-EPMC6214145 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Integrative Analysis of lncRNAs, miRNAs, and mRNA-Associated ceRNA Network in an Atopic Dermatitis Recurrence Model.

Wang Xiaoyu X Bao Kaifan K Wu Peng P Yu Xi X Wang Can C Ji Lv L Hong Min M

International journal of molecular sciences 20181020 10

Atopic dermatitis (AD) is a prevalent inflammatory skin disease characterized by its chronic nature and relapse. Ample evidence suggests that non-coding RNAs play a major role in AD pathogenesis. However, the mechanism remains unknown, particularly in AD recurrence. Dynamic morphological and cytokine changes were measured throughout the whole course of an FITC-induced AD recurrence murine model. Microarray assay and integrative analysis were performed to comprehensively explore long non-coding R ...[more]

PMID: 30347841

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Project description:BackgroundAtopic dermatitis (AD) is a prevalent chronic inflammatory skin disease whose pathophysiology involves the interplay between genetic and environmental factors, ultimately leading to dysfunction of the epidermis. While several treatments are effective in symptom management, many existing therapies offer only temporary relief and often come with side effects. For this reason, the formulation of an effective therapeutic plan is challenging and there is a need for more effective and targeted treatments that address the root causes of the condition. Here, we hypothesise that modelling the complexity of the molecular buildup of the atopic dermatitis can be a concrete means to drive drug discovery.MethodsWe preprocessed, harmonised and integrated publicly available transcriptomics datasets of lesional and non-lesional skin from AD patients. We inferred co-expression network models of both AD lesional and non-lesional skin and exploited their interactional properties by integrating them with a priori knowledge in order to extrapolate a robust AD disease module. Pharmacophore-based virtual screening was then utilised to build a tailored library of compounds potentially active for AD.ResultsIn this study, we identified a core disease module for AD, pinpointing known and unknown molecular determinants underlying the skin lesions. We identified skin- and immune-cell type signatures expressed by the disease module, and characterised the impaired cellular functions underlying the complex phenotype of atopic dermatitis. Therefore, by investigating the connectivity of genes belonging to the AD module, we prioritised novel putative biomarkers of the disease. Finally, we defined a tailored compound library by characterising the therapeutic potential of drugs targeting genes within the disease module to facilitate and tailor future drug discovery efforts towards novel pharmacological strategies for AD.ConclusionsOverall, our study reveals a core disease module providing unprecedented information about genetic, transcriptional and pharmacological relationships that foster drug discovery in atopic dermatitis.

Dataset Information

Integrative Analysis of lncRNAs, miRNAs, and mRNA-Associated ceRNA Network in an Atopic Dermatitis Recurrence Model.

Publications

Integrative Analysis of lncRNAs, miRNAs, and mRNA-Associated ceRNA Network in an Atopic Dermatitis Recurrence Model.

Similar Datasets

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