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Network analysis of psoriasis reveals biological pathways and roles for coding and long non-coding RNAs

BACKGROUND: Psoriasis is an immune-mediated, inflammatory disorder of the skin characterized by chronic inflammation and hyperproliferation of the epidermis. Differential expression analysis of microarray or RNA-seq data have shown that thousands of coding and non-coding genes are differentially exp...

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Autores principales: Ahn, Richard, Gupta, Rashmi, Lai, Kevin, Chopra, Nitin, Arron, Sarah T., Liao, Wilson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5084355/
https://www.ncbi.nlm.nih.gov/pubmed/27793094
http://dx.doi.org/10.1186/s12864-016-3188-y
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author Ahn, Richard
Gupta, Rashmi
Lai, Kevin
Chopra, Nitin
Arron, Sarah T.
Liao, Wilson
author_facet Ahn, Richard
Gupta, Rashmi
Lai, Kevin
Chopra, Nitin
Arron, Sarah T.
Liao, Wilson
author_sort Ahn, Richard
collection PubMed
description BACKGROUND: Psoriasis is an immune-mediated, inflammatory disorder of the skin characterized by chronic inflammation and hyperproliferation of the epidermis. Differential expression analysis of microarray or RNA-seq data have shown that thousands of coding and non-coding genes are differentially expressed between psoriatic and healthy control skin. However, differential expression analysis may fail to detect perturbations in gene coexpression networks. Sensitive detection of such networks may provide additional insight into important disease-associated pathways. In this study, we applied weighted gene coexpression network analysis (WGCNA) on RNA-seq data from psoriasis patients and healthy controls. RESULTS: RNA-seq was performed on skin samples from 18 psoriasis patients (pre-treatment and post-treatment with the TNF-α inhibitor adalimumab) and 16 healthy controls, generating an average of 52.3 million 100-bp paired-end reads per sample. Using WGCNA, we identified 3 network modules that were significantly correlated with psoriasis and 6 network modules significantly correlated with biologic treatment, with only 16 % of the psoriasis-associated and 5 % of the treatment-associated coexpressed genes being identified by differential expression analysis. In a majority of these correlated modules, more than 50 % of coexpressed genes were long non-coding RNAs (lncRNA). Enrichment analysis of these correlated modules revealed that short-chain fatty acid metabolism and olfactory signaling are amongst the top pathways enriched for in modules associated with psoriasis, while regulation of leukocyte mediated cytotoxicity and regulation of cell killing are amongst the top pathways enriched for in modules associated with biologic treatment. A putative autoantigen, LL37, was coexpressed in the module most correlated with psoriasis. CONCLUSIONS: This study has identified several networks of coding and non-coding genes associated with psoriasis and biologic drug treatment, including networks enriched for short-chain fatty acid metabolism and olfactory receptor activity, pathways that were not previously identified through differential expression analysis and may be dysregulated in psoriatic skin. As these networks are comprised mostly of non-coding genes, it is likely that non-coding genes play critical roles in the regulation of pathways involved in the pathogenesis of psoriasis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3188-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-50843552016-10-31 Network analysis of psoriasis reveals biological pathways and roles for coding and long non-coding RNAs Ahn, Richard Gupta, Rashmi Lai, Kevin Chopra, Nitin Arron, Sarah T. Liao, Wilson BMC Genomics Research Article BACKGROUND: Psoriasis is an immune-mediated, inflammatory disorder of the skin characterized by chronic inflammation and hyperproliferation of the epidermis. Differential expression analysis of microarray or RNA-seq data have shown that thousands of coding and non-coding genes are differentially expressed between psoriatic and healthy control skin. However, differential expression analysis may fail to detect perturbations in gene coexpression networks. Sensitive detection of such networks may provide additional insight into important disease-associated pathways. In this study, we applied weighted gene coexpression network analysis (WGCNA) on RNA-seq data from psoriasis patients and healthy controls. RESULTS: RNA-seq was performed on skin samples from 18 psoriasis patients (pre-treatment and post-treatment with the TNF-α inhibitor adalimumab) and 16 healthy controls, generating an average of 52.3 million 100-bp paired-end reads per sample. Using WGCNA, we identified 3 network modules that were significantly correlated with psoriasis and 6 network modules significantly correlated with biologic treatment, with only 16 % of the psoriasis-associated and 5 % of the treatment-associated coexpressed genes being identified by differential expression analysis. In a majority of these correlated modules, more than 50 % of coexpressed genes were long non-coding RNAs (lncRNA). Enrichment analysis of these correlated modules revealed that short-chain fatty acid metabolism and olfactory signaling are amongst the top pathways enriched for in modules associated with psoriasis, while regulation of leukocyte mediated cytotoxicity and regulation of cell killing are amongst the top pathways enriched for in modules associated with biologic treatment. A putative autoantigen, LL37, was coexpressed in the module most correlated with psoriasis. CONCLUSIONS: This study has identified several networks of coding and non-coding genes associated with psoriasis and biologic drug treatment, including networks enriched for short-chain fatty acid metabolism and olfactory receptor activity, pathways that were not previously identified through differential expression analysis and may be dysregulated in psoriatic skin. As these networks are comprised mostly of non-coding genes, it is likely that non-coding genes play critical roles in the regulation of pathways involved in the pathogenesis of psoriasis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3188-y) contains supplementary material, which is available to authorized users. BioMed Central 2016-10-28 /pmc/articles/PMC5084355/ /pubmed/27793094 http://dx.doi.org/10.1186/s12864-016-3188-y Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Ahn, Richard
Gupta, Rashmi
Lai, Kevin
Chopra, Nitin
Arron, Sarah T.
Liao, Wilson
Network analysis of psoriasis reveals biological pathways and roles for coding and long non-coding RNAs
title Network analysis of psoriasis reveals biological pathways and roles for coding and long non-coding RNAs
title_full Network analysis of psoriasis reveals biological pathways and roles for coding and long non-coding RNAs
title_fullStr Network analysis of psoriasis reveals biological pathways and roles for coding and long non-coding RNAs
title_full_unstemmed Network analysis of psoriasis reveals biological pathways and roles for coding and long non-coding RNAs
title_short Network analysis of psoriasis reveals biological pathways and roles for coding and long non-coding RNAs
title_sort network analysis of psoriasis reveals biological pathways and roles for coding and long non-coding rnas
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5084355/
https://www.ncbi.nlm.nih.gov/pubmed/27793094
http://dx.doi.org/10.1186/s12864-016-3188-y
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