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

Abstract

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.

Keywords: Gene expression; Long non-coding RNA (lncRNA); Psoriasis; RNA-seq; Weighted gene coexpression network analysis (WGCNA).

Fig. 1

WGCNA identifies genes associated with psoriasis a and biologic treatment b not identified by DE. Venn diagram of genes identified by WGCNA or DE that are associated with psoriasis in PPvNN a or with biologic treatment in PPvPT b. Values in parantheses are the count of coding genes to lncRNAs

Fig. 2

Intramodular analysis reveals hub genes in the top correlated module in PPvNN. Graphical illustration of intramodular analysis starting with identification of the most correlated modules and plotting MM against GS for the top correlated modules a. After hub genes are identified, a network plot of these genes is produced b. In this case, the network plot is of the hub genes of the PPvNN blue module. The relative size of each hub indicates the degree of connectivity (number of edges) for each gene