Finding specific Regulators of Inflammatory Skin Disease

Abstract

Psoriasis is one of the most common chronic inflammatory disorder, but still until now many of the underlying mechanisms remain unclear. In this study we analyse large-scale public high-throughput sequencing data by performing differential expression analysis, pathway enrichment and integrating a gene random forest and gene set enrichment analysis to create a regulatory network. To distinguish markers of common skin inflammation from disease specific ones, we further integrate data of the skin inflammatory disease Atopic Dermatitis. We find that common differential expressed genes across all datasets are involved in immune system pathways, similar to the common genes of both diseases. In addition the disease-unique genes also show up in pro-inflammatory pathways, showing that both diseases are activated by different mechanism. Moreover, we find that Psoriasis and Atopic Dermatitis share many regulators, but we are able to distinguish unique regulators such as PRDM1, STAT3 and NR4A3 and create a gene regulatory network. Further, cellular deconvolution shows keratinization and infiltration of immune cells dominated by Monocytes and CD4+ T-cells.