507 Comparative analysis of inflammatory skin diseases reveals shared and distinct gene signature profiles in lesional and nonlesional regions

Abstract

Although different inflammatory skin diseases are characterized by unique clinical features, current understanding regarding the comparative molecular features is limited. Moreover, the gene expression profiles of nonlesional uninvolved skin have not been fully delineated. To determine how the molecular profiles of inflammatory skin diseases are unique or similar between conditions, we carried out a comprehensive analysis of gene expression from cutaneous lupus erythematosus (CLE), psoriasis, atopic dermatitis, and systemic sclerosis. Gene set variation analysis (GSVA), revealed that, compared to healthy control samples, lesional samples from each condition had distinct features, but all four diseases displayed common enrichment in many inflammatory signatures, including the type 1 interferon, tumor necrosis factor, and IL-23 gene signatures. Nonlesional samples also differed from healthy control samples as well as each disease compared to the other using GSVA. Indeed, nonlesional samples proved to be more discriminatory for the specific inflammatory condition than their lesional counterparts as determined by comprehensive analyses consisting of GSVA, classification and regression tree (CART) analysis, and machine learning (ML) models. Altogether, our results suggest a model of skin pathogenesis in which patients exhibit disease-specific abnormalities in their “pre-lesional” skin; however, upon initiation of clinically apparent disease, dermal inflammatory responses may lead to similar and unique inflammatory molecular manifestations among diseases. Dissection of key inflammatory pathways enriched in both clinically involved and uninvolved skin can advance the understanding of the pathogenesis of these conditions and identify novel therapies.