INTEGRATIVE TRANSCRIPTOME DATA ANALYSIS REVEALS PSORIASIS SIGNATURE GENES AND ITS POTENTIAL ROLE IN DRUG REPURPOSING

Abstract

Expression profiling of gene transcripts had been applied in biomedical researches successfully for over a decade. Psoriasis being a chronic inflammatory skin disorder have complex pathological features and unmet pharmacological demands. Therefore, a number of research studies have identified the genes which are differentially expressed in psoriasis skin as compared to the control or normal skin. Although, there is a considerable variance in the differentially expressed gene (DEG) list as reported by several research groups and the precise cause of psoriasis occurrence is still not understood entirely. In this study, the gene expression data from three different microarray studies, consisting of 117 samples in total and more than 1,35,000 transcripts, was analysed with the help of a ranking based approach. Subsequently, the 66 psoriatic gene expression signatures identified in total, were consistently showing dysregulation across the three studies. Furthermore, functional annotation of the identified genes implicated their role in skin development, epidermal development, keratinocyte differentiation, inflammation, immune response, and antimicrobial humoral response. By using a bioinformatics approach, skin development and keratinocyte differentiation pathway were identified as most over represented pathways among 66 signature genes. The main role of keratinocytes is in barrier function due to their presence in the epidermis. An enhanced understanding of keratinocytes function in psoriasis will prove to be important in developing novel barrier therapies for the disease. Finally, a framework is presented which identifies potential drug repositioning opportunities utilising a systemic data-driven approach which helps to discover association amongst genes, diseases and drugs. Such mechanisms facilitated potential drug repurposing for psoriasis by identifying and suggesting new indications of existing drugs.