Decoding Psoriasis: Integrated Bioinformatics Approach to Understand Hub Genes and Involved Pathways

Area of Science:

• Dermatology
• Immunology
• Genomics

Background:

• Psoriasis is a chronic, immune-mediated skin disorder with significant global prevalence.
• The exact causes and disease mechanisms of psoriasis remain largely unknown.
• Psoriasis is associated with comorbidities and psychological distress, highlighting its systemic impact.

Purpose of the Study:

• To identify potential therapeutic targets for psoriasis.
• To gain a deeper understanding of the molecular pathways involved in psoriasis pathogenesis.
• To uncover novel differentially expressed genes (DEGs) and their roles in disease development.

Main Methods:

• Gene expression profiles (GSE13355, GSE14905) were retrieved from the Gene Expression Omnibus (GEO) database.
• Differentially expressed genes (DEGs) in lesional and non-lesional psoriasis skin were identified using R software.
• Pathway analysis (Kyoto Encyclopaedia of Genes and Genomes) and protein-protein interaction network construction (Cytoscape) were performed.

Main Results:

• A total of 1013 DEGs were identified in lesional psoriasis skin, with 557 upregulated and 456 downregulated.
• Seven DEGs were identified in non-lesional skin, and a disease gene network revealed 75 potentially novel DEGs.
• Top hub genes, including IL1B, STAT3, CCNB1, and CCNA2, were identified, with enriched pathways related to cytokine-cytokine receptor interactions and keratinocyte differentiation.

Conclusions:

• The identified hub genes and novel DEGs enhance understanding of psoriasis pathogenesis.
• The identified hub genes represent promising candidates for future therapeutic target exploration in psoriasis treatment.
• This research provides a foundation for developing targeted therapies for psoriasis based on its molecular underpinnings.