Deciphering psoriasis. A bioinformatic approach.

Area of Science:

• Genomics
• Bioinformatics
• Dermatology

Background:

• Psoriasis is an immune-mediated inflammatory disease affecting skin and joints.
• Characterized by keratinocyte hyperproliferation and immune cell infiltration.
• The precise cause and full genomic impact remain incompletely understood.

Purpose of the Study:

• To investigate the genomic alterations associated with psoriasis using data mining and bioinformatic scripting.
• To reveal a new dimension of psoriasis's effect at the genomic level.

Main Methods:

• Utilized a custom pipeline of Perl and MySql scripts.
• Analyzed data from the NCBI Gene Expression Omnibus (GEO) database, specifically DataSet Record GDS4602 (Series GSE13355).
• Explored gene expression changes in affected psoriatic tissues.

Main Results:

• Identified up-regulation of cell cycle genes (e.g., CCNB1, CCNA2, CDK1) and dynamin system genes (e.g., GBPs, MXs).
• Observed down-regulation of key antioxidant genes, including catalase (CAT) and superoxide dismutases (SOD1-3).
• Provided a comprehensive list of human genes and their altered expression in psoriasis.

Conclusions:

• Psoriasis affects gene expression across all chromosomes and impacts multiple biological functions.
• The inheritable nature of the psoriasis phenotype and environmental influences suggest an epigenetic origin.
• Findings align with the known hereditary and complex genetic background of psoriasis.