Identification of Differentially Expressed Genes between Lesional versus Non-lesional Skin Samples of Psoriasis Patients Using a Meta-analysis

• Activity Number: 528
• Type: Contributed
• Date/Time: Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistical Education
• Author(s): Suyan Tian*+ and Mayte Suárez-Fariñas
• Companies: The Rockefeller University and The Rockefeller University
• Keywords: Meta-analysis ; Microarray ; Psoriasis ; Differentially expressed genes

Abstract

Psoriasis is a common chronic inflammatory skin disease. Its causes are not fully understood even though a genetic component is believed as a must. Using microarray experiments, many researchers have been trying to identify genes associated with psoriasis pathology. This genomic phenotype of the disease can serve as a basis in many applications. However, it is commonly observed that the resulting set of differentially expressed genes (DEGs) greatly differs across experiments due to variations introduced at all stages of the microarray studies pipeline. Thus a statistically based meta-analytic approach, which combines the results of individual studies, is needed. Here, a random effect meta-analysis on 5 microarray data sets including 193 lesional and non-lesional pairs was conducted. Among 5395 genes used in the analysis, 677 (12.5%) were up-expressed and 443 (8.2%) were down-expressed. It represents a much larger set than the intersection of DEGs upon individual studies, which consisted of 78 and 22 down-regulated genes. In conclusion, meta-analysis would produce a pool of good candidates for revealing psoriasis pathology, and thus identify potential treatments.