Psoriasis is a complex
autoimmune disease with multiple genes and
proteins being involved in its pathogenesis. Despite the efforts performed to understand mechanisms of
psoriasis pathogenesis and to identify diagnostic and prognostic targets, disease-specific and effective
biomarkers were still not available. This study is compiled regarding clinical validation of computationally proposed
biomarkers at gene and
protein expression levels through qRT-PCR and ELISA techniques using skin biopsies and blood plasma. We identified several gene and
protein clusters as systems
biomarkers and presented the importance of gender difference in
psoriasis. A gene cluster comprising of PI3, IRF9, IFIT1 and NMI were found as positively correlated and differentially co-expressed for women, whereas SUB1 gene was also included in this cluster for men. The differential expressions of IRF9 and NMI in women and SUB1 in men were validated at gene expression level via qRT-PCR. At
protein level, PI3 was abundance in disease states of both genders, whereas PC4
protein and WIF1
protein were significantly higher in healthy states than disease states of male group and female group, respectively. Regarding abundancy of PI3 and WIF1
proteins in women, and PI3 and PC4 in men may be assumed as systems
biomarkers at
protein level.