  Background: Psoriasis is a multifactorial chronic inflammatory disorder of
the skin with significant morbidity, characterized by hyper proliferation of
the epidermis. Even though psoriasis etiology is not fully understood, it is
believed to be multifactorial with numerous key components. Methods: In order
to cast light on the complex molecular interactions in psoriasis vulgaris at
both protein-protein interactions and transcriptomics levels, we analyzed a set
of microarray gene expression analysis consisting of 170 paired lesional and
non-lesional samples. Afterwards, a network analysis was conducted on
protein-protein interaction network of differentially expressed genes based on
micro- and macro-level network metrics at a systemic level standpoint. Results:
We found 17 top communicative genes, all of which experimentally proven to be
pivotal in psoriasis were identified in two modules, namely, cell cycle and
immune system. Intra- and inter-gene interaction subnetworks from the top
communicative genes might provide further insight into the corresponding
characteristic mechanisms. Conclusions: Potential gene combinations for
therapeutic/diagnostics purposes were identified. Moreover, our proposed
pipeline could be of interest to a broader range of biological network analysis
studies.
