Vitiligo is the most common cause of skin, hair, and oral depigmentation which is known as an autoimmune disorder. Genetic and environmental factors have important roles in the progression of the disease. Dysregulation of gene expression, like microRNAs (miRNA), may serve as major relevant factors. Several biological processes are involved in vitiligo disease and developing a comprehensive approach helps us to better understand the molecular mechanisms of disease. In this research, we describe how a weighted gene co-expression network analysis as a systems biology approach assists to define the primary gene modules, hub genes, and messenger RNA (mRNA)-miRNA regulatory network in vitiligo disease as the novel biomarkers. The results demonstrated a module with a high correlation with vitiligo state. Moreover, gene enrichment analysis showed that this module's genes were mostly involved in some biological activities including G protein-coupled receptors signaling pathway, lymphocyte chemotaxis, chemokine activity, neutrophil migration, granulocyte chemotaxis, etc. The co-expression network was constructed using top hub genes of the correlated module which are named as CXCL10, ARL9, AKR1B10, COX7B, RPL26, SPA17, NDUFAF2, RPF2, DAPL1, RPL34, CWC15, NDUFB3, RPL26L1, ACOT13, HSPB11, and NSA2. MicroRNAs prediction tool (miRWalk) revealed top miRNAs correlated with the interested module. Finally, a drug-target network was constructed which indicated interactions of some food and drug administration (FDA) approved drugs with hub genes. Our findings specified one important module and main hub genes which can be considered as novel biomarkers for vitiligo therapeutic purposes.
Logic-based models in systems biology: a predictive and parameter-free network analysis method
