Abstract
Psoriasis is a multifactorial inflammatory skin disease characterized by increased proliferation of keratinocytes, activation of immune cells and susceptibility to metabolic syndrome. Systems biology approach makes it possible to reveal novel important factors in the pathogenesis of the disease. Protein-protein, protein-DNA, merged (containing both protein-protein and protein-DNA interactions) and chemical-protein interaction networks were constructed consisting of differentially expressed genes (DEG) between lesional and non-lesional skin samples of psoriatic patients and/or the encoded proteins. DEGs were determined by microarray meta-analysis using MetaOMICS package. We used STRING for protein-protein, CisRED for protein-DNA and STITCH for chemical-protein interaction network construction. General network-, cluster- and motif-analysis were carried out in each network. Many DEG-coded proteins (CCNA2, FYN, PIK3R1, CTGF, F3) and transcription factors (AR, TFDP1, MEF2A, MECOM) were identified as central nodes, suggesting their potential role in psoriasis pathogenesis. CCNA2, TFDP1 and MECOM might play role in the hyperproliferation of keratinocytes, whereas FYN may be involved in the disturbed immunity in psoriasis. AR can be an important link between inflammation and insulin resistance, while MEF2A has role in insulin signaling. A controller sub-network was constructed from interlinked positive feedback loops that with the capability to maintain psoriatic lesional phenotype. Analysis of chemical-protein interaction networks detected 34 drugs with previously confirmed disease-modifying effects, 23 drugs with some experimental evidences, and 21 drugs with case reports suggesting their positive or negative effects. In addition, 99 unpublished drug candidates were also found, that might serve future treatments for psoriasis.
Highlights
Psoriasis is a multifactorial inflammatory skin disease
The study by Johnson-Huang et al was already excluded after sample quality analysis with arrayQualityMetrics package, because at least two samples from one phenotype group are needed for MetaQC analysis and only one non-lesional sample remained after sample filtering
The software calculated six quality control (QC) measures created principal component analysis (PCA) biplot and standardized mean rank summary (SMR) score to help in the identification of problematic studies
Summary
Psoriasis is a multifactorial inflammatory skin disease. A recent systematic review reported a prevalence from 0% (Taiwan) to 2.1% (Italy) in children and from 0.91% (United States) to 8.5% (Norway) in adults.[1]. Several genomewide association studies have been carried out and until now 36 susceptibility loci have been identified.[2] Environmental triggers are reported such as drugs, smoking, mental stress, skin injury, Streptococcal infection, hormonal changes etc.[3] Psoriasis is an immune-mediated disease. Important immune cells and cytokines have been identified in disease pathogenesis such as IL6, IL17A, TNF etc.[4] Autoimmune basis for chronic inflammation is supposed, no consistent antigen has been found. Patients with psoriasis have higher risk for metabolic syndrome, and risk increases with disease severity. Both diseases have immunological basis with common cytokines and genetic risk loci like CDKAL1.[5] Keratinocyte hyperproliferation is present in lesional phenotype and is responsible for scale formation. Keratinocyte differentiation markers like keratin 1 and keratin 10 are downregulated and parakeratosis (keratinocytes with nuclei in the stratum granulosum) is present.[3]
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