Finding Gene Regulatory Networks in Psoriasis: Application of a Tree-Based Machine Learning Approach

Identification and verification of three autophagy-related genes as potential biomarkers for the diagnosis of psoriasis

Psoriasis vulgaris is the most common form of the four clinical types. However, early diagnosis of psoriasis vulgaris is difficult due to the lack of effective biomarkers. The aim of this study was to screen potential biomarkers for the diagnosis of psoriasis. In our study, we downloaded the original data from GSE30999 and GSE41664, and the autophagy-related genes list from human autophagy database to identify differentially expressed autophagy-related genes (DERAGs) by R software. Then Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for DERAGs. DERAGs were validated by the other four databases (GSE13355, GSE14905, GSE6710, and GSE55201) to screen biomarkers with high diagnostic value for the early diagnosis of psoriasis vulgaris. Finally, DERAGs were verified in our clinical blood samples by ELISA. A total of 12 DERAGs were identified between 123 paired non-lesional and lesional skin samples from patients with psoriasis vulgaris. GO and KEGG enrichment analysis indicated the TORC2 complex was more enriched and the NOD-like receptor signaling pathway was mostly enriched. Three autophagy-related genes (BIRC5, NAMPT and BCL2) were identified through bioinformatics analysis and verified by ELISA in clinical blood samples. And these genes showed high diagnostic value for the early diagnosis of psoriasis vulgaris. We identified three autophagy-related genes (BIRC5, NAMPT and BCL2) with high diagnostic value for the early diagnosis of psoriasis vulgaris through bioinformatics analysis and clinical samples. Therefore, we proposed that BIRC5, NAMPT and BCL2 may be as potential biomarkers for the early diagnosis of psoriasis vulgaris. In addition, BIRC5, NAMPT and BCL2 may affect the development of psoriasis by regulating autophagy.

Sericin coated thin polymeric films reduce keratinocyte proliferation via the mTOR pathway and epidermal inflammation through IL17 signaling in psoriasis rat model

Therapeutic treatment forms can play significant roles in resolving psoriatic plaques or promoting wound repair in psoriatic skin. Considering the biocompatibility, mechanical strength, flexibility, and adhesive properties of silk fibroin sheets/films, it is useful to combine them with anti-psoriatic agents and healing stimulants, notably silk sericin. Here, we evaluate the curative properties of sericin-coated thin polymeric films (ScF) fabricated from silk fibroin, using an imiquimod-induced psoriasis rat model. The film biocompatibility and psoriatic wound improvement capacity was assessed. A proteomics study was performed to understand the disease resolving mechanisms. Skin-implantation study exhibited the non-irritation property of ScF films, which alleviate eczema histopathology. Immunohistochemical and gene expression revealed the depletion of β-defensin, caspase-3 and -9, TNF-α, CCL-20, IL-1β, IL-17, TGF-β, and Wnt expressions and S100a14 mRNA level. The proteomics study suggested that ScF diminish keratinocyte proliferation via the mTOR pathway by downregulating mTOR protein, corresponding to the modulation of TNF-α, Wnt, and IL-1β levels, leading to the enhancement of anti-inflammatory environment by IL-17 downregulation. Hematology data demonstrated the safety of using these biomaterials, which provide a potential therapeutic-option for psoriasis treatment due to desirable effects, especially anti-proliferation and anti-inflammation, functioning via the mTOR pathway and control of IL-17 signaling.

Construction of a three commitment points for S phase entry cell cycle model and immune-related ceRNA network to explore novel therapeutic options for psoriasis

While competing endogenous RNAs (ceRNAs) play pivotal roles in various diseases, the proliferation and differentiation of keratinocytes are becoming a research focus in psoriasis. Therefore, the three commitment points for S phase entry (CP1-3) cell cycle model has pointed to a new research direction in these areas. However, it is unclear what role ceRNA regulatory mechanisms play in the interaction between keratinocytes and the immune system in psoriasis. In addition, the ceRNA network-based screening of potential therapeutic agents for psoriasis has not been explored. Therefore, we used multiple bioinformatics approaches to construct a ceRNA network for psoriasis, identified CTGF as the hub gene, and constructed a ceRNA subnetwork, after which validation datasets authenticated the results' accuracy. Subsequently, we used multiple online databases and the single-sample gene-set enrichment analysis algorithm, including the CP1-3 cell cycle model, to explore the mechanisms accounting for the increased proliferation and differentiation of keratinocytes and the possible roles of the ceRNA subnetwork in psoriasis. Next, we performed cell cycle and cell trajectory analyses based on a single-cell RNA-seq dataset of psoriatic skin biopsies. We also used weighted gene co-expression network analysis and single-gene batch correlation analysis-based gene set enrichment analysis to explore the functions of CTGF. Finally, we used the Connectivity Map to identify MS-275 (entinostat) as a novel treatment for psoriasis, SwissTargetPrediction to predict drug targets, and molecular docking to investigate the minimum binding energy and binding sites of the drug to target proteins.