Discovering Novel Biomarkers Associated with the Pathogenesis of Psoriasis: Evidence from Bioinformatic Analysis

Ursolic Acid Formulations Effectively Induce Apoptosis and Limit Inflammation in the Psoriasis Models In Vitro

Psoriasis, a prevalent inflammatory skin disorder affecting a significant percentage of the global population, poses challenges in its management, necessitating the exploration of novel cost-effective and widely accessible therapeutic options. This study investigates the potential of ursolic acid (UA), a triterpenoid known for its anti-inflammatory and pro-apoptotic properties, in addressing psoriasis-related inflammation and keratinocyte hyperproliferation. The research involved in vitro models employing skin and immune cells to assess the effects of UA on psoriasis-associated inflammation. The presented research demonstrates the limiting effects of UA on IL-6 and IL-8 production in response to the inflammatory stimuli and limiting effects on the expression of psoriatic biomarkers S100A7, S100A8, and S100A9. Further, the study reveals promising outcomes, demonstrating UA's ability to mitigate inflammatory responses and hyperproliferation of keratinocytes by the induction of non-inflammatory apoptosis, as well as a lack of the negative influence on other cell types, including immune cells. Considering the limitations of UA's poor solubility, hybrid systems were designed to enhance its bioavailability and developed as hybrid nano-emulsion and bi-gel topical systems to enhance bioavailability and effectiveness of UA. One of them in particular-bi-gel-demonstrated high effectiveness in limiting the pathological response of keratinocytes to pro-psoriatic stimulation; this was even more prominent than with ursolic acid alone. Our results indicate that topical formulations of ursolic acid exhibit desirable anti-inflammatory activity in vitro and may be further employed for topical psoriasis treatment.

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.

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.

Towards Personalized Medicine in Psoriasis: Current Progress

Although innovative targeted therapies have positively revolutionized psoriasis treatment shifting treatment goals to complete or almost complete skin clearance, primary or secondary lack of efficacy is still possible. Hence, identifying robust biomarkers that reflect the various clinical psoriasis phenotypes would allow stratify patients in subgroups or endotypes, and tailor treatments according to the characteristics of each individual (precision medicine). To sum up the current progress in personalized medicine for psoriasis, we performed a review on the available evidence on biomarkers predictive of response to psoriasis treatments, with focus on phototherapy and systemic agents. Relevant literature published in English was searched for using the following databases from the last five years up to March 20, 2022: PubMed, Embase, Google Scholar, EBSCO, MEDLINE, and the Cochrane library. Currently, more evidence exists towards biologicals, as justified by the huge health care costs as compared to phototherapy or conventional systemic drugs. Among them, most of the studies focused on anti-TNF and IL12/23, with still few on IL17 (mainly secukinumab). The most discussed biomarker gene is the HLA-C*02:06 status that has been shown to be associated with psoriasis, and also differential response to biologicals. Although its positivity is associated with great response to MTX, debatable results were retrieved concerning both anti-TNF and IL12/23 while it seems not to affect secukinumab response. Personalized treatment in psoriasis would provide excellent outcome minimizing the risk of side effects. To date, although several candidates were proposed and assessed, the scarcity and heterogeneity of the results do not allow the identification of the gold-standard biomarker per each treatment. Anyway, the creation of a more comprehensive panel would be more reliable for the treatment decision process.