Associations between PTPN2 gene polymorphisms and psoriasis in Northeastern China

PTPN2 inhibits the proliferation of psoriatic keratinocytes by dephosphorylation of STAT3

Psoriasis is a recurrent and protracted disease that severely impacts the patient's physical and mental health. Thus, there is an urgent need to explore its pathogenesis to identify therapeutic targets. The expression level of protein tyrosine phosphatase nonreceptor type 2 (PTPN2) was analyzed by immunohistochemistry techniques in psoriatic tissues and imiquimod-induced psoriatic mouse models. PTPN2 and signal transducer and activator of transcription 3 (STAT3) were overexpressed or silenced in human keratinocytes or an interleukin (IL)-6-induced psoriasis HaCaT cell model using overexpression plasmid transfection or small interfering RNA technology in vitro, and the effects of PTPN2 on STAT3, HaCaT cell function, and autophagy levels were investigated using reverse transcription-quantitative polymerase chain reaction, Western blot, Cell Counting Kit 8, 5-ethynyl-20-deoxyuridine, flow cytometry, and transmission electron microscopy. PTPN2 expression was found to be significantly downregulated in psoriatic tissues. Then, the in vitro antipsoriatic properties of PTPN2 were investigated in an IL-6-induced psoriasis-like cell model, and the results demonstrated that inhibition of keratinocyte proliferation by PTPN2 may be associated with elevated STAT3 dephosphorylation and autophagy levels. These findings provide novel insights into the mechanisms of autophagy in psoriatic keratinocytes and may be essential for developing new therapeutic strategies to improve inflammatory homeostasis in psoriatic patients.

Psoriasis: An Immunogenetic Perspective

Psoriasis is an erythematous-squamous dermatosis with a polygenic inheritance history. Both environmental and genetic factors play a role in the etiology of the disease. Over the past two decades, numerous linkage analyzes and genome-wide association studies have been conducted to investigate the role of genetic variation in disease pathogenesis and progression. To date, >70 psoriasis susceptibility loci have been identified, including HLA-Cw6, IL12B, IL23R, and LCE3B/3C. Some genetic markers are used in clinical diagnosis, prognosis, treatment, and personalized new drug development that can further explain the pathogenesis of psoriasis. This review summarizes the immunological mechanisms involved in the etiopathogenesis of psoriasis and recent advances in susceptibility genes and highlights new potential targets for therapeutic intervention.

Identification of 67 Pleiotropic Genes Associated With Seven Autoimmune/Autoinflammatory Diseases Using Multivariate Statistical Analysis

Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery, this univariate approach has limitations in detecting complex genotype-phenotype correlations. Multivariate analysis is essential to identify shared genetic risk factors acting through common biological mechanisms of autoimmune/autoinflammatory diseases. In this study, GWAS summary statistics, including 41,274 single nucleotide polymorphisms (SNPs) located in 11,516 gene regions, were analyzed to identify shared variants of seven autoimmune/autoinflammatory diseases using the metaCCA method. Gene-based association analysis was used to refine the pleiotropic genes. In addition, GO term enrichment analysis and protein-protein interaction network analysis were applied to explore the potential biological functions of the identified genes. A total of 4,962 SNPs (P < 1.21 × 10-6) and 1,044 pleotropic genes (P < 4.34 × 10-6) were identified by metaCCA analysis. By screening the results of gene-based P-values, we identified the existence of 27 confirmed pleiotropic genes and highlighted 40 novel pleiotropic genes that achieved statistical significance in the metaCCA analysis and were also associated with at least one autoimmune/autoinflammatory in the VEGAS2 analysis. Using the metaCCA method, we identified novel variants associated with complex diseases incorporating different GWAS datasets. Our analysis may provide insights for the development of common therapeutic approaches for autoimmune/autoinflammatory diseases based on the pleiotropic genes and common mechanisms identified.