The skin circadian clock gene F3 as a potential marker for psoriasis severity and its bidirectional relationship with IL-17 signaling in keratinocytes.

OBJECTIVE: Psoriasis is an immune-mediated skin disease where the IL-17 signaling pathway plays a crucial role in its development. Chronic circadian rhythm disorder in psoriasis pathogenesis is gaining more attention. The relationship between IL and 17 signaling pathway and skin clock genes remains poorly understood. METHODS: GSE121212 with psoriatic lesion and healthy controls was used as the exploration cohort for searching analysis. Datasets GSE54456, GSE13355, GSE14905, GSE117239, GSE51440, and GSE137218 were applied to validation analysis. Single-cell RNA sequencing (scRNA-seq) dataset GSE173706 was used to explore the F3 expression and related pathway activities in single-cell levels. Through intersecting with high-expression DEGs, F3 was selected as the signature skin circadian gene in psoriasis for further investigation. Functional analyses, including correlation analyses, prediction of transcription factors, protein-protein interaction, and single gene GSEA to explore the potential roles of F3. ssGSEA algorithm was performed to uncover the immune-related characteristics of psoriasis. We further explored F3 expression in the specific cell population in scRNA-seq dataset, besides this, AUCell analysis was performed to explore the pathway activities and the results were further compared between the specific cell cluster. Immunohistochemistry experiment, RT-qPCR was used to validate the location and expression of F3, small interfering RNA (siRNA) transfection experiment in HaCaT, and transcriptome sequencing analysis were applied to explore the potential function of F3. RESULTS: F3 was significantly down-regulated in psoriasis and interacted with IL-17 signaling pathway. Low expression of F3 could upregulate the receptor of JAK-STAT signaling, thereby promoting keratinocyte inflammation. CONCLUSION: Our research revealed a bidirectional link between the skin circadian gene F3 and the IL-17 signaling pathway in psoriasis, suggesting that F3 may interact with the IL-17 pathway by activating JAK-STAT within keratinocytes and inducing abnormal intracellular inflammation.

Transcription Factor IRF7 is Involved in Psoriasis Development and Response to Guselkumab Treatment.

Purpose: Guselkumab is a highly effective biologic agent for treating psoriasis. This study aimed to explore potential transcription factors involved in psoriasis pathogenesis and response to guselkumab treatment, aiming to provide new therapeutic strategies for psoriasis. Patients and Methods: We analyzed gene expression and single-cell RNA-seq data from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) that upregulated in psoriasis and downregulated after guselkumab treatment were subjected to enrichment analyses. Single-cell regulatory network inference and clustering (SENIC) and regulon module analyses identified different regulon activities between the lesion and non-lesion skin of psoriasis. Cell-cell communication analysis revealed interactions among specific cell clusters. Transcription factor (TF) regulons were identified from the guselkumab-specific regulon network. Gene set enrichment analysis (GSEA) confirmed the IRF7 regulon in the validation cohort. Finally, the expression level of IRF7 was identified in plaque psoriasis before and after 12 weeks of guselkumab therapy by immunohistochemical experiment. Results: 799 DEGs were downregulated after guselkumab treatment. Enrichment analyses highlighted the interleukin-17 (IL-17) pathway in this gene set. The M2 module exhibited the primary difference in regulon activity. Strong cell-cell interactions were observed between keratinocytes and immune cells. IRF7 regulon had significant roles in psoriasis and treatment response, as validated by GSEA analysis using the IL-17 signaling pathway as a reference. The immunohistochemical analysis unveiled substantial differences in the expression levels of IRF7 in psoriatic skin samples before and after 12 weeks of guselkumab treatment. Conclusion: IRF7 may be the key player in psoriasis pathogenesis and the therapeutic process involving guselkumab. Targeting IRF7 might offer new therapeutic strategies for psoriasis.

Identification of potential biomarkers and infiltrating immune cells from scalp psoriasis.

BACKGROUND: Scalp psoriasis seriously affects the appearance and psychological status of patients. The aim of this study was to investigate the effect and potential mechanism of RPL9 and TIFA in scalp psoriasis, so as to provide a precise and effective way for the clinical treatment of scalp psoriasis. METHODS: The Gene Expression Omnibus (GEO) database was employed to download the GSE75343 dataset to search for differentially expressed genes (DEGs) in scalp psoriasis through Sangerbox. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) enrichment analysis, functional enrichment analysis, immune cell infiltration analysis, immune responses and correlation analysis with 12 hub genes were performed. Then, STRING was used to develop a protein-protein interaction (PPI) network, used Cytoscape to locate hub genes, and SVM-RFE and random forest were utilized to identified RPL9 as the targeted gene. TIFA-RPL9 interaction predictions were made viathe Open Targets Platform and Uniprot. Further, the RPL9 and TIFA expression, molecular mechanism, and function were assessed in scalp psoriasis. RESULTS: Immunohistochemistry, qPCR, and western blotting verified that RPL9 and TIFA were highly expressed in lesional tissues of scalp psoriasis and IL17A-stimulated HaCaT cells. RPL9 knockdown effectively suppressed the proliferative capacity of IL17A-stimulated HaCaT cells in the CCK8 assay. The co-immunoprecipitation results revealed that RPL9 could interact with TIFA in IL17A-stimulated HaCaT cells. In qPCR and western blotting, RPL9 knockdown significantly inhibited TIFA at the mRNA and protein levels in IL17A-stimulated HaCaT cells. In ELISA, the secretion of TNF-α was markedly inhibited after downregulating RPL9 in IL17A-stimulated HaCaT cells. CONCLUSION: To our knowledge, we have elucidated the expression and role of RPL9 and TIFA in scalp psoriatic skin and keratinocytes, and our findings confirm that RPL9 might act as a candidate therapeutic target for scalp psoriasis.

The SELP, CD93, IL2RG, and VAV1 Genes Associated with Atherosclerosis May Be Potential Diagnostic Biomarkers for Psoriasis.

Purpose: Psoriasis and atherosclerosis are immunometabolic diseases. This study aimed to integrate bioinformatics and updated public resources to find potential biological markers associated with atherosclerosis that can cause psoriasis. Patients and Methods: Microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened, and functional enrichment analysis was performed. We identified psoriasis and atherosclerosis common immune-related genes (PA-IRGs) by overlapping immune-related genes (IRGs) with genes in the module most associated with psoriasis and atherosclerosis obtained by weighted gene co-expression network analysis (WGCNAs). Receiver operating characteristic (ROC) was conducted to evaluate the predictive ability. The skin expression levels of diagnostic biomarkers were further verified by immunohistochemical staining. CIBERSORT, single-sample gene set enrichment analysis (ssGSEA), and Pearson's correlation analysis were applied to evaluate immune and lipid metabolism relationships in psoriatic tissues. In addition, a lincRNA-miRNA-mRNA network was constructed to find the pathogenesis in which diagnostic markers may be involved. Results: Four PA-IRGs (SELP, CD93, IL2RG, and VAV1) demonstrated the optimal diagnostic value, with an AUC above 0.8. The immune cell infiltration analysis showed that dendritic resting cells, NK cell activation, neutrophils, macrophages M2, macrophages M0, and B-cell memory were highly abundant in psoriasis. Immune response analysis showed that TNF family members, chemokine receptors, interferons, natural killer cells, and TGF-ß family members might be involved in psoriasis. Diagnostic biomarkers are strongly associated with various infiltrating immune cells, immune responses, and lipid metabolism. A lincRNA-miRNA-mRNA regulatory network consisting of 31 lincRNAs and 23 miRNAs was constructed. LINC00662 is involved in modulating four diagnostic biomarkers. Conclusion: This study identified atherosclerosis-related genes SELP, CD93, VAV1, and IL2RG as potential psoriasis diagnostic markers. Provide novel insights into the possible regulatory mechanisms involved in psoriasis.

ZNF384: A Potential Therapeutic Target for Psoriasis and Alzheimer's Disease Through Inflammation and Metabolism.

Background: Psoriasis is an immune-related skin disease notable for its chronic inflammation of the entire system. Alzheimer's disease (AD) is more prevalent in psoriasis than in the general population. Immune-mediated pathophysiologic processes may link these two diseases, but the mechanism is still unclear. This article aimed to explore potential molecular mechanisms in psoriasis and AD. Methods: Gene expression profiling data of psoriasis and AD were acquired in the Gene Expression Omnibus (GEO) database. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were first applied in two datasets. Differentially expressed genes (DEGs) of two diseases were identified, and common DEGs were selected. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed to explore common biological pathways. Signature transcription factors (STFs) were identified and their diagnostic values was calculated by receiver operating characteristic (ROC) curve analysis in the exploration cohort and verified in the validation cohort. The expression levels of STFs were further investigated in the validation cohort and the GTEx Portal Database. Additionally, four kinds of interaction analysis were performed: correlation analysis among STFs, gene-gene, chemical-protein, and protein-ligand interaction analyses. In the end, we predicted the transcription factor that potentially regulates STFs. Results: Biosynthesis and metabolic pathways were enriched in GSEA analysis. In ssGSEA analysis, most immunoreaction gene lists exhibited differential enrichment in psoriasis cases, whereas three receptor-related gene lists did in AD. The KEGG analysis of common DEGs redetermined inflammatory and metabolic pathways essential in both diseases. 5 STFs (PPARG, ZFPM2, ZNF415, HLX, and ANHX) were screened from common DEGs. The ROC analysis indicated that all STFs have diagnostic values in two diseases, especially ZFPM2. The correlation analysis, gene-gene, chemical-protein, and protein-ligand interaction analyses suggested that STFs interplay and involve inflammation and aberrant metabolism. Eventually, ZNF384 was the predicted transcription factor regulating PPARG, ZNF415, HLX, and ANHX. Conclusions: The STFs (PPARG, ZFPM2, ZNF415, HLX, and ANHX) may increase the morbidity rate of AD in psoriasis by initiating a positive feedback loop of excessive inflammation and metabolic disorders. ZNF384 is a potential therapeutic target for psoriasis and AD by regulating PPARG, ZNF415, HLX, and ANHX.