In our previous work, we built the model of PPARγ dependent pathways involved in the development of the psoriatic lesions. Peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor and transcription factor which regulates the expression of many proinflammatory genes. We tested the hypothesis that low levels of PPARγ expression promote the development of psoriatic lesions triggering the IL17-related signaling cascade. Skin samples of normally looking and lesional skin donated by psoriasis patients and psoriatic CD3+ Tcells samples (n = 23) and samples of healthy CD3+ T cells donated by volunteers (n = 10) were analyzed by real-time PCR, ELISA and immunohistochemistry analysis. We found that the expression of PPARγ is downregulated in human psoriatic skin and laser treatment restores the expression. The expression of IL17, STAT3, FOXP3, and RORC in psoriatic skin before and after laser treatment were correlated with PPARγ expression according to the reconstructed model of PPARγ pathway in psoriasis.In conclusion, we report that PPARγ weakens the expression of genes that contribute in the development of psoriatic lesion. Our data show that transcriptional regulation of PPARγ expression by FOSL1 and by STAT3/FOSL1 feedback loop may be central in the psoriatic skin and T-cells.

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In women, the flow of psoriasis is influenced by each phase of a woman’s life cycle. According to previous findings, significant changes in the levels of sex hormones affect the severity of the disease. Aim: The aim of this study was to identify the estrogen-responsive genes that could be responsible for the exacerbation of psoriasis in menopausal women. Methods: Skin samples of lesional skin donated by psoriasis patients (n = 5) were compared with skin samples of healthy volunteers (n = 5) using liquid chromatography–tandem mass spectrometry (LC–MS/MS). The set of differentially expressed proteins was subjected to protein ontology analysis to identify differentially expressed estrogen-responsive proteins. The expression of discovered proteins was validated by qPCR and ELISA on four groups of female participants. The first group included ten psoriasis patients without menopause; the second included eleven postmenopausal patients; the third included five healthy volunteers without menopause; and the fourth included six postmenopausal volunteers. Moreover, the participants’ blood samples were used to assess the levels of estradiol, progesterone, and testosterone. Results: We found that the levels of estradiol and progesterone were significantly lower and the levels of testosterone were significantly higher in the blood of patients compared to the control. The protein ontology analysis of LC–MS/MS data identified six proteins, namely HMOX1, KRT19, LDHA, HSPD1, MAPK1, and CA2, differentially expressed in the lesional skin of female patients compared to male patients. ELISA and qPCR experiments confirmed differential expression of the named proteins and their mRNA. The genes encoding the named proteins were differentially expressed in patients compared to volunteers. However, KRT19 and LDHA were not differentially expressed when we compared patients with and without menopause. All genes, except MAPK1, were differentially expressed in patients with menopause compared to the volunteers with menopause. HMOX1, KRT19, HSPD1, and LDHA were differentially expressed in patients without menopause compared to the volunteers without menopause. However, no significant changes were found when we compared healthy volunteers with and without menopause. Conclusion: Our experiments discovered a differential expression of six estrogen-controlled genes in the skin of female patients. Identification of these genes and assessment of the changes in their expression provide insight into the biological effects of estrogen in lesional skin. The results of proteomic analysis are available via ProteomeXchange with identifier PXD021673.

In this review paper, we discuss the contribution of proteomic studies to the discovery of disease-specific biomarkers to monitor the disease and evaluate available treatment options for psoriasis. Psoriasis is one of the most prevalent skin disorders driven by a Th17-specific immune response. Although potential patients have a genetic predisposition to psoriasis, the etiology of the disease remains unknown. During the last two decades, proteomics became deeply integrated with psoriatic research. The data obtained in proteomic studies facilitated the discovery of novel mechanisms and the verification of many experimental hypotheses of the disease pathogenesis. The detailed data analysis revealed multiple differentially expressed proteins and significant changes in proteome associated with the disease and drug efficacy. In this respect, there is a need for proteomic studies to characterize the role of the disease-specific biomarkers in the pathogenesis of psoriasis, develop clinical applications to choose the most efficient treatment options and monitor the therapeutic response.

Mental disorders participate in the development of psoriasis as predisposing factors; a correlation of dermatological diseases with pathological anxiety and stress was shown. The aim of this study is to find the associations between SNV in genes COMT (rs4680), DBH

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The approximate algebraic methods of the solution of a tomography problem of restitution of the performances of extended physical fields in matching with neural-like method of the solution of such problem are considered. The analyses of methods and results ofmodeling are made.

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