College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK.
Present Address: Bioinformatics, Mahila Mahavidyalay, Banaras Hindu University, Varanasi, India.
Sci Rep. 2021 Jan 26;11(1):2204. doi: 10.1038/s41598-020-80507-7.
Psoriasis is a chronic inflammatory skin disease clinically characterized by the appearance of red colored, well-demarcated plaques with thickened skin and with silvery scales. Recent studies have established the involvement of a complex signalling network of interactions between cytokines, immune cells and skin cells called keratinocytes. Keratinocytes form the cells of the outermost layer of the skin (epidermis). Visible plaques in psoriasis are developed due to the fast proliferation and unusual differentiation of keratinocyte cells. Despite that, the exact mechanism of the appearance of these plaques in the cytokine-immune cell network is not clear. A mathematical model embodying interactions between key immune cells believed to be involved in psoriasis, keratinocytes and relevant cytokines has been developed. The complex network formed of these interactions poses several challenges. Here, we choose to study subnetworks of this complex network and initially focus on interactions involving [Formula: see text], IL-23/IL-17, and IL-15. These are chosen based on known evidence of their therapeutic efficacy. In addition, we explore the role of IL-15 in the pathogenesis of psoriasis and its potential as a future drug target for a novel treatment option. We perform steady state analyses for these subnetworks and demonstrate that the interactions between cells, driven by cytokines could cause the emergence of a psoriasis state (hyper-proliferation of keratinocytes) when levels of [Formula: see text], IL-23/IL-17 or IL-15 are increased. The model results explain and support the clinical potentiality of anti-cytokine treatments. Interestingly, our results suggest different dynamic scenarios underpin the pathogenesis of psoriasis, depending upon the dominant cytokines of subnetworks. We observed that the increase in the level of IL-23/IL-17 and IL-15 could lead to psoriasis via a bistable route, whereas an increase in the level of [Formula: see text] would lead to a monotonic and gradual disease progression. Further, we demonstrate how this insight, bistability, could be exploited to improve the current therapies and develop novel treatment strategies for psoriasis.
银屑病是一种慢性炎症性皮肤病,临床上表现为红色、界限清楚的斑块,皮肤增厚,有银色鳞屑。最近的研究表明,细胞因子、免疫细胞和皮肤细胞(角质形成细胞)之间存在一个复杂的信号网络相互作用,参与其中。角质形成细胞构成皮肤最外层(表皮)的细胞。银屑病中的可见斑块是由于角质形成细胞的快速增殖和异常分化而形成的。尽管如此,细胞因子-免疫细胞网络中这些斑块出现的确切机制尚不清楚。已经建立了一个数学模型,该模型体现了被认为与银屑病有关的关键免疫细胞与角质形成细胞和相关细胞因子之间的相互作用。这些相互作用形成的复杂网络带来了一些挑战。在这里,我们选择研究这个复杂网络的子网,并最初关注涉及[公式:见文本]、IL-23/IL-17 和 IL-15 的相互作用。选择这些是基于它们在治疗中的有效性的已知证据。此外,我们还研究了 IL-15 在银屑病发病机制中的作用及其作为新型治疗选择的潜在药物靶点的作用。我们对这些子网进行了稳态分析,并证明了细胞因子驱动的细胞之间的相互作用可能导致银屑病状态(角质形成细胞过度增殖)的出现,当[公式:见文本]、IL-23/IL-17 或 IL-15 的水平增加时。模型结果解释并支持了抗细胞因子治疗的临床潜力。有趣的是,我们的结果表明,根据子网的主要细胞因子,不同的动态情况支持银屑病的发病机制。我们观察到,IL-23/IL-17 和 IL-15 水平的增加可能通过双稳态途径导致银屑病,而[公式:见文本]水平的增加则会导致疾病的单调和逐渐进展。此外,我们展示了这种洞察力,即双稳态,如何被利用来改善当前的治疗方法并为银屑病开发新的治疗策略。