Feng Chun, Yan Wen, Mei Zhen, Luo Xin
Department of Dermatology, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Department of Dermatology, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
J Environ Manage. 2025 Jun;385:125708. doi: 10.1016/j.jenvman.2025.125708. Epub 2025 May 10.
Psoriasis is a common immune - mediated skin disease, the pathogenesis of which is not completely elucidated. Environmental factors are key to its onset and progression. Bisphenol A (BPA) is a ubiquitous environmental pollutant that endangers human health. Previous research shows that BPA exposure disrupts immunity and causes skin inflammation and autoimmune diseases. However, the role and molecular mechanisms of BPA in psoriasis are unclear. In this study, we used network toxicology, machine learning, and bioinformatics to study BPA - induced psoriasis mechanisms. Public database analyses identified 100 potential targets, with significant enrichment in the PI3K - AKT and Chemokine signaling pathways. Machine learning identified five core targets: PTAFR, MMP9, CXCR2, IDO1, and LCK. These genes are highly expressed in psoriatic lesion tissues than controls and associated to immune cell infiltration. Molecular docking and dynamics simulations confirmed stable interactions between BPA and these targets, which supports their role in disease progression. We also developed a novel Adverse Outcome Pathway (AOP) framework for BPA-induced psoriasis, providing key toxicological insights into the risks of exposure. These findings highlight the impact of BPA on immune regulation, offering a foundation for understanding associated health risks and formulating mitigation strategies. Our study provides an in-depth exploration of the molecular mechanisms underlying BPA-induced psoriasis. The findings underscore the practical application of integrating network toxicology, machine learning, multidimensional bioinformatics approaches, and AOP frameworks in assessing environmental pollutant risks. Furthermore, it lays the foundation for understanding BPA-related health risks and developing strategies to mitigate its impact on psorasis.
银屑病是一种常见的免疫介导性皮肤病，其发病机制尚未完全阐明。环境因素是其发病和进展的关键。双酚A（BPA）是一种普遍存在的环境污染物，危害人类健康。先前的研究表明，接触BPA会破坏免疫力，导致皮肤炎症和自身免疫性疾病。然而，BPA在银屑病中的作用和分子机制尚不清楚。在本研究中，我们使用网络毒理学、机器学习和生物信息学来研究BPA诱导的银屑病机制。公共数据库分析确定了100个潜在靶点，在PI3K - AKT和趋化因子信号通路中显著富集。机器学习确定了五个核心靶点：PTAFR、MMP9、CXCR2、IDO1和LCK。这些基因在银屑病病变组织中的表达高于对照组，并与免疫细胞浸润相关。分子对接和动力学模拟证实了BPA与这些靶点之间的稳定相互作用，支持它们在疾病进展中的作用。我们还为BPA诱导的银屑病开发了一种新的不良结局途径（AOP）框架，为接触风险提供了关键的毒理学见解。这些发现突出了BPA对免疫调节的影响，为理解相关健康风险和制定缓解策略提供了基础。我们的研究深入探讨了BPA诱导银屑病的分子机制。这些发现强调了整合网络毒理学、机器学习、多维生物信息学方法和AOP框架在评估环境污染物风险中的实际应用。此外，它为理解与BPA相关的健康风险以及制定减轻其对银屑病影响的策略奠定了基础。
