Zhu Linyu, Ye Zhiyu, Wang Ling, Chen Shaomin, Guo Menger, Zhang Lvya, Wu Yuansheng
The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou 510405, China; Department of Dermatovenereology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou 510405, China; Department of Traditional Chinese Medicine, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
J Genet Eng Biotechnol. 2025 Sep;23(3):100526. doi: 10.1016/j.jgeb.2025.100526. Epub 2025 Jun 18.
Regulated cell death (RCD) is crucial for the advancement of psoriasis, and providing opportunities as diagnostic indicators and drug sensitivity markers for psoriasis. Nevertheless, there is a lack of exploration regarding a thorough evaluation of RCD and psoriasis. 10 transcriptome datasets from psoriasis patients were retrieved, and then RCD mRNA profile was generated consensus cluster. Subsequently, RCD.score was conducted through machine-learning. Two psoriasis subclasses were identified., each exhibiting distinctive molecular patterns and immunologic landscape. Specifically, patients in molecular cluster B exhibited an immunosuppressive microenvironment, suggesting a non-inflamed immune infiltration phenotype. Then, an RCD.score was conducted, and RCD.score demonstrated promising diagnostic capabilities across 10 datasets. High RCD.score category exhibited a more active immune microenvironment, suggesting an inflamed immune infiltration phenotype. Additionally, scRNA-seq revealed an association between cell types and RCD.score, and RCD.score was higher in the T cells and psoriasis patients. Furthermore, Mendelian randomization screening revealed five genes (CDH6, MTHFR, DNMT3A, SETD1A, and RGS14) as feature genes for psoriasis, and validated in psoriasis patients. Recognizing RCD.score serves as an essential resource for prediction of psoriasis diagnostic, carrying wide-ranging implications for clinical practice.
程序性细胞死亡（RCD）对银屑病的进展至关重要，并为银屑病提供了作为诊断指标和药物敏感性标志物的机会。然而，目前缺乏对RCD与银屑病进行全面评估的探索。检索了10个来自银屑病患者的转录组数据集，然后生成了RCD mRNA谱的共识聚类。随后，通过机器学习进行RCD评分。识别出了两个银屑病亚类，每个亚类都表现出独特的分子模式和免疫格局。具体而言，分子聚类B中的患者表现出免疫抑制微环境，提示一种非炎症性免疫浸润表型。然后，进行了RCD评分，RCD评分在10个数据集中显示出有前景的诊断能力。高RCD评分类别表现出更活跃的免疫微环境，提示一种炎症性免疫浸润表型。此外，单细胞RNA测序揭示了细胞类型与RCD评分之间的关联，并且在T细胞和银屑病患者中RCD评分更高。此外，孟德尔随机化筛选揭示了五个基因（CDH6、MTHFR、DNMT3A、SETD1A和RGS14）作为银屑病的特征基因，并在银屑病患者中得到验证。认识到RCD评分是预测银屑病诊断的重要资源，对临床实践具有广泛的意义。
