Tang Hao, Wang Jiacheng, Zhang Shuhao, Feng Guanglong, Cheng Xiangshu, Meng Xin, Chen Rui, Wang Jiaqi, Jiang Yongshuai, Zhang Ruijie, Lv Wenhua
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Department of CT Diagnosis, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Front Immunol. 2025 Sep 1;16:1601705. doi: 10.3389/fimmu.2025.1601705. eCollection 2025.
Psoriasis is a chronic immune-mediated skin disease driven by the interleukin-23/interleukin-17 cytokine axis, yet its immunopathogenesis remains incompletely understood. Housekeeping genes, traditionally considered stably expressed across tissues and cell types, have not been systematically investigated for their role in psoriasis. Here, we aimed to identify psoriasis-associated housekeeping genes and explore their molecular mechanisms and clinical implications.
We integrated multi-cohort data and identified psoriasis-associated housekeeping genes using weighted gene co-expression network analysis combined with differential expression analysis. Single-cell transcriptomic analysis was performed to identify cell-type specific expression patterns, while ligand-receptor interaction analysis was applied to evaluate pathway activation and interactions with downstream target genes. In addition, multiple diagnostic models were established for psoriasis detection.
We identified 34 housekeeping genes associated with psoriasis and observed that the co-expression relationships between six genes (APOL2, DCUN1D3, UBE2F, HIGD1A, PPIF, and STAT3) and known psoriasis-related genes differed significantly between diseased and healthy individuals. Furthermore, single-cell transcriptomic analysis revealed that these housekeeping genes were differentially expressed primarily in basal, spinous, supraspinous, and proliferating keratinocytes. Ligand-receptor interaction analysis demonstrated significant activation of the IL - 17, IL - 6, and midkine (MK) pathways within keratinocyte subpopulations, which led to the upregulation of STAT3, EIF5A, and RAN, thereby promoting keratinocyte hyperproliferation and enhancing immune reactivity. Finally, among the various diagnostic models developed, the averaged neural network (avNNet) model emerged as the best performer, achieving over 90% classification accuracy across multiple independent datasets. Moreover, its scores were strongly correlated with the Psoriasis Area and Severity Index (correlation coefficient = 0.74, P = 4.4e-47).
This study redefines housekeeping genes as dual-function regulators in psoriasis pathogenesis, with the avNNet model enabling clinical translation of these molecular insights toward precision-targeted therapies and biomarker-based management strategies.
银屑病是一种由白细胞介素-23/白细胞介素-17细胞因子轴驱动的慢性免疫介导性皮肤病，但其免疫发病机制仍未完全阐明。管家基因传统上被认为在不同组织和细胞类型中稳定表达，尚未对其在银屑病中的作用进行系统研究。在此，我们旨在鉴定与银屑病相关的管家基因，并探索其分子机制和临床意义。
我们整合了多队列数据，并使用加权基因共表达网络分析结合差异表达分析来鉴定与银屑病相关的管家基因。进行单细胞转录组分析以确定细胞类型特异性表达模式，同时应用配体-受体相互作用分析来评估通路激活以及与下游靶基因的相互作用。此外，建立了多种用于银屑病检测的诊断模型。
我们鉴定出34个与银屑病相关的管家基因，并观察到六个基因（载脂蛋白L2、含E3泛素连接酶结构域蛋白1D3、泛素结合酶E2F、高表达蛋白1A、亲环蛋白F和信号转导及转录激活因子3）与已知银屑病相关基因之间的共表达关系在患病个体和健康个体之间存在显著差异。此外，单细胞转录组分析显示这些管家基因主要在基底角质形成细胞、棘层角质形成细胞、颗粒层角质形成细胞和增殖角质形成细胞中差异表达。配体-受体相互作用分析表明角质形成细胞亚群内白细胞介素-17、白细胞介素-6和中期因子通路显著激活，这导致信号转导及转录激活因子3、真核翻译起始因子5A和RAN上调，从而促进角质形成细胞过度增殖并增强免疫反应性。最后，在开发的各种诊断模型中，平均神经网络（avNNet）模型表现最佳，在多个独立数据集中实现了超过90%的分类准确率。此外，其评分与银屑病面积和严重程度指数高度相关（相关系数 = 0.74，P = 4.4×10⁻⁴⁷）。
本研究将管家基因重新定义为银屑病发病机制中的双功能调节因子，avNNet模型使这些分子见解能够临床转化为精准靶向治疗和基于生物标志物的管理策略。
