Hou Mengyi, Sun Yanting
Department of Laboratory Medicine, People's Hospital of Chongqing Liang Jiang New Area, Chongqing, 401122, People's Republic of China.
Centre of Clinical Laboratory, The First Affiliated Hospital of Soochow University, Suzhou, 215006, People's Republic of China.
Clin Cosmet Investig Dermatol. 2025 Mar 17;18:601-615. doi: 10.2147/CCID.S494806. eCollection 2025.
Psoriasis is a chronic inflammatory skin disorder with complex molecular mechanisms. While previous studies have demonstrated altered levels of arachidonic acid and its metabolites in psoriatic lesions, the specific roles of arachidonic acid metabolism (AAM) genes in the molecular pathogenesis and immune dysregulation of psoriasis remain poorly understood. This study aimed to investigate the role of AAM genes in the pathogenesis and immune dysregulation of psoriasis using an integrative bioinformatics approach.
Gene expression data from psoriasis patients and healthy controls were obtained from the Gene Expression Omnibus database and analyzed. Differentially expressed genes were identified, and functional enrichment analyses were performed. Weighted gene co-expression network analysis (WGCNA) and machine learning techniques were employed to identify psoriasis associated AAM genes. Single-sample gene set enrichment analysis (ssGSEA) and immune cell composition analysis were conducted to explore functional implications. Transcription factor prediction analysis was performed to identify potential regulators of key AAM genes.
Differential expression analysis revealed 469 dysregulated genes in psoriasis, with functional enrichment highlighting the involvement of epidermis development, immune response, and inflammation. WGCNA and machine learning approaches identified , and as key AAM genes. ssGSEA showed elevated inflammation and immune response in psoriasis, with key AAM genes correlating with specific pathways. Immune cell composition analysis revealed increased infiltration of inflammatory cells in psoriatic skin. Transcription factor prediction analysis identified shared transcription factors for the key AAM genes, suggesting coordinated regulation of their expression in psoriasis.
This integrative analysis identified key AAM genes associated with psoriasis pathogenesis and immune dysregulation, providing novel insights into the molecular basis of psoriasis. The findings highlight potential therapeutic targets and biomarkers, which could lead to improved diagnosis and treatment strategies for this chronic inflammatory skin disorder.
银屑病是一种具有复杂分子机制的慢性炎症性皮肤病。虽然先前的研究已经证明银屑病皮损中花生四烯酸及其代谢产物水平发生了改变,但花生四烯酸代谢(AAM)基因在银屑病分子发病机制和免疫失调中的具体作用仍知之甚少。本研究旨在使用综合生物信息学方法研究AAM基因在银屑病发病机制和免疫失调中的作用。
从基因表达综合数据库中获取银屑病患者和健康对照的基因表达数据并进行分析。鉴定差异表达基因,并进行功能富集分析。采用加权基因共表达网络分析(WGCNA)和机器学习技术来鉴定与银屑病相关的AAM基因。进行单样本基因集富集分析(ssGSEA)和免疫细胞组成分析以探索功能意义。进行转录因子预测分析以鉴定关键AAM基因的潜在调节因子。
差异表达分析显示银屑病中有469个失调基因,功能富集突出了表皮发育、免疫反应和炎症的参与。WGCNA和机器学习方法鉴定出[具体基因未给出]作为关键AAM基因。ssGSEA显示银屑病中炎症和免疫反应升高,关键AAM基因与特定途径相关。免疫细胞组成分析显示银屑病皮肤中炎症细胞浸润增加。转录因子预测分析鉴定出关键AAM基因的共同转录因子,表明它们在银屑病中表达的协同调节。
这项综合分析鉴定出了与银屑病发病机制和免疫失调相关的关键AAM基因,为银屑病的分子基础提供了新的见解。这些发现突出了潜在的治疗靶点和生物标志物,这可能会导致针对这种慢性炎症性皮肤病的诊断和治疗策略得到改善。