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综合分析确定FERMT3是瘢痕疙瘩形成和代谢综合征中代谢重编程的关键调节因子。

Integrative analysis identifies FERMT3 as a key regulator of metabolic reprogramming in keloid scarring and metabolic syndrome.

作者信息

Lin Qian, Cai Beichen, Dong Feng, Ke Ruonan, Shan Xiuying, Ni Xuejun, Chen Lu, Cai Chuanshu, Wang Biao

机构信息

Department of Plastic Surgery, the First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China.

Department of Plastic Surgery, Binhai Campus of the First Affiliated Hospital, National Regional Medical Center, Fujian Medical University, Fuzhou, 350212, China.

出版信息

Funct Integr Genomics. 2025 Sep 10;25(1):188. doi: 10.1007/s10142-025-01705-y.

Abstract

Keloid scarring and Metabolic Syndrome (MS) are distinct conditions marked by chronic inflammation and tissue dysregulation, suggesting shared pathogenic mechanisms. Identifying common regulatory genes could unveil novel therapeutic targets. Methods. We performed an integrative analysis of public microarray datasets from keloid, MS, and respective healthy control tissues. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify shared gene modules. A diagnostic gene signature was developed using LASSO regression and machine learning, and validated on independent datasets. Single-cell RNA sequencing (scRNA-seq) data were analyzed to localize gene expression to specific cell types. The function of a top candidate gene, FERMT3, was investigated via in vitro experiments in macrophages and fibroblasts. Results. We identified 2,788 differentially expressed genes (DEGs) in keloids and 2,639 in MS compared to healthy controls, with 146 genes overlapping. WGCNA identified a key co-expression module (termed the "salmon" module) significantly associated with both conditions and enriched in metabolic and immune pathways. A 23-gene signature demonstrated fair to good predictive performance for both keloids (validation AUC = 0.783) and MS (AUC = 0.905). scRNA-seq analysis revealed that FERMT3 was highly expressed in macrophages and fibroblasts in keloid tissue. In vitro, modulation of FERMT3 in these cell types significantly altered their metabolic profiles (glycolysis, oxidative phosphorylation), inflammatory cytokine production, proliferation, and migration. Conclusions. Our integrative analysis identifies a shared transcriptomic signature between keloids and MS and highlights FERMT3 as a key potential regulator of the metabolic and inflammatory phenotypes in these conditions. These findings suggest that FERMT3 could be a promising therapeutic target for diseases driven by fibro-metabolic dysregulation.

摘要

瘢痕疙瘩和代谢综合征(MS)是两种不同的病症,其特征为慢性炎症和组织调节异常,提示存在共同的致病机制。识别共同的调控基因可能会揭示新的治疗靶点。方法。我们对来自瘢痕疙瘩、MS及各自健康对照组织的公共微阵列数据集进行了综合分析。使用加权基因共表达网络分析(WGCNA)来识别共享基因模块。利用套索回归和机器学习开发了一种诊断基因特征,并在独立数据集上进行了验证。分析单细胞RNA测序(scRNA-seq)数据,以将基因表达定位到特定细胞类型。通过在巨噬细胞和成纤维细胞中进行体外实验,研究了顶级候选基因FERMT3的功能。结果。与健康对照相比,我们在瘢痕疙瘩中鉴定出2788个差异表达基因(DEG),在MS中鉴定出2639个,有146个基因重叠。WGCNA识别出一个关键的共表达模块(称为“鲑鱼”模块),与这两种病症均显著相关,且在代谢和免疫途径中富集。一个由23个基因组成的特征对瘢痕疙瘩(验证AUC = 0.783)和MS(AUC = 0.905)均表现出良好至优秀的预测性能。scRNA-seq分析显示,FERMT3在瘢痕疙瘩组织中的巨噬细胞和成纤维细胞中高度表达。在体外,这些细胞类型中FERMT3的调节显著改变了它们的代谢谱(糖酵解、氧化磷酸化)、炎性细胞因子产生、增殖和迁移。结论。我们的综合分析确定了瘢痕疙瘩和MS之间的共享转录组特征,并突出了FERMT3作为这些病症中代谢和炎症表型的关键潜在调节因子。这些发现表明,FERMT3可能是由纤维代谢失调驱动的疾病的一个有前景的治疗靶点。

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