School of Medicine, Zhejiang University, Hangzhou, 310009, China.
Department of Dermatology, Hangzhou Third People's Hospital, Affiliated Hangzhou Dermatology Hospital, Zhejiang University School of Medicine, West Lake Ave 38, Hangzhou, 310009, China.
Sci Rep. 2024 Feb 15;14(1):3800. doi: 10.1038/s41598-024-54278-4.
Alopecia areata (AA) is a common non-scarring hair loss condition driven by the collapse of immune privilege and oxidative stress. The role of ferroptosis, a type of cell death linked to oxidative stress, in AA is yet to be explored, even though it's implicated in various diseases. Using transcriptome data from AA patients and controls from datasets GSE68801 and GSE80342, we aimed to identify AA diagnostic marker genes linked to ferroptosis. We employed Single-sample gene set enrichment analysis (ssGSEA) for immune cell infiltration evaluation. Correlations between ferroptosis-related differentially expressed genes (FRDEGs) and immune cells/functions were identified using Spearman analysis. Feature selection was done through Support vector machine-recursive feature elimination (SVM-RFE) and LASSO regression models. Validation was performed using the GSE80342 dataset, followed by hierarchical internal validation. We also constructed a nomogram to assess the predictive ability of FRDEGs in AA. Furthermore, the expression and distribution of these molecules were confirmed through immunofluorescence. Four genes, namely SLC40A1, LCN2, CREB5, and SLC7A11, were identified as markers for AA. A prediction model based on these genes showed high accuracy (AUC = 0.9052). Immunofluorescence revealed reduced expression of these molecules in AA patients compared to normal controls (NC), with SLC40A1 and CREB5 showing significant differences. Notably, they were primarily localized to the outer root sheath and in proximity to the sebaceous glands. Our study identified several ferroptosis-related genes associated with AA. These findings, emerging from the integration of immune cell infiltration analysis and machine learning, contribute to the evolving understanding of diagnostic and therapeutic strategies in AA. Importantly, this research lays a solid foundation for subsequent studies exploring the intricate relationship between AA and ferroptosis.
斑秃（AA）是一种常见的非瘢痕性脱发疾病，其发病机制与免疫豁免崩溃和氧化应激有关。尽管铁死亡在各种疾病中都有涉及，但铁死亡作为一种与氧化应激相关的细胞死亡方式，在 AA 中的作用仍有待探索。本研究利用来自数据集 GSE68801 和 GSE80342 的 AA 患者和对照的转录组数据，旨在鉴定与铁死亡相关的 AA 诊断标志物基因。我们采用单样本基因集富集分析（ssGSEA）进行免疫细胞浸润评估。使用 Spearman 分析鉴定铁死亡相关差异表达基因（FRDEGs）与免疫细胞/功能之间的相关性。通过支持向量机递归特征消除（SVM-RFE）和 LASSO 回归模型进行特征选择。使用 GSE80342 数据集进行验证，然后进行内部验证。我们还构建了一个列线图来评估 FRDEGs 在 AA 中的预测能力。此外，通过免疫荧光证实了这些分子的表达和分布。鉴定到 SLC40A1、LCN2、CREB5 和 SLC7A11 这 4 个基因作为 AA 的标志物。基于这些基因的预测模型表现出较高的准确性（AUC=0.9052）。免疫荧光显示与正常对照（NC）相比，AA 患者这些分子的表达降低，SLC40A1 和 CREB5 有显著差异。值得注意的是，它们主要定位于外根鞘，靠近皮脂腺。本研究鉴定到一些与 AA 相关的铁死亡相关基因。这些发现，源于免疫细胞浸润分析和机器学习的整合，有助于深入了解 AA 的诊断和治疗策略。重要的是，本研究为后续研究探索 AA 与铁死亡之间的复杂关系奠定了坚实的基础。
