Liu Lichun, Lai Yongxing, Zhan Zhidong, Fu Qingxian, Jiang Yuelian
Department of Pharmacy, Fujian Children's Hospital, Fuzhou, China.
Department of Geriatric Medicine, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.
Front Genet. 2022 Aug 11;13:911119. doi: 10.3389/fgene.2022.911119. eCollection 2022.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder with clinical presentation and prognostic heterogeneity. Ferroptosis is a regulated non-apoptotic cell death program implicated in the occurrence and progression of various diseases. Therefore, we aimed to explore ferroptosis-related molecular subtypes in ASD and further illustrate the potential mechanism. A total of 201 normal samples and 293 ASD samples were obtained from the Gene Expression Omnibus (GEO) database. We used the unsupervised clustering analysis to identify the molecular subtypes based on ferroptosis-related genes (FRGs) and evaluate the immune characteristics between ferroptosis subtypes. Ferroptosis signatures were identified using the least absolute shrinkage and selection operator regression (LASSO) and recursive feature elimination for support vector machines (SVM-RFE) machine learning algorithms. The ferroptosis scores based on seven selected genes were constructed to evaluate the ferroptosis characteristics of ASD. We identified 16 differentially expressed FRGs in ASD children compared with controls. Two distinct molecular clusters associated with ferroptosis were identified in ASD. Analysis of immune infiltration revealed immune heterogeneity between the two clusters. Cluster2, characterized by a higher immune score and a larger number of infiltrated immune cells, exhibited a stronger immune response and was markedly enriched in immune response-related signaling pathways. Additionally, the ferroptosis scores model was capable of predicting ASD subtypes and immunity. Higher levels of ferroptosis scores were associated with immune activation, as seen in Cluster2. Lower ferroptosis scores were accompanied by relative immune downregulation, as seen in Cluster1. Our study systematically elucidated the intricate correlation between ferroptosis and ASD and provided a promising ferroptosis score model to predict the molecular clusters and immune infiltration cell profiles of children with ASD.
自闭症谱系障碍（ASD）是一种具有临床表现和预后异质性的神经发育障碍。铁死亡是一种受调控的非凋亡性细胞死亡程序，与多种疾病的发生和发展有关。因此，我们旨在探索ASD中铁死亡相关的分子亚型，并进一步阐明其潜在机制。从基因表达综合数据库（GEO）中获取了总共201个正常样本和293个ASD样本。我们使用无监督聚类分析，基于铁死亡相关基因（FRGs）识别分子亚型，并评估铁死亡亚型之间的免疫特征。使用最小绝对收缩和选择算子回归（LASSO）以及支持向量机递归特征消除（SVM-RFE）机器学习算法识别铁死亡特征。构建基于七个选定基因的铁死亡评分，以评估ASD的铁死亡特征。与对照组相比，我们在ASD儿童中鉴定出16个差异表达的FRGs。在ASD中鉴定出两个与铁死亡相关的不同分子簇。免疫浸润分析揭示了两个簇之间的免疫异质性。以较高的免疫评分和更多浸润免疫细胞为特征的簇2表现出更强的免疫反应，并且在免疫反应相关信号通路中显著富集。此外，铁死亡评分模型能够预测ASD亚型和免疫情况。如在簇2中所见，较高水平的铁死亡评分与免疫激活相关。如在簇1中所见，较低的铁死亡评分伴随着相对的免疫下调。我们的研究系统地阐明了铁死亡与ASD之间的复杂相关性，并提供了一个有前景的铁死亡评分模型，以预测ASD儿童的分子簇和免疫浸润细胞谱。
