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基于机器学习和实验验证揭示与缺氧诱导因子1α(HIF1A)通路相关的自闭症谱系障碍的发病机制和潜在生物标志物。

Unraveling pathogenesis and potential biomarkers for autism spectrum disorder associated with HIF1A pathway based on machine learning and experiment validation.

作者信息

Cui Jinru, Li Heli, Hu Cong, Zhang Feiyan, Li Yunjie, Weng Ying, Yang Liping, Li Yingying, Yao Minglan, Li Hao, Luo Xiaoping, Hao Yan

机构信息

Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.

Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.

出版信息

Neurobiol Dis. 2025 Jan;204:106763. doi: 10.1016/j.nbd.2024.106763. Epub 2024 Dec 8.

Abstract

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a high social burden and limited treatments. Hypoxic condition of the brain is considered an important pathological mechanism of ASD. HIF1A is a key participant in brain hypoxia, but its contribution to the pathophysiological landscape of ASD remains unclear.

METHODS

ASD-related datasets were obtained from GEO database, and HIF1A-related genes from GeneCards. Co-expression module analysis identified module genes, which were intersected with HIF1A-related genes to identify common genes. Machine learning identified hub genes from intersection genes and PPI networks were constructed to explore relationships among hub and HIF1A. Single-cell RNA sequencing analyzed hub gene distribution across cell clusters. ASD mouse model was created by inducing maternal immune activation (MIA) with poly(I:C) injections, verified through behavioral tests. Validation of HIF1A pathway and hub genes was confirmed through Western Blot, qPCR, and immunofluorescence in ASD mice and microglia BV-2 cells.

RESULTS

Using CEMiTool and GeneCards, 45 genes associated with ASD and HIF1A pathway were identified. Machine learning identified CDKN1A, ETS2, LYN, and SLC16A3 as potential ASD diagnostic markers. Single-cell sequencing pinpointed activated microglia as key immune cells. Behavioral tests showed MIA offspring mice exhibited typical ASD-like behaviors. Immunofluorescence confirmed the activation of microglia and HIF1A pathway in frontal cortex of ASD mice. Additionally, IL-6 contributed to ASD by activating JUN/HIF1A pathway, affecting CDKN1A, LYN, and SLC16A3 expression in microglia.

CONCLUSIONS

HIF1A-related genes CDKN1A, ETS2, LYN, and SLC16A3 are strong diagnostic markers for ASD and the activation of IL-6/JUN/HIF1A pathway in microglia contributes to the pathogenesis of ASD.

摘要

背景

自闭症谱系障碍(ASD)是一种神经发育障碍,社会负担沉重且治疗手段有限。大脑的缺氧状态被认为是ASD的一种重要病理机制。缺氧诱导因子1α(HIF1A)是大脑缺氧的关键参与者,但其对ASD病理生理格局的贡献仍不清楚。

方法

从基因表达综合数据库(GEO数据库)获取与ASD相关的数据集,并从基因卡片(GeneCards)获取与HIF1A相关的基因。共表达模块分析确定模块基因,将其与HIF1A相关基因进行交集分析以确定共同基因。机器学习从交集基因中识别出枢纽基因,并构建蛋白质-蛋白质相互作用(PPI)网络以探索枢纽基因与HIF1A之间的关系。单细胞RNA测序分析枢纽基因在细胞簇中的分布。通过注射聚肌苷酸胞嘧啶核苷酸(poly(I:C))诱导母体免疫激活(MIA)创建ASD小鼠模型,并通过行为测试进行验证。通过蛋白质免疫印迹法(Western Blot)、实时定量聚合酶链反应(qPCR)和免疫荧光法在ASD小鼠和小胶质细胞BV-2细胞中对HIF1A通路和枢纽基因进行验证。

结果

使用CEMiTool和GeneCards,鉴定出与ASD和HIF1A通路相关的45个基因。机器学习确定细胞周期蛋白依赖性激酶抑制剂1A(CDKN1A)、ETS转录因子2(ETS2)、淋巴细胞特异性蛋白酪氨酸激酶(LYN)和溶质载体家族16成员3(SLC16A3)为潜在的ASD诊断标志物。单细胞测序确定活化的小胶质细胞是关键免疫细胞。行为测试表明,MIA后代小鼠表现出典型的ASD样行为。免疫荧光证实ASD小鼠额叶皮质中小胶质细胞和HIF1A通路的激活。此外,白细胞介素6(IL-6)通过激活JUN/HIF1A通路,影响小胶质细胞中CDKN1A、LYN和SLC16A3的表达,从而导致ASD。

结论

与HIF1A相关的基因CDKN1A、ETS2、LYN和SLC16A3是ASD的强诊断标志物,小胶质细胞中IL-6/JUN/HIF1A通路的激活促成了ASD的发病机制。

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