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对人类和实验老鼠样本的综合分析确定了缺血性中风的生物标志物

Qingfa Chen¹, Xiaolu Li², Ye Yang²

¹Department of Rehabilitation, Fujian Medical University Union Hospital, Fuzhou, 350001, Fujian, China.

Molecular neurobiology

|September 26, 2024

概括

调查缺血性中风 (IS),这项研究确定了转化生长因子β1 (Tgfb1) 作为一个关键基因. Tgfb1显示出作为IS生物标志物的潜力,与疾病严重程度相关.

科学领域:

基因组学就是基因组学.
分子生物学分子生物学
神经科学是一个神经科学.

背景情况:

缺血性中风 (IS) 的遗传转录特征和分子机制尚未完全理解.
缺血性中风是全球残疾和死亡的主要原因,需要进一步研究其潜在的病理学.

研究的目的:

阐明缺血性中风 (IS) 的遗传转录特征和分子机制.
通过全面的基因表达分析,识别IS的潜在生物标志物.

主要方法:

从基因表达综合 (GEO) 数据库中从中脑动脉封闭 (MCAO) 的老鼠获得的mRNA和miRNA表达特征.
选差异表达基因 (DEGs) 和miRNAs (DEMs),然后进行基因组和功能丰富分析.
利用权重基因共同表达网络分析 (WGCNA) 和最小绝对收缩和选择运算符 (LASSO) 回归来识别关键的IS相关基因,包括枢纽基因.

主要成果:

确定了780个DEG和56个DEM,在IS中显著丰富了与免疫炎症相关的途径.
发现了354个关键的IS相关基因,其中选择了6个特征基因.
转化生长因子β1 (Tgfb1) 被确定为枢纽基因,在多个数据集中得到验证,并在MCAO模型大鼠和IS患者中得到证实. Tgfb1表达与修改的兰金级分数负相关.

结论:

这项研究扩大了对缺血性中风背后的遗传特征和分子机制的理解.
转化生长因子β1 (Tgfb1) 被提议作为缺血性中风的潜在诊断生物标志物,其表达与疾病严重程度有关.

关键词:

基因组丰富分析分析机器学习是机器学习.一次性中风,中风.权重基因共同表达网络分析.

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