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基于机器学习和生物信息学分析的股骨头亡的综合分析

Zheng Chen¹, Yuankang Jiang¹, Suwen Wu¹

¹Guangzhou University of Chinese Medicine Third Clinical Medical College, Guangzhou, China.

|June 19, 2023

概括

这项研究确定了关键基因 (TNF,NOS3,CASP3) 和诊断生物标志物 (APOD,CASP3,NOS3,TNF),用于骨骨 (ONFH),使用生物信息学分析氧化应激途径.

科学领域:

基因组学和生物信息学
分子生物学分子生物学
免疫学免疫学免疫学

背景情况:

股骨头骨死 (ONFH) 是一种具有不清楚分子机制的衰弱性疾病.
了解ONFH的发病性对于识别诊断生物标志物和治疗点至关重要.
生物信息学方法提供了一个强大的工具,以阐明复杂的疾病机制.

研究的目的:

通过生物信息学分析阐明ONFH背后的分子机制.
在ONFH中识别与氧化应激相关的差异表达基因.
发现ONFH潜在的诊断生物标志物和治疗点.

主要方法:

下载的ONFH基因表达数据 (GSE74089) 来自基因表达Omnibus.
使用R软件 ("limma"包) 进行差异基因表达分析.
执行了基因本体学,KEGG通路丰富,蛋白质-蛋白质相互作用网络构建,LASSO,SVM,cytoHubba,CIBERSORT,GSVA和分子对接.

主要成果:

鉴定出144个不同表达的与氧化压力相关的基因,富含活性氧物种和AGE-RAGE信号.
发现APOD和TMEM161A作为特征基因,TNF,NOS3和CASP3作为关键基因.
验证了APOD,CASP3,NOS3和TNF作为具有强大的诊断能力的潜在诊断生物标志物;确定了基因斯坦作为潜在的治疗化合物.

结论:

TNF,NOS3和CASP3在ONFH的病变发生过程中发挥着关键作用.
APOD,CASP3,NOS3和TNF显示出作为ONFH诊断生物标志物的巨大潜力.
生物信息学分析为ONFH机制和生物标志物发现提供了宝贵的见解.

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