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通过生物信息学,机器学习和实验验证方法对性心肌病中与PANoptosis相关的基因进行分析

Yiheng Yang¹, Jiahao Zou¹, Peng Yang¹

¹Department of Cardiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China.

Experimental and therapeutic medicine

|December 31, 2025

概括

研究人员确定了两个关键的PANoptosis相关基因 (PRG),RIPK2和GADD45B,与败血性心肌病 (SCM) 有关. 这些基因显示出诊断潜力,并可能为SCM提供新的治疗点.

科学领域:

心脏病学心脏病学
分子生物学分子生物学
免疫学免疫学免疫学

背景情况:

败血性心肌病 (SCM) 的发病原因尚不清楚.
泛亡是一种新兴的编程细胞死亡途径.
在SCM中识别关键基因对于开发诊断和治疗方法至关重要.

研究的目的:

确定与败血性心肌病 (SCM) 相关的关键PANoptosis相关基因 (PRGs).
探索已识别的PRG的诊断价值和监管网络.
在SCM模型中验证关键PRG的表达.

主要方法:

对基因表达综合数据集的生物信息学分析.
机器学习算法 (LASSO,SVM-RFE,随机森林) 用于PRG选.
免疫透分析 (CIBERSORT),ceRNA网络构建和定量PCR验证.

主要成果:

确定了21个差异表达的PRG,其中RIPK2和GADD45B被选为关键基因.
RIPK2和GADD45B具有很高的诊断价值,并且与中性粒细胞具有积极的相关性.
构建了一个ceRNA网络,并预测了10种潜在的药物. 在LPS诱导的SCM模型中,RIPK2和GADD45B被上调.

结论:

RIPK2和GADD45B被确定为关键的PRG,与SCM病原发生有关.
这些基因有可能成为SCM的诊断生物标志物.
准RIPK2和GADD45B可能为SCM提供新的治疗策略.

关键词:

这就是PANoptosis.生物信息学是一种生物信息学.机器学习是机器学习.败血症是什么败血症是什么败血性心肌病症是什么意思

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