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在基于机器学习的基础上,识别与昼夜节律相关的基因分类模式和对心力衰竭的免疫透分析

Xuefu Wang¹, Jin Rao², Li Zhang³

¹School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.

|March 21, 2024

概括

这项研究确定了与心力衰竭 (HF) 相关的五个关键昼夜节律基因 (CRG),并根据CRG表达和免疫透揭示了不同的HF患者亚组. 这些发现为HF治疗提供了潜在的治疗点.

科学领域:

心血管生物学心血管生物学
时间生物学时间生物学
基因组学就是基因组学.

背景情况:

昼夜节律显著影响心脏功能,但对心力衰竭 (HF) 的分子联系尚未完全理解.
研究与昼夜节律相关的基因 (CRG) 在HF病变发生中的作用,对于开发新的治疗策略至关重要.

研究的目的:

在心力衰竭 (HF) 中识别差异表达的昼夜节律相关基因 (DE-CRGs).
利用基于特征基因的机器学习算法开发HF的诊断模型.
探索基于CRG表达的HF分子亚型及其与免疫透和生物功能的关联.

主要方法:

使用基因表达总 (GEO) 数据库对高频样本中CRG的差异基因表达分析.
机器学习算法 (LASSO回归) 用于特征基因选择和诊断模型构建.
共识聚类和非负矩阵因子化 (NMF) 用于HF样本亚型化,其次是免疫透和基因组变异分析 (GSVA).

主要成果:

在HF患者中,有13个CRG的差异表达,确定了5个关键诊断基因:NAMPT,SERPINA3,MAPK10,NPPA和SLC2A1.1.
肝炎患者被分为两个不同的群体,具有不同的生物功能和免疫特征.
免疫透分析显示了子组之间的显著差异,其中一个子组表现出更高的免疫评分和透. 像GRIN2A,DLG1,ERBB4,LRRC7和NRG1这样的枢纽基因与高频率有关.

结论:

已识别的诊断基因为心力衰竭提供了潜在的治疗点.
在HF中了解昼夜节律,免疫反应和能量代谢之间的相互作用可以指导未来的治疗策略.
这项研究为进一步研究高频频的分子机制提供了基础.

关键词:

生物信息学是一种生物信息学.循环节律是循环节律的节奏.心脏衰竭是因为心脏衰竭.免疫系统的透.机器学习是机器学习.没有监督的集群.

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