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基于生物信息学和机器学习的皮肤衰老中的关键昼夜节律基因的识别

Xiao Xiao¹, Hao Feng¹, Yangying Liao¹

¹Department of Dermatology, Hunan Provincial People’s Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, Hunan 410002, China.

|October 31, 2023

概括

这项研究确定了三种关键的昼夜节律基因 (CRG) SIRT1,ARNTL和ATF4涉及皮肤衰老. 这些基因在老化皮肤下调节,并与免疫细胞的变化有关,为皮肤老化提供了潜在的生物标志物.

科学领域:

基因组学和分子生物学
时间生物学时间生物学
皮肤病学皮肤病学

背景情况:

皮肤衰老与昼夜节律的破坏和昼夜节律相关基因 (CRG) 的改变表达有关.
了解皮肤衰老的分子机制对于开发有效的干预措施至关重要.

研究的目的:

通过生物信息学和机器学习,确定参与皮肤衰老的关键CRG.
探索CRG,信号通路和免疫细胞透在皮肤衰老中的关联.
评估已识别的CRG作为生物标志物的潜力,以区分年轻和老化的皮肤.

主要方法:

从GEO数据库下载和分析皮肤衰老基因表达数据集.
采用生物信息学和机器学习技术来识别重要的CRG.
进行了途径丰富分析和与免疫细胞透相关的CRG表达.

主要成果:

确定了与皮肤衰老相关的39个CRG,富含诸如葡萄糖信号传递和胰岛素抵抗等途径.
通过机器学习将SIRT1,ARNTL和ATF4确定为与皮肤衰老相关的关键CRG.
发现SIRT1,ARNTL,ATF4表达和免疫细胞透 (例如NK细胞,巨细胞) 之间的相关性.
证明SIRT1,ARNTL和ATF4在老化皮肤下调,可以区分年轻和老化的皮肤组织.

结论:

SIRT1,ARNTL和ATF4是与皮肤衰老相关的关键CRG.
这些CRG可能作为皮肤衰老的潜在风险基因.
已识别的CRG与老化期间皮肤免疫微环境的变化有关.

关键词:

生物信息学是一种生物信息学.昼夜节律昼夜节律免疫透免疫透是什么?机器学习是机器学习.皮肤老化皮肤老化

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