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基于机器学习的心力衰竭和慢性病共享签名基因和免疫微环境亚型的识别

Xuefu Wang¹, Jin Rao², Xiangyu Chen²

¹School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, People's Republic of China.

Journal of inflammation research

|March 27, 2024

概括

这项研究确定了五个关键基因作为诊断心力衰竭 (HF) 和慢性病 (CKD) 的潜在生物标志物,揭示了涉及免疫失调和代谢障碍的共同分子机制.

科学领域:

心血管医学心血管医学
腎臟病學 (nephrology) 是一種醫學專業.
分子生物学分子生物学

背景情况:

心力衰竭 (HF) 和慢性病 (CKD) 呈现出复杂的相互关系.
了解这种器官间相互作用的分子机制至关重要.
对于这两种疾病来说,识别敏感和特定的生物标志物是一个重要的临床需求.

研究的目的:

澄清 HF 和 CKD 之间的相互作用背后的分子机制.
确定敏感和特定的生物标志物,用于同时诊断HF和CKD.
探索同时存在的HF和CKD的分子亚型和免疫特征.

主要方法:

对HF和CKD微阵列数据集的差异基因表达分析.
机器学习用于使用ROC曲线和RT-PCR的生物标志物识别和验证.
对分子亚型的共识聚类和对免疫细胞透分析的ssGSEA.

主要成果:

确定了33个与炎症,免疫和代谢途径相关的交叉基因.
五个枢纽基因 (PHLDA1,ATP1A1,IFIT2,HLTF,MPP3) 被选为最佳的诊断生物标志物.
发现了HF和CKD的独特的免疫和代谢亚型,具有显著的免疫失调.

结论:

已识别的五个交叉基因显示,它们有可能成为HF和CKD的诊断生物标志物.
代谢障碍和随后的免疫细胞激活是HF和CKD常见病原发生的关键.
一个ImmuneScore模型准确地预测了分子亚型,帮助风险分层.

关键词:

生物信息学是一种生物信息学.慢性脏疾病慢性脏疾病心脏衰竭是因为心脏衰竭.免疫力和炎症发生.代谢障碍代谢障碍是一种代谢障碍.

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