开发与COVID-19严重性相关的基线代谢签名:来自13个美国中心的潜在试验的见解
Kaifeng Yang1, Zhiyu Kang1, Weihua Guan1
1Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA.
Metabolites
|November 24, 2023
概括
代谢性疾病增加了COVID-19的严重程度. 一种新的三种代谢物签名,包括特定的lysophosphatidylcholine,dihydroceramide和triacylglyceride,准确地预测严重的COVID-19,帮助临床决策.
科学领域:
- 代谢学 代谢学 代谢学
- 传染病流行病学 传染病流行病学
- 机器学习在医学中的应用
背景情况:
- 代谢性疾病是严重COVID-19的已知危险因素之一.
- 导致COVID-19严重程度的特定代谢途径尚不清楚.
研究的目的:
- 为了确定预先预测严重COVID-19的基线代谢特征.
- 为风险分层定义一种新的代谢学特征.
主要方法:
- 通过使用Biocrates平台对133个人的血液样本中630种向代谢物的分析.
- 应用重新采样技术和机器学习模型来识别预测代谢特征.
- 使用发明路径分析 (IPA) 进行功能丰富分析.
主要成果:
- 一个三种代谢物签名 (lysophosphatidylcholine a C17:0,二水胺 (d18:0/24:1) 和三甘油 (20:4_36:4)) 实现了高分辨率 (AUROC 0.978,F1 0.942).
- IPA揭示了氨基酸代谢途径的显著丰富.
- 观察到基因激活蛋白激酶激酶5 (MAP2K5) 的差异激活.
结论:
- 与脂质代谢相关的代谢物有效地区分轻度和中度/重度的COVID-19.
- MAP2K5途径为严重的COVID-19提供了潜在的治疗标.
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