Department of Laboratory Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China.
Princeton High School, Princeton, NJ 08540, USA.
Future Microbiol. 2021 May;16:577-588. doi: 10.2217/fmb-2021-0047. Epub 2021 May 11.
To understand the pathological progress of COVID-19 and to explore the potential biomarkers. The COVID-19 pandemic is ongoing. There is metabolomics research about COVID-19 indicating the rich information of metabolomics is worthy of further data mining. We applied bioinformatics technology to reanalyze the published metabolomics data of COVID-19. Benzoate, β-alanine and 4-chlorobenzoic acid were first reported to be used as potential biomarkers to distinguish COVID-19 patients from healthy individuals; taurochenodeoxycholic acid 3-sulfate, glucuronate and N,N,N-trimethyl-alanylproline betaine TMAP are the top classifiers in the receiver operating characteristic curve of COVID-severe and COVID-nonsevere patients. These unique metabolites suggest an underlying immunoregulatory treatment strategy for COVID-19.
为了了解 COVID-19 的病理进展并探索潜在的生物标志物。 COVID-19 大流行仍在继续。有关于 COVID-19 的代谢组学研究表明,代谢组学的丰富信息值得进一步挖掘数据。我们应用生物信息学技术重新分析了已发表的 COVID-19 代谢组学数据。首次报道苯甲酸、β-丙氨酸和 4-氯苯甲酸可用作潜在的生物标志物,将 COVID-19 患者与健康个体区分开来;牛磺胆酸 3-硫酸盐、葡萄糖醛酸和 N,N,N-三甲基丙氨酸脯氨酸甜菜碱 TMAP 是 COVID-重型和 COVID-非重型患者接受者操作特征曲线的顶级分类器。这些独特的代谢物表明 COVID-19 存在潜在的免疫调节治疗策略。