Division of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD 20850, USA.
Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Int J Mol Sci. 2023 Dec 26;25(1):346. doi: 10.3390/ijms25010346.
Understanding the molecular underpinnings of disease severity and progression in human studies is necessary to develop metabolism-related preventative strategies for severe COVID-19. Metabolites and metabolic pathways that predispose individuals to severe disease are not well understood. In this study, we generated comprehensive plasma metabolomic profiles in >550 patients from the Longitudinal EMR and Omics COVID-19 Cohort. Samples were collected before ( = 441), during ( = 86), and after ( = 82) COVID-19 diagnosis, representing 555 distinct patients, most of which had single timepoints. Regression models adjusted for demographics, risk factors, and comorbidities, were used to determine metabolites associated with predisposition to and/or persistent effects of COVID-19 severity, and metabolite changes that were transient/lingering over the disease course. Sphingolipids/phospholipids were negatively associated with severity and exhibited lingering elevations after disease, while modified nucleotides were positively associated with severity and had lingering decreases after disease. Cytidine and uridine metabolites, which were positively and negatively associated with COVID-19 severity, respectively, were acutely elevated, reflecting the particular importance of pyrimidine metabolism in active COVID-19. This is the first large metabolomics study using COVID-19 plasma samples before, during, and/or after disease. Our results lay the groundwork for identifying putative biomarkers and preventive strategies for severe COVID-19.
了解人类研究中疾病严重程度和进展的分子基础对于开发与代谢相关的严重 COVID-19 预防策略是必要的。导致个体易患严重疾病的代谢物和代谢途径尚不清楚。在这项研究中,我们在来自纵向电子病历和组学 COVID-19 队列的 >550 名患者中生成了全面的血浆代谢组学图谱。样本在 COVID-19 诊断之前(=441)、期间(=86)和之后(=82)采集,代表了 555 个不同的患者,其中大多数只有一个时间点。调整了人口统计学、风险因素和合并症的回归模型用于确定与 COVID-19 严重程度的易感性和/或持续性相关的代谢物,以及在疾病过程中是短暂/持续存在的代谢物变化。鞘脂/磷脂与严重程度呈负相关,并在疾病后持续升高,而修饰核苷酸与严重程度呈正相关,并在疾病后持续降低。与 COVID-19 严重程度分别呈正相关和负相关的胞苷和尿苷代谢物急性升高,反映了嘧啶代谢在活动性 COVID-19 中的特殊重要性。这是第一个使用 COVID-19 血浆样本在疾病之前、期间和/或之后进行的大型代谢组学研究。我们的结果为确定严重 COVID-19 的潜在生物标志物和预防策略奠定了基础。