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Omics-Driven Systems Interrogation of Metabolic Dysregulation in COVID-19 Pathogenesis.

ABSTRACT: The coronavirus disease 2019 (COVID-19) pandemic presents an unprecedented threat to global public health. Herein, we utilized a combination of targeted and untargeted tandem mass spectrometry to analyze the plasma lipidome and metabolome in mild, moderate, and severe COVID-19 patients and healthy controls. A panel of 10 plasma metabolites effectively distinguished COVID-19 patients from healthy controls (AUC = 0.975). Plasma lipidome of COVID-19 resembled that of monosialodihexosyl ganglioside (GM3)-enriched exosomes, with enhanced levels of sphingomyelins (SMs) and GM3s, and reduced diacylglycerols (DAGs). Systems evaluation of metabolic dysregulation in COVID-19 was performed using multiscale embedded differential correlation network analyses. Using exosomes isolated from the same cohort, we demonstrated that exosomes of COVID-19 patients with elevating disease severity were increasingly enriched in GM3s. Our work suggests that GM3-enriched exosomes may partake in pathological processes related to COVID-19 pathogenesis and presents the largest repository on the plasma lipidome and metabolome distinct to COVID-19.

SUBMITTER: Song JW

PROVIDER: S-EPMC7311890 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Omics-Driven Systems Interrogation of Metabolic Dysregulation in COVID-19 Pathogenesis.

Song Jin-Wen JW Lam Sin Man SM Fan Xing X Cao Wen-Jing WJ Wang Si-Yu SY Tian He H Chua Gek Huey GH Zhang Chao C Meng Fan-Ping FP Xu Zhe Z Fu Jun-Liang JL Huang Lei L Xia Peng P Yang Tao T Zhang Shaohua S Li Bowen B Jiang Tian-Jun TJ Wang Raoxu R Wang Zehua Z Shi Ming M Zhang Ji-Yuan JY Wang Fu-Sheng FS Shui Guanghou G

Cell metabolism 20200624 2

The coronavirus disease 2019 (COVID-19) pandemic presents an unprecedented threat to global public health. Herein, we utilized a combination of targeted and untargeted tandem mass spectrometry to analyze the plasma lipidome and metabolome in mild, moderate, and severe COVID-19 patients and healthy controls. A panel of 10 plasma metabolites effectively distinguished COVID-19 patients from healthy controls (AUC = 0.975). Plasma lipidome of COVID-19 resembled that of monosialodihexosyl ganglioside ...[more]

PMID: 32610096

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Project description:Background metabolic changes through SARS-CoV-2 infection has been reported but not fully comprehended. This metabolic dysregulation affects multiple organs during COVID-19 and its early detection can be used as a prognosis marker of severity. Therefore, we aimed to characterize metabolic and cytokine profile at COVID-19 onset and its relationship with disease severity to identify metabolic profiles predicting disease progression. Material and Methods we performed a retrospective cross-sectional study in 123 COVID-19 patients which were stratified as asymptomatic/mild, moderate and severe according to the highest COVID-19 severity status, and a group of healthy controls. We performed an untargeted plasma metabolic profiling (gas chromatography and capillary electrophoresis-mass spectrometry (GC and CE-MS)) and cytokine evaluation. Results After data filtering and identification we observed 105 metabolites dysregulated (66 GC-MS and 40 CE-MS) which shown different expression patterns for each COVID-19 severity status. These metabolites belonged to different metabolic pathways including amino acid, energy, and nitrogen metabolism among others. Severity-specific metabolic dysregulation was observed, as an increased transformation of L-tryptophan into L-kynurenine. Thus, metabolic profiling at hospital admission differentiate between severe and moderate patients in the later phase of worse evolution. Several plasma pro-inflammatory biomarkers showed significant correlation with deregulated metabolites, specially with L-kynurenine and L-tryptophan. Finally, we describe a strong sex-related dysregulation of metabolites, cytokines and chemokines between severe and moderate patients. In conclusion, metabolic profiling of COVID-19 patients at disease onset is a powerful tool to unravel the SARS-CoV-2 molecular pathogenesis. Conclusions This technique makes it possible to identify metabolic phenoconversion that predicts disease progression and explains the pronounced pathogenesis differences between sexes.

Dataset Information

Omics-Driven Systems Interrogation of Metabolic Dysregulation in COVID-19 Pathogenesis.

Publications

Omics-Driven Systems Interrogation of Metabolic Dysregulation in COVID-19 Pathogenesis.

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