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المؤلفAbdallah, Abdallah Musa
المؤلفDoudin, Asmma
المؤلفSulaiman, Theeb Osama
المؤلفJamil, Omar
المؤلفArif, Rida
المؤلفSada, Fatima Al
المؤلفYassine, Hadi M.
المؤلفElrayess, Mohamed A.
المؤلفElzouki, Abdel Naser
المؤلفEmara, Mohamed M.
المؤلفThillaiappan, Nagendra Babu
المؤلفCyprian, Farhan S.
تاريخ الإتاحة2024-08-15T07:49:28Z
تاريخ النشر2024-01-01
اسم المنشورFrontiers in Immunology
المعرّفhttp://dx.doi.org/10.3389/fimmu.2024.1353903
الاقتباسAbdallah, A. M., Doudin, A., Sulaiman, T. O., Jamil, O., Arif, R., Sada, F. A., ... & Cyprian, F. S. (2024). Metabolic predictors of COVID-19 mortality and severity: A Survival Analysis. Frontiers in Immunology, 15, 1353903.‏
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85193968992&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/57751
الملخصIntroduction: The global healthcare burden of COVID-19 pandemic has been unprecedented with a high mortality. Metabolomics, a powerful technique, has been increasingly utilized to study the host response to infections and to understand the progression of multi-system disorders such as COVID-19. Analysis of the host metabolites in response to SARS-CoV-2 infection can provide a snapshot of the endogenous metabolic landscape of the host and its role in shaping the interaction with SARS-CoV-2. Disease severity and consequently the clinical outcomes may be associated with a metabolic imbalance related to amino acids, lipids, and energy-generating pathways. Hence, the host metabolome can help predict potential clinical risks and outcomes. Methods: In this prospective study, using a targeted metabolomics approach, we studied the metabolic signature in 154 COVID-19 patients (males=138, age range 48-69 yrs) and related it to disease severity and mortality. Blood plasma concentrations of metabolites were quantified through LC-MS using MxP Quant 500 kit, which has a coverage of 630 metabolites from 26 biochemical classes including distinct classes of lipids and small organic molecules. We then employed Kaplan-Meier survival analysis to investigate the correlation between various metabolic markers, disease severity and patient outcomes. Results: A comparison of survival outcomes between individuals with high levels of various metabolites (amino acids, tryptophan, kynurenine, serotonin, creatine, SDMA, ADMA, 1-MH and carnitine palmitoyltransferase 1 and 2 enzymes) and those with low levels revealed statistically significant differences in survival outcomes. We further used four key metabolic markers (tryptophan, kynurenine, asymmetric dimethylarginine, and 1-Methylhistidine) to develop a COVID-19 mortality risk model through the application of multiple machine-learning methods. Conclusions: Metabolomics analysis revealed distinct metabolic signatures among different severity groups, reflecting discernible alterations in amino acid levels and perturbations in tryptophan metabolism. Notably, critical patients exhibited higher levels of short chain acylcarnitines, concomitant with higher concentrations of SDMA, ADMA, and 1-MH in severe cases and non-survivors. Conversely, levels of 3-methylhistidine were lower in this context.
اللغةen
الناشرFrontiers Media SA
الموضوعbiomarkers
COVID-19
critical
metabolites
mortality
severe
العنوانMetabolic predictors of COVID-19 mortality and severity: a survival analysis
النوعArticle
رقم المجلد15
dc.accessType Open Access


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