Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19

López‐Hernández, Yamilé; Monárrez‐Espino, Joel; Oostdam, Ana Sofía Herrera van; Castañeda-Delgado, Julio Enrique; Zhang, Lun; Zheng, Jiamin; Oropeza-Valdez, Juan José; Mandal, Rupasri; González, Fátima de Lourdes Ochoa; Moreno, Juan Carlos Borrego; Trejo-Medinilla, Flor M.; López, Jesús Adrián; Moreno, José María Villagrán; Wishart, David S.

doi:10.1038/s41598-021-94171-y

Cited by 48 publications

(61 citation statements)

References 43 publications

(44 reference statements)

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“…4d). Physiologically these findings have been previously shown to correlate with increased viral titer and increased fatty acid oxidation (Doğan et al, 2021;Kimhofer et al, 2020;López-Hernández et al, 2021;Overmyer et al, 2021;Roberts et al, 2022;Thomas et al, 2020).…”

Section: Discussionmentioning

confidence: 79%

Leveraging metabolic modeling to identify functional metabolic alterations associated with COVID-19 disease severity

et al. 2022

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Objective Since the COVID-19 pandemic began in early 2020, SARS-CoV2 has claimed more than six million lives world-wide, with over 510 million cases to date. To reduce healthcare burden, we must investigate how to prevent non-acute disease from progressing to severe infection requiring hospitalization. Methods To achieve this goal, we investigated metabolic signatures of both non-acute (out-patient) and severe (requiring hospitalization) COVID-19 samples by profiling the associated plasma metabolomes of 84 COVID-19 positive University of Virginia hospital patients. We utilized supervised and unsupervised machine learning and metabolic modeling approaches to identify key metabolic drivers that are predictive of COVID-19 disease severity. Using metabolic pathway enrichment analysis, we explored potential metabolic mechanisms that link these markers to disease progression. Results Enriched metabolites associated with tryptophan in non-acute COVID-19 samples suggest mitigated innate immune system inflammatory response and immunopathology related lung damage prevention. Increased prevalence of histidine- and ketone-related metabolism in severe COVID-19 samples offers potential mechanistic insight to musculoskeletal degeneration-induced muscular weakness and host metabolism that has been hijacked by SARS-CoV2 infection to increase viral replication and invasion. Conclusions Our findings highlight the metabolic transition from an innate immune response coupled with inflammatory pathway inhibition in non-acute infection to rampant inflammation and associated metabolic systemic dysfunction in severe COVID-19.

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Section: Discussionmentioning

confidence: 79%

Leveraging metabolic modeling to identify functional metabolic alterations associated with COVID-19 disease severity

et al. 2022

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“…Yamilé López-Hernández et al. identified 3 metabolites combinations that can discriminate between COVID-19 patients and HC, with an AUC of 0.947 ( 21 ). Song JW et al.…”

Section: Discussionmentioning

confidence: 99%

Metabolite profile of COVID-19 revealed by UPLC-MS/MS-based widely targeted metabolomics

Li²,

et al. 2022

Front. Immunol.

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The metabolic characteristics of COVID-19 disease are still largely unknown. Here, 44 patients with COVID-19 (31 mild COVID-19 patients and 13 severe COVID-19 patients), 42 healthy controls (HC), and 42 patients with community-acquired pneumonia (CAP), were involved in the study to assess their serum metabolomic profiles. We used widely targeted metabolomics based on an ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS). The differentially expressed metabolites in the plasma of mild and severe COVID-19 patients, CAP patients, and HC subjects were screened, and the main metabolic pathways involved were analyzed. Multiple mature machine learning algorithms confirmed that the metabolites performed excellently in discriminating COVID-19 groups from CAP and HC subjects, with an area under the curve (AUC) of 1. The specific dysregulation of AMP, dGMP, sn-glycero-3-phosphocholine, and carnitine was observed in the severe COVID-19 group. Moreover, random forest analysis suggested that these metabolites could discriminate between severe COVID-19 patients and mild COVID-19 patients, with an AUC of 0.921. This study may broaden our understanding of pathophysiological mechanisms of COVID-19 and may offer an experimental basis for developing novel treatment strategies against it.

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“…The investigations of the immune-metabolic signature also found signs of an activated TRP degradation pathway (TRP → Formyl-KYN → KYN) [ 35 , 37 ]. This pathway is determined by the enzymatic activity of indoleamine 2,3-dioxygenase 1 (IDO1), a pleotropic enzyme with immunoregulatory effects.…”

Section: Discussionmentioning

confidence: 99%

Increased Kynurenine Indicates a Fatal Course of COVID-19

et al. 2021

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(1) Background: An inefficient immune response accompanied by an overwhelming inflammatory reaction is involved in severe courses of COVID-19. Kynurenine (KYN) has important immune-modulatory functions and may contribute to a failure in controlling SARS-CoV-2. The present study aims to explore biomarkers that hint at a fatal outcome of COVID-19 early on. (2) Methods: We established a cohort of 148 hospitalized COVID-19 patients for this study. Thirty-one patients died due to a severe COVID-19 course, and 117 recovered within 90 days. We built a biobank by collecting left-over material from these patients whenever blood arrived at the central laboratory of our University hospital for analysis of routine markers. The scientific laboratory analysis comprised KYN, Tryptophan (TRP), KYN/TRP ratio, ferritin, interleukin-6 (IL-6), C-reactive protein (CRP), creatinine, N-terminal pro-natriuretic peptide (NTproBNP), troponin T (TnT), fibrinogen, D-Dimer, prothrombin time (PT), activated partial thromboplastin time (aPTT), antithrombin (AT), protein C, protein S, factor XIII, lupus aPTT, angiotensin-2, vitamin D metabolites, and telomeres in all COVID-19 patients. Basic clinical characteristics and anteceding diseases including cardiovascular, oncologic, renal, hypertension, pulmonary, metabolic (diabetes, obesity) were recorded in a database together with the laboratory data. (3) Results: At the time of diagnosis of SARS-CoV-2 infection those patients who deceased within 90 days afterwards due to COVID-19, had a significantly higher age, higher KYN, KYN/TRP ratio, ferritin, creatinine, and NTproBNP values than SARS-CoV-2 patients who survived COVID-19 along the same time span. In a Kaplan-Meier analysis the variables age, KYN, ferritin, D-Dimer, TnT, NTproBNP, and creatinine showed a significant influence on survival time. Gender, however, showed no influence. In a combined Cox regression analysis KYN had the highest hazard ratio (1.188, 95% CI: 1.071–1.319) followed by age (1.041, 95% CI: 1.011–1.073). In a ROC analysis, KYN values above the cut off limit of 4.82 nmol/l (as specified by Youden index) had a sensitivity of 82% (95% CI: 66–95%) and a specificity of 72% (95% CI: 65–82%) to predict COVID-19 related death within 90 days observation time. (4) Conclusions: Kynurenine is a promising blood biomarker to predict an increased risk of mortality in SARS-CoV-2 infected people already at the time of the first positive SARS-CoV-2 verification detected in these persons.

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Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19

Cited by 48 publications

References 43 publications

Leveraging metabolic modeling to identify functional metabolic alterations associated with COVID-19 disease severity

Leveraging metabolic modeling to identify functional metabolic alterations associated with COVID-19 disease severity

Metabolite profile of COVID-19 revealed by UPLC-MS/MS-based widely targeted metabolomics

Increased Kynurenine Indicates a Fatal Course of COVID-19

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