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Open accessJournal ArticleDOI: 10.1016/J.METABOL.2021.154739

The serum metabolome of COVID-19 patients is distinctive and predictive.

02 Mar 2021-Metabolism-clinical and Experimental (W.B. Saunders)-Vol. 118, pp 154739-154739
Abstract: Background Metabolism is critical for sustaining life, immunity and infection, but its role in COVID-19 is not fully understood. Methods Seventy-nine COVID-19 patients, 78 healthy controls (HCs) and 30 COVID-19-like patients were recruited in a prospective cohort study. Samples were collected from COVID-19 patients with mild or severe symptoms on admission, patients who progressed from mild to severe symptoms, and patients who were followed from hospital admission to discharge. The metabolome was assayed using gas chromatography–mass spectrometry. Results Serum butyric acid, 2-hydroxybutyric acid, l -glutamic acid, l -phenylalanine, l -serine, l -lactic acid, and cholesterol were enriched in COVID-19 and COVID-19-like patients versus HCs. Notably, d -fructose and succinic acid were enriched, and citric acid and 2-palmitoyl-glycerol were depleted in COVID-19 patients compared to COVID-19-like patients and HCs, and these four metabolites were not differentially distributed in non-COVID-19 groups. COVID-19 patients had enriched 4-deoxythreonic acid and depleted 1,5-anhydroglucitol compared to HCs and enriched oxalic acid and depleted phosphoric acid compared to COVID-19-like patients. A combination of d -fructose, citric acid and 2-palmitoyl-glycerol distinguished COVID-19 patients from HCs and COVID-19-like patients, with an area under the curve (AUC) > 0.92 after validation. The combination of 2-hydroxy-3-methylbutyric acid, 3-hydroxybutyric acid, cholesterol, succinic acid, L-ornithine, oleic acid and palmitelaidic acid predicted patients who progressed from mild to severe COVID-19, with an AUC of 0.969. After discharge, nearly one-third of metabolites were recovered in COVID-19 patients. Conclusions The serum metabolome of COVID-19 patients is distinctive and has important value in investigating pathogenesis, determining a diagnosis, predicting severe cases, and improving treatment.

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Topics: Succinic acid (53%), Lactic acid (51%), Metabolome (51%) ... show more
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17 results found


Journal ArticleDOI: 10.1515/CCLM-2021-0367
Mario Plebani1Institutions (1)
Abstract: The lockdown due to the coronavirus disease 2019 (COVID-19), a major healthcare challenge, is a worldwide threat to public health, social stability, and economic development. The pandemic has affected all aspects of society, dramatically changing our day-to-day lives and habits. It has also changed clinical practice, including practices of clinical laboratories. After one year, it is time to rethink what has happened, and is still happening, in order to learn lessons for the future of laboratory medicine and its professionals. While examining this issue, I was inspired by Italo Calvino's famous work, "Six memos for the next millennium".But I rearranged the Author's six memos into "Visibility, quickness, exactitude, multiplicity, lightness, consistency".

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5 Citations


Open accessJournal ArticleDOI: 10.1016/J.XCRM.2021.100369
21 Jul 2021-
Abstract: There is an urgent need to identify which COVID-19 patients will develop life-threatening illness so that medical resources can be optimally allocated and rapid treatment can be administered early in the disease course, when clinical management is most effective. To aid in the prognostic classification of disease severity, we perform untargeted metabolomics on plasma from 339 patients, with samples collected at six longitudinal time points. Using the temporal metabolic profiles and machine learning, we build a predictive model of disease severity. We discover that a panel of metabolites measured at the time of study entry successfully determine disease severity. Through analysis of longitudinal samples, we confirm that the majority of these markers are directly related to disease progression and that their levels return to baseline upon disease recovery. Finally, we validate that these metabolites are also altered in a hamster model of COVID-19.

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Topics: Biomarker (cell) (52%)

4 Citations


Open accessJournal ArticleDOI: 10.1371/JOURNAL.PONE.0256784
30 Aug 2021-PLOS ONE
Abstract: Viral sepsis has been proposed as an accurate term to describe all multisystemic dysregulations and clinical findings in severe and critically ill COVID-19 patients. The adoption of this term may help the implementation of more accurate strategies of early diagnosis, prognosis, and in-hospital treatment. We accurately quantified 110 metabolites using targeted metabolomics, and 13 cytokines/chemokines in plasma samples of 121 COVID-19 patients with different levels of severity, and 37 non-COVID-19 individuals. Analyses revealed an integrated host-dependent dysregulation of inflammatory cytokines, neutrophil activation chemokines, glycolysis, mitochondrial metabolism, amino acid metabolism, polyamine synthesis, and lipid metabolism typical of sepsis processes distinctive of a mild disease. Dysregulated metabolites and cytokines/chemokines showed differential correlation patterns in mild and critically ill patients, indicating a crosstalk between metabolism and hyperinflammation. Using multivariate analysis, powerful models for diagnosis and prognosis of COVID-19 induced sepsis were generated, as well as for mortality prediction among septic patients. A metabolite panel made of kynurenine/tryptophan ratio, IL-6, LysoPC a C18:2, and phenylalanine discriminated non-COVID-19 from sepsis patients with an area under the curve (AUC (95%CI)) of 0.991 (0.986-0.995), with sensitivity of 0.978 (0.963-0.992) and specificity of 0.920 (0.890-0.949). The panel that included C10:2, IL-6, NLR, and C5 discriminated mild patients from sepsis patients with an AUC (95%CI) of 0.965 (0.952-0.977), with sensitivity of 0.993(0.984-1.000) and specificity of 0.851 (0.815-0.887). The panel with citric acid, LysoPC a C28:1, neutrophil-lymphocyte ratio (NLR) and kynurenine/tryptophan ratio discriminated severe patients from sepsis patients with an AUC (95%CI) of 0.829 (0.800-0.858), with sensitivity of 0.738 (0.695-0.781) and specificity of 0.781 (0.735-0.827). Septic patients who survived were different from those that did not survive with a model consisting of hippuric acid, along with the presence of Type II diabetes, with an AUC (95%CI) of 0.831 (0.788-0.874), with sensitivity of 0.765 (0.697-0.832) and specificity of 0.817 (0.770-0.865).

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Topics: Sepsis (54%), Kynurenine (51%)

2 Citations


Open accessJournal ArticleDOI: 10.3389/FGENE.2021.721556
Abstract: Coronavirus disease 2019 (COVID-19) pandemic triggered an unprecedented global effort in developing rapid and inexpensive diagnostic and prognostic tools. Since the genome of SARS-CoV-2 was uncovered, detection of viral RNA by RT-qPCR has played the most significant role in preventing the spread of the virus through early detection and tracing of suspected COVID-19 cases and through screening of at-risk population. However, a large number of alternative test methods based on SARS-CoV-2 RNA or proteins or host factors associated with SARS-CoV-2 infection have been developed and evaluated. The application of metabolomics in infectious disease diagnostics is an evolving area of science that was boosted by the urgency of COVID-19 pandemic. Metabolomics approaches that rely on the analysis of volatile organic compounds exhaled by COVID-19 patients hold promise for applications in a large-scale screening of population in point-of-care (POC) setting. On the other hand, successful application of mass-spectrometry to detect specific spectral signatures associated with COVID-19 in nasopharyngeal swab specimens may significantly save the cost and turnaround time of COVID-19 testing in the diagnostic microbiology and virology laboratories. Active research is also ongoing on the discovery of potential metabolomics-based prognostic markers for the disease that can be applied to serum or plasma specimens. Several metabolic pathways related to amino acid, lipid and energy metabolism were found to be affected by severe disease with COVID-19. In particular, tryptophan metabolism via the kynurenine pathway were persistently dysregulated in several independent studies, suggesting the roles of several metabolites of this pathway such as tryptophan, kynurenine and 3-hydroxykynurenine as potential prognostic markers of the disease. However, standardization of the test methods and large-scale clinical validation are necessary before these tests can be applied in a clinical setting. With rapidly expanding data on the metabolic profiles of COVID-19 patients with varying degrees of severity, it is likely that metabolomics will play an important role in near future in predicting the outcome of the disease with a greater degree of certainty.

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Topics: Population (53%), Kynurenine pathway (50%)

2 Citations


Open accessJournal ArticleDOI: 10.1016/J.CLNESP.2021.06.011
Abstract: COVID-19 has re-established the significance of analyzing the organism through a metabolic perspective to uncover the dynamic interconnections within the biological systems. The role of micronutrient status and metabolic health emerge as pivotal in COVID-19 pathogenesis and the immune system's response. Metabolic disruption, proceeding from modifiable factors, has been proposed as a significant risk factor accounting for infection susceptibility, disease severity and risk for post-COVID complications. Metabolomics, the comprehensive study and quantification of intermediates and products of metabolism, is a rapidly evolving field and a novel tool in biomarker discovery. In this article, we propose that leveraging insulin resistance biomarkers along with biomarkers of micronutrient deficiencies, will allow for a diagnostic window and provide functional therapeutic targets. Specifically, metabolomics can be applied as: a. At-home test to assess the risk of infection and propose nutritional support, b. A screening tool for high-risk COVID-19 patients to develop serious illness during hospital admission and prioritize medical support, c(i). A tool to match nutritional support with specific nutrient requirements for mildly ill patients to reduce the risk for hospitalization, and c(ii). for critically ill patients to reduce recovery time and risk of post-COVID complications, d. At-home test to monitor metabolic health and reduce post-COVID symptomatology. Metabolic rewiring offers potential virtues towards disease prevention, dissection of high-risk patients, taking actionable therapeutic measures, as well as shielding against post-COVID syndrome.

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Topics: Risk assessment (53%)

1 Citations


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43 results found


Open accessJournal ArticleDOI: 10.1016/S0140-6736(20)30183-5
Chaolin Huang1, Yeming Wang2, Xingwang Li3, Lili Ren4  +25 moreInstitutions (8)
24 Jan 2020-The Lancet
Abstract: A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not.

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26,390 Citations


Open accessJournal ArticleDOI: 10.1056/NEJMOA2001316
Qun Li1, Xuhua Guan1, Peng Wu2, Xiaoye Wang1  +43 moreInstitutions (6)
Abstract: Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the...

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Topics: Coronavirus (54%)

10,234 Citations


Open accessJournal ArticleDOI: 10.1016/J.CELL.2020.02.052
16 Apr 2020-Cell
Abstract: The recent emergence of the novel, pathogenic SARS-coronavirus 2 (SARS-CoV-2) in China and its rapid national and international spread pose a global health emergency. Cell entry of coronaviruses depends on binding of the viral spike (S) proteins to cellular receptors and on S protein priming by host cell proteases. Unravelling which cellular factors are used by SARS-CoV-2 for entry might provide insights into viral transmission and reveal therapeutic targets. Here, we demonstrate that SARS-CoV-2 uses the SARS-CoV receptor ACE2 for entry and the serine protease TMPRSS2 for S protein priming. A TMPRSS2 inhibitor approved for clinical use blocked entry and might constitute a treatment option. Finally, we show that the sera from convalescent SARS patients cross-neutralized SARS-2-S-driven entry. Our results reveal important commonalities between SARS-CoV-2 and SARS-CoV infection and identify a potential target for antiviral intervention.

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Topics: Proteases (52%)

10,193 Citations


Open accessJournal ArticleDOI: 10.1126/SCIENCE.ABA9757
Matteo Chinazzi1, Jessica T. Davis1, Marco Ajelli2, Corrado Gioannini3  +14 moreInstitutions (8)
06 Mar 2020-Science
Abstract: Motivated by the rapid spread of coronavirus disease 2019 (COVID-19) in mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated on the basis of internationally reported cases and shows that, at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in mainland China but had a more marked effect on the international scale, where case importations were reduced by nearly 80% until mid-February. Modeling results also indicate that sustained 90% travel restrictions to and from mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.

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Topics: Mainland China (53%)

2,084 Citations


Open accessJournal ArticleDOI: 10.1093/CID/CIAA344
Juanjuan Zhao, Quan Yuan1, Haiyan Wang, Wei Liu1  +21 moreInstitutions (2)
Abstract: BACKGROUND: The novel coronavirus SARS-CoV-2 is a newly emerging virus. The antibody response in infected patients remains largely unknown, and the clinical value of antibody testing has not been fully demonstrated. METHODS: 173 patients with SARS-CoV-2 infection were enrolled. Their serial plasma samples (n = 535) collected during hospitalization were tested for total antibodies (Ab), IgM, and IgG against SARS-CoV-2. The dynamics of antibodies with disease progress were analyzed. RESULTS: Among 173 patients, the seroconversion rates for Ab, IgM, and IgG were 93.1%, 82.7%, and 64.7%, respectively. The reason for the negative antibody findings in 12 patients might be due to the lack of blood samples at the later stage of illness. The median seroconversion times for Ab, IgM, and then IgG were days 11, 12, and 4, respectively. The presence of antibodies was <40% among patients within 1 week of onset, and rapidly increased to 100.0% (Ab), 94.3% (IgM), and 79.8% (IgG) by day 15 after onset. In contrast, RNA detectability decreased from 66.7% (58/87) in samples collected before day 7 to 45.5% (25/55) during days 15-39. Combining RNA and antibody detection significantly improved the sensitivity of pathogenic diagnosis for COVID-19 (P < .001), even in the early phase of 1 week from onset (P = .007). Moreover, a higher titer of Ab was independently associated with a worse clinical classification (P = .006). CONCLUSIONS: Antibody detection offers vital clinical information during the course of SARS-CoV-2 infection. The findings provide strong empirical support for the routine application of serological testing in the diagnosis and management of COVID-19 patients.

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Topics: Seroconversion (62%), Immunoglobulin M (60%), Immunoglobulin G (53%) ... show more

1,829 Citations


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