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

Shi, Ding; Ren, Yan; Lv, Longxian; Jiang, Huiyong; Lu, Yingfeng; Sheng, Jifang; Xie, Jiao-Jiao; Wu, Wenrui; Xia, Jiafeng; Xu, Kaijin; Gu, Silan; Chen, Yanfei; Huang, Chao; Guo, Jing; Du, Yi‐Ling; Li, Lanjuan

doi:10.1016/j.metabol.2021.154739

Cited by 103 publications

(118 citation statements)

References 44 publications

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“…Previous studies revealed that COVID-19 patients during the infection period had metabolic abnormalities in TCA cycle, purine and lipid metabolism. [11][12][13][14]19 In our study, we found that these pathways remained disturbed in the recovered COVID-19 patients 3 months after discharge when compared with HCs, especially in the RCs, which suggests that metabolic abnormalities in COVID-19 patients failed to fully return to normal levels even 3 months after discharge from the hospital.…”

Section: Discussionmentioning

confidence: 56%

“…10 Recent studies have revealed that metabolic dysregulation in COVID-19 patients and metabolites may help stratify patients in terms of disease severity during hospitalisation. [11][12][13][14][15][16][17] Moreover, it has been reported that after discharge, only one-third of the metabolites were recovered, 14 and some metabolites continued to be abnormal in recovered COVID-19 patients. 18,19 In addition, we recently found that discharged patients with pulmonary sequelae also had disordered plasma metabolite profiles.…”

Section: Introductionmentioning

confidence: 99%

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Plasma Metabolomic Profiles in Recovered COVID-19 Patients without Previous Underlying Diseases 3 Months After Discharge

Zhang¹,

Luo²,

Xu³

et al. 2021

JIR

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Background: It remains unclear whether discharged COVID-19 patients have fully recovered from severe complications, including the differences in the post-infection metabolomic profiles of patients with different disease severities. Methods: COVID-19-recovered patients, who had no previous underlying diseases and were discharged from Wuhan Union Hospital for 3 months, and matched healthy controls (HCs) were recruited in this prospective cohort study. We examined the blood biochemical indicators, cytokines, lung computed tomography scans, including 39 HCs, 18 recovered asymptomatic (RAs), 34 recovered moderate (RMs), and 44 recovered severe/ critical patients (RCs). A liquid chromatography-mass spectrometry-based metabolomics approach was employed to profile the global metabolites of fasting plasma of these participants. Results: Clinical data and metabolomic profiles suggested that RAs recovered well, but some clinical indicators and plasma metabolites in RMs and RCs were still abnormal as compared with HCs, such as decreased taurine, succinic acid, hippuric acid, some indoles, and lipid species. The disturbed metabolic pathway mainly involved the tricarboxylic cycle, purine, and glycerophospholipid metabolism. Moreover, metabolite alterations differ between RMs and RCs when compared with HCs. Correlation analysis revealed that many differential metabolites were closely associated with inflammation and the renal, pulmonary, heart, hepatic, and coagulation system functions. Conclusion:We uncovered metabolite clusters pathologically relevant to the recovery state in discharged COVID-19 patients which may provide new insights into the pathogenesis of potential organ damage in recovered patients.

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Section: Discussionmentioning

confidence: 56%

Section: Introductionmentioning

confidence: 99%

Plasma Metabolomic Profiles in Recovered COVID-19 Patients without Previous Underlying Diseases 3 Months After Discharge

Zhang¹,

Luo²,

Xu³

et al. 2021

JIR

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“…Other authors have also explored how the presence of these comorbidities influences the metabolomics differences found in COVID-19 patients concerning healthy controls and patients with different severity grades. Shi et al [ 83 ] compared the serum metabolome profiles of COVID-19 patients with and without comorbidities. The results showed that none of the groups of patients with hypertension, diabetes or fatty liver disease could be distinguished from patients without comorbidities.…”

Section: Discussionmentioning

confidence: 99%

Immunometabolic signatures predict risk of progression to sepsis in COVID-19

et al. 2021

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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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“…The metabolome was assayed as described previously ( 16 , 17 ). Briefly, 20 mg of feces or 200 μL of the serum was added to 800 μL of precooled chromatography grade methanol (Sigma-Aldrich, St. Louis, MO, USA).…”

Section: Methodsmentioning

confidence: 99%

Mechanism of the Immunomodulatory Effect of the Combination of Live Bifidobacterium, Lactobacillus, Enterococcus, and Bacillus on Immunocompromised Rats

et al. 2021

Front. Immunol.

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Immunodeficiency is a very common condition in suboptimal health status and during the development or treatment of many diseases. Recently, probiotics have become an important means for immune regulation. The present study aimed to investigate the mechanism of the immunomodulatory effect of a combination of live Bifidobacterium, Lactobacillus, Enterococcus, and Bacillus (CBLEB), which is a drug used by approximately 10 million patients every year, on cyclophosphamide-immunosuppressed rats. Cyclophosphamide (40 mg/kg) was intraperitoneally injected to induce immunosuppression in a rat model on days 1, 2, 3, and 10. Starting from day 4, the rats were continuously gavaged with CBLEB solution for 15 days. The samples were collected to determine routine blood test parameters, liver and kidney functions, serum cytokine levels, gut microbiota, fecal and serum metabolomes, transcriptomes, and histopathological features. The results indicated that CBLEB treatment reduced cyclophosphamide-induced death, weight loss, and damage to the gut, liver, spleen, and lungs and eliminated a cyclophosphamide-induced increase in the mean hemoglobin content and GGT, M-CSF, and MIP-3α levels and a decrease in the red blood cell distribution width and total protein and creatinine levels in the blood. Additionally, CBLEB corrected cyclophosphamide-induced dysbiosis of the gut microbiota and eliminated all cyclophosphamide-induced alterations at the phylum level in rat feces, including the enrichment in Proteobacteria, Fusobacteriota, and Actinobacteriota and depletion of Spirochaetota and Cyanobacteria. Furthermore, CBLEB treatment alleviated cyclophosphamide-induced alterations in the whole fecal metabolome profile, including enrichment in 1-heptadecanol, succinic acid, hexadecane-1,2-diol, nonadecanoic acid, and pentadecanoic acid and depletion of benzenepropanoic acid and hexane. CBLEB treatment also alleviated cyclophosphamide-induced enrichment in serum D-lyxose and depletion of serum succinic acid, D-galactose, L-5-oxoproline, L-alanine, and malic acid. The results of transcriptome analysis indicated that the mechanism of the effect of CBLEB was related to the induction of recovery of cyclophosphamide-altered carbohydrate metabolism and signal transduction. In conclusion, the present study provides an experimental basis and comprehensive analysis of application of CBLEB for the treatment of immunodeficiency.

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

Cited by 103 publications

References 44 publications

Plasma Metabolomic Profiles in Recovered COVID-19 Patients without Previous Underlying Diseases 3 Months After Discharge

Plasma Metabolomic Profiles in Recovered COVID-19 Patients without Previous Underlying Diseases 3 Months After Discharge

Immunometabolic signatures predict risk of progression to sepsis in COVID-19

Mechanism of the Immunomodulatory Effect of the Combination of Live Bifidobacterium, Lactobacillus, Enterococcus, and Bacillus on Immunocompromised Rats

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