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Usefulness of fibrosis-4 (FIB-4) score and metabolic alterations in the prediction of SARS-CoV-2 severity.

ABSTRACT: Despite vaccination programs, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains a public health problem. Identifying key prognostic determinants of severity of the disease may help better focus health resources. The negative prognostic role for metabolic and hepatic alterations is established; however, the interplay among different metabolic comorbidities and their interconnections with the liver have never been explored.The objective of this study is to evaluate the impact of liver alterations in addition to metabolic comorbidities as a predictor of SARS-CoV-2 severity. 382 SARS-CoV-2 patients were enrolled. Severe SARS-CoV-2 was diagnosed according to international consensus. Transaminases > 2 times the upper limit of normality (2ULN), hepatic steatosis (by ultrasound and/or computed tomography in 133 patients), and FIB-4 defined liver alterations. All data were collected on admission. The results are severe SARS-CoV-2 infection in 156 (41%) patients (mean age 65 ± 17; 60%males). Prevalence of obesity was 25%; diabetes, 17%; hypertension, 44%; dyslipidaemia, 29%; with 13% of the cohort with ≥ 3 metabolic alterations. Seventy patients (18%) had transaminases > 2ULN, 82 (62%) steatosis; 199 (54%) had FIB-4 < 1.45 and 45 (12%) > 3.25. At multivariable analysis, ≥ 3 metabolic comorbidities (OR 4.1, CI 95% 1.8-9.1) and transaminases > 2ULN (OR 2.6, CI 95% 1.3-6.7) were independently associated with severe SARS-CoV-2. FIB-4 < 1.45 was a protective factor (OR 0.42, CI 95% 0.23-0.76). Hepatic steatosis had no impact on disease course. The presence of metabolic alterations is associated with severe SARS-CoV-2 infection, and the higher the number of coexisting comorbidities, the higher the risk of severe disease. Normal FIB-4 values are inversely associated with advanced SARS-CoV-2 regardless of metabolic comorbidities, speculating on use of these values to stratify the risk of severe infection.

SUBMITTER: Rosa L

PROVIDER: S-EPMC9244481 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.

Project description:Background Coronavirus disease 2019 is a type of acute infectious pneumonia and frequently confused with influenza since the initial symptoms. When the virus colonized the patient's mouth, it will cause changes of the oral microenvironment. However, few studies on the alterations of metabolism of the oral microenvironment affected by SARS-CoV-2 infection have been reported. In this study, we explored metabolic alterations of oral microenvironment after SARS-CoV-2 infection. Methods Untargeted metabolomics (UPLC-MS) was used to investigate the metabolic changes between oral secretion samples of 25 COVID-19 and 30 control participants. To obtain the specific metabolic changes of COVID-19, we selected 25 influenza patients to exclude the metabolic changes caused by the stress response of the immune system to the virus. Multivariate analysis (PCA and PLS-DA plots) and univariate analysis (students’ t-test) were used to compare the differences between COVID-19 patients and the controls. Online hiplot tool was used to perform heatmap analysis. Metabolic pathway analysis was conducted by using the MetaboAnalyst 5.0 web application. Results PLS-DA plots showed significant separation of COVID-19 patients and the controls. A total of 45 differential metabolites between COVID-19 and control group were identified. Among them, 35 metabolites were defined as SARS-CoV-2 specific differential metabolites. Especially, the levels of cis-5,8,11,14,17-eicosapentaenoic acid and hexanoic acid changed dramatically based on the FC values. Pathway enrichment found the most significant pathways were tyrosine-related metabolism. Further, we found 10 differential metabolites caused by the virus indicating the body’s metabolism changes after viral stimulation. Moreover, adenine and adenosine were defined as influenza virus-specific differential metabolites. Conclusions This study revealed that 35 metabolites and tyrosine-related metabolism pathways were significantly changed after SARS-CoV-2 infection. The metabolic alterations of oral microenvironment in COVID-19 provided new insights into its molecular mechanisms for research and prognostic treatment. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-022-07979-y.

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Usefulness of fibrosis-4 (FIB-4) score and metabolic alterations in the prediction of SARS-CoV-2 severity.

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