COVID-19: A complex disease with a unique metabolic signature.

Plasma of COVID-19 patients contains a strong metabolomic/lipoproteomic signature, revealed by the NMR analysis of a cohort of >500 patients sampled during various waves of COVID-19 infection, corresponding to the spread of different variants, and having different vaccination status. This composite signature highlights common traits of the SARS-CoV-2 infection. The most dysregulated molecules display concentration trends that scale with disease severity and might serve as prognostic markers for fatal events. Metabolomics evidence is then used as input data for a sex-specific multi-organ metabolic model. This reconstruction provides a comprehensive view of the impact of COVID-19 on the entire human metabolism. The human (male and female) metabolic network is strongly impacted by the disease to an extent dictated by its severity. A marked metabolic reprogramming at the level of many organs indicates an increase in the generic energetic demand of the organism following infection. Sex-specific modulation of immune response is also suggested.

Profiling metabolites and lipoproteins in COMETA, an Italian cohort of COVID-19 patients.

Metabolomics and lipidomics have been used in several studies to define the biochemical alterations induced by COVID-19 in comparison with healthy controls. Those studies highlighted the presence of a strong signature, attributable to both metabolites and lipoproteins/lipids. Here, 1H NMR spectra were acquired on EDTA-plasma from three groups of subjects: i) hospitalized COVID-19 positive patients (≤21 days from the first positive nasopharyngeal swab); ii) hospitalized COVID-19 positive patients (>21 days from the first positive nasopharyngeal swab); iii) subjects after 2-6 months from SARS-CoV-2 eradication. A Random Forest model built using the EDTA-plasma spectra of COVID-19 patients ≤21 days and Post COVID-19 subjects, provided a high discrimination accuracy (93.6%), indicating both the presence of a strong fingerprint of the acute infection and the substantial metabolic healing of Post COVID-19 subjects. The differences originate from significant alterations in the concentrations of 16 metabolites and 74 lipoprotein components. The model was then used to predict the spectra of COVID-19>21 days subjects. In this group, the metabolite levels are closer to those of the Post COVID-19 subjects than to those of the COVID-19≤21 days; the opposite occurs for the lipoproteins. Within the acute phase patients, characteristic trends in metabolite levels are observed as a function of the disease severity. The metabolites found altered in COVID-19≤21 days patients with respect to Post COVID-19 individuals overlap with acute infection biomarkers identified previously in comparison with healthy subjects. Along the trajectory towards healing, the metabolome reverts back to the "healthy" state faster than the lipoproteome.

Delirium and IL-6 added to clinical scores improves their performance: a prospective analysis of CALL, PREDI-CO, MRS score applied to a population of patients admitted to internal medicine ward.

This study aimed to evaluate the effectiveness of various scoring systems in predicting in-hospital mortality for COVID-19 patients admitted to the internal medicine ward. We conducted a prospective collection of clinical data from patients admitted to the Internal Medicine Unit at Santa Maria Nuova Hospital in Florence, Italy, with confirmed pneumonia caused by SARS-CoV-2. We calculated three scoring systems: the CALL score, the PREDI-CO score, and the COVID-19 in-hospital Mortality Risk Score (COVID-19 MRS). The primary endpoint was in-hospital mortality. : A total of 681 patients were enrolled in the study, with a mean age of 68.8 ± 16.1 years, and 54.8% of them were male. Non-survivors had significantly higher scores in all prognostic systems compared to survivors (MRS: 13 [12- 15] vs. 10 [8-12]; CALL: 12 [10-12] vs. 9 [7-11]; PREDI-CO: 4 [3-6] vs. 2 [1-4]; all p<0.001). The receiver operating characteristic (ROC) analysis yielded the following area under the curve (AUC) values: MRS 0.85, CALL 0.78, PREDI-CO 0.77. The addition of Delirium and IL6 to the scoring systems improved their discriminative ability, resulting in AUC values of 0.92 for MRS, 0.87 for CALL, and 0.84 for PREDI-CO. The mortality rate increased significantly across increasing quartiles (p<0.001). In conclusion the COVID-19 in-hospital Mortality Risk Score (MRS) demonstrated reasonable prognostic stratification for patients admitted to the internal medicine ward with SARS-CoV-2-induced pneumonia. The inclusion of Delirium and IL6 as additional prognostic indicators in the scoring systems enhanced their predictive performance, specifically in determining in-hospital mortality among COVID-19 patients.