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1.
Front Immunol ; 13: 912579, 2022.
Article in English | MEDLINE | ID: covidwho-2313484

ABSTRACT

Background: Coronavirus-19 (COVID-19) disease is driven by an unchecked immune response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus which alters host mitochondrial-associated mechanisms. Compromised mitochondrial health results in abnormal reprogramming of glucose metabolism, which can disrupt extracellular signalling. We hypothesized that examining mitochondrial energy-related signalling metabolites implicated in host immune response to SARS-CoV-2 infection would provide potential biomarkers for predicting the risk of severe COVID-19 illness. Methods: We used a semi-targeted serum metabolomics approach in 273 patients with different severity grades of COVID-19 recruited at the acute phase of the infection to determine the relative abundance of tricarboxylic acid (Krebs) cycle-related metabolites with known extracellular signaling properties (pyruvate, lactate, succinate and α-ketoglutarate). Abundance levels of energy-related metabolites were evaluated in a validation cohort (n=398) using quantitative fluorimetric assays. Results: Increased levels of four energy-related metabolites (pyruvate, lactate, a-ketoglutarate and succinate) were found in critically ill COVID-19 patients using semi-targeted and targeted approaches (p<0.05). The combined strategy proposed herein enabled us to establish that circulating pyruvate levels (p<0.001) together with body mass index (p=0.025), C-reactive protein (p=0.039), D-Dimer (p<0.001) and creatinine (p=0.043) levels, are independent predictors of critical COVID-19. Furthermore, classification and regression tree (CART) analysis provided a cut-off value of pyruvate in serum (24.54 µM; p<0.001) as an early criterion to accurately classify patients with critical outcomes. Conclusion: Our findings support the link between COVID-19 pathogenesis and immunometabolic dysregulation, and show that fluorometric quantification of circulating pyruvate is a cost-effective clinical decision support tool to improve patient stratification and prognosis prediction.


Subject(s)
COVID-19 , Biomarkers , C-Reactive Protein , Creatinine , Glucose , Humans , Ketoglutaric Acids , Lactates , Prognosis , Pyruvic Acid , SARS-CoV-2 , Succinates , Tricarboxylic Acids
2.
Int J Mol Sci ; 24(2)2023 Jan 10.
Article in English | MEDLINE | ID: covidwho-2216329

ABSTRACT

The autophagy gene ATG7 has been shown to be essential for the induction of autophagy, a process that used to be suppressed in nonalcoholic fatty liver disease (NAFLD). However, the specific role of ATG7 in NAFLD remains unclear. The aim of this study was to analyze hepatic ATG7 mRNA and ATG7 protein expression regarding obesity-associated NAFLD. Patients included women classified into normal weight (NW, n = 6) and morbid obesity (MO, n = 72). The second group was subclassified into normal liver (NL, n = 11), simple steatosis (SS, n= 29), and nonalcoholic steatohepatitis (NASH, n = 32). mRNA expression was analyzed by RT-qPCR and protein expression was evaluated by Western blotting. Our results showed that NASH patients presented higher ATG7 mRNA and ATG7 protein levels. ATG7 mRNA expression was increased in NASH compared with SS, while ATG7 protein abundance was enhanced in NASH compared with NL. ATG7 mRNA correlated negatively with the expression of some hepatic lipid metabolism-related genes and positively with endocannabinoid receptors, adiponectin hepatic expression, and omentin levels. These results suggest that ATG7-mediated autophagy may play an important role in the pathogenesis of NAFLD, especially in NASH, perhaps playing a possible protective role. However, this is a preliminary study that needs to be further studied.


Subject(s)
Non-alcoholic Fatty Liver Disease , Humans , Female , Non-alcoholic Fatty Liver Disease/complications , Non-alcoholic Fatty Liver Disease/genetics , Non-alcoholic Fatty Liver Disease/metabolism , Autophagy-Related Protein 7/genetics , Autophagy-Related Protein 7/metabolism , RNA, Messenger/genetics , RNA, Messenger/metabolism , Liver/metabolism , Obesity/complications , Obesity/genetics , Obesity/metabolism
3.
Frontiers in immunology ; 13, 2022.
Article in English | EuropePMC | ID: covidwho-2045164

ABSTRACT

Background Coronavirus-19 (COVID-19) disease is driven by an unchecked immune response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus which alters host mitochondrial-associated mechanisms. Compromised mitochondrial health results in abnormal reprogramming of glucose metabolism, which can disrupt extracellular signalling. We hypothesized that examining mitochondrial energy-related signalling metabolites implicated in host immune response to SARS-CoV-2 infection would provide potential biomarkers for predicting the risk of severe COVID-19 illness. Methods We used a semi-targeted serum metabolomics approach in 273 patients with different severity grades of COVID-19 recruited at the acute phase of the infection to determine the relative abundance of tricarboxylic acid (Krebs) cycle-related metabolites with known extracellular signaling properties (pyruvate, lactate, succinate and α-ketoglutarate). Abundance levels of energy-related metabolites were evaluated in a validation cohort (n=398) using quantitative fluorimetric assays. Results Increased levels of four energy-related metabolites (pyruvate, lactate, a-ketoglutarate and succinate) were found in critically ill COVID-19 patients using semi-targeted and targeted approaches (p<0.05). The combined strategy proposed herein enabled us to establish that circulating pyruvate levels (p<0.001) together with body mass index (p=0.025), C-reactive protein (p=0.039), D-Dimer (p<0.001) and creatinine (p=0.043) levels, are independent predictors of critical COVID-19. Furthermore, classification and regression tree (CART) analysis provided a cut-off value of pyruvate in serum (24.54 µM;p<0.001) as an early criterion to accurately classify patients with critical outcomes. Conclusion Our findings support the link between COVID-19 pathogenesis and immunometabolic dysregulation, and show that fluorometric quantification of circulating pyruvate is a cost-effective clinical decision support tool to improve patient stratification and prognosis prediction.

4.
J Pers Med ; 12(3)2022 Mar 03.
Article in English | MEDLINE | ID: covidwho-1732102

ABSTRACT

The cytokine signature present in COVID-19 could provide information on the pathogenic mechanisms of the disease and could identify possible prognostic biomarkers and possible therapeutic targets. In this longitudinal work, we studied the clinical and biochemical parameters and circulating cytokine levels of 146 patients at the time of admission for COVID-19 and 4-6 weeks later. The main objective of this study was to determine whether basal cytokines could be early prognostic biomarkers of COVID-19, and also to analyze the impact of comorbidities, such as obesity or metabolic syndrome (MS), in the cytokine profile. The levels of most inflammatory cytokines were elevated on admission in relation to the level that was reached 4-6 weeks later, except for IL-1ß, which was lower on admission; these levels were irrespective of the presence of obesity or MS since the cytokine storm masks these inflammatory processes. Among the cytokines analyzed, those that correlated with a worse prognosis of COVID-19 were resistin, IL-6, IL-8, IL-15, MCP-1 and TNF-α. Specifically, resistin and IL-15 are the best early predictors of requiring invasive ventilation. Therefore, resistin and IL-15 should be included in the personalized treatment decision algorithm of patients with COVID-19.

5.
Glob Epidemiol ; 4: 100071, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-1611740

ABSTRACT

BACKGROUND: The changes in shield strategies, treatments, emergence variants, and healthcare pathways might shift the profile and outcome of patients hospitalized with COVID-19 in successive waves of the outbreak. METHODS: We retrospectively analysed the characteristics and in-hospital outcomes of all patients admitted with COVID-19 in eight university hospitals of Catalonia (North-East Spain) between Feb 28, 2020 and Feb 28, 2021. Using a 7-joinpoint regression analysis, we split admissions into four waves. The main hospital outcomes included 30-day mortality and admission to intensive care unit (ICU). FINDINGS: The analysis included 17,027 subjects admitted during the first wave (6800; 39.9%), summer wave (1807; 10.6%), second wave (3804; 22.3%), and third wave (4616; 27.1%). The highest 30-day mortality rate was reported during the first wave (17%) and decreased afterwards, remaining stable at 13% in the second and third waves (overall 30% reduction); the lowest mortality was reported during the summer wave (8%, 50% reduction). ICU admission became progressively more frequent during successive waves. In Cox regression analysis, the main factors contributing to differences in 30-day mortality were the epidemic wave, followed by gender, age, diabetes, chronic kidney disease, and neoplasms. INTERPRETATION: Although in-hospital COVID-19 mortality remains high, it decreased substantially after the first wave and is highly dependent of patient's characteristics and ICU availability. Highest mortality reductions occurred during a wave characterized by younger individuals, an increasingly frequent scenario as vaccination campaigns progress. FUNDING: This work did not receive specific funding.

6.
J Pers Med ; 11(3)2021 Mar 22.
Article in English | MEDLINE | ID: covidwho-1154442

ABSTRACT

In SARS-CoV-2-infected patients, obesity, hypertension, and diabetes are dangerous factors that may result in death. Priority in detection and specific therapies for these patients are necessary. We wanted to investigate the impact of obesity and metabolic syndrome (MS) on the clinical course of COVID-19 and whether prognostic biomarkers described are useful to predict the evolution of COVID-19 in patients with obesity or MS. This prospective cohort study included 303 patients hospitalized for COVID-19. Participants were first classified according to the presence of obesity; then, they were classified according to the presence of MS. Clinical, radiologic, and analytical parameters were collected. We reported that patients with obesity presented moderate COVID-19 symptoms and pneumonia, bilateral pulmonary infiltrates, and needed tocilizumab more frequently. Meanwhile, patients with MS presented severe pneumonia and respiratory failure more frequently, they have a higher mortality rate, and they also showed higher creatinine and troponin levels. The main findings of this study are that IL-6 is a potential predictor of COVID-19 severity in patients with obesity, while troponin and LDH can be used as predictive biomarkers of COVID-19 severity in MS patients. Therefore, treatment for COVID-19 in patients with obesity or MS should probably be intensified and personalized.

7.
Rev Esp Cardiol (Engl Ed) ; 74(1): 24-32, 2021 Jan.
Article in English, Spanish | MEDLINE | ID: covidwho-989111

ABSTRACT

INTRODUCTION AND OBJECTIVES: Cardiac troponin, a marker of myocardial injury, is frequently observed in patients with COVID-19 infection. Our objective was to analyze myocardial injury and its prognostic implications in patients with and without COVID-19 infection treated in the same period of time. METHODS: The present study included patients treated in a university hospital with cardiac troponin I measurements and with suspected COVID-19 infection, confirmed or ruled out by polymerase chain reaction analysis. The impact was analyzed of cardiac troponin I positivity on 30-day mortality. RESULTS: In total, 433 patients were distributed among the following groups: confirmed COVID-19 (n=186), 22% with myocardial injury (n=41); and ruled out COVID-19 (n=247), 21.5% with myocardial injury (n=52). The confirmed and ruled out COVID-19 groups had a similar age, sex, and cardiovascular history. Mortality was significantly higher in the confirmed COVID-19 group than in the ruled out group (19.9% vs 5.3%, P <.001). In Cox multivariate regression analysis, cardiac troponin I was a predictor of mortality in both groups (confirmed COVID-19 group: HR, 3.54; 95%CI, 1.70-7.34; P=.001; ruled out COVID-19 group: HR, 5.57; 95%CI, 1.70-18.20; P=.004). The predictive model analyzed by ROC curves was similar in the 2 groups (P=.701), with AUCs of 0.808 in the confirmed COVID-19 group (0.750-0.865) and 0.812 in the ruled out COVID-19 group (0.760-0.864). CONCLUSIONS: Myocardial injury is detected in 1 in every 5 patients with confirmed or ruled out COVID-19 and predicts 30-day mortality to a similar extent in both circumstances.


Subject(s)
COVID-19/mortality , Cardiomyopathies/mortality , SARS-CoV-2 , Troponin I/blood , Aged , COVID-19/blood , COVID-19/complications , COVID-19/diagnosis , COVID-19 Nucleic Acid Testing/statistics & numerical data , Cardiomyopathies/blood , Confidence Intervals , Female , Hospitalization/statistics & numerical data , Hospitals, University , Humans , Intensive Care Units/statistics & numerical data , Lung/diagnostic imaging , Male , Middle Aged , Prognosis , ROC Curve , Regression Analysis , Retrospective Studies , Risk Factors
8.
Rev Esp Cardiol ; 74(1): 24-32, 2021 Jan.
Article in Spanish | MEDLINE | ID: covidwho-759286

ABSTRACT

INTRODUCTION AND OBJECTIVES: Cardiac troponin, a marker of myocardial injury, is frequently observed in patients with COVID-19 infection. Our objective was to analyze myocardial injury and its prognostic implications in patients with and without COVID-19 infection treated in the same period of time. METHODS: The present study included patients treated in a university hospital with cardiac troponin I measurements and with suspected COVID-19 infection, confirmed or ruled out by polymerase chain reaction analysis. The impact was analyzed of cardiac troponin I positivity on 30-day mortality. RESULTS: In total, 433 patients were distributed among the following groups: confirmed COVID-19 (n = 186), 22% with myocardial injury (n = 41); and ruled out COVID-19 (n = 247), 21.5% with myocardial injury (n = 52). The confirmed and ruled out COVID-19 groups had a similar age, sex, and cardiovascular history. Mortality was significantly higher in the confirmed COVID-19 group than in the ruled out group (19.9% vs 5.3%, P < .001). In Cox multivariate regression analysis, cardiac troponin I was a predictor of mortality in both groups (confirmed COVID-19 group: HR, 3.54; 95%CI, 1.70-7.34; P = .001; ruled out COVID-19 group: HR, 5.57; 95%CI, 1.70-18.20; P = .004). The predictive model analyzed by ROC curves was similar in the 2 groups (P = .701), with AUCs of 0.808 in the confirmed COVID-19 group (0.750-0.865) and 0.812 in the ruled out COVID-19 group (0.760-0.864). CONCLUSIONS: Myocardial injury is detected in 1 in every 5 patients with confirmed or ruled out COVID-19 and predicts 30-day mortality to a similar extent in both circumstances.

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