Absolute quantification of plasma cytokines and metabolome reveals the glycylproline regulating antibody-fading in convalescent COVID-19 patients
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Blood
DISEASE(S): Covid-19
PROVIDER: ST001933 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| mwtab | Other |
Items per page: 5 1 - 1 of 1 |
Similar Datasets
Project description:Pneumonia is a common cause of morbidity and mortality and is most often caused by bacterial pathogens. COVID-19 is characterized by lung infection with potential progressive organ failure. The systemic consequences of both disease on the systemic blood metabolome are not fully understood. The aim of this study was to compare the blood metabolome of both diseases and we hypothesize that plasma metabolomics may help to identify the systemic effects of these diseases. Therefore, we profiled the plasma metabolome of 43 cases of COVID-19 pneumonia, 23 cases of non-COVID-19 pneumonia, and 26 controls using a non-targeted approach. Metabolic alterations differentiating the three groups were detected, with specific metabolic changes distinguishing the two types of pneumonia groups. A comparison of venous and arterial blood plasma samples from the same subjects revealed the distinct metabolic effects of pulmonary pneumonia. In addition, a machine learning signature of four metabolites was predictive of the disease outcome of COVID-19 subjects with an area under the curve (AUC) of 86 ± 10 %. Overall, the results of this study uncover systemic metabolic changes that could be linked to the etiology of COVID-19 pneumonia and non-COVID-19 pneumonia.
| S-EPMC9693035 | biostudies-literature
Project description: Not available
| S-BSST719 | biostudies-other
Project description:Circulating microRNAs (miRNAs) have been shown to be excellent disease diagnostic or prognostic biomarkers in a wide range of chronic and acute inflammatory and infectious diseases including viral respiratory infection. Crucially, circulating miRNA levels are thought to reflect the state of the diseased tissue. Despite their proven value as mechanism-based clinical stratification indicators, miRNAs have only started being explored in the context of COVID-19. here, we aimed to explore whether integrating miRNA with other clinical and biological measurements would reveal more accurate correlates of COVID-19 severity and outcome, and to identify severity-specific correlations of miRNAs with COVID-19-associated inflammatory mediators, clinical parameters, and otucome.
2021-12-09 | GSE189610 | GEO
Project description:Coronavirus disease 2019 (COVID-19) can be asymptomatic or lead to a wide spectrum of symptoms, ranging from mild upper respiratory system involvement to acute respiratory distress syndrome, multi-organ damage and death. In this study, we explored the potential of microRNAs (miRNA) in delineating patient condition and in predicting clinical outcome. Analysis of the circulating miRNA profile of COVID-19 patients, sampled at different hospitalization intervals after admission, allowed to identify miR-144-3p as a dynamically regulated miRNA in response to COVID-19.
2023-01-27 | GSE195898 | GEO
Project description:The COVID-19 pandemic has incurred tremendous costs worldwide and is still threatening public health in the "new normal." The association between neutralizing antibody levels and metabolic alterations in convalescent patients with COVID-19 is still poorly understood. In the present work, we conducted absolutely quantitative profiling to compare the plasma cytokines and metabolome of ordinary convalescent patients with antibodies (CA), convalescents with rapidly faded antibodies (CO), and healthy subjects. As a result, we identified that cytokines such as M-CSF and IL-12p40 and plasma metabolites such as glycylproline (gly-pro) and long-chain acylcarnitines could be associated with antibody fading in COVID-19 convalescent patients. Following feature selection, we built machine-learning-based classification models using 17 features (six cytokines and 11 metabolites). Overall accuracies of more than 90% were attained in at least six machine-learning models. Of note, the dipeptide gly-pro, a product of enzymatic peptide cleavage catalyzed by dipeptidyl peptidase 4 (DPP4), strongly accumulated in CO individuals compared with the CA group. Furthermore, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination experiments in healthy mice demonstrated that supplementation of gly-pro down-regulates SARS-CoV-2-specific receptor-binding domain antibody levels and suppresses immune responses, whereas the DPP4 inhibitor sitagliptin can counteract the inhibitory effects of gly-pro upon SARS-CoV-2 vaccination. Our findings not only reveal the important role of gly-pro in the immune responses to SARS-CoV-2 infection but also indicate a possible mechanism underlying the beneficial outcomes of treatment with DPP4 inhibitors in convalescent COVID-19 patients, shedding light on therapeutic and vaccination strategies against COVID-19.
| S-EPMC9407385 | biostudies-literature
Project description:The lack of available biomarkers for diagnosing and predicting different stages of coronavirus disease 2019 (COVID-19) is currently one of the main challenges that clinicians are facing. Recent evidence indicates that the plasma levels of specific miRNAs may be significantly modified in COVID-19 patients. Large-scale deep sequencing analysis of small RNA expression was performed on plasma samples from 40 patients hospitalized for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (between March and May 2020) (median 13.50 [IQR 9–24] days since symptoms initiation) and 21 healthy noninfected individuals. Patients were categorized as hospitalized not requiring oxygen therapy (n = 6), hospitalized requiring low-flow oxygen (n = 23), and hospitalized requiring high-flow oxygen support (n = 11). A total of 1218 different micro(mi)RNAs were identified. When compared with healthy noninfected donors, SARS-CoV-2 infected patients showed significantly (fold change [FC] >1.2 and adjusted p [padj] <0.05) altered expression of 190 miRNAs. The top 10 differentially expressed (DE) miRNAs were miR-122-5p, let-7b-5p, miR-146a-5p, miR-342-3p, miR-146b-5p, miR-629-5p, miR-24-3p, miR-12136, let-7a-5p, and miR-191-5p, which displayed FC and padj values ranging from 153 to 5 and 2.51 × 10-32 to 2.21 × 10-21, respectively, which unequivocally diagnosed SARS-CoV-2 infection. No differences in blood cell counts and biochemical plasma parameters, including interleukin 6, ferritin and D-dimer, were observed between COVID-19 patients on high-flow oxygen therapy, low-flow oxygen therapy, or not requiring oxygen therapy. Notably, 31 significantly deregulated miRNAs were found when patients on high- and low-flow oxygen therapy were compared. Similarly, 6 DE miRNAs were identified between patients on high flow and those not requiring oxygen therapy. SARS-CoV-2 infection generates a specific miRNA signature in hospitalized patients. Furthermore, specific miRNA profiles are associated with COVID-19 prognosis in severe patients.
2024-04-03 | GSE230092 | GEO
Project description:The oral mucosa is the first site of SARS-CoV-2 entry and replication, and it plays a central role in the early defense against infection. Thus, SARS-CoV-2 viral load, miRNAs, cytokines, and neutralizing activity (NA) were assessed in saliva and plasma from mild (MD) and severe (SD) COVID-19 patients. Here we show that of the 84 miRNAs analysed, 8 are differently express in plasma and saliva of SD. In particular: 1) miRNAs let-7a-5p, let-7b-5p, let-7c-5p are significantly downregulated; and 2) miR-23a and b, miR-29c, as well as three immunomodulatory miRNAs (miR-34a-5p, miR-181d-5p, miR-146) are significantly upregulated. The production of pro-inflammatory cytokines (IL-1β, IL-2, IL-6, IL-8, IL-9 and TNFα) and chemokines (CCL2 and RANTES) increase in both saliva and plasma of SD and MD. Notably, disease severity correlates with NA and immune activation. Monitoring these parameters could help to predict disease outcome and identify new markers of disease progression.
2023-07-19 | GSE235978 | GEO
Project description:The ongoing outbreak of novel coronavirus (SARS-CoV-2) disease 2019 (COVID-19) has been declared a pandemic by the World Health Organization. This disease is marked by its rapid progression from mild to severe conditions, particularly in the absence of adequate medical care. And the mortality rate of COVID-19 in critically ill cases can reach over 60%. However, the physiological changes associated with COVID-19 progress under different conditions are barely understood. In this study, we performed untargeted metabolomics and lipidomic analyses of plasma from COVID-19 patients. We found a positive correlation between the alteration of metabolites and the course of disease deterioration in COVID-19 patients, indicating that the development of disease affects the metabolism of metabolites.
2020-03-31 | PXD018307 |
Project description:Background: Extracellular vesicles are a valuable source of biomarkers and display the pathophysiological status of various diseases. In COVID-19, EVs are explored in several studies for their ability to reflect molecular changes caused by SARS-CoV-2 infection and impacts on disease progression. Methods: In this study, we used a label-free shotgun proteomics approach to identify and quantify any alterations in EVs proteins abundance in severe COVID-19 patients. We isolated plasma extracellular vesicles from healthy donors and patients with severe COVID-19 by size exclusion chromatography (SEC). Then, flow cytometry was performed to assess the origin of EVs and investigate the presence of circulating procoagulant EVs in COVID-19 patients. A total protein extraction was performed and samples were analyzed by nLC-MS/MS in a Q-Exactive HF-X. Finally, computational analyzes were applied to sign biological processes related to disease pathogenesis. Results: We report significant changes in the proteome of EVs from patients with severe COVID-19. Differently expressed proteins in the disease groups were associated with platelet degranulation, integrin cell surface interaction, and acute inflammatory response. Flow cytometry experiments indicated an increase in total circulating EVs and with TF-dependent procoagulant activity.
2022-05-31 | PXD032808 | Pride
Project description:Coronavirus disease 2019 (COVID-19) is an unprecedented global threat caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The COVID-19 pandemic is a global health crisis. Recent reports have exposed an astonishing case fatality rate of 61.5% for critical cases, increasing sharply with age and for patients with underlying comorbidities. Mass spectrometry (MS)-based proteomics has the potential to become an ideal technology to be applied in this urgent situations, because it can quickly deliver substantial amounts of clinical and biological information from blood plasma or serum in an untargeted fashion. Furthermore, these MS-based proteomic workflows for biomarker discovery and profiling are well established. However, only two studies have presently applied proteomics to serum of COVID-19 patients with moderate proteome depth. Therefore, it is necessary to gain a more detailed understanding with in-depth proteome of plasma or serum to develop prognostic or predictive protein markers. In this study, we performed in-depth proteome profiling of undepleted plasma samples using BoxCar acquisition method from an exploratory cohort comprising ten COVID-19 patients to identify candidate biomarkers for disease severity evaluation.
2021-05-15 | PXD020354 | Pride