Integrated metabolic and inflammatory signatures associated with severity, fatality, and recovery of COVID-19
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
TISSUE(S): Blood
DISEASE(S): Covid-19
PROVIDER: ST002291 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
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Project description:The clinical evolution of COVID-19 pneumonia is poorly understood. Identifying the metabolic pathways that are altered early with viral infection and their association with disease severity is crucial to understand COVID-19 pathophysiology, and guide clinical decisions. This study aimed at assessing the critical metabolic pathways altered with disease severity in hospitalized COVID-19 patients. Forty-nine hospitalized patients with COVID-19 pneumonia were enrolled in a prospective, observational, single-center study in Barcelona, Spain. Demographic, clinical, and analytical data at admission were registered. Plasma samples were collected within the first 48 h following hospitalization. Patients were stratified based on the severity of their evolution as moderate (N = 13), severe (N = 10), or critical (N = 26). A panel of 221 biomarkers was measured by targeted metabolomics in order to evaluate metabolic changes associated with subsequent disease severity. Our results show that obesity, respiratory rate, blood pressure, and oxygen saturation, as well as some analytical parameters and radiological findings, were all associated with disease severity. Additionally, ceramide metabolism, tryptophan degradation, and reductions in several metabolic reactions involving nicotinamide adenine nucleotide (NAD) at inclusion were significantly associated with respiratory severity and correlated with inflammation. In summary, assessment of the metabolomic profile of COVID-19 patients could assist in disease severity stratification and even in guiding clinical decisions.
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Project description:In this study, we sought to identify circulating microRNA (miRNA) signatures associated with COVID-19 severity and outcome through small RNA-sequencing of serum samples from 89 COVID-19 patients and 45 healthy controls. As results, a set of miRNAs associated with lung disease, vascular damage and inflammation were upregulated in serum of COVID-19 patients vs controls, while miRNAs that inhibit pro-inflammatory cytokines and chemokines, angiogenesis and stress response were downregulated. In addition, patients with severe COVID-19 vs mild or moderate disease had a circulating miRNA signature associated with sepsis, hearth failure, tissue fibrosis, inflammation, and impairment of type I IFN and antiviral responses. A subset of the differentially expressed miRNAs predicted ICU admission, sequelae and mortality in COVID-19 patients. Investigation of the differentially expressed circulating miRNAs in relevant human cell types in vitro showed that some of these miRNAs were modulated directly by SARS-CoV-2 infection or indirectly by type I IFN stimulation.
2022-05-03 | GSE201790 | GEO
Project description:Coronavirus disease 2019 (COVID-19) has been threatening public health for the last 3 years globally. So far, the pathophysiology of the disease and therapeutic strategies have not clearly known yet. In this project, performing label-free plasma proteomics analysis, we aimed at identifying severity biomarkers for COVID-19 prognosis and proposing potential drugs against the disease symptoms by building the signaling network of significantly regulated proteins and finding the corresponding virus-host interactions. A total of 38 plasma samples from 13 COVID-19 PCR positive individuals and 5 plasma samples from healthy individuals were collected for the analysis. According to the WHO criteria, the severity of our patients was categorized as moderate (n=4), severe (n=3), and critical (n=6). Also, blood samples were collected in different time points after the symptom onset: (1) 1-5 day (± 2 days); early infection, (2) 5-15 days (± 2 days); inflammatory response, and after 15 days (± 2 days); recovery which shows the first PCR negative result from a nasal swab. In summary, we found significantly regulated proteins between COVID-19 patients and uninfected individuals and proposed some critical patient-specific prognostic biomarkers, which can be used as an early predictor of the disease severity. Also, we created a COVID-19 related plasma protein network modulated by SARS-CoV2 viral proteins and indicated clinically significant targets for the disease symptoms.
2023-03-11 | PXD031813 | Pride
Project description:BackgroundSARS-CoV-2 infection represents a global health problem that has affected millions of people. The fine host immune response and its association with the disease course have not yet been fully elucidated. Consequently, we analyze circulating B cell subsets and their possible relationship with COVID-19 features and severity.MethodsUsing a multiparametric flow cytometric approach, we determined B cell subsets frequencies from 52 COVID-19 patients, grouped them by hierarchical cluster analysis, and correlated their values with clinical data.ResultsThe frequency of CD19+ B cells is increased in severe COVID-19 compared to mild cases. Specific subset frequencies such as transitional B cell subsets increase in mild/moderate cases but decrease with the severity of the disease. Memory B compartment decreased in severe and critical cases, and antibody-secreting cells are increased according to the severity of the disease. Other non-typical subsets such as double-negative B cells also showed significant changes according to disease severity. Globally, these differences allow us to identify severity-associated patient clusters with specific altered subsets. Finally, respiratory parameters, biomarkers of inflammation, and clinical scores exhibited correlations with some of these subpopulations.ConclusionsThe severity of COVID-19 is accompanied by changes in the B cell subpopulations, either immature or terminally differentiated. Furthermore, the existing relationship of B cell subset frequencies with clinical and laboratory parameters suggest that these lymphocytes could serve as potential biomarkers and even active participants in the adaptive antiviral response mounted against SARS-CoV-2.
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Project description:Severely-afflicted COVID-19 patients can exhibit disease manifestations representative of sepsis, including acute respiratory distress syndrome and multiple organ failure. We hypothesized that diagnostic tools used in managing all-cause sepsis, such as clinical criteria, biomarkers, and gene expression signatures, should extend to COVID-19 patients. Here we analyzed the whole blood transcriptome of 124 early (1-5 days post-hospital admission) and late (6-20 days post-admission) sampled patients with confirmed COVID-19 infections from hospitals in Quebec, Canada. Mechanisms associated with COVID-19 severity were identified between severity groups (ranging from mild disease to the requirement for mechanical ventilation and mortality), and established sepsis signatures were assessed for dysregulation. Specifically, gene expression signatures representing pathophysiological events, namely cellular reprogramming, organ dysfunction, and mortality, were significantly enriched and predictive of severity and lethality in COVID-19 patients. Mechanistic endotypes reflective of distinct sepsis aetiologies and therapeutic opportunities were also identified in subsets of patients, enabling prediction of potentially-effective repurposed drugs. The expression of sepsis gene expression signatures in severely-afflicted COVID-19 patients indicates that these patients should be classified as having severe sepsis. Accordingly, in severe COVID-19 patients, these signatures should be strongly considered for the mechanistic characterization, diagnosis, and guidance of treatment using repurposed drugs.
2022-12-18 | GSE221234 | GEO
Project description:The Corona Virus Disease 2019 (COVID-19) pandemic has attracted increasing worldwide attention. While metabolic-associated fatty liver disease (MAFLD) affects a quarter of world population, its impact on COVID-19 severity has not been characterized. We identified 55 MAFLD patients with COVID-19, who were 1:1 matched by age, sex and obesity status to non-aged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients without MAFLD. Our results demonstrate that in patients aged less than 60 years with COVID-19, MAFLD is associated with an approximately fourfold increase (adjusted odds ratio 4.07, 95% confidence interval 1.20-13.79, P = .02) in the probability for severe disease, after adjusting for confounders. Healthcare professionals caring for patients with COVID-19 need to be aware that there is a positive association between MAFLD and severe illness with COVID-19.
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2022-03-01 | E-MTAB-10970 | biostudies-arrayexpress