Name (Synonyms) | Correlation | |
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drug1204 | Guduchi Ghan Vati Wiki | 0.71 |
drug2926 | To assess for development of IgG antibodies against SARS-CoV2 Wiki | 0.71 |
Name (Synonyms) | Correlation | |
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D058070 | Asymptomatic Diseases NIH | 0.82 |
D003333 | Coronaviridae Infections NIH | 0.32 |
D012327 | RNA Virus Infections NIH | 0.32 |
D014777 | Virus Diseases NIH | 0.08 |
D003141 | Communicable Diseases NIH | 0.06 |
D007239 | Infection NIH | 0.04 |
D045169 | Severe Acute Respiratory Syndrome NIH | 0.03 |
D018352 | Coronavirus Infections NIH | 0.03 |
Name (Synonyms) | Correlation |
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There are 2 clinical trials
As of March 25, 2020, 414,179 cases and 18,440 deaths secondary to Coronavirus 2019 disease (COVID-19) have been reported worldwide. The unfavorable course of the patients is characterized on the immunological level by an intense pro-inflammatory response which can go as far as a cytokinic storm. This pandemic affects a naive world population from an immunological point of view with respect to SARS-CoV-2 responsible for COVID-19. The evolution is favorable without hospitalization in almost 85% of cases. Among patients hospitalized for pneumonia, some will not require ventilatory support while others will need intensive care. To date, two main types of unfavorable evolution have been described. The first is a bi-phasic evolution beginning with a paucisymptomatic form which is worsened secondarily with respiratory distress associated with a decrease in the viral load in the airways. The second is associated with persistent high viral loads in the airways and detection of the virus in the blood. These different clinical profiles could depend on the quantitative and qualitative response of the innate immune system. At the early stage of a viral infection the innate immunity is capable of detecting certain conserved microbial patterns (PAMP, pathogen-associated molecular pattern) recognized by receptors dedicated to these patterns (PRR, pattern recognition receptor). This process allows to initiate the pro-inflammatory response via different signaling pathways. Activating multiprotein complexes called inflammasomes, which cause pro-IL-1β and pro-IL-18 to be transformed into active pro-inflammatory cytokines are one of these pathways. The central role of inflammasomes in the secretion of these pro-inflammatory cytokines deserves an in-depth study of their activation during COVID-19, whereas the inadequate inflammatory response appears to be the determining factor in the unfavorable development of patients. The objective of this project is to analyze the level of activation of the inflammasomes and then to search for inactivating or activating mutations among the genes which code for the proteins constituting the inflammasomes in Covid-19 patients. The identification of mutations in patients with a serious clinical presentation or even death would be followed by fundamental work by analyzing in a cellular model the impact of these mutations on the secretion of IL-1β.
Description: Percentage of immune cells with inflammasome positive labeling using flow cytometry in comparison to controls
Measure: Level of activation of inflammasomes in monocytes and polymorphonuclear neutrophils during COVID-19 Time: At inclusionDescription: Identification of genes nucleotide polymorphisms by Whole Exome Sequensing and bioinformatics analysis. Analysis of activating or inactivating mutations of NLRP3 NLRC4 AIM2 and Pyrin inflammasomes in patients with severe COVID-19.
Measure: Genes nucleoside polymorphism analysis Time: At inclusionMetabolomics is the analysis of small molecules in a biological sample (cells, tissues or biological fluids). It can potentially detect very sensitively any change related to a pathology or exposure to a toxic agent. The analyses are fast, inexpensive and therefore applicable in routine, particularly in health care. Given the emergence of this new disease, COVID-19, there is a real need to better understand the pathophysiological mechanisms of SARS-CoV-2 infection. In this context, metabolomics could have a place and could lead to the development of interesting diagnostic or prognostic tools. The objective of this study is to identify, through the analysis of biological samples (blood and urine), whether there is a metabolomic signature in patients with COVID-19.
Description: Identify a metabolomic profile using liquid chromatography combined with mass spectrometry (LC-MS) on the serum and urine of COVID-19 patients
Measure: Identifying the metabolomic signature Time: 4 weeks after the inclusionDescription: Identification of the metabolomic profile of patients infected with SARS CoV 2 in the following subgroups: pauci-symptomatic patients, symptomatic patients without clinical severity criteria, and critically ill COVID-19 patients.
Measure: Identification of the metabolomic profile according to clinical severity. Time: 4 weeks after the inclusion