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In a study by a Chinese research team, molecular markers have been identified in blood that have been shown to be predictive of severe COVID-19 outcomes resulting from SARS-CoV-2 coronavirus infection.
Study results expand understanding of the pathophysiology and clinical progress of COVID-19 with the potential to identify early during the course of infection which individuals are at highest risk of developing serious conditions and requiring hospital care. In addition to pneumonia and septic syndrome, a smaller proportion of patients have also developed severe gastrointestinal and / or cardiovascular symptoms, as well as neurological manifestations after SARS-COV-2 infection. This is possible because the angiotensin converting enzyme 2 (ACE 2) receptor that SARS-COV-2 uses for cell entry is found in organs other than the lungs, including the heart, liver, kidney, the pancreas, the small intestine and also the CNS. (Central Nervous System), especially the non-neuronal glial cells of the brain.
The study took a multi-biotic approach that integrates data from different omics disciplines, including cutting-edge transcriptomic, proteomic and metabolomic technologies to identify significant correlated molecular alterations in COVID-19 patients, especially severe cases. The work evaluated data from 83 individuals in three groups, 16 severe cases, 50 mild and 17 healthy controls without the virus. Serial blood and throat smear samples were collected from all participants, and to determine if the pathophysiology of COVID-19 was associated with particular molecular changes, a total of 23,373 expressed genes, 9,439 proteins, 327 metabolites, and 769 extracellular RNA (exRNA ) circulating in the blood was examined. The profiles were significantly different between the three groups.
There were significant differences between mild and severe cases in various immune markers such as type 1 interferon and inflammatory cytokines, which were elevated in the latter, while the former showed robust T-cell responses that presumably helped halt the progression of the disease . A remarkable and unexpected finding was the existence of significant correlations between the multimicrobial data and the biochemical or blood parameters of classic diagnosis. This was particularly reflected in proteomic analysis where there was a significant down-regulation in the tricarboxylic acid or “Krebs” cycle (TCA) and the glycolytic pathways used to release stored energy in mild and severe patients compared to healthy controls. . In contrast, well-known host defense pathways, such as the T-cell receptor signaling pathway, were elevated in COVID-19 patients.
Another potentially valuable finding for future clinical application was the existence of an association between viral load and disease prognosis in patients with severe COVID-19. Unfortunately, six of the patients with severe symptoms died and had significantly higher SARS-CoV-2 RNA loads in their throats upon admission to the hospital than those who survived. A notable finding here was that proteins involved in antiviral processes, including T-cell and B-cell receptor signaling pathways, were positively associated with changes in viral load in severely surviving patients. Finally, specific molecules were identified as biomarkers of subsequent COVID-19 outcomes and used to create prognostic classification models. Predictive models based on four types of data worked well, especially those that exploit clinical covariates and proteomic data, suggesting a possible framework for identifying patients likely to develop severe symptoms in advance so that treatments can address accordingly.
