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A team of US scientists from the University of Chicago, NCH Healthcare System, and University of South Florida has identified a specific set of genes associated with a poor prognosis for coronavirus disease 2019 (COVID-19). The study is currently available on bioRxiv* prepress server.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the aetiological pathogen of COVID-19, has high infectivity and pathogenicity. Although a substantial percentage of individuals infected with SARS-CoV-2 remain asymptomatic or mildly symptomatic, some groups of people, such as the elderly or people with comorbidities, are highly susceptible to developing severe COVID-19.
Since the emergence of the COVID-19 pandemic, many studies have been conducted to identify the molecular and genetic risk factors associated with the severity of the disease. In this context, elevated blood levels and certain pro-inflammatory biomarkers, such as ferritin, C-reactive proteins, and procalcitonin, have been shown to predispose COVID-19 patients to develop critical illnesses requiring mechanical ventilation. However, further studies are needed to identify and characterize reliable biomarkers that can prioritize the best treatment options based on disease severity.
Current study design
According to the available literature, COVID-19 survivors are susceptible to developing pulmonary fibrosis, which is a lung disease caused by damage and scarring of the lung tissue. In light of this fact, the scientists repurposed a signature of 52 genes, which they had previously developed to predict the mortality risk of patients with pulmonary fibrosis and to predict the clinical consequences of SARS-CoV-2 infection.
Of a set of 52 genes, they analyzed the expression of 50 genes using peripheral blood samples collected from SARS-CoV-2 patients. In addition, they conducted single cell expression analyzes to identify the cellular sources of these genes. They excluded two non-coding ANNs as they were not available in some data sets.
Important remarks
Of the 50 genes studied, 7 showed increased expression and 43 showed reduced expression. Using a classification algorithm, the scientists identified low-risk and high-risk genomic profiles. They observed that people with a high-risk genomic profile were significantly older and had a higher risk of developing severe COVID-19. Furthermore, the need for ICU admission or mechanical ventilation was significantly higher among them. Blood levels of lactate, C-reactive protein, and d-dimer were also significantly higher in people with a high-risk genomic profile than in those with a low-risk genomic profile.
To identify the cellular sources of 50 genes, they conducted a patient-level analysis using the classification algorithm, which had identified five low-risk and three high-risk genomic profiles. Comparing the proportions of different cell types between the low-risk and high-risk profiles, they observed that people with high-risk profiles exhibited higher proportions of red blood cells, monocytes, neutrophils, and dendritic cells. In contrast, higher percentages of T and B lymphocytes, natural killer cells, and antibody-producing plasmablasts were found in people with low-risk genomic profiles.
To further validate the data, they conducted a cell-type-specific analysis using the classification algorithm, which had identified 46 high-risk and 109 low-risk genomic profiles. The results revealed that red blood cells, neutrophils, monocytes, eosinophils and dendritic cells comprised the high-risk profiles, while T and B lymphocytes, natural killer cells and plasmablasts comprised the low-risk profiles. These results indicate that robust T- and B-cell-mediated immune responses may reduce the risk of developing severe COVID-19.
Signature-based genomic risk profiles of 50 genes predict negative outcomes in SARSCoV-2. Grouping of SARS-CoV-2 infected individuals based on signature-derived genomic risk profiles (high vs low) of 50 genes using SAMS in discovery (A) and validation cohorts (B). Each column represents a subject and each row represents a gene. A log-based two-color scale is displayed next to the heat maps; red indicates a greater expression than the geometric mean of the samples and green a decrease. S = SARS-CoV-2 severe disease. M = SARS-CoV-2 mild disease.
Meaning of the study
The study results indicate that the expression profiles of 50 genes in peripheral blood can predict the clinical outcome of COVID-19 patients. The study also identifies the cellular sources of these genes. Taken together, important biomarkers identified in the study can be used to classify COVID-19 patients based on the severity of their disease, which in turn can facilitate the proper utilization of medical resources, including life-saving therapies and equipment. This can also reduce the risk and cost of unnecessary hospitalizations.
*Important Notice
bioRxiv publishes preliminary scientific reports that are not peer-reviewed and therefore should not be considered conclusive, guide clinical practice / health-related behavior, or treated as consolidated information.
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