ABSTRACT
Abstract-Nowadays the possible influence of the coronavirus infection on cartilage degeneration and synovial membrane inflammation during chronic joint pathology-osteoarthritis-remains largely unelucidated. The aim of the presented work is to analyze the TGFB1, FOXO1, and COMP gene expression and free radical generation intensity in blood of patients suffering from osteoarthritis after beating the SARS-CoV2 infection. The work was carried out using molecular genetics and biochemistry methods. The decrease of the TGFB1 and FOXO1 expression level was shown to be more evident in the osteoarthritis patients after COVID-19 if compared to the group with knee osteoarthritis during simultaneous and more prominent diminishing of both superoxide dismutase and catalase activity (possibly indicating cell redox state disruption and TGF- P1-FOXO1 signaling attenuation) in patients with osteoarthritis after SARS-CoV2 disease. At the same time, the more prominent decrease of COMP gene expression level was demonstrated in patients with osteoarthritis after COVID-19 compared to the group with knee osteoarthritis and more intense increase of the COMP concentration in patients with osteoarthritis after the SARS-CoV2 infection was revealed. These data indicate more significant activation of cell destructive processes after the infection as well as further pathology progression.
ABSTRACT
Recently an outbreak that emerged in Wuhan, China in December 2019, spread to the whole world in a short time and killed >1,410,000 people. It was determined that a new type of beta coronavirus called severe acute respiratory disease coronavirus type 2 (SARS-CoV-2) was causative agent of this outbreak and the disease caused by the virus was named as coronavirus disease 19 (COVID19). Despite the information obtained from the viral genome structure, many aspects of the virus-host interactions during infection is still unknown. In this study we aimed to identify SARS-CoV-2 encoded microRNAs and their cellular targets. We applied a computational method to predict miRNAs encoded by SARS-CoV-2 along with their putative targets in humans. Targets of predicted miRNAs were clustered into groups based on their biological processes, molecular function, and cellular compartments using GO and PANTHER. By using KEGG pathway enrichment analysis top pathways were identified. Finally, we have constructed an integrative pathway network analysis with target genes. We identified 40 SARS-CoV-2 miRNAs and their regulated targets. Our analysis showed that targeted genes including NFKB1, NFKBIE, JAK1-2, STAT3-4, STAT5B, STAT6, SOCS1-6, IL2, IL8, IL10, IL17, TGFBR1-2, SMAD2-4, HDAC1-6 and JARID1A-C, JARID2 play important roles in NFKB, JAK/STAT and TGFB signaling pathways as well as cells' epigenetic regulation pathways. Our results may help to understand virus-host interaction and the role of viral miRNAs during SARS-CoV-2 infection. As there is no current drug and effective treatment available for COVID19, it may also help to develop new treatment strategies.