Introducing APOA1 as a key protein in COVID-19 Infection: a bioinformatics approach
Gastroenterology and Hepatology from Bed to Bench,
20 September 2020
Aim: Introducing diagnostic and therapeutic biomarker candidates via the identification of central dysregulated proteins in COVID-19 patients is the aim of this study.
Background: The ongoing worldwide pandemic of novel coronavirus disease urges the requirements for effective clinical diagnosis and therapy approaches. Molecular studies especially proteomics can be considered as suitable methods to discover the hidden aspect of the disease.
Methods: Differentially expressed proteins (DEPs) of three patients with demonstrated severe condition (S-COVID-19) were compared to the healthy cases by the proteomics study. Cytoscape software and STRING database were used to construct protein-protein interaction (PPI) network. The central DEPs were identified via topological analysis of the network. ClueGO+CluePedia was applied to find the biological processes related to the central nodes. MCODE Molecular Complex Detection (MCODE) was used to discover protein complexes.
Results: Numbers of 242 DEPs among 256 query ones were included in the network. Centrality analysis of the network assigned 16 hub-bottlenecks that nine were presented in the highest-scored protein complex. The number of 10 protein complexes was determined. APOA1 as the protein complex seed and, APP, EGF, and C3 are the top hub-bottlenecks of the network. The results specify that up-regulation of C3 and down-regulation of APOA1 in urine play role in stiffness in respiration and accordingly, the severity of COVID-19. Moreover, dysregulation of APP and APOA1 both could be as a part of possible adverse effects of COVID-19 on the nervous system. A low level of urinary EGF can be considered as an indicator of a defective kidney in the presence of the virus.
Conclusion: In conclusion, the introduced central proteins particularly APOA1 can be considered as therapeutic targets and diagnostic biomarker candidates related to the coronavirus disease after complementary studies.
- Keywords: Urine Proteome, (S-COVID-19), Protein-protein interaction network analysis, Biomarker, Biological process
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