PropertyValue
?:abstract
  • Aim: Introducing possible diagnostic and therapeutic biomarker candidates via the identification of chief dysregulated proteins in COVID-19 patients is the aim of this study Background: Molecular studies, especially proteomics, can be considered as suitable approaches for discovering the hidden aspect of the disease Methods: Differentially expressed proteins (DEPs) of three patients with demonstrated severe condition (S-COVID-19) were compared to healthy cases by a proteomics study Cytoscape software and STRING database were used to construct the protein-protein interaction (PPI) network The central DEPs were identified through topological analysis of the network ClueGO+CluePedia were applied to find the biological processes related to the central nodes MCODE molecular complex detection (MCODE) was used to discover protein complexes Results: A total of 242 DEPs from among 256 query ones were included in the network Centrality analysis of the network assigned 16 hub-bottlenecks, nine of which were presented in the highest-scored protein complex Ten protein complexes were determined APOA1 was identified as the protein complex seed, and APP, EGF, and C3 were the top hub-bottlenecks of the network The results specify that up-regulation of C3 and down-regulation of APOA1 in urine play a role in the stiffness in respiration and, accordingly, the severity of COVID-19 Moreover, dysregulation of APP and APOA1 could both contribute to the possible adverse effects of COVID-19 on the nervous system Conclusion: The introduced central proteins of the S-COVID-19 interaction network, particularly APOA1, can be considered as diagnostic and therapeutic targets related to the coronavirus disease after being approved with complementary studies © 2020 RIGLD, Research Institute for Gastroenterology and Liver Diseases
is ?:annotates of
?:creator
?:journal
  • Gastroenterology_and_Hepatology_from_Bed_to_Bench
?:license
  • unk
?:publication_isRelatedTo_Disease
is ?:relation_isRelatedTo_publication of
?:source
  • WHO
?:title
  • Introducing APOA1 as a key protein in COVID-19 infection: A bioinformatics approach
?:type
?:who_covidence_id
  • #940480
?:year
  • 2020

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