| Property | Value |
|---|
|
?: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.
|
|
is
?:annotates
of
|
|
|
?:creator
|
|
|
?:externalLink
|
|
|
?:journal
|
-
Gastroenterol_Hepatol_Bed_Bench
|
|
?:license
|
|
|
?:pdf_json_files
|
-
document_parses/pdf_json/a2d1ccc543a40eb4b29eb626289d0e03d97db743.json
|
|
?:pmc_json_files
|
-
document_parses/pmc_json/PMC7682979.xml.json
|
|
?:pmcid
|
|
|
?:publication_isRelatedTo_Disease
|
|
|
is
?:relation_isRelatedTo_publication
of
|
|
|
?:sha_id
|
|
|
?:source
|
|
|
?:title
|
-
Introducing APOA1 as a key protein in COVID-19 infection: a bioinformatics approach
|
|
?:type
|
|
|
?:year
|
|
![[This page as RDF]](https://research.tib.eu/covid-19/static/rdf-icon.gif){kind=icon}