Cargando…

Introducing APOA1 as a key protein in COVID-19 infection: a bioinformatics approach

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 asp...

Descripción completa

Detalles Bibliográficos
Autores principales: Zamanian Azodi, Mona, Arjmand, Babak, Zali, Alireza, Razzaghi, Mohammadreza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Shaheed Beheshti University of Medical Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682979/
https://www.ncbi.nlm.nih.gov/pubmed/33244380
_version_ 1783612784933601280
author Zamanian Azodi, Mona
Arjmand, Babak
Zali, Alireza
Razzaghi, Mohammadreza
author_facet Zamanian Azodi, Mona
Arjmand, Babak
Zali, Alireza
Razzaghi, Mohammadreza
author_sort Zamanian Azodi, Mona
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7682979
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Shaheed Beheshti University of Medical Sciences
record_format MEDLINE/PubMed
spelling pubmed-76829792020-11-25 Introducing APOA1 as a key protein in COVID-19 infection: a bioinformatics approach Zamanian Azodi, Mona Arjmand, Babak Zali, Alireza Razzaghi, Mohammadreza Gastroenterol Hepatol Bed Bench Original Article 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. Shaheed Beheshti University of Medical Sciences 2020 /pmc/articles/PMC7682979/ /pubmed/33244380 Text en ©2020 RIGLD, Research Institute for Gastroenterology and Liver Diseases This is an Open Access article distributed under the terms of the Creative Commons Attribution License, (http://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Zamanian Azodi, Mona
Arjmand, Babak
Zali, Alireza
Razzaghi, Mohammadreza
Introducing APOA1 as a key protein in COVID-19 infection: a bioinformatics approach
title Introducing APOA1 as a key protein in COVID-19 infection: a bioinformatics approach
title_full Introducing APOA1 as a key protein in COVID-19 infection: a bioinformatics approach
title_fullStr Introducing APOA1 as a key protein in COVID-19 infection: a bioinformatics approach
title_full_unstemmed Introducing APOA1 as a key protein in COVID-19 infection: a bioinformatics approach
title_short Introducing APOA1 as a key protein in COVID-19 infection: a bioinformatics approach
title_sort introducing apoa1 as a key protein in covid-19 infection: a bioinformatics approach
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682979/
https://www.ncbi.nlm.nih.gov/pubmed/33244380
work_keys_str_mv AT zamanianazodimona introducingapoa1asakeyproteinincovid19infectionabioinformaticsapproach
AT arjmandbabak introducingapoa1asakeyproteinincovid19infectionabioinformaticsapproach
AT zalialireza introducingapoa1asakeyproteinincovid19infectionabioinformaticsapproach
AT razzaghimohammadreza introducingapoa1asakeyproteinincovid19infectionabioinformaticsapproach