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Bioinformatics analysis reveals molecular connections between non-alcoholic fatty liver disease (NAFLD) and COVID-19

The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has devastatingly impacted people’s lives. Non-alcoholic fatty liver disease (NAFLD) is fatal comorbidity of COVID-19 seen with potential risk factors to develop severe symptoms. This research focuses on determining and el...

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Autores principales: Abolfazli, Pouria, Aghajanzadeh, Taha, Ghaderinasrabad, Melina, Apue Nchama, Cristina Nkene, Mokhlesi, Amir, Talkhabi, Mahmood
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9078374/
https://www.ncbi.nlm.nih.gov/pubmed/35525888
http://dx.doi.org/10.1007/s12079-022-00678-y
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author Abolfazli, Pouria
Aghajanzadeh, Taha
Ghaderinasrabad, Melina
Apue Nchama, Cristina Nkene
Mokhlesi, Amir
Talkhabi, Mahmood
author_facet Abolfazli, Pouria
Aghajanzadeh, Taha
Ghaderinasrabad, Melina
Apue Nchama, Cristina Nkene
Mokhlesi, Amir
Talkhabi, Mahmood
author_sort Abolfazli, Pouria
collection PubMed
description The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has devastatingly impacted people’s lives. Non-alcoholic fatty liver disease (NAFLD) is fatal comorbidity of COVID-19 seen with potential risk factors to develop severe symptoms. This research focuses on determining and elucidating the molecular factors and connections that might contribute to the severity of SARS-CoV-2 infection in NAFLD patients. Here, we comprehensively inspected the genes involved in NAFLD and SARS-CoV-2 entry factors (SCEFs) found by searching through the DisGeNet database and literature review, respectively. Further, we identified the SCEFs-related proteins through protein-protein interaction (PPI) network construction, MCODE, and Cytohubba. Next, the shared genes involved in NAFLD and SARS-CoV-2 entry, and hub gene were determined, followed by the GO and KEGG pathways analysis. X2K database was used to construct the upstream regulatory network of hub genes, as well as to identify the top ten candidates of transcription factors (TFs) and protein kinases (PKs). PPI analysis identified connections between 4 top SCEFs, including ACE, ADAM17, DPP4, and TMPRSS2 and NAFLD-related genes such as ACE, DPP4, IL-10, TNF, and AKT1. GO and KEGG analysis revealed the top ten biological processes and pathways, including cytokine-mediated signaling, PI3K-Akt, AMPK, and mTOR signaling pathways. The upstream regulatory network revealed that AKT1 and MAPK14 as important PKs and HIF1A and SP1 as important TFs associated with AKT1, IL-10, and TNF. The molecular connections identified between COVID-19 and NAFLD may shed light on discovering the causes of the severity of SARS-CoV-2 infected NAFLD patients.
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spelling pubmed-90783742022-05-09 Bioinformatics analysis reveals molecular connections between non-alcoholic fatty liver disease (NAFLD) and COVID-19 Abolfazli, Pouria Aghajanzadeh, Taha Ghaderinasrabad, Melina Apue Nchama, Cristina Nkene Mokhlesi, Amir Talkhabi, Mahmood J Cell Commun Signal NUTS and BOLTS The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has devastatingly impacted people’s lives. Non-alcoholic fatty liver disease (NAFLD) is fatal comorbidity of COVID-19 seen with potential risk factors to develop severe symptoms. This research focuses on determining and elucidating the molecular factors and connections that might contribute to the severity of SARS-CoV-2 infection in NAFLD patients. Here, we comprehensively inspected the genes involved in NAFLD and SARS-CoV-2 entry factors (SCEFs) found by searching through the DisGeNet database and literature review, respectively. Further, we identified the SCEFs-related proteins through protein-protein interaction (PPI) network construction, MCODE, and Cytohubba. Next, the shared genes involved in NAFLD and SARS-CoV-2 entry, and hub gene were determined, followed by the GO and KEGG pathways analysis. X2K database was used to construct the upstream regulatory network of hub genes, as well as to identify the top ten candidates of transcription factors (TFs) and protein kinases (PKs). PPI analysis identified connections between 4 top SCEFs, including ACE, ADAM17, DPP4, and TMPRSS2 and NAFLD-related genes such as ACE, DPP4, IL-10, TNF, and AKT1. GO and KEGG analysis revealed the top ten biological processes and pathways, including cytokine-mediated signaling, PI3K-Akt, AMPK, and mTOR signaling pathways. The upstream regulatory network revealed that AKT1 and MAPK14 as important PKs and HIF1A and SP1 as important TFs associated with AKT1, IL-10, and TNF. The molecular connections identified between COVID-19 and NAFLD may shed light on discovering the causes of the severity of SARS-CoV-2 infected NAFLD patients. Springer Netherlands 2022-05-07 2022-12 /pmc/articles/PMC9078374/ /pubmed/35525888 http://dx.doi.org/10.1007/s12079-022-00678-y Text en © The International CCN Society 2022
spellingShingle NUTS and BOLTS
Abolfazli, Pouria
Aghajanzadeh, Taha
Ghaderinasrabad, Melina
Apue Nchama, Cristina Nkene
Mokhlesi, Amir
Talkhabi, Mahmood
Bioinformatics analysis reveals molecular connections between non-alcoholic fatty liver disease (NAFLD) and COVID-19
title Bioinformatics analysis reveals molecular connections between non-alcoholic fatty liver disease (NAFLD) and COVID-19
title_full Bioinformatics analysis reveals molecular connections between non-alcoholic fatty liver disease (NAFLD) and COVID-19
title_fullStr Bioinformatics analysis reveals molecular connections between non-alcoholic fatty liver disease (NAFLD) and COVID-19
title_full_unstemmed Bioinformatics analysis reveals molecular connections between non-alcoholic fatty liver disease (NAFLD) and COVID-19
title_short Bioinformatics analysis reveals molecular connections between non-alcoholic fatty liver disease (NAFLD) and COVID-19
title_sort bioinformatics analysis reveals molecular connections between non-alcoholic fatty liver disease (nafld) and covid-19
topic NUTS and BOLTS
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9078374/
https://www.ncbi.nlm.nih.gov/pubmed/35525888
http://dx.doi.org/10.1007/s12079-022-00678-y
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