PropertyValue
?:abstract
  • Objective: Exploring the relationship between diabetes mellitus targets and ACE2 of the receptor of novel coronavirus(2019-nCoV) through a protein interaction network to provide new perspectives for clinical use Methods: Diabetes mellitus targets were obtained from the GeneCards and OMIM databases Targets with a relevance score exceeding 10 were included, and ACE2 protein was manually added The initial protein interaction network was obtained through String and then imported into Cytoscape 3 7 1 We selected the protein targets directly related to ACE2 as the target of the final analysis and imported them into String again in order to obtain the protein interaction network Module identification, GO analysis and KEGG pathway analysis were performed respectively The impact of ACE2 on the entire network was analyzed by scoring the module where it located Results: 19 ACE2-related proteins were finally selected from diabetes mellitus targets Three functional modules were found through the cluster analysis These modules involved G protein-coupled receptor binding, antioxidant activity, and insulin-like growth factor receptor binding The main signal pathways involved were the renin angiotensin system signal pathway, the type 2 diabetes mellitus signal pathway, and the FOXA2 signal pathway The scoring results showed that REN, AGT, INS, NOS3, IL6, and CRP scored the highest Conclusions: ACE2 is widely associated with diabetes mellitus key proteins COVID-19 may impact RAS of diabetes mellitus patients then induce serious complications Clinical use of RAS inhibitors may reduce the impact of COVID-19 infection on diabetes mellitus patients Copyright © 2020 by the Chinese Medical Association
is ?:annotates of
?:creator
?:journal
  • Chinese_Journal_of_Endocrinology_and_Metabolism
?:license
  • unk
?:publication_isRelatedTo_Disease
is ?:relation_isRelatedTo_publication of
?:source
  • WHO
?:title
  • Interrelationship between 2019-nCoV receptor ACE2 and diabetes mellitus target based on protein interaction network
?:type
?:who_covidence_id
  • #886206
?:year
  • 2020

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