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Interrelationship between 2019-nCov receptor DPP4 and diabetes mellitus targets based on protein interaction network.
Gao, Qian; Zhang, Wenjun; Li, Tingting; Yang, Guojun; Zhu, Wei; Chen, Naijun; Jin, Huawei.
  • Gao Q; Affiliated Hospital of Shaoxing University of Endocrine and Metabolism Department, Zhejiang, China. 420293991@qq.com.
  • Zhang W; Affiliated Hospital of Shaoxing University of Endocrine and Metabolism Department, Zhejiang, China.
  • Li T; Affiliated Hospital of Shaoxing University of Endocrine and Metabolism Department, Zhejiang, China.
  • Yang G; Affiliated Hospital of Shaoxing University of Endocrine and Metabolism Department, Zhejiang, China.
  • Zhu W; Affiliated Hospital of Shaoxing University of Endocrine and Metabolism Department, Zhejiang, China.
  • Chen N; Affiliated Hospital of Shaoxing University of Endocrine and Metabolism Department, Zhejiang, China.
  • Jin H; Affiliated Hospital of Shaoxing University of Endocrine and Metabolism Department, Zhejiang, China.
Sci Rep ; 12(1): 188, 2022 01 07.
Article in English | MEDLINE | ID: covidwho-1612207
ABSTRACT
Patients with diabetes are more likely to be infected with Coronavirus disease 2019 (COVID-19), and the risk of death is significantly higher than ordinary patients. Dipeptidyl peptidase-4 (DPP4) is one of the functional receptor of human coronavirus. Exploring the relationship between diabetes mellitus targets and DPP4 is particularly important for the management of patients with diabetes and COVID-19. We intend to study the protein interaction through the protein interaction network in order to find a new clue for the management of patients with diabetes with COVID-19. Diabetes mellitus targets were obtained from GeneCards database. Targets with a relevance score exceeding 20 were included, and DPP4 protein was added manually. The initial protein interaction network was obtained through String. The targets directly related to DPP4 were selected as the final analysis targets. Importing them into String again to obtain the protein interaction network. Module identification, gene ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were carried out respectively. The impact of DPP4 on the whole network was analyzed by scoring the module where it located. 43 DPP4-related proteins were finally selected from the diabetes mellitus targets and three functional modules were found by the cluster analysis. Module 1 was involved in insulin secretion and glucagon signaling pathway, module 2 and module 3 were involved in signaling receptor binding. The scoring results showed that LEP and apoB in module 1 were the highest, and the scores of INS, IL6 and ALB of cross module associated proteins of module 1 were the highest. DPP4 is widely associated with key proteins in diabetes mellitus. COVID-19 may affect DPP4 in patients with diabetes mellitus, leading to high mortality of diabetes mellitus combined with COVID-19. DPP4 inhibitors and IL-6 antagonists can be considered to reduce the effect of COVID-19 infection on patients with diabetes.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Dipeptidyl Peptidase 4 / Diabetes Mellitus, Type 2 / Protein Interaction Maps / SARS-CoV-2 / COVID-19 Type of study: Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-021-03912-6

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Dipeptidyl Peptidase 4 / Diabetes Mellitus, Type 2 / Protein Interaction Maps / SARS-CoV-2 / COVID-19 Type of study: Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-021-03912-6