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Comprehensive bioinformatics analysis and systems biology approaches to identify the interplay between COVID-19 and pericarditis.
Li, Daisong; Chen, Ruolan; Huang, Chao; Zhang, Guoliang; Li, Zhaoqing; Xu, Xiaojian; Wang, Banghui; Li, Bing; Chu, Xian-Ming.
Afiliación
  • Li D; Department of Cardiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Chen R; Department of Cardiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Huang C; Department of Cardiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Zhang G; Department of Cardiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Li Z; Department of Cardiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Xu X; Department of Cardiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Wang B; Department of Cardiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Li B; Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China.
  • Chu XM; Department of Dermatology, The Affiliated Haici Hospital of Qingdao University, Qingdao, China.
Front Immunol ; 15: 1264856, 2024.
Article en En | MEDLINE | ID: mdl-38455049
ABSTRACT

Background:

Increasing evidence indicating that coronavirus disease 2019 (COVID-19) increased the incidence and related risks of pericarditis and whether COVID-19 vaccine is related to pericarditis has triggered research and discussion. However, mechanisms behind the link between COVID-19 and pericarditis are still unknown. The objective of this study was to further elucidate the molecular mechanisms of COVID-19 with pericarditis at the gene level using bioinformatics analysis.

Methods:

Genes associated with COVID-19 and pericarditis were collected from databases using limited screening criteria and intersected to identify the common genes of COVID-19 and pericarditis. Subsequently, gene ontology, pathway enrichment, protein-protein interaction, and immune infiltration analyses were conducted. Finally, TF-gene, gene-miRNA, gene-disease, protein-chemical, and protein-drug interaction networks were constructed based on hub gene identification.

Results:

A total of 313 common genes were selected, and enrichment analyses were performed to determine their biological functions and signaling pathways. Eight hub genes (IL-1ß, CD8A, IL-10, CD4, IL-6, TLR4, CCL2, and PTPRC) were identified using the protein-protein interaction network, and immune infiltration analysis was then carried out to examine the functional relationship between the eight hub genes and immune cells as well as changes in immune cells in disease. Transcription factors, miRNAs, diseases, chemicals, and drugs with high correlation with hub genes were predicted using bioinformatics analysis.

Conclusions:

This study revealed a common gene interaction network between COVID-19 and pericarditis. The screened functional pathways, hub genes, potential compounds, and drugs provided new insights for further research on COVID-19 associated with pericarditis.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Pericarditis / COVID-19 Idioma: En Revista: Front Immunol Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Pericarditis / COVID-19 Idioma: En Revista: Front Immunol Año: 2024 Tipo del documento: Article