Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients

BMC Med Genomics. 2023 Mar 25;16(1):59. doi: 10.1186/s12920-023-01490-2.

Abstract

The risk of severe condition caused by Corona Virus Disease 2019 (COVID-19) increases with age. However, the underlying mechanisms have not been clearly understood. The dataset GSE157103 was used to perform weighted gene co-expression network analysis on 100 COVID-19 patients in our analysis. Through weighted gene co-expression network analysis, we identified a key module which was significantly related with age. This age-related module could predict Intensive Care Unit status and mechanical-ventilation usage, and enriched with positive regulation of T cell receptor signaling pathway biological progress. Moreover, 10 hub genes were identified as crucial gene of the age-related module. Protein-protein interaction network and transcription factors-gene interactions were established. Lastly, independent data sets and RT-qPCR were used to validate the key module and hub genes. Our conclusion revealed that key genes were associated with the age-related phenotypes in COVID-19 patients, and it would be beneficial for clinical doctors to develop reasonable therapeutic strategies in elderly COVID-19 patients.

Keywords: Aging; COVID-19; T-cell immunity; Weighted gene.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19* / genetics
  • Cell Differentiation
  • Gene Expression Profiling
  • Gene Regulatory Networks
  • Humans
  • Phenotype
  • Physicians*