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

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. Throug...

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Detalles Bibliográficos
Autores principales: Lin, Yao, Li, Yueqi, Chen, Hubin, Meng, Jun, Li, Jingyi, Chu, Jiemei, Zheng, Ruili, Wang, Hailong, Pan, Peijiang, Su, Jinming, Jiang, Junjun, Ye, Li, Liang, Hao, An, Sanqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039774/
https://www.ncbi.nlm.nih.gov/pubmed/36966292
http://dx.doi.org/10.1186/s12920-023-01490-2
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01490-2.