| Autor: |
Yao Lin, Yueqi Li, Hubin Chen, Jun Meng, Jingyi Li, Jiemei Chu, Ruili Zheng, Hailong Wang, Peijiang Pan, Jinming Su, Junjun Jiang, Li Ye, Hao Liang, Sanqi An |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
BMC Medical Genomics, Vol 16, Iss 1, Pp 1-14 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1755-8794 |
| DOI: |
10.1186/s12920-023-01490-2 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
