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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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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
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author 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
author_facet 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
author_sort Lin, Yao
collection PubMed
description 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.
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spelling pubmed-100397742023-03-27 Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients 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 BMC Med Genomics Research 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. BioMed Central 2023-03-25 /pmc/articles/PMC10039774/ /pubmed/36966292 http://dx.doi.org/10.1186/s12920-023-01490-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
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
Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients
title Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients
title_full Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients
title_fullStr Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients
title_full_unstemmed Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients
title_short Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients
title_sort weighted gene co-expression network analysis revealed t cell differentiation associated with the age-related phenotypes in covid-19 patients
topic Research
url 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
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