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Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients

BACKGROUND: Currently, the rate of morbidity and mortality in acute respiratory distress syndrome (ARDS) remains high. One of the potential reasons for the poor and ineffective therapies is the lack of early and credible indicator of risk prediction that would help specific treatment of severely aff...

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Autores principales: Shi, Songchang, Wei, Shuo, Pan, Xiaobin, Zhang, Lihui, Zhang, Shujuan, Wang, Xincai, Shi, Songjing, Lin, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440545/
https://www.ncbi.nlm.nih.gov/pubmed/36056346
http://dx.doi.org/10.1186/s12890-022-02130-8
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author Shi, Songchang
Wei, Shuo
Pan, Xiaobin
Zhang, Lihui
Zhang, Shujuan
Wang, Xincai
Shi, Songjing
Lin, Wei
author_facet Shi, Songchang
Wei, Shuo
Pan, Xiaobin
Zhang, Lihui
Zhang, Shujuan
Wang, Xincai
Shi, Songjing
Lin, Wei
author_sort Shi, Songchang
collection PubMed
description BACKGROUND: Currently, the rate of morbidity and mortality in acute respiratory distress syndrome (ARDS) remains high. One of the potential reasons for the poor and ineffective therapies is the lack of early and credible indicator of risk prediction that would help specific treatment of severely affected ARDS patients. Nevertheless, assessment of the clinical outcomes with transcriptomics of ARDS by alveolar macrophage has not been performed. METHODS: The expression data GSE116560 was obtained from the Gene Expression Omnibus databases (GEO) in NCBI. This dataset consists of 68 BAL samples from 35 subjects that were collected within 48 h of ARDS. Differentially expressed genes (DEGs) of different outcomes were analyzed using R software. The top 10 DEGs that were up- or down-regulated were analyzed using receiver operating characteristic (ROC) analysis. Kaplan–Meier survival analysis within two categories according to cut-off and the value of prediction of the clinical outcomes via DEGs was verified. GO enrichment, KEGG pathway analysis, and protein–protein interaction were also used for functional annotation of key genes. RESULTS: 24,526 genes were obtained, including 235 up-regulated and 292 down-regulated DEGs. The gene ADORA3 was chosen as the most obvious value to predict the outcome according to the ROC and survival analysis. For functional annotation, ADORA3 was significantly augmented in sphingolipid signaling pathway, cGMP-PKG signaling pathway, and neuroactive ligand-receptor interaction. Four genes (ADORA3, GNB1, NTS, and RHO), with 4 nodes and 6 edges, had the highest score in these clusters in the protein–protein interaction network. CONCLUSIONS: Our results show that the prognostic prediction of early biomarkers of transcriptomics as identified in alveolar macrophage in ARDS can be extended for mechanically ventilated critically ill patients. In the long term, generalizing the concept of biomarkers of transcriptomics in alveolar macrophage could add to improving precision-based strategies in the ICU patients and may also lead to identifying improved strategy for critically ill patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-022-02130-8.
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spelling pubmed-94405452022-09-04 Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients Shi, Songchang Wei, Shuo Pan, Xiaobin Zhang, Lihui Zhang, Shujuan Wang, Xincai Shi, Songjing Lin, Wei BMC Pulm Med Research BACKGROUND: Currently, the rate of morbidity and mortality in acute respiratory distress syndrome (ARDS) remains high. One of the potential reasons for the poor and ineffective therapies is the lack of early and credible indicator of risk prediction that would help specific treatment of severely affected ARDS patients. Nevertheless, assessment of the clinical outcomes with transcriptomics of ARDS by alveolar macrophage has not been performed. METHODS: The expression data GSE116560 was obtained from the Gene Expression Omnibus databases (GEO) in NCBI. This dataset consists of 68 BAL samples from 35 subjects that were collected within 48 h of ARDS. Differentially expressed genes (DEGs) of different outcomes were analyzed using R software. The top 10 DEGs that were up- or down-regulated were analyzed using receiver operating characteristic (ROC) analysis. Kaplan–Meier survival analysis within two categories according to cut-off and the value of prediction of the clinical outcomes via DEGs was verified. GO enrichment, KEGG pathway analysis, and protein–protein interaction were also used for functional annotation of key genes. RESULTS: 24,526 genes were obtained, including 235 up-regulated and 292 down-regulated DEGs. The gene ADORA3 was chosen as the most obvious value to predict the outcome according to the ROC and survival analysis. For functional annotation, ADORA3 was significantly augmented in sphingolipid signaling pathway, cGMP-PKG signaling pathway, and neuroactive ligand-receptor interaction. Four genes (ADORA3, GNB1, NTS, and RHO), with 4 nodes and 6 edges, had the highest score in these clusters in the protein–protein interaction network. CONCLUSIONS: Our results show that the prognostic prediction of early biomarkers of transcriptomics as identified in alveolar macrophage in ARDS can be extended for mechanically ventilated critically ill patients. In the long term, generalizing the concept of biomarkers of transcriptomics in alveolar macrophage could add to improving precision-based strategies in the ICU patients and may also lead to identifying improved strategy for critically ill patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-022-02130-8. BioMed Central 2022-09-02 /pmc/articles/PMC9440545/ /pubmed/36056346 http://dx.doi.org/10.1186/s12890-022-02130-8 Text en © The Author(s) 2022 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
Shi, Songchang
Wei, Shuo
Pan, Xiaobin
Zhang, Lihui
Zhang, Shujuan
Wang, Xincai
Shi, Songjing
Lin, Wei
Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients
title Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients
title_full Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients
title_fullStr Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients
title_full_unstemmed Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients
title_short Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients
title_sort identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ards patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440545/
https://www.ncbi.nlm.nih.gov/pubmed/36056346
http://dx.doi.org/10.1186/s12890-022-02130-8
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