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Proteomic and clinical biomarkers for acute mountain sickness in a longitudinal cohort
Ascending to high-altitude by non-high-altitude natives is a well-suited model for studying acclimatization to extreme environments. Acute mountain sickness (AMS) is frequently experienced by visitors. The diagnosis of AMS mainly depends on a self-questionnaire, revealing the need for reliable bioma...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170681/ https://www.ncbi.nlm.nih.gov/pubmed/35668171 http://dx.doi.org/10.1038/s42003-022-03514-6 |
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author | Yang, Jing Jia, Zhilong Song, Xinyu Shi, Jinlong Wang, Xiaoreng Zhao, Xiaojing He, Kunlun |
author_facet | Yang, Jing Jia, Zhilong Song, Xinyu Shi, Jinlong Wang, Xiaoreng Zhao, Xiaojing He, Kunlun |
author_sort | Yang, Jing |
collection | PubMed |
description | Ascending to high-altitude by non-high-altitude natives is a well-suited model for studying acclimatization to extreme environments. Acute mountain sickness (AMS) is frequently experienced by visitors. The diagnosis of AMS mainly depends on a self-questionnaire, revealing the need for reliable biomarkers for AMS. Here, we profiled 22 AMS symptom phenotypes, 65 clinical indexes, and plasma proteomic profiles of AMS via a combination of proximity extension assay and multiple reaction monitoring of a longitudinal cohort of 53 individuals. We quantified 1069 proteins and validated 102 proteins. Via differential analysis, machine learning, and functional association analyses. We found and validated that RET played an important role in the pathogenesis of AMS. With high-accuracies (AUCs > 0.9) of XGBoost-based models, we prioritized ADAM15, PHGDH, and TRAF2 as protective, predictive, and diagnostic biomarkers, respectively. Our findings shed light on the precision medicine for AMS and the understanding of acclimatization to high-altitude environments. |
format | Online Article Text |
id | pubmed-9170681 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-91706812022-06-08 Proteomic and clinical biomarkers for acute mountain sickness in a longitudinal cohort Yang, Jing Jia, Zhilong Song, Xinyu Shi, Jinlong Wang, Xiaoreng Zhao, Xiaojing He, Kunlun Commun Biol Article Ascending to high-altitude by non-high-altitude natives is a well-suited model for studying acclimatization to extreme environments. Acute mountain sickness (AMS) is frequently experienced by visitors. The diagnosis of AMS mainly depends on a self-questionnaire, revealing the need for reliable biomarkers for AMS. Here, we profiled 22 AMS symptom phenotypes, 65 clinical indexes, and plasma proteomic profiles of AMS via a combination of proximity extension assay and multiple reaction monitoring of a longitudinal cohort of 53 individuals. We quantified 1069 proteins and validated 102 proteins. Via differential analysis, machine learning, and functional association analyses. We found and validated that RET played an important role in the pathogenesis of AMS. With high-accuracies (AUCs > 0.9) of XGBoost-based models, we prioritized ADAM15, PHGDH, and TRAF2 as protective, predictive, and diagnostic biomarkers, respectively. Our findings shed light on the precision medicine for AMS and the understanding of acclimatization to high-altitude environments. Nature Publishing Group UK 2022-06-06 /pmc/articles/PMC9170681/ /pubmed/35668171 http://dx.doi.org/10.1038/s42003-022-03514-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Yang, Jing Jia, Zhilong Song, Xinyu Shi, Jinlong Wang, Xiaoreng Zhao, Xiaojing He, Kunlun Proteomic and clinical biomarkers for acute mountain sickness in a longitudinal cohort |
title | Proteomic and clinical biomarkers for acute mountain sickness in a longitudinal cohort |
title_full | Proteomic and clinical biomarkers for acute mountain sickness in a longitudinal cohort |
title_fullStr | Proteomic and clinical biomarkers for acute mountain sickness in a longitudinal cohort |
title_full_unstemmed | Proteomic and clinical biomarkers for acute mountain sickness in a longitudinal cohort |
title_short | Proteomic and clinical biomarkers for acute mountain sickness in a longitudinal cohort |
title_sort | proteomic and clinical biomarkers for acute mountain sickness in a longitudinal cohort |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170681/ https://www.ncbi.nlm.nih.gov/pubmed/35668171 http://dx.doi.org/10.1038/s42003-022-03514-6 |
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