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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...

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Autores principales: Yang, Jing, Jia, Zhilong, Song, Xinyu, Shi, Jinlong, Wang, Xiaoreng, Zhao, Xiaojing, He, Kunlun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
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.
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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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