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Development of clinical phenotypes and biological profiles via proteomic analysis of trauma patients

BACKGROUND: Trauma is a heterogeneous condition, and specific clinical phenotypes may identify target populations that could benefit from certain treatment strategies. In this retrospective study, we determined clinical phenotypes and identified new target populations of trauma patients and their tr...

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Autores principales: Tachino, Jotaro, Matsumoto, Hisatake, Sugihara, Fuminori, Seno, Shigeto, Okuzaki, Daisuke, Kitamura, Tetsuhisa, Komukai, Sho, Kido, Yoshiyuki, Kojima, Takashi, Togami, Yuki, Katayama, Yusuke, Nakagawa, Yuko, Ogura, Hiroshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357328/
https://www.ncbi.nlm.nih.gov/pubmed/35933364
http://dx.doi.org/10.1186/s13054-022-04103-z
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author Tachino, Jotaro
Matsumoto, Hisatake
Sugihara, Fuminori
Seno, Shigeto
Okuzaki, Daisuke
Kitamura, Tetsuhisa
Komukai, Sho
Kido, Yoshiyuki
Kojima, Takashi
Togami, Yuki
Katayama, Yusuke
Nakagawa, Yuko
Ogura, Hiroshi
author_facet Tachino, Jotaro
Matsumoto, Hisatake
Sugihara, Fuminori
Seno, Shigeto
Okuzaki, Daisuke
Kitamura, Tetsuhisa
Komukai, Sho
Kido, Yoshiyuki
Kojima, Takashi
Togami, Yuki
Katayama, Yusuke
Nakagawa, Yuko
Ogura, Hiroshi
author_sort Tachino, Jotaro
collection PubMed
description BACKGROUND: Trauma is a heterogeneous condition, and specific clinical phenotypes may identify target populations that could benefit from certain treatment strategies. In this retrospective study, we determined clinical phenotypes and identified new target populations of trauma patients and their treatment strategies. METHODS: We retrospectively analyzed datasets from the Japan Trauma Data Bank and determined trauma death clinical phenotypes using statistical machine learning techniques and evaluation of biological profiles. RESULTS: The analysis included 71,038 blunt trauma patients [median age, 63 (interquartile range [IQR], 40–78) years; 45,479 (64.0%) males; median Injury Severity Score, 13 (IQR, 9–20)], and the derivation and validation cohorts included 42,780 (60.2%) and 28,258 (39.8%) patients, respectively. Of eight derived phenotypes (D-1–D-8), D-8 (n = 2178) had the highest mortality (48.6%) with characteristic severely disturbed consciousness and was further divided into four phenotypes: D-8α, multiple trauma in the young (n = 464); D-8β, head trauma with lower body temperature (n = 178); D-8γ, severe head injury in the elderly (n = 957); and D-8δ, multiple trauma, with higher predicted mortality than actual mortality (n = 579). Phenotype distributions were comparable in the validation cohort. Biological profile analysis of 90 trauma patients revealed that D-8 exhibited excessive inflammation, including enhanced acute inflammatory response, dysregulated complement activation pathways, and impaired coagulation, including downregulated coagulation and platelet degranulation pathways, compared with other phenotypes. CONCLUSIONS: We identified clinical phenotypes with high mortality, and the evaluation of the molecular pathogenesis underlying these clinical phenotypes suggests that lethal trauma may involve excessive inflammation and coagulation disorders. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13054-022-04103-z.
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spelling pubmed-93573282022-08-08 Development of clinical phenotypes and biological profiles via proteomic analysis of trauma patients Tachino, Jotaro Matsumoto, Hisatake Sugihara, Fuminori Seno, Shigeto Okuzaki, Daisuke Kitamura, Tetsuhisa Komukai, Sho Kido, Yoshiyuki Kojima, Takashi Togami, Yuki Katayama, Yusuke Nakagawa, Yuko Ogura, Hiroshi Crit Care Research BACKGROUND: Trauma is a heterogeneous condition, and specific clinical phenotypes may identify target populations that could benefit from certain treatment strategies. In this retrospective study, we determined clinical phenotypes and identified new target populations of trauma patients and their treatment strategies. METHODS: We retrospectively analyzed datasets from the Japan Trauma Data Bank and determined trauma death clinical phenotypes using statistical machine learning techniques and evaluation of biological profiles. RESULTS: The analysis included 71,038 blunt trauma patients [median age, 63 (interquartile range [IQR], 40–78) years; 45,479 (64.0%) males; median Injury Severity Score, 13 (IQR, 9–20)], and the derivation and validation cohorts included 42,780 (60.2%) and 28,258 (39.8%) patients, respectively. Of eight derived phenotypes (D-1–D-8), D-8 (n = 2178) had the highest mortality (48.6%) with characteristic severely disturbed consciousness and was further divided into four phenotypes: D-8α, multiple trauma in the young (n = 464); D-8β, head trauma with lower body temperature (n = 178); D-8γ, severe head injury in the elderly (n = 957); and D-8δ, multiple trauma, with higher predicted mortality than actual mortality (n = 579). Phenotype distributions were comparable in the validation cohort. Biological profile analysis of 90 trauma patients revealed that D-8 exhibited excessive inflammation, including enhanced acute inflammatory response, dysregulated complement activation pathways, and impaired coagulation, including downregulated coagulation and platelet degranulation pathways, compared with other phenotypes. CONCLUSIONS: We identified clinical phenotypes with high mortality, and the evaluation of the molecular pathogenesis underlying these clinical phenotypes suggests that lethal trauma may involve excessive inflammation and coagulation disorders. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13054-022-04103-z. BioMed Central 2022-08-06 /pmc/articles/PMC9357328/ /pubmed/35933364 http://dx.doi.org/10.1186/s13054-022-04103-z 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
Tachino, Jotaro
Matsumoto, Hisatake
Sugihara, Fuminori
Seno, Shigeto
Okuzaki, Daisuke
Kitamura, Tetsuhisa
Komukai, Sho
Kido, Yoshiyuki
Kojima, Takashi
Togami, Yuki
Katayama, Yusuke
Nakagawa, Yuko
Ogura, Hiroshi
Development of clinical phenotypes and biological profiles via proteomic analysis of trauma patients
title Development of clinical phenotypes and biological profiles via proteomic analysis of trauma patients
title_full Development of clinical phenotypes and biological profiles via proteomic analysis of trauma patients
title_fullStr Development of clinical phenotypes and biological profiles via proteomic analysis of trauma patients
title_full_unstemmed Development of clinical phenotypes and biological profiles via proteomic analysis of trauma patients
title_short Development of clinical phenotypes and biological profiles via proteomic analysis of trauma patients
title_sort development of clinical phenotypes and biological profiles via proteomic analysis of trauma patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357328/
https://www.ncbi.nlm.nih.gov/pubmed/35933364
http://dx.doi.org/10.1186/s13054-022-04103-z
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