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Sepsis: deriving biological meaning and clinical applications from high-dimensional data

The pathophysiology of sepsis is multi-facetted and highly complex. As sepsis is a leading cause of global mortality that still lacks targeted therapies, increased understanding of its pathogenesis is vital for improving clinical care and outcomes. An increasing number of investigations seeks to unr...

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Autores principales: Schuurman, Alex R., Reijnders, Tom D. Y., Kullberg, Robert F. J., Butler, Joe M., van der Poll, Tom, Wiersinga, W. Joost
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8105470/
https://www.ncbi.nlm.nih.gov/pubmed/33961170
http://dx.doi.org/10.1186/s40635-021-00383-x
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author Schuurman, Alex R.
Reijnders, Tom D. Y.
Kullberg, Robert F. J.
Butler, Joe M.
van der Poll, Tom
Wiersinga, W. Joost
author_facet Schuurman, Alex R.
Reijnders, Tom D. Y.
Kullberg, Robert F. J.
Butler, Joe M.
van der Poll, Tom
Wiersinga, W. Joost
author_sort Schuurman, Alex R.
collection PubMed
description The pathophysiology of sepsis is multi-facetted and highly complex. As sepsis is a leading cause of global mortality that still lacks targeted therapies, increased understanding of its pathogenesis is vital for improving clinical care and outcomes. An increasing number of investigations seeks to unravel the complexity of sepsis through high-dimensional data analysis, enabled by advances in -omics technologies. Here, we summarize progress in the following major -omics fields: genomics, epigenomics, transcriptomics, proteomics, lipidomics, and microbiomics. We describe what these fields can teach us about sepsis, and highlight current trends and future challenges. Finally, we focus on multi-omics integration, and discuss the challenges in deriving biological meaning and clinical applications from these types of data.
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spelling pubmed-81054702021-05-10 Sepsis: deriving biological meaning and clinical applications from high-dimensional data Schuurman, Alex R. Reijnders, Tom D. Y. Kullberg, Robert F. J. Butler, Joe M. van der Poll, Tom Wiersinga, W. Joost Intensive Care Med Exp Reviews The pathophysiology of sepsis is multi-facetted and highly complex. As sepsis is a leading cause of global mortality that still lacks targeted therapies, increased understanding of its pathogenesis is vital for improving clinical care and outcomes. An increasing number of investigations seeks to unravel the complexity of sepsis through high-dimensional data analysis, enabled by advances in -omics technologies. Here, we summarize progress in the following major -omics fields: genomics, epigenomics, transcriptomics, proteomics, lipidomics, and microbiomics. We describe what these fields can teach us about sepsis, and highlight current trends and future challenges. Finally, we focus on multi-omics integration, and discuss the challenges in deriving biological meaning and clinical applications from these types of data. Springer International Publishing 2021-05-07 /pmc/articles/PMC8105470/ /pubmed/33961170 http://dx.doi.org/10.1186/s40635-021-00383-x Text en © The Author(s) 2021 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/) .
spellingShingle Reviews
Schuurman, Alex R.
Reijnders, Tom D. Y.
Kullberg, Robert F. J.
Butler, Joe M.
van der Poll, Tom
Wiersinga, W. Joost
Sepsis: deriving biological meaning and clinical applications from high-dimensional data
title Sepsis: deriving biological meaning and clinical applications from high-dimensional data
title_full Sepsis: deriving biological meaning and clinical applications from high-dimensional data
title_fullStr Sepsis: deriving biological meaning and clinical applications from high-dimensional data
title_full_unstemmed Sepsis: deriving biological meaning and clinical applications from high-dimensional data
title_short Sepsis: deriving biological meaning and clinical applications from high-dimensional data
title_sort sepsis: deriving biological meaning and clinical applications from high-dimensional data
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8105470/
https://www.ncbi.nlm.nih.gov/pubmed/33961170
http://dx.doi.org/10.1186/s40635-021-00383-x
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