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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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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. |
format | Online Article Text |
id | pubmed-8105470 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
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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