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Identification of sepsis subtypes in critically ill adults using gene expression profiling
INTRODUCTION: Sepsis is a syndromic illness that has traditionally been defined by a set of broad, highly sensitive clinical parameters. As a result, numerous distinct pathophysiologic states may meet diagnostic criteria for sepsis, leading to syndrome heterogeneity. The existence of biologically di...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3682285/ https://www.ncbi.nlm.nih.gov/pubmed/23036193 http://dx.doi.org/10.1186/cc11667 |
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author | Maslove, David M Tang, Benjamin M McLean, Anthony S |
author_facet | Maslove, David M Tang, Benjamin M McLean, Anthony S |
author_sort | Maslove, David M |
collection | PubMed |
description | INTRODUCTION: Sepsis is a syndromic illness that has traditionally been defined by a set of broad, highly sensitive clinical parameters. As a result, numerous distinct pathophysiologic states may meet diagnostic criteria for sepsis, leading to syndrome heterogeneity. The existence of biologically distinct sepsis subtypes may in part explain the lack of actionable evidence from clinical trials of sepsis therapies. We used microarray-based gene expression data from adult patients with sepsis in order to identify molecularly distinct sepsis subtypes. METHODS: We used partitioning around medoids (PAM) and hierarchical clustering of gene expression profiles from neutrophils taken from a cohort of septic patients in order to identify distinct subtypes. Using the medoids learned from this cohort, we then clustered a second independent cohort of septic patients, and used the resulting class labels to evaluate differences in clinical parameters, as well as the expression of relevant pharmacogenes. RESULTS: We identified two sepsis subtypes based on gene expression patterns. Subtype 1 was characterized by increased expression of genes involved in inflammatory and Toll receptor mediated signaling pathways, as well as a higher prevalence of severe sepsis. There were differences between subtypes in the expression of pharmacogenes related to hydrocortisone, vasopressin, norepinephrine, and drotrecogin alpha. CONCLUSIONS: Sepsis subtypes can be identified based on different gene expression patterns. These patterns may generate hypotheses about the underlying pathophysiology of sepsis and suggest new ways of classifying septic patients both in clinical practice, and in the design of clinical trials. |
format | Online Article Text |
id | pubmed-3682285 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36822852013-06-25 Identification of sepsis subtypes in critically ill adults using gene expression profiling Maslove, David M Tang, Benjamin M McLean, Anthony S Crit Care Research INTRODUCTION: Sepsis is a syndromic illness that has traditionally been defined by a set of broad, highly sensitive clinical parameters. As a result, numerous distinct pathophysiologic states may meet diagnostic criteria for sepsis, leading to syndrome heterogeneity. The existence of biologically distinct sepsis subtypes may in part explain the lack of actionable evidence from clinical trials of sepsis therapies. We used microarray-based gene expression data from adult patients with sepsis in order to identify molecularly distinct sepsis subtypes. METHODS: We used partitioning around medoids (PAM) and hierarchical clustering of gene expression profiles from neutrophils taken from a cohort of septic patients in order to identify distinct subtypes. Using the medoids learned from this cohort, we then clustered a second independent cohort of septic patients, and used the resulting class labels to evaluate differences in clinical parameters, as well as the expression of relevant pharmacogenes. RESULTS: We identified two sepsis subtypes based on gene expression patterns. Subtype 1 was characterized by increased expression of genes involved in inflammatory and Toll receptor mediated signaling pathways, as well as a higher prevalence of severe sepsis. There were differences between subtypes in the expression of pharmacogenes related to hydrocortisone, vasopressin, norepinephrine, and drotrecogin alpha. CONCLUSIONS: Sepsis subtypes can be identified based on different gene expression patterns. These patterns may generate hypotheses about the underlying pathophysiology of sepsis and suggest new ways of classifying septic patients both in clinical practice, and in the design of clinical trials. BioMed Central 2012 2012-10-04 /pmc/articles/PMC3682285/ /pubmed/23036193 http://dx.doi.org/10.1186/cc11667 Text en Copyright ©2012 Maslove et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Maslove, David M Tang, Benjamin M McLean, Anthony S Identification of sepsis subtypes in critically ill adults using gene expression profiling |
title | Identification of sepsis subtypes in critically ill adults using gene expression profiling |
title_full | Identification of sepsis subtypes in critically ill adults using gene expression profiling |
title_fullStr | Identification of sepsis subtypes in critically ill adults using gene expression profiling |
title_full_unstemmed | Identification of sepsis subtypes in critically ill adults using gene expression profiling |
title_short | Identification of sepsis subtypes in critically ill adults using gene expression profiling |
title_sort | identification of sepsis subtypes in critically ill adults using gene expression profiling |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3682285/ https://www.ncbi.nlm.nih.gov/pubmed/23036193 http://dx.doi.org/10.1186/cc11667 |
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