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Untargeted metabolomic profiling of sepsis-induced cardiac dysfunction
OBJECTIVE: Sepsis is a life-threatening condition secondary to infection that evolves into a dysregulated host response and is associated with acute organ dysfunction. Sepsis-induced cardiac dysfunction is one of the most complex organ failures to characterize. This study performed comprehensive met...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9978788/ https://www.ncbi.nlm.nih.gov/pubmed/36875476 http://dx.doi.org/10.3389/fendo.2023.1060470 |
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author | Cao, Yan Liu, Zhengyu Ma, Wenfeng Fang, Chen Pei, Yanfang Jing, Yingxia Huang, Jie Han, Xiaotong Xiao, Weiwei |
author_facet | Cao, Yan Liu, Zhengyu Ma, Wenfeng Fang, Chen Pei, Yanfang Jing, Yingxia Huang, Jie Han, Xiaotong Xiao, Weiwei |
author_sort | Cao, Yan |
collection | PubMed |
description | OBJECTIVE: Sepsis is a life-threatening condition secondary to infection that evolves into a dysregulated host response and is associated with acute organ dysfunction. Sepsis-induced cardiac dysfunction is one of the most complex organ failures to characterize. This study performed comprehensive metabolomic profiling that distinguished between septic patients with and without cardiac dysfunction. METHOD: Plasma samples collected from 80 septic patients were analysed by untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics. Principal component analysis (PCA), partial least squares discrimination analysis (PLS-DA), and orthogonal partial least square discriminant analysis (OPLS-DA) were applied to analyse the metabolic model between septic patients with and without cardiac dysfunction. The screening criteria for potential candidate metabolites were as follows: variable importance in the projection (VIP) >1, P < 0.05, and fold change (FC) > 1.5 or < 0.7. Pathway enrichment analysis further revealed associated metabolic pathways. In addition, we constructed a subgroup metabolic analysis between the survivors and non-survivors according to 28-day mortality in the cardiac dysfunction group. RESULTS: Two metabolite markers, kynurenic acid and gluconolactone, could distinguish the cardiac dysfunction group from the normal cardiac function group. Two metabolites, kynurenic acid and galactitol, could distinguish survivors and non-survivors in the subgroup analysis. Kynurenic acid is a common differential metabolite that could be used as a candidate for both diagnosis and prognosis for septic patients with cardiac dysfunction. The main associated pathways were amino acid metabolism, glucose metabolism and bile acid metabolism. CONCLUSION: Metabolomic technology could be a promising approach for identifying diagnostic and prognostic biomarkers of sepsis-induced cardiac dysfunction. |
format | Online Article Text |
id | pubmed-9978788 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99787882023-03-03 Untargeted metabolomic profiling of sepsis-induced cardiac dysfunction Cao, Yan Liu, Zhengyu Ma, Wenfeng Fang, Chen Pei, Yanfang Jing, Yingxia Huang, Jie Han, Xiaotong Xiao, Weiwei Front Endocrinol (Lausanne) Endocrinology OBJECTIVE: Sepsis is a life-threatening condition secondary to infection that evolves into a dysregulated host response and is associated with acute organ dysfunction. Sepsis-induced cardiac dysfunction is one of the most complex organ failures to characterize. This study performed comprehensive metabolomic profiling that distinguished between septic patients with and without cardiac dysfunction. METHOD: Plasma samples collected from 80 septic patients were analysed by untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics. Principal component analysis (PCA), partial least squares discrimination analysis (PLS-DA), and orthogonal partial least square discriminant analysis (OPLS-DA) were applied to analyse the metabolic model between septic patients with and without cardiac dysfunction. The screening criteria for potential candidate metabolites were as follows: variable importance in the projection (VIP) >1, P < 0.05, and fold change (FC) > 1.5 or < 0.7. Pathway enrichment analysis further revealed associated metabolic pathways. In addition, we constructed a subgroup metabolic analysis between the survivors and non-survivors according to 28-day mortality in the cardiac dysfunction group. RESULTS: Two metabolite markers, kynurenic acid and gluconolactone, could distinguish the cardiac dysfunction group from the normal cardiac function group. Two metabolites, kynurenic acid and galactitol, could distinguish survivors and non-survivors in the subgroup analysis. Kynurenic acid is a common differential metabolite that could be used as a candidate for both diagnosis and prognosis for septic patients with cardiac dysfunction. The main associated pathways were amino acid metabolism, glucose metabolism and bile acid metabolism. CONCLUSION: Metabolomic technology could be a promising approach for identifying diagnostic and prognostic biomarkers of sepsis-induced cardiac dysfunction. Frontiers Media S.A. 2023-02-16 /pmc/articles/PMC9978788/ /pubmed/36875476 http://dx.doi.org/10.3389/fendo.2023.1060470 Text en Copyright © 2023 Cao, Liu, Ma, Fang, Pei, Jing, Huang, Han and Xiao https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Cao, Yan Liu, Zhengyu Ma, Wenfeng Fang, Chen Pei, Yanfang Jing, Yingxia Huang, Jie Han, Xiaotong Xiao, Weiwei Untargeted metabolomic profiling of sepsis-induced cardiac dysfunction |
title | Untargeted metabolomic profiling of sepsis-induced cardiac dysfunction |
title_full | Untargeted metabolomic profiling of sepsis-induced cardiac dysfunction |
title_fullStr | Untargeted metabolomic profiling of sepsis-induced cardiac dysfunction |
title_full_unstemmed | Untargeted metabolomic profiling of sepsis-induced cardiac dysfunction |
title_short | Untargeted metabolomic profiling of sepsis-induced cardiac dysfunction |
title_sort | untargeted metabolomic profiling of sepsis-induced cardiac dysfunction |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9978788/ https://www.ncbi.nlm.nih.gov/pubmed/36875476 http://dx.doi.org/10.3389/fendo.2023.1060470 |
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