Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.

Despite advancements in ventilator technologies, lung supportive and rescue therapies, the outcome and prognostication in acute respiratory distress syndrome (ARDS) remains incremental and ambiguous. Metabolomics is a potential insightful measure to the diagnostic approaches practiced in critical di...

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Main Authors: Akhila Viswan, Chandan Singh, Ratan Kumar Rai, Afzal Azim, Neeraj Sinha, Arvind Kumar Baronia
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5667881?pdf=render
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author Akhila Viswan
Chandan Singh
Ratan Kumar Rai
Afzal Azim
Neeraj Sinha
Arvind Kumar Baronia
author_facet Akhila Viswan
Chandan Singh
Ratan Kumar Rai
Afzal Azim
Neeraj Sinha
Arvind Kumar Baronia
author_sort Akhila Viswan
collection DOAJ
description Despite advancements in ventilator technologies, lung supportive and rescue therapies, the outcome and prognostication in acute respiratory distress syndrome (ARDS) remains incremental and ambiguous. Metabolomics is a potential insightful measure to the diagnostic approaches practiced in critical disease settings. In our study patients diagnosed with mild and moderate/severe ARDS clinically governed by hypoxemic P/F ratio between 100-300 but with indistinct molecular phenotype were discriminated employing nuclear magnetic resonance (NMR) based metabolomics of mini bronchoalveolar lavage fluid (mBALF). Resulting biomarker prototype comprising six metabolites was substantiated highlighting ARDS susceptibility/recovery. Both the groups (mild and moderate/severe ARDS) showed distinct biochemical profile based on 83.3% classification by discriminant function analysis and cross validated accuracy of 91% using partial least squares discriminant analysis as major classifier. The predictive performance of narrowed down six metabolites were found analogous with chemometrics. The proposed biomarker model consisting of six metabolites proline, lysine/arginine, taurine, threonine and glutamate were found characteristic of ARDS sub-stages with aberrant metabolism observed mainly in arginine, proline metabolism, lysine synthesis and so forth correlating to diseased metabotype. Thus NMR based metabolomics has provided new insight into ARDS sub-stages and conclusively a precise biomarker model proposed, reflecting underlying metabolic dysfunction aiding prior clinical decision making.
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spelling doaj.art-5d5ad0db4f5b43089052c5043e41afc32022-12-22T00:12:41ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-011211e018754510.1371/journal.pone.0187545Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.Akhila ViswanChandan SinghRatan Kumar RaiAfzal AzimNeeraj SinhaArvind Kumar BaroniaDespite advancements in ventilator technologies, lung supportive and rescue therapies, the outcome and prognostication in acute respiratory distress syndrome (ARDS) remains incremental and ambiguous. Metabolomics is a potential insightful measure to the diagnostic approaches practiced in critical disease settings. In our study patients diagnosed with mild and moderate/severe ARDS clinically governed by hypoxemic P/F ratio between 100-300 but with indistinct molecular phenotype were discriminated employing nuclear magnetic resonance (NMR) based metabolomics of mini bronchoalveolar lavage fluid (mBALF). Resulting biomarker prototype comprising six metabolites was substantiated highlighting ARDS susceptibility/recovery. Both the groups (mild and moderate/severe ARDS) showed distinct biochemical profile based on 83.3% classification by discriminant function analysis and cross validated accuracy of 91% using partial least squares discriminant analysis as major classifier. The predictive performance of narrowed down six metabolites were found analogous with chemometrics. The proposed biomarker model consisting of six metabolites proline, lysine/arginine, taurine, threonine and glutamate were found characteristic of ARDS sub-stages with aberrant metabolism observed mainly in arginine, proline metabolism, lysine synthesis and so forth correlating to diseased metabotype. Thus NMR based metabolomics has provided new insight into ARDS sub-stages and conclusively a precise biomarker model proposed, reflecting underlying metabolic dysfunction aiding prior clinical decision making.http://europepmc.org/articles/PMC5667881?pdf=render
spellingShingle Akhila Viswan
Chandan Singh
Ratan Kumar Rai
Afzal Azim
Neeraj Sinha
Arvind Kumar Baronia
Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.
PLoS ONE
title Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.
title_full Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.
title_fullStr Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.
title_full_unstemmed Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.
title_short Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.
title_sort metabolomics based predictive biomarker model of ards a systemic measure of clinical hypoxemia
url http://europepmc.org/articles/PMC5667881?pdf=render
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