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Discovery of a New Biomarker Pattern for Differential Diagnosis of Acute Ischemic Stroke Using Targeted Metabolomics

Stroke is one of the leading causes of disability all over the world. However, biomarkers for fast differential diagnosis of acute ischemic stroke (AIS) from vertigo or headache, remains lacking. Using a direct-infusion mass spectrometry method, it is possible to establish an efficient method for AI...

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Autores principales: Sun, Ruitan, Li, Yan, Cai, Ming, Cao, Yunfeng, Piao, Xiangyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761218/
https://www.ncbi.nlm.nih.gov/pubmed/31608005
http://dx.doi.org/10.3389/fneur.2019.01011
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author Sun, Ruitan
Li, Yan
Cai, Ming
Cao, Yunfeng
Piao, Xiangyu
author_facet Sun, Ruitan
Li, Yan
Cai, Ming
Cao, Yunfeng
Piao, Xiangyu
author_sort Sun, Ruitan
collection PubMed
description Stroke is one of the leading causes of disability all over the world. However, biomarkers for fast differential diagnosis of acute ischemic stroke (AIS) from vertigo or headache, remains lacking. Using a direct-infusion mass spectrometry method, it is possible to establish an efficient method for AIS differential diagnosis that requires only a few minutes. Thirty-eight clearly diagnosed AIS patients and 46 patients with a main complaint of vertigo were enrolled in this study. There was a total of 58 metabolites that were measured by our targeted metabolomics method, and the data were analyzed by pattern recognition algorithms. As a result, a clear classification between AIS and vertigo patients was achieved. Acylcarnitines are the major discriminating metabolites between the two groups. Arginine and its ratio, which is related to urea cycle metabolites, including arginine/ornithine and citrulline/arginine, also accounted for the classification. Interestingly, the levels of these metabolites were also found to be restored among recovering AIS patients (n = 11), which indicated that the metabolic alterations are possibly related to AIS development. Based on the characters from the data pattern reorganization, a novel biomarkers pattern was established using a binary logistic model, which contained arginine, arginine/ornithine, vaccenylcarnitine, and hydroxylbutyrylcarnitine. This biomarkers pattern achieved an area under the receiver operating characteristic curve of 0.89 for the differential diagnosis of AIS. Considering the efficiency and the diagnostic performance of the biomarkers pattern, our method has potential future use for the clinical application.
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spelling pubmed-67612182019-10-13 Discovery of a New Biomarker Pattern for Differential Diagnosis of Acute Ischemic Stroke Using Targeted Metabolomics Sun, Ruitan Li, Yan Cai, Ming Cao, Yunfeng Piao, Xiangyu Front Neurol Neurology Stroke is one of the leading causes of disability all over the world. However, biomarkers for fast differential diagnosis of acute ischemic stroke (AIS) from vertigo or headache, remains lacking. Using a direct-infusion mass spectrometry method, it is possible to establish an efficient method for AIS differential diagnosis that requires only a few minutes. Thirty-eight clearly diagnosed AIS patients and 46 patients with a main complaint of vertigo were enrolled in this study. There was a total of 58 metabolites that were measured by our targeted metabolomics method, and the data were analyzed by pattern recognition algorithms. As a result, a clear classification between AIS and vertigo patients was achieved. Acylcarnitines are the major discriminating metabolites between the two groups. Arginine and its ratio, which is related to urea cycle metabolites, including arginine/ornithine and citrulline/arginine, also accounted for the classification. Interestingly, the levels of these metabolites were also found to be restored among recovering AIS patients (n = 11), which indicated that the metabolic alterations are possibly related to AIS development. Based on the characters from the data pattern reorganization, a novel biomarkers pattern was established using a binary logistic model, which contained arginine, arginine/ornithine, vaccenylcarnitine, and hydroxylbutyrylcarnitine. This biomarkers pattern achieved an area under the receiver operating characteristic curve of 0.89 for the differential diagnosis of AIS. Considering the efficiency and the diagnostic performance of the biomarkers pattern, our method has potential future use for the clinical application. Frontiers Media S.A. 2019-09-19 /pmc/articles/PMC6761218/ /pubmed/31608005 http://dx.doi.org/10.3389/fneur.2019.01011 Text en Copyright © 2019 Sun, Li, Cai, Cao and Piao. http://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 Neurology
Sun, Ruitan
Li, Yan
Cai, Ming
Cao, Yunfeng
Piao, Xiangyu
Discovery of a New Biomarker Pattern for Differential Diagnosis of Acute Ischemic Stroke Using Targeted Metabolomics
title Discovery of a New Biomarker Pattern for Differential Diagnosis of Acute Ischemic Stroke Using Targeted Metabolomics
title_full Discovery of a New Biomarker Pattern for Differential Diagnosis of Acute Ischemic Stroke Using Targeted Metabolomics
title_fullStr Discovery of a New Biomarker Pattern for Differential Diagnosis of Acute Ischemic Stroke Using Targeted Metabolomics
title_full_unstemmed Discovery of a New Biomarker Pattern for Differential Diagnosis of Acute Ischemic Stroke Using Targeted Metabolomics
title_short Discovery of a New Biomarker Pattern for Differential Diagnosis of Acute Ischemic Stroke Using Targeted Metabolomics
title_sort discovery of a new biomarker pattern for differential diagnosis of acute ischemic stroke using targeted metabolomics
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6761218/
https://www.ncbi.nlm.nih.gov/pubmed/31608005
http://dx.doi.org/10.3389/fneur.2019.01011
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