Cargando…

High-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction

High-throughput metabolic profiling technology has been used for biomarker discovery and to reveal underlying metabolic mechanisms. Sepsis-induced myocardial dysfunction (SMD) is a common complication in sepsis patients, and severely affects their quality of life. However, the pathogenesis of SMD is...

Descripción completa

Detalles Bibliográficos
Autores principales: Liang, Qun, Liu, Han, Li, Xiuli, Hairong, Panguo, Sun, Peiyang, Yang, Yang, Du, Chunpeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9087870/
https://www.ncbi.nlm.nih.gov/pubmed/35548688
http://dx.doi.org/10.1039/c8ra07572g
_version_ 1784704248016011264
author Liang, Qun
Liu, Han
Li, Xiuli
Hairong, Panguo
Sun, Peiyang
Yang, Yang
Du, Chunpeng
author_facet Liang, Qun
Liu, Han
Li, Xiuli
Hairong, Panguo
Sun, Peiyang
Yang, Yang
Du, Chunpeng
author_sort Liang, Qun
collection PubMed
description High-throughput metabolic profiling technology has been used for biomarker discovery and to reveal underlying metabolic mechanisms. Sepsis-induced myocardial dysfunction (SMD) is a common complication in sepsis patients, and severely affects their quality of life. However, the pathogenesis of SMD is currently unclear, and there has been inadequate basic research. In this study, metabolic profiling was explored by liquid chromatography/mass spectrometry (LC/MS) combined with chemometrics and bioinformatic analysis. The global metabolome data were analyzed using chemometrics analysis including principal component analysis and partial least squares discriminant analysis for significant metabolites. Variable importance for projection values obtained utilizing a pattern recognition method were used to identify potential biomarkers. The differential metabolites were putatively identified using the metabolome database and bioinformatics analysis was conducted via Ingenuity Pathway Analysis (IPA) to predict the likely functional alterations. In total, 21 differential metabolites were found in SMD and these were involved in phenylalanine, tyrosine and tryptophan biosynthesis, arachidonic acid metabolism, glycine, serine and threonine metabolism, and so on. The analysis revealed that the metabolites were strongly related to molecular transport, and small molecule biochemistry metabolic pathways. The present study indicates that high-throughput metabolic profiling, combined with chemometrics and a bioinformatic platform, can reveal the likely functional alterations in disease and could provide more precise and credible information in the basic research of disease pathogenesis.
format Online
Article
Text
id pubmed-9087870
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher The Royal Society of Chemistry
record_format MEDLINE/PubMed
spelling pubmed-90878702022-05-10 High-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction Liang, Qun Liu, Han Li, Xiuli Hairong, Panguo Sun, Peiyang Yang, Yang Du, Chunpeng RSC Adv Chemistry High-throughput metabolic profiling technology has been used for biomarker discovery and to reveal underlying metabolic mechanisms. Sepsis-induced myocardial dysfunction (SMD) is a common complication in sepsis patients, and severely affects their quality of life. However, the pathogenesis of SMD is currently unclear, and there has been inadequate basic research. In this study, metabolic profiling was explored by liquid chromatography/mass spectrometry (LC/MS) combined with chemometrics and bioinformatic analysis. The global metabolome data were analyzed using chemometrics analysis including principal component analysis and partial least squares discriminant analysis for significant metabolites. Variable importance for projection values obtained utilizing a pattern recognition method were used to identify potential biomarkers. The differential metabolites were putatively identified using the metabolome database and bioinformatics analysis was conducted via Ingenuity Pathway Analysis (IPA) to predict the likely functional alterations. In total, 21 differential metabolites were found in SMD and these were involved in phenylalanine, tyrosine and tryptophan biosynthesis, arachidonic acid metabolism, glycine, serine and threonine metabolism, and so on. The analysis revealed that the metabolites were strongly related to molecular transport, and small molecule biochemistry metabolic pathways. The present study indicates that high-throughput metabolic profiling, combined with chemometrics and a bioinformatic platform, can reveal the likely functional alterations in disease and could provide more precise and credible information in the basic research of disease pathogenesis. The Royal Society of Chemistry 2019-01-24 /pmc/articles/PMC9087870/ /pubmed/35548688 http://dx.doi.org/10.1039/c8ra07572g Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Chemistry
Liang, Qun
Liu, Han
Li, Xiuli
Hairong, Panguo
Sun, Peiyang
Yang, Yang
Du, Chunpeng
High-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction
title High-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction
title_full High-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction
title_fullStr High-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction
title_full_unstemmed High-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction
title_short High-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction
title_sort high-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9087870/
https://www.ncbi.nlm.nih.gov/pubmed/35548688
http://dx.doi.org/10.1039/c8ra07572g
work_keys_str_mv AT liangqun highthroughputmetabolicprofilingcombinedwithchemometricsandbioinformaticanalysisrevealsfunctionalalterationsinmyocardialdysfunction
AT liuhan highthroughputmetabolicprofilingcombinedwithchemometricsandbioinformaticanalysisrevealsfunctionalalterationsinmyocardialdysfunction
AT lixiuli highthroughputmetabolicprofilingcombinedwithchemometricsandbioinformaticanalysisrevealsfunctionalalterationsinmyocardialdysfunction
AT hairongpanguo highthroughputmetabolicprofilingcombinedwithchemometricsandbioinformaticanalysisrevealsfunctionalalterationsinmyocardialdysfunction
AT sunpeiyang highthroughputmetabolicprofilingcombinedwithchemometricsandbioinformaticanalysisrevealsfunctionalalterationsinmyocardialdysfunction
AT yangyang highthroughputmetabolicprofilingcombinedwithchemometricsandbioinformaticanalysisrevealsfunctionalalterationsinmyocardialdysfunction
AT duchunpeng highthroughputmetabolicprofilingcombinedwithchemometricsandbioinformaticanalysisrevealsfunctionalalterationsinmyocardialdysfunction