NMR Metabolomics and Random Forests Models to Identify Potential Plasma Biomarkers of Blood Stasis Syndrome With Coronary Heart Disease Patients

BackgroundCoronary heart disease (CHD) remains highly prevalent and is one of the largest causes of death worldwide. Blood stasis syndrome (BSS) is the main syndrome associated with CHD. However, the underlying biological basis of BSS with CHD is not yet been fully understood.Materials and MethodsWe...

Full description

Bibliographic Details
Main Authors: Lin-Lin Zhao, Xin-Jian Qiu, Wen-Bo Wang, Ruo-Meng Li, Dong-Sheng Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-09-01
Series:Frontiers in Physiology
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fphys.2019.01109/full
id doaj-5cdd799196334469995c5fb5a0faaae2
record_format Article
spelling doaj-5cdd799196334469995c5fb5a0faaae22020-11-24T22:20:30ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2019-09-011010.3389/fphys.2019.01109465172NMR Metabolomics and Random Forests Models to Identify Potential Plasma Biomarkers of Blood Stasis Syndrome With Coronary Heart Disease PatientsLin-Lin Zhao0Xin-Jian Qiu1Wen-Bo Wang2Ruo-Meng Li3Dong-Sheng Wang4Health Management Department, The Third Xiangya Hospital, Central South University, Changsha, ChinaInstitute of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Changsha, ChinaInstitute of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Changsha, ChinaTraditional Chinese Medicine Department, The Third Xiangya Hospital, Central South University, Changsha, ChinaInstitute of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University, Changsha, ChinaBackgroundCoronary heart disease (CHD) remains highly prevalent and is one of the largest causes of death worldwide. Blood stasis syndrome (BSS) is the main syndrome associated with CHD. However, the underlying biological basis of BSS with CHD is not yet been fully understood.Materials and MethodsWe proposed a metabolomics method based on 1H-NMR and random forest (RF) models to elucidate the underlying biological basis of BSS with CHD. Firstly, 58 cases of CHD patients, including 27 BSS and 31 phlegm syndrome (PS), and 26 volunteers were recruited from Xiangya Hospital affiliated to Central South University. A 1 mL venous blood sample was collected for NMR analysis. Secondly, principal component analysis (PCA), partial least squares discrimination analysis (PLS-DA) and RF was applied to observe the classification of each group, respectively. Finally, RF and multidimensional scaling (MDS) were utilized to discover the plasma potential biomarkers in CHD patients and CHD–BSS patients.ResultsThe models constructed by RF could visually discriminate BSS from PS in CHD patients. Simultaneously, we obtained 12 characteristic metabolites, including lysine, glutamine, taurine, tyrosine, phenylalanine, histidine, lipid, citrate, choline, lactate, α-glucose, β-glucose related to the CHD patients, and Choline, β-glucose, α-glucose and tyrosine were considered as potential biomarkers of CHD–BSS.ConclusionThe combining of 1H-NMR profiling with RF models was a useful approach to analyze complex metabolomics data (should be deleted). Choline, β-glucose, α-glucose and tyrosine were considered as potential biomarkers of CHD–BSS.https://www.frontiersin.org/article/10.3389/fphys.2019.01109/fullcoronary heart diseaseblood stasis syndromemetabolomicsrandom forestsZHENG typesSystems Biology
collection DOAJ
language English
format Article
sources DOAJ
author Lin-Lin Zhao
Xin-Jian Qiu
Wen-Bo Wang
Ruo-Meng Li
Dong-Sheng Wang
spellingShingle Lin-Lin Zhao
Xin-Jian Qiu
Wen-Bo Wang
Ruo-Meng Li
Dong-Sheng Wang
NMR Metabolomics and Random Forests Models to Identify Potential Plasma Biomarkers of Blood Stasis Syndrome With Coronary Heart Disease Patients
Frontiers in Physiology
coronary heart disease
blood stasis syndrome
metabolomics
random forests
ZHENG types
Systems Biology
author_facet Lin-Lin Zhao
Xin-Jian Qiu
Wen-Bo Wang
Ruo-Meng Li
Dong-Sheng Wang
author_sort Lin-Lin Zhao
title NMR Metabolomics and Random Forests Models to Identify Potential Plasma Biomarkers of Blood Stasis Syndrome With Coronary Heart Disease Patients
title_short NMR Metabolomics and Random Forests Models to Identify Potential Plasma Biomarkers of Blood Stasis Syndrome With Coronary Heart Disease Patients
title_full NMR Metabolomics and Random Forests Models to Identify Potential Plasma Biomarkers of Blood Stasis Syndrome With Coronary Heart Disease Patients
title_fullStr NMR Metabolomics and Random Forests Models to Identify Potential Plasma Biomarkers of Blood Stasis Syndrome With Coronary Heart Disease Patients
title_full_unstemmed NMR Metabolomics and Random Forests Models to Identify Potential Plasma Biomarkers of Blood Stasis Syndrome With Coronary Heart Disease Patients
title_sort nmr metabolomics and random forests models to identify potential plasma biomarkers of blood stasis syndrome with coronary heart disease patients
publisher Frontiers Media S.A.
series Frontiers in Physiology
issn 1664-042X
publishDate 2019-09-01
description BackgroundCoronary heart disease (CHD) remains highly prevalent and is one of the largest causes of death worldwide. Blood stasis syndrome (BSS) is the main syndrome associated with CHD. However, the underlying biological basis of BSS with CHD is not yet been fully understood.Materials and MethodsWe proposed a metabolomics method based on 1H-NMR and random forest (RF) models to elucidate the underlying biological basis of BSS with CHD. Firstly, 58 cases of CHD patients, including 27 BSS and 31 phlegm syndrome (PS), and 26 volunteers were recruited from Xiangya Hospital affiliated to Central South University. A 1 mL venous blood sample was collected for NMR analysis. Secondly, principal component analysis (PCA), partial least squares discrimination analysis (PLS-DA) and RF was applied to observe the classification of each group, respectively. Finally, RF and multidimensional scaling (MDS) were utilized to discover the plasma potential biomarkers in CHD patients and CHD–BSS patients.ResultsThe models constructed by RF could visually discriminate BSS from PS in CHD patients. Simultaneously, we obtained 12 characteristic metabolites, including lysine, glutamine, taurine, tyrosine, phenylalanine, histidine, lipid, citrate, choline, lactate, α-glucose, β-glucose related to the CHD patients, and Choline, β-glucose, α-glucose and tyrosine were considered as potential biomarkers of CHD–BSS.ConclusionThe combining of 1H-NMR profiling with RF models was a useful approach to analyze complex metabolomics data (should be deleted). Choline, β-glucose, α-glucose and tyrosine were considered as potential biomarkers of CHD–BSS.
topic coronary heart disease
blood stasis syndrome
metabolomics
random forests
ZHENG types
Systems Biology
url https://www.frontiersin.org/article/10.3389/fphys.2019.01109/full
work_keys_str_mv AT linlinzhao nmrmetabolomicsandrandomforestsmodelstoidentifypotentialplasmabiomarkersofbloodstasissyndromewithcoronaryheartdiseasepatients
AT xinjianqiu nmrmetabolomicsandrandomforestsmodelstoidentifypotentialplasmabiomarkersofbloodstasissyndromewithcoronaryheartdiseasepatients
AT wenbowang nmrmetabolomicsandrandomforestsmodelstoidentifypotentialplasmabiomarkersofbloodstasissyndromewithcoronaryheartdiseasepatients
AT ruomengli nmrmetabolomicsandrandomforestsmodelstoidentifypotentialplasmabiomarkersofbloodstasissyndromewithcoronaryheartdiseasepatients
AT dongshengwang nmrmetabolomicsandrandomforestsmodelstoidentifypotentialplasmabiomarkersofbloodstasissyndromewithcoronaryheartdiseasepatients
_version_ 1725774783050678272