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...
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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 |
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