Plasma Metabolites Alert Patients With Chest Pain to Occurrence of Myocardial Infarction

Myocardial infarction (MI) is one of the leading causes of death worldwide, and knowing the early warning signs of MI is lifesaving. To expand our knowledge of MI, we analyzed plasma metabolites in MI and non-MI chest pain cases to identify markers for alerting about MI occurrence based on metabolom...

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Main Authors: Nan Aa, Ying Lu, Mengjie Yu, Heng Tang, Zhenyao Lu, Runbing Sun, Liansheng Wang, Chunjian Li, Zhijian Yang, Jiye Aa, Xiangqing Kong, Guangji Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-04-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2021.652746/full
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author Nan Aa
Ying Lu
Mengjie Yu
Heng Tang
Zhenyao Lu
Runbing Sun
Liansheng Wang
Chunjian Li
Zhijian Yang
Jiye Aa
Xiangqing Kong
Guangji Wang
author_facet Nan Aa
Ying Lu
Mengjie Yu
Heng Tang
Zhenyao Lu
Runbing Sun
Liansheng Wang
Chunjian Li
Zhijian Yang
Jiye Aa
Xiangqing Kong
Guangji Wang
author_sort Nan Aa
collection DOAJ
description Myocardial infarction (MI) is one of the leading causes of death worldwide, and knowing the early warning signs of MI is lifesaving. To expand our knowledge of MI, we analyzed plasma metabolites in MI and non-MI chest pain cases to identify markers for alerting about MI occurrence based on metabolomics. A total of 230 volunteers were recruited, consisting of 146 chest pain patients admitted with suspected MI (85 MIs and 61 non-MI chest pain cases) and 84 control individuals. Non-MI cardiac chest pain cases include unstable angina (UA), myocarditis, valvular heart diseases, etc. The blood samples of all suspected MI cases were collected not longer than 6 h since the onset of chest pain. Gas chromatography–mass spectrometry and liquid chromatography–mass spectrometry were applied to identify and quantify the plasma metabolites. Multivariate statistical analysis was utilized to analyze the data, and principal component analysis showed MI could be clearly distinguished from non-MI chest pain cases (including UA and other cases) in the scores plot of metabolomic data, better than that based on the data constructed with medical history and clinical biochemical parameters. Pathway analysis highlighted an upregulated methionine metabolism and downregulated arginine biosynthesis in MI cases. Receiver operating characteristic curve (ROC) and adjusted odds ratio (OR) were calculated to evaluate potential markers for the diagnosis and prediction ability of MI (MI vs. non-MI cases). Finally, gene expression profiles from the Gene Expression Omnibus (GEO) database were briefly discussed to study differential metabolites' connection with plasma transcriptomics. Deoxyuridine (dU), homoserine, and methionine scored highly in ROC analysis (AUC > 0.91), sensitivity (>80%), and specificity (>94%), and they were correlated to LDH and AST (p < 0.05). OR values suggested, after adjusting for gender, age, lipid levels, smoking, type II diabetes, and hypertension history, that high levels of dU of positive logOR = 3.01, methionine of logOR = 3.48, and homoserine of logOR = 1.61 and low levels of isopentenyl diphosphate (IDP) of negative logOR = −5.15, uracil of logOR = −2.38, and arginine of logOR = −0.82 were independent risk factors of MI. Our study highlighted that metabolites belonging to pyrimidine, methionine, and arginine metabolism are deeply influenced in MI plasma samples. dU, homoserine, and methionine are potential markers to recognize MI cases from other cardiac chest pain cases after the onset of chest pains. Individuals with high plasma abundance of dU, homoserine, or methionine have increased risk of MI, too.
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spelling doaj.art-04563c9c6f4a47058f8a223ad34c15c82022-12-21T19:54:45ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2021-04-01810.3389/fcvm.2021.652746652746Plasma Metabolites Alert Patients With Chest Pain to Occurrence of Myocardial InfarctionNan Aa0Ying Lu1Mengjie Yu2Heng Tang3Zhenyao Lu4Runbing Sun5Liansheng Wang6Chunjian Li7Zhijian Yang8Jiye Aa9Xiangqing Kong10Guangji Wang11Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Laboratory, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaLaboratory of Metabolomics, Jiangsu Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaLaboratory of Metabolomics, Jiangsu Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, ChinaLaboratory of Metabolomics, Jiangsu Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaLaboratory of Metabolomics, Jiangsu Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, ChinaDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaLaboratory of Metabolomics, Jiangsu Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, ChinaMyocardial infarction (MI) is one of the leading causes of death worldwide, and knowing the early warning signs of MI is lifesaving. To expand our knowledge of MI, we analyzed plasma metabolites in MI and non-MI chest pain cases to identify markers for alerting about MI occurrence based on metabolomics. A total of 230 volunteers were recruited, consisting of 146 chest pain patients admitted with suspected MI (85 MIs and 61 non-MI chest pain cases) and 84 control individuals. Non-MI cardiac chest pain cases include unstable angina (UA), myocarditis, valvular heart diseases, etc. The blood samples of all suspected MI cases were collected not longer than 6 h since the onset of chest pain. Gas chromatography–mass spectrometry and liquid chromatography–mass spectrometry were applied to identify and quantify the plasma metabolites. Multivariate statistical analysis was utilized to analyze the data, and principal component analysis showed MI could be clearly distinguished from non-MI chest pain cases (including UA and other cases) in the scores plot of metabolomic data, better than that based on the data constructed with medical history and clinical biochemical parameters. Pathway analysis highlighted an upregulated methionine metabolism and downregulated arginine biosynthesis in MI cases. Receiver operating characteristic curve (ROC) and adjusted odds ratio (OR) were calculated to evaluate potential markers for the diagnosis and prediction ability of MI (MI vs. non-MI cases). Finally, gene expression profiles from the Gene Expression Omnibus (GEO) database were briefly discussed to study differential metabolites' connection with plasma transcriptomics. Deoxyuridine (dU), homoserine, and methionine scored highly in ROC analysis (AUC > 0.91), sensitivity (>80%), and specificity (>94%), and they were correlated to LDH and AST (p < 0.05). OR values suggested, after adjusting for gender, age, lipid levels, smoking, type II diabetes, and hypertension history, that high levels of dU of positive logOR = 3.01, methionine of logOR = 3.48, and homoserine of logOR = 1.61 and low levels of isopentenyl diphosphate (IDP) of negative logOR = −5.15, uracil of logOR = −2.38, and arginine of logOR = −0.82 were independent risk factors of MI. Our study highlighted that metabolites belonging to pyrimidine, methionine, and arginine metabolism are deeply influenced in MI plasma samples. dU, homoserine, and methionine are potential markers to recognize MI cases from other cardiac chest pain cases after the onset of chest pains. Individuals with high plasma abundance of dU, homoserine, or methionine have increased risk of MI, too.https://www.frontiersin.org/articles/10.3389/fcvm.2021.652746/fullmyocardial infarctionrisk factorsbiomarkermetabolomicsargininedeoxyuridine
spellingShingle Nan Aa
Ying Lu
Mengjie Yu
Heng Tang
Zhenyao Lu
Runbing Sun
Liansheng Wang
Chunjian Li
Zhijian Yang
Jiye Aa
Xiangqing Kong
Guangji Wang
Plasma Metabolites Alert Patients With Chest Pain to Occurrence of Myocardial Infarction
Frontiers in Cardiovascular Medicine
myocardial infarction
risk factors
biomarker
metabolomics
arginine
deoxyuridine
title Plasma Metabolites Alert Patients With Chest Pain to Occurrence of Myocardial Infarction
title_full Plasma Metabolites Alert Patients With Chest Pain to Occurrence of Myocardial Infarction
title_fullStr Plasma Metabolites Alert Patients With Chest Pain to Occurrence of Myocardial Infarction
title_full_unstemmed Plasma Metabolites Alert Patients With Chest Pain to Occurrence of Myocardial Infarction
title_short Plasma Metabolites Alert Patients With Chest Pain to Occurrence of Myocardial Infarction
title_sort plasma metabolites alert patients with chest pain to occurrence of myocardial infarction
topic myocardial infarction
risk factors
biomarker
metabolomics
arginine
deoxyuridine
url https://www.frontiersin.org/articles/10.3389/fcvm.2021.652746/full
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