Comprehensive metabolomic characterization of atrial fibrillation
BackgroundUsing human humoral metabolomic profiling, we can discover the diagnostic biomarkers and pathogenesis of disease. The specific characterization of atrial fibrillation (AF) subtypes with metabolomics may facilitate effective and targeted treatment, especially in early stages.ObjectivesBy in...
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Frontiers Media S.A.
2022-08-01
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Series: | Frontiers in Cardiovascular Medicine |
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Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2022.911845/full |
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author | Chengcan Lu Chengcan Lu Chengcan Lu Chunyan Liu Di Mei Mengjie Yu Jian Bai Xue Bao Min Wang Kejia Fu Xin Yi Weihong Ge Jizhong Shen Yuzhu Peng Yuzhu Peng Yuzhu Peng Wei Xu |
author_facet | Chengcan Lu Chengcan Lu Chengcan Lu Chunyan Liu Di Mei Mengjie Yu Jian Bai Xue Bao Min Wang Kejia Fu Xin Yi Weihong Ge Jizhong Shen Yuzhu Peng Yuzhu Peng Yuzhu Peng Wei Xu |
author_sort | Chengcan Lu |
collection | DOAJ |
description | BackgroundUsing human humoral metabolomic profiling, we can discover the diagnostic biomarkers and pathogenesis of disease. The specific characterization of atrial fibrillation (AF) subtypes with metabolomics may facilitate effective and targeted treatment, especially in early stages.ObjectivesBy investigating disturbed metabolic pathways, we could evaluate the diagnostic value of biomarkers based on metabolomics for different types of AF.MethodsA cohort of 363 patients was enrolled and divided into a discovery and validation set. Patients underwent an electrocardiogram (ECG) for suspected AF. Groups were divided as follows: healthy individuals (Control), suspected AF (Sus-AF), first diagnosed AF (Fir-AF), paroxysmal AF (Par-AF), persistent AF (Per-AF), and AF causing a cardiogenic ischemic stroke (Car-AF). Serum metabolomic profiles were determined by gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Metabolomic variables were analyzed with clinical information to identify relevant diagnostic biomarkers.ResultsThe metabolic disorders were characterized by 16 cross-comparisons. We focused on comparing all of the types of AF (All-AFs) plus Car-AF vs. Control, All-AFs vs. Car-AF, Par-AF vs. Control, and Par-AF vs. Per-AF. Then, 117 and 94 metabolites were identified by GC/MS and LC-QTOF-MS, respectively. The essential altered metabolic pathways during AF progression included D-glutamine and D-glutamate metabolism, glycerophospholipid metabolism, etc. For differential diagnosis, the area under the curve (AUC) of specific metabolomic biomarkers ranged from 0.8237 to 0.9890 during the discovery phase, and the predictive values in the validation cohort were 78.8–90.2%.ConclusionsSerum metabolomics is a powerful way to identify metabolic disturbances. Differences in small–molecule metabolites may serve as biomarkers for AF onset, progression, and differential diagnosis. |
first_indexed | 2024-04-13T11:15:43Z |
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issn | 2297-055X |
language | English |
last_indexed | 2024-04-13T11:15:43Z |
publishDate | 2022-08-01 |
publisher | Frontiers Media S.A. |
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series | Frontiers in Cardiovascular Medicine |
spelling | doaj.art-8b426a449ae44ddf9061ff699cacf0102022-12-22T02:48:59ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2022-08-01910.3389/fcvm.2022.911845911845Comprehensive metabolomic characterization of atrial fibrillationChengcan Lu0Chengcan Lu1Chengcan Lu2Chunyan Liu3Di Mei4Mengjie Yu5Jian Bai6Xue Bao7Min Wang8Kejia Fu9Xin Yi10Weihong Ge11Jizhong Shen12Yuzhu Peng13Yuzhu Peng14Yuzhu Peng15Wei Xu16Nanjing Drum Tower Hospital, China Pharmaceutical University, Nanjing, ChinaDepartment of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Cardiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaNanjing Drum Tower Hospital, China Pharmaceutical University, Nanjing, ChinaNanjing Drum Tower Hospital, China Pharmaceutical University, Nanjing, ChinaKey Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, ChinaDepartment of Cardiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Cardiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaNanjing Drum Tower Hospital, China Pharmaceutical University, Nanjing, ChinaKey Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, ChinaDepartment of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaNanjing Drum Tower Hospital, China Pharmaceutical University, Nanjing, ChinaDepartment of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaDepartment of Cardiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, ChinaNanjing Drum Tower Hospital, China Pharmaceutical University, Nanjing, ChinaBackgroundUsing human humoral metabolomic profiling, we can discover the diagnostic biomarkers and pathogenesis of disease. The specific characterization of atrial fibrillation (AF) subtypes with metabolomics may facilitate effective and targeted treatment, especially in early stages.ObjectivesBy investigating disturbed metabolic pathways, we could evaluate the diagnostic value of biomarkers based on metabolomics for different types of AF.MethodsA cohort of 363 patients was enrolled and divided into a discovery and validation set. Patients underwent an electrocardiogram (ECG) for suspected AF. Groups were divided as follows: healthy individuals (Control), suspected AF (Sus-AF), first diagnosed AF (Fir-AF), paroxysmal AF (Par-AF), persistent AF (Per-AF), and AF causing a cardiogenic ischemic stroke (Car-AF). Serum metabolomic profiles were determined by gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Metabolomic variables were analyzed with clinical information to identify relevant diagnostic biomarkers.ResultsThe metabolic disorders were characterized by 16 cross-comparisons. We focused on comparing all of the types of AF (All-AFs) plus Car-AF vs. Control, All-AFs vs. Car-AF, Par-AF vs. Control, and Par-AF vs. Per-AF. Then, 117 and 94 metabolites were identified by GC/MS and LC-QTOF-MS, respectively. The essential altered metabolic pathways during AF progression included D-glutamine and D-glutamate metabolism, glycerophospholipid metabolism, etc. For differential diagnosis, the area under the curve (AUC) of specific metabolomic biomarkers ranged from 0.8237 to 0.9890 during the discovery phase, and the predictive values in the validation cohort were 78.8–90.2%.ConclusionsSerum metabolomics is a powerful way to identify metabolic disturbances. Differences in small–molecule metabolites may serve as biomarkers for AF onset, progression, and differential diagnosis.https://www.frontiersin.org/articles/10.3389/fcvm.2022.911845/fullatrial fibrillationmetabolomicsdiagnostic modelrisk factorsbiomarker |
spellingShingle | Chengcan Lu Chengcan Lu Chengcan Lu Chunyan Liu Di Mei Mengjie Yu Jian Bai Xue Bao Min Wang Kejia Fu Xin Yi Weihong Ge Jizhong Shen Yuzhu Peng Yuzhu Peng Yuzhu Peng Wei Xu Comprehensive metabolomic characterization of atrial fibrillation Frontiers in Cardiovascular Medicine atrial fibrillation metabolomics diagnostic model risk factors biomarker |
title | Comprehensive metabolomic characterization of atrial fibrillation |
title_full | Comprehensive metabolomic characterization of atrial fibrillation |
title_fullStr | Comprehensive metabolomic characterization of atrial fibrillation |
title_full_unstemmed | Comprehensive metabolomic characterization of atrial fibrillation |
title_short | Comprehensive metabolomic characterization of atrial fibrillation |
title_sort | comprehensive metabolomic characterization of atrial fibrillation |
topic | atrial fibrillation metabolomics diagnostic model risk factors biomarker |
url | https://www.frontiersin.org/articles/10.3389/fcvm.2022.911845/full |
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