Metabonomic Biomarkers of Plaque Burden and Instability in Patients With Coronary Atherosclerotic Disease After Moderate Lipid‐Lowering Therapy
Background Contemporary risk assessment in patients with coronary atherosclerotic disease (CAD) often relies on invasive angiography. However, we aimed to explore the potential of metabolomic biomarkers in reflecting residual risk in patients with CAD after moderate lipid‐lowering therapy. Methods a...
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Wiley
2024-12-01
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| Series: | Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease |
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| Online Access: | https://www.ahajournals.org/doi/10.1161/JAHA.124.036906 |
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| author | Zhendong Mei Lili Xu Qingxia Huang Chenhao Lin Mengyao Yu Shalaimaiti Shali Hongyi Wu Yijing Lu Runda Wu Zhen Wang Lingfeng Luo Zhonghan Sun Liang Sun Juying Qian Guochong Chen Huiru Tang Kang Yao Yan Zheng Yuxiang Dai Junbo Ge |
| author_facet | Zhendong Mei Lili Xu Qingxia Huang Chenhao Lin Mengyao Yu Shalaimaiti Shali Hongyi Wu Yijing Lu Runda Wu Zhen Wang Lingfeng Luo Zhonghan Sun Liang Sun Juying Qian Guochong Chen Huiru Tang Kang Yao Yan Zheng Yuxiang Dai Junbo Ge |
| author_sort | Zhendong Mei |
| collection | DOAJ |
| description | Background Contemporary risk assessment in patients with coronary atherosclerotic disease (CAD) often relies on invasive angiography. However, we aimed to explore the potential of metabolomic biomarkers in reflecting residual risk in patients with CAD after moderate lipid‐lowering therapy. Methods and Results We analyzed serum metabolomic profile among 2560 patients with newly diagnosed CAD undergoing moderate lipid‐lowering therapy, through nuclear magnetic resonance spectroscopy and quantified 175 metabolites, predominantly lipoproteins and their components. CAD severity was evaluated using Gensini score for plaque burden and circulating cardiac troponin T levels for plaque instability. The association of metabolites with CAD severity was examined using multivariate linear regression, and the underlying potential causality was explored using a 2‐sample Mendelian randomization approach. Two composite metabolomic indices were constructed to reflect CAD severity using least absolute shrinkage and selection operator linear regression, and their associations with risk of major adverse cardiac events during a median follow‐up of 3.8 years were evaluated using Cox models. Our investigation revealed that triglycerides and apolipoprotein B in low‐density lipoprotein particles displayed stronger associations with CAD severity compared with the clinically used low‐density lipoprotein cholesterol marker. In large high‐density lipoprotein, components like cholesterol, cholesterol esters, triglyceride, apolipoprotein A1/A2 showed inverse associations with CAD severity. Certain metabolites, including apolipoprotein B and dihydrothymine, showed a putative causal link with Gensini score. Notably, per standard deviation increase in Gensini score–based metabolomic index was associated with 14.8% higher major adverse cardiac event risk (hazard ratio, 1.148 [95% CI, 1.018–1.295]) independent of demographic factors, medication use, and disease status. Conclusions Our findings highlight the potential of nuclear magnetic resonance–based metabolomics in identifying novel biomarkers of plaque burden and instability. Metabolites related to plaque burden may facilitate noninvasive assessment of CAD prognosis. |
| format | Article |
| id | doaj-art-97d9acceddcb4c9cbce924c40deb26c1 |
| institution | OA Journals |
| issn | 2047-9980 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
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| series | Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease |
| spelling | doaj-art-97d9acceddcb4c9cbce924c40deb26c12025-08-20T01:57:54ZengWileyJournal of the American Heart Association: Cardiovascular and Cerebrovascular Disease2047-99802024-12-01132410.1161/JAHA.124.036906Metabonomic Biomarkers of Plaque Burden and Instability in Patients With Coronary Atherosclerotic Disease After Moderate Lipid‐Lowering TherapyZhendong Mei0Lili Xu1Qingxia Huang2Chenhao Lin3Mengyao Yu4Shalaimaiti Shali5Hongyi Wu6Yijing Lu7Runda Wu8Zhen Wang9Lingfeng Luo10Zhonghan Sun11Liang Sun12Juying Qian13Guochong Chen14Huiru Tang15Kang Yao16Yan Zheng17Yuxiang Dai18Junbo Ge19Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital Fudan University Shanghai ChinaState Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute Fudan University Shanghai ChinaHuman Phenome Institute, Zhangjiang Fudan International Innovation Center Fudan University Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaState Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute Fudan University Shanghai ChinaState Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute Fudan University Shanghai ChinaMinistry of Education Key Laboratory of Public Health Safety, School of Public Health, Institute of Nutrition Fudan University Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaDepartment of Nutrition and Food Hygiene, School of Public Health Suzhou Medical College of Soochow University Suzhou ChinaState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital Fudan University Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases National Clinical Research Center for Interventional Medicine Shanghai ChinaBackground Contemporary risk assessment in patients with coronary atherosclerotic disease (CAD) often relies on invasive angiography. However, we aimed to explore the potential of metabolomic biomarkers in reflecting residual risk in patients with CAD after moderate lipid‐lowering therapy. Methods and Results We analyzed serum metabolomic profile among 2560 patients with newly diagnosed CAD undergoing moderate lipid‐lowering therapy, through nuclear magnetic resonance spectroscopy and quantified 175 metabolites, predominantly lipoproteins and their components. CAD severity was evaluated using Gensini score for plaque burden and circulating cardiac troponin T levels for plaque instability. The association of metabolites with CAD severity was examined using multivariate linear regression, and the underlying potential causality was explored using a 2‐sample Mendelian randomization approach. Two composite metabolomic indices were constructed to reflect CAD severity using least absolute shrinkage and selection operator linear regression, and their associations with risk of major adverse cardiac events during a median follow‐up of 3.8 years were evaluated using Cox models. Our investigation revealed that triglycerides and apolipoprotein B in low‐density lipoprotein particles displayed stronger associations with CAD severity compared with the clinically used low‐density lipoprotein cholesterol marker. In large high‐density lipoprotein, components like cholesterol, cholesterol esters, triglyceride, apolipoprotein A1/A2 showed inverse associations with CAD severity. Certain metabolites, including apolipoprotein B and dihydrothymine, showed a putative causal link with Gensini score. Notably, per standard deviation increase in Gensini score–based metabolomic index was associated with 14.8% higher major adverse cardiac event risk (hazard ratio, 1.148 [95% CI, 1.018–1.295]) independent of demographic factors, medication use, and disease status. Conclusions Our findings highlight the potential of nuclear magnetic resonance–based metabolomics in identifying novel biomarkers of plaque burden and instability. Metabolites related to plaque burden may facilitate noninvasive assessment of CAD prognosis.https://www.ahajournals.org/doi/10.1161/JAHA.124.036906coronary atherosclerosis severitymetabolomicsprognosisrisk assessment |
| spellingShingle | Zhendong Mei Lili Xu Qingxia Huang Chenhao Lin Mengyao Yu Shalaimaiti Shali Hongyi Wu Yijing Lu Runda Wu Zhen Wang Lingfeng Luo Zhonghan Sun Liang Sun Juying Qian Guochong Chen Huiru Tang Kang Yao Yan Zheng Yuxiang Dai Junbo Ge Metabonomic Biomarkers of Plaque Burden and Instability in Patients With Coronary Atherosclerotic Disease After Moderate Lipid‐Lowering Therapy Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease coronary atherosclerosis severity metabolomics prognosis risk assessment |
| title | Metabonomic Biomarkers of Plaque Burden and Instability in Patients With Coronary Atherosclerotic Disease After Moderate Lipid‐Lowering Therapy |
| title_full | Metabonomic Biomarkers of Plaque Burden and Instability in Patients With Coronary Atherosclerotic Disease After Moderate Lipid‐Lowering Therapy |
| title_fullStr | Metabonomic Biomarkers of Plaque Burden and Instability in Patients With Coronary Atherosclerotic Disease After Moderate Lipid‐Lowering Therapy |
| title_full_unstemmed | Metabonomic Biomarkers of Plaque Burden and Instability in Patients With Coronary Atherosclerotic Disease After Moderate Lipid‐Lowering Therapy |
| title_short | Metabonomic Biomarkers of Plaque Burden and Instability in Patients With Coronary Atherosclerotic Disease After Moderate Lipid‐Lowering Therapy |
| title_sort | metabonomic biomarkers of plaque burden and instability in patients with coronary atherosclerotic disease after moderate lipid lowering therapy |
| topic | coronary atherosclerosis severity metabolomics prognosis risk assessment |
| url | https://www.ahajournals.org/doi/10.1161/JAHA.124.036906 |
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