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Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease

BACKGROUND: Coronary artery disease (CAD) is a metabolically perturbed pathological condition. However, the knowledge of metabolic signatures on outcomes of CAD and their potential causal effects and impacts on left ventricular remodeling remains limited. We aim to assess the contribution of plasma...

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Autores principales: Zhu, Qian, Qin, Min, Wang, Zixian, Wu, Yonglin, Chen, Xiaoping, Liu, Chen, Ma, Qilin, Liu, Yibin, Lai, Weihua, Chen, Hui, Cai, Jingjing, Liu, Yemao, Lei, Fang, Zhang, Bin, Zhang, Shuyao, He, Guodong, Li, Hanping, Zhang, Mingliang, Zheng, Hui, Chen, Jiyan, Huang, Min, Zhong, Shilong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9569076/
https://www.ncbi.nlm.nih.gov/pubmed/36242008
http://dx.doi.org/10.1186/s13578-022-00863-x
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author Zhu, Qian
Qin, Min
Wang, Zixian
Wu, Yonglin
Chen, Xiaoping
Liu, Chen
Ma, Qilin
Liu, Yibin
Lai, Weihua
Chen, Hui
Cai, Jingjing
Liu, Yemao
Lei, Fang
Zhang, Bin
Zhang, Shuyao
He, Guodong
Li, Hanping
Zhang, Mingliang
Zheng, Hui
Chen, Jiyan
Huang, Min
Zhong, Shilong
author_facet Zhu, Qian
Qin, Min
Wang, Zixian
Wu, Yonglin
Chen, Xiaoping
Liu, Chen
Ma, Qilin
Liu, Yibin
Lai, Weihua
Chen, Hui
Cai, Jingjing
Liu, Yemao
Lei, Fang
Zhang, Bin
Zhang, Shuyao
He, Guodong
Li, Hanping
Zhang, Mingliang
Zheng, Hui
Chen, Jiyan
Huang, Min
Zhong, Shilong
author_sort Zhu, Qian
collection PubMed
description BACKGROUND: Coronary artery disease (CAD) is a metabolically perturbed pathological condition. However, the knowledge of metabolic signatures on outcomes of CAD and their potential causal effects and impacts on left ventricular remodeling remains limited. We aim to assess the contribution of plasma metabolites to the risk of death and major adverse cardiovascular events (MACE) as well as left ventricular remodeling. RESULTS: In a prospective study with 1606 Chinese patients with CAD, we have identified and validated several independent metabolic signatures through widely-targeted metabolomics. The predictive model respectively integrating four metabolic signatures (dulcitol, β-pseudouridine, 3,3ʹ,5-Triiodo-l-thyronine, and kynurenine) for death (AUC of 83.7% vs. 76.6%, positive IDI of 0.096) and metabolic signatures (kynurenine, lysoPC 20:2, 5-methyluridine, and l-tryptophan) for MACE (AUC of 67.4% vs. 59.8%, IDI of 0.068) yielded better predictive value than trimethylamine N-oxide plus clinical model, which were successfully applied to predict patients with high risks of death (P = 0.0014) and MACE (P = 0.0008) in the multicenter validation cohort. Mendelian randomisation analysis showed that 11 genetically inferred metabolic signatures were significantly associated with risks of death or MACE, such as 4-acetamidobutyric acid, phenylacetyl-l-glutamine, tryptophan metabolites (kynurenine, kynurenic acid), and modified nucleosides (β-pseudouridine, 2-(dimethylamino) guanosine). Mediation analyses show that the association of these metabolites with the outcomes could be partly explained by their roles in promoting left ventricular dysfunction. CONCLUSIONS: This study provided new insights into the relationship between plasma metabolites and clinical outcomes and its intermediate pathological process left ventricular dysfunction in CAD. The predictive model integrating metabolites can help to improve the risk stratification for death and MACE in CAD. The metabolic signatures appear to increase death or MACE risks partly by promoting adverse left ventricular dysfunction, supporting potential therapeutic targets of CAD for further investigation. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13578-022-00863-x.
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spelling pubmed-95690762022-10-16 Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease Zhu, Qian Qin, Min Wang, Zixian Wu, Yonglin Chen, Xiaoping Liu, Chen Ma, Qilin Liu, Yibin Lai, Weihua Chen, Hui Cai, Jingjing Liu, Yemao Lei, Fang Zhang, Bin Zhang, Shuyao He, Guodong Li, Hanping Zhang, Mingliang Zheng, Hui Chen, Jiyan Huang, Min Zhong, Shilong Cell Biosci Research BACKGROUND: Coronary artery disease (CAD) is a metabolically perturbed pathological condition. However, the knowledge of metabolic signatures on outcomes of CAD and their potential causal effects and impacts on left ventricular remodeling remains limited. We aim to assess the contribution of plasma metabolites to the risk of death and major adverse cardiovascular events (MACE) as well as left ventricular remodeling. RESULTS: In a prospective study with 1606 Chinese patients with CAD, we have identified and validated several independent metabolic signatures through widely-targeted metabolomics. The predictive model respectively integrating four metabolic signatures (dulcitol, β-pseudouridine, 3,3ʹ,5-Triiodo-l-thyronine, and kynurenine) for death (AUC of 83.7% vs. 76.6%, positive IDI of 0.096) and metabolic signatures (kynurenine, lysoPC 20:2, 5-methyluridine, and l-tryptophan) for MACE (AUC of 67.4% vs. 59.8%, IDI of 0.068) yielded better predictive value than trimethylamine N-oxide plus clinical model, which were successfully applied to predict patients with high risks of death (P = 0.0014) and MACE (P = 0.0008) in the multicenter validation cohort. Mendelian randomisation analysis showed that 11 genetically inferred metabolic signatures were significantly associated with risks of death or MACE, such as 4-acetamidobutyric acid, phenylacetyl-l-glutamine, tryptophan metabolites (kynurenine, kynurenic acid), and modified nucleosides (β-pseudouridine, 2-(dimethylamino) guanosine). Mediation analyses show that the association of these metabolites with the outcomes could be partly explained by their roles in promoting left ventricular dysfunction. CONCLUSIONS: This study provided new insights into the relationship between plasma metabolites and clinical outcomes and its intermediate pathological process left ventricular dysfunction in CAD. The predictive model integrating metabolites can help to improve the risk stratification for death and MACE in CAD. The metabolic signatures appear to increase death or MACE risks partly by promoting adverse left ventricular dysfunction, supporting potential therapeutic targets of CAD for further investigation. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13578-022-00863-x. BioMed Central 2022-10-14 /pmc/articles/PMC9569076/ /pubmed/36242008 http://dx.doi.org/10.1186/s13578-022-00863-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhu, Qian
Qin, Min
Wang, Zixian
Wu, Yonglin
Chen, Xiaoping
Liu, Chen
Ma, Qilin
Liu, Yibin
Lai, Weihua
Chen, Hui
Cai, Jingjing
Liu, Yemao
Lei, Fang
Zhang, Bin
Zhang, Shuyao
He, Guodong
Li, Hanping
Zhang, Mingliang
Zheng, Hui
Chen, Jiyan
Huang, Min
Zhong, Shilong
Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease
title Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease
title_full Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease
title_fullStr Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease
title_full_unstemmed Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease
title_short Plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease
title_sort plasma metabolomics provides new insights into the relationship between metabolites and outcomes and left ventricular remodeling of coronary artery disease
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9569076/
https://www.ncbi.nlm.nih.gov/pubmed/36242008
http://dx.doi.org/10.1186/s13578-022-00863-x
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