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

Cell & Bioscience

Research

Chen Liu¹  Qilin Ma²  Xiaoping Chen³  Weihua Lai⁴  Yonglin Wu⁵  Zixian Wang⁵  Qian Zhu⁶  Shilong Zhong⁶  Min Qin⁶  Yibin Liu⁶  Hui Chen⁷  Shuyao Zhang⁸  Hanping Li⁹  Jiyan Chen⁹  Guodong He^1,10  Bin Zhang^1,10  Min Huang^1,11  Fang Lei^1,12  Yemao Liu^1,12  Jingjing Cai^1,12  Hui Zheng^1,13  Mingliang Zhang^1,13 

[1] Department of Cardiology, The First Affiliated Hospital of Sun Yat-Sen University, 510080, Guangzhou, Guangdong, China;Department of Cardiology, Xiangya Hospital, Central South University, 410008, Changsha, Hunan, China;Department of Clinical Pharmacology, Xiangya Hospital, Central South University, 410008, Changsha, Hunan, China;Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong, China;Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong, China;Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong, China;Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong, China;Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong, China;School of Medicine, South China University of Technology, 510080, Guangzhou, Guangdong, China;Department of Pharmacy, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong, China;School of Medicine, South China University of Technology, 510080, Guangzhou, Guangdong, China;Department of Pharmacy, Guangzhou Red Cross Hospital, Jinan University, 510220, Guangzhou, Guangdong, China;Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong, China;Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 510080, Guangzhou, Guangdong, China;School of Medicine, South China University of Technology, 510080, Guangzhou, Guangdong, China;Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-Sen University, 510006, Guangzhou, Guangdong, China;Institute of Model Animal, Wuhan University, 430072, Wuhan, Hubei, China;Wuhan Metware Biotechnology Co., Ltd., 430000, Wuhan, Hubei, China;

关键词: Metabolomics;    Coronary artery disease;    Death;    Major adverse cardiovascular events;    Metabolic signature;    Left ventricular remodeling;    Mendelian randomisation;   

DOI  :  10.1186/s13578-022-00863-x

 received in 2022-01-26, accepted in 2022-07-28,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundCoronary 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.ResultsIn 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.ConclusionsThis 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

【 授权许可】

CC BY   
© The Author(s) 2022. corrected publication 2022

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