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

Qian Zhu; Min Qin; Zixian Wang; Yonglin Wu; Xiaoping Chen; Chen Liu; Qilin Ma; Yibin Liu; Weihua Lai; Hui Chen; Jingjing Cai; Yemao Liu; Fang Lei; Bin Zhang; Shuyao Zhang; Guodong He; Hanping Li; Mingliang Zhang; Hui Zheng; Jiyan Chen; Min Huang; Shilong Zhong

doi:10.1186/s13578-022-00863-x

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

Cell Biosci. 2022 Oct 14;12(1):173. doi: 10.1186/s13578-022-00863-x.

Authors

Qian Zhu^#^{1

2

3}, Min Qin^#^{1

2

3}, Zixian Wang^{1

2}, Yonglin Wu^{1

2}, Xiaoping Chen⁴, Chen Liu⁵, Qilin Ma⁶, Yibin Liu^{1

2

3}, Weihua Lai¹, Hui Chen^{1

3}, Jingjing Cai⁷, Yemao Liu⁷, Fang Lei⁷, Bin Zhang^{2

3}, Shuyao Zhang⁸, Guodong He^{2

3}, Hanping Li², Mingliang Zhang⁹, Hui Zheng⁹, Jiyan Chen², Min Huang¹⁰, Shilong Zhong^{11

12

13}

Affiliations

¹ Department of Pharmacy, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China.
² Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China.
³ School of Medicine, South China University of Technology, Guangzhou, 510080, Guangdong, China.
⁴ Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
⁵ Department of Cardiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China.
⁶ Department of Cardiology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
⁷ Institute of Model Animal, Wuhan University, Wuhan, 430072, Hubei, China.
⁸ Department of Pharmacy, Guangzhou Red Cross Hospital, Jinan University, Guangzhou, 510220, Guangdong, China.
⁹ Wuhan Metware Biotechnology Co., Ltd., Wuhan, 430000, Hubei, China.
¹⁰ Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, Guangdong, China.
¹¹ Department of Pharmacy, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China. gdph_zhongsl@gd.gov.cn.
¹² Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China. gdph_zhongsl@gd.gov.cn.
¹³ School of Medicine, South China University of Technology, Guangzhou, 510080, Guangdong, China. gdph_zhongsl@gd.gov.cn.

^# Contributed equally.

Abstract

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, 3,3',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.

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

Abstract

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