Metabolic Modulation and Potential Biomarkers of the Prognosis Identification for Severe Aortic Stenosis after TAVR by a Metabolomics Study

Author:

Liao Yanbiao1ORCID,Liu Chang1ORCID,Xiong Tianyuan1ORCID,Zhao Mingyue2ORCID,Zheng Wen3ORCID,Feng Yuan1ORCID,Li Yijian1ORCID,Ou Yuanweixiang1ORCID,Zhao Zhengang1ORCID,Peng Yong1ORCID,Wei Jiafu1ORCID,Li Qiao1ORCID,Meng Wei4ORCID,Liu Xiaojing23ORCID,Chen Mao1ORCID

Affiliation:

1. Department of Cardiology, West China Hospital, Sichuan University, 37 Guoxue Street, Chengdu 610041, China

2. Laboratory of Cardiovascular Diseases, Regenerative Medicine Research Center, West China Hospital, Sichuan University, 37 Guoxue Street, Chengdu 610041, China

3. Laboratory of Mitochondrial Biology, West China-Washington Mitochondria and Metabolism Center, West China Hospital, Sichuan University, No. 88, Keyuan South Road, High-Tech Zone, Chengdu 610093, China

4. Department of Cardiovascular Surgery, West China Hospital, Sichuan University, 37 Guoxue Street, Chengdu 610041, China

Abstract

Objectives. To investigate the metabolic profile in patients with aortic stenosis (AS) after transcatheter aortic valve replacement (TAVR) and explore the potential biomarkers to predict prognosis after TAVR based on metabolomics. Methods and Results. Fifty-nine consecutive AS patients were prospectively recruited. Blood samples from the ascending aorta, coronary sinus, and peripheral vein at before and after TAVR were collected, respectively. Liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry were performed to analyze the metabolic profile before and after TAVR. Influential metabolites were identified by integrating the univariate test, multivariate analysis, and weighted gene coexpression network analysis (WGCNA) algorithm. PLS-DA analysis revealed a significant extremely early (within 30 minutes after TAVR) alterations of metabolites in the ascending aorta, coronary sinus, and peripheral vein. The early (within 7 days after TAVR) changed metabolites in the peripheral vein were involved in purine metabolism, primary bile acid biosynthesis, glycerolipid metabolism, amino sugar and nucleotide sugar metabolism, one carbon pool by folate and alanine, and the aspartate and glutamate metabolism pathway. We used volcano plots to find that the cardiac-specific changed metabolites were enriched to the sphingolipid metabolism pathway after TAVR. Besides, WGCNA algorithm was performed to reveal that arginine and proline metabolites could reflect left ventricle regression to some extent. Conclusion. This is the first study to reveal systemic and cardiac metabolites changed significantly in patients with AS after TAVR. Some altered metabolites involved in the arginine and proline metabolism pathway in the peripheral vein could predict left ventricle regression, which merited further study.

Funder

Sichuan University

Publisher

Hindawi Limited

Subject

Cardiology and Cardiovascular Medicine

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