Literature DB >> 29861102

Interventional left atrial appendage closure may affect metabolism of essential amino acids and bioenergetic efficacy.

J Rusnak1, M Behnes2, A Saleh1, C Fastner1, K Sattler1, C Barth1, A Wenke1, B Sartorius1, K Mashayekhi3, U Hoffmann1, G Yuecel1, S Lang1, M Borggrefe1, I Akin1.   

Abstract

BACKGROUND: Interventional closure of left atrial appendage (LAAC) represents an alternative for stroke prevention in patients with non-valvular atrial fibrillation. Whether LAAC may affect metabolomic pathways has not been investigated yet. This study evaluates the impact of LAAC on the metabolism of essential amino acids, kynurenine and creatinine.
METHODS: Peripheral blood samples of prospectively enrolled patients undergoing successful LAAC were taken before (T0) and 6 months after (T1, mid-term follow-up). Targeted metabolomic profiling was performed using electrospray ionization liquid chromatography-mass spectrometry (ESI-LC-MS/MS) and MS/MS measurements focusing on metabolism of essential amino acids.
RESULTS: 44 patients with non-valvular AF (mean CHA2DS2-VASc score 4, mean HAS-BLED score 4) were enrolled. Changes in metabolites of essential amino acids, myocardial contraction and bioenergetic efficacy, such as phenylalanine (percentage change 8.2%, p = 0.006), tryptophan (percentage change 20.3%, p = 0.0006), tyrosine (percentage change 20.2%, p = 0.0001), creatinine (percentage change 7.2%, p > 0.05) and kynurenine (percentage change 8.3%, p = 0.0239) were found at mid-term follow-up.
CONCLUSIONS: LAAC may affect the metabolism of essential amino acids and bioenergetic efficacy. ClinicalTrials.gov Identifier: NCT02985463.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Atrial fibrillation; Creatinine; Essential amino acids; Kynurenine; Left atrial appendage; Metabolomics

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Year:  2018        PMID: 29861102     DOI: 10.1016/j.ijcard.2018.05.031

Source DB:  PubMed          Journal:  Int J Cardiol        ISSN: 0167-5273            Impact factor:   4.164


  3 in total

1.  Comprehensive metabolomic and proteomic analyses reveal candidate biomarkers and related metabolic networks in atrial fibrillation.

Authors:  Juntuo Zhou; Lijie Sun; Liwen Chen; Shuwang Liu; Lijun Zhong; Ming Cui
Journal:  Metabolomics       Date:  2019-06-21       Impact factor: 4.290

2.  Prediction model based on machine learning for short- and long-term adverse events in left atrial appendage closure.

Authors:  Xiaogang Zhang; Bei Tian; Xinpeng Cong; Shu-Wen Hao; Qiang Huan; Can Jin; Luoning Zhu; Zhong-Ping Ning
Journal:  J Thorac Dis       Date:  2022-06       Impact factor: 3.005

3.  Targeting amino acids metabolic profile to identify novel metabolic characteristics in atrial fibrillation.

Authors:  Jianqing She; Manyun Guo; Hongbing Li; Junhui Liu; Xiao Liang; Peining Liu; Bo Zhou; Simin Liu; Yangyang Deng; Bowen Lou; Chaofeng Sun; Zuyi Yuan; Yue Wu
Journal:  Clin Sci (Lond)       Date:  2018-10-05       Impact factor: 6.124

  3 in total

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