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

Rusnak, Jonas; Behnes, Michael; Saleh, Ahmad; Fastner, Christian; Sattler, Katherine; Barth, Christian; Wenke, Annika; Sartorius, Benjamin; Mashayekhi, Kambis; Hoffmann, Ursula; Yuecel, Goekhan; Lang, Siegfried; Borggrefe, Martin; Akın, İbrahim

doi:10.1016/j.ijcard.2018.05.031

Cited by 9 publications

(8 citation statements)

References 71 publications

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“…Recent advances in metabolic profiling technologies have enhanced the feasibility of high-throughput patient screening for diagnosing various disease states [37,38], and an increasing number of studies are utilizing metabolomics approaches to identify metabolic alterations and pathogenic factors in AF [39–42]. However, one previous study has not found altered metabolites in AF, making the metabolic regulation in AF controversial [19].…”

Section: Discussionmentioning

confidence: 99%

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

She

Guo

et al. 2018

Clinical Science

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Atrial fibrillation (AF) is the most common cardiac arrhythmia whose incidence is on the rise globally. However, the pathophysiologic mechanism of AF remains poorly understood and there has been a lack of circulatory markers to diagnose and predict prognosis of AF. In the present study, by measuring metabolic profile and analyzing plasma amino acid levels in AF patients, we sought to determine whether amino acid metabolism was correlated to the occurrence of AF. Consecutive patients admitted to hospital for AF were enrolled. Plasma samples were obtained after overnight fast and a profile of 61 amino acids was then measured using gas chromatography/mass spectrometry (GC/MS). Twenty-three AF and thirty-seven control patients were enrolled in the study. A number of plasma amino acids were altered in AF, which showed significant prediction value for AF. Intriguingly, circulating 4-hydroxypyrrolidine-2-carboxylic was gradually lowered with the persistence of AF. Plasma amino acid levels were more strongly correlated with each other in AF as compared with control. By utilizing non-target metabolic profile surveys, we have found a number of altered amino acids, which exhibit diagnostic value for AF. Enhanced amino acids correlation network further identified AF as a metabolism disorder.

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Section: Discussionmentioning

confidence: 99%

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

She

Guo

et al. 2018

Clinical Science

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“…The findings of a comprehensive prospective cohort study indicate a positive correlation between heightened phenylalanine levels and an augmented risk of cardiovascular complications [32]. Through targeted metabolomics analysis, Rusnak revealed changes in essential amino acid levels in patients with interventional closure of the left atrial appendage [33]. Therefore, metabolic remodeling plays a significant role in the onset and sustenance of AF.…”

Section: Discussionmentioning

confidence: 99%

Identification of metabolic biomarkers in atrial fibrillation patients via the integrated application of proteomics and metabolomics

Chao,

Xu,

Zhang

et al. 2024

Preprint

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Atrial fibrillation (AF) is a prevalent clinical arrhythmia characterized by an irregular cardiac rhythm, increasing the risk of developing stroke and heart failure. In order to explore the potential role of serum indicators, the study employed a combination of targeted metabolomics and Tandem Mass Tag (TMT) based proteomics to examine metabolic characteristics and biomarkers in the serum of patients with AF. Furthermore, the verification of protein expressions with diagnostic significance for AF was conducted in patients of larger sample sizes by ELISA. Proteomics and metabolomics identified 174 differentially expressed proteins (DEPs) and 294 differentially metabolites (DMs) in AF patients, respectively. The clustering and functional enrichment analysis identified the complement and coagulation cascade as the primary pathway dysregulating DEPs. According to the integrated study, the most enriched proteomics and metabolomics pathways were platelet activation and cholesterol metabolism. lactate dehydrogenase A (LDHA), lactate dehydrogenase B (LDHB), and transgelin 2 (TAGLN2) were significantly expressed in AF patients, while plasminogen (PLG) was low. In conclusion, the current study found that platelet activation, cholesterol metabolism, and the complement and coagulation cascade pathways may affect AF progression. The study also showed that LDHA, LDHB, TAGLN2, and PLG may be potential AF biomarkers.

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“…In addition, several blood biomarkers have been shown to be associated with the presence of LAA thrombosis. Brain natriuretic peptide (BNP), mean erythrocyte volume, mean platelet volume, and eosinophil count have additional diagnostic effects above CHADS 2 (16,17). Clinical risk factors included hypertension, congestive heart failure, age, female, structural heart disease or cardiomyopathy, use of antiarrhythmic drugs, persistent and paroxysmal atrial fibrillation, and higher CHADS 2 score (18,19).…”

Section: Discussionmentioning

confidence: 99%

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

Zhang¹,

Tian²,

Cong³

et al. 2022

J Thorac Dis

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

Cited by 9 publications

References 71 publications

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

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

Identification of metabolic biomarkers in atrial fibrillation patients via the integrated application of proteomics and metabolomics

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

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