Biomarkers and key pathways in atrial fibrillation associated with mitral valve disease identified by multi-omics study

Metabolomics Analysis Identifies Differential Metabolites as Biomarkers for Acute Myocardial Infarction

Myocardial infarction (MI), including ST-segment elevation MI (STEMI) and non-ST-segment elevation MI (NSTEMI), is still a leading cause of death worldwide. Metabolomics technology was used to explore differential metabolites (DMs) as potential biomarkers for early diagnosis of STEMI and NSTEMI. In the study, 2531 metabolites, including 1925 DMs, were discovered. In the selected 27 DMs, 14 were successfully verified in a new cohort, and the AUC values were all above 0.8. There were 10 in STEMI group, namely L-aspartic acid, L-acetylcarnitine, acetylglycine, decanoylcarnitine, hydroxyphenyllactic acid, ferulic acid, itaconic acid, lauroylcarnitine, myristoylcarnitine, and cis-4-hydroxy-D-proline, and 5 in NSTEMI group, namely L-aspartic acid, arachidonic acid, palmitoleic acid, D-aspartic acid, and palmitelaidic acid. These 14 DMs may be developed as biomarkers for the early diagnosis of MI with high sensitivity and specificity. These findings have particularly important clinical significance for NSTEMI patients because these patients have no typical ECG changes.

Metabolomics and Biomarkers for Paroxysmal and Persistent Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) is the most common type of arrhythmia worldwide and is associated with serious complications. This study investigated the metabolic biomarkers associated with AF and the differences in metabolomics and associated metabolic biomarkers between paroxysmal AF (AFPA) and persistent AF.

METHODS AND RESULTS

Plasma samples were prospectively collected from patients with AF and patients in sinus rhythm with negative coronary angiography. The patients were divided into 3 groups: AFPA, persistent AF, and sinus rhythm (N=54). Metabolomics (n=36) using ultra-high-performance liquid chromatography mass spectrometry was used to detect differential metabolites that were validated in a new cohort (n=18). The validated metabolites from the validation phase were further analyzed by receiver operating characteristic. Among the 36 differential metabolites detected by omics assay, 4 were successfully validated with area under the curve >0.8 (P<0.05). Bioinformatics analysis confirmed the enrichment pathways of unsaturated fatty acid biosynthesis, glyoxylate and dicarboxylate metabolism, and carbon metabolism. Arachidonic acid was a potential biomarker of AFPA, glycolic acid and L-serine were biomarkers of AFPA and persistent AF, and palmitelaidic acid was a biomarker of AFPA.

CONCLUSIONS

In this metabolomics study, we detected 36 differential metabolites in AF, and 4 were validated with high sensitivity and specificity. These differential metabolites are potential biomarkers for diagnosis and monitoring of disease course. This study therefore provides new insights into the precision diagnosis and management of AF.

Lysine crotonylation of SERCA2a correlates to cardiac dysfunction and arrhythmia in Sirt1 cardiac-specific knockout mice

Protein post-translational modifications (PTMs) are important regulators of protein functions and produce proteome complexity. SIRT1 has NAD+-dependent deacylation of acyl-lysine residues. The present study aimed to explore the correlation between lysine crotonylation (Kcr) on cardiac function and rhythm in Sirt1 cardiac-specific knockout (ScKO) mice and related mechanism. Quantitative proteomics and bioinformatics analysis of Kcr were performed in the heart tissue of ScKO mice established with a tamoxifen-inducible Cre-loxP system. The expression and enzyme activity of crotonylated protein were assessed by western blot, co-immunoprecipitation, and cell biology experiment. Echocardiography and electrophysiology were performed to investigate the influence of decrotonylation on cardiac function and rhythm in ScKO mice. The Kcr of SERCA2a was significantly increased on Lys120 (1.973 folds). The activity of SERCA2a decreased due to lower binding energy of crotonylated SERCA2a and ATP. Changes in expression of PPAR-related proteins suggest abnormal energy metabolism in the heart. ScKO mice had cardiac hypertrophy, impaired cardiac function, and abnormal ultrastructure and electrophysiological activities. We conclude that knockout of SIRT1 alters the ultrastructure of cardiac myocytes, induces cardiac hypertrophy and dysfunction, causes arrhythmia, and changes energy metabolism by regulating Kcr of SERCA2a. These findings provide new insight into the role of PTMs in heart diseases.

Cross-Sectional Gene-Smoking Interaction Analysis in Relation to Subclinical Atherosclerosis-Results From the IMPROVE Study

BACKGROUND

Smoking is associated with carotid intima-media thickness (C-IMT). However, knowledge about how genetics may influence this association is limited. We aimed to perform nonhypothesis driven gene-smoking interaction analyses to identify potential genetic variants, among those included in immune and metabolic platforms, that may modify the effect of smoking on carotid intima-media thickness.

METHODS

We used baseline data from 1551 men and 1700 women, aged 55 to 79, included in a European multi-center study. Carotid intima-media thickness maximum, the maximum of values measured at different locations of the carotid tree, was dichotomized with cut point values ≥75, respectively. Genetic data were retrieved through use of the Illumina Cardio-Metabo- and Immuno- Chips. Gene-smoking interactions were evaluated through calculations of Synergy index (S). After adjustments for multiple testing, P values of <2.4×10-7 for S were considered significant. The models were adjusted for age, sex, education, physical activity, type of diet, and population stratification.

RESULTS

Our screening of 207 586 SNPs available for analysis, resulted in the identification of 47 significant gene-smoking synergistic interactions in relation to carotid intima-media thickness maximum. Among the significant SNPs, 28 were in protein coding genes, 2 in noncoding RNA and the remaining 17 in intergenic regions.

CONCLUSIONS

Through nonhypothesis-driven analyses of gene-smoking interactions, several significant results were observed. These may stimulate further research on the role of specific genes in the process that determines the effect of smoking habits on the development of carotid atherosclerosis.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Integration of proteomic and metabolomic characterization in atrial fibrillation-induced heart failure

BACKGROUND

The exact mechanism of atrial fibrillation (AF)-induced heart failure (HF) remains unclear. Proteomics and metabolomics were integrated to in this study, as to describe AF patients' dysregulated proteins and metabolites, comparing patients without HF to patients with HF.

METHODS

Plasma samples of 20 AF patients without HF and another 20 with HF were analyzed by multi-omics platforms. Proteomics was performed with data independent acquisition-based liquid chromatography-tandem mass spectrometry (LC-MS/MS), as metabolomics was performed with LC-MS/MS platform. Proteomic and metabolomic results were analyzed separately and integrated using univariate statistical methods, multivariate statistical methods or machine learning model.

RESULTS

We found 35 up-regulated and 15 down-regulated differentially expressed proteins (DEPs) in AF patients with HF compared to AF patients without HF. Moreover, 121 up-regulated and 14 down-regulated differentially expressed metabolites (DEMs) were discovered in HF patients compared to AF patients without HF. An integrated analysis of proteomics and metabolomics revealed several significantly enriched pathways, including Glycolysis or Gluconeogenesis, Tyrosine metabolism and Pentose phosphate pathway. A total of 10 DEPs and DEMs selected as potential biomarkers provided excellent predictive performance, with an AUC of 0.94. In addition, subgroup analysis of HF classification was performed based on metabolomics, which yielded 9 DEMs that can distinguish between AF and HF for HF classification.

CONCLUSIONS

This study provides novel insights to understanding the mechanisms of AF-induced HF progression and identifying novel biomarkers for prognosis of AF with HF by using metabolomics and proteomics analyses.

Application of plasma metabolome for monitoring the effect of rivaroxaban in patients with nonvalvular atrial fibrillation

Rivaroxaban, an oral factor Xa inhibitor, has been used to treating a series of thromboembolic disorders in clinical practice. Measurement of the anticoagulant effect of rivaroxaban is important to avoid serious bleeding events, thus ensuring the safety and efficacy of drug administration. Metabolomics could help to predict differences in the responses among patients by profiling metabolites in biosamples. In this study, plasma metabolomes before and 3 hours after rivaroxaban intake in 150 nonvalvular atrial fibrillation (NVAF) patients and 100 age/gender-matched controls were analyzed by liquid chromatography coupled with mass spectrometry (LC-MS/MS). When compared with controls, a total of thirteen plasma metabolites were differentially expressed in the NVAF patients. Pathway analysis revealed that purine and lipid metabolism were dysregulated. A panel of three metabolites (17a-ethynylestradiol, tryptophyl-glutamate and adenosine) showed good predictive ability to distinguish nonvalvular atrial fibrillation with an area under the receiver operating characteristic curve (AUC) of 1 for the discovery phase and 1 for validation. Under rivaroxaban treatment, a total of seven metabolites changed, the lipid and glycosylphosphatidylinositol biosynthesis pathways were altered and the panel consisting of avocadene, prenyl glucoside and phosphatidylethanolamine showed predictive ability with an AUC of 0.86 for the discovery dataset and 0.82 for the validation. The study showed that plasma metabolomic analyses hold the potential to differentiate nonvalvular atrial fibrillation and can help to monitor the effect of rivaroxaban anticoagulation.

Moricizine prevents atrial fibrillation by late sodium current inhibition in atrial myocytes

Background

Enhanced late sodium current (INaL) is reportedly related to an increased risk of atrial fibrillation (AF). Moricizine, as a widely used anti-arrhythmia drug for suppressing ventricular tachycardia, has also been shown to prevent paroxysmal AF. However, the mechanism of its therapeutic effect remains poorly understood.

Methods

Angiotensin II (Ang II) was induced in C57Bl/6 mice (male wild-type) for 4 weeks to increase the susceptibility of AF, and acetylcholine-calcium chloride was used to induce AF. The whole-cell patch-clamp technique was used to detect INaL from isolated atrial myocytes. The expression of proteins in atrial of mice and HL-1 cells were examined by Western-blot.

Results

The results showed that moricizine significantly inhibited Ang II-mediated atrial enlargement and reduced AF vulnerability. We found that the densities of INaL were enhanced in Ang II-treated left and right atrial cardiomyocytes. Simultaneously, the Ang II-induced increase in INaL currents density was alleviated by the administration of moricizine, and no alteration in Nav1.5 expression was observed. In normal isolated atrial myocytes, moricizine significantly reduced Sea anemone toxin II (ATX II)-enhanced INaL density with a reduction of peak sodium currents. In addition, moricizine reduced the Ang II-induced upregulation of phosphorylated calcium/calmodulin-dependent protein kinase-II (p-CaMKII) in both the left and right atria. In HL-1 cells, moricizine also reduced the upregulation of p-CaMKII with Ang II and ATX II intervention, respectively.

Conclusions

Our results indicate that Ang II enhances the INaL via activation of CaMKII. Moricizine inhibits INaL and reduces CaMKII activation, which may be one of the mechanisms of moricizine suppression of AF.

Further Advances in Atrial Fibrillation Research: A Metabolomic Perspective

Atrial fibrillation involves an important type of heart arrhythmia caused by a lack of control in the electrical signals that arrive in the heart, produce an irregular auricular contraction, and induce blood clotting, which finally can lead to stroke. Atrial fibrillation presents some specific characteristics, but it has been treated and prevented using conventional methods similar to those applied to other cardiovascular diseases. However, due to the influence of this pathology on the mortality caused by cerebrovascular accidents, further studies on the molecular mechanism of atrial fibrillation are required. Our aim here is provide a compressive review of the use of metabolomics on this condition, from the study of the metabolic profile of plasma to the development of animal models. In summary, most of the reported studies highlighted alterations in the energetic pathways related to the development of the condition.