The Four Key Genes Participated in and Maintained Atrial Fibrillation Process via Reprogramming Lipid Metabolism in AF Patients

Expression characteristics of lipid metabolism-related genes and correlative immune infiltration landscape in acute myocardial infarction

Lipid metabolism is an important part of the heart's energy supply. The expression pattern and molecular mechanism of lipid metabolism-related genes (LMRGs) in acute myocardial infarction (AMI) are still unclear, and the link between lipid metabolism and immunity is far from being elucidated. In this study, 23 Common differentially expressed LMRGs were discovered in the AMI-related mRNA microarray datasets GSE61144 and GSE60993. These genes were mainly related to "leukotriene production involved in inflammatory response", "lipoxygenase pathway", "metabolic pathways", and "regulation of lipolysis in adipocytes" pathways. 12 LMRGs (ACSL1, ADCY4, ALOX5, ALOX5AP, CCL5, CEBPB, CEBPD, CREB5, GAB2, PISD, RARRES3, and ZNF467) were significantly differentially expressed in the validation dataset GSE62646 with their AUC > 0.7 except for ALOX5AP (AUC = 0.699). Immune infiltration analysis and Pearson correlation analysis explored the immune characteristics of AMI, as well as the relationship between these identified LMRGs and immune response. Lastly, the up-regulation of ACSL1, ALOX5AP, CEBPB, and GAB2 was confirmed in the mouse AMI model. Taken together, LMRGs ACSL1, ALOX5AP, CEBPB, and GAB2 are significantly upregulated in AMI patients' blood, peripheral blood of AMI mice, myocardial tissue of AMI mice, and therefore might be new potential biomarkers for AMI.

GLP-1 receptor agonists and myocardial metabolism in atrial fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia. Many medical conditions, including hypertension, diabetes, obesity, sleep apnea, and heart failure (HF), increase the risk for AF. Cardiomyocytes have unique metabolic characteristics to maintain adenosine triphosphate production. Significant changes occur in myocardial metabolism in AF. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have been used to control blood glucose fluctuations and weight in the treatment of type 2 diabetes mellitus (T2DM) and obesity. GLP-1RAs have also been shown to reduce oxidative stress, inflammation, autonomic nervous system modulation, and mitochondrial function. This article reviews the changes in metabolic characteristics in cardiomyocytes in AF. Although the clinical trial outcomes are unsatisfactory, the findings demonstrate that GLP-1 RAs can improve myocardial metabolism in the presence of various risk factors, lowering the incidence of AF.

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.

Transcriptomic analysis reveals the lipid metabolism-related gene regulatory characteristics and potential therapeutic agents for myocardial ischemia-reperfusion injury

Background

Impaired energy balance caused by lipid metabolism dysregulation is an essential mechanism of myocardial ischemia-reperfusion injury (MI/RI). This study aims to explore the lipid metabolism-related gene (LMRG) expression patterns in MI/RI and to find potential therapeutic agents.

Methods

Differential expression analysis was performed to screen the differentially expressed genes (DEGs) and LMRGs in the MI/RI-related dataset GSE61592. Enrichment and protein-protein interaction (PPI) analyses were performed to identify the key signaling pathways and genes. The expression trends of key LMRGs were validated by external datasets GSE160516 and GSE4105. The corresponding online databases predicted miRNAs, transcription factors (TFs), and potential therapeutic agents targeting key LMRGs. Finally, the identified LMRGs were confirmed in the H9C2 cell hypoxia-reoxygenation (H/R) model and the mouse MI/RI model.

Results

Enrichment analysis suggested that the "lipid metabolic process" was one of the critical pathways in MI/RI. Further differential expression analysis and PPI analysis identified 120 differentially expressed LMRGs and 15 key LMRGs. 126 miRNAs, 55 TFs, and 51 therapeutic agents were identified targeting these key LMRGs. Lastly, the expression trends of Acadm, Acadvl, and Suclg1 were confirmed by the external datasets, the H/R model and the MI/RI model.

Conclusion

Acadm, Acadvl, and Suclg1 may be the key genes involved in the MI/RI-related lipid metabolism dysregulation; and acting upon these factors may serve as a potential therapeutic strategy.

Phosphatidylethanolamine aggravates Angiotensin II-induced atrial fibrosis by triggering ferroptosis in mice

As atrial fibrosis is the main feature of atrial structural remodeling, inhibiting atrial fibrosis is crucial to the prevention of atrial fibrillation (AF) progression. Research has shown the correlation between abnormal lipid metabolism and AF progression. However, the effect of specific lipids on atrial fibrosis remains unclear. In the present study, we applied ultra-high-performance lipidomics to analyze the lipid profiles in patients with AF and identify phosphatidylethanolamine (PE) as the differential lipid associated with AF. To detect the effect of the differential lipid on atrial fibrosis, we performed the intraperitoneal injection of Angiotensin II (Ang II) to mice to induce atrial fibrosis and supplemented PE in diets. We also treated atrial cells with PE to evaluate the cellular effect of PE. We found that PE supplementation aggravated atrial fibrosis and increased the expression of the fibrosis-related protein in vitro and in vivo. Moreover, we detected the effect of PE on the atrium. We found that PE increased oxidation products and regulated the expression of ferroptosis-related proteins, which could be alleviated by a ferroptosis inhibitor. PE increased peroxidation and mitochondrial damage in vitro, which promoted cardiomyocyte death induced by Ang II. Examination of protein expression in cardiomyocytes indicated that PE triggered ferroptosis and caused cell death to participate in myocardium fibrosis. In summary, our findings demonstrated the differential lipid profiles of AF patients and revealed the potential effect of PE on atrial remodelling, suggesting that inhibition of PE and ferroptosis might serve as a potential therapy to prevent AF progression.

Integrative single-cell RNA sequencing and metabolomics decipher the imbalanced lipid-metabolism in maladaptive immune responses during sepsis

Background

To identify differentially expressed lipid metabolism-related genes (DE-LMRGs) responsible for immune dysfunction in sepsis.

Methods

The lipid metabolism-related hub genes were screened using machine learning algorithms, and the immune cell infiltration of these hub genes were assessed by CIBERSORT and Single-sample GSEA. Next, the immune function of these hub genes at the single-cell level were validated by comparing multiregional immune landscapes between septic patients (SP) and healthy control (HC). Then, the support vector machine-recursive feature elimination (SVM-RFE) algorithm was conducted to compare the significantly altered metabolites critical to hub genes between SP and HC. Furthermore, the role of the key hub gene was verified in sepsis rats and LPS-induced cardiomyocytes, respectively.

Results

A total of 508 DE-LMRGs were identified between SP and HC, and 5 hub genes relevant to lipid metabolism (MAPK14, EPHX2, BMX, FCER1A, and PAFAH2) were screened. Then, we found an immunosuppressive microenvironment in sepsis. The role of hub genes in immune cells was further confirmed by the single-cell RNA landscape. Moreover, significantly altered metabolites were mainly enriched in lipid metabolism-related signaling pathways and were associated with MAPK14. Finally, inhibiting MAPK14 decreased the levels of inflammatory cytokines and improved the survival and myocardial injury of sepsis.

Conclusion

The lipid metabolism-related hub genes may have great potential in prognosis prediction and precise treatment for sepsis patients.

Multiple targets related to mitochondrial function unveiled by metabolomics and proteomics profiles of hearts from atrial fibrillation patients

Background: The prominent mitochondrial metabolic changes of the atrium reportedly have significant impact on electrical signals and structural remodeling which play important roles in the occurrence and development of atrial fibrillation (AF). However, the mechanism is not completely known.

Objective: This study was aimed to explore the mitochondrial metabolism reprogrammed in AF patients by integrating metabolomics as well as proteomics of human atrium tissues.

Methods and Results: Left atrial tissue samples were harvested from 10 non-valvular AF patients and 10 matched samples from healthy donors for transplantation. In metabolomics analysis, 113 metabolites were upregulated and 10 metabolites were downregulated in AF, where multiple pathways related to mitochondrial energy metabolism were enriched. Correlation analysis between the differentially expressed proteins and metabolites identified several hub proteins related to mitochondrial function including Glycerol-3-phosphate dehydrogenase 2 (GPD2), Synemin (SYNM), Plectin (PLEC), with MCC score of 27, 17, 16, respectively, which have the most interactions with the dysregulated metabolites and ranked at the top in network string interactions scored by MCC method. All 330 differentially expressed proteins including 225 upregulated and 105 downregulated molecules were revealed and analyzed, which identified the downregulation of GPD2 (p = 0.02 and FC = 0.77), PLEC (p &lt; 0.001 and FC = 0.71) and SYNM (p = 0.04 and FC = 0.76) in AF patients. Gene Set Variation Analysis (GSEA) showed mitochondrial metabolism-associated pathways including oxidative phosphorylation (NES: −1.73) and ATP biosynthetic process (NES: −2.29), were dramatically diversified in human AF. In GSVA, the expression levels of GPD2, PLEC, and SYNM were demonstrated to be associated with multiple metabolic pathways related to mitochondrial function (e.g., lipid metabolism and AMP activated protein kinase signaling) and cardiac structural and electrical remodeling (e.g., contractile fiber, ion homeostasis), which were proven vital in the development and maintenance of AF.

Conclusion: In all, this study provides new insights into understanding the mechanisms of AF progression, especially the reprogramming mitochondrial metabolism, and identifies several genes related to mitochondrial function as novel targets for AF, which may be involved in the occurrence and development of AF.

The Impact of Sleep Disturbance on Gut Microbiota, Atrial Substrate, and Atrial Fibrillation Inducibility in Mice: A Multi-Omics Analysis

This study examined the effect of sleep disturbance on gut microbiota (GM), atrial substrate, and atrial fibrillation (AF) inducibility. C57BL/6 mice were subjected to six weeks of sleep deprivation (SD) using the method of modified multiple-platform. Transesophageal burst pacing was performed to evaluate AF inducibility. Feces, plasma, and an atrium were collected and analyzed by 16s rRNA sequencing, liquid chromatography−mass spectrometry (LC-MS)-based metabolome, histological studies, and transcriptome. Higher AF inducibility (2/30 of control vs. 15/30 of SD, p = 0.001) and longer AF duration (p < 0.001), concomitant with aggravated fibrosis, collagen, and lipid accumulation, were seen in the SD mice compared to control mice. Meanwhile, elevated alpha diversity, higher abundance of Flavonifractor, Ruminococcus, and Alloprevotella, as well as imbalanced functional pathways, were observed in the gut of SD mice. Moreover, the global patterns for the plasma metabolome were altered, e.g., the decreased butanoate metabolism intermediates in SD mice. In addition, disrupted metabolic homeostasis in the SD atrium, such as fatty acid metabolism, was analyzed by the transcriptome. These results demonstrated that the crosstalk between GM and atrial metabolism might be a promising target for SD-mediated AF susceptibility.

Association between triglyceride-glucose index and atrial fibrillation: A retrospective observational study

BACKGROUND

Insulin resistance is associated with atrial remodeling as well as atrial fibrillation (AF). However, there was limited evidence on the relationship of triglyceride-glucose index (TyG) index, a simple, valuable marker of insulin resistance, with AF. Thus, we aimed to investigate the association between TyG index and AF among hospitalized patients.

METHODS

A retrospective observational study was conducted in Daping Hospital, which included 356 hospitalized patients from the Department of Cardiology. Clinical and biochemical parameters were collected from electronic medical records and AF was diagnosed from electrocardiogram (ECG) findings.

RESULTS

We found that the TyG index was significantly higher in the AF group than in the group without AF. Multivariate logistic regression revealed that hypertension (OR = 1.756, 95%CI 1.135-2.717, P = 0.011) and TyG index (OR = 2.092, 95%CI 1.412-3.100, P<0.001) were positively associated with AF. The analysis of the area under the ROC curve was performed and revealed that area under curve (AUC) of TyG index was 0.600 (95%CI, 0.542-0.659, P = 0.001), the optimal critical value was 8.35, the sensitivity was 65.4%, and the specificity was 52.0%. Additional subgroup analyses of diabetic and non-diabetic subjects were also performed and found the TyG index was increased in non-diabetic subjects with AF. Furthermore, a logistic regression analysis showed TyG index was associated with AF (OR = 3.065, 95% CI, 1.819-5.166, P<0.001) in non-diabetic subjects. However, TyG index was not associated with AF in diabetic subjects.

CONCLUSION

Elevated TyG index is an independent risk factor for AF among non-diabetic hospitalized patients.