Biomarkers In Atrial Fibrillation Research Articles

Proteomic and genomic evaluation of plasma protein biomarkers for atrial fibrillation

Abstract Background Atrial fibrillation (AF) is a common arrhythmia and an important cause of ischemic stroke. Several plasma proteins have been suggested as biomarkers for the risk of AF and subsequent stroke in previous studies, but validation in independent cohorts is needed. Large-scale integration of proteomics with genetic and clinical data holds potential for refinement of disease prediction and risk stratification. Purpose This study aimed to evaluate previously suggested plasma protein biomarkers of AF and ischemic stroke using plasma protein measurements in a large cohort. Methods Ten tentative protein biomarkers previously associated with AF or ischemic stroke in AF patients, were evaluated in a nested case-control study comprising 49,757 individuals from the UK biobank (UKB). Plasma proteins were measured by normalized protein expression on the Olink platform. Outcomes were incident AF and ischemic stroke. The proteins were evaluated in Cox regression models adjusted for sex, age, and clinical risk factors. To assess whether the proteins were independent predictors, they were evaluated in sensitivity analyses with additional adjustment for NT-proBNP levels. Polygenic risk scores were calculated for plasma protein concentrations using the PRS-CS-auto algorithm and tested for association with AF or ischemic stroke in an independent subset of the UKB cohort without plasma protein measurements (n=379,392). Results All ten plasma proteins were associated with incident AF in the primary model, and eight were associated with incident ischemic stroke (P-values < 0.0025 for all). Adjusted for NT-proBNP levels, the proteins interleukin-6, GDF15, angiopoietin 2, and Troponin-I remained independently associated with AF, and the proteins GDF15, Cystatin-C, interleukin-6, ADAMTS13, and FGF23 remained independently associated with ischemic stroke. Polygenic risk scores for NT-proBNP and angiopoietin 2 were associated with increased rates of AF. No polygenic scores were significantly associated with ischemic stroke. Conclusion Large-scale proteomic evaluation validated ten plasma proteins associated AF and found eight to be associated with ischemic stroke. Seven proteins were associated with AF or ischemic stroke independently of NT-proBNP levels. Additional genomic evaluation provided evidence of associations between incident AF and genetically predicted plasma levels of angiopoietin 2 and NT-proBNP. As proteomic analyses of the plasma proteome become cheaper and more readily available, these findings could contribute to future risk stratification and selection of individuals for AF screening programs.Proteins associated with AFProteins associated with ischemic stroke

MicroRNAs and other biomarkers of atrial fibrillation in ischemic stroke patients.

This study aimed to evaluate the ability of selected microRNAs as biomarkers of atrial fibrillation (AF) in ischemic stroke patients in comparison with other established biochemical biomarkers. A prospective case-control study of consecutive ischemic stroke patients with AF admitted to a comprehensive stroke center was conducted. The control group consisted of patients with ischemic stroke with no AF detected on prolonged (at least 3 weeks) Holter ECG monitoring. As potential biomarkers of AF, we analyzed the plasma levels of microRNAs (miR-21, miR-29b, miR-133b, miR-142-5p, miR-150, miR-499, and miR-223-3p) and 13 biochemical biomarkers at admission. The predictive accuracy of biomarkers was assessed by calculating the area under the receiver operating characteristic curve. The data of 117 patients were analyzed (61 with AF, 56 with no AF, 46% men, median age 73 years, median National Institutes of Health Stroke Scale 6). Biochemical biomarkers (N-terminal pro-B-type natriuretic peptide [NT-proBNP], high-sensitivity cardiac troponin I, fibrinogen, C-reactive protein, eGFR, and total triglycerides) were significantly associated with AF. NT-proBNP had the best diagnostic performance for AF with area under the receiver operating characteristic curve 0.92 (95%, CI 0.86-0.98); a cutoff value of >528 ng/L had a sensitivity of 79% and a specificity of 97%. None of the other biomarkers, including microRNAs, was associated with AF. Conventional biochemical biomarkers (NT-proBNP, high-sensitivity cardiac troponin I, fibrinogen, C-reactive protein, eGFR, and triglycerides), but not microRNAs (miR-21, miR-29b, miR-133b, miR-142-5p, miR-150, miR-499, and miR-223-3p) were significantly associated with AF in our ischemic stroke cohort.

MiR-450a-2-3p targets ERK(1/2) to ameliorate ISO-induced cardiac fibrosis in mice

ObjectiveCardiac fibrosis is an important contributor to atrial fibrillation (AF). Our aim was to identify biomarkers for AF using bioinformatics methods and explore the regulatory mechanism of miR-450a-2-3p in cardiac fibrosis in mice.MethodsTwo datasets, GSE115574 and GSE79768, were obtained from the Gene Expression Omnibus (GEO) database and subsequently merged for further analysis. Differential gene expression analysis was performed to identify differentially expressed genes (DEGs) and miR-450a-2-3p-related differentially expressed genes (MRDEGs). To investigate the underlying mechanism of cardiac fibrosis, a mouse model was established by treating mice with isoproterenol (ISO) and the miR-450a-2-3p agomir.ResultsA total of 127 DEGs and 31 MRDEGs were identified and subjected to Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to determine the functions and pathways involved in AF. In the animal model, histological analysis using HE and Masson staining, as well as quantification of the collagen volume fraction (CVF), was performed. The increased expression of α-smooth muscle actin (α-SMA), collagen type I (COL1), collagen type III (COL3), and extracellular signal-regulated kinase 1/2 (ERK(1/2)) at both the transcriptional and translational levels indicated the significant development of myocardial fibrosis in mice induced with isoproterenol (ISO). In addition, the cross-sectional area of cardiomyocytes and the expression of atrial natriuretic peptide (NPPA) and brain natriuretic peptide (NPPB) were increased in the ISO group compared with the control group. However, after overexpression of the miR-450a-2-3p agomir through caudal vein injection, there was a notable improvement in cardiac morphology in the treated group. The expression levels of α-SMA, COL1, COL3, ERK(1/2), NPPA, and NPPB were also significantly decreased.ConclusionOur study reveals the mechanistic connection between ISO-induced myocardial fibrosis and the miR-450a-2-3p/ERK(1/2) signaling pathway, highlighting its role in the development of cardiac fibrosis. Modulating miR-450a-2-3p expression and inhibiting ERK(1/2) activation are promising approaches for therapeutic intervention in patients with AF.

Identification of potential biomarkers for atrial fibrillation and stable coronary artery disease based on WGCNA and machine algorithms

BackgroundPatients with atrial fibrillation (AF) often have coronary artery disease (CAD), but the biological link between them remains unclear. This study aims to explore the common pathogenesis of AF and CAD and identify common biomarkers.MethodsGene expression profiles for AF and stable CAD were downloaded from the Gene Expression Omnibus database. Overlapping genes related to both diseases were identified using weighted gene co-expression network analysis (WGCNA), followed by functional enrichment analysis. Hub genes were then identified using the machine learning algorithm. Immune cell infiltration and correlations with hub genes were explored, followed by drug predictions. Hub gene expression in AF and CAD patients was validated by real-time qPCR.ResultsWe obtained 28 common overlapping genes in AF and stable CAD, mainly enriched in the PI3K-Akt, ECM-receptor interaction, and relaxin signaling pathway. Two hub genes, COL6A3 and FKBP10, were positively correlated with the abundance of MDSC, plasmacytoid dendritic cells, and regulatory T cells in AF and negatively correlated with the abundance of CD56dim natural killer cells in CAD. The AUCs of COL6A3 and FKBP10 were all above or close to 0.7. Drug prediction suggested that collagenase clostridium histolyticum and ocriplasmin, which target COL6A3, may be potential drugs for AF and stable CAD. Additionally, COL6A3 and FKBP10 were upregulated in patients with AF and CAD.ConclusionCOL6A3 and FKBP10 may be key biomarkers for AF and CAD, providing new insights into the diagnosis and treatment of this disease.

Distinct functional and molecular profiles between physiological and pathological atrial enlargement offer potential new therapeutic opportunities for atrial fibrillation.

Atrial fibrillation (AF) remains challenging to prevent and treat. A key feature of AF is atrial enlargement. However, not all atrial enlargement progresses to AF. Atrial enlargement in response to physiological stimuli such as exercise is typically benign and reversible. Understanding the differences in atrial function and molecular profile underpinning pathological and physiological atrial remodelling will be critical for identifying new strategies for AF. The discovery of molecular mechanisms responsible for pathological and physiological ventricular hypertrophy has uncovered new drug targets for heart failure. Studies in the atria have been limited in comparison. Here, we characterised mouse atria from (1) a pathological model (cardiomyocyte-specific transgenic (Tg) that develops dilated cardiomyopathy [DCM] and AF due to reduced protective signalling [PI3K]; DCM-dnPI3K), and (2) a physiological model (cardiomyocyte-specific Tg with an enlarged heart due to increased insulin-like growth factor 1 receptor; IGF1R). Both models presented with an increase in atrial mass, but displayed distinct functional, cellular, histological and molecular phenotypes. Atrial enlargement in the DCM-dnPI3K Tg, but not IGF1R Tg, was associated with atrial dysfunction, fibrosis and a heart failure gene expression pattern. Atrial proteomics identified protein networks related to cardiac contractility, sarcomere assembly, metabolism, mitochondria, and extracellular matrix which were differentially regulated in the models; many co-identified in atrial proteomics data sets from human AF. In summary, physiological and pathological atrial enlargement are associated with distinct features, and the proteomic dataset provides a resource to study potential new regulators of atrial biology and function, drug targets and biomarkers for AF.

Expression profile of circulating miRNAs in patients with atrial fibrillation-dominated cardioembolic stroke: A systematic review and bioinformatics analysis

BackgroundCardioembolic stroke is a type of ischemic stroke with high disability and mortality, a high recurrence rate and poor prognosis. miRNAs have been explored as potential noninvasive biomarkers in atrial fibrillation and ischemic stroke, but their expression profile in cardioembolic stroke still needs to be explored. This study will explore the differences in miRNA expression between cardioembolic stroke patients and healthy people through meta-analysis and attempt to analyze the target genes by bioinformatics analysis. MethodsLiterature databases and gene expression databases were searched from the inception date to June 2022. The study reported the circulating miRNA expression profiles in cardioembolic stroke patients and healthy controls. miRNAs with significantly differential expression and their target genes were analyzed. ResultsThree articles and one gene expression dataset were included in the analysis. The results showed that miR-21–5p (SMD: 2.16; 95 % CI: 1.57, 2.75; p < 0.001), miR-943, miR-145–3p, and miR-3148 were upregulated in cardioembolic stroke patients compared with controls. The downregulated miRNAs included miR-3136–5p, miR-2277–5p, and miR-2277–3p. The area under the receiver operating characteristic curve of miR-21–5p for cardioembolic stroke was 0.975 (0.933–0.989). For the enrichment results, the target genes of upregulated miRNAs were enriched in the MAPK signaling pathway, Ras signaling pathway, etc. The target genes of downregulated miRNAs were also enriched in the Ras signaling pathway. ConclusionsThis study suggested that circulating miR-21–5p is upregulated in cardioembolic stroke patients compared to healthy controls. The Ras signaling pathway plays an important role in pathogenesis according to enrichment analysis.

Compressed Deep Learning Models for Wearable Atrial Fibrillation Detection through Attention.

Deep learning (DL) models have shown promise for the accurate detection of atrial fibrillation (AF) from electrocardiogram/photoplethysmography (ECG/PPG) data, yet deploying these on resource-constrained wearable devices remains challenging. This study proposes integrating a customized channel attention mechanism to compress DL neural networks for AF detection, allowing the model to focus only on the most salient time-series features. The results demonstrate that applying compression through channel attention significantly reduces the total number of model parameters and file size while minimizing loss in detection accuracy. Notably, after compression, performance increases for certain model variants in key AF databases (ADB and C2017DB). Moreover, analyzing the learned channel attention distributions after training enhances the explainability of the AF detection models by highlighting the salient temporal ECG/PPG features most important for its diagnosis. Overall, this research establishes that integrating attention mechanisms is an effective strategy for compressing large DL models, making them deployable on low-power wearable devices. We show that this approach yields compressed, accurate, and explainable AF detectors ideal for wearables. Incorporating channel attention enables simpler yet more accurate algorithms that have the potential to provide clinicians with valuable insights into the salient temporal biomarkers of AF. Our findings highlight that the use of attention is an important direction for the future development of efficient, high-performing, and interpretable AF screening tools for wearable technology.

Circulating microRNAs and DNA Methylation as Regulators of Direct Oral Anticoagulant Response in Atrial Fibrillation and Key Elements for the Identification of the Mechanism of Action (miR-CRAFT): Study Design and Patient Enrolment.

Direct oral anticoagulants (DOACs) are the standard treatment for thromboembolic protection in atrial fibrillation (AF) patients. Epigenetic modifications, such as DNA methylation and microRNAs, have emerged as potential biomarkers of AF. The epigenetics of DOACs is still an understudied field. It is largely unknown whether epigenetic modifications interfere with DOAC response or whether DOAC treatment induces epigenetic modifications. To fill this gap, we started the miR-CRAFT (Circulating microRNAs and DNA methylation as regulators of Direct Oral Anticoagulant Response in Atrial Fibrillation) research study. In miR-CRAFT, we follow, over time, changes in DNA methylation and microRNAs expression in naïve AF patients starting DOAC treatment. The ultimate goal of miR-CRAFT is to identify the molecular pathways epigenetically affected by DOACs, beyond the coagulation cascade, that are potentially mediating DOAC pleiotropic actions and to propose specific microRNAs as novel circulating biomarkers for DOAC therapy monitoring. We herein describe the study design and briefly present the progress in participant enrolment.

MiR-486-5p diagnosed atrial fibrillation, predicted the risk of left atrial fibrosis, and regulated angiotensin II-induced cardiac fibrosis via modulating PI3K/Akt signaling through targeting FOXO1.

This study focused on miR-486-5p in atrial fibrillation (AF) evaluating its clinical significance and revealing its regulatory mechanism in cardiac fibroblasts, aiming to explore a novel biomarker for AF. The study enrolled 131 AF patients and 77 non-AF individuals. With the help of polymerase chain reaction (PCR), the expression of miR-486-5p was evaluated. The significance of miR-486-5p in the diagnosis of AF and the occurrence of left atrial fibrosis (LAF) was assessed by receiver operating curve (ROC) and logistic analyses. The regulatory effect and mechanism of miR-486-5p on cardiac fibrosis were investigated in human cardiac fibroblasts treated with angiotensin II. miR-486-5p was significantly upregulated in AF patients and discriminated AF patients from non-AF individuals. Increasing miR-486-5p showed a significant association with decreasing left ventricular ejection fraction (LVEF), increasing left atrial diameter (LAD) and left ventricular end-diastolic diameter (LVEDd), and the high incidence of LAF in AF patients. Moreover, miR-486-5p was identified as a risk factor for LAF and could distinguish AF patients with LAF and without LAF. In cardiac fibroblasts, angiotensin II induced the upregulation of miR-486-5p and promoted cell proliferation, migration, and collagen synthesis. miR-486-5p negatively regulated forkhead box O1 (FOXO1) and its knockdown could reverse the promoted effect of angiotensin II. FOXO1 alleviated the effect of miR-486-5p, and the miR-486-5p/FOXO1 could activate PI3K/Akt signaling. The activation of PI3K/Akt signaling alleviated the enhanced proliferation, migration, and collagen synthesis of cardiac fibroblasts induced by angiotensin II, and its inhibition showed opposite effects. Increased miR-486-5p served as a biomarker for the diagnosis and development prediction of AF. miR-486-5p regulated cardiac fibroblast viability and collagen synthesis via modulating the PI3K/Akt signaling through targeting FOXO1.

Circulating levels of potential markers of ischemic stroke in patients with the different forms of atrial fibrillation and chronic heart failure

Atrial fibrillation (AF) is the most common abnormal type of heart rhythm (cardiac arrhythmia), which is considered the leading cause of stroke. There have been limited studies on the prognostic markers for atrial disease and AF-associated ischemic stroke, despite the high demand for this procedure in daily clinical practice to monitor disease course and assess risk of stroke in patients with AF and chronic heart failure (CHF). Thus, the aim of the present study was to evaluate the levels of serum biomarkers related to ischemic stroke in CHF patients with the different forms of AF. Forty-six patients with various types of AF (paroxysmal, persistent and permanent) with or without ischemic stroke were enrolled in the study, 36 clinically healthy donors served as a control. The levels of inducible nitric oxide synthase (iNOS), vascular endothelial growth factor (VEGF) and angiostatins (AS) were evaluated by western blot analysis in the serum. The levels of active matrix metalloproteinases (MMPs) were analysed by gelatin zymography. Elevated levels of iNOS were shown in patients with all AF forms as compared with control, but iNOS levels in post-ischemic patients were significantly higher than that in paroxysmal AF individuals. However, the levels of VEGF and AS did not differ from the baseline value in patients with paroxysmal AF, while dramatic increase of their contents was shown in post-stroke patients with persistent and permanent types of AF. Elevated active MMP-9 levels were shown to be associated with the diagnosis of all AF forms, regardless of the occurrence of stroke. Taken together, our findings­ demonstrate that tested proteins can be considered as valuable biomarkers of AF forms transformation and potentially useful for ischemic stroke risk stratification in patients with AF and CHF. Observed changes in regulatory protein levels may expand our understanding of pathological roles of endothelial function dysregulation, disrupted angiogenesis balance and abnormal tissue remodeling in AF and associated ischemic events. Keywords: angiostatins, atrial fibrillation, biomarkers, iNOS, ischemic stroke, MMP-9, VEGF

Identification of common mechanisms and biomarkers of atrial fibrillation and heart failure based on machine learning.

Atrial fibrillation (AF) is the most common arrhythmia. Heart failure (HF) is a disease caused by heart dysfunction. The prevalence of AF and HF were progressively increasing over time. The co-existence of AF and HF presents a significant therapeutic challenge. In order to provide new ideas for the diagnosis of AF and HF, it is necessary to carry out biomarker related studies. The training set and validation set data of AF and HF patient samples were downloaded from the GEO database, 'limma' was used to compare the differences in gene expression levels between the disease group and the normal group to screen for differentially expressed genes (DEGs). Weighted correlation network analysis (WGCNA) identified the modules with the highest positive correlation with AF and HF. Functional enrichment and PPI network construction of key genes were carried out. Biomarkers were screened by machine learning. The infiltration of immune cells in AF and HF groups was evaluated by R-packet 'CIBERSORT'. The miRNA network was constructed and potential therapeutic agents for biomarker genes were predicted through the drugbank database. Through WGCNA analysis, it was found that the modules most positively correlated with AF and HF were MEturquoise (r=0.21, P value=0.09) and MEbrown (r=0.62, P value=8e-12), respectively. We screened 25 genes that were highly correlated with both AF and HF. Lasso regression analysis results showed 7 and 20 core genes in AF and HF groups, respectively. The top 20 important genes in AF and HF groups were obtained as core genes by RF model analysis. Four biomarkers were obtained after the intersection of core genes in four groups, namely, GLUL, NCF2, S100A12, and SRGN. The diagnostic efficacy of four genes in AF validation sets was good (AUC: GLUL 0.76, NCF2 0.64, S100A12 0.68, and SRGN 0.76), as well as in the HF validation set (AUC: GLUL 0.76, NCF2 0.84, S100A12 0.92, and SRGN 0.68). The highest correlation with neutrophils was observed for GLUL, NCF2, and S100A12, while SRGN exhibited the strongest correlation with T cells CD4 memory resting in the AF group. GLUL, NCF2, S100A12, and SRGN were most associated with neutrophils in the HF group. A total of 101 miRNAs were predicted by four genes, and GLUL, NCF2, and S100A12 predicted a total of 10 potential therapeutic agents. We identified four biological markers that are highly correlated with AF and HF, namely, GLUL, NCF2, S100A12, and SRGN. Our findings provide theoretical basis for the clinical diagnosis and treatment of AF and HF.

Amino acid profile alteration in age-related atrial fibrillation

BackgroundAmino acids (AAs) are one of the primary metabolic substrates for cardiac work. The correlation between AAs and both atrial fibrillation (AF) and aging has been documented. However, the relationship between AAs and age-related AF remains unclear.MethodsInitially, the plasma AA levels of persistent AF patients and control subjects were assessed, and the correlations between AA levels, age, and other clinical indicators were explored. Subsequently, the age-related AF mouse model was constructed and the untargeted myocardial metabolomics was conducted to detect the level of AAs and related metabolites. Additionally, the gut microbiota composition associated with age-related AF was detected by a 16S rDNA amplicon sequencing analysis on mouse fecal samples.ResultsHigher circulation levels of lysine (Student’s t-test, P = 0.001), tyrosine (P = 0.002), glutamic acid (P = 0.008), methionine (P = 0.008), and isoleucine (P = 0.014), while a lower level of glycine (P = 0.003) were observed in persistent AF patients. The feature AAs identified by machine learning algorithms were glutamic acid and methionine. The association between AAs and age differs between AF and control subjects. Distinct patterns of AA metabolic profiles were observed in the myocardial metabolites of aged AF mice. Aged AF mice had lower levels of Betaine, L-histidine, L-alanine, L-arginine, L-Pyroglutamic acid, and L-Citrulline compared with adult AF mice. Aged AF mice also presented a different gut microbiota pattern, and its functional prediction analysis showed AA metabolism alteration.ConclusionThis study provided a comprehensive network of AA disturbances in age-related AF from multiple dimensions, including plasma, myocardium, and gut microbiota. Disturbances of AAs may serve as AF biomarkers, and restoring their homeostasis may have potential benefits for the management of age-related AF.

The epicardial adipose tissue confined in the atrioventricular groove can be used to assess atrial adipose tissue and atrial dysfunction in cardiac magnetic resonance imaging.

The growing interest in epicardial adipose tissue (EAT) as a biomarker of atrial fibrillation is limited by the difficulties in isolating EAT from other paracardial adipose tissues. We tested the feasibility and value of measuring the pure EAT contained in the atrioventricular groove (GEAT) using cardiovascular magnetic resonance (CMR) imaging in patients with distinct metabolic disorders. CMR was performed on 100 patients from the MetaCardis cohort: obese (n = 18), metabolic syndrome (MSD) (n = 25), type-2 diabetes (T2D) (n = 42), and age- and gender-matched healthy controls (n = 15). GEAT volume measured from long-axis views was obtained in all patients with a strong correlation between GEAT and atrial EAT (r = 0.95; P < 0.0001). GEAT volume was higher in the three groups of patients with metabolic disorders and highest in the MSD group compared with controls. GEAT volume, as well as body mass and body fat, allowed obese, T2D, and MSD patients to be distinguished from controls. GEAT T1 relaxation and peak longitudinal left atrial (LA) strain in CMR were decreased in T2D patients. Logistic regression and random forest machine learning methods were used to create an algorithm combining GEAT volume, GEAT T1, and peak LA strain to identify T2D patients from other groups with an area under curve (AUC) of 0.81 (Se: 77%, Spe: 80%; 95% confidence interval 0.72-0.91, P < 0.0001). Atrioventricular groove adipose tissue characteristics measured during routine CMR can be used as a proxy of atrial EAT and integrated in a multi-parametric CMR biomarker for early identification of atrial cardiomyopathy.

Exploring the shared biomarkers between cardioembolic stroke and atrial fibrillation by WGCNA and machine learning.

Cardioembolic Stroke (CS) and Atrial Fibrillation (AF) are prevalent diseases that significantly impact the quality of life and impose considerable financial burdens on society. Despite increasing evidence of a significant association between the two diseases, their complex interactions remain inadequately understood. We conducted bioinformatics analysis and employed machine learning techniques to investigate potential shared biomarkers between CS and AF. We retrieved the CS and AF datasets from the Gene Expression Omnibus (GEO) database and applied Weighted Gene Co-Expression Network Analysis (WGCNA) to develop co-expression networks aimed at identifying pivotal modules. Next, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the shared genes within the modules related to CS and AF. The STRING database was used to build a protein-protein interaction (PPI) network, facilitating the discovery of hub genes within the network. Finally, several common used machine learning approaches were applied to construct the clinical predictive model of CS and AF. ROC curve analysis to evaluate the diagnostic value of the identified biomarkers for AF and CS. Functional enrichment analysis indicated that pathways intrinsic to the immune response may be significantly involved in CS and AF. PPI network analysis identified a potential association of 4 key genes with both CS and AF, specifically PIK3R1, ITGAM, FOS, and TLR4. In our study, we utilized WGCNA, PPI network analysis, and machine learning to identify four hub genes significantly associated with CS and AF. Functional annotation outcomes revealed that inherent pathways related to the immune response connected to the recognized genes might could pave the way for further research on the etiological mechanisms and therapeutic targets for CS and AF.

Identification and validation of aging-related genes in atrial fibrillation.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in the clinic. Aging plays an essential role in the occurrence and development of AF. Herein, we aimed to identify the aging-related genes associated with AF using bioinformatics analysis. Transcriptome profiles of AF were obtained from the GEO database. Differential expression analysis was performed to identify AF-specific aging-related genes. GO and KEGG enrichment analyses were performed. Subsequently, the LASSO, SVM-RFE, and MCC algorithms were applied to screen aging-related genes. The mRNA expression of the screened genes was validated in the left atrial samples of aged rapid atrial pacing-induced AF canine models and their counterparts. The ROC curves of them were drawn to evaluate their diagnostic potential. Moreover, CIBERSORT was used to estimate immune infiltration. A correlation analysis between screened aging-related genes and infiltrating immune cells was performed. A total of 24 aging-related genes were identified, which were found to be mainly involved in the FoxO signaling pathway, PI3K-Akt signaling pathway, longevity regulating pathway, and peroxisome according to functional enrichment analysis. LASSO, SVM-RFE, and MCC algorithms identified three genes (HSPA9, SOD2, TXN). Furthermore, the expression levels of HSPA9 and SOD2 were validated in aged rapid atrial pacing-induced AF canine models. HSPA9 and SOD2 could be potential diagnostic biomarkers for AF, as evidenced by the ROC curves. Immune infiltration and correlation analysis revealed that HSPA9 and SOD2 were related to immune cell infiltrates. Collectively, these findings provide novel insights into the potential aging-related genes associated with AF. HSPA9 and SOD2 may play a significant role in the occurrence and development of AF.

Diabetic atrial cardiomyopathy can be identified by multiparametric mri MRI associating atrio-ventricular groove adipose tissue and left atrial strain profiles

Abstract Background Epicardial adipose tissue (EAT) is tightly associated with neighboring myocardium with free diffusion between the two tissues of fatty acid, peptides and adipokines. In specific circumstances EAT can favors myocardial remodeling and, for instance, contribute to the risk of atrial fibrillation (AF). Thereby, there is a growing interest for EAT as a biomarker of AF however, which is limited by difficulties of delineation of EAT vs. other paracardial adipose tissues. The atrio-ventricular groove adipose tissue (GEAT) has been proven to be pure epicardial adipose tissue. Purpose We tested the feasibility and value of measuring pure EAT of the atrio-ventricular groove (GEAT) using routine cardiovascular magnetic resonance imaging (CMR) in a cohort of patients with distinct metabolic disorders and studied its correlates to determine a CMR cardiometabolic score. Methods One hundred patients from the METACARDIS cohort (EU FP7) who had MRI, all in sinus rhythm and without overt clinical heart disease, were divided into 4 groups based on distinct metabolic profiles: metabolic syndrome (MSD, n=25), severe obesity (SO, BMI ≥ 35 kg/m2, n=18), type-2 diabetes (T2D, n=42) and healthy controls (n=15). Atrioventricular groove EAT volume was measured from cine SSFP MRI images in four-, three-, two-chamber and short-axis views; atrial EAT volume was measured from four- and two-chamber views. Native T1-mapping values of EAT at the anterior atrioventricular groove excluding the coronary vessels were measured from the MOLLI sequence (basal short-axis slice). Results CMR was performed in 100 patients from the MetaCardis cohort. GEAT volume measured from end-diastolic long axis views was obtained in all patients with a high correlation between GEAT and atrial EAT (r=0.95; P&amp;lt;0.0001). GEAT volume was higher in the 3 groups of patients with metabolic disorders and highest in MSD. Together with age, body mass, fat distribution, GEAT volume allowed to distinguish obese, T2D and MSD from controls. T2D patients were uniquely characterized in CMR by decreased GEAT T1 relaxation and decreased peak longitudinal left atrial strain. We developed a CMR score by logistic regression and Random Forest machine-learning algorithm combining GEAT volume, T1 and peak LA strain that identified T2D patients with an AUC of 0.81 (Se:77%, Spe:80%; 95%-CI 0.72–0.91, p &amp;lt;0.0001). Conclusion The epicardial adipose tissue of the AV groove measured by CMR can be used as the proxy of atrial EAT and, in combination with atrial strain and T1 relaxation, allows the early identification of the atrial cardiomyopathy associated with diabetes. There is diagnostic value of a multiparametric CMR approach for the detection of subclinical atrial cardiomyopathy and potentially to identify patients at risk of atrial fibrillation and stroke.

Abstract 18481: Paroxysmal Atrial Fibrillation and Sleep Apnea: Diurnal Patterning of Autonomic Function and Influence of CPAP Therapy

Introduction: Autonomic nervous system (ANS) dysfunction is implicated in sleep-disordered breathing (SDB) and atrial fibrillation (AF). Hypothesis: We hypothesize that ANS measures of heart rate variability (HRV) exhibit diurnal differences in paroxysmal AF(PAF) relative to SDB severity and is impacted by continuous positive airway pressure (CPAP). Methods: Data from the Sleep Apnea and Atrial Fibrillation Biomarkers and Electrophysiologic Atrial Triggers (SAFEBEAT) study including PAF (7-24 day ECG monitoring), concomitant actigraphy and SDB from polysomnography at baseline and 3-months post-CPAP were analyzed. Linear mixed-effects models were used to assess SDB (apnea hypopnea index (AHI), hypoxia (%sleep time with SaO2&lt;90% and nadir SaO2) and diurnal average HRV (frequency domain (sympathovagal)): low-frequency range (LF), high-frequency range (HF), LF/HF; time domain: mean of normal RR interval (MNN), standard deviation of NN intervals (SDNN), SD1(Poincare plot standard deviation) and effect of 3-month CPAP. Results: In 44869 five-minute epochs from 109 participants with SDB and PAF, during wakefulness, associations of AHI and LFP, nadir SaO2 with sympathovagal measures (LFP, LHR) and time domain measures (SDNN, SD2) were observed. A sleep-wake significant interaction was observed with all HRV measures and stronger associations in wake than sleep. Baseline to follow-up CPAP time domain measures were increased during wakefulness (MNN, SDNN, RMSSD, CV, SD1, and SD2) and increased during sleep (MNN, SD2, LHR). Conclusions: Diurnal variation of autonomic measures in moderate to severe SDB was observed and association with SDB severity was more pronounced during wakefulness; CPAP influenced autonomic function. These findings in earlier onset AF may contribute to electrophysiological remodeling with implications for ANS-specific chronobiology in SDB.

Circulating Neuropeptide Y May Be a Biomarker for Diagnosing Atrial Fibrillation

Introduction: Sympathetic nervous system disorder promotes atrial fibrillation (AF), and neuropeptide Y (NPY) is an important neurotransmitter. This study aimed to explore the predictive value of plasma NPY in patients with AF. Methods: Five hundred seventy-six patients were divided into AF (including paroxysmal and long-standing persistent AF; 360) and sinus rhythm (SR) groups (216). NPY level was detected using enzyme-linked immunosorbent assay, and NPY mRNA expression level was detected using quantitative polymerase chain reaction. Logistic regression was used to analyse the risk factors for AF; the correlations between blood NPY level and age, body mass index (BMI), left ventricular ejection fraction, left atrial diameter (LAD), and European Heart rate Association (EHRA) score in patients with AF were determined. The receiver operating characteristic (ROC) curve was utilised to predict AF. Results: Plasma NPY levels were found to be higher in patients with AF than in patients with SR and in patients with long-standing persistent AF than in patients with paroxysmal AF; blood NPY mRNA levels were higher in the paroxysmal and long-standing persistent AF groups compared to the SR group (p < 0.05). Increased age {odds ratio (OR) = 1.201 (95% confidence interval [CI]: 1.01, 1.427)} and high NPY [OR = 1.239 (95% CI: 1.022, 1.501)] were factors found to affect AF detrimentally. NPY was associated with BMI (r = 0.5856, p < 0.05), LAD (r = 0.4023, p < 0.05), and EHRA score (r = 0.898, p < 0.05). The ROC curve for the predictive value of plasma NPY levels for AF showed an area under the curve (AUC) value of 0.919 (p < 0.05), while that for long-standing persistent AF showed an AUC of 0.784 (p < 0.05). Conclusion: Circulating NPY may be a promising molecular biomarker of AF.

0613 Actigraphy-Based Sleep Disruption and Diurnal Biomarkers of Autonomic Function in Paroxysmal Atrial Fibrillation

Abstract Introduction Sleep architectural disruption is associated with atrial fibrillation (AF), however, associated autonomic influences remain unclear and it is unknown if this detriment persists during wakefulness. We hypothesize diurnal-patterned associations of sleep disruption and autonomic dysfunction in patients with paroxysmal AF Methods We analyzed data from the Sleep Apnea and Atrial Fibrillation Biomarkers and Electrophysiologic Atrial Triggers (SAFEBEAT) study designed to examine paroxysmal AF and sleep apnea involving simultaneous collection of continuous electrocardiogram monitoring (Heartrak Telemetry®) and actigraphy (Actiwatch GTX) for 7-21 days. Heart rate variability (HRV) measures in frequency and time domains were used as surrogates of autonomic function and averaged per sleep/wake per day. A linear mixed-effects model assuming compound symmetry correlation structure was used to assess the relationship of HRV with actigraphy-derived sleep data. Results The analytic sample (age 60.1±12 years, body mass index 32.6±6.7 kg/m², 36% female, 75% White) included 108 participants with paroxysmal AF. Significant associations were observed between sleep indices and HRV measures during wakefulness: a) Sleep latency with high-frequency power (HFP), b) total sleep time, wakefulness after sleep onset (WASO) and number of awakenings with low-frequency power (LFP), and c) Sleep efficiency with standard deviation of normal R-R intervals (SDNN) and coefficient of variation (CV). During sleep, a) total sleep time was associated with LFP/HFP ratio (LHR), and b) number of awakenings with LHR. Significant sleep-wake interactions were observed between a) Sleep latency and HFP, b) Sleep efficiency with SDNN and CV, c) WASO with SDNN, CV, and LFP, and d) number of awakenings with CV and LFP. Conclusion Our novel findings indicate actigraphy-based measures of sleep disruption were associated with autonomic function alterations and these relationships exhibited diurnal variability in patients with paroxysmal AF. Results provide unique insights into differential relationships of immediate (during sleep) versus sustained (during wakefulness) autonomic dysfunction related to sleep disruption which may contribute to atrial arrhythmogenesis Support (if any)

Atrial fibrillation screening to prevent stroke in patients with high NT-proBNP - a post-hoc analysis of the randomized LOOP study

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): The Innovation Fund Denmark Background and aims Stroke is a leading cause of mortality and disability, and atrial fibrillation (AF) is an important and potentially modifiable risk factor for stroke. AF screening can substantially increase the amount of patients diagnosed and treated, but randomized trials have yet to demonstrate a significant decrease in strokes following screening. N-terminal prohormone of brain natriuretic peptide (proBNP) is an established biomarker for AF and could potentially be used to select patients for screening. We a used randomized trial of AF screening vs usual care to investigated the usefulness of proBNP as a tool to select patients for screening to prevent outcomes. Methods The LOOP Study randomized AF-naïve individuals aged &amp;gt;70 years with additional stroke risk factors in a 1:3 ratio to either continuous AF screening using implantable loop recorder (ILR) with initiation of anticoagulation upon detection of AF, or usual care. In this post-hoc analysis, study participants with a baseline measurement of proBNP were included, and the effect of screening vs usual care was compared in groups according to proBNP tertiles. Results Of 6004 participants randomized, 5819 (97%) had proBNP measured. The tertiles of proBNP were at &amp;lt;11, 11-22, and 22 pmol/L (Figure 1). A total of 1014 participants (17.4%) were diagnosed with AF (ILR 32.1% vs Control 12.5%), and 310 (5.3%) endured a stroke or systemic arterial embolism (SAE) (ILR 4.5% vs Control 5.6%). In the lower two tertiles of proBNP, 13% were diagnosed with AF (ILR 26.6% vs Control 8.3%), and 4.6% endured a stroke or SAE (ILR 4.6% vs Control 4.6%), whereas in the highest tertile of proBNP, 25.9% were diagnosed with AF (ILR 42.9% vs 20.3%), and 6.73% endured a stroke or SAE (ILR 4.4% vs Control 7.5%). In the lower two tertiles of proBNP, there was no protective effect from AF screening as compared with usual care (hazard ratio (HR) 1.00 (95% CI 0.71-1.41), p=0.999), whereas in the highest tertile of proBNP there was a significant effect of screening (HR 0.59 (95% CI 0.37-0.93), p=0.021) (Figure 2). More details including proBNP cutoffs, and the impact on stroke subtypes, disability and mortality will be presented at the Congress. Conclusions In a population at increased risk of stroke, proBNP pose a useful biomarker to select individuals for AF screening to prevent stroke. In persons with increased proBNP, the effect of screening could be significant, whereas there is no signal towards effects from screening in people with normal proBNP levels.