Protein Biomarkers and Risk of Atrial Fibrillation: The FHS

Associations between Dietary Phenolic Compounds and Biomarkers of Atrial Fibrillation Risk in Adults with Metabolic Syndrome: A Longitudinal Analysis

INTRODUCTION

Phenolic compounds (PC) may reduce the risk of cardiovascular disease due to their anti-inflammatory and antioxidant effects. Examining relationships between dietary intake of total PC and atrial fibrillation (AF) risk biomarkers in a Mediterranean population with metabolic syndrome may offer new insights about AF physiopathology.

OBJECTIVE

This observational study aims to analyze the relationship between total PC intake and serum levels of five AF-related biomarkers over 5 years in 566 participants from the PREDIMED-Plus trial.

METHODS

In participants with metabolic syndrome (mean age: 65.1 years, 40.4% women), blood biomarkers were measured at baseline, 3, and 5 years: N-terminal pro B-type natriuretic peptide (NT-proBNP) (atrial stretch), high-sensitivity Troponin T (hs-TnT) (myocardial damage), high-sensitivity C-reactive protein (hs-CRP) (inflammation), procollagen type 1 carboxy-terminal propeptide (PICP) (fibrosis), and 3-nitrotyrosine (3-NT) (oxidative stress). PC intake was assessed using a validated 143-item food frequency questionnaire and the Phenol-Explorer database. Changes in log-transformed biomarkers levels were evaluated with multivariable-adjusted mixed linear models. Sources of between-person variability in total PC intake were also evaluated.

RESULTS

Over 5-year, participants with moderate-high baseline PC intake (quartiles 2-4) showed a 39.5% (95%CI 27.4%;52.6%; p<0.001) increase in NT-proBNP concentrations compared to a 20.5% (95%CI% 3.4%,40.3%; p=0.03) increase in the lowest quartile, (ptime*categories =0.04). When PC intake was updated over follow-up, moderate-high intake showed a 32.2% (95%CI 19.5%;46.2%, p<0.001) increase in NT-proBNP vs. a 27.3% (95%CI 6.5%;52.1%, p=0.004) in the lowest quartile, (ptime*categories =0.02). Participants with moderate-high PC intake undergoing intensive lifestyle intervention (ILI) showed smaller increases in hs-TnT than those with lower intake. Chocolate was the main contributor to between-person variability in PC intake.

CONCLUSION

Our results shows that higher PC intake was associated with larger increases in NT-proBNP concentrations. In participants undergoing an ILI and higher PC intake, a lower increase in hs-TnT levels was found. Future research is warranted to better understand the role of dietary intake of PC in AF-related pathways.

Recurrent atrial fibrillation markers post radiofrequency catheter ablation

Atrial fibrillation (AF), the most common type of heart arrhythmia, is recognized as an independent risk factor for stroke. Fortunately, catheter ablation (CA) offers an effective treatment option for AF patients. However, numerous studies have reported suboptimal outcomes, as AF recurrence rates often remain elevated even after CA. Consequently, there exists a need for early identification of patients prone to recurrence, necessitating anti-inflammatory and/or antiarrhythmic treatment post-CA. The discovery and application of markers associated with AF recurrence could significantly aid in this early identification process. In this review, we present an overview of AF recurrence markers from three distinct perspectives (biochemical, imaging, and electrocardiographic markers).

Transcriptomics, Proteomics and Bioinformatics in Atrial Fibrillation: A Descriptive Review

Atrial fibrillation (AF) is the most frequent cardiac arrhythmia, with an estimated five million cases globally. This condition increases the likelihood of developing cardiovascular complications such as thromboembolic events, with a fivefold increase in risk of both heart failure and stroke. Contemporary challenges include a better understanding AF pathophysiology and optimizing therapeutical options due to the current lack of efficacy and adverse effects of antiarrhythmic drug therapy. Hence, the identification of novel biomarkers in biological samples would greatly impact the diagnostic and therapeutic opportunities offered to AF patients. Long noncoding RNAs, micro RNAs, circular RNAs, and genes involved in heart cell differentiation are particularly relevant to understanding gene regulatory effects on AF pathophysiology. Proteomic remodeling may also play an important role in the structural, electrical, ion channel, and interactome dysfunctions associated with AF pathogenesis. Different devices for processing RNA and proteomic samples vary from RNA sequencing and microarray to a wide range of mass spectrometry techniques such as Orbitrap, Quadrupole, LC-MS, and hybrid systems. Since AF atrial tissue samples require a more invasive approach to be retrieved and analyzed, blood plasma biomarkers were also considered. A range of different sample preprocessing techniques and bioinformatic methods across studies were examined. The objective of this descriptive review is to examine the most recent developments of transcriptomics, proteomics, and bioinformatics in atrial fibrillation.

NT-proBNP improves prediction of cardiorenal complications in type 2 diabetes: the Hong Kong Diabetes Biobank

AIMS/HYPOTHESIS

N-terminal pro B-type natriuretic peptide (NT-proBNP) is a natriuretic peptide that is strongly associated with congestive heart failure (CHF). The utility of NT-proBNP for prediction of cardiovascular events and renal endpoints, compared with clinical risk factors, has not been evaluated in detail. We hypothesise that NT-proBNP can improve risk stratification and prediction of cardiorenal events in type 2 diabetes, beyond that provided by clinical risk factors.

METHODS

NT-proBNP was measured in 1993 samples from the Hong Kong Diabetes Biobank, a multicentre prospective diabetes cohort and biobank. A cut-off of ≥125 pg/ml was used to define elevated NT-proBNP. Associations between elevated NT-proBNP and incident cardiovascular and renal endpoints were examined using Cox regression, adjusted for sex, age and duration of diabetes, as well as other covariates. Prognostic and incremental predictive values of NT-proBNP in diabetes cardiorenal complications, compared with those of the Joint Asia Diabetes Evaluation risk equations for CHD, CHF and kidney failure, were evaluated using the concordance index (C index), net reclassification improvement index, integrated discrimination improvement index and relative integrated discrimination improvement index.

RESULTS

A total of 24.7% of participants had elevated NT-proBNP. Participants with elevated NT-proBNP at baseline had a more adverse cardiometabolic profile, with 2-4-fold higher frequency of complications at baseline. Adjusting for age at baseline, sex and duration of diabetes, elevated NT-proBNP was associated with incident atrial fibrillation (HR 4.64 [95% CI 2.44, 8.85]), CHD (HR 4.21 [2.46, 7.21]), CVD (HR 3.32 [2.20, 5.01]) and CHF (HR 4.18 [2.18, 8.03]; all p<0.001). All these associations remained significant after further adjustment for additional covariates. Elevated NT-proBNP had good discriminative ability for various cardiorenal endpoints, with C index of 0.83 (95% CI 0.76, 0.90) for CHD, 0.88 (0.81, 0.94) for atrial fibrillation, 0.89 (0.83, 0.95) for CHF, 0.81 (0.77, 0.84) for 40% drop in eGFR and 0.88 (0.84, 0.92) for kidney failure. Models incorporating NT-proBNP had improved prediction compared with established clinical risk models. Sensitivity analyses including alternative cut-off of NT-proBNP, as well as use of other risk engines of CHD, yielded similar results.

CONCLUSIONS/INTERPRETATION

NT-proBNP demonstrated a promising ability to serve as a prognostic marker for a variety of cardiorenal complications in type 2 diabetes. Considering NT-proBNP in clinical assessments could potentially help identify high-risk individuals who may benefit from more intensive therapies.

Novel Drug Targets for Atrial Fibrillation Identified Through Mendelian Randomization Analysis of the Blood Proteome

PURPOSE

Novel, effective, and safe preventive therapy targets for AF are still needed. Circulating proteins with causal genetic evidence are promising candidates. We aimed to systematically screen circulating proteins for AF drug targets and determine their safety and efficacy using genetic methods.

METHODS

The protein quantitative trait loci (pQTL) of up to 1949 circulating proteins were retrieved from nine large genome-proteome-wide association studies. Two-sample Mendelian Randomization (MR) and colocalization analyses were used to estimate the causal effects of proteins on the risk of AF. Furthermore, phenome-wide MR was conducted to depict side effects and the drug-target databases were searched for drug validation and repurposing.

RESULTS

Systematic MR screen identified 30 proteins as promising AF drug targets. Genetically predicted 12 proteins increased AF risk (TES, CFL2, MTHFD1, RAB1A, DUSP13, SRL, ANXA4, NEO1, FKBP7, SPON1, LPA, MANBA); 18 proteins decreased AF risk (PMVK, UBE2F, SYT11, CHMP3, PFKM, FBP1, TNFSF12, CTSZ, QSOX2, ALAD, EFEMP1, FLRT2, LRIG1, OLA1, SH3BGRL3, IL6R, B3GNT8, FCGR2A). DUSP13 and TNFSF12 possess strong colocalization evidence. For the proteins that were identified, extended phe-MR analysis was conducted to assess their side-effect profiles, while drug-target databases provided information on their approved or investigated indications.

CONCLUSION

We identified 30 circulating proteins as potential preventive targets for AF.

Insulin-like Growth Factor-Binding Protein-1 (IGFBP-1) as a Biomarker of Cardiovascular Disease

Insulin-like growth factor-binding protein-1 (IGFBP-1) contributes to the regulation of IGFs for metabolism and growth and has IGF-independent actions. IGFBP-1 in the circulation is derived from the liver, where it is inhibited by insulin and stimulated by multiple factors, including proinflammatory cytokines. IGFBP-1 levels are influenced by sex and age, which also determine cardiometabolic risk and patterns of disease presentation. While lower circulating IGFBP-1 concentrations are associated with an unfavorable cardiometabolic risk profile, higher IGFBP-1 predicts worse cardiovascular disease outcomes. This review explores these associations and the possible roles of IGFBP-1 in the pathophysiology of atherosclerosis. We recommend the evaluation of dynamic approaches, such as simultaneous measurements of fasting IGFBP-1 and proinsulin level in response to an oral glucose challenge, as well as multi-marker approaches incorporating markers of inflammation.

Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using plasma proteomics profiling

AIMS

Atrial fibrillation (AF) is the most common sustained arrhythmia among patients with hypertrophic cardiomyopathy (HCM), increasing symptom burden and stroke risk. We aimed to construct a plasma proteomics-based model to predict new-onset AF in patients with HCM and determine dysregulated signalling pathways.

METHODS AND RESULTS

In this prospective, multi-centre cohort study, we conducted plasma proteomics profiling of 4986 proteins at enrolment. We developed a proteomics-based machine learning model to predict new-onset AF using samples from one institution (training set) and tested its predictive ability using independent samples from another institution (test set). We performed a survival analysis to compare the risk of new-onset AF among high- and low-risk groups in the test set. We performed pathway analysis of proteins significantly (univariable P < 0.05) associated with new-onset AF using a false discovery rate (FDR) threshold of 0.001. The study included 284 patients with HCM (training set: 193, test set: 91). Thirty-seven (13%) patients developed AF during median follow-up of 3.2 years [25-75 percentile: 1.8-5.2]. Using the proteomics-based prediction model developed in the training set, the area under the receiver operating characteristic curve was 0.89 (95% confidence interval 0.78-0.99) in the test set. In the test set, patients categorized as high risk had a higher rate of developing new-onset AF (log-rank P = 0.002). The Ras-MAPK pathway was dysregulated in patients who developed incident AF during follow-up (FDR < 1.0 × 10-6).

CONCLUSION

This is the first study to demonstrate the ability of plasma proteomics to predict new-onset AF in HCM and identify dysregulated signalling pathways.

Enhanced prediction of atrial fibrillation risk using proteomic markers: a comparative analysis with clinical and polygenic risk scores

BACKGROUND

Proteomic biomarkers have shown promise in predicting various cardiovascular conditions, but their utility in assessing the risk of atrial fibrillation (AF) remains unclear. This study aimed to develop and validate a protein-based risk score for predicting incident AF and to compare its predictive performance with traditional clinical risk factors and polygenic risk scores in a large cohort from the UK Biobank.

METHODS

We analysed data from 36 129 white British individuals without prior AF, assessing 2923 plasma proteins using the Olink Explore 3072 assay. The cohort was divided into a training set (70%) and a test set (30%) to develop and validate a protein risk score for AF. We compared the predictive performance of this score with the HARMS2-AF risk model and a polygenic risk score.

RESULTS

Over an average follow-up of 11.8 years, 2450 incident AF cases were identified. A 47-protein risk score was developed, with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) being the most significant predictor. In the test set, the protein risk score (per SD increment, HR 1.94; 95% CI 1.83 to 2.05) and NT-proBNP alone (HR 1.80; 95% CI 1.70 to 1.91) demonstrated superior predictive performance (C-statistic: 0.802 and 0.785, respectively) compared with HARMS2-AF and polygenic risk scores (C-statistic: 0.751 and 0.748, respectively).

CONCLUSIONS

A protein-based risk score, particularly incorporating NT-proBNP, offers superior predictive value for AF risk over traditional clinical and polygenic risk scores, highlighting the potential for proteomic data in AF risk stratification.

Plasma Proteomic Insights for Identification of Novel Predictors and Potential Drug Targets in Atrial Fibrillation: A Prospective Cohort Study and Mendelian Randomization Analysis

BACKGROUND

Currently, there are no reliable methods for predicting and preventing atrial fibrillation (AF) in its early stages. This study aimed to identify plasma proteins associated with AF to discover biomarkers and potential drug targets.

METHODS

The UK Biobank Pharma Proteomics Project examined 2923 circulating proteins using the Olink platform, forming the basis of this prospective cohort study. The UK Biobank Pharma Proteomics Project included a randomly selected discovery cohort and the consortium-selected replication cohort. The study's end point was incident AF, identified using International Classification of Diseases, Tenth Revision codes. The association between plasma proteins and incident AF was evaluated using Cox proportional hazard models in both cohorts. Proteins present in both cohorts underwent Mendelian randomization analysis to delineate causal connections, utilizing cis-protein quantitative trait loci as genetic tools. The predictive efficacy of the identified proteins for AF was assessed using the area under the receiver operating characteristic curve, and their druggability was explored.

RESULTS

Data from 38 784 participants were included in this study. Incident AF cases were identified in the discovery cohort (1894; 5.5%) within a median follow-up of 14.5 years and in the replication cohort (451; 10.6%) within a median follow-up of 14.4 years. Twenty-one proteins linked to AF were identified in both cohorts. Specifically, COL4A1 (collagen IV α-1; odds ratio, 1.11 [95% CI, 1.04-1.19]; false discovery rate, 0.016) and RET (proto-oncogene tyrosine-protein kinase receptor Ret; odds ratio, 0.96 [95% CI, 0.94-0.98]; false discovery rate, 0.013) demonstrated a causal link with AF, and RET is druggable. COL4A1 improved the short- and long-term predictive performance of established AF models, as evidenced by significant enhancements in the area under the receiver operating characteristic, integrated discrimination improvement, and net reclassification index, all with P values below 0.05.

CONCLUSIONS

COL4A1 and RET are associated with the development of AF. RET is identified as a potential drug target for AF prevention, while COL4A1 serves as a biomarker for AF prediction. Future studies are needed to evaluate the effectiveness of targeting these proteins to reduce AF risk.

Integrating Clinical, Genetic, and Electrocardiogram-Based Artificial Intelligence to Estimate Risk of Incident Atrial Fibrillation

Background

AF risk estimation is feasible using clinical factors, inherited predisposition, and artificial intelligence (AI)-enabled electrocardiogram (ECG) analysis.

Objective

To test whether integrating these distinct risk signals improves AF risk estimation.

Methods

In the UK Biobank prospective cohort study, we estimated AF risk using three models derived from external populations: the well-validated Cohorts for Aging in Heart and Aging Research in Genomic Epidemiology AF (CHARGE-AF) clinical score, a 1,113,667-variant AF polygenic risk score (PRS), and a published AI-enabled ECG-based AF risk model (ECG-AI). We estimated discrimination of 5-year incident AF using time-dependent area under the receiver operating characteristic (AUROC) and average precision (AP).

Results

Among 49,293 individuals (mean age 65±8 years, 52% women), 825 (2.4%) developed AF within 5 years. Using single models, discrimination of 5-year incident AF was higher using ECG-AI (AUROC 0.705 [95%CI 0.686-0.724]; AP 0.085 [0.071-0.11]) and CHARGE-AF (AUROC 0.785 [0.769-0.801]; AP 0.053 [0.048-0.061]) versus the PRS (AUROC 0.618, [0.598-0.639]; AP 0.038 [0.028-0.045]). The inclusion of all components ("Predict-AF3") was the best performing model (AUROC 0.817 [0.802-0.832]; AP 0.11 [0.091-0.15], p<0.01 vs CHARGE-AF+ECG-AI), followed by the two component model of CHARGE-AF+ECG-AI (AUROC 0.802 [0.786-0.818]; AP 0.098 [0.081-0.13]). Using Predict-AF3, individuals at high AF risk (i.e., 5-year predicted AF risk >2.5%) had a 5-year cumulative incidence of AF of 5.83% (5.33-6.32). At the same threshold, the 5-year cumulative incidence of AF was progressively higher according to the number of models predicting high risk (zero: 0.67% [0.51-0.84], one: 1.48% [1.28-1.69], two: 4.48% [3.99-4.98]; three: 11.06% [9.48-12.61]), and Predict-AF3 achieved favorable net reclassification improvement compared to both CHARGE-AF+ECG-AI (0.039 [0.015-0.066]) and CHARGE-AF+PRS (0.033 [0.0082-0.059]).

Conclusions

Integration of clinical, genetic, and AI-derived risk signals improves discrimination of 5-year AF risk over individual components. Models such as Predict-AF3 have substantial potential to improve prioritization of individuals for AF screening and preventive interventions.

Factors Associated With Fatigue in Persons With Atrial Fibrillation in the Atherosclerosis Risk in Communities (ARIC) Study

BACKGROUND

Atrial fibrillation (AF) is a common cardiac arrhythmia affecting over 6 million people in the U.S. Fatigue is a frequent symptom of AF, yet no underlying biological mechanisms have been identified in AF-related fatigue as in other chronic conditions such as cancer or HIV fatigue (inflammation, tissue injury). We aimed to identify biomarkers and correlates of AF-fatigue in ARIC participants.

METHODS

Participants with AF from ARIC visit 5 (2011-2013) were included in the study. Multiple linear regression was used to estimate the association of high sensitivity troponin (hs-TnT), N-terminal fragment B-type natriuretic peptide (NT-proBNP) and high sensitivity C-reactive protein (hsCRP) levels with self-reported fatigue (SF-12 and PROMIS Fatigue Scale), depressive symptoms (Center for Epidemiological Studies Depression survey), and physical functioning (Short Physical Performance Battery) scores. All biomarkers underwent natural-log transformation.

RESULTS

There were 446 participants (mean age: 78 y ± 5; 44% women). In adjusted analyses, NT-proBNP was associated with AF-fatigue (β: 0.11, 95% CI: 0.03, 0.19), increased depressive symptoms (β: 0.44, 95% CI: 0.19, 0.70), and decreased physical function (β: -0.48, 95% CI: -0.72, -0.23). Hs-TnT was also associated with elevated AF-fatigue (β: 0.24, 95% CI: 0.09, 0.39) along with decreased physical function (β: -1.19, 95% CI: -1.64, -0.75). No significant associations were found with hsCRP and fatigue.

CONCLUSION

Increased levels of cardiac injury biomarkers, depressive symptoms, and decreased physical function were associated with AF-fatigue. Inflammation was not associated with AF-fatigue; other physiological pathways, such as cardiac overload or myocardial injury may be more relevant in AF-fatigue.

Prostaglandin I2 signaling prevents angiotensin II-induced atrial remodeling and vulnerability to atrial fibrillation in mice

Atrial fibrillation (AF) is the most common arrhythmia, and atrial fibrosis is a pathological hallmark of structural remodeling in AF. Prostaglandin I2 (PGI2) can prevent the process of fibrosis in various tissues via cell surface Prostaglandin I2 receptor (IP). However, the role of PGI2 in AF and atrial fibrosis remains unclear. The present study aimed to clarify the role of PGI2 in angiotensin II (Ang II)-induced AF and the underlying molecular mechanism. PGI2 content was decreased in both plasma and atrial tissue from patients with AF and mice treated with Ang II. Treatment with the PGI2 analog, iloprost, reduced Ang II-induced AF and atrial fibrosis. Iloprost prevented Ang II-induced atrial fibroblast collagen synthesis and differentiation. RNA-sequencing analysis revealed that iloprost significantly attenuated transcriptome changes in Ang II-treated atrial fibroblasts, especially mitogen-activated protein kinase (MAPK)-regulated genes. We demonstrated that iloprost elevated cAMP levels and then activated protein kinase A, resulting in a suppression of extracellular signal-regulated kinase1/2 and P38 activation, and ultimately inhibiting MAPK-dependent interleukin-6 transcription. In contrast, cardiac fibroblast-specific IP-knockdown mice had increased Ang II-induced AF inducibility and aggravated atrial fibrosis. Together, our study suggests that PGI2/IP system protects against atrial fibrosis and that PGI2 is a therapeutic target for treating AF.The prospectively registered trial was approved by the Chinese Clinical Trial Registry. The trial registration number is ChiCTR2200056733. Data of registration was 2022/02/12.

Circulating adipose tissue proteins involved in atrial fibrillation: An explorative scoping review

Obesity increases the risk of atrial fibrillation (AF), potentially through proteins secreted by adipose tissue (AT) that affect atrial electrical and structural remodeling. We aim to give a comprehensive overview of circulating AT proteins involved in inflammation and fibrosis, that are associated with prevalent AF (paroxysmal or persistent) and the risk on developing new-onset AF. These include adipokines, defined as proteins enriched in AT as adiponectin, but also proteins less specific to AT. We systematically performed an explorative search for studies reporting associations between proteins secreted from cells residing in the AT and AF, and additionally assessed the effect of obesity on these proteins by a secondary search. The AT proteins involved in inflammation were mostly increased in patients with prevalent and new-onset AF, and with obesity, while the AT enriched adipokines were mostly not associated with AF. This review provides insight into circulating adipose tissue proteins involved in AF substrate formation.

Pathophysiology and clinical relevance of atrial myopathy

Atrial myopathy is a condition that consists of electrical, structural, contractile, and autonomic remodeling of the atria and is the substrate for development of atrial fibrillation, the most common arrhythmia. Pathophysiologic mechanisms driving atrial myopathy are inflammation, oxidative stress, atrial stretch, and neurohormonal signals, e.g., angiotensin-II and aldosterone. These mechanisms initiate the structural and functional remodeling of the atrial myocardium. Novel therapeutic strategies are being developed that target the pathophysiologic mechanisms of atrial myopathy. In this review, we will discuss the pathophysiology of atrial myopathy, as well as diagnostic and therapeutic strategies.

Exercise-Dependent Modulation of Immunological Response Pathways in Endurance Athletes With and Without Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) is a common arrhythmia characterized by uncoordinated atrial electrical activity. Lone AF occurs in the absence of traditional risk factors and is frequently observed in male endurance athletes, who face a 2- to 5-fold higher risk of AF compared with healthy, moderately active males. Our understanding of how endurance exercise contributes to the pathophysiology of lone AF remains limited. This study aimed to characterize the circulating protein fluctuations during high-intensity exercise as well as explore potential biomarkers of exercise-associated AF.

METHODS AND RESULTS

A prospective cohort of 12 male endurance cyclists between the ages of 40 and 65 years, 6 of whom had a history of exercise-associated AF, were recruited to participate using a convenience sampling method. The circulating proteome was subsequently analyzed using multiplex immunoassays and aptamer-based proteomics before, during, and after an acute high-intensity endurance exercise bout to assess temporality and identify potential markers of AF. The endurance exercise bout resulted in significant alterations to proteins involved in immune modulation (eg, growth/differentiation factor 15), skeletal muscle metabolism (eg, α-actinin-2), cell death (eg, histones), and inflammation (eg, interleukin-6). Subjects with AF differed from those without, displaying modulation of proteins previously known to have associations with incident AF (eg, C-reactive protein, insulin-like growth factor-1, and angiopoietin-2), and also with proteins having no previous association (eg, tapasin-related protein and α2-Heremans-Schmid glycoprotein).

CONCLUSIONS

These findings provide insights into the proteomic response to acute intense exercise, provide mechanistic insights into the pathophysiology behind AF in athletes, and identify targets for future study and validation.

Disturbed atrial metabolism, shear stress, and cardiac load contribute to atrial fibrillation after ablation: AXAFA biomolecule study

AIMS

Different disease processes can combine to cause atrial fibrillation (AF). Their contribution to recurrent AF after ablation in patients is not known. Cardiovascular processes associated with recurrent AF after AF ablation were determined by quantifying biomolecules related to inflammation, metabolism, proliferation, fibrosis, shear stress, atrial pressure, and others in the AXAFA biomolecule study.

METHODS AND RESULTS

Twelve circulating cardiovascular biomolecules (ANGPT2, BMP10, CA125, hsCRP, ESM1, FABP3, FGF23, GDF15, IGFBP7, IL6, NT-proBNP, and hsTnT) were quantified in plasma samples obtained prior to a first AF ablation using high-throughput, high-precision assays. Cox regression was used to identify biomolecules associated with recurrent AF during the first 3 months after AF ablation. In 433 patients (64 years [58, 70]; 33% women), baseline concentrations of ANGPT2, BMP10, hsCRP, FGF23, FABP3, GDF15, and NT-proBNP were elevated in patients with recurrent AF (120/433; 28%). After adjustment for 11 clinical features and randomized treatment, elevated NT-proBNP [hazard ratio (HR) 1.58, 95% confidence interval (1.29, 1.94)], ANGPT2 [HR 1.37, (1.12, 1.67)], and BMP10 [HR 1.24 (1.02, 1.51)] remained associated with recurrent AF. Concentrations of ANGPT2, BMP10, and NT-proBNP decreased in patients who remained arrhythmia free, but not in patients with recurrent AF, highlighting their connection to AF. The other eight biomarkers showed unchanged concentrations.

CONCLUSION

Elevated concentrations of ANGPT2, BMP10, and NT-proBNP are associated with recurrent AF after a first AF ablation, suggesting that processes linked to disturbed cardiomyocyte metabolism, altered atrial shear stress, and increased load contribute to AF after AF ablation in patients.

Predictive value of soluble suppression of tumorigenicity 2 in atrial fibrillation: a systematic review and meta-analysis

Purpose

Atrial fibrosis is the main pathological basis for the pathogenesis and progression of atrial fibrillation (AF). Soluble suppression of tumorigenicity 2 (sST2) is involved in fibrosis. Recent studies have explored its predictive value in AF outcomes. We performed this study to assess whether sST2 is an independent biomarker of AF outcomes and explore the potential mechanism.

Methods

PubMed, Web of Science, EMBASE, and Cochrane Library databases were searched systematically from inception through July 1, 2023, to identify relevant studies. Outcomes of interest included occurrence, recurrence, and major adverse cardiac events (MACEs) of AF. This meta-analysis was reported following the criteria outlined in PRISMA 2020, and the protocol was registered in PROSPERO (number: CRD42023459789). All statistical analyses were performed using the STATA version 16.

Result

Twenty four studies with 14,755 patients were included in the meta-analysis. The meta-analyses found that sST2 was significantly associated with the risk of occurrence [HR:1.04, 95% CI: 1.02-1.07, P < 0.01; I2 = 67.8%], recurrence [HR:1.09, 95% CI: 1.02-1.16, P < 0.01; I2 = 89.5%], and MACEs (HR:1.60, 95% CI: 1.13-2.27, P < 0.01; I2 = 82.0%) of AF. Furthermore, patients with AF showed higher sST2 than controls without AF (SMD: 0.41, 95% CI: 0.27-0.54, P < 0.01; I2 = 0%), and AF patients with recurrence after catheter ablation (CA) showed significantly higher sST2 than those without recurrence (SMD: 0.81, 95% CI: 0.33-1.28, P < 0.01; I2 = 83.9%). Sensitivity analyses showed that the outcomes were stable.

Conclusions

Higher sST2 was association with an increased risk of occurrence, recurrence, and MACEs of AF. Assessing sST2 can be used as a potential screening method to predict AF outcomes.

Systematic Review Registration

PROSPERO (CRD42023459789).

An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions

Early detection of atrial fibrillation (AF) enables initiation of anticoagulation and early rhythm control therapy to reduce stroke, cardiovascular death, and heart failure. In a cross-sectional, observational study, we aimed to identify a combination of circulating biomolecules reflecting different biological processes to detect prevalent AF in patients with cardiovascular conditions presenting to hospital. Twelve biomarkers identified by reviewing literature and patents were quantified on a high-precision, high-throughput platform in 1485 consecutive patients with cardiovascular conditions (median age 69 years [Q1, Q3 60, 78]; 60% male). Patients had either known AF (45%) or AF ruled out by 7-day ECG-monitoring. Logistic regression with backward elimination and a neural network approach considering 7 key clinical characteristics and 12 biomarker concentrations were applied to a randomly sampled discovery cohort (n = 933) and validated in the remaining patients (n = 552). In addition to age, sex, and body mass index (BMI), BMP10, ANGPT2, and FGF23 identified patients with prevalent AF (AUC 0.743 [95% CI 0.712, 0.775]). These circulating biomolecules represent distinct pathways associated with atrial cardiomyopathy and AF. Neural networks identified the same variables as the regression-based approach. The validation using regression yielded an AUC of 0.719 (95% CI 0.677, 0.762), corroborated using deep neural networks (AUC 0.784 [95% CI 0.745, 0.822]). Age, sex, BMI and three circulating biomolecules (BMP10, ANGPT2, FGF23) are associated with prevalent AF in unselected patients presenting to hospital. Findings should be externally validated. Results suggest that age and different disease processes approximated by these three biomolecules contribute to AF in patients. Our findings have the potential to improve screening programs for AF after external validation.

Proteome-Wide Mendelian Randomization Analysis Identified Potential Drug Targets for Atrial Fibrillation

Background Finding effective and safe therapeutic drugs for atrial fibrillation (AF) is an important concern for clinicians. Proteome-wide Mendelian randomization analysis provides new ideas for finding potential drug targets. Methods and Results Using a proteome-wide Mendelian randomization approach, we assessed the genetic predictive causality between thousands of proteins and AF risk and found that genetically predicted plasma levels of phosphomevalonate kinase, tumor necrosis factor ligand superfamily member 12, sulfhydryl oxidase 2, interleukin-6 receptor subunit alpha, and low-affinity immunoglobulin gamma Fc region receptor II-b might decrease AF risk, while genetically predicted plasma levels of beta-mannosidase, collagen alpha-1(XV) chain, ANXA4 (annexin A4), COF2 (cofilin-2), and RAB1A (Ras-related protein Rab-1A) might increase AF risk (P<3.4×10-5). By using different Mendelian randomization methods and instrumental variable selection thresholds, we performed sensitivity analyses in 30 scenarios to test the robustness of positive findings. Replication analyses were also performed in independent samples to further avoid false-positive findings. Drugs targeting tumor necrosis factor ligand superfamily member 12, interleukin-6 receptor subunit alpha, low-affinity immunoglobulin gamma Fc region receptor II-b, and annexin A4 are approved or in development. The results of the phenome-wide Mendelian randomization analysis showed that changing the plasma levels of phosphomevalonate kinase, cofilin-2, annexin A4, Ras-related protein Rab-1A, sulfhydryl oxidase 2, and collagen alpha-1(XV) chain did not increase the risk of other diseases while decreasing the risk of AF. Conclusions We found a significant causal association between genetically predicted levels of 10 plasma proteins and AF risk. Four of these proteins have drugs targeting them that are approved or in development, and our results suggest the potential for these drugs to treat AF or cause AF. Sulfhydryl oxidase 2, low-affinity immunoglobulin gamma Fc region receptor II-b, and beta-mannosidase have not been suggested by previous laboratory or epidemiological studies to be associated with AF and may reveal new pathophysiological pathways as well as therapeutic targets for AF.

Predictive value of pre-procedural N-terminal pro-B-type natriuretic peptide level for atrial fibrillation recurrence after radiofrequency catheter ablation

Introduction

N-terminal pro-B-type natriuretic peptide (NT-proBNP) has been demonstrated as a valuable risk marker for mortality and morbidity of cardiovascular disease. Recurrence after atrial fibrillation (AF) radiofrequency catheter ablation remains common.

Aim

We investigated the predictive value of the pre-procedural level of NT-proBNP to differentiate high-risk patients for post-ablation AF recurrence.

Material and methods

326 individuals with nonvalvular AF and preserved systolic function after enduring an initial radiofrequency catheter ablation (RFCA) between March 2018 and December 2019 were categorized into a recurrent group and a non-AF recurrent group. The serum NT-proBNP levels were examined before the ablation procedure. The researchers used multivariate logistic regression to find the determinants of AF recurrence.

Results

During a 14-month (interquartile range (IQR): 12-16) median follow-up, AF recurred in 84 (25.8%) patients. Patients in the recurrence group had considerably greater pre-ablation NT-proBNP levels (389.4 vs. 141.7 pg/ml, p < 0.001 in non-paroxysmal AF and 348.0 vs. 99.4 pg/ml, p < 0.001 in paroxysmal AF) as well as a greater left atrium (40 vs. 36 mm, p = 0.01 in non-paroxysmal AF and 38 vs. 36 mm, p = 0.01 in paroxysmal AF) than the non-AF recurrence group. A cut-off value of NT-proBNP ≥ 168.05 pg/ml identified AF recurrence with a sensitivity of 78.6% and specificity of 53.7% (area under ROC curve 0.68, 95% confidence interval (CI) 0.62-0.74, p < 0.001). Kaplan-Meier examination revealed that the elevated NT-proBNP (≥ 168.05 pg/ml) group presented a considerably shorter period without an occurrence compared to the low-NT-proBNP group (18.4 vs. 22.2 months, log-rank p = 0.001). Multivariate cox regression investigation showed that a level of NT-proBNP ≥ 168.05 pg/ml (hazard ratio (HR): 2.89, 95% CI: 1.71-4.903, p < 0.001) was a reliable predictor of AF recurrence after RFCA.

Conclusions

A high pre-ablation NT-proBNP level was associated with AF recurrence, and it was also discovered to be a prognostic factor of recurrence of AF following RFCA.

Biomarker Changes Associated With Both Dulaglutide and Cardiovascular Events in the REWIND Randomized Controlled Trial: A Nested Case-Control Post Hoc Analysis

OBJECTIVE

The glucagon-like peptide-1 receptor agonist dulaglutide reduced MACE in the Researching Cardiovascular Events with a Weekly Incretin in Diabetes (REWIND) trial. This article expores the relationship of selected biomarkers to both dulaglutide and major adverse cardiovascular events (MACE).

RESEARCH DESIGN AND METHODS

In this post hoc analysis, stored fasting baseline and 2-year plasma samples from 824 REWIND participants with MACE during follow-up and 845 matched non-MACE participants were analyzed for 2-year changes in 19 protein biomarkers. Two-year changes in 135 metabolites were also analyzed in 600 participants with MACE during follow-up and in 601 matched non-MACE participants. Linear and logistic regression models were used to identify proteins that were associated with both dulaglutide treatment and MACE. Similar models were used to identify metabolites that were associated with both dulaglutide treatment and MACE.

RESULTS

Compared with placebo, dulaglutide was associated with a greater reduction or lesser 2-year rise from baseline in N-terminal prohormone of brain natriuretic peptide (NT-proBNP), growth differentiation factor 15 (GDF-15), high-sensitivity C-reactive protein, and a greater 2-year rise in C-peptide. Compared with placebo, dulaglutide was also associated with a greater fall from baseline in 2-hydroxybutyric acid and a greater rise in threonine (P < 0.001). Increases from baseline in two of the proteins (but neither metabolite) were associated with MACE, including NT-proBNP (OR 1.267; 95% CI 1.119, 1.435; P < 0.001) and GDF-15 (OR 1.937; 95% CI 1.424, 2.634; P < 0.001).

CONCLUSIONS

Dulaglutide was associated with a reduced 2-year rise from baseline of NT-proBNP and GDF-15. Higher rises of these biomarkers were also associated with MACE.

The Role of Major Biomarkers of Stress in Atrial Fibrillation: A Literature Review

Numerous studies have reported that physical or emotional stress can provoke atrial fibrillation (AF) or vice versa, which suggests a potential link between exposure to external stressors and AF. This review article sought to describe in detail the relationship between major stress biomarkers and the pathogenesis of AF and presents up-to-date knowledge on the role of physiological and psychological stress in AF patients. For this purpose, this review article contends that plasma cortisol is linked to a greater risk of AF. A previous study has investigated the association between increased copeptin levels and paroxysmal AF (PAF) in rheumatic mitral stenosis and reported that copeptin concentration was not independently associated with AF duration. Reduced levels of chromogranin were measured in patients with AF. Furthermore, the dynamic activity of antioxidant enzymes, including catalase as well as superoxide dismutase, was examined in PAF patients during a period of <48 h. Malondialdehyde activity, serum high-sensitivity C-reactive protein, and high mobility group box 1 protein concentrations were significantly greater in patients with persistent AF or PAF compared to controls. Pooled data from 13 studies confirmed a significant reduction in the risk of AF related to the administration of vasopressin. Other studies have revealed the mechanism of action of heat shock proteins (HSPs) in preventing AF and also discussed the therapeutic potential of HSP-inducing compounds in clinical AF. More research is required to detect other biomarkers of stress, which have not been reported in the pathogenesis of AF. Further studies are required to identify their mechanism of action and drugs to manage these biomarkers of stress in AF patients, which might help to reduce the prevalence of AF globally.

A polygenic risk score predicts atrial fibrillation in cardiovascular disease

AIMS

Interest in targeted screening programmes for atrial fibrillation (AF) has increased, yet the role of genetics in identifying patients at highest risk of developing AF is unclear.

METHODS AND RESULTS

A total of 36,662 subjects without prior AF were analyzed from four TIMI trials. Subjects were divided into quintiles using a validated polygenic risk score (PRS) for AF. Clinical risk for AF was calculated using the CHARGE-AF model. Kaplan-Meier event rates, adjusted hazard ratios (HRs), C-indices, and net reclassification improvement were used to determine if the addition of the PRS improved prediction compared with clinical risk and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Over 2.3 years, 1018 new AF cases developed. AF PRS predicted a significant risk gradient for AF with a 40% increased risk per 1-SD increase in PRS [HR: 1.40 (1.32-1.49); P < 0.001]. Those with high AF PRS (top 20%) were more than two-fold more likely to develop AF [HR 2.45 (1.99-3.03), P < 0.001] compared with low PRS (bottom 20%). Furthermore, PRS provided an additional gradient of risk stratification on top of the CHARGE-AF clinical risk score, ranging from a 3-year incidence of 1.3% in patients with low clinical and genetic risk to 8.7% in patients with high clinical and genetic risk. The subgroup of patients with high clinical risk, high PRS, and elevated NT-proBNP had an AF risk of 16.7% over 3 years. The C-index with the CHARGE-AF clinical risk score alone was 0.65, which improved to 0.67 (P < 0.001) with the addition of NT-proBNP, and increased further to 0.70 (P < 0.001) with the addition of the PRS.

CONCLUSION

In patients with cardiovascular conditions, AF PRS is a strong independent predictor of incident AF that provides complementary predictive value when added to a validated clinical risk score and NT-proBNP.

Neuromodulation therapy for atrial fibrillation

Atrial fibrillation has a multifactorial pathophysiology influenced by cardiac autonomic innervation. Both sympathetic and parasympathetic influences are profibrillatory. Innovative therapies targeting the neurocardiac axis include catheter ablation or pharmacologic suppression of ganglionated plexi, renal sympathetic denervation, low-level vagal stimulation, and stellate ganglion blockade. To date, these therapies have variable efficacy. As our understanding of atrial fibrillation and the cardiac nervous system expands, our approach to therapeutic neuromodulation will continue evolving for the benefit of those with AF.

A Differential Profile of Biomarkers between Patients with Atrial Fibrillation and Healthy Controls

Atrial fibrillation (AF) is explained by anatomical and electrophysiological changes in the atria determined by high pressure, dilatation, infiltration and inflammation in the myocardium. There are some biomarkers implicated in these processes, namely, NT-proBNP, high sensitivity troponin (Hs-Tn), urate, galectin-3, ST2, C reactive protein and fibrinogen. The aim of this study was to assess differences in these biomarkers between patients with AF and healthy controls. We designed a cross-sectional study consecutively including all patients undergoing electrical cardioversion in our hospital for persistent AF and matched healthy controls. We included 115 patients with persistent non-valvular AF and 33 healthy subjects. The biomarkers NT-proBNP, ST2 and Hs-Tn T were significantly related to the presence of AF (1054 ± 833.30 vs. 58.31 ± 59.40, p < 0.001; 35.43 ± 15.89 vs. 27.43 ± 10.95, p < 0.001 and 10.25 ± 6.11 vs. 8.42 ± 6.85, p < 0.001, respectively). NT-proBNP was the best biomarker differentiating AF patients (area under the curve 0.995). The best NT-proBNP cut-off point to differentiate AF was 102 pg/mL; for Hs-Tn T it was 11.5 ng/L and for ST2 it was 37.7 ng/mL. It is possible that these biomarkers intervene at the onset of AF and have no role in AF maintenance.

Biomarkers associated with rhythm status after cardioversion in patients with atrial fibrillation

Biomarkers may help to improve our knowledge about the complex pathophysiology of atrial fibrillation (AF). In this study we sought to identify significant changes in biomarkers and clinical measures in patients with and without AF recurrence after electrical cardioversion. We measured 21 conventional and new biomarkers before and 30 days after electrical cardioversion and assessed the associations of changes in biomarker levels with rhythm status at follow-up. Significant between-group changes were observed for bone morphogenetic protein 10 (BMP10), N-terminal pro-B-type natriuretic peptide (NT-proBNP) and total bilirubin. Their respective changes were - 10.4%, - 62.0% and - 25.6% in patients with sinus rhythm, and 3.1%, 1.1% and - 9.4% in patients with recurrent AF, for a between-group difference of - 13.5% (95% confidence interval [CI] - 19.3% to - 7.6%; P < 0.001), - 63.1% (95% CI - 76.6% to - 49.6%; P < 0.001) and - 16.3% (95% CI - 27.9% to - 4.7%; P = 0.007). In multivariable models, the reductions of BMP10 and NT-proBNP were significantly associated with follow-up rhythm status (β coefficient per 1 - SD decrease, - 3.85; 95% CI - 6.34 to - 1.35; P = 0.003 for BMP10 and - 5.84; 95% CI - 10.22 to - 1.47; P = 0.009 for NT-proBNP. In conclusion, changes in BMP10 und NT-proBNP levels were independently associated with rhythm status after cardioversion, suggesting that these markers may be dependent on the actual heart rhythm.

Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research

The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.

Proteomics and Risk of Atrial Fibrillation in Older Adults (From the Atherosclerosis Risk in Communities [ARIC] Study)

Plasma proteomic profiling may aid in the discovery of novel biomarkers upstream of the development of atrial fibrillation (AF). We used data from the Atherosclerosis Risk in Communities study to examine the relation between large-scale proteomics and incident AF in a cohort of older-aged adults in the United States. We quantified 4,877 plasma proteins in Atherosclerosis Risk in Communities participants at visit 5 (2011-2013) using an aptamer-based proteomic profiling platform. We used Cox proportional hazards models to assess the association between protein levels and incident AF, and explored relation of selected protein biomarkers using annotated pathway analysis. Our study included 4,668 AF-free participants (mean age 75 ± 5 years; 59% female; 20% Black race) with proteomic measures. A total of 585 participants developed AF over a mean follow-up of 5.7 ± 1.7 years. After adjustment for clinical factors associated with AF, N-terminal pro-B-type natriuretic peptide (NT-proBNP) was associated with the risk of incident AF (hazard ratio, 1.82; 95% CI, 1.68 to 1.98; p, 2.91 × 10-45 per doubling of NT-proBNP). In addition, 36 other proteins were also significantly associated with incident AF after Bonferroni correction. We further adjusted for medication use and estimated glomerular filtration rate and found 17 proteins, including angiopoietin-2 and transgelin, that remained significantly associated with incident AF. Pathway analyses implicated the inhibition of matrix metalloproteases as the top canonical pathway in AF pathogenesis. In conclusion, using a large-scale proteomic platform, we identified both novel and established proteins associated with incident AF and explored mechanistic pathways of AF development.

Total NT-proBNP, a novel biomarker related to recurrent atrial fibrillation

Background

Novel circulating biomarkers may help in understanding the underlying mechanisms of atrial fibrillation (AF), a challenge for AF management and prevention of cardiovascular (CV) events. Whether glycosylation affects the prognostic value of N-terminal pro-B type natriuretic peptide (NT-proBNP) in AF is still unknown.

Objectives

To test how deglycosylated total NT-proBNP, NT-proBNP and a panel of biomarkers are associated with: (1) recurrent AF, (2) first hospitalization for CV reasons.

Methods

A total of 382 patients of the GISSI-AF trial in sinus rhythm with a history of AF, echocardiographic variables, total NT-proBNP, NT-proBNP and nine additional biomarkers [Total N-terminal pro-B type natriuretic peptide (Total NT proBNP), N-terminal pro-B type natriuretic peptide (NTproBNP), Angiopoietin 2 (Ang2), Bone morphogenic protein-10 (BMP10), Dickkopf-related protein-3 (DKK3), Endothelial cell specific molecule-1 (ESM1), Fatty acid-binding protein 3 (FABP3), Fibroblast growth factor 23 (FGF23), Growth differentiation factor-15 (GDF15), Insulin-like growth factor-binding protein-7 (IGFBP7) and Myosin binding protein C3 (MYPBC3)]. were assayed at baseline, 6 and 12 months under blind conditions in a laboratory at Roche Diagnostics, Penzberg, Germany. The associations between circulating biomarkers and AF at the 6- and 12-month visits, and their predictive value, were assessed in multivariable models with logistic regression analysis and Cox proportional hazards regression analysis. Biomarkers associations were modelled for 1SD increase in their level.

Results

Over a median follow-up of 365 days, 203/382 patients (53.1%) had at least one recurrence of AF and 16.3% were hospitalized for CV reasons. Total NT-proBNP, NT-proBNP, Ang2 and BMP10 showed the strongest associations with ongoing AF. Natriuretic peptides also predicted recurrent AF (total NT-proBNP: HR:1.19[1.04–1.36], p = 0.026; NT-proBNP: HR:1.19[1.06–1.35], p = 0.016; Ang2: HR:1.07[0.95–1.20], p = 0.283; BMP10: HR:1.09[0.96–1.25], p = 0.249) and CV hospitalization (total NT-proBNP: HR:1.57[1.29–1.90], p < 0.001 1.63], p = 0.097).

Conclusions

The association of total NT-proBNP with the risk of AF first recurrence was similar to that of NT-proBNP, suggesting no influence of glycosylation. Analogous results were obtained for the risk of first hospitalization for CV reasons. Natriuretic peptides, Ang2 and BMP10 were associated with ongoing AF. Findings from the last two biomarkers point to a pathogenic role of cardiac extracellular matrix and cardiomyocyte growth in the myocardium of the right atrium and ventricle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-02358-y.

Association Between Apelin and Atrial Fibrillation in Patients With High Risk of Ischemic Stroke

Background: Atrial fibrillation (AF) is associated with high risk of stroke preventable by timely initiation of anticoagulation. Currently available screening tools based on ECG are not optimal due to inconvenience and high costs. Aim of this study was to study the diagnostic value of apelin for AF in patients with high risk of stroke.

Methods: We designed a multicenter, matched-cohort study. The population consisted of three study groups: a healthy control group (34 patients) and two matched groups of 60 patients with high risk of stroke (AF and non-AF group). Apelin levels were examined from peripheral blood.

Results: Apelin was significantly lower in AF group compared to non-AF group (0.694 ± 0.148 vs. 0.975 ± 0.458 ng/ml, p = 0.001) and control group (0.982 ± 0.060 ng/ml, p < 0.001), respectively. Receiver operating characteristic (ROC) analysis of apelin as a predictor of AF scored area under the curve (AUC) of 0.658. Apelin's concentration of 0.969 [ng/ml] had sensitivity = 0.966 and specificity = 0.467. Logistic regression based on manual feature selection showed that only apelin and NT-proBNP were independent predictors of AF. Logistic regression based on selection from bivariate analysis showed that only apelin was an independent predictor of AF. A logistic regression model using repeated stratified K-Fold cross-validation strategy scored an AUC of 0.725 ± 0.131.

Conclusions: Our results suggest that apelin might be used to rule out AF in patients with high risk of stroke.

Pathophysiological pathways in patients with heart failure and atrial fibrillation

Aims

Atrial fibrillation (AF) and heart failure (HF) are two growing epidemics that frequently co-exist. We aimed to gain insights into the underlying pathophysiological pathways in HF patients with AF by comparing circulating biomarkers using pathway overrepresentation analyses.

Methods and results

From a panel of 92 biomarkers from different pathophysiological domains available in 1620 patients with HF, we first tested which biomarkers were dysregulated in patients with HF and AF (n = 648) compared with patients in sinus rhythm (n = 972). Secondly, pathway overrepresentation analyses were performed to identify biological pathways linked to higher plasma concentrations of biomarkers in patients who had HF and AF. Findings were validated in an independent HF cohort (n = 1219, 38% with AF). Patient with AF and HF were older, less often women, and less often had a history of coronary artery disease compared with those in sinus rhythm. In the index cohort, 24 biomarkers were up-regulated in patients with AF and HF. In the validation cohort, eight biomarkers were up-regulated, which all overlapped with the 24 biomarkers found in the index cohort. The strongest up-regulated biomarkers in patients with AF were spondin-1 (fold change 1.18, P = 1.33 × 10⁻¹²), insulin-like growth factor-binding protein-1 (fold change 1.32, P = 1.08 × 10⁻⁸), and insulin-like growth factor-binding protein-7 (fold change 1.33, P = 1.35 × 10⁻¹⁸). Pathway overrepresentation analyses revealed that the presence of AF was associated with activation amyloid-beta metabolic processes, amyloid-beta formation, and amyloid precursor protein catabolic processes with a remarkable consistency observed in the validation cohort.

Conclusion

In two independent cohorts of patients with HF, the presence of AF was associated with activation of three pathways related to amyloid-beta. These hypothesis-generating results warrant confirmation in future studies.

The role of brain natriuretic peptide in atrial fibrillation: a substudy of the Substrate Modification with Aggressive Blood Pressure Control for Atrial Fibrillation (SMAC-AF) trial

BACKGROUND

Catheter ablation is an established therapy for atrial fibrillation but is limited by recurrence; efforts have been made to identify biomarkers that predict recurrence. We investigated the effect of baseline NT-proBNP on AF recurrence following catheter ablation in patients randomized to aggressive (< 120/80 mmHg) or standard blood pressure management (< 140/90 mmHg) in the Substrate Modification with Aggressive Blood Pressure Control trial (SMAC-AF).

METHODS

The SMAC-AF study included 173 patients resistant or intolerant to at least one class I or III antiarrhythmic drug. We studied the effect of baseline NT-proBNP on the primary outcome of AF recurrence > 3 months post-ablation.

RESULTS

Of the 173 patients, 88 were randomized to the aggressive cohort, and 85 into the standard group. The primary outcome occurred in 61.4% of those in the aggressive arm, versus 61.2% in the standard arm. In the aggressive group, logNT-proBNP predicted recurrence (HR 1.28, p = 0.04, adjusted HR 1.43, p = 0.03), while in the standard cohort, it did not (HR 0.94, p = 0.62, adjusted HR 0.83, p = 0.22). NT-proBNP ≥ 280 pg/mL also predicted occurrence in the aggressive (HR 1.98, p = 0.02) but not the standard cohort (HR 1.00, p = 1.00).

CONCLUSION

We conclude that pre-ablation NT-proBNP may be useful in predicting recurrence in hypertensive patients and identifying patients who benefit from aggressive blood control and upstream therapies.

TRIAL REGISTRATION

NCT00438113, registered February 21, 2007.

New biomarkers from multiomics approaches: improving risk prediction of atrial fibrillation

Atrial fibrillation (AF) is a common cardiac arrhythmia leading to many adverse outcomes and increased mortality. Yet the molecular mechanisms underlying AF remain largely unknown. Recent advances in high-throughput technologies make large-scale molecular profiling possible. In the past decade, multiomics studies of AF have identified a number of potential biomarkers of AF. In this review, we focus on the studies of multiomics profiles with AF risk. We summarize recent advances in the discovery of novel biomarkers for AF through multiomics studies. We also discuss limitations and future directions in risk assessment and discovery of therapeutic targets for AF.

VCAM-1 as a predictor biomarker in cardiovascular disease

The vascular cellular adhesion molecule-1 (VCAM-1) is a protein that canonically participates in the adhesion and transmigration of leukocytes to the interstitium during inflammation. VCAM-1 expression, together with soluble VCAM-1 (sVCAM-1) induced by the shedding of VCAM-1 by metalloproteinases, have been proposed as biomarkers in immunological diseases, cancer, autoimmune myocarditis, and as predictors of mortality and morbidity in patients with chronic heart failure (HF), endothelial injury in patients with coronary artery disease, and arrhythmias. This revision aims to discuss the role of sVCAM-1 as a biomarker to predict the occurrence, development, and preservation of cardiovascular disease.

Large-scale screening studies for atrial fibrillation - is it worth the effort?

Atrial fibrillation (AF) is a common disease with increasing prevalence, approximately 3.2% in the adult population. In addition, about one third of AF cases are considered asymptomatic. Due to increased longevity, increased detection and increased prevalence of risk factors, the prevalence of AF is expected to at least double by the year 2060. Patients with AF have an increased risk for ischaemic stroke, heart failure, death and cognitive decline. Treatment with oral anticoagulation reduces the risk of ischaemic stroke and mortality, and the effect on cognitive decline is being studied. Based on the increasing prevalence of AF, its often asymptomatic and paroxysmal presentation and the efficacy of oral anticoagulation treatment, screening for AF has been proposed. AF seems to fulfil most of the Wilson-Jungner criteria for screening issued by the World Health Organization, but some knowledge gaps remain, gaps that will be addressed by several ongoing studies. The knowledge gaps in AF screening consist of the magnitude of the net benefit or net harm inflicted by AF screening because the oral anticoagulation treatment will also increase the risk of bleeding, and the psychological effects of AF screening are not very well studied. So far, the AF screening recommendations issued by the European Society of Cardiology have had limited impact on national and regional AF screening activities. Several large-scale AF screening studies will report results on hard endpoints within the next few years, and these results will hopefully manifest AF as a cardiovascular disease which we need to pay more attention to.

Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease

Background

Atrial fibrillation (AF) is the most common arrhythmia with poorly understood mechanisms. We aimed to investigate the biological mechanism of AF and to discover feature genes by analyzing multi-omics data and by applying a machine learning approach.

Methods

At the transcriptomic level, four microarray datasets (GSE41177, GSE79768, GSE115574, GSE14975) were downloaded from the Gene Expression Omnibus database, which included 130 available atrial samples from AF and sinus rhythm (SR) patients with valvular heart disease. Microarray meta-analysis was adopted to identified differentially expressed genes (DEGs). At the proteomic level, a qualitative and quantitative analysis of proteomics in the left atrial appendage of 18 patients (9 with AF and 9 with SR) who underwent cardiac valvular surgery was conducted. The machine learning correlation-based feature selection (CFS) method was introduced to selected feature genes of AF using the training set of 130 samples involved in the microarray meta-analysis. The Naive Bayes (NB) based classifier constructed using training set was evaluated on an independent validation test set GSE2240.

Results

863 DEGs with FDR < 0.05 and 482 differentially expressed proteins (DEPs) with FDR < 0.1 and fold change > 1.2 were obtained from the transcriptomic and proteomic study, respectively. The DEGs and DEPs were then analyzed together which identified 30 biomarkers with consistent trends. Further, 10 features, including 8 upregulated genes (CD44, CHGB, FHL2, GGT5, IGFBP2, NRAP, SEPTIN6, YWHAQ) and 2 downregulated genes (TNNI1, TRDN) were selected from the 30 biomarkers through machine learning CFS method using training set. The NB based classifier constructed using the training set accurately and reliably classify AF from SR samples in the validation test set with a precision of 87.5% and AUC of 0.995.

Conclusion

Taken together, our present work might provide novel insights into the molecular mechanism and provide some promising diagnostic and therapeutic targets of AF.

Atrial fibrillation rhythm is associated with marked changes in metabolic and myofibrillar protein expression in left atrial appendage

Atrial fibrillation (AF) is strongly associated with risk of stroke and heart failure. AF promotes atrial remodeling that increases risk of stroke due to left atrial thrombogenesis, and increases energy demand to support high rate electrical activity and muscle contraction. While many transcriptomic studies have assessed AF-related changes in mRNA abundance, fewer studies have assessed proteomic changes. We performed a proteomic analysis on left atrial appendage (LAA) tissues from 12 patients with a history of AF undergoing elective surgery; atrial rhythm was documented at time of surgery. Proteomic analysis was performed using liquid chromatography with mass spectrometry (LC/MS-MS). Data-dependent analysis identified 3090 unique proteins, with 408 differentially expressed between sinus rhythm and AF. Ingenuity Pathway Analysis of differentially expressed proteins identified mitochondrial dysfunction, oxidative phosphorylation, and sirtuin signaling among the most affected pathways. Increased abundance of electron transport chain (ETC) proteins in AF was accompanied by decreased expression of ETC complex assembly factors, tricarboxylic acid cycle proteins, and other key metabolic modulators. Discordant changes were also evident in the contractile unit with both up and downregulation of key components. Similar pathways were affected in a comparison of patients with a history of persistent vs. paroxysmal AF, presenting for surgery in sinus rhythm. Together, these data suggest that while the LAA attempts to meet the energetic demands of AF, an uncoordinated response may reduce ATP availability, contribute to tissue contractile and electrophysiologic heterogeneity, and promote a progression of AF from paroxysmal episodes to development of a substrate amenable to persistent arrhythmia.