B-type natriuretic peptide and C-reactive protein in the prediction of atrial fibrillation risk: the CHARGE-AF Consortium of community-based cohort studies

Innovative approaches to atrial fibrillation prediction: should polygenic scores and machine learning be implemented in clinical practice?

Atrial fibrillation (AF) prediction and screening are of important clinical interest because of the potential to prevent serious adverse events. Devices capable of detecting short episodes of arrhythmia are now widely available. Although it has recently been suggested that some high-risk patients with AF detected on implantable devices may benefit from anticoagulation, long-term management remains challenging in lower-risk patients and in those with AF detected on monitors or wearable devices as the development of clinically meaningful arrhythmia burden in this group remains unknown. Identification and prediction of clinically relevant AF is therefore of unprecedented importance to the cardiologic community. Family history and underlying genetic markers are important risk factors for AF. Recent studies suggest a good predictive ability of polygenic risk scores, with a possible additive value to clinical AF prediction scores. Artificial intelligence, enabled by the exponentially increasing computing power and digital data sets, has gained traction in the past decade and is of increasing interest in AF prediction using a single or multiple lead sinus rhythm electrocardiogram. Integrating these novel approaches could help predict AF substrate severity, thereby potentially improving the effectiveness of AF screening and personalizing the management of patients presenting with conditions such as embolic stroke of undetermined source or subclinical AF. This review presents current evidence surrounding deep learning and polygenic risk scores in the prediction of incident AF and provides a futuristic outlook on possible ways of implementing these modalities into clinical practice, while considering current limitations and required areas of improvement.

AI-enabled left atrial volumetry in coronary artery calcium scans (AI-CACTM) predicts atrial fibrillation as early as one year, improves CHARGE-AF, and outperforms NT-proBNP: The multi-ethnic study of atherosclerosis

BACKGROUND

Coronary artery calcium (CAC) scans contain actionable information beyond CAC scores that is not currently reported.

METHODS

We have applied artificial intelligence-enabled automated cardiac chambers volumetry to CAC scans (AI-CACTM) to 5535 asymptomatic individuals (52.2% women, ages 45-84) that were previously obtained for CAC scoring in the baseline examination (2000-2002) of the Multi-Ethnic Study of Atherosclerosis (MESA). AI-CAC took on average 21 ​s per CAC scan. We used the 5-year outcomes data for incident atrial fibrillation (AF) and assessed discrimination using the time-dependent area under the curve (AUC) of AI-CAC LA volume with known predictors of AF, the CHARGE-AF Risk Score and NT-proBNP. The mean follow-up time to an AF event was 2.9 ​± ​1.4 years.

RESULTS

At 1,2,3,4, and 5 years follow-up 36, 77, 123, 182, and 236 cases of AF were identified, respectively. The AUC for AI-CAC LA volume was significantly higher than CHARGE-AF for Years 1, 2, and 3 (0.83 vs. 0.74, 0.84 vs. 0.80, and 0.81 vs. 0.78, respectively, all p ​< ​0.05), but similar for Years 4 and 5, and significantly higher than NT-proBNP at Years 1-5 (all p ​< ​0.01), but not for combined CHARGE-AF and NT-proBNP at any year. AI-CAC LA significantly improved the continuous Net Reclassification Index for prediction of AF over years 1-5 when added to CHARGE-AF Risk Score (0.60, 0.28, 0.32, 0.19, 0.24), and NT-proBNP (0.68, 0.44, 0.42, 0.30, 0.37) (all p ​< ​0.01).

CONCLUSION

AI-CAC LA volume enabled prediction of AF as early as one year and significantly improved on risk classification of CHARGE-AF Risk Score and NT-proBNP.

Effect of an Intensive Lifestyle Intervention on Circulating Biomarkers of Atrial Fibrillation-Related Pathways among Adults with Metabolic Syndrome: Results from a Randomized Trial

Background: Lifestyles influence atrial fibrillation (AF) risk. Determining the effect of lifestyle interventions on blood concentrations of biomarkers of AF-related pathways could help understand AF pathophysiology and contribute to AF prevention. Methods: We studied 532 participants enrolled in the PREDIMED-Plus trial, a Spanish randomized trial conducted in adults (55-75 years) with metabolic syndrome and body mass index between 27-40 kg/m2. Eligible participants were randomized 1:1 to an intensive lifestyle intervention, emphasizing physical activity, weight loss, and adherence to an energy-reduced Mediterranean diet or to a control group. Serum biomarkers [carboxy-terminal propeptide of procollagen type I (PICP), high-sensitivity troponin T (hsTnT), high-sensitivity C reactive protein (hsCRP), 3-nitrotyrosine (3-NT), and N-terminal propeptide of B-type natriuretic peptide (NT-proBNP)] were measured at baseline, 3 and 5 years after randomization. Mixed models were used to evaluate the effect of intervention on changes in biomarkers through year 5. Mediation analysis was performed to examine the proportion mediated by each component of the intervention. Results: At baseline, participants' mean age was 65, 40% were female, and 50% were assigned to the intervention. After five years, mean changes in log-transformed biomarkers were -0.01 (PICP), 0.20 (hsTnT), -0.17 (hsCRP), 0.12 (3-NT), and 0.27 (NT-proBNP). Compared to the control group, participants in the intervention group experienced greater decreases in hsCRP (-14%, 95% confidence interval (CI) -26%, 0%) or smaller increases in 3-NT (-16%, 95% CI -25%, -5%) and NT-proBNP (-12%, 95% CI -23%, 1%). The intervention had minimal impact on hsTnT (-3%, 95% CI -7%, 2%) or PICP concentrations (-2%, 95% CI -9%, 6%). The effect of the intervention on hsCRP was primarily mediated by weight loss (89% at year 5). Conclusions: Over five years, a dietary and lifestyle intervention for weight-loss favorably affected concentrations of hsCRP, 3-NT, and NT-proBNP, pointing to specific mechanisms in pathways linking lifestyles and AF.

Assessing the association between triglyceride-glucose index and atrial fibrillation: a systematic review and meta-analysis

BACKGROUND

An essential relationship between insulin resistance (IR) and atrial fibrillation (AF) has been demonstrated. Among the methods used to assess IR, the triglyceride-glucose (TyG) index is the more straightforward, dimensionless, and low-cost tool. However, the possible usage of this index in clinical practice to predict and diagnose AF has yet to be determined and consolidated.

OBJECTIVE AND RATIONALE

Herein, we performed a systematic review and meta-analysis to assess the association between the TyG index and AF.

METHODS

Databases (PubMed, Embase, Scopus, and Web of Science) were systematically searched for studies evaluating the TyG index in AF. The inclusion criteria were observational studies investigating AF and TyG index correlation in individuals older than 18 years, while preclinical studies and those without the relevant data were excluded. Random effect meta-analyses comparing TyG levels between AF and non-AF cases, AF recurrence after radiofrequency ablation, and post-procedural AF were performed using standardized mean differences (SMD) with their matching 95% confidence intervals (CIs).

RESULTS

Our screening identified nine studies to be analyzed, including 6,171 participants including 886 with AF. The meta-analysis demonstrated that the TyG index resulted higher in patients with AF than non-AF counterparts (SMD 1.23, 95% CI 0.71 to 1.75, I2 98%, P < 0.001). Subgroup analysis showed the same results for post-procedure AF (SMD 0.99, 95% CI 0.78 to 1.20, I2 10%, P < 0.001) and post-ablation AF (SMD 1.25, 95% CI 1.07 to 1.43, I2 46%, P < 0.001), while no difference was found in population-based cohorts (SMD 1.45, 95% CI - 0.41 to 3.31, I2 100%, P = 0.13). Publication year (P = 0.036) and sample size (P = 0.003) showed significant associations with the effect size, using multivariable meta-regression.

CONCLUSION

The TyG index is an easy-to-measure surrogate marker of IR in patients with AF. Further clinical studies are warranted to demonstrate its ability for routine clinical use and as a screening tool.

AI-enabled Left Atrial Volumetry in Cardiac CT Scans Improves CHARGE-AF and Outperforms NT-ProBNP for Prediction of Atrial Fibrillation in Asymptomatic Individuals: Multi-Ethnic Study of Atherosclerosis

Background

Coronary artery calcium (CAC) scans contain actionable information beyond CAC scores that is not currently reported.

Methods

We have applied artificial intelligence-enabled automated cardiac chambers volumetry to CAC scans (AI-CAC), taking on average 21 seconds per CAC scan, to 5535 asymptomatic individuals (52.2% women, ages 45-84) that were previously obtained for CAC scoring in the baseline examination (2000-2002) of the Multi-Ethnic Study of Atherosclerosis (MESA). We used the 5-year outcomes data for incident atrial fibrillation (AF) and compared the time-dependent AUC of AI-CAC LA volume with known predictors of AF, the CHARGE-AF Risk Score and NT-proBNP (BNP). The mean follow-up time to an AF event was 2.9±1.4 years.

Results

At 1,2,3,4, and 5 years follow-up 36, 77, 123, 182, and 236 cases of AF were identified, respectively. The AUC for AI-CAC LA volume was significantly higher than CHARGE-AF or BNP at year 1 (0.836, 0.742, 0.742), year 2 (0.842, 0.807,0.772), and year 3 (0.811, 0.785, 0.745) (p<0.02), but similar for year 4 (0.785, 0.769, 0.725) and year 5 (0.781, 0.767, 0.734) respectively (p>0.05). AI-CAC LA volume significantly improved the continuous Net Reclassification Index for prediction of AF over years 1-5 when added to CAC score (0.74, 0.49, 0.53, 0.39, 0.44), CHARGE-AF Risk Score (0.60, 0.28, 0.32, 0.19, 0.24), and BNP (0.68, 0.44, 0.42, 0.30, 0.37) respectively (p<0.01).

Conclusion

AI-CAC LA volume enabled prediction of AF as early as one year and significantly improved on risk classification of CHARGE-AF Risk Score and BNP.

2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation.

METHODS

A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate.

STRUCTURE

Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.

2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Patients With Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation.

METHODS

A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate.

STRUCTURE

Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.

Mendelian randomization provides evidence for a causal effect of serum insulin-like growth factor family concentration on risk of atrial fibrillation

BACKGROUND

Atrial fibrillation (AF) is one of the most common persistent arrhythmias among adult cardiovascular diseases. It is important to identify potential risk factors for AF. Members of the insulin-like growth factor (IGF) family exert a variety of effects on various cell types in the context of the pathogenesis of cardiovascular diseases, and previous population-based studies indicate associations between IGF family members and AF. However, the causal effects of IGF family members in AF have not been evaluated.

AIM

In the current study two-sample Mendelian Randomization (MR) was used to assess genetic relationships between IGF family members and AF.

METHODS

MR was performed based on genome-wide association study (GWAS) datasets, and concentration levels of 14 IGF family members were retrieved. An initial MR analysis was conducted to identify single nucleotide polymorphisms potentially associated with IGF serum concentrations. A GWAS meta-analysis including 60620 AF cases and 970216 control participants of European ancestry was then conducted to identify AF causal effects. Two-sample MR packages were used to perform MR analysis in R. MR-Egger, weighted median (WM), and inverse variance weighted (IVW) methods were used.

RESULTS

In two-sample MR assessments there were lower levels of circulating IGF binding protein 3 in both WM [odds ratio (OR) 0.964, 95% confidence interval (CI) 0.940-0.960, P = 0.006] and IVW (OR 0.968, 95%CI: 0.947-0.987, P = 0.001) analyses. Higher serum levels of IGF2 receptor were associated with AF (OR 1.045, 95%CI: 1.016-1.076, P = 0.039). In reverse MR analysis conducted to investigate casual effects, elevated levels of circulating CYR61 were associated with AF (OR 1.060, 95%CI: 1.005-1.119, P = 0.031).

CONCLUSION

The results of the present study provide novel insights into the pathogenesis of AF, and the implications of serum IGF family member concentrations when assessing the risk of AF. The study generated evidence on the potential roles of developmental pathological effects in the pathogenesis of AF. Further observational and experimental studies are critically needed.

Association of alcohol consumption with circulating biomarkers of atrial fibrillation-related pathways in a population at high cardiometabolic risk

Background

The effect of alcohol consumption on cardiovascular health, including atrial fibrillation risk, remains controversial. Evaluating the association of alcohol consumption with circulating atrial fibrillation-related biomarkers may help better understand the relevant mechanistic underpinnings.

Methods

We studied 523 participants from 3 sites for the PREDIMED-Plus study, a weight-loss randomized intervention trial in metabolically unhealthy adults. N-terminal pro-B-type natriuretic protein (NTproBNP), high sensitivity troponin-T (hsTnT), high-sensitivity C-reactive protein (hsCRP), 3-nitrotyrosine (3-NT), and procollagen type 1 carboxy-terminal propeptide (PICP) were measured in fasting serum samples at baseline and years 3 and 5 of follow-up. We calculated alcohol consumption in drinks/day (1 drink = 14 grams alcohol) with validated food frequency questionnaires at each visit. Using multiple linear regression and mixed models we estimated the association of alcohol consumption with log-transformed biomarkers at baseline and longitudinally adjusting for potential confounders.

Results

Among 523 participants (mean age: 65 years, 40% female), mean alcohol consumption was 1 drink/day. Cross-sectionally, alcohol consumption was not associated with cardiac biomarker concentrations. Longitudinally, compared to non-consumers, heavy drinkers (≥4 drinks/day) had smaller increases in hsTnT (β: -0.11, 95%CI: -0.20, -0.01)and PICP (β: -0.15, 95%CI: -0.30, 0.01) over the 5-year follow-up. In contrast, those who increased alcohol consumption over the 5-year period experienced greater increases in hsCRP (β: 0.42, 95%CI: 0.11, 0.73) compared to those whose drinking behavior stayed the same.

Conclusion

Alcohol consumption was associated with complex changes in circulating biomarkers, including comparatively lower fibrotic and myocardial damage, but higher levels of overall inflammation over time. These results underscore the need for further research to better understand the effects of alcohol on cardiovascular health.

Relationship of atrial fibrillation and N terminal pro brain natriuretic peptide in heart failure patients

N terminal pro brain natriuretic peptide (NT-proBNP) plays an important role in the diagnosis and prognosis of heart failure (HF). The plasma level of NT-proBNP in atrial fibrillation (AF) patients was higher than of sinus rhythm patients. In HF, NT-proBNP levels are affected by the concomitant presence of AF, making it difficult to distinguish between HF and AF in patients with elevated NT-proBNP. Several other diseases, such as renal failure and pulmonary embolism, are known to further increase NT-proBNP levels in patients with concomitant HF. Therefore, NT-proBNP is a sensitive but non-specific marker for the detection of HF. AF is very important in this regard because among patients with HF regardless of ejection fraction, symptoms such as shortness of breath and atrial enlargement develop and can mimic HF. In the present study, we investigated whether the prognostic value of natriuretic peptides in HF holds true for patients with concomitant AF.

A proteomic analysis of atrial fibrillation in a prospective longitudinal cohort (AGES-Reykjavik study)

AIMS

Atrial fibrillation (AF) is associated with high risk of comorbidities and mortality. Our aim was to examine causal and predictive relationships between 4137 serum proteins and incident AF in the prospective population-based Age, Gene/Environment Susceptibility-Reykjavik (AGES-Reykjavik) study.

METHODS AND RESULTS

The study included 4765 participants, of whom 1172 developed AF. Cox proportional hazards regression models were fitted for 4137 baseline protein measurements adjusting for known risk factors. Protein associations were tested for replication in the Cardiovascular Health Study (CHS). Causal relationships were examined in a bidirectional, two-sample Mendelian randomization analysis. The time-dependent area under the receiver operating characteristic curve (AUC)-statistic was examined as protein levels and an AF-polygenic risk score (PRS) were added to clinical risk models. The proteomic signature of incident AF consisted of 76 proteins, of which 63 (83%) were novel and 29 (38%) were replicated in CHS. The signature included both N-terminal prohormone of brain natriuretic peptide (NT-proBNP)-dependent (e.g. CHST15, ATP1B1, and SVEP1) and independent components (e.g. ASPN, AKR1B, and LAMA1/LAMB1/LAMC1). Nine causal candidates were identified (TAGLN, WARS, CHST15, CHMP3, COL15A1, DUSP13, MANBA, QSOX2, and SRL). The reverse causal analysis suggested that most AF-associated proteins were affected by the genetic liability to AF. N-terminal prohormone of brain natriuretic peptide improved the prediction of incident AF events close to baseline with further improvements gained by the AF-PRS at all time points.

CONCLUSION

The AF proteomic signature includes biologically relevant proteins, some of which may be causal. It mainly reflects an NT-proBNP-dependent consequence of the genetic liability to AF. N-terminal prohormone of brain natriuretic peptide is a promising marker for incident AF in the short term, but risk assessment incorporating a PRS may improve long-term risk assessment.

Predictors of Low Voltage Zone and Sex Differences in Low Voltage Zone Distribution in Patients with Atrial Fibrillation

Background

Previous studies have revealed the left atrial (LA) low voltage zone (LVZ) are tightly linked to the recurrence of atrial fibrillation (AF). Furthermore ablation that targets the LA LVZ can improve patient prognosis. The aim of this study was to identify potential clinical predictors of the LA LVZ, to investigate possible sex differences in the distribution of LA LVZ, and to examine the relationship between LA LVZ and AF recurrence.

Methods

A total of 108 patients who underwent AF catheter ablation and LA high-density electro-anatomic mapping were enrolled in the study. Of these, 56 patients with LA LVZ ≥ 5% were assigned to the LVZ group, while the remaining 52 patients with LA LVZ < 5% were assigned to the non-LVZ group. Clinical characteristics and laboratory results for all patients were collected and compared between the two groups.

Results

Multivariate logistic regression analysis revealed that persistent AF (odds ratio [OR] = 4.563, 95% confidence interval [CI]: 1.194-17.431, p = 0.026), left atrial volume (LAV, OR = 1.030, 95% CI: 1.001-1.061, p = 0.044) and brain natriuretic peptide (BNP, OR = 1.010, 95% CI: 1.002-1.019, p = 0.015) were independent predictors for the presence of LA LVZ. In addition, female sex (OR = 7.161, 95% CI: 1.518-33.792, p = 0.013), LAV (OR = 1.028, 95% CI: 1.002-1.055, p = 0.035) and BNP (OR = 1.009, 95% CI: 1.001-1.016, p = 0.018) were independent predictors of severe LA LVZ (LA LVZ > 20%). The extent of LVZ was significantly greater in females than in males (32.8% ± 15.5% vs. 23.5% ± 12.7%, p = 0.021), especially in the anterior (34.5% ± 16.7% vs. 20.0% ± 16.4%, p = 0.003) and septal (44.9% ± 17.1% vs. 29.0% ± 18.9%, p = 0.004) walls. During follow-up, AF recurrence was significantly higher in patients with LA LVZ than in those without LA LVZ (31.3% vs. 12.8%, respectively, p = 0.023).

Conclusions

In this study cohort, persistent AF, LAV and BNP were independent predictors of LA LVZ. Furthermore, female sex, LAV and BNP were independent predictors of severe LA LVZ. Females had a significantly greater extent of LVZ than males, especially in the anterior and septal walls. Patients with LA LVZ had a higher risk of recurrent AF.

Effect of an intensive lifestyle intervention on circulating biomarkers of atrial fibrillation-related pathways among adults with metabolic syndrome

Background Lifestyles influence atrial fibrillation (AF) risk. Blood biomarkers can characterize the atrial substrate that facilitates the development of AF. Therefore, determining the effect of lifestyle interventions on blood concentrations of biomarkers of AF-related pathways could help understand AF pathophysiology and contribute to AF prevention. Methods We studied 471 participants enrolled in the PREDIMED-Plus trial, a Spanish randomized trial conducted in adults (55-75 years) with metabolic syndrome and body mass index between 27-40 kg/m2. Eligible participants were randomized 1:1 to an intensive lifestyle intervention, emphasizing physical activity, weight loss, and adherence to an energy-reduced Mediterranean diet or to a control group. Serum biomarkers [carboxy-terminal propeptide of procollagen type I (PICP), high-sensitivity troponin T (hsTnT), high-sensitivity C reactive protein (hsCRP), 3-nitrotyrosine (3-NT), and N-terminal propeptide of B-type natriuretic peptide (NT-proBNP)] were measured at baseline, 3 and 5 years after randomization. Mixed models were used to evaluate the effect of intervention on changes in biomarkers through year 5. Mediation analysis was performed to examine the proportion mediated by each component of the intervention. Results At baseline, participants' mean age was 65, 41% were female, and 50% were assigned to the intervention. After five years, mean changes in log-transformed biomarkers were -0.03 (PICP), 0.19 (hsTnT), -0.15 (hsCRP), 0.12 (3-NT), and 0.30 (NT-proBNP). Compared to the control group, participants in the intervention group experienced greater decreases in hsCRP (-16%, 95% confidence interval (CI) -28%, -1%) or smaller increases in 3-NT (-15%, 95% CI -25%, -4%) and NT-proBNP (-13%, 95% CI -25%, 0%). The intervention had minimal impact on hsTnT (-3%, 95% CI -8%, 2%) or PICP concentrations (-0%, 95% CI -9%, 9%). The effect of the intervention on hsCRP was primarily mediated by weight loss (73% and 66% at years 3 and 5). Conclusion Over five years, a dietary and lifestyle intervention for weight-loss favorably affected concentrations of hsCRP, 3-NT, and NT-proBNP, pointing to specific mechanisms in pathways linking lifestyles and AF.

Associations of risk factor burden and genetic predisposition with the 10-year risk of atrial fibrillation: observations from a large prospective study of 348,904 participants

BACKGROUND

Understanding the effects of risk factor burden and genetic predisposition on the long-term risk of atrial fibrillation (AF) is important to improve public health initiatives. However, the 10-year risk of AF considering risk factor burden and genetic predisposition is unknown.

METHODS

A total of 348,904 genetically unrelated participants without AF at baseline from the UK were categorized into three groups: index ages 45 years (n = 84,206), 55 years (n=117,520), and 65 years (n=147,178). Optimal, borderline, or elevated risk factor burden was determined by body mass index, blood pressure, diabetes mellitus, alcohol consumption, smoking status, and history of myocardial infarction or heart failure. Genetic predisposition was estimated using the polygenic risk score (PRS), constructed using 165 predefined genetic risk variants. The combined effects of risk factor burden and PRS on the risk of incident AF in 10 years were estimated for each index age. Fine and Gray models were developed to predict the 10-year risk of AF.

RESULTS

The overall 10-year risk of AF was 0.67% (95% CI: 0.61-0.73%) for index age 45 years, 2.05% (95% CI: 1.96-2.13%) for index age 55 years, and 6.34% (95% CI: 6.21-6.46%) for index age 65 years, respectively. An optimal risk factor burden was associated with later AF onset regardless of genetic predisposition and sex (P < 0.001). Significant synergistic interactions were observed for risk factor burden with PRS at each index age (P < 0.05). Participants with an elevated risk factor burden and high PRS had the highest 10-year risk of AF in reference to those who had both an optimal risk factor burden and a low PRS. At younger ages, optimal risk burden and high PRS might also lead to later onset of AF, compared to the joint effect of elevated risk burden and low/intermediate PRS.

CONCLUSIONS

Risk factor burden together with a genetic predisposition is associated with the 10-year risk of AF. Our results may be helpful in selecting high-risk individuals for primary prevention of AF and facilitating subsequent health interventions.

Inflammatory proteomics profiling for prediction of incident atrial fibrillation

OBJECTIVE

Atrial fibrillation (AF) has emerged as a common condition in older adults. Cardiovascular risk factors only explain about 50% of AF cases. Inflammatory biomarkers may help close this gap as inflammation can alter atrial electrophysiology and structure. This study aimed to determine a cytokine biomarker profile for this condition in the community using a proteomics approach.

METHODS

This study uses cytokine proteomics in participants of the Finnish population-based FINRISK cohort studies 1997/2002. Risk models for 46 cytokines were developed to predict incident AF using Cox regressions. Furthermore, the association of participants' C reactive protein (CRP) and N-terminal pro B-type natriuretic peptide (NT-proBNP) concentrations with incident AF was examined.

RESULTS

In 10 744 participants (mean age of 50.9 years, 51.3% women), 1246 cases of incident AF were observed (40.5% women). The main analyses, adjusted for participants' sex and age, suggested that higher concentrations of macrophage inflammatory protein-1β (HR=1.11; 95% CI 1.04, 1.17), hepatocyte growth factor (HR=1.12; 95% CI 1.05, 1.19), CRP (HR=1.17; 95% CI 1.10, 1.24) and NT-proBNP (HR=1.58; 95% CI 1.45, 1.71) were associated with increased risk of incident AF. In further clinical variable-adjusted models, only NT-proBNP remained statistically significant.

CONCLUSION

Our study confirmed NT-proBNP as a strong predictor for AF. Observed associations of circulating inflammatory cytokines were primarily explained by clinical risk factors and did not improve risk prediction. The potential mechanistic role of inflammatory cytokines measured in a proteomics approach remains to be further elucidated.

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.

Risk prediction of atrial fibrillation and its complications in the community using hs troponin I

AIMS

Atrial fibrillation (AF) is becoming increasingly common. Traditional cardiovascular risk factors (CVRF) do not explain all AF cases. Blood-based biomarkers reflecting cardiac injury such as high-sensitivity troponin I (hsTnI) may help close this gap.

METHODS

We investigated the predictive ability of hsTnI for incident AF in 45,298 participants (median age 51.4 years, 45.0% men) across European community cohorts in comparison to CVRF and established biomarkers (C-reactive protein, N-terminal pro B-type natriuretic peptide).

RESULTS

During a median follow-up of 7.7 years, 1734 (3.8%) participants developed AF. Those in the highest hsTnI quarter (≥4.2 ng/L) had a 3.91-fold (95% confidence interval (CI) 3.30, 4.63; p < .01) risk for developing AF compared to the lowest quarter (<1.4 ng/L). In multivariable-adjusted Cox proportional hazards models a statistically significant association was seen between hsTnI and AF (hazard ratio (HR) per 1 standard deviation (SD) increase in log10(hsTnI) 1.08; 95% CI 1.01, 1.16; p = .03). Inclusion of hsTnI did improve model discrimination (C-index CVRF 0.811 vs. C-index CVRF and hsTnI 0.813; p < .01). Higher hsTnI concentrations were associated with heart failure (HR per SD 1.37; 95% CI 1.12, 1.68; p < .01) and overall mortality (HR per SD 1.24; 95% CI 1.09, 1.41; p < .01).

CONCLUSION

hsTnI as a biomarker of myocardial injury does not improve prediction of AF incidence beyond classical CVRF and NT-proBNP. However, it is associated with the AF-related disease heart failure and mortality likely reflecting underlying subclinical cardiovascular impairment.

Exploring the incremental utility of circulating biomarkers for robust risk prediction of incident atrial fibrillation in European cohorts using regressions and modern machine learning methods

AIMS

To identify robust circulating predictors for incident atrial fibrillation (AF) using classical regressions and machine learning (ML) techniques within a broad spectrum of candidate variables.

METHODS AND RESULTS

In pooled European community cohorts (n = 42 280 individuals), 14 routinely available biomarkers mirroring distinct pathophysiological pathways including lipids, inflammation, renal, and myocardium-specific markers (N-terminal pro B-type natriuretic peptide [NT-proBNP], high-sensitivity troponin I [hsTnI]) were examined in relation to incident AF using Cox regressions and distinct ML methods. Of 42 280 individuals (21 843 women [51.7%]; median [interquartile range, IQR] age, 52.2 [42.7, 62.0] years), 1496 (3.5%) developed AF during a median follow-up time of 5.7 years. In multivariable-adjusted Cox-regression analysis, NT-proBNP was the strongest circulating predictor of incident AF [hazard ratio (HR) per standard deviation (SD), 1.93 (95% CI, 1.82-2.04); P < 0.001]. Further, hsTnI [HR per SD, 1.18 (95% CI, 1.13-1.22); P < 0.001], cystatin C [HR per SD, 1.16 (95% CI, 1.10-1.23); P < 0.001], and C-reactive protein [HR per SD, 1.08 (95% CI, 1.02-1.14); P = 0.012] correlated positively with incident AF. Applying various ML techniques, a high inter-method consistency of selected candidate variables was observed. NT-proBNP was identified as the blood-based marker with the highest predictive value for incident AF. Relevant clinical predictors were age, the use of antihypertensive medication, and body mass index.

CONCLUSION

Using different variable selection procedures including ML methods, NT-proBNP consistently remained the strongest blood-based predictor of incident AF and ranked before classical cardiovascular risk factors. The clinical benefit of these findings for identifying at-risk individuals for targeted AF screening needs to be elucidated and tested prospectively.

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.

Predicting Atrial Fibrillation after Ischemic Stroke: Clinical, Genetics, and Electrocardiogram Modelling

INTRODUCTION

Detection of atrial fibrillation (AF) is challenging in patients after ischaemic stroke due to its paroxysmal nature. We aimed to determine the utility of a combined clinical, electrocardiographic, and genetic variable model to predict AF in a post-stroke population.

MATERIALS AND METHODS

We performed a cohort study at a single comprehensive stroke centre from November 09, 2009, to October 31, 2017. All patients recruited were diagnosed with acute ischaemic stroke or transient ischaemic attacks. Electrocardiographic variables including p-wave terminal force (PWTF), corrected QT interval (QTc), and genetic variables including single nucleotide polymorphisms (SNPs) at the 4q25 (rs2200733) were evaluated. Clinical, electrocardiographic and genetic variables of patients without AF and those who developed AF were compared. Multiple logistic regression analysis and receiver operating characteristics were performed to identify parameters and determine their ability to predict the occurrence of AF.

RESULTS

Out of 709 patients (median age of 59 years, inter-quartile range 52-67) recruited, sixty (8.5%) were found to develop AF on follow-up. Age (odds ratio [OR]): 3.49, 95% confidence interval [CI]: 2.03-5.98, p < 0.0001), hypertension (OR: 2.76, 95% CI: 1.36-5.63, p = 0.0052), and valvular heart disease (OR: 8.49, 95% CI: 2.62-27.6, p < 0.004) were the strongest predictors of AF, with an area under receiver operating value of 0.76 (95% CI: 0.70-0.82), and 0.82 (95% CI: 0.77-0.87) when electrocardiographic variables (PWTF and QTc) were added. SNP did not improve prediction modelling.

CONCLUSION

We demonstrated that a model combining clinical and electrocardiographic variables provided robust prediction of AF in our post-stroke population. Role of SNP in prediction of AF was limited.

Atrial Fibrillation, thromboembolic risk, and the potential role of the natriuretic peptides, a focus on BNP and NT-proBNP - A narrative review

Atrial fibrillation (AF) is one of the most commonly encountered arrythmia in clinical practice. AF itself can be driven by genetic predisposition, ectopic electrical activity, and abnormal atrial tissue substrates. Often there is no single etiological mechanism, but rather a combination of factors that feed back to remodel and worsen tissue substrate, "AF begets AF". The clinical consequences of AF can often include emboli, heart failure, and early mortality. The classical AF cardioembolic (CE) concept requires thrombus formation in the left atrial appendage, with subsequent embolization. The temporal dissociation between AF occurrence and CE events has thrown doubt on AF as the driver of this mechanism. Instead, there has been a resurgence of the "atrial cardiomyopathy" (ACM) concept. An ACM is proposed as a potential mechanism of embolic disease through promotion of prothrombotic mechanisms, with AF instead reflecting atrial disease severity. Regardless, AF has been implicated in 25% to 30% of cryptogenic strokes. Natriuretic peptide(NP)s have been shown to be elevated in AF, with higher levels of both NT-proBNP and BNP being predictive of incidental AF. NPs potentially reflect the atrial environment and could be used to identify an underlying ACM. Therefore, this narrative review examines this evidence and mechanisms that may underpin the role of NPs in identifying atrial dysfunction, with focus on both, BNP and NTproBNP. We explore their potential role in the prediction and screening for both, ACM and AF. Moreover, we compare both NPs directly to ascertain a superior biomarker.

Growth Differentiation Factor 15 and the Subsequent Risk of Atrial Fibrillation: The Atherosclerosis Risk in Communities Study

BACKGROUND

Growth differentiation factor 15 (GDF-15) is a stress-responsive biomarker associated with several types of cardiovascular diseases. However, conflicting results have been reported regarding its association with incident atrial fibrillation (AF) in the general population.

METHODS

In 10 234 White and Black Atherosclerosis Risk in Communities (ARIC) Study participants (mean age 60 years, 20.5% Blacks) free of AF at baseline (1993 to 1995), we quantified the association of GDF-15 with incident AF using Cox regression models. GDF-15 concentration was measured by an aptamer-based proteomic method. AF was defined as AF diagnosis by electrocardiogram at subsequent ARIC visits or AF diagnosis in hospitalization records or death certificates. Harrell's c-statistic and categorical net reclassification improvement were computed for risk discrimination and reclassification.

RESULTS

There were 2217 cases of incident AF over a median follow-up of 20.6 years (incidence rate 12.3 cases/1000 person-years). After adjusting for potential confounders, GDF-15 was independently associated with incident AF, with a hazard ratio (HR) of 1.42 (95% CI, 1.24-1.62) for the top vs bottom quartile. The result remained consistent (HR 1.23 [95% CI, 1.07-1.41]) even after further adjusting for 2 cardiac biomarkers, cardiac troponin T and natriuretic peptide. The results were largely consistent across demographic subgroups. The addition of GDF-15 modestly improved the c-statistic by 0.003 (95% CI, 0.001-0.006) beyond known risk factors of AF.

CONCLUSIONS

In this community-based biracial cohort, higher concentrations of GDF-15 were independently associated with incident AF, supporting its potential value as a clinical marker of AF risk.

MR-proANP measured at admission is associated with incident atrial fibrillation in STEMI patients

Atrial fibrillation (AF) is common following ST-segment elevation myocardial infarction (STEMI). Increased blood levels of mid regional pro atrial natriuretic peptide (MR-proANP) have been associated with a greater risk of incident AF. However, knowledge of the value of MR-proANP in predicting incident AF after STEMI is sparse. To assess whether MR-proANP measured at admission is associated with development of incident AF in patients with STEMI. 673 STEMI patients with no history of AF treated with primary percutaneous coronary intervention (pPCI) were prospectively enrolled from September 2006 to December 2008. Blood samples were drawn before the procedure. MR-proANP was measured by an automated processing assay. End point was incident AF. Median follow-up time was 5.5 years (interquartile-range 4.7-6.0), during which 63 patients developed AF. In a multivariable Cox regression model adjusted for relevant clinical and biochemical variables, MR-proANP was significantly associated with the development of AF (HR 1.18 per 100 pmol, 95% CI 1.11-1.28, p < 0.001). In a subgroup of patients who underwent echocardiography (N = 360), MR-proANP remained significantly associated with the development of AF (HR 1.39 per 100 pmol, 95% CI 1.13-1.71, p = 0.002) after adjusting for clinical and biochemical variables and left ventricular ejection fraction. When stratifying patients according to tertiles of MR-proANP, patients in the upper tertile displayed an 11 times greater risk of developing AF during follow-up as compared to patients in the lower tertile (HR 11.1, 95% CI 4.4-28.2, p < 0.001). Plasma MR-proANP measured at admission is an independent predictor of incident AF after STEMI.

Machine learning-based identification of risk-factor signatures for undiagnosed atrial fibrillation in primary prevention and post-stroke in clinical practice

AIMS

Atrial fibrillation (AF) carries a substantial risk of ischemic stroke and other complications, and estimates suggest that over a third of cases remain undiagnosed. AF detection is particularly pressing in stroke survivors. To tailor AF screening efforts, we explored German health claims data for routinely available predictors of incident AF in primary care and post-stroke using machine learning methods.

METHODS AND RESULTS

We combined AF predictors in patients over 45 years of age using claims data in the InGef database (n = 1 476 391) for (i) incident AF and (ii) AF post-stroke, using machine learning techniques. Between 2013-2016, new-onset AF was diagnosed in 98 958 patients (6.7%). Published risk factors for AF including male sex, hypertension, heart failure, valvular heart disease, and chronic kidney disease were confirmed. Component-wise gradient boosting identified additional predictors for AF from ICD-codes available in ambulatory care. The area under the curve (AUC) of the final, condensed model consisting of 13 predictors, was 0.829 (95% confidence interval (CI) 0.826-0.833) in the internal validation, and 0.755 (95% CI 0.603-0.890) in a prospective validation cohort (n = 661). The AUC for post-stroke AF was of 0.67 (95% CI 0.651-0.689) in the internal validation data set, and 0.766 (95% CI 0.731-0.800) in the prospective clinical cohort.

CONCLUSION

ICD-coded clinical variables selected by machine learning can improve the identification of patients at risk of newly diagnosed AF. Using this readily available, automatically coded information can target AF screening efforts to identify high-risk populations in primary care and stroke survivors.

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.

The Relationship between Blood Lipids and Risk of Atrial Fibrillation: Univariable and Multivariable Mendelian Randomization Analysis

We performed univariable and multivariable Mendelian randomization (MR) analysis to evaluate the association between blood lipids and risk of atrial fibrillation (AF), including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), Apolipoprotein A1, and Apolipoprotein B.

METHODS

Data on the single nucleotide polymorphisms (SNPs) related to blood lipids were obtained from the UK Biobank study with more than 300,000 subjects of White British European ancestry, and data for AF were from the latest meta-analysis of Genome-wide association study (GWASs) with six independent cohorts with more than 1,000,000 subjects of European ancestry. The univariable MR analysis was conducted to explore whether genetic evidence of individual lipid-related traits was significantly associated with AF risks and multivariable MR analysis with three models was performed to assess the independent effects of lipid-related traits.

RESULTS

The IVW estimate showed that genetically predicted LDL-C (OR: 1.016, 95% CI: 0.962-1.073, p = 0.560), HDL-C (OR: 0.951, 95% CI: 0.895-1.010, p = 0.102), TG (OR: 0.961, 95% CI: 0.889-1.038, p = 0.313), Apolipoprotein A1 (OR: 0.978, 95% CI: 0.933-1.025, p = 0.356), and Apolipoprotein B (OR: 1.008, 95% CI: 0.959-1.070, p = 0.794) were not causally associated with the risk of AF. Sample mode (OR: 0.852, 95% CI: 0.731-0.993, p = 0.043) and weighted mode (OR: 0.907, 95% CI: 0.841-0.979, p = 0.013) showed that a 1-unit increase in TG (mmol/L) was causally associated with a 14.8% and 9.3% relative decrease in AF risk, respectively. The multivariable MR analysis with model 1, 2, and 3 indicated that TG, LDL-C, HDL-C, Apolipoprotein A1, and Apolipoprotein B were not associated with the lower risk for AF.

CONCLUSIONS

Our multivariable Mendelian randomization analysis (MVMR) finding suggested no genetic evidence of lipid traits was significantly associated with AF risk. Furthermore, more work is warranted to confirm the potential association between lipid traits and AF risks.

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.

Heart-Brain Relationship in Stroke

The patient presenting with stroke often has cardiac-related risk factors which may be involved in the mechanism of the stroke. The diagnostic assessment is predicated on recognition of this potential relationship. Naturally, an accurate history is of utmost importance in discerning a possible cause and effect relationship. The EKG is obviously an important clue as well as it allows immediate assessment for possible cardiac arrhythmia, such as atrial fibrillation, for possible acute ischemic changes reflective of myocardial ischemia, or there may be indirect factors such as the presence of left ventricular hypertrophy, typically seen with longstanding hypertension, which could be indicative of a hypertensive mechanism for a patient presenting with intracerebral hemorrhage. For all presentations in the emergency room, the vital signs are important. An elevated body temperature in a patient presenting with acute stroke raises concern about possible infective endocarditis. An irregular-irregular pulse is an indicator of atrial fibrillation. A markedly elevated blood pressure is not uncommon in both the acute ischemic and acute hemorrhagic stroke setting. One tends to focus on possible cardioembolic stroke if there is the sudden onset of maximum neurological deficit versus the stepwise progression more characteristic of thrombotic stroke. Because of the more sudden loss of vascular supply with embolic occlusion, seizure or syncope at onset tends to be supportive of this mechanism. Different vascular territory involvement on neuroimaging is also a potential indicator of cardioembolic stroke. Identification of a cardiogenic source of embolus in such a setting certainly elevates this mechanism in the differential. There have been major advances in management of acute cerebrovascular disease in recent decades, such as thrombolytic therapy and endovascular thrombectomy, which have somewhat paralleled the advances made in cardiovascular disease. Unfortunately, the successful limitation of myocardial damage in acute coronary syndrome, with intervention, does not necessarily mirror a similar salutary effect on functional outcome with cerebral infarction. The heart can also affect the brain from a cerebral perfusion standpoint. Transient arrhythmias can result in syncope, while cardiac arrest can result in hypoxic-ischemic encephalopathy. Cardiogenic dementia has been identified as a mechanism of cognitive impairment associated with severe cardiac failure. Structural cardiac abnormalities can also play a role in brain insult, and this can include tumors, such as atrial myxoma, patent foramen ovale, with the potential for paradoxical cerebral embolism, and cardiomyopathies, such as Takotsubo, can be associated with precipitous cardioembolic events.

NT-proBNP as a marker for atrial fibrillation and heart failure in four observational outpatient trials

Aims

Heart failure (HF) and atrial fibrillation (AF) frequently coexist and are both associated with increased levels of N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP). It is known that AF impairs the diagnostic accuracy of NT‐proBNP for HF. The aim of the present study was to compare the diagnostic and predictive accuracy of NT‐proBNP for HF and AF in stable outpatients with cardiovascular risk factors.

Methods and results

Data were obtained from the DIAST‐CHF trial, a prospective cohort study that recruited individuals with cardiovascular risk factors and followed them up for 12 years. Data were validated in three independent population‐based cohorts using the same inclusion/exclusion criteria: LIFE‐Adult (n = 2869), SHIP (n = 2013), and SHIP‐TREND (n = 2408). Serum levels of NT‐proBNP were taken once at baseline. The DIAST‐CHF study enrolled 1727 study participants (47.7% female, mean age 66.9 ± 8.1 years). At baseline, patients without AF or HF (n = 1375) had a median NT‐proBNP of 94 pg/mL (interquartile range 51;181). In patients with AF (n = 93), NT‐proBNP amounted to 667 (215;1130) pg/mL. It was significantly higher than in the first group (P < 0.001) and compared with those with only HF [n = 201; 158 (66;363) pg/mL; P < 0.001]. The highest levels of NT‐proBNP [868 (213;1397) pg/mL] were measured in patients with concomitant HF and AF (n = 58; P < 0.001 vs. control and vs. HF, P = 1.0 vs. AF). In patients with AF, NT‐proBNP levels did not differ between those with HF and preserved ejection fraction (EF) > 50% [n = 38; 603 (175;1070) pg/mL] and those without HF (P = 1.0). Receiver‐operating characteristic curves of NT‐proBNP showed a similar area under the curve (AUC) for the detection of AF at baseline (0.84, 95% CI [0.79–0.88]) and for HF with EF < 50% (0.78 [0.72–0.85]; P = 0.18). The AUC for HF with EF > 50% was significantly lower (0.61 [0.56–0.65]) than for AF (P = 0.001). During follow‐up, AF was newly diagnosed in 157 (9.1%) and HF in 141 (9.6%) study participants. NT‐proBNP was a better predictor of incident AF during the first 2 years (AUC: 0.79 [0.75–0.83]) than of newly diagnosed HF (0.59 [0.55–0.63]; P < 0.001). Data were validated in three independent population‐based cohorts (LIFE‐Adult, n = 2869; SHIP, n = 2013; and SHIP‐TREND, n = 2408).

Conclusions

In stable outpatients, NT‐proBNP is a better marker for prevalent and incident AF than for HF. In AF patients, the diagnostic value of NT‐proBNP for HF with EF > 50% is very limited.

Biomarkers in the clinical management of patients with atrial fibrillation and heart failure

Atrial fibrillation (AF) and heart failure (HF) are two cardiovascular diseases with an increasing prevalence worldwide. These conditions share common pathophysiologiesand frequently co-exit. In fact, the occurrence of either condition can 'cause' the development of the other, creating a new patient group that demands different management strategies to that if they occur in isolation. Regardless of the temproral association of the two conditions, their presence is linked with adverse cardiovascular outcomes, increased rate of hospitalizations, and increased economic burden on healthcare systems. The use of low-cost, easily accessible and applicable biomarkers may hasten the correct diagnosis and the effective treatment of AF and HF. Both AF and HF effect multiple physiological pathways and thus a great number of biomarkers can be measured that potentially give the clinician important diagnostic and prognostic information. These will then guide patient centred therapeutic management. The current biomarkers that offer potential for guiding therapy, focus on the physiological pathways of miRNA, myocardial stretch and injury, oxidative stress, inflammation, fibrosis, coagulation and renal impairment. Each of these has different utility in current clinincal practice.

6-year change in high sensitivity cardiac troponin T and the risk of atrial fibrillation in the Atherosclerosis Risk in Communities cohort

BACKGROUND

Circulating high sensitivity cardiac troponin T (hs-cTnT) is associated with incidence of atrial fibrillation (AF), but the association of changes in hs-cTnT over time on incident AF has not been explored.

HYPOTHESIS

Six-year increase in circulating hs-cTnT will be associated with increased risk of AF and will contribute to improved prediction of incident AF.

METHODS

We conducted a prospective cohort analysis of 8431 participants from the Atherosclerosis Risk in Communities (ARIC) study. hs-cTnT change was categorized at visit 2 and 4 as undetectable (<5 ng/L), detectable (≥5 ng/L, <14 ng/L), or elevated (≥14 ng/L). We used Cox regression to examine the association between the combination of hs-cTnT categories at two visits and incident AF. We also assessed the impact of adding absolute hs-cTnT change on risk discrimination for AF by C-statistics and net reclassification improvement (NRI).

RESULTS

Over a mean follow-up of 16.5 years, 1629 incident AF cases were diagnosed. Among participants with undetectable hs-cTnT at visit 2, the multivariable HR of AF was 1.28 (95% CI 1.12-1.48) among those with detectable or elevated hs-cTnT at visit 4 compared to those in which hs-cTnT remained undetectable. Among those with detectable hs-cTnT at visit 2, compared to those who remained in the detectable hs-cTnT group, reduction to undetectable at visit 4 was associated with lower risk of AF (HR 0.74, 95% CI 0.59-0.94), while increment to elevated was associated with higher AF risk (HR 1.30, 95% CI 1.01-1.68). Adding hs-cTnT change to our main model with baseline hs-cTnT did not result in significant improvement in the C-statistic or substantial NRI.

CONCLUSION

Six-year increase in circulating hs-cTnT was associated with elevated risk of incident AF.

Prediction of Atrial Fibrillation Using Machine Learning: A Review

There has been recent immense interest in the use of machine learning techniques in the prediction and screening of atrial fibrillation, a common rhythm disorder present with significant clinical implications primarily related to the risk of ischemic cerebrovascular events and heart failure. Prior to the advent of the application of artificial intelligence in clinical medicine, previous studies have enumerated multiple clinical risk factors that can predict the development of atrial fibrillation. These clinical parameters include previous diagnoses, laboratory data (e.g., cardiac and inflammatory biomarkers, etc.), imaging data (e.g., cardiac computed tomography, cardiac magnetic resonance imaging, echocardiography, etc.), and electrophysiological data. These data are readily available in the electronic health record and can be automatically queried by artificial intelligence algorithms. With the modern computational capabilities afforded by technological advancements in computing and artificial intelligence, we present the current state of machine learning methodologies in the prediction and screening of atrial fibrillation as well as the implications and future direction of this rapidly evolving field.

Risk prediction of atrial fibrillation in the community combining biomarkers and genetics

AIMS

Classical cardiovascular risk factors (CVRFs), biomarkers, and common genetic variation have been suggested for risk assessment of atrial fibrillation (AF). To evaluate their clinical potential, we analysed their individual and combined ability of AF prediction.

METHODS AND RESULTS

In N = 6945 individuals of the FINRISK 1997 cohort, we assessed the predictive value of CVRF, N-terminal pro B-type natriuretic peptide (NT-proBNP), and 145 recently identified single-nucleotide polymorphisms (SNPs) combined in a developed polygenic risk score (PRS) for incident AF. Over a median follow-up of 17.8 years, n = 551 participants (7.9%) developed AF. In multivariable-adjusted Cox proportional hazard models, NT-proBNP [hazard ratio (HR) of log transformed values 4.77; 95% confidence interval (CI) 3.66-6.22; P < 0.001] and the PRS (HR 2.18; 95% CI 1.88-2.53; P < 0.001) were significantly related to incident AF. The discriminatory ability improved asymptotically with increasing numbers of SNPs. Compared with a clinical model, AF risk prediction was significantly improved by addition of NT-proBNP and the PRS. The C-statistic for the combination of CVRF, NT-proBNP, and the PRS reached 0.83 compared with 0.79 for CVRF only (P < 0.001). A replication in the Dutch Prevention of REnal and Vascular ENd-stage Disease (PREVEND) cohort revealed similar results. Comparing the highest vs. lowest quartile, NT-proBNP and the PRS both showed a more than three-fold increased AF risk. Age remained the strongest risk factor with a 16.7-fold increased risk of AF in the highest quartile.

CONCLUSION

The PRS and the established biomarker NT-proBNP showed comparable predictive ability. Both provided incremental predictive value over standard clinical variables. Further improvements for the PRS are likely with the discovery of additional SNPs.

Extracellular matrix remodeling precedes atrial fibrillation: Results of the PREDICT-AF trial

BACKGROUND

To which extent atrial remodeling occurs before atrial fibrillation (AF) is unknown.

OBJECTIVE

The PREventive left atrial appenDage resection for the predICtion of fuTure Atrial Fibrillation (PREDICT-AF) study investigated such subclinical remodeling, which may be used for risk stratification and AF prevention.

METHODS

Patients (N = 150) without a history of AF with a CHA₂DS₂-VASc score of ≥2 at an increased risk of developing AF were included. The left atrial appendage was excised and blood samples were collected during elective cardiothoracic surgery for biomarker discovery. Participants were followed for 2 years with Holter monitoring to determine any atrial tachyarrhythmia after a 50-day blanking period.

RESULTS

Eighteen patients (12%) developed incident AF, which was associated with increased tissue gene expression of collagen I (COL1A1), collagen III (COL3A1), and collagen VIII (COL8A2), tenascin-C (TNC), thrombospondin-2 (THBS2), and biglycan (BGN). Furthermore, the fibroblast activating endothelin-1 (EDN1) and sodium voltage-gated channel β subunit 2 (SCN2B) were associated with incident AF whereas the Kir2.1 channel (KCNJ2) tended to downregulate. The plasma levels of COL8A2 and TNC correlated with tissue expression and predicted incident AF. A gene panel including tissue KCNJ2, COL1A1, COL8A2, and EDN1 outperformed clinical prediction models in discriminating incident AF.

CONCLUSION

The PREDICT-AF study demonstrates that atrial remodeling occurs long before incident AF and implies future potential for early patient identification and therapies to prevent AF (ClinicalTrials.gov identifier NCT03130985).

Left atrial appendage thrombus and cerebrovascular events post-transcatheter aortic valve implantation

AIMS

To elucidate the frequency and clinical impact of left atrial appendage thrombus (LAAT) in patients set for transcatheter aortic valve implantation (TAVI).

METHODS AND RESULTS

All patients undergoing TAVI between January 2014 and June 2020 with analysable multislice computed tomography (MSCT) for LAAT were included. Baseline and procedural characteristics were collected, pre-procedural MSCT's were retrospectively analysed for LAAT presence. The primary endpoint was defined as the cumulative incidence of any cerebrovascular event (stroke or transient ischaemic attack) within the first year after TAVI. A Cox proportional hazards model was used to identify predictors.A total of 1050 cases had analysable MSCT. Median age was 80 [interquartile range (IQR) 74-84], median Society of Thoracic Surgeons' Predicted Risk Of Mortality (STS-PROM) was 3.4% (IQR 2.3-5.5). Thirty-six percent were on oral anticoagulant therapy for atrial fibrillation (AF). LAAT was present in 48 (4.6%) of cases. Patients with LAAT were at higher operative risk [STS-PROM: 4.9% (2.9-7.1) vs. 3.4% (2.3-5.5), P = 0.01], had worse systolic left ventricular function [EF 52% (35-60) vs. 55% (45-65), P = 0.01] and more permanent pacemakers at baseline (35% vs. 10%, P < 0.01). All patients with LAAT had a history of AF and patients with LAAT were more often on vitamin K antagonist-treatment than patients without LAAT [43/47 (91%) vs. 232/329 (71%), P < 0.01]. LAAT [hazard ratio (HR) 2.94 (1.39-6.22), P < 0.01] and the implantation of more than one valve [HR 4.52 (1.79-11.25), P < 0.01] were independent predictors for cerebrovascular events.

CONCLUSION

Patients with MSCT-identified LAAT were at higher risk for cerebrovascular events during the first year after TAVI.

Biomarkers for Risk Assessment in Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) is associated with an increased risk of thromboembolism, which can be significantly reduced with anticoagulant treatment. Key goals in the clinical management of AF are the identification of patients at high risk for developing AF and accurate stratification of the risk of stroke and systemic embolic events (S/SEE) as well as treatment-related major bleeding.

CONTENT

In this review, we describe the expanding evidence regarding the use of circulating biomarkers for predicting the risks of both incident AF and its clinically important complications of S/SEE and treatment-related major bleeding. We also review emerging biomarker-based scores for assessing these risks.

SUMMARY

Patients with AF undergo progressive cardiac structural remodeling, which may precede the onset of the arrhythmia. Abnormal concentrations of circulating biomarkers reflecting the underlying pathophysiologic mechanisms of hemodynamic stress (i.e., natriuretic peptides), inflammation (i.e., C-reactive protein), and myocardial fibrosis identify patients at higher risk of developing AF. Circulating biomarkers can also be used to identify patients with AF who are at greatest risk for developing S/SEE or major bleeding. In particular, biomarkers of hemodynamic stress, myocardial injury (i.e., cardiac troponin), and coagulation activity (i.e., D-dimer) are key indicators of thromboembolic risk, and cardiac troponin and growth-differentiation factor-15 are strongly associated with risk of anticoagulant-related major bleeding. The biomarker-based age, biomarker, clinical history (ABC)-stroke and ABC-bleeding risk scores improve risk stratification for S/SEE and major bleeding, respectively, when compared with traditional clinical risk scores like the CHA2DS2-VASc and HAS-BLED scores.

Prediction of Incident Atrial Fibrillation in Chronic Kidney Disease: The Chronic Renal Insufficiency Cohort Study

BACKGROUND AND OBJECTIVES

Atrial fibrillation (AF) is common in CKD and associated with poor kidney and cardiovascular outcomes. Prediction models developed using novel methods may be useful to identify patients with CKD at highest risk of incident AF. We compared a previously published prediction model with models developed using machine learning methods in a CKD population.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

We studied 2766 participants in the Chronic Renal Insufficiency Cohort study without prior AF with complete cardiac biomarker (N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin T) and clinical data. We evaluated the utility of machine learning methods as well as a previously validated clinical prediction model (Cohorts for Heart and Aging Research in Genomic Epidemiology [CHARGE]-AF, which included 11 predictors, using original and re-estimated coefficients) to predict incident AF. Discriminatory ability of each model was assessed using the ten-fold cross-validated C-index; calibration was evaluated graphically and with the Grønnesby and Borgan test.

RESULTS

Mean (SD) age of participants was 57 (11) years, 55% were men, 38% were Black, and mean (SD) eGFR was 45 (15) ml/min per 1.73 m2; 259 incident AF events occurred during a median of 8 years of follow-up. The CHARGE-AF prediction equation using original and re-estimated coefficients had C-indices of 0.67 (95% confidence interval, 0.64 to 0.71) and 0.67 (95% confidence interval, 0.64 to 0.70), respectively. A likelihood-based boosting model using clinical variables only had a C-index of 0.67 (95% confidence interval, 0.64 to 0.70); adding N-terminal pro-B-type natriuretic peptide, high-sensitivity troponin T, or both biomarkers improved the C-index by 0.04, 0.01, and 0.04, respectively. In addition to N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin T, the final model included age, non-Hispanic Black race/ethnicity, Hispanic race/ethnicity, cardiovascular disease, chronic obstructive pulmonary disease, myocardial infarction, peripheral vascular disease, use of angiotensin-converting enzyme inhibitor/angiotensin receptor blockers, calcium channel blockers, diuretics, height, and weight.

CONCLUSIONS

Using machine learning algorithms, a model that included 12 standard clinical variables and cardiac-specific biomarkers N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin T had moderate discrimination for incident AF in a CKD population.

Prediction models for atrial fibrillation applicable in the community: a systematic review and meta-analysis

Aims

Atrial fibrillation (AF) is a common arrhythmia associated with an increased stroke risk. The use of multivariable prediction models could result in more efficient primary AF screening by selecting at-risk individuals. We aimed to determine which model may be best suitable for increasing efficiency of future primary AF screening efforts.

Methods and results

We performed a systematic review on multivariable models derived, validated, and/or augmented for AF prediction in community cohorts using Pubmed, Embase, and CINAHL (Cumulative Index to Nursing and Allied Health Literature) through 1 August 2019. We performed meta-analysis of model discrimination with the summary C-statistic as the primary expression of associations using a random effects model. In case of high heterogeneity, we calculated a 95% prediction interval. We used the CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) checklist for risk of bias assessment. We included 27 studies with a total of 2 978 659 unique participants among 20 cohorts with mean age ranging from 42 to 76 years. We identified 21 risk models used for incident AF risk in community cohorts. Three models showed significant summary discrimination despite high heterogeneity: CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology) [summary C-statistic 0.71; 95% confidence interval (95% CI) 0.66–0.76], FHS-AF (Framingham Heart Study risk score for AF) (summary C-statistic 0.70; 95% CI 0.64–0.76), and CHA₂DS₂-VASc (summary C-statistic 0.69; 95% CI 0.64–0.74). Of these, CHARGE-AF and FHS-AF had originally been derived for AF incidence prediction. Only CHARGE-AF, which comprises easily obtainable measurements and medical history elements, showed significant summary discrimination among cohorts that had applied a uniform (5-year) risk prediction window.

Conclusion

CHARGE-AF appeared most suitable for primary screening purposes in terms of performance and applicability in older community cohorts of predominantly European descent.

Sex-related differences in risk factors, outcome, and quality of life in patients with permanent atrial fibrillation: results from the RACE II study

AIMS

Atrial fibrillation (AF) risk factors translate into disease progression. Whether this affects women and men differently is unclear. We aimed to investigate sex differences in risk factors, outcome, and quality of life (QoL) in permanent AF patients.

METHODS AND RESULTS

The Rate Control Efficacy in Permanent Atrial Fibrillation (RACE II) randomized 614 patients, 211 women and 403 men, to lenient or strict rate control. In this post hoc analysis risk factors, cardiovascular events during 3-year follow-up (cardiovascular death, heart failure hospitalization, stroke, systemic embolism, bleeding, and life-threatening arrhythmic events), outcome parameters, and QoL were compared between the sexes. Women were older (71 ± 7 vs. 66 ± 8 years, P < 0.001), had more hypertension (70 vs. 57%, P = 0.002), and heart failure with preserved ejection fraction (36 vs. 17%, P < 0.001), but less coronary artery disease (13 vs. 21%, P = 0.02). Women had more risk factors (3.7 ± 1.2 vs. 2.9 ± 1.4, P < 0.001) Cardiovascular events occurred in 46 (22%) women and 59 (15%) men (P = 0.03). Women had a 1.52 times [95% confidence interval (CI) 1.03-2.24] higher yearly cardiovascular event-rate [8.2% (6.0-10.9) vs. 5.4% (4.1-6.9), P = 0.03], but this was no longer significant after adjusting for the number of underlying risk factors. Women had reduced QoL, irrespective of age and heart rate but negatively influenced by their risk factors.

CONCLUSION

In this permanent AF population, women had more accumulation of AF risk factors than men. The observed higher cardiovascular event rate in women was no longer significant after adjusting for the number of risk factors. Further, QoL was negatively influenced by the higher number of risk factors in women. This suggests that sex differences may be driven by the greater risk factor burden in women.

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.

Preoperative levels of natriuretic peptides and the incidence of postoperative atrial fibrillation after noncardiac surgery: a prospective cohort study

BACKGROUND

Postoperative atrial fibrillation (POAF) is associated with clinically significant short- and long-term complications after noncardiac surgery. Our aim was to describe the incidence of clinically important POAF after noncardiac surgery and establish the prognostic value of N-terminal pro-brain-type natriuretic peptide (NT-proBNP) in this context.

METHODS

The Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) Study was a prospective cohort study involving patients aged 45 years and older who had inpatient noncardiac surgery that was performed between August 2007 and November 2013. We determined 30-day incidence of clinically important POAF (i.e., resulting in angina, congestive heart failure, symptomatic hypotension or requiring treatment) using logistic regression models to analyze the association between preoperative NT-proBNP and POAF.

RESULTS

In 37 664 patients with no history of atrial fibrillation, we found that the incidence of POAF was 1.0% (95% confidence interval [CI] 0.9%-1.1%; 369 events); 3.2% (95% CI 2.3%-4.4%) in patients undergoing major thoracic surgery, 1.3% (95% CI 1.2%-1.5%) in patients undergoing major nonthoracic surgery and 0.2% (95% CI 0.1%-0.3%) in patients undergoing low-risk surgery. In a subgroup of 9789 patients with preoperative NT-proBNP measurements, the biomarker improved the prediction of POAF risk over conventional prognostic factors (likelihood ratio test p < 0.001; fraction of new information from NT-proBNP was 16%). Compared with a reference NT-proBNP measurement set at 100 ng/L, adjusted odds ratios for the occurrence of POAF were 1.31 (95% CI 1.15-1.49) at 200 ng/L, 2.07 (95% CI 1.27-3.36) at 1500 ng/L and 2.39 (95% CI 1.26-4.51) at 3000 ng/L.

INTERPRETATION

We determined that the incidence of clinically important POAF after noncardiac surgery was 1.0%. We also found that preoperative NT-proBNP levels were associated with POAF independent of established prognostic factors. Trial registration: ClinicalTrials.gov, no. NCT00512109.

Atrial Fibrillation After Ischemic Stroke Detected by Chest Strap-Style 7-Day Holter Monitoring and the Risk Predictors: EDUCATE-ESUS

AIM

This study aimed to investigate the diagnostic yield of 7-day Holter monitoring for detecting covert atrial fibrillation (AF) in patients with recent embolic stroke of undetermined source (ESUS) and to identify the pre-entry screening biomarkers that had significant associations with later detection of AF (clinicaltrials.gov. NCT02801708).

METHODS

A total of 206 patients who have recent ESUS without previously documented AF underwent Holter electrocardiography using a chest strap-style monitor. External validation of biomarkers predictive of AF was performed using 83 patients with ESUS who were implanted with insertable cardiac monitors.

RESULTS

The 7-day Holter monitoring started at a median of 13 days after the onset of stroke. AF was detected in 14 patients, and three of these showed a single AF episode lasting ＜2 min. The median time delay to the first documented AF was 50 h. Each of serum brain natriuretic peptide ≥ 66.0 pg/mL (adjusted odds ratio 5.23), atrial premature contractions (APCs) ≥ 345 beats (3.80), and APC short runs ≥ 13 (5.74) on 24-h Holter prior to the 7-day Holter showed a significant association with detection of AF, independent of age and physiological findings in this derivation cohort, and all of these showed a significant association in the validation cohort (adjusted odds ratio 6.59, 7.87, and 6.16, respectively).

CONCLUSIONS

In recent ESUS patients, the detection rate of AF using the 7-day Holter monitoring was 6.8% (95% CI 4.1%-11.1%). Brain natriuretic peptide, APC count, and APC short runs in the standard clinical workup seemed to be predictors of covert AF.

Incidence of Atrial Fibrillation in Persons with Very High Serum Levels of N-Terminal Pro-B-Type Natriuretic Peptide: The Multi-Ethnic Study of Atherosclerosis

Objective

While persons in the upper fourth or fifth of the distribution of serum levels of N-terminal pro-B type natriuretic peptide (NT-proBNP) are at a sharply increased risk of developing atrial fibrillation, their absolute risk of this condition (about 20 per 1000 per year) is not clearly high enough to justify prevention or early detection measures. We sought to determine whether the incidence of atrial fibrillation among persons with VERY high levels of NT-proBNP might be sufficiently high to warrant further action.

Design and Setting

Among persons enrolled in the Multi-Ethnic Study of Atherosclerosis, we documented rates of new onset atrial fibrillation in those with increasingly high serum levels of NT-proBNP.

Results

There was a monotonic increase in the incidence of atrial fibrillation with increasing serum level of NT-proBNP, reaching rates of about 50–70 cases per 1000 person-years among those in the upper 3.1% of the distribution (above 422 pg/mL). In this group the incidence tended to be somewhat higher still among persons who were at increased risk of atrial fibrillation for other reasons (eg older age), but in no subgroup did the incidence reach 100 per 1000 person-years.

Conclusion

Serum levels of NT-proBNP have a considerable ability to predict the development of atrial fibrillation. However, the value of screening middle aged and older adults for these levels hinges largely on the ability of interventions in screen-positive people to lead to a reduced incidence of atrial fibrillation and its complications.

Sparsely methylated mitochondrial cell free DNA released from cardiomyocytes contributes to systemic inflammatory response accompanied by atrial fibrillation

Systemic inflammation is assumed to be the consequence and the cause of atrial fibrillation (AF); however, the underlying mechanism remains unclear. We aimed to evaluate the level of cell-free DNA (cfDNA) in patients with AF and AF mimicking models, and to illuminate its impact on inflammation. Peripheral blood was obtained from 54 patients with AF and 104 non-AF controls, and cfDNA was extracted. We extracted total cfDNA from conditioned medium after rapid pacing to HL-1 cells. Nuclear and mitochondrial DNA were separately extracted and fragmented to simulate nuclear-cfDNA (n-cfDNA) and mitochondrial-cfDNA (mt-cfDNA). The AF group showed higher cfDNA concentration than the non-AF group (12.6 [9.0–17.1] vs. 8.1 [5.3–10.8] [ng/mL], p < 0.001). The copy numbers of n-cfDNA and mt-cfDNA were higher in AF groups than in non-AF groups; the difference of mt-cfDNA was particularly apparent (p = 0.011 and p < 0.001, respectively). Administration of total cfDNA and mt-cfDNA to macrophages significantly promoted IL-1β and IL-6 expression through TLR9, whereas n-cfDNA did not. Induction of cytokine expression by methylated mt-cfDNA was lower than that by unmethylated mt-cfDNA. Collectively, AF was associated with an increased cfDNA level, especially mt-cfDNA. Sparsely methylated mt-cfDNA released from cardiomyocytes may be involved in sterile systemic inflammation accompanied by AF.

Risk markers of incident atrial fibrillation in patients with coronary heart disease

BACKGROUND

In patients with coronary heart disease (CHD), atrial fibrillation (AF) is associated with increased morbidity and mortality. We investigated the associations between clinical risk factors and biomarkers with incident AF in patients with CHD.

METHODS AND RESULTS

Around 13,153 patients with optimally treated CHD included in the STabilization of Atherosclerotic plaque By Initiation of darapLadIb TherapY (STABILITY) trial with plasma samples obtained at randomization. Mean follow-up time was 3.5 years. The association between clinical risk factors and biomarkers with incident AF was estimated with Cox-regression models. Validation was performed in 1,894 patients with non-ST-elevation acute coronary syndrome included in the FRISC-II trial. The median (min-max) age was 64 years (range 26-92) and 2,514 (19.1%) were women. A total of 541 patients, annual incidence rate of 1.2%, developed AF during follow-up. In multivariable models, older age, higher levels of NT-proBNP, higher body mass index (BMI), male sex, geographic regions, low physical activity, and heart failure were independently associated with increased risk of incident AF with hazard ratios ranging from 1.04 to 1.79 (P ≤ .05). NT-proBNP improved the C-index from 0.70 to 0.71. In the validation cohort, age, BMI, and NT-proBNP were associated with increased risk of incident AF with similar hazard ratios.

CONCLUSIONS

In patients with optimally treated CHD, the incidence of new AF was 1.2% per year. Age, NT-proBNP as a marker of impaired cardiac function, and BMI were the strongest factors, independently and consistently associated with incident AF. Male sex and low physical activity may also contribute to the risk of AF in patients with CHD.

Biomarkers in Atrial Fibrillation: Pathogenesis and Clinical Implications

Biomarkers derived from the key components of the pathophysiology of atrial fibrillation (AF) and its complications have the potential to play an important role in earlier characterization of AF phenotype and in risk prediction of adverse clinical events, which may translate into improved management strategies. C-reactive protein, natriuretic peptides, cardiac troponins, growth differentiation factor-15, and fibroblast growth factor-23 have been shown to be the most promising biomarkers in AF. Some biomarkers have already been included in clinical risk scores to predict postoperative AF, thromboembolism, major bleeding, and death. Considerably more work is needed to bring these novel biomarkers into routine clinical management of patients with AF.