Association of Longitudinal Changes in Cardiac Biomarkers With Atrial and Ventricular Arrhythmias (from the Atherosclerosis Risk in Communities [ARIC] Study)

What Do We Know So Far About Ventricular Arrhythmias and Sudden Cardiac Death Prediction in the Mitral Valve Prolapse Population? Could Biomarkers Help Us Predict Their Occurrence?

PURPOSE OF THE REVIEW

To summarize currently available data on the topic of mitral valve prolapse (MVP) and its correlation to the occurrence of atrial and ventricular arrhythmias. To assess the prognostic value of several diagnostic methods such as transthoracic echocardiography, transesophageal echocardiography, cardiac magnetic resonance, cardiac computed tomography, electrocardiography, and electrophysiology concerning arrhythmic episodes. To explore intra and extracellular biochemistry of the cardiovascular system and its biomarkers as diagnostic tools to predict rhythm disturbances in the MVP population.

RECENT FINDINGS

MVP is a common and mainly benign valvular disorder. It affects 2-3% of the general population. MVP is a heterogeneous and highly variable phenomenon with three structural phenotypes: myxomatous degeneration, fibroelastic deficiency, and forme fruste. Exercise intolerance, supraventricular tachycardia, and chest discomfort are the symptoms that are often paired with psychosomatic components. Though MVP is thought to be benign, the association between isolated MVP without mitral regurgitation (MR) or left ventricle dysfunction, with ventricular arrhythmia (VA) and sudden cardiac death (SCD) has been observed. The incidence of SCD in the MVP population is around 0.6% per year, which is 6 times higher than the occurrence of SCD in the general population. Often asymptomatic MVP population poses a challenge to screen for VA and prevent SCD. Therefore, it is crucial to carefully assess the risk of VA and SCD in patients with MVP with the use of various tools such as diagnostic imaging and biochemical and genetic screening.

Role of ideal cardiovascular health metrics in reducing risk of incident arrhythmias

AIMS

Cardiovascular health (CVH) has been proven to reduce cardiovascular disease burden and mortality, but data are lacking regarding cardiac arrhythmias. The aim of this study was to assess the association between CVH metrics and atrial fibrillation/flutter (AF), ventricular arrhythmias, and bradyarrhythmias.

METHODS AND RESULTS

This study analysed data from the Atherosclerosis Risk in Communities (ARIC) cohort, with participants recruited from four different communities across the United States. Cardiovascular health metrics were scored at baseline (1987-89) following the American Heart Association's recommendations and categorized as poor, intermediate, or ideal. Arrhythmia episodes were diagnosed by International Classification of Diseases (ICD)-9 code. Adjusted associations were estimated using Cox models and event rates and population attributable fractions were calculated by CVH metrics category. The study population consisted of 13 078 participants, with 2548 AF, 1363 ventricular arrhythmias, and 706 bradyarrhythmias occurred. The adjusted hazard ratios (HRs) for ideal (vs. poor) CVH metrics were 0.59 [95% confidence interval (CI): 0.50-0.69] for AF, 0.38 (95% CI: 0.28-0.51) for ventricular arrhythmias, and 0.70 (95% CI: 0.51-0.97) for bradyarrhythmia. The risk of incident arrhythmias decreased steadily as the CVH metrics improved from 0 to 14 scores. The adjusted population attributable fractions were calculated to be 29.9% for AF, 54.4% for ventricular arrhythmias, and 21.9% for bradyarrhythmia, respectively. The association between CVH metrics and incident arrhythmias was also seen in people who remained free of coronary heart disease over the follow-up.

CONCLUSION

Achieving ideal CVH metrics recommendations by AHA in midlife was associated with a lower risk of incident arrhythmias later in life.

Development and Validation of a Novel Predictive Model for the Early Differentiation of Cardiac and Non-Cardiac Syncope

Background

The diagnosis of cardiac syncope remains a challenge. This study sought to develop and validate a diagnostic model for the early identification of individuals likely to have a cardiac cause.

Methods

877 syncope patients with a determined cause were retrospectively enrolled at a tertiary heart center. They were randomly divided into the training set and validation set at a 7:3 ratio. We analyzed the demographic information, medical history, laboratory tests, electrocardiogram, and echocardiogram by the least absolute shrinkage and selection operator (LASSO) regression for selection of key features. Then a multivariable logistic regression analysis was performed to identify independent predictors and construct a diagnostic model. The receiver operating characteristic curves, area under the curve (AUC), calibration curves, and decision curve analysis were used to evaluate the predictive accuracy and clinical value of this nomogram.

Results

Five independent predictors for cardiac syncope were selected: BMI (OR 1.088; 95% CI 1.022-1.158; P =0.008), chest symptoms preceding syncope (OR 5.251; 95% CI 3.326-8.288; P <0.001), logarithmic NT-proBNP (OR 1.463; 95% CI 1.240-1.727; P <0.001), left ventricular ejection fraction (OR 0.940; 95% CI 0.908-0.973; P <0.001), and abnormal electrocardiogram (OR 6.171; 95% CI 3.966-9.600; P <0.001). Subsequently, a nomogram based on a multivariate logistic regression model was developed and validated, yielding AUC of 0.873 (95% CI 0.845-0.902) and 0.856 (95% CI 0.809-0.903), respectively. The calibration curves showcased the nomogram's reasonable calibration, and the decision curve analysis demonstrated good clinical utility.

Conclusion

A diagnostic tool providing individualized probability predictions for cardiac syncope was developed and validated, which may potentially serve as an effective tool to facilitate early identification of such patients.

Role of Cardiac Natriuretic Peptides in Heart Structure and Function

Cardiac natriuretic peptides (NPs), atrial NP (ANP) and B-type NP (BNP) are true hormones produced and released by cardiomyocytes, exerting several systemic effects. Together with C-type NP (CNP), mainly expressed by endothelial cells, they also exert several paracrine and autocrine activities on the heart itself, contributing to cardiovascular (CV) health. In addition to their natriuretic, vasorelaxant, metabolic and antiproliferative systemic properties, NPs prevent cardiac hypertrophy, fibrosis, arrhythmias and cardiomyopathies, counteracting the development and progression of heart failure (HF). Moreover, recent studies revealed that a protein structurally similar to NPs mainly produced by skeletal muscles and osteoblasts called musclin/osteocrin is able to interact with the NPs clearance receptor, attenuating cardiac dysfunction and myocardial fibrosis and promoting heart protection during pathological overload. This narrative review is focused on the direct activities of this molecule family on the heart, reporting both experimental and human studies that are clinically relevant for physicians.

Blood-Based Biomarkers to Search for Atrial Fibrillation in High-Risk Asymptomatic Individuals and Cryptogenic Stroke Patients

Background

Atrial fibrillation (AF) increases the risk of ischemic stroke in asymptomatic individuals and may be the underlying cause of many cryptogenic strokes. We aimed to test the usefulness of candidate blood-biomarkers related to AF pathophysiology in two prospective cohorts representative of those populations.

Methods

Two hundred seventy-four subjects aged 65–75 years with hypertension and diabetes from the AFRICAT cohort, and 218 cryptogenic stroke patients aged >55 years from the CRYPTO-AF cohort were analyzed. AF was assessed by 4 weeks of monitoring with a wearable Holter device (NuuboTM™). Blood was collected immediately before monitoring started. 10 candidate biomarkers were measured by automated immunoassays (Roche, Penzberg) in the plasma of all patients. Univariate and logistic regression analyses were performed in each cohort separately.

Results

Atrial fibrillation detection rate was 12.4% (AFRICAT cohort) and 22.9% (CRYPTO-AF cohort). 4 biomarkers were significantly increased in asymptomatic individuals with AF [Troponin-T, Angiopoietin-2 (Ang-2), Endocan, and total N-terminal pro-B type natriuretic peptide (NT-proBNP)] and 7 biomarkers showed significantly higher concentrations in cryptogenic stroke patients with AF detection [growth differentiation factor 15, interleukin 6, Troponin-T, Ang-2, Bone morphogenic protein 10, Dickkopf-related protein 3 (DKK-3), and total NT-proBNP]. The models including Ang-2 and total NT-proBNP [AUC 0.764 (0.665–0.863)], and Ang-2 and DKK-3 [AUC = 0.733 (0.654–0.813)], together with age and sex, showed the best performance to detect AF in high-risk asymptomatic individuals, and in cryptogenic stroke patients, respectively.

Conclusion

Blood-biomarkers, in particular, total NT-proBNP, DKK-3, and Ang-2, were associated with AF reflecting two mechanistically different pathways involved in AF pathophysiology (AF stretch and vascular changes). The combination of these biomarkers could be useful in AF screening strategies in the primary care setting and also for searching AF after cryptogenic stroke.