Assessment of causality of natriuretic peptides and atrial fibrillation and heart failure: a Mendelian randomization study in the FINRISK cohort

Biomarkers of heart failure: advances in omics studies

Heart failure is a complex syndrome characterized by progressive circulatory dysfunction, manifesting clinically as pulmonary and systemic venous congestion, alongside inadequate tissue perfusion. The early identification of HF, particularly at the mild and moderate stages (stages B and C), presents a clinical challenge due to the overlap of signs, symptoms, and natriuretic peptide levels with other cardiorespiratory pathologies. Nonetheless, early detection coupled with timely pharmacological intervention is imperative for enhancing patient outcomes. Advances in high-throughput omics technologies have enabled researchers to analyze patient-derived biofluids and tissues, discovering biomarkers that are sensitive and specific for HF diagnosis. Due to the diversity of HF etiology, it is insufficient to study the diagnostic data of early HF using a single omics technology. This study reviewed the latest progress in genomics, transcriptomics, proteomics, and metabolomics for the identification of HF biomarkers, offering novel insights into the early clinical diagnosis of HF. However, the validity of biomarkers depends on the disease status, intervention time, genetic diversity and comorbidities of the subjects. Moreover, biomarkers lack generalizability in different clinical settings. Hence, it is imperative to conduct multi-center, large-scale and standardized clinical trials to enhance the diagnostic accuracy and utility of HF biomarkers.

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.

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.

Plasma angiopoietin-2 and its association with heart failure in patients with atrial fibrillation

AIMS

Several biomarkers are associated with clinical outcomes in patients with atrial fibrillation (AF), but a causal relationship has not been established. This study aimed to evaluate angiopoietin-2, a novel candidate biomarker of endothelial inflammation and vascular remodelling, in patients with AF.

METHODS AND RESULTS

Angiopoietin-2 was measured in plasma obtained from patients with AF treated with aspirin monotherapy (exploration cohort, n = 2987) or with oral anticoagulation (validation cohort, n = 13 079). Regression models were built to assess the associations between angiopoietin-2, clinical characteristics, and outcomes. In both cohorts, plasma angiopoietin-2 was independently associated with AF on the baseline electrocardiogram and persistent/permanent AF, age, history of heart failure, female sex, tobacco use/smoking, body mass index, renal dysfunction, diabetes, and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Angiopoietin-2 was independently associated with subsequent hospitalization for heart failure after adjusting for age, creatinine, and clinical characteristics in the exploration cohort [c-index 0.79, 95% confidence interval (CI) 0.75-0.82; third vs. first quartile, hazard ratio (HR) 1.74, 95% CI 1.26-2.41] and in the validation cohort (c-index 0.76, 95% CI 0.74-0.78; HR 1.58, 95% CI 1.37-1.82). In both cohorts, the association persisted when also adjusting for NT-proBNP (P ≤ 0.001). In full multivariable models also adjusted for NT-proBNP, angiopoietin-2 did not show statistically significant associations with ischaemic stroke, cardiovascular and all-cause death, or major bleeding that were consistent across the two cohorts.

CONCLUSIONS

In patients with AF, plasma levels of angiopoietin-2 were independently associated with subsequent hospitalization for heart failure and provided incremental prognostic value to clinical risk factors and NT-proBNP.

Atrial fibrillation prediction by combining ECG markers and CMR radiomics

Atrial fibrillation (AF) is the most common cardiac arrhythmia. It is associated with a higher risk of important adverse health outcomes such as stroke and death. AF is linked to distinct electro-anatomic alterations. The main tool for AF diagnosis is the Electrocardiogram (ECG). However, an ECG recorded at a single time point may not detect individuals with paroxysmal AF. In this study, we developed machine learning models for discrimination of prevalent AF using a combination of image-derived radiomics phenotypes and ECG features. Thus, we characterize the phenotypes of prevalent AF in terms of ECG and imaging alterations. Moreover, we explore sex-differential remodelling by building sex-specific models. Our integrative model including radiomics and ECG together resulted in a better performance than ECG alone, particularly in women. ECG had a lower performance in women than men (AUC: 0.77 vs 0.88, p < 0.05) but adding radiomics features, the accuracy of the model was able to improve significantly. The sensitivity also increased considerably in women by adding the radiomics (0.68 vs 0.79, p < 0.05) having a higher detection of AF events. Our findings provide novel insights into AF-related electro-anatomic remodelling and its variations by sex. The integrative radiomics-ECG model also presents a potential novel approach for earlier detection of AF.

Therapeutic Targets for Heart Failure Identified Using Proteomics and Mendelian Randomization

BACKGROUND

Heart failure (HF) is a highly prevalent disorder for which disease mechanisms are incompletely understood. The discovery of disease-associated proteins with causal genetic evidence provides an opportunity to identify new therapeutic targets.

METHODS

We investigated the observational and causal associations of 90 cardiovascular proteins, which were measured using affinity-based proteomic assays. First, we estimated the associations of 90 cardiovascular proteins with incident heart failure by means of a fixed-effect meta-analysis of 4 population-based studies, composed of a total of 3019 participants with 732 HF events. The causal effects of HF-associated proteins were then investigated by Mendelian randomization, using cis-protein quantitative loci genetic instruments identified from genomewide association studies in more than 30 000 individuals. To improve the precision of causal estimates, we implemented an Mendelian randomization model that accounted for linkage disequilibrium between instruments and tested the robustness of causal estimates through a multiverse sensitivity analysis that included up to 120 combinations of instrument selection parameters and Mendelian randomization models per protein. The druggability of candidate proteins was surveyed, and mechanism of action and potential on-target side effects were explored with cross-trait Mendelian randomization analysis.

RESULTS

Forty-four of ninety proteins were positively associated with risk of incident HF (P<6.0×10-4). Among these, 8 proteins had evidence of a causal association with HF that was robust to multiverse sensitivity analysis: higher CSF-1 (macrophage colony-stimulating factor 1), Gal-3 (galectin-3) and KIM-1 (kidney injury molecule 1) were positively associated with risk of HF, whereas higher ADM (adrenomedullin), CHI3L1 (chitinase-3-like protein 1), CTSL1 (cathepsin L1), FGF-23 (fibroblast growth factor 23), and MMP-12 (matrix metalloproteinase-12) were protective. Therapeutics targeting ADM and Gal-3 are currently under evaluation in clinical trials, and all the remaining proteins were considered druggable, except KIM-1.

CONCLUSIONS

We identified 44 circulating proteins that were associated with incident HF, of which 8 showed evidence of a causal relationship and 7 were druggable, including adrenomedullin, which represents a particularly promising drug target. Our approach demonstrates a tractable roadmap for the triangulation of population genomic and proteomic data for the prioritization of therapeutic targets for complex human diseases.

Exploring the Causal Effects of Circulating ST2 and Galectin-3 on Heart Failure Risk: A Mendelian Randomization Study

Background

Heart failure (HF), primarily caused by conditions such as coronary heart disease or cardiomyopathy, is a global health problem with poor prognosis and heavy burden on healthcare systems. As biomarkers of myocardial injury and fibrosis, suppression of tumorigenicity 2 (ST2) and galectin-3 were recommended for prognosis stratification in HF guidelines. However, the causality between these two mediators and HF remains obscure. This study aimed to explore the causal relationship of genetically determined ST2 and galectin-3 with the risk of HF.

Methods

We used the two-sample Mendelian randomization (MR) method, incorporating available genome-wide association summary statistics, to investigate the causal association of ST2 and galectin-3 with HF risk. We applied inverse-variance weighted analysis as the main method of analysis.

Results

In our final MR analysis, 4 single-nucleotide polymorphisms (SNPs) of ST2 and galectin-3, respectively, were identified as valid instrumental variables. Fixed-effect inverse variance weighted (IVW) analysis indicated that genetically predicted ST2 and galectin-3 were not causally associated with HF risk 3. [odds ratio (OR) = 0.9999, 95% confidence interval [CI] = 0.9994–1.0004, p = 0.73; OR = 1.0002, 95% CI = 0.9994–1.0010, p = 0.60, respectively]. These findings were robust in sensitivity analyses, including MR-Egger regression and leave-one-out analysis.

Conclusion

This MR study provided no evidence for the causal effects of ST2 and galectin-3 on HF risk.

Biomarkers for Predicting the Occurrence and Progression of Atrial Fibrillation: Soluble Suppression of Tumorigenicity 2 Protein and Tissue Inhibitor of Matrix Metalloproteinase-1

BACKGROUND

Soluble suppression of tumorigenicity 2 protein (sST2) and tissue inhibitor of matrix metalloproteinase (TIMP)-1 are involved in multiple pathogenic pathways, including cardiac remodeling, which is the main pathology of atrial fibrillation (AF). This study aims to investigate the previously unexplored relationship between the serum levels of sST2, TIMP-1, and AF.

METHODS

This was a prospective cross-sectional study conducted at the Capital Medical University Affiliated Beijing Anzhen Hospital between June 2019 and July 2020, with a total of 359 participants. The clinical characteristics and laboratory results of the patients were compared, and multivariable ordinal logistic regression was used to evaluate the relationship between serum sST2, TIMP-1, and AF.

RESULTS

The participants included 110 patients with sinus rhythm (SR), 113 with paroxysmal AF (the paroxysmal AF group), and 136 with persistent AF (the persistent AF group). It was found that the sST2 levels gradually increased in these three groups, from 9.1 (6.7-12.4 pg/ml) in the SR group to 14.0 (10.4-20.8 pg/ml) in the paroxysmal AF group and to 19.0 (13.1-27.8) pg/ml) in the persistent AF group (p  <  0.001). The multivariable ordinal logistic regression model for sST2 and TIMP-1 demonstrated that sST2 had an area under the receiver operating characteristic (ROC) curve (AUC) of 0.797 (95% confidence interval (CI) 0.749-0.846, p  <  0.001) and TIMP-1 had an AUC of 0.795 (95% CI 0.750-0.841, p=0.000). The multivariable ordinal logistic regression model for sST2 and TIMP-1 showed good discrimination between SR and AF, with an AUC of 0.846, and the addition of clinical factors, such as brain natriuretic peptide (BNP), left atrial diameter, age, and gender, to the biomarker model improved the detection of SR and AF (AUC 0.901).

CONCLUSIONS

In this cohort study, sST2 and TIMP-1 were associated with AF progression, independent of clinical characteristics and biomarkers. Soluble ST2 and TIMP-1 combined with age, elevated N-terminal-pro hormone BNP(NT-BNP), and an enlarged left atrium were able to demonstrate the progression of AF reliably.

Using a Two-Sample Mendelian Randomization Method in Assessing the Causal Relationships Between Human Blood Metabolites and Heart Failure

Background: Heart failure (HF) is the main cause of morbidity and mortality worldwide, and metabolic dysfunction is an important factor related to HF pathogenesis and development. However, the causal effect of blood metabolites on HF remains unclear.

Objectives: Our chief aim is to investigate the causal relationships between human blood metabolites and HF risk.

Methods: We used an unbiased two-sample Mendelian randomization (MR) approach to assess the causal relationships between 486 human blood metabolites and HF risk. Exposure information was obtained from Sample 1, which is the largest metabolome-based genome-wide association study (mGWAS) data containing 7,824 Europeans. Outcome information was obtained from Sample 2, which is based on the results of a large-scale GWAS meta-analysis of HF and contains 47,309 cases and 930,014 controls of Europeans. The inverse variance weighted (IVW) model was used as the primary two-sample MR analysis method and followed the sensitivity analyses, including heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis.

Results: We observed that 11 known metabolites were potentially related to the risk of HF after using the IVW method (P < 0.05). After adding another four MR models and performing sensitivity analyses, we found a 1-SD increase in the xenobiotics 4-vinylphenol sulfate was associated with ~22% higher risk of HF (OR [95%CI], 1.22 [1.07–1.38]).

Conclusions: We revealed that the 4-vinylphenol sulfate may nominally increase the risk of HF by 22% after using a two-sample MR approach. Our findings may provide novel insights into the pathogenesis underlying HF and novel strategies for HF prevention.

STOP-HF Trial: Higher Endogenous BNP and Cardiovascular Protection in Subjects at Risk for Heart Failure

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Among subjects at risk for heart failure (Stage A and B), the minor C allele of the B-type natriuretic peptide (BNP) genetic variant rs198389 is associated with higher circulating levels of BNP.

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Rs198389 C allele is also associated with lower risk of hypertension, new onset of left ventricular systolic dysfunction, and major adverse cardiovascular events.

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These data support the role of BNP genetic testing and BNP-based therapy for the prevention of heart failure.

B-type natriuretic peptide (BNP) possesses blood-pressure–lowering, antifibrotic, and aldosterone-suppressing properties. In Stage A and B heart failure, the carriers of the minor C allele of the BNP genetic variant rs198389 have higher circulating levels of BNP and are at decreased risk of hypertension, new-onset left ventricular systolic dysfunction, and hospitalization for major adverse cardiovascular events. Future studies are warranted to investigate the role of BNP genetic testing and BNP-based therapy in the prevention of heart failure.