Pathophysiological pathways in patients with heart failure and atrial fibrillation

Mendelian Randomization Study Reveals Causal Pathways for Hypertrophic Cardiomyopathy, Cardiovascular Proteins, and Atrial Fibrillation

Aims/Background Research evidence has demonstrated a significant association between hypertrophic cardiomyopathy (HCM) and atrial fibrillation (AF), but the causality and pattern of this link remain unexplored. Therefore, this study investigated the causal relationship between HCM and AF using a two-sample and bidirectional Mendelian randomization (MR) approach. Additionally, this assessed the role of cardiovascular proteins (CPs) associated with cardiovascular diseases between HCM and AF by applying a two-step MR analysis. Methods Data for HCM, AF, and 90 CPs were obtained from the Finn Gen and IEU Open GWAS Project databases. MR-Egger, inverse variance weighting (IVW), weighted median estimator (WME), weighted mode, and simple mode were used to estimate causal inferences. Furthermore, Cochran's Q test, MR-Egger's intercept terms, and Leave-one-out methods determined the heterogeneity, horizontal pleiotropy, and sensitivity. Additionally, mediation effects were used to assess the role of CPs in the relationship between HCM and AF. Results Two-sample and bidirectional MR analysis revealed HCM as a risk factor for AF (odds ratio (OR) = 1.008, 95% confidence interval (CI): 1.001-1.016, p = 0.029) and AF was found to increase the risk of developing HCM (OR = 1.145, 95% CI: 0.963-1.361, p = 0.126). Moreover, Two-step MR analyses indicated that 5 CPs were causally associated with HCM; 12 CPs with AF and 1 CP (Melusin) with both HCM and AF. Additionally, Melusin was observed as a protective factor for both HCM and AF and may serve as a mediator variable for these two conditions (mediation effect 0.0004, mediation ratio 5.5178%, 95% CI: 5.4624-5.5731). Conclusion HCM may increase the risk of developing AF, with Melusin serving as a mediator for this risk.

Comprehensive Proteomics Profiling Identifies Circulating Biomarkers to Distinguish Hypertrophic Cardiomyopathy From Other Cardiomyopathies With Left Ventricular Hypertrophy

BACKGROUND

Distinguishing hypertrophic cardiomyopathy (HCM) from other cardiomyopathies with left ventricular hypertrophy (LVH), such as hypertensive LVH, transthyretin amyloid cardiomyopathy, and aortic stenosis, is sometimes challenging. Using plasma proteomics profiling, we aimed to identify circulating biomarkers and dysregulated signaling pathways specific to HCM.

METHODS

In this multicenter case-control study, plasma proteomics profiling was performed in cases with HCM and controls with hypertensive LVH, transthyretin amyloid cardiomyopathy, and aortic stenosis. Two-thirds of patients enrolled earlier in each disease group were defined as the training set and the remaining one-third as the test set. Protein concentrations in HCM were compared with those in hypertensive LVH (comparison 1), transthyretin amyloid cardiomyopathy (comparison 2), and aortic stenosis (comparison 3). Candidate proteins that meet the following 2 criteria were selected: (1) higher abundance in HCM throughout all 3 comparisons or lower abundance in HCM throughout all 3 comparisons with univariable P<0.05 and |log2(fold change)| >0.5 in both the training and test sets and (2) independently associated with HCM with multivariable P<0.05 after adjusting for clinical parameters significantly different between HCM and controls. Using the selected candidate proteins, a logistic regression model to distinguish HCM from controls was developed in the training set and applied to the test set. Finally, pathway analysis was performed in each comparison using proteins with different abundance.

RESULTS

Overall, 4979 proteins in 1415 patients (HCM, n=879; hypertensive LVH, n=331; transthyretin amyloid cardiomyopathy, n=169; aortic stenosis, n=36) were analyzed. Of those, 5 proteins were selected as candidate proteins. The logistic regression model with these 5 proteins had an area under the receiver operating characteristic curve of 0.86 (95% CI, 0.82-0.89) in the test set. The MAPK (mitogen-activated protein kinase) and HIF-1 (hypoxia-inducible factor 1) pathways were dysregulated in HCM throughout the 3 comparisons.

CONCLUSIONS

This study identified circulating biomarkers that distinguish HCM from other cardiomyopathies with LVH independently from confounders and revealed signaling pathways associated with HCM.

Integrative proteomic analyses across common cardiac diseases yield mechanistic insights and enhanced prediction

Cardiac diseases represent common highly morbid conditions for which molecular mechanisms remain incompletely understood. Here we report the analysis of 1,459 protein measurements in 44,313 UK Biobank participants to characterize the circulating proteome associated with incident coronary artery disease, heart failure, atrial fibrillation and aortic stenosis. Multivariable-adjusted Cox regression identified 820 protein-disease associations-including 441 proteins-at Bonferroni-adjusted P < 8.6 × 10-6. Cis-Mendelian randomization suggested causal roles aligning with epidemiological findings for 4% of proteins identified in primary analyses, prioritizing therapeutic targets across cardiac diseases (for example, spondin-1 for atrial fibrillation and the Kunitz-type protease inhibitor 1 for coronary artery disease). Interaction analyses identified seven protein-disease associations that differed Bonferroni-significantly by sex. Models incorporating proteomic data (versus clinical risk factors alone) improved prediction for coronary artery disease, heart failure and atrial fibrillation. These results lay a foundation for future investigations to uncover disease mechanisms and assess the utility of protein-based prevention strategies for cardiac diseases.

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

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

Tissue-resident memory T cells in epicardial adipose tissue comprise transcriptionally distinct subsets that are modulated in atrial fibrillation

Atrial fibrillation (AF) is the most common sustained arrhythmia and carries an increased risk of stroke and heart failure. Here we investigated how the immune infiltrate of human epicardial adipose tissue (EAT), which directly overlies the myocardium, contributes to AF. Flow cytometry analysis revealed an enrichment of tissue-resident memory T (TRM) cells in patients with AF. Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell T cell receptor (TCR) sequencing identified two transcriptionally distinct CD8+ TRM cells that are modulated in AF. Spatial transcriptomic analysis of EAT and atrial tissue identified the border region between the tissues to be a region of intense inflammatory and fibrotic activity, and the addition of TRM populations to atrial cardiomyocytes demonstrated their ability to differentially alter calcium flux as well as activate inflammatory and apoptotic signaling pathways. This study identified EAT as a reservoir of TRM cells that can directly modulate vulnerability to cardiac arrhythmia.

Integrative proteomic analyses across common cardiac diseases yield new mechanistic insights and enhanced prediction

Cardiac diseases represent common highly morbid conditions for which underlying molecular mechanisms remain incompletely understood. Here, we leveraged 1,459 protein measurements in 44,313 UK Biobank participants to characterize the circulating proteome associated with incident coronary artery disease, heart failure, atrial fibrillation, and aortic stenosis. Multivariable-adjusted Cox regression identified 820 protein-disease associations-including 441 proteins-at Bonferroni-adjusted P <8.6×10 -6 . Cis -Mendelian randomization suggested causal roles that aligned with epidemiological findings for 6% of proteins identified in primary analyses, prioritizing novel therapeutic targets for different cardiac diseases (e.g., interleukin-4 receptor for heart failure and spondin-1 for atrial fibrillation). Interaction analyses identified seven protein-disease associations that differed Bonferroni-significantly by sex. Models incorporating proteomic data (vs. clinical risk factors alone) improved prediction for coronary artery disease, heart failure, and atrial fibrillation. These results lay a foundation for future investigations to uncover novel disease mechanisms and assess the clinical utility of protein-based prevention strategies for cardiac diseases.

IGFBP-7 and Outcomes in Heart Failure With Reduced Ejection Fraction: Findings From DAPA-HF

BACKGROUND

Insulin-like growth factor-binding protein-7 (IGFBP-7) has been proposed as a potential prognostic biomarker in heart failure (HF), but the association between elevation in IGFBP-7 and HF outcomes in ambulant patients with heart failure with reduced ejection fraction (HFrEF) is unknown.

OBJECTIVES

The authors addressed this question in a post hoc analysis of the DAPA-HF (Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure) trial.

METHODS

The primary outcome was a composite of cardiovascular death or a worsening HF event. The risk of adverse outcome was compared across tertiles of IGFBP-7 concentration by means of Cox proportional hazard models adjusted for N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin T (hsTnT). The efficacy of randomized treatment across IGFBP-7 tertiles was assessed. Change in IGFBP-7 at 12 months was compared with the use of geometric means.

RESULTS

A total of 3,158 patients had IGFBP-7 measured at baseline, and 2,493 had a repeated measure at 12 months. Patients in the highest tertile of IGFBP-7 had evidence of more advanced HFrEF. The adjusted HR for the primary endpoint in tertile 3, compared with tertile 1, was 1.48 (95% CI: 1.17-1.88). There was no modification of the benefit of dapagliflozin by baseline IGFBP-7 (P interaction = 0.34). Dapagliflozin did not change IGFBP-7 levels over 1 year (P = 0.34).

CONCLUSIONS

Higher IGFBP-7 in patients with HFrEF was associated with worse clinical profile and an increased risk of adverse clinical outcomes. IGFBP-7 provided prognostic information incremental to clinical variables, NT-proBNP, and hsTnT. The benefit of dapagliflozin was not modulated by IGFBP-7 level. (Study to Evaluate the Effect of Dapagliflozin on the Incidence of Worsening Heart Failure or Cardiovascular Death in Patients With Chronic Heart Failure [DAPA-HF]; NCT03036124).

Inflammatory pathways in heart failure with preserved left ventricular ejection fraction: implications for future interventions

Many patients with symptoms and signs of heart failure have a left ventricular ejection fraction ≥50%, termed heart failure with preserved ejection fraction (HFpEF). HFpEF is a heterogeneous syndrome mainly affecting older people who have many other cardiac and non-cardiac conditions that often cast doubt on the origin of symptoms, such as breathlessness, or signs, such as peripheral oedema, rendering them neither sensitive nor specific to the diagnosis of HFpEF. Currently, management of HFpEF is mainly directed at controlling symptoms and treating comorbid conditions such as hypertension, atrial fibrillation, anaemia, and coronary artery disease. HFpEF is also characterized by a persistent increase in inflammatory biomarkers. Inflammation may be a key driver of the development and progression of HFpEF and many of its associated comorbidities. Detailed characterization of specific inflammatory pathways may provide insights into the pathophysiology of HFpEF and guide its future management. There is growing interest in novel therapies specifically designed to target deregulated inflammation in many therapeutic areas, including cardiovascular disease. However, large-scale clinical trials investigating the effectiveness of anti-inflammatory treatments in HFpEF are still lacking. In this manuscript, we review the role of inflammation in HFpEF and the possible implications for future trials.

Biomarker signature and pathophysiological pathways in patients with chronic heart failure and metabolic syndrome

AIM

The comorbidities that collectively define metabolic syndrome are common in patients with heart failure. However, the role of metabolic syndrome in the pathophysiology of heart failure is not well understood. We therefore investigated the clinical and biomarker correlates of metabolic syndrome in patients with heart failure.

METHODS AND RESULTS

In 1103 patients with heart failure, we compared the biomarker expression using a panel of 363 biomarkers among patients with (n = 468 [42%]) and without (n = 635 [58%]) metabolic syndrome. Subsequently, a pathway overrepresentation analysis was performed to identify key biological pathways. Findings were validated in an independent cohort of 1433 patients with heart failure of whom 615 (43%) had metabolic syndrome. Metabolic syndrome was defined as the presence of three or more of five criteria, including central obesity, elevated serum triglycerides, reduced high-density lipoprotein cholesterol, insulin resistance and hypertension. The most significantly elevated biomarkers in patients with metabolic syndrome were leptin (log2 fold change 0.92, p = 5.85 × 10^-21 ), fatty acid-binding protein 4 (log2 fold change 0.61, p = 1.21 × 10^-11 ), interleukin-1 receptor antagonist (log2 fold change 0.47, p = 1.95 × 10^-13 ), tumour necrosis factor receptor superfamily member 11a (log2 fold change 0.35, p = 4.16 × 10^-9 ), and proto-oncogene tyrosine-protein kinase receptor Ret (log2 fold change 0.31, p = 4.87 × 10^-9 ). Network analysis identified 10 pathways in the index cohort and 6 in the validation cohort, all related to inflammation. The primary overlapping pathway in both the index and validation cohorts was up-regulation of the natural killer cell-mediated cytotoxicity pathway.

CONCLUSION

Metabolic syndrome is highly prevalent in heart failure and is associated with biomarkers and pathways relating to obesity, lipid metabolism and immune responses underlying chronic inflammation.