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ACE2 (angiotensin-converting enzyme 2) is a key component of the renin-angiotensin-aldosterone system. Yet, little is known about the clinical and biologic correlates of circulating ACE2 levels in humans. We assessed the clinical and proteomic correlates of plasma (soluble) ACE2 protein levels in human heart failure. We measured plasma ACE2 using a modified aptamer assay among PHFS (Penn Heart Failure Study) participants (n=2248). We performed an association study of ACE2 against ≈5000 other plasma proteins measured with the SomaScan platform. Plasma ACE2 was not associated with ACE inhibitor and angiotensin-receptor blocker use. Plasma ACE2 was associated with older age, male sex, diabetes mellitus, a lower estimated glomerular filtration rate, worse New York Heart Association class, a history of coronary artery bypass surgery, and higher pro-BNP (pro-B-type natriuretic peptide) levels. Plasma ACE2 exhibited associations with 1011 other plasma proteins. In pathway overrepresentation analyses, top canonical pathways associated with plasma ACE2 included clathrin-mediated endocytosis signaling, actin cytoskeleton signaling, mechanisms of viral exit from host cells, EIF2 (eukaryotic initiation factor 2) signaling, and the protein ubiquitination pathway. In conclusion, in humans with heart failure, plasma ACE2 is associated with various clinical factors known to be associated with severe coronavirus disease 2019 (COVID-19), including older age, male sex, and diabetes mellitus, but is not associated with ACE inhibitor and angiotensin-receptor blocker use. Plasma ACE2 protein levels are prominently associated with multiple cellular pathways involved in cellular endocytosis, exocytosis, and intracellular protein trafficking. Whether these have a causal relationship with ACE2 or are relevant to novel coronavirus-2 infection remains to be assessed in future studies.

Background: Better risk stratification strategies are needed to enhance clinical care and trial design in heart failure with preserved ejection fraction (HFpEF)., Objectives: The purpose of this study was to assess the value of a targeted plasma multi-marker approach to enhance our phenotypic characterization and risk prediction in HFpEF., Methods: In this study, the authors measured 49 plasma biomarkers from TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist) trial participants (n = 379) using a Multiplex assay. The relationship between biomarkers and the risk of all-cause death or heart failure-related hospital admission (DHFA) was assessed. A tree-based pipeline optimizer platform was used to generate a multimarker predictive model for DHFA. We validated the model in an independent cohort of HFpEF patients enrolled in the PHFS (Penn Heart Failure Study) (n = 156)., Results: Two large, tightly related dominant biomarker clusters were found, which included biomarkers of fibrosis/tissue remodeling, inflammation, renal injury/dysfunction, and liver fibrosis. Other clusters were composed of neurohormonal regulators of mineral metabolism, intermediary metabolism, and biomarkers of myocardial injury. Multiple biomarkers predicted incident DHFA, including 2 biomarkers related to mineral metabolism/calcification (fibroblast growth factor-23 and OPG [osteoprotegerin]), 3 inflammatory biomarkers (tumor necrosis factor-alpha, sTNFRI [soluble tumor necrosis factor-receptor I], and interleukin-6), YKL-40 (related to liver injury and inflammation), 2 biomarkers related to intermediary metabolism and adipocyte biology (fatty acid binding protein-4 and growth differentiation factor-15), angiopoietin-2 (related to angiogenesis), matrix metalloproteinase-7 (related to extracellular matrix turnover), ST-2, and N-terminal pro-B-type natriuretic peptide. A machine-learning-derived model using a combination of biomarkers was strongly predictive of the risk of DHFA (standardized hazard ratio: 2.85; 95% confidence interval: 2.03 to 4.02; p < 0.0001) and markedly improved the risk prediction when added to the MAGGIC (Meta-Analysis Global Group in Chronic Heart Failure Risk Score) risk score. In an independent cohort (PHFS), the model strongly predicted the risk of DHFA (standardized hazard ratio: 2.74; 95% confidence interval: 1.93 to 3.90; p < 0.0001), which was also independent of the MAGGIC risk score., Conclusions: Various novel circulating biomarkers in key pathophysiological domains are predictive of outcomes in HFpEF, and a multimarker approach coupled with machine-learning represents a promising strategy for enhancing risk stratification in HFpEF., (Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Objectives: This study sought to assess if clinical phenogroups differ in comprehensive biomarker profiles, cardiac and arterial structure/function, and responses to spironolactone therapy., Background: Previous studies identified distinct subgroups (phenogroups) of patients with heart failure with preserved ejection fraction (HFpEF)., Methods: Among TOPCAT (Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist Trial) participants, we performed latent-class analysis to identify HFpEF phenogroups based on standard clinical features and assessed differences in multiple biomarkers measured from frozen plasma; cardiac and arterial structure/function measured with echocardiography and arterial tonometry; prognosis; and response to spironolactone., Results: Three HFpEF phenogroups were identified. Phenogroup 1 (n = 1,214) exhibited younger age, higher prevalence of smoking, preserved functional class, and the least evidence of left ventricular (LV) hypertrophy and arterial stiffness. Phenogroup 2 (n = 1,329) was older, with normotrophic concentric LV remodeling, atrial fibrillation, left atrial enlargement, large-artery stiffening, and biomarkers of innate immunity and vascular calcification. Phenogroup 3 (n = 899) demonstrated more functional impairment, obesity, diabetes, chronic kidney disease, concentric LV hypertrophy, high renin, and biomarkers of tumor necrosis factor-alpha-mediated inflammation, liver fibrosis, and tissue remodeling. Compared with phenogroup 1, phenogroup 3 exhibited the highest risk of the primary endpoint of cardiovascular death, heart failure hospitalization, or aborted cardiac arrest (hazard ratio [HR]: 3.44; 95% confidence interval [CI]: 2.79 to 4.24); phenogroups 2 and 3 demonstrated similar all-cause mortality (phenotype 2 HR: 2.36; 95% CI: 1.89 to 2.95; phenotype 3 HR: 2.26, 95% CI: 1.77 to 2.87). Spironolactone randomized therapy was associated with a more pronounced reduction in the risk of the primary endpoint in phenogroup 3 (HR: 0.75; 95% CI: 0.59 to 0.95; p for interaction = 0.016). Results were similar after excluding participants from Eastern Europe., Conclusions: We identified important differences in circulating biomarkers, cardiac/arterial characteristics, prognosis, and response to spironolactone across clinical HFpEF phenogroups. These findings suggest distinct underlying mechanisms across clinically identifiable phenogroups of HFpEF that may benefit from different targeted interventions., (Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Little data are available regarding the determinants and prognostic significance of serum albumin in Heart Failure with Preserved Ejection Fraction (HFpEF). We sought to examine the phenotypic correlates of albumin and its independent prognostic implications in HFpEF. We analyzed data from 3,254 subjects enrolled the TOPCAT trial. We stratified subjects according to tertiles of albumin and examined differences in various phenotypic traits between these strata, including 8 protein biomarkers selected ad hoc and measured from frozen samples available in a subset of participants (n = 372). We also assessed the relationship between albumin and the trial primary endpoint. Lower albumin was associated with older age, black race, and greater prevalence of NYHA class III-IV, peripheral arterial disease, atrial fibrillation and diabetes mellitus. Lower albumin was also associated with increased levels of several inflammatory biomarkers, markers of liver fibrosis, albuminuria, and greater arterial stiffness, diastolic dysfunction and pulmonary hypertension. Albumin was a strong predictor of the primary trial endpoint, even after adjustment for the MAGGIC risk score (hazard ratio [HR] 0.72, confidence interval [CI] 0.67 to 0.78; p <0.0001) and prespecified traditional risk factors (HR 0.78, CI 0.71 to 0.85; p <0.0001). Lower albumin was strongly associated with a worse prognosis even well within normal ranges (>3.5 g/dL), with a sharp increase in risk between 4.6 and 3.6 g/dL. In conclusion, albumin is an integrated marker of various adverse processes in HFpEF, including inflammation, subclinical liver disease, arterial stiffness, and renal disease. Albumin is a powerful risk predictor independent of traditional risk prediction models, even within normal ranges., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background Heterogeneity in the underlying processes that contribute to heart failure with preserved ejection fraction ( HF p EF ) is increasingly recognized. Diabetes mellitus is a frequent comorbidity in HF p EF , but its impact on left ventricular and arterial structure and function in HF p EF is unknown. Methods and Results We assessed the impact of diabetes mellitus on left ventricular cellular and interstitial hypertrophy (assessed with cardiac magnetic resonance imaging, including T1 mapping pregadolinium and postgadolinium administration), arterial stiffness (assessed with arterial tonometry), and pulsatile arterial hemodynamics (assessed with in-office pressure-flow analyses and 24-hour ambulatory monitoring) among 53 subjects with HF p EF (32 diabetic and 21 nondiabetic subjects). Despite few differences in clinical characteristics, diabetic subjects with HFpEF exhibited a markedly greater left ventricular mass index (78.1 [95% CI , 70.4-85.9] g versus 63.6 [95% CI , 55.8-71.3] g; P=0.0093) and indexed extracellular volume (23.6 [95% CI , 21.2-26.1] mL/m 2 versus 16.2 [95% CI , 13.1-19.4] mL/m 2 ; P=0.0008). Pronounced aortic stiffening was also observed in the diabetic group (carotid-femoral pulse wave velocity, 11.86 [95% CI , 10.4-13.1] m/s versus 8.8 [95% CI , 7.5-10.1] m/s; P=0.0027), with an adverse pulsatile hemodynamic profile characterized by increased oscillatory power (315 [95% CI , 258-373] mW versus 190 [95% CI , 144-236] mW; P=0.0007), aortic characteristic impedance (0.154 [95% CI , 0.124-0.183] mm Hg/mL per second versus 0.096 [95% CI , 0.072-0.121] mm Hg/mL per second; P=0.0024), and forward (59.5 [95% CI , 52.8-66.1] mm Hg versus 40.1 [95% CI , 31.6-48.6] mm Hg; P=0.0010) and backward (19.6 [95% CI , 16.2-22.9] mm Hg versus 14.1 [95% CI , 10.9-17.3] mm Hg; P=0.0169) wave amplitude. Abnormal pulsatile hemodynamics were also evident in 24-hour ambulatory monitoring, despite the absence of significant differences in 24-hour systolic blood pressure between the groups. Conclusions Diabetes mellitus is a key determinant of left ventricular remodeling, arterial stiffness, adverse pulsatile hemodynamics, and ventricular-arterial interactions in HF p EF . Clinical Trial Registration URL : https://www.clinicaltrials.gov . Unique identifier: NCT 01516346.