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Aims: The HFA-PEFF score was developed to optimize diagnosis and to aid in early recognition of heart failure (HF) with preserved ejection fraction (HFpEF) in patients who present with HF-like symptoms. Recognizing early-HFpEF phenogroups is essential to better understand progression towards overt HFpEF and pave the way for early intervention and treatment. Whether the HFA-PEFF domain scores can identify 'early-HFpEF' phenogroups remains unknown. The aims of this pilot study are to (i) identify distinct phenogroups by cluster analysis of HFA-PEFF domain scores in subjects that present with HF-like symptoms and (ii) study whether these phenogroups may be associated with distinct blood proteome profiles., Methods and Results: Subjects referred to the Cardiology Centers of the Netherlands, location Utrecht, with non-acute possibly cardiac-related symptoms (such as dyspnoea or fatigue) were prospectively enrolled in the HELPFul cohort (N = 507) and were included in the current analysis. Inclusion criteria for this study were (i) age ≥ 45 years and (ii) a left ventricular ejection fraction (LVEF) ≥ 50%, in the absence of a history of HF, coronary artery disease, congenital heart disease, or any previous cardiac interventions. Multinominal-based clustering with latent class model using the HFA-PEFF domain scores (functional, structural, and biomarker scores) as input was used to detect distinct phenotypic clusters. For each bootstrapping run, the 92 Olink proteins were analysed for their association with the identified phenogroups. Four distinct phenogroups were identified in the current analysis (validated by bootstrapping 1000×): (i) no left ventricular diastolic dysfunction (no LVDD, N = 102); (ii) LVDD with functional left ventricular (LV) abnormalities (N = 204); (iii) LVDD with functional and structural LV abnormalities (N = 204); and (iv) LVDD with functional and structural LV abnormalities and elevated BNP (N = 107). The HFA-PEFF total score risk categories significantly differed between the phenogroups (P < 0.001), with an increase of the HFA-PEFF score from Phenogroup 1 to 4 (low/intermediate/high HFA-PEFF risk score: Phenogroup 1: 88%/12%/0%; Phenogroup 2: 9%/91%/0%; Phenogroup 3: 0%/92%/8%; Phenogroup 4: 5%/83%/12%). Thirty-two out of the 92 Olink protein biomarkers significantly differed among the phenogroups. The top eight biomarkers-N-terminal prohormone brain natriuretic peptide, growth differentiation factor-15, matrix metalloproteinase-2, osteoprotegerin, tissue inhibitor of metalloproteinase-4, chitinase-3-like protein 1, insulin-like growth factor-binding protein 2, and insulin-like growth factor-binding protein 7-are mainly involved in inflammation and extracellular matrix remodelling, which are currently proposed key processes in HFpEF pathophysiology., Conclusions: This study identified distinct phenogroups by using the HFA-PEFF domain scores in ambulant subjects referred for HF-like symptoms. The newly identified phenogroups accompanied by their circulating biomarkers profile might aid in a better understanding of the pathophysiological processes involved during the early stages of the HFpEF syndrome., (© 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Aims: Heart failure (HF) represents a clinical syndrome resulting from different aetiologies and degrees of heart diseases. Among these, a key role is played by primary heart muscle disease (cardiomyopathies), which are the combination of multifactorial environmental insults in the presence or absence of a known genetic predisposition. The aim of the Maastricht Cardiomyopathy registry (mCMP-registry; NCT04976348) is to improve (early) diagnosis, risk stratification, and management of cardiomyopathy phenotypes beyond the limits of left ventricular ejection fraction (LVEF)., Methods and Results: The mCMP-registry is an investigator-initiated prospective registry including patient characteristics, diagnostic measurements performed as part of routine clinical care, treatment information, sequential biobanking, quality of life and economic impact assessment, and regular follow-up. All subjects aged ≥16 years referred to the cardiology department of the Maastricht University Medical Center (MUMC+) for HF-like symptoms or cardiac screening for cardiomyopathies are eligible for inclusion, irrespective of phenotype or underlying causes. Informed consented subjects will be followed up for 15 years. Two central approaches will be used to answer the research questions related to the aims of this registry: (i) a data-driven approach to predict clinical outcome and response to therapy and to identify clusters of patients who share underlying pathophysiological processes; and (ii) a hypothesis-driven approach in which clinical parameters are tested for their (incremental) diagnostic, prognostic, or therapeutic value. The study allows other centres to easily join this initiative, which will further boost research within this field., Conclusions: The broad inclusion criteria, systematic routine clinical care data-collection, extensive study-related data-collection, sequential biobanking, and multi-disciplinary approach gives the mCMP-registry a unique opportunity to improve diagnosis, risk stratification, and management of HF and (early) cardiomyopathy phenotypes beyond the LVEF limits., (© 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Aims: Global longitudinal strain (GLS) has become an alternative to left ventricular ejection fraction (LVEF) to determine systolic function of the heart. The absence of cut-off values is one of the limitations preventing full clinical implementation. The aim of this study is to determine a cut-off value of GLS for an increased risk of adverse events in individuals with a normal LVEF., Methods and Results: Echocardiographic images of 502 subjects (52% female, mean age 48 ± 15) with an LVEF ≥ 55% were analysed using speckle tracking-based GLS. The primary endpoint was cardiovascular death or cardiac hospitalization. The analysis of Cox models with splines was performed to visualize the effect of GLS on outcome. A cut-off value was suggested by determining the optimal specificity and sensitivity. The median GLS was -22.2% (inter-quartile range -20.0 to -24.9%). In total, 35 subjects (7%) had a cardiac hospitalization and/or died because of cardiovascular disease during a follow-up of 40 (5-80) months. There was a linear correlation between the risk for adverse events and GLS value. Subjects with a normal LVEF and a GLS between -22.9% and -20.9% had a mildly increased risk (hazard ratio 1.01-2.0) for cardiac hospitalization or cardiovascular mortality, and the risk was doubled for subjects with a GLS of -20.9% and higher. The optimal specificity and sensitivity were determined at a GLS value of -20.0% (hazard ratio 2.49; 95% confidence interval: 1.71-3.61)., Conclusions: There is a strong correlation between cardiac adverse events and GLS values in subjects with a normal LVEF. In our single-centre study, -20.0% was determined as a cut-off value to identify subjects at risk. A next step should be to integrate GLS values in a multi-parametric model., (© 2021 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Aims: Parvovirus B19 (B19V) is often assumed to be a cause of dilated cardiomyopathy (DCM), based on the quantification of B19V DNA in endomyocardial biopsies (EMB). Whether the presence of B19V DNA correlates with active infection is still debated. Application of the enzyme endonuclease to blood samples results in degradation of B19V DNA remnants but leaves viral particles intact, which enables differentiation between active and past infection. In this study, the susceptibility to degradation by endonuclease of B19V DNA in blood was compared between DCM patients and a control group of recent B19V infections., Methods and Results: Twenty blood samples from 20 adult patients with DCM, who previously tested positive for B19V DNA in EMB and/or blood, were tested with B19V PCR before and after application of endonuclease to the samples. Six blood samples tested positive for B19V DNA with a mean viral load of 2.3 × 10 4  IU/mL. In five samples, B19V DNA became undetectable after endonuclease (100% load reduction); in one sample DNA load showed a 23% log load reduction (viral load before endonuclease: 9.1 × 10 4  IU/mL; after: 6.5 × 10 3  IU/mL). Presence of cardiac inflammation did not differ between patients with B19V DNAemia (1/4) and patients without B19V DNAemia (6/14) (P value = 1.0). In all 18 control samples of proven recent B19V infections, DNA remained detectable after application of endonuclease, showing only a mean log load reduction of 2.3% (mean viral load before endonuclease: 8.1 × 10 11  IU/mL; after: 8.0 × 10 11  IU/mL). Load reduction differed significantly between the DCM group and the control group; indicating the presence of intact viral particles in the control group with proven active infection and the presence of DNA remnants in the DCM group (P value = 0.000)., Conclusion: During recent B19V infection, viral DNA levels in blood were unaffected by endonuclease. In contrast, B19V DNA in blood in patients with DCM became undetectable or strongly reduced after application of endonuclease. Circulating viral DNA in this subset of patients with presumed parvovirus-associated DCM does not consist of intact viral particles. Viral replicative activity cannot be assumed from demonstrating B19V DNA in cardiac tissue or in blood in DCM patients., (© 2021 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)