Phenomapping in heart failure with preserved ejection fraction: insights, limitations, and future directions

Clustering of Cardiovascular Risk Factors and Heart Failure in Older Adults from the Brazilian Far North

Given the aging global population, identifying heart failure (HF) phenotypes has become crucial, as distinct disease characteristics can influence treatment and prognosis in older adults. This study aimed to analyze the association between clustering of cardiovascular risk factors and HF in older adults. A cross-sectional epidemiological study was conducted with 1322 older adults (55% women, mean age 70.4) seen in primary health care. Diagnosis of HF was performed by a cardiologist based on diagnostic tests and medical history. Cardiovascular risk factors included hypertension, diabetes, hypercholesterolemia, and smoking. Using logistic regression, potential associations were tested. Individual risk factor analysis showed that older adults with hypertension, diabetes, or hypercholesterolemia had up to 7.6 times higher odds to have HF. The cluster where older adults had only one risk factor instead of none increased the odds of HF by 53.0%. Additionally, the odds of older patients having HF ranged from 3.59 times for the two-risk factor cluster to 20.61 times for the simultaneous presence of all four factors. The analysis of clusters substantially increasing HF risk in older adults revealed the importance of individualizing subgroups with distinct HF pathophysiologies. The clinical significance of these clusters can be beneficial in guiding a more personalized therapeutic approach.

Risk Factors and Outcomes Associated With Heart Failure With Preserved and Reduced Ejection Fraction in People With Chronic Kidney Disease

BACKGROUND

Heart failure (HF) is associated with poor outcomes in people with chronic kidney disease, yet it is unknown whether outcomes differ by HF subtype. This study aimed to examine associations of incident HF with preserved ejection fraction (HFpEF) versus HF with reduced ejection fraction (HFrEF) with progression to end-stage kidney disease (ESKD) and mortality.

METHODS

We studied individuals with chronic kidney disease in the CRIC study (Chronic Renal Insufficiency Cohort) who were free of HF at cohort entry. Incident HF hospitalizations were adjudicated and classified into HFpEF (ejection fraction, ≥50%) or HFrEF (ejection fraction, <50%) based on echocardiograms performed during the hospitalization or at a research study visit. ESKD was defined as need for chronic dialysis or kidney transplant. Cox proportional hazards were used to evaluate the association of time-updated HF subtype with risk of ESKD and mortality, adjusting for demographics, comorbidities, and medication use.

RESULTS

Among the 3557 study participants without HF at cohort entry, mean age was 57 years and mean estimated glomerular filtration rate was 45 mL/min per 1.73 m2. A total of 682 participants had incident HF. Incidence rates for HFpEF and HFrEF were 0.9 (95% CI, 0.8-1.0) and 0.7 (95% CI, 0.6-0.8) per 100 person-years, respectively (Pdifference=0.005). Associations of incident HF with progression to ESKD were not statistically different for HFpEF (hazard ratio, 2.06 [95% CI, 1.66-2.56]) and HFrEF (hazard ratio, 1.80 [95% CI, 1.36-2.38]; P=0.42). The associations with mortality were stronger for HFrEF (hazard ratio, 2.73 [95% CI, 2.24-3.33]) compared with HFpEF (hazard ratio, 1.99 [95% CI, 1.65-2.40]; P=0.0002).

CONCLUSIONS

In a chronic kidney disease population, the rates of HFpEF hospitalizations were greater than that of HFrEF. Risk of ESKD was high but not statically different across HF subtypes. There was a stronger association of HFrEF with mortality. Prevention and treatment of both HFpEF and HFrEF should be central priorities to improve outcomes in chronic kidney disease.

Redefining Diabetic Cardiomyopathy: Perturbations in Substrate Metabolism at the Heart of Its Pathology

Cardiovascular disease represents the leading cause of death in people with diabetes, most notably from macrovascular diseases such as myocardial infarction or heart failure. Diabetes also increases the risk of a specific form of cardiomyopathy, referred to as diabetic cardiomyopathy (DbCM), originally defined as ventricular dysfunction in the absence of underlying coronary artery disease and/or hypertension. Herein, we provide an overview on the key mediators of DbCM, with an emphasis on the role for perturbations in cardiac substrate metabolism. We discuss key mechanisms regulating metabolic dysfunction in DbCM, with additional focus on the role of metabolites as signaling molecules within the diabetic heart. Furthermore, we discuss the preclinical approaches to target these perturbations to alleviate DbCM. With several advancements in our understanding, we propose the following as a new definition for, or approach to classify, DbCM: "diastolic dysfunction in the presence of altered myocardial metabolism in a person with diabetes but absence of other known causes of cardiomyopathy and/or hypertension." However, we recognize that no definition can fully explain the complexity of why some individuals with DbCM exhibit diastolic dysfunction, whereas others develop systolic dysfunction. Due to DbCM sharing pathological features with heart failure with preserved ejection fraction (HFpEF), the latter of which is more prevalent in the population with diabetes, it is imperative to determine whether effective management of DbCM decreases HFpEF prevalence.

ARTICLE HIGHLIGHTS

Relationship of interleukin-16 with different phenogroups in acute heart failure with preserved ejection fraction

AIMS

Interleukin-16 (IL-16) has been reported to mediate left ventricular myocardial fibrosis and stiffening in patients with heart failure with preserved ejection fraction (HFpEF). We sought to elucidate whether IL-16 has a distinct impact on pathophysiology and prognosis across different subphenotypes of acute HFpEF.

METHODS AND RESULTS

We analysed 211 patients enrolled in a prospective multicentre registry of acute decompensated HFpEF for whom serum IL-16 levels after stabilization were available (53% female, median age 81 [interquartile range 75-85] years). We divided this sub-cohort into four phenogroups using our established clustering algorithm. The study endpoint was all-cause death. Patients were subclassified into phenogroup 1 ('rhythm trouble' [n = 69]), phenogroup 2 ('ventricular-arterial uncoupling' [n = 49]), phenogroup 3 ('low output and systemic congestion' [n = 41]), and phenogroup 4 ('systemic failure' [n = 52]). After a median follow-up of 640 days, 38 patients had died. Among the four phenogroups, phenogroup 2 had the highest IL-16 level. The IL-16 level showed significant associations with indices of cardiac hypertrophy, diastolic dysfunction, and congestion only in phenogroup 2. Furthermore, the IL-16 level had a significant predictive value for all-cause death only in phenogroup 2 (C-statistic 0.750, 95% confidence interval 0.606-0.863, P = 0.017), while there was no association between the IL-16 level and the endpoint in the other phenogroups.

CONCLUSIONS

Our results indicated that the serum IL-16 level had a significant association with indices that reflect the pathophysiology and prognosis of HFpEF in a specific phenogroup in acute HFpEF.

Identifying subgroups in heart failure patients with multimorbidity by clustering and network analysis

This study presents a workflow for identifying and characterizing patients with Heart Failure (HF) and multimorbidity utilizing data from Electronic Health Records. Multimorbidity, the co-occurrence of two or more chronic conditions, poses a significant challenge on healthcare systems. Nonetheless, understanding of patients with multimorbidity, including the most common disease interactions, risk factors, and treatment responses, remains limited, particularly for complex and heterogeneous conditions like HF. We conducted a clustering analysis of 3745 HF patients using demographics, comorbidities, laboratory values, and drug prescriptions. Our analysis revealed four distinct clusters with significant differences in multimorbidity profiles showing differential prognostic implications regarding unplanned hospital admissions. These findings underscore the considerable disease heterogeneity within HF patients and emphasize the potential for improved characterization of patient subgroups for clinical risk stratification through the use of EHR data.

Rationale and design of the PACIFIC-PRESERVED (PhenomApping, ClassIFication and Innovation for Cardiac dysfunction in patients with heart failure and PRESERVED left ventricular ejection fraction) study

BACKGROUND

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome that is poorly defined, reflecting an incomplete understanding of its pathophysiology.

AIM

To redefine the phenotypic spectrum of HFpEF.

METHODS

The PACIFIC-PRESERVED study is a prospective multicentre cohort study designed to perform multidimensional deep phenotyping of patients diagnosed with HFpEF (left ventricular ejection fraction≥50%), patients with heart failure with reduced ejection fraction (left ventricular ejection fraction≤40%) and subjects without overt heart failure (3:2:1 ratio). The study proposes prospective investigations in patients during a 1-day hospital stay: physical examination; electrocardiogram; performance-based tests; blood samples; cardiac magnetic resonance imaging; transthoracic echocardiography (rest and low-level exercise); myocardial shear wave elastography; chest computed tomography; and non-invasive measurement of arterial stiffness. Dyspnoea, depression, general health and quality of life will be assessed by dedicated questionnaires. A biobank will be established. After the hospital stay, patients are asked to wear a connected garment (with digital sensors) to collect electrocardiography, pulmonary and activity variables in real-life conditions (for up to 14 days). Data will be centralized for machine-learning-based analyses, with the aim of reclassifying HFpEF into more distinct subgroups, improving understanding of the disease mechanisms and identifying new biological pathways and molecular targets. The study will also serve as a platform to enable the development of innovative technologies and strategies for the diagnosis and stratification of patients with HFpEF.

CONCLUSIONS

PACIFIC-PRESERVED is a prospective multicentre phenomapping study, using novel analytical techniques, which will provide a unique data resource to better define HFpEF and identify new clinically meaningful subgroups of patients.

The Therapy and Management of Heart Failure with Preserved Ejection Fraction: New Insights on Treatment

Heart failure with preserved ejection fraction (HFpEF) is a clinical syndrome characterised by the presence of diastolic dysfunction and elevated left ventricular filling pressure, in the setting of a left ventricular ejection fraction of at least 50%. Despite the epidemiological prevalence of HFpEF, a prompt diagnosis is challenging and many uncertainties exist. HFpEF is characterised by different phenotypes driven by various cardiac and non-cardiac comorbidities. This is probably the reason why several HFpEF clinical trials in the past did not reach strong outcomes to recommend a single therapy for this syndrome; however, this paradigm has recently changed, and the unmet clinical need for HFpEF treatment found a proper response as a result of a new class of drug, the sodium-glucose cotransporter 2 inhibitors, which beneficially act through the whole spectrum of left ventricular ejection fraction. The aim of this review was to focus on the therapeutic target of HFpEF, the role of new drugs and the potential role of new devices to manage the syndrome.

Exercise intolerance in heart failure with preserved ejection fraction: Causes, consequences and the journey towards a cure

Heart failure with preserved ejection fraction (HFpEF) accounts for over 50% of all heart failure cases nationwide and continues to rise in its prevalence. The complex, multi-organ involvement of the HFpEF clinical syndrome requires clinicians and investigators to adopt an integrative approach that considers the contribution of both cardiac and non-cardiac function to HFpEF pathophysiology. Thus, this symposium review outlines the key points from presentations covering the contributions of disease-related changes in cardiac function, arterial stiffness, peripheral vascular function, and oxygen delivery and utilization to exercise tolerance in patients with HFpEF. While many aspects of HFpEF pathophysiology remain poorly understood, there is accumulating evidence for a decline in vascular health in this patient group that may be remediable through pharmacological and lifestyle interventions and could improve outcomes and clinical status in this ever-growing patient population.

HFpEF and sex: understanding the role of sex differences

Heart failure is a complex clinical syndrome with many etiological factors and complex pathophysiology affecting millions worldwide. Males and females can have distinct clinical presentation and prognosis, and there is an emerging understanding of the factors that highlight the similarities and differences to synthesize and present available data for sex-specific differences in heart failure with preserved ejection fraction (HFpEF). While the majority of data demonstrate more similarities than differences between females and males in terms of heart failure, there are key differences. Data showed that females have a higher risk of developing HFpEF, but a lower risk of mortality and hospitalization. This can be conditioned by different profiles of comorbidities, postmenopausal changes in sex hormone levels, higher levels of inflammation and chronic microvascular dysfunction in females. These factors, combined with different left ventricular dimensions and function, which are more pronounced with age, lead to a higher prevalence of LV diastolic dysfunction at rest and exercise. As a result, females have lower exercise capacity and quality of life when compared to males. Females also have different activities of systems responsible for drug transformation, leading to different efficacy of drugs as well as higher risk of adverse drug reactions. These data prove the necessity for creating sex-specific risk stratification scales and treatment plans.

Novel Strategies in Diagnosing Heart Failure with Preserved Ejection Fraction: A Comprehensive Literature Review

Heart failure (HF) with preserved ejection fraction (HFpEF) is a prevalent global condition affecting approximately 50% of the HF population. With the aging of the worldwide population, its incidence and prevalence are expected to rise even further. Unfortunately, until recently, no effective medications were available to reduce the high mortality and hospitalization rates associated with HFpEF, making it a significant unmet need in cardiovascular medicine. Although HFpEF is commonly defined as HF with normal ejection fraction and elevated left ventricular filling pressure, performing invasive hemodynamic assessments on every individual suspected of having HFpEF is neither feasible nor practical. Consequently, several clinical criteria and diagnostic tools have been proposed to aid in diagnosing HFpEF. Overall, these criteria and tools are designed to assist healthcare professionals in identifying and evaluating patients who may have HFpEF based on a combination of signs, symptoms, biomarkers, and non-invasive imaging findings. By employing these non-invasive diagnostic approaches, clinicians can make informed decisions regarding the best pharmacological and rehabilitation strategies for individuals with suspected HFpEF. This literature review aims to provide an overview of all currently available methods for diagnosing and monitoring this disabling condition.

The PACIFIC ontology for heterogeneous data management in cardiology

With the emergence of health data warehouses and major initiatives to collect and analyze multi-modal and multisource data, data organization becomes central. In the PACIFIC-PRESERVED (PhenomApping, ClassIFication, and Innovation for Cardiac Dysfunction - Heart Failure with PRESERVED LVEF Study, NCT04189029) study, a data driven research project aiming at redefining and profiling the Heart Failure with preserved Ejection Fraction (HFpEF), an ontology was developed by different data experts in cardiology to enable better data management in a complex study context (multisource, multiformat, multimodality, multipartners). The PACIFIC ontology provides a cardiac data management framework for the phenomapping of patients. It was built upon the BMS-LM (Biomedical Study -Lifecycle Management) core ontology and framework, proposed in a previous work to ensure data organization and provenance throughout the study lifecycle (specification, acquisition, analysis, publication). The BMS-LM design pattern was applied to the PACIFIC multisource variables. In addition, data was structured using a subset of MeSH headings for diseases, technical procedures, or biological processes, and using the Uberon ontology anatomical entities. A total of 1372 variables were organized and enriched with annotations and description from existing ontologies and taxonomies such as LOINC to enable later semantic interoperability. Both, data structuring using the BMS-LM framework, and its mapping with published standards, foster interoperability of multimodal cardiac phenomapping datasets.

Insights into the Interaction of Heart Failure with Preserved Ejection Fraction and Sleep-Disordered Breathing

Heart failure with preserved ejection fraction (HFpEF) is emerging as a widespread disease with global socioeconomic impact. Patients with HFpEF show a dramatically increased morbidity and mortality, and, unfortunately, specific treatment options are limited. This is due to the various etiologies that promote HFpEF development. Indeed, cluster analyses with common HFpEF comorbidities revealed the existence of several HFpEF phenotypes. One especially frequent, yet underappreciated, comorbidity is sleep-disordered breathing (SDB), which is closely intertwined with the development and progression of the "obese HFpEF phenotype". The following review article aims to provide an overview of the common HFpEF etiologies and phenotypes, especially in the context of SDB. As general HFpEF therapies are often not successful, patient- and phenotype-individualized therapeutic strategies are warranted. Therefore, for the "obese HFpEF phenotype", a better understanding of the mechanistic parallels between both HFpEF and SDB is required, which may help to identify potential phenotype-individualized therapeutic strategies. Novel technologies like single-cell transcriptomics or CRISPR-Cas9 gene editing further broaden the groundwork for deeper insights into pathomechanisms and precision medicine.

Empagliflozin induces the transcriptional program for nutrient homeostasis in skeletal muscle in normal mice

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) improve heart failure (HF) outcomes across a range of patient characteristics. A hypothesis that SGLT2i induce metabolic change similar to fasting has recently been proposed to explain their profound clinical benefits. However, it remains unclear whether SGLT2i primarily induce this change in physiological settings. Here, we demonstrate that empagliflozin administration under ad libitum feeding did not cause weight loss but did increase transcripts of the key nutrient sensors, AMP-activated protein kinase and nicotinamide phosphoribosyltransferase, and the master regulator of mitochondrial gene expression, PGC-1α, in quadriceps muscle in healthy mice. Expression of these genes correlated with that of PPARα and PPARδ target genes related to mitochondrial metabolism and oxidative stress response, and also correlated with serum ketone body β-hydroxybutyrate. These results were not observed in the heart. Collectively, this study revealed that empagliflozin activates transcriptional programs critical for sensing and adaptation to nutrient availability intrinsic to skeletal muscle rather than the heart even in normocaloric condition. As activation of PGC-1α is sufficient for metabolic switch from fatigable, glycolytic metabolism toward fatigue-resistant, oxidative mechanism in skeletal muscle myofibers, our findings may partly explain the improvement of exercise tolerance in patients with HF receiving empagliflozin.

Recent successes in heart failure treatment

Remarkable recent advances have revolutionized the field of heart failure. Survival has improved among individuals with heart failure and a reduced ejection fraction and for the first time, new therapies have been shown to improve outcomes across the entire ejection fraction spectrum of heart failure. Great strides have been taken in the treatment of specific cardiomyopathies such as cardiac amyloidosis and hypertrophic cardiomyopathy, whereby conditions once considered incurable can now be effectively managed with novel genetic and molecular approaches. Yet there remain substantial residual unmet needs in heart failure. The translation of successful clinical trials to improved patient outcomes is limited by large gaps in implementation of care, widespread lack of disease awareness and poor understanding of the socioeconomic determinants of outcomes and how to address disparities. Ongoing clinical trials, advances in phenotype segmentation for precision medicine and the rise in technology solutions all offer hope for the future.

The non-steroidal mineralocorticoid receptor antagonist finerenone and heart failure with preserved ejection fraction

Finerenone is a novel non-steroidal mineralocorticoid receptor (MR) antagonist (MRA) with high binding affinity, high MR selectivity and a short plasma half-life. In two major endpoint-driven clinical trials in patients with chronic kidney disease and type 2 diabetes mellitus (FIDELIO-DKD and FIGARO-DKD), finerenone induced significant cardiorenal protective actions, and has been recently approved for treatment of these patients. Heart failure with preserved ejection fraction (HFpEF) is a devastating clinical syndrome with increasing prevalence and poor prognosis. Pharmacological therapy of HFpEF is very limited and new therapeutic options are urgently needed. Finerenone has been shown to improve multiple pathophysiological parameters of HFpEF in preclinical models. In consonance, pre-specified subgroup analyses of FIDELIO-DKD and FIGARO-DKD suggested a potential beneficial effect of finerenone in HFpEF. This review will discuss the pharmacodynamic and -kinetic profile of finerenone. We will provide a general overview over the complex pathophysiology of HFpEF and data from pre-clinical studies, focusing on how finerenone improves multiple components of this pathophysiology. Finally, we will discuss current and future clinical trials with finerenone in heart failure patients focusing on HFpEF.

Heart Failure With Preserved Ejection Fraction: JACC Scientific Statement

The incidence and prevalence of heart failure with preserved ejection fraction (HFpEF) continue to rise in tandem with the increasing age and burdens of obesity, sedentariness, and cardiometabolic disorders. Despite recent advances in the understanding of its pathophysiological effects on the heart, lungs, and extracardiac tissues, and introduction of new, easily implemented approaches to diagnosis, HFpEF remains under-recognized in everyday practice. This under-recognition presents an even greater concern given the recent identification of highly effective pharmacologic-based and lifestyle-based treatments that can improve clinical status and reduce morbidity and mortality. HFpEF is a heterogenous syndrome and recent studies have suggested an important role for careful, pathophysiological-based phenotyping to improve patient characterization and to better individualize treatment. In this JACC Scientific Statement, we provide an in-depth and updated examination of the epidemiology, pathophysiology, diagnosis, and treatment of HFpEF.

Deep Learning for Echocardiography: Introduction for Clinicians and Future Vision: State-of-the-Art Review

Exponential growth in data storage and computational power is rapidly narrowing the gap between translating findings from advanced clinical informatics into cardiovascular clinical practice. Specifically, cardiovascular imaging has the distinct advantage in providing a great quantity of data for potentially rich insights, but nuanced interpretation requires a high-level skillset that few individuals possess. A subset of machine learning, deep learning (DL), is a modality that has shown promise, particularly in the areas of image recognition, computer vision, and video classification. Due to a low signal-to-noise ratio, echocardiographic data tend to be challenging to classify; however, utilization of robust DL architectures may help clinicians and researchers automate conventional human tasks and catalyze the extraction of clinically useful data from the petabytes of collected imaging data. The promise is extending far and beyond towards a contactless echocardiographic exam-a dream that is much needed in this time of uncertainty and social distancing brought on by a stunning pandemic culture. In the current review, we discuss state-of-the-art DL techniques and architectures that can be used for image and video classification, and future directions in echocardiographic research in the current era.