Heart failure (HF) is a complex clinical syndrome characterized by symptoms and signs caused by abnormal cardiac function and/or structure that leads to decreased cardiac output and/or increased intracardiac pressures.

HF patients can have different phenotypes according to morphofunctional characteristics of the disease, and receive different therapeutic approaches.14^,15 Based on this, patients are usually classified into patients with HF with reduced ejection fraction (HFrEF), marked by left ventricular ejection fraction (LVEF) lower than 40% - and HF with preserved ejection fraction (HFpEF), characterized by LVEF greater than 50%. Recently, the European Society of Cardiology has proposed a new phenotype - “HF with midrange ejection fraction” - with intermediate ejection fraction (LVEF between 40 and 49%) and a clinical profile different from HFeEF and HFpEF.16

The main diagnostic criteria of HFPEF - the focus of this study - are the clinical profile of LVEF equal to or greater than 50%, increased levels of brain natriuretic peptide (BNP) (greater than 35pg/mL or NT-proBNP greater than 125 pg/mL) and at least one of these two criteria - important structural cardiac disease (left ventricular hypertrophy and/or increased left atrium) and diastolic dysfunction.16

HFPEF is characterized by reduced end-diastolic volume, left ventricular hypertrophy, and increased left atrial volume and left ventricular filling pressure. These pathophysiological abnormalities are associated with increased left ventricular stiffness, decreased left ventricular relaxation, cardiomyocyte hypertrophy, myocardial interstitial fibrosis and reduced intramyocardial capillaries.17^-19 In addition, a proportion of patients with HFpEF present atrial fibrillation, which further aggravates cardiac function.20

The classical presentations - HFeEF and HFpEF - used to be distinguished only by the remodeling pattern of cardiac chambers and extension of myocardial dysfunction, culminating in different therapeutic responses. However, it is known today that morphofunctional changes are also based on molecular alterations, which are also different between these conditions.10

Left ventricular diastolic dysfunction, an important diagnostic criterion for HFPEF, may be explained by increased myocardial stiffness, resulting from changes in extracellular matrix and/or cardiomyocytes.10 There are evidence that extracellular matrix stiffness results mainly from collagen metabolism. Excess deposition of type I collagen, the subtype with the highest stiffness property, is explained by increased synthesis and/or decreased degradation of this compound. Type I collagen synthesis can be measured by procollagen type I carboxy-terminal propeptide, which derives from type I procollagen and acts as a biomarker. Decreased degradation of type I collagen is caused by downregulation of matrix metalloproteinases (MMPs) and/or upregulation of tissue inhibitors of metalloproteinases (TIMPs). TIMP-1 plasma levels have also been suggested as promising biomarkers in HFPEF.9^,10

Excess collagen is found in only one third of patients with HFPEF, even in the presence of ventricular stiffness, which usually results from an intrinsic cardiomyocyte condition, and may be related to the protein structure and/or to the disruption of the sarcomere structure.9^,10

Cardiomyocyte structure depends directly on regulation of constituent proteins, and myocardial stiffness may indicate an unbalance in this process. One of the main proteins involved in this regulation is titin, an elastic constituent protein of cardiomyocytes, with two isoforms - N2B (stiffer) and N2BA (more compliant). Changes in the ratio of one isoform to the other and phosphorylation of the fibers, as well as oxidative stress can have an impact on myocardial compliance, leading to stiffness.9^,18

Disruption of sarcomere structure is the mechanical factor of ventricular relaxation. It is an energy-consuming reaction, and, for this reason, the lack of energy stores impairs a normal left ventricular relaxation. Recent studies have demonstrated a decreased phosphate creatinine/adenosine ratio in patients with HFPEF, which is consistent with a decline in myocardial energy store.21^-23

In addition to interstitial (collagen-related changes) and structural (regulation of constituent proteins) changes, unbalanced levels of chemical mediators, especially of monophosphate cyclic guanine (cGMP), may also explain myocardial stiffness in HEPEF. Activation of protein kinase G (PKG) by cGMP results in phosphorylation cascade of proteins important for cardiomyocyte integrity - phosphorylation of titins inhibits cardiac hypertrophy and increases myocardial compliance, phosphorylation of potassium channels inhibits tissue ischemia, and phosphorylation of troponin I increases left ventricular relaxation. Also, PKG activation by cGMP increases calcium reuptake by sarcoplasmic reticulum.9

Low BNP, microvascular inflammation and oxidative stress, which are common in several conditions, such as obesity and insulin resistance, suppresses GMPc synthesis pathways. This, in turn, inhibits PKG phosphorylation cascade and culminates in myocardial stiffness, characteristic of HFPEF.8^,9

Although HFPEF is commonly referred as diastolic HF, the disease is not limited to ventricular relaxation problems. A study24 demonstrated that myocardial contractility may be decreased in HFPEF, even if the end-systolic elastance (ESE) - used to measure myocardial contractility - is increased.24 This apparent contradiction may be explained by the influence of cardiac chamber geometry on ESE. Concentric hypertrophy, characteristic of HFPEF, independently increases ESE, even with reduced left ventricular contractility.21

In HFPEF, vascular stiffness is generalized, resulting in elevated pressure, which aggravates ventricular stiffness and attenuates vascular dilation in exercise, thereby decreasing blood supply to musculoskeletal system. Increased vessel stiffness, associated with elevated left heart pressure, increases pulmonary pressure and consequently the mortality of these patients.21

Defects in diastolic, systolic, vascular and chronothropic functions elucidate the heterogeneous nature and complexity of HFPEF. Its multiple pathophysiological factors indicate the need of phenotyping of these patients, and identification of specific causes of the worsening of each phenotype. This strategy has become increasingly possible with biomolecular advances in medicine and will possibly guide therapeutic decisions based on specific pathophysiological changes.

Epigenetics is an emerging science involving the study of changes in the regulation of genes and their expression, regardless of their sequences. Environmental factors can affect intracellular signaling pathways in a way that can affect chromatin structure, resulting in the passage of altered gene expression patterns to the offspring by epigenetic memory, affecting the phenotypes of the diseases.25^,26

New evidence suggests the involvement of epigenetic regulation in target cells related to cardiovascular pathogenesis, including HF and its different phenotypes.27 Cardiomyocytes, for example, can adapt to environmental stress by epigenetic regulation. This dysregulation in genetic expression provides information about the pathogenesis of cardiac and vascular remodeling, dysfunction of progenitor cells and endogenous repair system, inflammation, fibrosis and cardiac dysfunction.28^,29

Four epigenetic mechanisms in cardiovascular diseases have been identified - DNA methylation, chromatin remodeling by adenosine triphosphate (ATP)-dependent enzymes, histone modification and microRNA-dependent mechanisms.30^-32 Recent findings have associated these mechanisms with HFPEF-related diseases; however, evidence on the role of epigenetics in changes in cardiac function and structure, and clinical trials corroborating theories involving both epigenetics and cardiovascular disease are still lacking. Advances in studies on this field should contribute to HF prevention and provide enough evidence for the stratification of HF phenotypes.

Current phenotyping tools combined with advances in genetics and systems biology have the potential to improve the classification of complex, heterogeneous systems, such as HFPEF. Analysis of patients’ data aiming to establish a pattern of these variables may be performed by machine learning algorithms. Machine learning is a field of artificial intelligence, in which a computer is programmed to learn the relationship between the objects of study by data processing and accumulate experience with previous problem-solving approaches. Machine learning algorithms are classified into supervised and unsupervised. While supervised learning is focused on outcome prevention, unsupervised learning aims to infer intrinsic structures of the data.

Therefore, in this approach, a large volume of data can be analyzed and mutually exclusive categories of HFPEF can be obtained by phenotype mapping of the syndrome and grouping of patients in subgroups according to phenotypic characteristics. Phenotypic classification of patients with HFPEF would be helpful to the development of clinical trials on therapeutic strategies specific to each phenotypic profile.12

A recent study was the first to identify phenogroups of a heart disease, and the first to use the machine learning technique as an approach to solve the heterogeneity of a cardiovascular syndrome by phenotype analysis.33

The data analyzed for patients’ classification using the machine learning approach included clinical variables, physical features, laboratory data and electrocardiogram and echocardiogram parameters.

Although the patients shared many clinical characteristics, they were classified in three subgroups with distinct characteristics and prognosis:33

In addition, different phenogroups had different clinical course and outcomes, and distinct risk stratification. Prognosis was divided into the following categories: death, hospitalization for non-cardiac causes, hospitalization for cardiac causes, and hospitalization for HF. In group 1, the most frequent prognostic factors were hospitalization for cardiovascular and hospitalization for non-cardiovascular diseases; in group 2, hospitalization for non-cardiovascular causes and HF, and in group 3, the most prevalent outcome was death, followed by hospitalization for HF.33

However, although ideally the subgroups should be mutually excluding, some patients had overlapping clinical features, especially in the analysis of group 1 patients (Figure 1). Even so, this was a pioneer study in the phenotyping of complex cardiovascular syndromes.33

Figure 1

In light of the above, one may infer that the use of the machine learning tool in international centers would provide new, essential information on HFPEF epidemiology.

Considering that this study was conducted in a North American setting,33 it is expected that results observed in the subgroups are different from those in South America. Therefore, application of the technique in Latin American prevalence studies is paramount for future phenotype mapping of HFPEF in Brazil.

Classical therapeutic approach of HFPEF has not reduced mortality and morbidity rates of these patients. Thus, considerable differences between the phenogroups indicate the importance of a specific therapeutic approach, since advances in therapies have been so far hampered by such phenotypic complexity. To deal with that, new therapies that have a direct effect on signaling cascades involved in the pathophysiology of the HFPEF have been proposed.34^,35 Today, these therapies varied from signaling pathways of systemic inflammation to myocardial elasticity, and additional therapies to different comorbidities associated with the same pattern of phenotypic predisposition to the disease.

Aging, obesity, systemic hypertension, type 2 diabetes mellitus, kidney failure, and sleep apnea can trigger a chronic systemic inflammation that affects the myocardium and other organs. The patient may have pulmonary hypertension, sodium retention and impaired oxygen extraction by skeletal muscles.

For patients with pulmonary congestion or metabolic risk, it is recommended the use of diuretics, statins, organic nitrites /nitrates, energy-intake restriction, stimulants of PKG pathway, and extracellular matrix-stimulating agents, like spironolactone.

For hypertension phenotype, anti-hypertensive are the most recommended treatment, such as angiotensin converting enzyme (ACE) inhibitors, angiotensin II receptor blockers and calcium channel blockers, highlighting the importance of this treatment to HF prevention, to vascular conditions not related to HF (such as stroke and myocardial infarction) and to improve the quality of life of HFPEF patients. The CHARM-Preserved, PEP-CHF and TOPCAT studies demonstrated a reduction in hospitalization rates of patients with HFPEF by blockage of the renin-angiotensin-aldosterone system. These studies used, respectively, an angiotensin II receptor blocker, ACE inhibitors and an aldosterone antagonist (spironolactone).36^-38 Inhibition of the renin-angiotensin-aldosterone system would be of benefit to the patients due to the association of neurohormonal activation with hypertension and volume retention.39^,40

Control of heart rate is mediated by activation of the sympathetic system, which has a direct effect on adverse outcomes in patients with HFPEF. A study derived from the I-Preserve study showed an association between increased heart rate and higher incidence of death for cardiovascular causes and hospitalizations in patients in sinus rhythm.41 Therefore, heart rate control would be an effective treatment target.

In patients with pulmonary hypertension, the use of dobutamine improved pulmonary vascular function, and studies on new pulmonary vasodilators targeting GMPc, endothelin and nitric oxide (NO)32 have also been developed (Table 1). In patients with kidney dysfunction, sildenafil had no significant effects in the RELAX clinical trial.42 Due to the high prevalence of patients with HFPEF and pulmonary hypertension, and its intrinsic relationship with morbidity and mortality, pulmonary vasodilation is paramount in the treatment of these patients.43

Based on the studies reviewed, we conclude that phenotype mapping in HFPEF has enabled the development of a new generation of clinical trials aimed at new therapeutic approaches (Figure 2).

Figure 2

HFPEF accounts for nearly half of HF patients on treatment and its prevalence has increased. Cardiovascular disease phenotypes are complex, with many influencing factors. Systemic inflammatory reaction and microvascular endothelial dysfunction lead to ventricular remodeling and dysfunction. Specific therapeutic interventions should be multifaceted and focused on stages of these signaling cascades. New therapeutic approaches should encompass metabolic control, modulation of inflammatory response, control of pulmonary hypertension, prevention of muscle weakness, and reduction of sodium and water retention. Due to the wide range of interventions, phenotype mapping becomes an essential tool for future investigations and clinical trials (to confirm the results). Possibly, there will be more significant changes as new genetic, cellular, molecular and immunologic biomarkers are incorporated and used to discriminate treatment groups in a clear and objective manner.

The term “phenocopies” was first used in the study of hypertrophic cardiomyopathies, in which a subgroup of diseases was found to mimic their phenotypic features. We found that this concept may be extended to HFPEF. Due to the heterogeneity nature of HFPEF, other diseases may have the same clinical phenotype and thereby be considered their “phenocopies”. Although both therapeutic intervention and prognosis of the diseases are different, their similar clinical presentation hampers the differential diagnosis. One pertinent example of a disease that mimics the clinical pattern of HFPEF is cardiac amyloidosis.44^,45

Cardiac amyloidosis is a restrictive cardiomyopathy, regardless of its type, characterized by progressive diastolic dysfunction followed by systolic dysfunction and arrhythmia. It may be first identified as exercise intolerance or HF. The diagnosis of cardiac amyloidosis is usually established in the late stages of the disease, since the disease affects the same elderly population affected by HFPEF. However, the exact contribution of amyloidosis to HFPEF has not been elucidated. Protein accumulation leads to asymptomatic left ventricular hypertrophy, with late diagnosis due to its gradual progression. Nevertheless, it is worth pointing out that individuals with HFPEF usually have other comorbidities that independently contribute to diastolic dysfunction.46^-48

In addition to cardiac amyloidosis, “phenocopies” include other diseases such as hypertrophic cardiomyopathy, cirrhotic cardiomyopathy,49 low-flow, low-gradient aortic stenosis, cardiac sarcoidosis and hemochromatosis (Figure 3).

Figure 3

The identification of “phenocopies” in HFPEF may enable an individualized approach to molecular targets and functional abnormalities, such as the use of certain drugs in senile amyloidosis, and betablockers and/or calcium channel antagonists in hypertrophic cardiomyopathy. Besides, the chance of diagnostic errors may decrease and that of early diagnosis of other diseases may increase when the presence of diseases that mimic HFPEF is considered.

The use of the machine learning technique for patients’ grouping by phenotypes allows the analysis of a wide variety of variables and relationship between them, and to classify them in mutually exclusive phenogroups. In addition to allowing a phenotype categorization and to contribute to a therapeutic revolution, the identification of possible “phenocopies” is crucial for the differential diagnosis of a HFPEF model (Figure 4).

Figure 4