HFpEF-any: Human Single-Nuclear Transcriptomics Challenging the Translational Validity of Current HFpEF Model

Heart failure can, at its broadest level, be divided into 2 major groups: the classic form, heart failure with reduced ejection fraction (HFrEF), and heart failure with preserved ejection fraction (HFpEF).¹ In both subsets, patients experience hallmark symptoms, such as exertional dyspnea, fatigue, edema, and exercise intolerance.¹ As its name suggests, HFrEF is defined by a decreased ejection fraction (≤40%), whereas HFpEF presents with a normal ejection fraction (≥50%) but impaired ventricular filling due to increased myocardial stiffness.¹ Although HFrEF is often considered the traditional form of heart failure, HFpEF is now the most common subtype worldwide.¹ It primarily affects geriatric adults, women, and individuals with concurrent cardiometabolic conditions, such as hypertension, obesity, diabetes, and chronic kidney disease.¹ Despite its high prevalence, HFpEF can be difficult to diagnose and treat, often resulting in poor outcomes. HFpEF is also highly heterogeneous, with wide variation across patients in underlying pathophysiology, associated comorbidities, and cardiac remodeling patterns.^1,2 Therapeutic development has also been limited and is the source of some controversy. Although newer pharmacotherapeutic agents, such as SGLT2 (sodium-glucose co-transporter 2) inhibitors, have shown modest benefit in HFpEF clinical trials, traditional heart failure therapies, including β-blockers, have produced inconsistent—and in some cases potentially unfavorable—results in this population.^1,2 Extrapolating HFrEF therapies to HFpEF is not working. Yet, it remains unclear why such therapies work in HFrEF but not in HFpEF, and why SGLT2 inhibitors work in both populations despite having no mortality benefit in HFpEF, thus underscoring the need for more knowledge in this area.

Difficult limitations also hinder progress in understanding HFpEF in basic and translational research design. Notably, approximately half of the existing rodent models labeled as HFpEF lack sufficient evidence to meet clinical diagnostic criteria for HFpEF.^1,3 Furthermore, most of these models induce a HFpEF phenotype using a single stressor^1,3 or use stressors that humans do not experience or experience through different processes.^4,5 Although convenient in the realm of translational science to minimize the effects of confounding variables, this inevitably fails to capture the chronic, multimorbid nature of HFpEF in humans.^1,2 Another hurdle in creating faithful translational models is the inability of animals to replicate key symptoms of heart failure, such as breathlessness, which makes it difficult to assess the extent of translational fidelity.¹ Finally, the underrepresentation of key populations in clinical research of HFpEF disease profiles, progression, and treatment, particularly women and racial and ethnic minorities, presents a huge shortcoming, as these groups are some of those most affected by HFpEF.⁶ Collectively, these challenges highlight the need for improved preclinical validation and more inclusive clinical studies across diverse patient populations. Because of these issues, therapeutic development has been hindered by a lack of knowledge of the mechanisms underlying HFpEF and a limited understanding of the cellular-level changes that occur in HFpEF (Figure).

Figure. Current Clinical-Translational Research Challenges Faced in the HFpEF Field.

This schematic highlights the diverse clinical populations affected by HFpEF and the comorbidities that contribute (left side), as well as the current clinical and research challenges in advancing knowledge and treatments for HFpEF patients (right side). With several different populations of people, including elderly and female patients, and several different comorbidities contributing, including obesity, hypertension, diabetes, chronic kidney disease, and atrial fibrillation, it is clear that different HFpEF subtypes exist, which are likely due to divergent underlying mechanistic changes. Research and treatment challenges have arisen due to this obvious disease heterogeneity, a lack of realistic pre-clinical models that reflect clinical disease, and a lack of diversity in participant recruitment into clinical studies, resulting in limited effective treatments.

In this issue of Circulation Research, Hahn et al⁷ have taken key steps to tease apart the molecular basis of human HFpEF using single-nuclear RNA sequencing in human endomyocardial biopsies, creating an atlas of key changes in the transcriptional landscape of HFpEF. The execution of studies of this nature has proven to be a major bottleneck in the field due to limited access to large quantities of high-quality human cardiac tissue. Although this is typically the case with endomyocardial biopsies, which are inherently small, Hahn et al⁷ have successfully applied genotype-based demultiplexing strategies to overcome this hurdle, effectively bypassing the need for larger samples. It is important to note, however, that this strategy pools samples, so it is entirely possible that some key features of HFpEF could still be masked by its use, and the ability to resolve individual patient heterogeneity is lost. This is likely a contributing factor to the small number of HFpEF samples in the study that could not be assigned to specific genotype clusters. In addition, further studies will be required to overcome the baseline differences in the control and HFpEF groups studied because, currently, the control group is predominantly composed of White and Hispanic populations, and the HFpEF group is primarily composed of Black populations, which could miss important demographic-based changes in the transcriptional signatures related to each group in the context of HFpEF. Despite these methodological and demographic-related issues, this study marks a major step forward in our cellular-based understanding of HFpEF, which has been beyond the reach of prior studies.

In addition to this methodological advancement, this study marks a major scientific turning point in our understanding of the factors that may contribute to changes in myocardial compliance and stiffness, as documented in other HFpEF cohorts. Hahn et al⁷ identified not only key transcriptional signatures related to immune activation, cardiomyocyte metabolism, and protein quality control, but also the distinct lack of signatures associated with activated fibroblast populations. These findings provide a significant advancement over previously published bulk RNA-sequencing–based studies from the same authors,⁸ which did not identify signatures of immune activation due to issues with capturing low-abundant cell types, whereas the present study was able to discern key signatures, including transcriptional changes in T-cell and macrophage populations.⁷ This suggests that bulk RNA-sequencing should be used and interpreted with caution, especially when an inflammatory contribution is likely, because key differences could be masked or missed entirely. The present studies also identified that not only do both cardiomyocytes and fibroblasts in the HFpEF heart exhibit the largest numbers of differentially expressed genes compared with other cell types, but many of these transcripts were not identified in previous studies using bulk sequencing,⁸ yet another cautionary tale when it comes to the use of global omics approaches to study diseases with significant cell-based changes, such as HFpEF. Although activated fibroblast populations were absent in the present studies, changes in genes that support fibrosis were observed.⁷ Previous studies from the same group using the same population have shown that cardiac fibrosis was evident in close to 90% of the patient samples assayed,⁹ suggesting that the fibroblasts in these present samples are past their initial activation stage, or they possess unique signatures when compared with HFrEF models. The activation of fibrotic signaling and the resultant accumulation of collagen in HFpEF are also consistent with the findings from several animal models,^4,5 which are thought to contribute to myocardial stiffness and perturbations in diastolic function. The present study also compared signatures of control and HFpEF patients with those of patients with dilated cardiomyopathy. These signatures identified by Hahn et al⁷ suggest that HFpEF involves many distinct transcriptional changes from those observed in dilated cardiomyopathy, including significant transcriptional differences between fibroblast populations, suggesting that HFpEF can not be considered or treated as a mild form of dilated cardiomyopathy.¹⁰

Although additional studies are needed to increase the diversity of the populations examined and increase the sample sizes of the present studies, these studies clearly challenge our understanding of the cellular changes that contribute to HFpEF. Hahn et al⁷ identified several novel transcriptional targets in the present study, including PLPP3, PTRDD, and MAP2K6, that could play significant roles in HFpEF pathogenesis. Although studies have not examined either PTRDD or MAP2K6 in the context of diastolic dysfunction and HFpEF, studies do suggest that changes in the protein product of PLPP3, may regulate diastolic function, albeit in a rodent high-fat diet model.¹¹ Key next steps for Hahn et al⁷ should be to more deeply examine these novel targets to determine their contributions to the pathogenesis of HFpEF. The implication that transcriptional dysregulation is multicellular in origin not only requires the field to examine HFpEF pathogenesis through a different lens but also calls for the reconsideration of therapies in the setting of HFpEF, which may not target the key drivers of pathology if multicellular and multiprocess-based in nature.

Although the present study reflects a major advancement in defining cell-based changes in HFpEF, several considerations and questions remain. Given the relatively small sample size, it remains unclear whether the documented changes in immune, metabolic, and protein quality control transcripts reflect the true diversity of the HFpEF population. This is especially important given the number of different HFpEF subtypes that have been defined,² and based on this, it is clear that additional studies are needed to define the transcriptional landscape of each subtype and determine subtype-specific drivers to enable personalized treatments. Related to this is the need to understand HFpEF at a system-wide level because it is clear that HFpEF extends well beyond the confines of the heart, involving changes in the liver, kidney, and skeletal muscle.^2,12,13 Notably, some of the currently published rodent studies in the HFpEF field that have taken a system-wide approach have identified significant metabolic changes,¹⁴ directly supporting some of the metabolic signatures described by Hahn et al,⁷ albeit with some of the identified targets divergent. Despite this, future mechanistic validation of the identified targets will provide additional insights and enable targeted approaches. This validation should consider whether the documented changes in the cardiac transcriptome in the present study could be indirectly affected by noncardiac contributions to HFpEF and, on a larger scale, consider the system-wide impacts. In addition, although women were included in these analyses,⁷ information on femalespecific risk factors, such as pregnancy and menopause, was not available. Because of the documented associations between cardiovascular pregnancy complications and the development of HFpEF,¹⁵ it will be important moving forward to not only study the underlying cell based changes that give rise to this increased risk in women, but also ensure the collection of this information at both clinical assessment and sample collection.

In summary, although remaining questions need to be addressed before we have a more complete understanding of the molecular and cellular drivers of HFpEF and can provide effective, personalized treatments, these studies have identified distinct HFpEF signatures and a list of candidate targets that the field can assess in future studies. Clearly, moving from transcriptional associations to causal drivers will be challenging, further complicated by the lack of appropriate animal models in which candidate targets can be examined, creating a barrier to clinical evaluation (Figure). Despite this, the present studies mark the beginnings of a well-mapped cell-based trajectory of HFpEF, which already exists in HFrEF, that the field will need to effectively examine and target moving forward.