Key result
Proposed biological framework addresses pathophysiological heterogeneity to personalize HFpEF diagnosis and treatment.
Why the study?
HFpEF risk and disease course reflect a variable interplay of pathophysiological processes in each individual, requiring a biologically plausible framework to guide a more personalised approach.
Cohort (n=902)
Advanced data science techniques can map continuous phenotypic and genetic variation in HFpEF, identifying distinct pathophysiological profiles with differing clinical outcomes to guide personalized management.
Supports personalised HFpEF care; extends understanding of its heterogeneous pathophysiology.
AIMS: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome commonly hypothesised to comprise discrete subtypes. This study aimed to characterise HFpEF heterogeneity using advanced data science techniques applied to deeply phenotyped, multi-modal cohorts. METHODS AND RESULTS: 902 patients with HF and a left ventricular ejection fraction ≥ 50% were prospectively recruited and underwent detailed clinical, imaging, and genetic profiling. Clustering algorithms were first applied to derive discrete subgroups. To overcome rigid subgroup assignment, DDRTree was applied to map continuous phenotypic and outcome variation onto a two-dimensional tree. Genome-wide association studies (GWAS) identified variants associated with tree dimensions. Internal validation assessed stability, and external validation was conducted in a UK Biobank HFpEF cohort (n=148). Sensitivity analyses included patients with mildly reduced ejection fraction (n=1154). Logistic regression compared HFpEF with comorbidity-matched controls (n=902). Whilst conventional clustering did not identify meaningful subgroups, DDRTree revealed a stable, interpretable tree structure, capturing continuous variation in cardiac structure and function, biomarkers and comorbidities. Over a median follow-up of 6.8 years, phenotypic complexes demonstrated differing risks of cardiovascular death, HF hospitalisation, adverse renal outcome, and infection hospitalisation. GWAS revealed a locus near CRACD associated with tree dimension one. Findings were reproducible in external and sensitivity analyses. A profile of cardiac and systemic characteristics that distinguish HFpEF from its associated comorbidities were identified. CONCLUSIONS: HFpEF risk and disease course reflect a variable interplay of pathophysiological processes in each individual. This study provides a biologically plausible framework to guide a more personalised approach to HFpEF.
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Soltani et al. (2026) conducted a cohort in Heart failure with preserved ejection fraction (HFpEF) (n=902). Phenotypic complexes derived via DDRTree vs. Comorbidity-matched controls was evaluated on Cardiovascular death, HF hospitalisation, adverse renal outcome, and infection hospitalisation. Over a median follow-up of 6.8 years, phenotypic complexes derived via DDRTree demonstrated differing risks of cardiovascular death, HF hospitalization, adverse renal outcomes, and infection.
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