Addressing Unmet Needs in Heart Failure with Preserved Ejection Fraction: Multi-Omics Approaches to Therapeutic Discovery

TL;DR

This paper reviews how multi-omics approaches can help discover new therapies for heart failure with preserved ejection fraction, a complex condition with limited treatment options.

Contribution

The paper introduces an integrative systems-biology framework for multi-omics research in HFpEF, emphasizing precision cardiology.

Findings

HFpEF is highly heterogeneous and includes overlapping inflammatory, fibrotic, and cardiometabolic endophenotypes.

Traditional diagnostic strategies have led to neutral outcomes in trials due to incomplete capture of HFpEF complexity.

Multi-omics and AI integration offer new opportunities for biomarker discovery and targeted therapies in HFpEF.

Abstract

Heart failure with preserved ejection fraction (HFpEF) accounts for about half of heart failure cases and is linked to aging, obesity, diabetes, and multimorbidity, yet disease-modifying therapies remain limited. A major barrier is heterogeneity: HFpEF comprises overlapping inflammatory, fibrotic, cardiometabolic, and hemodynamic/vascular endophenotypes embedded within systemic cardiorenal and cardiohepatic cross-talk, which conventional metrics such as left ventricular ejection fraction (LVEF), natriuretic peptides (NPs), and standard imaging capture incompletely. In this narrative review, we synthesize clinical, mechanistic, and trial data to describe HFpEF endophenotypes and their multi-organ interactions; critically appraise why traditional diagnostic and enrollment strategies contributed to neutral outcomes in landmark trials; and survey emerging cardiovascular multi-omics studies. We then outline an integrative systems-biology framework that applies (i) within-layer analyses and cross-layer integration, (ii) network-based driver nomination and biomarker discovery, and (iii) target nomination to link molecular programs with circulating markers and candidate therapies. Finally, we discuss practical challenges in implementing multi-omics HFpEF research and highlight future directions such as artificial intelligence (AI)-enabled multi-omics integration, cross-organ profiling, and biomarker-guided, endotype-enriched platform trials. Collectively, these advances position HFpEF as a proving ground for precision cardiology, in which therapies are matched to molecularly defined disease programs rather than ejection-fraction cutoffs alone.

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