Clinical Phenotypes of Heart Failure With Preserved Ejection Fraction to Select Preclinical Animal Models

Willem B. van Ham, Elise L. Kessler, Marish I.F.J. Oerlemans, M. Louis Handoko, Joost P.G. Sluijter, Toon A.B. van Veen, Hester M. den Ruijter, and Saskia C.A. de Jager

Published: August 2022


At least one-half of the growing heart failure population consists of heart failure with preserved ejection fraction (HFpEF). The limited therapeutic options, the complexity of the syndrome, and many related comorbidities emphasize the need for adequate experimental animal models to study the etiology of HFpEF, as well as its comorbidities and pathophysiological changes. The strengths and weaknesses of available animal models have been reviewed extensively with the general consensus that a “1-size-fits-all” model does not exist, because no uniform HFpEF patient exists. In fact, HFpEF patients have been categorized into HFpEF phenogroups based on comorbidities and symptoms. In this review, we therefore study which animal model is best suited to study the different phenogroups—to improve model selection and refinement of animal research. Based on the published data, we extrapolated human HFpEF phenogroups into 3 animal phenogroups (containing small and large animals) based on reports and definitions of the authors: animal models with high (cardiac) age (phenogroup aging); animal models focusing on hypertension and kidney dysfunction (phenogroup hypertension/kidney failure); and models with hypertension, obesity, and type 2 diabetes mellitus (phenogroup cardiometabolic syndrome). We subsequently evaluated characteristics of HFpEF, such as left ventricular diastolic dysfunction parameters, systemic inflammation, cardiac fibrosis, and sex-specificity in the different models. Finally, we scored these parameters concluded how to best apply these models. Based on our findings, we propose an easy-to-use classification for future animal research based on clinical phenogroups of interest.

Full Access Link: JACC: Basic to Translational Science