Multimodal data-driven clustering analysis of heart failure patients identifies two distinct patterns of heart failure with preserved ejection fraction: Results from the PACIFIC-PRESERVED study
Heart failure with preserved ejection fraction (HFpEF) accounts for over half of heart failure cases but remains poorly defined due to its clinical heterogeneity. In the prospective PACIFIC-Preserved cohort (NCT04189029, n = 155), we applied multimodal deep phenotyping, including high-throughput proteomics, and unsupervised machine learning to identify biologically distinct HFpEF subgroups. Multiview clustering revealed two major HFpEF phenogroups: PEF1, characterized by inflammatory signaling, TNF receptor activation, cardio-skeletal injury, and greater renal dysfunction; and PEF2, marked by endothelial stress and milder perturbations. Conventional diagnostics alone could not reliably distinguish these subgroups, but a multimodal classifier integrating clinical, imaging, and proteomic variables achieved high predictive accuracy (F1-score 0.87). External validation in the MEDIA-DHF cohort (n = 456) confirmed that PEF1 was independently associated with adverse outcomes (adjusted HR 2.27, 95% CI 1.04–4.94). These findings establish a classifier-driven, biologically informed stratification of HFpEF, providing a framework for precision medicine in heart failure. Heart failure with preserved ejection fraction is clinically heterogeneous, complicating efforts to identify patients at highest risk. Here, the authors show that integrating proteomics with machine learning reveals two biologically distinct subtypes with different prognoses, including a high-risk inflammatory cardiorenal phenotype.
Authors
- Guillaume Jondeau (ORCID: https://orcid.org/0000-0002-0101-2076)
- Mathieu Pernot (ORCID: https://orcid.org/0000-0001-6713-4642)
- Philip Janiak (ORCID: https://orcid.org/0000-0002-7902-2514)
- Nicolas Girerd (ORCID: https://orcid.org/0000-0002-3278-2057)
- Olivier Hanon (ORCID: https://orcid.org/0000-0002-4697-122X)
- Caroline Fraslon
- Andrea Ruiz‐Velasco (ORCID: https://orcid.org/0000-0003-0660-5855)
- Pierre‐Yves Hervé (ORCID: https://orcid.org/0000-0002-5525-1750)
- Frédérique Chézalviel-Guilbert (ORCID: https://orcid.org/0000-0001-9731-4951)
- Philippe Boutinaud (ORCID: https://orcid.org/0000-0003-3662-1119)
- Gilles Soulat (ORCID: https://orcid.org/0000-0003-4165-6113)
- Benoît Tyl (ORCID: https://orcid.org/0000-0001-5297-8412)
- Élie Mousseaux (ORCID: https://orcid.org/0000-0002-8076-1445)
- Thibaud Damy (ORCID: https://orcid.org/0000-0003-4058-3848)
- Alfonso Sartorius
- Jean‐Sébastien Hulot (ORCID: https://orcid.org/0000-0001-5463-6117)
- Hüseyin Fırat (ORCID: https://orcid.org/0000-0002-1257-8518)
- Ariel Cohen (ORCID: https://orcid.org/0000-0002-3329-2412)
- P. Boutouyrie
- Richard Isnard
- Liliane Berkani
- Damien Logeart
- Kevin Duarte
- Jean-Joseph Christophe
Institutions
- Centre National de la Recherche Scientifique (FR)
- Inserm (FR)
- Université Paris Cité (FR)
- Université Paris Sciences et Lettres (FR)
- Sanofi (France) (FR)
- Sorbonne Université (FR)
- Assistance Publique – Hôpitaux de Paris (FR)
- Hôpital Européen Georges-Pompidou (FR)
- Hôpital Saint-Antoine (FR)
- Hôpital Broca (FR)
- Hôpital Européen (FR)
- Firalis (France) (FR)
- Hôpital Lariboisière (FR)
- Pitié-Salpêtrière Hospital (FR)
- Simulation Technologies (United States) (US)
- Hôpitaux Universitaires Henri-Mondor (FR)
- Paris Cardiovascular Research Center (FR)
- Centre de Recherche Saint-Antoine (FR)
- Servier (France) (FR)
- DuPont (France) (FR)
- Hôpital Bichat-Claude-Bernard (FR)
- French Clinical Research Infrastructure Network (FR)
- Physique pour la médecine Paris (FR)
- Université de Lorraine (FR)
- ESPCI Paris (FR)
Publication Details
- Journal
- Nature Communications
- Published
- 2026-09-15
- DOI
- https://doi.org/10.1038/s41467-026-77642-6
- Primary Topic
- Cardiac Fibrosis and Remodeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00