Rationale: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome with substantial unmet diagnostic and therapeutic needs. Circulating lipid metabolism is increasingly implicated in HFpEF pathophysiology but has not been systematically leveraged for molecular stratification. Objective: To determine whether plasma lipidomics can identify molecular phenogroups of HFpEF associated with distinct clinical characteristics and outcomes. Methods and Results: Untargeted plasma lipidomics was performed in non-HF subjects and HFpEF patients from a primary Belgian cohort and an independent Canadian cohort (n=177 in each cohort). In the Belgian cohort, 235 unique lipids spanning 19 subclasses were annotated, including 96 significantly associated with HFpEF (q<0.02). Unsupervised analyses revealed marked lipidomic heterogeneity, with a distinct HFpEF subgroup separable from non-HF subjects. Hierarchical clustering identified three phenogroups with divergent lipid profiles and clinical features. One phenogroup exhibited severe atrial dysfunction, congestion-related biomarkers, elevated indices of cardiac and liver fibrosis, and markedly reduced survival, a second was characterized by prominent metabolic syndrome features, and a third by preserved renal function. Cross-cohort comparison using a supervised classifier trained on 158 shared lipids confirmed analogous lower-risk phenogroups in the Canadian cohort, while the high-risk phenotype was underrepresented. A signature of 10 lipids across six subclasses, including long-chain acylcarnitines, ether phosphatidylcholines, and oxidized sphingomyelins, discriminated the high-risk group and correlated with markers of disease severity. Conclusion: Our findings demonstrate that HFpEF comprises metabolically distinct patient subgroups across cohorts, revealing specific lipidomic dysfunctions that deepen our understanding of HFpEF heterogeneity and underlying pathophysiology.

The authors have declared no competing interest.

BECAME-HF was supported by bilateral research programs between the Fonds de Recherche du Quebec (FRQ, Québec, Canada) and the Fonds National de la Recherche Scientifique (FNRS, Brussels, Belgium) (Bilateral research projects FRQ-FNRS - PINT-BILAT-P 2018), by the Action de Recherche Concertée of the Wallonia-Brussels Federation (ARC 23/28-132), and by grants from the Fondation Saint- Luc (Brussels, Belgium). This project also benefited from infrastructure supported by the Canada Foundation for Innovation (grant numbers 12126, 20415, and 36283 to JCT and CDR) and the MHI Foundation. Computational work was funded in part by a National Sciences and Engineering Research Council (NSERC) Discovery Grant to JGH (RGPIN-2022-04262). NM, SL and CR were supported by Fondation Saint Luc, Belgium. JGH holds a Tier 2 Canada Research Chair (CRC) in responsible multi-omics data science, JCT holds a Tier 1 CRC in personalized and translational medicine, ACP is post-doctorate Clinical Master Specialist at FNRS, SH is a senior research associate of FNRS.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The study was conducted in accordance with the Declaration of Helsinki and approved by local ethics committees in Belgium (Comite déthique Hospitalo-Facultaire, Cliniques universitaires Saint-Luc and UCLouvain; approvals 2012/23AVR/199 and 2018/19MAR/118) and Canada (Montreal Heart Institute protocol #2017-2316). All participants provided written informed consent.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

The lipidomic and metabolomic datasets generated and analyzed in this study are derived from human clinical cohorts. Processed lipidomic data matrices (log₂-transformed, normalized, and batch-corrected), including lipid annotations and cluster assignments, are available in a public repository (to be provided). Summary-level data supporting the main findings of this study are provided in the Supplementary Tables. All custom code used for lipidomic data processing, statistical analyses, clustering, and visualization was written in R and is available on GitHub [https://github.com/HussinLab/BECAME_HF/] with appropriate documentation. Any additional information required to reanalyze the raw data is available from the corresponding authors upon reasonable request, subject to institutional data-sharing agreements and ethical approval.

https://github.com/HussinLab/BECAME_HF/