DOI: 10.1093/ejhf/xuag193.418 ISSN: 1388-9842

Circulating mitochondrial and metabolic biomarkers in HFpEF: from energetic failure to clinical prediction - a systematic review

S Satishkumar, S M B Fernandes, D Rose Tom, D Abraham Georgie, F Mohmadrafi Mansuri, I Ajith, F Abdul Kareem, R Agladze

Abstract

Background/Purpose

Heart failure with preserved ejection fraction (HFpEF) is increasingly recognized as a systemic metabolic and mitochondrial disorder, yet current diagnostic and prognostic tools rely largely on non-specific cardiac biomarkers. Circulating mitochondrial and metabolic biomarkers may better capture underlying energetic failure and improve risk stratification, but their clinical utility remains unclear.

Methods

We conducted a PRISMA 2020-compliant systematic review registered with PROSPERO. We searched PubMed, Embase, Scopus, and Cochrane Library from January 1, 2020 to November 1, 2025, for case-control, cross-sectional, and RCT-based biomarker analyses in adults with HFpEF (ejection fraction > 50% or study-defined).We used HFpEF, biomarker, mitochondrial, and metabolomics MeSH terms. Risk of bias was assessed using tool-specific approaches according to study design. Randomized controlled trials were evaluated using the Cochrane Risk of Bias 2 (RoB 2) tool, while non-randomized observational studies were assessed using the Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) tools.

Results

Of 336 records, 41 studies were included. Two randomized trials (RoB 2) had overall low risk of bias, although some biomarker analyses were unplanned and may have been selectively reported. Most observational studies (ROBINS-I) had moderate overall risk, mainly due to residual confounding, missing data, and selective reporting. Mitochondrial and metabolic biomarkers such as lactate, circulating mtDNA, branched-chain amino acids, and acylcarnitines were consistently linked to congestion, reduced exercise capacity, and incident heart failure; for example, higher cell-free mtDNA was independently associated with congestion (OR 3.33, 95% CI 1.02–10.90). A nine-metabolite plasma panel including acylcarnitines and amino acid derivatives distinguished HFpEF from hypertensive controls with an AUC of 0.98, 94% sensitivity, and 100% specificity. Proteomic and inflammatory panels identified high-risk HFpEF clusters with nearly twofold higher cardiovascular events, while SERPINA3 and remodeling markers differentiated HFpEF from other phenotypes. Lipidomic, transcriptomic, and metabolomic markers (ceramide ratios, GATA3/IFNG, 9-metabolite panel) showed good diagnostic and prognostic performance, supporting a robust multi-omic HFpEF profile.

Conclusion

Circulating mitochondrial, metabolic, and other omics-based biomarkers provide information beyond natriuretic peptides to distinguish HFpEF, flag higher-risk patients, and reflect congestion and reduced exercise capacity. Together, they support biomarker-based HFpEF subtyping and provide a practical framework for designing targeted trials and improving individual risk assessment.

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