Metabolomics: Energy Biomarkers Across Heart Failure Stages
- 3 days ago
- 4 min read
The failing heart runs low on fuel well before symptoms force a diagnosis, yet routine cardiology almost never measures that fuel directly. A serum metabolomics study of 210 patients set out to map the shortfall across the ACC/AHA stages of heart failure. Xiao Zhang and colleagues paired untargeted screening with a targeted energy-metabolite panel, then asked which molecules track the slide from at-risk Stage A to symptomatic Stage C. Their answer points straight at the cell's power supply.
Key Takeaways
Serum metabolomics can stage heart failure by reading the heart's energy supply, not just its symptoms or ejection fraction.
As disease advances to Stage C, ATP, ADP and AMP fall while malic acid rises, a signature of stalled energy production.
Malic acid stood out as a candidate biomarker; patients in the highest quartile carried roughly seven times the odds of advanced disease.
The cohort is cross-sectional, so these serum markers still need longitudinal testing before they guide any clinical decision.
What Serum Metabolomics Reveals About a Failing Heart
Two mass spectrometry platforms did the heavy lifting. Untargeted metabolomics on a Q Exactive Plus flagged broad differences between groups, and a targeted LC-MS assay on a QTRAP 6500+ then quantified the energy metabolites that matter for cardiac work. Features were kept when the VIP score exceeded 1 and the adjusted p-value fell below 0.05. Pathway enrichment kept circling back to the same neighborhoods: the citric acid cycle, central carbon metabolism, and amino acid turnover. Building on the old argument that the failing heart is an engine out of fuel (Neubauer, 2007), these serum numbers give the metaphor something concrete to stand on.
Key Findings
Energy currency drops with stage. Stage C serum showed lower glucose-6-phosphate, fructose-6-phosphate and phosphoenolpyruvate alongside reduced ATP, ADP and AMP, consistent with glycolytic and high-energy phosphate depletion.
TCA intermediates move the other way. Malic acid, fumaric acid and citric acid climbed as disease worsened, hinting at a backed-up or compensating tricarboxylic acid cycle.
A dose-response emerged for malic acid. Patients in the top quartile carried an odds ratio of 7.61 for advanced heart failure versus the bottom quartile (p < 0.05).
Branched-chain amino acids rose too, echoing reports that impaired BCAA catabolism travels with cardiac energy stress.
Figure 1. Study workflow, tracing enrollment of heart failure patients across Stages A, B and C through untargeted serum screening and targeted quantification of energy metabolites. Adapted from Zhang et al. (2026), Journal of Translational Medicine.
Reading Energy Collapse in Serum
The pattern is coherent in a way that clinical metabolite data often is not. Substrates that feed glycolysis and the high-energy phosphates that power contraction both fall as patients move toward symptomatic failure, while several downstream TCA acids accumulate. Read together, that looks less like a single broken enzyme and more like a whole engine losing the ability to turn fuel into usable work. One caveat sits underneath all of it: serum is a distant proxy for what a cardiomyocyte is doing, so these shifts describe systemic metabolism, not myocardial flux measured in place.
Why Stage Matters for Biomarker Panels
Most heart failure biomarker work anchors on natriuretic peptides, which report wall stress rather than fuel status. A metabolite panel that separates Stage B from Stage C adds a different axis, one tied to energetics instead of hemodynamics. The odds ratio for malic acid is large, and that is worth some skepticism until it replicates in an independent cohort with harder outcomes attached. Still, a marker that moves early, before overt symptoms, is exactly what a screening panel wants.
In Practice: Trusting a Serum Metabolite Panel
Energy metabolites such as ATP and malic acid degrade fast, so quench timing and the pre-analytical window often decide whether a serum panel replicates at all. On Dalton client work we run this style of targeted LC-MS metabolomics with careful batch correction across plates, since a stage-discriminating signal is only as trustworthy as the sample handling behind it. Groups building a serum readout of cardiac energetics can see how our targeted metabolomics services fit inside a wider multi-omics biomarker discovery program before locking in a cohort.
Frequently Asked Questions
What is metabolomics used for in heart failure? Metabolomics measures the small molecules produced by metabolism, which lets researchers see how the heart is using energy. In heart failure it can flag disrupted fuel handling, such as falling ATP or rising organic acids, that standard tests miss. This study used it to characterize serum energy metabolism across disease stages.
Can serum metabolomics detect the stage of heart failure? In this cohort of 210 patients, serum metabolite levels shifted in step with ACC/AHA stage, and malic acid tracked advanced disease strongly. That supports staging by metabolite signature, but the study was cross-sectional, so it shows association rather than a validated diagnostic. Longitudinal work is needed before clinical use.
How many samples does a metabolomics biomarker study need? It depends on effect size and how many groups you compare. This project screened 210 serum samples with untargeted analysis, then confirmed candidates in a smaller targeted set of 60. A discovery-plus-confirmation design like that is a practical way to control false positives on a realistic budget.
Conclusion
A serum energy-metabolite signature that tracks heart failure stage is believable here, and malic acid is a reasonable lead worth chasing further. What the design cannot show is whether these markers predict who will actually progress, because every sample was drawn at one time point. For anyone building a cardiac biomarker panel, the practical lesson is to nail down metabolite stability and sampling before scaling the cohort.
Related Reading
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Citation
Zhang, X., Wang, D., Liu, J., Zhang, D., & Wang, C. (2026). Untargeted-targeted metabolomics: energy metabolism characteristics in heart failure staging and discovery of novel biomarkers. Journal of Translational Medicine, 24(1), 259. https://doi.org/10.1186/s12967-026-07711-3
Note
This blog post summarizes findings from the above-cited research. Figures are adapted from the original publication. For full details, please refer to the source article.
By Seungjun Yeo, CEO at Dalton Bioanalytics. Specializing in multi-omics mass spectrometry for drug discovery and biomarker research.