Multi-Omics: Plasma VDAC1 Signals Atrial Fibrillation
About a third of atrial fibrillation (AF) patients relapse within a year of treatment, and no routine blood test reports on the atrial substrate itself. Wang and colleagues applied plasma multi-omics to coronary sinus blood from persistent AF patients, using supraventricular tachycardia (SVT) patients as controls. Their data point to voltage-dependent anion channel 1 (VDAC1), an outer mitochondrial membrane protein, as a candidate marker of mitochondrial injury.
Key Takeaways
Plasma multi-omics can detect mitochondrial and lipid stress in persistent atrial fibrillation that NT-proBNP does not capture.
VDAC1 is a candidate blood biomarker for AF-related mitochondrial injury, not yet a validated diagnostic test.
Ten-per-arm discovery sets generate hypotheses; candidates need larger independent cohorts before clinical use.
Paired Multi-Omics From Coronary Sinus Plasma
Coronary sinus blood was drawn from 37 AF and 36 SVT patients before ablation. That venous bed drains the myocardium, so it should carry more cardiac signal than a peripheral draw. Ten patients per group underwent diaPASEF proteomics on a depleted plasma proteome plus untargeted metabolomics; ELISA then covered 35 per arm. Four GEO atrial datasets and a single-nucleus RNA-seq atlas supplied tissue support.
Key Findings
A mitochondrial hub among 3,268 plasma proteins: 217 proteins differed, and network ranking placed VDAC1 among top hubs with citrate synthase (CS).
ELISA results held in new patients: Median VDAC1 was 758.2 versus 573.6 pg/mL across 35 per arm (P < 0.001), and the gap persisted in newly recruited patients alone.
Lipids dominated the metabolome: Lipid species led the 505 differential metabolites, with glycerophospholipid and linoleic acid metabolism most perturbed.
Discrimination survived adjustment: VDAC1 gave an AUC of 0.816 and stayed significant after correcting for age, sex, BMI, creatinine, hypertension, and amiodarone.
Figure 1. Study workflow. Plasma went to a discovery set (10 per group) for 4D-DIA proteomics, untargeted metabolomics, and pathway analysis, and to an ELISA set (35 per group). A bioinformatics arm reanalyzed GEO and single-nucleus datasets. All arms converge on elevated VDAC1. Adapted from Wang et al. (2026), International Journal of Cardiology: Heart & Vasculature.
Where Proteins and Metabolites Converge
Eight KEGG pathways reached P < 0.01 in both layers, mostly lipid and carbon metabolism. That is where cross-omics analysis earns its keep: a TCA cycle signal in the proteome means more when acylcarnitines and ketone bodies move in the same plasma. Some top features (hopanes, dibutyl phthalate) look like contamination, which the authors concede.
A Marker Distinct From Wall Stress
VDAC1 tracked left atrial diameter (r = 0.342) but not NT-proBNP. That dissociation is the paper's most useful clinical detail, suggesting VDAC1 reports mitochondrial stress rather than wall stress. Atrial transcripts were higher in all four GEO datasets and localized to cardiomyocytes. Caveats remain. Controls were younger, and amiodarone independently lowered VDAC1. Geyer and colleagues (2017) warned that plasma candidates from small discovery sets often fail to replicate, and ten per arm sits squarely in that risk zone.
Why Paired Plasma Layers Matter
The VDAC1 hub became convincing because TCA and lipid metabolites shifted in the same twenty samples, the core case for integrated proteomics and metabolomics. Coronary sinus plasma is scarce; three samples here dropped out of ELISA for insufficient volume. At Dalton, Omni-MS captures both layers from one injection, so there's no split-volume tradeoff or cross-batch alignment to defend, issues that often decide whether a multi-omics biomarker discovery program survives validation.
Frequently Asked Questions
What is multi-omics used for in cardiovascular research?
Multi-omics measures two or more molecular layers, such as proteins and metabolites, in the same patients. Agreement across layers makes a candidate biomarker more credible than a single-layer hit.
Is VDAC1 a blood biomarker for atrial fibrillation?
It is a candidate, not an established test. Plasma VDAC1 separated persistent AF from SVT with an AUC of 0.816, but larger cohorts with peripheral blood are needed.
How many samples does a plasma multi-omics biomarker study need?
Discovery often starts with 10 to 30 samples per group, which only supports hypothesis generation. Validation usually needs hundreds of independent samples, and single-aliquot workflows keep volume and cost down.
Conclusion
Circulating VDAC1 is now a believable marker of mitochondrial stress in persistent AF. It isn't yet shown to add value beyond ECG and existing biomarkers, or to behave the same in peripheral blood. Pairing VDAC1 with NT-proBNP in cardiometabolic panels looks worth testing, since they track different biology.
Related Reading
See how we run these analyses in one lab: Dalton's multi-omics CRO services.
Citation
Wang, J., Chen, X., Zhang, Z., & Gui, C. (2026). Multi-omics profiling of circulating proteins and metabolites in persistent atrial fibrillation: VDAC1 identified as a candidate circulating protein. International Journal of Cardiology. Heart & Vasculature, 66, 102004. https://doi.org/10.1016/j.ijcha.2026.102004
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.