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Updated: Sep 22, 2025

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
Plasma proteomic analysis of association between atrial fibrillation, coronary microvascular disease and heart
Gunjan Dixit1, John Blair1, Cevher Ozcan1
1Department of Medicine, Section of Cardiology, Heart and Vascular Center, University of Chicago 5841 S. Maryland Avenue, MC 6080, Chicago 60637, IL, USA.
Insights
Plasma proteomic analysis identified novel biomarkers linking atrial fibrillation (AF), coronary microvascular disease (CMD), and heart failure with preserved ejection fraction (HFpEF). These findings offer mechanistic insights into this prevalent clinical association.
Area of Science:
- Cardiovascular Medicine
- Proteomics
- Biomarker Discovery
Background:
- The association between atrial fibrillation (AF), coronary microvascular disease (CMD), and heart failure with preserved ejection fraction (HFpEF) is common but mechanistically unclear.
- Understanding the underlying pathways is crucial for effective clinical management.
Purpose of the Study:
- To identify novel plasma biomarkers and elucidate mechanistic pathways underlying the concomitant occurrence of AF, CMD, and HFpEF.
- To explore the proteomic profile associated with this specific triad of cardiovascular conditions.
Main Methods:
- Employed an unbiased, label-free quantitative proteomics approach using liquid chromatography-mass spectrometry on plasma samples from 18 patients.
- Analyzed circulating proteins to identify candidate biomarkers for the combined presence of AF, CMD, and HFpEF.
Main Results:
- Identified 130 dysregulated proteins, with 35 serving as candidate biomarkers for the AF-CMD-HFpEF association.
- Elevated SAA1, LRG1, and APOC3, and downregulated LCP1, PON1, and C1S were observed. Specific proteins correlated with individual conditions (e.g., PON1 with HFpEF, C1S with CMD).
- Associated proteins relate to inflammation, extracellular remodeling, oxidative stress, and coagulation.
Conclusions:
- Plasma proteomic profiling offers valuable biomarkers and mechanistic insights into the complex association between AF, CMD, and HFpEF.
- SAA1, LRG1, APOC3, LCP1, PON1, and C1S are potential candidate markers for risk stratification and understanding underlying mechanisms.
Abstract:
The clinical association between atrial fibrillation (AF), coronary microvascular disease (CMD) and heart failure with preserved ejection fraction (HFpEF) is highly prevalent, however the mechanism behind this association is not known. We hypothesized that plasma proteomic analysis can identify novel biomarkers and the mechanistic pathways in concomitant AF, CMD and HFpEF. To discover circulating biomarkers for the association between AF, CMD and HFpEF, an unbiased label-free quantitative proteomics approach was used in plasma derived from patients who underwent coronary physiology studies (n=18). Circulating proteins were analyzed by liquid chromatography-mass spectrometry and screened to determine candidate biomarkers of the concomitant AF, CMD and HFpEF. We identified 130 dysregulated proteins across the groups with the independent patient replicates. Among those, 35 proteins were candidate biomarkers of the association between AF, CMD and HFpEF. We found significantly elevated SAA1, LRG1 and APOC3 proteins in the coexistence of AF, CMD and HFpEF, whereas LCP1, PON1 and C1S were markedly downregulated in their associations. AF was associated with reduced LCP1, KLKB1 and C4A in these patients. Combined downregulation of PON1 and C1S was a marker of concurrent HFpEF and CMD. PON1 was associated with HFpEF while C1S was a marker of CMD. These proteins are related to inflammation, extra cellular remodeling, oxidative stress, and coagulation. In conclusion, plasma proteomic profile provides biomarkers and mechanistic insight into the association of AF, CMD and HFpEF. SAA1, LRG1, APOC3, LCP1, PON1 and C1S are candidate markers for the risk stratification of their associations and potential underlying mechanistic pathways.
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