Heart failure & cardiomyopathies
Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using plasma proteomics profiling
Authors' conclusion
This is the first study to demonstrate the ability of plasma proteomics to predict new-onset AF in HCM and identify dysregulated signalling pathways.
Study context
- Population
- Patients with hypertrophic cardiomyopathy (HCM)training set 193, test set 91
- Participants
- 284 patients
- Exposure
- Proteomics-based high-risk vs low-risk classification
- Outcome
- New-onset AF
- Follow-up
- Median 3.2 years [25-75 percentile: 1.8-5.2]
Methodological detailsmulticentre, proteomics-based machine learning prediction model, independent test set, Plasma proteomics profiling of 4986 proteins at enrolment
- Multicentre
- Proteomics-based machine learning prediction model
- Independent test set
- Plasma proteomics profiling of 4986 proteins at enrolment
Main finding
As reported in the abstract
Prediction of new-onset AF (test set)
AUC of proteomics-based model in test set
0.89
95% CI 0.78–0.99
Patients developing atrial fibrillation (AF)
Thirty-seven (13%)
Observational data: associations, not effects.
Further findings
Pathway analysis
- Ras-MAPK pathway dysregulated in patients who developed incident AF
- False discovery rate (FDR) < 1.0 × 10-6
Original publication
Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using plasma proteomics profiling. Europace. Published 23 October 2024. doi:10.
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