Key result
Novel 47-protein score is linked to ~94% higher incident AF risk per SD.
Why the study?
Does a protein-based risk score improve the prediction of incident atrial fibrillation compared with traditional clinical and polygenic risk scores in individuals without prior AF?
Cohort (n=36,129)
Does a protein-based risk score improve the prediction of incident atrial fibrillation compared with traditional clinical and polygenic risk scores in individuals without prior AF?
Hazard Ratio: 1.94 (95% CI 1.83–2.05)
A protein-based risk score, particularly driven by NT-proBNP, significantly improves the prediction of incident atrial fibrillation compared to traditional clinical and polygenic risk scores.
Background Proteomic biomarkers have shown promise in predicting various cardiovascular conditions, but their utility in assessing the risk of atrial fibrillation (AF) remains unclear. This study aimed to develop and validate a protein-based risk score for predicting incident AF and to compare its predictive performance with traditional clinical risk factors and polygenic risk scores in a large cohort from the UK Biobank. Methods We analysed data from 36 129 white British individuals without prior AF, assessing 2923 plasma proteins using the Olink Explore 3072 assay. The cohort was divided into a training set (70%) and a test set (30%) to develop and validate a protein risk score for AF. We compared the predictive performance of this score with the HARMS 2 -AF risk model and a polygenic risk score. Results Over an average follow-up of 11.8 years, 2450 incident AF cases were identified. A 47-protein risk score was developed, with N-terminal prohormone of brain natriuretic peptide (NT-proBNP) being the most significant predictor. In the test set, the protein risk score (per SD increment, HR 1.94; 95% CI 1.83 to 2.05) and NT-proBNP alone (HR 1.80; 95% CI 1.70 to 1.91) demonstrated superior predictive performance (C-statistic: 0.802 and 0.785, respectively) compared with HARMS 2 -AF and polygenic risk scores (C-statistic: 0.751 and 0.748, respectively). Conclusions A protein-based risk score, particularly incorporating NT-proBNP, offers superior predictive value for AF risk over traditional clinical and polygenic risk scores, highlighting the potential for proteomic data in AF risk stratification.
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Liu et al. (2024) conducted a cohort in Atrial fibrillation (n=36,129). 47-protein risk score vs. HARMS 2-AF risk model and polygenic risk score was evaluated on Incident atrial fibrillation (HR 1.94, 95% CI 1.83 to 2.05). A 47-protein risk score predicted incident atrial fibrillation (HR 1.94 per SD increment; 95% CI 1.83-2.05) with superior performance compared to traditional clinical and polygenic risk scores.
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