Aims Atrial fibrillation (AF) is a progressive disease, but identifying patients at risk for AF progression is challenging. We aimed to identify factors associated with AF progression. Methods and results Atrial fibrillation progression was assessed in 392 patients with recent-onset paroxysmal or persistent AF included in the prospective, observational, multicentre identification of a risk profile to guide atrial fibrillation (AF-RISK) study. Progression of AF was assessed by Holter monitoring and 2-week event recorder at baseline and 1-year follow-up. AF progression was defined as: (i) doubling in AF burden at 1 year compared to baseline with a minimum AF burden of 10% in paroxysmal AF; or (ii) transition from paroxysmal to persistent or permanent AF; or (iii) persistent to permanent AF. Age was 60 ± 11 years, 62% were men, and 83% had paroxysmal AF. At 1 year, 52 (13%) had AF progression (11% in paroxysmal; 26% in persistent AF). Multivariable logistic regression showed that left atrial volume [odds ratio (OR) per 10 mL 1.251, 95% confidence interval (CI) 1.078–1.450; P < 0.001], N-terminal pro-B-type natriuretic peptide (NT-proBNP; OR per standard deviation increase 1.583, 95% CI 1.099–2.281; P = 0.014), and plasminogen activator inhibitor-1 (PAI-1; OR per standard deviation increase 0.660, 95% CI 0.472–0.921; P = 0.015) were associated with AF progression. In an additional follow-up of 1.9 (0.9–3.3) years patients with AF progression developed more cardiovascular events and all-cause mortality (12.4%/year vs. 2.3%/year, P < 0.001). Conclusion Atrial fibrillation progression occurred in 13% of patients with recent-onset AF during 1-year follow-up. Left atrial volume, NT-proBNP, and PAI-1 were associated with AF progression. Patients with AF progression had a higher event rate. Trial registration number Clinicaltrials.gov NCT01510210.

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Previous studies have shown several metabolic biomarkers to be associated with prevalent and incident atrial fibrillation (AF), but the results have not been replicated. We investigated metabolite profiles of 2,458 European ancestry participants from the Framingham Heart Study without AF at the index exam and followed them for 10 years for new-onset AF. Amino acids, organic acids, lipids, and other plasma metabolites were profiled by liquid chromatography-tandem mass spectrometry using fasting plasma samples. We conducted Cox proportional hazard analyses for association between metabolites and new-onset AF. We performed hypothesis generating analysis to identify novel metabolites and hypothesis testing analysis to confirm the previously reported associations between metabolites and AF. Mean age was 55.1±9.9 years, and 53% were women. Incident AF developed in 156 participants (6.3%) in 10 years of follow-up. A total of 217 metabolites were examined, consisting of 54 positively charged metabolites, 59 negatively charged metabolites, and 104 lipids. None of the 217 metabolites met our a priori specified Bonferroni corrected level of significance in the multivariable analyses. We were unable replicate previous results demonstrating associations between metabolites that we had measured and AF. In conclusion, in our metabolomics approach, none of the metabolites we tested were significantly associated with the risk of future AF.