Identification of Biomarkers for Predicting New-Onset Atrial Fibrillation: A Systematic Review and Meta-Analysis

Area of Science:

• Cardiology
• Biomarker Discovery
• Epidemiology

Background:

• Atrial fibrillation (AF) is a progressive condition involving atrial remodeling and dysfunction.
• Early identification and risk stratification are crucial for preventing adverse cardiovascular events and stroke.

Purpose of the Study:

• To systematically review biomarkers that predict new-onset atrial fibrillation (AF).
• To highlight the potential of these biomarkers for early diagnosis, risk stratification, and prevention strategies.

Main Methods:

• A systematic literature search was conducted across major databases (PubMed, Scopus, Web of Science, Google Scholar) from January 2014 to November 2025.
• PRISMA 2020 guidelines were followed, excluding studies on specific populations or postoperative AF.
• Study quality was assessed using the Newcastle-Ottawa scale, with effect sizes reported as Hazard Ratios (HR) and 95% Confidence Intervals (CIs).

Main Results:

• Ten cohort studies involving 472,581 patients revealed 18 biomarkers associated with increased AF risk, notably NT-proBNP and sVCAM-1.
• Nine biomarkers, including ADAMTS13 (HR 0.78, 95%CI 0.70-0.88), were linked to lower AF incidence.
• Meta-analysis confirmed NT-proBNP's association with higher AF incidence (HR 1.37, 95%CI 1.19-1.59), while Lp(a) showed a 3% increase per 20 mg/dL increment.

Conclusions:

• Established biomarkers like NT-proBNP, alongside emerging ones such as Lp(a) and sVCAM-1, show promise in AF diagnosis and management.
• Further large-scale prospective studies are essential to validate and optimize the predictive utility of these biomarkers for new-onset AF.