Atrial fibrillation (AF) is a common heart arrhythmia and a major cause of cardioembolic stroke. Therefore, accurate prediction is desirable to allow high-risk individuals to be identified early and their risk lowered before complications arise. Polygenic risk scores (PRS) have become a popular method of quantifying aggregated genetic risk from common variants, but their clinical value in atrial fibrillation remains uncertain. This literature review discusses the associations between PRS and AF risk, and the evidence for their clinical utility in AF prediction. Stroke risk in AF patients is also considered. Despite consistent associations between PRS and AF risk, the performance of PRS as a standalone tool for AF prediction was poor. However, addition of PRS to existing AF prediction models commonly increased predictive performance above that of the clinical models alone, including in cohorts with comorbid cardiovascular disease. Associations between PRS and cardioembolic stroke risk in AF patients have also been reported, but improvements to stroke prediction models from PRS have been minimal. PRS are likely to add value to existing clinical AF prediction models, however, standardisation of PRS across studies and populations will likely be required before they can be meaningfully adopted into routine clinical practice
