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Updated: Jan 4, 2026

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
Monogenic and Polygenic Contributions to Atrial Fibrillation Risk: Results From a National Biobank
Seung Hoan Choi1, Sean J Jurgens1, Lu-Chen Weng1,2
1From the Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., L.-C.W., J.P.P., C.R., M.C., C.J.-Y.L., A.W.H., A.V.K., S.A.L., P.T.E.).
Rationale:
Genome-wide association studies have identified over 100 genetic loci for atrial fibrillation (AF); recent work described an association between loss-of-function (LOF) variants in TTN and early-onset AF.
Objective:
We sought to determine the contribution of rare and common genetic variation to AF risk in the general population.
Methods:
The UK Biobank is a population-based study of 500 000 individuals including a subset with genome-wide genotyping and exome sequencing. In this case-control study, we included AF cases and controls of genetically determined white-European ancestry; analyses were performed using a logistic mixed-effects model adjusting for age, sex, the first 4 principal components of ancestry, empirical relationships, and case-control imbalance. An exome-wide, gene-based burden analysis was performed to examine the relationship between AF and rare, high-confidence LOF variants in genes with ≥10 LOF carriers. A polygenic risk score for AF was estimated using the LDpred algorithm. We then compared the contribution of AF polygenic risk score and LOF variants to AF risk.
Results:
The study included 1546 AF cases and 41 593 controls. In an analysis of 9099 genes with sufficient LOF variant carriers, a significant association between AF and rare LOF variants was observed in a single gene, TTN (odds ratio, 2.71, P=2.50×10-8). The association with AF was more significant (odds ratio, 6.15, P=3.26×10-14) when restricting to LOF variants located in exons highly expressed in cardiac tissue (TTNLOF). Overall, 0.44% of individuals carried TTNLOF variants, of whom 14% had AF. Among individuals in the highest 0.44% of the AF polygenic risk score only 9.3% had AF. In contrast, the AF polygenic risk score explained 4.7% of the variance in AF susceptibility, while TTNLOF variants only accounted for 0.2%.
Conclusions:
Both monogenic and polygenic factors contribute to AF risk in the general population. While rare TTNLOF variants confer a substantial AF penetrance, the additive effect of many common variants explains a larger proportion of genetic susceptibility to AF.
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