Epigenetic Age and the Risk of Incident Atrial Fibrillation
Authors: Roberts Jason D. , Vittinghoff Eric , Lu Ake T. , Alonso Alvaro , Wang Biqi , Sitlani Colleen M. , Mohammadi-Shemirani Pedrum , Fornage Myriam , Kornej Jelena , Brody Jennifer A. , Arking Dan E. , Lin Honghuang , Heckbert Susan R. , Prokic Ivana , Ghanbari Mohsen , Skanes Allan C. , Bartz Traci M. , Perez Marco V. , Taylor Kent D. , Lubitz Steven A. , Ellinor Patrick T. , Lunetta Kathryn L. , Pankow James S. , Paré Guillaume , Sotoodehnia Nona , Benjamin Emelia J. , Horvath Steve , Marcus Gregory M. 
Published: September 2021

Background:

The most prominent risk factor for atrial fibrillation (AF) is chronological age; however, underlying mechanisms are unexplained. Algorithms using epigenetic modifications to the human genome effectively predict chronological age. Chronological and epigenetic predicted ages may diverge in a phenomenon referred to as epigenetic age acceleration (EAA), which may reflect accelerated biological aging. We sought to evaluate for associations between epigenetic age measures and incident AF.

Methods:

Measures for 4 epigenetic clocks (Horvath, Hannum, DNA methylation [DNAm] PhenoAge, and DNAm GrimAge) and an epigenetic predictor of PAI-1 (plasminogen activator inhibitor-1) levels (ie, DNAm PAI-1) were determined for study participants from 3 population-based cohort studies. Cox models evaluated for associations with incident AF and results were combined via random-effects meta-analyses. Two-sample summary-level Mendelian randomization analyses evaluated for associations between genetic instruments of the EAA measures and AF.

Results:

Among 5600 participants (mean age, 65.5 years; female, 60.1%; Black, 50.7%), there were 905 incident AF cases during a mean follow-up of 12.9 years. Unadjusted analyses revealed all 4 epigenetic clocks and the DNAm PAI-1 predictor were associated with statistically significant higher hazards of incident AF, though the magnitudes of their point estimates were smaller relative to the associations observed for chronological age. The pooled EAA estimates for each epigenetic measure, with the exception of Horvath EAA, were associated with incident AF in models adjusted for chronological age, race, sex, and smoking variables. After multivariable adjustment for additional known AF risk factors that could also potentially function as mediators, pooled EAA measures for 2 clocks remained statistically significant. Five-year increases in EAA measures for DNAm GrimAge and DNAm PhenoAge were associated with 19% (adjusted hazard ratio [HR], 1.19 [95% CI, 1.09–1.31];
P
<0.01) and 15% (adjusted HR, 1.15 [95% CI, 1.05–1.25];
P
<0.01) higher hazards of incident AF, respectively. Mendelian randomization analyses for the 5 EAA measures did not reveal statistically significant associations with AF.

Conclusions:

Our study identified adjusted associations between EAA measures and incident AF, suggesting that biological aging plays an important role independent of chronological age, though a potential underlying causal relationship remains unclear. These aging processes may be modifiable and not constrained by the immutable factor of time.