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Roberts JD, Vittinghoff E, Lu AT, et al. Epigenetic Age and the Risk of Incident Atrial Fibrillation. Circulation. 2021;144(24):1899-1911doi: 10.1161/CIRCULATIONAHA.121.056456.
Roberts, J. D., Vittinghoff, E., Lu, A. T., Alonso, A., Wang, B., Sitlani, C. M., Mohammadi-Shemirani, P., Fornage, M., Kornej, J., Brody, J. A., Arking, D. E., Lin, H., Heckbert, S. R., Prokic, I., Ghanbari, M., Skanes, A. C., Bartz, T. M., Perez, M. V., Taylor, K. D., Lubitz, S. A., Ellinor, P. T., Lunetta, K. L., Pankow, J. S., Paré, G., Sotoodehnia, N., Benjamin, E. J., Horvath, S., & Marcus, G. M. (2021). Epigenetic Age and the Risk of Incident Atrial Fibrillation. Circulation, 144(24), 1899-1911. https://doi.org/10.1161/CIRCULATIONAHA.121.056456
Roberts, Jason D, et al. "Epigenetic Age and the Risk of Incident Atrial Fibrillation." Circulation vol. 144,24 (2021): 1899-1911. doi: https://doi.org/10.1161/CIRCULATIONAHA.121.056456
Roberts JD, Vittinghoff E, Lu AT, Alonso A, Wang B, Sitlani CM, Mohammadi-Shemirani P, Fornage M, Kornej J, Brody JA, Arking DE, Lin H, Heckbert SR, Prokic I, Ghanbari M, Skanes AC, Bartz TM, Perez MV, Taylor KD, Lubitz SA, Ellinor PT, Lunetta KL, Pankow JS, Paré G, Sotoodehnia N, Benjamin EJ, Horvath S, Marcus GM. Epigenetic Age and the Risk of Incident Atrial Fibrillation. Circulation. 2021 Dec 14;144(24):1899-1911. doi: 10.1161/CIRCULATIONAHA.121.056456. Epub 2021 Sep 30. PMID: 34587750.
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Circulation. 2021 Dec 14;144(24):1899-1911. doi: 10.1161/CIRCULATIONAHA.121.056456. Epub 2021 Sep 30.

Epigenetic Age and the Risk of Incident Atrial Fibrillation.

Circulation

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

Affiliations

  1. Population Health Research Institute (J.D.R., P.M-S., G.P.).
  2. Section of Cardiac Electrophysiology, Division of Cardiology, Department of Medicine, Western University, London, ON, Canada (J.D.R., A.C.S.).
  3. Department of Epidemiology and Biostatistics (E.V.) University of California, San Francisco.
  4. Department of Human Genetics, David Geffen School of Medicine (A.T.L., S.H.); University of California, Los Angeles.
  5. Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA (A.A.).
  6. Framingham Heart Study, Framingham, MA (B.W., J.K., H.L., E.J.B.).
  7. Departments of Biostatistics (B.W., K.L.L.), School of Public Health.
  8. Cardiovascular Health Research Unit (C.M.S., J.A.B., S.R.H., T.M.B., N.S.).
  9. Medicine (C.M.S., J.A.B., T.M.B., N.S.); University of Washington, Seattle.
  10. Departments of Medical Sciences (P.M-S.), McMaster University, Hamilton, ON, Canada.
  11. Thrombosis and Atherosclerosis Research Institute, Department of Medicine, David Braley Cardiac, Vascular, and Stroke Research Institute (P.M-S., G.P.); McMaster University, Hamilton, ON, Canada.
  12. Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston (M.F.).
  13. Sections of Cardiovascular Medicine (J.K., E.J.B.), Department of Medicine, School of Medicine; Boston University, MA.
  14. McKusick-Nathans Institute, Department of Genetic Medicine, Baltimore, MD (D.E.A.).
  15. Computational Biomedicine (H.L.), Department of Medicine, School of Medicine; Boston University, MA.
  16. Departments of Epidemiology (S.R.H., N.S.), University of Washington, Seattle.
  17. Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands (I.P., M.G.).
  18. Biostatistics (T.M.B.), University of Washington, Seattle.
  19. Division of Cardiovascular Medicine, Stanford University School of Medicine, CA (M.V.P.).
  20. Institute for Translational Genomics, The Lundquist Institute at Harbour-University of California, Los Angeles Medical Center, Torrance, CA (K.D.T.).
  21. Cardiovascular Research Center (S.A.L., P.T.E.); Massachusetts General Hospital, Boston.
  22. Cardiac Arrhythmia Service (S.A.L., P.T.E.), Massachusetts General Hospital, Boston.
  23. Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge (S.A.L., P.T.E.).
  24. Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (J.S.P.).
  25. Pathology and Molecular Medicine (G.P.); McMaster University, Hamilton, ON, Canada.
  26. Division of Cardiology (N.S.).
  27. Epidemiology (E.J.B.), School of Public Health.
  28. Department of Biostatistics, School of Public Health (S.H.); University of California, Los Angeles.
  29. Section of Cardiac Electrophysiology, Division of Cardiology, Department of Medicine (G.M.M.); University of California, San Francisco.

PMID: 34587750 DOI: 10.1161/CIRCULATIONAHA.121.056456

Abstract

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];

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.

Keywords: aging; atrial fibrillation; epigenomics; genetics

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