Epigenetic Age and the Risk of Incident Atrial Fibrillation

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

doi:10.1161/CIRCULATIONAHA.121.056456

Epigenetic Age and the Risk of Incident Atrial Fibrillation

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. LubitzPatrick T. Ellinor, Kathryn L. Lunetta, James S. Pankow, Guillaume Paré, Nona Sotoodehnia, Emelia J. Benjamin, Steve Horvath, Gregory M. Marcus

Epidemiology & Community Health

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

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]; 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.

Original language	English (US)
Pages (from-to)	1899-1911
Number of pages	13
Journal	Circulation
Volume	144
Issue number	24
DOIs	https://doi.org/10.1161/CIRCULATIONAHA.121.056456
State	Published - Dec 14 2021

Bibliographical note

Funding Information:
ARIC (Atherosclerosis Risk in Communities) was funded, in whole or in part, with federal funds from the National Institutes of Health (NIH), National Heart, Lung, and Blood Institute (NHLBI) and US Department of Health and Human Services (contract Nos. HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, and HHSN268201700005I). Funding was also provided by the NIH (No. 5RC2HL102419, R01NS087541, K24HL148521), and the American Heart Association (No. 16EIA26410001). FHS (Framingham Heart Study) was funded by the NIH, NHLBI (Nos. 75N92019D00031, HHSN268201500001I, R01HL128914, and 2R01 HL092577) and American Heart Association (18SFRN34110082). The laboratory work for this FHS was funded by the NIH, NHLBI, Division of Intramural Research and by a Director’s Challenge Award from the NIH. Infrastructure for the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium is supported in part by the NHLBI (grant No. R01HL105756). CHS (Cardiovascular Heart Study) research was supported by the NHLBI (contract Nos. HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, and N01HC85086; grant Nos. U01HL080295, U01HL130114, K08HL116640, R01HL087652, R01HL092111, R01HL103612, R01HL105756, R01HL103612, R01HL111089, R01HL116747, and R01HL120393). Additional support was provided by the National Institute of Neurological Disorders and Stroke; National Institute on Aging (No. R01AG023629); and the Merck Foundation/Society of Epidemiological Research, as well as the Laughlin family, Alpha Phi Foundation, and Locke Charitable Foundation. A full list of principal CHS investigators and institutions can be found at https://CHS-NHLBI.org . Genotyping data were provided, in part, by the National Center for Advancing Translational Sciences (grant No. UL1TR000124) and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (grant No. DK063491 to the Southern California Diabetes Endocrinology Research Center). Drs Lu and Horvath are supported by a NIH U01 grant (No. U01AG060908–01). Dr Kornej received funding from the Marie Sklodowska-Curie Actions under the European Union’s Horizon 2020 research and innovation program (grant No. 838259). Dr Lubitz is supported by the NIH (grant No. 1R01HL139731) and American Heart Association (grant No. 18SFRN34250007). Dr Sotoodehnia is supported by the NHLBI (No. R01HL141989).

Funding Information:
Regents of the University of California (the employer of Drs Horvath and Lu) has filed patents surrounding several epigenetic biomarkers of aging (including GrimAge), listing Drs Horvath and Lu as inventors. Dr Lubitz receives sponsored research support from Bristol-Myers Squibb–Pfizer, Bayer AG, Boehringer Ingelheim, and Fitbit; has consulted for Bristol-Myers Squibb–Pfizer and Bayer AG; and participates in a research collaboration with IBM. Dr Ellinor is supported by a grant from Bayer AG to the Broad Institute focused on the genetics and therapeutics of cardiovascular diseases; and has served on advisory boards or consulted for Bayer AG, Quest Diagnostics, MyoKardia, and Novartis. Dr Benjamin serves as an uncompensated member for the MyHeartLab Steering Committee. The MyHeartLab Study is a principal investigator–initiated study from the University of California–San Francisco (Principal Investigator: Jeffrey Olgin, MD), through a research grant to University of California–San Francisco from Samsung. The other authors report no conflicts.

Publisher Copyright:
© 2021 Lippincott Williams and Wilkins. All rights reserved.

Keywords

aging
atrial fibrillation
epigenomics
genetics

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10.1161/CIRCULATIONAHA.121.056456

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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., ... 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, 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 2021, 'Epigenetic Age and the Risk of Incident Atrial Fibrillation', Circulation, vol. 144, no. 24, pp. 1899-1911. https://doi.org/10.1161/CIRCULATIONAHA.121.056456

@article{5fc7663a42c14204836554f959fea097,

title = "Epigenetic Age and the Risk of Incident Atrial Fibrillation",

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]; 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.",

keywords = "aging, atrial fibrillation, epigenomics, genetics",

author = "Roberts, {Jason D.} and Eric Vittinghoff and Lu, {Ake T.} and Alvaro Alonso and Biqi Wang and Sitlani, {Colleen M.} and Pedrum Mohammadi-Shemirani and Myriam Fornage and Jelena Kornej and Brody, {Jennifer A.} and Arking, {Dan E.} and Honghuang Lin and Heckbert, {Susan R.} and Ivana Prokic and Mohsen Ghanbari and Skanes, {Allan C.} and Bartz, {Traci M.} and Perez, {Marco V.} and Taylor, {Kent D.} and Lubitz, {Steven A.} and Ellinor, {Patrick T.} and Lunetta, {Kathryn L.} and Pankow, {James S.} and Guillaume Par{\'e} and Nona Sotoodehnia and Benjamin, {Emelia J.} and Steve Horvath and Marcus, {Gregory M.}",

note = "Funding Information: ARIC (Atherosclerosis Risk in Communities) was funded, in whole or in part, with federal funds from the National Institutes of Health (NIH), National Heart, Lung, and Blood Institute (NHLBI) and US Department of Health and Human Services (contract Nos. HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, and HHSN268201700005I). Funding was also provided by the NIH (No. 5RC2HL102419, R01NS087541, K24HL148521), and the American Heart Association (No. 16EIA26410001). FHS (Framingham Heart Study) was funded by the NIH, NHLBI (Nos. 75N92019D00031, HHSN268201500001I, R01HL128914, and 2R01 HL092577) and American Heart Association (18SFRN34110082). The laboratory work for this FHS was funded by the NIH, NHLBI, Division of Intramural Research and by a Director{\textquoteright}s Challenge Award from the NIH. Infrastructure for the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium is supported in part by the NHLBI (grant No. R01HL105756). CHS (Cardiovascular Heart Study) research was supported by the NHLBI (contract Nos. HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, and N01HC85086; grant Nos. U01HL080295, U01HL130114, K08HL116640, R01HL087652, R01HL092111, R01HL103612, R01HL105756, R01HL103612, R01HL111089, R01HL116747, and R01HL120393). Additional support was provided by the National Institute of Neurological Disorders and Stroke; National Institute on Aging (No. R01AG023629); and the Merck Foundation/Society of Epidemiological Research, as well as the Laughlin family, Alpha Phi Foundation, and Locke Charitable Foundation. A full list of principal CHS investigators and institutions can be found at https://CHS-NHLBI.org . Genotyping data were provided, in part, by the National Center for Advancing Translational Sciences (grant No. UL1TR000124) and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (grant No. DK063491 to the Southern California Diabetes Endocrinology Research Center). Drs Lu and Horvath are supported by a NIH U01 grant (No. U01AG060908–01). Dr Kornej received funding from the Marie Sklodowska-Curie Actions under the European Union{\textquoteright}s Horizon 2020 research and innovation program (grant No. 838259). Dr Lubitz is supported by the NIH (grant No. 1R01HL139731) and American Heart Association (grant No. 18SFRN34250007). Dr Sotoodehnia is supported by the NHLBI (No. R01HL141989). Funding Information: Regents of the University of California (the employer of Drs Horvath and Lu) has filed patents surrounding several epigenetic biomarkers of aging (including GrimAge), listing Drs Horvath and Lu as inventors. Dr Lubitz receives sponsored research support from Bristol-Myers Squibb–Pfizer, Bayer AG, Boehringer Ingelheim, and Fitbit; has consulted for Bristol-Myers Squibb–Pfizer and Bayer AG; and participates in a research collaboration with IBM. Dr Ellinor is supported by a grant from Bayer AG to the Broad Institute focused on the genetics and therapeutics of cardiovascular diseases; and has served on advisory boards or consulted for Bayer AG, Quest Diagnostics, MyoKardia, and Novartis. Dr Benjamin serves as an uncompensated member for the MyHeartLab Steering Committee. The MyHeartLab Study is a principal investigator–initiated study from the University of California–San Francisco (Principal Investigator: Jeffrey Olgin, MD), through a research grant to University of California–San Francisco from Samsung. The other authors report no conflicts. Publisher Copyright: {\textcopyright} 2021 Lippincott Williams and Wilkins. All rights reserved.",

year = "2021",

month = dec,

day = "14",

doi = "10.1161/CIRCULATIONAHA.121.056456",

language = "English (US)",

volume = "144",

pages = "1899--1911",

journal = "Circulation",

issn = "0009-7322",

publisher = "Lippincott Williams and Wilkins",

number = "24",

}

TY - JOUR

T1 - Epigenetic Age and the Risk of Incident Atrial Fibrillation

AU - Roberts, Jason D.

AU - Vittinghoff, Eric

AU - Lu, Ake T.

AU - Alonso, Alvaro

AU - Wang, Biqi

AU - Sitlani, Colleen M.

AU - Mohammadi-Shemirani, Pedrum

AU - Fornage, Myriam

AU - Kornej, Jelena

AU - Brody, Jennifer A.

AU - Arking, Dan E.

AU - Lin, Honghuang

AU - Heckbert, Susan R.

AU - Prokic, Ivana

AU - Ghanbari, Mohsen

AU - Skanes, Allan C.

AU - Bartz, Traci M.

AU - Perez, Marco V.

AU - Taylor, Kent D.

AU - Lubitz, Steven A.

AU - Ellinor, Patrick T.

AU - Lunetta, Kathryn L.

AU - Pankow, James S.

AU - Paré, Guillaume

AU - Sotoodehnia, Nona

AU - Benjamin, Emelia J.

AU - Horvath, Steve

AU - Marcus, Gregory M.

N1 - Funding Information: ARIC (Atherosclerosis Risk in Communities) was funded, in whole or in part, with federal funds from the National Institutes of Health (NIH), National Heart, Lung, and Blood Institute (NHLBI) and US Department of Health and Human Services (contract Nos. HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, and HHSN268201700005I). Funding was also provided by the NIH (No. 5RC2HL102419, R01NS087541, K24HL148521), and the American Heart Association (No. 16EIA26410001). FHS (Framingham Heart Study) was funded by the NIH, NHLBI (Nos. 75N92019D00031, HHSN268201500001I, R01HL128914, and 2R01 HL092577) and American Heart Association (18SFRN34110082). The laboratory work for this FHS was funded by the NIH, NHLBI, Division of Intramural Research and by a Director’s Challenge Award from the NIH. Infrastructure for the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium is supported in part by the NHLBI (grant No. R01HL105756). CHS (Cardiovascular Heart Study) research was supported by the NHLBI (contract Nos. HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, and N01HC85086; grant Nos. U01HL080295, U01HL130114, K08HL116640, R01HL087652, R01HL092111, R01HL103612, R01HL105756, R01HL103612, R01HL111089, R01HL116747, and R01HL120393). Additional support was provided by the National Institute of Neurological Disorders and Stroke; National Institute on Aging (No. R01AG023629); and the Merck Foundation/Society of Epidemiological Research, as well as the Laughlin family, Alpha Phi Foundation, and Locke Charitable Foundation. A full list of principal CHS investigators and institutions can be found at https://CHS-NHLBI.org . Genotyping data were provided, in part, by the National Center for Advancing Translational Sciences (grant No. UL1TR000124) and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (grant No. DK063491 to the Southern California Diabetes Endocrinology Research Center). Drs Lu and Horvath are supported by a NIH U01 grant (No. U01AG060908–01). Dr Kornej received funding from the Marie Sklodowska-Curie Actions under the European Union’s Horizon 2020 research and innovation program (grant No. 838259). Dr Lubitz is supported by the NIH (grant No. 1R01HL139731) and American Heart Association (grant No. 18SFRN34250007). Dr Sotoodehnia is supported by the NHLBI (No. R01HL141989). Funding Information: Regents of the University of California (the employer of Drs Horvath and Lu) has filed patents surrounding several epigenetic biomarkers of aging (including GrimAge), listing Drs Horvath and Lu as inventors. Dr Lubitz receives sponsored research support from Bristol-Myers Squibb–Pfizer, Bayer AG, Boehringer Ingelheim, and Fitbit; has consulted for Bristol-Myers Squibb–Pfizer and Bayer AG; and participates in a research collaboration with IBM. Dr Ellinor is supported by a grant from Bayer AG to the Broad Institute focused on the genetics and therapeutics of cardiovascular diseases; and has served on advisory boards or consulted for Bayer AG, Quest Diagnostics, MyoKardia, and Novartis. Dr Benjamin serves as an uncompensated member for the MyHeartLab Steering Committee. The MyHeartLab Study is a principal investigator–initiated study from the University of California–San Francisco (Principal Investigator: Jeffrey Olgin, MD), through a research grant to University of California–San Francisco from Samsung. The other authors report no conflicts. Publisher Copyright: © 2021 Lippincott Williams and Wilkins. All rights reserved.

PY - 2021/12/14

Y1 - 2021/12/14

N2 - 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.

AB - 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.

KW - aging

KW - atrial fibrillation

KW - epigenomics

KW - genetics

UR - http://www.scopus.com/inward/record.url?scp=85122714336&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85122714336&partnerID=8YFLogxK

U2 - 10.1161/CIRCULATIONAHA.121.056456

DO - 10.1161/CIRCULATIONAHA.121.056456

M3 - Article

C2 - 34587750

AN - SCOPUS:85122714336

SN - 0009-7322

VL - 144

SP - 1899

EP - 1911

JO - Circulation

JF - Circulation

IS - 24

ER -

Epigenetic Age and the Risk of Incident Atrial Fibrillation

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