Abstract MP71: Smoking and Biological Aging Acceleration Measured by Midlife Proteomic Aging Clocks: Insights from the Multi-Ethnic Study of Atherosclerosis (MESA)

Background: Biological age may provide unique health insights beyond chronological age. Proteomic aging clocks (PACs) assess a person’s biological age, and a positive deviation of biological age from chronological age is known as age acceleration. Smoking has been associated with greater risk of age-related diseases and conditions. It is also associated with age acceleration in previous studies that assessed biological age using DNA methylation-based epigenetic clocks; however, this association has not been investigated using PACs. Methods: A total of 5,762 participants free of CVD from the Multi-Ethnic Study of Atherosclerosis (MESA) had over 7,000 plasma proteins measured using an aptamer-based proteomic profiling platform at exam 1 (2000-2002). Two previously published midlife PACs (ARIC and Lehallier) were calculated from available proteins in MESA, and we calculated age acceleration for each PAC as residuals after regressing PAC on chronological age. We used linear regression to assess the association of self-reported smoking (status, pack-years, and secondhand smoke exposure) with age acceleration measured using both PACs, adjusting for demographics and other potential confounders. Results: The analytic sample was 52% female with a mean age of 62 years (range 45-84) and a race/ethnicity breakdown of 39% White, 12% Chinese, 26% Black, and 23% Hispanic. For smoking, 13% were current smokers, 49% had a total pack-years > 0, and 37% of never smokers had exposure to secondhand smoke. The age acceleration median was -0.15 years using the ARIC midlife PAC and -0.13 years using the Lehallier midlife PAC ( Table ). Smoking status and secondhand smoke exposure in non-smokers were not associated with age acceleration measured by either PAC. Pack-years in ever smokers was positively associated with age acceleration after adjustment for demographics only (model 1). Additional adjustment slightly attenuated the association between pack-years and age acceleration (model 2). Conclusion: Further research is needed to examine the effect of smoking on age acceleration measured by other PACs and determine how these associations compare to those between smoking and epigenetic aging clocks.

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Journal
Circulation
Published
2025-03-11
DOI
https://doi.org/10.1161/cir.151.suppl_1.mp71
Primary Topic
Cardiovascular Health and Risk Factors
Type
article
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article

Abstract MP71: Smoking and Biological Aging Acceleration Measured by Midlife Proteomic Aging Clocks: Insights from the Multi-Ethnic Study of Atherosclerosis (MESA)

Ruth F. Dubin, Shuo Wang, James S. Pankow, Rajat Deo et al.
Circulation
Cardiovascular Health and Risk Factors
article

Abstract MP71: Smoking and Biological Aging Acceleration Measured by Midlife Proteomic Aging Clocks: Insights from the Multi-Ethnic Study of Atherosclerosis (MESA)

Ruth F. Dubin, Shuo Wang, James S. Pankow, Rajat Deo, Peter Ganz, Jeffrey R. Misialek, Anna E. Prizment, Pamela L. Lutsey, Sanaz Sedaghat, Yongmei Liu, Weihua Guan
article en

Abstract

Background: Biological age may provide unique health insights beyond chronological age. Proteomic aging clocks (PACs) assess a person’s biological age, and a positive deviation of biological age from chronological age is known as age acceleration. Smoking has been associated with greater risk of age-related diseases and conditions. It is also associated with age acceleration in previous studies that assessed biological age using DNA methylation-based epigenetic clocks; however, this association has not been investigated using PACs. Methods: A total of 5,762 participants free of CVD from the Multi-Ethnic Study of Atherosclerosis (MESA) had over 7,000 plasma proteins measured using an aptamer-based proteomic profiling platform at exam 1 (2000-2002). Two previously published midlife PACs (ARIC and Lehallier) were calculated from available proteins in MESA, and we calculated age acceleration for each PAC as residuals after regressing PAC on chronological age. We used linear regression to assess the association of self-reported smoking (status, pack-years, and secondhand smoke exposure) with age acceleration measured using both PACs, adjusting for demographics and other potential confounders. Results: The analytic sample was 52% female with a mean age of 62 years (range 45-84) and a race/ethnicity breakdown of 39% White, 12% Chinese, 26% Black, and 23% Hispanic. For smoking, 13% were current smokers, 49% had a total pack-years > 0, and 37% of never smokers had exposure to secondhand smoke. The age acceleration median was -0.15 years using the ARIC midlife PAC and -0.13 years using the Lehallier midlife PAC ( Table ). Smoking status and secondhand smoke exposure in non-smokers were not associated with age acceleration measured by either PAC. Pack-years in ever smokers was positively associated with age acceleration after adjustment for demographics only (model 1). Additional adjustment slightly attenuated the association between pack-years and age acceleration (model 2). Conclusion: Further research is needed to examine the effect of smoking on age acceleration measured by other PACs and determine how these associations compare to those between smoking and epigenetic aging clocks.

CirculationVol. 151(Suppl_1)
Duke University (US), University of Minnesota System (US), Chan Zuckerberg Initiative (United States) (US), University of Pennsylvania (US), The University of Texas Southwestern Medical Center (US)
Openalex Percentile: Top 87%
Cardiovascular Health and Risk Factors
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