TY - JOUR
T1 - A new monocyte epigenetic clock reveals nonlinear effects of alcohol consumption on biological aging in three independent cohorts (N = 2242)
AU - Liang, Xiaoyu
AU - Sinha, Rajita
AU - Justice, Amy C.
AU - Cohen, Mardge H.
AU - Aouizerat, Bradley E.
AU - Xu, Ke
N1 - Funding Information:
The project was supported by the National Institute on Drug Abuse [R03 DA039745 (Xu), R01 DA038632 (Xu), R01 DA047063 (Xu and Aouizerat), R01 DA047820 (Xu and Aouizerat)], R01 DA013892 (Sinha), PL1 DA024859 (Sinha). COMpAAAS/Veterans Aging Cohort Study, a CHAART Cooperative Agreement, is supported by the National Institutes of Health: National Institute on Alcohol Abuse and Alcoholism (U24‐AA020794, U01‐AA020790, U01‐AA020795, U01‐AA020799; U10‐AA013566‐completed) and in kind by the US Department of Veterans Affairs. In addition to grant support from NIAAA, we gratefully acknowledge the scientific contributions of Dr. Kendall Bryant, our Scientific Collaborator. Additional grant support from the National Institute on Drug Abuse R01‐DA035616 is acknowledged. MWCCS (Principal Investigators): Atlanta CRS (Ighovwerha Ofotokun, Anandi Sheth, and Gina Wingood), U01‐HL146241; Bronx CRS (Kathryn Anastos and Anjali Sharma), U01‐HL146204; Brooklyn CRS (Deborah Gustafson and Tracey Wilson), U01‐HL146202; Data Analysis and Coordination Center (Gypsyamber D’Souza, Stephen Gange and Elizabeth Golub), U01‐HL146193; Chicago‐Cook County CRS (Mardge Cohen and Audrey French), U01‐HL146245; Northern California CRS (Bradley Aouizerat, Jennifer Price, and Phyllis Tien), U01‐HL146242; Metropolitan Washington CRS (Seble Kassaye and Daniel Merenstein), U01‐HL146205; Miami CRS (Maria Alcaide, Margaret Fischl, and Deborah Jones), U01‐HL146203; UAB‐MS CRS (Mirjam‐Colette Kempf, Jodie Dionne‐Odom, and Deborah Konkle‐Parker), U01‐HL146192; UNC CRS (Adaora Adimora), U01‐HL146194. The MWCCS is funded primarily by the National Heart, Lung, and Blood Institute (NHLBI), with additional co‐funding from the Eunice Kennedy Shriver National Institute Of Child Health & Human Development (NICHD), National Institute On Aging (NIA), National Institute Of Dental & Craniofacial Research (NIDCR), National Institute Of Allergy And Infectious Diseases (NIAID), National Institute Of Neurological Disorders And Stroke (NINDS), National Institute Of Mental Health (NIMH), National Institute On Drug Abuse (NIDA), National Institute Of Nursing Research (NINR), National Cancer Institute (NCI), National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institute on Deafness and Other Communication Disorders (NIDCD), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute on Minority Health and Health Disparities (NIMHD), and in coordination and alignment with the research priorities of the National Institutes of Health, Office of AIDS Research (OAR). MWCCS data collection is also supported by UL1‐TR000004 (UCSF CTSA), P30‐AI‐050409 (Atlanta CFAR), P30‐AI‐050410 (UNC CFAR), and P30‐AI‐027767 (UAB CFAR).
Publisher Copyright:
© 2022 by the Research Society on Alcoholism.
PY - 2022
Y1 - 2022
N2 - Background: Assessing the effect of alcohol consumption on biological age is essential for understanding alcohol use-related comorbidities and mortality. Previously developed epigenetic clocks are mainly based on DNA methylation in heterogeneous cell types, which provide limited knowledge on the impacts of alcohol consumption at the individual cellular level. Evidence shows that monocytes play an important role in both alcohol-induced pathophysiology and the aging process. In this study, we developed a novel monocyte-based DNA methylation clock (MonoDNAmAge) to assess the impact of alcohol consumption on monocyte age. Methods: A machine learning method was applied to select a set of chronological age-associated DNA methylation CpG sites from 1202 monocyte methylomes. Pearson correlation was tested between MonoDNAmAge and chronological age in three independent cohorts (Ntotal = 2242). Using the MonoDNAmAge clock and four established clocks (i.e., HorvathDNAmAge, HannumDNAmAge, PhenoDNAmAge, GrimDNAmAge), we then evaluated the effect of alcohol consumption on epigenetic aging in the three cohorts [i.e., Yale Stress Center Community Study (YSCCS), Veteran Aging Cohort Study (VACS), Women's Interagency HIV Study (WIHS)] using linear and quadratic models. Results: The MonoDNAmAge, comprised of 186 CpG sites, was moderately to strongly correlated with chronological age in the three cohorts (r = 0.90, p = 3.12E−181 in YSCCS; r = 0.54, p = 1.75E−96 in VACS; r = 0.66, p = 1.50E−60 in WIHS). More importantly, we found a nonlinear association between MonoDNAmAge and alcohol consumption (pmodel = 4.55E−08, (Formula presented.) = 7.80E−08 in YSCCS; pmodel = 1.85E−02, (Formula presented.) = 3.46E−02 in VACS). Heavy alcohol consumption increased EAAMonoDNAmAge up to 1.60 years while light alcohol consumption decreased EAAMonoDNAmAge up to 2.66 years. These results were corroborated by the four established epigenetic clocks (i.e., HorvathDNAmAge, HannumDNAmAge, PhenoDNAmAge, GrimDNAmAge). Conclusions: The results suggest a nonlinear relationship between alcohol consumption and its effects on epigenetic age. Considering adverse effects of alcohol consumption on health, nonlinear effects of alcohol use should be interpreted with caution. The findings, for the first time, highlight the complex effects of alcohol consumption on biological aging.
AB - Background: Assessing the effect of alcohol consumption on biological age is essential for understanding alcohol use-related comorbidities and mortality. Previously developed epigenetic clocks are mainly based on DNA methylation in heterogeneous cell types, which provide limited knowledge on the impacts of alcohol consumption at the individual cellular level. Evidence shows that monocytes play an important role in both alcohol-induced pathophysiology and the aging process. In this study, we developed a novel monocyte-based DNA methylation clock (MonoDNAmAge) to assess the impact of alcohol consumption on monocyte age. Methods: A machine learning method was applied to select a set of chronological age-associated DNA methylation CpG sites from 1202 monocyte methylomes. Pearson correlation was tested between MonoDNAmAge and chronological age in three independent cohorts (Ntotal = 2242). Using the MonoDNAmAge clock and four established clocks (i.e., HorvathDNAmAge, HannumDNAmAge, PhenoDNAmAge, GrimDNAmAge), we then evaluated the effect of alcohol consumption on epigenetic aging in the three cohorts [i.e., Yale Stress Center Community Study (YSCCS), Veteran Aging Cohort Study (VACS), Women's Interagency HIV Study (WIHS)] using linear and quadratic models. Results: The MonoDNAmAge, comprised of 186 CpG sites, was moderately to strongly correlated with chronological age in the three cohorts (r = 0.90, p = 3.12E−181 in YSCCS; r = 0.54, p = 1.75E−96 in VACS; r = 0.66, p = 1.50E−60 in WIHS). More importantly, we found a nonlinear association between MonoDNAmAge and alcohol consumption (pmodel = 4.55E−08, (Formula presented.) = 7.80E−08 in YSCCS; pmodel = 1.85E−02, (Formula presented.) = 3.46E−02 in VACS). Heavy alcohol consumption increased EAAMonoDNAmAge up to 1.60 years while light alcohol consumption decreased EAAMonoDNAmAge up to 2.66 years. These results were corroborated by the four established epigenetic clocks (i.e., HorvathDNAmAge, HannumDNAmAge, PhenoDNAmAge, GrimDNAmAge). Conclusions: The results suggest a nonlinear relationship between alcohol consumption and its effects on epigenetic age. Considering adverse effects of alcohol consumption on health, nonlinear effects of alcohol use should be interpreted with caution. The findings, for the first time, highlight the complex effects of alcohol consumption on biological aging.
KW - alcohol consumption
KW - epigenetic age acceleration
KW - monocyte epigenetic clock
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U2 - 10.1111/acer.14803
DO - 10.1111/acer.14803
M3 - Article
C2 - 35257385
AN - SCOPUS:85126339847
JO - Alcoholism: Clinical and Experimental Research
JF - Alcoholism: Clinical and Experimental Research
SN - 0145-6008
ER -