Meta-Analysis

. 2018 Feb;23(2):422-433.

doi: 10.1038/mp.2016.192. Epub 2016 Nov 15.

A DNA methylation biomarker of alcohol consumption

C Liu^{1

2

3}, R E Marioni^{4

5

6}, Å K Hedman⁷, L Pfeiffer^{8

9}, P-C Tsai¹⁰, L M Reynolds¹¹, A C Just¹², Q Duan¹³, C G Boer¹⁴, T Tanaka¹⁵, C E Elks¹⁶, S Aslibekyan¹⁷, J A Brody¹⁸, B Kühnel^{8

9}, C Herder^{19

20}, L M Almli²¹, D Zhi²², Y Wang²³, T Huan^{1

2}, C Yao^{1

2}, M M Mendelson^{1

2}, R Joehanes^{1

2

24}, L Liang²⁵, S-A Love²³, W Guan²⁶, S Shah^{6

27}, A F McRae^{6

27}, A Kretschmer^{8

9}, H Prokisch^{28

29}, K Strauch^{30

31}, A Peters^{8

9

32}, P M Visscher^{4

6

27}, N R Wray^{6

27}, X Guo³³, K L Wiggins¹⁸, A K Smith²¹, E B Binder³⁴, K J Ressler³⁵, M R Irvin¹⁷, D M Absher³⁶, D Hernandez³⁷, L Ferrucci¹⁵, S Bandinelli³⁸, K Lohman¹¹, J Ding³⁹, L Trevisi⁴⁰, S Gustafsson⁷, J H Sandling^{41

42}, L Stolk¹⁴, A G Uitterlinden^{14

43}, I Yet¹⁰, J E Castillo-Fernandez¹⁰, T D Spector¹⁰, J D Schwartz⁴⁴, P Vokonas⁴⁵, L Lind⁴⁶, Y Li⁴⁷, M Fornage⁴⁸, D K Arnett⁴⁹, N J Wareham¹⁶, N Sotoodehnia¹⁸, K K Ong¹⁶, J B J van Meurs¹⁴, K N Conneely⁵⁰, A A Baccarelli⁵¹, I J Deary^{4

52}, J T Bell¹⁰, K E North²³, Y Liu¹¹, M Waldenberger^{8

9}, S J London⁵³, E Ingelsson^{7

54}, D Levy^{1

2}

Affiliations

¹ The Framingham Heart Study, Framingham, MA, USA.
² The Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA.
³ Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
⁴ Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
⁵ Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
⁶ Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia.
⁷ Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
⁸ Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
⁹ Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
¹⁰ Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
¹¹ Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA.
¹² Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹³ Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
¹⁴ Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands.
¹⁵ Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA.
¹⁶ MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
¹⁷ Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
¹⁸ Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
¹⁹ German Center for Diabetes Research (DZD), München-Neuherberg, Germany.
²⁰ Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany.
²¹ Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.
²² School of Biomedical Informatics and School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
²³ Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
²⁴ Hebrew SeniorLife, Harvard Medical School, Boston, MA, USA.
²⁵ Harvard School of Public Health, Harvard University, Boston, MA, USA.
²⁶ Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
²⁷ Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.
²⁸ Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
²⁹ Institute of Human Genetics, Technische Universität München, München, Germany.
³⁰ Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany.
³¹ Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
³² DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.
³³ Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA.
³⁴ Max-Planck Institute of Psychiatry, Munich, Germany.
³⁵ Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, MA, USA.
³⁶ HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.
³⁷ Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.
³⁸ Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence, Italy.
³⁹ Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
⁴⁰ Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁴¹ Department of Medical Sciences, Rheumatology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
⁴² Department of Medical Sciences, Molecular Medicine and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
⁴³ Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.
⁴⁴ Departments of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁴⁵ VA Boston Healthcare System and Boston University Schools of Public Health and Medicine, Jamaica Plain, MA, USA.
⁴⁶ Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden.
⁴⁷ Department of Genetics, Department of Biostatistics and Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA.
⁴⁸ Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston TX, USA.
⁴⁹ College of Public Health, University of Kentucky, Lexington, KY, USA.
⁵⁰ Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA.
⁵¹ Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
⁵² Department of Psychology, University of Edinburgh, Edinburgh, UK.
⁵³ Department of Health and Human Services, Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA.
⁵⁴ Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.

PMID: 27843151
PMCID: PMC5575985
DOI: 10.1038/mp.2016.192

Meta-Analysis

A DNA methylation biomarker of alcohol consumption

C Liu et al. Mol Psychiatry. 2018 Feb.

. 2018 Feb;23(2):422-433.

doi: 10.1038/mp.2016.192. Epub 2016 Nov 15.

Authors

Affiliations

¹ The Framingham Heart Study, Framingham, MA, USA.
² The Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA.
³ Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
⁴ Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
⁵ Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
⁶ Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia.
⁷ Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
⁸ Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
⁹ Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
¹⁰ Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
¹¹ Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA.
¹² Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹³ Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
¹⁴ Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands.
¹⁵ Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA.
¹⁶ MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
¹⁷ Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
¹⁸ Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA.
¹⁹ German Center for Diabetes Research (DZD), München-Neuherberg, Germany.
²⁰ Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany.
²¹ Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.
²² School of Biomedical Informatics and School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
²³ Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
²⁴ Hebrew SeniorLife, Harvard Medical School, Boston, MA, USA.
²⁵ Harvard School of Public Health, Harvard University, Boston, MA, USA.
²⁶ Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
²⁷ Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.
²⁸ Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
²⁹ Institute of Human Genetics, Technische Universität München, München, Germany.
³⁰ Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany.
³¹ Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
³² DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.
³³ Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, USA.
³⁴ Max-Planck Institute of Psychiatry, Munich, Germany.
³⁵ Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, MA, USA.
³⁶ HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.
³⁷ Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.
³⁸ Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence, Italy.
³⁹ Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA.
⁴⁰ Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁴¹ Department of Medical Sciences, Rheumatology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
⁴² Department of Medical Sciences, Molecular Medicine and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
⁴³ Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.
⁴⁴ Departments of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁴⁵ VA Boston Healthcare System and Boston University Schools of Public Health and Medicine, Jamaica Plain, MA, USA.
⁴⁶ Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden.
⁴⁷ Department of Genetics, Department of Biostatistics and Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA.
⁴⁸ Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston TX, USA.
⁴⁹ College of Public Health, University of Kentucky, Lexington, KY, USA.
⁵⁰ Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA.
⁵¹ Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
⁵² Department of Psychology, University of Edinburgh, Edinburgh, UK.
⁵³ Department of Health and Human Services, Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA.
⁵⁴ Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.

PMID: 27843151
PMCID: PMC5575985
DOI: 10.1038/mp.2016.192

Abstract

The lack of reliable measures of alcohol intake is a major obstacle to the diagnosis and treatment of alcohol-related diseases. Epigenetic modifications such as DNA methylation may provide novel biomarkers of alcohol use. To examine this possibility, we performed an epigenome-wide association study of methylation of cytosine-phosphate-guanine dinucleotide (CpG) sites in relation to alcohol intake in 13 population-based cohorts (n_total=13 317; 54% women; mean age across cohorts 42-76 years) using whole blood (9643 European and 2423 African ancestries) or monocyte-derived DNA (588 European, 263 African and 400 Hispanic ancestry) samples. We performed meta-analysis and variable selection in whole-blood samples of people of European ancestry (n=6926) and identified 144 CpGs that provided substantial discrimination (area under the curve=0.90-0.99) for current heavy alcohol intake (⩾42 g per day in men and ⩾28 g per day in women) in four replication cohorts. The ancestry-stratified meta-analysis in whole blood identified 328 (9643 European ancestry samples) and 165 (2423 African ancestry samples) alcohol-related CpGs at Bonferroni-adjusted P<1 × 10^-7. Analysis of the monocyte-derived DNA (n=1251) identified 62 alcohol-related CpGs at P<1 × 10^-7. In whole-blood samples of people of European ancestry, we detected differential methylation in two neurotransmitter receptor genes, the γ-Aminobutyric acid-A receptor delta and γ-aminobutyric acid B receptor subunit 1; their differential methylation was associated with expression levels of a number of genes involved in immune function. In conclusion, we have identified a robust alcohol-related DNA methylation signature and shown the potential utility of DNA methylation as a clinically useful diagnostic test to detect current heavy alcohol consumption.

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Conflict of interest statement

Erik Ingelsson is an advisor and consultant for Precision Wellness Inc (Redwood City, CA). The remaining authors declare no conflict of interest.

Figures

**Figure 1**
Overview of the study design. ARIC, The Atherosclerosis Risk in Communities study; BMI, body mass index; DNAm, DNA methylation value; FHS, the Framingham Heart Study; I (light/at-risk/heavy drinkers versus non-drinkers), the indicator variable for light drinkers versus non-drinkers, at-risk drinkers versus non-drinkers and heavy drinkers versus non-drinkers; KORA F4, The Cooperative Health Research in the Region of Augsburg study; LASSO, least absolute shrinkage and selection operator; LBC, The Lothian Birth Cohort; MESA, The Multi-Ethnic Study of Atherosclerosis; WBCs, white blood cell counts.

**Figure 2**
A biomarker of heavy alcohol drinking. Four sets of cytosine-phosphate-guanine dinucleotides (CpGs) were selected at s=0.12 (5 CpGs), s=0.08 (23 CpGs), s=‘lambda.1se’ (78 CpGs) and s=‘lambda.min’ (144 CpGs) using least absolute shrinkage and selection operator (LASSO) in the Framingham Heart Study (FHS) cohort (the training cohort). ROC analysis was performed to classify heavy drinkers versus non-drinkers (left figure) and heavy drinkers versus light drinkers (right figure). ‘Non-drinkers’ were subjects with no alcohol consumption (i.e., g per day=0); ‘light drinkers’ were subjects who consumed 0<g per day⩽28 in men and 0<g per day⩽14 in women; ‘heavy drinkers’ were subjects who consumed ⩾42 g per day in men and ⩾28 g per day in women. ARIC, The Atherosclerosis Risk in Communities study; KORA F4, The Cooperative Health Research in the Region of Augsburg study; LBC1936, The Lothian Birth Cohort 1936; MESA, The Multi-Ethnic Study of Atherosclerosis.

**Figure 3**
Meta-analysis of epigenome-wide association of alcohol intake in European ancestry (EA) whole-blood samples: the Manhattan plot (top) and the volcano plot (bottom). The DNA methylation proportion was the outcome variable, grams alcohol consumed per day (g per day) was the predictor variable, adjusting for age, sex, body mass index, technical covariates and white blood cell counts. The inverse-variance weighted random-effects model was performed in meta-analysis using all whole blood DNA samples of EA.

**Figure 4**
Comparison of regression coefficients of the significant cytosine-phosphate-guanine dinucleotides (CpGs) in association analysis of the continuous alcohol trait (g per day): (a) between European and African whole-blood samples; (b) the Forest plot of effect estimates and standard errors of cg11376147 in all study cohorts; and (c) between European whole-blood and CD14+ monocyte samples. (a) Includes a list of CpGs with P<1 × 10⁻⁷ in EA or AA whole-blood samples and (c) includes a list of CpGs with P<1 × 10⁻⁷ in EA whole-blood samples or in monocyte samples of mixed ancestries. The Pearson’s correlation was r=0.64 between the effect estimates in (a) and r=0.72 in (c). MM, monocyte, mixed ancestries; WB AA, whole blood, African ancestry; WB EA, whole blood, European ancestry.

**Figure 5**
The γ-aminobutyric acid-A (GABA-A) receptor, delta (*GABRD*): the associations of the 36 cytosine-phosphate-guanine dinucleotides (CpGs) within *GABRD*, genomic and regulatory features and correlation of methylation measurements. The results were obtained in meta-analysis of the association analysis of 9643 whole-blood-derived DNA samples of European ancestry (EA) individuals. The correlation of these 36 CpGs was calculated using the methylation measurements at 36 CpGs, adjusting for age, sex, technical covariates and white cell blood counts in the Framingham Heart Study samples.

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Comment in

Overestimation of the classification accuracy of a biomarker for assessing heavy alcohol use.
Hattab MW, Clark SL, van den Oord EJCG. Hattab MW, et al. Mol Psychiatry. 2018 Nov;23(11):2114-2115. doi: 10.1038/mp.2017.181. Mol Psychiatry. 2018. PMID: 28894303 Free PMC article. No abstract available.

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A DNA methylation biomarker of alcohol consumption

Affiliations

A DNA methylation biomarker of alcohol consumption

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Comment in

References

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical