Despite extensive anti-drinking efforts, 8.5% of US adults abuse or are dependent on alcohol. Excessive drinkers are at higher risk for morbidity and negative health consequences such as such as cancer and neurocognitive decline. While genetic sequence variation contributes to alcohol addiction, mounting evidence suggests that DNA methylation may provide complementary information. First, methylation marks may improve the prediction of alcohol addiction risk as they can capture fundamentally different disease processes and directly affect gene expression. Second, methylation studies may increase our understanding of alcohol addiction. For example, phenomena such as withdrawal and tolerance suggest that repeated alcohol use creates a ?biological memory? affecting future responses to alcohol. Because alcohol induced epigenetic changes can persist over time and have lasting effects, DNA methylation could shed light on such mechanisms. Third, in addition to tissue specificity, substantial concordance in methylation also often exists across tissues, including brain and blood. The possibility that methylation sites in brain can have corresponding marks in blood that can be measured cost-effectively in easy to collect genomic DNA from blood, makes these sites potentially very powerful biomarkers for use in the clinic to improve the trajectory of alcohol addiction development, diagnosis, and treatment. PAR-16-234 calls for innovative analyses of existing data to study alcohol addiction. To identify methylation biomarkers predicting alcohol use and related health risks, we will bring together an unprecedented combination of existing next-generation sequencing data to perform methylome-wide association studies (MWAS) in three samples with PhenX measures of alcohol. Furthermore, whereas alcohol methylation studies have historically been restricted to a limited number of CpGs, we propose to screen all ~28 million common CpGs in the human genome. The sample size, ~3,300, which will be the largest alcohol methylation study to date, is unprecedented, offering the opportunity to perform methylation biomarker investigations with high statistical power at low cost because the methylation data has already been generated. Successful completion of this project will generate biomarkers to improve the diagnosis and prognosis of alcohol addiction and related health risks.

Public Health Relevance

Alcohol addiction is the third leading lifestyle-related cause of death in the U.S. and is often comorbid with other serious medical conditions such as cardiovascular disease, cirrhosis of the liver and cancer. The goal of this proposal is to develop methylation biomarkers for alcohol addiction and related health risks. Methylation biomarkers can eventually be used to improve the diagnosis, prognosis and treatment of alcohol disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Type
Research Project (R01)
Project #
1R01AA026057-01
Application #
9366113
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Chin, Hemin R
Project Start
2017-09-15
Project End
2020-08-31
Budget Start
2017-09-15
Budget End
2018-08-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Michigan State University
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
193247145
City
East Lansing
State
MI
Country
United States
Zip Code
48824
Dick, Danielle M (2018) Mapping Risk from Genes to Behavior: The Enduring and Evolving Influence of Irving Gottesman's Endophenotype Concept. Twin Res Hum Genet 21:306-309
Clark, Shaunna L; Costin, Blair N; Chan, Robin F et al. (2018) A Whole Methylome Study of Ethanol Exposure in Brain and Blood: An Exploration of the Utility of Peripheral Blood as Proxy Tissue for Brain in Alcohol Methylation Studies. Alcohol Clin Exp Res 42:2360-2368
Han, Laura K M; Aghajani, Moji; Clark, Shaunna L et al. (2018) Epigenetic Aging in Major Depressive Disorder. Am J Psychiatry 175:774-782
Shabalin, Andrey A; Hattab, Mohammad W; Clark, Shaunna L et al. (2018) RaMWAS: fast methylome-wide association study pipeline for enrichment platforms. Bioinformatics 34:2283-2285
Hattab, M W; Clark, S L; van den Oord, E J C G (2017) Overestimation of the classification accuracy of a biomarker for assessing heavy alcohol use. Mol Psychiatry :