While biometric genetic studies have long indicated substantial heritability for drinking behaviors and addiction, progress in mapping this influence onto specific genetic variants has been slow and once found, these genetic variants have only modest predictive power. DNA methylation studies represent a promising complement to genetic studies focusing on sequence variation because methylation is directly related to gene expression and can potentially be used as a biomarker for alcohol disorders. The overarching goal of this proposal is to provide the candidate the training and research opportunities necessary to utilize next generation sequencing methods, such as methylome sequencing, to study drinking behaviors and addiction, thus supporting the candidate's long-term career goal of becoming an independent investigator in the area. General training goals include strengthening knowledge of substantive issues in drinking behaviors and addiction and statistical genetics, and building proficiency in bioinformatics and computer programming. Proposed training in these areas consists of an interlocking program of coursework, intensive mentoring, summer programs, reading groups, seminar series and conferences, with special attention to training in research ethics. Direct mentoring is a key feature of this program, with access to leading experts in each of the proposed training areas (i.e., Drs. Edwin van den Oord and Dr. Michael Neale - statistical genetics, bioinformatics and programming, Dr. Michael Miles and David Goldman - substantive expertise in the genetics of drinking behaviors and addiction) representing a core strength of the proposed training plan. The candidate proposes to apply acquired skills in the research portion of the project by conducting a multistage whole methylome analysis to study drinking behaviors and addiction. Methodologically, this project focuses on integrating genomic methods with statistical models to better understand disease mechanisms. This will be facilitated by bringing together an unprecedented combination of whole methylome datasets, including a meta-analysis of data from Swedish national population registries and the EpiTwin project sample, with a combined total sample size of approximately 5,800 individuals. The """"""""discovery"""""""" phase meta-analysis will then be followed by validating the top findings in a follow-up sample of approximately 500 individuals using a """"""""gold standard"""""""" technology that will fine map the locations of methylated sites associated with drinking behaviors and addiction. The project will be further complimented in a final analytical stage in which causal models will be fitted to data on validated methylation sites, and addiction, health and drinking outcomes to investigate the direction of causation between methylation sites and drinking behaviors and addiction. A rodent study will complement the human work and will help gain traction on the issue of whether methylation sites associated with drinking behaviors and addiction can be used as biomarkers for alcoholism.
This K01 award will provide the applicant with the training and resources necessary to establish a program of research that will more precisely articulate the disease mechanisms behind drinking behaviors and addiction. The proposed project's goal of identifying methylated regions of the genome associated with drinking behaviors and outcomes will help identify the genetic underpinnings of addiction in these substances and can ultimately be used to improve the prevention and treatment of drinking outcomes and addiction by identifying biomarkers for alcohol disorders.
|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, Mohammad W; Shabalin, Andrey A; Clark, Shaunna L et al. (2017) Correcting for cell-type effects in DNA methylation studies: reference-based method outperforms latent variable approaches in empirical studies. Genome Biol 18:24|
|Clark, Shaunna L; McClay, Joseph L; Adkins, Daniel E et al. (2017) Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence. Alcohol Clin Exp Res 41:711-718|
|Cho, Seung Bin; Aliev, Fazil; Clark, Shaunna L et al. (2017) Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders. Behav Genet 47:405-415|
|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 :|
|Clark, Shaunna L; McClay, Joseph L; Adkins, Daniel E et al. (2016) Deep Sequencing of Three Loci Implicated in Large-Scale Genome-Wide Association Study Smoking Meta-Analyses. Nicotine Tob Res 18:626-31|
|Clark, Shaunna L; Gillespie, Nathan A; Adkins, Daniel E et al. (2016) Psychometric modeling of abuse and dependence symptoms across six illicit substances indicates novel dimensions of misuse. Addict Behav 53:132-40|
|Neale, Michael C; Clark, Shaunna L; Dolan, Conor V et al. (2016) Regime Switching Modeling of Substance Use: Time-Varying and Second-Order Markov Models and Individual Probability Plots. Struct Equ Modeling 23:221-233|
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