Drug addiction is a chronically relapsing disease associated with deficits in brain function and structure in regions that underlie reward processing and self-control, manifesting as a pernicious syndrome of impaired response inhibition and salience attribution (iRISA). This syndrome is likely further modulated by select genetic variations that precede and/or exacerbate the addiction, evidenced by studies that have examined the influence of single nucleotide polymorphisms (SNPs) on brain and behavior. However, this approach is fundamentally limited insofar as individual SNPs (e.g., DAT1, MAOA) are likely to explain only a small portion of behavior in complex disorders such as addiction. To move the field forward, this proposal seeks to implement an innovative analysis pipeline to fundamentally expand upon the menu of genetic factors that may contribute to cocaine addiction (i.e., beyond traditional candidate genes) while simultaneously avoiding the potential pitfalls of genome-wide association (GWAS) studies (i.e., insufficient statistical power). The analysis pipeline proceeds according to the following steps, which will be applied to an already-collected sample (Sample 1) and a new, ongoing sample (Sample 2): (A) probing for group differences between individuals with cocaine use disorder (iCUD) and healthy controls (HC) in structural gray matter volume (GMV), a reliable and robust neuroimaging modality; (B) for those regions exhibiting between-group differences, using a freely-available brain Atlas to map and identify gene SNPs, coexpression networks, and region-specific transcripts; and (C) using DNA samples for empirical testing of these same select genes, SNPs, and networks in iCUD and HC for verification of influence. For Sample 2 specifically, an additional primary outcome of interest is the prospective prediction of future drug use in iCUD, assessed as part of 4 follow-up study sessions with multiple, valid objective and subjective drug use probes. In sum, this study uses a novel data-driven imaging genetics approach to identify previously uncharacterized genetic differences between iCUD and HC, which in turn will be used to correlate with brain morphology and predict drug-relevant outcomes in cocaine addiction.

Public Health Relevance

This research has the potential to identify in human cocaine addiction targeted genetic factors that associate with brain morphology and predict future drug use. With this new genetic information in hand, future clinical interventions can target the most vulnerable individuals for additional therapies, enabling more appropriate and efficient allocation of scarce clinical resources.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01DA037452-06
Application #
9668121
Study Section
Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section (NPAS)
Program Officer
Lin, Yu
Project Start
2015-05-01
Project End
2020-03-31
Budget Start
2019-04-01
Budget End
2020-03-31
Support Year
6
Fiscal Year
2019
Total Cost
Indirect Cost
Name
State University New York Stony Brook
Department
Psychiatry
Type
Schools of Medicine
DUNS #
804878247
City
Stony Brook
State
NY
Country
United States
Zip Code
11794
Moeller, Scott J; Fink, David S; Gbedemah, Misato et al. (2018) Trends in Illicit Drug Use Among Smokers and Nonsmokers in the United States, 2002-2014. J Clin Psychiatry 79:
Guttman, Zoe; Moeller, Scott J; London, Edythe D (2018) Neural underpinnings of maladaptive decision-making in addictions. Pharmacol Biochem Behav 164:84-98
Moeller, Scott J; Paulus, Martin P (2018) Toward biomarkers of the addicted human brain: Using neuroimaging to predict relapse and sustained abstinence in substance use disorder. Prog Neuropsychopharmacol Biol Psychiatry 80:143-154
Moeller, Scott J; Zilverstand, Anna; Konova, Anna B et al. (2018) Neural Correlates of Drug-Biased Choice in Currently Using and Abstinent Individuals With Cocaine Use Disorder. Biol Psychiatry Cogn Neurosci Neuroimaging 3:485-494
Sullivan, Ryan M; Perlman, Greg; Moeller, Scott J (2018) Meta-analysis of aberrant post-error slowing in substance use disorder: implications for behavioral adaptation and self-control. Eur J Neurosci :
Alia-Klein, Nelly; Preston-Campbell, Rebecca N; Moeller, Scott J et al. (2018) Trait anger modulates neural activity in the fronto-parietal attention network. PLoS One 13:e0194444
Moeller, Scott J; Okita, Kyoji; Robertson, Chelsea L et al. (2018) Low Striatal Dopamine D2-type Receptor Availability is Linked to Simulated Drug Choice in Methamphetamine Users. Neuropsychopharmacology 43:751-760
Rabin, Rachel A; Moeller, Scott J (2017) Commentary on Stewart et al. (2017): Stimulants and marijuana-the potential value in studying substance co-use. Addiction 112:1578-1579
Parvaz, Muhammad A; Moeller, Scott J; d'Oleire Uquillas, Federico et al. (2017) Prefrontal gray matter volume recovery in treatment-seeking cocaine-addicted individuals: a longitudinal study. Addict Biol 22:1391-1401
Parvaz, Muhammad A; Moeller, Scott J; Malaker, Pias et al. (2017) Abstinence reverses EEG-indexed attention bias between drug-related and pleasant stimuli in cocaine-addicted individuals. J Psychiatry Neurosci 42:78-86

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