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.
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.
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