Multilocus Genetic Profile for Dopamine Signaling Predicts Ventral Striatum Reactivity

Abstract

Research integrating neuroimaging and molecular genetics has yielded important insights into how variability in brain chemistry predicts individual differences in brain function, behavior and related risk for psychopathology. However, existing studies have been limited by their focus on the independent effects of single polymorphisms with modest impact on brain chemistry. Here, we explored the effects of five functional polymorphisms affecting dopamine (DA) signaling on reward-related ventral striatum (VS) reactivity, measured with BOLD fMRI, in a sample of 69 Caucasians. We also compiled individual multilocus genetic profile scores reflecting the additive effects of alleles conferring relatively increased DA signaling across the five polymorphic loci: DAT1 9-repeat, DRD4 7-repeat, DRD2 -141C Del, DRD2 Taq1A C (A2), and COMT 158 Met. These multilocus DA profile scores accounted for 10.9% of the inter-individual variability in reward-related VS reactivity. In contrast, none of the individual polymorphisms accounted for significant variability. Our results show that biologically informed multilocus genetic profiles have unique promise as indices of variability in brain chemistry that may yield advances in mapping individual differences in behaviorally relevant brain function. In turn, such genetic profiles may fuel gene-environment interactions research establishing trajectories of risk for psychopathology.

Functional Genetic Variation in Dopamine Signaling Moderates Prefrontal Cortical Activity During Risky Decision Making

“…In concordance with our data, two prior reports found that an aggregate of genes provided a stronger account of the neural substrates underlying reward reactivity of the striatum than individual genes (Nikolova et al, 2011;Stice et al, 2012). Despite opposite scoring algorithms employed for DAT1 and DRD4 genotypes in these two studies, both found that ventral striatal reactivity to food or monetary reward varied as a function of a multilocus genetic score.…”

“…Genetic composite scores have been used as an index for dopaminergic activity, and a link between genes involved in dopamine signaling capacity and ventral striatal reactivity to rewards has been demonstrated (Nikolova et al, 2011;Stice et al, 2012). Because neuropsychiatric disorders that feature decisionmaking deficits are associated with dysregulated dopamine function (Frank et al, 2007;Rahman et al, 2001), understanding the link between markers for striatal dopamine activity and neural function in healthy individuals may help select therapeutic targets for pathological conditions.…”

Predicting White Matter Integrity from Multiple Common Genetic Variants

“…Biffi et al (2010) found that 3% of the variance in MRI-derived volumes of several brain regions could be explained from a number of candidate genes for Alzheimer's disease. Nikolova et al (2011) showed 11% of the variance in ventral striatal reactivity could be explained from their panel of five polymorphisms. We also found that our candidate polymorphisms displayed extensive, significant effects on 82% of the volume of the corpus callosum, when cumulatively modeled at a voxelwise FA basis, which captures more spatial detail than an average measure of FA across the corpus callosum.…”

“…Carayol et al (2010), for instance, reported on the cumulative effect of four candidate SNPs on the risk for autism, using a casecontrol approach. These models are beginning to be applied to brain imaging in the context of neuropsychiatric disorders (Biffi et al, 2010;Hibar et al, 2011a;Nikolova et al, 2011), and may provide more biologically meaningful predictions with implications for personalized diagnosis and therapy.…”

“…As mentioned above, individual effects of single genetic variants on white matter structure have been explored, but a multilocus approach has not yet been taken. The utility of a multilocus candidate gene model in predicting an imagingderived outcome was recently explored in the context of structural MRI (Biffi et al, 2010) and functional MRI (Nikolova et al, 2011), but its applications in DTI and detailed three-dimensional maps of brain structure appear novel. In this paper, we incorporate a subject's genetic signature, at key loci, into a multilocus model.…”