Variation on the dopamine D2 receptor gene (DRD2) is associated with basal ganglia-to-frontal structural connectivity

Author’s Accepted Manuscript Variation on the Dopamine D2 Receptor gene (DRD2) is associated with basal ganglia-to-frontal structural connectivity Sebastian Markett, Marcel A. de Reus, Martin Reuter, Christian Montag, Bernd Weber, JanChristoph Schoene-Bake, Martijn P. van den Heuvel

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S1053-8119(17)30294-X http://dx.doi.org/10.1016/j.neuroimage.2017.04.005 YNIMG13946

To appear in: NeuroImage Received date: 21 November 2016 Revised date: 31 March 2017 Accepted date: 3 April 2017 Cite this article as: Sebastian Markett, Marcel A. de Reus, Martin Reuter, Christian Montag, Bernd Weber, Jan-Christoph Schoene-Bake and Martijn P. van den Heuvel, Variation on the Dopamine D2 Receptor gene (DRD2) is associated with basal ganglia-to-frontal structural connectivity, NeuroImage, http://dx.doi.org/10.1016/j.neuroimage.2017.04.005 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Variation on the Dopamine D2 Receptor gene (DRD2) is associated with basal ganglia-tofrontal structural connectivity

Sebastian Markett1,2*, Marcel A. de Reus3, Martin Reuter1,2, Christian Montag4,5, Bernd Weber2,6,7, Jan-Christoph Schoene-Bake8, and Martijn P. van den Heuvel3

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Department of Psychology, University of Bonn, Germany

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Center for Economics and Neuroscience, University of Bonn, Germany

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Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands

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Institute of Psychology and Education, Ulm University, Ulm, Germany

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Key Laboratory for NeuroInformation / Center for Information in Medicine, School of Life Science

and Technology, University of Electronic Science and Technology of China, Chengdu, China 6

Department of Epileptology, University of Bonn, Germany

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Neuroimaging Section, Life and Brain Center, Bonn, Germany

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Auf der Bult Hospital, Hanover, Germany

*

Please address correspondence to: Dr. Sebastian Markett. Department of Psychology, University

of Bonn, Kaiser-Karl-Ring 9, 53111 Bonn, Germany. +49 228 73 4219. [email protected]

Abstract: Dopaminergic neurotransmission in the mesocortical system is crucial for higher order cognition. Common variation on the dopamine D2 receptor (DRD2) gene has been linked to individual differences in dopaminergic signaling and was also repeatedly associated to cognitive markers. The relationship between dopaminergic genetic variants and neurostructural properties of the mesocortical system, however, has received little attention so far. Recently, the direction of a dopaminergic manipulation was predicted from the integrity of fiber tracts between subcortical areas and the

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frontal lobes. Fiber tract integrity was therefore proposed as an indicator of baseline dopamine activity. This raises the question whether DRD2 variants that relate to dopamine turnaround are also linked to fiber tract integrity. In the present study we assessed associations between the DRD2 rs6277 polymorphism and subcortical connections from connectome maps derived from diffusion weighted imaging in n = 105 healthy volunteers (43 males and 62 females). Carriers of the CC genotype who are characterized by elevated striatal dopamine turnaround showed higher integrity in terms of fractional anisotropy on fiber tracts between the basal ganglia and frontal regions compared to carriers of the CT and TT variant. Our results indicate that structural connectivity could serve as a conceptual link between genetically determined individual differences in dopaminergic activity and effects of dopamine challenges on executive functioning.

1. Introduction Dopamine has long been recognized as a key neurotransmitter for a wide range of cognitive control functions, including working memory (Brozoski et al., 1979; Nieoullon, 2002; Robbins, 2005; Cools, 2008). Dopamine is thought to modulate information flow in a neural system consisting of the basal ganglia and the frontal lobe (Williams et al., 2002; Honey et al., 2003; Kayser et al., 2012; Archard & Bullmore, 2007; Kelly et al., 2009; Cole et al., 2012; 2013a, 2013b, Mueller et al., 2014). This system has been described as key neural circuitry underlying flexible goal-oriented behavior (Posthuma & Dagher, 2006; Ystad et al., 2011; Nee & Brown, 2013). Recently, it has been shown that the effect of a pharmacological challenge with the D2 receptor agonist bromocriptine on this circuitry varies with the integrity of white matter fiber tracts implicated in this system (van Schouwenburg et al., 2013). Fractional anisotropy, a summary measure of fiber tract integrity, predicted whether bromocriptine enhanced or decreased neural activity during attentional switching. Such paradoxical effects after D2 receptor stimulation are oftentimes attributed to individual differences in baseline dopamine activity (Kimberg et al., 1997; Gibbs & D’Esposito, 2005; Cools et al., 2007; Cools & D’Esposito, 2011). This raises the question how the integrity of these fiber tracts relates to baseline dopamine activity. Baseline dopaminergic activity is affected by situational factors such as stress, sleep, and arousal in a state-like manner (Robbins, 1997; Pruessner et al., 2004; Volkow et al., 2008). However, it be-

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comes more and more apparent that stable, trait-like individual differences in dopaminergic activity exist that are thought to be affected by genetic variation in the dopaminergic pathway (Bilder et al., 2004; Reuter et al., 2006; Savitz et al., 2006; Dickinsons et al., 2009; Montag & Reuter, 2014). One genetic factor that is thought to index individual differences in striatal baseline dopamine turnaround is DRD2 rs6277, a single nucleotide polymorphism on the dopamine D2 receptor gene DRD2. This naturally occurring genetic variation affects striatal receptor availability (Hirvonen et al., 2005), presumably by affecting post-transcriptional mRNA stability (Duan et al., 2003), and has been linked to cognitive functioning (Rodriguez-Jiminez et al. 2006; Markett et al., 2010; 2011a; Colzato et al., 2011; Felten et al., 2013) and impulsivity (Colzato et al., 2010; Markett et al., 2014), striatal morphology (Markett et al., 2013), and striato-frontal functional connectivity (Stelzel et al., 2010). Throughout these literatures, particularly the CC genotype which can be found in about 25% of the Caucasian population was shown to relate to better cognitive performance and higher baseline dopamine turnover. DRD2 rs6277 is in strong linkage disequlibirum with other DRD2 polymorphisms with implications for individual differences in dopaminergic functioning (Markett et al, 2010; Zhang et al., 2007; Laakso et al., 2005). Because in vitro work suggests a putative functional mechanism for DRD2 rs6277 on the mRNA level (Duan et al., 2003) and our previous work found DRD2 rs6277 to show strongest behavioral associations among several DRD2 polymorphisms (Markett et al., 2010), we focus our present study on this polymorphism and ask if it is associated with white matter connectivity in subcortical-frontal systems. We seek to test this hypothesis by combining connectomic data with molecular genetic data to assess a possible association between DRD2 genotypes (DRD2 rs6277) and prominent subcortical to frontal white matter tracts. We hypothesize to find increased fiber tract integrity in carriers of the CC genotype.

2. Methods Participants A total of N = 105 (43 males and 62 females; mean-age: 28.74, SD = 10.94) healthy Caucasian participants were included. All participants were recruited from the database of the Bonn Gene Brain Behavior Project (BGBBP) and were free of past or present psychiatric or neurological disor-

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ders as assessed by a screening questionnaire. The risk of unwanted population stratification effects was minimized by ensuring that all participants reported to be of Central European descent and to speak German as first language. All participants provided buccal swabs for genotyping along with their informed written consent to link the genetic information to the neuroimaging data. The study protocol was in accordance with the Declaration of Helsinki and approved by the ethics committee of the University Clinics in Bonn.

Genotyping DNA was extracted from buccal cells. Automated purification of genomic DNA was conducted by means of the MagNA Pure(R) LC system using a commercial extraction kit (MagNA Pure LC DNA isolation kit; Roche Diagnostics, Mannheim, Germany). Genotyping was performed by real time polymerase chain reaction (RT-PCR) using melting curve detection analysis on a Light Cycler System (Roche Diagnostics, Mannheim, Germany). The primers and probes used (TIB MOLBIOL, Berlin, Germany) for the RT-PCR were as follows: Forward primer: 5’-GAACTTGTCCGGCTTTACC-3’ Backward primer: 5’-CAATCTTGGGGTGGTCTTT-3’ Anchor hybridisation probe: 5’-LCRed640-CCCCGCCAAACCAGAGAAGAAT-phosphate-3’ Sensor hybridisation probe: 5’-TCCACAGCACTCCCGACA-fluorescein-3’

Image Acquisition All MRI data were acquired at the Life & Brain Center Bonn, Germany on a 3T Magnetom Trio Scanner (Siemens, Erlangen, Germany) using an eight channel head coil. Diffusion weighted imaging (DWI) data was acquired using single-shot, dual echo, spin-echo planar (EPI) imaging (TR = 12 s, TE = 100 ms, 72 axial slices, 1.72 x 1.72 x 1.72 mm resolution, no cardiac gating). As parallel imaging scheme, a GRAPPA technique with an acceleration factor of 2.0 was chosen. Diffusion gradients were isotropically distributed (60 directions, b-value = 1000s/m^2). Seven additional data sets with no diffusion weighting were acquired, combined with one after each block of ten diffusionweighted images as an anatomical reference for motion correction. Along with the diffusion-

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weighted data, a high-resolution T1-weighted image was acquired using an MP-RAGE sequence (160 slices, TR = 1300, TI = 650, TE = 3.97 ms, resolution 1 x 1 x 1 mm, flip angle 10°).

Connectome Reconstruction Structural connectomes were reconstructed as described previously (Markett et al., 2016; de Reus & van den Heuvel, 2014, Schmidt et al., 2014; van den Heuvel et al., 2015): Fiber pathways were reconstructed using the Fiber Assignment by Continuous Tracking Algorithm (Mori et al., 1999), after correcting the DWI data for motion and possible eddy-current distortions and after determining each voxel’s principal diffusion direction using a robust tensor fitting algorithm. Eight seeds were placed evenly distributed within each white matter voxel and streamlines were propagated starting from each seed following the principle diffusion direction from voxel to voxel. This resulted in a comprehensive map of streamlines which represented the spatial distribution of fiber pathways across the brain. The macroscopic connectome was reconstructed in each participant based on a cortical and subcortical gray matter parcellation obtained from the T1-weighted images using the Freesurfer software suite (Fischl et al., 2004). In total, 34 bilateral cortical and 7 bilateral subcortical regions of interest (ROIs) were selected based on Freesurfer’s Desikan-Killiany atlas. Each individual brain network was modeled as a graph G=(V, E), with the 82 ROIs from the Freesurfer parcellation defined as network nodes V, and for each pair of nodes a connecting edge E was placed between the nodes if one or more reconstructed tractography streamlines were found to touch both ROIs. Five weighted network (adjacency) matrices were computed for each participant: (1) a matrix with edges weighted according to the number of reconstructed streamlines touching both ROIs (number of streamlines, NOS), (2) a matrix with edges weighted according to fractional anisotropy (FA) values, and matrices with edges weighted according to (3) axial diffusivity (AD), (4) radial diffusivity (RD), and (5) mean diffusivity (MD).

Fiber tracts of interest We followed Peper et al. (2014) and selected intrahemispheric fiber tracts of interest based on our hypothesis of altered subcortical to frontal connectivity: (1) subcortico-frontal (2) basal gangliafrontal, (3) subcortico-subcortical, and (4) frontal-frontal. Our cortical-subcortical partition encom-

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passed seven subcortical, three basal ganglia, and eleven frontal regions of interest. In order to mitigate the problem of multiple comparisons, we decided to take a global to local approach and focus our analysis on subcortical-frontal connectivity first and then explore this effect further in a set of follow-up analysis on subsets of subcortical and frontal sites. This exploratory analyses also include assessments of connectivity between frontal nodes and the putamen, the caudate, and palladium, respectively. The selected tracts were characterized by mean number of streamlines (NOS), mean FA, mean AD, mean RD, and mean MD values. Throughout the results section, unadjusted NOS values are reported. However, normalizing NOS of an edge e(i,j) by the sum of the volume of the two connected regions i and j (van den Heuvel & Sporns, 2011) revealed similar effects.

Statistical analyses Separate mixed-model analyses of variance (ANOVA) with DRD2 genotype (CC vs. CT vs. TT) as between- and hemisphere (left vs right) as within-subject factor were used to assess genotypefiber tract association. Participants’ age was treated as covariate. This procedure resulted in five (edge weights) times four (fiber tracts of interest) ANOVA models. The family-wise error was controlled by using a Bonferroni-adjusted statistical threshold of p = .05 / 20 = .0025. Following this main analysis, found effects were exploratively assessed in depth. This included testing for associations between DRD2 genotype and more specific connections if the more global fiber tracts of interest analysis suggested an association. Because these test are not independent from the main Bonferroni-adjusted statistical tests, we correct separately for these post-hoc tests by adjusting pvalues for all post-hoc tests with the Bonferroni-method. We additionally complemented our analysis by Bayes factor ANOVAs with DRD2 genotype as between-subject factor, hemisphere as within-subject factor and age as covariate (Love et al, 2015; Rouder et al., 2012). In contrast to the more common frequentist approach, Bayesian tests compare the likelihood of the data given the null and the alternative hypothesis. This results in the Bayes factor which is the ratio between the two likelihoods and reflects the amount of evidence for either hypothesis. The Bayes factor states graded evidence for effects and invariances and can

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therefore also quantify confidence in the absence of the effects of traditional null hypothesis significance tests (Rouder et al., 2016). All calculations were performed with the freely available JASP software package (jasp-stats.org) using default prior scales. Because we were mainly interested in DRD2 genotype effects, we treated all other effects as nuisance and report Bayes factors for the comparisons between models with the DRD2 factor and the null model with all other effects (BF01). Increasing BF01 factors yield more evidence in favor of the null hypothesis. A Bayes factor of BF01=5, for instance, states that the data are five times more likely given the null hypothesis than the alternative hypothesis. BF01 = .2, on the other hand, would mean that the data are 1/.2 = 5 times more likely given the alternative hypothesis than the null hypothesis (Jarosz & Wiley, 2014).

3. Results

Genotype frequencies for DRD2 rs6277 were CC n = 23, CT n = 50, TT n = 32 (test for HardyWeinberg-Equilibrium Chi2 = .173, df = 1, n.s.). Participants’ sex was not related to DRD2 genotype (Chi2 = .825, df = 2, n.s.). Table 1 lists statistics from the ANOVA models. We observed an association between DRD2 genotype and mean FA on subcortico-frontal connections, irrespective of hemisphere and age (F(2,101)=5.249, p =.007) and between mean FA on basal-ganglia to frontal connections and DRD2 genotype, again irrespective of hemisphere and age (F(2,101)=7.264, p =.001). After correction for the family-wise error, only the association between DRD2 genotype and basal-ganglia to frontal connections remained significant. The corresponding Bayes factor of BF01 = .031 suggests that the data are 32.258 times more likely given the alternative hypothesis than the null hypothesis. According to convention, this value suggests very strong evidence in favor of the association between mean FA-values and DRD2 (Boekel et al., 2015). Carriers of the homozygous CC genotype showed largest white matter tract integrity on connections between the basal ganglia and frontal sites. The effect is illustrated in figure 1 which shows the fiber tracts of interest and FA values depending on DRD2 genotype. Please note that the association between DRD2 genotype and mean FA on fiber connections between the basal ganglia and frontal regions hold when controlling

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for the number of streamlines by treating mean NOS on basal ganglia to frontal connections as additional covariate in the ANOVA model (F(2,100) = 7.017, p = .001). All other effects were not significant (see table 1). Most Bayes factors fell in the range of BF01 = 3 to 10, which suggests moderate evidence in favor of the null hypothesis (i.e. no association between DRD2 genotype and structural connectivity).

In a next step, we explored the observed association further by exploring associations between frontal sites and the three basal ganglia regions of interest (caudate, putamen, pallidum) separately. Mean FA on frontal connections from the caudate and from the pallidum showed a similar DRD2 effect, where carriers of the DRD2 C/C genotype had highest FA values. No effect was found for the putamen (main effects of DRD2: caudate F(2,101) = 7.378, pcorr = .003, BF01 = .028; putamen F(2,101) = 3.716, pcorr = .084, BF01 = .491; pallidum F(2,101) = 5.478, pcorr = .018, BF01 = .13). P-values where Bonferroni adjusted for three tests. Descriptive statistics are given in figure 2. No effect was observed for hemisphere and the interaction between DRD2 and hemisphere.

4. Discussion Combining connectomic data from diffusion-weighted imaging with genomic data in human volunteers we found that carriers of the DRD2 rs6277 CC genotype showed higher mean FA values on white matter tracts linking the basal ganglia structure with the frontal cortices. This was mostly attributable to the caudate and pallidum regions. FA reflects restrictions on water diffusion by axonal membranes and their insulating myelin sheets and is regarded to have high sensitivity to microstructural integrity of a white matter tract (Alexander et al., 2011; Alba-Ferrara & de Erausquin, 2013). We thus conclude that white matter tracts between frontal areas and the caudate as well as the pallidum are characterized by a higher structural integrity in carriers of the rs6277 CC genotype.

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The prefrontal cortex receives dopaminergic input mainly via the mesocortical dopaminergic pathways that originate in the midbrain’s ventral tegmental area and pass through the basal ganglia, particularly the striatum, before innervating the frontal lobes. A central way by which dopamine is thought to affect cognitive processing is through its action on neural circuitry connecting the basal ganglia with the frontal lobe of the brain which have been described as parallel cortico-striatothalamic loops (Alexander et al., 1986). Dopamine D2 receptors are abundantly expressed in mesocortical systems (Winterer & Weinberger, 2007) and activity and functional connectivity in these systems is affected by pharmacological stimulation of D2 receptors (Cools et al., 2007; Wallace et al., 2011). Baseline dopamine levels seem to be important when considering pharmacological effects and genetic disposition has been hypothesized to directly affect baseline dopaminergic levels. The identification of specific genetic markers, however, is an ongoing research endeavor (Cools et al., 2009; Cools & D’Esposito, 2011). DRD2 rs6277 is one of several polymorphisms on the DRD2 gene whose putative functionality have been addressed previously. In vitro work has linked the T-allele of DRD2 rs6277 to decreased mRNA stability in vitro (Duan et al., 2003) and in vivo work has linked the T-allele to higher DRD2 binding potential in the striatum (Hirvonen et al., 2005). This increase in binding potential was largely driven by decreases in receptor affinity but not availability, a pattern which is likely to reflect less competition between tonic dopamine and tracer molecules for binding sites (Hirvonen et al., 2009). Following this argumentation, the CC genotype which was associated with increased fiber tract integrity in the present study is characterized by increased tonic dopamine levels in the basal ganglia. Other polymorphisms with relevance for D2 receptor functioning are rs1800497 (DRD2/ANKK1 Taq1a) and rs2283265. The rs1800497 polymorphism is located downstream to the DRD2 promotor region on a gene called ANKK1, about 15,000 bases away from DRD2 rs6277. Even though, rs1800497 is not located on the DRD2 gene, it has also been linked to reduced striatal D2 receptor binding potential (Pohjalainen et al., 1998) and to increased striatal dopamine synthesis capacity (Laakso et al., 2005). These counterintuitive findings are commonly explained by a strong linkage disequilibrium with functional variations on the DRD2 gene. Following this argumentation, rs1800497 itself would not be causally involved in any alterations of receptor functioning but reside

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on a haplotype block that includes variation with functional effects, such as DRD2 rs228265. This SNP is an intronic variant on the DRD2 gene, about 500 bases upstream from DRD2 rs6277. There is in vitro and in vivo evidence that rs2283265 affects the alternative splicing of the DRD2 gene into the presynaptic short and postsynaptic long receptor isoform (Zhang et al., 2007). All three mentioned DRD2 variants are correlated and thus not inherited independently from each other. Even though the initial functionality studies do not indicate that the observed effects for rs1800497 and rs2283265 generalize to rs6277, we have repeatedly observed strong linkage disequilibrium indicative of a common haplotype block between all three SNPs (Jocham et al., 2009; Markett et al., 2010; Stelzel et al., 2010). In these studies, the rs6277 C-allele (reduced binding potential, Hirvonen et al., 2005) resides on a haplotype block with the rs1800497 A1-allele (increased dopamine synthesis capacity, Laakso et al., 2005) and the rs2283265 T-allele (relatively more pre-synaptic receptors, Zhang et al., 2007). The present finding of increased structural integrity of basal-ganglia-to-frontal connections in DRD2 rs6277 CC-carriers could therefore relate to a reduced striatal binding potential of D2 receptors, but also increased presynaptic synthesis capacity, which is likely to reflect an increased phasic dopaminergic response (Grace, 1991; Bilder et al., 2004). This view, however, is speculative until future molecular work reconciles the precise functional effects of DRD2 variants in vivo.

The mentioned DRD2 haplotype block with the rs6277 C-allele has been linked to increased functional connectivity between the basal ganglia and frontal cortex during task processing (Stelzel et al., 2010). Such stronger functional connectivity could relate to the observed increase in structural connectivity in CC-carriers. Experience-depending changes in FA have been reported in other contexts (Zatorre et al., 2012). It may be the case that higher baseline dopamine activity leads to stronger functional coupling between basal ganglia and frontal sites which may culminate in higher myelination of fiber tracts. FA is sensitive to axon myelination, but also to axon diameter or packing density, making a direct interpretation of potential biological underpinnings speculative (Song et al., 2002; Takahashi et al., 2002; Jones et al., 2013). We note that findings appear to be specific to FA with no association between DRD2 and MD, AD, and/or RD measures. MD is argued to be related to cellularity and membrane density (Alexander et al., 2011) and changes in FA in the absence of

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MD changes might reflect differences in coherent fiber structure without general tissue loss (Zhang et al., 2010) which potentially points towards an association between DRD2 and fiber tract architecture. A related open question is how genetic variation on DRD2 can lead to changes in FA. One recent study has characterized the relationship between dopamine synthesis capacity and DWI parameters, however, the analysis was restricted to the striatum and no relationship with FA values was observed (Kawaguchi et al., 2014). Studies have also shown that striatal dopamine release interacts with the functioning of neural growth factors (Goggi et al., 2003) but it is currently unclear how this relationship translates into consequences for structural connectivity. Recent studies have linked cortical gene expression patterns to long-range white matter connectivity in both healthy (Fulcher and Fornito, 2015; Vértes et al., 2016; Krienen et al., 2016) and diseased conditions (Romme et al, 2016), but more work is needed to further characterize molecular processes associated with DRD2 variation and structural brain connectivity.

The present finding fits well with research assessing individual differences in the response to dopaminergic stimulation. The inverted-U shaped model of dopamine functioning contents that the individual default of the frontostriatal system or, in other words, baseline dopaminergic activity determines the effects of dopaminergic pharmacological intervention (Cools & D’Esposito, 2011). Additional receptor stimulation by a dopamine agonist would benefit those with low baseline dopamine activity but would push those with higher baseline dopamine activity past the point of optimal signaling. Beneficial effects of dopaminergic stimulation on cognitive functioning have only been observed in a subgroup of people characterized either by high trait impulsivity (Cools et al., 2007), low working memory capacity (Kimberg et al., 1997), or low frontostriatal fiber tract integrity (van Schouwenburg et al., 2013). In contrast, detrimental effects of dopamine stimulation have been observed in people scoring in the opposite direction on these measures, sparking the idea that these measures index baseline dopamine activity. This has been corroborated by the demonstration that impulsivity and working memory capacity relate closely to different aspects of dopamine activity such as synthesis capacity (Cools et al., 2008) or receptor-binding (Buckholtz et al., 2010). The rs6277 CC genotype has been linked to higher working memory capacity (Markett et al., 2010; 2011) and lower trait impulsivity (Markett et al., 2014). The present finding suggests a

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further association with frontostriatal fiber tract integrity. A collation of these findings suggest that the CC genotype relates to all of those measures that have been used to index baseline dopamine activity and predict pharmacological effects of D2 receptor stimulation. If DRD2 genetic variation does indeed affect baseline dopamine levels it should be also possible to predict the effects of dopaminergic stimulation directly from genetic variation. Colzato et al (2016) have confirmed this prediction by demonstrating that the administration of the dopamine precursor L-tyrosine impairs executive control performance in carriers of the DRD2 rs6277 CC genotype but enhanced performance in carriers of the TT variant. Some limitations of the present study need to be mentioned. The sample size, albeit large for an imaging study, is comparably small for a genetic association study. Furthermore, the study has only a narrow focus on one polymorphism within the dopaminergic genetic pathway. We encourage future replication in a larger data set and the inclusion of all known dopamine-related polymorphisms in order to strengthen the present finding which has to be considered preliminary until replicated. This should particularly include other DRD2 SNPs such as the mentioned rs1800497 and rs2283265 which will help to characterize the whole picture of the neurocognitive relevance of the DRD2 gene. Lastly, we focussed only on structural connectivity and did not collect resting-state functional connectivity data. Future replications may also want to include functional connectivity measures as well. Abnormal dopamine signaling contributes to Parkinson’s disease, attentional deficit hyperactivity; addiction, symptoms and schizophrenia and dopamine receptors are the primary targets of medication in these disorders (Seeman & van Tol, 1994). Understanding the consequences of variation in the genetic underpinnings of dopamine receptor functioning is crucial for developing more effective drugs with reduced side effects. Ultimately, the aim would be to provide patients with the right drug and also the right dose depending on their personal genetic makeup.

Funding and Disclosure: M.P.v.d.H. was supported by a VIDI grant of the Netherlands Organization for Scientific Research (NWO), a Rudolf Magnus Fellowship and an MQ Fellowship. C.M. (MO-2363/3-1) is supported by a Heisenberg grant of the German Research Foundation (DFG). J.C.S.B. was supported by the

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Gerok Program of the BONFOR Commission, University of Bonn. None of the authors declares any conflict of interest.

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Figure 1: FA values depending on DRD2 genotypes (C/C, C/T, T/T) and hemisphere (L,R) on selected fiber tracts. (A) subcortical to frontal, (B) basal ganglia to frontal, (C) within subcortical, (D) and within frontal. Group means are given by the solid horizontal lines, the thin boxes represent 1.96 SEM confidence intervals and the solid vertical line indicates one standard deviation. Connectome plots are given for anatomical reference and show connections present in >95% of participants.

Figure 2: FA values on connections between the three basal ganglia regions and frontal sites, depending on genotype. Group means are given by the solid horizontal lines, the thin boxes represent 1.96 SEM confidence intervals and the solid vertical line indicates one standard deviation. Connectome plots are given for anatomical reference and show connections present in >95% of participants. Please note that only the genotype differences for caudate and pallidum corrections hold multiple comparison correction.

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24

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Table 1: Statistics for the DRD2 genotype main effects on different structural connectivity measures (number of streamlines, fractional anisotrophy, axial diffusivity, radial diffusivity, and mean diffusivity) on the four fiber tracts of interest. All F-statistics are with F(2,101). BF01 columns give Bayes factors for the comparison of a model containing DRD2 as factor versus a null model with all other effects. Following convention (Boekel et al., 2015), BF01 between 1 and 3 indicate anecdotal evidence for the null hypothesis (i.e. absence of association with DRD2 genotype), BF01 between 3 and 10 indicate moderate evidence in favor of the null hypothesis. BF01 < 1 indicate evidence in favor of the alternative hypothesis. Only statistics in bold face hold Bonferroni correction (pcorr = .025). NO S F

p

subcorticalfrontal

.59 0

.55 6

basalgangliafrontal

.48 1

within subcortical within frontal

FA BF0 1

F

p

AD

RD

MD

BF0 1

F

p

BF0 1

F

p

BF0 1

F

p

BF0 1

4.60 5.249 .007 7

.138

.40 2

.67 0

3.82 8

1.19 3

.30 8

2.84 6

.426

.65 5

4.51 8

.62 0

4.87 7.305 .001 * * 4

.031 *

.43 7

.64 7

3.66 4

2.72 3

.07 1

1.00 7

1.15 5

.31 9

2.58 8

.39 7

.67 3

5.44 1.298 .277 9

4.05 3

.16 3

.85 0

9.85 4

.721

.48 9

7.00 6

.276

.76

9.55 2

.51 2

.60 1

5.51 1.716 .185 2

3.13 1

.60 1

.55 0

6.48 0

.665

.52 2

6.01 2

.585

.55 9

5.85 7

Highlights

• • • •

We investigate associations between the DRD2 gene and structural connectivity. Connectivity data are analyzed in a connectome framework. DRD2 is associated with fiber tract integrity between basal ganglia and frontal cortices. Higher integrity is linked to the DRD2 variant that is beneficial for cognition.

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