Nicotinergic Modulation of Attention-Related Neural Activity Differentiates Polymorphisms of DRD2 and CHRNA4 Receptor Genes

<div><p>Cognitive and neuronal effects of nicotine show high interindividual variability. Recent findings indicate that genetic variations that affect the cholinergic and dopaminergic neurotransmitter system impact performance in cognitive tasks and effects of nicotine. The current pharmacogenetic functional magnetic resonance imaging (fMRI) study aimed to investigate epistasis effects of CHRNA4/DRD2 variations on behavioural and neural correlates of visuospatial attention after nicotine challenge using a data driven partial least squares discriminant analysis (PLS-DA) approach. Fifty young healthy non-smokers were genotyped for CHRNA4 (rs1044396) and DRD2 (rs6277). They received either 7 mg transdermal nicotine or a matched placebo in a double blind within subject design prior to performing a cued target detection task with valid and invalid trials. On behavioural level, the strongest benefits of nicotine in invalid trials were observed in participants carrying both, the DRD2 T- and CHRNA4 C+ variant. Neurally, we were able to demonstrate that different DRD2/CHRNA4 groups can be decoded from the pattern of brain activity in invalid trials under nicotine. Neural substrates of interindividual variability were found in a network of attention-related brain regions comprising the pulvinar, the striatum, the middle and superior frontal gyri, the insula, the left precuneus, and the right middle temporal gyrus. Our findings suggest that polymorphisms in the CHRNA4 and DRD2 genes are a relevant source of individual variability in pharmacological studies with nicotine.</p></div

Visual cueing paradigm (A) and behavioural results (B).

<p><b>A.</b> Scheme of the three task conditions; valid (120), invalid (30), catch (20), and zero (50, no cue and no target, not depicted) trials were presented in randomized order with a SOA of 2000 ms. <b>B.</b> Difference of the validity effect (slowing of RTs due to invalidly cued trials as compared to valid trials) between nicotine and placebo. The CHRNA4 C+ and DRD2 T- genotype group shows a significant benefit from nicotine. The significant three-way interaction of <i>genotype group</i> x <i>treatment</i> x <i>condition</i> as displayed in the current figure was identified by post-hoc ANOVAs to be driven by the <i>genotype group</i> x <i>treatment</i> interaction during invalid trials.</p

Identified brain regions contributing to genotype classification.

<p>¹ Center of gravity coordinate of the clusters.</p><p>² Only clusters that exceeded the voxel extent threshold of k≥40 are reported.</p><p>³ Clusters showing increased (+) or decreased (-) BOLD levels under nicotine (p≤0.05) for each genotype group (CHRNA4 / DRD2) during invalid trials. Post-hoc tests of mean cluster BETA values; tendencies (p≤0.1) are indicated by rectangle brackets.</p><p>Identified brain regions contributing to genotype classification.</p

Experiment design.

<p><b>Top:</b> Order of the resting state (RS) and task periods (T) with the number of acquired whole brain scans. The task was separated from the resting state periods by brief instructions. Task periods (T1 to T5) were continuously measured and later split up into five scan periods with the same length. The post-task resting state period (RS2 and RS3) was also measured continuously and split up later for the analyses. The changes from the first resting state period (RS1) to the first task period (T1) as well as from the last task period (T5) to the first post-task resting state period (RS2) are referred to as ‘task switch’. <b>Bottom:</b> Scheme of the vigilance task during the task period. Participants were instructed to detect a red fixation cross (here depicted in bold).</p

Long-Term Effects of Attentional Performance on Functional Brain Network Topology

<div><p>Individuals differ in their cognitive resilience. Less resilient people demonstrate a greater tendency to vigilance decrements within sustained attention tasks. We hypothesized that a period of sustained attention is followed by prolonged changes in the organization of “resting state” brain networks and that individual differences in cognitive resilience are related to differences in post-task network reorganization. We compared the topological and spatial properties of brain networks as derived from functional MRI data (N = 20) recorded for 6 mins before and 12 mins after the performance of an attentional task. Furthermore we analysed changes in brain topology during task performance and during the switches between rest and task conditions. The cognitive resilience of each individual was quantified as the rate of increase in response latencies over the 32-minute time course of the attentional paradigm. On average, functional networks measured immediately post-task demonstrated significant and prolonged changes in network organization compared to pre-task networks with higher connectivity strength, more clustering, less efficiency, and shorter distance connections. Individual differences in cognitive resilience were significantly correlated with differences in the degree of recovery of some network parameters. Changes in network measures were still present in less resilient individuals in the second half of the post-task period (i.e. 6–12 mins after task completion), while resilient individuals already demonstrated significant reductions of functional connectivity and clustering towards pre-task levels. During task performance brain topology became more integrated with less clustering and higher global efficiency, but linearly decreased with ongoing time-on-task. We conclude that sustained attentional task performance has prolonged, “hang-over” effects on the organization of post-task resting-state brain networks; and that more cognitively resilient individuals demonstrate faster rates of network recovery following a period of attentional effort.</p></div

Vigilance decrements in the attentional task.

<p>(<b>A</b>) Median reaction times averaged across subjects for each of the 96 target presentations during the task are shown. Solid line: The robust fit regression showed a significant RT increase/vigilance decrement. (<b>B</b>) On the individual level, participants showed a large variability in their change in RTs during task performance. For each subject, the individual robust fits for the RTs were used to estimate the RT change at the end of the task. For illustration we divided the participants into a group with significant RT increase (red, referred to as ‘attentional impaired’ subjects) and without a significant RT increase (blue, referred to as ‘attentional resilient’ subjects). However, to test the correlation between network parameters and behavioural performance without loss of information, the individual RTs increases were used and tested for a linear relationship.</p

Pairwise comparisons of resting state data: Effects on (i) mean connectivity strength, (ii) network topology, (iii) physical distances and (iv) its correlations with performance.

(a)<p>Change between resting states, paired t-tests, df = 19.</p>(b)<p>Differences between resting states correlated with individual vigilance decrements.</p>(c)<p>Group comparison between attentionally impaired and resilient subjects (see text), two-sample t-tests, df = 18.</p

Illustration of parcellation routine for seed region/node definition.

<p>Cortical and subcortical brain regions were parcellated into 442 brain nodes. (<b>A</b>) The parcellation routine was based on an anatomically parcellated and labeled T1 volume provided by the AAL toolbox (Tzourio-Mazoyer et al., 2002). (<b>B</b>) The parcellation routine randomly and homogenously split the larger AAL regions into 442 smaller subparcels while preserving the macro-anatomical borders as defined in the AAL-template. (<b>C</b>) This parcellation approach creates more homogenous seed region sizes as compared to the original AAL-template so that possible biasing effects of parcel sizes on functional connectivity (Salvador et al., 2008; Fornito et al., 2010) were prevented. The main statistical analyses were repeated with alternative templates in order to assure that the reported effects of the RS data analysis were not driven by a singular parcellation template (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074125#pone.0074125.s001" target="_blank">File S1</a>).</p

Pairwise comparisons of resting state and task data before and following task switches (R1, T1, T5 and R2): Effects on (i) mean connectivity strength, (ii) network topology, (iii) physical distances.

(a)<p>Paired t-tests, df = 19.</p>(b)<p>T-tests based on averaged values for RS1/T1, respectively T5/RS2.</p

Changes in nodal network clustering over resting state fMRI periods.

<p><b>Top:</b> Clustering changed over the three resting state fMRI periods. Following task performance all brain regions show higher clustering or cliquishness. <b>Bottom left:</b> Significantly different changes in clustering at nodal level (yellow) were evident among others in visual cortex and basal forebrain; brain areas involved in the processing of visual sustained attention tasks. <b>Bottom right:</b> Significant changes in clustering in the post-task phase that were related to vigilance decline were found among others in the thalamus (red).</p