Resting-state functional connectivity and presynaptic monoamine signaling in Alcohol Dependence

Abstract

Alcohol Dependence (AD) is a chronic relapsing disorder with high degrees of morbidity and mortality. While multiple neurotransmitter systems are involved in the complex symptomatology of AD, monoamine dysregulation and subsequent neuroadaptations have been long postulated to play an important role. Presynaptic monoamine transporters, such as the vesicular monoamine transporter 1 (VMAT1), are likely critical as they represent a key common entry point for monoamine regulation and may represent a shared pathway for susceptibility to AD. Excessive monoaminergic signaling as mediated by genetic variation in VMAT1 might affect functional brain connectivity in particular in alcoholics compared to controls. We conducted resting-state fMRI functional connectivity (FC) analysis using the independent component analysis (ICA) approach in 68 AD subjects and 72 controls. All subjects were genotyped for the Thr136Ile (rs1390938) variant in VMAT1. Functional connectivity analyses showed a significant increase of resting-state FC in 4 networks in alcoholics compared to controls (P < 0.05, corrected). The FC was significantly positively correlated with Alcohol Dependence Scale (ADS). The hyperfunction allele 136Ile was associated with a significantly decreased FC in the Default Mode Network, Prefrontal Cortex Network, and Executive Control Network in alcohol dependent participants (P < 0.05, corrected), but not in controls. Our data suggest that increased FC might represent a neuroadaptive mechanism relevant to AD that is furthermore mediated by genetic variation in VMAT1. The hyperfunction allele Thr136Ile might have a protective effect that is, in particular, relevant in AD by mechanism of increased monoamine transport into presynaptic storage vesicles.

Keywords: SLC18A1; genetics; mPFC; monoamine transporter; presynaptic; resting-state.

Figure 1

Functional connectivity differences between cases and controls (A) and between Thr136Thr and Ile136 Carriers in Cases (B). (A) FC differences between cases and controls. Compared with controls, cases showed increased within‐network FC in a‐DMN, p‐DMN, L‐ECN, R‐ECN, SN and PFCN. Group‐level Networks were obtained using Probabilistic Independent Component Analysis. Subject‐specific maps were obtained using dual regression technique. Then, cluster‐based two‐sample t‐test was carried out to assess statistically significant differences in FC between the groups. Age, gender and ancestry informative marker (AIM) were used as nuisance covariates for each NOI. The statistical threshold was set at P < 0.05, FWE‐corrected for multiple comparisons. The FC maps were overlaid onto the mean standardized structural T1 1‐mm MNI template and visualized using Mricrogl. (B) In AD individuals (cases), compared with Thr136Thr individuals, Thr136lle/Ile136Ile carriers showed decreased FC in a‐DMN, p‐DMN, L‐ECN, R‐ECN and PFCN. The statistical threshold was set at P < 0.05, corrected for multiple comparisons through FWE. There were no significant differences in controls.

Figure 2

Relationship between FC in ADS Scores in Cases. Scatterplot of ADS and FC in cases. Positive correlations were found between ADS and FC within DMN (P = 0.0004), ECN (P < 0.0001), SN (P < 0.0001) and PFCN (P < 0.0001) in cases. The parameter estimate images from stage 2 of the dual regression were used to calculate the mean FC within each NOI in AD. Linear regression was used in SAS to model the relationship between the two variables and blue lines represent the regression line. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]