Decoding diagnosis and lifetime consumption in alcohol dependence from grey-matter pattern information.

OBJECTIVE: We investigated the potential of computer-based models to decode diagnosis and lifetime consumption in alcohol dependence (AD) from grey-matter pattern information. As machine-learning approaches to psychiatric neuroimaging have recently come under scrutiny due to unclear generalization and the opacity of algorithms, our investigation aimed to address a number of methodological criticisms. METHOD: Participants were adult individuals diagnosed with AD (N = 119) and substance-naïve controls (N = 97) ages 20-65 who underwent structural MRI. Machine-learning models were applied to predict diagnosis and lifetime alcohol consumption. RESULTS: A classification scheme based on regional grey matter attained 74% diagnostic accuracy and predicted lifetime consumption with high accuracy (r = 0.56, P < 10-10 ). A key advantage of the classification scheme was its algorithmic transparency, revealing cingulate, insular and inferior frontal cortices as important brain areas underlying classification. Validation of the classification scheme on data of an independent trial was successful with nearly identical accuracy, addressing the concern of generalization. Finally, compared to a blinded radiologist, computer-based classification showed higher accuracy and sensitivity, reduced age and gender biases, but lower specificity. CONCLUSION: Computer-based models applied to whole-brain grey-matter predicted diagnosis and lifetime consumption in AD with good accuracy. Computer-based classification may be particularly suited as a screening tool with high sensitivity.

Orbitofrontal structural markers of negative affect in alcohol dependence and their associations with heavy relapse-risk at 6 months post-treatment.

BACKGROUND: Alcohol relapse is often occurring to regulate negative affect during withdrawal. On the neurobiological level, alcoholism is associated with gray matter (GM) abnormalities in regions that regulate emotional experience such as the orbitofrontal cortex (OFC). However, no study to our knowledge has investigated the neurobiological unpinning of affect in alcoholism at early withdrawal and the associations of OFC volume with long-term relapse risk. METHODS: One hundred and eighty-two participants were included, 95 recently detoxified alcohol dependent patients (ADP) and 87 healthy controls (HC). We measured affective states using the positive and negative affect schedule (PANAS). We collected T1-weighted brain structural images and performed Voxel-based morphometry (VBM). RESULTS: Findings revealed GM volume decrease in alcoholics in the prefrontal cortex (including medial OFC), anterior cingulate gyrus, and insula. GM volume in the medial OFC was positively associated with NA in the ADP group. Cox regression analysis predicted that risk to heavy relapse at 6 months increases with decreased GM volume in the medial OFC. CONCLUSIONS: Negative affect during alcohol withdrawal was positively associated with OFC volume. What is more, increased GM volume in the OFC also moderated risk to heavy relapse at 6 months. Reduced GM in the OFC poses as risk to recovery from alcohol dependence and provides valuable insights into transient negative affect states during withdrawal that can trigger relapse. Implications exist for therapeutic interventions signifying the OFC as a neurobiological marker to relapse and could explain the inability of ADP to regulate internal negative affective states.

Functional neuroimaging effects of recently discovered genetic risk loci for schizophrenia and polygenic risk profile in five RDoC subdomains.

Recently, 125 loci with genome-wide support for association with schizophrenia were identified. We investigated the impact of these variants and their accumulated genetic risk on brain activation in five neurocognitive domains of the Research Domain Criteria (working memory, reward processing, episodic memory, social cognition and emotion processing). In 578 healthy subjects we tested for association (i) of a polygenic risk profile score (RPS) including all single-nucleotide polymorphisms (SNPs) reaching genome-wide significance in the recent genome-wide association studies (GWAS) meta-analysis and (ii) of all independent genome-wide significant loci separately that showed sufficient distribution of all allelic groups in our sample (105 SNPs). The RPS was nominally associated with perigenual anterior cingulate and posterior cingulate/precuneus activation during episodic memory (PFWE(ROI)=0.047) and social cognition (PFWE(ROI)=0.025), respectively. Single SNP analyses revealed that rs9607782, located near EP300, was significantly associated with amygdala recruitment during emotion processing (PFWE(ROI)=1.63 × 10-4, surpassing Bonferroni correction for the number of SNPs). Importantly, this association was replicable in an independent sample (N=150; PFWE(ROI)<0.025). Other SNP effects previously associated with imaging phenotypes were nominally significant, but did not withstand correction for the number of SNPs tested. To assess whether there was true signal within our data, we repeated single SNP analyses with 105 randomly chosen non-schizophrenia-associated variants, observing fewer significant results and lower association probabilities. Applying stringent methodological procedures, we found preliminary evidence for the notion that genetic risk for schizophrenia conferred by rs9607782 may be mediated by amygdala function. We critically evaluate the potential caveats of the methodological approaches employed and offer suggestions for future studies.

Dopamine-modulated aversive emotion processing fails in alcohol-dependent patients.

Negative mood states after alcohol detoxification may enhance the relapse risk. As recently shown in healthy volunteers, dopamine storage capacity (V d) in the left amygdala was positively correlated with functional activation in the left amygdala and anterior cingulate cortex (ACC) during an emotional task; high functional connectivity between the amygdala and the ACC, a region important for emotion regulation, was associated with low trait anxiety. Based on these findings, we now tested whether detoxified alcohol-dependent patients have a disrupted modulation of the anterior cingulate cortex activation in response to aversive stimuli by amygdala dopamine. Furthermore, we asked whether disrupted functional coupling between amygdala and ACC during aversive processing is related to trait anxiety.We used combined 6-[18F]-fluoro-l-DOPA positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and Spielberger's state-trait anxiety questionnaire (STAI) in 11 male detoxified alcohol-dependent patients compared to 13 matched healthy controls.Unlike healthy controls, patients showed no significant correlation between our PET metric for dopamine storage capacity (FDOPA V d), in left amygdala and activation in left ACC. Moreover, the functional connectivity between amygdala and ACC during processing of aversive emotional stimuli was reduced in patients. Voxel-based morphometry did not reveal any discernible group differences in amygdala volume.These results suggest that dopamine-modulated corticolimbic circuit function is important for responding to emotional information such that apparent functional deficits in this neuromodulatory circuitry may contribute to trait anxiety in alcohol-dependent patients.

The dopamine system in mediating alcohol effects in humans.

Recent brain-imaging studies revealed that the development and maintenance of alcohol dependence is determined by a complex interaction of different neurotransmitter systems and multiple psychological factors. In this context, the dopaminergic reinforcement system appears to be of fundamental importance. We focus on the excitatory and depressant effects of acute versus chronic alcohol intake and its impact on dopaminergic neurotransmission. Furthermore, we describe alterations in dopaminergic neurotransmission as associated with symptoms of alcohol dependence. We specifically focus on neuroadaptations to chronic alcohol consumption and their effect on central processing of alcohol-associated and reward-related stimuli. Dysfunctional reward processing, impaired reinforcement learning and increased salience attribution to alcohol-associated stimuli enable alcohol cues to drive alcohol seeking and consumption. Finally, we will discuss how the neurobiological and neurochemical mechanisms of alcohol-associated alterations in reward processing and learning can interact with personality traits, cognition and emotion processing.