• Energy Research

The Monkey Alcohol Tissue Research Resource (MATRR) is a repository and analytics platform for detailed data derived from well-documented nonhuman primate (NHP) alcohol self-administration studies. This macaque model has demonstrated categorical drinking norms reflective of human drinking populations, resulting in consumption pattern classifications of very heavy drinking (VHD), heavy drinking (HD), binge drinking (BD), and low drinking (LD) individuals. Here, we expand on previous findings that suggest ethanol drinking patterns during initial drinking to intoxication can reliably predict future drinking category assignment.The classification strategy uses a machine-learning approach to examine an extensive set of daily drinking attributes during 90 sessions of induction across 7 cohorts of 5 to 8 monkeys for a total of 50 animals. A Random Forest classifier is employed to accurately predict categorical drinking after 12 months of self-administration.Predictive outcome accuracy is approximately 78% when classes are aggregated into 2 groups, "LD and BD" and "HD and VHD." A subsequent 2-step classification model distinguishes individual LD and BD categories with 90% accuracy and between HD and VHD categories with 95% accuracy. Average 4-category classification accuracy is 74%, and provides putative distinguishing behavioral characteristics between groupings.We demonstrate that data derived from the induction phase of this ethanol self-administration protocol have significant predictive power for future ethanol consumption patterns. Importantly, numerous predictive factors are longitudinal, measuring the change of drinking patterns through 3 stages of induction. Factors during induction that predict future heavy drinkers include being younger at the time of first intoxication and developing a shorter latency to first ethanol drink. Overall, this analysis identifies predictive characteristics in future very heavy drinkers that optimize intoxication, such as having increasingly fewer bouts with more drinks. This analysis also identifies characteristic avoidance of intoxicating topographies in future low drinkers, such as increasing number of bouts and waiting longer before the first ethanol drink.

Here, we map a quantitative trait locus (QTL) with a large effect on predisposition to barbiturate (pentobarbital) withdrawal to a 0.44 Mb interval of mouse chromosome 1 syntenic with human 1q23.2. We report a detailed analysis of the genes within this interval and show that it contains 15 known and predicted genes, 12 of which demonstrate validated genotype-dependent transcript expression and/or nonsynonymous coding sequence variation that may underlie the influence of the QTL on withdrawal. These candidates are involved in diverse cellular functions including intracellular trafficking, potassium conductance and spatial buffering, and multimolecular complex dynamics, and indicate both established and novel aspects of neurobiological response to sedative-hypnotics. This work represents a substantial advancement toward identification of the gene(s) that underlie the phenotypic effects of the QTL. We identifyKcnj9as a particularly promising candidate and report the development of aKcnj9-null mutant model that exhibits significantly less severe withdrawal from pentobarbital as well as other sedative-hypnotics (zolpidem and ethanol) versus wild-type littermates. Reduced expression ofKcnj9, which encodes GIRK3 (Kir3.3), is associated with less severe sedative-hypnotic withdrawal. A multitude of QTLs for a variety of complex traits, including diverse responses to sedative-hypnotics, have been detected on distal chromosome 1 in mice, and as many as four QTLs on human chromosome 1q have been implicated in human studies of alcohol dependence. Thus, our results will be primary to additional efforts to identify genes involved in a wide variety of behavioral responses to sedative-hypnotics and may directly facilitate progress in human genetics.

Aldosterone regulates electrolyte and fluid homeostasis through binding to the mineralocorticoid receptors (MRs). Previous work provides evidence for a role of aldosterone in alcohol use disorders (AUDs). We tested the hypothesis that high functional activity of the mineralocorticoid endocrine pathway contributes to vulnerability for AUDs. In Study 1, we investigated the relationship between plasma aldosterone levels, ethanol self-administration and the expression of CYP11B2 and MR (NR3C2) genes in the prefrontal cortex area (PFC) and central nucleus of the amygdala (CeA) in monkeys. Aldosterone significantly increased after 6- and 12-month ethanol self-administration. NR3C2 expression in the CeA was negatively correlated to average ethanol intake during the 12 months. In Study 2, we measured Nr3c2 mRNA levels in the PFC and CeA of dependent and nondependent rats and the correlates with ethanol drinking during acute withdrawal. Low Nr3c2 expression levels in the CeA were significantly associated with increased anxiety-like behavior and compulsive-like drinking in dependent rats. In Study 3, the relationship between plasma aldosterone levels, alcohol drinking and craving was investigated in alcohol-dependent patients. Non-abstinent patients had significantly higher aldosterone levels than abstinent patients. Aldosterone levels positively correlated with the number of drinks consumed, craving and anxiety scores. These findings support a relationship between ethanol drinking and the aldosterone/MR pathway in three different species.

Association studies implicate the multiple PDZ domain protein (MUPP1/MPDZ) gene in risk for alcoholism in humans and alcohol withdrawal in mice. Although manipulation of theMpdzgene by homologous recombination and bacterial artificial chromosome transgenesis has suggested that its expression affects alcohol withdrawal risk, the potential confounding effects of linked genes and developmental compensation currently limit interpretation. Here, using RNA interference (RNAi), we directly test the impact ofMpdzexpression on alcohol withdrawal severity and provide brain regional mechanistic information. Lentiviral‐mediated delivery ofMpdzshort hairpin RNA (shRNA) to the caudolateral substantia nigra pars reticulata (clSNr) significantly reducesMpdzexpression and exacerbates alcohol withdrawal convulsions compared with control mice that delivered a scrambled shRNA. Neither baseline nor pentylenetetrazol‐enhanced convulsions differed betweenMpdzshRNA and control animals, indicatingMpdzexpression in the clSNr does not generally affect seizure susceptibility. To our knowledge, these represent the firstin vivo MpdzRNAi analyses, and provide the first direct evidence thatMpdzexpression impacts behavior. Our results confirm thatMpdzis a quantitative trait gene for alcohol withdrawal and demonstrate that its expression in the clSNr is crucially involved in risk for alcohol withdrawal.

Association studies implicate multiple PDZ domain protein (MPDZ/MUPP1) sequence and/or expression in risk for alcoholism in humans and ethanol withdrawal (EW) in mice, but confirmation has been hindered by the dearth of targeted genetic models. We report the creation of transgenic (MPDZ-TG) and knockout heterozygote (Mpdz(+/-) ) mice, with increased (2.9-fold) and decreased (53%) target expression, respectively. Both models differ in EW compared with wild-type littermates (P ≤ 0.03), providing compelling evidence for an inverse relationship between Mpdz expression and EW severity. Additionally, ethanol consumption is reduced up to 18% (P = 0.006) in Mpdz(+/-) , providing the first evidence implicating Mpdz in ethanol self-administration.

Physiological dependence and associated withdrawal episodes can constitute a powerful motivational force that perpetuates drug use and abuse. Using robust behavioral models of drug physiological dependence in mice, positional cloning, and sequence and expression analyses, we identified an addiction-relevant quantitative trait gene, Mpdz. Our findings provide a framework to define the protein interactions and neural circuit by which this gene's product (multiple PDZ domain protein) affects drug dependence, withdrawal and relapse.

AbstractThis is the first description of the relationship between chronic ethanol self‐administration and the brain transcriptome in a non‐human primate (rhesus macaque). Thirty‐one male animals self‐administered ethanol on a daily basis for over 12 months. Gene transcription was quantified with RNA‐Seq in the central nucleus of the amygdala (CeA) and cortical Area 32. We constructed coexpression and cosplicing networks, and we identified areas of preservation and areas of differentiation between regions and network types. Correlations between intake and transcription included largely distinct gene sets and annotation categories across brain regions and between expression and splicing; positive and negative correlations were also associated with distinct annotation groups. Membrane, synaptic and splicing annotation categories were over‐represented in the modules (gene clusters) enriched in positive correlations (CeA); our cosplicing analysis further identified the genes affected only at the exon inclusion level. In the CeA coexpression network, we identified Rab6b, Cdk18 and Igsf21 among the intake‐correlated hubs, while in the Area 32, we identified a distinct hub set that included Ppp3r1 and Myeov2. Overall, the data illustrate that excessive ethanol self‐administration is associated with broad expression and splicing mechanisms that involve membrane and synapse genes.

Previous studies on changes in murine brain gene expression associated with the selection for ethanol preference have used F2 intercross or heterogeneous stock (HS) founders, derived from standard laboratory strains. However, these populations represent only a small proportion of the genetic variance available in Mus musculus. To investigate a wider range of genetic diversity, we selected mice for ethanol preference using an HS derived from the eight strains of the collaborative cross. These HS mice were selectively bred (four generations) for high and low ethanol preference. The nucleus accumbens shell of naive S4 mice was interrogated using RNA sequencing (RNA‐Seq). Gene networks were constructed using the weighted gene coexpression network analysis assessing both coexpression and cosplicing. Selection targeted one of the network coexpression modules (greenyellow) that was significantly enriched in genes associated with receptor signaling activity including Chrna7, Grin2a, Htr2a and Oprd1. Connectivity in the module as measured by changes in the hub nodes was significantly reduced in the low preference line. Of particular interest was the observation that selection had marked effects on a large number of cell adhesion molecules, including cadherins and protocadherins. In addition, the coexpression data showed that selection had marked effects on long non‐coding RNA hub nodes. Analysis of the cosplicing network data showed a significant effect of selection on a large cluster of Ras GTPase‐binding genes including Cdkl5, Cyfip1, Ndrg1, Sod1 and Stxbp5. These data in part support the earlier observation that preference is linked to Ras/Mapk pathways.