A relationship between the aldosterone-mineralocorticoid receptor pathway and alcohol drinking: preliminary translational findings across rats, monkeys and humans.

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.

Effects of selection for ethanol preference on gene expression in the nucleus accumbens of HS-CC mice.

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.

Genes, behavior and next-generation RNA sequencing.

Advances in next-generation sequencing suggest that RNA-Seq is poised to supplant microarray-based approaches for transcriptome analysis. This article briefly reviews the use of microarrays in the brain-behavior context and then illustrates why RNA-Seq is a superior strategy. Compared with microarrays, RNA-Seq has a greater dynamic range, detects both coding and noncoding RNAs, is superior for gene network construction, detects alternative spliced transcripts, detects allele specific expression and can be used to extract genotype information, e.g. nonsynonymous coding single nucleotide polymorphisms. Examples of where RNA-Seq has been used to assess brain gene expression are provided. Despite the advantages of RNA-Seq, some disadvantages remain. These include the high cost of RNA-Seq and the computational complexities associated with data analysis. RNA-Seq embraces the complexity of the transcriptome and provides a mechanism to understand the underlying regulatory code; the potential to inform the brain-behavior relationship is substantial.

Gene networks and haloperidol-induced catalepsy.

The current study examined the changes in striatal gene network structure induced by short-term selective breeding from a heterogeneous stock for haloperidol response. Brain (striatum) gene expression data were obtained using the Illumina WG 8.2 array, and the datasets from responding and non-responding selected lines were independently interrogated using a weighted gene coexpression network analysis (WGCNA). We detected several gene modules (groups of coexpressed genes) in each dataset; the membership of the modules was found to be largely concordant, and a consensus network was constructed. Further validation of the network topology showed that using approximately 35 samples is sufficient to reliably infer the transcriptome network. An in-depth analysis showed significant changes in network structure and gene connectivity associated with the selected lines; these changes were validated using a bootstrapping procedure. The most dramatic changes were associated with a gene module richly annotated with neurobehavioral traits. The changes in network connectivity were concentrated in the links between this module and the rest of the network, in addition to changes within the module; this observation is consistent with recent results in protein and metabolic networks. These results suggest that a network-based strategy will help identify the genetic factors associated with haloperidol response.

Detection of reciprocal quantitative trait loci for acute ethanol withdrawal and ethanol consumption in heterogeneous stock mice.

RATIONALE: Previous studies have suggested that there is an inverse genetic relationship between ethanol consumption (two-bottle choice, continuous access) and ethanol withdrawal (e.g., Metten et al., Behav Brain Res 95:113-122, 1998a). OBJECTIVES: The current study used short-term selective breeding from heterogeneous stock (HS) animals to examine this relationship. The primary goal of the current study was to determine if reciprocal quantitative trait loci (QTLs) could be found in the selectively bred lines. The advantage of detecting QTLs in HS animals is that it is possible to extract a haplotype signature for the QTL, which in turn can be used to narrow the number of candidate genes generated from gene expression and sequence databases (see, e.g., Hitzemann et al., Mamm Genome 14:733-747, 2003). RESULTS: Seven reciprocal QTLs were detected on chromosomes (Chr) 1 (two), 3, 6, 11, 16, and 17 that exceeded the nominal LOD threshold of 10; genetic drift, which occurs during selection, dramatically increases the LOD threshold. The proximal Chr 1 QTL was examined in some detail. The haplotype structure of the QTL was such that the LP/J allele was associated with low withdrawal and high consumption. The QTL appears to be located in a gene-poor region between 170 and 173 Mbp. Based on available sequence data, two plausible candidate genes emerge-Nos1ap and Atf6alpha. CONCLUSIONS: The data presented here confirm some aspects of the negative genetic relationship between acute ethanol withdrawal and ethanol consumption. The QTL data point to the potential involvement of NO signaling and/or the unfolded protein response.