Genomic Insights into Acute Alcohol Tolerance

Abstract

Alcohol "sensitivity" has been proposed as a predictive factor for development of alcohol dependence (Schuckit et al., 2005). Most measures of alcohol sensitivity in humans and animals include a component that can be ascribed to acute functional tolerance (AFT). AFT is a form of tolerance that develops within a single period of alcohol exposure and has a genetic component. We used microarray technology as well as quantitative trait locus analysis of phenotypic and gene expression data across 30 BXD recombinant inbred strains of mice, 20 inbred strains of mice, and two replicate lines of mice selectively bred for differences in AFT, to identify differentially expressed candidate genes that contribute to predisposition to AFT. Eight candidate genes were identified by our statistical and filtering methods. The location of brain expression of these genes was mapped using the Allen Brain Atlas (http://www.brainmap.org), and the transcript location and molecular pathway analysis indicated that brain structures and biochemical pathways implicated in long-term potentiation and memory might also participate in the generation of acute functional alcohol tolerance.The term ethanol (alcohol) tolerance refers to a decreased behavioral response to a given dose of alcohol after prior experience with alcohol or the need for a greater dose of ethanol to produce a given level of effect. Alcohol tolerance is an important diagnostic criterion for alcohol dependence in the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) (American Psychiatric Association, 1994).Functional (pharmacodynamic) alcohol tolerance manifests itself in three different forms: chronic (Tabakoff et al., 1986), rapid (Khanna et al., 2002), or acute (Mellanby, 1919. Acute functional tolerance (AFT) refers to the tolerance that is manifested during a single session of alcohol drinking (Mellanby, 1919), and it can start to develop within minutes after an individual starts to imbibe alcohol. The phenomenon of AFT was initially described by Mellanby (1919) through experiments that showed that humans display a greater degree of intoxication at a given blood alcohol concentration on the rising phase of the blood alcohol curve than at the same alcohol concentration on the falling phase of the blood alcohol curve. Acute functional alcohol tolerance is a neuronal resistance to alcohol effects (Tabakoff et al., 1986); however, its molecular mechanism is still not well characterized.Sons of alcoholics (SOA) are three to five times more likely to develop alcohol dependence than sons of nonalcoholics (Cotton, 1979). SOA also display less alcohol intoxication when measurements are made at least 1 h after drinking alcohol. The low level of response to alcohol has been found to predict future alcohol dependence (Schuckit et al., 2005), and both men and women with no prior history of alcohol dependence, but with a positive family history of alcohol dependence, display a lower response to alcohol than those with no family history of alcohol dependence (Schuck...

RETRACTED ARTICLE: Identification of gene expression profile in the rat brain resulting from acute alcohol intoxication

“…It is noteworthy that gene expression is a sensitive measurement of the functional state of a cell or tissue, and the importance of gene expression in drug addiction has been demonstrated in humans and animal models [21,22]. In addition, genomewide measures of gene expression can identify patterns of gene activity and might provide a better means for individual risk assessment or brain damage assessment in patients with acute alcoholic intoxication [23]. We designed an in vivo mouse model of acute alcohol intoxication in this study and examined the gene expression profile changes in CNS tissue, which was used to identify the molecular targets affected by acute alcohol intoxication; additionally, we aimed to reveal the molecular mechanisms of the effects of alcohol on brain cells and further assess CNS damage caused by acute alcohol intoxication.…”

Disease-driven detection of differential inherited SNP modules from SNP network

“…After locating these SNPs in genes (the start and end positions of genes were obtained from the GENE database of NCBI as of February 2002), we obtained 222 candidate genes associated with alcoholism. Among these genes, many have been previously demonstrated to be associated with alcoholism, including GRM7 (Vadasz et al, 2007), NRXN1 (Shah et al, 2010;Wisniowiecka-Kowalnik et al, 2010), ERBB4 (Luo and Miller, 2000), GRIA1 (Hu et al, 2008), ITPR1 (Saito et al, 1996), NTS (Ehlers et al, 1999;Erwin et al, 2001), TTN (Hunter et al, 2003), LAMB1 (Mash et al, 2007) and VWF (Mash et al, 2007). NRXN1 is the only gene that could also be detected by haplotype analysis.…”

“…Interestingly, we also found that several candidate genes participate in more than one pathway, facilitating the crosstalk among pathways. Most of these crosstalk genes have been verified to be alcoholism genes, such as TTN (Hunter et al, 2003), ITPR1 (Saito et al, 1996), and GRIA1 (Hu et al, 2008), and they provide more indepth information to further explore the aetiology of alcoholism.…”

Whole Brain and Brain Regional Coexpression Network Interactions Associated with Predisposition to Alcohol Consumption

“…The availability of genome-wide measures of gene (transcript) expression levels provides the opportunity to identify gene coexpression networks, which have been reported to reflect biologically meaningful clustering of gene products [4], [5], [6] A further benefit of this approach is the identification of the genetic basis for regulation of the coexpression networks (genetics of gene expression), i.e., determination of the genetic markers or genomic regions that are associated with quantitative variation of transcript expression levels [7]. At the single gene level, the correlation of gene expression levels with a complex biological trait, combined with quantitative trait locus (QTL) analysis that identifies common genomic regions that regulate gene expression (eQTL) and the biological trait (bQTL), has been used by us and others to identify candidate genes for various complex phenotypes [8], [9], [10], [11], [12]. The same approach can be applied to transcriptional networks comprising gene coexpression modules.…”