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DAHCHOUR A. and DE WITTE P. Acamprosate decreases the hypermotility during repeated
ethanol withdrawal. Alcohol. 18: 77-81, 1999.
DAHCHOUR A. and DE WITTE P. Effect of repeated ethanol withdrawal on microdialysate
glutamate release in the hippocampus. Alcohol. Clin. Exp. Res. 23: 1698-1703, 1999.
DAHCHOUR A. and DE WITTE P. Ethanol and amino acids in the CNS: assessment of the
pharmacological actions of acamprosate. Progress Neurobiol. 60: 343-362, 2000.
DAHCHOUR A. and DE WITTE P. Taurine blocks the glutamate increase in the nucleus
accumbens microdialysate during ethanol withdrawn rats. Pharmacol. Biochem. Behav. 65:
345-350, 2000.
DAHCHOUR A. and DE WITTE P. L’acamprosate réduit la mortalité pendant les sevrages
itératifs expérimentaux chez le rat. Alcoologie et addictologie. 23 : 437-440, 2001.
DAHCHOUR A. and DE WITTE P. Effects of acamprosate on excitatory amino acids during
repeated ethanol withdrawal: an in vivo microdialysis study. (Submitted for publication).
family study designed to identify genes that affect the risk for alcohol dependence and
alcohol-related traits and behaviors. Alcoholism is a complex genetic disease, so there
will be no single “gene for alcoholism.” We expect that variations in many different
genes, interacting with each other and with the environment, will affect the risk for
alcoholism. This makes the task of finding genes that affect the risk very difficult.
COGA was founded as a large collaboration among six (now nine) sites across the
United States, to bring together a range of expertise and to allow collection of a large
sample of families of alcoholics.
allow the use of multiple methods of genetic analysis. Systematic recruitment of
subjects from alcoholism treatment facilities was followed by careful assessment of
the subjects and their family members. Control families were also recruited. In
addition to extensive interview data, using the Semi-Structured Assessment for the
Genetics of Alcoholism (SSAGA), we obtained electroencephalograms (EEGs) to
measure overall brain activity and event-related potentials (ERPs) elicited in response
to specific stimuli. The richness of the data collected allows exploration of many
phenotypes related to alcoholism, in addition to analyses under standard diagnostic
systems (DSM-IV, ICD-10). We collected a large sample, interviewing approximately
12,000 people.
regions that contain gene(s) affecting the risk for alcoholism. More than 1.2 million
genotypes were generated on 2,310 individuals from families of alcoholics and 1,238
individuals from control families in this phase of the research. This strategy also
allowed identification of regions that contain gene(s) affecting the
reveal biological processes intermediate between the genes and the behaviors.
alcoholism, and a region on chromosome 4 that appears protective (Reich et al 1998
Am J Med Genet 81:207; Foroud et al Alc Clin Exp Res 24:933). A region affecting
severity of the disease was mapped to chromosome 16 (Foroud et al. 1998 Alc Clin
Exp Res 22:2035). The region on chromosome 4 that appeared protective also
contains gene(s) that affect the maximum number of drinks consumed in a 24 hour
period (Saccone et al. Am J Med Genet 96:632). This region contains a cluster of 7
alcohol dehydrogenase genes, strong candidates because prior results have shown that
polymorphisms of these genes affect the risk for alcoholism. There was also evidence
that the locus on chromosome 1 influenced vulnerability to alcoholism and affective
disorder (Nurnberger et al Am J Psych 158:718). In contrast, we found no evidence
that variations in the dopamine receptor DRD2 gene or in the serotonin transporter
HTT gene were related to the risk for alcoholism (Edenberg et al 1998 Alc Clin Exp
Res 22:505 and Alc Clin Exp Res 22:1080).
children prior to exposure, and has been suggested as a phenotypic marker for
vulnerability to alcoholism (Porjesz et al 1998 Alc Clin Exp Res 22:1317). We
identified regions on chromosomes 2, 5, 6, and 13 that contain genes influencing the
voltage of the P3 event-related potential (Begleiter 1998 Electroenceph Clin
Neurophys 108:244). In the ADH region of chromosome 4, there is an interaction
between genes affecting diagnosis and those affecting ERP (Williams et al 1999 Am J
Hum Genet 65:1148). In more recent work, we have identified a locus that affects the
beta frequency of the EEG (Porjesz et al 2002 PNAS 99:3729). This was located in a
cluster of genes encoding GABA(A) receptors.
affect the risk for alcoholism and related phenotypes. We are genotyping SNPs in key
regions, using high-throughput technology, and analyzing them for linkage
disequilibrium with the traits. Because linkage disequilibrium extends over much
shorter distances than linkage to microsatellites, this should allow us to greatly narrow
the regions and identify individual genes.
PHENOTYPES WITH RESPECT TO ALCOHOL
CONSUMPTION
model a fundamental aspect of human alcoholism such as excessive alcohol drinking.
These lines have been termed UChB, AA, P, HAD, and sP. Together with the alcohol-
accepting line, a line of alcohol-non preferring rats (UChA, ANA, NP, LAD and sNP,
respectively) has been derived from the same foundation stock.
These line couples of alcohol-preferring and -non preferring rats have been generated
for the same phenotype (preference or aversion for alcohol over water and high or low
alcohol intake under the standard homecage two-bottle 10% alcohol vswater choice
with unlimited access for 24 hours/day), using similar procedures of selective
breeding, and adopting similar cut-offs for the evaluation of alcohol preference and
consumption. Selective breeding programs started from individuals of outbred
populations with maximum difference in alcohol drinking behavior; the highest
alcohol-consuming individuals were mated to start the alcohol-preferring lines and,
conversely, the lowest alcohol-consuming individuals were mated to generate the
alcohol-non preferring lines. At each generation, offspring were first tested for
alcohol preference and avoidance, and then mated again, until fulfillment of selective
criteria in virtually the totality of the line rats.
As a result of this selective breeding, alcohol-preferring rats typically consume
approximately 6 g/kg/day alcohol and avoid water almost completely. This appears to
be a feature common to all rat lines. In contrast, alcohol-avoiding rats greatly prefer
water over the alcohol solution and consume daily less than 0.5 g/kg alcohol.
The genetic selection of alcohol preference or avoidance phenotypes has yielded
theoretically differential segregation only at those genes involved in the control of
alcohol preference and intake, randomizing all other loci that are not related to or
influenced by genes regulating alcohol drinking behavior. Thus, alcohol-preferring
and -non preferring rats constitute valid animal models for investigation of the
genetically determined, neurochemical and behavioral traits associated and/or
causally related to alcohol reinforcement and aversion.
However, although selected under similar procedures, these rat lines have been
differentiated for a number of genetically controlled traits, likely associated to the
development of alcohol preference. For instance, the rat lines selected for high alcohol
intake have been reported to greatly differ in a) initial sensitivity to alcohol, b)
anxiety-related behaviors, c) development of relapse-like drinking (i,e, the so-called
alcohol deprivation effect), and d) baseline levels of brain neurotransmitters likely
involved in the mediation of alcohol reinforcement.
A possible explanation for these disparities may reside in the likely differences
existing in the genetic make-up of these rat lines. In other words, although these rat
lines have been selected for the same phenotype following similar breeding
procedures, the above discrepancies suggest that a) different genotypes are involved
in the development of alcohol preference, and b) the contribution of each genotype
may vary among these rat lines. These differences apparently result in multiple forms
of high alcohol preference, which appear to reproduce the different types of alcoholics
better than a theoretical single animal model.
Consistently, the effect of different drugs on voluntary alcohol intake has been
reported to vary markedly among the different lines of alcohol-preferring rats,
reproducing the large variability with which pharmacotherapies may affect alcohol
drinking among the different subgroups of alcoholics. These data also suggest that
differences may exist in the neural substrates mediating the reinforcing properties of
alcohol in these rat lines.
APPROACHES
the development and introduction of clinically effective pharmacological treatments
in this disorder. Presently available compounds have been developed based on a priori
knowledge of the role of opioid, amino acid and serotonergic transmission,
respectively. This kind of “candidate system strategy” has proven its utility, but has
limitations when it comes to discovery of novel target systems, and therefore restricts
the range of potential novel treatments.
Recently, behavioral genomics strategies have provided useful tools in the search for
novel treatment targets. A strategy which has become feasible is to analyse global
expression patterns in brain areas controlling relevant behaviors. This approach can be
applied to validated animal models based on genetic selection, or models based on
environmental manipulations leading to neuroadaptive processes underlying the
transition from a non-dependent to a dependent state. By contrasting expression
patterns in lines selected for high alcohol consumptions with that of lines selected for
low intake levels, or between subjects with vs without neuroadaptation, novel
candidate genes may be identified, whose products, when differentially expressed,
may render subject vulnerable for developing dependence, or encode the dependent
phenotype. An important and complementary behavioral genomics strategy is
quantitative trait locus (QTL) analysis of behavioral traits such as high alcohol
consumption. Focused follow up analysis of expression, and finally molecular
(transgenic overexpression or knock-out) and pharmacological validation of candidate
targets closes the loop in this strategy.
The complementarity of these methods has recently been illustrated by a QTL for
high alcohol consumption found by Carr et al. in the Indiana alcohol preferring (P)
rat. This QTL contributes appr. one third of the variance of alcohol preference, and
maps to markers within the prepro-neuropeptide Y (NPY) gene. In our laboratory,
expression analysis within a second genetic model, the Finnish AA rat indicates
differential expression of NPY and its receptors, which may contribute to the
phenotype in this line. Separate work in genetically engineered mice by Thiele and
coworkers indicates inverse correlation between NPY expression and alcohol self-
administration in NPY transgenic and null-mutant mice. Finally, as predicted by these
studies, we have recently found that pharmacological targeting of the NPY system
markedly and selectively suppresses operant alcohol-self-administration on limited
access. The sensitivity for this effects is enhanced in subjects with a history of
dependence, indicating an underlying neuroadaptive process involving the NPY
system.
We have more recently applied a similar strategy to a novel model of the transition
from a low- to high-drinking state. Following repeated cycles of EtOH vapor