Quantitative trait loci involved in genetic predisposition to acute alcohol withdrawal in mice

Abstract

Alcohol dependence (alcoholism) is accompanied by evidence of tolerance, withdrawal (physiological dependence), or compulsive behavior related to alcohol use. Studies of strain and individual differences using animal models for acute physiological dependence liability are useful means to identify potential genetic determinants of liability in humans. Behavioral and quantitative trait analyses were conducted using animal models for high risk versus resistance to acute physiological dependence. Using a two-step genetic mapping strategy, loci on mouse chromosomes 1, 4, and 11 were mapped that contain genes that influence alcohol withdrawal severity. In the aggregate, these three risk markers accounted for 68% of the genetic variability in alcohol withdrawal. Candidate genes in proximity to the chromosome 11 locus include genes encoding the alpha1, alpha6, and gamma2 subunits of type-A receptors for the inhibitory neurotransmitter, GABA. In addition, suggestive linkage is indicated for two loci on mouse chromosome 2, one near Gad1 encoding glutamic acid decarboxylase, and the other near the El2 locus which influences the seizure phenotype in the neurological mutant strain El. The present analyses detect and map some of the loci that increase risk to develop physiological dependence and may facilitate identification of genes related to the development of alcoholism. Syntenic conservation between human and mouse chromosomes suggests that human homologs of genes that increase risk for physiological dependence may localize to 1q21-q32, 2q24-q37/11p13, 9p21-p23/1p32-p22.1, and 5q32-q35.

Fig. 1.

Phenotypic relationship between baseline and postethanol withdrawal convulsions in BXD RI strains. Each data point identifies the strain mean ± SEM for baseline (x-axis) and postethanol withdrawal convulsions (area under the curve,y-axis) for the BXD RI strains (e.g., 9 represents strain BXD-9) or the B6 or D2 progenitor strains. The least squares linear regression of postethanol withdrawal severity on baseline convulsion scores using 21 BXD RI strains is shown (r = 0.66, p < 0.01) and did not include the two progenitor strains. Residual alcohol withdrawal severities for the BXD RI strains and their progenitor strains are measured as the vertical distance between theregression line and the strain means for postethanol withdrawal area under the curve.

Fig. 2.

Linkage analysis using B6D2 F2 intercross mice provides evidence for a QTL influencing alcohol withdrawal on chromosome 4. Alcohol withdrawal was indexed using the handling-induced convulsion. The mice were scored for baseline handling-induced convulsions immediately before administration of 4 gm/kg ethanol (thearrow marks ethanol injection at time 0), and hourly between 2 and 12 hr after alcohol administration. Data represent the mean raw scores ± SEM for baseline and postethanol handling-induced convulsions. Alcohol administration initially lowers convulsion scores (0–4 hr). Later, convulsion scores increase above baseline, indicating a state of withdrawal hyperexcitability, which peaks ∼6–7 hr after alcohol administration. From 451 F2 intercross mice tested for physiological dependence, we genotyped 167 mice with the highest withdrawal scores and 167 mice with the lowest withdrawal scores. B6D2 F2 mice homozygous for the D2 allele atD4Mit186, a marker located 42.6–45.5 cM from the centromere, showed more severe withdrawal than B6B6 homozygous F2 mice.Inset, Gene dosage at D4Mit186 has a significant influence on alcohol withdrawal severity calculated as area under the curve [F_(2,331) = 3.3,p = 0.02). *D2D2 homozygotes have more severe withdrawal than B6B6 homozygotes or B6D2 heterozygotes (Tukey HSD test,p < 0.05).

Fig. 3.

Allelic frequencies at loci on chromosomes 1, 4, and 11 cosegregate with phenotypic selection for acute alcohol withdrawal severity. A, The selection response [mean ± SEM is shown for the first four generations of selective breeding (S1–S4)] for differences in acute withdrawal liability (HAW and LAW). On they-coordinate, alcohol withdrawal severity is shown as the computed area under the curve(AUC), calculated on the basis of the time course for handling-induced convulsions measured between 4 and 12 hr after alcohol administration. B, In generations S1–S4, gene frequency at Tyrp1 for the D2 allele diverged in the two oppositely selected lines approximately in parallel with the trait under selection. By generation S2, the HAW and LAW lines differed in their gene frequencies (q) for the D2 allele for Tyrp1(q_HAW = 0.89,q_LAW = 0.22, z = 4.18,p = 1 × 10⁻⁵). Similarly, in generations S2 and S4, allelic frequencies at C,D1Mit206 (q_HAW = 0.57,q_LAW = 0.17, z = 2.47,p = 0.006 using generation S2) andD, D11Mit174(q_HAW = 0.39,q_LAW = 0.76, z = 2.34,p = 0.008 in generation S2) diverged approximately in parallel with alcohol withdrawal severity. Because allelic frequencies of the D2 and B6 alleles at the markers shown diverged in the HAW and LAW lines approximately in parallel with divergence of the trait under selection, these data indicate that QTL underlying differences in alcohol withdrawal between the HAW and LAW lines are linked to the markers Tyrp1 (chromosome 4, 38 cM),D1Mit206 (chromosome 1, 96 cM), andD11Mit174 (chromosome 11, 20 cM).

Fig. 4.

Estimated confidence intervals and candidate genes for alcohol withdrawal QTL identified on chromosomes 1, 2, 4, and 11. The markers tested using the B6D2 F2 population are shown, and their map positions (Silver et al., 1996) indicated in centiMorgans from the centromere (at 0 cM). Estimated 1.0 LOD confidence intervals for the positions of QTL on mouse chromosomes 1, 2 (proximal), and 11 are shown (boxed regions), based on interval analysis of our B6D2 F2 data using MAPMAKER/QTL. For chromosome 4, the boxed regionindicates the range of markers examined in our F2 data, but the 1.0 LOD confidence interval for this QTL actually extends beyond the range of markers examined. For chromosome 2, the 1.0 LOD confidence interval is shown only for the proximal QTL, because MAPMAKER/QTL interval analysis cannot resolve the influence of two linked QTL with opposite effects on a phenotype. The position of the best correlated marker for each separate experiment (i.e., RI, F2, or S2) is also indicated within eachboxed region. Candidate genes located within or near the 1.0 LOD confidence intervals are also shown (from Silver et al., 1996).El2, an epilepsy quantitative trait locus, is located ∼75 cM (between 53 and 80 cM) distal to the centromere of chromosome 2 (Frankel et al., 1995).

Fig. 5.

Alcohol withdrawal severity in F2 mice recombinant between D2Mit9 and D2Mit17. Data represent the mean ± SEM for F2 mice recombinant betweenD2Mit9 (37 cM) and D2Mit17 (69 cM), markers associated with two opposing QTL detected within the proximal and distal regions of chromosome 2. Recombinant F2 mice with risk alleles at both QTL (i.e., D2D2 at D2Mit9 and B6B6 atD2Mit17, n = 6 mice) showed higher handling-induced convulsion scores during withdrawal than recombinant F2 mice that possess protective alleles at both QTL (i.e., B6B6 atD2Mit9 and D2D2 at D2Mit17,n = 3 mice). Inset, Genotype atD2Mit9 and D2Mit17 has a significant influence on alcohol withdrawal severity calculated as area under the curve (*p < 0.05, two-tailedt test).

Fig. 6.

The C57BL/6J strain shows greater GAD activity as compared with DBA/2J mice. Total brain GAD activity was 31% higher in mice from the B6 progenitor strain as compared with the D2 strain (1282 ± 107 and 976 ± 48 pmol [¹⁴C]CO₂/mg protein per minute were generated, respectively) (*p < 0.05, two-tailedt test). Data represent the mean ± SEM for five independent experiments performed in triplicate.