0145-6008/92/1603-05 11$3.00/0 ALCOHOLISM: CLINICAL A N D EXPERIMENTAL RESEARCH
Vol. 16, No. 3 May/June 1992
Classical Genetic Analyses of Responses to Sedative= Hypnotic Drugs in Crosses Derived from Long-Sleep and Short-Sleep Mice Christopher M. de Fiebre, Rodney J. Marley, Lucinda L. Miner, Nancy Ellen C. de Fiebre, Jeanne M. Wehner, and Allan C. Collins
membranes as measured by electron spin resonance and fluorescence polarization techniques (reviewed in Ref. 4). Several years ago we reported the results of a study that compared the sensitivities of two selectively bred mouse lines to the anesthetic effects of 17 sedative-hypnotic drugs including barbiturate^.^ The mouse lines used in this study were selectively bred for differences in duration of ethanolinduced anesthesia or sleep time.6’7These mouse lines, designated long-sleep (LS) and short-sleep (SS), differ in duration of ethanol-induced sleep-time because of differences in central nervous system sensitivity to ethanol; only small differences in the rate of ethanol elimination exist.’ Our analysis of the relative sensitivities of the two mouse lines to the 17 test drugs yielded an interesting result: the mouse lines differed in sensitivity to drugs with relatively low lipid solubility whereas they did not differ in sensitivity to highly lipid soluble drugs. This suggeststhat the selective breeding of these mice was specific for anesthetic agents with lipid solubilities which are similar to ethanol. The actions of ethanol, in all probability, are quite complex. The anesthetic actions, for example, are probably due to actions on more than one system as suggested WIDE VARIETY of compounds such as noble gases, by estimates of the number of genes that influence ethanolalkanes and alcohols as well as more chemically induced sleep-time. Two estimates of the number of genes complex agents such as some barbiturates and steroids are or, more correctly, “effective factors” that regulate the capable of eliciting surgical levels of anesthesia. A casual differential anesthetic sensitivities of the LS-SS mice to examination of the structures of the many compounds ethanol have been made. Dudek and Abbott’ obtained an that elicit anesthesia fails to reveal anything resembling a estimate of 8.8 factors using a Mendelian cross method common structure. The only relationship that has emerged identical to that used in the present study and DeFries et is that anesthetic potency increases along with lipid solu- a1.I’ obtained an estimate of 7.1 from an analysis of the bilit~.’-~ This finding might mean that anesthesia results sleep-time responses of the 27 recombinant inbred strains from a nonspecific interaction between the drug and one that have been derived from the LS-SS mice. These findor more components of the neuronal membrane as is ings argue that the anesthetic effects of ethanol are polysuggested by the observation that a wide variety of agents genically determined and that ethanol affects a number of with anesthetic properties increase the fluidity of lipid systems to elicit anesthesia. It is not known how many factors regulate the anesthetic action of other sedativeFrom the Institute for Behavioral Genetics (C.M.dF., R.J.M., L.L.M., hypnotic drugs and whether there is any overlap between J.M. W..A.C.C.), SchoolofPharmacy(C.M.dF., R.J.M., J.M. W.,A.C.C.), the effective factors that regulate the anesthetic effects of and Department of Psychology (L.L.M., M.E.dF., A.C.C.), University of the various sedative-hypnotic drugs. The finding that LSColorado, Boulder, Colorado. SS differences are specific for agents with low lipid soluReceived for publication July 9, 1991; accepted January 27, 1992 This work was supported by AA-03527, MH-16880, HD-07289, and bilities, however, suggests that there is differential genetic DA-00116. regulation of sensitivity to lipid insoluble and lipid soluble Reprint requests: Dr. Allan C. Collins, Institute for Behavioral Geagents. netics, Campus Box 447, University of Colorado, Boulder, CO 80309The examination of the relative sensitivities of the LS 044 7. and SS mice to other sedative-hypnotic drugs was a first Copyright 0 1992 by The Research Society on Alcoholism. A classical (Mendelian) genetic analysis of responses to eight sedative-hypnotic compounds (ethanol, urethane, trifluoroethanol, chloral hydrate, barbital, paraldehyde, methyprylon, pentobarbital) was conducted in crosses derived from mouse lines that were selectively bred for differential duration of anesthesia following ethanol. The sleep-time responses of these mice, the long-sleep (LS) and short-sleep (SS) mouse lines, as well as the F1, F2 and backcross (F1 x LS, F1 x SS) generations were measured. Generally, differences in responses among the generations were greater for water soluble compounds than were differences for more lipid soluble compounds. Also, the inheritance of responses to water soluble compoundscould be explained primarily by additive effects of alleles while the inheritance patternsfor more lipid soluble compoundswere more complex. Genetic correlation with ethanol response decreased with increasing lipophilicity.These results suggest that the selection of the LS-SS mouse lines was specific for water soluble anesthetic agents. Because several of these agents are known to act at GABA receptors,examination of the interactions of compounds which differ in lipid solubility at GABA receptors from LS and SS mice may prove useful in elucidating the mechanism of the anesthetic actions of ethanol and other drugs. Key Words: Chloral Hydrate, Paraldehyde, Alcohol, Barbiturates, Methyprylon.
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AIcoholClin Exp Res, Vol 16, No 3 , 1992: pp 51 1-521
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DE FIEBRE ET AL.
512
step in assessing whether there is overlap in the genetic barbital, methyprylon, and urethane was 0.01 ml/g. Due to the known sensitivity of LS and SS mice to high concentrations of regulation of sensitivitiesto ethanol and to other sedative- differential ethanol," this agent was administered as a 20% w/v solution and dose hypnotic drugs. However, a problem associated with ex- was adjusted by varying the injection volume. Dose-response curves were amining correlated responses such as these in the LS and generated for each drug for the LS-SS parental lines. From these data, SS mouse lines is that inbreeding has occurred as selection the dose at which maximal LS-SS differences were seen was chosen for proceeded. The inbreeding coefficients, calculated for gen- testing the other generations as follows: ethanol, 80 mmol/kg; urethane, 14 mmol/kg; trifluoroethanol, 12 mmol/kg; chloral hydrate, 2.12 mmol/ eration 33 animals, were 0.60 and 0.79 for the LS and SS kg; barbital, 1.25 mmol/kg; methyprylon, 1.O mmol/kg; paraldehyde, lines, respectively.' ' This inbreeding has increased the 7.57 mmol/kg; and pentobarbital, 0.31 mmol/kg. probability that chance associations will be obtained; thus, our observation that the LS-SS difference in sensitivity to the anesthetic effects of sedative-hypnotic drugs decreases Sleep Time The procedures for the sleep-time test were similar for each of the with an increase in lipid solubility5 might have arisen because of chance fixation of alleles (genes) that regulate compounds tested. All testing took place in an isolated, temperaturecontrolled room. Mice were injected with drug and the time between loss high or low sensitivity to drugs other than ethanol. One and regaining of the righting reflex was measured. Animals were judged way of determining whether or not apparent associations to have lost the righting reflex when they could not right themselves are due to chance fixation of alleles or whether genetic three times within a 30-sec period after being placed on their backs in a correlations exist is to assess the cosegregation of traits, in V-shaped trough. Similarly, animals were judged to have regained the this case sleep-time response to ethanol and other sedative- righting response when they could right themselves three times within a 30-sec period. If an animal failed to lose the righting response, a sleep hypnotic agents, in genetically segregating populations. time of zero was recorded. It has been our experience that sleep times in The studies reported here replicate our earlier findings excess of 180 min are frequently associated with a high incidence of that LS-SS differences decrease with increasing lipid sol- lethality. Therefore, in order to avoid the potential confounds related to ubilities. We also report the use of a Mendelian cross lethality, the maximal sleep time allowed was 180 min. analysis to test further the potential association between ethanol sensitivity and sensitivity to the anesthetic effects Data Analyses of several other drugs. The results obtained suggest that Data for all drugs were analyzed by analysis of variance (ANOVA) to ethanol shares sites or mechanisms of action with other assess the main and interactive effects of generation and sex. Because all water soluble agents including several that are not alcohols of the generations were not tested at a single dose, it was not possible to and are believed to act at specific neuronal receptor sites. assess the effects of drug dose in the segregating generations. However, METHODS Animals Both sexes of the LS and SS mice as well as mice bred for use in the Mendelian analyses were used in these studies. The classical analysis was constructed by reciprocal crosses of LS and SS mice to produce the F l generation. It is assumed that the LS and SS mice are homozygous at all loci which regulate the sleep-time response to ethanol. While the F1 animals are heterozygous at all loci where the parental LS-SS mice differ, they should be isogenic at all loci involved in the sleep-time response. Thus, the LS, SS, and F1 animals can be considered pseudo-isogenic. Mice from the F1 generation were intercrossed to produce the F2 generation. Crosses of male and female F1 animals to both sexes of the parental LS and SS generations were made to produce the two backcross generations (F1 x LS and F1 x SS). Rearrangements of genes occur in the F2 and backcross generations thereby breaking down spurious associations between traits. All mice were raised at the Institute for Behavioral Genetics, kept on a 12-hr light:12-hr dark cycle and were allowed food (Wayne Lab Blox) and water ad libitum. Mice were weaned at 25 days of age and were housed with one to five like-sex littermates. Animals were 60 to 100 days old when tested. All animals were tested only once and all testing was conducted between 8:OO AM and 4:OO PM.
Drug Administration All of the drugs, with the exception of methyprylon, were obtained from Sigma Chemical Co. (St. Louis, MO). Methyprylon was a generous gift of Roche Laboratories (Nutley, NJ). These drugs were administered by intraperitoneal injection of the drug dissolved in physiological saline. The injection volume for trifluoroethanol, chloral hydrate, and paraldehyde was 0.02 ml/g, whereas the injection volume for barbital, pento-
for the LS-SS parental generations, the main and interactive effects of dose were assessed by ANOVA. For those analyses in which significant effects were found, the results were subjected to the Tukey B post hoc test. Because no sex differences were found for any of the drugs, all of the genetic analyses described below were performed with data from the two sexes combined. Additionally, ED6,,,,,," values, the dose at which animals slept an average of 60 min, were calculated and the entire doseresponse curves for the LS-SS parental lines were analyzed by a computerized regression line comparison program. This program sequentially tests for: (1) differences in homogeneity of variance (an F test), (2) differences in slope (a t test) and ( 3 )whether the lines are superimposable (i.e., identical) (a t test). This method of analysis takes into account all points on the linear portions of the dose-response curves and therefore is more powerful than using a a t test to test for differences in values. Also, unlike using an ANOVA, the entire dose-response curves for two groups can be compared even when the doses given to the two groups do not overlap. Therefore, this method allows greater flexibility in analyzing dose-response data than is possible by ANOVA. The classical (Mendelian) cross data were initially analyzed using the method of Br~el1.I~ A graphic triangle is constructed with this method. Mean values are plotted on the ordinate while gene dosage is plotted on the abscissa. The mean values of the nonsegregating, pseudo-isogenic populations (LS, SS, and F l generations) are plotted to form the three corners of the triangle. If genetic control of a trait is purely additive (i.e., there is no dominance or epistasis) the F1 generation will fall directly on the line which connects the two parental generations. This point, the midparent value, is halfway between the two parental generations and is equivalent to the average ofthe parental means. In the absence of epistasis any deviation of the F1 generation from this midparent value is indicative of dominance. Furthermore, any deviation of the three segregating generations (F2, F1 X LS, and F l x SS) from the lines of the triangle is indicative of epistatic interaction. In the absence of epistasis, the F2 generation is expected to lie halfway between the two backcross generations.
RESPONSE TO SEDATIVE-HYPNOTIC DRUGS
513
The genetic data were then subjected to the means analysis of Mather and Jinks.I4 This more sophisticated analysis utilizes a weighted (by variance) least squares regression approach to obtain estimates of the midparent value (m), an additive genetic effect ([d]) and a dominance genetic effect ([h]) as well as the three epistatic parameters [i], b] and [I] . For actual data sets, the fit of genetic models containing any or all of these parameters can be assessed through x 2 testing. The expectations of a full genetic model containing all of these parameters are presented in Table 1. Data for each of the drugs were first fitted to a model which only included the m parameter; i.e., all other parameters were set to zero. If there was no segregation among the generations, this model would fit the data (i.e., a nonsignificant x2 would be calculated). Subsequently, data were fitted to each of the genetic models listed in Table 2 and the fit of each of these models was assessed by x 2 testing. The relative fit of models was assessed by comparing the ratios of respective x2 degrees of freedom (an F test; e.g., Ref. 9). The simplest model which fit the data was the best fitting model in each case. Genetic correlations, the degree to which two traits are related, were calculated between response to ethanol and response to the other sedative-hypnotic agents. Using data from the six generations, genetic correlations were estimated by the calculated Pearson product-moment corTable 1. Assumptions of a Full Genetic Model Including the Parameters: m, Midparent Value; [d], Summation of Additive Genetic Effects; [h], Summation of Dominance Deviations: [i] Epistatic Interaction between Homozygous Pairs of Alleles; b], Epistatic Interaction between Homozygous and Heterozygous Pairs of Alleles; and [I] Epistatic Interaction between Heterozygous Pairs of Alleles Full model Generation with epistasis P1
(LS)
pz (SS) F1 F2
Bq (Fi X LS) Bz F, X SS)
Table 2.
+ [i] m + [d] + [i] rn + [hl + [I1 m + %[h] + 'h[I] m - %[d] + Vz[h] + %[i] - lh[j] + %[I] rn - [d]
m + %[d1 + M[h] + U[il
+ ihb] + l/4[I]
Genetic Models and Degrees of Freedom for Each Model Tested Using the Means Analysis of Mather and Jinks (1977) df
relation coefficient between the mean sleep-time values for ethanol and the mean sleep-time values for the other agents. This method of estimating genetic correlations is approximate but has been used previously with inbred strains and no significant differences have been found in results obtained using this method versus more sophisticated method^.'^.'^ The relationship between these genetic correlations and the lipid solubility of the drugs employed in these studies was analyzed by a correlational analysis. Specifically, the correlation between the log of the octanol/ water partition coefficients (log p) and the genetic correlation with ethanol response was calculated. Similarly, the correlation between the log of the octanol/water partition coefficients (log p) and the ratio of SS to LS ED60mln values was calculated. The octanol/water correlation coefficients used were those determined by Leo et al." Due to concerns to be addressed in the discussion, data for trifluoroethanol and methyprylon were omitted from the analysis.
RESULTS
The sleep-time responses of the LS-SS parental lines to eight sedative-hypnotic drugs as well as the responses of crosses derived from these mice are presented in Figs. 1 through 8. EDhOmin values for the LS-SS parental lines as well as the results from the comparison of the LS-SS doseresponse curves are presented in Table 3. Figs. 1 through 8 present data for the eight drugs in order of increasing lipid solubility with the responses to the least lipid soluble drug (ethanol) presented in Fig. 1 and the responses to the most lipid soluble drug (pentobarbital) presented in Fig. 8. In the upper panels of the figures, the response of the six generations to a single dose of each compound is presented. In the upper left panels, values are presented in bar graph form while, in the upper right panels, values are presented in genetic triangle form.13 In the lower panels, dose-response curves for the LS-SS parental generations are presented. While significant differences were found among the generations for all drugs tested (see figure captions for P values), the degree of these differences varied among the agents. Also, the pattern of inheritance differed dependent upon the drug tested. The responses to ethanol are presented in Fig. 1. LS and SS mice differed markedly at the one common dose with which they were tested (80 mmol/kg), F( 1,36) = 627.88, p < 0.0001. Analysis of the dose-response curves also reveal large LS-SS differences (see Table 3). The genetic triangle displays an inheritance pattern which is primarily additive. The means analysis, however, reveals that a simple additive or additive-dominance model does not fit these data. Instead epistasis is indicated. It should be noted that both ceiling and floor effects could be responsible for this. Most of the LS mice tested at this dose were anesthetized for the maximal 180 min while most of the SS and many of the Fl x SS mice never lost the righting response at this dose. Post hoc analyses (Tukey B) reveal that the SS do not differ from the F1 x SS backcross generation presumably because of floor effects. This lack of a difference in all probability is the cause of the apparent epistasis. Responses to urethane are presented in Fig. 2. Similar to the finding for ethanol, the LS and SS lines differed markedly at the one common dose at which they were
DE FIEBRE ET AL.
514 Table 3. Comparison of the Sleep-Time Responses of LS and SS Mice to Eight Sedative Hypnotic Compounds
Ls ED60 mm
ss EDBOrnln
ED60mm Ratio (SS/LS)
Ethanol
52.69 & 1.216
101.9 f 1.028
1.93
Urethane
11.49 f 0.390
22.03 f 0.857
1.92
Trifluoroethanol
6.827 f 0.685
17.95 f 0.730
2.63
Drug
t Slope
dt
3.32 p < 0.005 220 2.45 p < 0.05 61 1.44
46 8.71 p < 0.0001 32 1.76
27.35 p < 0.0001 221 8.68 p < 0.0001 62 6.74 p < 0.0001 57 6.81 p < 0.0001 76 4.64 p < 0.0005 51 7.32 p < 0.0001 47 14.87 p < 0.0001 33 0.73
NS
NS
57
58
NS
1.829 ? 0.048
Chloral hydrate
2.255 f 0.052
1.23
56 0.20 NS
0.848 f 0.054
Barbital
1.166 f 0.078
1.38
75 1.04 NS
5.972 f 0.375
Paraldehyde
6.931 rt 0.252
1.16
50 1.51 NS
Methyprylon
0.716 f 0.036
Pentobarbital
0.241 f 0.008
.**..
0.238 f 0.009
fff..
0.99
t Identity
df
EDsomb.values (%SO) in mmol/kg) were calculated and the linear portions of the LS and SS dose-response curves were compared using a cornputenzed regression line comparison program as descrlbed in the methods *"*** An EDsomln value was not calculated for SS mice for methyprylon because the slope of the dose-response curve was not significantly greater than zero.
ETHANOL (11 OLS 0 3 s W F l OF2 A F 1 X LS 5 F 1 X SS
h
d
.i150 v
g
100
b
I
5 vl
50
0
Is F1 F l FZ F1 X
La
X
SS
ss
/
I
75
Fig. 1. Genetic analysis of the sleep-time response to ethanol of mice derived from a cross of LS and SS mice. The six generations differ in response to this agent; F(5,87) = 76.23, p < 0.0001. A means analysis was used to determine the genetic model which best fit the data for this drug. A model which included the parameters m, [d], [h], [i] and [I] best fit the data (~'(1)= 2 . 1 3 ; ~ > 0.10). Each bar or point represents the mean +SEM for six to 22 animals. " * ' p < 0.00010.
0
****
40 50 60 70 80
100
120
DOSE (mmol/kg)
tested (14 mmol/kg) with the LS line showing much greater sensitivity than the SS line, F( 1,23) = 3252.6, p < 0.0001. Also, the dose-response curves for these lines differ markedly (see Table 3). The genetic triangle indicates an inheritance pattern which is primarily additive. This bnding is supported by the means analysis. Fig. 3 presents the responses to trifluoroethanol. The LS mice were much more sensitive to this agent than were the SS mice at the one common dose at which both of these lines were tested (12 mmol/kg), F( 1,23) = 561.6, p < 0.0001 and, as shown in Table 3, the dose-response curves differ. Unlike the pattern for ethanol and urethane,
the genetic triangle indicates dominance as the primary inheritance pattern. Post hoc analyses reveal that only the LS mice and the F l x LS backcross generation differ from the SS mice. Furthermore, the response of the F2 generation is more similar to the response of the F l X SS backcross generation than the response of the F1 x LS generation. Consistent with this, the means analysis reveals that the inheritance is additive with significant deviations due to epistatic interactions. As was the case with ethanol and urethane, floor and ceiling effects may be partially responsible for the observed inheritance pattern. It should also be noted that variability was considerable
515
RESPONSE TO SEDATIVE-HYPNOTIC DRUGS
2 .r.
E w
W
3 H
model which included only the parameters m and [d] best fit the data (~'(4)= 8.13; p > 0.05). Each bar or point represents the mean +SEM for nine to 15 animals. '""p < 0.0001.
,. i
1751 OLS 150- oss 125.-
100-
I
75-
a
50.-
rn
25OT
****
o,
?
O ,"H 0
TRIFLUOROETHANOL (log ~ = 0 . 3 6 5 ) A
*z 1 C
v
W
I W
a
3v)
.::I
A F i X SS
0
50
MD
+ IJ
I S FA F1 FZ Fl SS X
is
X
ss
Fig. 3. Genetic analysis of the sleep-time response to trifluoroethanol. The six generations differ in response to this agent; f(5,56) = 24.54, p < 0.0001, The best fitting model included the parameters m, [d], [i] and 01 (~'(2) = 0.12; p > 0.90). Each bar or point represents the mean ~ S E M for nine to 22 animals. **'* p c 0.0001.
DOSE (mmol/kg)
with both the F2 and F1 x LS generations having animals that were anesthetized for the maximum of 180 min and animals that did not lose the righting reflex. Furthermore, unlike the situation with all of the other drugs tested, lethality (at 24 hr) was approximately 100% at all doses for all generations. Responses to chloral hydrate are presented in Fig. 4. While the LS and SS lines differed in response to thi's agent with the LS line displaying greater sensitivity (line x dose: F(3,71) = 6.802, p c 0.001), the difference in ED6orn,,,values is not as great as that which was seen for the first three agents examined (see ratios in Table 3). The genetic triangle indicates an inheritance pattern which is primarily additive, but the means analysis indicates that epistasis is involved. Post hoc analyses corrob-
orate this finding with the LS mice not differing from the F2 generation and the F1 and two backcross generations not differing from the SS mice. The sleep-time response of these animals to barbital and to paraldehyde are presented in Figs. 5 and 6, respectively. The LS and SS lines differed following administration of both of these agents [barbital: F(1,54)= 30.008, p < 0.0001; paraldehyde: F(1,lll) = 170.5, p < 0.0001], but no line x dose interaction was seen for either drug. The line comparison detected LS-SS differences in sensitivity to both of these agents (see Table 3). These differences, however, are not as great as those seen for ethanol as values. The displayed by the smaller ratio of ED6~,,,i,, inheritance pattern for both of these agents can be explained by simple additivity.
DE FIEBRE ET AL.
516
CHLORAL HYDRATE (log p=0.56)
-i 1
-
I loot + MDH + IL*
100
50
r~
X
.!3 E
n
W
a
I I
FZ T I X
SS
-
AFixss
\
01
17!j-OLS 150- oss 125100-
-
v
I I Fig. 4. Genetic analysis of the sleep-time response to chloral hydrate. The generations differ; F(5,53) = 8.70, p c 0.0001.A complex model which included the parameters in, [d], [h], [i] and [I] best fit the data (~‘(1) = 0.44; p > 0.50). Each bar or point represents the mean ~ S E Mfor nine to 12 animals. ” p < 0.01, *** p < 0.001, *’** p < 0.0001.
H
1.5
2.5
2.0
DOSE (mmol/kg)
I rn Is
3 vl
25 501 0
Fig. 5. Genetic analysis of the sleep-time response to barbital. The generations differ in response to this drug; F(5,70) = 4.92, p < 0.001, A simple additive model which included the parameters m and [d] best fit the data (~‘(4)= 3.79; p > 0.55). Each bar or point represents the mean +SEM for six to 18 animals. * p < 0.05, ** p < 0.01, *’** p c: 0.0001
ss
1 i,!
0 : .75 1.0 1.25 1.5
:
2.0
:
2.5
DOSE (mmol/kg)
The sleep-time responses to methyprylon are presented in Fig. 7. LS mice were more sensitive to the anesthetic properties of this drug than were SS mice, F( 1,36) = 15 1.7, p < 0.0001; however, this drug elicited a most unusual response in the SS mice. Long-lasting seizures, rather than a typical anesthetic response were observed. Animals that seized were given a zero sleep-time score. LS mice and mice of the other derived generations exhibited more classical anesthetic responses. However, several animals of the F2 and F1 x SS generations also failed to lose the righting response and exhibited seizures. While genetic models were not fitted to the seizure data, these findings suggest that the seizure response is a recessive trait. The inheritance of the anesthetic response is best described by an additive model with some epistasis. The genetic triangle reveals that the response of the F2 generation deviates the
most from the expectations of a simple additive model. Post hoc analysis supports this in that the F2 generation does not differ significantly from the SS line. The pattern for inheritance of sensitivity to pentobarbital is quite different from the inheritance seen for the other agents as can be seen in Fig. 8. ANOVA and the analysis of the dose-response curves revealed that LS and SS mice did not differ following administration of this compound, F( 451) = 0.69, p = 0.41 (see Table 3). While overall differences were found among the six generations (see figure legend for F value), post hoc analysis revealed significant differences only between the SS and F2 and the SS and Fl X SS generations. The means analysis reveals that a complex model including additivity and all three epistatic parameters best describe the data for this drug. The relationship between the genetic correlation to
517
RESPONSE TO SEDATIVE-HYPNOTIC DRUGS
\
h
'3c
S L .
150
150-
w 100 2]
100::
Y
oss
WF1 OF2 AFl X L S AF1 X SS
H
I
m
50
50-
0
0.
'MD Is
Fig. 6. Genetic analysis of the sleep-time response to paraidehyde. The six generations differ; F(5,75) = 14.35,~< 0.0001. An additive model which included the parameters m and [d] best fit the data (~'(4)= 6.19; p > 0.15). Each bar or point represents the mean ~ S E Mfor 10 to 18 animals. **** p < 0.0001.
5s
n
* :< 125
rn
0-
****
7.0
7.5
8.0
8.5
* * * y o
9.0
9.5
DOSE (mmol/kg)
METHYPRYLON n
'i150
WFl
3e
100
$
50
OF2
AFl X I3 AF1 X SS
v
I
Y VY
0
I3 F1 Fl FZ F1 SS X X Is 9s
5
50.25.-
/r
Fig. 7. Genetic analysis of the sleep-time response to methyprylon. The six generations differ in response to this agent; F(5,64) = 15.972, p < 0.0001. A model that included the parameters m, [d] and [j] best fit the data (~'(3)= 2.16; p > 0.50). Each bar or point represents the mean +SEM for 10 to 18 animals. " " p < 0.0001.
******** DOSE (mmol/kg)
ethanol response and the lipophilicity of the other agents is presented in Fig. 9 (methyprylon and trifluoroethanol are excluded). Genotypic correlation increases with decreasing lipid solubility ( Y = -0.97 f 0.03; p < 0.01). Similarly, the relationship of the LS-SS difference in sleeptime to the log of the octanol/water partition coefficient for ethanol and these same drugs are presented in Fig. 9. The LS-SS difference decreases in a linear fashion as lipid solubility increases (Y = -0.85 & 0.12; p < 0.05).
results obtained clearly demonstrate that the LS and SS mice differ most in sensitivity to drugs with limited lipid solubility and, as lipid solubility increases, the LS-SS differential decreases. As shown here and in the earlier s t ~ d ythe , ~ association between lipid solubility and the LSSS differential is true for alcohols, nonalcohols and barbiturates. In the earlier study, many values were estimated from dose-response curves with as few as three test doses. The dose-response curves constructed for the LS and SS lines in this study are better defined than those DISCUSSION in the previous study because more drug doses were emThe results presented here replicate our earlier report ployed; hence, the calculated EDhominvalues in this study that differences between the LS and SS mice in sensitivity are also better defined. The finding of a significant correto the anesthetic effects of various sedative-hypnotic agents lation between the LS-SS differential and log p is therefore are influenced by the lipid solubility of the drug.' The more reliable in the present study. Furthermore, the rep-
518
DE FIEBRE ET AL.
-
r
-c!-
'2 $jE
PENTOBARBITAL (log p=Z.03)
150
v
100
I
f$
3 v)
50 AFlXLS AF1 X SS
0 Is
ss
MD
+ IJL Fig. 8. Genetic analysis of the sleeptime response to pentobarbital. The six generations differ; F(5,73)= 3.07, p < 0.05. A complex model which included the parameters m, [d], [i], b] and [I]best fit the data (~'(1)= 0.001;p > 0.95). Each bar or point represents the mean +-SEM for 10 to 18 animals. ' p < 0.5.
DOSE (mmol/kg)
thermore, as noted previously, it seems likely that substantial inbreeding has occurred within these mouse lines." Thus, in this respect the major assumptions of Mendelian cross data may not have been violated. The segregation pattern of ethanol sensitivity yielded results that are best explained by an additive or additivedominance model with some epistasis (gene interaction). We suspect that a simple additive model best explains the regulation of ethanol sensitivity. This notion is consistent with the findings of Dudek and Abbott' and DeFries et r = -0.85 a]." It is probable that ceiling and floor effects in our data p ( 0.05 are responsible for the deviations seen from this model. Almost all of the LS mice given the 80 mmol/kg dose slept for the maximal 180 min. Therefore, the sleep-time 1.25response recorded for these mice probably represents an 1.00underestimate of the true sensitivity of these mice to ethanol. In contrast, virtually all of the SS and many of 0.0 0.5 1.0 1.5 2.0 the F1 x SS mice challenged with the 80 mmol/kg dose LOG P failed to lose the righting response. The recorded sleep Fig. 9. A relationship between lipid solubility (log p) and the genetic correlation times of zero overestimate the true sensitivity of these between responsiveness to sedative-hypnotic compounds and ethanol responsivemice. In fact, regression analysis of the LS-SS dose-reness. 8: relationship between lipid solubility (log p) and the ratio of SS to LS ED,. values for sleep-time. (E,ethanol; U, urethane: C, chloral hydrate; B, barbital; P. sponse curves reveals that while the LS estimate is close paraldehyde;PB, pentobarbital). to the true sensitivity of these mice, the SS score greatly lication of our earlier findings is particularly striking be- overestimates the sensitivity of these mice. It is because of these ceiling-floor problems that we did not calculate the cause only six drugs were utilized in the present study. Most classical cross analyses use inbred strains as the number of effective factors that influence ethanol sleep founding population. Since the study used here used se- time in this study. The segregation patterns for trifluoroethanol and methlectively bred mouse lines some caution should be taken yprylon were quite different from that of ethanol and were in interpreting the results. However, selection generally not included in the analyses presented in Fig. 9. Trifluoleads to homozygosity at those alleles that regulate the roethanol was not included because mice treated with the selected-for response. Therefore, the LS-SS mice should drug almost invariably died within 24 hr after drug treatbe homozygous for all of the genes that influence long and ment regardless of whether anesthesia was seen. This short sleep time, respectively. Consequently, in this repattern of lethality was not seen for any of the other drugs spect, the approach used here does not violate any major tested. The lethal effects may have arisen because trifluoassumptions used in analyzing Mendelian cross data. Fur-
RESPONSE TO SEDATIVE-HYPNOTIC DRUGS
roacetic acid, the probable major metabolite of trifluoroethanol, is highly toxic." It might be that differences seen among and within the generations in sleep-time response are confounded by differences in production of, or toxic response to, trifluoroacetic acid. Methyprylon was not included because the SS mice, and several of the F2 and Fl X SS animals, failed to lose the righting response and exhibited convulsions instead. This might be indicative that a convulsant metabolite is formed in some animals, but this is doubtful because animals exhibited convulsions very shortly after methyprylon administration. Nevertheless, the response of these animals to trifluoroethanol and methyprylon makes genetic modeling or other analyses of an anesthetic response questionable. Therefore, methyprylon and trifluoroethanol were not included in the analyses presented in the top half of Fig. 9, but removal of these drugs from the analyses does not affect the significance of the relationship between the genetic correlation to ethanol response and the log of the octanol/water partition coefficient ( r = -0.96 & 0.03; p < 0.001 with these drugs omitted and r = -0.97 +- 0.03, p < 0.00 1 with these drugs included). Only small LS-SS differences in sensitivity to chloral hydrate were detected and the segregation pattern did not fit a simple model. It has been argued that the depressant actions of chloral hydrate are due to its rapid conversion to the more lipid soluble t r i c h l o r ~ e t h a n o l (log ' ~ ~ ~p~= 0.85)." Recently, we presented evidence that chloral hyTherefore, the drate has anesthetic activity of its sleep-time response to chloral hydrate is probably mediated by both chloral hydrate and its active metabolite, trichloroethanol. If this is the case, the segregation analysis for chloral hydrate may be different from ethanol because of differences among the generations in rate of formation of trichloroethanol as well as differences in sensitivity to chloral hydrate and its major metabolite. In addition, the ratios and log p values (Fig. correlation between ED60min 9) may be confounded by an inaccurate estimate of the partition coefficient. The partition coefficient for the biologically active species in vivo is probably somewhere between the partition coefficients for chloral hydrate and trichloroethanol. Pentobarbital, the most lipid soluble drug tested, showed very small LS-SS differences and inheritance of response to this drug did not fit an additive model. Several studies have compared the relative responses of the LS and SS mice to p e n t ~ b a r b i t a l . ~ ?With ~ ' - ~ the ~ exception of the study of Alpern and McIntyre,*' all of these studies obtained results which agree with those obtained in the current study; i.e., depending on the pentobarbital dose, either no LS-SS difference was seen or the SS mice were slightly more responsive. Any differences in the responsiveness of LS and SS mice to pentobarbital, however, appear to be due pharmacokinetic factors and not to differences in CNS sensitivity.24s26 Several other genetic studies provide additional evi-
519
dence that genetic influences on ethanol- and pentobarbital-induced sleep-time are different. Two earlier studies examined the relative sensitivities of the LS and SS mice and derived generations to several sedative-hypnotic drug^.^^,^^ In both studies the inheritance pattern for pentobarbital sensitivity differed from the inheritance pattern for ethanol sensitivity. Recently, Allan and Harris3' examined the sleep-times of 93 heterogeneous stock (HS) mice following pentobarbital (50 mg/kg) and ethanol (3.5 g/kg). The correlation between pentobarbital- and ethanol-induced sleep-time was nonsignificant ( r = 0.09). The results of all of these studies may mean that ethanol and pentobarbital elicit their hypnotic effects via totally different mechanisms. Alternatively, it may be that no genetic variance exists for those sites that are affected by both drugs in the LS and SS lines or in the HS mice from which they were derived. A significant correlation between log p and genetic correlation was found in the analysis presented in the top half of Fig. 9, but examination of the figure reveals that the significance of the relationship is primarily due to the lack of a genetic correlation between pentobarbital and ethanol. Significant genetic correlations were found between ethanol and all of the other agents tested except for pentobarbital, the most lipid soluble agent tested. While not shown in the analysis in Fig. 9, a genetic correlation for methyprylon, the next most lipid soluble agent, and alcohol was calculated. This was also not significant. In the present study, no drugs with lipid solubilities between those of methyprylon (log p = 0.77) and pentobarbital (log p = 2.03) were tested. While little is known about the molecular mechanisms of action of anesthetic drugs such as urethane, chloral hydrate and paraldehyde, considerable progress has been made in recent years in understanding the mechanisms of action of the barbiturates. A major site of action for the barbiturates appears to be associated with the GABAbenzodiazepine receptor. There are differences, however, among the barbiturates in their actions at this receptor complex. Leeb-Lundberg and Olsen" have observed that lipid soluble barbiturates are much more potent in increasing the affinity of [3H]-diazepamfor its binding site on rat cortical membranes than are water soluble barbiturates. The results reported here are consistent with this finding in that the inheritance pattern for the relatively lipid insoluble barbital was markedly different from the inheritance pattern obtained with pentobarbital. It may be that a comparison of the effects of water and lipid soluble barbiturates on properties of the GABA receptor will provide much needed insight into a major mechanism of action of ethanol. Mendelian or classical crosses have been used only rarely to assess genetic associations between drug responses and the results of such an analysis must not be interpreted too broadly. The observation that the segregation patterns for two traits are similar does not necessarily mean that
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the genes which regulate these two traits are identical. Rather, this result might only mean that similar models explain each segregation pattern. For example, LS mice frequently have a peach coat color and SS are frequently albino but if coat color segregated into the various generations along with ethanol sensitivity this would not necessarily mean that “coat color genes” are also alcohol genes. However, if the segregation patterns for two traits are clearly different, the argument can be made that it is not likely that the two traits that are associated in the parental strains are regulated by precisely the same gene or set of genes. Thus, the results reported here do not prove that the same genes regulate ethanol and barbital or other water soluble drug sleep-time responses, but these results clearly argue that different genes regulate the hypnotic responses to ethanol and pentobarbital. As with all correlational analyses, the reliability of a correlation increases with the number of observations, but it is best to remember that correlation does not necessarily mean causation. Nonetheless, the observation that sensitivity to the anesthetic actions of all of the water soluble drugs is genetically correlated with sensitivity to the anesthetic actions of ethanol argues that the LS-SS differences in sensitivity to the anesthetic actions of water soluble drugs does not occur by chance. The intent of a classical cross analysis is to break down linkage, and if two traits show differing patterns of inheritance, an argument can be made for differential genetic regulation. Thus, because the apparent association between ethanol and water soluble anesthetic drug response was not broken down, it seems possible that the anesthetic responses to ethanol and these other water soluble drugs are regulated by some of the same genes. However, more stringent tests must be done to assess whether common genes regulate traits which show similar inheritance patterns. One strategy is to measure the correlation between two traits in a segregating population such as an F2 generation or a heterogeneous stock, but this method may provide erroneous information if measuring the first trait affects the second. This, we believe, is a significant concern when measuring drug-induced anesthesia because many animals exhibit symptoms of toxicity after testing. Therefore, the method of choice is to use animals with identical genotype where each animal is tested only once. Recombinant inbred strains, which are derived by inbreeding the F2 generation derived from crossing two parental strains, are especially valuable in testing genetic associations because the procedure used in developing recombinant inbreds breaks down linkage and then fixes genes in new configurations. The accompanying paper32used recombinant inbred strains derived from the LS and SS mice to test whether the anesthetic responses to drugs with low lipid solubility are regulated by the same genes. The results obtained are in agreement with the results reported in Fig. 9 in this paper: there is a significant negative correlation between lipid solubility and the degree of genetic com-
DE FIEBRE ET AL.
monality. In other words, more genes are shared in common that regulate the sleep-time response for water soluble drugs than for lipid soluble drugs. As noted above, recombinant inbred strains may be the best tool available to test genetic hypotheses concerning ethanol and other drug actions, but recombinant inbred strains, although very valuable, are often not available. Consequently, their utility is often limited. However, the genetics of alcohol literature is rich with studies that have utilized only two strains or lines of animals and attempted to correlate biochemical differences with genetically influenced behavioral differences. The interpretation of such studies is severely limited by a lack of degrees of freedom. This is especially the case if the parental line difference is one which was developed using a selective breeding program that did not include replicate lines as is the case with the LS-SS selection. The results reported here suggest that the classical cross may be of value in testing genetic hypotheses. While this method increases available degrees of freedom, we must emphasize that the results obtained should not be interpreted too broadly. In summary, the segregation patterns for all of the drugs tested were not identical, but the similarity was greater for those compounds with similar lipid solubilities. One possible explanation for these findings is that the overlap with ethanol in terms of sites or mechanisms of action decreases as lipid solubility increases. The finding that ethanol’s anesthetic actions are regulated by seven to eight “effective factor^"^*'^ might mean that ethanol exerts its effects by altering the activities of seven to eight gene products. If each of these gene products is equieffective in regulating sleep-time, researchers are faced with the difficult task of attempting to explain only a small fraction of the response on the basis of actions on a specific gene product. It may be that greater progress could be made if future studies include analyses of the actions of drugs that showed differential segregation patterns in the study reported here. ACKNOWLEDGMENTS The authors would like to thank Dr. John DeFries for his helpful advice on the analysis of these data and Ms. Alyssa Gonzales for assistance in preparation of the manuscript.
REFERENCES I . Meyer HH: Zur Theorie der Alkoholnarkose. 1. Mitt. Welche Eigenschaft der Anasthetika bedingt ihre narkotische Wirkung? Arch Exp Pathol Pharmakol42:109, 1899 2. Meyer HH: Zur Theorie der Alkoholnarkose. 111. Mitt. Der Einfluss wechseinder Temperatur auf Wirkungsstarke und Teilungskoefficient der Narkotiva. Arch Exp Pathol Pharmakol 46:338, 1901 3. Overton E Studien uber die Narkose zugleich ein Beitrag zur allgemeinen Pharmacologie. Jena, G Fisher, 1901 4. Goldstein DB: The effects of drugs on membrane fluidity. Ann Rev Pharmacol Toxicol24:43-64, 1984 5. Marley RJ, Miner LL, Wehner JM, Collins AC: Differential effects of central nervous system depressants in long-sleep and shortsleep mice. J Pharmacol Exp Ther 238:1028-1033, 1986 6. McClearn GE, Kakihana R: Selective breeding for ethanol sensitivity in mice. Behav Genet 3:409-410, 1973
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7. McClearn GE, Kakihana R: Selective breeding for ethanol sensitivity: SS and LS mice, in McClearn GE, Deitrich RA, Erwin VG (eds): Development of Animal Models as Pharmacogenetic Tools. (Department of Health and Human Services Publication ADM 8 I - I I33), Washington DC, United States Government Printing Office, 198 I , p 147 8. Gilliam DM, Collins AC: Circadian and genetic effects on ethanol elimination in LS and SS mice. Alcohol Clin Exp Res 6:344-349, 1982 9. Dudek BC, Abbott ME: A biometrical genetic analysis of ethanol response in selectively bred long-sleep and short-sleep mice. Behav Genet l4:1-19, 1984 10. DeFries JC, Wilson JR, Erwin VG, Petersen DR: LS X SS recombinant inbred strains of mice: initial characterization. Alcohol CIin Exp Res 13:196-200, 1989 11. Goldman D, Nelson R, Deitrich RA, et al: Genetic brain polypeptide variants in inbred mice and in mouse strains with high and low sensitivity to alcohol. Brain Res 341:130-138, 1985 12. Gilliam DM, Collins AC: Concentration-dependent effects of ethanol in long-sleep and short-sleep mice. Alcohol Clin Exp Res 7:337342, 1983 13. Bruell JH: Dominance and segregation in the inheritance of quantitative behavior in mice, in Bliss, EL (ed): Roots of Behavior. New York, Harper & Row, 1962, p 92 14. Mather K, Jinks J L Introduction to Biometrical Genetics. Ithaca, NY, Cornell University Press, 1977 15. Blizard DA, Bailey DW: Genetic correlation between open-field activity and defecation: Analysis with the CXB recombinant-inbred strains. Behav Genet 9:349-357, 1979 16. Hegmann JP, Possidente B: Estimating genetic correlations from inbred strains. Behav Genet 11:103-114, 1981 17. Leo A, Hansch C, Elkins D: Partition coefficients and their uses. Chem Rev 71525-615, 1971 18. Airaksinen MM, Tammisto T: Toxic actions of the metabolites of halothane: LDSoand some metabolic effects of trifluoroethanol and trifluoroacetic acid in mice and guinea pigs. Ann Med Exp Biol Fenn 46~242-248, 1968 19. Owens AH, Marshall EK, Broeun GO, et al: A comparative evaluation of the hypnotic potency of chloral hydrate and trichloroethanol. Bull Johns Hopkins Hosp 96:71-76, 1955
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20. Kaplan HL, Forner RB, Hughes WF, Jain NC: Chloral hydrate and metabolism in human subjects. J Forensic Sci 12:295-304, 1967 2 1. Erwin VG, Heston WDW, McClearn GE: Effect of hypnotics on mice genetically selected for sensitivity to ethanol. Pharmacol Biochem Behav 4:679-683, 1976 22. Siemens AJ, Chan AWK: Differential effects of pentobarbital and ethanol in mice. Life Sci 19:581-590, 1976 23. Sanders B, Sharpless SK, Collins AC, et al: Activating and anesthetic effects of general depressants. Psychopharmacology 56: 185- 189, 1978 24. OConnor MF, Howerton TC, Collins AC: Effects of pentobarbital in mice selected for differential sensitivity to ethanol. Pharmacol Biochem Behav 17:245-248, 1982 25. Dudek BC, Phillips TJ: Locomotor stimulant and intoxicant properties of methanol, ethanol, tertiary butanol and pentobarbital in long-sleep and short-sleep mice. Subst Alcohol Actions-Misuse 4:3 1-36, 1983 26. Howerton TC, O’Connor MF, Collins AC: Lipid solubility is correlated with hypnotic and hypothermic responses of long-sleep (LS) and short-sleep (SS) mice to various depressant drugs. J Pharmacol Exp Ther 227:389-393, 1983 27. Alpern HP, McIntyre TD: Evidence that the selectively bred longand short-sleep mouse lines display common narcotic reactions to many depressants. Psychopharmacology 85:456-459, 1985 28. Dudek BC, Abbott ME, Phillips TJ: Stimulant and depressant properties of sedative-hypnotics in mice selectively bred for differential sensitivity to ethanol. Psychopharmacology 82:46-5 1, 1984 29. Howerton TC, Burch JB, OConnor MR, et a1 A genetic analysis of ethanol, pentobarbital, and methyprylon sleep-time response. Alcohol Clin Exp Res 8546-550, 1984 30. Allan AM, Harris RA: Sensitivity to ethanol hypnosis and modulation of chloride channels does not cosegregate with pentobarbital sensitivity in HS mice. Alcohol Clin Exp Res 13:428-434, 1989 3 I . Leeb-Lundberg F, Olsen RW: Interactions of barbiturates of various pharmacological categories with benzodiazepine receptors. Mol Pharmacol2 1 :320-328, 1982 32. Wehner JM, Pounder JI, Parham C, Collins AC: A recombinant inbred strain analysis of the sleep-time responses to several sedativehypnotics. Alcohol Clin Exp Res 16522-528, 1992
Vol. 16, No. 3 May/June 1992
Classical Genetic Analyses of Responses to Sedative= Hypnotic Drugs in Crosses Derived from Long-Sleep and Short-Sleep Mice Christopher M. de Fiebre, Rodney J. Marley, Lucinda L. Miner, Nancy Ellen C. de Fiebre, Jeanne M. Wehner, and Allan C. Collins
membranes as measured by electron spin resonance and fluorescence polarization techniques (reviewed in Ref. 4). Several years ago we reported the results of a study that compared the sensitivities of two selectively bred mouse lines to the anesthetic effects of 17 sedative-hypnotic drugs including barbiturate^.^ The mouse lines used in this study were selectively bred for differences in duration of ethanolinduced anesthesia or sleep time.6’7These mouse lines, designated long-sleep (LS) and short-sleep (SS), differ in duration of ethanol-induced sleep-time because of differences in central nervous system sensitivity to ethanol; only small differences in the rate of ethanol elimination exist.’ Our analysis of the relative sensitivities of the two mouse lines to the 17 test drugs yielded an interesting result: the mouse lines differed in sensitivity to drugs with relatively low lipid solubility whereas they did not differ in sensitivity to highly lipid soluble drugs. This suggeststhat the selective breeding of these mice was specific for anesthetic agents with lipid solubilities which are similar to ethanol. The actions of ethanol, in all probability, are quite complex. The anesthetic actions, for example, are probably due to actions on more than one system as suggested WIDE VARIETY of compounds such as noble gases, by estimates of the number of genes that influence ethanolalkanes and alcohols as well as more chemically induced sleep-time. Two estimates of the number of genes complex agents such as some barbiturates and steroids are or, more correctly, “effective factors” that regulate the capable of eliciting surgical levels of anesthesia. A casual differential anesthetic sensitivities of the LS-SS mice to examination of the structures of the many compounds ethanol have been made. Dudek and Abbott’ obtained an that elicit anesthesia fails to reveal anything resembling a estimate of 8.8 factors using a Mendelian cross method common structure. The only relationship that has emerged identical to that used in the present study and DeFries et is that anesthetic potency increases along with lipid solu- a1.I’ obtained an estimate of 7.1 from an analysis of the bilit~.’-~ This finding might mean that anesthesia results sleep-time responses of the 27 recombinant inbred strains from a nonspecific interaction between the drug and one that have been derived from the LS-SS mice. These findor more components of the neuronal membrane as is ings argue that the anesthetic effects of ethanol are polysuggested by the observation that a wide variety of agents genically determined and that ethanol affects a number of with anesthetic properties increase the fluidity of lipid systems to elicit anesthesia. It is not known how many factors regulate the anesthetic action of other sedativeFrom the Institute for Behavioral Genetics (C.M.dF., R.J.M., L.L.M., hypnotic drugs and whether there is any overlap between J.M. W..A.C.C.), SchoolofPharmacy(C.M.dF., R.J.M., J.M. W.,A.C.C.), the effective factors that regulate the anesthetic effects of and Department of Psychology (L.L.M., M.E.dF., A.C.C.), University of the various sedative-hypnotic drugs. The finding that LSColorado, Boulder, Colorado. SS differences are specific for agents with low lipid soluReceived for publication July 9, 1991; accepted January 27, 1992 This work was supported by AA-03527, MH-16880, HD-07289, and bilities, however, suggests that there is differential genetic DA-00116. regulation of sensitivity to lipid insoluble and lipid soluble Reprint requests: Dr. Allan C. Collins, Institute for Behavioral Geagents. netics, Campus Box 447, University of Colorado, Boulder, CO 80309The examination of the relative sensitivities of the LS 044 7. and SS mice to other sedative-hypnotic drugs was a first Copyright 0 1992 by The Research Society on Alcoholism. A classical (Mendelian) genetic analysis of responses to eight sedative-hypnotic compounds (ethanol, urethane, trifluoroethanol, chloral hydrate, barbital, paraldehyde, methyprylon, pentobarbital) was conducted in crosses derived from mouse lines that were selectively bred for differential duration of anesthesia following ethanol. The sleep-time responses of these mice, the long-sleep (LS) and short-sleep (SS) mouse lines, as well as the F1, F2 and backcross (F1 x LS, F1 x SS) generations were measured. Generally, differences in responses among the generations were greater for water soluble compounds than were differences for more lipid soluble compounds. Also, the inheritance of responses to water soluble compoundscould be explained primarily by additive effects of alleles while the inheritance patternsfor more lipid soluble compoundswere more complex. Genetic correlation with ethanol response decreased with increasing lipophilicity.These results suggest that the selection of the LS-SS mouse lines was specific for water soluble anesthetic agents. Because several of these agents are known to act at GABA receptors,examination of the interactions of compounds which differ in lipid solubility at GABA receptors from LS and SS mice may prove useful in elucidating the mechanism of the anesthetic actions of ethanol and other drugs. Key Words: Chloral Hydrate, Paraldehyde, Alcohol, Barbiturates, Methyprylon.
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step in assessing whether there is overlap in the genetic barbital, methyprylon, and urethane was 0.01 ml/g. Due to the known sensitivity of LS and SS mice to high concentrations of regulation of sensitivitiesto ethanol and to other sedative- differential ethanol," this agent was administered as a 20% w/v solution and dose hypnotic drugs. However, a problem associated with ex- was adjusted by varying the injection volume. Dose-response curves were amining correlated responses such as these in the LS and generated for each drug for the LS-SS parental lines. From these data, SS mouse lines is that inbreeding has occurred as selection the dose at which maximal LS-SS differences were seen was chosen for proceeded. The inbreeding coefficients, calculated for gen- testing the other generations as follows: ethanol, 80 mmol/kg; urethane, 14 mmol/kg; trifluoroethanol, 12 mmol/kg; chloral hydrate, 2.12 mmol/ eration 33 animals, were 0.60 and 0.79 for the LS and SS kg; barbital, 1.25 mmol/kg; methyprylon, 1.O mmol/kg; paraldehyde, lines, respectively.' ' This inbreeding has increased the 7.57 mmol/kg; and pentobarbital, 0.31 mmol/kg. probability that chance associations will be obtained; thus, our observation that the LS-SS difference in sensitivity to the anesthetic effects of sedative-hypnotic drugs decreases Sleep Time The procedures for the sleep-time test were similar for each of the with an increase in lipid solubility5 might have arisen because of chance fixation of alleles (genes) that regulate compounds tested. All testing took place in an isolated, temperaturecontrolled room. Mice were injected with drug and the time between loss high or low sensitivity to drugs other than ethanol. One and regaining of the righting reflex was measured. Animals were judged way of determining whether or not apparent associations to have lost the righting reflex when they could not right themselves are due to chance fixation of alleles or whether genetic three times within a 30-sec period after being placed on their backs in a correlations exist is to assess the cosegregation of traits, in V-shaped trough. Similarly, animals were judged to have regained the this case sleep-time response to ethanol and other sedative- righting response when they could right themselves three times within a 30-sec period. If an animal failed to lose the righting response, a sleep hypnotic agents, in genetically segregating populations. time of zero was recorded. It has been our experience that sleep times in The studies reported here replicate our earlier findings excess of 180 min are frequently associated with a high incidence of that LS-SS differences decrease with increasing lipid sol- lethality. Therefore, in order to avoid the potential confounds related to ubilities. We also report the use of a Mendelian cross lethality, the maximal sleep time allowed was 180 min. analysis to test further the potential association between ethanol sensitivity and sensitivity to the anesthetic effects Data Analyses of several other drugs. The results obtained suggest that Data for all drugs were analyzed by analysis of variance (ANOVA) to ethanol shares sites or mechanisms of action with other assess the main and interactive effects of generation and sex. Because all water soluble agents including several that are not alcohols of the generations were not tested at a single dose, it was not possible to and are believed to act at specific neuronal receptor sites. assess the effects of drug dose in the segregating generations. However, METHODS Animals Both sexes of the LS and SS mice as well as mice bred for use in the Mendelian analyses were used in these studies. The classical analysis was constructed by reciprocal crosses of LS and SS mice to produce the F l generation. It is assumed that the LS and SS mice are homozygous at all loci which regulate the sleep-time response to ethanol. While the F1 animals are heterozygous at all loci where the parental LS-SS mice differ, they should be isogenic at all loci involved in the sleep-time response. Thus, the LS, SS, and F1 animals can be considered pseudo-isogenic. Mice from the F1 generation were intercrossed to produce the F2 generation. Crosses of male and female F1 animals to both sexes of the parental LS and SS generations were made to produce the two backcross generations (F1 x LS and F1 x SS). Rearrangements of genes occur in the F2 and backcross generations thereby breaking down spurious associations between traits. All mice were raised at the Institute for Behavioral Genetics, kept on a 12-hr light:12-hr dark cycle and were allowed food (Wayne Lab Blox) and water ad libitum. Mice were weaned at 25 days of age and were housed with one to five like-sex littermates. Animals were 60 to 100 days old when tested. All animals were tested only once and all testing was conducted between 8:OO AM and 4:OO PM.
Drug Administration All of the drugs, with the exception of methyprylon, were obtained from Sigma Chemical Co. (St. Louis, MO). Methyprylon was a generous gift of Roche Laboratories (Nutley, NJ). These drugs were administered by intraperitoneal injection of the drug dissolved in physiological saline. The injection volume for trifluoroethanol, chloral hydrate, and paraldehyde was 0.02 ml/g, whereas the injection volume for barbital, pento-
for the LS-SS parental generations, the main and interactive effects of dose were assessed by ANOVA. For those analyses in which significant effects were found, the results were subjected to the Tukey B post hoc test. Because no sex differences were found for any of the drugs, all of the genetic analyses described below were performed with data from the two sexes combined. Additionally, ED6,,,,,," values, the dose at which animals slept an average of 60 min, were calculated and the entire doseresponse curves for the LS-SS parental lines were analyzed by a computerized regression line comparison program. This program sequentially tests for: (1) differences in homogeneity of variance (an F test), (2) differences in slope (a t test) and ( 3 )whether the lines are superimposable (i.e., identical) (a t test). This method of analysis takes into account all points on the linear portions of the dose-response curves and therefore is more powerful than using a a t test to test for differences in values. Also, unlike using an ANOVA, the entire dose-response curves for two groups can be compared even when the doses given to the two groups do not overlap. Therefore, this method allows greater flexibility in analyzing dose-response data than is possible by ANOVA. The classical (Mendelian) cross data were initially analyzed using the method of Br~el1.I~ A graphic triangle is constructed with this method. Mean values are plotted on the ordinate while gene dosage is plotted on the abscissa. The mean values of the nonsegregating, pseudo-isogenic populations (LS, SS, and F l generations) are plotted to form the three corners of the triangle. If genetic control of a trait is purely additive (i.e., there is no dominance or epistasis) the F1 generation will fall directly on the line which connects the two parental generations. This point, the midparent value, is halfway between the two parental generations and is equivalent to the average ofthe parental means. In the absence of epistasis any deviation of the F1 generation from this midparent value is indicative of dominance. Furthermore, any deviation of the three segregating generations (F2, F1 X LS, and F l x SS) from the lines of the triangle is indicative of epistatic interaction. In the absence of epistasis, the F2 generation is expected to lie halfway between the two backcross generations.
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513
The genetic data were then subjected to the means analysis of Mather and Jinks.I4 This more sophisticated analysis utilizes a weighted (by variance) least squares regression approach to obtain estimates of the midparent value (m), an additive genetic effect ([d]) and a dominance genetic effect ([h]) as well as the three epistatic parameters [i], b] and [I] . For actual data sets, the fit of genetic models containing any or all of these parameters can be assessed through x 2 testing. The expectations of a full genetic model containing all of these parameters are presented in Table 1. Data for each of the drugs were first fitted to a model which only included the m parameter; i.e., all other parameters were set to zero. If there was no segregation among the generations, this model would fit the data (i.e., a nonsignificant x2 would be calculated). Subsequently, data were fitted to each of the genetic models listed in Table 2 and the fit of each of these models was assessed by x 2 testing. The relative fit of models was assessed by comparing the ratios of respective x2 degrees of freedom (an F test; e.g., Ref. 9). The simplest model which fit the data was the best fitting model in each case. Genetic correlations, the degree to which two traits are related, were calculated between response to ethanol and response to the other sedative-hypnotic agents. Using data from the six generations, genetic correlations were estimated by the calculated Pearson product-moment corTable 1. Assumptions of a Full Genetic Model Including the Parameters: m, Midparent Value; [d], Summation of Additive Genetic Effects; [h], Summation of Dominance Deviations: [i] Epistatic Interaction between Homozygous Pairs of Alleles; b], Epistatic Interaction between Homozygous and Heterozygous Pairs of Alleles; and [I] Epistatic Interaction between Heterozygous Pairs of Alleles Full model Generation with epistasis P1
(LS)
pz (SS) F1 F2
Bq (Fi X LS) Bz F, X SS)
Table 2.
+ [i] m + [d] + [i] rn + [hl + [I1 m + %[h] + 'h[I] m - %[d] + Vz[h] + %[i] - lh[j] + %[I] rn - [d]
m + %[d1 + M[h] + U[il
+ ihb] + l/4[I]
Genetic Models and Degrees of Freedom for Each Model Tested Using the Means Analysis of Mather and Jinks (1977) df
relation coefficient between the mean sleep-time values for ethanol and the mean sleep-time values for the other agents. This method of estimating genetic correlations is approximate but has been used previously with inbred strains and no significant differences have been found in results obtained using this method versus more sophisticated method^.'^.'^ The relationship between these genetic correlations and the lipid solubility of the drugs employed in these studies was analyzed by a correlational analysis. Specifically, the correlation between the log of the octanol/ water partition coefficients (log p) and the genetic correlation with ethanol response was calculated. Similarly, the correlation between the log of the octanol/water partition coefficients (log p) and the ratio of SS to LS ED60mln values was calculated. The octanol/water correlation coefficients used were those determined by Leo et al." Due to concerns to be addressed in the discussion, data for trifluoroethanol and methyprylon were omitted from the analysis.
RESULTS
The sleep-time responses of the LS-SS parental lines to eight sedative-hypnotic drugs as well as the responses of crosses derived from these mice are presented in Figs. 1 through 8. EDhOmin values for the LS-SS parental lines as well as the results from the comparison of the LS-SS doseresponse curves are presented in Table 3. Figs. 1 through 8 present data for the eight drugs in order of increasing lipid solubility with the responses to the least lipid soluble drug (ethanol) presented in Fig. 1 and the responses to the most lipid soluble drug (pentobarbital) presented in Fig. 8. In the upper panels of the figures, the response of the six generations to a single dose of each compound is presented. In the upper left panels, values are presented in bar graph form while, in the upper right panels, values are presented in genetic triangle form.13 In the lower panels, dose-response curves for the LS-SS parental generations are presented. While significant differences were found among the generations for all drugs tested (see figure captions for P values), the degree of these differences varied among the agents. Also, the pattern of inheritance differed dependent upon the drug tested. The responses to ethanol are presented in Fig. 1. LS and SS mice differed markedly at the one common dose with which they were tested (80 mmol/kg), F( 1,36) = 627.88, p < 0.0001. Analysis of the dose-response curves also reveal large LS-SS differences (see Table 3). The genetic triangle displays an inheritance pattern which is primarily additive. The means analysis, however, reveals that a simple additive or additive-dominance model does not fit these data. Instead epistasis is indicated. It should be noted that both ceiling and floor effects could be responsible for this. Most of the LS mice tested at this dose were anesthetized for the maximal 180 min while most of the SS and many of the Fl x SS mice never lost the righting response at this dose. Post hoc analyses (Tukey B) reveal that the SS do not differ from the F1 x SS backcross generation presumably because of floor effects. This lack of a difference in all probability is the cause of the apparent epistasis. Responses to urethane are presented in Fig. 2. Similar to the finding for ethanol, the LS and SS lines differed markedly at the one common dose at which they were
DE FIEBRE ET AL.
514 Table 3. Comparison of the Sleep-Time Responses of LS and SS Mice to Eight Sedative Hypnotic Compounds
Ls ED60 mm
ss EDBOrnln
ED60mm Ratio (SS/LS)
Ethanol
52.69 & 1.216
101.9 f 1.028
1.93
Urethane
11.49 f 0.390
22.03 f 0.857
1.92
Trifluoroethanol
6.827 f 0.685
17.95 f 0.730
2.63
Drug
t Slope
dt
3.32 p < 0.005 220 2.45 p < 0.05 61 1.44
46 8.71 p < 0.0001 32 1.76
27.35 p < 0.0001 221 8.68 p < 0.0001 62 6.74 p < 0.0001 57 6.81 p < 0.0001 76 4.64 p < 0.0005 51 7.32 p < 0.0001 47 14.87 p < 0.0001 33 0.73
NS
NS
57
58
NS
1.829 ? 0.048
Chloral hydrate
2.255 f 0.052
1.23
56 0.20 NS
0.848 f 0.054
Barbital
1.166 f 0.078
1.38
75 1.04 NS
5.972 f 0.375
Paraldehyde
6.931 rt 0.252
1.16
50 1.51 NS
Methyprylon
0.716 f 0.036
Pentobarbital
0.241 f 0.008
.**..
0.238 f 0.009
fff..
0.99
t Identity
df
EDsomb.values (%SO) in mmol/kg) were calculated and the linear portions of the LS and SS dose-response curves were compared using a cornputenzed regression line comparison program as descrlbed in the methods *"*** An EDsomln value was not calculated for SS mice for methyprylon because the slope of the dose-response curve was not significantly greater than zero.
ETHANOL (11 OLS 0 3 s W F l OF2 A F 1 X LS 5 F 1 X SS
h
d
.i150 v
g
100
b
I
5 vl
50
0
Is F1 F l FZ F1 X
La
X
SS
ss
/
I
75
Fig. 1. Genetic analysis of the sleep-time response to ethanol of mice derived from a cross of LS and SS mice. The six generations differ in response to this agent; F(5,87) = 76.23, p < 0.0001. A means analysis was used to determine the genetic model which best fit the data for this drug. A model which included the parameters m, [d], [h], [i] and [I] best fit the data (~'(1)= 2 . 1 3 ; ~ > 0.10). Each bar or point represents the mean +SEM for six to 22 animals. " * ' p < 0.00010.
0
****
40 50 60 70 80
100
120
DOSE (mmol/kg)
tested (14 mmol/kg) with the LS line showing much greater sensitivity than the SS line, F( 1,23) = 3252.6, p < 0.0001. Also, the dose-response curves for these lines differ markedly (see Table 3). The genetic triangle indicates an inheritance pattern which is primarily additive. This bnding is supported by the means analysis. Fig. 3 presents the responses to trifluoroethanol. The LS mice were much more sensitive to this agent than were the SS mice at the one common dose at which both of these lines were tested (12 mmol/kg), F( 1,23) = 561.6, p < 0.0001 and, as shown in Table 3, the dose-response curves differ. Unlike the pattern for ethanol and urethane,
the genetic triangle indicates dominance as the primary inheritance pattern. Post hoc analyses reveal that only the LS mice and the F l x LS backcross generation differ from the SS mice. Furthermore, the response of the F2 generation is more similar to the response of the F l X SS backcross generation than the response of the F1 x LS generation. Consistent with this, the means analysis reveals that the inheritance is additive with significant deviations due to epistatic interactions. As was the case with ethanol and urethane, floor and ceiling effects may be partially responsible for the observed inheritance pattern. It should also be noted that variability was considerable
515
RESPONSE TO SEDATIVE-HYPNOTIC DRUGS
2 .r.
E w
W
3 H
model which included only the parameters m and [d] best fit the data (~'(4)= 8.13; p > 0.05). Each bar or point represents the mean +SEM for nine to 15 animals. '""p < 0.0001.
,. i
1751 OLS 150- oss 125.-
100-
I
75-
a
50.-
rn
25OT
****
o,
?
O ,"H 0
TRIFLUOROETHANOL (log ~ = 0 . 3 6 5 ) A
*z 1 C
v
W
I W
a
3v)
.::I
A F i X SS
0
50
MD
+ IJ
I S FA F1 FZ Fl SS X
is
X
ss
Fig. 3. Genetic analysis of the sleep-time response to trifluoroethanol. The six generations differ in response to this agent; f(5,56) = 24.54, p < 0.0001, The best fitting model included the parameters m, [d], [i] and 01 (~'(2) = 0.12; p > 0.90). Each bar or point represents the mean ~ S E M for nine to 22 animals. **'* p c 0.0001.
DOSE (mmol/kg)
with both the F2 and F1 x LS generations having animals that were anesthetized for the maximum of 180 min and animals that did not lose the righting reflex. Furthermore, unlike the situation with all of the other drugs tested, lethality (at 24 hr) was approximately 100% at all doses for all generations. Responses to chloral hydrate are presented in Fig. 4. While the LS and SS lines differed in response to thi's agent with the LS line displaying greater sensitivity (line x dose: F(3,71) = 6.802, p c 0.001), the difference in ED6orn,,,values is not as great as that which was seen for the first three agents examined (see ratios in Table 3). The genetic triangle indicates an inheritance pattern which is primarily additive, but the means analysis indicates that epistasis is involved. Post hoc analyses corrob-
orate this finding with the LS mice not differing from the F2 generation and the F1 and two backcross generations not differing from the SS mice. The sleep-time response of these animals to barbital and to paraldehyde are presented in Figs. 5 and 6, respectively. The LS and SS lines differed following administration of both of these agents [barbital: F(1,54)= 30.008, p < 0.0001; paraldehyde: F(1,lll) = 170.5, p < 0.0001], but no line x dose interaction was seen for either drug. The line comparison detected LS-SS differences in sensitivity to both of these agents (see Table 3). These differences, however, are not as great as those seen for ethanol as values. The displayed by the smaller ratio of ED6~,,,i,, inheritance pattern for both of these agents can be explained by simple additivity.
DE FIEBRE ET AL.
516
CHLORAL HYDRATE (log p=0.56)
-i 1
-
I loot + MDH + IL*
100
50
r~
X
.!3 E
n
W
a
I I
FZ T I X
SS
-
AFixss
\
01
17!j-OLS 150- oss 125100-
-
v
I I Fig. 4. Genetic analysis of the sleep-time response to chloral hydrate. The generations differ; F(5,53) = 8.70, p c 0.0001.A complex model which included the parameters in, [d], [h], [i] and [I] best fit the data (~‘(1) = 0.44; p > 0.50). Each bar or point represents the mean ~ S E Mfor nine to 12 animals. ” p < 0.01, *** p < 0.001, *’** p < 0.0001.
H
1.5
2.5
2.0
DOSE (mmol/kg)
I rn Is
3 vl
25 501 0
Fig. 5. Genetic analysis of the sleep-time response to barbital. The generations differ in response to this drug; F(5,70) = 4.92, p < 0.001, A simple additive model which included the parameters m and [d] best fit the data (~‘(4)= 3.79; p > 0.55). Each bar or point represents the mean +SEM for six to 18 animals. * p < 0.05, ** p < 0.01, *’** p c: 0.0001
ss
1 i,!
0 : .75 1.0 1.25 1.5
:
2.0
:
2.5
DOSE (mmol/kg)
The sleep-time responses to methyprylon are presented in Fig. 7. LS mice were more sensitive to the anesthetic properties of this drug than were SS mice, F( 1,36) = 15 1.7, p < 0.0001; however, this drug elicited a most unusual response in the SS mice. Long-lasting seizures, rather than a typical anesthetic response were observed. Animals that seized were given a zero sleep-time score. LS mice and mice of the other derived generations exhibited more classical anesthetic responses. However, several animals of the F2 and F1 x SS generations also failed to lose the righting response and exhibited seizures. While genetic models were not fitted to the seizure data, these findings suggest that the seizure response is a recessive trait. The inheritance of the anesthetic response is best described by an additive model with some epistasis. The genetic triangle reveals that the response of the F2 generation deviates the
most from the expectations of a simple additive model. Post hoc analysis supports this in that the F2 generation does not differ significantly from the SS line. The pattern for inheritance of sensitivity to pentobarbital is quite different from the inheritance seen for the other agents as can be seen in Fig. 8. ANOVA and the analysis of the dose-response curves revealed that LS and SS mice did not differ following administration of this compound, F( 451) = 0.69, p = 0.41 (see Table 3). While overall differences were found among the six generations (see figure legend for F value), post hoc analysis revealed significant differences only between the SS and F2 and the SS and Fl X SS generations. The means analysis reveals that a complex model including additivity and all three epistatic parameters best describe the data for this drug. The relationship between the genetic correlation to
517
RESPONSE TO SEDATIVE-HYPNOTIC DRUGS
\
h
'3c
S L .
150
150-
w 100 2]
100::
Y
oss
WF1 OF2 AFl X L S AF1 X SS
H
I
m
50
50-
0
0.
'MD Is
Fig. 6. Genetic analysis of the sleep-time response to paraidehyde. The six generations differ; F(5,75) = 14.35,~< 0.0001. An additive model which included the parameters m and [d] best fit the data (~'(4)= 6.19; p > 0.15). Each bar or point represents the mean ~ S E Mfor 10 to 18 animals. **** p < 0.0001.
5s
n
* :< 125
rn
0-
****
7.0
7.5
8.0
8.5
* * * y o
9.0
9.5
DOSE (mmol/kg)
METHYPRYLON n
'i150
WFl
3e
100
$
50
OF2
AFl X I3 AF1 X SS
v
I
Y VY
0
I3 F1 Fl FZ F1 SS X X Is 9s
5
50.25.-
/r
Fig. 7. Genetic analysis of the sleep-time response to methyprylon. The six generations differ in response to this agent; F(5,64) = 15.972, p < 0.0001. A model that included the parameters m, [d] and [j] best fit the data (~'(3)= 2.16; p > 0.50). Each bar or point represents the mean +SEM for 10 to 18 animals. " " p < 0.0001.
******** DOSE (mmol/kg)
ethanol response and the lipophilicity of the other agents is presented in Fig. 9 (methyprylon and trifluoroethanol are excluded). Genotypic correlation increases with decreasing lipid solubility ( Y = -0.97 f 0.03; p < 0.01). Similarly, the relationship of the LS-SS difference in sleeptime to the log of the octanol/water partition coefficient for ethanol and these same drugs are presented in Fig. 9. The LS-SS difference decreases in a linear fashion as lipid solubility increases (Y = -0.85 & 0.12; p < 0.05).
results obtained clearly demonstrate that the LS and SS mice differ most in sensitivity to drugs with limited lipid solubility and, as lipid solubility increases, the LS-SS differential decreases. As shown here and in the earlier s t ~ d ythe , ~ association between lipid solubility and the LSSS differential is true for alcohols, nonalcohols and barbiturates. In the earlier study, many values were estimated from dose-response curves with as few as three test doses. The dose-response curves constructed for the LS and SS lines in this study are better defined than those DISCUSSION in the previous study because more drug doses were emThe results presented here replicate our earlier report ployed; hence, the calculated EDhominvalues in this study that differences between the LS and SS mice in sensitivity are also better defined. The finding of a significant correto the anesthetic effects of various sedative-hypnotic agents lation between the LS-SS differential and log p is therefore are influenced by the lipid solubility of the drug.' The more reliable in the present study. Furthermore, the rep-
518
DE FIEBRE ET AL.
-
r
-c!-
'2 $jE
PENTOBARBITAL (log p=Z.03)
150
v
100
I
f$
3 v)
50 AFlXLS AF1 X SS
0 Is
ss
MD
+ IJL Fig. 8. Genetic analysis of the sleeptime response to pentobarbital. The six generations differ; F(5,73)= 3.07, p < 0.05. A complex model which included the parameters m, [d], [i], b] and [I]best fit the data (~'(1)= 0.001;p > 0.95). Each bar or point represents the mean +-SEM for 10 to 18 animals. ' p < 0.5.
DOSE (mmol/kg)
thermore, as noted previously, it seems likely that substantial inbreeding has occurred within these mouse lines." Thus, in this respect the major assumptions of Mendelian cross data may not have been violated. The segregation pattern of ethanol sensitivity yielded results that are best explained by an additive or additivedominance model with some epistasis (gene interaction). We suspect that a simple additive model best explains the regulation of ethanol sensitivity. This notion is consistent with the findings of Dudek and Abbott' and DeFries et r = -0.85 a]." It is probable that ceiling and floor effects in our data p ( 0.05 are responsible for the deviations seen from this model. Almost all of the LS mice given the 80 mmol/kg dose slept for the maximal 180 min. Therefore, the sleep-time 1.25response recorded for these mice probably represents an 1.00underestimate of the true sensitivity of these mice to ethanol. In contrast, virtually all of the SS and many of 0.0 0.5 1.0 1.5 2.0 the F1 x SS mice challenged with the 80 mmol/kg dose LOG P failed to lose the righting response. The recorded sleep Fig. 9. A relationship between lipid solubility (log p) and the genetic correlation times of zero overestimate the true sensitivity of these between responsiveness to sedative-hypnotic compounds and ethanol responsivemice. In fact, regression analysis of the LS-SS dose-reness. 8: relationship between lipid solubility (log p) and the ratio of SS to LS ED,. values for sleep-time. (E,ethanol; U, urethane: C, chloral hydrate; B, barbital; P. sponse curves reveals that while the LS estimate is close paraldehyde;PB, pentobarbital). to the true sensitivity of these mice, the SS score greatly lication of our earlier findings is particularly striking be- overestimates the sensitivity of these mice. It is because of these ceiling-floor problems that we did not calculate the cause only six drugs were utilized in the present study. Most classical cross analyses use inbred strains as the number of effective factors that influence ethanol sleep founding population. Since the study used here used se- time in this study. The segregation patterns for trifluoroethanol and methlectively bred mouse lines some caution should be taken yprylon were quite different from that of ethanol and were in interpreting the results. However, selection generally not included in the analyses presented in Fig. 9. Trifluoleads to homozygosity at those alleles that regulate the roethanol was not included because mice treated with the selected-for response. Therefore, the LS-SS mice should drug almost invariably died within 24 hr after drug treatbe homozygous for all of the genes that influence long and ment regardless of whether anesthesia was seen. This short sleep time, respectively. Consequently, in this repattern of lethality was not seen for any of the other drugs spect, the approach used here does not violate any major tested. The lethal effects may have arisen because trifluoassumptions used in analyzing Mendelian cross data. Fur-
RESPONSE TO SEDATIVE-HYPNOTIC DRUGS
roacetic acid, the probable major metabolite of trifluoroethanol, is highly toxic." It might be that differences seen among and within the generations in sleep-time response are confounded by differences in production of, or toxic response to, trifluoroacetic acid. Methyprylon was not included because the SS mice, and several of the F2 and Fl X SS animals, failed to lose the righting response and exhibited convulsions instead. This might be indicative that a convulsant metabolite is formed in some animals, but this is doubtful because animals exhibited convulsions very shortly after methyprylon administration. Nevertheless, the response of these animals to trifluoroethanol and methyprylon makes genetic modeling or other analyses of an anesthetic response questionable. Therefore, methyprylon and trifluoroethanol were not included in the analyses presented in the top half of Fig. 9, but removal of these drugs from the analyses does not affect the significance of the relationship between the genetic correlation to ethanol response and the log of the octanol/water partition coefficient ( r = -0.96 & 0.03; p < 0.001 with these drugs omitted and r = -0.97 +- 0.03, p < 0.00 1 with these drugs included). Only small LS-SS differences in sensitivity to chloral hydrate were detected and the segregation pattern did not fit a simple model. It has been argued that the depressant actions of chloral hydrate are due to its rapid conversion to the more lipid soluble t r i c h l o r ~ e t h a n o l (log ' ~ ~ ~p~= 0.85)." Recently, we presented evidence that chloral hyTherefore, the drate has anesthetic activity of its sleep-time response to chloral hydrate is probably mediated by both chloral hydrate and its active metabolite, trichloroethanol. If this is the case, the segregation analysis for chloral hydrate may be different from ethanol because of differences among the generations in rate of formation of trichloroethanol as well as differences in sensitivity to chloral hydrate and its major metabolite. In addition, the ratios and log p values (Fig. correlation between ED60min 9) may be confounded by an inaccurate estimate of the partition coefficient. The partition coefficient for the biologically active species in vivo is probably somewhere between the partition coefficients for chloral hydrate and trichloroethanol. Pentobarbital, the most lipid soluble drug tested, showed very small LS-SS differences and inheritance of response to this drug did not fit an additive model. Several studies have compared the relative responses of the LS and SS mice to p e n t ~ b a r b i t a l . ~ ?With ~ ' - ~ the ~ exception of the study of Alpern and McIntyre,*' all of these studies obtained results which agree with those obtained in the current study; i.e., depending on the pentobarbital dose, either no LS-SS difference was seen or the SS mice were slightly more responsive. Any differences in the responsiveness of LS and SS mice to pentobarbital, however, appear to be due pharmacokinetic factors and not to differences in CNS sensitivity.24s26 Several other genetic studies provide additional evi-
519
dence that genetic influences on ethanol- and pentobarbital-induced sleep-time are different. Two earlier studies examined the relative sensitivities of the LS and SS mice and derived generations to several sedative-hypnotic drug^.^^,^^ In both studies the inheritance pattern for pentobarbital sensitivity differed from the inheritance pattern for ethanol sensitivity. Recently, Allan and Harris3' examined the sleep-times of 93 heterogeneous stock (HS) mice following pentobarbital (50 mg/kg) and ethanol (3.5 g/kg). The correlation between pentobarbital- and ethanol-induced sleep-time was nonsignificant ( r = 0.09). The results of all of these studies may mean that ethanol and pentobarbital elicit their hypnotic effects via totally different mechanisms. Alternatively, it may be that no genetic variance exists for those sites that are affected by both drugs in the LS and SS lines or in the HS mice from which they were derived. A significant correlation between log p and genetic correlation was found in the analysis presented in the top half of Fig. 9, but examination of the figure reveals that the significance of the relationship is primarily due to the lack of a genetic correlation between pentobarbital and ethanol. Significant genetic correlations were found between ethanol and all of the other agents tested except for pentobarbital, the most lipid soluble agent tested. While not shown in the analysis in Fig. 9, a genetic correlation for methyprylon, the next most lipid soluble agent, and alcohol was calculated. This was also not significant. In the present study, no drugs with lipid solubilities between those of methyprylon (log p = 0.77) and pentobarbital (log p = 2.03) were tested. While little is known about the molecular mechanisms of action of anesthetic drugs such as urethane, chloral hydrate and paraldehyde, considerable progress has been made in recent years in understanding the mechanisms of action of the barbiturates. A major site of action for the barbiturates appears to be associated with the GABAbenzodiazepine receptor. There are differences, however, among the barbiturates in their actions at this receptor complex. Leeb-Lundberg and Olsen" have observed that lipid soluble barbiturates are much more potent in increasing the affinity of [3H]-diazepamfor its binding site on rat cortical membranes than are water soluble barbiturates. The results reported here are consistent with this finding in that the inheritance pattern for the relatively lipid insoluble barbital was markedly different from the inheritance pattern obtained with pentobarbital. It may be that a comparison of the effects of water and lipid soluble barbiturates on properties of the GABA receptor will provide much needed insight into a major mechanism of action of ethanol. Mendelian or classical crosses have been used only rarely to assess genetic associations between drug responses and the results of such an analysis must not be interpreted too broadly. The observation that the segregation patterns for two traits are similar does not necessarily mean that
520
the genes which regulate these two traits are identical. Rather, this result might only mean that similar models explain each segregation pattern. For example, LS mice frequently have a peach coat color and SS are frequently albino but if coat color segregated into the various generations along with ethanol sensitivity this would not necessarily mean that “coat color genes” are also alcohol genes. However, if the segregation patterns for two traits are clearly different, the argument can be made that it is not likely that the two traits that are associated in the parental strains are regulated by precisely the same gene or set of genes. Thus, the results reported here do not prove that the same genes regulate ethanol and barbital or other water soluble drug sleep-time responses, but these results clearly argue that different genes regulate the hypnotic responses to ethanol and pentobarbital. As with all correlational analyses, the reliability of a correlation increases with the number of observations, but it is best to remember that correlation does not necessarily mean causation. Nonetheless, the observation that sensitivity to the anesthetic actions of all of the water soluble drugs is genetically correlated with sensitivity to the anesthetic actions of ethanol argues that the LS-SS differences in sensitivity to the anesthetic actions of water soluble drugs does not occur by chance. The intent of a classical cross analysis is to break down linkage, and if two traits show differing patterns of inheritance, an argument can be made for differential genetic regulation. Thus, because the apparent association between ethanol and water soluble anesthetic drug response was not broken down, it seems possible that the anesthetic responses to ethanol and these other water soluble drugs are regulated by some of the same genes. However, more stringent tests must be done to assess whether common genes regulate traits which show similar inheritance patterns. One strategy is to measure the correlation between two traits in a segregating population such as an F2 generation or a heterogeneous stock, but this method may provide erroneous information if measuring the first trait affects the second. This, we believe, is a significant concern when measuring drug-induced anesthesia because many animals exhibit symptoms of toxicity after testing. Therefore, the method of choice is to use animals with identical genotype where each animal is tested only once. Recombinant inbred strains, which are derived by inbreeding the F2 generation derived from crossing two parental strains, are especially valuable in testing genetic associations because the procedure used in developing recombinant inbreds breaks down linkage and then fixes genes in new configurations. The accompanying paper32used recombinant inbred strains derived from the LS and SS mice to test whether the anesthetic responses to drugs with low lipid solubility are regulated by the same genes. The results obtained are in agreement with the results reported in Fig. 9 in this paper: there is a significant negative correlation between lipid solubility and the degree of genetic com-
DE FIEBRE ET AL.
monality. In other words, more genes are shared in common that regulate the sleep-time response for water soluble drugs than for lipid soluble drugs. As noted above, recombinant inbred strains may be the best tool available to test genetic hypotheses concerning ethanol and other drug actions, but recombinant inbred strains, although very valuable, are often not available. Consequently, their utility is often limited. However, the genetics of alcohol literature is rich with studies that have utilized only two strains or lines of animals and attempted to correlate biochemical differences with genetically influenced behavioral differences. The interpretation of such studies is severely limited by a lack of degrees of freedom. This is especially the case if the parental line difference is one which was developed using a selective breeding program that did not include replicate lines as is the case with the LS-SS selection. The results reported here suggest that the classical cross may be of value in testing genetic hypotheses. While this method increases available degrees of freedom, we must emphasize that the results obtained should not be interpreted too broadly. In summary, the segregation patterns for all of the drugs tested were not identical, but the similarity was greater for those compounds with similar lipid solubilities. One possible explanation for these findings is that the overlap with ethanol in terms of sites or mechanisms of action decreases as lipid solubility increases. The finding that ethanol’s anesthetic actions are regulated by seven to eight “effective factor^"^*'^ might mean that ethanol exerts its effects by altering the activities of seven to eight gene products. If each of these gene products is equieffective in regulating sleep-time, researchers are faced with the difficult task of attempting to explain only a small fraction of the response on the basis of actions on a specific gene product. It may be that greater progress could be made if future studies include analyses of the actions of drugs that showed differential segregation patterns in the study reported here. ACKNOWLEDGMENTS The authors would like to thank Dr. John DeFries for his helpful advice on the analysis of these data and Ms. Alyssa Gonzales for assistance in preparation of the manuscript.
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RESPONSE TO SEDATIVE-HYPNOTIC DRUGS
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