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NEUROPHARMACOLOGY

The Heritability of Antinociception: Common Pharmacogenetic Mediation of Five Neurochemically Distinct Analgesics

Department of Psychology and Program in Neuroscience, University of Illinois at Urbana-Champaign, Champaign, Illinois (S.G.W., E.J.C., K.A.M., J.J.H., B.M., L.H., J.S.M.); Department of Psychology, McGill University, Montreal, Quebec, Canada (S.B.S., K.S., J.S.M.); and Department of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, Illinois (S.L.R.-Z.)

Received July 17, 2002; accepted October 7, 2002.

	Abstract

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The heritability of nociception and antinociception has been well established in the mouse. The pharmacogenetics of morphine analgesia are fairly well characterized, but far less is known about other analgesics. The purpose of this work was to begin the systematic genetic study of non-µ-opioid analgesics. We tested mice of 12 inbred mouse strains for baseline nociceptive sensitivity (49°C tail-withdrawal assay) and subsequent antinociceptive sensitivity to systemic administration of (trans)-3,4-dichloro-N-methyl-N-[2-(1-pyrrolidinyl)-cyclohexyl]benzeneacetamide methane-sulfonate hydrate (U50,488; 10–150 mg/kg), a -opioid receptor agonist; (R)-(+)-[2,3-dihydro-5-methyl-3-(4-morpholinylmethyl)pyrrolo[1,2,3-de]-1,4-benzoxazin-6-yl]-1-naphthalenylmethanone (WIN55,212-2; 0.5–480 mg/kg), a synthetic cannabinoid receptor agonist; epibatidine (7.5–150 µg/kg), a nicotinic receptor agonist; clonidine (0.1–5 mg/kg), an ₂-adrenergic receptor agonist; and, for purposes of comparison, the prototypic µ-opioid receptor agonist, morphine (5–200 mg/kg). Robust interstrain variability was observed in nociceptive sensitivity and in the antinociceptive effects of each of the drugs, with extreme-responding strains exhibiting antinociceptive potencies differing up to 37-fold. Unexpectedly, we observed moderate-to-high genetic correlations of strain sensitivities to the five drugs (r = 0.39–0.77). We also found moderate-to-high correlations between baseline nociceptive sensitivity and subsequent analgesic response to each drug (r = 0.33–0.68). The generalizability of these findings was established in follow-up experiments investigating morphine and clonidine inhibition of formalin test nociception. Despite the fact that each drug activates a unique receptor, our results suggest that the potency of each drug is affected by a common set of genes. However, the genes in question may affect antinociception indirectly, via a primary action on baseline nociceptive sensitivity.

Even though morphine and other µ-opioid agonists remain the most common drug therapies for moderate-to-severe pain, morphine has well known side effects and can be insufficiently efficacious at well tolerated doses (Jaffe and Martin, 1990). This has encouraged the use of alternatives or adjuncts such as -opioid (see Millan, 1990) and -adrenergic agonists (see MacPherson, 2000), and the development of novel analgesic classes such as cannabinoid (see Martin and Lichtman, 1998) and nicotinic receptor agonists (see Flores and Hargreaves, 1999). All of these drugs are thought to inhibit pain by activating descending pain-modulatory pathways, but the extent to which their underlying circuitries are distinct from morphine is unclear. An appreciation of whether common or distinct genetic factors contribute to the variable efficacy of alternative analgesics may improve our understanding of analgesic physiology and may facilitate the development of individualized pain therapies.

Genetic correlation analysis can be used to assess whether two or more traits have common genetic determination (see Crabbe et al., 1990), even prior to the identification of the relevant genes. Because the genetic correlation of two traits demonstrates the existence of common genes affecting both traits, common biochemical and/or neuronal mediation is implied. Inbred mouse strains, which are homozygous at virtually all genetic loci, are well suited for assessing genetic correlation among traits (see Mogil, 2000 for a detailed explanation). We previously studied genetic correlations among multiple assays of nociception in the mouse, providing evidence for the existence of major "types" of pain (thermal, chemical, mechanical allodynia, thermal hyperalgesia, and afferent-dependent thermal hyperalgesia) as defined by genetic codetermination (Mogil et al., 1999a,b; Lariviere et al., 2002).

Our aim presently is to investigate sensitivity to inhibition of nociception produced by multiple analgesic compounds in a common set of inbred mouse strains. These data can be used to establish heritability, identify extreme-responding strains for use in QTL mapping efforts, and to assess genetic correlations among the drugs and with basal nociceptive sensitivity. To these ends, we determined full dose-response relationships in 12 inbred mouse strains to systemic injection of five different analgesic compounds active on the 49°C tail-withdrawal test: 1) morphine; 2) the -opioid receptor agonist, U-50,488; 3) the cannabinoid CB-1 receptor agonist, WIN 55,212-2; 4) the neuronal nicotinic receptor agonist, epibatidine; and, 5) the ₂-adrenergic receptor agonist, clonidine. Based on the previous demonstration of strain differences by ourselves and others (Kunos et al., 1987; Pick et al., 1991; Onaivi et al., 1996; Flores et al., 1999; Wilson et al., 1999; Barrett et al., 2002), it was anticipated that sensitivity to each of these drugs would be heritable. Because each drug binds to and activates unique receptors, one might postulate that different genes would mediate variability in responses to each one. That is, the default assumption (a null hypothesis of zero genetic correlation) would be that variability is produced by alternate forms or expression levels of the specific receptor protein in each case. However, all these drugs are known to interact with descending pain-modulatory neuronal circuitry, and thus genes with common effects on several of the drugs may exist. Genetic correlation among antinociceptive responses to these disparate compounds would imply the existence of such genes.

Whereas the thermal nociceptive assay employed here has been shown to predict clinical efficacy of opiate analgesics, clinical pain is long-lasting, and typically inflammatory or neuropathic in nature. Thus, to establish the generalizability of findings to a nociceptive assay with greater clinical relevance, a smaller follow-up study was also conducted, involving single-dose administration of morphine and clonidine to a subset of strains on the formalin test of tonic chemical/inflammatory nociception.

	Materials and Methods

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Subjects. Male and female mice of the outbred strain, CD-1 (Hsd:ICR), were obtained from Harlan (Indianapolis, IN). Male and female mice of the following 12 inbred strains, 129P3, A, AKR, BALB/c, C3H/He, C57BL/6, C57BL/10, C58, CBA, DBA/2, RIIIS, and SM (all "J" substrains), were obtained from The Jackson Laboratory (Bar Harbor, ME). Mice were bred in our temperature-controlled (22 ± 2°C) vivarium on a 12-h light/dark cycle (lights on at 7:00 AM). Mice were weaned at 18 to 21 days of age, housed with same-sex littermates in groups of two to five, and given ad libitum access to food (Harlan Teklad 8604) and tap water. All mice (n = 6–30/strain/dose/drug) were naive when tested, at not less than 6 weeks of age. An approximately equal number of male and female mice were tested in each condition.

Nociceptive Testing. The 49°C tail-withdrawal/immersion test, originally described by Ben-Bassat et al. (1959) and modified by Janssen et al. (1963), was used to measure reflexive responses to thermal nociception. A spinal reflex was preferable in this case to other nociceptive assays because antinociceptive doses of opioid, cannabinoid, and nicotinic drugs may produce motoric impairments that are likely to confound assessment of antinociception in assays requiring a coordinated behavioral response. During testing, mice were gently restrained in a cardboard-bottomed cloth holder, and the distal half of the tail was immersed in water maintained at 49 ± 0.2°C by a thermal circulator. The latency to a reflexive withdrawal response was measured to the nearest 0.1 s by an experienced observer. For increased accuracy, two latency determinations separated by at least 10 s were made and averaged together at each time point. A 15-s cut-off was imposed to prevent any possible tissue damage and to decrease the possibility of repeated-measures effects.

In a separate experiment, the formalin test (Dubuisson and Dennis, 1977) was used. Mice were injected subcutaneously into the plantar surface of the right hindpaw, with 20 µl of 5% formalin, using a 25 µl Hamilton microsyringe attached to a 30-gauge needle. Mice were immediately returned to their Plexiglas observation chamber (12 x 12 cm; 20 cm high), and the presence/absence of licking or biting of the affected hindpaw was sampled for 5 consecutive seconds of each minute for the next 40 min. As described by Saddi and Abbott (2000), and confirmed by our own pilot studies (data not shown), a sampling strategy yields highly accurate data in this assay, especially in the late/tonic phase. The early/acute and late/tonic phases were defined as 0 to 5 min and 5 to 40 min postinjection, respectively.

Although only one stimulus intensity was used in these experiments (49°C water and 20 µl of 5% formalin), it has been previously demonstrated using similar assays that the relative nociceptive and morphine antinociceptive sensitivities of inbred mouse strains are preserved with changes in stimulus intensity (Elmer et al., 1997).

Drugs. Dose-response relationships were in all cases collected using a between-subjects design, not cumulative dosing. The µ-opioid receptor agonist, morphine sulfate (National Institute for Drug Abuse, Rockville, MD), was dissolved in saline and administered in doses ranging from 5 to 200 mg/kg. The selective -opioid receptor agonist, (±)-trans-U50,488 methanesulfonate (Tocris Inc., Ballwin, MO), was dissolved in saline and administered in doses ranging from 10 to 150 mg/kg. The high affinity cannabinoid CB-1 receptor agonist, R(+)-WIN 55,212-2 mesylate (Tocris), was dissolved in a 50% propylene glycol/saline solution and administered in doses ranging from 0.5 to 480 mg/kg. In pilot studies, even 100% propylene glycol had no discernible antinociceptive properties in the 49°C tail-withdrawal test. The nicotinic acetylcholine receptor agonist, (±)-epibatidine dihydrochloride (Sigma-Aldrich, St. Louis, MO), was dissolved in saline and administered in doses ranging from 7.5 to 150 µg/kg. The selective ₂-adrenergic receptor agonist, clonidine (Sigma-Aldrich), was dissolved in saline and administered in doses ranging from 0.1 to 5 mg/kg. The starting dose for all strains was based on pilot data obtained in CD-1 mice (data not shown). Final dose ranges of all drugs were determined as the experiments progressed, in an attempt to gather data encompassing the entire linear phase of the dose-response curve for each strain and drug. Successively higher and lower doses were tested in each strain until the following criteria were fulfilled: a) data from at least three doses per strain were obtained; b) the lowest dose yielded maximum percentage of antinociception (see below) of 35%; and, c) the highest dose yielded maximum percentage of antinociception of 65%. All drugs were administered i.p. in a volume of 10 ml/kg.

In the formalin test experiment, 5 mg/kg morphine and 0.025 mg/kg clonidine were used. These doses were based on pilot data from CD-1 mice.

Experimental Protocol. Nociceptive testing occurred immediately before, and 15, 30, and 60 min postinjection for all drugs except for the shorter-acting epibatidine, which occurred immediately before and 10, 20, and 30 min postinjection.

In the formalin test experiment, 6 of the 12 strains were used, representing a range of basal sensitivities to formalin based on previous data (Mogil et al., 1999a), as were outbred CD-1 mice (as no attempt to estimate heritability was made in this limited experiment). Because the formalin test should only be applied once to an individual mouse, separate groups of saline- and drug-pretreated subjects were tested. Mice were habituated to individual Plexiglas observation chambers for 30 min, given a systemic injection of saline or drug (5 mg/kg morphine or 0.025 mg/kg clonidine), and returned to their chambers. Twenty minutes later, every mouse received an intraplantar injection of 5% formalin and was then sampled for formalin-induced licking behavior as described above. Immediately after the cessation of testing, mice were sacrificed and both hindpaws were severed at the ankle and weighed as previously described (Mogil et al., 1998). The difference in weight between injected and noninjected hindpaws was used as a measure of inflammation. Data from eight mice were discarded based on low inflammation values (i.e., inadequate formalin injection).

Data Analysis. Percentage of antinociception (i.e., percentage of the maximum possible effect) at each time point was calculated for individual mice as: [(postdrug latency – baseline latency)/(cut-off latency – baseline latency)] x 100. The maximal percentage of antinociception at any time point was used as the dependent measure of drug response (see below). We have observed that none of the 12 strains tested here displays significant changes in nociceptive sensitivity after saline injection using a 49°C stimulus (S. G. Wilson and J. S. Mogil, unpublished data). Strain differences were initially assessed using analysis of covariance (SYSTAT v.10.0; Systat Software Inc., Richmond, CA) with dose entered as a covariate when using antinociception as the dependent measure. Dose-response curves, comprised of three to four doses of each drug within the linear portion of the dose-response relationship for each strain (see above), were used to calculate half-maximal antinociceptive dose (AD₅₀) (Tallarida and Murray, 1981).

Because strain-dependent antinociception may be manifested as differences in duration and/or peak response magnitude (see, e.g., Flores et al., 1999), we also calculated total antinociception (using areas under the curve) over the entire testing period. Indeed, strain differences in antinociceptive duration were noted (data not shown). AD₅₀s were less precise for total antinociception, however. Because the genetic correlations among traits were essentially equivalent using either measure, for simplicity we present only peak antinociception data.

In the formalin test experiment, formalin responding was quantified as the percentage of samples in each phase (early/acute, 0–5 min; late/tonic, 5–40 min) in which the mouse exhibited licking behavior. Drug antinociception at the single dose used was quantified as percentage of antinociception in each phase with respect to the mean values of the saline-treated animals of their strain.

Inbred strains are virtually genetically identical within strain, and thus narrow-sense heritability (h²) can be estimated from the between-strain (i.e., additive) genetic variation (V_a) and the within-strain (error) variation (V_e) using the formula: h² = V_a/(V_a+ V_e) (Falconer and Mackay, 1996), which is based on the population intraclass correlation coefficient. Sample variance components were estimated by equating the mean squares from an analysis of variance fitting the effects of strain and dose to the expected mean squares; this method is most appropriate for the small sample sizes used and potential violations of normality (Lynch and Walsh, 1998). Because the sample size per strain and dose varied in our data set, we used an approximation for the standard error of h² (Swiger et al., 1964).

Genetic correlations among traits (baseline latency and drug AD₅₀s) were assessed using correlation coefficients applied to inbred strain means. Because the joint distribution of the traits was not always normal, and we were interested in any common relationship between dependent measures and not necessarily the linear relationship, we chose to employ Spearman's correlation (r_s) for rank data in all cases. However, Pearson's correlations yielded very similar results (not shown). The criterion level of significance in all experiments was chosen as = 0.05.

	Results

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Strain Differences in Baseline Sensitivity and Heritability Estimates. Collapsing across drug, we observed a main effect of strain (F_11,1548 = 30.1, p < 0.001) on baseline nociceptive sensitivity to the 49°C tail-withdrawal test. Strain sensitivities were highly correlated with those previously reported (r_s = 0.89, p < 0.005) (Mogil et al., 1999a). The heritability of baseline nociceptive sensitivity to the 49°C tail-withdrawal test was estimated as h² = 0.26 ± 0.08.

Strain Differences in Antinociceptive Sensitivity and Heritability Estimates. Significant main effects of mouse strain were obtained for every analgesic (p < 0.001 in all cases). Dose-response curves for peak antinociceptive sensitivity to morphine, U50,488, WIN55,212-2, epibatidine, and clonidine for each strain are shown in Figs. 1 2 3 4 5. At the peak time point, robust (65%) antinociception was achieved at the highest dose tested in every case but two: AKR and CBA mice were found to be particularly insensitive to the antinociceptive effects of epibatidine, and the highest dose shown in each case was associated with lethality in these strains (see Fig. 4). AD₅₀s with associated 95% confidence intervals are shown in Table 1. No strain was the most or least sensitive to all drugs, although more general patterns of sensitivity can be evinced (see below). Heritability estimates of peak nociceptive sensitivity for each drug ranged from h² = 0.12 (U50,488) to 0.42 (clonidine) (see Table 1). Heritability estimates based on total antinociception over the entire testing period overlapped those for peak antinociceptive sensitivity for all drugs except U50,488, for which an estimate of h² = 0.21 was obtained for the former measure, suggesting the existence of additional genetic factors for that drug of specific relevance to duration of antinociception.

View larger version (34K): [in this window] [in a new window]   Fig. 1. Dose-response curves of antinociceptive sensitivity of 12 inbred mouse strains to morphine sulfate, defined as the maximum percentage of antinociception relative to baseline nociceptive sensitivity at any time point (see the text). Symbols represent the mean ± S.E.M. of six or more mice.

View larger version (36K): [in this window] [in a new window]   Fig. 2. Dose-response curves of antinociceptive sensitivity of 12 inbred mouse strains to U50,488, defined as the maximum percentage of antinociception relative to baseline nociceptive sensitivity at any time point (see the text). Symbols represent the mean ± S.E.M. of six or more mice.

View larger version (35K): [in this window] [in a new window]   Fig. 3. Dose-response curves of antinociceptive sensitivity of 12 inbred mouse strains to WIN55,212-2, defined as the maximum percentage of antinociception relative to baseline nociceptive sensitivity at any time point (see the text). Symbols represent the mean ± S.E.M. of six or more mice.

View larger version (34K): [in this window] [in a new window]   Fig. 4. Dose-response curves of antinociceptive sensitivity of 12 inbred mouse strains to epibatidine, defined as the maximum percentage of antinociception relative to baseline nociceptive sensitivity at any time point (see the text). Symbols represent the mean ± S.E.M. of six or more mice. , dose associated with significant lethality in that strain, precluding the use of higher doses.

View larger version (35K): [in this window] [in a new window]   Fig. 5. Dose-response curves of antinociceptive sensitivity of 12 inbred mouse strains to clonidine, defined as the maximum percentage of antinociception relative to baseline nociceptive sensitivity at any time point (see the text). Symbols represent the mean ± S.E.M. of six or more mice.

Sex Differences. For baseline nociception, we found a significant main effect of sex (F_1,1536 = 9.0, p < 0.005; male: 2.84 ± 0.04 s; female: 2.68 ± 0.04 s) but no significant sex by strain interaction (F_11,1536 = 1.1, p = 0.33). Sex-specific heritability in both males and females was h² = 0.26.

For antinociception, we observed a significant main effect of sex only for clonidine (F_1,199 = 17.4, p < 0.001). The sex by strain interaction was significant for morphine, WIN55,212-2, and epibatidine (p < 0.01, p < 0.05, and p < 0.05, respectively). Because sample sizes were too low to properly assess the presence of sex differences in individual cases, sex-specific AD₅₀s are not shown. However, they were calculated, and males were more sensitive to drug-induced antinociception than females in 9 of the 13 instances where AD₅₀s appeared to differ. Such a finding would be broadly in line with the existing rodent literature, in which males generally (but not exclusively, depending on strain) display increased antinociception relative to females where differences exist (Kest et al., 1999; Mogil et al., 2000; Barrett et al., 2002; see Craft, 2002). Heritability estimates calculated from sex-specific data subsets were similar for morphine, epibatidine, and clonidine. U50,488 antinociception appeared more highly heritable in females (h² = 0.22 versus 0.09, respectively), whereas WIN55,212-2 antinociception was more highly heritable in males (h² = 0.44 versus 0.24). It should be noted finally that the genetic correlations described below were very similar, regardless of whether male-only, female-only, or combined data were considered.

Genetic Correlations. Correlations between ranked strain sensitivities (i.e., AD₅₀s) to morphine, U50,488, WIN55,212-2, epibatidine, and clonidine are shown in Fig. 6. Because we were unable to obtain full, linear dose-response curves in AKR and CBA mice given epibatidine due to lethality at the highest doses tested (see above), correlations involving epibatidine were based on values from the remaining 10 strains only. Of the 10 possible correlations among five analgesics, 9 were significant at the = 0.05 level before correction for multiple comparisons, 7 were significant after 5% false discovery rate control (Benjamini and Hochberg, 1995), and none remained significant after Bonferroni correction. Figure 7 illustrates correlations between baseline nociceptive sensitivity and antinociception from each of the five drugs. Of the five correlations, three were significant before correction, two after false discovery rate control, and none after Bonferroni correction. We note that since the main purpose of this work is to generate hypotheses, the significance of individual correlations is not an overriding concern here.

View larger version (28K): [in this window] [in a new window]   Fig. 6. Genetic correlations (rs) between half-maximal antinociceptive dose (AD50) estimates of morphine, U50,488, WIN55,212-2, epibatidine, and clonidine among 12 inbred strains (10 inbred strains for epibatidine). Each symbol represents one inbred strain, ranked by their AD50s (low AD50s, indicative of high sensitivity, to the left).

View larger version (12K): [in this window] [in a new window]   Fig. 7. Negative genetic correlations (rs) between half-maximal antinociceptive dose (AD50) estimates to five analgesics and baseline nociceptive sensitivity of 12 inbred strains on the 49°C tail-withdrawal nociceptive assay. Each symbol represents one inbred strain, ranked by their mean baseline latencies on the x-axis [low latencies (i.e., high sensitivity to nociception) to the left] and their AD50sonthe y-axis [low AD50s (i.e., high sensitivity to antinociception) at the bottom].

Formalin Test Experiment. There were no significant strain differences in formalin-induced inflammation as indexed by difference in hindpaw weight. Morphine displayed anti-inflammatory actions (p < 0.001), but clonidine did not. Although strain differences in the anti-inflammatory actions of morphine were seen (p < 0.005), there was no significant correlation between those actions and morphine antinociception (r_s =–0.20).

Responses of saline-treated mice were significantly strain-dependent in the early/acute (F_7,86 = 3.2, p < 0.005) and late/tonic phase (F_7,86 = 6.7, p < 0.001), and highly correlated (early/acute: r_s = 0.60; late/tonic: r_s = 0.94) with previously collected data in which mice were tested without saline pretreatment (Mogil et al., 1999a). The high correlation, approaching unity in the late/tonic phase, speaks both to the reliability of inbred strain differences on the formalin test and the accuracy of the sampling approach. The correlation of formalin test sensitivity and tail-withdrawal test sensitivity in the six common strains in the present experiment was found to be r_s = 0.77. Such a high correlation was unexpected based on our previous findings of considerable genetic independence of these assays (r_s = 0.26; Mogil et al., 1999b), but the previous findings were based on a comparison of 11 strains.

Morphine antinociception was significantly strain-dependent in both phases (early/acute: F_6,55 = 5.5, p < 0.001; late/tonic: F_6,55 = 5.8, p < 0.001). Clonidine only produced significant antinociception of late-phase responding, and this antinociception was also strain-dependent (F_6,71 = 2.3, p < 0.05). For the sake of comparison among the drugs, and because the purpose of this experiment was to establish greater clinical relevance, we hereinafter report only late/tonic phase data, which are most reflective of clinical pain. As shown in Fig. 8, saline-treated formalin sensitivity in the late phase was highly correlated with morphine antinociception (r_s =–0.79, p < 0.05) and clonidine antinociception (r_s = –0.86, p < 0.05). Thus, in the formalin test too, strains more sensitive to the nociceptive stimulus are simultaneously less sensitive to inhibition of that stimulus by analgesic drugs. Furthermore, morphine antinociception and clonidine antinociception on the formalin test were significantly correlated (r_s = 0.71, p = 0.05).

View larger version (27K): [in this window] [in a new window]   Fig. 8. Genetic correlations (rs) between sensitivity to late/tonic phase formalin-induced licking (in saline-treated mice) and morphine antinociception (5 mg/kg; in a) or clonidine antinociception (0.025 mg/kg; in b) in seven mouse strains. In c, the genetic correlation between morphine and clonidine antinociception on the formalin test is shown. Each symbol represents one strain, ranked by their mean late/tonic phase licking behavior or their mean single-dose antinociception scores (see the text).

	Discussion

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Strain Dependence of Nociception and Antinociception. In agreement with much previous data, baseline nociceptive sensitivity to both thermal and chemical/inflammatory stimuli, and drug inhibition of these stimuli, were found to be strain-dependent in the mouse. That morphine antinociception varies with mouse genotype has been reported many times (see Mogil et al., 1996b; Mogil, 1999). Genotypic dependence of -opioid antinociception has also been shown on several occasions (e.g., Pick et al., 1991; Barrett et al., 2002).

By comparison, much less is known about the genetics underlying antinociceptive sensitivity to other drug classes. Onaivi et al. (1996) reported strain-dependent antinociception from the prototypic cannabinoid, ⁹-tetrahydrocannabinol, in three mouse strains, and Seale et al. (1996) observed large strain differences in nicotine antinociception between two outbred mouse stocks. Our laboratory has previously reported that cannabinoid- and epibatidine-induced antinociception are genotype-dependent based on single-dose strain surveys (Flores et al., 1999; Wilson et al., 1999). To our knowledge, mouse strains have not been examined for differential antinociceptive sensitivity to clonidine, although differences among rat strains have been observed for clonidine inhibition of formalin nociception (Kunos et al., 1987) and mechanical allodynia (Lee et al., 1997).

The present study is novel in its concurrent evaluation of multiple strains and multiple drugs, allowing for the systematic evaluation of the genetic basis of drug antinociception as a class of related traits. Furthermore, as full dose-response information is compiled, we expect that these data may become a valuable resource for the design of future experiments and the interpretation of transgenic studies, given that the antinociception-resistant C57BL/6 strain is the default genetic background on which null mutations are constructed (see Lariviere et al., 2001).

Genetic Correlations among Analgesics. The surprisingly high genetic correlation of mouse strain sensitivity to morphine, U50,488, WIN55,212-2, epibatidine, and clonidine provides evidence for the existence of common genes responsible for variability in antinociceptive magnitude. In turn, this genetic commonality implies at least partial commonality of the physiological mediation of these traits. The correlation between morphine and clonidine was also seen on the formalin test, suggesting that this phenomenon is more than an idiosyncrasy of the tail-withdrawal assay. This finding strongly suggests that the gene(s) responsible for variability in analgesic drug response are not those coding for the receptor being bound by that drug, in which case five different proteins (and thus five different genes) would be implicated. We believe that these data therefore argue against a common assumption of pharmacogenetics researchers that pharmaco-dynamic variability will be explained primarily by polymorphisms in or near the gene coding for the drug's molecular binding site. Given that these five drugs are also biotransformed and degraded by largely separate enzymatic pathways, it is not at all clear how a pharmacokinetic explanation could account for the genetic correlation.

To our knowledge, only three studies have ever attempted to address the issue of genetic commonality or dissociation among multiple analgesics. In one study by Belknap et al. (1987), mice selectively bred for high and low levorphanol (a µ-opioid agonist) inhibition of thermal nociception were found to similarly diverge in their antinociceptive responses to morphine, the -opioid U50,488, the mixed-action opioids ethylketazocine and pentazocine, and clonidine. However, the magnitude of the divergence was greatly reduced in the case of clonidine and the -opioid drugs, leading to the conclusion that sensitivity to these analgesics was mediated largely independently from that of levorphanol and morphine. Note, though, that the opposite conclusion (i.e., genetic commonality) is also clearly supported by these data. In an analogous selective breeding project, this time for swim stress-induced antinociception, we found that selection also affected morphine, levorphanol, and U50,488 antinociception, and argued for genetic commonality (Marek et al., 1993; Mogil et al., 1995). Finally, an independence of the genetic mediation of µ-and -opioid antinociception was postulated by Pick et al. (1991), based on a comparison of dose-response curves for morphine and U50,488 in three strains (outbred CD-1, outbred Swiss-Webster, and inbred BALB/c). None of these findings can be addressed specifically, since different genotypes were compared relative to the present work.

"Master" Antinociception Genes? The clear prediction of the present finding, genetic correlation of sensitivity to disparate analgesics, is that a "master" gene or set of genes may exist, contributing to variable responses to all of them. We are currently applying QTL mapping to these antinociception traits, to identify common gene loci. In the meantime, one way to determine what that gene or genes might be is to consider commonalities in the known mechanisms of action—neuroanatomical and biochemical—of these drugs.

For instance, it is possible that the relevant gene products are located in a central nervous system location downstream of the binding site of each drug, where mechanisms of pain inhibition have converged. Indeed, each of these drugs is known to produce antinociception at least partially by activating classic descending pain-inhibitory circuitry that modulates the processing of nociceptive information at the spinal level (see Basbaum and Fields, 1984). It is also the case that each of these drug classes can produce analgesia when administered intrathecally (see Yaksh, 1999), suggesting that the convergence point could be in the spinal cord.

One of our goals was to compare analgesics that acted via opioid or nonopioid mechanisms. Therefore, we chose two opioid receptor agonists and agonists of three other nonopioid receptor types. A large literature dissociates µ-opioid from -opioid antinociception, and although high doses of naloxone or naltrexone will block U50,488 antinociception as well as morphine antinociception, the molecular binding sites for these drugs have been clearly established in both pharmacological and transgenic experiments as the µ and receptor, respectively (see Pasternak, 1993; Kieffer, 1999). That does not, however, rule out the possible involvement of, say, µ-opioid receptors downstream of the receptor binding site in the mediation of U50,488 antinociception. Indeed, it has been recently shown that administration of -funaltrexamine, a µ-selective antagonist, can shift the U50,488 dose-response curve 5-fold to the right in rats (Craft et al., 2001).

In fact, even the nonopioid analgesics may be at least partially dependent on opioid mechanisms. A large literature describes synergistic interactions between clonidine and morphine (e.g., Wilcox et al., 1987). Considerable confusion still surrounds the question of whether systemic clonidine antinociception in rodents requires opioid receptor activation, since some studies show naloxone or naltrexone antagonism of the effect or morphine/clonidine cross-tolerance (e.g., Tchakarov et al., 1985; Sierralta et al., 1996; Tejwani and Rattan, 2000) and some do not (e.g., Spaulding et al., 1979; Yamazaki and Kaneto, 1985). Where shown, the naloxone sensitivity of clonidine antinociception was found to be test-dependent (Tejwani and Rattan, 2000), dose-dependent (Sierralta et al., 1996), or strain-dependent (Tchakarov et al., 1985).

The complex interactions between morphine and cannabinoids have been noted for almost three decades (Fernandes and Hill, 1974). Although naloxone and naltrexone are generally without effect on cannabinoids, the work of Welch and colleagues has established a clear dependence of ⁹-tetrahydrocannabinol on dynorphin activation of -opioid receptors (also see Reche et al., 1996; e.g., Mason et al., 1999). However, this cannabinoid/-opioid relationship may be specific to ⁹-tetrahydrocannabinol, since the -selective antagonist nor-binaltorphimine is without effect on two other CB-1 receptor agonists, CP55,940 and anandamide (e.g., Mason et al., 1999). Because the naloxone/naltrexone and nor-binaltorphimine sensitivity of WIN55,212-2 antinociception has never been evaluated directly, it is premature to speculate on possible opioid-mediated effects of this analgesic.

A similar story emerges for nicotinic analgesics. Synergistic relationships appear to exist between nicotine and morphine antinociception (Davenport et al., 1990; Suh et al., 1996; Zarrindast et al., 1996), including some reports of naloxone antagonism of nicotine antinociception (Molinero and Del Rio, 1987; Aceto et al., 1993). However, epibatidine antinociception is unanimously reported as naloxone/naltrexone-insensitive (Damaj et al., 1994, unpublished observations; Bonhaus et al., 1995; Khan et al., 1998), as is antinociception from the potent nicotinic agonist, ABT-594 (Decker et al., 1998).

Finally, it is also possible that the "master" gene(s) are related to signal transduction mechanisms common to each analgesic. The µ-opioid, -opioid, CB₁, and ₂-adrenergic receptors are all members of the superfamily of G-protein-coupled receptors, and all produce cellular inhibition mediated by pertussis toxin-sensitive proteins of the G_i/G_o families (see Limbird, 1988; Ameri, 1999; Connor and Christie, 1999). Intracellular effects produced by activation of these receptors include inhibition of adenylyl cyclase, activation of phospholipase C, activation of inwardly rectifying K⁺ channels, inhibition of voltage-gated Ca²⁺ channels, stimulation of intracellular Ca²⁺ release, and stimulation of mitogen-activated protein kinase. Differential alleles at genes related to any one of these functions could thus affect antinociception in the same direction regardless of the initiating receptor protein. Although nicotinic acetylcholine receptors are excitatory, they do share with the other compounds an interaction with calcium-dependent intracellular effectors (see Flores and Hargreaves, 1999).

Genetic Correlations between Nociception and Antinociception. The inverse correlation between basal nociceptive sensitivity and morphine antinociception replicates previous findings (Belknap et al., 1983; Panocka et al., 1986; Mogil et al., 1996a; Elmer et al., 1997; Kest et al., 1999). We now extend the phenomenon to include the formalin test, but more importantly, we show presently that the correlation between nociceptive and antinociceptive sensitivity is not restricted to morphine but rather appears to hold for a number of disparate analgesic compounds.

In an elegant study of this issue, Elmer et al. (1997) pointed out that a correlation between nociception and antinociception could be explained either by a "parallel" or a "serial" mechanism. That is, either a common (pleiotropic) genetic and physiological substrate is relevant to both phenotypes, or genetic influences on the first (nociception) subsequently affect the second (antinociception). An example of a parallel mechanism would be the existence (and strain-dependence) of antinociceptive "tone", involving the tonic release of endogenous analgesic substances. If some strains had more tone, perhaps by virtue of possessing higher µ-opioid receptor density (and assuming the tonic release of, say, -endorphin), then they would be simultaneously less sensitive to basal nociception and more sensitive to exogenous activation of those same receptors. The existence of opioid tone is quite controversial, with some studies reporting naloxone- or naltrexone-induced hyperalgesia (e.g., Buchsbaum et al., 1977) but many others not (e.g., El-Sobky et al., 1976). Using standard "high" doses of naloxone (1–10 mg/kg), we observed no evidence of reliable hyperalgesia in any of the 12 strains studied here (S. B. Smith and J. S. Mogil, unpublished data). The ability of the CB₁ antagonist, SR 14176A, to produce hyperalgesia in mice suggests the existence of cannabinoid tone (Richardson et al., 1997). It is difficult to see why opioid or cannabinoid tone would affect analgesic potency of other compounds, however.

Elmer et al. (1997) instead argue for a serial mechanism and point to studies suggesting that a direct relationship exists between stimulus intensity and the fractional receptor occupancy (i.e., the proportion of receptors currently bound by ligand) required to produce antinociception (Dirig and Yaksh, 1995). In their study and the present one, mouse strains more sensitive to nociception effectively experience a higher stimulus intensity, which would thus necessitate a higher dose of analgesic. Importantly, the stimulus intensity-dependence of ₂-adrenergic drugs, including clonidine, has also been demonstrated (Saeki and Yaksh, 1992). Note that to the extent that the serial explanation of the genetic correlation between basal nociception and drug antinociception is true, then there are no "antinociception genes", only nociception genes. We think this rather striking possibility deserves further theoretical and experimental attention.

An attempt was made to distinguish between the competing serial and parallel hypotheses by examining genetic correlations of the residuals of antinociception scores after the influence of baseline latencies was removed. This analysis (not shown) resulted in lower correlations overall (mean r_s = 0.35 versus mean r_s = 0.62 for raw antinociception scores), suggesting that much of the correlation among analgesics can be explained statistically by the nociception-antinociception correlation. However, in some cases (mostly involving clonidine) the correlations between analgesics were preserved or even slightly enhanced, suggesting a shared component of antinociception independent of nociception. At the present time we are unable to resolve the issue and consider both hypotheses viable.

Future Directions and Clinical Implications. The present data suggest that simultaneous QTL mapping projects investigating baseline nociceptive sensitivity and multiple drug antinociception phenotypes would reveal common QTLs, within which the "master" genes would be found. The optimal hybrid population for such an effort would involve strains consistently sensitive and resistant, respectively, to all phenotypes studied here. Efforts are underway to do this, using an F₂ intercross between 129P3 mice (mean tail-withdrawal latency: 3.2 s; average antinociception rank: 2.0 of 12) and C57BL/6 mice (mean tail-withdrawal latency: 2.1 s; average antinociception rank: 9.4 of 12).

This study appears to have unfortunate clinical implications, should it be relevant to human pharmacogenetics. A considerable proportion of clinical pain patients are non- or only partially responsive to morphine and other opiates at doses with acceptable side effect profiles (Maier et al., 2002). These findings suggest that such patients will also show poor responsivity to existing alternative analgesic choices such as opioids with -agonist activity (e.g., pentazocine) or ₂-adrenergics (e.g., clonidine, dexmedetomidine). It should be noted, however, that all the drugs studied here are centrally acting analgesics active on the murine tail-withdrawal assay. It is unclear whether other analgesic classes with peripheral actions would display the same patterns of strain-dependence. Finally, although the analgesic efficacy of central compounds may be coinherited, their side effect profiles are likely determined by entirely different sets of genes (e.g., Belknap et al., 1989), and individualized treatment decisions would be made on this basis as well.

	Acknowledgements

 
We thank Brenda Edwards and Galina Cotton for excellent animal care, and Dr. Michael Ossipov for the use of his dose-response curve analysis software. Thanks to Dr. Christopher Flores for helpful discussions, and to the two anonymous reviewers for very useful suggestions.

	Footnotes

 
DOI: 10.1124/jpet.102.041889.

This work was supported by U.S. Public Health Service Grants DA11394 and DE12735 (J.S.M.), and by the Canada Foundation for Innovation and the Canada Research Chairs program. S.G.W. was supported by a National Research Service Award (DA6000).

ABBREVIATIONS: QTL, quantitative trait locus; U50,488, (trans)-3,4-dichloro-N-methyl-N-[2-(1-pyrrolidinyl)-cyclohexyl]benzeneacetamide methane-sulfonate hydrate; WIN55,212-2, (R)-(+)-[2,3-dihydro-5-methyl-3-(4-morpholinylmethyl)pyrrolo[1,2,3-de]-1,4-benzoxazin-6-yl]-1-naphthalenylmethanone; AD₅₀, half-maximal antinociceptive dose; CP55,940, (1R,3R,4R)-3-[2-hydroxy-4-(1,1-dimethylheptyl)phenyl]-4-(3-hydroxypropyl)-cyclohexan-1-ol; SR 14176A, N-(piperidin-1-yl)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-1H-pyrazole-3-carboximide hydrochloride; ABT-594, (R)-5-(2-azetidinylmethoxy)-2-chloropyridine.

Address correspondence to: Dr. Jeffrey S. Mogil, Dept. of Psychology, McGill University, 1205 Dr. Penfield Ave., Montreal, QC H3A 1B1, Canada. E-mail: jeff{at}hebb.psych.mcgill.ca

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