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- Materials and methods
- Supporting Information
Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In this study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine (MA)-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography–mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate, FDR <0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent MA levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization.
Repeated administration of psychostimulants, including methamphetamine (MA), results in a progressive enhancement of the drugs' behavioral activating effects through a process known as behavioral sensitization (BSn). Observed in both animal models and humans (Pierce & Kalivas 1997; Strakowski & Sax 1998), Behavioral sensitization is thought to reflect aspects of the neural adaptations underlying addictive behaviors and motivational states (Robinson & Berridge 2008; Steketee & Kalivas 2011; Wise & Bozarth 1987). Research into the neurochemistry of MA-induced BSn has traditionally focused primarily on dopaminergic neurotransmission. This approach has shown that the psychostimulatory effects of MA are associated with elevated synaptic dopamine (DA) levels due to increased DA release from presynaptic terminals and inhibited reuptake, particularly in mesolimbic neurons projecting from the ventral tegmental area to the nucleus accumbens. Thus, activity-dependent synaptic plasticity and remodeling of the mesolimbic dopaminergic pathway are known to play an important role in psychostimulant sensitization and dependence (Nestler 2001). However, the neurochemical mechanisms underlying BSn are complex and incompletely understood, extending beyond mesolimbic DA to include GABAergic and glutamatergic neurotransmission (Pierce & Kalivas 1997; Steketee 2003), as well as recently identified molecular mediators (e.g. shati and piccolo, Niwa et al. 2008). While trending toward broader consideration beyond established pathways, no research to date has applied a nontargeted metabolomics approach to comprehensively investigate neurochemical variation associated with BSn.
Metabolomics is an emerging platform that seeks to interrogate the full complement of endogenous small molecules (typically <1500 Da) within a sample in a nontargeted fashion. Thus, instead of limiting focus to specific candidate metabolites or metabolic reaction sets, metabolomics approaches quantitatively assay the entire range of metabolites present in a sample to characterize its overall biochemical state. Although MA sensitization has not yet been investigated using metabolomics, the platform has successfully identified biochemical signatures for other CNS pathologies including schizophrenia, Parkinson's and motor neuron disease (Bogdanov et al. 2008; Pears et al. 2005; Prabakaran et al. 2004). Thus, metabolomics offers the possibility of comprehensively mapping neurochemical profiles associated with MA-induced BSn, facilitating the identification of novel mechanisms, biomarkers and therapeutic targets.
To date, metabolomics studies of psychiatric disorders have generally focused on readily obtained biomaterials in humans (e.g. urine and serum) (Kaddurah-Daouk & Krishnan 2009). While human metabolomics research has obvious translational clinical potential, it is also characterized by various limitations including expense, difficulty controlling confounders and inability to access relevant tissue. Mouse metabolomics circumvent many of these limitations, cost-effectively providing control of genetic background and environmental confounders, primary tissue access and precise behavioral phenotype measurement (Dunn et al. 2011). These advantages, paired with extensive genomic and phenotypic database resources, make mouse metabolomics a valuable research strategy for disorders with robust experimental models (Peters et al. 2007). Following this rationale, we analyzed the relationship between longitudinal measures of MA-induced BSn and 301 metabolite levels quantified via nontargeted liquid and gas chromatography–mass spectrometry (GS–MS) of 48 murine brain samples.
- Top of page
- Materials and methods
- Supporting Information
As expected, results indicated that for all 10 phenotypes the mean behavioral activating effects of MA significantly sensitized with repeated administration (P < 0.05; Fig. S3). The degree of sensitization significantly varied across individual mice (P < 0.05; Table S1). For each phenotype, measures quantifying mouse-specific MA-induced BSn were extracted from linear mixed models as BLUPs (Robinson 1991). All BSn measures were approximately normally distributed with no significant outliers/skewness (Fig. S4). Factor analysis of sensitization measures indicated three substantial factors underlying the measures (explaining 91% cumulative variance). Factor 1 (65% variance) was well-represented by sensitization in total distance (TD) (λ = 0.97), Factor 2 (15% variance) by stereotypy number (SN) (λ = 0.78), and Factor 3 (11% variance) by margin time (MT) (λ = 0.74) (Table S2; Fig. S5). These three BSn measures were used as metabolomics outcomes and raw data used to generate them is presented, by strain, in longitudinal scatterplots with superimposed strain mean trajectories in Fig. 1. Analysis of variance results indicated that these three sensitization measures varied in heritability, with approximately half of sensitization variance due to strain differences for TD (P = 6.60E−06, R2 = 0.46) and SN (P = 9.63E−06, R2 = 0.45), while a nonsignificant proportion of sensitization variance was attributable to strain for MT (P = 0.19, R2 = 0.15). See Table S3 for anova results for strain effects on all 10 behavioral indicators.
Figure 1. Longitudinal scatterplots, by strain, of all MA-test mice repeated assessments for behavioral outcomes used in metabolomics analyses. Mean strain sensitization trajectories are superimposed over scatterplots. A stochastic jitter was used to prevent overlay of points occurring on the same day.
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Metabolomics association analyses were conducted as a series of 903 bivariate linear regressions using cluster-robust standard errors, one for each metabolite-outcome combination. Q-Q plots show that associations were generally stronger than expected by chance, with nine associations achieving metabolome-wide significance (q < 0.05), 2 for TD, 5 for SN and 2 for MT (Fig. 2). Specifically, TD was significantly associated with ribulose and homocarnosine. Stereotypy number was significantly associated with isovalerylcarnitine, pantothenate, glutarylcarnitine, N-acetylglutamate and 4-guanidinobutanoate. Margin time was significantly associated with betaine and myo-inositol (Table 1). All results were robust to adjusting for the acute locomotor effects of MA. However, Spearman rank sensitivity analyses indicated that the ribulose-TD, glutarylcarnitine-SN, N-acetylglutamate-SN and betaine-MT associations were driven by outlying mice. Similarly, sensitivity analyses examining the influence of individual strains indicated outlying metabolite levels among 129S1/SvImJ drove the isovalerylcarnitine-SN association. Consequently, these five nonrobust associations are excluded from further analysis (Fig. S6). The four robust associations are visualized in Fig. 3. As shown by standardized regression coefficients (β column, Table 1), for each of the robust associations a 1 SD change in metabolite level was associated with 0.35–0.5 SD change in the corresponding BSn measure. Thus, metabolite levels explained 12–25% of sensitization outcome variance in bivariate models (R2 column, Table 1). Among the robustly significant metabolites, anova results indicated high heritability for homocarnosine (P = 5.12E−17, R2 = 0.89), pantothenate (P = 1.40E−07, R2 = 0.66) and 4-guanidinobutanoate (P = 1.62E−13, R2 = 0.83), and nonsignificant heritability for myo-inositol (P = 0.17, R2 = 0.21). Strain anova results for all 301 assayed metabolites, summarized in Fig. S7, demonstrate significant heritability (P < 0.05) for a majority (68.8%) of metabolites, and high heritability (h2 > 0.70) for substantial minority (13.0%) of metabolites.
Figure 2. Nine neurochemical levels were significantly associated with MA-induced BSn (q < 0.05). Q-Q plots compare observed –log(10) P-values to expected –log(10) P-values under the null distribution for bivariate associations of BSn measures (a, total distance; b, stereotypy number; c, margin time) to 301 neurochemical levels. Each point represents a neurochemical-BSn association P-value and points falling above the null expectation, represented by the dark gray line, are higher than expected by chance. Light gray lines indicate 95% confidence intervals for each P-value rank. All metabolome-wide significant P-values are labeled.
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Table 1. Parameter estimates for metabolome-wide significant (q < 0.05) sensitization-neurochemical associations
|Sensitization outcome||Neurochemical||Primary analysis||Sensitivity analysis|
|Adj. acute||Spearman rank|
Figure 3. Associations of homocarnosine to TD, pantothenate and 4-guanidinobutanoate to SN, and myo-inositol to MT were robust across the examined inbred strain panel. Sensitivity analyses indicated that the statistical significance of these associations was robust to outlying mice and the exclusion of any single strain.
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Next, to determine whether the observed robustly significant associations were a direct result of concurrent MA level, we adjusted the sensitization-metabolite associations for MA level in brain homogenate at sacrifice. Results indicated that MA level did not significantly mediate associations, with marginal metabolite-sensitization associations remaining highly significant (P < 0.001) (Fig. 4; Table S4). Next, we adjusted the metabolite-sensitization associations for strain differences to determine to what extent significant associations were due to genetic differences. Results indicated that associations were generally largely determined by genetic variation between strains, with marginal metabolite effects attenuated to nonsignificant levels when adjusting for strain for homocarnosine-TD, pantothenate-SN and 4-guanidinobutanoate-SN (P > 0.05; Fig. 4). The myo-inositol-MT association was an exception—it was not substantially influenced by strain differences, with its marginal metabolite-sensitization association remaining large and significant (P < 0.001; Fig. 4). These results were consistent with one way anova results showing significant heritability for all implicated metabolites and sensitization outcomes, with the exceptions of myo-inositol and MT.
Figure 4. Among robust associations, neurochemical concentrations explained 12–25% of BSn variance and, with the exception of myo-inositol, were largely mediated by genetic differences. The first columns (light gray) describe unconditional BSn variance explained by the metabolite, with R2 ranging from 0.251 (homocarnosine) to 0.121 (4-guanidinobutanoate) (P < 0.001; bars represent SEM). The second columns (dark gray) describe marginal BSn variance explained by metabolite adjusting for concurrent MA brain levels (partial R2), with R2M remaining highly significant (P < 0.001). The third columns (medium gray) represents the metabolite partial R2 adjusting for strain, which was nonsignificant for homocarnosine, pantothenate and 4-guanidinobutanoate (P > 0.05), but significant for myo-inositol (P < 0.001). Thus, estimates of the proportion of metabolite-BSn associations explained by strain were high (H2 = 0.70–0.99) for all associations except myo-inositol (H2 = 0.06), as shown in the final column (black) of each panel.
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Finally, we collapsed metabolite levels into strain means and examined the correlations of the metabolite strain means between the MA-test mice analyzed here and mice sacrificed at baseline (i.e. no MA exposure). The rationale for this analysis is that if, (1) the strain differences explain a large majority of metabolite-sensitization associations, and (2) the correlations of strain metabolite means pre- and post-MA sensitization are very high, it can be transitively inferred that, (3) significant results reflect associations between baseline strain neurochemical differences and sensitization. This proved to be the case for metabolites in associations substantially accounted for by strains differences, with homocarnosine (P = 0.0001, R2 = 0.94), pantothenate (P = 0.0001, R2 = 0.94) and 4-guanidinobutanoate (P = 0.0003, R2 = 0.90) all showing a very high degree of correspondence between strain means pre- and post-MA sensitization. A lower, though still substantial, correlation was observed for myo-inositol (P = 0.013, R2 = 0.67), further suggesting a unique mechanism for the myo-inositol-MT association relative to the other robust associations. The full results of pre- and post-sensitization strain mean correlations for all 301 assayed metabolites are summarized in Fig. S8 and indicate variable correlation strength, but with far more significant associations than expected by chance (61.8% at P < 0.05).
- Top of page
- Materials and methods
- Supporting Information
Here we report the first nontargeted metabolomics analysis to globally characterize neurochemical differences associated with MA-induced BSn. Association testing between sensitization measures and 301 mass spectrometry-derived metabolite levels, measured across eight inbred mouse strains, identified four novel, robust BSn-metabolite associations. Previous research indicates plausible biological mechanisms for several of these associations.
In addition to the primary sensitization metabolomics association analysis, we also analyzed the longitudinal activity data and metabolite battery separately. Results from our activity phenotype modeling yielded several notable findings. First, mean MA-induced BSn was significant across all activity measures and the magnitude of sensitization varied markedly across strains (Figs. S3,1). While previous research on strain differences in psychostimulant BSn has yielded mixed findings due to modest statistical power, the strain differences observed here were consistent with the most commonly reported patterns, showing increased BSn in DBA/2J and C57BL/6J, particularly relative to A/J and 129/J strains (Chen et al. 2007; Eisener-Dorman et al. 2011; Mead et al. 2002; Thomsen & Caine 2011). Next, consistent with findings from BXD recombinant inbred strains (Philip et al. 2010), we found that strain accounted for a significant proportion of sensitization variance (h2 = 33–50%, P < 0.001) for all sensitization phenotypes except margin time (h2 = 15%, P = 0.19) (Table S3). Independent analyses of the metabolite battery indicated that heritability ranged widely for the 301 metabolites considered, with most metabolites significantly heritable, many metabolites, including homocarnosine (h2 = 89%), highly heritable, but 31.2% of metabolites, including myo-inositol, showing nonsignificant heritability (P < 0.05) (Fig. S7).
Results from the primary association analyses of MA-induced activity sensitization (TD, SN and MT) and the 301 brain metabolites indicated four metabolite-sensitization associations were metabolome-wide significant (q < 0.05) and satisfied all sensitivity criteria: homocarnosine-TD (β = −0.50, P = 2.25E−05), pantothenate-SN (β = 0.47, P = 1.29E−04), 4-guanidinobutanoate-SN (β = −0.35, P = 4.59E−04) and myo-inositol-MT (β = −0.47, P = 4.86E−04; Fig. 3). Among these implicated metabolites, the association of homocarnosine to TD provides clear biological rationale, suggesting that strain-based differences in homocarnosine-mediated cortical excitability moderate the magnitude of MA-induced psychomotor sensitization. This interpretation is supported by research showing that homocarnosine, a CNS dipeptide of GABA and histidine, is intimately related to GABAergic function and serves as a potent inhibitory neuromodulator (Petroff et al. 1998b). Brain homocarnosine levels dose-dependently increase in response to antiepileptic drugs including vigabatrin and topiramate, with the degree of homocarnosine increase strongly correlating with seizure control (Petroff et al. 1998a, 1999). Moreover, homocarnosine has been indirectly implicated in MA-induced sensitization by studies showing that vigabatrin is effective in treating psychostimulant dependence (Brodie et al. 2005; Gerasimov et al. 1999). Vigabatrin is thought to influence psychostimulant addiction through tonically inhibiting both endogenous and psychostimulant-induced extracellular striatal DA release (Dewey et al. 1992; Gerasimov et al. 1999). Additional clinical research has shown that homocarnosine's cortical inhibitory effects are relevant to several related outcomes, including alcohol dependence and panic disorder (Behar et al. 1999; Goddard et al. 2001).
Homocarnosine's neural function remains incompletely understood. Although it has been established that hydrolysis of homocarnosine can rapidly liberate GABA in brain, the balance of evidence suggests that homocarnosine most likely exerts inhibitory effects in of itself, without conversion to GABA (Jackson et al. 1994; Petroff 2002). This is supported by recent studies of homocarnosine function in rat hippocampus indicating that while both homocarnosine and GABA exerted inhibitory effects, homocarnosine showed no effect on membrane potential; its effects were blocked by pretreatment with GABAA inhibitors; and its presence reduced the frequency but not the burst characteristics of induced seizure-like activity (Petroff & Williamson 2009). Thus, consistent with our findings, it appears that homocarnosine's inhibitory action does not function through increasing GABA levels, but rather through shifting the balance from intracellular to synaptic locations of neurotransmitter.
The 4-guanidinobutanoate-SN association suggests a related GABAergic mechanism. 4-Guanidinobutanoate is a relatively poorly studied metabolite formed by the transfer of the guanidino group from arginine to GABA via transamination (Jansen et al. 2006; Schulze et al. 1998). While research on the neural function of this metabolite is sparse, there is some indication that it exerts GABAergic effects in rodent CNS (Bowery & Brown 1974). Intriguingly, as with homocarnosine, 4-guanidinobutanoate levels are elevated by vigabtrin treatment (Schulze et al. 1998). These facts, combined with the substantial correlation observed with homocarnosine in the current data (r = 0.58; P < 0.001), suggest that 4-guanidinobutanoate is plausible biomarker of GABAergic inhibition and perhaps a causal factor in attenuating MA-induced BSn.
The myo-inositol-MT association is also consistent with previous research. Margin time, or thigmotaxis, is a well-established index of anxiety in mice, which has been validated using several anxiogenic and anxiolytic drugs (Simon et al. 1994). Consistent with our results, there is a large body of research in both rodents and humans indicating a negative correlation between CNS myo-inositol levels and anxiety disorders /behaviors (Benjamin et al. 1995; Einat & Belmaker 2001). This research has demonstrated that chronic myo-inositol administration, but not acute, increases open field activity in rodents and that chronic exposure increases rodent myo-inositol levels in various brain regions, including cortex and hippocampus (Cohen et al. 1997; Einat & Belmaker 2001). Human post-mortem research has shown that reduced myo-inositol levels in frontal cortex are associated with bipolar disorder and suicide, suggesting that endogenous levels are relevant to anxiety-related phenotypes (Shimon et al. 1997). While the precise mechanism by which myo-inositol exerts its anxiolytic effects remains obscure, the metabolite is a key precursor of the phosphoinositide secondary messenger cycle, which is activated following ligand binding with G-protein coupled receptors across several neurotransmitter systems including serotonergic (5-HT1C and 5-HT2) and dopaminergic (D1) receptor types (Kim et al. 2005). Finally, the pantothenate-SN finding is entirely novel, with no notable support from previous research.
Synthesizing all results yields a consistent causal interpretation, with the notable exception of the myo-inositol-MT finding. Thus, the homocarnosine-TD, 4-guanidinobutanoate-SN and pantothenate-SN associations all share several notable features—all of these metabolites and sensitization dimensions are highly heritable in this mouse panel; strain means of the metabolites are virtually perfectly correlated between untreated and MA sensitized mice; and the covariances of metabolites and sensitization measures are highly heritable. Furthermore, analyses controlling for acute MA activity effects and MA brain levels at sacrifice rule out the possibilities that these findings reflect differences in MA metabolism rates or the acute activity-inducing effects of MA. Additionally, none of the significant associations identified here overlap findings from our previous metabolomics analysis of the direct neurochemical effects of MA exposure (Mcclay et al. 2013). Cumulatively, these findings strongly suggest that baseline strain differences in the implicated neurochemicals substantially influence the magnitude MA-induced TD and SN sensitization.
The myo-inositol-MT finding suggests a different, and less certain, causal interpretation. Unlike the other significant associations, myo-inositol and MT were not significantly heritable in this sample, nor was their covariance. Furthermore, the correlation of strain means in untreated and MA sensitized mice indicated substantially less stability than was observed for the other significant metabolites. Thus, this finding is not attributable to strain differences and it is possible that the association may be due to myo-inositol levels differentially shifting as a consequence of repeated MA exposure, rather than baseline neurochemical differences. Given the causal ambiguity of this finding, it may be reasonable to regard it with a heightened degree of skepticism. However, the result is entirely consistent with a large body of previous research showing negative correlations between CNS myo-inositol levels and anxiety traits, including open field measures similar to MT (Einat & Belmaker 2001; Shimon et al. 1997), supporting its validity as a true discovery.
These results suggest promising directions for future research. Given that the predominant pattern in the significant findings suggests common genetic variation producing baseline neurochemical differences that then substantially predict the magnitude of MA-induced sensitization, future research using a heterogeneous, genetically diverse sample of mice, such as latter generations of the collaborative cross (Iraqi et al. 2012), would be advantageous for several reasons. First, the increased genetic diversity would offer greater statistical power and reduce the risk of spurious association (Flint & Eskin 2012). Second, genomewide genotypes are freely available for the founder strains and hundreds of crosses of the collaborative cross panel (Iraqi et al. 2012), enabling inexpensive genetic mapping of both metabolite levels and sensitization variables. Notwithstanding these merits, an awareness of the limits of generalizability between mouse models and humans is warranted given known species differences in potentially relevant neurochemical pathways, such as neuroactive steroid modulation of GABAergic signaling (Nguyen et al. 1995).
Another topic relevant to future research is the use of whole brain homogenate in this study, the selection of which was influenced by volume requirements for the nontargeted metabolomic assay (Evans et al. 2009; Ohta et al. 2009). While, in principle, volume requirements could have been met through pooling specific regions across mice within strains, implicit in such pooling is the strong assumption of no within-strain variance, which would have precluded investigating heritability and missed the myo-inositol-MT finding, which was driven by within-strain variance. Another, more general limitation of the metabolomics platform is its exclusive focus on changes to the overall metabolite pool. Thus, highly localized effects, such as synaptic release of neurotransmitters, will not be detectable in the tissue homogenate because it is impossible to distinguish between, for example, vesicular and synaptic neurotransmitter molecules. Despite these limitations, the multiple robust signals detected here demonstrate the method's value as a screening tool. Clearly, this is only the first stage in understanding the role of these metabolites in psychostimulant abuse. Accordingly, we encourage future research into the roles of the implicated metabolites in targeted assays of candidate brain regions.
In conclusion, using nontargeted metabolomic profiling, we identified multiple neurochemical signatures in MA-induced sensitization. Specific results include the finding that relative abundance of two specific GABAergic metabolites, homocarnosine and 4-guanidinobutanoate, attenuate the magnitude of MA psychomotor sensitization. Further, consistent with previous research, we found myo-inositol negatively associated with sensitization of MA's anxiogenic effects. While the estimated risk of false discoveries was quite low, independent replication and targeted follow-up will be necessary to confirm and elaborate these findings. To facilitate this, we have made P-values from the primary analysis available for download (http://www.people.vcu.edu/˜ejvandenoord/) as a resource supporting future replication, follow-up or data integration efforts. It is hoped that this research will encourage further metabolomics applications to identify novel neurochemical mechanisms and potential therapeutic targets in neuropsychiatric disorders.