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. Author manuscript; available in PMC: 2015 May 15.
Published in final edited form as: Drug Alcohol Depend. 2013 Aug 8;133(2):759–762. doi: 10.1016/j.drugalcdep.2013.07.029

Effects of methamphetamine on the noradrenergic activity biomarker salivary alpha-amylase*

Colin N Haile 1,#, Richard De La Garza II 1, James J Mahoney III 1, Thomas F Newton 1
PMCID: PMC4432865  NIHMSID: NIHMS514422  PMID: 23968815

Abstract

Background

Methamphetamine (METH) potently activates the sympathetic nervous system (SNS) by increasing central and peripheral norepinephrine (NE). Salivary α-amylase (sAA) is a biomarker of SNS activation that correlates with plasma NE levels. The purpose of this study was to determine the impact of METH on sAA activity and whether changes in sAA activity were correlated with subjective effects ratings.

Methods

Non-treatment seeking METH-dependent volunteers (N=8) participated in this within-subjects laboratory-based study. Volunteers received randomly administered intravenous METH (0mg, 30mg) and sAA activity, cardiovascular measures and subjective ratings were assessed at baseline (−15 min) and five post-METH time points (10, 20, 30, 45, and 60 min).

Results

METH (30mg) increased sAA activity over time. sAA activity significantly correlated with diastolic blood pressure following 0mg METH and systolic blood pressure following 30mg METH. Subjective ratings (ANY EFFECT, HIGH, GOOD, STIMULATED, LIKE, WLLING TO PAY) highly correlated with sAA over five post-METH time points (N=40; r’s=0.543–0.684, p’s <0.001). Age, body mass index and METH amount received on a mg/kg basis were significantly associated with sAA activity. Multiple linear regression analysis indicated sAA activity remained a significant predictor of subjective ratings following METH after controlling for these factors.

Conclusions

The NE peripheral biomarker sAA activity is associated with METH’s subjective effects.

Keywords: norepinephrine, methamphetamine, psychostimulants, sympathetic nervous system, salivary alpha-amylase

1. INTRODUCTION

Methamphetamine (METH) rapidly increases central dopamine (DA) and norepinephrine (NE) neurotransmission by acting as a substrate for presynaptic and vesicular monoamine transporters, reversing their action and increasing cytosolic and synaptic transmitter levels (Sulzer, 2011). Increases in synaptic catecholamine levels within specific brain mesocorticolimbic circuitry are thought to mediate METH’s reinforcing effects (Vollm et al., 2004). Although most research has focused on DA, accumulating evidence indicates NE may play an important role in mediating METH’s effects (Weinshenker and Schroeder, 2007). Indeed, METH induces NE release more potently than DA and medications that target NE attenuate stimulant-induced positive subjective drug effects and decrease drug use (Colfax et al., 2011; Haile et al., 2012; Newton et al., 2012).

Salivary α-amylase (sAA) is better known as the enzyme responsible for the digestion of starch but has been shown to be a biomarker of stress-induced activation of the sympathetic nervous system (SNS; Nater and Rohleder, 2009). Stress-induced increases in plasma NE correlate with sAA activity (Thoma et al., 2012). Similar to stress, adrenergic agonists and medications that facilitate the release of NE also increase sAA activity whereas adrenergic antagonists reduce sAA activity (Andrews and Pruessner, 2013; Ehlert et al., 2006; van Stegeren et al., 2006).

To our knowledge, there are no studies assessing the impact of acute METH administration on sAA activity. Therefore, we conducted the present study in non-treatment seeking METH-dependent volunteers to determine if METH administration would alter sAA activity and if sAA activity was related to METH’s cardiovascular and subjective effects.

2. METHODS

2.1 Subjects

Data included in this study were obtained from eight non-treatment seeking METH-dependent individuals who were taking part in other studies in our laboratory. This study was conducted at the Baylor College of Medicine (BCM) and the Michael E. DeBakey Veteran’s Administration Medical Center (MEDVAMC). Subjects were paid for their participation. All gave consent after being fully informed about the study protocol.

All subjects (7 male, 1 female; African American-2, Caucasian-5, Hispanic-1) met DSM-IV-TR criteria for METH-dependence. Additional inclusion criteria were age between 18–55 years (mean age, 38.13±2.92 yrs), a history of METH use (mean yrs METH use, 19±2.31; last 30 days, 18.06±2.25) by smoking or intravenous routes (smoke-2, IV-1, all routes-5), being in good health, confirmed by a physician and clinical laboratory blood chemistry tests. Subjects were excluded if criteria were met for dependence on other drugs except for nicotine (mean yrs use, 19±4.04; last 30 days, 26.25±3.75) and cannabis (mean yrs use, 13.29±5.11; last 30 days, 3.88±3.73). All subjects had used alcohol in the past but did not meet criteria for dependence (mean yrs use, 15.88±3.82; last 30 days, 2.50±1.83).

2.2 Study design

This study was conducted using a double-blind, placebo controlled, randomized within-subjects design. The study protocol consisted of a single test day with two sessions (AM and PM) where the participant randomly received 0mg (saline) or 30mg METH. Infusions were administered with the participant resting in a hospital bed. Subjective ratings were obtained using visual analog scales (0 and 100). Cardiovascular measures (HR, systolic, SBP, diastolic, DBP) and electrocardiograms (ECG) were collected at baseline (−15 min) and five time points throughout each session (10, 20, 30, 45, and 60 min) following infusion. Participants were allowed to smoke cigarettes up to 30 min prior to each infusion session only. Sterile METH for human use was provided by NIDA’s medication supply program (RTI International, Research Triangle Park, NC) and prepared by the MEDVAMC Research Pharmacy.

2.3 Salivary α-amylase activity (sAA)

Salivary α-amylase activity was determined using a commercially available kit (Salimetrics, State College, PA, USA). Saliva samples were obtained using the Salimetrics Oral Swab which was placed under the tongue for 30 seconds at the same time participants provided subjective effects ratings. Samples were then stored at −80° C until assayed in our laboratory.

2.4 Data analysis

Data analysis was performed using SigmaStat 12.0 (SYSTAT Software Inc., San Jose, CA, USA). Normality (Shapiro-Wilk) and equal variance tests revealed the sAA data was found to be highly skewed so log-transformed values were used in the analysis. Untransformed values were used to generate Figure 1 (A.) Cardiovascular measures, subjective ratings, sAA activity and salivary flow rate were assessed using a two-way repeated measures analysis of variance (METH dose: 0mg and 30mg; time: - 15–60min) with time as the repeated factor. Significant main effects were followed with pair-wise multiple comparison procedures (Bonferroni t-test). Regression analysis (Pearson’s and Spearman Rank Order) was used to determine possible relationships between sAA activity, cardiovascular measures and subjective ratings over all time points within the session except baseline (N=40, 10–60min). Body mass index (BMI), diurnal rhythms, gender and age may influence sAA activity (Rohleder and Nater, 2009). Therefore, factors that showed a significant relationship with sAA activity were included in a Multiple Regression Analysis model assessing their ability to predict a given dependent variable (e.g. ANY EFFECT, HIGH). An additional Multiple Regression Analysis model that included the time (AM/PM) in which a participant randomly received METH was used to ascertain whether diurnal or order effects influenced sAA. Extra diagnostic tests were employed to assess the potential impact of each individual data point (DFFITSi statistic, leverage and Cooke’s Distance). Significance was set at p<0.05 and all data are presented as mean ± standard error.

Figure 1.

Figure 1

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Impact of METH (0mg and 30mg) administration on salivary α-amylase activity (A) and salivary flow rate (B) over time. Time in minutes is relative to the administration of METH. Data is presented as mean±SEM. Significance is denoted by * (p<0.05).

3. RESULTS

3.1 Effects of METH on subjective ratings and cardiovascular measures

Infusion of 30mg METH significantly increased HR (METH dose×time interaction, F5,95=3.64, p<0.05), SBP and DBP (F’s >2.8, p’s<0.05) over time compared to 0mg METH. Post-hoc pair-wise multiple comparisons revealed significant differences from 0mg METH at all time points except baseline (−15 min) following METH (p’s <0.05). Main effects and interactions (F’s >3.19, p’s<0.05) were found for ratings of ANY EFFECT, HIGH, GOOD, LIKE, STIMULATED, $ WILLING TO PAY. Post-hoc pair-wise multiple comparisons following significant main effects revealed differences between METH doses and subjective measures at all time points except baseline (p’s <0.05).

3.2 Effects of METH on salivary alpha-amylase activity

As shown in Figure 1 A., sAA activity differed over time and was dependent upon METH dose. This statement is supported by a significant main effect for METH dose (F1,95 =40.30, p<0.001) and time (F5,95 =2.97, p<0.05) and a METH dose×time interaction (F5,95 =3.95, p<0.05). Post-hoc comparisons indicated significant differences in sAA activity at time points 20–60 min (p’s<0.05). There were no main effects found for METH dose or time and no interactions for salivary flow rate, a potential confound (Figure 1 B., F’s<1.80, p’s>0.05).

3.3 Association between salivary alpha-amylase activity and cardiovascular measures and subjective ratings over all time points

For these analyses, we included measures from each time point following infusion, so the sample sizes were 40 (5 time points and 8 participants). Regression analysis revealed that DBP (N=40, r=0.431; p<0.006) was positively correlated with sAA activity following 0mg METH and SBP (N=40, r=0.689; p<0.001) following 30mg METH (see supplementary material for additional analysis1).

None of the subjective ratings were correlated with sAA following 0mg METH over all time points (N=40, p’s>0.05). Table 1 shows correlations between subjective ratings and sAA activity. Analysis with Spearman Rank Order also yielded similar results as presented in Table 1, but also revealed a significant negative association for BAD (rs=−0.306, p=0.054). Age (r=0.479, p=0.002; r=419, p=0.007) and BMI (r=0.592, p<0.001; r=0.708, p<0.001) were negatively correlated with sAA following 0mg and 30mg METH respectively. METH amount received calculated as 30mg/weight (kg) for each participant correlated positively with sAA (r=0.528, p<0.001) (see supplemental material for additional analysis2).

Table 1.

Correlations between salivary α-amylase activity and subjective ratings following METH (30mg)

METH
Salivary α-amylase r P-value
ANY EFFECT 0.680 <0.001
HIGH 0.684 <0.001
GOOD 0.666 <0.001
STIMULATED 0.543 <0.001
LIKE 0.623 <0.001
BAD −0.219 0.175
DESIRE −0.149 0.360
DEPRESSED −0.021 0.897
ANXIOUS 0.040 0.804
LIKELY TO USE −0.245 0.127
WILLING TO PAY 0.682 <0.001
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r=Pearson product-moment correlation coefficient

N=40 for each association

A multiple linear regression analysis model was employed that included age, BMI, amount of METH received, and sAA activity as predictors of each subjective rating over all time points. Analysis showed that sAA activity remained a significant predictor for subjective ratings ANY EFFECT, HIGH, GOOD, STIMULATED, LIKE and WILLING TO PAY in response to 30mg METH (r2s=0.417–0.616; t’s=2.613–4.083; p’s=0.013-<0.001). Further analysis indicated that the ability of sAA to serve as a predictor for subjective ratings was not significantly influenced by when (N=2-AM/N=6-PM) a participant received METH (p’s>0.05). Diagnostic tests (DFFITSi statistic, leverage and Cooke’s Distance) yielded no data points with overt influence.

4. DISCUSSION

The present study assessed the impact of METH on sAA activity, a peripheral biomarker of NE and SNS activation. We found that METH dramatically increased sAA and that sAA correlated with subjective ratings for ANY EFFECT, HIGH, GOOD, STIMULATED, LIKE and WILLING TO PAY. Although BMI, age and METH amount (mg/kg) were also strongly associated with sAA activity, we found that even after statistically controlling for these factors, sAA remained a significant predictor of these subjective ratings following METH. This is the first study to document the relationship between sAA activity and subjective effects in response to METH.

That METH increased sAA activity is consistent with studies showing pharmacological, psychological and physical stress that elevates peripheral NE levels is associated with concomitant increases in sAA (Nater and Rohleder, 2009). Stress-induced changes in sAA correlate with plasma NE which generally reflects central levels (Chatterton et al., 1996; Thoma et al., 2012; Tsuji et al., 1986). METH also stimulates the SNS by preferentially elevating both central and peripheral NE (Cruickshank and Dyer, 2009; Rothman et al., 2001). Similar to METH, nicotine also increases sAA activity in humans and sAA levels correspond with amount of nicotine intake in smokers (Maier et al., 1991; Thoma et al., 2012). Taken together, our finding that intravenous METH increases sAA activity is consistent with studies showing that other interventions that increase NE transmission also increase sAA activity (Ehlert et al., 2006).

We found that sAA activity correlated with, and predicted certain subjective effects produced by METH. Somewhat similar to our findings, Oswald and colleagues demonstrated that plasma cortisol correlated with subjective ratings (e.g., HIGH, GOOD, LIKE) following intravenous amphetamine in healthy adults (Oswald et al., 2005). This finding is consistent with the present study since sAA activity correlates with cortisol levels following stress (Almela et al., 2011).

Our results revealed that increases in sAA activity following 0 mg METH positively correlated with DBP, but not SBP or HR. That sAA activity did not correlate with cardiovascular indices that signal sympathetic activation is understandable. It is less clear however why sAA activity would correlate with DBP. METH-induced increases in SBP were highly correlated with sAA activity, indicating potent SNS activation. Our finding that sAA activity following METH administration was not associated with HR is in contrast to studies assessing the effects of stress on sAA (Almela et al., 2011; Bosch et al., 2003; Chatterton et al., 1996; Nater and Rohleder, 2009).

The present study has a number of limitations. First, saliva collection methods, orthostatic changes, general activity, patient demographics and salivary flow rate can significantly influence sAA (Bosch et al., 2011; Nater and Rohleder, 2009). We collected un-stimulated saliva and found no differences in salivary flow rate between groups. Further, participants were confined to a hospital bed throughout the entire experiment, controlling for possible orthostatic and activity effects on sAA. Nevertheless, the present study should be considered preliminary since the sample size employed was small and composed predominantly of males. Importantly, although a significant number of studies have linked sAA and plasma NE, NE levels were not assessed in our study therefore we cannot affirm a direct relationship between METH-induced increases of peripheral NE and sAA activity.

In conclusion, we found that METH administration increased sAA activity, a peripheral biomarker of central NE. sAA activity was highly correlated with subjective ratings following METH.

Supplementary Material

01

Acknowledgements

We would like to thank the nursing staff from the Baylor College of Medicine general Clinical Research Center (GCRC) for their assistance. This material is the result of work supported with resources and the use of facilities at the Michael E. DeBakey VA medical center.

Role of Funding Source

Funding for this study was provided by NIH (TF Newton: R25DA28976, R01DA023468, P50DA18197). The NIH had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.

Footnotes

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*

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:…

Contributors

Drs. De La Garza, Newton and Mahoney designed the study and wrote the protocol. Dr. Haile managed the literature searches, summaries of previous related work and undertook the statistical analysis. Drs. Haile and Newton wrote the first draft of the manuscript. All authors significantly contributed to and have approved the final manuscript.

Conflict of Interest

The authors report no conflicts of interest in conducting this study.

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