Large-scale neurochemical metabolomics analysis identifies multiple compounds associated with methamphetamine exposure

Abstract

Methamphetamine (MA) is an illegal stimulant drug of abuse with serious negative health consequences. The neurochemical effects of MA have been partially characterized, with a traditional focus on classical neurotransmitter systems. However, these directions have not yet led to novel drug treatments for MA abuse or toxicity. As an alternative approach, we describe here the first application of metabolomics to investigate the neurochemical consequences of MA exposure in the rodent brain. We examined single exposures at 3 mg/kg and repeated exposures at 3 mg/kg over 5 days in eight common inbred mouse strains. Brain tissue samples were assayed using high-throughput gas and liquid chromatography mass spectrometry, yielding quantitative data on >300 unique metabolites. Association testing and false discovery rate control yielded several metabolome-wide significant associations with acute MA exposure, including compounds such as lactate (p = 4.4 × 10^-5, q = 0.013), tryptophan (p = 7.0 × 10^-4, q = 0.035) and 2-hydroxyglutarate (p = 1.1 × 10^-4, q = 0.022). Secondary analyses of MA-induced increase in locomotor activity showed associations with energy metabolites such as succinate (p = 3.8 × 10^-7). Associations specific to repeated (5 day) MA exposure included phosphocholine (p = 4.0 × 10^-4, q = 0.087) and ergothioneine (p = 3.0 × 10^-4, q = 0.087). Our data appear to confirm and extend existing models of MA action in the brain, whereby an initial increase in energy metabolism, coupled with an increase in behavioral locomotion, gives way to disruption of mitochondria and phospholipid pathways and increased endogenous antioxidant response. Our study demonstrates the power of comprehensive MS-based metabolomics to identify drug-induced changes to brain metabolism and to develop neurochemical models of drug effects.

Keywords: Drugs of abuse; Inbred mice; Mass spectrometry; Neurotoxicity; Psychostimulants.

Fig. 1

Quantile-quantile (QQ) plot of all p values in primary analysis. The plot compares observed p values to expected p values under the null distribution. Each point represents a neurochemical association p value and points falling above the null expectation, represented by the red line, are higher than expected by chance. The blue line represents the 95 % confidence interval. A total of 301 metabolites were tested for association with each of the three experimental conditions. The fact that many p values fall above the red (and upper blue) line indicates many small effects. Twelve findings were significant after false discovery rate control at the 10 % level (q < 0.1) and these are identified in the figure (Color figure online)