Abstract
Objective: Chronic METH use results in neurodegenerative alternations in the human brain. The present study aimed to assess the long-term METH impact on brain metabolite concentrations in cases meeting the DSM-5 criteria regarding METH use.
Method: We recruited 42 METH users meeting the DSM-5 criteria and 21 healthy controls. Psychotic signs were measured using the Positive and Negative Syndrome Scale (PANSS). Proton magnetic resonance spectroscopy (1HMRS) evaluating Myo-inositol (Ml), Choline (Cho), Glutamine plus Glutamate (Glx), N-acetyl aspartate (NAA), and Creatine (Cre) were obtained in the dopaminergic pathway (Frontal Cortex, Substantia nigra, Ventral Tegmental Area (VTA), Nucleus Accumbens (NAc), Hippocampus, Striatum,) the subjects. All participants collected urine specimens for 24 hours to measure presence of specific metabolites including METH metabolite level, 5-Hydroxy indoleacetic acid metabolite (for serotonin level monitoring), and metanephrine metabolite (for dopamine level monitoring).
Results: Dopamine and Serotonin increased in the METH group (P < 0.001). METH caused an increase in the Cre (P < 0.001) and a decline in the Glx (P < 0.001), NAA (P = 0.008), and MI (P < 0.001) metabolite concentrations of dopamine circuits in METH users in comparison with healthy subjects. We found no change in Cho metabolite concentration. Psychological data and the neurometabolite concentrations in the studied area of the brain were significantly correlated.
Conclusion: There is an association between METH use and active neurodegeneration in the dopamine circuit, and it causes serious mental illness. 1HMRS can detect patient’s deterioration and progression of disease as well as follow-up management in patients with METH use disorder.
Key Words: Brain, Dopamine, Magnetic Resonance Spectroscopy, Methamphetamine, Serotonin, Substance-Related Disorders
Methamphetamine (METH) use can cause compulsive consumption and craving despite its severe adverse effects (1). METH use disorders, following opioid use disorders, are responsible for a major part of the global burden of drug use. According to the United Nations report in 2020, about 27 million people worldwide (0.5% of the adult population) are estimated to have used amphetamine-type stimulants in the past year. The past-year use of METH in Asia is at a similar level (0.5 per cent) to the world average (2). The past-year prevalence of METH use in Iran is estimated around 0.4% of the population aged 15–64 (3). Evidence suggest that METH causes the greatest global health concern. Its usage is associated with psychotic symptoms and morphological and neurochemical dysfunctions affecting several brain areas (4, 5). METH-induced psychiatric signs are anxiety, irritability, psychosis, and changes in mood. In METH psychosis, positive psychotic symptoms (paranoid delusions and hallucinations) are much more commonly reported compared to negative symptoms (poverty of speech, psychomotor retardation, and a flattened affect) (6).
METH stimulates the nigrostriatal pathways, mesocortical circuit, and the mesolimbic which have been associated with the reward system (7). METH can cause alternation in dopaminergic, serotonergic, and noradrenergic systems by stimulating secretion of monoamines, inhibiting monoamine reuptake, inactivating presynaptic vesicular monoamine transporter 2, and a reduction in the effectiveness of monoamine metabolic enzymes (8, 9). However, METH effects in the human brain on glutamate and glutamine (Glx), and key neurometabolites such as N-acetylaspartate (NAA), myo-inositol (MI), choline (Cho), and creatine (Cre) are poorly understood. Changes in these neurometabolites could be informative regarding the mechanism of action of METH drugs and their dependence potential in humans. NAA is a neuronal marker and reflects neuronal integrity, viability, and number (10). Cre may be a marker of brain energy metabolism (11). Glx is a marker of cognitive function (12). Cho serves as a marker for enhanced membrane turnover, cell growth and cell division, or inflammation, and increased Cho has been associated with gliosis and membrane breakdown (13). MI is generally considered a marker for gliosis (14). Significant long-term alternation of neurometabolites found in METH consumers is linked to psychomotor defect (15).
Neurochemical alternations in human METH consumers were detected using proton magnetic resonance spectroscopy (1HMRS) that is capable of quantifying different neurometabolites in the millimolar levels range in targeted brain regions (16). 1HMRS has demonstrated neurometabolites disturbances in brain tissue in METH use including NAA, Cre, Glx, Cho, and MI (17-22). Most of the 1HMRS studies focused on cingulate (19, 23-25), basal ganglia (26), frontal cortex (22, 27-29) with less evidence in the dopaminergic circuit including Nucleus Accumbemce (NAc), Ventral Tegmental Area (VTA), Substantia nigra, Hippocampus, Prefrontal Cortex (PFC), and Striatum. Although numerous studies have examined the METH-induced alternation of neurometabolites, few have investigated the association of alternation of neurometabolites with psychological symptoms. This study was performed to expand the prior investigations of neurometabolites in patients with METH use disorder. Both 1HMRS and psychological tests were performed in METH users and healthy controls. The aim of this study was to first assess neurometabolites alternation as neuronal integrity and glial markers (NAA, Cre, Glx, Cho, MI) in targeted brain regions as reward circuit. In addition, the study aimed to determine correlates of neurometabolites with neuropsychiatric symptoms in METH user subjects and healthy controls with 1HMRS.
Materials and Methods
Participants
This study was designed and performed in February, 2019 in Shahroud, Iran. Two groups were studied: 42 METH abusing subjects and 21 non-substance-abusing control subjects. The subjects signed the written informed consent before entering this research. Inclusion criteria were (i) age 18–50 yr; (ii) lifetime diagnosis of DSM-5 METH use, according to the Structured Clinical Interview for DSM-5; (iii) no use of medications or herbal medicine affecting the brain. Exclusion criteria were (i) drug use except for METH (not for nicotine and caffeine) for the past year; (ii) current or past non–drug-related psychiatric disorders; (iii) current or past significant medical, neurological disorder or trauma affecting the CNS (cerebrovascular or seizure disease); (iv) severe hepatic, respiratory, renal, endocrine disease, AIDS or loss of consciousness lasting 30 min or more; and (v) metal implant or any other contraindications to MR scanning.
METH users were selected from outpatient drug use camps. All patients were interviewed by a psychiatrist and a neurologist, considering the inclusion and exclusion criteria. The control group was selected from the local community and was homogenous with the METH group (not for METH use background). To detect the current use of METH, urine screening was conducted: urine analysis at the baseline interview and before the MRS scan. All participants were current METH user. Then, all participants collected urine specimens for 24 hours to measure presence of specific metabolites including METH metabolite level, 5-Hydroxy indoleacetic acid metabolite (for serotonin level monitoring), and metanephrine metabolite (for dopamine level monitoring).
Positive and Negative Syndrome Scale (PANSS)
Psychotic symptoms were assessed with the full 30-item PANSS, which has been used previously validated in the Persian population (30). Analysis of the PANSS Data was done based on the standard three factors and the five-factor models. Regarding five-factor models, the items on the PANSS were categorized into the factors as follows followed by summing: negative (N1, N2, N3, N4, N6, G7, G13, and G16), positive (items P1, P3, P5, P6, G9, and G12), anxiety/depression (G1, G2, G3, G4, and G6), disorganization (P2, N5, N7, G5, G10, G11, and G15), excitement (P4, P7, G8, and G14) dimensions (31).
Proton Magnetic Resonance Spectroscopy Data
1HMRS imaging as the MRS multivoxel version as well as prescriptive structural MRI were obtained in a session. 1HMRS spectra of reward pathway (PFC, Hippocampus, VTA, Substantia nigra, NAc, Striatum) was conducted on 1.5T Siemens (Avanto, Imamhosein Hospital, Shahroud University of Medical Sciences, Iran) with standard head coil (18 channel) and the subsequent criterion: T1 image parameters with ms parameters (TE = 1.53.3.21.4.89.6.57ms, TR = 1500) (FOV = 256mm) (FA = 7), 160 cut, with 10min scan time, and sectional thickness about 1mm. Then 3D CSI imaging with the following criteria: TR = 1500, TE = 270 and, VOI = 100.50.80, FOV = 160.160.160, NEX = 2, 15 mm sectional thickness. CHESS automatic pulse twice with 2TE and 2VOIs showed in 15min. Analysis was performed with the console Siemens syngo software and measuring the curvature of the NAA, Cre, Cho, Glx, MI with 2VOIs (left and right five brain regions) with 2 TE short and high and after achieving the corresponding curve. The spectrum of neurometabolites were sent to the neuroradiologist.
Magnetic Resonance Post-processing
1HMRS imaging spectra were obtained by the spectroscopic evaluation software (syngosimens) and levels of neurometabolites were obtained in the brain areas by statistical analysis (Note: Glx concentration due to limited field strength (1.5 T) was low SNR).
Statistical analysis
SPSS 20 was used to analyze data using a Student’s t-test to compare the means of the metabolites in METH consumers and controls. The correlation between the metabolites and each clinical parameter, such as duration of METH usage, PANSS score, and Subscale of PANSS were assessed by Pearson’s correlation coefficient at P < 0.05. The metabolites were calculated in the reward pathway (PFC, Hippocampus, VTA, Substantia nigra, NAc, Striatum). For error avoidance, repeated-measures ANOVA was applied for repeated values of the right and left hemispheres.
Ethical Approval
The research was approved by the local Ethics Committee of Shahroud University of Medical Sciences and has been performed under the ethical standards of the Declaration of Helsinki (Ethical code: IR. SHMU.1397.132). The present study was completed in accordance with the Declaration of Helsinki and the Ethical Guidelines for Medical and Health research established by ministry of Health and Medical Education and Ministry of Science, Research and Technology, Iran. All the participants provided their informed written consent for participation in the present study.
Results
No significant difference was found regarding age, sex, handedness, and socioeconomic status between the 42 METH users (34 men, 8 women; 38.04 ± 8.03 yr) and 21 healthy control subjects (14 men, 7 women; 38.42 ± 10.87 yr). The METH consumers used crystalline METH via inhalational and intravenous routes. They had used the drug for 4±3 years. The mean daily estimated METH use was 0.5 grams.
Table 1 demonstrated significant differences in the total concentration of Dopamine, Serotonin (in urine), NAA, Cre, Glx, and MI brain metabolites in the studied areas of the brain between METH users and Healthy controls, while two groups showed no significant differences in Cho. Mean (±SD) scores of total PANSS in the METH user group was 79.66±57.93.
Table 1.
Metabolites (ppm, Mean ± SD) | METH Users (n = 42) | Healthy Controls (n = 21) | Sig. |
---|---|---|---|
Dopamine | 4.21±1.25 | 2.38±0.8 | <0.001* |
Serotonin | 3.75±1.38 | 1.9±0.69 | <0.001* |
NAA | 22.24±5.6 | 26.14±4.6 | 0.008 * |
Cre | 12.02±3.1 | 7.78±1.4 | <0.001* |
Cho | 9.6±3.2 | 9.7±2.11 | 0.89 |
Glx | 2.5±1.43 | 4.6±1.1 | <0.001* |
MI | 2.59±1.33 | 4.9±1.29 | <0.001* |
Significantly different from controls, Abbreviations: METH, Methamphetamine; ppm, parts per million; NAA, N-acetyl aspartate; Cho, Choline; Cre, Creatine; Ml, Myo-inositol; Glx, Glutamine plus Glutamate; PANSS; Positive and Negative Syndrome Scale.
Table 2 showed changes in amounts of NAA, Cre, Glx, and MI metabolites that were significantly correlated (negatively) with the PANSS total score and psychiatric disorders. Nonetheless, the PANSS total score and the Cho measure were not correlated. Furthermore, there is a significant association between the changes in metabolism of MI, and NAA, Cre, and Glx metabolites.
Table 2.
PANSS | NAA | Cre | Cho | Glx | MI | |
---|---|---|---|---|---|---|
PANSS | 1 | |||||
NAA |
r = -0.39 p = 0.002* |
1 | ||||
Cre |
r = -0.57 p < 0.001* |
r = -0.14 p = 0.25 |
1 | |||
Cho |
r = -0.05 p = 0.7 |
r = 0.04 p = 0.72 |
r = 0.07 p = 0.58 |
1 | ||
Glx |
r = -0.55 p < 0.001* |
r = 0.09 p = 0.48 |
r = -0.27 p = 0.03* |
r = -0.05 p = 0.68 |
1 | |
MI |
r = -0.59 p < 0.001* |
r = 0.26 p = 0.04* |
r = -0.32 p = 0.01* |
r = 0.03 p = 0.82 |
r = 0.57 p < 0.001* |
1 |
Abbreviations: METH, Methamphetamine; NAA, N-acetyl aspartate; Cho, Choline; Cre, Creatine; Ml, Myo-inositol; Glx, Glutamine plus Glutamate; PANSS; Positive and Negative Syndrome Scale.
Table 3 showed that there was significant reduction in NAA metabolite levels in the METH group correlated with psychotic symptoms (Positive subscale in PANSS test) in the studied areas compared to the controls. Changes in Cho and Glx metabolism and psychological symptoms were associated.
Table 3.
Positive
subscale |
Negative
subscale |
Disorganization
subscale |
Excitement
subscale |
Anxiety/depression
subscale |
Total | |
---|---|---|---|---|---|---|
Dopamine |
r = -0.07 p = 0.67 |
r = -0.12 p = 0.44 |
r = -0.16 p = 0.32 |
r = -0.17 p = 0.29 |
r = -0.19 p = 0.23 |
r = 0.13 p = 0.41 |
Serotonin |
r = 0.23 p = 0.14 |
r = -0.09 p = 0.54 |
r = 0.005 p = 0.97 |
r = 0.05 p = 0.75 |
r = -0.18 p = 0.28 |
r = 0.14 p = 0.38 |
NAA |
r = -0.31 p = 0.04* |
r = 0.07 p = 0.65 |
r = -0.03 p = 0.85 |
r = 0.04 p = 0.77 |
r = 0.06 p = 0.71 |
r = -0.2 p = 0.18 |
Cre |
r = -.08 p = 0.58 |
r = -0.06 p = 0.7 |
r = -0.04 p = 0.98 |
r = -0.006 p = 0.97 |
r = -0.12 p = 0.43 |
r = 0.03 p = 0.86 |
Cho |
r = 0.05 p = 0.76 |
r = 0.37 p = 0.01* |
r = 0.24 p = 0.12 |
r = 0.4 p = 0.008* |
r = 0.19 p = 0.22 |
r = -0.05 p = 0.75 |
Glx |
r = 0.47 p = 0.002* |
r = 0.19 p = 0.22 |
r = 0.08 p = 0.62 |
r = 0.06 p = 0.72 |
r = -0.09 p = 0.56 |
r = 0.19 p = 0.22 |
MI |
r = 0.21 p = 0.18 |
r = 0.01 p = 0.93 |
r = -0.11 p = 0.49 |
r = -0.1 p = 0.52 |
r = -0.03 p = 0.85 |
r = 0.14 p = 0.37 |
Significantly different from controls, Abbreviations: METH, Methamphetamine; NAA, N-acetyl aspartate; Cho, Choline; Cre, Creatine; Glx, Glutamine; Ml, Myo-inositol plus Glutamate; PANSS; Positive and Negative Syndrome Scale.
Table 4 showed there was a negative correlation between NAA changes with duration of use and METH dosage. Changes in the amount of Cho, Glx, and MI with dose and duration of METH use have a positive correlation. Our findings showed there was no significant correlation between Cre and duration of consumption and METH dosage.
Table 4.
NAA | Cho | Cr | Glx | MI | |
---|---|---|---|---|---|
Dose of METH |
r = -0.421 p < 0.007* |
r = 0.482 p < 0.002* |
r = 0.121 p < 0.458 |
r = 0.681 p < 0.0001* |
r = 0.569 p < 0.0001* |
Duration of Use |
r = -0.415 p < 0.008* |
r = 0.351 p < 0.026* |
r = 0.164 p < 0.313 |
r = 0.571 p < 0.0001* |
r = 0.392 p < 0.012* |
Significantly different from controls, Abbreviations: METH, Methamphetamine; NAA, N-acetyl aspartate; Cho, Choline; Cre, Creatine; Ml, Myo-inositol; Glx, Glutamine plus Glutamate.
Discussion
We evaluated long-term METH use impact on brain metabolite concentration in cases who met the DSM-5 criteria regarding METH addiction. Our results showed that subsequent to consumption of METH and continuation of use, neurodegradation extended over various areas of the brain, especially serotonergic and dopaminergic (reward-related circuitry). The major findings obtained from the present study are as follows: (1) METH induced an increase in Dopamine and Serotonin (in urine sample); (2) METH caused elevation in Cre and a reduction in the NAA, Glx, and MI metabolite concentrations of dopamine circuits (PFC, VTA, NAc, Striatum, Substantia nigra, Hippocampus) in METH users compared to control subjects: (3) We found no change in Cho metabolite concentration; (4) A significant correlation was detected between psychological values and neurometabolite concentrations in the studied area of the brain.
Difference in brain metabolites between METH consumers and normal cases has been widely compared through 1HMRS. The associated brain areas were PFC (27, 28), anterior cingulate cortices (ACC) (24, 25), hippocampus, amygdala (32), and basal ganglia (26). The key role of the reward circuit and the mesocorticolimbic circuit in drug use has been demonstrated in literature. However, the 1HMRS assessment of all mentioned brain regions together has obtained less attention.
Our findings, in line with previous studies, showed decreased NAA metabolite concentration in the METH user group (19, 33). Finding abnormally low NAA in the METH users is consistent with the pattern associated with neuronal loss or damage (34). Related psychological findings have also been reported in other studies (29, 35). Another consistent finding was a decrease of Glx in the studied area (27). The effect of METH is associated with dopamine and serotonin as well as other neurotransmitters, including glutamate (36, 37). The decreased Glx may be due to the loss of glutamatergic neurons.
Inconsistent findings include Cre, MI, and Cho levels (5, 16, 19, 38). Our obtained finding was decreased MI which may indicate reduced glial density or function in response to prolonged METH use. However, METH-induced neurotoxicity associated with decreased glial reactivity remains currently unknown (39). We did not detect a significant difference in the Cho level and significantly increased Cre level in METH users than the control group. This inconsistency in some metabolite levels may be due to differences in dosage and duration of METH use (40). Chronic users of METH show elevated levels of Glx, MI, and Cho, and reduced levels of NAA and Cre compared to healthy controls in a variety of cortical regions (18-20, 22, 26, 41, 42). METH-induced psychiatric signs are common, including irritability, anxiety, psychosis, and mood abnormalities (15).
According to previous research, those with chronic METH psychosis and no use of METH, had psychotic symptoms (43). There were no differences in delusion patterns between cases with schizophrenia and chronic psychosis due to METH and auditory hallucinations were the most common type of hallucination (44). Our results also show that there was decline in concentration of NAA and elevation in Glx metabolites consistent with enhancement in positive symptoms (hallucinations, delusions) in METH users. Another study found persistent METH psychosis as well as schizophrenia with same severity and rate, and the two groups obtained significantly higher PANSS scores compared with cases with acute METH psychosis (44). Based on the PANSS scale scores in the current research, it was found that the severity and frequencies of positive symptoms were significantly associated with neurometabolite concentrations than negative manifestations. Negative manifestations, like flat affect, apathy, social isolation, poverty of speech, loss of drive, and anhedonia were found in cases with psychosis due to METH. However, in the present research, no significant association was observed between these symptoms and other variables.
Present findings showed that in the METH group, neurometabolite concentrations were significantly correlated with psychotic symptoms. In the present research, the total PANSS score significantly correlated with abnormal concentration of NAA, Cre, Glx, and MI. Moreover, positive symptoms significantly correlated with lower NAA and high Glx. Also, negative symptoms and excitement correlated with Cho. The present results add to the growing body of literature indicating abnormalities in neurometabolites in particular brain regions correlated with psychiatric symptoms. Liemburg et al. (2016) performed a 1HMRS study and showed that the chronicity of schizophrenia was related to decreased levels of Glx and NAA in PFC (45). In contrast with our results, Callicott et al. (2000) reported lower prefrontal NAA predicted more severe negative symptoms in patients with schizophrenia (46). Patients with untreated psychosis display significant increase in total Cho in the left anterior cingulate and left thalamus (47) and there is correlation between high Cho concentrations in the caudate nucleus in schizophrenic patients (48). Rothermundt et al. (2007) reported schizophrenic patients showed high myo-inositol concentrations (49).
Suggestions for future studies
Both detailed research using resting-state functional connectivity and studies utilizing a task such as cue-associated craving need to extend and deepen our knowledge of the neurobiological bases of drug abuse. Future studies by researchers are suggested to perform more detailed research on brain microstructural abnormalities of METH users with single-voxel spectroscopy and fiber-tract sites of the reward system. They are also recommended to study functional connectivity in the neurocircuitry of the brain in METH users through diffusion tensor imaging (DTI).
Limitation
In terms of study limitations, first, due to the difficulty of access to METH users, the sample size was small and second, sample finding was resolved by assistance of peer user friends.
Conclusion
METH consumption correlates with reduced neuronal integrity and viability, particularly in dopamine pathways (PFC, VTA, Striatum, NAc, Substantia nigra, Hippocampus). There is an association between METH addiction and active neurodegeneration in the dopamine circuit, and it causes serious mental illness. 1HMRS can detect patient’s deterioration and progression of disease as well as follow-up management in patients with METH use disorder.
Acknowledgment
The authors wish to thank all the participants in this project. The paper was extracted from an M.Sc. thesis on Medical Imaging (Shahid Beheshti University of Medical Sciences, Tehran, Iran) and the authors gratefully acknowledge Shahroud University of Medical Sciences for funding this research (Grant No: 9792).
Conflict of Interest
None.
References
- 1.Chen JC, Chen PC, Chiang YC. Molecular mechanisms of psychostimulant addiction. Chang Gung Med J. 2009;32(2):148–54. [PubMed] [Google Scholar]
- 2.World Drug Report 2020. United Nations Office on Drugs and Crime. 2020. [Google Scholar]
- 3.World Drug Report 2019. United Nations Office on Drugs and Crime, 2019 Contract No.: 4. [Google Scholar]
- 4.Chang L, Alicata D, Ernst T, Volkow N. Structural and metabolic brain changes in the striatum associated with methamphetamine abuse. Addiction. 2007;102 (Suppl 1):16–32. doi: 10.1111/j.1360-0443.2006.01782.x. [DOI] [PubMed] [Google Scholar]
- 5.Sung YH, Yurgelun-Todd DA, Shi XF, Kondo DG, Lundberg KJ, McGlade EC, et al. Decreased frontal lobe phosphocreatine levels in methamphetamine users. Drug Alcohol Depend. 2013;129(1-2):102–9. doi: 10.1016/j.drugalcdep.2012.09.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Thomas E, Lategan H, Verster C, Kidd M, Weich L. Methamphetamine-induced psychosis: Clinical features, treatment modalities and outcomes. S Afr J Psychiatr. 2016;22(1):980. doi: 10.4102/sajpsychiatry.v22i1.980. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Cruickshank CC, Dyer KR. A review of the clinical pharmacology of methamphetamine. Addiction. 2009;104(7):1085–99. doi: 10.1111/j.1360-0443.2009.02564.x. [DOI] [PubMed] [Google Scholar]
- 8.Chiu VM, Schenk JO. Mechanism of action of methamphetamine within the catecholamine and serotonin areas of the central nervous system. Curr Drug Abuse Rev. 2012;5(3):227–42. doi: 10.2174/1874473711205030227. [DOI] [PubMed] [Google Scholar]
- 9.Howell LL, Kimmel HL. Monoamine transporters and psychostimulant addiction. Biochem Pharmacol. 2008;75(1):196–217. doi: 10.1016/j.bcp.2007.08.003. [DOI] [PubMed] [Google Scholar]
- 10.Demougeot C, Garnier P, Mossiat C, Bertrand N, Giroud M, Beley A, et al. N-Acetylaspartate, a marker of both cellular dysfunction and neuronal loss: its relevance to studies of acute brain injury. J Neurochem. 2001;77(2):408–15. doi: 10.1046/j.1471-4159.2001.00285.x. [DOI] [PubMed] [Google Scholar]
- 11.Lowe MT, Kim EH, Faull RL, Christie DL, Waldvogel HJ. Dissociated expression of mitochondrial and cytosolic creatine kinases in the human brain: a new perspective on the role of creatine in brain energy metabolism. J Cereb Blood Flow Metab. 2013;33(8):1295–306. doi: 10.1038/jcbfm.2013.84. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Bustillo JR, Chen H, Gasparovic C, Mullins P, Caprihan A, Qualls C, et al. Glutamate as a marker of cognitive function in schizophrenia: a proton spectroscopic imaging study at 4 Tesla. Biol Psychiatry. 2011;69(1):19–27. doi: 10.1016/j.biopsych.2010.08.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.van Waarde A, Elsinga PH. Proliferation markers for the differential diagnosis of tumor and inflammation. Curr Pharm Des. 2008;14(31):3326–339. doi: 10.2174/138161208786549399. [DOI] [PubMed] [Google Scholar]
- 14.Hattingen E, Raab P, Franz K, Zanella FE, Lanfermann H, Pilatus U. Myo-inositol: a marker of reactive astrogliosis in glial tumors? NMR Biomed. 2008;21(3):233–41. doi: 10.1002/nbm.1186. [DOI] [PubMed] [Google Scholar]
- 15.Nordahl TE, Salo R, Leamon M. Neuropsychological effects of chronic methamphetamine use on neurotransmitters and cognition: a review. J Neuropsychiatry Clin Neurosci. 2003;15(3):317–25. doi: 10.1176/jnp.15.3.317. [DOI] [PubMed] [Google Scholar]
- 16.Burger A, Brooks SJ, Stein DJ, Howells FM. The impact of acute and short-term methamphetamine abstinence on brain metabolites: A proton magnetic resonance spectroscopy chemical shift imaging study. Drug Alcohol Depend. 2018;185:226–37. doi: 10.1016/j.drugalcdep.2017.11.029. [DOI] [PubMed] [Google Scholar]
- 17.Howells FM, Uhlmann A, Temmingh H, Sinclair H, Meintjes E, Wilson D, et al. 1H-magnetic resonance spectroscopy (1H-MRS) in methamphetamine dependence and methamphetamine induced psychosis. Schizophr res. 2014;153(1-3):122–8. doi: 10.1016/j.schres.2014.01.029. [DOI] [PubMed] [Google Scholar]
- 18.Ernst T, Chang L. Adaptation of brain glutamate plus glutamine during abstinence from chronic methamphetamine use. J Neuroimmune Pharmacol. 2008;3(3):165–72. doi: 10.1007/s11481-008-9108-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Nordahl TE, Salo R, Possin K, Gibson DR, Flynn N, Leamon M, et al. Low N-acetyl-aspartate and high choline in the anterior cingulum of recently abstinent methamphetamine-dependent subjects: a preliminary proton. MRS study Magnetic resonance spectroscopy. Psychiatry Res. 2002;116(1-2):43–52. doi: 10.1016/s0925-4927(02)00088-4. [DOI] [PubMed] [Google Scholar]
- 20.Nordahl TE, Salo R, Natsuaki Y, Galloway GP, Waters C, Moore CD, et al. Methamphetamine users in sustained abstinence: a proton magnetic resonance spectroscopy study. Arch Gen Psychiatry. 2005;62(4):444–52. doi: 10.1001/archpsyc.62.4.444. [DOI] [PubMed] [Google Scholar]
- 21.Chang L, Munsaka SM, Kraft-Terry S, Ernst T. Magnetic resonance spectroscopy to assess neuroinflammation and neuropathic pain. J Neuroimmune Pharmacol. 2013;8(3):576–93. doi: 10.1007/s11481-013-9460-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Sung YH, Cho SC, Hwang J, Kim SJ, Kim H, Bae S, et al. Relationship between N-acetyl-aspartate in gray and white matter of abstinent methamphetamine abusers and their history of drug abuse: a proton magnetic resonance spectroscopy study. Drug Alcohol Depend. 2007;88(1):28–35. doi: 10.1016/j.drugalcdep.2006.09.011. [DOI] [PubMed] [Google Scholar]
- 23.Yücel M, Lubman DI, Harrison BJ, Fornito A, Allen NB, Wellard RM, et al. A combined spectroscopic and functional MRI investigation of the dorsal anterior cingulate region in opiate addiction. Mol Psychiatry. 2007;12(7):611. doi: 10.1038/sj.mp.4001955. 91-702. [DOI] [PubMed] [Google Scholar]
- 24.Kim JE, Kim GH, Hwang J, Kim JY, Renshaw PF, Yurgelun-Todd DA, et al. Metabolic alterations in the anterior cingulate cortex and related cognitive deficits in late adolescent methamphetamine users. Addict Biol. 2018;23(1):327–36. doi: 10.1111/adb.12473. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Cloak CC, Alicata D, Chang L, Andrews-Shigaki B, Ernst T. Age and sex effects levels of choline compounds in the anterior cingulate cortex of adolescent methamphetamine users. Drug Alcohol Depend. 2011;119(3):207–15. doi: 10.1016/j.drugalcdep.2011.06.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Sekine Y, Minabe Y, Ouchi Y, Takei N, Iyo M, Nakamura K, et al. Association of dopamine transporter loss in the orbitofrontal and dorsolateral prefrontal cortices with methamphetamine-related psychiatric symptoms. Am J Psychiatry. 2003;160(9):1699–701. doi: 10.1176/appi.ajp.160.9.1699. [DOI] [PubMed] [Google Scholar]
- 27.Su H, Chen T, Zhong N, Jiang H, Du J, Xiao K, et al. γ-aminobutyric acid and glutamate/glutamine alterations of the left prefrontal cortex in individuals with methamphetamine use disorder: a combined transcranial magnetic stimulation-magnetic resonance spectroscopy study. Ann Transl Med. 2020;8(6):347. doi: 10.21037/atm.2020.02.95. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Su H, Chen T, Zhong N, Jiang H, Du J, Xiao K, et al. Decreased GABA concentrations in left prefrontal cortex of methamphetamine dependent patients: A proton magnetic resonance spectroscopy study. J Clin Neurosci. 2020;71:15–20. doi: 10.1016/j.jocn.2019.11.021. [DOI] [PubMed] [Google Scholar]
- 29.Mondino M, Brunelin J, Saoud M. N-Acetyl-Aspartate Level is Decreased in the Prefrontal Cortex in Subjects At-Risk for Schizophrenia. Front Psychiatry. 2013;4:99. doi: 10.3389/fpsyt.2013.00099. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Ghamari Givi H, Moulavi P, Heshmati R. Exploration of the factor structure of positive and negative syndrome scale in schizophernia spectrum disorder. J clin psychol. 2010;2(2):1–10. [Google Scholar]
- 31.Opler MGA, Yavorsky C, Daniel DG. Positive and Negative Syndrome Scale (PANSS) Training: Challenges, Solutions, and Future Directions. Innov Clin Neurosci. 2017;14(11-12):77–81. [PMC free article] [PubMed] [Google Scholar]
- 32.Bu Q, Lv L, Yan G, Deng P, Wang Y, Zhou J, et al. NMR-based metabonomic in hippocampus, nucleus accumbens and prefrontal cortex of methamphetamine-sensitized rats. Neurotoxicology. 2013;36:17–23. doi: 10.1016/j.neuro.2013.02.007. [DOI] [PubMed] [Google Scholar]
- 33.Grachev ID, Kumar R, Ramachandran TS, Szeverenyi NM. Cognitive interference is associated with neuronal marker N-acetyl aspartate in the anterior cingulate cortex: an in vivo (1)H-MRS study of the Stroop Color-Word task. Mol Psychiatry. 2001;6(5):496. doi: 10.1038/sj.mp.4000940. 529-39. [DOI] [PubMed] [Google Scholar]
- 34.Ariyannur PS, Moffett JR, Manickam P, Pattabiraman N, Arun P, Nitta A, et al. Methamphetamine-induced neuronal protein NAT8L is the NAA biosynthetic enzyme: implications for specialized acetyl coenzyme A metabolism in the CNS. Brain Res. 2010;1335:1–13. doi: 10.1016/j.brainres.2010.04.008. [DOI] [PubMed] [Google Scholar]
- 35.London ED, Kohno M, Morales AM, Ballard ME. Chronic methamphetamine abuse and corticostriatal deficits revealed by neuroimaging. Brain Res. 2015;1628(Pt A):174–85. doi: 10.1016/j.brainres.2014.10.044. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Almalki AH, Das SC, Alshehri FS, Althobaiti YS, Sari Y. Effects of sequential exposure to ethanol and methamphetamine on tissue contents of dopamine, serotonin and glutamate in Wistar rats. Neurosci Lett. 2018;665:61–66. doi: 10.1016/j.neulet.2017.11.043. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Althobaiti YS, Almalki AH, Das SC, Alshehri FS, Sari Y. Effects of repeated high-dose methamphetamine and ceftriaxone post-treatments on tissue content of dopamine and serotonin as well as glutamate and glutamine. Neurosci Lett. 2016;634:25–31. doi: 10.1016/j.neulet.2016.09.058. [DOI] [PubMed] [Google Scholar]
- 38.Wu Q, Qi C, Long J, Liao Y, Wang X, Xie A, et al. Metabolites Alterations in the Medial Prefrontal Cortex of Methamphetamine Users in Abstinence: A (1)H MRS Study. Front Psychiatry. 2018;9:478. doi: 10.3389/fpsyt.2018.00478. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Friend DM, Keefe KA. Glial reactivity in resistance to methamphetamine-induced neurotoxicity. J Neurochem. 2013;125(4):566–74. doi: 10.1111/jnc.12201. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Kim YT, Lee SW, Kwon DH, Seo JH, Ahn BC, Lee J. Dose-dependent frontal hypometabolism on FDG-PET in methamphetamine abusers. J Psychiatr Res. 2009;43(14):1166–70. doi: 10.1016/j.jpsychires.2009.03.011. [DOI] [PubMed] [Google Scholar]
- 41.Ernst T, Chang L, Leonido-Yee M, Speck O. Evidence for long-term neurotoxicity associated with methamphetamine abuse: A 1H MRS study. Neurology. 2000;54(6):1344–9. doi: 10.1212/wnl.54.6.1344. [DOI] [PubMed] [Google Scholar]
- 42.Rae CD. A guide to the metabolic pathways and function of metabolites observed in human brain 1H magnetic resonance spectra. Neurochem Res. 2014;39(1):1–36. doi: 10.1007/s11064-013-1199-5. [DOI] [PubMed] [Google Scholar]
- 43.Akiyama K, Saito A, Shimoda K. Chronic methamphetamine psychosis after long-term abstinence in Japanese incarcerated patients. Am J Addict. 2011;20(3):240–9. doi: 10.1111/j.1521-0391.2011.00124.x. [DOI] [PubMed] [Google Scholar]
- 44.Wearne TA, Cornish JL. A Comparison of Methamphetamine-Induced Psychosis and Schizophrenia: A Review of Positive, Negative, and Cognitive Symptomatology. Front Psychiatry. 2018;9:491. doi: 10.3389/fpsyt.2018.00491. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Liemburg E, Sibeijn-Kuiper A, Bais L, Pijnenborg G, Knegtering H, van der Velde J, et al. Prefrontal NAA and Glx Levels in Different Stages of Psychotic Disorders: a 3T 1H-MRS Study. Sci Rep. 2016;6:21873. doi: 10.1038/srep21873. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Callicott JH, Bertolino A, Egan MF, Mattay VS, Langheim FJ, Weinberger DR. Selective relationship between prefrontal N-acetylaspartate measures and negative symptoms in schizophrenia. Am J Psychiatry. 2000;157(10):1646–51. doi: 10.1176/appi.ajp.157.10.1646. [DOI] [PubMed] [Google Scholar]
- 47.Théberge J, Al-Semaan Y, Drost DJ, Malla AK, Neufeld RW, Bartha R, et al. Duration of untreated psychosis vs. N-acetylaspartate and choline in first episode schizophrenia: a 1H magnetic resonance spectroscopy study at 4.0 Tesla. Psychiatry Res. 2004;131(2):107–14. doi: 10.1016/j.pscychresns.2004.04.002. [DOI] [PubMed] [Google Scholar]
- 48.Juan R, Bustillo M D, Laura M, Rowland M A, John Lauriello M D, Helen Petropoulos B E, Roger Hammond M D, Blaine Hart M D, et al. High Choline Concentrations in the Caudate Nucleus in Antipsychotic-Naive Patients With Schizophrenia. Am J Psychiatry. 2002;159(1):130–3. doi: 10.1176/appi.ajp.159.1.130. PubMed PMID: 11772701. [DOI] [PubMed] [Google Scholar]
- 49.Rothermundt M, Ohrmann P, Abel S, Siegmund A, Pedersen A, Ponath G, et al. Glial cell activation in a subgroup of patients with schizophrenia indicated by increased S100B serum concentrations and elevated myo-inositol. Prog Neuropsychopharmacol Biol Psychiatry. 2007;31(2):361–4. doi: 10.1016/j.pnpbp.2006.09.013. [DOI] [PubMed] [Google Scholar]