Edited by: Feng Liu, Tianjin Medical University General Hospital, China
Reviewed by: Gabriele Ende, Zentralinstitut für Seelische Gesundheit (ZI), Germany; Jeffrey A. Stanley, Wayne State University School of Medicine, United States
This article was submitted to Neuroimaging and Stimulation, a section of the journal Frontiers in Psychiatry
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Methamphetamine is one of the most consumed amphetamine-type stimulants (ATS) worldwide. According to the World Drug Report 2017 (
1H magnetic resonance spectroscopy (1H MRS) provides an invasive method to explore the metabolites in the brain. Previous 1H MRS research on MA dependent (MAD) subjects shows alterations in n-acetyl-aspartate (NAA) (
The mPFC is a terminal region of the mesocorticolimbic dopamine system which has been reported to modulate reward seeking behavior (
The data were collected as a part of the brain imaging study on methamphetamine-induced psychotic symptoms, a study hosted at the Second Xiangya Hospital of Central South University. One hundred and twenty-six subjects (61 MAD subjects and 65 drug-free healthy subjects, age 19–45) were enrolled in this study. Subjects between 18 and 45 years were entitled to participate in the study. MAD volunteers were recruited from The Kangda Voluntary Drug Rehabilitation Centers in Hunan Province. All MA users fulfiled the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) criteria (
Demographics of participants and MA use variables in MRS study.
Age (range) | 29.0 ± 5.8 (19–40) | 30.0 ± 6.1 (21–45) | 0.38 |
Gender(female/male) | 54/7 | 53/12 | 0.33 |
Education(years) | 11.5 ± 2.9 | 12.4 ± 2.6 | 0.07 |
BMI | 24.0 ± 3.2 | 22.8 ± 3.2 | 0.08 |
CPD | 20 (10, 20) | 16 (5, 20) | < 0.01 |
BDI Score | 11.0 ± 7.8 | 4 (0, 8) | < 0.01 |
Total AI Score | 75.6 ± 16.0 | 71.5 ± 16.7 | 0.17 |
STAI-Y1 | 35.0 ± 8.0 | 33.5 ± 9.9 | 0.37 |
STAI-Y2 | 40.6 ± 9.9 | 38.0 ± 8.8 | 0.12 |
Age started using MA (years old) | 23.9 ± 5.7 | ||
Duration of MA use (months) | 51.2 ± 26.8 | ||
Abstinence from using MA(days) | 42.7 ± 20.9 |
Structural MRI and MRS data were acquired with a Siemens Magnetom Trio 3.0 T MR scanner (Siemens, Erlangen, Germany) using an eight-channel standard quadrature headcoil at the Magnetic Resonance Center of Hunan provincial People's Hospital, China. Three-dimensional T1-weighted images were collected using a gradient echo sequence (repetition time = 2,000 ms, echo time = 2.26 ms, field of view = 256 × 256 mm, flip angle = 8°, matrix size = 256 × 256, number of slices = 176, slice thickness = 1 mm). Using these images, a single 1H MRS voxel was placed on the corpus callosumand centered on the intrahemispheric fissure, including medial superior frontal gyrus and anterior cingulate cortices, not containing the orbitofrontal cortex (see Figure
Region of interest in medial prefrontal cortex in coronal, sagittal and transverse views.
1H MRS spectra were automatically fit with linear combination model (LCModel version 6.3–1B [LCMODEL Inc. CA (
1H MRS data.Spectra of the unfiltered data superimposed with the LCModel fit.
Segmentation was performed on T1-weighted images using New Segment+DARTEL in Data Processing & Analysis of Brain Imaging (
Tissue fraction of the region of interest in the mPFC.
Gray matter fraction | 0.44 ± 0.08 | 0.46 ± 0.01 | 0.06 |
White matter fraction | 0.30 ± 0.06 | 0.32 ± 0.02 | 0.10 |
CSF fraction | 0.23 ± 0.05 | 0.23 ± 0.01 | 0.85 |
Statistical analysis was performed with SPSS 20 (IBM Inc. New York, USA). Assumption of normality of each variable was tested with the Shapiro–Wilk test. Because of non-normality of the data, CPD and BDI scores were compared using a Mann-Whitney U test, and gender with Chi-square test for independence. Metabolite concentrations were reported as mean ± standard deviation. General Linear Model multivariate analysis was used to evaluate group differences in metabolite ratios controlling for CPD and gray matter tissue fraction in the voxle. Correlation analyses between metabolite ratios and each of clinical parameters, including age, months of MA use, days of abstinence, age of onset of MA use, CPD, BDI, total STAI scores, STAI-Y1 score, and STAI-Y2 score were performed using Pearson's or Spearman's correlation analysis, followed by Bonferroni test. Statistical significance was defined at
The groups did not differ in gender, mean age, BMI, or years of education (Table
Segmentation indicates the fractional contribution of gray matter, white matter and CSF in the MAD group = 44% gray, 30% white and 23% CSF and in healthy control group = 46% gray, 32% white and 23% CSF. No differences in the fractions of gray (
There was no difference between the MAD group and control group in FWHM (
FWHM, S/N, and CRLB values between MAD subjects (n = 61) and healthy controls (
FWHM(ppm) | 0.05 (0.05, 0.06) | 0.06 (0.048, 0.067) | 0.23 |
S/N | 28.85 ± 5.01 | 37.91 ± 7.96 | < 0.01 |
CRLB values for NAA | 0.03 (0.03, 0.04) | 0.02 (0.02, 0.03) | < 0.01 |
CRLB values for mI | 0.04 (0.03, 0.04) | 0.03 (0.03, 0.04) | < 0.01 |
CRLB values for GPC+PC | 0.02 (0.02, 0.03) | 0.02 (0.02, 0.02) | 0.12 |
CRLB values for Glu | 0.06 (0.05, 0.06) | 0.05 (0.05, 0.06) | < 0.01 |
The MAD group and control group did not differ significantly in absolute PCr+Cr values (mean = 6.47 vs. 6.58,
Metabolite concentrations in the mPFC of MAD subjects (
PCr+Cr | 6.47 ± 0.83 | 6.58 ± 0.70 | 0.44 |
NAA/PCr+Cr | 1.12 ± 0.08 | 1.17 ± 0.07 | 0.01 |
mI//PCr+Cr | 0.85 ± 0.09 | 0.80 ± 0.09 | < 0.01 |
GPC+PC/PCr+Cr | 0.27 ± 0.03 | 0.27 ± 0.03 | 0.78 |
Glu/PCr+Cr | 1.03 ± 0.15 | 0.95 ± 0.14 | < 0.01 |
For the MA users, there were no significant correlation between ratios of metabolites and MA use variables. There were no significant correlation between age, CPD and metabolite ratios.
There was no significant difference in PCr+Cr levels between MAD group and control group, so the differences in NAA/PCr+Cr, mI/PCr+Cr, and Glu/PCr+Cr between groups are probably due to the differences in NAA, mI and Glu levels between groups. The first finding of the present study is that the NAA/PCr+Cr ratio was increased in the mPFC of MAD subjects. Finding the decreased ratio of NAA/PCr+Cr among MAD subjects is consistent with previous studies (
The second finding is that the ratio of mI/PCr+Cr was significantly increased in the mPFC of MAD subjects compared with healthy controls. The increased ratio of mI/PCr+Cr in MAD group is in line with previous studies, which were reported in frontal gray matter and white matter of MA users (
The final finding is a significant increase in ratios of Glu/PCr+Cr in the mPFC of MAD subjects. The most consistent alteration across MA abuse was reduction in NAA, while change in Glu was inconsistent. Glx and Glu were reported to be lower in the mPFC (
This is a relatively large sample study to report of increased ratio of Glu/PCr+Cr in the mPFC among MAD subjects, although preclinical studies have found such findings (
In the research conducted by Sailasuta et al., around 36% of normal glial tricarboxylic acid (TCA) cycle rate was significant reduced in frontal brain of abstinent MA abusers, which may impact the glutamate-glutamine cyle and thus result in accumulation of Glu (
Furthermore, the increased extracellular Glu concentration is considered as an important factor of relapse. Glutamateric signal system plays an important role in drug-seeking behavior. It has been reported that the activation of Glu transporter (
This study has several limitations. First, most of subjects in this study were men, making it impossible to explore the influence of gender confidently. Second, the characteristics of MAD subjects in this study, including the range of duration of MA use and abstinence, and the drug used in the abstinence would be possible confounding factors. Third, the study is cross-sectional, it is unclear whether alterations in these metabolites would reverse completely during continued abstinence or would persist. Furthermore, MAD subjects had a higher CPD than the controls, and this difference was significant. We noted this difference, controlled this covariate in statistical analysis process and discussed their possible impacts on our MRS results. We concluded that this difference in CPD between the MAD subjects and healthy controls is unlikely to be the reason for the statistically significant alterations of metabolites of the mPFC. Our study is a relatively large sample and we controlled the cigarette smoking when comparing the metabolites. Finally, there were significant differences between MAD subjects and controls in the S/N ratios and CRLB values. But the S/N ratios and CRLB values in both groups characterize relatively good quality of our data. Future studies should include more women MAD subjects, measure alterations longitudinally when MAD subjects using MA (if possible), at the beginning of abstinence, and after longer duration (6–24 months) of abstinence, and match subjects' cigarette smoking.
Our findings suggest that the alterations in ratios of Glu/PCr+Cr of the mPFC may underlie the pathophysiology of neurological injury in MA abuse. MA cause the Glu concentration elevation, which has neurotoxicity and may lead to NAA concentration decreased and mI increased. This study implicates that Glu plays an important role in MA dependent disorder, reducing Glu concentration or increasing the activity of Glu receptors in the mPFC may be of great clinical significance in the treatment.
YL, JT, JLi, and TL contributed conception and design of the study. QW, CQ, and AX organized the database. QW performed the statistical analysis and wrote the first draft of the manuscript. JLo, YL, XW, YT, and JT revised the manuscript. TL, BY and WH advised on the statistical analysis, interpretation of findings, and reviewed drafts of the manuscript.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We acknowledge all the professionals in Kangda Voluntary Drug Rehabilitation Centers who helped a lot in data collection. The authors thank all the subjects who participated in this study.