Increase of α-Synuclein in the Peripheral Blood of Subjects with Methamphetamine Use Disorder

Abstract

Objective

Methamphetamine (MA) use has created significant public health problems worldwide. Its chronic abuse causes neurotoxicity resulting in disruption of neural plasticity and early onset of neurodegenerative diseases. Therefore, there is need for a biomarker to evaluate the neurotoxicity caused by MA. This study investigates the expression levels of α-synuclein (α-Syn), brain-derived neurotrophic factor (BDNF), and neuron-specific enolase (NSE) in the blood of patients with MA use disorder to identify potential biomarkers.

Methods

We collected blood samples from 60 subjects (30 normal healthy controls and 30 patients with MA use disorder [MA group]). We used multiplex assay kits to analyze the expression levels of α-Syn, BDNF, and NSE in the blood of these subjects.

Results

Beck Depression Inventory and Beck Anxiety Inventory scale scores were significantly different between the control and MA groups. The expression level of α-Syn in the MA group was significantly increased compared to that in the control group (z value=-1.986, p=0.0473). In contrast, BDNF in the MA group tended to increase as the duration of MA use increased (r=0.323, p=0.082).

Conclusion

We identified an increase of α-Syn in the blood of the MA group. This finding suggests that the α-Syn level increases in the brain after exposure to MA by passing through the blood brain barrier. This result provides useful information for potential biomarkers in diagnosis of neurodegenerative diseases caused by MA abuse.

INTRODUCTION

Methamphetamine (MA) use has created significant public health problems worldwide. It is a psychostimulant that users are prone to abuse because it can be easily synthesized using drugs such as ephedrine and pseudo-ephedrine, which are the raw materials for over-the-counter cold medicines [1]. Acute MA exposure excites the sympathetic nervous system and induces euphoria, enhanced energy, alertness, and libido [2,3]. In contrast, chronic MA exposure can not only induce personality changes such as delusions, violence, and psychotic behavior, but also pulmonary hypertension, stroke, myocardial infarction, and neurocognitive impairments [4,5]. Chronic MA abuse also disrupts neural plasticity and causes neurodegenerative diseases such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) [6,7]. Therefore, it is important to identify biomarkers that can be used in the diagnosis and treatment of diseases/impairments caused by MA.

α-synuclein (α-Syn) is a presynaptic protein that is enriched in dopaminergic neurons in the brain and participates in exocytosis, vesicle trafficking, neurotransmitter packing, and regulation of dopamine release [8,9]. Overexpression or aggregation of α-Syn leads to the formation of Lewy bodies, which are intracellular inclusions implicated in the development or progression of PD [10]. Recently, several studies have demonstrated that chronic MA use leads to an increase in the α-Syn level in the brain of MA users and animal models [11-13]. MA not only induces α-Syn accumulation in neurons by dysregulating the ubiquitin-proteasome system and molecular chaperone autophagy but also promotes α-Syn phosphorylation, contributing to neurotoxicity and PD-like pathological changes [14-16]. Beyond its well-established role in PD, α-Syn dysregulation has also been implicated in psychiatric disorders. Elevated serum levels of α-Syn have been reported in patients with major depression disorder, suggesting a potential link between α-Syn and depression [17]. Furthermore, α-Syn accumulation in serotonergic neurons has been associated with mood and emotional disturbances, mirroring neuropsychiatric symptoms observed in PD [18]. These findings suggest that α-Syn dysregulation may contribute to the pathophysiology of certain psychiatric conditions, further emphasizing the need to investigate its role in MA-induced neurotoxicity and psychiatric comorbidities.

Brain-derived neurotrophic factor (BDNF), a neurotrophin, plays an important role in synaptic connectivity and regulation of neuronal outgrowth, differentiation, repair, and survival [19,20]. A decrease in BDNF has been reported to affect the pathology of spinal cord injuries and neurodegenerative diseases including AD and PD [21]. Previous studies have reported that BDNF is involved in substance addiction, including to drugs and alcohol [22-24]. According to a meta-analysis by Ornell et al. [25], people actively using substances such as alcohol and cocaine have a lower level of BDNF in the blood compared to those who are not using such substances. Therefore, a change in the blood level of BDNF in patients with drug dependence (including MA) can be a sign of drug addiction or symptoms of neurodegenerative diseases induced by drug addiction.

Neuron-specific enolase (NSE, γ-enolase), which is predominantly found in the cytoplasm of neurons in the central nervous system (CNS), regulates neuronal glycolysis and is involved in cell survival, energy metabolism, and neuroplastic pathways [26,27]. Two prior studies found that the expression level of NSE was altered in the brains of addictive drug users [28,29]. MA exposure to mesencephalic cultures and monkeys induced a decrease in NSE in both the cultures and hippocampi of the monkeys [30,31]. On the contrary, elevated serum NSE levels have been observed in certain neuropsychiatric conditions among adolescents, such as post-traumatic stress disorder (PTSD) and attention-deficit hyperactivity disorder (ADHD). Adolescents with PTSD exhibited significantly higher NSE levels compared to those with major depressive disorder and healthy controls [32]. Similarly, adolescents with internet addiction comorbid with ADHD or anxiety disorders have been reported to show increased plasma NSE concentrations, suggesting underlying neuronal injury in these populations [33]. Conversely, a study that analyzed cerebrospinal fluid (CSF) and serum of patients with schizophrenia did not find significant elevations, indicating that NSE alterations may not serve as a universal marker across all psychiatric disorders [34]. Therefore, further evaluation of serum NSE in patients with MA use disorder is necessary to explore its potential as a biomarker.

Some studies have shown that the neurotoxic effects of MA induce structural and functional impairments in the blood-brain barrier (BBB) [35,36]. The BBB is an important structure that regulates the homeostasis of the brain microenvironment. The BBB protects the CNS by restricting the free movement of substances between the CNS and blood [37]. Therefore, disruption of the BBB caused by MA neurotoxicity may allow pathogenic agents (e.g., inflammatory factors and virus) to enter the CNS and growth factors and cytokines produced in the brain to enter the bloodstream [38]. On the basis of these prior studies, we hypothesized that expression changes of α-Syn, BDNF, and NSE in the brain due to MA abuse would affect their concentrations in the blood. We measured these concentrations in the blood and confirmed that secretion of α-Syn increased with MA abuse. Therefore, it is possible that α-Syn could be used as a biomarker to diagnose MA abuse.

METHODS

Participants

We recruited subjects who were addicted to MA (n=30) and normal (n=30) subjects from Eulgi University Gangnam Eulgi Hospital, Incheon Chamsarang Hospital, and Seoul St. Mary’s Hospital. The participants were females and male adults aged 18 years or older. The patients with MA use disorder, who were recruited from Eulgi University Gangnam Eulgi Hospital and Incheon Chamsarang Hospital met the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) diagnostic criteria for severe MA use order. All patients had undergone withdrawal for 1 to 2 weeks prior to participation. Individuals with an axis I psychiatric disorder (including other substance use disorder except nicotine), those unable to communicate adequately, or those with a Global Assessment of Functioning scale score below 45 were excluded. All participants in both the MA and control groups were confirmed to be free of any medication use (including type, dose, and duration) at the time of blood collection to eliminate potential confounding effects of medication on biomarker levels. The normal control group was recruited from individuals who visited the smoking cessation clinic at Seoul St. Mary’s Hospital. The inclusion criteria for the control group were as follows: 1) no lifetime or current diagnosis of psychotic disorders, mood disorders, or organic mental disorders, as determined by structured clinical interviews based on the DSM-5 criteria; 2) no history of exposure to amphetamine-type stimulants, including MA, for non-medical purposes. The exclusion criteria for the control group were as follows: 1) a history or symptoms of epilepsy or seizure disorder, or if there were findings suggestive of epilepsy on electroencephalography examination; 2) diagnosis of a neurodegenerative disease such as AD, PD, Huntington’s disease, or Lewy body dementia (not including drug-induced cognitive dysfunction); 3) presence of a serious internal or surgical disease; 4) pregnant or lactating status; and 5) judgement of unsuitability for this experiment by a psychiatrist. To minimize potential biases and enhance comparability, we matched the control and MA groups for age and sex. All subjects provided informed written consent for this study. The study was approved by the Institutional Review Board of The Catholic University of Korea, Seoul St. Mary’s Hospital (IRB No. KC17TNSI0253).

Measurements

Demographic information

Participants recorded their sex, age, years of education, socioeconomic status, and drug use history.

Beck Anxiety Inventory

The frequency of anxiety symptoms was measured using the Beck Anxiety Inventory (BAI) scale [39].

Beck Depression Inventory

The Beck Depression Inventory (BDI) was used to evaluate the risk of depression and the severity of depressive symptoms [40].

Blood collection and immunoassay

Blood samples were collected from the participants and centrifuged at 1,000×g for 20 minutes. The upper phase containing serum was transferred into a fresh tube and stored at -80°C until used for the immunoassay. BDNF, NSE, and α-Syn were analyzed using bead-based multiplex assay kits. This multiplex assay is advantageous in that it can analyze multiple proteins simultaneously and requires small volume samples. The secretion levels of BDNF, NSE, and α-Syn were analyzed with Human Magnetic Luminex assay kits (BDNF, LXSAHM-01; NSE, and α-Syn, LXSAHM-02) (R&D Systems). Before the immunoassay, the serum samples were diluted in assay buffer 1:50 for BDNF and 1:2 for NSE and α-Syn. After 50 μL of the microparticle cocktail was added into each well of the plate, 50 μL of standard or the diluted sample was added into each well. The plate was incubated at room temperature (RT) for 2 hours, and the liquid was removed after applying a magnet to the bottom of the plate. Next, each well of the plate was washed three times using 100 μL of wash buffer. After 50 μL of diluted biotin antibody cocktail was added into each well, the plate was covered with foil (to protect it from light) and incubated at RT for 1 hour. The plate was washed three times with 100 μL of wash buffer, combined with 50 μL of streptavidin-phycoerythrin, covered with foil, and incubated at RT for 30 minutes. After washing three times with 100 μL of wash buffer, another 100 μL of wash buffer was added to each well, and the absorbance of the plate was analyzed on the Luminex 200TM (EMD Millipore).

Statistical analysis

Statistical analyses were conducted with SPSS 18.0 software (SPSS Inc.) and GraphPad Prism 9 software (GraphPad). To compare demographic variables, clinical variables, and the three protein expression levels between the control and MA groups, unpaired t-tests were used for normally distributed variables, while Mann–Whitney U tests were applied for nonparametric variables. Normality was assessed using both the Kolmogorov–Smirnov test and the Shapiro–Wilk test, considering the small sample size (n=30 per group). For normally distributed data, results were presented as mean±SD, and for nonparametric data, they were reported as median and interquartile range. Correlations between the duration of MA use and expression levels of each protein in the MA group were performed by Spearman’s correlation analysis. In addition, simple linear regression analysis was conducted to further explore the association between the duration of MA use and expression levels of each protein. p<0.05 was considered statistically significant.

RESULTS

Demographic and clinical characteristics

The sociodemographic and clinical characteristics of the participants are presented in Table 1. There was no significant difference between the control and MA groups in age, sex, or smoking. However, the total years of education and socioeconomic status were both significantly higher in the control group than in the MA group (p<0.001). In addition, there was a significant difference in alcohol use between the two groups (p<0.001). The majority of the control group (96.7%) reported alcohol use, whereas only 53.3% of the MA group reported alcohol use. This discrepancy may be attributed to behavioral changes related to substance use patterns or differences in self-reported alcohol consumption due to MA-related lifestyle factors. Furthermore, there were significant differences in the BDI and BAI scores (p<0.001) between the control and MA groups.

Table 1.

Demographic and clinical characteristics of participants

Characteristic	Control (N=30)	MA (N=30)	p-value
Age (yr)	35.4±7.9	39.5±9.6	0.074
Sex			0.197
Male	29 (96.7)	25 (83.3)
Female	1 (3.3)	5 (16.7)
Total education (yr)	16.2±2.3	12.2±3.4	0.000***
Socioeconomic status			0.000***
High	3 (10.0)	0 (0.0)
Middle	25 (83.3)	16 (53.3)
Low	2 (6.7)	14 (46.7)
Smoking			0.052
Yes	30 (100)	25 (83.3)
No	0 (0.0)	5 (16.7)
Alcohol			0.000***
Yes	29 (96.7)	16 (53.3)
No	1 (3.3)	14 (46.7)
BAI scale	3.2±3.1	21.6±16.2	0.000***
BDI scale	4.2±4.1	21.6±14.4	0.000***

Data are presented as mean±standard deviation or number (%).

^***p<0.001.

MA, methamphetamine; BAI, Beck Anxiety Inventory; BDI, Beck Depression Inventory

Secretion levels of α-Syn, BDNF, and NSE

To investigate whether neural plasticity and neurological disease-related proteins were associated with MA use disorder, we analyzed the expression levels of α-Syn, BDNF, and NSE in the peripheral blood of the control and MA groups. Before analyzing protein expression differences between groups, outliers in protein expression of samples within each group were identified and removed. To assess the normality of protein expression levels, Q-Q plots and histograms were examined (Figure 1). α-Syn expression deviated significantly from normality in the control group (Shapiro–Wilk W=0.9006, p=0.0102; Kolmogorov–Smirnov KS distance=0.1827, p=0.0144), while the MA group conformed to a normal distribution (Shapiro–Wilk W=0.9468, p=0.1384). BDNF exhibited normality in both groups (Shapiro–Wilk W=0.9466, p=0.1373 for control; W=0.9575, p=0.2665 for MA). In contrast, NSE showed significant deviations in both groups (Shapiro–Wilk W=0.8832, p=0.0040 for control; W=0.6387, p<0.0001 for MA). Given these findings, nonparametric tests were used for α-Syn and NSE, while an unpaired t-test was applied for BDNF. The expression level of α-Syn was significantly higher in the MA (963.69±365.72 pg/mL) group than in the control (775.58±199.74 pg/mL) group (z value=-1.986, p=0.0473) (Figure 2A). In contrast, the BDNF level did not differ between two groups (t=0.2763, df=58, p=0.7833) (Figure 2B), with a mean difference of 0.5918±2.142 ng/mL (95% confidence interval [CI]: -3.696 to 4.880). The variance between groups was not significant (F=1.110, p=0.7802). The NSE expression level was comparable between the control (14.87±7.75 ng/mL) and MA (16.56±13.33 ng/mL) groups (z value=-0.319, p=0.757) (Figure 2C).

Figure 1.

O-Q plots and histograms for α-Syn, BDNF, and NSE distributions. A-C: Q-Q plots for α-Syn, BDNF, and NSE comparing sample quantiles to theoretical normal quantiles. The red diagonal line represents the expected normal distribution and deviations indicate departures from normality in each protein’s expression levels. D-F: Histograms with density plots for α-Syn, BDNF, and NSE showing the distribution of expression levels in the Control (blue) and MA (red) groups. The density curves provide a smoothed representation of the data, highlighting differences between groups. α-Syn, α-synuclein; BDNF, brain-derived neurotrophic factor; NSE, neuron-specific enolase; MA, methamphetamine.

Figure 2.

Expression levels of proteins in the blood of normal controls (control) and patients with MA dependence. A: Comparison of the expression level of α-Syn between control (N=29) and MA (N=30) groups. B: Comparison of the expression level of BDNF between control (N=30) and MA (N=30) groups. C: Comparison of the expression level of NSE between control (N=29) and MA (N=28) groups. ^*p<0.05. α-Syn, α-synuclein; BDNF, brain-derived neurotrophic factor; NSE, neuron-specific enolase; MA, methamphetamine.

Correlation of α-Syn, BDNF, or NSE protein level and duration of MA use

We examined the correlation between the duration of MA use and the expression levels of each target protein. The duration of MA use in the MA group was not correlated with the concentration of α-Syn (r=0.074, p=0.698) (Figure 3A). In addition, comparison of α-Syn levels between short-term (≤5 years) and long-term (>5 years) MA use in the MA group showed no significantly difference (t=0.7079, df=28, p=0.4849) (Figure 3D). The mean α-Syn concentration was 912.7±105.42 pg/mL in the short-term use of MA group and 1,008±86.30 pg/mL in the long-term use of MA group, with a mean difference of -95.57±135.0 pg/mL (95% CI: -372.1 to 181.0). The effect size was small (η²=0.01758), suggesting that the duration of MA use has minimal influence on α-Syn levels. Duration of MA use and BDNF concentration in the MA group tended to be positively correlated but was not significant (r=0.323, p=0.082) (Figure 3B). Comparison of BDNF levels between short-term and long-term MA use revealed a statistically significant difference (t=2.518, df=28, p=0.0178) (Figure 3E). The mean BDNF concentration was significantly higher in long-term MA use group (30.61±2.25 ng/mL) compared to short-term MA use group (23.41±1.65 ng/mL), with a mean difference of 7.207±2.862 ng/mL (95% CI: 1.344 to 13.07). The effect size was large (η²=0.1847), suggesting that prolonged MA use may influence BDNF expression. Variance between the groups was not significantly different (F=2.125, p=0.1798), confirming the validity of the t-test results. In contrast, NSE concentration exhibited a negative correlation trend with the duration of MA use; however, this relationship was not statistically significant (r=-0.300, p=0.121) (Figure 3C). Furthermore, comparison of NSE levels between short-term and long-term MA use showed no significant difference in both parametric and nonparametric analyses. The unpaired t-test indicated a trend toward lower NSE levels in long-term use of MA group (12.37±0.97 ng/mL) compared to short-term use of MA group (20.75±4.76 ng/mL), but the difference was not significant (t=1.723, df=26, p=0.0967) (Figure 3F). Due to the violation of the equal variance assumption (F=24.19, p<0.0001), a Mann-Whitney U test was conducted, which similarly showed no significant difference (p=0.3064, U=75). These results suggest that NSE levels are not strongly influenced by MA use duration.

Figure 3.

Correlation between protein expression and MA use duration in patients with MA use disorder and group-wise comparison of protein levels. A: Correlation of α-Syn expression with MA use duration (N=30). B: Correlation of BDNF expression with MA use duration (N=30). C: Correlation of NSE expression with MA use duration (N=28). The black dashed lines represent the 95% confidence interval for the regression model. D: Estimation plot comparing α-Syn levels between patients with MA use disorder with short-term (≤5 years, N=14) and long-term (>5 years, N=16) MA use. E: Estimation plot comparing BDNF levels between patients with MA use disorder with short-term (≤5 years, N=14) and long-term (>5 years, N=16) MA use. F: Estimation plot comparing NSE levels between patients with MA use disorder with short-term (≤5 years, N=14) and long-term (>5 years, N=14) MA use. ^*p<0.05. α-Syn, α-synuclein; BDNF, brain-derived neurotrophic factor; NSE, neuron-specific enolase; MA, methamphetamine.

DISCUSSION

MA abuse not only disrupts neurotransmitter systems, but also causes neurotoxicity in the brain. In addition, neurotoxicity caused by chronic MA use triggers neurocognitive impairments, leading to the onset of neurodegenerative diseases such as AD and PD. Therefore, it would be very useful if there were blood biomarkers that could identify brain impairments in patients with MA use disorder. In the present study, we investigated the expression levels of three proteins in the blood of patients with MA use disorder to evaluate their utility as biomarkers.

Previous studies have reported that substance use and withdrawal often accompany symptoms of depression [41-43]. According to a self-report, MA users experience psychological symptoms such as anxiety, depression, and suicidal thoughts [41,44]. A previous study found that depression was the most common psychiatric symptom of amphetamine users in Australia [45]. More recently, in a study of subjects experiencing early MA withdrawal (abstinence for 1–7 days), depression was significantly correlated with anxiety [46]. This result demonstrates that MA use induces both depression and anxiety. We similarly found that depression and anxiety symptoms in the MA group (abstinence within 2 weeks) were five times higher than in the control group. Our findings are meaningful because depression and anxiety were compared between the control and MA groups, unlike other research teams that only studied MA-dependent patients [46,47]. Our results also suggest that MA users continue to suffer from depression and anxiety even during initial MA withdrawal. In addition, we observed a significantly lower rate of alcohol use in the MA group compared to the control group. This result may be related to lifestyle changes or behavioral adaptations associated with chronic MA use. MA users may avoid alcohol consumption due to interactions or undesirable combined effects with MA, reflecting a distinct substance-use pattern compared to the general population. However, this discrepancy could also reflect underreporting or variations in the reliability of self-reported alcohol use among individuals with substance abuse disorders. Future studies are warranted to further investigate the impact of concurrent alcohol use on biomarker levels in patients with MA use disorder.

In this study, the α-Syn level was significantly increased in the blood of patients with MA use disorder. Dopaminergic neurons are the main source of α-Syn, which plays a pivotal role in the development or progression of PD through the formation of intracellular inclusions [8,10]. Previous studies have reported that MA treatment increased α-Syn expression within dopaminergic neurons of the substantia nigra in mice [48] and in dopaminergic SK-N-SH cells [49]. Our group also previously observed upregulated expression of α-Syn mRNA in chronically MA-treated monkeys [31]. In contrast, other studies showed that MA led not only to the upregulation and aggregation of α-Syn in many regions of the brain including the hippocampus and olfactory bulb in mice [50], but also to the formation of cytoplasmic multilamellar bodies in PC12 cells [51]. Furthermore, recent findings suggest that MA-induced oxidative stress and neuroinflammation contribute to α-Syn post-translational modifications, including phosphorylation and aggregation, which exacerbate synaptic dysfunction and neurotoxicity [14-16]. Post-mortem studies of chronic MA abusers have similarly revealed increased α-Syn accumulation in the substantia nigra, aligning with these experimental findings [9,13,52]. MA is also known to disrupt the BBB, facilitating the transfer of α-Syn from the brain into the bloodstream [53-56]. This supports the hypothesis that chronic MA exposure not only enhances α-Syn expression in the brain but also contributes to its accumulation in the peripheral circulation, potentially serving as an early indicator of neurodegenerative processes. Taken together, these findings suggest that chronic MA use leads to increased α-Syn levels in both the brain and blood, providing indirect evidence of its role in PD risk. These changes persist even into the withdrawal period, suggesting long-lasting neurobiological consequences.

BDNF participates in neurogenesis and neuroprotection [57]. In addition, BDNF regulates both short- and long-lasting synaptic interactions that play a role in cognition and memory [58]. In the present study, the expression level of serum BDNF did not differ between the MA and normal control groups. This result is consistent with our previous study, in which chronic exposure to MA did not affect BDNF mRNA expression in the hippocampi of monkeys [31]. Although there are species and tissue differences, our results indicate that MA did not significantly affect BDNF expression in either primates or humans. In contrast, other studies that analyzed blood BDNF levels in patients with MA use disorder during MA withdrawal found that patients had higher BDNF concentrations than did healthy controls [59,60]. Previous reports have suggested that BDNF expression increases following CNS impairment, possibly as a compensatory mechanism [61,62]. Based on these findings, Kim et al. [59] proposed that neurotoxicity due to high-dose MA exposure might induce a BDNF increase similar to that observed in CNS-impaired patients during the addiction recovery process. In addition, an in vitro study reported that MA treatment stimulated BDNF expression in primary neurons [63]. Interestingly, in our study, BDNF concentration showed a positive correlation trend with the duration of MA use, although it was not statistically significant. However, when comparing BDNF levels between short-term (≤5 years) and long-term (>5 years) MA use groups, we found that patients with long-term MA use had significantly higher serum BDNF levels than those with short-term MA use (p=0.0178). This suggests that prolonged MA exposure may upregulate BDNF expression, potentially as a compensatory response to MA-induced neurotoxicity. Although the role of BDNF in substance addiction remains controversial, our findings support the idea that BDNF expression is associated with the duration of MA use within patients with MA use disorder. This aligns with previous reports suggesting that chronic drug exposure may trigger neuroplasticity-related changes in BDNF regulation. Further studies are needed to determine whether BDNF upregulation in long-term MA users reflects a neuroprotective adaptation or an alternative underlying mechanism of addiction-related neurobiological changes.

As described previously, NSE is responsible for neuroplastic pathways as well as neuronal glycolysis in the brain, and its level is affected by addictive drug use [28,29]. In a study of Liao et al. [28], the level of NSE mRNA decreased in immortalized lymphoblastoid cell lines that originated from subjects with heroin dependence. In our previous study, acute high-dose exposure and chronic exposure of MA to cynomolgus monkeys also led to a decrease in the NSE mRNA level in the hippocampus [31]. These two studies imply that the NSE level may be reduced in the blood of patients with MA use disorder. Unfortunately, in this study, the level of NSE did not change in the blood of patients with MA use disorder. However, there tended to be a negative correlation between the duration of drug administration and the NSE level in patients, although it was not significant. Given that blood samples were collected from patients who had been abstinent from MA for more than 24 hours, NSE concentrations may vary depending on the duration and progression of withdrawal.

In summary, we investigated whether blood proteins associated with neurodegeneration and neural plasticity changed in patients with MA use disorder after MA withdrawal. We identified an increase in the α-Syn level in the blood of patients with MA use disorder, even during MA withdrawal. This result suggests that α-Syn increases in the brain after exposure to MA (because it crosses the BBB). We also found that the BDNF level increases with prolonged exposure to MA, implying it as a compensatory mechanism after brain injury. Nevertheless, this study has some limitations. First, the sample size was relatively small, which may have limited the statistical power to detect subtle differences in protein expression. To mitigate this limitation, we conducted statistical assessments such as Q-Q plots, histograms, and normality tests to evaluate data distribution and ensure the appropriateness of parametric or nonparametric statistical analysis. These methods helped validate our findings despite the sample size constraint. However, future studies with larger cohorts are necessary to confirm our results and improve the generalizability of these findings. Second, variability in withdrawal durations may have influenced biomarker levels. While all patients with MA use disorder had undergone withdrawal for 1 to 2 weeks prior to participation, differences in protein expression may still exist depending on individual variations in withdrawal severity and progression. Future studies should account for the effects of withdrawal duration and symptom severity to better understand MA-induced neurobiological changes. Third, despite matching the control and MA groups for age, sex, and smoking status, significant differences in socioeconomic status and education level remained. These factors may act as confounders, as socioeconomic disparities influence health and neurobiological functioning. Fourth, this study relied on peripheral blood biomarkers to infer neurotoxicity, which has inherent limitations. Although α-Syn, BDNF, and NSE are linked to neurodegenerative changes, their direct correlation with CNS pathology remains uncertain. Peripheral biomarker levels can be affected by systemic factors such as metabolic and inflammatory responses, potentially confounding interpretations of MA-related neurotoxicity. Future studies should incorporate neuroimaging or CSF analysis for a more comprehensive assessment of CNS changes in MA use disorder. Despite these limitations, the observed increase in peripheral α-Syn levels in patients with MA use disorder suggests its potential as a biomarker for MA-induced neurotoxicity and neurodegenerative processes. Further research is warranted to validate α-Syn as a biomarker for MA-related brain dysfunction and explore its role in assessing long-term neurobiological consequences of MA abuse.