Abstract
Introduction:
Children with autism spectrum disorder (ASD) often experience reduced quality of life due to core autistic traits, such as restricted and repetitive behaviors (RRBs), yet no pharmacological treatments have been established to date. Oxidative stress, a potential contributor to ASD pathology, may reduce taurine and glutathione (GSH) levels. Although animal studies have reported altered antioxidant levels, studies investigating the brain antioxidant levels in individuals with ASD remain limited. This study investigated whether reduced antioxidant levels in the anterior cingulate cortex (ACC), a region consistently characterized by functional and metabolic abnormalities in individuals with ASD, and closely associated with RRBs.
Methods:
A total of 44 children with ASD and 40 typically developing controls were enrolled in this study. Diagnoses were confirmed using the Autism Diagnostic Observation Schedule-Second Edition (ADOS-2). Magnetic resonance spectroscopy was used to quantify taurine and GSH levels in the ACC. Statistical analyses were conducted to compare metabolite levels between the groups and assess associations with ADOS-2 subscale scores.
Results:
The ASD group exhibited significantly lower taurine levels, whereas GSH levels remained unchanged. Taurine levels were negatively correlated with RRBs but not with social affect.
Discussion:
These findings suggest that reduced taurine levels in the ACC of children with ASD, alongside unchanged GSH levels, may indicate distinct biosynthetic pathways and functional roles of these metabolites in oxidative stress defense mechanisms associated with ASD pathology. Taurine depletion may disrupt physiological processes associated with RRBs and could serve as a potential therapeutic target for symptom management.
1 Introduction
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by impairments in social interaction and communication, along with restricted and repetitive behavior (RRB) (1). According to a survey conducted by the Centers for Disease Control and Prevention, ASD affects approximately 1 in 54 individuals (2). These core features are associated with a reduced quality of life in affected individuals (3, 4). Ongoing neuroimaging research aims to elucidate the underlying pathological mechanisms of ASD (5, 6). Several studies have indicated that individuals with ASD may exhibit both functional (7, 8) and metabolic abnormalities in the anterior cingulate cortex (ACC) (9–11), which is a region strongly associated with RRBs (12, 13). Investigating the molecular targets associated with ASD pathology in the ACC may facilitate the identification of potential pharmacological candidates for symptom management.
Growing evidence indicates that oxidative stress contributes to the pathogenesis of ASD (14–17). The maternal immune activation model, a widely used animal model manifesting ASD-related behavioral abnormalities, has demonstrated that prenatal exposure to immune challenges induces oxidative stress (18). Oxidative stress occurs when the production of reactive oxygen species exceeds the antioxidant defense capacity, resulting in cellular damage (19). BTBRT + Itpr3tf/J (BTBR) mice, which exhibit ASD-like behavioral phenotypes, have reduced serum glutathione (GSH) levels (20). A meta-analysis further demonstrated that individuals with ASD have decreased blood antioxidant levels (21). However, only a few studies have examined antioxidant levels in the living brains of individuals with ASD using magnetic resonance spectroscopy (MRS) (22). These studies focused exclusively on GSH and reported no significant changes in brain levels (23–26).
Taurine (Tau) is a β-amino acid with well-established cytoprotective properties, including functions in energy metabolism, inhibitory neurotransmission, calcium homeostasis, and antioxidative defense (27). Notably, Tau modulates antioxidant defense networks both directly and indirectly (28). It scavenges free radicals (29, 30), reduces lipid peroxidation (31–33), and enhances superoxide dismutase activity (34, 35). Tau is primarily acquired through dietary sources, such as beef, chicken, fish, and shellfish, but can also be synthesized endogenously from sulfate in mammals (36–38). Selective eating behaviors in individuals with ASD may contribute to low Tau levels (39). This hypothesis is supported by studies reporting decreased blood Tau levels in children with ASD compared to typically developing (TD) controls (40–42); however, some studies have found no significant differences (43).
To our knowledge, no studies have measured Tau levels in the brains of individuals with ASD using MRS, with reports to date limited to findings in a model of maternal autoantibody exposure in rats (44). Examining brain levels of Tau and GSH may provide insights into the mechanisms of oxidative stress underlying ASD. The present study is the first in vivo investigation to test the hypothesis that children with ASD experience oxidative stress, as indicated by decreased brain levels of Tau and GSH, which may be associated with core autistic traits.
2 Materials and methods
2.1 Participants
A total of 44 children with ASD were recruited from the outpatient clinic of the Department of Psychiatry at Nara Medical University Hospital and an affiliated psychiatric clinic. Diagnoses were established by two trained psychiatrists according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and the Japanese version of the Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) (45). Among the children with ASD, nine were diagnosed with comorbid neuropsychiatric conditions, including attention deficit hyperactivity disorder (ADHD) (n = 6), adjustment disorder with tic disorder (n = 1), obsessive–compulsive disorder (n = 1), and learning deficits (n = 1). Psychotropic medications were prescribed to 18 children with ASD during the study period, including antidepressants (n = 4), hypnotic agents (n = 9), antipsychotics (n = 11), anxiolytics (n = 3), ADHD medications (n = 5), and mood stabilizers (n = 2). The severity of social affect (SA) and RRBs was assessed using the ADOS-2 (45).
A total of 40 children with TD were recruited from the general population through advertisements and word of mouth. None of the TD participants had a history of psychiatric or neurological disorders. Screening was conducted using the Japanese version of the Autism Spectrum Quotient (AQ-J) (46, 47). TD children aged <15 years with a parent-reported AQ-J score of ≤24 (47) and those aged ≥16 years with a self-reported AQ-J score of ≤25 were included in the analysis (48). We recruited all participants between March 2021 and January 2023.
Cognitive function was assessed in all participants using the Das–Naglieri Cognitive Assessment System (DN-CAS) (49, 50). The DN-CAS is a theory-driven instrument based on the Planning, Attention, Simultaneous, and Successive cognitive processing model (51). Participants in the ASD and TD groups who obtained a total DN-CAS score of <70 and exhibited structural brain abnormalities on T1-weighted magnetic resonance imaging (MRI) were excluded.
2.2 Acquisition of magnetic resonance imaging and magnetic resonance spectroscopy data
All MRI and MRS examinations were performed using a 3T scanner (Siemens MAGNETOM Skyra, Erlangen, Germany) equipped with a 32-channel receiver head coil. Three-dimensional volumetric images were acquired using a T1-weighted gradient-echo sequence, yielding a gapless series of thin sagittal sections (repetition time (TR) = 2,500 ms; echo time (TE) = 2.18 ms; inversion time (TI) = 1,000 ms; field of view (FOV) = 256 mm; flip angle = 8°; acquisition matrix = 320 × 300; and slice thickness = 0.8 mm). Anatomical images were used to localize the voxels of interest (VOIs) for MRS, which were positioned in the ACC (Figure 1A). As described in previous studies (52, 53), the MRS of the ACC was performed using a short TE spin-echo full-intensity acquired localized single-voxel spectroscopy sequence (54) with the following parameters: TE = 8.5 ms, TR = 3,000 ms, 128 averages, and VOI dimensions = 30 × 20 × 20 mm3. This sequence was specifically developed to acquire full-intensity signals from a defined VOI using an ultrashort TE and has been employed in previous studies to quantify GSH (53, 55). One child with ASD and three typically developing (TD) children who exhibited severe head motion were excluded from the analysis, resulting in a final sample of 44 children with ASD and 40 TD children.
Figure 1
Representative VOIs, MRS spectrum, and scatterplots of metabolite levels in a child with ASD. (A) VOI (30 × 20 × 20 mm3) in the ACC of a child with ASD. ACC, anterior cingulate cortex; VOI, volume of interest; MRS, magnetic resonance spectroscopy (B) Representative MRS spectrum.
2.3 MRS data analysis
A weighted combination of receiver channels was applied, followed by the removal of motion-corrupted averages, spectrum registration for frequency and phase drift correction, and pre-subtraction sub-spectral alignment. These preprocessing steps were conducted in MATLAB 2021a (The Mathworks, Natick, MA, USA) using the FID-A toolkit prior to signal averaging and data analysis (56). MRS data were analyzed using LCModel software version 6.3-1R (Stephen Provencher, Oakville, ON, Canada) (57), which applies linear combination modeling of the acquired spectra using simulated basis function. The neurochemical basis set included nine macromolecular functions, consistent with those employed in a previous study (52). An example of the spectrum is shown in Figure 1B. Metabolite concentrations were quantified using tissue water as an internal reference. To account for partial volume effects, the fractions of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) within the VOIs were calculated by segmenting the T1-weighted images using Gannet 3.0 software (58). The assumed water concentrations for WM, GM, and CSF were 35,880 mM, 43,300 mM, and 55,556 mM, respectively (59). These values were subsequently corrected based on the partial volume fractions of GM, WM, and CSF using a previously established equation (60) and adjusted according to the T2 relaxation times specific to Tau and GSH (60, 61), as reported in previous studies. The final metabolite concentrations (μmol/g) were normalized to the combined GM and WM fractions to account for the CSF content within the VOI. We summarized the MRS methods using the MRSinMRS CHECKLIST (Supplementary Table 1) (62).
2.4 Statistical analysis
Data are expressed as mean ± standard deviation. Independent sample t-tests and χ2 tests were used to assess group differences in demographic characteristics and voxel-wise MRS data. Spearman’s partial rank-order correlation analyses were conducted to assess the correlations between MRS-derived metabolite levels and ADOS-2 subscale scores. All statistical analyses were performed using IBM SPSS Statistics for Windows, version 25 (IBM Corp., Armonk, NY, USA). A two-tailed p-value of <0.05 was considered significant for both group comparisons and correlation analysis.
3 Results
3.1 Participant characteristics
The demographic characteristics of the participants are summarized in Table 1. A total of 44 children with ASD and 40 TD children were enrolled, with ages ranging from 8 to 16 years in both groups. No significant differences were observed between the ASD and TD groups in terms of sex, age, or DN-CAS full-scale scores.
Table 1
| Characteristic | ASD (n = 44) | TD (n = 40) | t or χ2 | p |
|---|---|---|---|---|
| Mean (SD), frequency (%) | Mean (SD), frequency (%) | |||
| Sex | χ2 = 0.12 | 0.45 | ||
| Female | 17 (38.6) | 14 (35.0) | ||
| Male | 27 (61.4) | 26 (65.0) | ||
| Age, years | 12.5 (2.7) | 11.9 (2.7) | t = 1.14 | 0.26 |
| DN-CAS full scale | 98.1 (13.9) | 98.1 (15.2) | t = −0.017 | 0.99 |
| ADOS-2 total scores | 12.5 (2.9) | NA | NA | NA |
Demographic and clinical characteristics of children with ASD and TD children.
ASD, autism spectrum disorder; ADOS-2, Autism Diagnostic Observation Schedule-Second Edition; DN-CAS, Das-Naglieri Cognitive Assessment System; SD, standard deviation; TD, typically developed.
3.2 Comparisons of metabolite levels between the ASD and TD groups
The spectral signal-to-noise ratio and linewidth in the ACC, as reported by LCModel, were 115.6 ± 15.5 in the ASD group and 116.4 ± 16.0 in the TD group for the signal-to-noise ratio, and 0.020 ± 0.003 ppm in the ASD group and 0.021 ± 0.004 ppm in the TD group for the linewidth (mean ± standard deviation), respectively. These results indicate excellent MRS data quality, with all measurements substantially exceeding the previously established criteria for the signal-to-noise ratio and linewidth (63). In this study, Tau and GSH levels were evaluated as markers of oxidative stress. The reliability of neurochemical quantification was evaluated using the Cramer–Rao lower bound (CRLB) provided by the LCModel for each metabolite. A CRLB cutoff of 30%, averaged across all scans, was used to determine the reliability (64). The average CRLB values for Tau and GSH were 10.6% ± 2.3% and 6.1% ± 0.9%, respectively, both of which satisfied the reliability threshold.
Tau levels in the ACC were significantly lower in children with ASD than in TD controls (4.48 [0.95] for the ASD group and 5.08 [0.69] for the TD group, t = −3.36, p = 0.001) (Figure 2). This difference remained significant in the analysis of covariance after controlling for psychotropic medication use (F = 6.94, p = 0.010), and comorbid neuropsychiatric conditions (F = 8.66, p = 0.004). The statistical significance persisted even after excluding 18 children with ASD exposed to psychotropic medications (t = −2.39, p = 0.022), and after excluding nine children with ASD presenting with comorbid neuropsychiatric conditions (t = −2.86, p = 0.006). However, no significant difference was found in GSH levels between the two groups (3.14 [0.29] for the ASD group and 3.21 [0.22] for the TD group; t = −1.34, p = 0.18).
Figure 2
Tau and GSH levels in the ACC of children with ASD and TD children. (A) Tau levels in the ACC were significantly decreased in children with ASD compared with TD children (p = 0.001). (B) No significant difference was observed in GSH levels between the two groups (p = 0.18). ACC, anterior cingulate cortex; ASD, autism spectrum disorder; GSH, glutathione; Tau, taurine; TD, typically developed. ***p <0.005. ns, not significant.
3.3 Correlations of metabolite levels with ADOS-2 scores in children with ASD
A significant negative correlation was observed between the Tau levels in the ACC and RRB subscale scores (r = −0.37, p = 0.015) in children with ASD (Figure 3). Meanwhile, no significant correlation was found between the Tau levels and SA subscale scores (r = −0.16, p = 0.31). The negative correlation between Tau levels and RRB subscale scores remained significant even after controlling for psychotropic medication use as a covariate (r = −0.37, p = 0.014) and after controlling for comorbid neuropsychiatric conditions as a covariate (r = −0.38, p = 0.013). In contrast, no correlation was found between GSH levels in the ACC and either RRB (r = −0.18, p = 0.25) or SA subscale scores (r = 0.18, p = 0.24) in the ASD group.
Figure 3
Correlation between ADOS-2 RRB scores and Tau levels in the ACC of children with ASD. A significant negative correlation was observed between ADOS-2 RRB subscale scores and Tau levels (r = −0.37, p = 0.015) in children with ASD. The shaded region indicates the 95% confidence interval. ACC, anterior cingulate cortex; ADOS-2, Autism Diagnostic Observation Schedule-Second Edition; ASD, autism spectrum disorder; RRB, restricted and repetitive behaviors; Tau, taurine.
4 Discussion
In this study, MRS was employed to assess the levels of Tau and GSH in the ACC of TD children and those with ASD. Significantly lower Tau levels were observed in the ACC of children with ASD than in TD controls, whereas no significant difference was found in GSH levels between the groups. Additionally, Tau levels in the ACC were significantly negatively correlated with RRB subscale scores, whereas GSH levels were not significantly correlated with autistic traits. The reliability of these findings is supported by the relatively large sample size and high spectral quality of the MRS data.
The findings of the present study are consistent with previous MRS studies (23–25) in reporting comparable GSH levels in children with ASD relative to TD controls; however, to our knowledge, this is the first study to demonstrate lower Tau levels in the ACC. Both GSH and Tau are synthesized from cysteine; however, it has been reported that the activity of cysteine sulfinate decarboxylase—an enzyme essential for Tau synthesis—is low (36). We speculate that this reduced enzymatic activity may result in comparable GSH levels and reduced Tau levels under oxidative stress in children with ASD. Furthermore, several animal studies have indicated that Tau can attenuate oxidative stress-induced reductions in GSH levels (35, 65–68). Collectively, these findings suggest that Tau may mitigate GSH depletion by exerting antioxidative effects, including scavenging free radicals (29, 30), inhibiting lipid peroxidation (31–33), and enhancing superoxide dismutase activity (34, 35).
According to the proposed hypothesis, children with ASD exhibit insufficient Tau levels in the ACC. Accumulating evidence indicates that Tau plays an important role in neurodevelopment (reviewed in (69)). Tau has been reported to function as a neurodevelopmental modulator through the GABAA receptor, and alterations in GABAA receptor activity during development have been shown to impair social interactions in offspring, which represent a core symptom of ASD (70). The present results are also supported by findings from both human and animal studies, which reported decreased Tau levels in ASD. For example, mice receiving gut microbiota transplants from human donors with ASD develop ASD-like behaviors and exhibit reduced Tau levels in the colon (71). Similarly, blood Tau levels have been reported to be lower in children with ASD than in TD children (40–42). The elevated urinary Tau levels observed in children with ASD (72, 73) suggest excessive urinary excretion. Moreover, restricted dietary patterns commonly associated with ASD traits (39) may result in reduced Tau intake, as this amino acid is predominantly obtained from dietary sources such as beef, chicken, fish, and shellfish (37, 38). Collectively, the combination of increased excretion and decreased dietary intake may impede Tau replenishment, which is crucial because Tau is consumed during oxidative stress.
Correlations between Tau levels in the ACC and RRB subscale were also observed in children with ASD. Tau performs numerous physiological functions in mammals (27), including antioxidant activities. In addition to its antioxidant properties, Tau has been implicated in the maintenance of neuronal functions, such as neurodevelopmental modulation (69), energy metabolism (74), inhibitory neurotransmission (75, 76), and calcium homeostasis modulation (77, 78). Tau depletion due to oxidative stress can disrupt these neuronal function. Given that the ACC has been associated with RRB in ASD (12), our findings suggest that impaired neuronal function in the ACC may be correlated with RRB. Furthermore, these findings suggest that Tau may serve as a potential pharmacological target for the treatment of RRB, which has recently been recognized as a core feature of ASD through analyses employing extended language model architectures (79). In line with this, there are studies reporting that taurine supplementation improves cognitive function and emotional behaviors in mice (80, 81), and more recently, a randomized, double-blind, placebo-controlled trial was conducted in children with ASD (82).
This study had some limitations. Despite being relatively large, the sample size of 44 children with ASD and 40 TD children may limit the generalizability of these findings. First, the participants in this study were exclusively Japanese, which might limit the generalizability of the findings to other populations. The inclusion of children with ASD who presented with comorbid conditions (83, 84) and those receiving psychotropic medications (85–87) introduced potential confounding effects on oxidative stress; nevertheless, after adjusting for these factors, taurine levels remained low in children with ASD. The exclusion of participants due to motion artifacts may have introduced a potential bias. The cross-sectional design of this study precludes the establishment of causal relationships; therefore, it remains unclear whether taurine depletion is a cause or consequence of RRBs. Moreover, age-related differences remained unaccounted for. Unmeasured factors, including dietary habits and gastrointestinal conditions, may also influence Tau and GSH levels. Restricting the analysis to the ACC may have limited the detection of broader neurochemical alterations associated with ASD. To advance the understanding of ASD, future research should be conducted with larger and more diverse samples, including multi−ethnic participants, employ longitudinal designs, and incorporate dietary assessments and a broader range of neurochemical markers.
Distinct patterns were identified in the two antioxidants examined in the ACC of children with ASD, with GSH levels remaining comparable and Tau levels significantly reduced. These findings may reflect differences in the biosynthetic pathways of GSH and Tau, and their respective roles in mitigating oxidative stress in ASD pathology. Tau depletion in the ACC may compromise its physiological functions, including its role as a neurodevelopmental modulator, potentially contributing to the manifestation of RRB in ASD. Collectively, these findings suggest that Tau may be a promising target for developing symptom-relieving therapies for ASD.
Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving humans were approved by Nara Medical University Ethics Medical Committee. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.
Author contributions
AM: Writing – original draft, Writing – review & editing, Data curation, Investigation. KM: Conceptualization, Investigation, Writing – original draft, Methodology, Writing – review & editing, Data curation. MT: Investigation, Writing – original draft, Writing – review & editing, Data curation. KU: Writing – review & editing, Investigation, Data curation, Writing – original draft. HO: Writing – review & editing, Writing – original draft, Data curation, Investigation. YF: Data curation, Writing – original draft, Writing – review & editing, Investigation. HY: Data curation, Writing – review & editing, Writing – original draft. RI: Data curation, Writing – original draft, Writing – review & editing. YTk: Supervision, Writing – original draft, Investigation. JN: Supervision, Writing – original draft, Investigation, Writing – review & editing. YY: Data curation, Writing – review & editing, Writing – original draft. TM: Writing – review & editing, Writing – original draft, Investigation, Data curation. YTi: Data curation, Writing – original draft, Writing – review & editing. TOc: Data curation, Writing – original draft, Writing – review & editing. TT: Investigation, Supervision, Writing – review & editing, Writing – original draft. TOk: Writing – review & editing, Investigation, Writing – original draft, Supervision. NI: Supervision, Investigation, Writing – review & editing, Writing – original draft. MM: Data curation, Funding acquisition, Conceptualization, Writing – original draft, Methodology, Investigation, Writing – review & editing, Supervision.
Funding
The author(s) declared financial support was received for this work and/or its publication. This work was supported by the Japan Society for the Promotion of Science KAKENHI (grant numbers: 16H06403, 16H06400, 16H02666, 16H05377, 20H03604, 23H04173, and 24K02386 to MM), AMED-PRIME (grant number: 21gm6310015h0002 to MM), AMED-CREST (grant numbers: 24gm1510009s0103 and 24gm1910004h0002 to MM), AMED (grant numbers: 21wm04250XXs0101, 21uk1024002h0002, and 25 wm0625510s0102 to MM), and Moonshot R&D (grant number: JPMJMS239F-1-2 to MM).
Acknowledgments
The authors would like to thank the magnetic resonance imaging technologists for their valuable assistance in acquiring the imaging data.
Conflict of interest
The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1700059/full#supplementary-material
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Summary
Keywords
autism spectrum disorder, restricted and repetitive behaviors, anterior cingulate cortex, taurine, glutathione
Citation
Minami A, Matsuoka K, Takahashi M, Ueda K, Ohnishi H, Fujimoto Y, Yoshikawa H, Ishida R, Takado Y, Near J, Yamatani Y, Miyasaka T, Tai Y, Ochi T, Tanaka T, Okada T, Iwata N and Makinodan M (2025) Association between decreased taurine levels in the anterior cingulate cortex and restricted and repetitive behaviors in autism spectrum disorder: a cross-sectional study. Front. Psychiatry 16:1700059. doi: 10.3389/fpsyt.2025.1700059
Received
05 September 2025
Revised
19 November 2025
Accepted
26 November 2025
Published
11 December 2025
Volume
16 - 2025
Edited by
Atsuo Fukuda, Hamamatsu University School of Medicine, Japan
Reviewed by
Hao Zhou, Guizhou Provincial People’s Hospital, China
Yulu Song, Johns Hopkins University, United States
Updates
Copyright
© 2025 Minami, Matsuoka, Takahashi, Ueda, Ohnishi, Fujimoto, Yoshikawa, Ishida, Takado, Near, Yamatani, Miyasaka, Tai, Ochi, Tanaka, Okada, Iwata and Makinodan.
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*Correspondence: Manabu Makinodan, manabu.makinodan@fujita-hu.ac.jp
†These authors have contributed equally to this work
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