Association of decreased thalamic neurotransmitter level with sensorimotor tract damage in patients with relapsing-remitting multiple sclerosis

Introduction

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS) that results in neurodegenerative changes, with symptoms of motor, sensory, and cognitive dysfunction (1). Previous studies have proposed several pathways that may drive neurodegeneration in MS, including demyelination, oxidative stress, and ion channel dysfunction, which may be associated with a disturbed state of homeostasis in the CNS due to excitation or inhibition (2,3).

The increased energy demand of impulse conduction along excitable demyelinated axons and decreased axonal adenosine triphosphate (ATP) production due to mitochondrial dysfunction and sodium channel redistribution in demyelinated axons leads to virtual hypoxia in chronically demyelinated axons (4). Based on these pathological changes, abnormal neuronal activity and impaired oxidative metabolism may be accompanied by altered levels of certain neurotransmitters such as γ-aminobutyric acid (GABA) and glutamate.

J-difference spectral editing sequence Mescher-Garwood point resolved spectroscopy (MEGA-PRESS) is able to overcome the problem of overlapping spectra of other major metabolites with the relatively low concentrations of GABA in proton magnetic resonance spectroscopy (¹H-MRS) and has been successfully applied to a number of neurological and psychiatric disorders (5-8). MEGA-PRESS can detect neurotransmitters that may be involved in the pathogenesis of MS, especially GABA and the complex of glutamate with its precursor glutamine (Glx) (9). A decreased GABA level in patients with MS is associated with the pathophysiological mechanisms of neurodegeneration and functional reorganization (10). An altered Glx level may be associated with impaired oxidative metabolic function in MS.

The thalamus is a highly organized deep gray-matter nuclei containing only a small number of myelinated and unmyelinated white-matter (WM) tracts, and its damage or dysfunction may result in sensorimotor, visual, and cognitive deficits (11). Previous studies have demonstrated that thalamic atrophy is already present in the early stage of MS and that pathological changes in the thalamus are associated with disease progression and disability accumulation in the future (12-14). There is a quantitative correlation between thalamic pathological alterations and microstructural damage in the thalamocortical tract, which is a highly interconnected brain hub, suggesting that deep gray-matter and WM pathological changes are interdependent in MS (15).

We speculate that pathological changes such as inflammatory response, myelin destruction, neuronal damage, and atrophy in the thalamus could have an impact on its neurotransmission efficacy, which may be related to the microstructural damage of the thalamocortical tract. Therefore, in this study, we attempted to determine the relationship between altered thalamic GABA and Glx levels and sensorimotor tract damage in patients with relapsing-remitting MS (RRMS) using the MEGA-PRESS sequence. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-219/rc).

Methods

Patient population

This prospective study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments and was approved by the Institutional Review Board of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (No. TJ-IRB20231102). Written informed consent was obtained from all patients.

The inclusion criteria were patients who (I) were diagnosed as RRMS according to the 2017 McDonald criteria; (II) had undergone magnetic resonance imaging (MRI) examination that included 3D T1-weighted imaging (T1WI), double inversion recovery (DIR), diffusion tensor imaging (DTI), and the MEGA-PRESS sequence; and (III) had no steroid therapy within 4 weeks before the MRI scan. From January 2024 to June 2024, a total of 57 patients with RRMS admitted to Tongji Hospital met the inclusion criteria. Seven patients were excluded due to meeting one of the following exclusion criteria: (I) images with motion artifacts (n=4); (II) administration of GABAergic agents (e.g., baclofen) prior to recruitment (n=2); and (III) the presence of other CNS disorders (n=1). Ultimately, 50 patients with RRMS were included in the study. Expanded Disability Status Scale (EDSS) scores were used to assess disease severity. Healthy volunteers who underwent the physical examination at the hospital during the same period as the study cohort were recruited as healthy controls (HCs). Conventional MRI was used to confirm that HCs had no CNS diseases such as cerebrovascular disease, demyelinating and neurodegenerative diseases, brain tumor, or trauma. A total of 43 age- and gender-matched HCs were included in the study. Tobacco, alcohol, and caffeine consumption were prohibited for 12 hours prior to MRI examination for all participants. Figure 1 provides the flowchart of participant enrollment.

Figure 1 Flowchart of participant enrollment. 3D, three-dimensional; CNS, central nervous system; DIR, double inversion recovery; DTI, diffusion tensor imaging; GABA, γ-aminobutyric acid; MEGA-PRESS, Mescher-Garwood point resolved spectroscopy; MRI, magnetic resonance imaging; RRMS, relapsing-remitting multiple sclerosis; T1WI, T1-weighted imaging.

Image acquisition

All MRI scans were performed with a 3-T MRI system (Ingenia Elition X, Philips Healthcare, Best, the Netherlands) with a 32-channel head coil. The three-dimensional (3D) T1WI sequence was conducted under the following parameters: repetition time/time to echo (TR/TE) =6.75/3.0 ms, slice thickness =1 mm, slice spacing =1 mm, field of view (FOV) =224×224×165 mm³, slice number =165, and compressed sensitivity encoding (SENSE) factor =2.5. The acquisition parameters for DIR were as follows: TR/TE =5,500/264.15 ms, slice thickness =1.1 mm, slice spacing =–0.55 mm, FOV =230×230×168 mm³, slice number =305, and compressed SENSE factor =5.5. DTI acquisitions were conducted in 64 unique directions in the anterior-posterior direction under the following parameters: TR/TE =4,800/96 ms, slice thickness =2 mm, slice spacing =0 mm, FOV =224×224×144 mm³, slice number =72, multiband SENSE =3, and nonzero b-value =1,000 s/mm². To correct the DTI image distortion, the other DWI sequence (b-value =0) was acquired in the opposite phase-encoding direction. The MEGA-PRESS sequence was used for GABA+ and Glx detection and was conducted under the following parameters: TR/TE =2,000/68 ms, spectral bandwidth =2 kHz, free induction decay =1,024 points, dynamic number =8, average per dynamic =16, sinc-Gaussian editing pulse =20 ms, on/off offsets =1.89/7.46 ppm, and variable power RF pulses with optimized relaxation delay water suppression. For the MEGA-PRESS sequence, a 50×30×30 mm³ volume of interest (VOI) was placed on the bilateral thalamus region (Figure 2A). No demyelinating lesion was included in the VOI.

Figure 2 Localization and post-processing of the MEGA-PRESS sequence (A,B) and the distribution of tracts of the standard SMATT in the bilateral hemisphere in native space (C). The red box represents the volume of interest of bilateral thalamus region. GABA, γ-aminobutyric acid; Glx, glutamate + glutamine; M1, primary motor cortex; MEGA-PRESS, Mescher-Garwood point resolved spectroscopy; PMd, dorsal premotor cortex; PMv, ventral premotor cortex; preSMA, pre-supplementary motor area; S1, primary somatosensory cortex; SMA, supplementary motor area; SMATT, sensorimotor area tract template.

MEGA-PRESS processing

The MEGA-PRESS sequence was processed with the Gannet 3.0 toolbox in MATLAB 2017a (MathWorks, Natick, MA, USA) (Figure 2B). As the edited GABA signal overlapped with macromolecules and homocarnosine signals at 3 ppm, the detected signal was termed GABA+ instead of GABA (5). GABA+ and Glx levels were evaluated relative to water amplitude in institutional units (IU). Normalized residual fitting errors were provided to assess spectral quality. The fitting errors for the spectra included in the statistical analysis were all less than 15%. Each spectroscopic voxel was co-registered to 3D T1WI, which was segmented to calculate the fractional content of gray matter, WM, and cerebrospinal fluid (CSF). Since the concentrations of GABA and Glx in the CSF are substantially lower than those in the brain parenchyma, consistent with previous magnetic resonance spectroscopy (MRS) studies, we assumed that the concentrations of GABA and Glx in the CSF were negligible (16-18). CSF correction for GABA+ and Glx levels was performed with Gannet’s default tissue correction method. The GABA+ and Glx levels were then finally quantified with adjustments for relaxation times and tissue composition (19).

DTI processing

All DTI data were preprocessed with MRtrix software (https://www.mrtrix.org), with the following steps being performed: data format conversion, image denoising, Gibbs ringing artifact removal, head motion and eddy current correction, and bias field correction. The DTI preprocessed data were then used to create the diffusion tensor and compute the eigenvectors and scalar metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) maps.

The regions of interest (ROIs) for MS lesions were placed by a neuroradiologist (6 years of experience) on the DIR images using ITK-SNAP software (version 3.8.0). Subsequently, a DIR-hyperintense lesion mask was registered together with the DIR to the preprocessed DTI data via FMRIB’s Linear Image Registration Tool (FLIRT; FMRIB Software Library 5.0.5). A standard sensorimotor area tract template (SMATT) was transformed from standard Montreal Neurological Institute (MNI) space into the native diffusion space of each participant via nonlinear FMRIB’s Non-linear Image Registration Tool (FNIRT) registrations, with the lesion mask weighted to zero to obtain the tract mask on the normal-appearing WM (NAWM) (20). The tracts of SMATT were defined based on six motor-related cortical regions: the primary motor cortex (M1), dorsal premotor cortex (PMd), ventral premotor cortex (PMv), supplementary motor area (SMA), pre-supplementary motor area (preSMA), and primary somatosensory cortex (S1). Figure 2C illustrates the distribution of tracts of the M1, PMd, PMv, preSMA, S1, and SMA in the left hemisphere in the native space. The mean value of the diffusion metric was calculated for SMATT template regions in the native space.

Statistical analysis

The Chi-squared test and independent samples t-test were used to compare the differences in demographic characteristics between patients with RRMS and HCs. The general linear model, with age and gender entered as covariates, was used to compare the differences in thalamic neurotransmitter levels and diffusion metrics of each tract between the RRMS and HC groups. The false-discovery rate (FDR) method was used to correct for multiple comparisons in different sensorimotor tracts. Partial correlation analysis adjusted for sex and age was used to determine the relationship between thalamic GABA+ and Glx in patients with RRMS and HC, respectively. To ascertain the relationship between thalamic neurotransmitter level and clinical characteristic, partial correlation analysis was performed in patients with RRMS with age and sex being controlled for. Partial correlation analysis between EDSS score and diffusion metrics of tracts in patients with RRMS and between thalamic neurotransmitter levels and diffusion metrics of tracts in patients with RRMS and HCs, respectively, was also conducted, with age, sex, and tract-specific lesion load (in patients only) being adjusted for. FDR was further applied for the correlation analyses in different sensorimotor tracts to account for the multiple comparisons involved. A corrected P value <0.05 was considered statistically significant. All statistical analyses were performed with SPSS version 26.0.0 (IBM Corp., Armonk, NY, USA).

Results

Demographic and clinical characteristics

The demographic and clinical data of patients with RRMS and HCs are presented in Table 1. There were no significant differences in gender (P=0.227) or age (P=0.287) between patients with RRMS and HCs. Twenty-eight patients with RRMS accepted disease-modifying therapy (DMT).

Alterations in thalamic neurotransmitter levels in patients with RRMS

The GABA+ and Glx levels in the thalamus of patients with RRMS and HCs were compared after adjustment for tissue composition. Figure 3 shows the comparison of GABA+ and Glx levels in the thalamus between patients with RRMS and HCs. Compared with HCs, patients with RRMS had significantly decreased thalamic GABA+ (2.859±0.451 vs. 3.092±0.283 IU; P=0.002) and Glx level (5.787±1.307 vs. 6.439±0.680 IU; P=0.002). There was a strong positive correlation between GABA+ and Glx in patients with RRMS (r=0.773; P<0.001; Figure S1) and in HCs (r=0.417; P=0.007).

Figure 3 The differences in GABA+ and Glx levels in the thalamus between patients with RRMS and HCs. GABA, γ-aminobutyric acid; Glx, glutamate + glutamine; HCs, healthy controls; RRMS, relapsing-remitting multiple sclerosis.

Figure 4 shows the relationship between neurotransmitter levels in the thalamus and the clinical characteristics in patients with RRMS. The GABA+ and Glx levels were significantly and negatively correlated with total lesion volume (GABA+: r=–0.409, P=0.004; Glx: r=–0.493, P<0.001) and disease duration (GABA+: r=–0.314, P=0.030; Glx: r=–0.348, P=0.015), respectively. There was no significant correlation between neurotransmitter levels and EDSS score.

Figure 4 Correlation analysis between thalamic neurotransmitter levels and clinical characteristics in patients with RRMS. EDSS, Expanded Disability Status Scale; GABA, γ-aminobutyric acid; Glx, glutamate + glutamine; r, correlation coefficient; RRMS, relapsing-remitting multiple sclerosis.

Alterations in diffusion metrics of the sensorimotor tract in patients with RRMS

Figure 5 shows the comparison of FA, MD, AD, and RD of the sensorimotor tract between patients with RRMS and HCs. The FA of the bilateral PMd, preSMA, S1, left SMA, right M1, and PMv tracts was significantly decreased in patients with RRMS as compared to HCs (corrected P value <0.05). Compared with that in HCs, the MD of the bilateral PMd, PMv, preSMA, S1, left SMA, and right M1 tracts were significantly increased in patients with RRMS (corrected P value <0.05). The AD and RD of the bilateral M1, PMd, PMv, preSMA, S1, and left SMA tracts were significantly increased in patients with RRMS as compared to HCs (corrected P value <0.05). Correlation analysis indicated that the FA of the bilateral PMd, preSMA, right M1, S1, and SMA tracts was significantly and negatively correlated with EDSS score (r=–0.321 to –0.492; corrected P value <0.05) (Figure 6).

Figure 5 The differences in the diffusion metrics of the sensorimotor tract between patients with RRMS and HCs. *, corrected P<0.05; **, corrected P<0.01; ***, corrected P<0.001. AD, axial diffusivity; FA, fractional anisotropy; HCs, healthy controls; L, left; M1, primary motor cortex; MD, mean diffusivity; PMd, dorsal premotor cortex; PMv, ventral premotor cortex; preSMA, pre-supplementary motor area; R, right; RD, radial diffusivity; RRMS, relapsing-remitting multiple sclerosis; S1, primary somatosensory cortex; SMA, supplementary motor area.

Figure 6 Correlation analysis between the EDSS score and diffusion metrics of the sensorimotor tract in patients with RRMS. Only statistically significant correlations present on partial correlations are shown. EDSS, Expanded Disability Status Scale; FA, fractional anisotropy; M1, primary motor cortex; PMd, dorsal premotor cortex; P_corr, corrected P value; preSMA, pre-supplementary motor area; r, the correlation coefficient; RRMS, relapsing-remitting multiple sclerosis; S1, primary somatosensory cortex; SMA, supplementary motor area.

Correlation between thalamic neurotransmitter levels and diffusion metrics of the sensorimotor tract

Figure 7 and Table S1 show the correlations between GABA+ levels in the thalamus and the diffusion metrics of tracts in patients with RRMS. The MD of the bilateral PMd, S1, right M1, PMv, preSMA, and SMA tracts was significantly and negatively correlated with the GABA+ level (r=–0.359 to –0.578; corrected P value <0.05). The AD of the bilateral M1, PMd, preSMA, S1, SMA, and right PMv tracts was significantly and negatively correlated with the GABA+ level (r=–0.294 to –0.561; corrected P value <0.05). The RD of the bilateral PMd, S1, right M1, PMv, preSMA, and SMA tracts was significantly and negatively correlated with the GABA+ level (r=–0.333 to –0.562; corrected P value<0.05).

Figure 7 Correlation analysis between GABA+ level in the thalamus and diffusion metrics of sensorimotor tract in patients with RRMS. *, corrected P<0.05. AD, axial diffusivity; FA, fractional anisotropy; GABA, γ-aminobutyric acid; L, left; M1, primary motor cortex; MD, mean diffusivity; P_corr, corrected P value; PMd, dorsal premotor cortex; PMv, ventral premotor cortex; preSMA, pre-supplementary motor area; r, the correlation coefficient; R, right; RD, radial diffusivity; RRMS, relapsing-remitting multiple sclerosis; S1, primary somatosensory cortex; SMA, supplementary motor area.

In the correlation analysis between the Glx level and diffusion metrics (Figure 8 and Table S2), there was a significant and positive correlation between the FA of the right PMv tract and Glx level (r=0.409; corrected P value =0.048). The MD and AD of the bilateral M1, PMd, preSMA, S1, SMA, and right PMv tracts were significantly and negatively correlated with the Glx level (MD: r=–0.305 to –0.538, corrected P value <0.05; AD: r=–0.367 to –0.595, corrected P value <0.05). The RD of the bilateral PMd, S1, left preSMA, right M1, PMv, and SMA tracts were significantly and negatively correlated with Glx level (r=–0.411 to –0.613; P<0.05).

Figure 8 Correlation analysis between Glx level in the thalamus and the diffusion metrics of the sensorimotor tract in patients with RRMS. *, corrected P<0.05. AD, axial diffusivity; FA, fractional anisotropy; Glx, glutamate + glutamine; L, left; M1, primary motor cortex; MD, mean diffusivity; P_corr, corrected P value; PMd, dorsal premotor cortex; PMv, ventral premotor cortex; preSMA, pre-supplementary motor area; r, the correlation coefficient; R, right; RD, radial diffusivity; RRMS, relapsing-remitting multiple sclerosis; S1, primary somatosensory cortex; SMA, supplementary motor area.

However, no significant correlation was found between thalamic neurotransmitter levels and diffusion metrics of the sensorimotor tract in HCs.

Discussion

Our study demonstrates that GABA+ and Glx concentrations in the thalamus are reduced in patients with RRMS, which suggests that an imbalance between excitatory and inhibitory neurotransmitters may be a key driver of neurodegeneration in MS. The neurotransmitter levels appeared to decrease further in patients with RRMS as the disease duration prolonged. Patients with RRMS also showed significant microstructural damage of the sensorimotor tract, which was significantly correlated with the degree of clinical disability. Moreover, to determine the relationship between thalamic neurotransmission and thalamocortical projection microstructural damage, a correlation analyses between neurotransmitter levels and diffusion metrics of the sensorimotor tract in patients with RRMS and HC, respectively, was conducted. We found that a decreased thalamic neurotransmitter level was associated with sensorimotor tract damage in patients with RRMS, while there was no significant correlation between thalamic neurotransmitter level and diffusion metrics in the sensorimotor tract of HCs.

The imbalance between excitatory and inhibitory neurotransmitters may be associated with the onset of a cascade of events leading to oxidative stress and neurodegeneration in MS (21,22). Previous studies have found altered GABA+ and Glx levels in regions such as the sensorimotor cortex, posterior cingulate cortex, and hippocampus in patients with MS (9,23). Kantorová et al. found that the positivity of oligoclonal bands in CSF were predisposed to metabolic changes and the rearrangement of inhibitory/excitatory neurotransmitters in the subcortical brain structures of patients with MS, and GABA ratios in the right thalamus and Glx ratios in the left hippocampus strongly predicted positivity for oligoclonal-band–positive status (24). Another study reported decreased Glx ratios in the hypothalamus that correlated with disease severity (25). Our study further confirmed the presence of abnormal GABA+ and Glx levels in the thalamus of patients with RRMS, suggesting that GABA and Glx may be potential imaging biomarkers of neurodegeneration. The alterations in neurotransmitter levels in the thalamus may be the result of inflammation-driven excitatory/inhibitory rearrangements. In addition, GABA+ and Glx may be more tightly coupled in patients with RRMS, possibly reflecting shared pathological influences and enhanced metabolic coupling in pathological states.

Inflammation and demyelination are prominent pathological features of MS and may be associated with synaptic dysfunction and neuronal-axonal degeneration and lead to abnormal neurotransmitter levels. A reduced GABA level may be caused by the dysfunction of GABA synthesis or the dysfunction of enzymes involved in the glutamate-glutamine cycle (26). Previous studies based on postmortem tissue analysis have found that the number of parvalbumin-positive GABAergic interneurons is reduced in the brain of patients with MS (27,28). In addition to causing a significant reduction in the density of neurotransmitter synapses, inflammation can also precipitate disturbances in the complex cytokine environment, resulting in diffuse changes in GABAergic neuron activity (29). Gilani et al. discovered the involvement of GABAergic system dysfunction in the pathogenesis of MS by treating experimental autoimmune encephalomyelitis mice with GABAergic drugs (30). Thus, the improvement to GABAergic nervous system function may represent a novel direction for the development of future pharmacologic strategies in MS.

Glutamate plays a key role in providing oxidative energy for neurons and astrocytes and producing GABA (10). Inflammatory cytokines can block the release and reuptake of glutamate by astrocytes through multiple pathways (31). A proton MR spectroscopic study found that ratio of Glx to total creatine in the thalamus was significantly lower in patients with clinically isolated syndrome without DMT treatment than that in HCs, suggesting that alterations in thalamic Glx levels occur in the early stages of the disease (32). MacMillan et al. found that glutamate level in the NAWM of patients with secondary progressive MS decreases over time, which may be related to microstructural damage (e.g., demyelination) (33). Previous studies have confirmed through in vivo myelin regeneration models that glutamate is involved in signaling and directing oligodendrocyte progenitor cells to differentiate into myelinating glial cells, suggesting that low glutamate levels may hinder myelin regeneration (34). However, it is possible that differences in single-voxel VOI placement and acquisition methods lead to discrepancies in the results of studies on glutamate concentration in patients with MS. Kantorová et al. found no significant difference between the thalamic Glx level in patients with RRMS and that in HC in the analysis of the special MEGA GABA-edited MR spectroscopy (35). Swanberg et al. measured glutamate concentration using short-echo-time stimulated echo acquisition mode (STEAM) and found that the prefrontal cortical glutamate level was decreased only in patients with progressive MS (8). Arm et al. analyzed the Glx level in the prefrontal cortex and sensorimotor cortex using the MEGA-PRESS sequence and found that the Glx concentration significantly decreased only in sensorimotor cortex (10). In summary, given that our study employed a cross-sectional analysis and only a small number of patients with RRMS, further large-sample longitudinal analysis of the progression of MS is warranted.

The thalamus connects the cerebral cortex and subcortical nuclei through WM fiber tracts. Thus, propagated through prograde and retrograde degenerative mechanisms, thalamic pathologic changes in MS may potentially affect other distal WM (36). We then consequently examined the relationship between altered neurotransmitter levels in the thalamus and WM microstructural damage. The sensorimotor tract was selected for analysis because it is one of the thalamocortical projections often involved in MS and is closely associated with the manifestations of sensory and motor dysfunction in patients with MS (36,37). There was a significant correlation between neurotransmitter levels and sensorimotor tract damage in patients with RRMS, with more severe WM microstructural damage often accompanied by more pronounced decreases in GABA+ and Glx levels. However, the thalamic neurotransmitter level was not significantly correlated with the diffusion metrics of the sensorimotor tract in HCs. After inflammation and demyelination occur, neuronal energy requirements increase in order to overcome the disturbances caused by oxidative stress and ion channel dysfunction. However, due to mitochondrial dysfunction, a persistent mismatch between cell body energy demand and supply in the thalamus may subsequently cause disruption of neuronal excitatory and inhibitory homeostasis, which after diffusion along axons in connected tracts, leads to pathological processes such as oxidative stress and neurodegeneration (4,38). In addition, thalamic dysfunction may be associated with lesions in connected WM tracts, which is similar to the mechanisms that cause microstructural damage to the NAWM (39). Primary local WM damage may propagate along the fibers and induce secondary damage to connected neurons in the thalamus, leading to altered neurotransmitter levels in the region (40). Our findings reflect the combination of two pathological processes in the deep gray matter and WM tracts of patients with MS.

Previous studies have found that abnormal GABA and glutamate concentrations in some brain regions of patients with MS are associated with motor and cognitive impairment (41,42). Damage to the thalamus and its connections may impair a wide range of neurologic functions, which may manifest in clinical symptoms such as sensorimotor dysfunction (11,43). Similar to MacMillan et al. (33), we did not find a correlation between altered neurotransmitter levels and clinical disability in patients with MS. However, we found a significant correlation between microstructural damage in the sensorimotor tract and EDSS score, which may be due to a more direct link between the sensorimotor tract and the manifestation of clinical symptoms. The impact of the imbalance between excitatory and inhibitory neurotransmitters in the thalamus on sensorimotor function needs to be clarified through larger patient samples and more detailed clinical and neuropsychological assessments.

Certain limitations should be considered in the interpretation of our results. First, the sample size was relatively small, so only limited results could be obtained. Our results need to be further validated in multicenter studies with large samples. Second, to achieve a desirable signal-to-noise ratio and to minimize time, we measured metabolite levels in larger VOIs, including the bilateral thalamus, but this made it impossible to assess metabolite concentrations in gray matter, WM, and the individual thalamus separately. Third, although DIR is typically superior in detecting WM lesions as compared to fluid-attenuated inversion recovery, the segmented lesion volumes may be smaller. In addition, we only examined the association between microstructural damage in sensorimotor tract and thalamic pathologic changes; however, the potential associations between other cerebral regions and tracts and the thalamus remain to be further investigated. Finally, although our study excluded patients who used GABAergic agents, not all patients received the same treatment modality for their disease, and the effect of treatment modality on GABA+ and Glx levels is not fully yet understood.

Conclusions

Our study demonstrates the important roles of GABA and glutamate in the pathophysiological mechanisms of RRMS and provides new insights into the relationship between altered neurotransmitter levels in deep gray-matter and WM microstructural damage. In the future, a deeper understanding of the potential role of neurotransmission in driving neurodegeneration in MS will be critical for developing effective neuroprotective strategies.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-219/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-219/dss

Funding: This study received funding from the National Natural Science Foundation of China (grant No. U22A20354).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-219/coif). All authors report that this study received funding from the National Natural Science Foundation of China (grant No. U22A20354). X.Z. is an employee of Philips Healthcare, which designed and manufactured the MRI scanner used in this work. However, the company had no role in the study design, data collection, data analysis, interpretation of data, writing of this manuscript, or the decision to submit it for publication. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This prospective study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments and was approved by the Institutional Review Board of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (No. TJ-IRB20231102). Written informed consent was obtained from all patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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