Assessment of glymphatic system function using DTI-ALPS in depressive disorders: a study of its correlation with clinical features and plasma GFAP levels

Introduction

With ongoing economic development and societal transformations, depressive disorders (DDs) have emerged as a highly prevalent mental health condition in China. According to data from the China Mental Health Survey, more than 95 million individuals in China are affected by depression, making it the second leading contributor to disease burden (1). DDs are characterized by a sad, empty, or irritable mood, accompanied by somatic and cognitive changes that significantly affect functioning.

According to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), DDs can be classified into disruptive mood dysregulation disorder, major depressive disorder (MDD), persistent depressive disorder (PDD), premenstrual dysphoric disorder, substance/medication-induced DD, and other specified or unspecified DDs (2). PDD, as defined in the DSM-5, comprises two distinct chronic subtypes: dysthymia, characterized by mild symptoms with a protracted course; and chronic MDD, characterized by severe, full-threshold symptoms lasting more than two years. PDD is a chronic form of depression characterized by a persistently low mood occurring most of the day, on more days than not, often accompanied by anxiety, somatic discomfort, and sleep disturbances. In adults, the required duration of symptoms is at least two years; in children and adolescents, the criterion is a minimum duration of one year (2).

During a depressive episode, individuals with depression may exhibit impairments in multiple cognitive domains, including attention, memory, response inhibition, and processing speed (3). Depression is considered a prodromal stage of dementia, and in a subset of patients, cognitive deterioration continues to progress despite the alleviation of depressive symptoms (4). Further, nearly half of individuals with treatment-resistant depression fail to achieve significant or sustained clinical improvement with currently available antidepressant therapies (5). Consequently, it is imperative to further investigate the pathogenesis of DDs and develop effective early intervention strategies.

Neuroinflammatory system dysregulation, triggered by repeated psychological trauma or chronic stress, is thought to increase vulnerability to depression (6). During this neuroinflammatory response, the functional impairment of astrocytes plays a crucial role in the emergence of depression-like behaviors (7). Glial fibrillary acidic protein (GFAP) is an intermediate filament protein residing in the cytoskeleton of astrocytes and can be released into the cerebrospinal fluid (CSF) and peripheral blood following astrocyte activation or injury. Elevated CSF GFAP levels reflect disturbances in astrocyte function, and are widely recognized as a potential biomarker for neurological and psychiatric disorders (8,9). Notably, recent studies have demonstrated that plasma GFAP levels increase as depressive symptom severity increases, and are significantly correlated with cognitive function scores (10).

The central nervous system possesses a waste clearance mechanism, defined as the glymphatic system (GS). This anatomically distinct pathway, localized to the perivascular spaces (PVSs) of cerebral vasculature, plays a pivotal role in clearing extracellular metabolic waste from the brain. The GS comprises three key components: the perivascular influx pathway mediated by aquaporin-4 (AQP4) expressed on astrocytic endfeet; the transparenchymal pathway that facilitates the exchange of CSF with interstitial fluid (ISF) to clear solutes from the extracellular space; and the perivascular efflux pathway responsible for draining waste products to the deep cervical lymph nodes (11,12). Research has shown that the chronic unpredictable mild stress (CUMS) mouse model of depression induces GS dysfunction, characterized by significant neuroinflammatory responses, attenuated arterial pulsatility, reduced vascular compliance, mislocalization and depolarization of AQP4 on astrocytic endfeet, and impaired clearance efficiency of exogenous amyloid-β (13,14). Wen et al. further confirmed that ketamine exerts antidepressant effects in the CUMS model by inhibiting astrocyte pyroptosis and promoting the restoration of glymphatic function, suggesting this pathway as a potential therapeutic target (13). Chronic stress has been shown to impair glymphatic clearance in models of depression, while antidepressant intervention can partially reverse this dysfunction (15). Therefore, investigating the association between glymphatic function and clinical characteristics, as well as plasma GFAP levels, in patients with DD, together with the underlying mechanisms, is of substantial theoretical and clinical importance.

Glymphatic function reflects the efficiency of CSF distribution in the brain parenchyma and its clearance capacity. Magnetic resonance imaging (MRI) combined with intrathecal gadolinium contrast enhancement currently represents the most established method for evaluating the GS in vivo. This technique provides time-resolved imaging and enables the quantitative measurement of CSF influx and efflux rates by detecting spatial and temporal variations in contrast agent signal intensity (16). However, as an invasive procedure, it involves inherent safety risks and technical complexities, which limit its widespread clinical application. Consequently, the development of a non-invasive method for assessing glymphatic function in clinical settings is of considerable importance. The Diffusion Tensor Imaging-Analysis along the Perivascular Space (DTI-ALPS) method, established by Taoka et al., serves as a non-invasive imaging technique that leverages the sensitivity of diffusion tensor imaging (DTI) to the anisotropic diffusion of water molecules to indirectly assess solute transport efficiency within the PVSs, reflecting GS function. At present, this method has been widely adopted for in vivo studies of the human GS (17), and has been validated as a reliable, practical tool with good reproducibility and stability.

This study aimed to evaluate GS function using the DTI-ALPS method in patients with DD, and to analyze the associations of this index with the clinical characteristics of DDs, as well as plasma GFAP levels, with the goal of elucidating potential neurobiological mechanisms. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2494/rc).

Methods

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of the Affiliated Hospital of Guilin Medical University (approval No. 2023YJSLL-21). Written informed consent was obtained from all participants, or from the parents or legal guardians of the participants aged under 18 years.

Participants

A total of 72 patients diagnosed with DD at the Department of Psychiatry and Psychology at the Affiliated Hospital of Guilin Medical University between August 2022 to March 2024 were enrolled in the study. Additionally, 44 healthy controls (HCs) with no significant history of major medical conditions, neurological disorders, or psychiatric illnesses were recruited. All participants were evaluated and diagnosed according to the diagnostic criteria for DDs in the DSM-5. All the enrolled individuals met the predefined inclusion and exclusion criteria. Due to inadequate MRI quality, nine patients and four HCs were excluded from the study, resulting in a final analytical sample of 63 patients and 40 HCs for the DTI-ALPS analysis. The core grouping criterion in this study was illness duration. Based on the chronic and persistent nature of depressive symptoms, the patients were divided into two groups: a PDD group meeting the DSM-5 criteria, comprising patients with both chronic MDD and dysthymia, and an operationally defined non-persistent depressive disorder (NPDD) group, comprising patients with a shorter symptom duration. This exploratory categorization was employed to investigate the association between the chronicity of DDs and specific neurobiological markers. The flowchart of participant recruitment is shown in Figure 1.

Figure 1 Flowchart of participant recruitment. DD, depressive disorder; HCs, healthy controls; NPDD, non-persistent depressive disorder; PDD, persistent depressive disorder.

The inclusion criteria for the patients were as follows: (I) age between 14 and 60 years; (II) a diagnosis of DD, with comorbid anxiety disorders allowed except for obsessive-compulsive disorder; and (III) adequate visual and auditory capacities, adequate cognitive comprehension, and right-handedness. The exclusion criteria were as follows: (I) significant or active systemic illness that could interfere with study assessments or interventions; (II) current use of medications known to affect cognitive function, such as psychostimulants, corticosteroids, or β-blockers; (III) a history of electroconvulsive therapy or repetitive transcranial magnetic stimulation within the previous two months; (IV) major chronic medical conditions, including hypertension, cardiac disease, respiratory disorders, or diabetes mellitus; (V) contraindications to MRI (e.g., claustrophobia, metallic implants, pregnancy, or lactation); and/or (VI) MRI evidence of significant intracranial abnormalities (e.g., lacunar infarction, white matter hyperintensities, or a Fazekas score >1), or image quality deemed inadequate due to motion artifacts or other technical factors precluding further analysis.

General information and clinical assessment scales

General demographic and clinical characteristics, including sex, age, smoking and alcohol history, education level, and duration of illness, were collected for all participants. Prior to MRI scanning, a comprehensive assessment of emotional states and psychosocial functioning was conducted using the following standardized instruments: the Activities of Daily Living (ADL) scale, Mini-Mental State Examination (MMSE), 17-item Hamilton Depression Rating Scale (HAMD-17), Patient Health Questionnaire-9 (PHQ-9), Pittsburgh Sleep Quality Index (PSQI), and the negative subscale of the Life Event Scale (LES-negative).

MRI data acquisition

Brain MRI scans were conducted on all participants using a GE SIGNA Architect 3.0T magnetic resonance apparatus (General Electric Healthcare, Waukesha, WI, USA) equipped with an 8-channel head coil, located at the Department of Radiology at the Affiliated Hospital of Guilin Medical University. The scans were performed between 9:00 AM and 5:00 PM according to a standardized imaging protocol. During the scanning process, the participants were required to remain motionless, awake, and relaxed to ensure consistent and reliable data acquisition. None of the patients suffered from an acute depressive episode within 24 hours before or during the MRI session.

The MRI scanning protocol included T1-weighted imaging, T2-weighted imaging, T2-weighted fluid-attenuated inversion recovery sequence, and DTI. The DTI data were acquired using the following parameters: echo time =104.8 ms; repetition time =3,945 ms; slice thickness =2.5 mm; matrix size =256×256; field of view =208×208 mm²; generalized autocalibrating partially parallel acquisitions with an acceleration factor =2; a diffusion-weighted imaging protocol comprising 64 isotropically distributed gradient directions optimized via electrostatic repulsion, and b values of 0, 1,000 s/mm². For B0 field inhomogeneity correction, one additional b=0 image with reversed phase-encoding was also collected for each participant.

The brain MRI data were preprocessed using the open-source DSI Studio software (May 2021 version, http://dsistudio.labsolver.org). The following preprocessing steps were employed: (I) estimation and correction of susceptibility-induced distortions in echo-planar imaging using reverse phase-encoded b=0 images; (II) combined correction for eddy current distortions and subject motion; and (III) generation of a brain mask through thresholding, smoothing, and defragmentation. Finally, the diffusion tensor model was fitted within this mask to compute scalar maps [e.g., fractional anisotropy (FA) and mean diffusivity (MD) maps].

DTI-ALPS processing

The DTI-ALPS method was used to quantitatively assess GS function. This approach evaluates the diffusion characteristics of water molecules along PVSs in orthogonal directions on axial slices at the level of the lateral ventricular body, reflecting the clearance efficiency of the GS. Diffusion tensor images were processed using DTI Studio software (www.mristudio.org) to generate color-coded FA maps, MD maps, and directional diffusivity maps along the X-axis (Dxx), Y-axis (Dyy), and Z-axis (Dzz). The DTI-ALPS index was calculated as follows: First, raw DTI data in DICOM (Digital Imaging and Communications in Medicine) format were loaded, into the software from a local directory, and a mask was applied to remove background signal, thereby improving reconstruction efficiency and visualization. The preprocessing steps included motion correction, correction for eddy current-induced distortions, and skull stripping. DTI reconstruction was subsequently performed to characterize the principal diffusion directions of white matter fibers, followed by the generation of FA maps and color-coded FA maps using fiber tractography. The color-coded FA map at the level of the lateral ventricular body enables differentiation of the three primary fiber orientations: red for left-right (X-axis), green for anterior-posterior (Y-axis), and blue for superior-inferior (Z-axis).

Neuropathological models of depression frequently highlight left-hemispheric regions involved in emotion regulation, informing our focus on the left hemisphere as a primary region of interest (ROI) for the preliminary analyses. A single experienced analyst, blinded to participant condition, manually drew all the ROIs according to a standardized protocol based on explicit anatomical landmarks. Two rectangular ROIs, each measuring 5 × 5 mm², were placed in the left cerebral hemisphere to minimize potential measurement bias arising from interhemispheric asymmetries. One ROI was positioned in the projection fiber region (predominantly oriented along the Z-axis), and the other in the association fiber region (predominantly oriented along the Y-axis) (see Figure 2). Visual inspection confirmed that the projection fiber ROI (ROIproj) contained exclusively blue voxels, while the association fiber ROI (ROIassoc) contained exclusively green voxels. Diffusivity values along the X-axis (Dxx), Y-axis (Dyy), and Z-axis (Dzz) were extracted from within each ROI. The DTI-ALPS index was then calculated using the following formula:

DTI-ALPSindex=mean(Dxxproj,Dxxassoc)mean(Dyyproj,Dzzassoc)[1]

Figure 2 Schematic diagram of ROI drawing. ROI, region of interest.

where Dxxproj and Dxxassoc represent the diffusivities along the X-axis in the projection and association fiber regions, respectively; Dyyproj denotes the diffusivity along the Y-axis in the projection fiber region; and Dzzassoc indicates the diffusivity along the Z-axis in the association fiber region. This ratio reflects the spatially specific diffusion characteristics of CSF-ISF exchange in the PVSs, serving as an indirect neuroimaging biomarker of GS function.

Blood sample collection and GFAP measurement

A standardized protocol was followed for blood sample collection and processing in all participants. Plasma GFAP levels were quantified using a double-antibody sandwich enzyme-linked immunosorbent assay (ELISA). Following an overnight fast, fasting peripheral venous blood samples were collected from all participants during a fixed morning time window (07:00–08:00) and immediately transferred into ethylenediaminetetraacetic acid (EDTA)-containing vacuum tubes. The samples were centrifuged at 4 ℃ (4,000 rpm, 20 minutes) to separate plasma, which was then aliquoted into nuclease- and protease-free microcentrifuge tubes, and stored at –80 ℃ until batch analysis. Repeated freeze-thaw cycles were strictly avoided to maintain sample integrity. For the ELISA procedure, standards solutions were prepared according to the manufacturer’s instructions. The optical density of each well was measured using a microplate reader, and GFAP concentrations were calculated by interpolating absorbance values onto a standard curve. This standardized protocol ensured the accurate and reproducible quantification of the plasma GFAP levels. All instruments were calibrated according to manufacturer specifications prior to analysis.

Statistical analysis

All statistical analyses were conducted using IBM SPSS Statistics version 28.0 (IBM, Armonk, NY, USA). The categorical variables are presented as the frequency and percentage (%), and were compared using the chi-squared test or Fisher’s exact test based on data distribution. The continuous variables were assessed for normality using the Kolmogorov-Smirnov test; most were non-normally distributed, and thus are presented as the median and interquartile range [M (P25, P75)] to reflect central tendency and variability. The Mann-Whitney U test (two groups) or Kruskal-Wallis H test (≥ three groups) was used for group comparisons. Post-hoc pairwise tests applied Bonferroni adjustment, with adjusted P values reported. Partial Spearman’s rank correlations were used to assess associations between the DTI-ALPS index and the clinical features of DDs, psychological scale scores, and plasma GFAP levels, adjusting for age, sex, and smoking. P values were adjusted for multiple comparisons using the Benjamini-Yekutieli false discovery rate (FDR) procedure. All statistical tests were two-tailed, and a P value <0.05 was considered statistically significant.

Results

Demographic data

The baseline characteristics of the three groups are summarized in Table 1. A significant difference was observed in the smoking rate across the groups (P<0.05), while no statistically significant differences were observed among the three groups in terms of gender distribution, alcohol use, age, or education level (P>0.05). Post-hoc pairwise comparisons revealed that the patients in the PDD group had a significantly longer illness duration and higher smoking rate compared to those in the NPDD group (P<0.05). Additionally, a significant difference in gender distribution was observed between the PDD and NPDD groups (P<0.05). No significant differences were observed for alcohol use, age, or education level between the PDD and NPDD groups (P>0.05).

Comparison of scale scores between NPDD and PDD groups

The PDD group exhibited significantly higher scores on the ADL, PSQI, and LES-negative scales compared to the NPDD group (P<0.05), while no significant differences were observed in the remaining assessments (P>0.05), as presented in Table 2.

Comparison of plasma GFAP levels among groups

Plasma GFAP concentrations in the HC, NPDD, and PDD groups were non-normally distributed and exhibited heterogeneous variances; therefore, group comparisons were performed using the Kruskal-Wallis H test. Post-hoc pairwise analyses with Bonferroni adjustment revealed that the PDD group had significantly higher GFAP levels than both the HC (P<0.001) and NPDD (P<0.001) groups. Conversely, no statistically significant difference was observed between the HC and NPDD groups (P>0.05). All pairwise comparisons applied adjusted P values via the Bonferroni method. Detailed results are provided in Table 3 and Figure 3A.

Figure 3 Plasma GFAP level and DTI-ALPS index in the study groups. (A) GFAP levels were significantly increased in the PDD group. (B) The DTI-ALPS index was significantly reduced in the PDD group. The data are presented as the median with the interquartile range. *, P <0.05 vs. HC and NPDD. DTI-ALPS, diffusion tensor imaging analysis along the perivascular space; GFAP, glial fibrillary acidic protein; HCs, healthy controls; NPDD, non-persistent depressive disorder; PDD, persistent depressive disorder.

Comparison of the DTI-ALPS index among groups

The DTI-ALPS index was non-normally distributed and exhibited heterogeneous variances across the HC, NPDD, and PDD groups; therefore, group comparisons were conducted using the Kruskal-Wallis H test. A statistically significant difference was observed in the DTI-ALPS index among the three groups (P=0.001). Post-hoc pairwise analyses with Bonferroni adjustment revealed that the PDD group had significantly lower DTI-ALPS indices compared to both the HC and NPDD groups (both P<0.001), while no significant difference was observed between the HC and NPDD groups (P>0.05). These findings are summarized in Table 4 and Figure 3B.

Correlation analysis of the DTI-ALPS index with plasma GFAP levels and clinical features

Partial correlation analyses were performed to evaluate the associations between the DTI-ALPS index and plasma GFAP levels, as well as the clinical features of DDs, across all participants, while controlling for sex, age, and smoking. After adjusting for these covariates, P values were adjusted for multiple comparisons using the Benjamini-Yekutieli FDR procedure, and a significant negative correlation was observed between the DTI-ALPS index and plasma GFAP concentration (r=−0.290, q=0.009). No other variables showed statistically significant associations with the DTI-ALPS index (all q>0.05). The detailed results are presented in Table 5.

Correlations between plasma GFAP levels and clinical characteristics

A partial correlation analysis was performed to assess the association between plasma GFAP concentration and depression-related clinical features across all participants, with sex, age, and smoking included as covariates. P values were adjusted for multiple comparisons using the Benjamini-Yekutieli method (FDR-controlled). After adjustment, plasma GFAP levels showed significant positive correlations with illness duration, HAMD-17 scores, PHQ-9 scores, and PSQI scores (all q<0.05), as well as a significant negative correlation with MMSE scores (r=–0.230, q=0.012). The results are summarized in Table 6.

Discussion

This study investigated the involvement of the GS in the chronic and persistent manifestation of depressive symptoms. The DTI-ALPS method was used to assess glymphatic function in DDs and its associations with clinical characteristics and plasma GFAP levels. Our results revealed that the DTI-ALPS index was significantly lower in the PDD group compared to both the HC and NPDD groups, and it showed a significant negative correlation with GFAP levels. These results extend our understanding of the mechanisms underlying depression and support the integration of neuroimaging with fluid biomarkers for the subtyping and staging of this heterogeneous disorder.

The DTI-ALPS method, first introduced by Taoka et al. in 2017 for Alzheimer’s disease (AD), has been established as a feasible approach for assessing glymphatic function, as evidenced by a significant positive correlation between the DTI-ALPS index and MMSE scores, indicating that impaired perivascular diffusion is associated with AD severity (17). In recent years, accumulating clinical evidence has demonstrated glymphatic dysfunction across a range of neurological disorders, including sleep disorders, Parkinson’s disease (PD), migraine, multiple sclerosis, and hydrocephalus, all evaluated using the DTI-ALPS approach (18-23). A decreased DTI-ALPS index has been observed in patients with MDD, and is correlated with psychiatric symptoms, cognitive deficits, and white matter disruption, highlighting its potential as a biomarker for glymphatic function assessment (24). This method leverages the orthogonal alignment of medullary veins (X-axis) relative to projection fibers (Y-axis) and association fibers (Z-axis) at the level of the lateral ventricles to selectively quantify diffusivity along perivascular pathways, thereby providing a non-invasive proxy for GS function. An index value close to 1 reflects minimal water diffusion with PVSs, while higher index values correspond to greater diffusivity along these pathways and are associated with more efficient glymphatic clearance.

According to Chen et al., alterations in the DTI-ALPS index are associated with cognitive decline, as well as markers of systemic oxidative stress and inflammation in advanced stages of disease (25). Impaired diffusion may arise from systemic oxidative stress and neuroinflammation, which disrupt convective exchange between CSF and ISF, leading to glymphatic dysfunction (26). Collectively, DTI-ALPS represents a feasible and informative technique for detecting GS function. However, its accuracy remains controversial. For example, Ringstad has argued that DTI-ALPS is a questionable marker of glymphatic clearance, as it may not account for CSF flow, and the continuity of PVSs between white and gray matter (27). While the results of DTI-ALPS studies should be interpreted with caution, the DTI-ALPS index still holds significant research value.

This study employed the DTI-ALPS method to assess glymphatic function in patients with DD. A significantly reduced DTI-ALPS index was observed in the patients with PDD compared to the HCs, providing evidence of impaired glymphatic function in this clinical population. However, the DTI-ALPS index may lack sufficient sensitivity to detect subtle differences in perivascular diffusion between NPDD and HC groups, suggesting that other comorbid factors could potentially influence cognitive function in NPDD. Our initial analyses focused on the left hemisphere, due to its involvement in depression-related neuropathological models of emotion regulation, and the consistent right-handedness and left-hemisphere language dominance among participants. Given the potential bilateral nature of glymphatic physiology, future research should include larger cohorts and bilateral evaluations to comprehensively map glymphatic changes in DDs.

Neuroimmune dysregulation and inflammation play a critical role in the pathogenesis of mood disorders. Repeated psychosocial or environmental stress induces central neuroinflammation, leading to depressive-like behaviors (28). Astrocytes are critical for maintaining normal neuronal function and regulating neurotransmitter balance, and their dysfunction is linked to the pathological progression of both depression and AD (29). GFAP, a marker protein of astrocytes, is regarded as a potential biomarker for neurological and psychiatric disorders (8). Studies have consistently shown that GFAP expression is reduced in depression-related brain regions (30,31), and S100B-positive astrocyte density is decreased in the hippocampus and locus coeruleus (32). Recent clinical evidence shows plasma GFAP is valuable for diagnosing and assessing depression severity, with levels correlating positively with disease progression and cognitive impairment, supporting its use as a novel diagnostic and staging biomarker (10). This observation points to a nuanced peripheral-central relationship beyond simple correspondence. This may be explained by blood-brain barrier compromise, which allows astrocytic GFAP to enter the circulation, and by the systemic nature of plasma GFAP relative to the regionally varied pathology of the brain (33). Thus, plasma GFAP elevation may better reflect dynamic neuroinflammatory glial responses than focal cellular changes. This study found that the plasma GFAP levels in the PDD group were significantly elevated compared to those in both the HC and NPDD groups, with GFAP concentrations positively correlated with illness duration, severity of depression, and cognitive impairment. These findings align with previous research.

The stress response exerts a complex and dynamic effect on the nervous system, wherein stressors of varying nature and intensity can elicit distinct physiological reactions. In contrast to chronic stress, acute stress promotes astrocyte proliferation and upregulates the expression of glutamate transporter-1 and glutamine synthetase (34), suggesting an adaptive mechanism through which astrocytes maintain homeostasis under short- to medium-term stress. In patients with PDD, prolonged or recurrent stress exposure may lead to more severe astrocytic damage or dysfunction, resulting in elevated plasma GFAP levels. Thus, the lack of a statistically significant difference in plasma GFAP levels between the NPDD and HC groups in this study may be attributed to the relatively milder intensity and shorter duration of psychosocial stress experienced by the NPDD patients, reflecting differential effects of distinct stress patterns on astrocytic function. Moreover, as a sample characteristic, the majority of patients in the NPDD group had a short illness duration of less than six months, while the PDD patients had a significantly longer course, suggesting that disease duration may also contribute to the observed differences in the GFAP levels. Thus, future studies involving larger cohorts and longitudinal designs are warranted to validate the interplay among stress patterns, disease progression, and GFAP dynamics.

We investigated the relationship between glymphatic function and astrocyte activation in depression by correlating the DTI-ALPS index with plasma GFAP levels. After adjusting for sex, age, and smoking, a significant negative correlation was observed, and this association survived rigorous correction for multiple comparisons, affirming its statistical robustness, suggesting an association between neuroinflammation and impaired waste clearance in depression. This finding may contribute to the understanding of both somatic and cognitive symptoms in patients. However, the observed moderate negative correlation suggests that, while statistically robust, its absolute clinical impact may be limited. This relationship warrants precise estimation through larger-scale studies.

Sleep plays a vital role in maintaining daily functioning and psychosomatic health, and is closely associated with glymphatic clearance (35,36). Accumulating evidence indicates that sleep enhances glymphatic activity, facilitating the removal of metabolic wastes such as amyloid-β and tau proteins (37,38). Neuroimaging studies show sleep-modulated glymphatic function: animal experiments have shown accelerated gadolinium clearance during sleep (39), and human studies have shown rapid T1 recovery post-sleep, indicating improved waste clearance (40). The DTI-ALPS method further confirms sleep-related glymphatic dynamics through CSF flow analysis (41). Clinically, obstructive sleep apnea patients exhibit reduced ALPS indices, which are correlated with disease severity and disrupted sleep (42,43). Similarly, chronic insomnia patients exhibit lower ALPS indices, along with impaired cerebrovascular reactivity and cognitive performance—deficits that can be improved through low-frequency repetitive transcranial magnetic stimulation (44,45). Together, these findings suggest that sleep disorders impair glymphatic function.

In this study, the PDD patients had higher PSQI scores than the HCs and NPDD patients, indicating poorer sleep quality. However, the DTI-ALPS index was not found to be correlated with the PSQI. This dissociation indicates potentially distinct mechanisms for subjective sleep complaints versus underlying glymphatic clearance. Glymphatic impairment, reflected by a lower ALPS index, might represent a persistent process conferring long-term risk for chronicity and cognitive decline, not acute symptomatology. These findings should be interpreted with caution due to the limited sample size, which reduces statistical power for detecting subtle effects or subgroup heterogeneity. Larger longitudinal cohorts incorporating objective sleep measures are needed to clarify the predictive value of glymphatic function in the chronic and persistent features of depressive symptoms.

Notably, this study found that the DTI-ALPS index, a measure of glymphatic function, was not significantly associated with cross-sectional clinical symptom severity (HAMD-17 or PHQ-9) or global cognitive function (MMSE) in patients with depression. This result prompts a deeper exploration of the role of the GS in a multifactorial disorder such as depression. The negative findings suggest that in such conditions, glymphatic dysfunction may not directly determine immediate symptomatology but rather act as a fundamental, persistent pathological process. Its role is more likely to create a “permissive environment” for downstream pathogenic mechanisms—by impairing clearance and exacerbating neuroinflammation—thereby primarily contributing to long-term disease progression risk, chronicity, and conversion. This aligns with an evolving perspective on neuroimaging biomarkers, in which indicators of cerebral perfusion, barrier function, or clearance systems may be more valuable for reflecting the pathological burden or predicting longitudinal trajectory than for correlating strongly with cross-sectional symptoms (46). Thus, the primary value of the identified “glymphatic-glial covariation” may serve as a putative biological marker for predicting disease progression or therapeutic outcomes, but this needs to be confirmed in future prospective longitudinal research.

This study had several limitations. First, its cross-sectional design and small sample size limit the generalizability of the findings. Larger prospective studies are needed to confirm the results. While the symptom-duration-based NPDD grouping allowed a preliminary test of chronicity, future studies should validate these findings in larger cohorts with finer, clinically-established subtypes (e.g., by course, symptoms, or biomarkers). Second, detailed antidepressant data were unavailable for covariate adjustment, and their potential effects on astrocytic AQP4 warrant caution in interpreting the results. Additionally, the DTI-ALPS index reflects glymphatic function near the lateral ventricles but may not represent whole-brain perivascular diffusion due to its reliance on regional diffusion parameters. The DTI-ALPS index may serve as an indirect measure of glymphatic function. Although it provides valuable insights into diffusivity within the PVSs, it does not directly assess glymphatic activity. As such, caution should be exercised when interpreting the DTI-ALPS index as an indicator of GS function. It should also be noted that all the ROIs were manually delineated. Although standardized protocols were followed, manual segmentation may introduce subjective bias. In the future, we intend to employ automated ROI definition based on probabilistic fiber tracking or use blinded multi-rater placement with reported intraclass correlation coefficient values to enhance objectivity and reproducibility. Finally, the cross-sectional design prevents the establishment of temporal sequences, limiting causal inference and the assessment of dynamic changes among the DTI-ALPS index, plasma biomarkers, cognition, and depression severity.

Conclusions

The DTI-ALPS index was found to be lower in the PDD group compared to both the HC and NPDD groups, and was correlated with plasma GFAP levels. These findings suggest that the covariation between glymphatic dysfunction and glial activation may represent a potential biological feature in the progression of DDs.

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-aw-2494/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2494/dss

Funding: This work was supported by the Guangxi Natural Science Foundation Program (No. 2023GXNSFAA026091), the National Natural Science Foundation of China (Nos. 82360283 and 81660208), and the Guangxi Medical and Health Key Discipline Construction Project.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2494/coif). The authors have no 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. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of the Affiliated Hospital of Guilin Medical University (approval No. 2023YJSLL-21). Written informed consent was obtained from all participants, or from the parents or legal guardians of those under age 18 years.

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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