A preliminary study of subcortical gray matter nucleus volumetric and morphological changes in diabetic retinopathy

Introduction

Diabetic retinopathy (DR) is a neurovascular degenerative condition caused by chronic hyperglycemia, and is one of the most common microvascular complications of diabetes (1). The disease progresses gradually and can be classified into two categories based on severity: non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). NPDR represents the early stage of DR, and typically presents with no obvious clinical symptoms, while PDR represents the advanced, severe stage of DR, and can lead to fibrovascular proliferation, retinal detachment, and even complete vision loss (2). Among patients with type 2 diabetes, the prevalence of DR is approximately 25.2%, with about 6.9% experiencing severe vision loss (3,4).

Numerous studies have reported a significant association between the presence of DR and an increased risk of dementia (5-7). The Edinburgh Type 2 Diabetes Study found a significant inverse correlation between the severity of DR and cognitive function scores, with patients with moderate-to-severe DR demonstrating the poorest cognitive performance (6). Further Exalto et al. demonstrated that vision-threatening DR, such as proliferative retinopathy and macular edema, is associated with a higher risk of dementia (5). A Danish registry-based study compared the risk of Alzheimer’s disease (AD) in diabetic patients with and without DR, and found that the risk of AD was significantly increased in those with DR. These findings suggest that DR, rather than diabetes alone, may serve as an important and specific biomarker for AD (7).

Recent studies suggest that DR and dementia share common pathological mechanisms, with neurovascular unit impairment being implicated as a key mechanism. This includes the disruption of both the inner blood-retinal barrier (BRB) and the blood-brain barrier (BBB) (8). BRB breakdown is a hallmark feature of DR, and similar BRB pathological changes have also been observed in patients with AD (9,10). Other AD-related biomarkers detectable in the retina include retinal nerve fiber layer thinning, ganglion cell loss, neuroinflammation, microvascular changes, functional/metabolic abnormalities, and the deposition of β-amyloid and hyperphosphorylated tau protein (11,12).

Given the increased risk of dementia in patients with DR, the early identification of associated structural brain changes and the implementation of interventions could help delay the progression of cognitive decline. Subcortical gray matter nuclei are involved in the regulation of cognitive functions through a series of neural circuits, and the atrophy of gray matter nuclei is a common brain structural change in diabetic patients (13,14). Volume measurement methods based on regions of interest (ROIs) or voxel-based morphometry have frequently been used to measure and compare the gray matter volume of different nuclei and brain regions in the brain. However, these two methods can only evaluate overall volumetric changes in different regions. Conversely, the vertex-based shape analysis method combines shape and appearance models, and directly uses the geometric shape/position on the structural boundary to accurately determine the structural boundary of the gray matter nuclei, thereby measuring geometric structural changes in different regions of the nuclei (15,16). We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1964/rc).

Methods

Participants

This study prospectively collected the data of 32 diabetic patients with DR (18 males and 14 females; age range, 33–69 years, average age, 54.16 years) and 38 age-, gender-, and education-matched healthy volunteers (14 males and 24 females; age range, 35–71 years; average age, 51.05 years).

Participants were included in the patient group if they met the following inclusion criteria: (I) were DR inpatients at the Department of Ophthalmology from March 2022 to June 2023; (II) had no mental disorders; (III) met the diagnostic criteria of the American Academy of Ophthalmology (AAO) for diabetes and DR; (IV) had PDR (stages IV–VI) of type 2 diabetes; (V) had no speech or hearing impairments; and (VI) were right-handed. Participants were included in the control group if they met the following inclusion criteria: (I) were healthy, middle-aged or elderly, with normal cognition, whose age, gender, and educational level were commensurate with the participants in the DR group; and (II) had no history of taking hypoglycemic drugs, with fasting blood glucose <6.1 mmol/L and 2-hour postprandial blood glucose <7.8 mmol/L.

Participants were excluded from both the DR and normal control groups if they met any of the following exclusion criteria: (I) had mental or neurodevelopment disorders; (II) had a history of other ocular pathologies; (III) had a history of cardiovascular diseases or other endocrine disorders; (IV) had a history of abuse of psychoactive substances; and/or (V) had a history of cerebrovascular diseases, brain tumors, or tumors in other regions.

This study was conducted in strict accordance with the ethical principles outlined in the Declaration of Helsinki and its subsequent amendments. The protocol was approved by the Scientific Research Ethics Committee of The Affiliated Taizhou People’s Hospital of Nanjing Medical University (approval No. KY 2022-79-01). Written informed consent was obtained from all participants.

Magnetic resonance imaging (MRI) parameters

The MRI data were acquired using a Siemens Skyra 3.0T magnetic resonance (MR) scanner equipped with a 16-channel head coil. All the participants were instructed to keep their eyes closed and remain in an awake state while keeping their heads still. Initially, routine T1-weighted imaging, T2-weighted imaging, and T2-fluid-attenuated inversion recovery sequences were obtained to rule out organic lesions in the brain. Participants with organic brain lesions were excluded from the study. Subsequently, high-resolution three-dimensional (3D)-T1 structural images were acquired using a magnetization-prepared rapid acquisition gradient echo sequence. The following scanning parameters were used: repetition time: 2,300 ms, echo time: 2.98 ms, flip angle: 9°, slices: 176, slice thickness: 1 mm, field of view: 256 mm × 256 mm, and voxel size: 1×1×1 mm.

Neuropsychological testing

The same neurologist collected demographic and clinically relevant data for the patients. Prior to the MRI scans, cognitive assessments were administered to all patients, including the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE). Additionally, the participants underwent psychological testing using the Self-Rating Anxiety Scale (SAS) and the Self-rating Depression Scale (SDS).

Data processing

The 3D-T1 images were automatically preprocessed and segmented using FreeSurfer (version 7.3.2; https://surfer.nmr.mgh.harvard.edu). The “recon-all” command in the default mode was implemented, and the automatic reconstruction process comprised 31 stages, including motion correction, non-uniform intensity correction, talairach transformation computation, normalization, skull stripping, automatic subcortical segmentation, non-brain tissue removal, white matter segmentation, tessellation, spherical mapping and registration, and cortical parcellation (see https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all) (Figure 1).

Figure 1 Segmentation map of gray matter nuclei.

For each subcortical gray matter nucleus, including the bilateral thalamus, caudate nucleus, putamen, globus pallidus, hippocampus, amygdala, and nucleus accumbens, the FMRIB Software Library (FSL) tool FMRIB’s Integrated Registration and Segmentation Tool (FIRST) used a deformable mesh model to create a surface mesh composed of a set of vertices and triangles. Since the number of vertices for each structure was fixed, the spatial positions of the corresponding vertices could be compared among participants. The average surface of different groups was calculated, and the specific position differences on these surfaces and their distances from the average surface were observed using the normal vector. A negative index indicated inward deviation from the average surface (contraction), while a positive index indicated outward deviation from the average surface (expansion); the comparison was performed based on the Montreal Neurological Institute (MNI) standard space.

Statistical analysis

Demographic data

The demographic characteristics, clinical parameters, and neuropsychological data of the two groups were compared using SPSS version 26.0. The continuous variables were compared using the Student’s t-test or Mann-Whitney U test, while the categorical variables were compared using the Chi-squared test. A significance threshold of P<0.05 (two-tailed) was applied.

Analysis of gray matter volume and morphology

Vertex-wise comparisons of the subcortical structure spatial profiles of the groups were conducted using general linear models in FSL. Non-parametric permutation testing (1,000 iterations) was employed to derive the group-level statistics, followed by threshold-free cluster enhancement (TFCE) for family-wise error correction across multiple comparisons. Statistical significance was defined as TFCE-corrected P<0.05.

Correlation analysis

Volume values of differentially expressed gray matter nuclei were extracted using FreeSurfer. Partial correlation analyses adjusted for age, education level, sex, and total intracranial volume (TIV) were performed in SPSS 26.0 to examine associations between the subcortical volumes, neurocognitive test scores, and clinical indices. Correlations were considered significant at P<0.05.

Results

Demographic and clinical characteristics

There were no statistically significant differences between the two groups in terms of age, education level, and scores on the anxiety and depression scales (P>0.05). However, there were significant differences in the MMSE and MoCA scores between the two groups (P<0.05) (Table 1).

Analysis of gray matter volume and morphology

The volume of the left thalamus in the DR group (6,979.556±827.230 mm³) was significantly smaller than that in the control group (7,051.274±910.482 mm³). The intergroup difference was statistically significant (t=4.805, P=0.032) (Table 2). The vertex-based morphological analysis revealed that compared with the control group, the morphology of the caudate nucleus in the DR group showed inward contraction in the medial region of the body tail and outward expansion in the dorsolateral region. The morphologic atrophy of the thalamic nuclei was concentrated in the posteromedial [dorsalis medialis (DM)] and thalamic occipital [pulvinar (Pu)] regions, while distension was observed in the ventral region (Figures 2-4).

Figure 2 The bilateral caudate nuclei showed significant differences in the surface area of the nucleus. The blue lines indicate the vertices shifted inward—the areas that are concave inward in the DR group compared to the normal control group; the red indicates the vertices shifted outward—the areas that are convex outward in the DR group compared to the normal control group. DR, diabetic retinopathy.

Figure 3 The bilateral thalami showed significant differences in the surface area of the nucleus. The blue lines indicate the vertices shifted inward—the areas that are concave inward in the DR group compared to the normal control group; the red indicates the vertices shifted outward—the areas that are convex outward in the DR group compared to the normal control group. DR, diabetic retinopathy.

Figure 4 There were significant differences between the DR group and the normal control group in the nucleus surface area. (A) Left caudate; (B) right caudate; (C) left thalamus; (D) right thalamus. DR, diabetic retinopathy.

Correlation

Age, educational level, gender, and TIV were taken as covariates. The partial correlation analysis results revealed that in the DR patients, the gray matter volume values of the bilateral thalamus were negatively correlated with the disease course (r=–0.517, P=0.005; r=–0.412, P=0.029); the deformation index value of the right thalamus was negatively correlated with the MMSE scores (r=–0.433, P=0.013); the deformation index value of the right caudate nucleus was negatively correlated with the SDS scores (r=–0.480, P=0.005) (Figure 5).

Figure 5 Correlation between the volume and deformation index of the subcortical gray matter nuclei in patients with DR and clinical indicators and neuropsychological cognitive outcomes. The gray matter volume values of the bilateral thalamus in the DR patients were negatively correlated with the disease course (r=–0.517, P=0.005; r=–0.412, P=0.029); the deformation index value of the right thalamus was negatively correlated with the MMSE scores (r=–0.433, P=0.013); the deformation index value of the right caudate nucleus was negatively correlated with the SDS scores (r=–0.480, P=0.005). DR, diabetic retinopathy; MMSE, Mini-Mental State Examination; SDS, Self-rating Depression Scale.

Discussion

Subcortical gray matter nuclei form complex neural circuits and networks through multiple neuronal communication pathways, participating in the regulation of sensory, motor, and cognitive functions. Previous studies have shown that the atrophy of these nuclei is a common cerebral structural change in patients with diabetes (17). In this study, we systematically investigated structural abnormalities in the subcortical gray matter nuclei of patients with DR using both volumetric analysis and vertex-based shape analysis. The results revealed that the volume of the left thalamus was significantly smaller in the DR group than the control group. Further, the morphological analysis identified shape changes in both the bilateral thalamus and the caudate nucleus. Given the critical role of subcortical nuclei in information transmission and integration in the brain, these structural changes may represent an underlying mechanism contributing to cognitive behavioral changes and neural dysfunction in DR patients.

The thalamus, a deep nuclear complex in the diencephalon situated between the midbrain and the cerebral cortex, is responsible for integrating signals from multiple regions of the central nervous system (18). Due to its critical anatomical position, it plays a central role in sensory and motor information transmission, cognitive behavior, and visual regulation (19,20), while also facilitating communication between distinct cortical areas (21). Recent animal studies have shown that specific neuronal populations in the superior colliculus relay visual information through the Pu nucleus, suggesting that this pathway has an important function in visual processing (22). The present study observed volume reduction in the left thalamus of the DR patients. These structural changes may disrupt visual information processing pathways, potentially leading to deficits in visuocognitive integration.

Further analysis revealed that the thalamic atrophy in the DR patients was primarily localized to the posteromedial region, including the DM and Pu regions. The DM establishes extensive connections through its distinct cellular subregions with multiple brain areas, including the orbitofrontal cortex, dorsomedial prefrontal cortex, medial temporal lobe, and the frontal eye fields (23-25), underpinning its role in cognitive and emotional regulation. As the largest thalamic association nucleus, the Pu nucleus exhibits specific connectivity patterns: its ventral portion links with the primary visual cortex (V1) and extrastriate visual areas, while its dorsal portion connects with the parietal and frontal cortices (26-28). It plays a key role in integrating visual, motor, and auditory stimuli (29). Emerging evidence highlights the importance of the Pu nucleus in visual pathway development and higher-order cognition, suggesting its impairment may contribute to various cognitive deficits (28). The present study observed morphological reductions in both the DM and Pu regions, indicating that structural abnormalities in these critical nuclei may reduce the efficiency of neural information transmission, thereby partially explaining the visual and cognitive impairments observed in patients with DR.

The caudate nucleus, a pair of C-shaped subcortical structures situated adjacent to the thalamus, plays a critical role in motor execution, cognition, learning memory, and emotional regulation (30,31). Caudate nucleus dysfunction is associated with a variety of neuropsychiatric disorders. The head of the caudate nucleus is closely connected to the medial frontal pole, while the middle part of the caudate nucleus receives input from the entire prefrontal cortex (32). The tail of the caudate nucleus interacts with the inferior temporal lobe, and participates in the processing of visual information and the control of movement (33,34). Lesions in the tail of the caudate nucleus can cause impaired visual discrimination of presented objects (35). The caudate nucleus receives visual input from the cortical association area, integrates and processes visual information, and plays a key role in the coordination of eye movements (36). The extensive visual receptive field in the caudate nucleus can quickly detect and respond to changes in the environment (37). This study observed a localized contraction in the medial portion of the caudate tail, which may be associated with visual deficits, while expansion in the dorsolateral region may represent a compensatory structural reorganization to enhance information processing efficiency in response to declined visual function.

The results of this study showed that the gray matter nuclei in the DR patients displayed both volumetric and morphological changes, and the morphological changes were more extensive than the overall volumetric changes. Morphological analysis does not rely on a predetermined core group; rather, it is based on a large number of vertices, shows differences in shape, and thus provides additional spatial resolution that reflect detailed changes beyond volumetric analysis (15,38). Even if the total gray matter nucleus volume has not changed significantly, different subregions may show morphological changes. Overall ROI-based measurements may not reveal significant differences due to the possibility of compensatory expansion areas. Volume segmentation and shape analyses are two complementary methodologies that together provide more comprehensive information on changes in the nucleus.

This study had several limitations. First, the sample size was relatively small, which might have affected the statistical power of the results to some extent. Second, this study adopted a cross-sectional design without dynamic observation of the disease process in patients with DR or a longitudinal analysis. Thus, future research should seek to meticulously classify DR patients, and conduct a comprehensive analysis of changes in brain structure and function at different stages of DR.

Conclusions

Our findings indicate that DR involves not only retinal pathology but also structural reorganization in the central nervous system. Morphological changes in the thalamus and caudate nucleus may contribute to DR-related neurological deficits by affecting sensory integration, visual processing, and cognitive regulation pathways. Notably, certain structural changes, such as expansion in the dorsolateral region of the caudate nucleus, may reflect compensatory mechanisms in the brain, which provides new insights into the plasticity of brain structure and function throughout disease progression. Future studies incorporating functional imaging and neurobehavioral assessments should be conducted to clarify the relationship between these structural changes and clinical manifestations in patients. From a clinical perspective, these findings suggest that the early structural assessment of subcortical nuclei may help identify DR patients at high risk of cognitive impairment and provide a rationale for the development of targeted interventions and therapeutic 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-24-1964/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-24-1964/dss

Funding: The research was supported by the Scientific Research Project of Jiangsu Provincial Health Commission (No. H2018093), the Fifth Round of the “333 Project” Scientific Research Funding of Jiangsu Province (No. BRA2017175), Six Talent Peaks Project in Jiangsu Province (No. 2015-WSN-119), and the Jiangsu Province 333 High-level Talents Scientific Research Project (No. BRA2020193).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1964/coif). All authors report that this research was supported by the Scientific Research Project of Jiangsu Provincial Health Commission (No. H2018093), the Fifth Round of the “333 Project” Scientific Research Funding of Jiangsu Province (No. BRA2017175), Six Talent Peaks Project in Jiangsu Province (No. 2015-WSN-119), and the Jiangsu Province 333 High-level Talents Scientific Research Project (No. BRA2020193). 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. The trial was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The Ethics Committee of The Affiliated Taizhou People’s Hospital of Nanjing Medical University approved this study (approval No. KY 2022-79-01). Informed consent was obtained from all patients included in the study.

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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