Glymphatic System Impairment in Type II Diabetes Mellitus Adults

Glymphatic System Impairment in Type II Diabetes Mellitus Adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Glymphatic System Impairment in Type II Diabetes Mellitus Adults Bhaswati Roy, Veronica Lubera, Kamal R Singh, Anshita Singh, Megan Carrier, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6467065/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Type 2 diabetes mellitus (T2DM) is associated with multiple systemic complications, including cognitive decline and increased risk of neurodegenerative diseases. The glymphatic system, a brain waste clearance pathway, can be impaired from sleep disturbances common in T2DM, has not been examined. Therefore, the aim was to evaluate glymphatic system in T2DM subjects using diffusion tensor imaging along the perivascular space (DTI-ALPS) index. A total of 78 T2DM adults and 106 healthy controls underwent for brain MRI. Sleep issues were assessed using the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS), and cognition with the Montreal Cognitive Assessment (MoCA). Group differences in DTI-ALPS, sleep metrics, and MoCA scores were assessed with analysis of covariance (covariates, age, sex, and BMI). T2DM patients exhibited higher PSQI (p = 0.03) and ESS (p = 0.004), reflecting poorer sleep quality and increased daytime sleepiness. MoCA scores were significantly lower in T2DM adults (p = 0.001), with impairments emerged in visuospatial skills, attention, and language. Also, significantly reduced DTI-ALPS values appeared in T2DM over controls (p = 0.003). T2DM adults show impaired glymphatic function along with poor sleep quality and day-time issues. The findings indicate that glymphatic dysfunction potentially-driven by metabolic, vascular, and sleep-related disturbances may exacerbate cognitive deficits in T2DM adults. Health sciences/Diseases/Neurological disorders Biological sciences/Neuroscience Sleep Cognition ALPS index Epworth sleepiness scale Magnetic resonance imaging Diffusion tensor imaging Figures Figure 1 Figure 2 Figure 3 Introduction Diabetes is a widespread chronic disorder, with a global prevalence of 10.5%; estimated 537 million adults (20–79 years), and expected to rise to 783 million by 2045 [ 1 ]. Type 2 diabetes mellitus (T2DM) accounts for more than 90% of total diabetes cases [ 2 ], and is associated with significant systemic complications, including cardiovascular, renal, and neural impairments. Along with brain tissue changes [ 3 – 5 ], T2DM increases the risk of cognition decline and neurodegenerative diseases, such as Alzheimer’s disease (AD) [ 6 ]. Multiple factors, including neuroinflammation, oxidative stress, and vascular changes in T2DM are recognized contributors to neural injury, yet the underlying mechanisms linking T2DM to progressive brain tissue changes are not fully understood. Recent studies suggest bidirectional links between T2DM and sleep disturbances, which play a critical role in cognitive health [ 7 – 9 ]. The glymphatic system, a recently identified waste clearance pathway in the brain is optimally regulated during sleep and may play a critical role in maintaining brain homeostasis. Dysfunction of this system could lead to neural changes in T2DM [ 10 ]. The glymphatic system, primarily active during sleep, facilitates the removal of neurotoxic waste products, including β-amyloid and tau protein, which are implicated in neurodegenerative diseases, including the AD [ 11 ]. The system relies on the coordinated function of aquaporin-4 (AQP4) water channels, situated in astrocytic end-feet near cerebral blood vessels, to facilitate the convective flow of cerebrospinal fluid and clear interstitial solutes from brain parenchyma [ 12 ]. Multiple animal studies have shown that glymphatic clearance can be compromised by factors, such as aging [ 13 ], high blood pressure [ 14 ], and metabolic dysfunction [ 15 ]. However, glymphatic system actions in humans with T2DM remains unexamined. Understanding the glymphatic status in T2DM adults could provide insights into the mechanisms of diabetes-associated cognitive decline and higher risks for AD and suggest potential therapeutic targets. T2DM adults commonly experience various sleep issues, including poor sleep quality, insomnia, and increased daytime sleepiness, which can be worsen due to T2DM-related factors, such as obesity, inflammation, and insulin resistance. In addition, T2DM-related sleep disruptions may contribute to poor glycemic control, creating a bidirectional relationship [ 7 ]. Sleep impairment has been associated with onset of cognitive decline at a younger age, dementia, and increased risk of developing AD [ 16 ]. More specifically, a recent meta-analysis conducted between T2DM patients with and without sleep issues showed a 1.55, 1.65, and 3.78 increased risks of AD, cognitive decline, and preclinical AD, respectively [ 16 ]. The buildup of amyloid-plaques and hyperphosphorylation of tau proteins composing neurofibrillary tangles in AD leads to the improper functioning of neurons and their eventual death [ 17 , 18 ]. Therefore, the glymphatic system has the potential to exacerbate risk of dementia and AD in T2DM patients and its mechanisms need to be studied. This study aims to examine the functionality of the glymphatic system in T2DM individuals by utilizing advanced imaging techniques. Magnetic resonance imaging (MRI) based diffusion tensor imaging along the perivascular space (DTI-ALPS) index offers a non-invasive, valuable means to better understand the glymphatic system in T2DM adults. The DTI-ALPS index leverages the principles of DTI to quantify fluid flow dynamics along the perivascular pathways and has been used in multiple conditions [ 19 , 20 ]. Therefore, the goal of our study was to examine glymphatic system function in T2DM adults in comparison to healthy controls using DTI-ALPS index. Materials and Methods Subjects A total of 78 T2DM adults (39 male and 39 female) and 106 control subjects (53 male and 53 female) were recruited for this study. Demographic and clinical data are presented in Table 1 . T2DM patient medication regimens were stable and each subject could lay supine for the MRI. Control subjects were healthy and had no history of hypertension or diabetes and were not on any medications that would lead to neural injury. T2DM patients were recruited from the UCLA Gonda Diabetes Center and healthy controls through flyer advertisement on the UCLA campus and the West Los Angeles area. Multiple conditions, including psychiatric disease (major depressive disorder, schizophrenia, and bipolar disorder), diagnosed neurological disorders (e.g., seizure history, traumatic brain injury), cardiovascular events, such as stroke or heart failure, structural chest or airway abnormalities affecting respiration, renal failure, dementia, cystic fibrosis, chronic obstructive pulmonary disease, substance dependencies, claustrophobia, body weight exceeding 160 kg due to MRI scanner limitations, or metallic implants were considered as exclusion criteria for both T2DM and controls. All T2DM and control subjects provided written informed consent before the study, and research protocol of this study was approved by the UCLA Institutional Review Board. In addition, all methods were performed in accordance with the relevant guidelines and regulations. Quality of Sleep and Day time Sleepiness Both the T2DM and control groups completed questionnaires assessing sleep quality and daytime sleepiness levels. The Pittsburgh Sleep Quality Index (PSQI) was used to measure sleep quality, while daytime sleepiness was evaluated through the Epworth Sleepiness Scale (ESS). Both assessments are well-established tools for assessing sleep quality and fatigue. A score of 5–21 on PSQI indicates poor sleep quality and a score of 10 or higher on ESS suggests excessive day time sleepiness. Cognition Examination Both T2DM and control subjects underwent the Montreal Cognitive Assessment (MoCA) test for rapid evaluation of multiple cognition sub domains, including visuospatial skills, executive functions, attention, memory, language, and orientation. A global MoCA score of 26 or more was considered normal [ 21 ]. Magnetic Resonance Imaging Brain imaging data were acquired using a 3.0-Tesla MRI scanner (Siemens Magnetom Prisma Fit, Erlangen, Germany), with participants positioned in a supine posture. To minimize head movement, foam padding was placed on either side of the head. High-resolution T1-weighted images were acquired with a magnetization-prepared rapid acquisition gradient-echo (MPRAGE) pulse sequence, with the following parameters: repetition time (TR) = 2200 ms, echo time (TE) = 2.41 ms, inversion time = 900 ms, flip angle = 9°, matrix size = 320 × 320, field of view (FOV) = 230 × 230 mm, slice thickness = 0.9 mm, and 192 slices. Proton density (PD) and T2-weighted images were obtained in the axial plane using a dual-echo turbo spin-echo sequence (TR = 10,000 ms; TE1,2 = 12, 124 ms; flip angle = 130°; matrix size = 256 × 256; FOV = 230 × 230; slice thickness = 3.5 mm). For DTI, data were collected using a single-shot echo planar imaging with a twice-refocused spin-echo pulse sequence (TR = 12,200 ms; TE = 87 ms; flip angle = 90°; bandwidth = 1,345 Hz/pixel; matrix size = 128 × 128; FOV = 230 × 230 mm; slice thickness = 1.7 mm, b = 0 and 800 s/mm 2 , diffusion directions = 30). Visual Assessment High-resolution T1-, PD-, and T2-weighted images were visually assessed to identify any major brain abnormalities, including cysts, tumors, or significant brain infarcts. DTI images were also checked for artifacts related to imaging or head motion. No participants included in this study displayed major brain pathologies or imaging artifacts. DTI Indices and ALPS Measurement Diffusion (b = 800 s/mm 2 ) and non-diffusion (b = 0 s/mm 2 ) weighted images were used to calculate diffusion tensor matrices, using the DTI-Studio software [ 22 ]. The average background noise level from outside the brain parenchyma was measured using diffusion- and non-diffusion weighted images to aid in removing of non-brain regions in the tensor calculation. Diffusivity maps, such as D xx , D yy , D zz , D xy , D yz , and D xz maps were computed. The DTI-ALPS index was calculated following the methodology outlined in previous studies [ 20 , 23 ]. Basically, the index was determined by analyzing diffusivity along the perivascular space’s direction over those of projection and association fibers on an axial slice at the level near the lateral ventricles, where the medullary veins are oriented perpendicular to the ventricular wall, which aligns with the x-axis, representing the perivascular space’s direction and the direction of both the projection (z-axis) and the association (y-axis) fibers is perpendicular to the direction of the perivascular space (Fig. 1 ). All the diffusivity maps were normalized to Montreal Neurological Institute (MNI) space. Using unified segmentation method, non-diffusion weighted (b0) images were normalized to MNI space and these normalization parameters were applied to the diffusivity maps. Two sets of regions of interest (ROIs) were placed in the areas corresponding to the projection and association fibers at the level of the lateral ventricle body on the normalized diffusivity maps. These ROIs provided values for diffusivity parameters (D xx , D yy , D zz , D xy , D yz , and D xz ) for each subject in projection and association fibers areas, and using these values, the ALPS index was calculated as: \(\:\text{A}\text{L}\text{P}\text{S}\:\text{i}\text{n}\text{d}\text{e}\text{x}=\frac{({D}_{xxpro}+\:{D}_{xxasc})/2}{\left({D}_{yypro}{+D}_{zzasc}\right)/2}\) where D xxpro and D yypro are D xx and D yy in the area of projection fibers and D xxasc and D zzasc are D xx and D zz in the association fiber areas. Statistical Analysis Differences in demographics and clinical data were analyzed using independent samples and Chi-square tests using the statistical package for the social sciences (SPSS, v 29.0, New York, NY, United States). Diffusivity values and ALPS indices were compared between the T2DM and controls using analysis of covariance (SPSS Software; ANCOVA; covariates, age, sex, and BMI). The results were corrected for multiple comparisons using the Bonferroni correction methods. A value of p < 0.05 was chosen to establish statistical significance. Results Demographic and clinical variables Demographic and other clinical variables of T2DM and control subjects are summarized in Table 1 . No significant differences in age (p = 0.09) or sex (p = 1.0) observed between T2DM and control subjects. However, the body mass index (p < 0.001) was significantly higher in T2DM over controls. The ESS (p = 0.004) and PSQI (p = 0.03) scores were significantly increased in T2DM over control subjects. Global MoCA scores were significantly lower in T2DM compared to controls (p = 0.001), with significant differences in visuospatial (p < 0.001), attention (p = 0.001), and language (p = 0.009) sub domains. Diffusion and ALPS indices The DTI-ALPS index (p = 0.003) was significantly decreased in T2DM compared to control subjects (Fig. 2 ). Also, D xz and D yy from projection fiber areas, and D zz derived from association fiber areas (Fig. 3 ), were significantly different between T2DM and controls (Table 1 ). Discussion We found significantly reduced DTI-ALPS indices, an indicator of impaired glymphatic system function, in T2DM over healthy controls. In addition, the diffusivity measures along projection and association fibers were altered in T2DM patients. The daytime sleepiness and sleep quality, measured using ESS and PSQI, showed enhanced daytime sleepiness symptom and poor sleep quality in T2DM over healthy controls. Also, the low MoCA scores observed in T2DM patients indicate early cognitive impairments associated with the condition. These findings suggest a critical interplay between metabolic dysregulation, glymphatic dysfunction, and sleep disturbances in T2DM adults that may contribute to the cognitive decline, as observed in this study, and pose early risks for dementia and AD. The findings of this study provide evidence that glymphatic system function is significantly impaired in individuals with T2DM compared to healthy controls. The glymphatic system plays a key role in clearing metabolic waste and maintaining neural function and this impairment in glymphatic clearance may contribute to the increased vulnerability of the brain in T2DM adults, including tissue changes [ 3 – 5 ], to exacerbate neurodegenerative and cognitive disorders. In T2DM adults, metabolic dysregulation, inflammation, and vascular dysfunction are prevalent, and the compromised glymphatic function observed in our study could be an underlying factor linking the condition with increased neurocognitive risks. Additionally, this study revealed that individuals with T2DM had higher ESS and worse PSQI scores, indicating greater daytime sleepiness and poorer sleep quality over healthy controls. Sleep is crucial for optimal glymphatic system function, as it is more active during sleep and facilitates cerebrospinal fluid flow, as well as enhances waste clearance from the brain parenchyma. The poor sleep quality observed in T2DM patients may further exacerbate glymphatic dysfunction, and this interplay creates a compounding cycle in which impaired sleep leads to reduced waste clearance, which in turn may contribute to cognition decline. These findings suggest that sleep disruptions in T2DM could be a driving factor in glymphatic system impairment and associated cognitive risks. Understanding this interrelationship highlights the importance of glymphatic system in T2DM and its potential as a therapeutic target to mitigate the early risks of Alzheimer's disease and other neurodegenerative conditions in this high-risk patient population. Recent animal studies investigating glymphatic system function in T2DM adults demonstrated alterations in the MRI markers of brain glymphatic measurements at both an early and advanced stage of diabetes suggesting a sensitive marker that could serve as an early diagnostic indicator for T2DM associated neurovascular damage and cognition decline [ 15 , 24 ]. In addition, the dependency of glymphatic clearance and cerebrospinal fluid- interstitial fluid exchange on aquaporin-4 water channel in different neurological conditions is well known [ 13 , 25 – 28 ], and the animal model of T2DM showed reducing trend in the aquaporin-4 expression with an increased disease severity of the condition, which indicate a similar mechanism may underlie glymphatic dysfunction in T2DM patients and suggest consideration of aquaporin-4 water channel is crucial for assessment of the glymphatic system status. Previous studies on T2DM and metabolic syndrome have shown association with increased neuroinflammation, oxidative stress, and vascular abnormalities [ 29 – 31 ], and all of these can hinder glymphatic system functionality [ 32 – 34 ]. Such disruptions may interfere the clearance of beta-amyloids and tau protein, leading to their accumulation and an increased risk of neurodegeneration. Our study supports the evidence that metabolic and vascular dysfunctions in T2DM are likely contributors to the decline in glymphatic system efficiency. In our study, the glymphatic impairment and high ESS and PSQI scores suggests that metabolic disturbances in T2DM may not only affect peripheral organs, but may also disrupt key processes within the brain, further reinforcing the need for targeted interventions to address glymphatic function in T2DM adults. Moreover, this study emphasizes the potential role of improving sleep in mitigating glymphatic dysfunction in T2DM patients. Given the established connection between glymphatic activity and sleep [ 10 , 20 ], therapeutic approaches that improve sleep quality, such as cognitive-behavioral therapy, lifestyle changes, and possibly medications targeting sleep architecture, could support glymphatic function. These interventions could be particularly valuable for individuals with T2DM who exhibit poor sleep quality and high daytime sleepiness, as improving sleep could enhance waste clearance and reduce the neurocognitive burden associated with T2DM adults. Conclusions This study provides robust evidence of impaired glymphatic function in individuals with T2DM adults, as reflected by significantly reduced DTI-ALPS index compared to healthy controls. Higher daytime sleepiness and worse sleep quality in T2DM patients further highlight the multifaceted impact of metabolic dysregulation impacting glymphatic system. The abnormal MoCA scores observed in T2DM patients emphasize the cognition impairments associated with glymphatic dysfunction and sleep disturbances. The observed glymphatic dysfunction, potentially driven by metabolic, vascular, and inflammatory abnormalities, suggests a mechanism linking T2DM with cognitive decline and the importance of targeting glymphatic system as a therapeutic strategy. Sleep-targeted therapies, such as cognitive-behavioral therapy, lifestyle modifications, and sleep-promoting medications, hold promise for mitigating glymphatic dysfunction and enhancing waste clearance in this high-risk population. The findings pave the way for research into therapeutic strategies that could improve glymphatic function and protect against neurodegenerative disorders and early risks for dementia and AD in T2DM adults. Declarations Data and Resource Availability The datasets generated during and/or analyzed in the current study are available from the corresponding author upon reasonable request. Conflict of Interest None Author Contribution R.K. were involved in the conception and design of the study. B.R., M.C., S.E.C, M.J.F., and R.K. were involved in the conduct of the study. B.R. and V.L. performed the analysis and interpretation of the results and wrote the first draft of the manuscript. KS and A.S edited the manuscript and all authors edited, reviewed, and approved the final version. R.K. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Acknowledgements: Grant Support : This research work was supported by National Institutes of Health R01 NR017190 and 3R01 NR017190-03S1. RK and BR were supported by 1R21 AG085268-01. Data Availability The datasets generated during and/or analyzed in the current study are available from the corresponding author upon reasonable request. References Sun, H. et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes research and clinical practice 183 , 109119, doi:10.1016/j.diabres.2021.109119 (2022). Willems, R. et al. Cost effectiveness review of text messaging, smartphone application, and website interventions targeting T2DM or hypertension. npj Digital Medicine 6 , 150, doi:10.1038/s41746-023-00876-x (2023). Roy, B. et al. Regional Brain Gray Matter Changes in Patients with Type 2 Diabetes Mellitus. Scientific reports 10 , 9925, doi:10.1038/s41598-020-67022-5 (2020). Roy, B., Choi, S. E., Freeby, M. J. & Kumar, R. Microstructural brain tissue changes contribute to cognitive and mood deficits in adults with type 2 diabetes mellitus. Scientific reports 13 , 9636, doi:10.1038/s41598-023-35522-9 (2023). Choi, S. E. et al. Prefrontal cortex brain damage and glycemic control in patients with type 2 diabetes. Journal of diabetes 12 , 465-473, doi:10.1111/1753-0407.13019 (2020). Butterfield, D. A., Di Domenico, F. & Barone, E. Elevated risk of type 2 diabetes for development of Alzheimer disease: A key role for oxidative stress in brain. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease 1842 , 1693-1706, doi:https://doi.org/10.1016/j.bbadis.2014.06.010 (2014). Brzecka, A. et al. Sleep Disturbances and Cognitive Impairment in the Course of Type 2 Diabetes-A Possible Link. Current neuropharmacology 19 , 78-91, doi:10.2174/1570159x18666200309101750 (2021). Holingue, C., Wennberg, A., Berger, S., Polotsky, V. Y. & Spira, A. P. Disturbed sleep and diabetes: A potential nexus of dementia risk. Metabolism 84 , 85-93, doi:https://doi.org/10.1016/j.metabol.2018.01.021 (2018). Henson, J. et al. Waking Up to the Importance of Sleep in Type 2 Diabetes Management: A Narrative Review. Diabetes Care 47 , 331-343, doi:10.2337/dci23-0037 (2024). Reddy, O. C. & van der Werf, Y. D. The Sleeping Brain: Harnessing the Power of the Glymphatic System through Lifestyle Choices. Brain sciences 10 , doi:10.3390/brainsci10110868 (2020). Jessen, N. A., Munk, A. S., Lundgaard, I. & Nedergaard, M. The Glymphatic System: A Beginner's Guide. Neurochemical research 40 , 2583-2599, doi:10.1007/s11064-015-1581-6 (2015). Mader, S. & Brimberg, L. Aquaporin-4 Water Channel in the Brain and Its Implication for Health and Disease. Cells 8 , doi:10.3390/cells8020090 (2019). Kress, B. T. et al. Impairment of paravascular clearance pathways in the aging brain. Ann Neurol 76 , 845-861, doi:10.1002/ana.24271 (2014). Mortensen, K. N., Sanggaard, S. & Mestre, H. Impaired Glymphatic Transport in Spontaneously Hypertensive Rats. Journal of Neuroscience 39 , 6365-6377, doi:10.1523/jneurosci.1974-18.2019 (2019). Jiang, Q. et al. Impairment of the glymphatic system after diabetes. J Cereb Blood Flow Metab 37 , 1326-1337, doi:10.1177/0271678x16654702 (2017). Andrade, A. G., Bubu, O. M., Varga, A. W. & Osorio, R. S. The Relationship between Obstructive Sleep Apnea and Alzheimer's Disease. Journal of Alzheimer's disease : JAD 64 , S255-s270, doi:10.3233/jad-179936 (2018). Frozza, R. L., Lourenco, M. V. & De Felice, F. G. Challenges for Alzheimer's Disease Therapy: Insights from Novel Mechanisms Beyond Memory Defects. Frontiers in neuroscience 12 , 37, doi:10.3389/fnins.2018.00037 (2018). Zuroff, L., Daley, D., Black, K. L. & Koronyo-Hamaoui, M. Clearance of cerebral Aβ in Alzheimer's disease: reassessing the role of microglia and monocytes. Cellular and Molecular Life Sciences 74 , 2167-2201, doi:10.1007/s00018-017-2463-7 (2017). Roy, B., Kumar, R., Sarovich, S. D. & Vacas, S. The Role of the Glymphatic System in Perioperative Neurocognitive Disorders. Journal of neurosurgical anesthesiology , doi:10.1097/ana.0000000000000973 (2024). Roy, B. et al. Impaired Glymphatic System Actions in Obstructive Sleep Apnea Adults. Frontiers in neuroscience 16 , 884234, doi:10.3389/fnins.2022.884234 (2022). Nasreddine, Z. S. et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society 53 , 695-699, doi:10.1111/j.1532-5415.2005.53221.x (2005). Jiang, H., van Zijl, P. C., Kim, J., Pearlson, G. D. & Mori, S. DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. Computer methods and programs in biomedicine 81 , 106-116, doi:10.1016/j.cmpb.2005.08.004 (2006). Taoka, T. et al. Evaluation of glymphatic system activity with the diffusion MR technique: diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer's disease cases. Japanese journal of radiology 35 , 172-178, doi:10.1007/s11604-017-0617-z (2017). Boyd, E. D. et al. The Glymphatic Response to the Development of Type 2 Diabetes. Biomedicines 12 , doi:10.3390/biomedicines12020401 (2024). Iliff, J. J. et al. A paravascular pathway facilitates CSF flow through the brain parenchyma and the clearance of interstitial solutes, including amyloid β. Science translational medicine 4 , 147ra111, doi:10.1126/scitranslmed.3003748 (2012). Plog, B. A. et al. Biomarkers of traumatic injury are transported from brain to blood via the glymphatic system. Journal of Neuroscience 35 , 518-526, doi:10.1523/jneurosci.3742-14.2015 (2015). Hasan-Olive, M. M., Enger, R., Hansson, H. A. & Nagelhus, E. A. Loss of perivascular aquaporin-4 in idiopathic normal pressure hydrocephalus. Glia 67 , 91-100, doi:10.1002/glia.23528 (2019). Iliff, J. J., Chen, M. J., Plog, B. A., Zeppenfeld, D. M. & Soltero, M. Impairment of glymphatic pathway function promotes tau pathology after traumatic brain injury. J ournal of Neuroscience 34 , 16180-16193, doi:10.1523/jneurosci.3020-14.2014 (2014). Oguntibeju, O. O. Type 2 diabetes mellitus, oxidative stress and inflammation: examining the links. International journal of physiology, pathophysiology and pharmacology 11 , 45-63 (2019). Bhatti, J. S. et al. Oxidative stress in the pathophysiology of type 2 diabetes and related complications: Current therapeutics strategies and future perspectives. Free Radical Biology and Medicine 184 , 114-134, doi:https://doi.org/10.1016/j.freeradbiomed.2022.03.019 (2022). Domingueti, C. P. et al. Diabetes mellitus: The linkage between oxidative stress, inflammation, hypercoagulability and vascular complications. Journal of Diabetes and its Complications 30 , 738-745, doi:https://doi.org/10.1016/j.jdiacomp.2015.12.018 (2016). Mogensen, F. L. & Delle, C. The Glymphatic System (En)during Inflammation. International journal of molecular sciences 22 , doi:10.3390/ijms22147491 (2021). Gędek, A., Koziorowski, D. & Szlufik, S. Assessment of factors influencing glymphatic activity and implications for clinical medicine. Frontiers in neurology 14 , 1232304, doi:10.3389/fneur.2023.1232304 (2023). Chen, H. L. et al. Associations among Cognitive Functions, Plasma DNA, and Diffusion Tensor Image along the Perivascular Space (DTI-ALPS) in Patients with Parkinson's Disease. Oxidative medicine and cellular longevity 2021 , 4034509, doi:10.1155/2021/4034509 (2021). Table Table 1 : Demographics, clinical variables, diffusivity and DTI-ALPS indices of T2DM patients and healthy controls. Variables T2DM (mean ± SD) [n=78] Controls (mean ± SD) [n=106] p values Age (years) 56.5 ± 7.5 54.7 ± 6.5 0.09 Sex (Male:Female) 39:39 53:53 1.0 Ethnicity African American 7 (9.0%) 16 (13.2%) Asian 16 (20.5%) 35 (28.9%) Hispanic 24 (30.8%) 20 (16.5%) White 23 (29.5%) 44 (36.4%) Other 7 (9.0%) 6 (5.0%) Unknown 1 0 BMI (kg/m 2 ) 29.4 ± 5.0 26.3± 4.2 <0.001 Heart Rate (beats/min) 77.3 ± 11.8 (n=68) 71.7 ± 10.9 0.002 Systolic BP (mmHg) 127.8 ± 15.3 (n=69) 120.7 ± 17.2 0.006 Diastolic BP (mmHg) 78.6 ± 10.4 (n=69) 78.8 ± 14.2 0.92 PSQI 5.7 ± 3.6 4.6 ± 2.8 (n=105) 0.03 ESS 6.7 ± 3.9 (n=69) 5.1 ± 3.3 0.004 Diabetes Duration (years) 10.7 ± 8.1 - A1c 7.04 ± 1.3 5.3 ± 0.4 (n=52) <0.001 MoCA Total Visuospatial Naming Attention Language Abstraction Delayed Recall Orientation 25.9 ± 2.5 4.2 ± 0.9 2.9 ± 0.3 5.1 ± 1.1 2.2 ± 1.0 1.9 ± 0.3 3.5 ± 1.4 5.9 ± 0.2 27.1 ± 2.3 4.5 ± 0.7 3.0 ± 0.2 5.6 ± 0.8 2.5 ± 0.7 2.0 ± 0.2 3.5 ± 1.5 6.0 ± 0.1 0.001 <0.001 0.27 0.001 0.009 0.13 0.98 0.12 Periventricular Projection Fiber Area (mean ± SD, x 10 -3 mm 2 /s) Periventricular Association Fiber Area (mean ± SD, x 10 -3 mm 2 /s) T2DM Controls p values T2DM Controls p values Dxx 0.72 ± 0.05 0.72 ± 0.05 1.0 0.69 ± 0.06 0.69 ± 0.06 0.43 Dxy 0.04 ± 0.01 0.05 ± 0.01 0.42 0.12 ± 0.03 0.12 ± 0.03 0.26 Dxz 0.04 ± 0.01 0.05 ± 0.01 0.001* 0.06 ± 0.01 0.06 ± 0.01 1 Dyy 0.61 ± 0.06 0.59 ± 0.06 0.03* 0.99 ± 0.06 1.01 ± 0.06 0.38 Dyz 0.20 ± 0.03 0.20 ± 0.03 0.26 0.08 ± 0.03 0.09 ± 0.03 0.03* Dzz 0.93 ± 0.07 0.93 ± 0.07 1.0 0.50 ± 0.05 0.47 ± 0.05 <0.001* T2DM (mean ± SD) Controls (mean ± SD) p values ALPS 1.296 ± 0.11 1.35 ± 0.11 0.003 Table Legend: ALPS = analysis along the perivascular space; T2DM = Type 2 Diabetes Miletus; SD = Standard Deviation; BP = Blood Pressure; BMI = Body Mass Index; MoCA = Montreal Cognitive Assessment; PSQI = Pittsburgh Sleep Quality Index; ESS = Epworth Sleepiness Scale, Dxx= diffusivity in x-direction; Dxy = diffusivity in x-y direction; Dxz = diffusivity in x-z direction; Dyy = diffusivity in y direction; Dyz = diffusivity in y-z direction; Dzz = diffusivity in z direction. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 04 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 22 Sep, 2025 Reviews received at journal 21 Sep, 2025 Reviewers agreed at journal 03 Sep, 2025 Reviewers agreed at journal 04 Aug, 2025 Reviews received at journal 09 Jul, 2025 Reviewers agreed at journal 01 Jul, 2025 Reviewers invited by journal 27 Jun, 2025 Editor assigned by journal 20 May, 2025 Editor invited by journal 21 Apr, 2025 Submission checks completed at journal 21 Apr, 2025 First submitted to journal 16 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Angeles","correspondingAuthor":false,"prefix":"","firstName":"Veronica","middleName":"","lastName":"Lubera","suffix":""},{"id":478611477,"identity":"01a6bdc1-c120-4c53-a116-c9114945b30c","order_by":2,"name":"Kamal R Singh","email":"","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":false,"prefix":"","firstName":"Kamal","middleName":"R","lastName":"Singh","suffix":""},{"id":478611478,"identity":"df3932a4-8553-487f-ac54-b1eddedeb47f","order_by":3,"name":"Anshita Singh","email":"","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":false,"prefix":"","firstName":"Anshita","middleName":"","lastName":"Singh","suffix":""},{"id":478611480,"identity":"88d0a17e-c9a4-4d1c-9e5b-a53daa8fc3c3","order_by":4,"name":"Megan Carrier","email":"","orcid":"","institution":"University of California at Los Angeles","correspondingAuthor":false,"prefix":"","firstName":"Megan","middleName":"","lastName":"Carrier","suffix":""},{"id":478611481,"identity":"cd1bd76c-a00e-4fe1-91bd-2266dc1da3c6","order_by":5,"name":"Sarah E Choi","email":"","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"E","lastName":"Choi","suffix":""},{"id":478611482,"identity":"c78b2fee-d8a3-4286-8abd-7154f2af0490","order_by":6,"name":"Matthew J Freeby","email":"","orcid":"","institution":"University of California at Los Angeles","correspondingAuthor":false,"prefix":"","firstName":"Matthew","middleName":"J","lastName":"Freeby","suffix":""},{"id":478611483,"identity":"7cd3b64f-89e7-4943-b8dc-cb91a9f457f8","order_by":7,"name":"Rajesh Kumar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYDACHjBpA8QJEAE+hCheLWkQLQeAFBuRWg6ToMW854zphp97zkfzs+cefPyB4bA8G/sBxgdv23BrkTnbY3az59nt3Jk975INDjAcNmzjSWA2nItHiwQ/j9kNngO3czfcyDGTAGpJYGNIYJPmJaDl5p8D53L338gx/wHWwv+A/TdeLbw9Zrd5DhzI3SCRY8YA1iKRwMaMVwvPsbLbMgeSc2eceWMsccYg3bBN4mGz5Jxz+LQkb7v55oBdbn97juGHigpreX7+5IMf3pTh1oIGDEAEYwPR6kfBKBgFo2AUYAcAJh9RfuI88G4AAAAASUVORK5CYII=","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":true,"prefix":"","firstName":"Rajesh","middleName":"","lastName":"Kumar","suffix":""}],"badges":[],"createdAt":"2025-04-17 01:53:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6467065/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6467065/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-36573-4","type":"published","date":"2026-02-04T15:58:15+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85858427,"identity":"414a360d-ed93-487e-93db-e6c8623636f6","added_by":"auto","created_at":"2025-07-02 11:56:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3540261,"visible":true,"origin":"","legend":"\u003cp\u003eRegions of interest (ROIs) taken for imaging are marked with a white star and close-up panel shows different fibers running through the projection (blue), association (green), and subcortical (red) areas along with directionality.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6467065/v1/23098a16824f1985a08cd163.png"},{"id":85858426,"identity":"1fd97770-54d8-4c23-8d6d-447d34bed8e9","added_by":"auto","created_at":"2025-07-02 11:56:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1461203,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots of perivascular space indexes in healthy controls and T2DM patients: (A) PSQI, (B) ESS, and (C) ALPS indexes.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6467065/v1/5e2f079886f44062ef36b18b.png"},{"id":85858435,"identity":"d8d06888-a5d9-4afe-952f-7d36beba1f1d","added_by":"auto","created_at":"2025-07-02 11:56:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2544452,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots of perivascular space indexes in T2DM patients and healthy controls: (A) Dxz in projection fibers, (B) Dyy, (C) Dzz in association fibers, (D) fractional anisotropy, (E) Dyz, and (F) radial diffusivity.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6467065/v1/03a950501e44262f3a756bda.png"},{"id":102234436,"identity":"6beb00a7-d155-43d4-a0d1-da78398c0dc1","added_by":"auto","created_at":"2026-02-09 16:11:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7475324,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6467065/v1/d7f8fcd7-d9c6-4f33-bedc-8c80ee5e7dbc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Glymphatic System Impairment in Type II Diabetes Mellitus Adults","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes is a widespread chronic disorder, with a global prevalence of 10.5%; estimated 537\u0026nbsp;million adults (20\u0026ndash;79 years), and expected to rise to 783\u0026nbsp;million by 2045 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Type 2 diabetes mellitus (T2DM) accounts for more than 90% of total diabetes cases [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], and is associated with significant systemic complications, including cardiovascular, renal, and neural impairments. Along with brain tissue changes [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], T2DM increases the risk of cognition decline and neurodegenerative diseases, such as Alzheimer\u0026rsquo;s disease (AD) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Multiple factors, including neuroinflammation, oxidative stress, and vascular changes in T2DM are recognized contributors to neural injury, yet the underlying mechanisms linking T2DM to progressive brain tissue changes are not fully understood. Recent studies suggest bidirectional links between T2DM and sleep disturbances, which play a critical role in cognitive health [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The glymphatic system, a recently identified waste clearance pathway in the brain is optimally regulated during sleep and may play a critical role in maintaining brain homeostasis. Dysfunction of this system could lead to neural changes in T2DM [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe glymphatic system, primarily active during sleep, facilitates the removal of neurotoxic waste products, including β-amyloid and tau protein, which are implicated in neurodegenerative diseases, including the AD [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The system relies on the coordinated function of aquaporin-4 (AQP4) water channels, situated in astrocytic end-feet near cerebral blood vessels, to facilitate the convective flow of cerebrospinal fluid and clear interstitial solutes from brain parenchyma [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Multiple animal studies have shown that glymphatic clearance can be compromised by factors, such as aging [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], high blood pressure [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and metabolic dysfunction [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, glymphatic system actions in humans with T2DM remains unexamined. Understanding the glymphatic status in T2DM adults could provide insights into the mechanisms of diabetes-associated cognitive decline and higher risks for AD and suggest potential therapeutic targets.\u003c/p\u003e \u003cp\u003eT2DM adults commonly experience various sleep issues, including poor sleep quality, insomnia, and increased daytime sleepiness, which can be worsen due to T2DM-related factors, such as obesity, inflammation, and insulin resistance. In addition, T2DM-related sleep disruptions may contribute to poor glycemic control, creating a bidirectional relationship [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Sleep impairment has been associated with onset of cognitive decline at a younger age, dementia, and increased risk of developing AD [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. More specifically, a recent meta-analysis conducted between T2DM patients with and without sleep issues showed a 1.55, 1.65, and 3.78 increased risks of AD, cognitive decline, and preclinical AD, respectively [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The buildup of amyloid-plaques and hyperphosphorylation of tau proteins composing neurofibrillary tangles in AD leads to the improper functioning of neurons and their eventual death [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Therefore, the glymphatic system has the potential to exacerbate risk of dementia and AD in T2DM patients and its mechanisms need to be studied.\u003c/p\u003e \u003cp\u003eThis study aims to examine the functionality of the glymphatic system in T2DM individuals by utilizing advanced imaging techniques. Magnetic resonance imaging (MRI) based diffusion tensor imaging along the perivascular space (DTI-ALPS) index offers a non-invasive, valuable means to better understand the glymphatic system in T2DM adults. The DTI-ALPS index leverages the principles of DTI to quantify fluid flow dynamics along the perivascular pathways and has been used in multiple conditions [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Therefore, the goal of our study was to examine glymphatic system function in T2DM adults in comparison to healthy controls using DTI-ALPS index.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003eA total of 78 T2DM adults (39 male and 39 female) and 106 control subjects (53 male and 53 female) were recruited for this study. Demographic and clinical data are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. T2DM patient medication regimens were stable and each subject could lay supine for the MRI. Control subjects were healthy and had no history of hypertension or diabetes and were not on any medications that would lead to neural injury. T2DM patients were recruited from the UCLA Gonda Diabetes Center and healthy controls through flyer advertisement on the UCLA campus and the West Los Angeles area. Multiple conditions, including psychiatric disease (major depressive disorder, schizophrenia, and bipolar disorder), diagnosed neurological disorders (e.g., seizure history, traumatic brain injury), cardiovascular events, such as stroke or heart failure, structural chest or airway abnormalities affecting respiration, renal failure, dementia, cystic fibrosis, chronic obstructive pulmonary disease, substance dependencies, claustrophobia, body weight exceeding 160 kg due to MRI scanner limitations, or metallic implants were considered as exclusion criteria for both T2DM and controls. All T2DM and control subjects provided written informed consent before the study, and research protocol of this study was approved by the UCLA Institutional Review Board. In addition, all methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eQuality of Sleep and Day time Sleepiness\u003c/h3\u003e\n\u003cp\u003eBoth the T2DM and control groups completed questionnaires assessing sleep quality and daytime sleepiness levels. The Pittsburgh Sleep Quality Index (PSQI) was used to measure sleep quality, while daytime sleepiness was evaluated through the Epworth Sleepiness Scale (ESS). Both assessments are well-established tools for assessing sleep quality and fatigue. A score of 5\u0026ndash;21 on PSQI indicates poor sleep quality and a score of 10 or higher on ESS suggests excessive day time sleepiness.\u003c/p\u003e\n\u003ch3\u003eCognition Examination\u003c/h3\u003e\n\u003cp\u003eBoth T2DM and control subjects underwent the Montreal Cognitive Assessment (MoCA) test for rapid evaluation of multiple cognition sub domains, including visuospatial skills, executive functions, attention, memory, language, and orientation. A global MoCA score of 26 or more was considered normal [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eMagnetic Resonance Imaging\u003c/h3\u003e\n\u003cp\u003eBrain imaging data were acquired using a 3.0-Tesla MRI scanner (Siemens Magnetom Prisma Fit, Erlangen, Germany), with participants positioned in a supine posture. To minimize head movement, foam padding was placed on either side of the head. High-resolution T1-weighted images were acquired with a magnetization-prepared rapid acquisition gradient-echo (MPRAGE) pulse sequence, with the following parameters: repetition time (TR)\u0026thinsp;=\u0026thinsp;2200 ms, echo time (TE)\u0026thinsp;=\u0026thinsp;2.41 ms, inversion time\u0026thinsp;=\u0026thinsp;900 ms, flip angle\u0026thinsp;=\u0026thinsp;9\u0026deg;, matrix size\u0026thinsp;=\u0026thinsp;320 \u0026times; 320, field of view (FOV)\u0026thinsp;=\u0026thinsp;230 \u0026times; 230 mm, slice thickness\u0026thinsp;=\u0026thinsp;0.9 mm, and 192 slices. Proton density (PD) and T2-weighted images were obtained in the axial plane using a dual-echo turbo spin-echo sequence (TR\u0026thinsp;=\u0026thinsp;10,000 ms; TE1,2\u0026thinsp;=\u0026thinsp;12, 124 ms; flip angle\u0026thinsp;=\u0026thinsp;130\u0026deg;; matrix size\u0026thinsp;=\u0026thinsp;256 \u0026times; 256; FOV\u0026thinsp;=\u0026thinsp;230 \u0026times; 230; slice thickness\u0026thinsp;=\u0026thinsp;3.5 mm). For DTI, data were collected using a single-shot echo planar imaging with a twice-refocused spin-echo pulse sequence (TR\u0026thinsp;=\u0026thinsp;12,200 ms; TE\u0026thinsp;=\u0026thinsp;87 ms; flip angle\u0026thinsp;=\u0026thinsp;90\u0026deg;; bandwidth\u0026thinsp;=\u0026thinsp;1,345 Hz/pixel; matrix size\u0026thinsp;=\u0026thinsp;128 \u0026times; 128; FOV\u0026thinsp;=\u0026thinsp;230 \u0026times; 230 mm; slice thickness\u0026thinsp;=\u0026thinsp;1.7 mm, b\u0026thinsp;=\u0026thinsp;0 and 800 s/mm\u003csup\u003e2\u003c/sup\u003e, diffusion directions\u0026thinsp;=\u0026thinsp;30).\u003c/p\u003e\n\u003ch3\u003eVisual Assessment\u003c/h3\u003e\n\u003cp\u003eHigh-resolution T1-, PD-, and T2-weighted images were visually assessed to identify any major brain abnormalities, including cysts, tumors, or significant brain infarcts. DTI images were also checked for artifacts related to imaging or head motion. No participants included in this study displayed major brain pathologies or imaging artifacts.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDTI Indices and ALPS Measurement\u003c/h2\u003e \u003cp\u003eDiffusion (b\u0026thinsp;=\u0026thinsp;800 s/mm\u003csup\u003e2\u003c/sup\u003e) and non-diffusion (b\u0026thinsp;=\u0026thinsp;0 s/mm\u003csup\u003e2\u003c/sup\u003e) weighted images were used to calculate diffusion tensor matrices, using the DTI-Studio software [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The average background noise level from outside the brain parenchyma was measured using diffusion- and non-diffusion weighted images to aid in removing of non-brain regions in the tensor calculation. Diffusivity maps, such as D\u003csub\u003exx\u003c/sub\u003e, D\u003csub\u003eyy\u003c/sub\u003e, D\u003csub\u003ezz\u003c/sub\u003e, D\u003csub\u003exy\u003c/sub\u003e, D\u003csub\u003eyz\u003c/sub\u003e, and D\u003csub\u003exz\u003c/sub\u003e maps were computed. The DTI-ALPS index was calculated following the methodology outlined in previous studies [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Basically, the index was determined by analyzing diffusivity along the perivascular space\u0026rsquo;s direction over those of projection and association fibers on an axial slice at the level near the lateral ventricles, where the medullary veins are oriented perpendicular to the ventricular wall, which aligns with the x-axis, representing the perivascular space\u0026rsquo;s direction and the direction of both the projection (z-axis) and the association (y-axis) fibers is perpendicular to the direction of the perivascular space (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAll the diffusivity maps were normalized to Montreal Neurological Institute (MNI) space. Using unified segmentation method, non-diffusion weighted (b0) images were normalized to MNI space and these normalization parameters were applied to the diffusivity maps. Two sets of regions of interest (ROIs) were placed in the areas corresponding to the projection and association fibers at the level of the lateral ventricle body on the normalized diffusivity maps. These ROIs provided values for diffusivity parameters (D\u003csub\u003exx\u003c/sub\u003e, D\u003csub\u003eyy\u003c/sub\u003e, D\u003csub\u003ezz\u003c/sub\u003e, D\u003csub\u003exy\u003c/sub\u003e, D\u003csub\u003eyz\u003c/sub\u003e, and D\u003csub\u003exz\u003c/sub\u003e) for each subject in projection and association fibers areas, and using these values, the ALPS index was calculated as: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{A}\\text{L}\\text{P}\\text{S}\\:\\text{i}\\text{n}\\text{d}\\text{e}\\text{x}=\\frac{({D}_{xxpro}+\\:{D}_{xxasc})/2}{\\left({D}_{yypro}{+D}_{zzasc}\\right)/2}\\)\u003c/span\u003e\u003c/span\u003e where D\u003csub\u003exxpro\u003c/sub\u003e and D\u003csub\u003eyypro\u003c/sub\u003e are D\u003csub\u003exx\u003c/sub\u003e and D\u003csub\u003eyy\u003c/sub\u003e in the area of projection fibers and D\u003csub\u003exxasc\u003c/sub\u003e and D\u003csub\u003ezzasc\u003c/sub\u003e are D\u003csub\u003exx\u003c/sub\u003e and D\u003csub\u003ezz\u003c/sub\u003e in the association fiber areas.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDifferences in demographics and clinical data were analyzed using independent samples and Chi-square tests using the statistical package for the social sciences (SPSS, v 29.0, New York, NY, United States). Diffusivity values and ALPS indices were compared between the T2DM and controls using analysis of covariance (SPSS Software; ANCOVA; covariates, age, sex, and BMI). The results were corrected for multiple comparisons using the Bonferroni correction methods. A value of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was chosen to establish statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDemographic and clinical variables\u003c/h2\u003e \u003cp\u003eDemographic and other clinical variables of T2DM and control subjects are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. No significant differences in age (p\u0026thinsp;=\u0026thinsp;0.09) or sex (p\u0026thinsp;=\u0026thinsp;1.0) observed between T2DM and control subjects. However, the body mass index (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was significantly higher in T2DM over controls. The ESS (p\u0026thinsp;=\u0026thinsp;0.004) and PSQI (p\u0026thinsp;=\u0026thinsp;0.03) scores were significantly increased in T2DM over control subjects. Global MoCA scores were significantly lower in T2DM compared to controls (p\u0026thinsp;=\u0026thinsp;0.001), with significant differences in visuospatial (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), attention (p\u0026thinsp;=\u0026thinsp;0.001), and language (p\u0026thinsp;=\u0026thinsp;0.009) sub domains.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDiffusion and ALPS indices\u003c/h2\u003e \u003cp\u003eThe DTI-ALPS index (p\u0026thinsp;=\u0026thinsp;0.003) was significantly decreased in T2DM compared to control subjects (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Also, D\u003csub\u003exz\u003c/sub\u003e and D\u003csub\u003eyy\u003c/sub\u003e from projection fiber areas, and D\u003csub\u003ezz\u003c/sub\u003e derived from association fiber areas (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), were significantly different between T2DM and controls (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe found significantly reduced DTI-ALPS indices, an indicator of impaired glymphatic system function, in T2DM over healthy controls. In addition, the diffusivity measures along projection and association fibers were altered in T2DM patients. The daytime sleepiness and sleep quality, measured using ESS and PSQI, showed enhanced daytime sleepiness symptom and poor sleep quality in T2DM over healthy controls. Also, the low MoCA scores observed in T2DM patients indicate early cognitive impairments associated with the condition. These findings suggest a critical interplay between metabolic dysregulation, glymphatic dysfunction, and sleep disturbances in T2DM adults that may contribute to the cognitive decline, as observed in this study, and pose early risks for dementia and AD.\u003c/p\u003e \u003cp\u003eThe findings of this study provide evidence that glymphatic system function is significantly impaired in individuals with T2DM compared to healthy controls. The glymphatic system plays a key role in clearing metabolic waste and maintaining neural function and this impairment in glymphatic clearance may contribute to the increased vulnerability of the brain in T2DM adults, including tissue changes [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], to exacerbate neurodegenerative and cognitive disorders. In T2DM adults, metabolic dysregulation, inflammation, and vascular dysfunction are prevalent, and the compromised glymphatic function observed in our study could be an underlying factor linking the condition with increased neurocognitive risks.\u003c/p\u003e \u003cp\u003eAdditionally, this study revealed that individuals with T2DM had higher ESS and worse PSQI scores, indicating greater daytime sleepiness and poorer sleep quality over healthy controls. Sleep is crucial for optimal glymphatic system function, as it is more active during sleep and facilitates cerebrospinal fluid flow, as well as enhances waste clearance from the brain parenchyma. The poor sleep quality observed in T2DM patients may further exacerbate glymphatic dysfunction, and this interplay creates a compounding cycle in which impaired sleep leads to reduced waste clearance, which in turn may contribute to cognition decline. These findings suggest that sleep disruptions in T2DM could be a driving factor in glymphatic system impairment and associated cognitive risks. Understanding this interrelationship highlights the importance of glymphatic system in T2DM and its potential as a therapeutic target to mitigate the early risks of Alzheimer's disease and other neurodegenerative conditions in this high-risk patient population.\u003c/p\u003e \u003cp\u003eRecent animal studies investigating glymphatic system function in T2DM adults demonstrated alterations in the MRI markers of brain glymphatic measurements at both an early and advanced stage of diabetes suggesting a sensitive marker that could serve as an early diagnostic indicator for T2DM associated neurovascular damage and cognition decline [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In addition, the dependency of glymphatic clearance and cerebrospinal fluid- interstitial fluid exchange on aquaporin-4 water channel in different neurological conditions is well known [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], and the animal model of T2DM showed reducing trend in the aquaporin-4 expression with an increased disease severity of the condition, which indicate a similar mechanism may underlie glymphatic dysfunction in T2DM patients and suggest consideration of aquaporin-4 water channel is crucial for assessment of the glymphatic system status.\u003c/p\u003e \u003cp\u003ePrevious studies on T2DM and metabolic syndrome have shown association with increased neuroinflammation, oxidative stress, and vascular abnormalities [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], and all of these can hinder glymphatic system functionality [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Such disruptions may interfere the clearance of beta-amyloids and tau protein, leading to their accumulation and an increased risk of neurodegeneration. Our study supports the evidence that metabolic and vascular dysfunctions in T2DM are likely contributors to the decline in glymphatic system efficiency. In our study, the glymphatic impairment and high ESS and PSQI scores suggests that metabolic disturbances in T2DM may not only affect peripheral organs, but may also disrupt key processes within the brain, further reinforcing the need for targeted interventions to address glymphatic function in T2DM adults.\u003c/p\u003e \u003cp\u003eMoreover, this study emphasizes the potential role of improving sleep in mitigating glymphatic dysfunction in T2DM patients. Given the established connection between glymphatic activity and sleep [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], therapeutic approaches that improve sleep quality, such as cognitive-behavioral therapy, lifestyle changes, and possibly medications targeting sleep architecture, could support glymphatic function. These interventions could be particularly valuable for individuals with T2DM who exhibit poor sleep quality and high daytime sleepiness, as improving sleep could enhance waste clearance and reduce the neurocognitive burden associated with T2DM adults.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provides robust evidence of impaired glymphatic function in individuals with T2DM adults, as reflected by significantly reduced DTI-ALPS index compared to healthy controls. Higher daytime sleepiness and worse sleep quality in T2DM patients further highlight the multifaceted impact of metabolic dysregulation impacting glymphatic system. The abnormal MoCA scores observed in T2DM patients emphasize the cognition impairments associated with glymphatic dysfunction and sleep disturbances. The observed glymphatic dysfunction, potentially driven by metabolic, vascular, and inflammatory abnormalities, suggests a mechanism linking T2DM with cognitive decline and the importance of targeting glymphatic system as a therapeutic strategy. Sleep-targeted therapies, such as cognitive-behavioral therapy, lifestyle modifications, and sleep-promoting medications, hold promise for mitigating glymphatic dysfunction and enhancing waste clearance in this high-risk population. The findings pave the way for research into therapeutic strategies that could improve glymphatic function and protect against neurodegenerative disorders and early risks for dementia and AD in T2DM adults.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData and Resource Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed in the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR.K. were involved in the conception and design of the study. B.R., M.C., S.E.C, M.J.F., and R.K. were involved in the conduct of the study. B.R. and V.L. performed the analysis and interpretation of the results and wrote the first draft of the manuscript. KS and A.S edited the manuscript and all authors edited, reviewed, and approved the final version. R.K. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrant Support\u003c/strong\u003e: This research work was supported by National Institutes of Health R01 NR017190 and 3R01 NR017190-03S1. RK and BR were supported by 1R21 AG085268-01.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed in the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSun, H.\u003cem\u003e et al.\u003c/em\u003e IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. \u003cem\u003eDiabetes research and clinical practice\u003c/em\u003e \u003cstrong\u003e183\u003c/strong\u003e, 109119, doi:10.1016/j.diabres.2021.109119 (2022).\u003c/li\u003e\n\u003cli\u003eWillems, R.\u003cem\u003e et al.\u003c/em\u003e Cost effectiveness review of text messaging, smartphone application, and website interventions targeting T2DM or hypertension. \u003cem\u003enpj Digital Medicine\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 150, doi:10.1038/s41746-023-00876-x (2023).\u003c/li\u003e\n\u003cli\u003eRoy, B.\u003cem\u003e et al.\u003c/em\u003e Regional Brain Gray Matter Changes in Patients with Type 2 Diabetes Mellitus. \u003cem\u003eScientific reports\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 9925, doi:10.1038/s41598-020-67022-5 (2020).\u003c/li\u003e\n\u003cli\u003eRoy, B., Choi, S. E., Freeby, M. J. \u0026amp; Kumar, R. Microstructural brain tissue changes contribute to cognitive and mood deficits in adults with type 2 diabetes mellitus. \u003cem\u003eScientific reports\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 9636, doi:10.1038/s41598-023-35522-9 (2023).\u003c/li\u003e\n\u003cli\u003eChoi, S. E.\u003cem\u003e et al.\u003c/em\u003e Prefrontal cortex brain damage and glycemic control in patients with type 2 diabetes. \u003cem\u003eJournal of diabetes\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 465-473, doi:10.1111/1753-0407.13019 (2020).\u003c/li\u003e\n\u003cli\u003eButterfield, D. A., Di Domenico, F. \u0026amp; Barone, E. Elevated risk of type 2 diabetes for development of Alzheimer disease: A key role for oxidative stress in brain. \u003cem\u003eBiochimica et Biophysica Acta (BBA) - Molecular Basis of Disease\u003c/em\u003e \u003cstrong\u003e1842\u003c/strong\u003e, 1693-1706, doi:https://doi.org/10.1016/j.bbadis.2014.06.010 (2014).\u003c/li\u003e\n\u003cli\u003eBrzecka, A.\u003cem\u003e et al.\u003c/em\u003e Sleep Disturbances and Cognitive Impairment in the Course of Type 2 Diabetes-A Possible Link. \u003cem\u003eCurrent neuropharmacology\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 78-91, doi:10.2174/1570159x18666200309101750 (2021).\u003c/li\u003e\n\u003cli\u003eHolingue, C., Wennberg, A., Berger, S., Polotsky, V. Y. \u0026amp; Spira, A. P. Disturbed sleep and diabetes: A potential nexus of dementia risk. \u003cem\u003eMetabolism\u003c/em\u003e \u003cstrong\u003e84\u003c/strong\u003e, 85-93, doi:https://doi.org/10.1016/j.metabol.2018.01.021 (2018).\u003c/li\u003e\n\u003cli\u003eHenson, J.\u003cem\u003e et al.\u003c/em\u003e Waking Up to the Importance of Sleep in Type 2 Diabetes Management: A Narrative Review. \u003cem\u003eDiabetes Care\u003c/em\u003e \u003cstrong\u003e47\u003c/strong\u003e, 331-343, doi:10.2337/dci23-0037 (2024).\u003c/li\u003e\n\u003cli\u003eReddy, O. C. \u0026amp; van der Werf, Y. D. The Sleeping Brain: Harnessing the Power of the Glymphatic System through Lifestyle Choices. \u003cem\u003eBrain sciences\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, doi:10.3390/brainsci10110868 (2020).\u003c/li\u003e\n\u003cli\u003eJessen, N. A., Munk, A. S., Lundgaard, I. \u0026amp; Nedergaard, M. The Glymphatic System: A Beginner\u0026apos;s Guide. \u003cem\u003eNeurochemical research\u003c/em\u003e \u003cstrong\u003e40\u003c/strong\u003e, 2583-2599, doi:10.1007/s11064-015-1581-6 (2015).\u003c/li\u003e\n\u003cli\u003eMader, S. \u0026amp; Brimberg, L. Aquaporin-4 Water Channel in the Brain and Its Implication for Health and Disease. \u003cem\u003eCells\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, doi:10.3390/cells8020090 (2019).\u003c/li\u003e\n\u003cli\u003eKress, B. T.\u003cem\u003e et al.\u003c/em\u003e Impairment of paravascular clearance pathways in the aging brain. \u003cem\u003eAnn Neurol\u003c/em\u003e \u003cstrong\u003e76\u003c/strong\u003e, 845-861, doi:10.1002/ana.24271 (2014).\u003c/li\u003e\n\u003cli\u003eMortensen, K. N., Sanggaard, S. \u0026amp; Mestre, H. Impaired Glymphatic Transport in Spontaneously Hypertensive Rats. \u003cem\u003eJournal of Neuroscience\u003c/em\u003e \u003cstrong\u003e39\u003c/strong\u003e, 6365-6377, doi:10.1523/jneurosci.1974-18.2019 (2019).\u003c/li\u003e\n\u003cli\u003eJiang, Q.\u003cem\u003e et al.\u003c/em\u003e Impairment of the glymphatic system after diabetes. \u003cem\u003eJ Cereb Blood Flow Metab\u003c/em\u003e \u003cstrong\u003e37\u003c/strong\u003e, 1326-1337, doi:10.1177/0271678x16654702 (2017).\u003c/li\u003e\n\u003cli\u003eAndrade, A. G., Bubu, O. M., Varga, A. W. \u0026amp; Osorio, R. S. The Relationship between Obstructive Sleep Apnea and Alzheimer\u0026apos;s Disease. \u003cem\u003eJournal of Alzheimer\u0026apos;s disease : JAD\u003c/em\u003e \u003cstrong\u003e64\u003c/strong\u003e, S255-s270, doi:10.3233/jad-179936 (2018).\u003c/li\u003e\n\u003cli\u003eFrozza, R. L., Lourenco, M. V. \u0026amp; De Felice, F. G. Challenges for Alzheimer\u0026apos;s Disease Therapy: Insights from Novel Mechanisms Beyond Memory Defects. \u003cem\u003eFrontiers in neuroscience\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 37, doi:10.3389/fnins.2018.00037 (2018).\u003c/li\u003e\n\u003cli\u003eZuroff, L., Daley, D., Black, K. L. \u0026amp; Koronyo-Hamaoui, M. Clearance of cerebral A\u0026beta; in Alzheimer\u0026apos;s disease: reassessing the role of microglia and monocytes. \u003cem\u003eCellular and Molecular Life Sciences\u003c/em\u003e \u003cstrong\u003e74\u003c/strong\u003e, 2167-2201, doi:10.1007/s00018-017-2463-7 (2017).\u003c/li\u003e\n\u003cli\u003eRoy, B., Kumar, R., Sarovich, S. D. \u0026amp; Vacas, S. The Role of the Glymphatic System in Perioperative Neurocognitive Disorders. \u003cem\u003eJournal of neurosurgical anesthesiology\u003c/em\u003e, doi:10.1097/ana.0000000000000973 (2024).\u003c/li\u003e\n\u003cli\u003eRoy, B.\u003cem\u003e et al.\u003c/em\u003e Impaired Glymphatic System Actions in Obstructive Sleep Apnea Adults. \u003cem\u003eFrontiers in neuroscience\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 884234, doi:10.3389/fnins.2022.884234 (2022).\u003c/li\u003e\n\u003cli\u003eNasreddine, Z. S.\u003cem\u003e et al.\u003c/em\u003e The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. \u003cem\u003eJournal of the American Geriatrics Society\u003c/em\u003e \u003cstrong\u003e53\u003c/strong\u003e, 695-699, doi:10.1111/j.1532-5415.2005.53221.x (2005).\u003c/li\u003e\n\u003cli\u003eJiang, H., van Zijl, P. C., Kim, J., Pearlson, G. D. \u0026amp; Mori, S. DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. \u003cem\u003eComputer methods and programs in biomedicine\u003c/em\u003e \u003cstrong\u003e81\u003c/strong\u003e, 106-116, doi:10.1016/j.cmpb.2005.08.004 (2006).\u003c/li\u003e\n\u003cli\u003eTaoka, T.\u003cem\u003e et al.\u003c/em\u003e Evaluation of glymphatic system activity with the diffusion MR technique: diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer\u0026apos;s disease cases. \u003cem\u003eJapanese journal of radiology\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 172-178, doi:10.1007/s11604-017-0617-z (2017).\u003c/li\u003e\n\u003cli\u003eBoyd, E. D.\u003cem\u003e et al.\u003c/em\u003e The Glymphatic Response to the Development of Type 2 Diabetes. \u003cem\u003eBiomedicines\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, doi:10.3390/biomedicines12020401 (2024).\u003c/li\u003e\n\u003cli\u003eIliff, J. J.\u003cem\u003e et al.\u003c/em\u003e A paravascular pathway facilitates CSF flow through the brain parenchyma and the clearance of interstitial solutes, including amyloid \u0026beta;. \u003cem\u003eScience translational medicine\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 147ra111, doi:10.1126/scitranslmed.3003748 (2012).\u003c/li\u003e\n\u003cli\u003ePlog, B. A.\u003cem\u003e et al.\u003c/em\u003e Biomarkers of traumatic injury are transported from brain to blood via the glymphatic system. \u003cem\u003eJournal of Neuroscience\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 518-526, doi:10.1523/jneurosci.3742-14.2015 (2015).\u003c/li\u003e\n\u003cli\u003eHasan-Olive, M. M., Enger, R., Hansson, H. A. \u0026amp; Nagelhus, E. A. Loss of perivascular aquaporin-4 in idiopathic normal pressure hydrocephalus. \u003cem\u003eGlia\u003c/em\u003e \u003cstrong\u003e67\u003c/strong\u003e, 91-100, doi:10.1002/glia.23528 (2019).\u003c/li\u003e\n\u003cli\u003eIliff, J. J., Chen, M. J., Plog, B. A., Zeppenfeld, D. M. \u0026amp; Soltero, M. Impairment of glymphatic pathway function promotes tau pathology after traumatic brain injury. J\u003cem\u003eournal of Neuroscience\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, 16180-16193, doi:10.1523/jneurosci.3020-14.2014 (2014).\u003c/li\u003e\n\u003cli\u003eOguntibeju, O. O. Type 2 diabetes mellitus, oxidative stress and inflammation: examining the links. \u003cem\u003eInternational journal of physiology, pathophysiology and pharmacology\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 45-63 (2019).\u003c/li\u003e\n\u003cli\u003eBhatti, J. S.\u003cem\u003e et al.\u003c/em\u003e Oxidative stress in the pathophysiology of type 2 diabetes and related complications: Current therapeutics strategies and future perspectives. \u003cem\u003eFree Radical Biology and Medicine\u003c/em\u003e \u003cstrong\u003e184\u003c/strong\u003e, 114-134, doi:https://doi.org/10.1016/j.freeradbiomed.2022.03.019 (2022).\u003c/li\u003e\n\u003cli\u003eDomingueti, C. P.\u003cem\u003e et al.\u003c/em\u003e Diabetes mellitus: The linkage between oxidative stress, inflammation, hypercoagulability and vascular complications. \u003cem\u003eJournal of Diabetes and its Complications\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, 738-745, doi:https://doi.org/10.1016/j.jdiacomp.2015.12.018 (2016).\u003c/li\u003e\n\u003cli\u003eMogensen, F. L. \u0026amp; Delle, C. The Glymphatic System (En)during Inflammation. \u003cem\u003eInternational journal of molecular sciences\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, doi:10.3390/ijms22147491 (2021).\u003c/li\u003e\n\u003cli\u003eGędek, A., Koziorowski, D. \u0026amp; Szlufik, S. Assessment of factors influencing glymphatic activity and implications for clinical medicine. \u003cem\u003eFrontiers in neurology\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 1232304, doi:10.3389/fneur.2023.1232304 (2023).\u003c/li\u003e\n\u003cli\u003eChen, H. L.\u003cem\u003e et al.\u003c/em\u003e Associations among Cognitive Functions, Plasma DNA, and Diffusion Tensor Image along the Perivascular Space (DTI-ALPS) in Patients with Parkinson\u0026apos;s Disease. \u003cem\u003eOxidative medicine and cellular longevity\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e, 4034509, doi:10.1155/2021/4034509 (2021).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e: Demographics, clinical variables, diffusivity and DTI-ALPS indices of T2DM patients and healthy controls.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eT2DM (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003cp\u003e[n=78]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003eControls (mean \u0026plusmn; SD) [n=106]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003ep values\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e56.5 \u0026plusmn; 7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e54.7 \u0026plusmn; 6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eSex (Male:Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e39:39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e53:53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;African American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e7 (9.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e16 (13.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Asian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e16 (20.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e35 (28.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e24 (30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e20 (16.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e23 (29.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e44 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e7 (9.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e6 (5.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e29.4 \u0026plusmn; 5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e26.3\u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eHeart Rate (beats/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e77.3 \u0026plusmn; 11.8 (n=68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e71.7 \u0026plusmn; 10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eSystolic BP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e127.8 \u0026plusmn; 15.3 (n=69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e120.7 \u0026plusmn; 17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eDiastolic BP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e78.6 \u0026plusmn; 10.4 (n=69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e78.8 \u0026plusmn; 14.2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003ePSQI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e5.7 \u0026plusmn; 3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e4.6 \u0026plusmn; 2.8 (n=105)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eESS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e6.7 \u0026plusmn; 3.9 (n=69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e5.1 \u0026plusmn; 3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eDiabetes Duration (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e10.7 \u0026plusmn; 8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eA1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e7.04 \u0026plusmn; 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e5.3 \u0026plusmn; 0.4 (n=52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eMoCA Total\u003c/p\u003e\n \u003cp\u003eVisuospatial\u003c/p\u003e\n \u003cp\u003eNaming\u003c/p\u003e\n \u003cp\u003eAttention\u003c/p\u003e\n \u003cp\u003eLanguage\u003c/p\u003e\n \u003cp\u003eAbstraction\u003c/p\u003e\n \u003cp\u003eDelayed Recall\u003c/p\u003e\n \u003cp\u003eOrientation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e25.9 \u0026plusmn; 2.5\u003c/p\u003e\n \u003cp\u003e4.2 \u0026plusmn; 0.9\u003c/p\u003e\n \u003cp\u003e2.9 \u0026plusmn; 0.3\u003c/p\u003e\n \u003cp\u003e5.1 \u0026plusmn; 1.1\u003c/p\u003e\n \u003cp\u003e2.2 \u0026plusmn; 1.0\u003c/p\u003e\n \u003cp\u003e1.9 \u0026plusmn; 0.3\u003c/p\u003e\n \u003cp\u003e3.5 \u0026plusmn; 1.4\u003c/p\u003e\n \u003cp\u003e5.9 \u0026plusmn; 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e27.1 \u0026plusmn; 2.3\u003c/p\u003e\n \u003cp\u003e4.5 \u0026plusmn; 0.7\u003c/p\u003e\n \u003cp\u003e3.0 \u0026plusmn; 0.2\u003c/p\u003e\n \u003cp\u003e5.6 \u0026plusmn; 0.8\u003c/p\u003e\n \u003cp\u003e2.5 \u0026plusmn; 0.7\u003c/p\u003e\n \u003cp\u003e2.0 \u0026plusmn; 0.2\u003c/p\u003e\n \u003cp\u003e3.5 \u0026plusmn; 1.5\u003c/p\u003e\n \u003cp\u003e6.0 \u0026plusmn; 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003ePeriventricular Projection Fiber Area\u003c/p\u003e\n \u003cp\u003e(mean \u0026plusmn; SD, x 10\u003csup\u003e-3\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003ePeriventricular Association Fiber Area\u003c/p\u003e\n \u003cp\u003e(mean \u0026plusmn; SD, x 10\u003csup\u003e-3\u003c/sup\u003e mm\u003csup\u003e2\u003c/sup\u003e/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eT2DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003ep values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eT2DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003ep values\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eDxx\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.72\u0026nbsp;\u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.72 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.69 \u0026plusmn; 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.69 \u0026plusmn; 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eDxy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.04\u0026nbsp;\u0026plusmn; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.05 \u0026plusmn; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.12 \u0026plusmn; 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.12 \u0026plusmn; 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eDxz\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.04\u0026nbsp;\u0026plusmn; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.05 \u0026plusmn; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.06 \u0026plusmn; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.06 \u0026plusmn; 0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eDyy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.61\u0026nbsp;\u0026plusmn; 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.59 \u0026plusmn; 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.03*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.99 \u0026plusmn; 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1.01 \u0026plusmn; 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eDyz\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.20\u0026nbsp;\u0026plusmn; 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.20 \u0026plusmn; 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.08 \u0026plusmn; 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.09 \u0026plusmn; 0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.03*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eDzz\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.93\u0026nbsp;\u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.93 \u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.50 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.47 \u0026plusmn; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026lt;0.001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003eT2DM (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003eControls (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003ep values\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eALPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 204px;\"\u003e\n \u003cp\u003e1.296 \u0026plusmn; 0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 176px;\"\u003e\n \u003cp\u003e1.35 \u0026plusmn; \u0026nbsp;0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 178px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable Legend:\u0026nbsp;\u003c/strong\u003eALPS = analysis along the perivascular space; T2DM = Type 2 Diabetes Miletus; SD = Standard Deviation; BP\u003cstrong\u003e\u0026nbsp;=\u0026nbsp;\u003c/strong\u003eBlood Pressure; BMI = Body Mass Index; MoCA = Montreal Cognitive Assessment; PSQI = Pittsburgh Sleep Quality Index; ESS = Epworth Sleepiness Scale,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eDxx= diffusivity in x-direction; Dxy = diffusivity in x-y direction; Dxz = diffusivity in x-z direction; Dyy = diffusivity in y direction; Dyz = diffusivity in y-z direction; Dzz = diffusivity in z direction.\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Sleep, Cognition, ALPS index, Epworth sleepiness scale, Magnetic resonance imaging, Diffusion tensor imaging","lastPublishedDoi":"10.21203/rs.3.rs-6467065/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6467065/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eType 2 diabetes mellitus (T2DM) is associated with multiple systemic complications, including cognitive decline and increased risk of neurodegenerative diseases. The glymphatic system, a brain waste clearance pathway, can be impaired from sleep disturbances common in T2DM, has not been examined. Therefore, the aim was to evaluate glymphatic system in T2DM subjects using diffusion tensor imaging along the perivascular space (DTI-ALPS) index. A total of 78 T2DM adults and 106 healthy controls underwent for brain MRI. Sleep issues were assessed using the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS), and cognition with the Montreal Cognitive Assessment (MoCA). Group differences in DTI-ALPS, sleep metrics, and MoCA scores were assessed with analysis of covariance (covariates, age, sex, and BMI). T2DM patients exhibited higher PSQI (p\u0026thinsp;=\u0026thinsp;0.03) and ESS (p\u0026thinsp;=\u0026thinsp;0.004), reflecting poorer sleep quality and increased daytime sleepiness. MoCA scores were significantly lower in T2DM adults (p\u0026thinsp;=\u0026thinsp;0.001), with impairments emerged in visuospatial skills, attention, and language. Also, significantly reduced DTI-ALPS values appeared in T2DM over controls (p\u0026thinsp;=\u0026thinsp;0.003). T2DM adults show impaired glymphatic function along with poor sleep quality and day-time issues. The findings indicate that glymphatic dysfunction potentially-driven by metabolic, vascular, and sleep-related disturbances may exacerbate cognitive deficits in T2DM adults.\u003c/p\u003e","manuscriptTitle":"Glymphatic System Impairment in Type II Diabetes Mellitus Adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-02 11:56:07","doi":"10.21203/rs.3.rs-6467065/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-22T09:33:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-21T18:54:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"330352024644303047761571608102072187337","date":"2025-09-03T11:57:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324334428206131196163065778135030070720","date":"2025-08-04T22:02:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-09T11:29:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"186102068696098536003464141545821452767","date":"2025-07-01T08:25:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-27T16:02:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-20T11:09:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-22T02:35:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-21T06:31:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-17T01:46:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6be0bc81-bcf1-4aed-a992-d005a9fbbd76","owner":[],"postedDate":"July 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":50817655,"name":"Health sciences/Diseases/Neurological disorders"},{"id":50817656,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2026-02-09T16:07:15+00:00","versionOfRecord":{"articleIdentity":"rs-6467065","link":"https://doi.org/10.1038/s41598-026-36573-4","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-02-04 15:58:15","publishedOnDateReadable":"February 4th, 2026"},"versionCreatedAt":"2025-07-02 11:56:07","video":"","vorDoi":"10.1038/s41598-026-36573-4","vorDoiUrl":"https://doi.org/10.1038/s41598-026-36573-4","workflowStages":[]},"version":"v1","identity":"rs-6467065","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6467065","identity":"rs-6467065","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}