Understanding Glymphatic's Role In Proteinopathies (GRIP): A single centre case-control study protocol.

Understanding Glymphatic’s Role In Proteinopathies (GRIP): A single centre case-control study protocol

Abstract

Alzheimer’s disease (AD), Parkinson’s disease (PD), and dementia with Lewy bodies (DLB) are proteinopathies characterized by pathological accumulation of amyloid beta, phosphorylated-tau, and alpha-synuclein. Impaired clearance of these proteins is thought to contribute to disease pathogenesis, whereas preserved or enhanced clearance may be compensatory. Beyond intracellular degradation within neurons and glial cells, an extracellular clearance pathway, the glymphatic system, facilitates cerebrospinal fluid flow into perivascular spaces, exchange with interstitial fluid, and subsequent clearance from the brain. Glymphatic transport may therefore be critical for removal of excess proteins and metabolic waste, and its dysfunction could promote protein aggregation and neurodegeneration. The Glymphatic’s Role In Proteinopathies (GRIP) study is an observational case-control imaging and biomarker study comparing glymphatic clearance in patients with AD, PD, and DLB versus healthy controls. We aim to recruit 70 participants: PD (n = 20), DLB (n = 10), AD (n = 20), and age- and sex-matched healthy controls (n = 20). The AD group will be stratified by pathology, with half amyloid-positive/tau-negative (A + T-) and half amyloid- and tau-positive (A + T+). The PD group will be stratified by disease duration. Participants will undergo baseline MRI followed by intrathecal injection of gadobutrol (0.25 mmol) and serial MRI at 5, 24, 48, and 72 hours. Influx and efflux of tracer will be modeled from T1 signal changes. Blood will be sampled repeatedly from 1 to 72 hours; cerebrospinal fluid will be collected at baseline. Individual glymphatic clearance will be estimated using population pharmacokinetic methods, where gadobutrol serves as a tracer. Sleep will be monitored with triaxial accelerometry and sleep diaries. The primary outcome is group differences in glymphatic clearance metrics between each disease group and controls; secondary analyses will explore associations with cognition, disease severity and duration, sleep quality, and cerebrospinal fluid protein levels.

Introduction

Parkinson’s disease (PD), Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB), also known as neurodegenerative disorders or proteinopathies, are multisystemic disorders with a huge disease burden involving cognitive decline and reduced life expectancy, in addition to motor symptoms. Currently no curative treatment exists. To develop effective therapeutic strategies, we need a deeper understanding of the underlying pathology of these diseases. Common for all three disorders is progressive neurodegeneration following progressive protein aggregation. While PD and DLB is neuropathologically characterized by aggregation of α-synuclein-rich Lewy bodies, AD is neuropathologically characterized by aggregation of amyloid-β in amyloid plaques and hyperphosphorylated tau in neurofibrillary tangles. Additionally, co-pathology is common among these diseases [1,2]. The glymphatic system is a glia-dependent clearance pathway that removes toxic waste products from the brain by cerebrospinal fluid (CSF) driven transport to interstitial space [3] and is proposed to play a central role in the pathogenesis of neurodegenerative diseases [4]. The current gold standard for measuring glymphatic clearance is to measure either how fast an exogenous CSF- tracer is cleared from the brain, or how fast an intrathecally administered CSF tracer reaches peripheral blood [5]. One way to measure glymphatic clearance rate in humans is through gMRI; injection of magnetic resonance imaging (MRI) contrast (gadobutrol) in the spinal canal followed by subsequent MRI scans to measure changes in contrast distribution within the CSF spaces, through the brain parenchyma to dural lymphatic vessels [6] and eventually to cervical lymph nodes [7]. In previous studies this has been performed in patients with idiopathic normal pressure hydrocephalus [8], subdural hematoma and subarachnoid hemorrhage [9], by quantitative measures of the amount of centrally administered gadobutrol cleared to peripheral blood [10,11] and under sleep-deprivation [12]. It has been shown that gadobutrol transport varies considerably among individuals and diseases [13,14].

Several other MRI modalities have been used to assess glymphatic function, including diffusion tensor imaging along perivascular spaces (DTI-ALPS) within the deep white matter [15–17]. However, the approach is strongly influenced by white matter microstructure and does not directly quantify cortical transport of substances [18,19]. In parallel, several non-invasive techniques are emerging. Ultra–high-field MRI, defined as field strengths of 7 T or higher in humans, provides a substantially increased signal-to-noise ratio (SNR) and enables improved spatial resolution compared with conventional systems [20]. This combined with modified T2-prepared imaging has identified region-specific drivers of CSF motion within the subarachnoid space (SAS) [21]. Heartbeat-synchronized dynamic DI has further enabled the characterization of fluid dynamics across the SAS, cortex, and white matter [22]. Despite these advances, the use of a gadolinium-based tracer in CSF remains the current gold standard for in vivo assessment of glymphatic function. Gadobutrol has been compared to Iodixanol, where the former showed stronger correlations with distribution in CSF [23].

The overall aim of this study is to investigate the efficiency of the extracellular waste clearance system by using intrathecal gadobutrol in patients with three different neurodegenerative disorders compared with healthy controls.

Materials and methods

Study cohort

The “Glymphatics Role In Proteinopathies” (GRIP) study aims to recruit a total of 70 participants, comprising patients with PD (n = 20), DLB (n = 10) and AD (n = 20). In addition, an age- and sex-matched control group of healthy individuals n = 20 will be included to facilitate comparative analyses across patient groups. Controls will be matched to the patient cohort to ensure balanced comparisons with respect to age and sex. See figure.

To be eligible for inclusion, participants must have a confirmed diagnosis of PD, DLB or AD for the patient groups, and be without a neurological disorder for the control group. Furthermore, both controls and patients must be between 50 and 75 years of age, and be able to provide written informed consent, as summarized in Fig 1. The PD cohort will be diagnosed according to the MDS criteria [24] and stratified into two subgroups: newly diagnosed PD (diagnosis within the past 2 years; n = 10) and established PD (diagnosis more than 5 years prior; n = 10). Disease duration is defined from the time of formal clinical diagnosis, including confirmation by a positive dopamine transporter (DAT) scan. The AD cohort will similarly be subdivided to capture different stages of the disease trajectory: half of the participants (n = 10) will have evidence of amyloidosis without hyperphosphorylated tau (A + T-) and the other half (n = 10) will have both amyloidosis and tauopathy (A + T+) as confirmed by CSF biomarkers [25], using the revised Alzheimer’s Association criteria [26]. Probable DLB with MCI will be diagnosed by an experienced neurologist or geriatrician according to current diagnostic criteria [27].

Patients with PD, DLB and healthy controls will be recruited through the neurological and geriatric outpatient clinics at Oslo University Hospital, Akershus University Hospital and via the Norwegian Parkinson Association and Norwegian Health Association. Recruitment strategies include webinars, podcasts, written study information distributed through newsletters, and oral presentations at local association meetings. Patients with AD will be recruited primarily from the Memory Outpatient Clinic at the Department of Neurology at Akershus University Hospital, based on CSF profiles consistent with AD pathology, in addition to advertisements and the Norwegian Health Association.

Potential participants will receive comprehensive information about the GRIP study both orally and in written form. The ability to provide informed consent is an essential requirement for participation; individuals with cognitive decline of such severity that it affects adequate understanding of the study procedures will therefore be excluded.

Additional exclusion criteria include: any history of hypersensitivity or allergic reactions to contrast agents; reduced kidney function (low estimated glomerular filtration rate, eGFR < 60mL/min/1.73m2); a history of severe allergic reactions; ongoing treatment with antiplatelet/anticoagulant medication; thrombocytopenia; and the presence of neurological disorders other than PD, DLB, or AD.

At inclusion we will record height and weight, vital signs (blood pressure, temperature, heart rate, oxygen saturation and respiratory rate), as well as previous medical history and current medications.

Ethical considerations

All participants in this study will be provided with comprehensive information about the study purpose, procedures, potential risks, and benefits. Informed consent will be obtained from each participant, ensuring their full understanding, voluntary participation and the possibility of withdrawing consent. The study is approved by the Regional committee for medical and health research ethics (REC) South East (#282297) and the Data protection official (DPO) at Oslo University Hospital (21/19051). Every effort will be made to minimize potential harm to participants. The participants will be carefully monitored to ensure their well-being throughout the imaging process. MRI sequences will be performed in prioritized order, to ensure the most important data points in case of the necessity of shortening down the scanning time due to discomfort. Since gadobutrol is an off-label tracer, it is important to note that the dose of 0.25 mmol was carefully selected based on safety studies [28].

The research team will continually monitor the study to identify and address any emerging ethical concerns or issues that may arise during the research. All collected data will be securely stored in compliance with data protection laws and regulations. Access to sensitive data will be restricted to authorized personnel only.

Cognitive and neurological testing

Each participant will undergo a standard clinical examination, with addition of the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) part I-IV [29]. Global cognitive function will be tested with Montreal Cognitive Assessment (MoCA) [30]. Learning, delayed recall and recognition will be tested using the word list memory and learning neuropsychological battery Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) [31], executive function using the Trail Making test part A and B [32], verbal phonemic fluency (Controlled Oral Word Association test (COWAT/FAS)) [33]. Cognitive impairment will be determined when results are 1.5 standard deviation below the normative mean within one or more cognitive domains, and applied norms will be local, and regression based [34–38].

Sleep assessment

All participants will be given a sleep diary with written and oral instructions for a total of two weeks (14 days), starting prior to gMRI and lasting at least a week after the gMRI protocol. Throughout this time, the participants will also be given a triaxial accelerometry (actigraphy) worn on the arm, provided by the Section of Clinical Neurophysiology. Additionally, five self-assessment sleep scales will be given REM Sleep Behavior Disorder Screening Questionnaire [RBDSQ] [39], Parkinson’s Disease Sleep Scale [PDSS-2] [40], Pittsburgh Sleep Quality Index [PSQI] [41], Insomnia Severity Index [ISI] [42] and Circadian Type Inventory [CTI] [43]. The study physician will offer instructions.

Glymphatic MRI (gMRI)

Included patients and controls will undergo a four-day protocol with five MRI sessions. The baseline MRI protocol consisting of T1 weighted (T1w), T2 weighted (T2w), diffusion tensor imaging (DTI), fluid-attenuated inversion recovery (FLAIR), susceptibility-weighted imaging (SWI), parenchyma T1-mapping [44] and T2w CSF T1-mapping [45]. While T1w and T2w will be used for anatomical segmentations, DTI will be used to model patient-specific white matter tracts and FLAIR and SWI, together with T1w and T2w will be used diagnostically to uncover subclinical previous cerebral events or anatomical abnormalities or variations. After the baseline MRI protocol, patients will undergo a lumbar puncture in the lateral position with a G25 atraumatic needle, where proper needle placement will be confirmed through a passive release of CSF. CSF for analyses will be collected. The MRI contrast agent Gadobutrol will be administered intrathecally as a CSF tracer at a dose of 0.25 mL of 1.0 mmol/mL (Gadobutrol; Gadovist, Bayer Pharma AG, Berlin, Germany) to enable quantification of CSF clearance and visualization of glymphatic influx and CSF transport. If needed, an interventional radiologist will perform an X-ray guidance lumbar puncture in the lateral position.

Subsequent MRI scans will be performed at approximately 5 hours, 24 hours, 48 hours and 72 hours after contrast injection, and consist of the T1w and the T1-mapping sequence for quantitative estimation of contrast enhancement in brain parenchyma and a T2w T1 mapping for segmentation of intracranial CSF spaces and for quantitative contrast enhancement in CSF [45]. A 3D T1-weighted Turbo Field Echo (T1w-TFE) sequence will be used for anatomical reference.

All MRI examinations will be performed on a 3T Philips Ingenia scanner (Philips Healthcare, Best, The Netherlands) using a 32-channel head coil.

The T1 mapping sequences and the T1w-TFE will be full brain coverage 3D acquisitions with 1 mm isotropic resolution. In addition to the above sequences, the baseline protocol includes standard clinical and glymphatic MRI sequences (1 mm isotropic 3D FLAIR, 0.7 mm isotropic 3D T2w imaging, susceptibility-weighted imaging [SWI], and 2.5 mm isotropic axial DTI [b-values 0, 1000s/mm3]), resulting in a total baseline scan duration of approximately 60 minutes. Follow-up imaging sessions will use a subset of these sequences, with a total scan time of approximately 30 minutes per session.

CSF handling and biomarker analysis

CSF will be collected immediately before intrathecal contrast administration. CSF will be collected in polypropylene tubes and processed according to the BIOMARKAPD protocol [46]. Briefly, samples will be centrifuged within 4 hours at 2,000 x g for 10 minutes at room temperature, aliquoted, and stored at −80°C until analysis. Additional aliquots will be stored for future exploratory biomarker analyses.

Routine CSF analyses will be performed immediately at the local laboratory, including cell count, lactate, glucose, total protein, and albumin ratio. A clinical validation of amyloidosis and tau pathology will be validated using commercial enzyme-linked immunosorbent assays (ELISAs) based on monoclonal antibodies. This will be used to determine CSF levels of amyloid-β 42, total tau, and phosphorylated tau (Innotest β-Amyloid (1–42), Innotest hTau Ag, and Innotest Phospho-Tau (181P); Fujirebio, Ghent, Belgium).

Blood sampling and analysis

Serial venous blood sampling will be performed to assess gadobutrol clearance from CSF to peripheral blood. Intravenous blood will be collected before intrathecal contrast administration and at 1, 2, 4, 6, 8, and 10 hours thereafter, followed by sampling every 4–6 hours for the patients admitted to the hospital the whole period. To reduce patient burden of sampling, blood will preferentially be drawn via an intravenous cannula. Before administering contrast, we will check platelet count (>150), creatinine, estimated glomerular filtration rate (eGFR < 60mL7min/1.73m2, CKD-EPI2021) and signs of infection (leukocytosis or elevated C-reactive protein). Additionally, standard clinical chemistry will be performed for all the participants.

To further reduce patient burden, we will perform volumetric absorptive microsampling of capillary blood using the Mitra (Trajan Scientific and Medical) devices. This allows the patient to perform self-sampling, thus more flexible sampling of capillary blood.

At the pre-contrast time point five Vacutainer tubes will be collected (one serum tube and four EDTA tubes). At all subsequent time points, one EDTA tube will be obtained. Samples will be stored in a fridge at 4°C until processing. For biobanking, tubes will be centrifuged at 1,500 x g for 15 minutes, plasma and serum aliquoted into 500 μl matrix tubes and stored at −80°C until analysis. Two EDTA tubes of whole blood will be stored directly without any pre-processing. For participants who do not require continuous hospitalization during the 5-day study period, at-home sampling will be performed with dried Mitra® blood spot analysis using capillary blood. For determination of total gadolinium (Gd) associated with gadobutrol contrast agent in peripheral blood, the plasma sample will be thoroughly mixed by repeated aspiration and dispersing with a pipette. Approximately 0.3 g of plasma will be transferred to a digestion vessel and the exact mass recorded prior to microwave-assisted digestion with concentrated ultrapure nitric acid and deionized Milli-Q water (3 mL water and 5 mL nitric acid). Digestion will be performed in an UltraCLAVE single reaction chamber microwave system (Milestone) using an 80-minute stepwise heating program, with a maximum temperature of 250°C held for 20 minutes. After cooling to room temperature, digested samples will be transferred to 50 mL polyethylene vials (VWR) and diluted with deionized water, in accordance with previously published protocols [10]. Gadolinium concentrations will be determined by inductively coupled plasma mass spectrometry (ICP-MS; Agilent 7700x, single- quadrupole MS; Agilent Technologies). Indium will be added online as an internal standard to all samples, calibration standards, blank samples and quality control samples to correct for variations in sample introduction, instrumental drift and matrix effects. NIST SRM 1515 Apple Leaves or NIST SRM 1547 Peach Leaves will be used as certified reference materials (CRMs) to provide an independent quality control of the sample digestion and ICP-MS determination of gadolinium, and to support the assessment of the trueness of gadolinium determination through comparison with the available indicative values.

PET imaging

[18F]Flutemetamol PET will be performed in n = 40 of the participants (n = 20 AD patients, n = 10 DLB patients and n = 10 controls). There are no specific preparations before [18F]Flutemetamol PET. All subjects will be given a bolus injection of approximately 185 MBq (5 mCi) intravenously. Subjects will be positioned head-first supine in the scanner followed by a low-dose CT scan acquisition for attenuation correction and anatomical co-localization. PET scanning in 3D-mode will start approximately 90 min after injection of [18F]Flutemetamol. PET data will be acquired in list-mode for 20 min (four frames of five minutes) and image reconstruction will be performed according to guidelines [47]. [18F]Flutemetamol PET images will be corrected for motion, if necessary, by removing afflicted frames obtained in list-mode. Attenuation corrected images co-registered with low-dose CT will be visually assessed for global and regional cortical tracer uptake according to validated standards by two experienced nuclear medicine physicians [48].

Semi-quantification will be performed in PMOD with co-registration of PET images to 3D T1 MRI. For global amyloid burden the Centiloid atlas will be applied. Image processing will be performed in batch analysis with inspection of VOI placement as quality control. Standard uptake value ratio (SUVR) with normalization to whole cerebellum will be converted to Centiloids (CL) and PMOD processing will be performed according to previously validated pipeline [49].

For regional amyloid burden we will measure [18F]Flutemetamol SUV in segmented cortical regions from the FreeSurfer pipeline. Whole cerebellum will be used as reference region to obtain regional SUVRs.

Image analysis and postprocessing

MRI images will be converted from Philips Enhanced DICOM files to NIfTI format using the dcm2niix software tool (https://github.com/rordenlab/dcm2niix) and data will be organized in a standardized structure similar to Brain Image Data Structure [50].

Brain segmentation and surface reconstruction will be performed using FreeSurfer’s recon-all processing pipeline [51–53], or similar automated segmentation tools [54], based on the pre-contrast 3D T1-weighted image. For automated CSF segmentation, our newly developed tool will be used (open-source on GitHub; https://github.com/jorgenriseth/grip-mixed.git). The CSF segmentation is created by thresholding a pre-contrast heavily T2 weighted image, and extrapolating brain segmentation labels to the CSF mask for SAS segmentation. All segmentations will be manually assessed by a neuroanatomist.

To enable tracking the regional time evolution of the tracer distribution, the contrast-enhanced MRI time series (5 hours, 24 hours, 48 hours and 72 hours) will be registered to the pre-contrast T1-weighted image for each participant. Greedy, FreeSurfer, or similar tools, will be used for image registration. T1 relaxation rates scales with tracer concentration. Hence, T1 maps from the T1-mapping sequences will be calculated to quantitatively assess the intrathecal tracer distribution in the brain and CSF. Furthermore, normalization of T1-weighted signal intensities enables semi-quantitative analysis of tracer distribution.

Diffusion tensor images will be corrected for susceptibility-induced [55] and eddy current-induced (FSL’s eddy) distortions before calculating the diffusion tensor and diffusion maps (FSL’s dtifit) [56]. An additional b = 0 scan with opposite phase encoding direction (anterior-to-posterior) to the DTI acquisition will be used as input for susceptibility correction.

Quantitative analysis of glymphatic clearance

To measure regional gMRI, we will use automated segmentation of the subarachnoid space that corresponds to specific regions of the cerebral cortex. This tool allows us to analyze gadolinium availability in these regions accurately. By integrating and analyzing both PET data and regional gMRI metrics enable us to focus on specific sub-regions of the cerebral cortex, facilitating a thorough investigation of the relationship between glymphatic clearance and protein aggregation.

Population pharmacokinetics methods for individual quantification of glymphatic clearance have previously been demonstrated to be of clinical significance, and associates with biomarkers of neurodegeneration [11]. By employing a rich sample regimen, especially in the initial absorption phase of intrathecally administered gadobutrol, we will be able to obtain accurate and precise estimates of individual glymphatic clearance.

These imaging-derived measures will then be integrated with clinical, cognitive, neuroimaging, and biomarker data. The primary outcome will be group differences in glymphatic clearance quantified from gMRI data and comparing each disease group with healthy controls.

Secondary analyses will examine associations between glymphatic clearance and cognitive performance, disease severity, disease duration, and CSF and PET protein levels.

The type of data and statistical analyses planned

Descriptive statistics will be calculated for all variables, and group differences between PD, AD, DLB, and controls will be assessed with appropriate parametric or non-parametric tests, with an initial emphasis on transparent characterization of the raw data.

To explore physiological mechanisms related to CSF circulation, glymphatic function, and clearance pathways, we will perform multi-physics modeling ranging from single one-compartment diffusion and advection simulations to complex multi-compartment fluid-structure interaction problems involving poro-elasticity, describing the transport of water, contrast and proteins between CSF, brain parenchyma, blood and dura. These models range from currently computationally feasible on a cohort of 70 [57,58] to complex multi-physics models that are currently not feasible [59,60] with the present methods. We do however anticipate significant improvement in the computational methodology in the following years.

These models will provide parameters such as transfer and clearance rates and effective distribution volumes, which will be compared between diagnostic groups and controls to identify potential disease-related alterations.

The analysis will proceed in phases. The first phase will focus on FreeSurfer-derived structural and CSF-related measures in PD patients versus healthy controls. In the second phase, the study will be expanded to include 20 AD and 10 DLB patients, with a shared or disease-specific control group, to determine whether CSF- and contrast-related patterns in PD generalize to or differ from those in AD and DLB. Across all phases, we will relate these imaging findings to clinical parameters, including cognitive function, sleep patterns, and other relevant measures, to compare profiles between the diagnostic groups.

Group differences in glymphatic clearance will be assessed using parametric tests (e.g., t‑tests or analysis of variance [ANOVA]) for normally distributed data, and non‑parametric tests (e.g., Mann-Whitney U test or Kruskal-Wallis test) for non‑normally distributed data. Associations between glymphatic clearance and cognitive performance, disease severity, disease duration, and CSF/PET protein levels will be examined using linear regression models for normally distributed variables and Spearman rank correlations for non‑normally distributed or ordinal variables. Model assumptions (normality, homoscedasticity, and absence of multicollinearity) will be checked using standard diagnostic procedures, and data transformations or robust/non‑parametric methods will be applied if assumptions are violated. Analyses will be adjusted for relevant covariates (e.g., age, sex, education, and intracranial volume), and multiple comparison correction will be applied where appropriate (e.g., false discovery rate).

User involvement

The GRIP study’s design, including participant information and consent procedures, has been developed in close collaboration with user representatives. These representatives have provided valuable input to ensure that patient perspectives are adequately addressed and that the consent materials are clear, comprehensible, and appropriately balanced regarding risks and benefits. An example of this is the length of MRI scanning. Another important feedback point from the user representative is the need for regular updates to study participants, as the direct patient involvement is intensive and brief, while the overall project duration is expected to be long. We therefore plan to provide updates to participants one to two times per year, either through seminars or informational letters. User representatives will be involved in discussions about the implications of the results, the need for further research, and suitable formats for communication to their members.

Status and timeline

Recruitment for this study began in summer 2022 and is ongoing, and so far, the PD patients and half of the controls are included. Inclusion is planned to continue to 2031. No formal data analyses on case-control differences glymphatic clearance have been performed to date.

Discussion

The GRIP study has several important methodological strengths. Unlike previous work, where gMRI has primarily been performed on clinical indication, this is the first study to apply gMRI purely for research purposes. The GRIP study will also perform gMRI in age-matched healthy controls, providing a more appropriate defined comparison group. Technically, this project advances beyond earlier gMRI studies that relied on conventional T1-weighted MRI with normalization to small regions of reference tissue (e.g., retroorbital fat) for semi-quantitative assessment of contrast enhancement [13]. These approaches are vulnerable to variability within small normalization regions. GRIP will instead exploit the fixed gray scale of the Look-Locker sequence to obtain quantitative measures in the brain parenchyma without dependence on such normalization, thereby reducing susceptibility to regional reference-tissue variability. Furthermore, to overcome limitations of using Look-Locker for CSF measurements, the project has developed a new MRI sequence that selectively detects the CSF signal [45]. This allows sensitive detection of subtle baseline signal differences reflecting variations in protein concentration, as well as quantitative R1 measurements in contrast-enhanced CSF. Basing the work on T1 mapping represents an advancement over previous approaches. More recently, this framework has been further refined as T1 mapping itself has technical challenges [61]. In addition, amyloid PET will be performed in AD and DLB patients, enabling comparison of regional protein aggregation with regional glymphatic clearance.

Another strength of the protocol is the extended follow-up time. Previous studies typically followed patients for up to 48 hours, with an additional scan after 4 weeks after intrathecal contrast administration and showed peak contrast enhancement at around 24 hours in most brain regions [10] with continued increase between 24 and 48 hours in deep white matter and deep nuclei such as the basal ganglia. To ensure that the phase of maximal efflux is captured, the GRIP study extends imaging to 72 hours.

The GRIP study also integrates comprehensive fluid biomarker assessment. Whereas earlier gMRI studies often administered intrathecal contrast without CSF sampling, GRIP includes CSF collection for biomarker analyses, including diagnostic markers. Compared with prior work, the study incorporates more frequent peripheral blood sampling, particularly immediately before and after sleep, to better characterize potential differences in clearance profiles between sleep and wakefulness. Finally, all participants will undergo out-of-lab sleep monitoring and will complete sleep diaries, allowing sleep quality, sleep fragmentation and sleep duration to be related directly to measures of glymphatic clearance.

The main limitation in the study design is the time-consuming MRI scanning protocol and potentially tiresome investigations. Furthermore, both lumbar- and venipuncture for CSF sampling, intrathecal injection and blood sampling might be bothersome for the study participants. For lumbar puncture including intrathecal MRI contrast administration there is a considerable risk of post-puncture headache some days following the procedure. Appropriate measures will be taken to reduce the risk (thin needle (G25) and atraumatic needle technique) and follow-up of the participant after the procedure with necessary care [62]. We acknowledge that the protocol is likely to be distressful for some participants, and we will follow each closely to ensure that all possible discomfort will be as low as possible.

The study requires frequent blood sampling during the first day of admission at the hospital ward. Blood will primarily be drawn through an indwelling venous catheter (cannula) to reduce discomfort and the number of separate needle insertions. However, additional blood draws by standard venipuncture may be necessary if cannulas clog. To further minimize discomfort and reduce the volume of venous blood required, we will also employ volumetric absorptive microsampling of capillary blood. This technique allows measurement of gadobutrol concentrations from small capillary samples, thereby limiting the need for repeated venous punctures.

This interdisciplinary study needs coordinated effort across multiple units at both the hospital and the university, making close collaboration particularly critical on the days when patients are admitted for inclusion. The PhD fellow will have a leading role in this process, ensuring that all involved units are appropriately informed and adequately prepared in advance of each inclusion.

Dissemination plan

The results from this project will be disseminated through several complementary channels targeting both the scientific community and relevant stakeholders, including patients, patient organizations, health services, and the public. We will submit the main findings to international, peer-reviewed journals, and separate manuscripts are planned to cover the MRI processing methods and quantitative calculations of the difference between glymphatic clearance in the three neurodegenerative disorders compared to healthy controls.

The project results will also be presented at relevant national and international scientific conferences. Study participants will receive feedback in the form of a short lay summary of the overall study results once the main analyses are completed. Clinically relevant individual findings, such as incidental MRI findings, will be communicated according to predefined clinical routines and in line with ethical approvals. All information for participants will be provided in clear, non-technical language, and participants will be offered the opportunity to ask questions.

Key findings will be communicated to relevant patient organizations through written summaries in lay language and, when appropriate, through short presentations at meetings, podcast or webinars.

Abbreviations

ADAlzheimer’s disease

PDParkinson’s disease

DLBDementia with Lewy bodies

CSFCerebrospinal fluid

SASSubarachnoid fluid/space?

MRIMagnetic resonance imaging

gMRIGlymphatic MRI

GRIPGlymphatic’s Role In Proteinopathies

DaTDopamine Transporter

MOCAMontreal Cognitive Assessment

CERADConsortium to Establish a Registry for Alzheimer’s Disease

COWATControlled Oral Word Association test

VOSPVisual Object and Space Perception

TMTTrail Making Test

ELISAenzyme-linked immunosorbent assay

EDTAEthylenediaminetetraacetic acid

T1wT1 weighted

T2wT2 weighted

DTIDiffusion tensor imaging

FLAIRFluid-attenuated inversion recovery

MixedMixed spin-echo inversion recovery

PETPositron Emission Tomography

REMRapid Eye Movements

RBDSQREM Sleep Behavior Disorder Screening Questionnaire

PDSS-2Parkinson’s Disease Sleep Scale

PSQIPittsburgh Sleep Quality Index

CTICircadian Type Inventory

ISIInsomnia sleep index

SCDSubjective Cognitive Decline

MCIMild Cognitive Impairment

CSFCerebrospinal fluid

MDS-UPDRSMovement Disorder Society Unified Parkinson’s Disease Rating Scale

Data Availability

The study generates data of a sensitive nature, including detailed clinical information and imaging data. All such data are stored and managed within the Services for Sensitive Data (TSD) platform, which provides secure, access-controlled storage in accordance with institutional and regulatory requirements. Access to the dataset is restricted and can be granted upon reasonable request to the project leader, subject to applicable ethical and legal approvals. We have, however, been able to make a full imaging series publicly available from one control(60), which can be downloaded from Zenodo: https://zenodo.org/records/14266867.

Funding Statement

We gratefully acknowledge the South-Eastern Norway Regional Health Authority (SLL, #2022022), the Norwegian Health Association (KN #25598 and #28398), European Research Council (KAM, #101141807), the foundation Stiftelsen Kristian Gerhard Jebsen through its center for Brain Fluids and by the Center of Advanced Study (CAS) at the Norwegian Academy of Science and Letters under the program Mathematical Challenges in Brain Mechanics (KAM) for their financial support for part of the study. We also thank the personnel of the inpatient ward at the Department of Neurology at OUS and the Intervention Centre for their commitment to facilitating data collection through patient admission and MRI scanning.

References

1.Spires-Jones TL, Attems J, Thal DR. Interactions of pathological proteins in neurodegenerative diseases. Acta Neuropathol. 2017;134(2):187–205. doi: 10.1007/s00401-017-1709-7

2.Gibson LL, Grinberg LT, Paes VR, Mueller C, Leite REP, Nunes PV, et al. Co-pathology in Alzheimer’s disease and Lewy body disease and its association with neuropsychiatric symptoms. Alzheimers Dement. 2025;21(9):e70693. doi: 10.1002/alz.70693

3.Qureshi T, Bjørkmo M, Nordengen K, Gundersen V, Utheim TP, Watne LO, et al. Slc38a1 conveys astroglia-derived glutamine into GABAergic interneurons for neurotransmitter GABA synthesis. Cells. 2020;9(7):1686. doi: 10.3390/cells9071686

4.Nedergaard M, Goldman SA. Glymphatic failure as a final common pathway to dementia. Science. 2020;370(6512):50–6. doi: 10.1126/science.abb8739

5.Keil SA, Jansson D, Braun M, Iliff JJ. Glymphatic dysfunction in Alzheimer’s disease: A critical appraisal. Science. 2025;389(6756):eadv8269. doi: 10.1126/science.adv8269

6.Ringstad G, Eide PK. Cerebrospinal fluid tracer efflux to parasagittal dura in humans. Nat Commun. 2020;11(1):354. doi: 10.1038/s41467-019-14195-x

7.Eide PK, Vatnehol SAS, Emblem KE, Ringstad G. Magnetic resonance imaging provides evidence of glymphatic drainage from human brain to cervical lymph nodes. Sci Rep. 2018;8(1):7194. doi: 10.1038/s41598-018-25666-4

8.Eide PK, Pripp AH, Ringstad G, Valnes LM. Impaired glymphatic function in idiopathic intracranial hypertension. Brain Commun. 2021;3(2):fcab043. doi: 10.1093/braincomms/fcab043

9.Eide PK, Hovd M, Valnes LM, Pripp A, Ringstad G. When blood hits the brain: Altered glymphatic and dural lymphatic function after surface bleeds. Acta Neurochir (Wien). 2026;168(1):3. doi: 10.1007/s00701-025-06760-9

10.Eide PK, Mariussen E, Uggerud H, Pripp AH, Lashkarivand A, Hassel B, et al. Clinical application of intrathecal gadobutrol for assessment of cerebrospinal fluid tracer clearance to blood. JCI Insight. 2021;6(9):e147063. doi: 10.1172/jci.insight.147063

11.Hovd MH, Mariussen E, Uggerud H, Lashkarivand A, Christensen H, Ringstad G, et al. Population pharmacokinetic modeling of CSF to blood clearance: Prospective tracer study of 161 patients under work-up for CSF disorders. Fluids Barriers CNS. 2022;19(1):55. doi: 10.1186/s12987-022-00352-w

12.Eide PK, Vinje V, Pripp AH, Mardal K-A, Ringstad G. Sleep deprivation impairs molecular clearance from the human brain. Brain. 2021;144(3):863–74. doi: 10.1093/brain/awaa443

13.Ringstad G, Valnes LM, Dale AM, Pripp AH, Vatnehol S-AS, Emblem KE, et al. Brain-wide glymphatic enhancement and clearance in humans assessed with MRI. JCI Insight. 2018;3(13):e121537. doi: 10.1172/jci.insight.121537

14.Eide PK, Valnes LM, Lindstrøm EK, Mardal K-A, Ringstad G. Direction and magnitude of cerebrospinal fluid flow vary substantially across central nervous system diseases. Fluids Barriers CNS. 2021;18(1):16. doi: 10.1186/s12987-021-00251-6

15.Ghaderi S, Mohammadi S, Jouzdani AF, Ahmadzadeh AM, Fatehi F. A systematic review and meta-analysis on glymphatic flow dysfunction in Parkinson’s disease and Parkinsonism spectrum. NPJ Parkinsons Dis. 2025;11(1):306. doi: 10.1038/s41531-025-01151-4

16.Zafari R, Kamroo A, Taherkhani T, Nabizdeh F, Aarabi MH, For Alzheimer’s Disease Neuroimaging Initiative (ADNI). DTI-ALPS index and its association with neuroinflammatory and neurodegenerative biomarkers and tau-PET in Alzheimer’s continuum. Neuroscience. 2026;609:101–15. doi: 10.1016/j.neuroscience.2026.05.010

17.Jungwon J, Lee JH, Choi C-H, Lee J. DTI-ALPS index as a predictor of cognitive decline over 1 year. Neuroradiology. 2025;67(1):163–70. doi: 10.1007/s00234-024-03521-w

18.Mossige I, Valnes LM, Storas TH, Emblem KE, Eide PK, Ringstad G. Comparing glymphatic function measures: diffusion tensor image analysis along perivascular spaces (DTI-ALPS) versus intrathecal contrast-enhanced MRI. Radiology. 2026;318(2):e252070.

19.Ringstad G. Glymphatic imaging: A critical look at the DTI-ALPS index. Neuroradiology. 2024;66(2):157–60. doi: 10.1007/s00234-023-03270-2

20.Ugurbil K. Magnetic resonance imaging at ultrahigh fields. IEEE Trans Biomed Eng. 2014;61(5):1364–79. doi: 10.1109/TBME.2014.2313619

21.Hirschler L, Runderkamp BA, Decker A, van Harten TW, Scheyhing P, Ehses P, et al. Region-specific drivers of CSF mobility measured with MRI in humans. Nat Neurosci. 2025;28(11):2392–401. doi: 10.1038/s41593-025-02073-3

22.Wen Q, Tong Y, Zhou X, Dzemidzic M, Ho CY, Wu Y-C. Assessing pulsatile waveforms of paravascular cerebrospinal fluid dynamics within the glymphatic pathways using dynamic diffusion-weighted imaging (dDWI). Neuroimage. 2022;260:119464. doi: 10.1016/j.neuroimage.2022.119464

23.Eide PK, Lashkarivand A, Hernes SS, Ringstad G, Hovd M. Estimation of human brain fluid clearance using intrathecal imaging contrast agents. Fluids Barriers CNS. 2026;23(1):79. doi: 10.1186/s12987-026-00826-1

24.Postuma RB, Berg D, Stern M, Poewe W, Olanow CW, Oertel W, et al. MDS clinical diagnostic criteria for Parkinson’s disease. Mov Disord. 2015;30(12):1591–601. doi: 10.1002/mds.26424

25.Jack CR Jr, Andrews JS, Beach TG, Buracchio T, Dunn B, Graf A, et al. Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s Association Workgroup. Alzheimers Dement. 2024;20(8):5143–69. doi: 10.1002/alz.13859

26.McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, et al. The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):263–9. doi: 10.1016/j.jalz.2011.03.005

27.McKeith IG, Boeve BF, Dickson DW, Halliday G, Taylor J-P, Weintraub D, et al. Diagnosis and management of dementia with Lewy bodies: Fourth consensus report of the DLB Consortium. Neurology. 2017;89(1):88–100. doi: 10.1212/WNL.0000000000004058

28.Sperre A, Karsrud I, Rodum AHS, Lashkarivand A, Valnes LM, Ringstad G, et al. Prospective safety study of intrathecal gadobutrol in different doses. Am J Neuroradiol. 2023;44(5):511–6. doi: 10.3174/ajnr.A7841

29.Goetz CG, Tilley BC, Shaftman SR, Stebbins GT, Fahn S, Martinez-Martin P, et al. Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): Scale presentation and clinimetric testing results. Mov Disord. 2008;23(15):2129–70. doi: 10.1002/mds.22340

30.Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–9. doi: 10.1111/j.1532-5415.2005.53221.x

31.Morris JC, Heyman A, Mohs RC, Hughes JP, van Belle G, Fillenbaum G, et al. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurology. 1989;39(9):1159–65. doi: 10.1212/wnl.39.9.1159

32.Battery AIT. Manual of directions and scoring. Washington, DC: War Department, Adjutant General’s Office; 1944.

33.Benton AL. Problems of test construction in the field of aphasia. Cortex. 1967.

34.Eliassen IV, Kirsebom B-E, Fladby T, Waterloo K, Sando SB, Hemminghyth MS, et al. Regression-based cognitive change norms applied in biochemically defined predementia Alzheimer’s disease. Neuropsychology. 2023;37(1):32–43. doi: 10.1037/neu0000853

35.Heaton RK. Revised comprehensive norms for an expanded Halstead-Reitan Battery: Demographically adjusted neuropsychological norms for African American and Caucasian adults, professional manual. Psychological Assessment Resources; 2004.

36.Espenes J, Hessen E, Eliassen IV, Waterloo K, Eckerström M, Sando SB, et al. Demographically adjusted trail making test norms in a Scandinavian sample from 41 to 84 years. Clin Neuropsychol. 2020;34(sup1):110–26. doi: 10.1080/13854046.2020.1829068

37.Kirsebom B-E, Espenes R, Hessen E, Waterloo K, Johnsen SH, Gundersen E, et al. Demographically adjusted CERAD wordlist test norms in a Norwegian sample from 40 to 80 years. Clin Neuropsychol. 2019;33(sup1):27–39. doi: 10.1080/13854046.2019.1574902

38.Lorentzen IM, Espenes J, Hessen E, Waterloo K, Bråthen G, Timón S, et al. Regression-based norms for the FAS phonemic fluency test for ages 40-84 based on a Norwegian sample. Appl Neuropsychol Adult. 2023;30(2):159–68. doi: 10.1080/23279095.2021.1918128

39.Stiasny-Kolster K, Mayer G, Schäfer S, Möller JC, Heinzel-Gutenbrunner M, Oertel WH. The REM sleep behavior disorder screening questionnaire--A new diagnostic instrument. Mov Disord. 2007;22(16):2386–93. doi: 10.1002/mds.21740

40.Chaudhuri KR, Pal S, DiMarco A, Whately-Smith C, Bridgman K, Mathew R, et al. The Parkinson’s disease sleep scale: A new instrument for assessing sleep and nocturnal disability in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 2002;73(6):629–35. doi: 10.1136/jnnp.73.6.629

41.Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213. doi: 10.1016/0165-1781(89)90047-4

42.Bastien CH, Vallières A, Morin CM. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med. 2001;2(4):297–307. doi: 10.1016/s1389-9457(00)00065-4

43.Di Milia L, Smith PA, Folkard S. A validation of the revised circadian type inventory in a working sample. Pers Individ Differ. 2005;39(7):1293–305. doi: 10.1016/j.paid.2005.04.012

44.Look DC, Locker DR. Time saving in measurement of NMR and EPR relaxation times. Rev Sci Instrum. 1970;41(2):250–1. doi: 10.1063/1.1684482

45.Storås TH, Lian SL, Mossige I, Riseth J, Svensson SF, Løvland G, et al. T2-weighted T1 mapping and automated segmentation of CSF: Assessment of solute gradients in the healthy brain. J Magn Reson Imaging. 2026;64(1):218–27. doi: 10.1002/jmri.70169

46.Reijs BLR, Teunissen CE, Goncharenko N, Betsou F, Blennow K, Baldeiras I, et al. The central biobank and virtual biobank of BIOMARKAPD: A resource for studies on neurodegenerative diseases. Front Neurol. 2015;6:216. doi: 10.3389/fneur.2015.00216

47.Minoshima S, Drzezga AE, Barthel H, Bohnen N, Djekidel M, Lewis DH, et al. SNMMI procedure standard/EANM practice guideline for amyloid PET imaging of the brain 1.0. J Nucl Med. 2016;57(8):1316–22. doi: 10.2967/jnumed.116.174615

48.Buckley CJ, Sherwin PF, Smith APL, Wolber J, Weick SM, Brooks DJ. Validation of an electronic image reader training programme for interpretation of [18F]flutemetamol β-amyloid PET brain images. Nucl Med Commun. 2017;38(3):234–41. doi: 10.1097/MNM.0000000000000633

49.Battle MR, Pillay LC, Lowe VJ, Knopman D, Kemp B, Rowe CC, et al. Centiloid scaling for quantification of brain amyloid with [18F]flutemetamol using multiple processing methods. EJNMMI Res. 2018;8(1):107. doi: 10.1186/s13550-018-0456-7

50.Gorgolewski KJ, Auer T, Calhoun VD, Craddock RC, Das S, Duff EP, et al. The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Sci Data. 2016;3:160044. doi: 10.1038/sdata.2016.44

51.Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 2006;31(3):968–80. doi: 10.1016/j.neuroimage.2006.01.021

52.Fischl B, van der Kouwe A, Destrieux C, Halgren E, Ségonne F, Salat DH, et al. Automatically parcellating the human cerebral cortex. Cereb Cortex. 2004;14(1):11–22. doi: 10.1093/cercor/bhg087

53.Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, et al. Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron. 2002;33(3):341–55. doi: 10.1016/s0896-6273(02)00569-x

54.Fortin M-A, Kristoffersen AL, Larsen MS, Lamalle L, Stirnberg R, Goa PE. GOUHFI: A novel contrast- and resolution-agnostic segmentation tool for ultra-high-field MRI. Imaging Neurosci (Camb). 2025;3:IMAG.a.960. doi: 10.1162/IMAG.a.960

55.Andersson JLR, Skare S, Ashburner J. How to correct susceptibility distortions in spin-echo echo-planar images: Application to diffusion tensor imaging. Neuroimage. 2003;20(2):870–88. doi: 10.1016/S1053-8119(03)00336-7

56.Andersson JLR, Sotiropoulos SN. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage. 2016;125:1063–78. doi: 10.1016/j.neuroimage.2015.10.019

57.Vinje V, Zapf B, Ringstad G, Eide PK, Rognes ME, Mardal K-A. Human brain solute transport quantified by glymphatic MRI-informed biophysics during sleep and sleep deprivation. Fluids Barriers CNS. 2023;20(1):62. doi: 10.1186/s12987-023-00459-8

58.Dreyer LW, Eklund A, Rognes ME, Malm J, Qvarlander S, Støverud K-H, et al. Modeling CSF circulation and the glymphatic system during infusion using subject specific intracranial pressures and brain geometries. Fluids Barriers CNS. 2024;21(1):82. doi: 10.1186/s12987-024-00582-0

59.Causemann M, Kuchta M, Masri R, Rognes ME. In-silico molecular enrichment and clearance of the human intracranial space. bioRxiv. 2025:2025.01.30.635680. doi: 2025.01.30.635680

60.Boon WM, Hornkjøl M, Kuchta M, Mardal K-A, Ruiz-Baier R. Parameter-robust methods for the Biot–Stokes interfacial coupling without Lagrange multipliers. J Comput Phys. 2022;467:111464. doi: 10.1016/j.jcp.2022.111464

61.Valnes LM, Storås TH, Vatnehol SAS, Ringstad G, Emblem KE, Eide PK. Optimized magnetic resonance T1 mapping for estimation of intrathecal contrast concentrations in human brain and ventricular cerebrospinal fluid. Magn Reson Med. 2026;95(4):2169–79. doi: 10.1002/mrm.70203

62.Nath S, Koziarz A, Badhiwala JH, Alhazzani W, Jaeschke R, Sharma S, et al. Atraumatic versus conventional lumbar puncture needles: A systematic review and meta-analysis. Lancet. 2018;391(10126):1197–204. doi: 10.1016/S0140-6736(17)32451-0

Associated Data

Data Availability Statement

The study generates data of a sensitive nature, including detailed clinical information and imaging data. All such data are stored and managed within the Services for Sensitive Data (TSD) platform, which provides secure, access-controlled storage in accordance with institutional and regulatory requirements. Access to the dataset is restricted and can be granted upon reasonable request to the project leader, subject to applicable ethical and legal approvals. We have, however, been able to make a full imaging series publicly available from one control(60), which can be downloaded from Zenodo: https://zenodo.org/records/14266867.