Decreased CSF clearance and increased brain amyloid in Alzheimer’s disease

doi:10.21203/rs.3.rs-900478/v1

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Decreased CSF clearance and increased brain amyloid in Alzheimer’s disease

https://doi.org/10.21203/rs.3.rs-900478/v1

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published 14 Mar, 2022

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In sporadic Alzheimer’s disease (AD), brain amyloid-beta (Aβ) deposition is believed to be a consequence of impaired Aβ clearance, but this relationship is not well established in living human subjects. CSF clearance, a major feature of brain glymphatic clearance (BGC), has been shown to be abnormal in AD murine models. Prior MRI phase contrast studies have reported reduced aqueductal CSF flow in AD. Using PET and tau tracer ¹⁸F-THK5117, we previously reported that the ventricular CSF clearance of the PET tracer was reduced in AD and associated with elevated brain Aβ levels. In the present study, using two PET tracers, ¹⁸F-THK5351 and ¹¹C-PiB to estimate CSF clearance, we observe that the ventricular CSF clearance measures were correlated (r = .66, p < .01), with reductions in AD of 18 and 27%, respectively. We also replicated a significant relationship between ventricular CSF clearance (¹⁸F-THK5331) and brain Aβ load (r = −.64, p < .01). With a larger sample size, we extended our observations to show that reduced CSF clearance is associated with reductions in cortical thickness and cognitive performance. Overall, the findings support the hypothesis that failed CSF clearance is a feature of AD that is related to Aβ deposition and to the pathology of AD. Longitudinal studies are needed to determine whether failed CSF clearance is a predictor of progressive amyloidosis or its consequence.

Clinical Pharmacology

Psychiatry

Pathology

Alzheimer’s disease (AD)

brain amyloid-beta (Aβ)

brain glymphatic clearance (BGC)

F-THK5331

MRI

PET

CSF clearance is impaired in mild AD and inversely related to brain Aβ deposition, and related to cognative function and cortical thickness.

Two decades after it was hypothesized that the amyloidosis of sporadic Alzheimer's disease (AD) is mechanistically related to the impaired clearance of Aβ [1,2], there is limited understanding of the pathophysiology of brain Aβ clearance in sporadic AD [3–5]. Part of the difficulty relates to the absence of direct, non-invasive methods to examine the role of human CSF as a carrier of Aβ and other waste molecules. Human lumbar spine CSF sampling studies with ¹³C₆-leucine have demonstrated a systemic Aβ clearance deficit in AD in the context of unchanged Aβ production [6]. Murine studies have revealed a brain glymphatic clearance system where waste products including Aβ are carried in the interstitial fluid (ISF) and CSF [7–9] and drain into immune modulated dural lymphatics [10]. In transgenic AD models, these clearance deficits are progressive [11].

Neuroimaging, including MRI and PET and computational fluid dynamics analysis have been employed to investigate the glymphatic transport function in the live animal and human brain [12]. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) showed potential to tracking glymphatic solute and fluid transport in the CNS with both intrathecal and intravenous Gd-DOTA injection [13–16]. Several quantification methods of the glymphatic clearance utilize the CSF and brain signal changes in dynamic PET [15,17,18]. We previously observed that ventricular CSF clearance was reduced in AD and inversely related to the magnitude of brain Aβ deposits measured using ¹¹C-PiB [17]. In the present study, a larger sample and a different tracer, ¹⁸F-THK5351, were used to measure CSF clearance. In each subject, ¹¹C-PiB was used to measure the amyloid burden, and MRI to estimate brain atrophy. Our results with ¹⁸F-THK5351 radiotracer replicate the prior AD clearance reductions and the association of these clearance deficits with Aβ lesions. We report for the first time that the magnitude of CSF clearance is inversely related to decreased cortical thickness and to decreased cognitive function.

Study Participants: 24 elderly subjects (age range 61–90 y, 10 male and 14 female) participated in this IRB approved study. Written informed consent was obtained from each participant or their legal caretakers. Participants included 9 normal controls (NL) and 15 AD subjects including 6 very mild cases (CDR = 0.5) and 9 with mild to moderate cognitive symptoms (CDR ≥ 1.0) [19] [20]. All subjects showed amyloid deposits in cerebral cortex with global PiB uptake ratio greater than 1.25 [21]. AD patients were recruited from the memory clinic of Tohoku University Hospital. The controls were recruited from the general community. Subject diagnoses were made at a consensus conference according to the National Institute of Neurological and Communicative Disorders and Stroke/AD and Related Disorders Association criteria [22]. All participants received standardized clinical and neuropsychological assessments, including CDR, MMSE and ADAS-cog.

PET and MRI Image Acquisition: Each study participant received within a 3-month interval, the clinical assessments, a high resolution T1-weighted MRI, and two dynamic PET exams, one exam performed with ¹⁸F-THK5351 tracer used to estimate CSF clearance and the other with ¹¹C-PiB- for Aβ. The syntheses of ¹⁸F-THK5351 and ¹¹C-PiB compounds were previously described [23] [24]. PET imaging was performed using an Eminence STARGATE PET-CT scanner (Shimadzu, Kyoto, Japan). On separate days, subjects received an intravenous injection of ¹⁸F-THK5351 (185 MBq), or ¹¹C-PiB (296 MBq). Dynamic PET data were obtained in list mode for 60 min for ¹⁸F-THK5351 and 70 min for ¹¹C-PiB. Images tracking the time course of ¹⁸F-THK5351 and ¹¹C-PiB exams were reconstructed to a 128 x 128 x 79 matrix of 2 x 2 x 2.6 mm voxels in 26 time frames for ¹⁸F-THK5351 and 25 frames for ¹¹C-PiB. MR images were obtained using a SIGNA 1.5 tesla unit (General Electric, Milwaukee, WI). The MRI protocol included a 3D volumetric acquisition of a T1-weighted gradient echo sequence with parameters: echo time/repetition time 2.4/50 ms; flip angle 45°; acquisition matrix 256 × 256; 1 excitation; field of view 22 cm; and a 2.0 mm slice thickness without gaps.

MRI Segmentation: FreeSurfer software (v. 6.1) was used for MRI brain segmentation [25]. Regions of Interest (ROIs) were determined for the neocortical gray matter (GM) and white matter (WM), the cerebellar gray matter, and the combined left + right lateral ventricle [26]. The whole brain ROI was derived from FreeSurfer aparc + aseg file [27] which includes the complete cerebral and cerebellar volume and pons. The average thickness of the neocortical GM was used as an index of brain atrophy. Statistical Parametric Mapping (SPM 12) software (www.fil.ion.ucl.ac.uk/spm) was used to calculate the total intracranial volumes. To optimize CSF sampling from the lateral ventricle and minimize partial volume contamination by brain tissue, an eroded lateral ventricle mask ELVM was created using the 4 mm 3D erosion of MRI-segmented ventricles. Both ¹⁸F-THK5351 and ¹¹C-PiB scans have been visually examined, and no choroid plexus binding was observed with both tracers.

PET Image Workflow: After decay correction, standardized uptake value (SUV) time-framed images were created by normalizing the reconstructed radioactivity by injected dose and body weight. To minimize the effect of head motion for each subject, the dynamic PET frames were realigned to the first-time frame using SPM. The anatomically segmented MR images were co-registered separately to the space of the ¹⁸F-THK5351 and ¹¹C-PiB PET scans using SPM12. Satisfactory inter-modality alignment was verified for each exam by an experienced neuroradiologist. Each PET time frame was partial volume corrected (PVC) using a modified one tissue model [28].

Estimations of PET tracer clearance: Ventricular CSF, whole brain and blood time activity curves (TAC) were derived for each participant. Tracer concentrations in the blood were sampled from the internal carotid artery, guided by MR scans that were co-registered to the PET data [29]. Blood TAC reached a peak within 2 min and approached low asymptotic time course by 4 min (Fig. 1a). Brain TACs reached a peak between 2 and 4 minutes after injection of tracer. The ventricular CSF clearance was derived from the slope of a linear regression fit of SUV(t) for ELVM (see MRI segmentation section) over 10–30 min [30]. The 10–30 min time frame was selected to minimize the potential contribution of blood in the choroid plexus. To control for the variability in the amount of radiotracer delivered to the brain across subjects, the slope was normalized by the total brain SUV of the tracer over the first 4 minutes after injection. To facilitate data interpretation and avoid dealing with negative quantities, the absolute value of the clearance slope was used. The resulting normalized absolute value slope was denoted as vCSF-SLOPE and used throughout this study to estimate CSF clearance rate.

PET SUVr Estimations of brain amyloid: The amyloid binding of cerebral grey matter was estimated using ¹¹C-PiB binding based on the 50–70 min interval, as we reported previously[31]. The uptake period with the cerebellar gray matter was used as the reference tissue in the standardized uptake value ratio (SUVr).

Statistical Analysis: The general linear model and univariate analysis of variance (ANOVA), with Tukey post hoc tests, were used to examine the vCSF-SLOPE across the NL and AD clinical groups. All significant results were confirmed using the nonparametric Mann–Whitney test with Bonferroni corrections for multiple comparisons. The relationships between the vCSF-SLOPE and Aβ binding, cortical thickness and cognitive function were tested using parametric correlation models, and nonparametric correlation models were tested if the the data was not normally distributed. The ventricular volume and age were tested as covariates in our regressions. All statistical tests were two-sided and significance was set at p < .05. All analyses were checked for violations of the model assumptions, and no conflicts were found.

Clinical data: The demographic data from the NL and AD groups are shown in Table 1. There were no age or gender differences by group. The ADAS-cog and MMSE were significantly different in AD subjects as compared with NL (ADAS-cog: F = 21.1 p < .01, MMSE: F = 23.5 p < .01).

Table 1

Participant demographic data
	N	age	Gender(M/F)	MMSE*	ADAS-cog*
NL	9	72.8 (8.9)	3/6	28.8(1.3)	4.8 (2.2)
AD	15	76.3 (8.9)	7/8	21.9(4.3)	16.5 (7.1)
Values are expressed as mean (SD); *p < .0.01, between NL and AD groups.

Clearance derived from ¹⁸F-THK5351 and ¹¹C-PiB tracers

Group vCSF Clearance Effect

Both ¹⁸F-THK5351 and ¹¹C-PiB tracers showed significantly lower vCSF-SLOPE in AD as compared with NL. The vCSF-SLOPE_THK5351 was reduced in AD by 20% (F = 10.2, p < .01). The vCSF-SLOPE_PiB was reduced by 28% in AD (F = 24.4, p < .01, see Table 2). The findings remained significant after PVC (p < .01 for all).

Within subject vCSF: Across the entire sample, the vCSF-SLOPE_THK5351 and vCSF-SLOPE_PiB were closely associated (r = .66, p < .01, n = 24, see Fig. 2). The correlation remained significant when the analysis was restricted to the AD group (r = .61, p < .05, n = 15).

The effects of CSF clearance on cortical thickness and the tracer binding

Group Tracer Binding Effects. The PiB PET examined within the 50–70 min SUVr showed significantly higher (46%) GM binding in AD as compared with NL (see Table 2). We also tested both tracers for binding during the interval when clearance measurements were made. From 10–30 min a PiB GM SUVr binding effect was observed in the AD group, significantly higher (by 22%, p < .01) than in NL. However, at 10–30 min, the difference in THK5331 SUVr, higher by 5% in AD vs NL, was not significant (p > .05).

Table 2

vCSF-SLOPE and tracer binding
Group	vCSF-SLOPE_THK5351	vCSF-SLOPE_PiB	¹¹C-PiB GM SUVr 50–70 min	¹¹C-PiB GM SUVr 10–30 min	¹⁸F-THK5351 GM SUVr 10–30 min
NL	.11(.02)	.11(.01)	1.28(0.17)	1.02(0.05)	1.30(0.12)
AD	.09(.02)	.08(.02)	1.88(0.30)	1.25(0.12)	1.37(0.10)
Diff. from normal	-18%, p < .01	-27%, p < .01	46%, p < .01	22%, p < .01	5%, NS

The relationship between vCSF clearance and amyloid binding. Across all subjects, the vCSF-SLOPE_THK5351 was inversely correlated with the Aβ GM binding (r=-.64, p < .01, n = 24, see Fig. 3). This correlation remained significant after PVC (r=-.72, n = 24, p < .01). Importantly, the relationship between vCSF-SLOPE and Aβ GM binding remained significant when restricted to the AD group (r = −.58, n = 15, p < .05). The relationship between vCSF-SLOPE and GM Aβ binding was not significant in the NL group (p > .05).

The relationship of CSF clearance and cortical thickness. The vCSF-SLOPE_THK5351 was positively correlated with the cerebral cortex thickness (r = .55, n = 24, p < .01). The correlation was a trend when restricted to the AD group (r = .45, n = 15, p = .08), reaching p < .05 significance in a one-tailed test. However, it was not significant in the NL group.

CSF Clearance, Ventricular Volume and age: To rule out ventricular size and age as confounds for the vCSF-SLOPE measure, we examined the ventricular volume and age as covariates in our regressions. We observed that for the total group the correlation between vCSF-SLOPE_THK5331 and Aβ GM binding remained significant after adjustment for the age and ventricular size (r = −.44, p < .05, n = 24). In an analysis restricted to the AD group, this relationship remained significant even after controlling for the age and ventricular size (r=-.56, n = 15, p < .05).

CSF clearance vs tracer binding and cognitive performance

Over all subjects, the vCSF clearance was inversely correlated with the ADAS-cog (vCSF-SLOPE_THK5351 r=-.55, p < .01, n = 24). Studying the clinical groups separately showed that only in the NL group did the association of vCSF-SLOPE_THK5351 and ADAS-cog remain significant (r=-.83, n = 9, p < 0.01). Over all subjects, the PiB tracer binding in GM was also correlated with the ADAS-cog (r = .77, p < .01, n = 24). Studying the two groups separately showed that only in the AD group did the association of the PiB tracer GM binding and ADAS-cog remain significant (r = .58, n = 15, p < .05).

The impaired clearance of CSF in AD: The impaired clearance of Aβ and the impaired clearance of the CSF and ISF that drains the Aβ from the brain has been suspected for many years as playing a role in the deposition of Aβ in the AD brain [32–35]. Abnormalities in several physiological clearance mechanisms that potentially underlie Aβ removal from the brain have been shown in animal models. These include clearance across the BBB [36], enzymatic degradation [37–39], perivascular Aβ lesions affecting ISF bulk flow [40], reduced glymphatic paravascular clearance in AD-Tg mice [7], lymphatic and immune related clearance failures [10], and defects in CSF absorption [41].

Prior MRI phase contrast studies have shown reduced CSF flow at the acqueduct in AD as compared to mild cognitive impairment (MCI) [42] and associated with cognitive deficits [43]. However, the phase contrast method directly measures pulsatile velocity rather than the flow and the results are highly variable across studies [44, 45]. Intrathecal MR contrast studies directly show CSF flow and the glymphatic transport of Gd-DTPA through the brain parenchyma [46, 47]. While dynamic contrast MRI appears to be more precise in evaluating the CSF clearance function, the intrathecal administration of contrast is more invasive and it has limited application in clinical practice. Compared to these MRI measures, our dynamic PET measure reflects tracer removal rate from the ventricle, which appears to more directly reflect the rate of CSF clearance.

PET studies show that small molecular weight PET tau and amyloid tracers demonstrate rapid brain penetrance and clearance, with over 70% of the injected dose cleared from the brain by the study end [48–50]. We exploited this feature in our studies as a potential CSF clearance biomarker [17]. Previously we reported in a small sample that ventricular CSF clearance is reduced in AD and inversely associated with brain Aβ levels. Now, using THK533, another radiotracer, and with a larger sample, we report a replication of our prior findings. Moreover, we report for the first time correlations between CSF clearance and brain atrophy and cognitive functioning as related to AD.

Recent transgenic AD mouse studies have demonstrated age-related reductions in ISF and CSF clearance as well as CSF clearance deficits prior to Aβ accumulation [7, 51]. In humans, using a ¹³C₆-leucine labelled Aβ and continuous lumbar spine CSF sampling, Bateman et al. observed that Aβ clearance was reduced 33% in AD but the Aβ production rate was unaffected [3, 6]. Consistent with Bateman et al., we observed a 20% reduction relative to NL group when CSF clearance was measured with ¹⁸F-THK5331 and 28% when measured with ¹¹C-PiB PET.

The present study replicates and extends our prior report that impaired human CSF clearance can be estimated in vivo using dynamic PET imaging [17]. We estimated the overall CSF clearance rate by quantifying the rate of change in tracer in lateral ventricles. With similar reasoning, Silverberg et al. used an invasive method with a ventricular catheter to test the hypothesis that impaired CSF dynamics were associated with AD (Silverberg et al., 2001). They estimated the CSF production rate using intrathecal pressure changes before and after a volume of CSF was removed. However, this method is invasive, and a method that does not perturb the very system that is being measured would be preferable. With our minimally invasive PET technique, we observed close relationships between the magnitude of reduced CSF clearance and an increased brain Aβ burden, the loss of brain tissue, and reduced memory performance.

Impaired CSF clearance and brain amyloid: Our dynamic PET data suggest ventricular CSF clearance could be a useful marker to monitor the CSF flow dysfunctions. Overall, our results are consistent with prior evidence showing that the increased residence time of Aβ contributes to its aggregation and fibrillization in the extracellular space [52]. We find reduced CSF clearance in AD for both THK5331 and PiB PET radiotracers. Moreover, the clearance measures were significantly correlated (r = .66, n = 24, p < .01) cross tracers. It is important to consider that the CSF flow is highly correlated across tracers even though the magnitude of brain binding is four-fold greater for the PiB tracer than for the THK5331 tracer. This supports the validity of the method and point towards a preference to the THK5331 for clearance estimations. Further highlighting the value of the method, the clearance correlation with the amyloid burden was seen in the total group as well separately within the AD group.

¹⁸F-THK5351 was developed as tau tracer, but off-target binding to Monoamine oxidase B has been reported, thus invalidating the tau specificity. Consequently, we did not use the THK5331 to estimate the tau burden. Therefore, it remains untested whether CSF clearance is related to tau binding. Other more selective tau tracers are now under investigation, which may establish the relationshiop between CSF clearance and brain tau binding.

The PiB tracer, which also demonstrated utility as a CSF clearance agent, appears to be partially confounded by disease-sensitive binding detectable in the time frame used to estimate CSF clearance. We believe this is reflected in the greater PiB clearance 27% vs 18% for THK5331, since some of the PiB tracer enters Aβ plaques even in the initial 10–30 min time window. Overall, as compared with PiB, THK53351 has an advantage as a clearance agent.

Impaired CSF clearance is associated with decreased cognitive function: The CSF clearance measure and the brain amyloid binding were both associated with cognitive function. Intriguingly, in the subgroups analysis, the association of CSF clearance and cognitive function was significant in the NL group(r=-.83, n = 9, p < 0.01), while the correlation between brain amyloid binding and cognitive function was significant in the AD group (r = .58, n = 15, p < .05). These data suggest that the CSF clearance measure could have potential in the early disease stages to serve as a biomarker to monitor prelesion disease progression. In the absence of longitudinal data, this remains speculative. Nevertheless, this observation agrees with a previous animal study that showed clearance deficits prior to Aβ lesions [7].

Confounds and study limitations: ventricular CSF clearance could be confounded by both specific and non-specific binding of the tracer in the brain. However, our tests suggest that for the time interval studied, a relative independence of clearance and binding effects for THK5331. This is supported by the observation that ¹⁸F-THK5351, unlike ¹¹C-PiB, did not show binding effect at the 10–30 min time interval. Additional evidence justifying that tracer brain binding has a negligible effect on CSF clearance rate is based on the high within-subject correlations for ¹⁸F-THK5351 and PiB (r = .66, p < 0.01), even though the tracers have different binding distribution volumes [53, 54]. Precise quantification would require using a radiotracer that has no known binding profile while retaining a profile of rapid blood-CSF-brain barrier penetrance and clearance [55]. Overall, the results suggest that brain tracer binding had limited effect on vCSF-SLOPE for ¹⁸F-THK5331 and ¹¹C-PiB.

We evaluated several other possible confounds, including choroid plexus binding and partial-volume errors. Neither tracer showed choroid plexus binding that could potentially bias the ventricular clearance estimates. The ventricular partial volume error, due to contamination by proximity to brain, was minimized by individually sampling the ventricle 4 mm from the brain and with subsequent partial volume corrections [56]. Partial volume correction did not change the results. Another possible confound, the enlarged ventricular volume in AD may cause tracer dilution, thereby altering the clearance function. This was also tested and fount not to affect our findings.

Overall, our cross-sectional findings are consistent with the hypothesis that CSF turnover reductions are found in AD. Moreover, these data support a mechanism whereby Aβ is deposited in brain due to reductions in CSF clearance [3, 35]. However, a longitudinal sample is needed for estimating the directionality of the relationship between impaired clearance and brain Aβ deposits.

Ethics approval and consent to participate: The protocol was approved by the Ethics Committee of Tohoku University Hospital.

Availability of data and materials: The datasets analyzed during the current study are available from the corresponding author on request.

Acknowledgments: The authors would also like to thank Dr. Louisa Bokacheva for review this manuscript.

Funding: This study was supported by NIH/NIA grants AG057848, RF1AG057570, R56 AG058913, AG022374, AG013616, AG012101, T32AG052909-01A1, NIH-HLB HL111724 and HL118624. The work at Tohoku University was supported by Health and Labor Sciences research grants from the Ministry of Health, Labor, and Welfare of Japan, a Grant-in-Aid for Scientific Research (B) (23390297), a Grant-in-Aid for Scientific Research on Innovative Areas (26117003), a grant from the Japan Advanced Molecular Imaging Program (J-AMP) of the Ministry of Education, Culture, Sports, Science and Technology, and the research fund from GE Healthcare and Sumitomo Electric Industries, Ltd.

Author contributions: YL, MdeL, and HRdesigned and conducted the study. NO, HY, LZ contributed to the acquisition of the imaging data and its interpretation LG, TB, GB, JB, P. DM, SN, SP, ET, SS, RC, NT contributed to data interpretation, LP was responsible for the statistical analyses

Competing interests: The authors declare that they have no competing interests.

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You are reading this latest preprint version

Decreased CSF clearance and increased brain amyloid in Alzheimer’s disease

Status:

Journal Publication

Version 1

Abstract

Figures

One Sentence Summary

Introduction

Materials And Methods

Results

Clearance derived from ¹⁸F-THK5351 and ¹¹C-PiB tracers

The effects of CSF clearance on cortical thickness and the tracer binding

CSF clearance vs tracer binding and cognitive performance

Discussion

Declarations

References

Status:

Journal Publication

Version 1

Decreased CSF clearance and increased brain amyloid in Alzheimer’s disease

Status:

Journal Publication

Version 1

Abstract

Figures

One Sentence Summary

Introduction

Materials And Methods

Results

Clearance derived from 18F-THK5351 and 11C-PiB tracers

The effects of CSF clearance on cortical thickness and the tracer binding

CSF clearance vs tracer binding and cognitive performance

Discussion

Declarations

References

Status:

Journal Publication

Version 1

Clearance derived from ¹⁸F-THK5351 and ¹¹C-PiB tracers