Distinct tau pathologies in the nucleus basalis of Meynert between early-onset and late-onset Alzheimer's disease patients revealed by positron emission tomography

Abstract

Background

Tau accumulation in the nucleus basalis of Meynert (nbM) has been documented in Alzheimer's disease (AD), but its relationship to neuropathological changes in other brain regions and cognitive deficits remains unclear, particularly between early-onset AD (EOAD) and late-onset AD (LOAD).

Objective

To evaluate tau accumulation patterns in the nbM and other brain regions in EOAD and LOAD using ¹⁸F-florzolotau PET and examine correlations with cognitive function.

Methods

Thirty-eight amyloid-positive AD patients (15 EOAD, 23 LOAD) and 46 healthy controls underwent ¹⁸F-florzolotau PET. Tau levels were quantified in the nbM and Braak-staging regions. Postmortem brain samples were examined to assess ¹⁸F-florzolotau binding to tau deposits.

Results

EOAD showed a higher overall tau burden, including in the nbM, compared with LOAD. However, nbM tau levels correlated more strongly with cognitive decline in LOAD than EOAD. The relationship between nbM tau and neocortical tau differed between EOAD and LOAD. Histopathology revealed abundant ¹⁸F-florzolotau labeling of neurofibrillary tangles (NFTs) and ghost tangles in AD nbM samples.

Conclusions

This study provides the first in vivo PET evidence of differential nbM tau pathology between EOAD and LOAD, with higher accumulation but weaker correlation to cognition in EOAD. The distinct relationships between nbM and cortical tau in EOAD and LOAD suggest divergent pathological trajectories. ¹⁸F-florzolotau PET successfully visualized NFTs and extracellular ghost tangles in the nbM across AD stages. These findings highlight the importance of considering age of onset when evaluating tau pathology and its clinical correlates in AD.

Keywords

Alzheimer's disease florzolotau (18F)histopathology nucleus basalis of Meynert PET tau

Introduction

Dementia poses a significant global health challenge, with its prevalence projected to triple by 2050, primarily due to an aging population.¹ Alzheimer's disease (AD) is the most common cause of dementia, characterized by neurodegeneration and the accumulation of extracellular amyloid-β (Aβ) plaques and intracellular neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau beyond the normal aging process. Most AD cases occur in old age, leading to a slow decline in cognitive function, especially in memory,² and eventually to a general deterioration of cognitive functions.

Approximately 5–6% of patients with AD are classified as having early-onset AD (EOAD), which develops before 65 years of age and is considered more heritable than late-onset AD (LOAD).^3,4 EOAD and LOAD differ significantly in their clinical presentation and course, with patients with EOAD experiencing faster cognitive decline than those with LOAD. Additionally, patients with EOAD often exhibit non-amnestic symptoms, such as executive dysfunction, language impairment, psychiatric symptoms, and visuospatial dysfunction, rather than memory loss. Consequently, these differences result in severe financial and occupational repercussions for patients with EOAD and their caregivers compared with those with LOAD.^5–7 Therefore, EOAD poses a significant social burden, warranting urgent clarification of its neuropathological characteristics along with the development of early diagnostic and therapeutic strategies. However, the neuropathological differences between EOAD and LOAD remain unclear.

Although Aβ accumulation in AD tends to saturate before the onset of clinical symptoms, past neuropathological studies have reported that hyperphosphorylated tau accumulation progresses more slowly than Aβ accumulation, correlating more closely with the clinical symptoms of AD.⁸ Postmortem studies have documented the fewest neurons in the nucleus basalis of Mynert (nbM) in hippocampal-sparing AD and greater accumulation of NFT, twice that observed in limbic-predominant AD,⁹ suggesting that nbM tau deposits may be more intense in EOAD than in LOAD. However, it remains undetermined whether the difference in the NFT load between EOAD and LOAD is characteristic of nbM or commonly observed across diverse brain regions. It also remains unclear whether the relationship between NFT load and clinical symptoms in the nbM differs between EOAD and LOAD. The nbM is an initiating nucleus of cholinergic neurons,^10–12 a brain region involved in various cognitive functions, such as memory, and executive functions.^13,14 Therefore, the relative abundance of tau lesions in the nbM compared with that in other brain areas may underlie the distinct symptomatic features in EOAD and LOAD cases.

Core neuropathological changes in AD can now be assessed noninvasively using positron emission tomography (PET) tracers specifically binding to abnormal protein aggregates. PET studies using amyloid tracers have reported high Aβ loads in several cortical and subcortical regions of EOAD compared with those in LOAD.^15,16 A recent PET study using a tau tracer, ¹⁸F-flortaucipir, has revealed enhanced tau accumulations in the frontal and temporoparietal cortices of patients with EOAD compared with those in patients with LOAD.^17,18 However, non-specific retentions of this tracer in the basal ganglia and neighboring areas, including the nbM, may impede assessments of nbM tau pathologies, and no PET reports with other imaging agents have investigated tau depositions in the basal forebrain.¹⁹ PET with florzolotau (18F) (¹⁸F-florzolotau), also known as ¹⁸F-PM-PBB3/¹⁸F-APN-1607, offers high-contrast tau imaging of the nbM, owing to its minimal retentions in the ventral striatum and basal forebrain regions.^20–22

This study aimed to evaluate tau accumulation patterns in the nbM and other brain regions in EOAD and LOAD using ¹⁸F-florzolotau PET. Subsequently, we clarified the relationship between tau accumulations in the nbM and limbic or neocortical regions characterized by Braak staging. Additionally, we evaluated the correlation between nbM tau depositions and cognitive functions in the EOAD and LOAD groups. The PET data were also supplemented by histopathological examination of the nbM sections of patients with AD and healthy controls (HCs) derived from a brain bank, as in previous assays.^23–25

Methods

Participants

Patients with AD were recruited from affiliated medical institutes. Patients who met Petersen's criteria and the National Institute of Neurological and Communicative Diseases and Stroke/Alzheimer's Disease and Related Disorders Association criteria were enrolled.^26,27 Each patient not only fulfilled the established clinical criteria for AD but was also positive on ¹¹C-PiB PET. Age-matched HCs from the National Institutes for Quantum and Radiological Science and Technology volunteer association also participated. The HCs did not have any neurological or psychiatric diseases. All participants were assessed on a neuropsychological battery, including the Mini-Mental State Examination (MMSE),²⁸ the Clinical Dementia Rating Scale Sum of Boxes (CDR SoB), and the Frontal Assessment Battery (FAB).^29–31 Subsequently, we included amyloid-positive patients with AD as the AD group and amyloid-negative HCs in the present analysis. All participants also underwent magnetic resonance imaging (MRI) examinations and tau PET scans. Written informed consent was obtained from all participants. The study protocol was approved by the Institutional Review Board of the National Institutes for Quantum Science and Technology (QST), Chiba, Japan. The current study was registered with the University Hospital Medical Information Network (UMIN 000030248). Information on educational levels was not available for five HCs.

PET acquisition and imaging data processing

A total of 38 ¹¹C-PiB-positive patients with AD and 46 age-matched HCs underwent PET with ¹⁸ F-florzolotau. Radiosynthesis of these PET ligands was conducted following a previously documented method.^20,32,33

For patients with AD, the injected radioactivities of ¹¹C-PiB and ¹⁸F-florzolotau were 515.5 MBq and 185.3 MBq, respectively, while the molar activities of ¹¹C-PiB and ¹⁸F-florzolotau at the time of injection were 74.9 GBq/μmol and 268.8 GBq/μmol, respectively. Among HCs, the injected radioactivities of ¹¹C-PiB and ¹⁸F-florzolotau were 513.9 MBq and 187.5 MBq, respectively, while the molar activities of ¹¹C-PiB and ¹⁸F-florzolotau at the time of injection were 76.3 GBq/μmol and 237.8 GBq/μmol, respectively. No significant differences were observed in the injected dose or molar activity of ¹¹C-PiB and ¹⁸F-florzolotau between the AD and HC groups.

Fifty minutes after an intravenous rapid bolus injection of ¹¹C-PiB, a 20-min PET acquisition (4 × 5-min frames) was performed using a Biograph mCT flow system (Siemens Healthcare, Erlangen, Germany) or an ECAT EXACT HR + (CTI-Siemens, Knoxville, TN, USA) PET scanner system, as described in the previous report.²⁰

Ninety minutes after an intravenous rapid bolus injection of ¹⁸F-florzolotau in a dim room to avoid photoracemization, a 20-min PET acquisition (4 × 5-min frames) was performed using the Biograph mCT flow system.

For each tau PET scan, a head-fixation device was used to minimize the patient's head movement during the PET measurements. The mCT flow system provided 109 sections with an axial field of view of 21.8 cm. The intrinsic spatial resolution was 5.9 mm in-plane and 5.5 mm full-width at half maximum axially. Images were reconstructed using a filtered back-projection algorithm with a Hanning filter (4.0 mm full-width at half-maximum). Attenuation correction was applied based on computed tomography images for randomness using the late coincidence counting method. All the PET images were corrected for scattering using the single-scatter simulation method.

MRI acquisition

These patients and 46 age-matched HCs underwent MRI using a 3-T MRI scanner (MAGNETOM Verio, Siemens, Germany). Three-dimensional volumetric acquisition of a T1-weighted gradient-echo sequence produced a gapless series of thin sagittal sections (echo time, 1.95 ms; repetition time, 2300 ms; inversion time, 900 ms; field of view, 250 mm; flip angle, 9°; acquisition matrix, 512 × 512; and axial slice thickness, 1 mm).

Data preprocessing and definition of regions of interest (ROIs)

All images were preprocessed using PMOD software (version 4.1, PMOD Technologies Ltd, Zurich, Switzerland), FreeSurfer 7.0 (http://surfer.nmr.mgh.harvard.edu/), MATLAB (The Mathworks, Natick, MA, USA), and Statistical Parametric Mapping software (SPM12, Wellcome Department of Cognitive Neurology). For each T1-weighted image, surface-based cortical reconstruction and volumetric subcortical segmentation were performed using FreeSurfer software. PET images were coregistered with individual anatomical T1-weighted MR images, and standardized uptake value ratio (SUVR) images were generated using each reference region. The cerebellar cortex was the reference region for the ¹¹C-PiB-PET and ¹⁸F-florzolotau PET images.

Tau accumulation was quantified using ROIs targeting tau pathology associated with AD: Braak-staging ROIs (I/II, III/IV, and V/VI) and the nbM. For Braak-staging ROIs, Desikan–Killiany–Tourville ROIs were generated using surface-based cortical reconstruction with FreeSurfer and combined with cortical and Braak-staging ROIs.³⁴ The resulting localization ROIs were of Braak stages I/II, III/IV, and V/VI, roughly corresponding to the anatomical definitions of the Braak stages of AD. The hippocampus was excluded from the Braak stage III/IV ROI due to potential spill-in from off-target binding in the choroid plexus. The nbM ROI was defined using stereotaxic probabilistic maps of the magnocellular cell groups in the human basal forebrain (SPM Anatomy Toolbox r 2.2b, http://www.fz-juelich.de/ inm/inm-1/DE/Forschung/). We also defined the nbM ROI using a combined Ch4 and Ch4p template atlas in the previous report.³⁵ To evaluate the nbM ROI in the same space as the Braak-staging ROIs, we transformed these templates to the native space from the Montreal Neurologic Institute space in a semi-automatic manner.³⁶ Firstly, we created a transformation matrix by normalizing the native T1 image to the Montreal Neurologic Institute space using diffeomorphic deformation (advanced normalization tools) implemented in PMOD software and calculated the inverse matrix. Subsequently, we transformed the nbM ROI template to the native space. Finally, we optimized the transformed ROI by manually adjusting its coordinates and contours (Figure 1A).

Figure 1.

ROIs and ¹⁸F-florzolotau accumulation in the nbM.

We measured the regional brain volumes of the nbM ROIs by dividing the raw volume of the nbM by the subject's intracranial volume (ICV) calculated using FreeSurfer and then multiplying by the average ICV for the entire dataset.

Analysis and assessments of amyloid and tau PET images

Parametric amyloid PET images were generated through voxel-based calculation of the SUVR to the cerebellar cortex within 50–70 min. In this study, patients were classified as Aβ-positive or negative based on visual inspection of ¹¹C-PiB SUVR images based on the standard method used in the Japanese Alzheimer's Disease Neuroimaging Initiative study.³⁷

Parametric tau PET images were generated through voxel-based calculations of the SUVR relative to the cerebral gray matter within 90–110 min.

Histopathological examination of the nbM using postmortem brains derived from patients with AD and control participants

To evaluate the neuropathological characteristics of the NFTs of the nbM in AD, we conducted histopathological examination using the Klüver-Barrera method, the Gallyas-Braak method, the AT8 antibody, and hematoxylin and eosin staining. To assess the detectability of NFTs of the nbM in AD by ¹⁸F-florzolotau, we also conducted fluorescent staining with florzolotau, immunostaining with AT8 and N1D antibodies, and the Gallyas-Braak method of the nbM in brain sections from 6 patients with AD and 2 control cases. Details of the pathological section preparation and clinical information are described in the Supplemental Table 1.

Statistical analyses

Statistical analyses were conducted using GraphPad Prism, version 9.5.1 (GraphPad Software, Boston, MA, USA). Thirty-eight patients with AD were categorized into two groups: EOAD, defined as onset before age 64 years, and LOAD, defined as onset after age 65 years.^3,38 Demographic data were compared among the groups using Fisher's exact test and the Mann–Whitney U test. We performed the Kruskal–Wallis test to compare the ICV-corrected volumes of the nbM ROIs among the EOAD, LOAD, and HC groups. The Mann–Whitney U test was performed to compare mean cortical ¹¹C-PiB SUVR values between the EOAD and LOAD groups. We compared the mean ROI ¹⁸F-florzolotau SUVR values among the EOAD, LOAD, and HC groups using the Kruskal–Wallis test and multiple comparisons with Bonferroni corrections. We also compared the ¹⁸F-florzolotau SUVR values in the Braak-staging ROIs among the EOAD, LOAD, and HC groups using the Kruskal–Wallis test and multiple comparisons with Bonferroni corrections. Furthermore, for both the EOAD and LOAD groups, correlations of the SUVR values in the nbM with those in the Braak stage I/II, Braak stage III/IV, and Braak stage V/VI ROIs were assessed using the Spearman's rank correlation coefficient analysis separately. Additionally, we analyzed the correlation between the ¹⁸ F-florzolotau SUVR values in the nbM and clinical status, according to assessments such as the MMSE, CDR SoB, FAB, and age, using Spearman's rank correlation coefficient analysis. These correlation analyses were performed without correction for multiple comparisons (alpha-value ≤ 0.05) since the correlations were exploratory and hypothesis-generating rather than confirmatory. We also compared the ratio of SUVR in the nbM and Braak-staging regions between the EOAD and LOAD groups without correction for multiple comparisons. The cut-off value of the nbM SUVR to discriminate between HC and ¹¹C-PiB (+) AD cases was determined using the area under the curve (AUC) of the receiver operating characteristic (ROC). The p values in the text are the adjusted P-values used when correction for multiple comparisons was performed.

Results

Demographic characteristics

We enrolled 38 ¹¹C-PiB-positive patients with AD along with 46 age-matched HCs. Table 1 displays the demographic and clinical characteristics of the participants. No significant differences were observed in age (U = 665, p > 0.06), sex (p = 0.27), or years of education (U = 684.5, p = 0.33) between patients with AD and HCs. The MMSE and FAB scores were significantly lower in the AD group (MMSE: U = 0, p < 0.0001; FAB: U = 242.5, p < 0.0001) than in the HC group. No significant differences were observed in sex (p > 0.99), years of education (U = 148.5, p = 0.46), MMSE scores (U = 169.0, p = 0.92), CDR SoB scores (U = 166, p = 0.85), or FAB scores (U = 71, p = 0.08) between the EOAD and LOAD groups. However, age was significantly lower in the EOAD group (U = 4.0, p < 0.0001) than in the LOAD group. None of the patients included in the current study had familial AD.

Table 1.

Demographic characteristics.

	Healthy Controls	Alzheimer's disease	Onset		Statistical test
	Healthy Controls	Total	Early Onset	Late Onset	Statistical test
N	46	38	15	23
Sex (Female/Male)	20/26	22/16	9/6	13/10	nsns
Mean age (y)	64.7 ± 10.8	69.2 ± 10.8	57.9 ± 6.1	76.3 ± 5.4	nsp < 0.001
Education (y)	14.4 ± 1.8	14.0 ± 2.4	14.5 ± 2.5	13.7 ± 2.3	nsns
MMSE	29.30 ± 0.8 (N = 46)	20.5 ± 6.0 (N = 38)	19.9 ± 7.0 (N = 15)	20.9 ± 5.3 (N = 23)	p < 0.001ns
CDR SoB	NE	4.75 ± 4.3 (N = 38)	4.9 ± 5.0 (N = 15)	4.6 ± 3.8 (N = 23)	NEns
FAB	16.3 ± 1.2 (N = 44)	12.5 ± 3.4 (N = 32)	14.1 ± 3.2 (N = 11)	11.7 ± 3.3 (N = 21)	p < 0.001ns

CDR SoB: Clinical Dementia Rating Sum of Boxes; FAB: Frontal Assessment Battery; MMSE: Mini-Mental State Examination; N: sample size; NE: not examined; ns: not significant.

Comparison of mean cortical ¹¹C-Pib SUVR values between the EOAD and LOAD groups

Amyloid PET images of one LOAD case exhibited head motion, resulting in a quality that was acceptable for visual assessment but not for quantitative analysis. Therefore, we excluded this case from the quantitative evaluation of amyloid burden. The Mann–Whitney U test showed no significant difference in ¹¹C-PiB SUVR values between the EOAD and LOAD groups (U = 114, p = 0.119).

Comparison of the ¹⁸F-florzolotau SUVR values in the nbm ROIs among the EOAD, LOAD, and HC groups

Representative PET images of focal ¹⁸F-florzolotau accumulation in the nbM are shown in Figure 1B. Retentions of ¹⁸F-florzolotau were elevated in large brain areas, including the nbM and limbic and neocortical regions of EOAD cases, whereas nbM tracer accumulations relative to other areas were enhanced in LOAD cases. We used the Kruskal–Wallis test to compare the ¹⁸F-florzolotau SUVR values of the nbM ROIs among the EOAD, LOAD, and HC groups (Figure 2A). The results indicated a significant difference among the three groups (H = 32.70, p < 0.0001). Post-hoc multiple comparisons demonstrated that the EOAD group exhibited significantly higher SUVR values than the LOAD group (p = 0.004) and the HC group (p < 0.0001). The comparison between the LOAD and HC groups on the Kruskal–Wallis test showed that the LOAD group had significantly higher SUVR values than the HC group (p = 0.046).

Figure 2.

Comparison of the ¹⁸F-florzolotau SUVR values of the nbM and Braak-staging ROIs among the EOAD, LOAD, and HC groups.

The Kruskal–Wallis test revealed no significant difference in the ICV-corrected volumes [cm³] of the nbM ROIs among the EOAD, LOAD, and HC groups (H = 3.69, p = 0.1575).

Comparison of the ¹⁸F-florzolotau SUVR values in the Braak-staging ROIs among the EOAD, LOAD, and HC groups

Next, we compared the differences in the ¹⁸F-florzolotau SUVR values of the three Braak-staging ROIs among the EOAD, LOAD, and HC groups (Figure 2B-D). Significant differences in the SUVR values were observed among the three groups in all three Braak-staging ROIs (Braak stage I/II: H = 60.98, p < 0.0001; Braak stage III/IV: H = 64.36, p < 0.0001; and Braak stage V/VI: H = 64.94, p < 0.0001). Post-hoc multiple comparisons revealed that the SUVR values in the EOAD and LOAD groups were significantly higher than those in the HC group for all three Braak-staging ROIs (Braak stages I/II, III/IV, and V/VI; p < 0.0001). Although the difference between the EOAD and LOAD groups was not significant, a trend toward a higher SUVR value was observed in the EOAD group than in the LOAD group across these ROIs (Braak stages I/II: p = 0.244, III/IV: p = 0.120, and V/VI: p = 0.079). The AUC of the ROC curve of the nbM SUVR values yielded moderate accuracy in discriminating between HCs and patients with AD (AUC = 0.80, 95% confidence interval: 0.70–0.90), and the cut-off value was estimated to be 1.246 (Supplemental Figure 1).

Association of the ¹⁸F-florzolotau SUVR values in the nbM ROIs with those in the Braak-staging ROIs

We assessed the correlation of the ¹⁸F-florzolotau SUVR values of the nbM ROIs with those of the three Braak-staging ROIs using the Spearman's rank correlation coefficient separately for the EOAD and LOAD groups (Figure 3). In patients with EOAD, there was no significant correlation between the ¹⁸F-florzolotau SUVR values in the nbM ROIs and those in Braak stage I/II ROIs (r = 0.38, unadjusted p = 0.165) (Figure 3A), III/IV ROIs (r = 0.40, unadjusted p = 0.145) (Figure 3B), and Braak stage V/VI ROIs (r = 0.30, unadjusted p = 0.277) (Figure 3C). In contrast, a significantly positive correlation was found between the ¹⁸F-florzolotau SUVR values of the nbM ROIs and those of Braak stage I/II ROIs (r = 0.50, unadjusted p = 0.014) (Figure 3A) and Braak-staging III/IV ROIs (r = 0.43, unadjusted p = 0.043) in patients with LOAD (Figure 3B). However, when considering multiple testing effects, the latter association did not remain statistically significant. There was no significant correlation between the nbM ROIs and Braak-staging V/VI ROIs in patients with LOAD (r = 0.25, unadjusted p = 0.245) (Figure 3C).

Figure 3.

Association of the ¹⁸F-florzolotau SUVR values of the nbM with those of the Braak-staging ROIs.

Association of the ¹⁸F-florzolotau SUVR values of the nbM with clinical scores

We investigated the association between the ¹⁸F-florzolotau SUVR values of the nbM and clinical scores separately in the EOAD and LOAD groups (Figure 4). In patients with EOAD, the nbM ¹⁸F-florzolotau SUVR values did not correlate with the MMSE (r = 0.38, unadjusted p = 0.159) (Figure 4A). Conversely, we observed a significant negative correlation between the ¹⁸F-florzolotau SUVR values in the nbM and the MMSE scores in patients with LOAD (r = −0.55, unadjusted p = 0.006) (Figure 4B). Correlation analysis of ¹⁸F-florzolotau SUVR values in Braak-staging ROIs with MMSE scores showed that higher ¹⁸F-florzolotau SUVR values in Braak-staging V/VI ROIs in EOAD are associated with lower MMSE scores, although not statistically significant (r = −0.41, unadjusted p = 0.126, Supplemental Figure 4). These results suggest that in LOAD, tau pathology in the nbM is associated with the clinical severity of AD, while in EOAD, tau pathology primarily in the neocortex contributes to AD severity. The association of ¹⁸F-florzolotau SUVR values in the nbM showed a trend of positive correlation with the CDR SoB scores in LOAD (r = 0.40, unadjusted p = 0.061) but not in EOAD (r = −0.40, unadjusted p = 0.139), albeit with no statistical significance. The ¹⁸F-florzolotau SUVR values in the nbM were positively associated with the FAB scores in the EOAD group (r = 0.69, unadjusted p = 0.022) but not in the LOAD group (r = −0.13, p = 0.59). There was no correlation between the nbM ¹⁸F-florzolotau SUVR values and age in both the EOAD (r = 0.02, unadjusted p = 0.957) and LOAD (r = 0.27, unadjusted p = 0.213) groups.

Figure 4.

Association between the nbM ¹⁸F-florzolotau SUVR values and MMSE scores.

Histopathological examination of the nbM

Typical neuropathological findings of the tau pathology of the nbM in AD are shown in Figure 5. In advanced AD cases, severe neuronal loss was evident. GB-positive structures were more numerous than AT8-positive NFTs formed in viable neurons, suggesting that tau lesions are predominantly ghost tangles.³⁹ In early AD cases, moderate neuronal loss was evident. The number of GB-positive structures was slightly higher than that of AT8-positive NFTs, suggesting that tau lesions predominantly consist of non-ghost NFTs. In the control case, few GB/AT8-positive structures are observed, and neurons are preserved in number and morphology.

Figure 5.

Progression of nbM tau pathology in AD.

To evaluate the visibility of tau lesions in the nbM by ¹⁸F-florzolotau PET, we further performed fluorescent staining with florzolotau, immunostaining with AT8 and N1D antibodies, and the Gallyas-Braak method of the nbM in brain sections from six patients with AD (3 advanced AD and 3 early AD cases) and two HCs (Figure 6). GB staining showed that tau lesions in the nbM were most numerous in advanced AD cases, followed by early AD cases, and least in control cases. In advanced AD cases, most of these GB-positive structures were negative with AT8, suggesting that they were ghost tangles.³⁹ In early AD cases and controls, both GB-positive/AT8-positive and GB-positive/AT8-negative structures were present, suggesting that tau lesions consisted of ghost tangles and NFTs formed in viable neurons. Regardless of the Braak stages, both NFTs and ghost tangles were visualized by florzolotau staining. Senile plaques were observed only in three AD cases with tau pathology above Braak stage V, but rarely in early AD and control cases with tau pathology below Braak stage IV.

Figure 6.

Histopathological examination of the nbM in postmortem brains of patients with AD and control cases.

Discussion

Tau is the primary constituent of NFTs, a pathological hallmark of AD. Postmortem and neuroimaging studies of AD suggest distinct spatial distributions of tau pathology between EOAD and LOAD, which could be associated with differential clinical features characteristic of each subtype.^9,40–42 In particular, enhanced tau accumulations in the nbM have been reported to be distinctive pathological features of EOAD versus LOAD.⁹ However, to our knowledge, no study has examined nbM tau depositions using PET. In the present study, we employed ¹⁸F-florzolotau for PET visualization and quantification of tau depositions within the nbM and in Braak-staging regions of patients with EOAD, LOAD, and HCs. Additionally, we explored the association between regional tau accumulation and neuropsychological performance. We found that tau accumulation in the nbM was the most prominent in EOAD, followed by LOAD. Moreover, the association between tau deposits in the nbM and those in the neocortex differed between EOAD and LOAD. These results, combined with data from the more recently published postmortem brain study,⁹ demonstrate the subtype-related heterogeneity of tau pathology trajectories in the nbM, presumably affecting the characteristics and advancement of clinical manifestations. Furthermore, the detectability of nbM tau pathologies by ¹⁸F-florzolotau-PET was supported by a high density of florzolotau-positive lesions observed in postmortem AD brain sections. Notably, nbM pathologies overwhelmed by ghost tangles could also be captured by the current imaging technology.

The nbM, located in the basal forebrain, houses cholinergic neurons responsible for producing acetylcholine, a neurotransmitter with widespread projections to various brain structures, including the neocortex.^11,12,43 This cholinergic system is a pivotal therapeutic target for AD, with evidence indicating its high vulnerability to neurofibrillary changes.⁴⁴ A recent neuroimaging study indicated that functional alteration of nbM begins in the early stages of AD.¹⁹ A large-scale postmortem assessment characterized the differential involvement of NFTs in the nbM among neuropathologic AD subtypes.⁹ Significantly, this report demonstrated greater accumulation of NFT in the nbM in hippocampal-sparing tau topology subtypes, twice that observed in limbic-predominant tau topology subtypes. Thus, the nbM tau pathologies are conceived to be more prominent in a large subset of EOAD cases than in LOAD cases. Correspondingly, our findings revealed that ¹⁸F-florzolotau SUVR values in the nbM were highest in EOAD, followed by those in LOAD, and significantly higher than those of HCs in both AD groups. These results suggest that tau accumulation in the nbM is an important pathophysiological factor that distinguishes the pathophysiology of EOAD from that of LOAD. Although previous studies elucidated more extensive tau depositions in the neocortex of patients with EOAD than in patients with LOAD,^45,46 the current work provides the first PET demonstration that tau accumulation in the nbM is more pronounced in EOAD cases. Although the neuronal nuclei, including the basal forebrain and the locus coeruleus, have been mentioned as areas of early tau accumulation in AD,⁴⁷ the conspicuous tau accumulation in the nbM is not included by Braak NFT staging. Instead, the basal forebrain is included in Braak pretangle stage c, which notes pre-tangle involvement of non-thalamic brainstem nuclei. Our findings suggest that tau accumulation within the nbM develops commonly in AD, but with substantial variability depending on the clinical onset age.

As shown in Figure 3, the present study showed that the abundance of tau deposition in the nbM has a distinct relationship with those in late Braak-staging (III–VI) regions between EOAD and LOAD. In the LOAD group, the ¹⁸F-florzolotau SUVR values in the nbM were positively correlated with those in the brain regions associated with early (I/II) and moderate (III/IV) Braak stage regions. A similar linear relationship was observed between tau lesions in the nbM and Braak stage V/VI regions. This suggests that tau accumulation in the nbM in LOAD follows the pathological trajectory outlined by Braak staging. In contrast, the EOAD group did not exhibit significant correlations between the ¹⁸F-florzolotau SUVR values in the nbM and any Braak-staging ROIs.

To further clarify the relationship between tau accumulation in the nbM and tau accumulation in the neocortex, additional analyses were performed. As shown in Supplemental Figures 2 and 3, the present study demonstrated that the abundance of tau deposits in the nbM relative to late Braak-staging (III–VI) regions in the pathological progression differs between EOAD and LOAD. Furthermore, the ratio of tau accumulations between the nbM and Braak-staging regions III/IV and V/VI regions (SUVR_nbM) is higher in the EOAD group than in the LOAD group, indicating that tau pathology in the neocortex and limbic system progresses more rapidly in EOAD. These results are highly consistent with those in a recent postmortem study that demonstrated rapid involvement of the limbic and neocortex in EOAD cases,⁹ suggesting that disruption of cholinergic projection circuits may be responsible for accelerating the extensive accumulation of tau. The distribution pattern of tau accumulation predominant in the limbic and neocortex may be due to the more pronounced and rapid deposition of Aβ in EOAD,¹⁸ resulting in accelerated tau deposition in Braak-staging III/IV and V/VI regions. Thus, the marked progression of tau accumulation in EOAD may be associated with the development of non-amnestic symptoms, such as executive dysfunction, language impairment, and psychiatric disorders.

In AD/non-AD tau pathologies, specifically in LOAD, a significant negative correlation between the ¹⁸F-florzolotau SUVR values in the nbM and MMSE scores suggested that nbM tau accumulations are implicated in general cognitive decline. Conversely, no significant correlation between the nbM SUVR values and scores of neuropsychological test was observed in patients with EOAD. However, the ¹⁸F-florzolotau SUVR values in Braak-staging V/VI regions tended to negatively correlate with MMSE scores (Supplemental Figure 3), indicating that general cognitive decline in EOAD cases was more closely related to tau pathology in the neocortex than that of the nbM. Thus, the diversity in the mode of progression of tau pathology in EOAD and LOAD may underlie the distinct associations of regional tau accumulation with general cognitive decline.

Histopathological examination suggested that GB-positive and AT8-negative tau deposition in the nbM of patients with advanced AD was a ghost tangle. In such cases, even after degeneration progressed in the nbM, a large number of extracellular ghost tangles remained in the neuropil (Figure 5) and were clearly positive for florzolotau. In contrast, in early AD cases, AT8-positive NFTs formed in viable neurons, and extracellular ghost tangles were evident and similarly stained with florzolotau. These results suggest that ¹⁸F-florzolotau-PET captures non-ghost NFTs and ghost tangles, manifesting early and late pathological features, respectively, and is, therefore, capable of visualizing the nbM tau lesions across all stages of AD. The small number of neurofibrillary changes observed in control cases also suggests that tau deposition in the nbM is triggered early in the pathological aging process. The absence of structures stained by N1D staining in the nbM of the early AD and control cases suggests that tau accumulation in the nbM occurs independently of Aβ deposition. Accordingly, cholinergic neurons are likely to be vulnerable to aging- and AD-associated tau pathologies. Previous studies have reported more NFTs in the nbM in EOAD than LOAD.⁹ However, given the lack of autopsied EOAD samples in our postmortem specimen, we could not assess the effect of the clinical onset age on florzolotau-labeled tau deposits in the nbM. Future studies will also be required to assess the extent of residual cholinesterase activity in the nbM.

To our knowledge, there are no PET studies focused on the quantification of tau accumulation in the nbM of AD patients. This may be due to off-target binding of first-generation tau PET tracers to monoamine oxidase A (MAO-A) or B (MAO-B) in the basal ganglia, precluding assessments of tau pathologies in brain regions anatomically proximal to the nbM.^48–50 In contrast, ¹⁸F-florzolotau does not cross-react with MAO-A and MAO-B and is accordingly suitable for evaluating nbM tau loads. In the future, PET with even higher spatial resolution is expected to capture tau lesions in this small anatomical structure.

This study has some limitations. First, although this study included both EOAD and LOAD cases, the sample size may have been small. Additionally, assessing the hippocampus, the preferred site for tau accumulation in AD, was challenging due to the off-target binding of ¹⁸F-florzolotau to the choroid plexus. Moreover, as this study was not longitudinal, assessing time-course changes in nbM versus limbic/neocortical tau accumulations of the EOAD and LOAD groups was not possible within the same individuals. Additionally, tau accumulations in the AD brain are known to be influenced by various genetic factors; nevertheless, Apolipoprotein E ε4 (APOE ε4) genotyping was not performed in this study. Therefore, the association between the APOE ε4 allele and tau accumulation in the nbM remains unknown. Investigating the relationship between APOE ε4 possession in EOAD and tau accumulation in the nbM warrants further exploration.⁵¹ Neuropathological evaluation using postmortem brains has only been performed on postmortem brains of LOAD cases, and the lack of evaluation of EOAD postmortem brains is a problem that constrains the interpretation of this study. In general, the time period from onset to autopsy needs to be aligned in order to compare tau accumulation between EOAD and LOAD. In the future, tau accumulation in nbM should be evaluated in the postmortem brains of EOADs.

In conclusion, this study provides unprecedented insights into the diversity of tau pathologies in AD, highlighting the significance of incorporating the nbM in the neuroimaging assessments as a key affected site. Our in-vivo and postmortem data also support the capability of ¹⁸F-florzolotau for detecting NFTs and ghost tangles in the nbM. Further studies with a larger sample size in a longitudinal paradigm are needed to elucidate the differential evolution of tau pathology in the basal forebrain relative to limbic and neocortical regions between EOAD and LOAD.

Supplemental Material

sj-docx-1-alz-10.1177_13872877241297382 - Supplemental material for Distinct tau pathologies in the nucleus basalis of Meynert between early-onset and late-onset Alzheimer's disease patients revealed by positron emission tomography

Supplemental material, sj-docx-1-alz-10.1177_13872877241297382 for Distinct tau pathologies in the nucleus basalis of Meynert between early-onset and late-onset Alzheimer's disease patients revealed by positron emission tomography by Hisaomi Suzuki, Kenji Tagai, Maiko Ono, Hiroshi Shimizu, Hironobu Endo, Hideki Matsumoto, Manabu Kubota, Yuko Kataoka, Sho Moriguchi, Shin Kurose, Masanori Ichihashi, Hitoshi Shinotoh, Kiwamu Matsuoka, Naomi Kokubo, Harutsugu Tatebe, Sayo Matsuura, Yasuharu Yamamoto, Yuki Momota, Kazunori Kawamura, Ming-Rong Zhang, Yuhei Takado, Hitoshi Shimada, Takahiko Tokuda, Mitsumoto Onaya, Masaru Mimura, Akiyoshi Kakita, Naruhiko Sahara, Hiroyuki Uchida, Makoto Higuchi and Keisuke Takahata in Journal of Alzheimer's Disease

Footnotes

Acknowledgments

The authors thank the radiation technologists, clinical coordinators, and members of the Brain Disorder Translational Team for their support with the positron emission tomography scans and the staff of the Department of Radiopharmaceuticals Development for their radioligand synthesis and metabolite analysis. We thank APRINOIA Therapeutics for sharing the ¹⁸F-florzorotau.

ORCID iDs

Hisaomi Suzuki

Kenji Tagai

Maiko Ono

Hiroshi Shimizu

Hironobu Endo

Hideki Matsumoto

Yuko Kataoka

Sho Moriguchi

Shin Kurose

Kiwamu Matsuoka

Naomi Kokubo

Harutsugu Tatebe

Sayo Matsuura

Yasuharu Yamamoto

Kazunori Kawamura

Ming-Rong Zhang

Yuhei Takado

Hitoshi Shimada

Mitsumoto Onaya

Masaru Mimura

Akiyoshi Kakita

Naruhiko Sahara

Hiroyuki Uchida

Makoto Higuchi

Keisuke Takahata

Author contributions

Hisaomi Suzuki (Conceptualization; Formal analysis; Investigation; Methodology; Resources; Visualization; Writing – original draft); Kenji Tagai (Conceptualization; Formal analysis; Investigation; Methodology; Validation; Visualization; Writing—review & editing); Maiko Ono (Formal analysis; Funding acquisition; Investigation; Resources; Visualization); Hiroshi Shimizu (Conceptualization; Formal analysis; Investigation; Resources; Supervision; Visualization; Writing—original draft); Hironobu Endo (Data curation; Investigation; Methodology); Hideki Matsumoto (Investigation); Manabu Kubota (Investigation); Yuko Kataoka (Investigation); Sho Moriguchi (Investigation; Methodology; Supervision); Shin Kurose (Formal analysis; Investigation); Masanori Ichihashi (Investigation); Hitoshi Shinotoh (Investigation); Kiwamu Matsuoka (Investigation); Naomi Kokubo (Investigation); Harutsugu Tatebe (Investigation); Sayo Matsuura (Investigation); Yasuharu Yamamoto (Investigation); Yuki Momota (Investigation); Kazunori Kawamura (Methodology; Resources); Ming-Rong Zhang (Resources); Yuhei Takado (Conceptualization; Investigation); Hitoshi Shimada (Conceptualization; Supervision); Takahiko Tokuda (Investigation; Supervision); Mitsumoto Onaya (Resources); Masaru Mimura (Supervision; Writing—review & editing); Akiyoshi Kakita (Conceptualization; Funding acquisition; Investigation; Resources; Supervision); Naruhiko Sahara (Resources; Supervision); Hiroyuki Uchida (Supervision; Writing—review & editing); Makoto Higuchi (Conceptualization; Funding acquisition; Supervision; Writing—review & editing); Keisuke Takahata (Conceptualization; Funding acquisition; Investigation; Methodology; Project administration; Validation; Writing—review & editing).

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Japan Agency for Medical Research and Development (AMED) under the grants JP18dm0207018, JP19dm0207072, JP18dk0207026, JP19dk0207049, 21wm0425015h0001, 20356355, 24wm0425019h0004 and 24wm0625304h0001; MEXT KAKENHI grants JP16H05324, JP18K07543, JP21K15705, and JP20K07935; and JST CREST grants JPMJCR1652 and JPMJMS2024 to Makoto Higuchi. It was also supported by Research Program on Emerging and Re-emerging Infectious Diseases from the Japan Agency for Medical Research and Development under grant number JP22fk0108513, JSPS KAKENHI (24K02374, 20K07935, 21442923, and 22497128), and MHLW KAKENHI (20GC1018 and 22GC1004) awarded to Keisuke Takahata, JSPS KAKENHI (20253107) to Sho Moriguchi, intramural research grant (6–8) for Neurological and Psychiatric Disorders of NCNP, and the Collaborative Research Project of the Brain Research Institute, Niigata University to Kenji Tagai, Maiko Ono, Hiroshi Shimizu and Akiyoshi Kakita.

Declaration of conflicting interests

Hitoshi Shimada, Ming-Rong Zhang, and Makoto Higuchi hold patents on compounds related to the present report (JP 5422782/EP 12 884 742.3/CA2894994/HK1208672). All other authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

Data supporting the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Supplemental material

Supplemental material for this article is available online.

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Supplementary Material

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Distinct tau pathologies in the nucleus basalis of Meynert between early-onset and late-onset Alzheimer's disease patients revealed by positron emission tomography

Abstract

Background

Objective

Methods

Results

Conclusions

Keywords

Introduction

Methods

Participants

PET acquisition and imaging data processing

MRI acquisition

Data preprocessing and definition of regions of interest (ROIs)

Analysis and assessments of amyloid and tau PET images

Histopathological examination of the nbM using postmortem brains derived from patients with AD and control participants

Statistical analyses

Results

Demographic characteristics

Comparison of mean cortical 11C-Pib SUVR values between the EOAD and LOAD groups

Comparison of the 18F-florzolotau SUVR values in the nbm ROIs among the EOAD, LOAD, and HC groups

Comparison of the 18F-florzolotau SUVR values in the Braak-staging ROIs among the EOAD, LOAD, and HC groups

Association of the 18F-florzolotau SUVR values in the nbM ROIs with those in the Braak-staging ROIs

Association of the 18F-florzolotau SUVR values of the nbM with clinical scores

Histopathological examination of the nbM

Discussion

Supplemental Material

sj-docx-1-alz-10.1177_13872877241297382 - Supplemental material for Distinct tau pathologies in the nucleus basalis of Meynert between early-onset and late-onset Alzheimer's disease patients revealed by positron emission tomography

Footnotes

Acknowledgments

ORCID iDs

Author contributions

Funding

Declaration of conflicting interests

Data availability

Supplemental material

References

Supplementary Material

Comparison of mean cortical ¹¹C-Pib SUVR values between the EOAD and LOAD groups

Comparison of the ¹⁸F-florzolotau SUVR values in the nbm ROIs among the EOAD, LOAD, and HC groups

Comparison of the ¹⁸F-florzolotau SUVR values in the Braak-staging ROIs among the EOAD, LOAD, and HC groups

Association of the ¹⁸F-florzolotau SUVR values in the nbM ROIs with those in the Braak-staging ROIs

Association of the ¹⁸F-florzolotau SUVR values of the nbM with clinical scores