Correspondence between in vivo ¹¹C-PiB PET amyloid imaging and post-mortem, region-matched assessment of plaques

Abstract

The definitive Alzheimer’s disease diagnosis requires post-mortem confirmation of neuropathological hallmarks – amyloid-β (Aβ) plaques and neurofibrillary tangles (NFTs). The advent of radiotracers for amyloid imaging presents an opportunity to investigate amyloid deposition in vivo. The ¹¹C-Pittsburgh Compound-B (PiB) PET ligand remains the most widely studied to date; however, regional variations in ¹¹C-PiB binding and the extent of agreement with neuropathological assessment have not been thoroughly investigated. We examined the correspondence among quantitative immunohistological assessments of Aβ and NFTs, regional ¹¹C-PiB load, and brain atrophy (MRI) in six older Baltimore Longitudinal Study of Aging participants who came to autopsy (imaging-autopsy interval range 0.2–2.4 years). The total number of Aβ plaques (6E10) and NFTs (PHF1) in paraffin sections from hippocampus, orbito-frontal cortex, anterior and posterior cingulate gyrus, precuneus and cerebellum were quantified using a technique guided by unbiased stereological principles. We report a general agreement between the regional measures of amyloid obtained via stereological assessment and imaging, with significant relationships evident for the anterior (r=0.87; p=0.02) and posterior (r=0.93; p=0.007) cingulate gyri, and the precuneus (r=0.98; p=0.001). Moreover, higher Aβ count in the hippocampus was associated with lower hippocampal volume (r= −0.86; p=0.03). No associations were observed between ¹¹C-PiB load and NFT count for any of the regions examined (p>0.2 in all regions) or between regional NFT count and corresponding brain volumes. The strong associations of PiB retention with region-matched, quantitative analyses of Aβ in post-mortem tissue offer support for the validity of ¹¹C-PiB-PET imaging as a method for evaluation of plaque burden in vivo.

INTRODUCTION

Considerable resources have been focused on developing disease-modifying strategies aimed at delaying the pathophysiological processes in Alzheimer’s disease (AD). Understanding pathologic mechanisms and biological risks is imperative to the discovery of biomarkers, pharmacological targets, and treatments. The preeminent explanation of AD pathogenesis, the ‘amyloid cascade hypothesis’, suggests that amyloid-β plaque (Aβ) deposition underlies neurodegeneration, subsequent brain atrophy, cognitive impairment and ultimately dementia [13].

The definitive diagnosis of AD still requires confirmation either by biopsy or autopsy. Post-mortem confirmation is based on neuropathological hallmarks – Aβ and neurofibrillary tangles (NFTs). Radiotracers for amyloid imaging now provide the opportunity to investigate fibrillar Aβ deposition in vivo. Thus, PET amyloid imaging agents hold promise not only for early diagnosis of AD, but can also add to the understanding of the pathogenesis of AD, the temporal course of amyloid deposition, and its relation to clinical manifestations. The ¹¹C-Pittsburgh Compound-B (PiB) ligand remains the most widely studied PET amyloid imaging agent to date but the validations against post-mortem measures of neuropathology are a few [1, 3, 4, 14, 16–17, 35–36].

In vitro, ¹¹C-PiB binds specifically to extracellular and vascular fibrillar Aβ [14, 21]. At PET tracer concentrations, ¹¹C-PiB does not significantly bind to other protein aggregates such as NFTs [14, 17, 19,] or Lewy bodies [10, 17]. The first ¹¹C-PiB study in humans performed in mild AD patients [19] reported patterns of PiB retention consistent with the classic pattern of amyloid deposition described in post-mortem studies of AD brains [2] and demonstrated approximately a twofold increase in ¹¹C-PiB retention in AD cases compared to non-demented individuals [19]. Moreover, ¹¹C-PiB shows promise in discriminating individuals with mild cognitive impairment (MCI) who progress vs. those who remain stable [11, 20, 27, 37,] and provides some utility for differential diagnosis of AD from frontotemporal dementia [9, 26, 29].

Regional variations in PiB binding and the extent of agreement with neuropathological assessment however, have not been thoroughly investigated, and unbiased stereological investigations are lacking given that stereology remains a time-consuming process not easily compatible with routine neuropathologic work. In a previous study [35], we reported variable agreement between the mean PiB cortical distribution volume ratio and the neuritic plaque score according to Consortium to Establish a Registry for AD (CERAD), routinely used for pathologic diagnosis of Alzheimer disease. The limited agreement may reflect the inherent methodological limitations and differences between imaging and CERAD semi-quantitative neuropathologic protocols. Here we extend those findings by examining the regional correspondence between PiB retention, quantitative immunohistological regional assessments of Aβ and NFTs, and regional brain atrophy in six older Baltimore Longitudinal Study of Aging (BLSA) participants.

MATERIALS AND METHODS

Participants

The sample consists of six participants (5 males and 1 female) from the BLSA – Neuroimaging (NI) sub-study [30, 31, 35], who underwent ¹¹C PiB-PET and MRI assessments and eventually came to autopsy. The autopsy cases in this manuscript are the same ones as those studied in a previously published manuscript [35]. Participants were between 78 and 87 years of age at the time of ¹¹C PiB PET imaging and received concurrent MRI scans. Imaging-autopsy intervals ranged between 0.2 to 2.4 years. All studies were approved by the local institutional review boards, and all participants gave written informed consent prior to each assessment. In addition, next of kin or legally designated power of attorney provided consent for autopsy.

Demographic, genetic and cognitive status data are presented in Table 1. Participants received routine neuropsychological and neurological exams. Interval medical history, medication review, and a structured informant and subject interview were documented at each visit [7, 18]. All participants were in general good health at the time of BLSA neuroimaging study enrollment, with exclusionary criteria encompassing CNS disease, severe cardiovascular disease, severe pulmonary disease, or metastatic cancer. None of the participants had Parkinson disease, epilepsy, or clinical stroke at the time of PiB PET imaging.

Table 1.

Demographic, genetic and cognitive status information.

	A	B	C	D	E	F
Age	80	78	79	87	85	84
Sex	M	F	M	M	M	M
Education (years)	19	18	15	18	16	20
Family History	−	−	+	−	−	+
APOE	3/3	3/4	2/3	3/3	3/3	3/4
CDR	0	0	0	0.5	0	1
CDR-SOB	0	0	0	0.5	0	4.5
MMSE	30	30	29	25	30	30
Imaging-Autopsy Interval (years)	1.7	2.4	2.4	1.1	1.4	0.2
Cause of Death	Acute Myeloid Leukemia	COPD	Stroke	Pseudo-membranous Colitis	Pulmonary Embolus	Coronary Artery Disease

Cognitive data is cognition at the last visit prior to death. CDR – Clinical Dementia Rating Scale; CDR-SOB = CDR – sum of boxes; MMSE = Mini-mental Status Examination; COPD = chronic obstructive pulmonary disease.

Cognitive status was determined based on standardized consensus diagnostic procedures for the BLSA [7]. The CDR Scale [25], typically informant-based, was administered at each visit including the one concurrent with PiB imaging. All six participants were non-demented at the time of scan, three remained cognitively stable, two developed MCI, and only one subject became demented prior to death.

Neuropathologic Evaluations

Histology

The brains were examined in the Division of Neuropathology of the Johns Hopkins University. The left hemibrain was fixed in 10% buffered formaldehyde for at least two weeks, then sectioned in the coronal plane. Tissue blocks from medial frontal gyrus (MFG), inferior parietal (IP) region, superior middle temporal gyrus (SMTG), visual cortex, amygdala, and entorhinal cortex were processed, embedded in paraffin, cut at 10 μm and stained using the Hirano modification of Bielchowky’s silver stain. Neuritic plaque burden was assessed on a semi-quantitative age-adjusted scale (CERAD 0, A, B, or C) [24] based on the MFG, IP, and SMTG. Neurofibrillary tangle staging was assigned a score (0–VI) [2]. Presence of CAA was assessed in regions used for CERAD evaluation on hematoxylin and eosin (H & E) stains. Evaluation for Lewy body pathology was also performed [22].

Immunohistochemistry

For imaging-pathology correlations, tissue blocks from the hippocampus, orbito-frontal cortex, anterior cingulate gyrus, posterior cingulate gyrus, precuneus and the cerebellum were processed, embedded in paraffin, and cut serially at 10 μm (yielding 50 sections). Using a random start, we selected five sections per region using a systematic 10-section interval. Sections were mounted on slides, deparaffinized, dehydrated in alcohols and xylene, formic acid and heat pretreated for 5 minutes, washed and blocked with normal serum, incubated with the Aβ antibody (6E10, Covance Inc., Princeton, New Jersey; dilution 1:500), washed and blocked with the biotinylated secondary antibody, followed by the avidin-biotin-peroxidase complex (ABC-Elite kit, Vector Laboratories, Burlingame, CA), counterstained with hematoxylin, and coversliped using Permount. Adjacent sections were stained with phosphorylated Tau-protein (PHF-1 clone, a gift from Dr. P. Davies, Albert Einstein College of Medicine, Bronx, NY; dilution 1:100). The Aβ and Tau stained sections were used to assess the respective fractional areas for these proteins. Additional adjacent sections were stained with cresyl violet and used for regional anatomical delineation. Lewy Body pathology was excluded in the diagnostic neuropathology work-up.

Stereology

Stereological measurements were performed with a Zeiss light microscope equipped with a 100X, NA 1.30, oil Plan neofluor ∞/0.17 objective interfaced with the Stereo-Investigator optical dissector software from MBF Biosciences, MicroBrightField, Inc. (Williston, VT, USA). The images were captured with a microFire video camera (Optronics, Goleta, CA, USA). The actual thickness of each section was measured in the 8 to 9 micron range. Aβ and Tau-protein immunoreactivities were measured using the area-fraction-fractionator probe (counting frame: 150 μm×150 μm), which allowed us to assess the burden of proteins of interest in these sections. We outlined a contour of cortical gray matter and selected sampling sites with a grid size = 800 μm × 800 μm. At each sampling site, a counting frame was superimposed, containing markers equally spaced from one another. The markers that co-localized with immunoreactivity were labeled as positive, whereas remaining markers were labeled negative. The area fraction was calculated as the number of positive markers divided by the total number of markers. All assessments were performed blinded to clinical and neuropathological diagnoses. Values for each region were averaged to arrive at the mean fraction of Aβ or Tau-protein immunoreactivity. Coefficients of error ranged between 0.07–0.12 for both.

PET Imaging

PET acquisition

Dynamic ¹¹C-PiB-PET images were acquired on a GE Advance scanner in three-dimensional mode with 33 time frames (70 min) obtained at rest. PET scanning immediately followed an intravenous bolus injection of a mean (SD) 14.7 (0.9) mCi ¹¹C-PiB with a mean (SD) specific activity of 5.1 (2.8; range 1.9–10.2) Ci/μmol. Participants were fitted with a thermoplastic mask to minimize motion during scanning. Two-dimensional transmission scans were used for attenuation correction of the emission scans. Dynamic images were reconstructed using filtered backprojection with a ramp filter (image size 128 × 128; pixel size, 2mm × 2 mm; slice thickness, 4.25 mm) and a spatial resolution of about 4.50-mm full width at half maximum at the center of the field of view.

MRI-based ROI definition for ¹¹C-PiB-PET

MRI scans acquired concurrently or closest in time to the ¹¹C-PiB-PET scan were used for region of interest (ROI) definition. MRI scans for ROI definition used either the SPGR volumetric scans from the 1.5 T GE Signa or a comparable T1-weighted volumetric imaging protocol on a Philips 1.5 T scanner, which replaced the GE scanner in 2006. Volumetric scans were co-registered to the mean of the first 20-min dynamic PET images for each participant using the mutual information method in the Statistical Parametric Mapping software (SPM2; Wellcome Department of Cognitive Neurology). ROIs were drawn manually on the co-registered MR images [28]. Cerebellum served as a reference region. The parametric images of distribution volume ratio (DVR) and R1 (=K1/K1 (reference tissue), the target to reference tissue ratio of tracer transport rate constant from vascular space to tissue) were generated by using a simplified reference tissue model and linear regression with spatial constraint algorithm [38, 39]. The mean cortical DVR was calculated by averaging DVR values from orbito-frontal, prefrontal, superior frontal, parietal, lateral temporal, occipital, and anterior and posterior cingulate regions [36]. For voxel-wise analysis, parametric images of DVR were spatially normalized using SPM2 with an R1 template [39], which provides better brain boundary definition in the case of low PiB retention. The ROI DVRs were obtained by applying MR-based ROIs to the DVR images.

MR Imaging

MRI acquisition

Scanning was performed on a GE Signa 1.5 Tesla scanner (Milwaukee, WI) using a high-resolution volumetric spoiled-grass (SPGR) axial series (TR = 35 ms, TE=5 ms, FOV= 24 cm, flip angle = 45°, matrix = 256 × 256, NEX= 1, voxel dimensions 0.94 mm × 0.94 mm × 1.5 mm).

MRI image analysis

MRI scans acquired concurrently or closest in time to the ¹¹C-PiB-PET scan were used to obtain regional volumes. Image processing procedures have been previously described in detail and validated [6, 8, 12, 30, 31]. Briefly, images were corrected for head tilt and rotation, and reformatted parallel to the anterior–posterior commissure plane. Extracranial tissue was removed using a semi-automated procedure followed by manual editing. Next, images were segmented into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). The final step involves stereotaxic normalization and tissue quantitation for specific regions of interest with a template-based deformation approach. An ICBM (International Consortium for Brain Mapping) standard MRI anatomical template (Montreal Neurologic Institute) served as the template and a hierarchical elastic matching algorithm was used for deformation and determination of volumes of interest [34]. All images were normalized individually to the same template. Voxel-based analysis utilizes the RAVENS approach [12], whereby local values of tissue density maps (for GM, WM, and CSF) reflect the amount of respective tissue in the vicinity of a voxel. Tissue densities are mathematical quantities measuring local tissue volumes and do not reflect any microstructural physical density of brain tissue.

RESULTS

Participants and Cognitive Status

Although all participants were non-demented at the time of scanning, participant F received a diagnosis of probable AD at last imaging visit, which occurred 55 days prior to death. Participant F also received a neuropathologic diagnosis of probable AD at autopsy based on CERAD neuritic plaque score and Braak NFT staging. Mild memory impairment by CDR (0.5) was documented in participants D and F.

Regional Distribution of PiB

Mean cortical DVR values ranged between 0.96 and 1.59. Highest regional DVR values were observed in the precuneus, as well as the anterior and posterior cingulate regions. Regional DVR values were the lowest for the hippocampus and generally low for the OFC (see Table 2; Figure 1).

Table 2.

Overview of regional ¹¹C-PiB DVR values and Aβ and Tau quantifications obtained employing techniques guided by unbiased stereological principles (area fractions).

Participant		HPC	OFC	Anterior Cingulate	Posterior Cingulate	Precuneus	Cortical DVR	CERAD	Braak
A	Aβ (%)	0	0	0	0	0	0.96	0	4
	PiB	1	0.93	1	1.03	1.07
	Tau (%)	0.30	0	0	0	0.02
	Diffuse	0	0	0	0	0
	Core	0	0	0	0	0
B	Aβ (%)	1.50	8.44	0.38	0	0	1.01	B	3
	PiB	1.04	0.96	1.03	1.16	1.17
	Tau (%)	0.47	0	0	0	0.02
	Diffuse	0	F	R	R	R
	Core	0	R	R	R	M
C	Aβ (%)	1.12	6.36	7.80	1.42	1.98	1.06	B	4
	PiB	1.02	0.92	1.22	1.24	1.27
	Tau (%)	6.24	0.04	0.44	0.01	0.05
	Diffuse	0	M	M	M	R
	Core	0	M	M	M	M
D	Aβ (%)	0.12	2.89	0.78	0	0.03	1.09	B	3
	PiB	0.95	1.12	1.21	0.91	0.91
	Tau (%)	3.92	0.04	0.26	0	0
	Diffuse	0	F	R	M	R
	Core	0	M	M	M	M
E	Aβ (%)	0.14	0	4.59	5.83	8.58	1.42	A	4
	PiB	1.13	1.27	1.55	1.48	1.94
	Tau (%)	0.90	0	0.21	0	0
	Diffuse	0	0	F	F	F
	Core	0	0	R	R	R
F	Aβ (%)	3.20	12.86	12.72	3.24	5.40	1.57	B	3
	PiB	0.94	1.49	1.84	1.92	1.58
	Tau (%)	3.93	0.05	0.21	0.09	0.21
	Diffuse	M	F	F	F	F
	Core	M	R	M	R	M

Figure 1.

Comparison of regional distribution of A) amyloid load in vivo (¹¹C-PiB DVR; from Sojkova et al., 2011) and B) corresponding Aβ immunohistochemistry (6E10) on a case-by-case basis. A) Voxel-wise ¹¹C-PiB distribution DVR maps are overlaid on the cortical surface and parasagittal slices. B) Area fraction of Aβ by 6E10 immunohistochemistry is represented on the y-axis. Each of six participants are denoted on x-axis corresponding to the labels used for DVR maps in A). Different colors represent each of the six regions examined.

Regional Distribution of Aβ and Tau

Upon immunohistochemical evaluation, the cerebellum was free of both Aβ by 6E10 and Tau by PHF1. Aβ was detected throughout the remaining regions of interest in this sample, with the exception of case A, which was free of Aβ across all sampled regions (see Figure 1). Aβ load was lowest in the hippocampus; intermediate in the posterior cingulate gyrus and the precuneus, and highest in the OFC and the anterior cingulate gyrus. Tau immunostaining was detected primarily in the hippocampus, and little or no Tau was detected in the remaining regions of interest.

PiB-Pathology Correspondence

Regional ¹¹C-PiB DVR values and Aβ and Tau loads are presented in Table 2. In general, there was an agreement between the regional measures of Aβ obtained via stereological assessment and imaging, with significant relationships evident for the anterior (r=0.87; p=0.02) and posterior (r=0.93; p=0.007) cingulate gyri, and the precuneus (r=0.98; p=0.001). Regional correspondence of amyloid by immunohistochemistry (6E10) and amyloid load obtained in vivo (¹¹C-PiB) is presented in Figures 1 and 2 on a case-by-case basis. No significant associations were observed between regional ¹¹C-PiB load and Tau immunohistochemistry for any of the regions examined (p>0.2 for all regions).

Figure 2.

Correspondence between regional amyloid load by ¹¹C-PiB and immunohistochemistry (6E10) in A) the hippocampus, B) orbito-frontal cortex, C) anterior cingulate gyrus, D) posterior cingulate gyrus, and E) the precuneus. Regional PiB DVR is represented on the y-axis; regional area fraction of Aβ by 6E10 immunohistochemistry is represented on the x-axis. F) Aβ by immunohistochemistry (6E10) in the precuneus (original magnification × 10).

Brain Volume–Pathology Correspondence

Higher Aβ count by immunohistochemistry in the hippocampus was associated with lower hippocampal volume (r= −0.86; p=0.03). No significant regional associations were observed between Tau immunohistochemistry or PiB DVR, respectively, or with other respective regional brain volumes investigated, although it should be noted that the cingulate gyrus volume we obtained was for anterior and posterior regions combined.

DISCUSSION

Fractional areas of Aβ (6E10) and Tau (PHF1) immunoreactivities in 5 random, systematically-selected paraffin sections from each of the following regions: hippocampus, orbito-frontal cortex, anterior cingulate gyrus, posterior cingulate gyrus, precuneus and the cerebellum were quantified employing technique guided by unbiased stereological principles. We compared these measures of Aβ and Tau with Aβ burden measured ante-mortem using PET and ¹¹C-PiB. We report an agreement between regional in vivo ¹¹C-PiB retention and region-matched, quantitative analyses of Aβ in post-mortem tissue.

Only a handful of studies to date have investigated the direct relationship between ¹¹C-PiB binding and neuropathology, one in AD [14], one in Parkinson’s Disease (PD) dementia [3] and two case reports of dementia with Lewy bodies (LBD) [3,17]. Although sample sizes were small (AD: n=1; PDD: n=3; LBD: n=1), all studies demonstrated high selectivity of ¹¹C-PiB for fibrillar Aβ deposits. A recent study also showed good agreement between ante-mortem imaging and autopsy findings for the 18-F amyloid imaging radiotracer, Florbetapir [5].

We recently investigated the correspondence between ¹¹C-PiB DVRs and CERAD-based neuropathological diagnoses in the same six individuals included in the present study. In our earlier study [35], using the Hirano modification of the Bielschowsky silver stain, we found only limited and variable agreement between CERAD score and mean cortical ¹¹C-PiB DVR. This study had a couple of important methodological limitations at the time: 1.) CERAD is a semi-quatitative rating based on a small volume of tissue in specific cortical regions, 2.) cortical PiB DVR, a summary score of eight cortical regions was used, both of which may have contributed to the limited agreement between neuropathological and imaging assessments of amyloid. Our current results suggest that much better agreement is observed in the same individuals using immunohistochemistry and quantitative stereological methodology when evaluating the regions typically showing the greatest ¹¹C-PiB retention. In the present investigation we systematically sampled throughout the regions of interest to better capture the distribution of amyloid deposition. Moreover, we examined the correspondence between imaging and post-mortem measures in regions showing the earliest evidence of ¹¹C-PiB retention, including precuneus and cingulate regions. This is especially important, given that most of the individuals evaluated here were non-demented and in non-demented individuals early Aβ deposition is observed in the precuneus/posterior cingulate and the anterior cingulate gyrus [23], regions not included in the CERAD neuropathological assessment.

Although the ‘amyloid cascade hypothesis’, which suggests that Aβ deposition underlies neurodegeneration, subsequent brain atrophy, cognitive impairment and ultimately dementia, has been the dominant explanation of AD pathogenesis to date [13]. Yet, the tangles often precede amyloid deposition and the tangles that are left in the extracellular space after the death of neurons that contain them (“ghost tangles”) provide direct evidence for neuronal death either caused by or at least associated with tangles [2, 40], posing a challenge for the ‘amyloid cascade hypothesis’. We also investigated the potential association between Tau immunohistochemistry and ¹¹C-PiB and found no relationship. Additionally, we found no relationships between regional brain volumes obtained from MRI scans closest in time to amyloid imaging and PiB retention. Moreover, there were no significant associations of brain volume with Aβ or Tau levels by immunohistochemistry, except for the significant relationships between hippocampal volume and Aβ-6E10 immunohistochemistry. As Jack and colleagues [15] note, both Aβ deposition and NFTs can be present in individuals who do not exhibit any clinical symptoms. The presence of NFTs, however, although widespread in demented individuals tends to be confined to the entorhinal cortex (Braak stage I–II) in asymptomatic individuals [15] and all participants in our study were clinically normal at the time of the scan. The relationships between brain volume and Aβ or Tau respectively will need to be revisited as the autopsy sample with prior imaging assessments grows, as we likely lacked power in the present sample to detect small changes. Moreover, a note of caution is in order considering that shorter MRI-PiB interval in some cases and refinement of image processing techniques that would allow us to separate anterior from posterior cingulate gyrus volumes might lead to positive findings in the future.

There are several limitations to our study. The strength of the relationship between amyloid by PiB vs. immunohistochemistry may be affected by different forms of Aβ. For example, PiB does not bind to a polymorphic form of Aβ [32], which may account for some of the discrepancy – especially in cases of low PiB retention yet moderate scores upon neuropathologic evaluation, particularly in the hippocampus and the orbito-frontal cortex. A recent study by Ikonomovic and colleagues [41] examined Aβ pathology in an individual with clinical diagnoses of probable Lewy body dementia and possible AD but no detectable PiB PET retention, suggesting a need for better defining the Aβ concentrations and binding levels needed to produce a positive PiB PET signal. The inherent problem of varied imaging-autopsy intervals may also affect the correspondence between imaging-neuropathologic assessments. Moreover, the truly unbiased stereological investigation would involve defining, dissecting, and cutting the entire structure of interest from which then random sections would be chosen for immunohistochemistry, while ours were selected from a 0.5 mm of tissue from the region of interest for practical purposes. Not sampling throughout the entire structure may have biased the estimation of Aβ plaques in individuals with potentially sparse or sporadically distributed plaques. Limitations notwithstanding, this study represents the largest of its kind to date and the only series to date including non-demented adults with variable levels of PiB retention. Moreover, a decade of prospective cognitive follow-up and consensus diagnosis makes this sample a unique and valuable resource.

Overall, we report an agreement between ante-mortem ¹¹C-PiB amyloid imaging and post-mortem quantitative assessment of Aβ deposition in a sample of six older, prospectively followed individuals. The strong correlation of in vivo PiB retention with region-matched, quantitative analyses of Aβ in post-mortem tissue offer support for the validity of ¹¹C-PiB-PET imaging as a method for evaluation of plaque burden in vivo. Prospective studies will not only be imperative in furthering our understanding of amyloid deposition and its role in the disease process, but also in guiding preventative and therapeutic strategies.