doi:10.1093/brain/aww139

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The relationship between cerebrospinal fluid markers of Alzheimer pathology and positron emission tomography tau imaging Brian A. Gordon,1,2 Karl Friedrichsen,1 Matthew Brier,3 Tyler Blazey,4 Yi Su,1 Jon Christensen,1 Patricia Aldea,1 Jonathan McConathy,1 David M. Holtzman,2,3,4,5 Nigel J. Cairns,2,3,5 John C. Morris,2,3 Anne M. Fagan,2,3,5 Beau M. Ances2,3,5 and Tammie L. S. Benzinger1,2,6

The two primary molecular pathologies in Alzheimer’s disease are amyloid-b plaques and tau-immunoreactive neurofibrillary tangles. Investigations into these pathologies have been restricted to cerebrospinal fluid assays, and positron emission tomography tracers that can image amyloid-b plaques. Tau tracers have recently been introduced into the field, although the utility of the tracer and its relationship to other Alzheimer biomarkers are still unknown. Here we examined tau deposition in 41 cognitively normal and 11 cognitively impaired older adults using the radioactive tau ligand 18F-AV-1451 (previously known as T807) who also underwent a lumbar puncture to assess cerebrospinal fluid levels of total tau (t-tau), phosphorylated tau181 (p-tau181) and amyloidb42. Voxel-wise statistical analyses examined spatial patterns of tau deposition associated with cognitive impairment. We then related the amount of tau tracer uptake to levels of cerebrospinal fluid biomarkers. All analyses controlled for age and gender and, when appropriate, the time between imaging and lumbar puncture assessments. Symptomatic individuals (Clinical Dementia Rating 4 0) demonstrated markedly increased levels of tau tracer uptake. This elevation was most prominent in the temporal lobe and temporoparietal junction, but extended more broadly into parietal and frontal cortices. In the entire cohort, there were significant relationships among all cerebrospinal fluid biomarkers and tracer uptake, notably for tau-related cerebrospinal fluid markers. After controlling for levels of amyloid-b42, the correlations with tau uptake were r = 0.490 (P 5 0.001) for t-tau and r = 0.492 (P 5 0.001) for p-tau181. Within the cognitively normal cohort, levels of amyloid-b42, but not t-tau or p-tau181, were associated with elevated tracer binding that was confined primarily to the medial temporal lobe and adjacent neocortical regions. AV-1451 tau binding in the medial temporal, parietal, and frontal cortices is correlated with tau-related cerebrospinal fluid measures. In preclinical Alzheimer’s disease, there is focal tauopathy in the medial temporal lobes and adjacent cortices.

1 Department of Radiology, Washington University in St. Louis, 660 South Euclid Avenue, St. Louis, Missouri 63110, USA 2 Knight Alzheimer’s Disease Research Center, Washington University in St. Louis, 4488 Forest Park Avenue, St. Louis, Missouri 63110, USA 3 Department of Neurology, Washington University in St. Louis, 660 South Euclid Avenue, St. Louis, Missouri 63110, USA 4 Division of Biology and Biomedical Sciences, Washington University in St. Louis, 660 South Euclid Avenue, St. Louis, Missouri 63110, USA 5 The Hope Center for Neurological Disorders, Washington University in St. Louis, 660 South Euclid Avenue, St. Louis, Missouri 63110, USA 6 Department of Neurological Surgery, Washington University in St. Louis, 660 South Euclid Avenue, St. Louis, Missouri 63108, USA Correspondence to: Brian A. Gordon, Washington University School of Medicine, 660 South Euclid, Campus Box 8225,

Received December 22, 2015. Revised April 25, 2016. Accepted April 26, 2016. Advance Access publication June 10, 2016 ß The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: [email protected]

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St. Louis, MO 63110, USA E-mail: [email protected]

Keywords: Alzheimer’s disease; cerebrospinal fluid; preclinical; positron emission tomography; tau imaging Abbreviations: CDR = Clinical Dementia Rating; p/t-tau = total/phosphorylated tau; SUVR = standardized uptake value ratio

Introduction The neuropathological hallmarks of Alzheimer’s disease are extracellular amyloid-b plaques and the intraneuronal neurofibrillary tangles primarily composed of hyperphosphorylated tau protein (Braak and Braak, 1991; Braak et al., 2006). Models of Alzheimer’s disease pathology posit a temporal trajectory such that disruptions in the balance of amyloid-b production and clearance are the initiating events in a biological cascade that leads to amyloid-b plaque formation as well as the development of neurodegenerative tau pathology (Hardy and Higgins, 1992; Jack et al., 2013). In research and clinical settings, tracking the levels and spread of these two pathologies may provide insight into an individual’s relative disease state and likely future cognitive decline. Extracellular amyloid-b aggregates into neuritic plaques and cerebral amyloid angiopathy. Early in the disease course diffuse amyloid-b plaques are seen in the frontal and parietal lobes, including the precuneus. As Alzheimer’s disease progresses, both diffuse and neuritic plaques are seen in more widespread neocortical areas with a stereotypical spread that follows the following sequence: neocortex, hippocampus, basal ganglia, brainstem, and cerebellum (Braak and Braak, 1991; Price et al., 1991; Thal et al., 2002). Levels of soluble amyloid-b can be measured in vivo by CSF assays of amyloid-b, and aggregated amyloid-b can be measured with PET imaging. In vitro autoradiography of PET amyloid tracers reveal a high affinity to plaques that are immunoreactive to amyloid-b42 or amyloid-b40 (Ikonomovic et al., 2008). In vivo PET binding correlates well with a decline of in vivo levels of CSF amyloid-b42 (Fagan et al., 2006) and post-mortem levels of insoluble amyloid-b and amyloid-b plaque load (Ikonomovic et al., 2008), and the average spatial deposition and spread observed with PET is highly similar to that seen histologically (Benzinger et al., 2013). Thus there is strong evidence that both PET and CSF measures reflect the underlying amyloid-b histopathology. In Alzheimer’s disease, a major component of the neurofibrillary tangle is the microtubule-associated protein tau, which aggregates to form paired helical filaments that contain hyperphosphorylated tau (Kidd, 1963). The accumulation and spread of neurofibrillary tangles occur in a stereotypical pattern. Pathology initially appears in the transentorhinal region before spreading to the entorhinal cortex, hippocampus and throughout the rest of the medial temporal lobe. From the medial temporal lobe the

pathology then spreads further into the association neocortex and finally involves primary sensory cortices (Arnold et al., 1991; Braak and Braak, 1991; Price et al., 1991; Delacourte et al., 1999; Braak et al., 2006). Until recently, in vivo measurements of tauopathy have been restricted to CSF measures of total tau (t-tau) and phosphorylated tau (p-tau181). There is increasing evidence that tauopathy confined to the medial temporal lobe may be an age-related phenomenon (Delacourte et al., 2002; Crary et al., 2014). Although this medial temporal lobe tau is initially independent of Alzheimer’s disease processes, the pathology is amplified by the deposition of aggregated amyloid-b, leading to the spread of neurofibrillary tangles to the neocortex (Delacourte et al., 2002). This spread of tau pathology is crucial as post-mortem studies show that neocortical neurofibrillary tangle pathology correlates with neurodegeneration and cognitive deficits while amyloid-b plaque density does not (Arriagada et al., 1992; Giannakopoulos et al., 2003). The advent of PET tau tracers that preferentially bind to paired helical filaments (Chien et al., 2013; Xia et al., 2013; Villemagne and Okamura, 2014; Marquie et al., 2015) has provided a new method to track not only the levels of tauopathy, but also the crucial spatial propagation of tauopathy throughout the brain. While the initial introduction of tau PET tracers has been very promising (Villemagne and Okamura, 2014; Villemagne et al., 2015; Johnson et al., 2016), there are still many unanswered questions. Foremost among these is the relationship between PET measures of tau and CSF levels of t-tau, p-tau181, and amyloid-b42. In this study we compare tau PET binding in cognitively normal and impaired individuals. Further, we relate CSF markers of Alzheimer’s disease pathology to PET measures of tauopathy at a voxel-wise level. As shown in preliminary work in the field, we hypothesized that tracer uptake would be elevated in impaired individuals. Additionally, we hypothesize that CSF measures, particularly CSF t-tau and p-tau181, would relate to elevated PET tau deposition in the medial temporal lobe and the neocortex.

Material and methods Participants Participants were drawn from ongoing studies of ageing at Washington University in St. Louis. All participants who had undergone both tau PET imaging and had a prior lumbar puncture were eligible for inclusion in the study.

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Forty-one cognitively normal [Clinical Dementia Rating (CDR) = 0 (Morris, 1993)] and 11 cognitively impaired (symptomatic) individuals (seven CDR 0.5, three CDR = 1, one CDR = 2) underwent both tau PET imaging with AV-1451 [previously known as T807 (Chien et al., 2013)] and a lumbar puncture to obtain CSF. On average the lumbar puncture and PET scan were completed within 18.2 months [median 8 months, standard deviation (SD) 27.5 months]. At the most recent assessment 8 of 11 impaired individuals had received a clinical diagnosis of Alzheimer’s disease, while three were given a diagnosis of dementia with uncertain aetiology. All of the cognitively impaired individuals and 40 of the cognitively normal individuals had PET amyloid imaging. Using PET amyloid tracers, 10 of 11 impaired individuals were amyloid-positive and one was amyloid-negative while 15 of 40 cognitively normal individuals were amyloid-positive. When examining cognitive status we excluded the impaired individual who was amyloid-negative. Demographics are presented in Table 1. Differences between groups were tested using t-tests and chi-squared tests as appropriate. Although a CDR of 0.5 can be considered mild cognitive impairment rather than dementia in some situations, they often represent gradations of the same pathological process and underlying aetiology rather than distinct processes. All participants provided written informed consent, and all procedures were approved by the Human Research Protection Office at Washington University in St. Louis.

CSF assessment CSF samples (20–25 ml) were collected after overnight fasting. Samples were gently inverted to avoid possible gradient effects, briefly centrifuged at low speed, and aliquoted (0.5 ml) into polypropylene tubes before being frozen at 84 C. Samples were analysed for t-tau, p-tau181, and amyloid-b42 by ELISA (INNOTEST; Fujirebio formerly Innogenetics). CSF values are presented as pg/ml. Measurement of two pooled CSF samples common to

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each assay plate (n = 8–9) run over the 3 years of analysis yielded intra- and inter-plate per cent coefficients of variability (%CV) of 2.64% and 12.02%, respectively, for amyloid-b42; 3.33% and 8.21%, respectively, for tau; and 1.40% and 6.70%, respectively, for p-tau181, similar to published reports (Shaw et al., 2009).

MRI Data were acquired on a Siemens Biograph mMR or Trio 3 T scanner. T1-weighted images were acquired using a magnetization prepared rapid acquisition gradient echo (MPRAGE) sequence with: repetition time = 2300 ms, echo time = 2.95 ms, flip angle = 9 , 176 slices, in plane resolution 240  256, slice thickness = 1.2 mm acquired in sagittal orientation. Images underwent volumetric segmentation using FreeSurfer 5.3 (http://freesurfer.net) to identify a cerebellar region of interest used in the PET analyses.

Tau PET imaging Tau PET imaging was performed using 18F-AV-1451 (previously known as T807; Chien et al., 2013). The tracer was synthesized at the Washington University school of Medicine. Participants received a single intravenous bolus injection of between 7.2 and 10.8 mCi of AV-1451. Data were acquired on a Biograph 40 PET/CT scanner (Siemens Medical Solutions). Images were reconstructed on a 256  256  109 matrix (1.34  1.34  2.03 mm voxels) using OSEM algorithm. As done in prior work using this tracer (Chien et al., 2013; Johnson et al., 2016) data for the 80–100 min post-injection window were examined. Data were converted to standardized uptake value ratios (SUVRs) using the whole cerebellum as a reference. To evaluate the spatial pattern of AV-1451 binding, for each participant data were aligned to their individual MPRAGE using a rigid body transform and additionally using a linear registration transformed to a common atlas space and resampled into a 3 mm isotropic resolution.

Table 1 Cohort demographics

n Age (years) Males, n (%) MMSE CDR Boxes APOE "4, n (%) Amyloid PET + Lag (months) Amyloid-b42 pg/ml t-tau pg/ml p-tau181 pg/ml

Cognitively normal

Cognitively impaired

Significance

41 74.1 27 29.3 0.0 16 15/40 17.3 884.5 382.9 67.8

11 77.9 6 25.5 4.4 5 10/11 18.9 671.3 690.6 100.1

t = 1.78, P = 0.08 2 = 0.48, P = 0.50 t = 5.70 P 5 0.000001 t = 9.09, P 5 0.000001 2 = 0.70, P = 0.74 2 = 6.04, P = 0.01 t = 0.18 P = 0.87 t = 1.90 P = 0.063 t = 3.23 P = 0.002 t = 2.40, P = 0.02

(5.8) (66%) (1.2) (39) (38%) (28.1) (309.3) (259.5) (38.3)

Unless otherwise noted values represent means and standard deviation. Lag = lag between PET and CSF assessments. CDR Boxes = CDR Sum of Boxes. MMSE = Mini-Mental State Examination (0–30, 30 = perfect score).

(8.2) (55%) (3.5) (3.1) (45) (91%) (28.3) (401.9) (353.6) (45.0)

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Although the primary focus of the current analysis is on voxel-wise patterns of PET tau tracer uptake, as a supplementary analysis data were also processed using a region of interest approach as detailed previously (Su et al., 2013, 2015). Briefly, in each brain region, a tissue mask (grey, white, CSF) was generated based on the FreeSurfer segmentation (Fischl et al., 2004) (http://freesurfer.net/). SUVR data from the left and right inferior temporal lobe region were extracted and averaged together to form one summary measure. CSF levels of tau were related to the extracted SUVR values with and without partial volume correction (Rousset et al., 1998; Su et al., 2015).

Amyloid PET imaging Amyloid-b PET imaging was performed within 13 months (mean 5.3 months, 3.4 SD) of the tau PET imaging session using either 11C-Pittsburgh compound B (n = 14) or florbetapir (n = 37) (also known as 18F-AV-45). As noted above, data were processed using a region of interest approach using Freesurfer. Amyloid deposition was summarized using the average across the left and right lateral orbitofrontal, medial orbitofrontal, rostral middle frontal, superior frontal, superior temporal, middle temporal, and precuneus regions. For 11C-Pittsburgh compound B scans information from dynamic acquisitions was used to calculate mean cortical binding potentials. For florbetapir scans data between the 50–70-min post-injection window were converted to SUVRs using the cerebellar grey as the reference region. 11 C-Pittsburgh compound B, with a mean cortical binding potential of 0.18, has been used previously to denote amyloid positivity (Vlassenko et al., 2011; Gordon et al., 2015). An equivalent florbetapier SUVR cut-off of 1.267 was defined using a linear regression in a cohort of 100 individuals who had both florbetapir and 11C-Pittsburgh compound B imaging as part of a cross-over study. Using these two cutoffs the individuals were classified as either amyloid-positive or amyloid-negative. An analysis comparing PET tau deposition in cognitively normal amyloid-positive and negative individuals is presented in the Supplementary material.

Statistics Voxel-wise analyses of the PET data were performed using non-parametric permutation testing implemented using Randomize (Winkler et al., 2014), which is part of the FSL software suite (http://fsl.fmrib.ox.ac.uk). This approach uses a similar statistical model design and setup as general linear modelling, but does not make assumptions about the null distribution. Permutation methods provide exact control of false positive rates and provide a more robust approach to analysing PET, structural MRI, and functional MRI neuroimaging data (Holmes et al., 1996; Nichols and Holmes, 2002). Identification of significant clusters in the data was performed using threshold-free cluster enhancement (Smith and Nichols, 2009) also implemented within the FSL software suite. To reduce the number of

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comparisons, a grey matter tissue mask was applied to the data. Significance maps were corrected for multiple comparisons using a familywise error rate of P 5 0.05. All statistical models (e.g. comparing CDR 0 versus CDR 4 0) included age and gender as covariates. When examining the relationship with CSF biomarkers, models additionally included the lag between CSF and PET tau assessments as an additional covariate.

Results Regional binding of AV-1451 in cognitively impaired and normal subjects Mean AV-1451 uptake maps are show for the impaired (Fig. 1A) and cognitively normal (Fig. 1B) cohorts. Areas of tau deposition that were significantly elevated in the impaired cohort are presented in Fig. 1C and coordinates characterizing the significant clusters are presented in Table 2. There were no areas where tau PET binding was significantly greater in cognitively normal individuals. Analyses excluded the one cognitively impaired individual who was amyloid-negative on PET. Supplementary Fig. 1 shows a surface rendering of the difference of AV-1451 uptake in cognitively impaired and normal individuals. All significance maps in the paper are also presented as movies (Supplementary material).

Relationship among PET tau binding and CSF biomarkers Significant positive relationships were found between PET tau deposition and CSF t-tau and p-tau181 (Fig. 2A and B). There was a significant negative relationship between PET tau deposition and levels of CSF amyloid-b42 (Fig. 2C). This negative relationship is expected as lower CSF amyloid-b42 levels are thought to reflect greater amyloid-b deposition in the brain. As expected, cognitively impaired individuals primarily, but not exclusively, drove these effects (see scatter plots in Fig. 2). As an estimate of effect size, we examined partial correlations using CSF measures and PET tau deposition in those voxels that were significant in the respective voxel-wise maps. When controlling for age, gender and lag between assessments, the partial correlation with PET tau was r = 0.52 (P 5 0.001) for t-tau, rpartial = 0.50 (P 5 0.001) for p-tau181 and rpartial = 0.45 (P 5 0.005) for amyloid-b42. As amyloid-b42 was modestly negatively correlated with both CSF t-tau (r = 0.29, P 5 0.05) and p-tau181 (r = 0.19, P = 0.17), we performed voxel-wise analyses that simultaneously included CSF amyloid-b42 with each measure of CSF tauopathy along with all covariates. This provided a way to estimate the unique relationships of each biomarker with PET tau deposition. In these combined

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Figure 1 Mean AV-1451 deposition represented as SUVRs for (A) cognitively impaired and (B) cognitively normal participants and (C) where they statistically differ. Elevated AV-1451 uptake is prominent throughout the medial temporal, parietal and occipital lobes as well as medial frontal regions.

Table 2 Loci characterizing prominent effects of cognitive impairment on tau deposition Right hemisphere x 2 2 27 43 22 1 59 58 59 25 29

Left hemisphere y

z 25 39 7 7 11 70 37 15 45 1 18

x 16 34 58 30 17 34 39 32 9 16 27

y

z

Region

51 50

48 37

32 24

25 27

2 18

28 28

Subcallosal cortex Cingulate gyrus Superior frontal gyrus Precentral gyrus Frontal orbital cortex Precuneus Supramarginal gyrus Inferior temporal gyrus Middle temporal gyrus Amygdala Parahippocampal gyrus

Coordinates are in in Montreal Neurological Institute space. Region labels are derived from the Harvard-Oxford Atlases.

models, the relationship between PET t-tau and p-tau181 remained widespread while the spatial relationship with amyloid-b42 was substantially reduced when controlling for p-tau181 and became non-significant when controlling for t-tau (Fig. 3A–C). Again partial correlations in

significant voxels can be used as a measure of effect size. After controlling for all covariates and amyloid-b42 the correlations were rpartial = 0.49 (P 5 0.001) for t-tau and rpartial = 0.49 (P 5 0.001) for p-tau181. When additionally controlling for hippocampal volume the values become

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Figure 2 Significant relationships in the entire sample between AV-1451 deposition and CSF (A) t-tau, (B) p-tau181 and (C) amyloid-b42. Significant negative associations in the cognitively normal cohort with (D) amyloid-b42. Analyses control for age, gender and the lag between CSF and PET sessions.

rpartial = 0.44 (P 5 0.005) for t-tau and rpartial = 0.44 (P 5 0.005) for p-tau181. When examining amyloid-b42, the partial correlation was rpartial = 0.56 (P 5 0.001) when controlling for all covariates and p-tau as shown in Fig. 3C. When additionally controlling for hippocampal volume the relationship becomes rpartial = 0.58 (P 5 0.001). Due to the modest sample size, we subsequently confirmed that the statistically significant relationships between CSF and PET measures remained after excluding two individuals with very high PET tau SUVRs (2 and 1.68), demonstrating that these relationships were not driven by extreme outliers.

Using a region of interest approach PET tau deposition (SUVRs) was extracted using the inferior temporal region of interest derived from Freesurfer and averaged across right and left hemispheres (Fig. 4). The correlation with AV-1451 uptake was r = 0.49 (P 5 0.001) for t-tau, r = 0.46 (P 5 0.001) for p-tau181 and r = 0.37 (P 5 0.01) for amyloid-b42. When using partial volume corrected SUVR the correlations were r = 0.47 (P 5 0.001) for t-tau, r = 0.45 (P 5 0.001) for p-tau181 and r = 0.34 (P 5 0.01) for amyloid-b42. This indicates no substantial effect of partial volume correction. Using the partial volume corrected data, when controlling for age,

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Figure 3 The relationship between CSF biomarkers and AV-1451 deposition controlling for other biomarkers. In the entire cohort the relationship between (A) CSF t-tau and tau deposition controlling for amyloid-b42 (B) CSF p-tau181 and tau deposition controlling for amyloid-b42 (C) amyloid-b42 deposition controlling for p-tau181. In the cognitively normal cohort the relationship between (D) tau deposition and CSF amyloid-b42 controlling for p-tau181. Analyses control for age, gender, and lag between CSF and PET sessions.

gender, the lag between assessments, and amyloid-b42 levels there is only a modest drop in correlation strength for t-tau (rpartial = 0.435 P 5 0.005) and for p-tau181 (rpartial = 0.415 P 5 0.005). Similarly when controlling for these covariates and levels of p-tau181, the relationship with amyloid-b42 only modestly changes (rpartial = 0.31 P 5 0.05). When additionally controlling for cognitive status (impaired or not) the values change to rpartial = 0.351 (P 5 0.05) for ttau, rpartial = 0.371 (P 5 0.05) for p-tau181 and rpar0.27 (P = 0.12) for amyloid-b42. Further controlling tial = for hippocampal volume modestly changes the values to

rpartial = 0.39 (P 5 0.05) for t-tau, rpartial = 0.37 (P 5 0.05) for p-tau181 and rpartial = 0.28 (P = 0.06) for amyloid-b42.

Relationships with CSF within the cognitively normal cohort In the cognitively normal older adults there were no significant positive or negative voxel-wise relationships with either CSF t-tau or p-tau181. Significant negative relationships were observed with amyloid-b42 (Fig. 2D). The negative relationship with amyloid-b42 remained even when

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Figure 4 Relationship between CSF tau and AV-1451 deposition (SUVR) in the average of the right and left inferior temporal lobe. The strength of the correlation is similar with (r = 0.488) and without (r = 0.474) partial volume correction.

controlling for p-tau181 (Fig. 3D) or t-tau (not shown). As a measure of effect size the partial correlation with amyloidb42 in significant voxels controlling for age, gender, and the lag between sessions was rpartial = 0.65 (P 5 0.001) in the initial contrast, and rpartial = 0.65 (P 5 0.001) when additionally controlling for p-tau181 or rpartial = 0.64 (P 5 0.001) when controlling for t-tau. Additionally controlling for hippocampal did not alter the strengths of these relationships.

Age and gender effects within cognitively normal cohort In the cognitively normal cohort, main effects of age and gender were examined. There was a significant gender effect, with females demonstrating significantly higher levels of tau deposition. As the effects consistently localized to the edges of the brain (Supplementary Fig. 2), this effect most likely represents small differences in tissue registration around the edges of the brain rather than a true gender effect. At the voxel-wise level there were no significant relationships with age. From the mean maps in the cognitively normal cohort (Fig. 1B), there appears to be elevated tau deposition in the basal ganglia as well as the medial temporal lobes. As exploratory analyses we placed a 6 mm spherical region of interest in the left and right basal ganglia and left and right anterior medial temporal lobe. Controlling for gender and levels of amyloid-b42, there was a significant correlation between age and tau deposition in the left (rpartial = 0.45, P 5 0.005), and right (rpartial = 0.43, P 5 0.01) basal ganglia as well as the right (rpartial = 0.44, P 5 0.01) but not left (rpartial = 0.17, P = 0.30) medial temporal seed.

Discussion Disease-modifying therapies are more likely to be efficacious when initiated before significant neurodegeneration

has occurred. PET tau imaging allows not only the quantification but also the spatial localization of such taurelated neuropathology in vivo. The current work visualizes the Alzheimer’s disease spatial PET signature of tau deposition in the brain. Additionally, for the first time, the current work demonstrates a relationship between elevations in PET tau and CSF biomarkers of Alzheimer’s disease pathology in both cognitively impaired and cognitively normal individuals. When comparing cognitively normal and impaired individuals, increased PET tau uptake was prominently seen throughout the medial temporal lobe, but also more broadly in the neocortex, notably the temporoparietal junction, posterior cingulate, precuneus, medial frontal cortex and the dorsal prefrontal cortex. These results are consistent with preliminary studies using PET tau tracers to examine Alzheimer’s disease, (Chien et al., 2013; Okamura et al., 2014; Villemagne et al., 2014; Johnson et al., 2016) and pathological work looking at the distribution of neurofibrillary tangles (Braak and Braak, 1991; Delacourte et al., 1999; Braak et al., 2006). This reaffirms that it is not just tau aggregation in the entorhinal cortex and hippocampus that is associated with Alzheimer’s disease, but also the spread of this pathology from the medial temporal lobe into other parts of the neocortex. Effects were usually bilateral, although deposition in the right hemisphere was more prominent. Examining the relationships between measures of CSF biomarkers and PET tau further elucidated the pathological processes occurring in Alzheimer’s disease beyond simply examining cognitive status. Similar spatial patterns were revealed for CSF t-tau, p-tau181 and amyloid-b42. These areas overlapped with the cognitive status effects, except the significant areas were broader and more likely to occur in both the left and right hemispheres. Analyses of amyloid-b PET tracers have consistently shown independent relationships between with CSF measures of both amyloid-b and tau (Fagan et al., 2006, 2009). Similarly we found that CSF levels of both tauopathy and amyloid-b42 were associated with increased PET tau

CSF assays and PET

deposition. To examine selective effects of the CSF markers, amyloid-b42 was entered alongside t-tau and p-tau181 into the voxel-wise models. When this was done the relationship between both CSF tauopathy measures and PET tau remained essentially unchanged, while the relationship between amyloid-b42 and PET tau was markedly reduced. Amyloid-b42 now only predicted elevated tau deposition in the lateral temporal lobe, precuneus, and posterior cingulate. These regions are stereotypical members of the default mode network, and regions known to demonstrate early elevations in amyloid-b deposition (Braak and Braak, 1991; Buckner et al., 2008). As such, markers of amyloid-b may be particularly sensitive to the health of tissue in these regions, even after using CSF tau to account for global measures of neuronal injury. In the cognitively normal cohort there were no significant associations between CSF measures of tau pathology and PET tau deposition. However, there was a significant negative relationship between amyloid-b42 levels and increased PET tau, even after controlling for t-tau or p-tau181. These effects were localized to the medial temporal lobe, precuneus, posterior cingulate cortex, as well as the temporoparietal junction. This finding is important for two reasons. First, early elevations seen with PET tau are tied to CSF markers of amyloid, not CSF t-tau or p-tau181. Decreasing levels of CSF amyloid-b42 are thought to be one of the earliest biomarkers of amyloid-b deposition and Alzheimer’s disease pathological processes (Jack et al., 2013). As such, amyloid-b markers can serve as a better indicator of very early disease progression. These results are consistent with the early role that amyloid plays in Alzheimer’s disease pathophysiology and prior evidence from animal models that early elevation in tau can be driven by amyloidosis (Maia et al., 2013). Due to the focal nature of the observed tau PET binding in the cognitively normal cohort, global CSF measures of t-tau or ptau181 early in the disease may simply be too diffusive or variance in the CSF measures may be influenced by nonAlzheimer’s disease sources such as head trauma or vascular damage (Hesse et al., 2001; Ost et al., 2006). As neurodegenerative processes tied to Alzheimer’s disease become more prominent near or after the onset of cognitive impairment, CSF measures of tauopathy now dominate the relationship with PET measures. Second, in cognitively normal individuals with abnormal amyloid-b42 levels, PET tau deposition progresses beyond the medial temporal lobe to involve components elements of the limbic system, and has begun encroaching on other isocortical regions. This suggests that individuals can be entering Braak Stages III and higher and still be cognitively normal (Price and Morris, 1999). Tauopathy in the absence of any amyloidosis and confined to the medial temporal lobes is thought to be primary age-related tauopathy (Delacourte et al., 2002; Crary et al., 2014). Our voxel-wise analyses did not demonstrate any significant age-related increases in tau deposition. Exploratory seed-based analyses did suggest age-related

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increases in tau in both the anterior medial temporal lobe as well as the basal ganglia. Still, further work is needed to understand what role age is playing in leading to elevations in this tau deposition and the potentially confounding nature of preclinical Alzheimer’s disease pathology that may mask primary age-related tauopathy. While the increases in medial temporal lobe deposition are consistent with primary age-related tauopathy, the interpretation of the age-related basal ganglia increase is unclear and warrants further investigation as tau PET becomes more widespread in the field. The distinction between increased tau pathology in healthy ageing and prodromal Alzheimer’s disease is an important one. This is a critical question that must be answered in future studies with larger populations as tau PET imaging becomes more prevalent. There are limitations to the current work. Although the cohort is larger than almost all prior work examining PET tau deposition in vivo, the modest sample size limits the ability to detect significant effects. Further work is needed with increasingly larger sample sizes and a broad sampling of the severity of tau pathology to replicate the results presented here. Due to its relatively recent introduction to the field, PET tau imaging sessions were more likely to occur after the collection of CSF data. This lag between sessions was controlled for in all analyses, although its inclusion did not significantly alter any of the results presented here. The approach taken here was to examine AV-1451 uptake at a voxel-wise level. While a region of interest approach over a larger volume (e.g. examine entire precuneus) can have advantages over a voxel-wise analysis, a voxel-wise approach provides more fine grained spatial information and is first needed to characterize the spatial pattern of PET tau binding in Alzheimer’s disease. Partial volume correction is routinely used for region of interest analyses of PET data, but its role in voxel-wise analyses is only now being explored (Wang and Fei, 2012; Coello et al., 2013; Funck et al., 2014). While this is an important methodological question, analyses using a region of interest approach on our data did not reveal a significant impact of partial volume correction (Fig. 4). As the progression from a preclinical to demented state represents a continual pathological process rather than discrete stages (Jack et al., 2010, 2013), the current analyses combine both cognitively normal and impaired individuals when examining CSF biomarkers in a continuous manner. Analyses additionally controlling for cognitive impairment status still indicate a significant relationship between levels of CSF tau and p-tau181 and PET tau deposition (Supplementary Fig. 3). However, in the current sample the cognitively impaired cohort is relatively mildly affected. The relationship between CSF and PET tau may change as the course of the disease progresses and impairment becomes more pronounced. Similarly CSF and PET tau represent two markers of neurodegeneration in Alzheimer’s disease. Future analyses could leverage multiple biomarkers of neurodegeneration such as metabolism, structure atrophy, neurogranin, and visinin-like protein-1 to gain a

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Figure 5 Time-activity curve for seven regions of interest in a participant with a full dynamic scan. The shapes of the curves across time are highly similar across all of the regions.

more complete understanding of evolving degeneration as the disease progresses. Finally both cognitively normal and impaired individuals exhibit high levels of tau deposition in the basal ganglia. This deposition was not increased in the impaired individuals, although our exploratory analyses did reveal an increase with age. Autoradiography has indicated that AV1451 does have off-target binding to cells containing melanin and to a small degree haemorrhagic lesions (Marquie et al., 2015). Still, the level of signal that is observed in the basal ganglia is unlikely to be driven solely by this phenomenon. The effect in the basal ganglia also does not appear to be driven by perfusion or tracer wash out, as its time-activity curve is highly similar to other regions of the brain (Fig. 5). Visual inspection of tracer binding overlaid on individuals’ MRI also suggests tracer binding to the choroid plexus. Such binding may obscure disease processes in adjacent tissue. Further work is needed to understand what is driving this off-target binding. When examining only those voxels with the strongest relationship to CSF tauopathy, the correlations between CSF and PET tau were 0.5, and a similar value was obtained when using an region of interest focused on the inferior temporal lobe (Fig. 4). While the strength of this association is on a par with studies relating PET and CSF measures of amyloid-b, this is still far from a perfect linear relationship. There is a strong possibility that that CSF and PET measures of tau are sensitive to overlapping but not exclusive forms of tauopathy. From autoradiographic studies it has been shown that AV-1451 strongly binds to tau lesions primarily made of paired helical filaments such as intra- and extra-neuronal tangles and dystrophic neurites, but has low affinity for neuronal and glial inclusions composed of straight tau filaments (Marquie et al., 2015). As

with previous PET tracers used to study Alzheimer’s disease, further work must be carried out to understand the tracer dynamics of PET tau tracers. The work presented here demonstrates the ability of tau PET to discriminate between cognitively normal and impaired individuals, its relationship to CSF measures of Alzheimer’s disease pathology, its relationship to preclinical levels of amyloid-b42 and preliminary evidence of primary age-related effects. This indicates the utility of integrating PET tau into studies of both preclinical and clinical Alzheimer’s disease in vivo.

Acknowledgements We acknowledge the support of Fred Simmons and Olga Mohan, the Barnes-Jewish Hospital Foundation, the Charles F. and Joanne Knight Alzheimer’s Research Initiative, the Hope Center for Neurological Disorders, the Mallinckrodt Institute of Radiology and the Paula and Rodger Riney fund. Avid Radiopharmeceuticals supplied materials and technology for the synthesis of AV1451. We thank our participants, without whom this study would not have been possible.

Funding Funding came from NIH grants P50AG00568132, P01AG00399132, P01AG02627610 and P30NS048056 along with UL1TR000448 from the National Center for Advancing Translational Sciences. BAG was supported by the American Society for Neuroradiology.

CSF assays and PET

Supplementary material Supplementary material is available at Brain online.

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