Medicine (Austin & Northern Health) - Research Publications

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    Plasma glial fibrillary acidic protein is associated with reactive astrogliosis assessed via 18F-SMBT-1 PET
    Chatterjee, P ; Dore, V ; Pedrini, S ; Krishnadas, N ; Thota, RN ; Bourgeat, P ; Rainey‐Smith, S ; Burnham, SC ; Fowler, C ; Taddei, K ; Mulligan, RS ; Ames, D ; Masters, CL ; Fripp, J ; Rowe, C ; Martins, RN ; Villemagne, VL (Wiley, 2022-12)
    Background Reactive astrogliosis is an early event along the Alzheimer’s disease (AD) continuum. We have shown that plasma glial fibrillary acidic protein (GFAP), reflecting reactive astrogliosis, is elevated in cognitively unimpaired individuals with preclinical AD (Chatterjee et al., 2021). We reported similar findings using 18F‐SMBT‐1, a PET tracer for monoamine oxidase B (MAO‐B) (Villemagne et al., 2022). To provide further evidence of their relationship with reactive astrogliosis we investigated the association between GFAP and 18F‐SMBT‐1 in the same participants. Method Plasma GFAP, Aβ42 and Aβ40 levels were measured using the Single Molecule Array platform in 71 participants comprising 54 healthy controls (12 Aβ+ and 42 Aβ‐), 11 MCI(3 Aβ+ and 8 Aβ‐) and 6 probable AD(5 Aβ+ and 1 Aβ‐) patients from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing cohort. These participants also underwent 18F‐SMBT‐1 and Aβ PET imaging. Aβ imaging results were expressed in Centiloids (CL; ≥20 CL classified as Aβ+). 18F‐SMBT‐1 Standard Uptake Value Ratio (SUVR) were generated using the subcortical white matter as reference region. Linear regression analyses were carried out using plasma GFAP levels as the dependent variable and regional 18F‐SMBT‐1 SUVR as the independent variable, before and after adjusting for age, sex, soluble Aβ (plasma Aβ1‐42/Aβ1‐40 ratio) and insoluble Aβ (Aβ PET). Result Plasma GFAP was significantly associated with 18F‐SMBT‐1 SUVR in brain regions of early Aβ deposition, such as the supramarginal gyrus (SG, β=.361, p=.002), posterior cingulate (PC, β=.308, p=.009), lateral temporal (LT, β=.299, p=.011), lateral occipital (LO, β=.313, p=.008) before adjusting for any covariates. After adjusting for covariates age, sex and soluble Aβ, GFAP was significantly associated with 18F‐SMBT‐1 PET signal in the SG (β=.333, p<.001), PC (β=.278, p=.005), LT (β=.256, p=.009), LO (β=.296, p=.004) and superior parietal (SP, β=.243, p=.016). On adjusting for age, sex and insoluble Aβ, GFAP was significantly associated with SMBT‐1 PET in the SG (β=.211, p=.037) however only a trend towards significance was observed in the PC (β=.186, p=.052) and LT (β=.171, p=.067) (Figure 1). Conclusion There is an association between plasma GFAP and regional SMBT‐1 PET that is primarily driven by brain Aβ load.
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    Alzheimer’s disease specific MRI brain regions are differentially associated with accelerated decline as defined using sigmoidal cognitive turning point methodology in amyloid‐positive AIBL participants
    Gillis, C ; Cespedes, MI ; Maserejian, NN ; Dore, V ; Maruff, P ; Fowler, C ; Rainey‐Smith, S ; Villemagne, VL ; Rowe, C ; Martins, RN ; Vacher, M ; Masters, CL ; Doecke, JD (Wiley, 2022-12)
    Background Variability in cognitive decline among adults with Alzheimer’s disease (AD) is seen across studies. While such variability is often modelled using linear models, in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, application of a sigmoidal methodology has shown excellent precision in modelling cognitive and biomarker changes. Here we expand these findings by examining associations of brain volumes in AD specific Regions of Interest (ROIs) with accelerated cognitive decline among amyloid‐beta positive (Ab+) AIBL participants. Method Longitudinal cognitive scores for the AIBL PACC, Language, Visuospatial functioning and CDR‐SB were mapped to sigmoidal trajectories, with a threshold defining the inflection point of accelerated cognitive decline. Participants to the left of the threshold were classified as having non‐accelerated decline (non‐accelerators), and participants beyond the threshold were classed as accelerators (Figure 1B). Using these classifications, we investigated differences in 16 ICV corrected ROI (left and right hemispheres pooled) for reductions in brain volume via generalised linear models adjusted for age, gender, and APOE‐e4 status. Three participant subgroups were tested: 1) Ab+/Tau unknown, 2) Ab+/Tau‐ and 3) Ab+/Tau+. Significant t‐values for the summed ROI volumes were mapped on a standard brain mesh for visualisation. Result Of regions tested, two stood out consistently amongst top markers in each of the participant subgroups and cognitive outcomes: 1) supramarginal volume and 2) middle temporal volume (Figure 1C). Largest volume differences between accelerators and non‐accelerators were seen in the Ab+/Tau+ group; whilst smallest p‐values were in the Ab+/Tau unknown group due to a larger sample size (Table 1). Brain mesh visualization showed most of the AD signature ROIs altered in accelerator groups as compared with non‐accelerator groups. Figure 1D shows the AD signature for each cognitive outcome amongst the Ab+/Tau participant group. Top ranked ROI for the left being middle temporal volume (T=7.10, PACC) and supramarginal volume (T=7.10, CDR‐SB). Conclusion Sigmoid analyses of MRI using binary cognitive scores show decreased ROI volumes in AIBL Ab+ participants with accelerated cognitive decline. This effect was mediated by known information on Tauopathy. Whilst effect sizes were high, smaller sample sizes in some groups affected p‐values and should therefore be replicated in larger samples.
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    Comparing the longitudinal progression of CSF biomarkers with PET Amyloid biomarkers for Alzheimer’s disease
    Cox, T ; Bourgeat, P ; Dore, V ; Doecke, JD ; Fripp, J ; Chatterjee, P ; Schindler, EE ; Benzinger, TLS ; Rowe, C ; Villemagne, VL ; Weiner, MW ; Morris, JC ; Masters, CL (Wiley, 2022-12)
    Background Cerebrospinal fluid (CSF) soluble biomarkers are useful at detecting pre‐clinical levels of Alzheimer’s disease (AD) biomarkers of b‐amyloid (Ab) and tau. Disease progression times for participants in longitudinal studies can be estimated for different biomarkers. Utilizing a new technique, this work compared the disease progression times between CSF and PET biomarkers. Methods Four hundred and ten participants from the Alzheimer’s Dementia Onset and Progression in International Cohorts (ADOPIC) including participants form ACS/OASIS, ADNI and AIBL with three or more data points of longitudinal CSF Ab42 and pTau181 (pTau) and Ab PET were selected. PET results were expressed in Centiloid (CL), (299 cognitively unimpaired, 107 mild cognitively impaired, 4 AD dementia; aged 69±9; 216 females (NAIBL=30, NADNI=252, NOASIS=128). Disease trajectory curves for individual biomarkers and the pTau/Ab42 ratio were created by: 1) Fitting a function to the rates of change of the variable of interest versus its mean value), 2) integrating the fit to obtain longitudinal trajectory curves as a function of disease progression time for each of the variables. The participants’ disease progression time along each curve were estimated. Threshold values for Ab PET and pTau/Ab42 ratios were calculated using a gaussian mixture model. Estimates of age of onset were calculated using the progression times. The participants’ disease progression times for each of the different variables were compared using rank correlations. Results Rank correlations for the progression times were: r(Ab42, Ab PET) = 0.75, r(pTau, Ab PET)=0.62, and r(pTau/Ab42, Ab PET)=0.83. The estimated ages at which participants’ reach Ab PET and the pTau/Ab42 ratio thresholds are compared in Fig 1, the average age at which were estimated to reach the threshold values were 55 yr for pTau/Ab42 (threshold of 0.021) and 61 yr for Ab PET (threshold of 22 CL). Conclusions The high correlation between pTau/Ab42 and Ab PET, indicates that pTau/Ab42 captures the progression of AD pathology better than the individual CSF biomarkers. On average participants’ reach abnormal levels of pTau/Ab42 earlier than Ab PET. Further work is required to understand individual variations in progression times.
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    Altered levels of plasma kallikrein‐7 in prodromal Alzheimer’s disease
    Roberts, BR ; Roberts, AM ; Cortes, L ; Fowler, C ; Villemagne, VL ; Masters, CL ; Ryan, TM (Wiley, 2022-12)
    Background The accumulation of Aβ is thought to be dependent on imbalances in production or clearance of the peptide. At the core of the production and the breakdown of Aβ are changes in the activity of proteases. Several studies have suggested that the level and activity of brain proteases involved in the clearance pathway are perturbed in the disease. Given that AD is essentially a protease disease, we sought to determine if key proteases were altered in the blood plasma fraction, reflecting changes that are occur in the brain. Method We used a fast commercial tool to investigate the level of 34 proteases in plasma between healthy controls and AD patients. Next we used an ELISA and western blot assays to validate results from the discovery assay. Result We discovered that the protease kallikrein‐7 (KLK7) was significantly elevated in AD plasma. We then asked how early in the disease time course is KLK7 elevated. We used plasma from cognitively normal cases (n=120) with either high or low levels of brain amyloid based on PET imaging and found that KLK7 leaves are decreased. Conclusion These results suggest that the plasma level of Kallikrein‐7 may be an important tool in detecting elevated levels of brain amyloid before symptoms of AD become apparent.
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    18F-MK6240 longitudinal tau PET in ageing and Alzheimer’s disease
    Krishnadas, N ; Dore, V ; Mulligan, RS ; Tyrrell, R ; Bozinovski, S ; Huang, K ; Lamb, F ; Burnham, SC ; Villemagne, VL ; Rowe, CC (Wiley, 2021-12)
    Background Longitudinal tau PET may prove useful for clinical trials, through its ability to detect patterns and rates of in vivo tau accumulation in ageing and Alzheimer’s disease (AD). Clinical trials are increasingly targeting the preclinical phase of AD. Flortaucipir studies estimate a 3% annual increase in global cortical tau SUVR in amyloid‐β positive (Aβ+ve) cognitively impaired (CI) cohorts, whereas either no change, or low rates of increase (0.5%), have been demonstrated in Aβ+ve cognitively unimpaired (CU) cohorts. F‐18 MK6240 is a novel tau tracer, with high target to background binding. We aimed to evaluate regional rates of 18F‐MK6240 accumulation in ageing and the AD continuum. Method We performed PET acquisition 90‐100 minutes post‐injection of 185MBq (±10%) 18F‐MK6240 at baseline and 12 months for 67 Aβ‐ve CU, 20 Aβ+ve CU and 19 Aβ+ve CI participants. SUVR (standardized uptake value ratio) for the entorhinal cortex, amygdala, hippocampus, parahippocampus and composite regions of interest (ROI) (Me, mesial temporal; Te, temporoparietal cortices) were generated using the cerebellar cortex as the reference region. Result Age did not significantly differ between the groups (mean age 74 ± 4.4 Aβ‐ve CU, 76.2 ± 5.7 Aβ+ve CU, 72.5 ± 6.4 Aβ+ve CI). Aβ+ve participants (CU and CI) had higher baseline tau SUVR and higher annual percentage increases in tau SUVR compared to Aβ‐ve participants in all regions examined (Table 1) (Figure 1). CU Aβ+ve participants had larger increases in Me vs Te (1.6% vs 0.7%), while CI Aβ+ve participants had larger increases in Te vs Me (4.3% vs 1.9%). Compared to Aβ‐ve CU participants, Aβ+ve CU participants had higher increases in the amygdala (2.9% vs 1.8%) and entorhinal cortex (1.9% vs 0.7%). Conclusion Longitudinal tau imaging using 18F‐MK6240 discriminates between ageing and stages of AD. Rate of accumulation in preclinical AD (Aβ+ve CU) was highest in mesial temporal regions, while in CI individuals, rates were highest in the temporoparietal cortex. The amygdala and entorhinal cortex may be early regions to discriminate tau accumulation between Aβ‐ve CU and Aβ+ve groups. However, as the variance is large, the precision of these estimates may be refined with a larger sample size. Recruitment is ongoing.
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    Examining the structural correlates of amyloid‐beta in people with DLB
    Gajamange, S ; Yassi, N ; Chin, KS ; Desmond, PM ; Villemagne, VL ; Rowe, CC ; Watson, R (Wiley, 2021-12)
    Background Dementia with Lewy bodies (DLB) is a neurodegenerative disorder characterized pathologically by the deposition of alpha synuclein. Many patients with DLB also have brain compatible with Alzheimer’s disease (namely Amyloid‐β and tau), which can lead to challenges with clinical diagnosis and management. In this study we aim to understand the influence of Aβ on brain atrophy in DLB patients. Method 19 participants with probable DLB underwent 3T MRI T1‐weighted (voxel size=0.8x0.8x0.8mm3, TR=2400ms, TE=2.31ms) and β‐amyloid (Aβ) PET (radiotracer 18F‐NAV4694) imaging. Participants were grouped into Aβ negative (n=10; age=71.6±5.8 years) and Aβ positive (n=9; age=75.1±4.3 years) with a threshold of 50 centiloid units to identify neuropathological change (Amadoru et al. 2020). Brain volume measures (regional subcortical grey matter and global white and grey matter) were segmented from T1‐weighted images with FreeSurfer (Fischl et al. 2002, Fischl 2012). Given previous literature suggesting prominence of thalamic structural changes in DLB, we also specifically analysed changes in the thalamus by segmenting the thalamus into 25 nuclei, which were then grouped into six regions (anterior, lateral, ventral, intralaminar, medial and posterior) (Watson et al. 2017, Iglesias et al. 2018). All brain volumes were expressed as fractions of intracranial volume to account for differences in head size. Group comparison analyses were not controlled for age and sex as both these covariates did not statistically differ between groups. Result Brain volume differed significantly between Aβ‐ and Aβ+ DLB patients in the left thalamus (Aβ‐:4.39±0.37x103, Aβ+:4.07±0.19x103, p=0.03) and right thalamus (Aβ‐:4.17±0.34x103, Aβ+:3.84±0.22 x103, p=0.03). Specifically, the ventral (LEFT; Aβ‐:1.78±0.15, Aβ+:1.63±0.14, p=0.03. RIGHT; Aβ‐:1.83±0.15, Aβ+:1.65±0.12, p=0.01) and posterior (LEFT; Aβ‐:1.30±0.12, Aβ+:1.17±0.10, p=0.04. RIGHT; Aβ‐:1.42±0.14, Aβ+:1.21±0.12, p=0.003) regions were significantly reduced in Aβ+ compared to Aβ‐ DLB patients. Conclusion We demonstrated significant thalamic atrophy in Aβ+ patients compared to Aβ‐ DLB patients. We did not observe significant differences in grey matter and hippocampal volume between patient groups. This study showed that AD‐related processes in DLB patients are associated with thalamic atrophy, specifically in the ventral and posterior regions. Future studies would benefit a larger DLB cohort to further understand the association between AD‐related pathology and the regional thalamic correlates of clinical function.
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    Identification of neurodevelopmental gene variants implicated in age‐related brain morphological changes and cortical atrophy
    Vacher, M ; Porter, T ; Milicic, L ; Dore, V ; Bourgeat, P ; Villemagne, VLL ; Doecke, JD ; Laws, SM ; Heng, JI (Wiley, 2021-12)
    Background Neurodevelopmental genes and their associated protein products are involved in a number of biological processes essential for brain assembly. Despite their relative importance, the impact of genetic variation in neurodevelopmental genes on the neurodegenerative and neurocognitive changes that occur in Alzheimer’s disease, is poorly characterised. Here, we investigated the associations between Single Nucleotide Polymorphisms (SNPs) in neurodevelopmental genes and brain volumetrics. Method From a curated list of 40 genes related to neurodevelopmental processes, we identified a set of 233 independent SNPs. The genotype data was generated from 715 unrelated individuals (Amyloid Beta (Ab) ‐ N=328, Ab+ N=387), enrolled in the Australian Imaging, Biomarker & Lifestyle (AIBL) study. We focused this research on the cortical grey, subcortical white matter, ventricular, and hippocampal volumes and used linear mixed models to assess whether specific genotypes were associated to regional volume changes over time. The associations with the traits of interest were assessed cross‐sectionally at baseline and longitudinally, over a 12‐year time span. Result At baseline, cross‐sectional analyses revealed one significant association between the variant, rs2923137, located in DRC7 (<20KB KATNB1) and ventricular volume (p = 2.13e‐4, β = 5.8). In the longitudinal analyses, we found that rs1142749, a marker located near TUBB4B, was consistently associated with accelerated rate of change in grey matter (p = 9.2e‐4, β = 0.034), hippocampal (p = 2.9e‐3, β = 0.025) and ventricular volume (p = 2.1e‐3, β = ‐0.028). Further, we observed that the strength and effects of these associations were exacerbated in Ab+ individuals but were absent in Ab negative sub‐population. Another noticeable link was identified between rs2555172 (DCHS1) and hippocampal volume change (p = 1.4e‐3, β = ‐0.024). The identified associations were independent of variation due to the APOE e4 allele and remained significant after correction for multiple comparisons. Conclusion The results support the hypothesis that genes associated with neurodevelopmental processes and signalling mechanisms are relevant to Alzheimer’s Disease. The identified associations suggest that mutations in key neurodevelopment genes could be linked to accelerated atrophy in specific areas of the brain.
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    Feasibility of short imaging protocols for [18F]PI-2620 tau‐PET in progressive supranuclear palsy
    Song, M ; Scheifele, M ; Barthel, H ; van Eimeren, T ; Beyer, L ; Marek, K ; Eckenweber, F ; Palleis, C ; Finze, A ; Kaiser, L ; Kern, M ; Nitschmann, A ; Biechele, G ; Katzdobler, S ; Bischof, GN ; Hammes, J ; Jessen, F ; Saur, D ; Schroeter, ML ; Rumpf, J ; Rullmann, M ; Schildan, A ; Patt, M ; Neumaier, B ; Stephens, AW ; Rauchmann, B ; Perneczky, R ; Levin, J ; Classen, J ; Höglinger, G ; Bartenstein, P ; Boening, G ; Ziegler, S ; Villemagne, VLL ; Drzezga, A ; Seibyl, JP ; Sabri, O ; Brendel, M (Wiley, 2021-12)
    Background Dynamic 60‐minute positron‐emission‐tomography (PET) imaging with the novel tau radiotracer [18F]PI‐2620 facilitated accurate discrimination between patients with progressive supranuclear palsy (PSP) and healthy controls (HCs). We now aimed to investigate if shorter acquisition and static time windows of [18F]PI‐2620 tau‐PET can be used for imaging of patients with PSP. Method We evaluated 37 patients at five different centers with probable or possible PSP Richardson syndrome (PSP‐RS) together with ten HCs. [18F]PI‐2620 PET was performed by a dynamic 60 minute scan. Distribution volume ratios (DVRs, multilinear reference tissue model 2, cerebellar reference) were calculated using full and truncated scan durations (0‐60, 0‐50, 0‐40, 0‐30, and 0‐20 minutes p.i.). Standardized uptake value ratios (SUVrs, cerebellar reference) were obtained from static imaging windows with 20 minutes duration (20‐40, 30‐50, and 40‐60 minutes p.i.). All DVR and SUVr data were compared with regard to their potential to discriminate patients with PSP‐RS from HCs in predefined subcortical and cortical target regions (effect size, receiver operating area under the curve (AUC), multi‐region classifier). Finally, we tested if shorter [18F]PI‐2620 PET imaging can also be applied to patients with Alzheimer’s disease (n=11). Result The effect size of 0‐50 and 0‐40 DVR was equivalent to 0‐60 DVR (averaged Cohen’s d: 1.22 and 1.16 vs. 1.26), whereas the performance dropped for 0‐30 or 0‐20 DVR. The 20‐40 SUVr indicated the best performance of all short static acquisition windows (averaged Cohen’s d: 0.99). The globus pallidus internus discriminated patients with PSP and healthy controls at a similarly high level for 0‐60 DVR (AUC: 0.96), 0‐40 DVR (AUC: 0.96), and 20‐40 SUVr (AUC: 0.94). The multi‐region classifier sensitivity of these time windows was consistently 86%. 0‐40 DVR showed similar performance in Alzheimer’s disease when compared to 0‐60 DVR. Conclusion Short dynamic acquisition and static imaging windows can be used for [18F]PI‐2620 PET imaging of PSP. 0‐40 minute dynamic scanning offers the best balance between accuracy and economic scanning and is may also be suitable for [18F]PI‐2620 PET imaging of Alzheimer’s disease.
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    Towards a universal cortical tau sampling mask
    Dore, V ; Bohorquez, SS ; Leuzy, A ; Shimada, H ; Bullich, S ; Bourgeat, P ; Burnham, SC ; Huang, K ; Krishnadas, N ; Fripp, J ; Takado, Y ; Stephens, AW ; Weimer, R ; Rowe, CC ; Higuchi, M ; Hansson, O ; Villemagne, VL (Wiley, 2021-12)
    Background The introduction of the AT(N) framework raised several issues in regards to the definition of T+. What brain regions should be sampled? Based on one or on multiple tracers? In this work, we developed a “universal” cortical tau mask for the AD continuum derived from all the major tau ligands. This “universal” cortical mask will serve as the common tau area for all tracers over which several different regional sampling VOI or composites can be then applied. Guaranteeing sampling of the same common regions is the first step to develop a common scale for all tau tracers: the CenTauR. Method 464 participants underwent tau scans with either 18F‐AV1451 (CN=54/AD=24), 18F‐MK6240 (CN=157/AD=22), 18F‐PI2620 (CN=10/AD=21), 18F‐PM‐PBB3 (CN=30/AD=28), 18F‐GTP1 (CN=15/AD=38) or 18F‐RO948 (CN=35/AD=30). All CN were Aß‐ and all AD were Aß+. The tau scans were spatially normalized using CapAIBL and the cerebellar cortex was used as reference region. For each tracer, a difference image between the means of the Aß‐ CN and Aß+ AD patients was generated. Difference images were subsequently thresholded at 1/3 of the difference between Aß‐ CN and Aß+ AD in the inferior temporal lobe. A single tau specific mask was then constructed from the intersection of all the specific tau tracer masks. A MRI‐derived grey matter mask at PET resolution was applied to the composite mask only sampling grey matter regions. Finally, the mask was mirrored and fused to remove the hemispherical asymmetry of tau pathology. Agreement between masks was assessed by dice‐scores. Result Visually, all the tracer‐specific masks appeared very similar. None of the known off‐target binding regions were discernible in the resulting masks (Figure 1). There was good agreement between all masks, with dice‐scores of 0.60 and 0.66 for cortical regions. Conclusion We constructed an “universal” tau mask for the AD continuum based on all the commonly used tau tracers aiming at standardizing tau sampling and quantification across tracers and across centres. The “universal” tau mask demarcates a tau specific space that can then be sub‐segmented into smaller regions to focus on specific areas or composite regions that might better capture early tau deposition and spreading.
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    Relationship between amyloid and tau levels and its impact on tau spreading
    Dore, V ; Krishnadas, N ; Bourgeat, P ; Huang, K ; Li, S ; Burnham, SC ; Masters, CL ; Fripp, J ; Villemagne, VL ; Rowe, CC (Wiley, 2021-12)
    Background Previous studies have shown that Aß‐amyloid (Aß) likely promotes tau to spread beyond the medial temporal lobe. However, the Aß levels necessary for tau to spread in the neocortex is still unclear. Method 466 participants underwent tau imaging with [18F]MK6420 and Aß imaging with [18F]NAV4694 (Fig. 1). Aß scans were quantified on the Centiloid (CL) scale with a cut‐off of 25CL for abnormal levels of Aß (A+). Tau scans were quantified in three regions of interest (ROI) (mesial temporal (Me); temporoparietal neocortex (Te); and rest of neocortex (R)) and four mesial temporal region (entorhinal cortex, amygdala, hippocampus and parahippocampus) using the cerebellar cortex as reference region. Regional tau thresholds were established as the 95%ile of the cognitively unimpaired A‐ subjects. The prevalence of abnormal tau levels (T+) along the Centiloid continuum was determined. Result The plots of prevalence of T+ (Fig. 2) show earlier and greater increase along the Centiloid continuum in the medial temporal area compared to neocortex. Prevalence of T+ was low but associated with Aß level between 10‐40 CL reaching 23% in Me, 15% in Te and 11% in R. Between 40‐70 CL, the prevalence of T+ subjects per CL increased four‐fold faster and at 70 CL was 64% in Me, 51% in Te and 37% in R. In cognitively unimpaired (Fig. 3), there were no T+ in R below 50 CL. The highest prevalence of T+ was found in the entorhinal cortex, reaching 40% at 40 CL and 80% at 60 CL. Conclusion Outside the entorhinal cortex, abnormal levels of cortical tau on PET are rarely found with Aß levels below 40 CL. Above 40 CL prevalence of T+ accelerates in all areas. Moderate Aß levels are required before neocortical tau becomes detectable.