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ObjectiveThe clinical phenotype of the rare behavioural variant of Alzheimer’s disease (bvAD) is insufficiently understood. Given the strong clinico-anatomical correlations of tau pathology in AD, we investigated the distribution of tau deposits in bvAD, in-vivo and ex-vivo, using positron emission tomography (PET) and postmortem examination.MethodsFor the tau PET study, seven amyloid-β positive bvAD patients underwent [18F]flortaucipir or [18F]RO948 PET. We converted tau PET uptake values into standardised (W-)scores, adjusting for age, sex and mini mental state examination in a ‘typical’ memory-predominant AD (n=205) group. W-scores were computed within entorhinal, temporoparietal, medial and lateral prefrontal, insular and whole-brain regions-of-interest, frontal-to-entorhinal and frontal-to-parietal ratios and within intrinsic functional connectivity network templates. For the postmortem study, the percentage of AT8 (tau)-positive area in hippocampus CA1, temporal, parietal, frontal and insular cortices were compared between autopsy-confirmed patients with bvAD (n=8) and typical AD (tAD;n=7).ResultsIndividual regional W-scores ≥1.96 (corresponding to p0.05).ConclusionsBoth in-vivo and ex-vivo, patients with bvAD showed heterogeneous distributions of tau pathology. Since key regions involved in behavioural regulation were not consistently disproportionally affected by tau pathology, other factors are more likely driving the clinical phenotype in bvAD.

Purpose We aimed to investigate associations between tau pathology and relative cerebral blood flow (rCBF), and their relationship with cognition in Alzheimer’s disease (AD), by using a single dynamic [18F]flortaucipir positron emission tomography (PET) scan. Methods Seventy-one subjects with AD (66 ± 8 years, mini-mental state examination (MMSE) 23 ± 4) underwent a dynamic 130-min [18F]flortaucipir PET scan. Cognitive assessment consisted of composite scores of four cognitive domains. For tau pathology and rCBF, receptor parametric mapping (cerebellar gray matter reference region) was used to create uncorrected and partial volume-corrected parametric images of non-displaceable binding potential (BPND) and R1, respectively. (Voxel-wise) linear regressions were used to investigate associations between BPND and/or R1 and cognition. Results Higher [18F]flortaucipir BPND was associated with lower R1 in the lateral temporal, parietal and occipital regions. Higher medial temporal BPND was associated with worse memory, and higher lateral temporal BPND with worse executive functioning and language. Higher parietal BPND was associated with worse executive functioning, language and attention, and higher occipital BPND with lower cognitive scores across all domains. Higher frontal BPND was associated with worse executive function and attention. For [18F]flortaucipir R1, lower values in the lateral temporal and parietal ROIs were associated with worse executive functioning, language and attention, and lower occipital R1 with lower language and attention scores. When [18F]flortaucipir BPND and R1 were modelled simultaneously, associations between lower R1 in the lateral temporal ROI and worse attention remained, as well as for lower parietal R1 and worse executive functioning and attention. Conclusion Tau pathology was associated with locally reduced rCBF. Tau pathology and low rCBF were both independently associated with worse cognitive performance. For tau pathology, these associations spanned widespread neocortex, while for rCBF, independent associations were restricted to lateral temporal and parietal regions and the executive functioning and attention domains. These findings indicate that each biomarker may independently contribute to cognitive impairment in AD.

Background The mechanism of synaptic loss in Alzheimer’s disease is poorly understood and may be associated with tau pathology. In this combined positron emission tomography (PET) and magnetoencephalography (MEG) study, we aimed to investigate spatial associations between regional tau pathology ([18F]flortaucipir PET), synaptic density (synaptic vesicle 2A [11C]UCB-J PET) and synaptic function (MEG) in Alzheimer’s disease. Methods Seven amyloid-positive Alzheimer’s disease subjects from the Amsterdam Dementia Cohort underwent dynamic 130-min [18F]flortaucipir PET, dynamic 60-min [11C]UCB-J PET with arterial sampling and 2 × 5-min resting-state MEG measurement. [18F]flortaucipir- and [11C]UCB-J-specific binding (binding potential, BPND) and MEG spectral measures (relative delta, theta and alpha power; broadband power; and peak frequency) were assessed in cortical brain regions of interest. Associations between regional [18F]flortaucipir BPND, [11C]UCB-J BPND and MEG spectral measures were assessed using Spearman correlations and generalized estimating equation models. Results Across subjects, higher regional [18F]flortaucipir uptake was associated with lower [11C]UCB-J uptake. Within subjects, the association between [11C]UCB-J and [18F]flortaucipir depended on within-subject neocortical tau load; negative associations were observed when neocortical tau load was high, gradually changing into opposite patterns with decreasing neocortical tau burden. Both higher [18F]flortaucipir and lower [11C]UCB-J uptake were associated with altered synaptic function, indicative of slowing of oscillatory activity, most pronounced in the occipital lobe. Conclusions These results indicate that in Alzheimer’s disease, tau pathology is closely associated with reduced synaptic density and synaptic dysfunction.

PurposeSemi-quantitative PET measures can be affected by changes in blood flow, whereas quantitative measures are not. The aim of the study was to compare semi-quantitative(SUVr) and quantitative(R1, BPND) parameters of longitudinal tau PET scans with [18F]flortaucipir, with respect to changes in blood flow.MethodsSubjects with subjective cognitive decline(SCD; n=38) and Alzheimer’s disease(AD) patients(n=24) underwent baseline(BL) and 2-year follow-up(FU) dynamic [18F]flortaucipir PET scans. BPND and R1 were estimated using RPM and SUVr(80-100min) was calculated (cerebellar gray as reference). For each region-of-interest ((trans)entorhinal, limbic and neocortical) and parameter, %change was calculated. Regional SUVrs were compared to corresponding DVR (= BPND+1) using paired T-tests. Additionally, simulations were performed to model effects of flow changes on BPND and SUVr in different binding categories. Thereafter, %bias for SUVr with respect to underlying binding and flow were evaluated.ResultsIn SCD, there was a difference between %change in the (trans)entorhinal ROI (DVR 2.56% vs SUVr 1.85%) only. In AD, a difference was found in the limbic ROI (DVR 6.61% vs SUVr 7.52%) only. R1 changes were small(+0.7% in SCD and -1.6% in AD). Simulations illustrated with increasing flow a decreased %bias for SUVr in low binding conditions, whereas a slightly increased bias was observed in high binding conditions.ConclusionSUVr provided an accurate estimate of specific binding for [18F]flortaucipir over a two-year follow-up. However, simulations showed that flow changes can affect [18F]flortaucipir SUVr, hence DVR/BPND should be preferred in more advanced disease stages and/or conditions that could induce significant flow changes like pharmacotherapeutic interventions.

PurposeEarly-onset Alzheimer’s disease (EOAD) and late-onset Alzheimer’s disease (LOAD) differ in neuropathological burden and type of cognitive deficits. Assessing tau pathology and relative cerebral blood flow (rCBF) measured with [18F]flortaucipir PET in relation to cognition may help explain these differences between EOAD and LOAD.MethodsSeventy-nine amyloid-positive individuals with a clinical diagnosis of AD (EOAD: n=35, age-at-PET=59±5, MMSE=23±4; LOAD: n=44, age-at-PET=71±5, MMSE=23±4) underwent a 130 minutes dynamic [18F]flortaucipir PET scan and extensive neuropsychological assessment. We extracted binding potentials (BPND) and R1 (proxy of rCBF) from parametric images using receptor parametric mapping, in medial and lateral temporal, parietal, occipital and frontal regions-of-interest and used nine neuropsychological tests covering memory, attention, language and executive functioning. We first examined differences between EOAD and LOAD in BPND or R1 using ANOVA (region-of-interest analysis) and voxel-wise contrasts. Next, we performed linear regression models to test for potential interaction effects between age-at-onset and BPND/R1 on cognition.ResultsBoth region-of-interest and voxel-wise contrasts showed higher [18F]flortaucipir BPND values across all neocortical regions in EOAD. By contrast, LOAD patients had lower R1 values (indicative of more reduced rCBF) in medial temporal regions. For both tau and flow in lateral temporal, and occipito-parietal regions, associations with cognitive impairment were stronger in EOAD than in LOAD (EOAD BPND -0.76≤stβ≤-0.48 vs LOAD -0.18≤stβ≤-0.02; EOAD R1 0.37≤stβ≤0.84 vs LOAD -0.25≤stβ≤0.16).ConclusionsCompared to LOAD, the degree of lateral temporal and occipito-parietal tau pathology and relative cerebral blood-flow is more strongly associated with cognition in EOAD.

Purpose In vivo Alzheimer’s disease (AD) biomarkers for tau pathology are cerebrospinal fluid (CSF) phosphorylated tau (p-tau) and [18F]flortaucipir positron emission tomography (PET). Our aim was to assess associations between CSF p-tau with [18F]flortaucipir PET and the associations of both tau biomarkers with cognition and atrophy. Methods We included 78 amyloid positive cognitively impaired patients (clinical diagnoses mild cognitive impairment (MCI, n = 8) and AD dementia (n = 45) and 25 cognitively normal subjects with subjective cognitive decline (SCD) (40% amyloid-positive)). Dynamic 130 min [18F]flortaucipir PET scans were acquired to generate binding potential (BPND) images using receptor parametric mapping and standardized uptake values ratios of 80–100 min (SUVr80-100min) post injection. We obtained regional BPND and SUVr from entorhinal, limbic, and neocortical regions-of-interest (ROIs), closely aligning to the neuropathological tau staging schemes. Cognition was assessed using MMSE and composite scores of four cognitive domains, and atrophy was measured using gray matter volume covering the major brain lobes. First, we used linear regressions to investigate associations between CSF p-tau (independent variable) and tau PET (dependent variable). Second, we used linear regressions to investigate associations between CSF p-tau, tau PET (separate independent variables, model 1), and cognition (dependent variable). We then assessed the independent effects of CSF p-tau and tau PET on cognition by simultaneously adding the other tau biomarker as a predictor (model 2). Finally, we performed the same procedure for model 1 and 2, but replaced cognition with atrophy. Models were adjusted for age, sex, time lag between assessments, education (cognition only), and total intracranial volume (atrophy only). Results Higher [18F]flortaucipir BPND was associated with higher CSF p-tau (range of standardized betas (sβ) across ROIs, 0.43–0.46; all p 18F]flortaucipir BPND was more strongly associated with cognition and atrophy than CSF p-tau. When [18F]flortaucipir BPND and CSF p-tau were entered simultaneously, [18F]flortaucipir BPND (range sβ = − 0.20 to – 0.57, all p ND. Conclusion Regional [18F]flortaucipir BPND correlated stronger with cognition and neurodegeneration than CSF p-tau, suggesting that tau PET more accurately reflects disease severity in AD.

Highlights • The amount of tau binding in DLB was minimal and did not differ from controls. • Relative cerebral blood flow (rCBF), but not tau PET, was related to cognitive impairment. • rCBF is more strongly related to clinical characteristics in DLB than tau PET., Purpose Alpha-synuclein often co-occurs with Alzheimer’s disease (AD) pathology in Dementia with Lewy Bodies (DLB). From a dynamic [18F]flortaucipir PET scan we derived measures of both tau binding and relative cerebral blood flow (rCBF). We tested whether regional tau binding or rCBF differed between DLB patients and AD patients and controls and examined their association with clinical characteristics of DLB. Methods Eighteen patients with probable DLB, 65 AD patients and 50 controls underwent a dynamic 130-minute [18F]flortaucipir PET scan. DLB patients with positive biomarkers for AD based on cerebrospinal fluid or amyloid PET were considered as DLB with AD pathology (DLB-AD+). Receptor parametric mapping (cerebellar gray matter reference region) was used to extract regional binding potential (BPND) and R1, reflecting (AD-specific) tau pathology and rCBF, respectively. First, we performed regional comparisons of [18F]flortaucipir BPND and R1 between diagnostic groups. In DLB patients only, we performed regression analyses between regional [18F]flortaucipir BPND, R1 and performance on ten neuropsychological tests. Results Regional [18F]flortaucipir BPND in DLB was comparable with tau binding in controls (p > 0.05). Subtle higher tau binding was observed in DLB-AD+ compared to DLB-AD- in the medial temporal and parietal lobe (both p

ObjectiveThe clinical phenotype of the rare behavioral variant of Alzheimer’s disease (bvAD) is insufficiently understood. Given the strong clinico-anatomical correlations of tau pathology in AD, we investigated the distribution of tau deposits in bvAD, in-vivo and ex-vivo, using PET and postmortem examination.MethodsFor the tau PET study, seven amyloid-P positive bvAD patients underwent [18F]flortaucipir or [18F]RO948 PET. We converted tau PET uptake values into standardized (W-)scores, by adjusting for age, sex and MMSE in a “typical” memory-predominant AD (n=205) group. W-scores were computed within entorhinal, temporoparietal, medial and lateral prefrontal, insular and whole-brain regions-of-interest, frontal-to-entorhinal and frontal-to-parietal ratios and within intrinsic functional connectivity network templates. For the postmortem study, the percentage of AT8 (tau)-positive area in hippocampus CA1, temporal, parietal, frontal and insular cortices were compared between autopsy-confirmed bvAD (n=8) and typical AD (n=7) patients.ResultsRegional W-scores ≥1.96 (corresponding to p0.05).ConclusionBoth in-vivo and ex-vivo, bvAD patients showed heterogeneous patterns of tau pathology. Since key regions involved in behavioral regulation were not consistently disproportionally affected by tau pathology, other factors are more likely driving the clinical phenotype in bvAD.

Background The panel of fluid- and imaging-based biomarkers available for neurodegenerative disease research is growing and has the potential to close important gaps in research and the clinic. With this growth and increasing use, appropriate implementation and interpretation are paramount. Various biomarkers feature nuanced differences in strengths, limitations, and biases that must be considered when investigating disease etiology and clinical utility. For example, neuropathological investigations of Alzheimer’s disease pathogenesis can fall in disagreement with conclusions reached by biomarker-based investigations. Considering the varied strengths, limitations, and biases of different research methodologies and approaches may help harmonize disciplines within the neurodegenerative disease field. Purpose of review Along with separate review articles covering fluid and imaging biomarkers in this issue of Alzheimer’s Research and Therapy, we present the result of a discussion from the 2019 Biomarkers in Neurodegenerative Diseases course at the University College London. Here, we discuss themes of biomarker use in neurodegenerative disease research, commenting on appropriate use, interpretation, and considerations for implementation across different neurodegenerative diseases. We also draw attention to areas where biomarker use can be combined with other disciplines to understand issues of pathophysiology and etiology underlying dementia. Lastly, we highlight novel modalities that have been proposed in the landscape of neurodegenerative disease research and care.

BackgroundThe panel of fluid- and imaging-based biomarkers available for neurodegenerative disease research is growing and has the potential to close important gaps in research and the clinic. With this growth and increasing use, appropriate implementation and interpretation are paramount. Various biomarkers feature nuanced differences in strengths, limitations, and biases that must be considered when investigating disease etiology and clinical utility. For example, neuropathological investigations of Alzheimer’s disease pathogenesis can fall in disagreement with conclusions reached by biomarker-based investigations. Considering the varied strengths, limitations, and biases of different research methodologies and approaches may help harmonize disciplines within the neurodegenerative disease field.Purpose of reviewAlong with separate review articles covering fluid and imaging biomarkers in this issue ofAlzheimer’s Research and Therapy, we present the result of a discussion from the 2019 Biomarkers in Neurodegenerative Diseases course at the University College London. Here, we discuss themes of biomarker use in neurodegenerative disease research, commenting on appropriate use, interpretation, and considerations for implementation across different neurodegenerative diseases. We also draw attention to areas where biomarker use can be combined with other disciplines to understand issues of pathophysiology and etiology underlying dementia. Lastly, we highlight novel modalities that have been proposed in the landscape of neurodegenerative disease research and care.

There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course “Biomarkers in neurodegenerative diseases”. In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis.

The authors regret to inform readers that the following error was detected in the original article. The values for entorhinal, limbic and neortical SUVr were switched between SCD Aβ + and Aβ- in Table 1 and have now been corrected. Unnecessary symbols in Table 2 have been removed.

Background: Off-target [ 18F]flortaucipir (tau) PET binding in the choroid plexus causes spill-in into the nearby hippocampus, which may influence the correlation between [ 18F]flortaucipir binding and measures of cognition. Previously, we showed that partial volume correction (combination of Van Cittert iterative deconvolution and HYPR denoising; PVC HDH) and manually eroding the hippocampus resulted in a significant decrease of the choroid plexus spill-in. In this study, we compared three different approaches for the quantification of hippocampal [ 18F]flortaucipir signal using a semi-automated technique, and assessed correlations with cognitive performance across methods. Methods: Dynamic 130 min [ 18F]flortaucipir PET scans were performed in 109 subjects (45 cognitively normal subjects (CN) and 64 mild cognitive impairment/Alzheimer's disease (AD) dementia patients. We extracted hippocampal binding potential (BP ND) using receptor parametric mapping with cerebellar grey matter as reference region. PVC HDH was performed. Based on our previous study in which we manually eroded 40% ± 10% of voxels of the hippocampus, three hippocampal volumes-of-interest (VOIs) were generated: a non-optimized 100% hippocampal VOI [100%], and combining HDH with eroding a percentage of the highest hippocampus BP ND voxels (i.e. lowering spill-in) resulting in optimized 50%[50%HDH] and 40%[40%HDH] hippocampal VOIs. Cognitive performance was assessed with the Mini-Mental State Examination (MMSE) and Rey auditory verbal learning delayed recall. We performed receiver operating characteristic analyses to investigate which method could best discriminate MCI/AD from controls. Subsequently, we performed linear regressions to investigate associations between the hippocampal [ 18F]flortaucipir BP ND VOIs and MMSE/delayed recall adjusted for age, sex and education. Results: We found higher hippocampal [ 18F]flortaucipir BP ND in MCI/AD patients (BP ND100%=0.27±0.15) compared to CN (BP ND100%= 0.07±0.13) and all methods showed comparable discriminative effects (AUC 100%=0.85[CI=0.78–0.93]; AUC 50%HDH=0.84[CI=0.74–0.92]; AUC 40%HDH=0.83[CI=0.74–0.92]). Across groups, higher [ 18F]flortaucipir BP ND was related to lower scores on MMSE (standardized β 100%=-0.38[CI=-0.57−0.20]; β 50%HDH= -0.37[CI=-0.54−0.19]; β 40%HDH=-0.35[CI=-0.53−0.17], all p100%=-0.64[CI=-0.79−0.49]; β 50%HDH= -0.61[CI=-0.76−0.46]; β 40%HDH=-0.59[CI=-0.75−0.44]; all p18F]flortaucipir PET is strongly associated with cognitive function. Both discrimination between diagnostic groups and associations between hippocampal [ 18F]flortaucipir BP ND and memory were comparable for all methods. The non-optimized 100% hippocampal VOI may be sufficient for clinical interpretation. However, proper correction for choroid plexus spillover and may be required in case of smaller effect sizes between subject groups or for longitudinal studies.