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IntroductionTau-positron emission tomography (PET) outcome data of patients with Alzheimer's disease (AD) cannot currently be meaningfully compared or combined when different tracers are used due to differences in tracer properties, instrumentation, and methods of analysis.MethodsUsing head-to-head data from five cohorts with tau PET radiotracers designed to target tau deposition in AD, we tested a joint propagation model (JPM) to harmonize quantification (units termed "CenTauR" [CTR]). JPM is a statistical model that simultaneously models the relationships between head-to-head and anchor point data. JPM was compared to a linear regression approach analogous to the one used in the amyloid PET Centiloid scale.ResultsA strong linear relationship was observed between CTR values across brain regions. Using the JPM approach, CTR estimates were similar to, but more accurate than, those derived using the linear regression approach.DiscussionPreliminary findings using the JPM support the development and adoption of a universal scale for tau-PET quantification.HighlightsTested a novel joint propagation model (JPM) to harmonize quantification of tau PET. Units of common scale are termed "CenTauRs". Tested a Centiloid-like linear regression approach. Using five cohorts with head-to-head tau PET, JPM outperformed linearregressionbased approach. Strong linear relationship was observed between CenTauRs values across brain regions.

IntroductionThe Centiloid (CL) project was developed to harmonize the quantification of amyloid beta (Aβ) positron emission tomography (PET) scans to a unified scale. The CL neocortical mask was defined using 11C Pittsburgh compound B (PiB), overlooking potential differences in regional distribution among Aβ tracers. We created a universal mask using an independent dataset of five Aβ tracers, and investigated its impact on inter-tracer agreement, tracer variability, and group separation.MethodsUsing data from the Alzheimer's Dementia Onset and Progression in International Cohorts (ADOPIC) study (Australian Imaging Biomarkers and Lifestyle + Alzheimer's Disease Neuroimaging Initiative + Open Access Series of Imaging Studies), age-matched pairs of mild Alzheimer's disease (AD) and healthy controls (HC) were selected: 18F-florbetapir (N = 147 pairs), 18F-florbetaben (N = 22), 18F-flutemetamol (N = 10), 18F-NAV (N = 42), 11C-PiB (N = 63). The images were spatially and standardized uptake value ratio normalized. For each tracer, the mean AD-HC difference image was thresholded to maximize the overlap with the standard neocortical mask. The universal mask was defined as the intersection of all five masks. It was evaluated on the Global Alzheimer's Association Interactive Network (GAAIN) head-to-head datasets in terms of inter-tracer agreement and variance in the young controls (YC) and on the ADOPIC dataset comparing separation between HC/AD and HC/mild cognitive impairment (MCI).ResultsIn the GAAIN dataset, the universal mask led to a small reduction in the variance of the YC, and a small increase in the inter-tracer agreement. In the ADOPIC dataset, it led to a better separation between HC/AD and HC/MCI at baseline.DiscussionThe universal CL mask led to an increase in inter-tracer agreement and group separation. Those increases were, however, very small, and do not provide sufficient benefits to support departing from the existing standard CL mask, which is suitable for the quantification of all Aβ tracers.HighlightsThis study built an amyloid universal mask using a matched cohort for the five most commonly used amyloid positron emission tomography tracers.There was a high overlap between each tracer-specific mask.Differences in quantification and group separation between the standard and universal mask were small.The existing standard Centiloid mask is suitable for the quantification of all amyloid beta tracers.

Traumatic brain injury (TBI) is common among military veterans and has been associated with an increased risk of dementia. It is unclear if this is due to increased risk for Alzheimer's disease (AD) or other mechanisms. This case control study sought evidence for AD, as defined by the 2018 National Institute on Aging - Alzheimer's Association (NIA-AA) research framework, by measuring tau, β-amyloid, and glucose metabolism using positron emission tomography (PET) in veterans with service-related TBI. Seventy male Vietnam war veterans-40 with TBI (age 68.0 ± 2.5 years) and 30 controls (age 70.1 ± 5.3 years)-with no prior diagnosis of dementia or mild cognitive impairment underwent β-amyloid (18F-Florbetaben), tau (18F-Flortaucipir), and fluorodeoxyglucose (18F-FDG) PET. The TBI cohort included 15 participants with mild, 16 with moderate, and nine with severe injury. β-Amyloid level was calculated using the Centiloid (CL) method and tau was measured by standardized uptake value ratios (SUVRs) using the cerebellar cortex as reference region. Analyses were adjusted for age and APOE-e4. The findings were validated in an independent cohort from the Department of Defense-Alzheimer's Disease Neuroimaging Initiative (DOD ADNI) study. There were no significant nor trending differences in β-amyloid or tau levels or 18F-FDG uptake between the TBI and control groups before and after controlling for covariates. The β-amyloid and tau findings were replicated in the DOD ADNI validation cohort and persisted when the Australian Imaging Biomarkers and Lifestyle study of aging-Veterans study (AIBL-VETS) and DOD ADNI cohorts were combined (114 TBI vs. 87 controls in total). In conclusion, no increase in the later life accumulation of the neuropathological markers of AD in veterans with a remote history of TBI was identified.

IntroductionBlood-based diagnostics and prognostics in sporadic Alzheimer's disease (AD) are important for identifying at-risk individuals for therapeutic interventions.MethodsIn three stages, a total of 34 leukocyte antigens were examined by flow cytometry immunophenotyping. Data were analyzed by logistic regression and receiver operating characteristic (ROC) analyses.ResultsWe identified leukocyte markers differentially expressed in the patients with AD. Pathway analysis revealed a complex network involving upregulation of complement inhibition and downregulation of cargo receptor activity and Aβ clearance. A proposed panel including four leukocyte markers - CD11c, CD59, CD91, and CD163 - predicts patients' PET Aβ status with an area under the curve (AUC) of 0.93 (0.88 to 0.97). CD163 was the top performer in preclinical models. These findings have been validated in two independent cohorts.ConclusionOur finding of changes on peripheral leukocyte surface antigens in AD implicates the deficit in innate immunity. Leukocyte-based biomarkers prove to be both sensitive and practical for AD screening and diagnosis.

IntroductionThe Centiloid scale was developed to harmonise the quantification of β-amyloid (Aβ) PET images across tracers, scanners, and processing pipelines. However, several groups have reported differences across tracers and scanners even after centiloid conversion. In this study, we aim to evaluate the impact of different pre and post-processing harmonisation steps on the robustness of longitudinal Centiloid data across three large international cohort studies.MethodsAll Aβ PET data in AIBL (N = 3315), ADNI (N = 3442) and OASIS3 (N = 1398) were quantified using the MRI-based Centiloid standard SPM pipeline and the PET-only pipeline CapAIBL. SUVR were converted into Centiloids using each tracer's respective transform. Global Aβ burden from pre-defined target cortical regions in Centiloid units were quantified for both raw PET scans and PET scans smoothed to a uniform 8 mm full width half maximum (FWHM) effective smoothness. For Florbetapir, we assessed the performance of using both the standard Whole Cerebellum (WCb) and a composite white matter (WM)+WCb reference region. Additionally, our recently proposed quantification based on Non-negative Matrix Factorisation (NMF) was applied to all spatially and SUVR normalised images. Correlation with clinical severity measured by the Mini-Mental State Examination (MMSE) and effect size, as well as tracer agreement in 11C-PiB-18F-Florbetapir pairs and longitudinal consistency were evaluated.ResultsThe smoothing to a uniform resolution partially reduced longitudinal variability, but did not improve inter-tracer agreement, effect size or correlation with MMSE. Using a Composite reference region for 18F-Florbetapir improved inter-tracer agreement, effect size, correlation with MMSE, and longitudinal consistency. The best results were however obtained when using the NMF method which outperformed all other quantification approaches in all metrics used.ConclusionsFWHM smoothing has limited impact on longitudinal consistency or outliers. A Composite reference region including subcortical WM should be used for computing both cross-sectional and longitudinal Florbetapir Centiloid. NMF improves Centiloid quantification on all metrics examined.

In 2018, the US National Institute on Aging and the Alzheimer's Association proposed a purely biological definition of Alzheimer's disease that relies on biomarkers. Although the intended use of this framework was for research purposes, it has engendered debate and challenges regarding its use in everyday clinical practice. For instance, cognitively unimpaired individuals can have biomarker evidence of both amyloid β and tau pathology but will often not develop clinical manifestations in their lifetime. Furthermore, a positive Alzheimer's disease pattern of biomarkers can be observed in other brain diseases in which Alzheimer's disease pathology is present as a comorbidity. In this Personal View, the International Working Group presents what we consider to be the current limitations of biomarkers in the diagnosis of Alzheimer's disease and, on the basis of this evidence, we propose recommendations for how biomarkers should and should not be used for diagnosing Alzheimer's disease in a clinical setting. We recommend that Alzheimer's disease diagnosis be restricted to people who have positive biomarkers together with specific Alzheimer's disease phenotypes, whereas biomarker-positive cognitively unimpaired individuals should be considered only at-risk for progression to Alzheimer's disease.

To improve understanding of Alzheimer's disease, large observational studies are needed to increase power for more nuanced analyses. Combining data across existing observational studies represents one solution. However, the disparity of such datasets makes this a non-trivial task. Here, a machine learning approach was applied to impute longitudinal neuropsychological test scores across two observational studies, namely the Australian Imaging, Biomarkers and Lifestyle Study (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) providing an overall harmonised dataset. MissForest, a machine learning algorithm, capitalises on the underlying structure and relationships of data to impute test scores not measured in one study aligning it to the other study. Results demonstrated that simulated missing values from one dataset could be accurately imputed, and that imputation of actual missing data in one dataset showed comparable discrimination (p

The Worldwide Alzheimer's Disease Neuroimaging Initiative (WW-ADNI) is a collaborative effort to investigate imaging and biofluid markers that can inform Alzheimer's disease treatment trials. It is a public-private partnership that spans North America, Argentina, Australia, Canada, China, Japan, Korea, Mexico, and Taiwan. In 2004, ADNI researchers began a naturalistic, longitudinal study that continues today around the globe. Through several successive phases (ADNI-1, ADNI-GO, ADNI-2, and ADNI-3), the study has fueled amyloid and tau phenotyping and refined neuroimaging methodologies. WW-ADNI researchers have successfully standardized analyses and openly share data without embargo, providing a rich data set for other investigators. On August 26, 2020, the Alzheimer's Association convened WW-ADNI researchers who shared updates from ADNI-3 and their vision for ADNI-4.

IntroductionWe sought to establish the relationships between standard postmortem measures of AD neuropathology and antemortem [11C]PIB-positron emission tomography ([11C]PIB-PET) analyzed with the Centiloid (CL) method, a standardized scale for Aβ-PET quantification.MethodsFour centers contributed 179 participants encompassing a broad range of clinical diagnoses, PET data, and autopsy findings.ResultsCL values increased with each CERAD neuritic plaque score increment (median -3 CL for no plaques and 92 CL for frequent plaques) and nonlinearly with Thal Aβ phases (increases were detected starting at phase 2) with overlap between scores/phases. PET-pathology associations were comparable across sites and unchanged when restricting the analyses to the 56 patients who died within 2 years of PET. A threshold of 12.2 CL detected CERAD moderate-to-frequent neuritic plaques (area under the curve = 0.910, sensitivity = 89.2%, specificity = 86.4%), whereas 24.4 CL identified intermediate-to-high AD neuropathological changes (area under the curve = 0.894, sensitivity = 84.1%, specificity = 87.9%).DiscussionOur study demonstrated the robustness of a multisite Centiloid [11C]PIB-PET study and established a range of pathology-based CL thresholds.

Impaired clearance of amyloid β (Aβ) in late-onset Alzheimer's disease (AD) affects disease progression. The role of peripheral monocytes in Aβ clearance from the central nervous system (CNS) is unclear. We use a flow cytometry assay to identify Aβ-binding monocytes in blood, validated by confocal microscopy, Western blotting, and mass spectrometry. Flow cytometry immunophenotyping and correlation with AD biomarkers are studied in 150 participants from the AIBL study. We also examine monocytes in human cerebrospinal fluid (CSF) and their migration in an APP/PS1 mouse model. The assay reveals macrophage-like Aβ-binding monocytes with high phagocytic potential in both the periphery and CNS. We find lower surface Aβ levels in mild cognitive impairment (MCI) and AD-dementia patients compared to cognitively unimpaired individuals. Monocyte infiltration from blood to CSF and migration from CNS to peripheral lymph nodes and blood are observed. Here we show that Aβ-binding monocytes may play a role in CNS Aβ clearance, suggesting their potential as a biomarker for AD diagnosis and monitoring. Impaired Aβ clearance in late-onset Alzheimer's disease (AD) affects progression. Here, the authors show that CD14 + CD16+ monocytes carry Aβ in peripheral circulation and CSF in AD, suggesting a role in Aβ clearance. [ABSTRACT FROM AUTHOR]

ObjectiveTo estimate the prevalence of amyloid positivity, defined by positron emission tomography (PET)/cerebrospinal fluid (CSF) biomarkers and/or neuropathological examination, in primary progressive aphasia (PPA) variants.MethodsWe conducted a meta-analysis with individual participant data from 1,251 patients diagnosed with PPA (including logopenic [lvPPA, n = 443], nonfluent [nfvPPA, n = 333], semantic [svPPA, n = 401], and mixed/unclassifiable [n = 74] variants of PPA) from 36 centers, with a measure of amyloid-β pathology (CSF [n = 600], PET [n = 366], and/or autopsy [n = 378]) available. The estimated prevalence of amyloid positivity according to PPA variant, age, and apolipoprotein E (ApoE) ε4 status was determined using generalized estimating equation models.ResultsAmyloid-β positivity was more prevalent in lvPPA (86%) than in nfvPPA (20%) or svPPA (16%; p

In 2011, the National Institute on Aging and Alzheimer's Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer's Association to update and unify the 2011 guidelines. This unifying update is labeled a "research framework" because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer's Association Research Framework, Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

IntroductionIdentifying at what point atrophy rates first change in Alzheimer's disease is important for informing design of presymptomatic trials.MethodsSerial T1-weighted magnetic resonance imaging scans of 94 participants (28 noncarriers, 66 carriers) from the Dominantly Inherited Alzheimer Network were used to measure brain, ventricular, and hippocampal atrophy rates. For each structure, nonlinear mixed-effects models estimated the change-points when atrophy rates deviate from normal and the rates of change before and after this point.ResultsAtrophy increased after the change-point, which occurred 1-1.5 years (assuming a single step change in atrophy rate) or 3-8 years (assuming gradual acceleration of atrophy) before expected symptom onset. At expected symptom onset, estimated atrophy rates were at least 3.6 times than those before the change-point.DiscussionAtrophy rates are pathologically increased up to seven years before "expected onset". During this period, atrophy rates may be useful for inclusion and tracking of disease progression.

ImportanceCerebral amyloid-β aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials.ObjectiveTo investigate whether amyloid-β aggregation is associated with cognitive functioning in persons without dementia.Design, setting, and participantsThis cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017.Main outcomes and measuresGlobal cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score ≤27 or memory z score≤-1.28) and to assess whether this association was moderated by age, sex, educational level, or apolipoprotein E genotype.ResultsAmong 2908 persons with normal cognition (mean [SD] age, 67.4 [12.8] years), amyloid positivity was associated with low memory scores after age 70 years (mean difference in amyloid positive vs negative, 4% [95% CI, 0%-7%] at 72 years and 21% [95% CI, 10%-33%] at 90 years) but was not associated with low MMSE scores (mean difference, 3% [95% CI, -1% to 6%], P = .16). Among 4133 patients with MCI (mean [SD] age, 70.2 [8.5] years), amyloid positivity was associated with low memory (mean difference, 16% [95% CI, 12%-20%], P

See O'Sullivan and Vann (doi:10.1093/aww166) for a scientific commentary on this article.About 15% of patients clinically diagnosed with Alzheimer's disease do not show high tracer retention on amyloid positon emission tomography imaging. The present study investigates clinical and demographic features, patterns of brain atrophy and hypometabolism and longitudinal clinical trajectories of these patients. Forty amyloid-negative patients carrying a pre-scan diagnosis of Alzheimer's disease dementia from four centres were included (11/29 females/males; mean age = 67 ± 9). Detailed clinical histories, including the clinical diagnoses before and after the amyloid scan and at follow-up, were collected. Patients were classified according to their pre-scan clinical phenotype as amnestic (memory predominant), non-amnestic (predominant language, visuospatial or frontal symptoms), or non-specific (diffuse cognitive deficits). Demographic, clinical, neuropsychological, magnetic resonance imaging and (18)F-fluorodeoxyglucose positon emission tomography data were compared to 27 amyloid-positive typical Alzheimer's disease cases (14/13 females/males; mean age = 71 ± 10) and 29 amyloid-negative controls (15/14 females/males; mean age = 69 ± 12) matched for age, gender and education. There were 21 amnestic, 12 non-amnestic, and seven non-specific amyloid-negative Alzheimer's disease cases. Amyloid-negative subgroups did not differ in age, gender or education. After the amyloid scan, clinicians altered the diagnosis in 68% of amyloid-negative patients including 48% of amnestic versus 94% of non-amnestic and non-specific cases. Amnestic amyloid-negative cases were most often reclassified as frontotemporal dementia, non-amnestic as frontotemporal dementia or corticobasal degeneration, and non-specific as dementia with Lewy bodies or unknown diagnosis. The longer-term clinical follow-up was consistent with the post-scan diagnosis in most cases (90%), including in amnestic amyloid-negative cases whose post-positon emission tomography diagnosis remained Alzheimer's disease. While the non-amnestic and non-specific amyloid-negative cases usually showed patterns of atrophy and hypometabolism suggestive of another degenerative disorder, the amnestic amyloid-negative cases had subtle atrophy and hypometabolism, restricted to the retrosplenial/posterior cingulate cortex. Patients with a negative amyloid positon emission tomography scan following an initial clinical diagnosis of Alzheimer's disease have heterogeneous clinical presentations and neuroimaging profiles; a majority showed a clinical progression that was consistent with a neurodegenerative condition. In contrast, in the subgroup of amnestic amyloid-negative cases, the clinical presentation and follow-up usually remained consistent with Alzheimer's disease. An alternative diagnosis was not made in about half of the amnestic amyloid-negative cases, highlighting the need for a clinical framework and terminology to define these patients, who may have underlying limbic-predominant, non-amyloid-related pathologies.