Challenges in the practical implementation of blood biomarkers for Alzheimer's disease.

Blood biomarkers have emerged as accessible, cost-effective, and highly promising tools for advancing the diagnostics of Alzheimer's disease. However, transitioning from cerebrospinal fluid biomarkers to blood biomarkers-eg, to verify amyloid ß pathology-requires careful consideration. This Series paper highlights the main challenges in the implementation of blood biomarkers for Alzheimer's disease in different possible contexts of use. Despite the robustness of measuring blood biomarker concentrations, the widespread adoption of blood biomarkers requires rigorous standardisation efforts to address inherent challenges in diverse contexts of use. The challenges include understanding the effect of pre-analytical and analytical conditions, potential confounding factors, and comorbidities that could influence outcomes of blood biomarkers and their use in diverse populations. Additionally, distinct scenarios present their own specific challenges. In memory clinics, the successful integration of blood biomarkers in diagnostic tests will require well-established diagnostic accuracy and comprehensive assessments of the effect of blood biomarkers on the diagnostic confidence and patient management of clinicians. In primary care settings, and even more when implemented in population-based screening programmes for which no experience with any biomarkers for Alzheimer's disease currently exists, the implementation of blood biomarkers will be challenged by the need for education of primary care clinical staff and clear guidelines. However, despite the challenges, blood biomarkers hold great promise for substantially enhancing the diagnostic accuracy and effectively streamlining referral processes, leading to earlier diagnosis and access to treatments. The ongoing efforts that are shaping the integration of blood biomarkers across diverse clinical settings pave the way towards precision medicine in Alzheimer's disease.

REAL AD-Validation of a realistic screening approach for early Alzheimer's disease.

Early diagnosis is crucial to treatment success. This is especially relevant for Alzheimer's disease (AD), with its protracted preclinical phase. Most health care systems do not have the resources to conduct large-scale AD screenings in middle-aged individuals in need of novel AD treatment options and early, accurate diagnosis. Recent developments in blood-based biomarkers and remote cognitive testing offer novel, cost-effective, and scalable methods to detect cognitive and biomarker changes that may indicate early AD. In research cohorts, promising results have been reported, but these modalities have not been validated in population-based settings. The validation of a realistic screening approach for early Alzheimer's disease (REAL AD) study aims to validate the diagnostic and prognostic performance of the combined use of blood-based biomarkers and remote cognitive testing as a screening approach for early AD employing an existing health care infrastructure (the Swedish Västra Götaland Region Primary Healthcare). REAL AD aims to provide a concrete, individualized diagnostic framework, which could significantly improve AD prognosis. HIGHLIGHTS: In Sweden, most Alzheimer's disease (AD) diagnoses are made in primary care, where access to AD biomarkers is almost non-existent. Most health care systems have limited resources for the screening of middle-aged adults for early evidence of AD pathology. Blood-based biomarkers and remote cognitive testing offer novel, cost-effective, and scalable methods for detecting cognitive and biomarker changes that may indicate early AD. The REAL AD study aims to validate the diagnostic and prognostic performance of blood-based biomarkers and remote cognitive testing as a screening approach for early AD in an existing primary health care infrastructure in the Västra Götaland Region in Sweden. Studies such as REAL AD will play a vital role in helping to move the field toward concrete implementation of biomarkers in AD diagnostic workup at all care levels, eventually providing more comprehensive treatments options for the large and growing AD population, and for those at risk.

The Early Perfusion Image Is Useful to Support the Visual Interpretation of Brain Amyloid-PET With 18F-Flutemetamol in Borderline Cases.

PURPOSE: Visual interpretation of brain amyloid-ß (Aß) PET can be difficult in individuals with borderline Aß burden. Coregistration with individual MRI is recommended in these cases, which, however, is not always available. This study evaluated coregistration with the early perfusion frames acquired immediately after tracer injection to support the visual interpretation of the late Aß-frames in PET with 18F-flutemetamol (FMM). PATIENTS AND METHODS: Fifty dual-time-window FMM-PET scans of cognitively normal subjects with 0 to 60 Centiloids were included retrospectively (70.1 ± 6.9 years, 56% female, MMSE score 28.9 ± 1.3, 42% APOE ɛ4 carrier). Regional Aß load was scored with respect to a 6-point Likert scale by 3 independent raters in the 10 regions of interest recommended for FMM reading using 3 different settings: Aß image only, Aß image coregistered with MRI, and Aß image coregistered with the perfusion image. The impact of setting, within- and between-readers variability, region of interest, and Aß-status was tested by repeated-measure analysis of variance of the Likert score. RESULTS: The Centiloid scale ranged between 2 and 52 (interquartile range, 7-19). Support of visual scoring by the perfusion image resulted in the best discrimination between Aß-positive and Aß-negative cases, mainly by improved certainty of excluding Aß plaques in Aß-negative cases (P = 0.030). It also resulted in significantly higher between-rater agreement. The setting effect was most pronounced in the frontal lobe and in the posterior cingulate cortex/precuneus area (P = 0.005). CONCLUSIONS: The early perfusion image is a suitable alternative to T1-weighted MRI to support the visual interpretation of the late Aß image in FMM-PET.

Influence of Different Diagnostic Criteria on Alzheimer Disease Clinical Research.

BACKGROUND AND OBJECTIVES: Updates in Alzheimer disease (AD) diagnostic guidelines by the National Institute on Aging-Alzheimer's Association (NIA-AA) and the International Working Group (IWG) over the past 11 years may affect clinical diagnoses. We assessed how these guidelines affect clinical AD diagnosis in a cohort of cognitively unimpaired (CU) and cognitively impaired (CI) individuals. METHODS: We applied clinical and biomarker data in algorithms to classify individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort according to the following diagnostic guidelines for AD: 2011 NIA-AA, 2016 IWG-2, 2018 NIA-AA, and 2021 IWG-3, assigning the following generic diagnostic labels: (1) not AD (nAD), (2) increased risk of developing AD (irAD), and (3) AD. Diagnostic labels were compared according to their frequency, convergence across guidelines, biomarker profiles, and prognostic value. We also evaluated the diagnostic discordance among the criteria. RESULTS: A total of 1,195 individuals (mean age 73.2 ± 7.2 years, mean education 16.1 ± 2.7, 44.0% female) presented different repartitions of diagnostic labels according to the 2011 NIA-AA (nAD = 37.8%, irAD = 23.0%, AD = 39.2%), 2016 IWG-2 (nAD = 37.7%, irAD = 28.7%, AD = 33.6%), 2018 NIA-AA (nAD = 40.7%, irAD = 9.3%, AD = 50.0%), and 2021 IWG-3 (nAD = 51.2%, irAD = 8.4%, AD = 48.3%) frameworks. Discordant diagnoses across all guidelines were found in 512 participants (42.8%) (138 [91.4%] occurring in only ß-amyloid [CU 65.4%, CI 34.6%] and 191 [78.6%] in only tau-positive [CU 71.7%, CI 28.3%] individuals). Differences in predicting cognitive impairment between nAD and irAD groups were observed with the 2011 NIA-AA (hazard ratio [HR] 2.21, 95% CI 1.34-3.65, p = 0.002), 2016 IWG-2 (HR 2.81, 95% CI 1.59-4.96, p < 0.000), and 2021 IWG-3 (HR 3.61, 95% CI 2.09-6.23, p < 0.000), but not with 2018 NIA-AA (HR 1.69, 95% CI 0.87-3.28, p = 0.115). DISCUSSION: Over 42% of the studied population presented discordant diagnoses when using the different examined AD criteria, mostly in individuals with a single positive biomarker. Except for 2018 NIA-AA, all guidelines identified asymptomatic individuals at risk of cognitive impairment. Our findings highlight important differences between the guidelines, emphasizing the necessity for updated criteria with enhanced staging metrics, considering clinical, research, therapeutic, and trial design aspects.

Advancing Tau PET Quantification in Alzheimer Disease with Machine Learning: Introducing THETA, a Novel Tau Summary Measure.

Alzheimer disease (AD) exhibits spatially heterogeneous 3- or 4-repeat tau deposition across participants. Our overall goal was to develop an automated method to quantify the heterogeneous burden of tau deposition into a single number that would be clinically useful. Methods: We used tau PET scans from 3 independent cohorts: the Mayo Clinic Study of Aging and Alzheimer's Disease Research Center (Mayo, n = 1,290), the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 831), and the Open Access Series of Imaging Studies (OASIS-3, n = 430). A machine learning binary classification model was trained on Mayo data and validated on ADNI and OASIS-3 with the goal of predicting visual tau positivity (as determined by 3 raters following Food and Drug Administration criteria for 18F-flortaucipir). The machine learning model used region-specific SUV ratios scaled to cerebellar crus uptake. We estimated feature contributions based on an artificial intelligence-explainable method (Shapley additive explanations) and formulated a global tau summary measure, Tau Heterogeneity Evaluation in Alzheimer's Disease (THETA) score, using SUV ratios and Shapley additive explanations for each participant. We compared the performance of THETA with that of commonly used meta-regions of interest (ROIs) using the Mini-Mental State Examination, the Clinical Dementia Rating-Sum of Boxes, clinical diagnosis, and histopathologic staging. Results: The model achieved a balanced accuracy of 95% on the Mayo test set and at least 87% on the validation sets. It classified tau-positive and -negative participants with an AUC of 1.00, 0.96, and 0.94 on the Mayo, ADNI, and OASIS-3 cohorts, respectively. Across all cohorts, THETA showed a better correlation with the Mini-Mental State Examination and the Clinical Dementia Rating-Sum of Boxes (ρ ≥ 0.45, P < 0.05) than did meta-ROIs (ρ < 0.44, P < 0.05) and discriminated between participants who were cognitively unimpaired and those who had mild cognitive impairment with an effect size of 10.09, compared with an effect size of 3.08 for meta-ROIs. Conclusion: Our proposed approach identifies positive tau PET scans and provides a quantitative summary measure, THETA, that effectively captures heterogeneous tau deposition observed in AD. The application of THETA for quantifying tau PET in AD exhibits great potential.

Scenarios for the long-term efficacy of amyloid-targeting therapies in the context of the natural history of Alzheimer's disease.

INTRODUCTION: Recent clinical trials of amyloid beta (Aß)-targeting therapies in Alzheimer's disease (AD) have demonstrated a clinical benefit over 18 months, but their long-term impact on disease trajectory is not yet understood. We propose a framework for evaluating realistic long-term scenarios. METHODS: Results from recent phase 3 trials of Aß-targeting antibodies were integrated with an estimate of the long-term patient-level natural history trajectory of the Clinical Dementia Rating-Sum of Boxes (CDR-SB) score to explore realistic long-term efficacy scenarios. RESULTS: Three distinct long-term efficacy scenarios were examined, ranging from conservative to optimistic. These extrapolations of positive phase 3 trials suggested treatments delayed onset of severe dementia by 0.3 to 0.6 years (conservative), 1.1 to 1.9 years (intermediate), and 2.0 to 4.2 years (optimistic). DISCUSSION: Our study provides a common language for long-term impact of disease-modifying treatments. Our work calls for studies with longer follow-up and results from early intervention trials to provide a comprehensive assessment of these therapies' true long-term impact. HIGHLIGHTS: We present long-term scenarios of the efficacy of AD therapies. In this framework, scenarios are defined relative to the natural history of AD. Long-term projections with different levels of optimism can be compared. It provides a common language for expressing beliefs about long-term efficacy.

Assessing CT-based Volumetric Analysis via Transfer Learning with MRI and Manual Labels for Idiopathic Normal Pressure Hydrocephalus.

Background: Brain computed tomography (CT) is an accessible and commonly utilized technique for assessing brain structure. In cases of idiopathic normal pressure hydrocephalus (iNPH), the presence of ventriculomegaly is often neuroradiologically evaluated by visual rating and manually measuring each image. Previously, we have developed and tested a deep-learning-model that utilizes transfer learning from magnetic resonance imaging (MRI) for CT-based intracranial tissue segmentation. Accordingly, herein we aimed to enhance the segmentation of ventricular cerebrospinal fluid (VCSF) in brain CT scans and assess the performance of automated brain CT volumetrics in iNPH patient diagnostics. Methods: The development of the model used a two-stage approach. Initially, a 2D U-Net model was trained to predict VCSF segmentations from CT scans, using paired MR-VCSF labels from healthy controls. This model was subsequently refined by incorporating manually segmented lateral CT-VCSF labels from iNPH patients, building on the features learned from the initial U-Net model. The training dataset included 734 CT datasets from healthy controls paired with T1-weighted MRI scans from the Gothenburg H70 Birth Cohort Studies and 62 CT scans from iNPH patients at Uppsala University Hospital. To validate the model's performance across diverse patient populations, external clinical images including scans of 11 iNPH patients from the Universitatsmedizin Rostock, Germany, and 30 iNPH patients from the University of Alabama at Birmingham, United States were used. Further, we obtained three CT-based volumetric measures (CTVMs) related to iNPH. Results: Our analyses demonstrated strong volumetric correlations (ϱ=0.91, p<0.001) between automatically and manually derived CT-VCSF measurements in iNPH patients. The CTVMs exhibited high accuracy in differentiating iNPH patients from controls in external clinical datasets with an AUC of 0.97 and in the Uppsala University Hospital datasets with an AUC of 0.99. Discussion: CTVMs derived through deep learning, show potential for assessing and quantifying morphological features in hydrocephalus. Critically, these measures performed comparably to gold-standard neuroradiology assessments in distinguishing iNPH from healthy controls, even in the presence of intraventricular shunt catheters. Accordingly, such an approach may serve to improve the radiological evaluation of iNPH diagnosis/monitoring (i.e., treatment responses). Since CT is much more widely available than MRI, our results have considerable clinical impact.

Amyloid-PET imaging predicts functional decline in clinically normal individuals.

BACKGROUND: There is good evidence that elevated amyloid-ß (Aß) positron emission tomography (PET) signal is associated with cognitive decline in clinically normal (CN) individuals. However, it is less well established whether there is an association between the Aß burden and decline in daily living activities in this population. Moreover, Aß-PET Centiloids (CL) thresholds that can optimally predict functional decline have not yet been established. METHODS: Cross-sectional and longitudinal analyses over a mean three-year timeframe were performed on the European amyloid-PET imaging AMYPAD-PNHS dataset that phenotypes 1260 individuals, including 1032 CN individuals and 228 participants with questionable functional impairment. Amyloid-PET was assessed continuously on the Centiloid (CL) scale and using Aß groups (CL < 12 = Aß-, 12 ≤ CL ≤ 50 = Aß-intermediate/Aß± , CL > 50 = Aß+). Functional abilities were longitudinally assessed using the Clinical Dementia Rating (Global-CDR, CDR-SOB) and the Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). The Global-CDR was available for the 1260 participants at baseline, while baseline CDR-SOB and A-IADL-Q scores and longitudinal functional data were available for different subsamples that had similar characteristics to those of the entire sample. RESULTS: Participants included 765 Aß- (61%, Mdnage = 66.0, IQRage = 61.0-71.0; 59% women), 301 Aß± (24%; Mdnage = 69.0, IQRage = 64.0-75.0; 53% women) and 194 Aß+ individuals (15%, Mdnage = 73.0, IQRage = 68.0-78.0; 53% women). Cross-sectionally, CL values were associated with CDR outcomes. Longitudinally, baseline CL values predicted prospective changes in the CDR-SOB (bCL*Time = 0.001/CL/year, 95% CI [0.0005,0.0024], p = .003) and A-IADL-Q (bCL*Time = -0.010/CL/year, 95% CI [-0.016,-0.004], p = .002) scores in initially CN participants. Increased clinical progression (Global-CDR > 0) was mainly observed in Aß+ CN individuals (HRAß+ vs Aß- = 2.55, 95% CI [1.16,5.60], p = .020). Optimal thresholds for predicting decline were found at 41 CL using the CDR-SOB (bAß+ vs Aß- = 0.137/year, 95% CI [0.069,0.206], p < .001) and 28 CL using the A-IADL-Q (bAß+ vs Aß- = -0.693/year, 95% CI [-1.179,-0.208], p = .005). CONCLUSIONS: Amyloid-PET quantification supports the identification of CN individuals at risk of functional decline. TRIAL REGISTRATION: The AMYPAD PNHS is registered at www.clinicaltrialsregister.eu with the EudraCT Number: 2018-002277-22.

Chemical signatures delineate heterogeneous amyloid plaque populations across the Alzheimer's disease spectrum.

Amyloid plaque deposition is recognized as the primary pathological hallmark of Alzheimer's disease(AD) that precedes other pathological events and cognitive symptoms. Plaque pathology represents itself with an immense polymorphic variety comprising plaques with different stages of amyloid fibrillization ranging from diffuse to fibrillar, mature plaques. The association of polymorphic Aß plaque pathology with AD pathogenesis, clinical symptoms and disease progression remains unclear. Advanced chemical imaging tools, such as functional amyloid microscopy combined with MALDI mass spectrometry imaging (MSI), are now enhanced by deep learning algorithms. This integration allows for precise delineation of polymorphic plaque structures and detailed identification of their associated Aß compositions. We here set out to make use of these tools to interrogate heterogenic plaque types and their associated biochemical architecture. Our findings reveal distinct Aß signatures that differentiate diffuse plaques from fibrilized ones, with the latter showing substantially higher levels of Aßx-40. Notably, within the fibrilized category, we identified a distinct subtype known as coarse-grain plaques. Both in sAD and fAD brain tissue, coarse grain plaques contained more Aßx-40 and less Aßx-42 compared with cored plaques. The coarse grain plaques in both sAD and fAD also showed higher levels of neuritic content including paired helical filaments (PHF-1)/phosphorylated phospho Tau-immunopositive neurites. Finally, the Aß peptide content in coarse grain plaques resembled that of vascular Aß deposits (CAA) though with relatively higher levels of Aß1-42 and pyroglutamated Aßx-40 and Aßx-42 species in coarse grain plaques. This is the first of its kind study on spatial in situ biochemical characterization of different plaque morphotypes demonstrating the potential of the correlative imaging techniques used that further increase the understanding of heterogeneous AD pathology. Linking the biochemical characteristics of amyloid plaque polymorphisms with various AD etiologies and toxicity mechanisms is crucial. Understanding the connection between plaque structure and disease pathogenesis can enhance our insights. This knowledge is particularly valuable for developing and advancing novel, amyloid-targeting therapeutics.

Plasma p-tau217 predicts cognitive impairments up to ten years before onset in normal older adults.

Importance: Positron emission tomography (PET) biomarkers are the gold standard for detection of Alzheimer amyloid and tau in vivo . Such imaging can identify cognitively unimpaired (CU) individuals who will subsequently develop cognitive impartment (CI). Plasma biomarkers would be more practical than PET or even cerebrospinal fluid (CSF) assays in clinical settings. Objective: Assess the prognostic accuracy of plasma p-tau217 in comparison to CSF and PET biomarkers for predicting the clinical progression from CU to CI. Design: In a cohort of elderly at high risk of developing Alzheimer's dementia (AD), we measured the proportion of CU individuals who developed CI, as predicted by Aß (A+) and/or tau (T+) biomarker assessment from plasma, CSF, and PET. Results from each method were compared with (A-T-) reference individuals. Data were analyzed from June 2023 to April 2024. Setting: Longitudinal observational cohort. Participants: Some 228 participants from the PREVENT-AD cohort were CU at the time of biomarker assessment and had 1 - 10 years of follow-up. Plasma was available from 215 participants, CSF from 159, and amyloid- and tau-PET from 155. Ninety-three participants had assessment using all three methods (main group of interest). Progression to CI was determined by clinical consensus among physicians and neuropsychologists who were blind to plasma, CSF, PET, and MRI findings, as well as APOE genotype. Exposures: Plasma Aß 42/40 was measured using IP-MS; CSF Aß 42/40 using Lumipulse; plasma and CSF p-tau217 using UGOT assay. Aß-PET employed the 18 F-NAV4694 ligand, and tau-PET used 18 F-flortaucipir. Main Outcome: Prognostic accuracy of plasma, CSF, and PET biomarkers for predicting the development of CI in CU individuals. Results: Cox proportional hazard models indicated a greater progression rate in all A+T+ groups compared to A-T-groups (HR = 6.61 [95% CI = 2.06 - 21.17] for plasma, 3.62 [1.49 - 8.81] for CSF and 9.24 [2.34 - 36.43] for PET). The A-T+ groups were small, but also characterized with individuals who developed CI. Plasma biomarkers identified about five times more T+ than PET. Conclusion and relevance: Plasma p-tau217 assessment is a practical method for identification of persons who will develop cognitive impairment up to 10 years later. Key Points: Question: Can plasma p-tau217 serve as a prognostic indicator for identifying cognitively unimpaired (CU) individuals at risk of developing cognitive impairments (CI)?Findings: In a longitudinal cohort of CU individuals with a family history of sporadic AD, almost all individuals with abnormal plasma p-tau217 concentrations developed CI within 10 years, regardless of plasma amyloid levels. Similar findings were obtained with CSF p-tau217 and tau-PET. Fluid p-tau217 biomarkers had the main advantage over PET of identifying five times more participants with elevated tau.Meaning: Elevated plasma p-tau217 levels in CU individuals strongly indicate future clinical progression.

Investigating reliable amyloid accumulation in Centiloids: Results from the AMYPAD Prognostic and Natural History Study.

INTRODUCTION: To support clinical trial designs focused on early interventions, our study determined reliable early amyloid-ß (Aß) accumulation based on Centiloids (CL) in pre-dementia populations. METHODS: A total of 1032 participants from the Amyloid Imaging to Prevent Alzheimer's Disease-Prognostic and Natural History Study (AMYPAD-PNHS) and Insight46 who underwent [18F]flutemetamol, [18F]florbetaben or [18F]florbetapir amyloid-PET were included. A normative strategy was used to define reliable accumulation by estimating the 95th percentile of longitudinal measurements in sub-populations (NPNHS = 101/750, NInsight46 = 35/382) expected to remain stable over time. The baseline CL threshold that optimally predicts future accumulation was investigated using precision-recall analyses. Accumulation rates were examined using linear mixed-effect models. RESULTS: Reliable accumulation in the PNHS was estimated to occur at >3.0 CL/year. Baseline CL of 16 [12,19] best predicted future Aß-accumulators. Rates of amyloid accumulation were tracer-independent, lower for APOE ε4 non-carriers, and for subjects with higher levels of education. DISCUSSION: Our results support a 12-20 CL window for inclusion into early secondary prevention studies. Reliable accumulation definition warrants further investigations.

Partial volume correction in longitudinal tau PET studies: is it really needed?

BACKGROUND: [18F]flortaucipir (FTP) tau PET quantification is known to be affected by non-specific binding in off-target regions. Although partial volume correction (PVC) techniques partially account for this effect, their inclusion may also introduce noise and variability into the quantification process. While the impact of these effects has been studied in cross-sectional designs, the benefits and drawbacks of PVC on longitudinal FTP studies is still under scrutiny. The aim of this work was to study the performance of the most common PVC techniques for longitudinal FTP imaging. METHODS: A cohort of 247 individuals from the Alzheimer's Disease Neuroimaging Initiative with concurrent baseline FTP-PET, amyloid-beta (Aß) PET and structural MRI, as well as with follow-up FTP-PET and MRI were included in the study. FTP-PET scans were corrected for partial volume effects using Meltzer's, a simple and popular analytical PVC, and both the region-based voxel-wise (RBV) and the iterative Yang (iY) corrections. FTP SUVR values and their longitudinal rates of change were calculated for regions of interest (ROI) corresponding to Braak Areas I-VI, for a temporal meta-ROI and for regions typically displaying off-target FTP binding (caudate, putamen, pallidum, thalamus, choroid plexus, hemispheric white matter, cerebellar white matter, and cerebrospinal fluid). The longitudinal correlation between binding in off-target and target ROIs was analysed for the different PVCs. Additionally, group differences in longitudinal FTP SUVR rates of change between Aß-negative (A-) and Aß-positive (A+), and between cognitively unimpaired (CU) and cognitively impaired (CI) individuals, were studied. Finally, we compared the ability of different partial-volume-corrected baseline FTP SUVRs to predict longitudinal brain atrophy and cognitive decline. RESULTS: Among off-target ROIs, hemispheric white matter showed the highest correlation with longitudinal FTP SUVR rates from cortical target ROIs (R2=0.28-0.82), with CSF coming in second (R2=0.28-0.42). Application of voxel-wise PVC techniques minimized this correlation, with RBV performing best (R2=0.00-0.07 for hemispheric white matter). PVC also increased group differences between CU and CI individuals in FTP SUVR rates of change across all target regions, with RBV again performing best (No PVC: Cohen's d = 0.26-0.66; RBV: Cohen's d = 0.43-0.74). These improvements were not observed for differentiating A- from A+ groups. Additionally, voxel-wise PVC techniques strengthened the correlation between baseline FTP SUVR and longitudinal grey matter atrophy and cognitive decline. CONCLUSION: Quantification of longitudinal FTP SUVR rates of change is affected by signal from off-target regions, especially the hemispheric white matter and the CSF. Voxel-wise PVC techniques significantly reduce this effect. PVC provided a significant but modest benefit for tasks involving the measurement of group-level longitudinal differences. These findings are particularly relevant for the estimations of sample sizes and analysis methodologies of longitudinal group studies.

Elevated CSF GAP-43 is associated with accelerated tau accumulation and spread in Alzheimer's disease.

In Alzheimer's disease, amyloid-beta (Aß) triggers the trans-synaptic spread of tau pathology, and aberrant synaptic activity has been shown to promote tau spreading. Aß induces aberrant synaptic activity, manifesting in increases in the presynaptic growth-associated protein 43 (GAP-43), which is closely involved in synaptic activity and plasticity. We therefore tested whether Aß-related GAP-43 increases, as a marker of synaptic changes, drive tau spreading in 93 patients across the aging and Alzheimer's spectrum with available CSF GAP-43, amyloid-PET and longitudinal tau-PET assessments. We found that (1) higher GAP-43 was associated with faster Aß-related tau accumulation, specifically in brain regions connected closest to subject-specific tau epicenters and (2) that higher GAP-43 strengthened the association between Aß and connectivity-associated tau spread. This suggests that GAP-43-related synaptic changes are linked to faster Aß-related tau spread across connected regions and that synapses could be key targets for preventing tau spreading in Alzheimer's disease.

Impact of simulated reduced injected dose on the assessment of amyloid PET scans.

PURPOSE: To investigate the impact of reduced injected doses on the quantitative and qualitative assessment of the amyloid PET tracers [18F]flutemetamol and [18F]florbetaben. METHODS: Cognitively impaired and unimpaired individuals (N = 250, 36% Aß-positive) were included and injected with [18F]flutemetamol (N = 175) or [18F]florbetaben (N = 75). PET scans were acquired in list-mode (90-110 min post-injection) and reduced-dose images were simulated to generate images of 75, 50, 25, 12.5 and 5% of the original injected dose. Images were reconstructed using vendor-provided reconstruction tools and visually assessed for Aß-pathology. SUVRs were calculated for a global cortical and three smaller regions using a cerebellar cortex reference tissue, and Centiloid was computed. Absolute and percentage differences in SUVR and CL were calculated between dose levels, and the ability to discriminate between Aß- and Aß + scans was evaluated using ROC analyses. Finally, intra-reader agreement between the reduced dose and 100% images was evaluated. RESULTS: At 5% injected dose, change in SUVR was 3.72% and 3.12%, with absolute change in Centiloid 3.35CL and 4.62CL, for [18F]flutemetamol and [18F]florbetaben, respectively. At 12.5% injected dose, percentage change in SUVR and absolute change in Centiloid were < 1.5%. AUCs for discriminating Aß- from Aß + scans were high (AUC ≥ 0.94) across dose levels, and visual assessment showed intra-reader agreement of > 80% for both tracers. CONCLUSION: This proof-of-concept study showed that for both [18F]flutemetamol and [18F]florbetaben, adequate quantitative and qualitative assessments can be obtained at 12.5% of the original injected dose. However, decisions to reduce the injected dose should be made considering the specific clinical or research circumstances.

COVID-19 Recovery: Consistent Absence of Cerebrospinal Fluid Biomarker Abnormalities in Patients With Neurocognitive Post-COVID Complications.

BACKGROUND: To investigate evidence of residual viral infection, intrathecal immune activation, central nervous system (CNS) injury, and humoral responses in cerebrospinal fluid (CSF) and plasma in patients recovering from coronavirus disease 2019 (COVID-19), with or without neurocognitive post-COVID condition (PCC). METHODS: Thirty-one participants (25 with neurocognitive PCC) underwent clinical examination, lumbar puncture, and venipuncture ≥3 months after COVID-19 symptom onset. Healthy volunteers were included. CSF and plasma severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid and spike antigen (N-Ag, S-Ag), and CSF biomarkers of immune activation and neuronal injury were analyzed. RESULTS: SARS-CoV-2 N-Ag or S-Ag were undetectable in all samples and no participant had pleocytosis. We detected no significant differences in CSF and plasma cytokine concentrations, albumin ratio, IgG index, neopterin, ß2M, or in CSF biomarkers of neuronal injury and astrocytic damage. Furthermore, principal component analysis (PCA1) analysis did not indicate any significant differences between the study groups in the marker sets cytokines, neuronal markers, or anti-cytokine autoantibodies. CONCLUSIONS: We found no evidence of ongoing viral replication, immune activation, or CNS injury in plasma or CSF in patients with neurocognitive PCC compared with COVID-19 controls or healthy volunteers, suggesting that neurocognitive PCC is a consequence of events suffered during acute COVID-19 rather than persistent viral CNS infection or residual CNS inflammation.

Demographically adjusted Rey-Osterrieth Complex Figure Test norms in a Swedish and Norwegian cohort aged 49-77 years and comparison with North American norms.

INTRODUCTION: The Rey-Osterrieth Complex Figure Test (RCFT) is one of the most commonly used neuropsychological tests in Sweden and Norway. However, no publications provide normative data for this population. The objective of this study was to present demographically adjusted norms for a Swedish and Norwegian population and to evaluate these in an independent comparison group. METHODS: The RCFT was administrated to 344 healthy controls recruited from the Swedish Gothenburg MCI study, the Norwegian Dementia Disease Initiation study, and the Swedish Cardiopulmonary Bioimage Study. Age ranged from 49 to 77 years (mean = 62.4 years, SD = 5.0 years), and education ranged from 6 to 24 years (mean = 13.3 years, SD = 3.0 years). Using a regression-based procedure, we investigated the effects of age, sex, and years of education on test performance. We compared and evaluated our Swedish and Norwegian norms with North American norms in an independent comparison group of 145 individuals. RESULTS: In healthy controls, age and education were associated with performance on the RCFT. When comparing normative RCFT performance in an independent comparison group, North American norms generally overestimated immediate and delayed recall performance. In contrast, our Swedish and Norwegian norms appear to better take into account factors of age and education. CONCLUSIONS: We presented demographically adjusted norms for the RCFT in a Swedish and Norwegian sample. This is the first normative study of the RCFT that presents normative data for this population. In addition, we showed that North American norms might produce inaccurate normative estimations in an independent comparison group.

CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration.

INTRODUCTION: Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that produced accurate and robust cranial CT tissue classification. MATERIALS AND METHODS: We analyzed 917 CT and 744 magnetic resonance (MR) scans from the Gothenburg H70 Birth Cohort, and 204 CT and 241 MR scans from participants of the Memory Clinic Cohort, Singapore. We tested associations between six CT-based volumetric measures (CTVMs) and existing clinical diagnoses, fluid and imaging biomarkers, and measures of cognition. RESULTS: CTVMs differentiated cognitively healthy individuals from dementia and prodromal dementia patients with high accuracy levels comparable to MR-based measures. CTVMs were significantly associated with measures of cognition and biochemical markers of neurodegeneration. DISCUSSION: These findings suggest the potential future use of CT-based volumetric measures as an informative first-line examination tool for neurodegenerative disease diagnostics after further validation. HIGHLIGHTS: Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.

Recruitment of pre-dementia participants: main enrollment barriers in a longitudinal amyloid-PET study.

BACKGROUND: The mismatch between the limited availability versus the high demand of participants who are in the pre-dementia phase of Alzheimer's disease (AD) is a bottleneck for clinical studies in AD. Nevertheless, potential enrollment barriers in the pre-dementia population are relatively under-reported. In a large European longitudinal biomarker study (the AMYPAD-PNHS), we investigated main enrollment barriers in individuals with no or mild symptoms recruited from research and clinical parent cohorts (PCs) of ongoing observational studies. METHODS: Logistic regression was used to predict study refusal based on sex, age, education, global cognition (MMSE), family history of dementia, and number of prior study visits. Study refusal rates and categorized enrollment barriers were compared between PCs using chi-squared tests. RESULTS: 535/1856 (28.8%) of the participants recruited from ongoing studies declined participation in the AMYPAD-PNHS. Only for participants recruited from clinical PCs (n = 243), a higher MMSE-score (ß = - 0.22, OR = 0.80, p < .05), more prior study visits (ß = - 0.93, OR = 0.40, p < .001), and positive family history of dementia (ß = 2.08, OR = 8.02, p < .01) resulted in lower odds on study refusal. General study burden was the main enrollment barrier (36.1%), followed by amyloid-PET related burden (PCresearch = 27.4%, PCclinical = 9.0%, X2 = 10.56, p = .001), and loss of research interest (PCclinical = 46.3%, PCresearch = 16.5%, X2 = 32.34, p < .001). CONCLUSIONS: The enrollment rate for the AMYPAD-PNHS was relatively high, suggesting an advantage of recruitment via ongoing studies. In this observational cohort, study burden reduction and tailored strategies may potentially improve participant enrollment into trial readiness cohorts such as for phase-3 early anti-amyloid intervention trials. The AMYPAD-PNHS (EudraCT: 2018-002277-22) was approved by the ethical review board of the VU Medical Center (VUmc) as the Sponsor site and in every affiliated site.

Advancing Tau-PET quantification in Alzheimer's disease with machine learning: introducing THETA, a novel tau summary measure.

Alzheimer's disease (AD) exhibits spatially heterogeneous 3R/4R tau pathology distributions across participants, making it a challenge to quantify extent of tau deposition. Utilizing Tau-PET from three independent cohorts, we trained and validated a machine learning model to identify visually positive Tau-PET scans from regional SUVR values and developed a novel summary measure, THETA, that accounts for heterogeneity in tau deposition. The model for identification of tau positivity achieved a balanced test accuracy of 95% and accuracy of ≥87% on the validation datasets. THETA captured heterogeneity of tau deposition, had better association with clinical measures, and corresponded better with visual assessments in comparison with the temporal meta-region-of-interest Tau-PET quantification methods. Our novel approach aids in identification of positive Tau-PET scans and provides a quantitative summary measure, THETA, that effectively captures the heterogeneous tau deposition seen in AD. The application of THETA for quantifying Tau-PET in AD exhibits great potential.