Tau-PET imaging predicts cognitive decline and brain atrophy progression in early Alzheimer's disease

Biomarker-guided decision making in clinical drug development for neurodegenerative disorders

Neurodegenerative disorders are characterized by complex neurobiological changes that are reflected in biomarker alterations detectable in blood, cerebrospinal fluid (CSF) and with brain imaging. As accessible proxies for processes that are difficult to measure, biomarkers are tools that hold increasingly important roles in drug development and clinical trial decision making. In the past few years, biomarkers have been the basis for accelerated approval of new therapies for Alzheimer disease and amyotrophic lateral sclerosis as surrogate end points reasonably likely to predict clinical benefit.Blood-based biomarkers are emerging for Alzheimer disease and other neurodegenerative disorders (for example, Parkinson disease, frontotemporal dementia), and some biomarkers may be informative across multiple disease states. Collection of CSF provides access to biomarkers not available in plasma, including markers of synaptic dysfunction and neuroinflammation. Molecular imaging is identifying an increasing array of targets, including amyloid plaques, neurofibrillary tangles, inflammation, mitochondrial dysfunction and synaptic density. In this Review, we consider how biomarkers can be implemented in clinical trials depending on their context of use, including providing information on disease risk and/or susceptibility, diagnosis, prognosis, pharmacodynamic outcomes, monitoring, prediction of response to therapy and safety. Informed choice of increasingly available biomarkers and rational deployment in clinical trials support drug development decision making and de-risk the drug development process for neurodegenerative disorders.

Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease

Identifying individuals with early-stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would enable better-informed medical, support and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. Across heterogeneous clinical phenotypes, patients with atypical AD consistently exhibit abnormal tau accumulation in the posterior nodes of the default mode network of the cerebral cortex. This evidence suggests that tau burden in this functional network could be a common imaging biomarker for prognostication across the syndromic spectrum of AD. Here, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes: Posterior Cortical Atrophy (n = 16); logopenic variant Primary Progressive Aphasia (n = 15); and amnestic syndrome with multi-domain impairment and young age of onset < 65 years (n = 17). All patients underwent MRI, tau PET and amyloid PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Atypical early AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, P < 0.001, Cohen's d = 0.95. Across clinical phenotypes, baseline tau in the default mode network was the strongest predictor of clinical decline (R2 = 0.30), outperforming a simpler model with baseline clinical impairment and demographic variables (R2 = 0.10), tau in other functional networks (R2 = 0.11-0.26) and the magnitude of cortical atrophy (R2 = 0.20) and amyloid burden (R2 = 0.09) in the default mode network. Overall, these findings point to the contribution of default mode network tau to predicting the magnitude of clinical decline in atypical early AD patients 1 year later. This simple measure could aid the development of a personalized prognostic, monitoring and treatment plan, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.

Local and distant atrophy mediate the relationship between tau pathology and cognition in temporoparietal region in Alzheimer's disease

BackgroundTau pathology is closely associated with brain atrophy and cognitive decline, but how it specifically influences local and distant gray matter volume (GMV) and cognitive function remains unclear.ObjectiveThis study aims to explore the spatial relationships between tau pathology, GMV and cognition using hybrid positron emission tomography/magnetic resonance imaging (PET/MRI).MethodsTwenty amyloid-β (Aβ)-positive Alzheimer's disease (AD) patients, 14 mild cognitive impairment (MCI) patients, and 22 Aβ-negative normal controls (NC) underwent standardized neuropsychological assessments and 18F-fortaucipir PET/MRI scans. We investigated the associations between regional tau standardized uptake value ratio (SUVR) and GMV in AD signature regions. Mediation analyses were conducted to explore the potential mediating effects of local and distant GMV in the relationship between tau pathology and cognition.ResultsThe study indicated that increased 18F-fortaucipir SUVR and decreased GMV were related to cognitive performance in MCI and AD patients. Compared to NC group, the number of brain regions with local and distant correlations between GMV and SUVR was greater in AD/MCI group. Mediation analysis revealed that GMV served as a significant mediator between tau pathology and cognition in local regions. Furthermore, distant effects were also observed, with hippocampal atrophy partially mediated the relationship between entorhinal cortex tau pathology and cognition. Meanwhile, medial parietal lobe atrophy partially mediated the relationship between medial temporal lobe tau deposition and cognition.ConclusionsOur findings provide an anatomically detailed insight into relationships between tau, GMV and cognition, especially in entorhinal cortex-hippocampus, temporal-parietal lobe cortical circuits.

Tau levels in platelets isolated from Huntington's disease patients serve as a biomarker of disease severity

Tau is a microtubule protein that is known to be hyperphosphorylated and to aggregate in several chronic neurodegenerative disorders. In many cases, in particular in Alzheimer's disease, the degree of tau pathology has been demonstrated to correlate with cognitive deficits and/or decline. In Huntington's disease (HD), a dominantly inherited neurodegenerative disorder, both cognitive impairments and abnormal tau expression have been reported to occur, along with the accumulation of the mutant huntingtin protein. In this respect, tau has been shown to be present in the cerebrospinal fluid of individuals with HD and to increase with disease progression. However, how this relates to changes in tau found in the periphery is largely unknown. In this study, we collected blood samples from patients with HD and isolated multiple blood components including plasma, platelets, and peripheral blood mononuclear cells to measure their tau levels and subsequently correlate these to cognitive impairments and disease stage. Our results suggest that the amount of tau, particularly N-terminal tau (NTA-tau) and total tau (t-tau), is elevated in all assayed blood components and that the quantity of tau within platelets, specifically, is strongly correlated with disease severity.

Subcortical tau burden correlates with regional brain atrophy and plasma markers in four-repeat tauopathy parkinsonism

Background18F-florzolotau positron emission tomography (PET) assists in the in vivo diagnosis of progressive supranuclear palsy (PSP).ObjectiveWe aimed to investigate the relationship between 18F-florzolotau uptake and clinical severity, structural volume changes, and plasma markers in four-repeat tauopathies.MethodsA total of 80 participants were recruited: 35 with PSP (11 with PSP-Richardson syndrome and 24 with PSP non-Richardson syndrome), 9 with corticobasal syndrome (CBS), 10 with Alzheimer's disease (AD), 8 with Parkinson's disease, and 18 controls. All participants underwent 18F-florzolotau PET, brain magnetic resonance imaging (MRI), and plasma biomarker investigation (total and phosphorylated tau [pTau181], neurofilament light chain, and glial fibrillary acidic protein [GFAP]).Results18F-Florzolotau uptake was significantly higher in the subcortical regions of the pallidum, subthalamic nucleus (STN), midbrain, red nucleus, and raphe nucleus in PSP patients compared to the other groups (all p < 0.01). Subcortical tau tracer retention assisted in distinguishing PSP and CBS from controls (AUC = 0.836, p < 0.001). Tau tracer retention could differentiate PSP and CBS from AD in cortical (p < 0.001) and subcortical regions (p = 0.028). The motor severity of PSP positively correlated with tau burden in STN (p = 0.044) and substantia nigra (p = 0.035). Tau tracer uptake was associated with cortical volume changes in CBS (p = 0.031), PSP non-Richardson syndrome (p = 0.003), and AD (p = 0.044). Cortical tau retention correlated with plasma levels of GFAP (p = 0.001) and pTau181 (p = 0.036).ConclusionsSubcortical 18F-Florzolotau uptake assist the diagnosis of 4R tauopathy parkinsonism. Additionally, regional tau burden contributes to structural brain volume changes and correlates with plasma levels of GFAP and pTau181.

Dynamic proportional loss of functional connectivity revealed change of left superior frontal gyrus in subjective cognitive decline: an explanatory study based on Chinese and Western cohorts

Brain network dynamics have been extensively explored in patients with subjective cognitive decline (SCD). However, these studies are susceptible to individual differences, scanning parameters, and other confounding factors. Therefore, how to reveal subtle SCD-related subtle changes remains unclear. Cross-sectional and longitudinal resting-state functional magnetic resonance imaging data from both Chinese and Western populations were analyzed. We proposed a framework of dynamic proportional loss of functional connectivity (DPLFC). After its stability was validated, the optimal parameters were applied for the clinical diagnosis of SCD. DPLFC yielded a relatively high intraclass correlation coefficient. In particular, the DPLFC of the left superior frontal gyrus (SFG) progressively decreased along the Alzheimer's disease (AD) continuum. Compared with the traditional index, the DPLFC had better classification performance between cognitively normal controls and patients with SCD. Furthermore, DPLFC was related to Aβ deposition and scale scores. Patients with lower DPLFC values had a greater risk of cognitive decline. Decreased DPLFC in the left SFG may be a potential AD-related neuroimaging biomarker at an early stage.

Greater baseline cortical atrophy in the dorsal attention network predicts faster clinical decline in Posterior Cortical Atrophy

BACKGROUND

Posterior Cortical Atrophy (PCA) is a clinical syndrome characterized by progressive visuospatial and visuoperceptual impairment. As the neurodegenerative disease progresses, patients lose independent functioning due to the worsening of initial symptoms and development of symptoms in other cognitive domains. The timeline of clinical progression is variable across patients, and the field currently lacks robust methods for prognostication. Here, evaluated the utility of MRI-based cortical atrophy as a predictor of longitudinal clinical decline in a sample of PCA patients.

METHODS

PCA patients were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit PCA Program. All patients had cortical thickness estimates from baseline MRI scans, which were used to predict longitudinal change in clinical impairment assessed by the CDR Sum-of-Boxes (CDR-SB) score. Multivariable linear regression was used to estimate the magnitude of cortical atrophy in PCA patients relative to a group of amyloid-negative cognitively unimpaired participants. Linear mixed-effects models were used to test hypotheses about the utility of baseline cortical atrophy for predicting longitudinal clinical decline.

RESULTS

Data acquired from 34 PCA patients (mean age = 65.41 ± 7.90, 71% females) and 24 controls (mean age = 67.34 ± 4.93, 50% females) were analyzed. 62% of the PCA patients were classified as having mild cognitive impairment (CDR 0.5) at baseline, with the rest having mild dementia (CDR 1). Each patient had at least one clinical follow-up, with the mean duration of 2.78 ± 1.62 years. Relative to controls, PCA patients showed prominent baseline atrophy in the posterior cortical regions, with the largest effect size observed in the visual network of the cerebral cortex. Cortical atrophy localized to the dorsal attention network, which supports higher-order visuospatial function, selectively predicted the rate of subsequent clinical decline.

CONCLUSIONS

These results demonstrate the utility of a snapshot measure of cortical atrophy of the dorsal attention network for predicting the rate of subsequent clinical decline in PCA. If replicated, this topographically-specific MRI-based biomarker could be useful as a clinical prognostication tool that facilitates personalized care planning.

Heterogeneity of cerebral atrophic rate in mild cognitive impairment and its interactive association with proteins related to microglia activity on longitudinal cognitive changes

BACKGROUND

Heterogeneity of cerebral atrophic rate commonly exists in mild cognitive impairment (MCI), which may be associated with microglia-involved neuropathology and have an influence on cognitive outcomes.

OBJECTIVE

We aim to explore the heterogeneity of cerebral atrophic rate among MCI and its association with plasma proteins related to microglia activity, with further investigation of their interaction effects on long-term cognition.

SUBJECTS

A total of 630 MCI subjects in the ADNI database were included, of which 260 subjects were available with baseline data on plasma proteins.

METHODS

Group-based multi-trajectory modeling (GBMT) was used to identify the latent classes with heterogeneous cerebral atrophic rates. Associations between latent classes and plasma proteins related to microglia activity were investigated with generalized linear models. Linear mixed effect models (LME) were implemented to explore the interaction effects between proteins related to microglia activity and identified latent classes on longitudinal cognitive changes.

RESULTS

Two latent classes were identified and labeled as the slow-atrophy class and the fast-atrophy class. Associations were found between such heterogeneity of atrophic rates and plasma proteins related to microglia activity, especially AXL receptor tyrosine kinase (AXL), CD40 antigen (CD40), and tumor necrosis factor receptor-like 2 (TNF-R2). Interaction effects on longitudinal cognitive changes showed that higher CD40 was associated with faster cognitive decline in the slow-atrophy class and higher AXL or TNF-R2 was associated with slower cognitive decline in the fast-atrophy class.

CONCLUSIONS

Heterogeneity of atrophic rates at the MCI stage is associated with several plasma proteins related to microglia activity, which show either protective or adverse effects on long-term cognition depending on the variability of atrophic rates.

SCD-Tron: Leveraging Large Clinical Language Model for Early Detection of Cognitive Decline from Electronic Health Records

Background

Early detection of cognitive decline during the preclinical stage of Alzheimer's disease is crucial for timely intervention and treatment. Clinical notes, often found in unstructured electronic health records (EHRs), contain valuable information that can aid in the early identification of cognitive decline. In this study, we utilize advanced large clinical language models, fine-tuned on clinical notes, to improve the early detection of cognitive decline.

Methods

We collected clinical notes from 2,166 patients spanning the 4 years preceding their initial mild cognitive impairment (MCI) diagnosis from the Enterprise Data Warehouse (EDW) of Mass General Brigham (MGB). To train the model, we developed SCD-Tron, a large clinical language model on 4,949 note sections labeled by experts. For evaluation, the trained model was applied to 1,996 independent note sections to assess its performance on real-world unstructured clinical data. Additionally, we used explainable AI techniques, specifically SHAP values, to interpret the models predictions and provide insight into the most influential features. Error analysis was also facilitated to further analyze the model's prediction.

Results

SCD-Tron significantly outperforms baseline models, achieving notable improvements in precision, recall, and AUC metrics for detecting Subjective Cognitive Decline (SCD). Tested on many real-world clinical notes, SCD-Tron demonstrated high sensitivity with only one false negative, crucial for clinical applications prioritizing early and accurate SCD detection. SHAP-based interpretability analysis highlighted key textual features contributing to model predictions, supporting transparency and clinician understanding.

Conclusion

SCD-Tron offers a novel approach to early cognitive decline detection by applying large clinical language models to unstructured EHR data. Pretrained on real-world clinical notes, it accurately identifies early cognitive decline and integrates SHAP for interpretability, enhancing transparency in predictions.

Greater baseline cortical atrophy in the dorsal attention network predicts faster clinical decline in Posterior Cortical Atrophy

Background and Objectives

Posterior Cortical Atrophy (PCA) is a clinical syndrome characterized by progressive visuospatial and visuoperceptual impairment. As the neurodegenerative disease progresses, patients lose independent functioning due to the worsening of initial symptoms and development of symptoms in other cognitive domains. The timeline of clinical progression is variable across patients, and the field currently lacks robust methods for prognostication. Here, evaluated the utility of MRI-based cortical atrophy as a predictor of longitudinal clinical decline in a sample of PCA patients.

Methods

PCA patients were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit PCA Program. All patients had cortical thickness estimates from baseline MRI scans, which were used to predict longitudinal change in clinical impairment assessed by the CDR Sum-of-Boxes (CDR-SB) score. Multivariable linear regression was used to estimate the magnitude of cortical atrophy in PCA patients relative to a group of amyloid-negative cognitively unimpaired participants. Linear mixed-effects models were used to test hypotheses about the utility of baseline cortical atrophy for predicting longitudinal clinical decline.

Results

Data acquired from 34 PCA patients (mean age = 65.41 ± 7.90, 71% females) and 24 controls (mean age = 67.34 ± 4.93, 50% females) were analyzed. Sixty-two percent of the PCA patients were classified as having mild cognitive impairment (CDR 0.5) at baseline, with the rest having mild dementia (CDR 1). Each patient had at least one clinical follow-up, with the mean duration of 2.78 ± 1.62 years. Relative to controls, PCA patients showed prominent baseline atrophy in the posterior cortical regions, with the largest effect size observed in the visual network of the cerebral cortex. Cortical atrophy localized to the dorsal attention network, which supports higher-order visuospatial function, selectively predicted the rate of subsequent clinical decline.

Discussion

These results demonstrate the utility of a snapshot measure of cortical atrophy of the dorsal attention network for predicting the rate of subsequent clinical decline in PCA. If replicated, this topographically-specific MRI-based biomarker could be useful as a clinical prognostication tool that facilitates personalized care planning.

Predicting regional tau accumulation with machine learning-based tau-PET and advanced radiomics

INTRODUCTION

Alzheimer's disease is partially characterized by the progressive accumulation of aggregated tau-containing neurofibrillary tangles. Although the association between accumulated tau, neurodegeneration, and cognitive decline is critical for disease understanding and clinical trial design, we still lack robust tools to predict individualized trajectories of tau accumulation. Our objective was to assess whether brain imaging biomarkers of flortaucipir-positron emission tomography (PET), in combination with clinical and genomic measures, could predict future pathological tau accumulation.

METHODS

We quantified the disease profile of participants (N = 276) using a comprehensive set of descriptors, including clinical/demographic (age, diagnosis, amyloid status, sex, race, ethnicity), genetic (apolipoprotein E [APOE]-ε4), and flortaucipir-PET imaging measures (regional flortaucipir standardized uptake value ratio [SUVr] and comprehensive radiomic texture features extracted from Automated Anatomical Labeling template regions). We trained an AdaBoost machine learning algorithm in a 2:1 split train-test configuration to derive a prognostic index that (i) stratifies individualized brain regions including global (AD-signature region) and lobar regions (frontal, occipital, parietal, temporal) into stable/slow- and fast-progressors based on future tau accumulation, and (ii) forecasts individualized regional annualized-rate-of-change in flortaucipir-PET SUVr. Further, we developed an adaptive model incorporating flortaucipir-PET measurements from the baseline and intermediate timepoints to predict annualized-rate-of-change.

RESULTS

In binary classification for predicting stable/slow- versus fast-progressors, the area-under-the-receiver-operating-characteristic curve was 0.86 in the AD-signature region and 0.83, 0.82, 0.84, and 0.83 in frontal, occipital, parietal, and temporal regions, respectively. The trained models successfully predicted annualized-rate-of-change of flortaucipir-PET regional flortaucipir SUVr in AD-signature and lobar regions (Pearson-correlation [R]: AD-signature = 0.73; frontal = 0.73; occipital = 0.71; parietal = 0.70; temporal = 0.69). The models' performance in predicting annualized-rate-of-change slightly increased when imaging features from intermediate timepoints were used in the adaptive setting (R: AD-signature = 0.79; frontal = 0.87; occipital = 0.83; parietal = 0.74; temporal = 0.82).

DISCUSSION

Taken together, our results propose a robust approach to predict future tau accumulation that may improve the ability to enroll, stratify, and gauge efficacy in clinical trial participants.

Highlights

Machine learning predicts the future rate of tau accumulation in Alzheimer's disease.Tau prediction in lobar/global regions benefits from diverse multimodal features.This prognostic index can serve as a sensitive tool for patient stratification.

Tau in neurodegenerative diseases: molecular mechanisms, biomarkers, and therapeutic strategies

The deposition of abnormal tau protein is characteristic of Alzheimer's disease (AD) and a class of neurodegenerative diseases called tauopathies. Physiologically, tau maintains an intrinsically disordered structure and plays diverse roles in neurons. Pathologically, tau undergoes abnormal post-translational modifications and forms oligomers or fibrous aggregates in tauopathies. In this review, we briefly introduce several tauopathies and discuss the mechanisms mediating tau aggregation and propagation. We also describe the toxicity of tau pathology. Finally, we explore the early diagnostic biomarkers and treatments targeting tau. Although some encouraging results have been achieved in animal experiments and preclinical studies, there is still no cure for tauopathies. More in-depth basic and clinical research on the pathogenesis of tauopathies is necessary.

Tau Positron Emission Tomography for Predicting Dementia in Individuals With Mild Cognitive Impairment

Importance

An accurate prognosis is especially pertinent in mild cognitive impairment (MCI), when individuals experience considerable uncertainty about future progression.

Objective

To evaluate the prognostic value of tau positron emission tomography (PET) to predict clinical progression from MCI to dementia.

Design, Setting, and Participants

This was a multicenter cohort study with external validation and a mean (SD) follow-up of 2.0 (1.1) years. Data were collected from centers in South Korea, Sweden, the US, and Switzerland from June 2014 to January 2024. Participant data were retrospectively collected and inclusion criteria were a baseline clinical diagnosis of MCI; longitudinal clinical follow-up; a Mini-Mental State Examination (MMSE) score greater than 22; and available tau PET, amyloid-β (Aβ) PET, and magnetic resonance imaging (MRI) scan less than 1 year from diagnosis. A total of 448 eligible individuals with MCI were included (331 in the discovery cohort and 117 in the validation cohort). None of these participants were excluded over the course of the study.

Exposures

Tau PET, Aβ PET, and MRI.

Main Outcomes and Measures

Positive results on tau PET (temporal meta-region of interest), Aβ PET (global; expressed in the standardized metric Centiloids), and MRI (Alzheimer disease [AD] signature region) was assessed using quantitative thresholds and visual reads. Clinical progression from MCI to all-cause dementia (regardless of suspected etiology) or to AD dementia (AD as suspected etiology) served as the primary outcomes. The primary analyses were receiver operating characteristics.

Results

In the discovery cohort, the mean (SD) age was 70.9 (8.5) years, 191 (58%) were male, the mean (SD) MMSE score was 27.1 (1.9), and 110 individuals with MCI (33%) converted to dementia (71 to AD dementia). Only the model with tau PET predicted all-cause dementia (area under the receiver operating characteristic curve [AUC], 0.75; 95% CI, 0.70-0.80) better than a base model including age, sex, education, and MMSE score (AUC, 0.71; 95% CI, 0.65-0.77; P = .02), while the models assessing the other neuroimaging markers did not improve prediction. In the validation cohort, tau PET replicated in predicting all-cause dementia. Compared to the base model (AUC, 0.75; 95% CI, 0.69-0.82), prediction of AD dementia in the discovery cohort was significantly improved by including tau PET (AUC, 0.84; 95% CI, 0.79-0.89; P < .001), tau PET visual read (AUC, 0.83; 95% CI, 0.78-0.88; P = .001), and Aβ PET Centiloids (AUC, 0.83; 95% CI, 0.78-0.88; P = .03). In the validation cohort, only the tau PET and the tau PET visual reads replicated in predicting AD dementia.

Conclusions and Relevance

In this study, tau-PET showed the best performance as a stand-alone marker to predict progression to dementia among individuals with MCI. This suggests that, for prognostic purposes in MCI, a tau PET scan may be the best currently available neuroimaging marker.

Vascular contributions to cognitive decline: Beyond amyloid and tau in the Harvard Aging Brain Study

In addition to amyloid and tau pathology, elevated systemic vascular risk, white matter injury, and reduced cerebral blood flow contribute to late-life cognitive decline. Given the strong collinearity among these parameters, we proposed a framework to extract the independent latent features underlying cognitive decline using the Harvard Aging Brain Study (N = 166 cognitively unimpaired older adults at baseline). We used the following measures from the baseline visit: cortical amyloid, inferior temporal cortex tau, relative cerebral blood flow, white matter hyperintensities, peak width of skeletonized mean diffusivity, and Framingham Heart Study cardiovascular disease risk. We used exploratory factor analysis to extract orthogonal factors from these variables and their interactions. These factors were used in a regression model to explain longitudinal Preclinical Alzheimer Cognitive Composite-5 (PACC) decline (follow-up = 8.5 ±2.7 years). We next examined whether gray matter volume atrophy acts as a mediator of factors and PACC decline. Latent factors of systemic vascular risk, white matter injury, and relative cerebral blood flow independently explain cognitive decline beyond amyloid and tau. Gray matter volume atrophy mediates these associations with the strongest effect on white matter injury. These results suggest that systemic vascular risk contributes to cognitive decline beyond current markers of cerebrovascular injury, amyloid, and tau.

The path to next-generation disease-modifying immunomodulatory combination therapies in Alzheimer's disease

The cautious optimism following recent anti-amyloid therapeutic trials for Alzheimer's disease (AD) provides a glimmer of hope after years of disappointment. Although these encouraging results represent discernible progress, they also highlight the need to enhance further the still modest clinical efficacy of current disease-modifying immunotherapies. Here, we highlight crucial milestones essential for advancing precision medicine in AD. These include reevaluating the choice of therapeutic targets by considering the key role of both central neuroinflammation and peripheral immunity in disease pathogenesis, refining patient stratification by further defining the inflammatory component within the forthcoming ATN(I) (amyloid, tau and neurodegeneration (and inflammation)) classification of AD biomarkers and defining more accurate clinical outcomes and prognostic biomarkers that better reflect disease heterogeneity. Next-generation immunotherapies will need to go beyond the current antibody-only approach by simultaneously targeting pathological proteins together with innate neuroinflammation and/or peripheral-central immune crosstalk. Such innovative immunomodulatory combination therapy approaches should be evaluated in appropriately redesigned clinical therapeutic trials, which must carefully integrate the neuroimmune component.

Combined in vivo MRI assessment of locus coeruleus and nucleus basalis of Meynert integrity in amnestic Alzheimer's disease, suspected-LATE and frontotemporal dementia

BACKGROUND

The locus coeruleus (LC) and the nucleus basalis of Meynert (NBM) are altered in early stages of Alzheimer's disease (AD). Little is known about LC and NBM alteration in limbic-predominant age-related TDP-43 encephalopathy (LATE) and frontotemporal dementia (FTD). The aim of the present study is to investigate in vivo LC and NBM integrity in patients with suspected-LATE, early-amnestic AD and FTD in comparison with controls.

METHODS

Seventy-two participants (23 early amnestic-AD patients, 17 suspected-LATE, 17 FTD patients, defined by a clinical-biological diagnosis reinforced by amyloid and tau PET imaging, and 15 controls) underwent neuropsychological assessment and 3T brain MRI. We analyzed the locus coeruleus signal intensity (LC-I) and the NBM volume as well as their relation with cognition and with medial temporal/cortical atrophy.

RESULTS

We found significantly lower LC-I and NBM volume in amnestic-AD and suspected-LATE in comparison with controls. In FTD, we also observed lower NBM volume but a slightly less marked alteration of the LC-I, independently of the temporal or frontal phenotype. NBM volume was correlated with the global cognitive efficiency in AD patients. Strong correlations were found between NBM volume and that of medial temporal structures, particularly the amygdala in both AD and FTD patients.

CONCLUSIONS

The alteration of LC and NBM in amnestic-AD, presumed-LATE and FTD suggests a common vulnerability of these structures to different proteinopathies. Targeting the noradrenergic and cholinergic systems could be effective therapeutic strategies in LATE and FTD.

Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease

Identifying individuals with early stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would allow professionals and loved ones to make better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. In this study, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes (Posterior Cortical Atrophy, logopenic variant Primary Progressive Aphasia, and amnestic syndrome with multi-domain impairment and age of onset < 65 years). All patients underwent structural magnetic resonance imaging (MRI), tau (18F-Flortaucipir) PET, and amyloid (either 18F-Florbetaben or 11C-Pittsburgh Compound B) PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Our sample of early atypical AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p < .001, d = 0.95. These AD patients showed prominent baseline tau burden in posterior cortical regions including the major nodes of the default mode network, including the angular gyrus, posterior cingulate cortex/precuneus, and lateral temporal cortex. Greater baseline tau in the broader default mode network predicted faster clinical decline. Tau in the default mode network was the strongest predictor of clinical decline, outperforming baseline clinical impairment, tau in other functional networks, and the magnitude of cortical atrophy and amyloid burden in the default mode network. Overall, these findings point to the contribution of baseline tau burden within the default mode network of the cerebral cortex to predicting the magnitude of clinical decline in a sample of atypical early AD patients one year later. This simple measure based on a tau PET scan could aid the development of a personalized prognostic, monitoring, and treatment plan tailored to each individual patient, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.

Alteration of functional connectivity network in population of objectively-defined subtle cognitive decline

The objectively-defined subtle cognitive decline individuals had higher progression rates of cognitive decline and pathological deposition than healthy elderly, indicating a higher risk of progressing to Alzheimer's disease. However, little is known about the brain functional alterations during this stage. Thus, we aimed to investigate the functional network patterns in objectively-defined subtle cognitive decline cohort. Forty-two cognitive normal, 29 objectively-defined subtle cognitive decline and 55 mild cognitive impairment subjects were included based on neuropsychological measures from the Alzheimer's disease Neuroimaging Initiative dataset. Thirty cognitive normal, 22 objectively-defined subtle cognitive declines and 48 mild cognitive impairment had longitudinal MRI data. The degree centrality and eigenvector centrality for each participant were calculated by using resting-state functional MRI. For cross-sectional data, analysis of covariance was performed to detect between-group differences in degree centrality and eigenvector centrality after controlling age, sex and education. For longitudinal data, repeated measurement analysis of covariance was used for comparing the alterations during follow-up period among three groups. In order to classify the clinical significance, we correlated degree centrality and eigenvector centrality values to Alzheimer's disease biomarkers and cognitive function. The results of analysis of covariance showed significant between-group differences in eigenvector centrality and degree centrality in left superior temporal gyrus and left precuneus, respectively. Across groups, the eigenvector centrality value of left superior temporal gyrus was positively related to recognition scores in auditory verbal learning test, whereas the degree centrality value of left precuneus was positively associated with mini-mental state examination total score. For longitudinal data, the results of repeated measurement analysis of covariance indicated objectively-defined subtle cognitive decline group had the highest declined rate of both eigenvector centrality and degree centrality values than other groups. Our study showed an increased brain functional connectivity in objectively-defined subtle cognitive decline individuals at both local and global level, which were associated with Alzheimer's disease pathology and neuropsychological assessment. Moreover, we also observed a faster declined rate of functional network matrix in objectively-defined subtle cognitive decline individuals during the follow-ups.

Elevated Amyloid-β PET Scan and Cognitive and Functional Decline in Mild Cognitive Impairment and Dementia of Uncertain Etiology

BACKGROUND

Elevated amyloid-β (Aβ) on positron emission tomography (PET) scan is used to aid diagnosis of Alzheimer's disease (AD), but many prior studies have focused on patients with a typical AD phenotype such as amnestic mild cognitive impairment (MCI). Little is known about whether elevated Aβ on PET scan predicts rate of cognitive and functional decline among those with MCI or dementia that is clinically less typical of early AD, thus leading to etiologic uncertainty.

OBJECTIVE

We aimed to investigate whether elevated Aβ on PET scan predicts cognitive and functional decline over an 18-month period in those with MCI or dementia of uncertain etiology.

METHODS

In 1,028 individuals with MCI or dementia of uncertain etiology, we evaluated the association between elevated Aβ on PET scan and change on a telephone cognitive status measure administered to the participant and change in everyday function as reported by their care partner.

RESULTS

Individuals with either MCI or dementia and elevated Aβ (66.6% of the sample) showed greater cognitive decline compared to those without elevated Aβ on PET scan, whose cognition was relatively stable over 18 months. Those with either MCI or dementia and elevated Aβ were also reported to have greater functional decline compared to those without elevated Aβ, even though the latter group showed significant care partner-reported functional decline over time.

CONCLUSIONS

Elevated Aβ on PET scan can be helpful in predicting rates of both cognitive and functional decline, even among cognitively impaired individuals with atypical presentations of AD.

A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles

Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.

Tau: a biomarker of Huntington's disease

Developing effective treatments for patients with Huntington's disease (HD)-a neurodegenerative disorder characterized by severe cognitive, motor and psychiatric impairments-is proving extremely challenging. While the monogenic nature of this condition enables to identify individuals at risk, robust biomarkers would still be extremely valuable to help diagnose disease onset and progression, and especially to confirm treatment efficacy. If measurements of cerebrospinal fluid neurofilament levels, for example, have demonstrated use in recent clinical trials, other proteins may prove equal, if not greater, relevance as biomarkers. In fact, proteins such as tau could specifically be used to detect/predict cognitive affectations. We have herein reviewed the literature pertaining to the association between tau levels and cognitive states, zooming in on Alzheimer's disease, Parkinson's disease and traumatic brain injury in which imaging, cerebrospinal fluid, and blood samples have been interrogated or used to unveil a strong association between tau and cognition. Collectively, these areas of research have accrued compelling evidence to suggest tau-related measurements as both diagnostic and prognostic tools for clinical practice. The abundance of information retrieved in this niche of study has laid the groundwork for further understanding whether tau-related biomarkers may be applied to HD and guide future investigations to better understand and treat this disease.

Selective neuronal vulnerability to deficits in RNA processing

Emerging evidence indicates that errors in RNA processing can causally drive neurodegeneration. Given that RNA produced from expressed genes of all cell types undergoes processing (splicing, polyadenylation, 5' capping, etc.), the particular vulnerability of neurons to deficits in RNA processing calls for careful consideration. The activity-dependent transcriptome remodeling associated with synaptic plasticity in neurons requires rapid, multilevel post-transcriptional RNA processing events that provide additional opportunities for dysregulation and consequent introduction or persistence of errors in RNA transcripts. Here we review the accumulating evidence that neurons have an enhanced propensity for errors in RNA processing alongside grossly insufficient defenses to clear misprocessed RNA compared to other cell types. Additionally, we explore how tau, a microtubule-associated protein implicated in Alzheimer's disease and related tauopathies, contributes to deficits in RNA processing and clearance.

Sensitivity of memory subtests and learning slopes from the ADAS-Cog to distinguish along the continuum of the NIA-AA Research Framework for Alzheimer's Disease

Despite extensive use of the Alzheimer's Disease (AD) Assessment Scale - Cognitive Subscale (ADAS-Cog) in AD research, exploration of memory subtests or process scores from the measure has been limited. The current study sought to establish validity for the ADAS-Cog Word Recall Immediate and Delayed Memory subtests and learning slope scores by showing that they are sensitive to AD biomarker status. Word Recall subtest and learning slope scores were calculated for 441 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90). All participants were categorized using the NIA-AA Research Framework - based on PET-imaging of β-amyloid (A) and tau (T) deposition - as Normal AD Biomarkers (A-T-), Alzheimer's Pathologic Change (A + T-), or Alzheimer's disease (A + T+). Memory subtest and learning slope performances were compared between biomarker status groups, and with regard to how well they discriminated samples with (A + T+) and without (A-T-) biomarkers. Lower Word Recall memory subtest scores - and scores for a particular learning slope calculation, the Learning Ratio - were observed for the AD (A + T+) group than the other biomarker groups. Memory subtest and Learning Ratio scores further displayed fair to good receiver operator characteristics when differentiating those with and without AD biomarkers. When comparing across learning slopes, the Learning Ratio metric consistently outperformed others. ADAS-Cog memory subtests and the Learning Ratio score are sensitive to AD biomarker status along the continuum of the NIA-AA Research Framework, and the results offer criterion validity for use of these subtests and process scores as unique markers of memory capacity.

Determinants of cognitive and brain resilience to tau pathology: a longitudinal analysis

Mechanisms of resilience against tau pathology in individuals across the Alzheimer's disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer's disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = -0.062, P = 0.032), higher education level (Stβinteraction = -0.072, P = 0.011) and higher intracranial volume (Stβinteraction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer's disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.

Intracellular accumulation of tau oligomers in astrocytes and their synaptotoxic action rely on Amyloid Precursor Protein Intracellular Domain-dependent expression of Glypican-4

Several studies including ours reported the detrimental effects of extracellular tau oligomers (ex-oTau) on glutamatergic synaptic transmission and plasticity. Astrocytes greatly internalize ex-oTau whose intracellular accumulation alters neuro/gliotransmitter handling thereby negatively affecting synaptic function. Both amyloid precursor protein (APP) and heparan sulfate proteoglycans (HSPGs) are required for oTau internalization in astrocytes but the molecular mechanisms underlying this phenomenon have not been clearly identified yet. Here we found that a specific antibody anti-glypican 4 (GPC4), a receptor belonging to the HSPG family, significantly reduced oTau uploading from astrocytes and prevented oTau-induced alterations of Ca2+-dependent gliotransmitter release. As such, anti-GPC4 spared neurons co-cultured with astrocytes from the astrocyte-mediated synaptotoxic action of ex-oTau, thus preserving synaptic vesicular release, synaptic protein expression and hippocampal LTP at CA3-CA1 synapses. Of note, the expression of GPC4 depended on APP and, in particular, on its C-terminal domain, AICD, that we found to bind Gpc4 promoter. Accordingly, GPC4 expression was significantly reduced in mice in which either APP was knocked-out or it contained the non-phosphorylatable amino acid alanine replacing threonine 688, thus becoming unable to produce AICD. Collectively, our data indicate that GPC4 expression is APP/AICD-dependent, it mediates oTau accumulation in astrocytes and the resulting synaptotoxic effects.

Identification of small molecules and related targets that modulate tau pathology in a seeded primary neuron model

Alzheimer's disease (AD) is characterized by the presence of tau protein inclusions and amyloid beta (Aβ) plaques in the brain, with Aβ peptides generated by cleavage of the amyloid precursor protein (APP) by BACE1 and γ-secretase. We previously described a primary rat neuron assay in which tau inclusions form from endogenous rat tau after seeding cells with insoluble tau isolated from the human AD brain. Here, we used this assay to screen an annotated library of ∼8700 biologically active small molecules for their ability to reduce immuno-stained neuronal tau inclusions. Compounds causing ≥30% inhibition of tau aggregates with <25% loss of DAPI-positive cell nuclei underwent further confirmation testing and assessment of neurotoxicity, and non-neurotoxic hits were subsequently analyzed for inhibitory activity in an orthogonal ELISA that quantified multimeric rat tau species. Of the 173 compounds meeting all criteria, a subset of 55 inhibitors underwent concentration-response testing and 46 elicited a concentration-dependent reduction of neuronal tau inclusions that were distinct from measures of toxicity. Among the confirmed inhibitors of tau pathology were BACE1 inhibitors, several of which, along with γ-secretase inhibitors/modulators, caused a concentration-dependent lowering of neuronal tau inclusions and a reduction of insoluble tau by immunoblotting, although they did not decrease soluble phosphorylated tau species. In conclusion, we have identified a diverse set of small molecules and related targets that reduce neuronal tau inclusions. Notably, these include BACE1 and γ-secretase inhibitors, suggesting that a cleavage product from a shared substrate, such as APP, might affect tau pathology.

Correlating continuously captured home-based digital biomarkers of daily function with postmortem neurodegenerative neuropathology

BACKGROUND

Outcome measures available for use in Alzheimer's disease (AD) clinical trials are limited in ability to detect gradual changes. Measures of everyday function and cognition assessed unobtrusively at home using embedded sensing and computing generated "digital biomarkers" (DBs) have been shown to be ecologically valid and to improve efficiency of clinical trials. However, DBs have not been assessed for their relationship to AD neuropathology.

OBJECTIVES

The goal of the current study is to perform an exploratory examination of possible associations between DBs and AD neuropathology in an initially cognitively intact community-based cohort.

METHODS

Participants included in this study were ≥65 years of age, living independently, of average health for age, and followed until death. Algorithms, run on the continuously-collected passive sensor data, generated daily metrics for each DB: cognitive function, mobility, socialization, and sleep. Fixed postmortem brains were evaluated for neurofibrillary tangles (NFTs) and neuritic plaque (NP) pathology and staged by Braak and CERAD systems in the context of the "ABC" assessment of AD-associated changes.

RESULTS

The analysis included a total of 41 participants (M±SD age at death = 92.2±5.1 years). The four DBs showed consistent patterns relative to both Braak stage and NP score severity. Greater NP severity was correlated with the DB composite and reduced walking speed. Braak stage was associated with reduced computer use time and increased total time in bed.

DISCUSSION

This study provides the first data showing correlations between DBs and neuropathological markers in an aging cohort. The findings suggest continuous, home-based DBs may hold potential to serve as behavioral proxies that index neurodegenerative processes.

Could tau-PET imaging contribute to a better understanding of the different patterns of clinical progression in Alzheimer's disease? A 2-year longitudinal study

BACKGROUND

Monitoring the progression of Tau pathology makes it possible to study the clinical diversity of Alzheimer's disease. In this 2-year longitudinal PET study, we aimed to determine the progression of [¹⁸F]-flortaucipir binding and of cortical atrophy, and their relationships with cognitive decline.

METHODS

Twenty-seven AD patients at the mild cognitive impairment/mild dementia stages and twelve amyloid-negative controls underwent a neuropsychological assessment, 3 T brain MRI, and [¹⁸F]-flortaucipir PET imaging (Tau1) and were monitored annually over 2 years with a second brain MRI and tau-PET imaging after 2 years (Tau2). We analyzed the progression of tau standardized uptake value ratio (SUVr) and grey matter atrophy both at the regional and voxelwise levels. We used mixed effects models to explore the relations between the progression of SUVr values, cortical atrophy, and cognitive decline.

RESULTS

We found an average longitudinal increase in tau SUVr values, except for the lateral temporoparietal cortex where the average SUVr values decreased. Individual analyses revealed distinct profiles of SUVr progression according to temporoparietal Tau1 uptake: high-Tau1 patients demonstrated an increase in SUVr values over time in the frontal lobe, but a decrease in the temporoparietal cortex and a rapid clinical decline, while low-Tau1 patients displayed an increase in SUVr values in all cortical regions and a slower clinical decline. Cognitive decline was strongly associated with the progression of regional cortical atrophy, but only weakly associated with SUVr progression.

CONCLUSIONS

Despite a relatively small sample size, our results suggest that tau-PET imaging could identify patients with a potentially "more aggressive" clinical course characterized by high temporoparietal Tau1 SUVr values and a rapid clinical progression. In these patients, the paradoxical decrease in temporoparietal SUVr values over time could be due to the rapid transition to ghost tangles, for which the affinity of the radiotracer is lower. They could particularly benefit from future therapeutic trials, the neuroimaging outcome measures of which deserve to be discussed.

Increased plasma DYRK1A with aging may protect against neurodegenerative diseases

Early markers are needed for more effective prevention of Alzheimer's disease. We previously showed that individuals with Alzheimer's disease have decreased plasma DYRK1A levels compared to controls. We assessed DYRK1A in the plasma of cognitively healthy elderly volunteers, individuals with either Alzheimer's disease (AD), tauopathies or Down syndrome (DS), and in lymphoblastoids from individuals with DS. DYRK1A levels were inversely correlated with brain amyloid β burden in asymptomatic elderly individuals and AD patients. Low DYRK1A levels were also detected in patients with tauopathies. Individuals with DS had higher DYRK1A levels than controls, although levels were lower in individuals with DS and with dementia. These data suggest that plasma DYRK1A levels could be used for early detection of at risk individuals of AD and for early detection of AD. We hypothesize that lack of increase of DYRK1A at middle age (40-50 years) could be a warning before the cognitive decline, reflecting increased risk for AD.

Tau as a biomarker of cognitive impairment and neuropsychiatric symptom in Alzheimer's disease

The A/T/N research framework has been proposed for the diagnosis and prognosis of Alzheimer's disease (AD). However, the spatial distribution of ATN biomarkers and their relationship with cognitive impairment and neuropsychiatric symptoms (NPS) need further clarification in patients with AD. We scanned 83 AD patients and 38 cognitively normal controls who independently completed the mini-mental state examination and Neuropsychiatric Inventory scales. Tau, Aβ, and hypometabolism spatial patterns were characterized using Statistical Parametric Mapping together with [18F]flortaucipir, [18F]florbetapir, and [18F]FDG positron emission tomography. Piecewise linear regression, two-sample t-tests, and support vector machine algorithms were used to explore the relationship between tau, Aβ, and hypometabolism and cognition, NPS, and AD diagnosis. The results showed that regions with tau deposition are region-specific and mainly occurred in inferior temporal lobes in AD, which extensively overlaps with the hypometabolic regions. While the deposition regions of Aβ were unique and the regions affected by hypometabolism were widely distributed. Unlike Aβ, tau and hypometabolism build up monotonically with increasing cognitive impairment in the late stages of AD. In addition, NPS in AD were associated with tau deposition closely, followed by hypometabolism, but not with Aβ. Finally, hypometabolism and tau had higher accuracy in differentiating the AD patients from controls (accuracy = 0.88, accuracy = 0.85) than Aβ (accuracy = 0.81), and the combined three were the highest (accuracy = 0.95). These findings suggest tau pathology is superior over Aβ and glucose metabolism to identify cognitive impairment and NPS. Its results support tau accumulation can be used as a biomarker of clinical impairment in AD.

Medial Temporal Lobe Atrophy in Predementia Alzheimer's Disease: A Longitudinal Multi-Site Study Comparing Staging and A/T/N in a Clinical Research Cohort

BACKGROUND

Atrophy of the medial temporal lobe (MTL) is a biological characteristic of Alzheimer's disease (AD) and can be measured by segmentation of magnetic resonance images (MRI).

OBJECTIVE

To assess the clinical utility of automated volumetry in a cognitively well-defined and biomarker-classified multi-center longitudinal predementia cohort.

METHODS

We used Automatic Segmentation of Hippocampal Subfields (ASHS) to determine MTL morphometry from MRI. We harmonized scanner effects using the recently developed longitudinal ComBat. Subjects were classified according to the A/T/N system, and as normal controls (NC), subjective cognitive decline (SCD), or mild cognitive impairment (MCI). Positive or negative values of A, T, and N were determined by cerebrospinal fluid measurements of the Aβ42/40 ratio, phosphorylated and total tau. From 406 included subjects, longitudinal data was available for 206 subjects by stage, and 212 subjects by A/T/N.

RESULTS

Compared to A-/T-/N- at baseline, the entorhinal cortex, anterior and posterior hippocampus were smaller in A+/T+orN+. Compared to NC A- at baseline, these subregions were also smaller in MCI A+. Longitudinally, SCD A+ and MCI A+, and A+/T-/N- and A+/T+orN+, had significantly greater atrophy compared to controls in both anterior and posterior hippocampus. In the entorhinal and parahippocampal cortices, longitudinal atrophy was observed only in MCI A+ compared to NC A-, and in A+/T-/N- and A+/T+orN+ compared to A-/T-/N-.

CONCLUSION

We found MTL neurodegeneration largely consistent with existing models, suggesting that harmonized MRI volumetry may be used under conditions that are common in clinical multi-center cohorts.