In Vivo Tau, Amyloid, and Gray Matter Profiles in the Aging Brain

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.

Change in Depressive Symptoms and Longitudinal Regional Amyloid Accumulation in Unimpaired Older Adults

Importance

Depressive symptoms in older adults may be a harbinger of Alzheimer disease (AD), even in preclinical stages. It is unclear whether worsening depressive symptoms are manifestations of regional distributions of core AD pathology (amyloid) and whether cognitive changes affect this relationship.

Objective

To evaluate whether increasing depressive symptoms are associated with amyloid accumulation in brain regions important for emotional regulation and whether those associations vary by cognitive performance.

Design, Setting, and Participants

Participants from the Harvard Aging Brain Study, a longitudinal cohort study, underwent annual assessments of depressive symptoms and cognition alongside cortical amyloid positron emission tomography (PET) imaging at baseline and every 2 to 3 years thereafter (mean [SD] follow-up, 8.6 [2.2] years). Data collection was conducted from September 2010 to October 2022 in a convenience sample of community-dwelling older adults who were cognitively unimpaired with, at most, mild baseline depression. Data were analyzed from October 2022 to December 2023.

Main Outcomes and Measures

Depression (Geriatric Depression Scale [GDS]-30-item), cognition (Preclinical Alzheimer Cognitive Composite-5 [PACC]), and a continuous measure of cerebral amyloid (Pittsburgh compound B [PiB] PET) examined in a priori-defined regions (medial orbitofrontal cortex [mOFC], lateral orbitofrontal cortex, middle frontal cortex [MFC], superior frontal cortex, anterior cingulate cortex, isthmus cingulate cortex [IC], posterior cingulate cortex, and amygdala). Associations between longitudinal GDS scores, regional amyloid slopes, and PACC slopes were assessed using linear mixed-effects models.

Results

In this sample of 154 individuals (94 [61%] female; mean [SD] age, 72.6 [6.4] years; mean (SD) education, 15.9 [3.1] years), increasing PiB slopes in the bilateral mOFC, IC, and MFC were associated with increasing GDS scores (mOFC: β = 11.07 [95% CI, 5.26-16.87]; t = 3.74 [SE, 2.96]; P = .004; IC: β = 12.83 [95% CI, 5.68-19.98]; t = 3.51 [SE, 3.65]; P = .004; MFC: β = 9.22 [95% CI, 2.25-16.20]; t = 2.59 [SE, 3.56]; P = .03). Even with PACC slope as an additional covariate, associations remained significant in these regions.

Conclusions and Relevance

In this cohort study of cognitively unimpaired older adults with, at most, mild baseline depressive symptoms, greater depressive symptoms over time were associated with amyloid accumulation in regions associated with emotional control. Furthermore, these associations persisted in most regions independent of cognitive changes. These results shed light on the neurobiology of depressive symptoms in older individuals and underscore the importance of monitoring for elevated mood symptoms early in AD.

Diverging Relationships among Amyloid, Tau, and Brain Atrophy in Early-Onset and Late-Onset Alzheimer's Disease

PURPOSE

Alzheimer's disease (AD) dementia may not be a single disease entity. Early-onset AD (EOAD) and late-onset AD (LOAD) have been united under the same eponym of AD until now, but disentangling the heterogeneity according to the age of sonset has been a major tenet in the field of AD research.

MATERIALS AND METHODS

Ninety-nine patients with AD (EOAD, n=54; LOAD, n=45) and 66 cognitively normal controls completed both [18F]THK5351 and [18F]flutemetamol (FLUTE) positron emission tomography scans along with structural magnetic resonance imaging and detailed neuropsychological tests.

RESULTS

EOAD patients had higher THK retention in the precuneus, parietal, and frontal lobe, while LOAD patients had higher THK retention in the medial temporal lobe. Intravoxel correlation analyses revealed that EOAD presented narrower territory of local FLUTE-THK correlation, while LOAD presented broader territory of correlation extending to overall parieto-occipito-temporal regions. EOAD patients had broader brain areas which showed significant negative correlations between cortical thickness and THK retention, whereas in LOAD, only limited brain areas showed significant correlation with THK retention. In EOAD, most of the cognitive test results were correlated with THK retention. However, a few cognitive test results were correlated with THK retention in LOAD.

CONCLUSION

LOAD seemed to show gradual increase in tau and amyloid, and those two pathologies have association to each other. On the other hand, in EOAD, tau and amyloid may develop more abruptly and independently. These findings suggest LOAD and EOAD may have different courses of pathomechanism.

Understanding the complex interplay between tau, amyloid and the network in the spatiotemporal progression of Alzheimer's Disease

INTRODUCTION

The interaction of amyloid and tau in neurodegenerative diseases is a central feature of AD pathophysiology. While experimental studies point to various interaction mechanisms, their causal direction and mode (local, remote or network-mediated) remain unknown in human subjects. The aim of this study was to compare mathematical reaction-diffusion models encoding distinct cross-species couplings to identify which interactions were key to model success.

METHODS

We tested competing mathematical models of network spread, aggregation, and amyloid-tau interactions on publicly available data from ADNI.

RESULTS

Although network spread models captured the spatiotemporal evolution of tau and amyloid in human subjects, the model including a one-way amyloid-to-tau aggregation interaction performed best.

DISCUSSION

This mathematical exposition of the "pas de deux" of co-evolving proteins provides quantitative, whole-brain support to the concept of amyloid-facilitated-tauopathy rather than the classic amyloid-cascade or pure-tau hypotheses, and helps explain certain known but poorly understood aspects of AD.

Genetic influences on brain and cognitive health and their interactions with cardiovascular conditions and depression

Approximately 40% of dementia cases could be prevented or delayed by modifiable risk factors related to lifestyle and environment. These risk factors, such as depression and vascular disease, do not affect all individuals in the same way, likely due to inter-individual differences in genetics. However, the precise nature of how genetic risk profiles interact with modifiable risk factors to affect brain health is poorly understood. Here we combine multiple data resources, including genotyping and postmortem gene expression, to map the genetic landscape of brain structure and identify 367 loci associated with cortical thickness and 13 loci associated with white matter hyperintensities (P < 5×10-8), with several loci also showing a significant association with cognitive function. We show that among 220 unique genetic loci associated with cortical thickness in our genome-wide association studies (GWAS), 95 also showed evidence of interaction with depression or cardiovascular conditions. Polygenic risk scores based on our GWAS of inferior frontal thickness also interacted with hypertension in predicting executive function in the Canadian Longitudinal Study on Aging. These findings advance our understanding of the genetic underpinning of brain structure and show that genetic risk for brain and cognitive health is in part moderated by treatable mid-life factors.

Behavioral and dysexecutive variant of Alzheimer's disease: Insights from structural and molecular imaging studies

Frontal variant Alzheimer's disease (AD) manifests with either behavioral or dysexecutive syndromes. Recent efforts to gain a deeper understanding of this phenotype have led to a re-conceptualization of frontal AD. Behavioral (bAD) and dysexecutive (dAD) phenotypes could be considered subtypes, as suggested by both clinical and neuroimaging studies. In this review, we focused on imaging studies to highlight specific brain patterns in these two uncommon clinical AD phenotypes. Although studies did not compare directly these two variants, a common epicenter located in the frontal cortex could be inferred. On the contrary, 18F-FDG-PET findings suggested differing metabolic patterns, with bAD showing specific involvement of frontal regions and dAD exhibiting widespread alterations. Structural MRI findings confirmed this pattern, suggesting that degeneration might involve neural circuits associated with behavioral control in bAD and attentional networks in dAD. Furthermore, molecular imaging has identified different neocortical tau distribution in bAD and dAD patients compared to typical AD patients, although the distribution is remarkably heterogeneous. In contrast, Aβ deposition patterns are less differentiated between these atypical variants and typical AD. Although preliminary, these findings underscore the complexity of AD frontal phenotypes and suggest that they represent distinct entities. Further research is essential to refine our understanding of the pathophysiological mechanisms in frontal AD.

The spatial distribution of coupling between tau and neurodegeneration in amyloid-β positive mild cognitive impairment

Synergies between amyloid-β (Aβ), tau, and neurodegeneration persist along the Alzheimer's disease (AD) continuum. This study aimed to evaluate the extent of spatial coupling between tau and neurodegeneration (atrophy) and its relation to Aβ positivity in mild cognitive impairment (MCI). Data from 409 participants were included (95 cognitively normal controls, 158 Aβ positive (Aβ+) MCI, and 156 Aβ negative (Aβ-) MCI). Florbetapir PET, Flortaucipir PET, and structural MRI were used as biomarkers for Aβ, tau and atrophy, respectively. Individual correlation matrices for tau load and atrophy were used to layer a multilayer network, with separate layers for tau and atrophy. A measure of coupling between corresponding regions of interest (ROIs) in the tau and atrophy layers was computed, as a function of Aβ positivity. Fewer than 25% of the ROIs across the brain showed heightened coupling between tau and atrophy in Aβ+ , relative to Aβ- MCI. Coupling strengths in the right rostral middle frontal and right paracentral gyri, in particular, mediated the association between Aβ burden and cognition in this sample.

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

Spatiotemporal Correlation between Amyloid and Tau Accumulations Underlies Cognitive Changes in Aging

It is poorly known how Aβ and tau accumulations associate at the spatiotemporal level in the in vivo human brain to impact cognitive changes in older adults prior to AD symptoms onset. In this study, we used a graph theory-based spatiotemporal analysis to characterize the cortical patterns of Aβ and tau deposits and their relationship with cognitive changes in the Harvard Aging Brain Study (HABS) cohort. We found that the temporal accumulations of interlinked Aβ and tau pathology display distinctive spatiotemporal correlations associated with early cognitive decline. Notably, we observed that baseline Aβ deposits-Thal amyloid phase Ⅱ-related to future increase of tau deposits, Braak stages Ⅰ-Ⅳ, both displaying linkage to the decline in multi-domain cognitive scores. We also found unimodal tau-to-tau and cognitive impairment associations in broad areas of Braak stages Ⅰ-Ⅳ. The unimodal Aβ-to-Aβ progressions were not associated with cognitive changes. Our results revealed a multifaceted correlation of the spatiotemporal Aβ and tau associations with cognitive decline over time, in which tau-to-tau and tau-Aβ interactions, and not Aβ independently, might be critical contributors to clinical trajectories toward AD in older adults.

Betula pendula Leaf Extract Targets the Interplay between Brain Oxidative Stress, Inflammation, and NFkB Pathways in Amyloid Aβ1-42-Treated Rats

Alzheimer's disease (AD) is known as the primary and most common cause of dementia in the middle-aged and elderly population worldwide. Chemical analyses of B. pendula leaf extract (BPE), performed using spectrophotometric and chromatographic methods (LC/MS), revealed high amounts of polyphenol carboxylic acids (gallic, chlorogenic, caffeic, trans-p-coumaric, ferulic, and salicylic acids), as well as flavonoids (apigenin, luteolin, luteolin-7-O-glucoside, naringenin, hyperoside, quercetin, and quercitrin). Four groups of Wistar rats were used in this experiment (n = 7/group): control (untreated), Aβ1-42 (2 μg/rat intracerebroventricular (i.c.v.), Aβ1-42 + BPE (200 mg/Kg b.w.), and DMSO (10 μL/rat). On the first day, one dose of Aβ1-42 was intracerebroventricularly administered to animals in groups 2 and 3. Subsequently, BPE was orally administered for the next 15 days to group 3. On the 16th day, behavioral tests were performed. Biomarkers of brain oxidative stress Malondialdehyde (MDA), (Peroxidase (PRx), Catalase (CAT), and Superoxid dismutase (SOD) and inflammation (cytokines: tumor necrosis factor -α (TNF-α), Interleukin 1β (IL-1β), and cyclooxygenase-2 (COX 2)) in plasma and hippocampus homogenates were assessed. Various protein expressions (Phospho-Tau (Ser404) (pTau Ser 404), Phospho-Tau (Ser396) (pTau Ser 396), synaptophysin, and the Nuclear factor kappa B (NFkB) signaling pathway) were analyzed using Western blot and immunohistochemistry in the hippocampus. The results show that BPE diminished lipid peroxidation and neuroinflammation, modulated specific protein expression, enhanced the antioxidant capacity, and improved spontaneous alternation behavior, suggesting that it has beneficial effects in AD.

Etiology of White Matter Hyperintensities in Autosomal Dominant and Sporadic Alzheimer Disease

Importance

Increased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors.

Objective

To estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes.

Design, Setting, and Participants

This cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers-the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer's Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019).

Main Outcome and Measures

The main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH.

Results

Data from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [P = .001]; ADNI: t = 2.7 [P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = -3.1 [P = .002]; ADNI: t = -5.6 [P < .001]; HABS: t = -2.2 [P = .03]), greater in older individuals (DIAN: t = 6.8 [P < .001]; ADNI: t = 9.1 [P < .001]; HABS: t = 5.4 [P < .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [P = .40]; ADNI: t = 0.6 [P = .50]; HABS: t = 1.8 [P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P < .001).

Conclusions and Relevance

The findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.

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.

Spatial association between distributed β-amyloid and tau varies with cognition

Several PET studies have explored the relationship between β-amyloid load and tau uptake at the early stages of Alzheimer's disease (AD) progression. Most of these studies have focused on the linear relationship between β-amyloid and tau at the local level and their synergistic effect on different AD biomarkers. We hypothesize that patterns of spatial association between β-amyloid and tau might be uncovered using alternative association metrics that account for linear as well as more complex, possible nonlinear dependencies. In the present study, we propose a new Canonical Distance Correlation Analysis (CDCA) to generate distinctive spatial patterns of the cross-correlation structure between tau, as measured by [18F]flortaucipir PET, and β-amyloid, as measured by [18F]florbetapir PET, from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We found that the CDCA-based β-amyloid scores were not only maximally distance-correlated to tau in cognitively normal (CN) controls and mild cognitive impairment (MCI), but also differentiated between low and high levels of β-amyloid uptake. The most distinctive spatial association pattern was characterized by a spread of β-amyloid covering large areas of the cortex and localized tau in the entorhinal cortex. More importantly, this spatial dependency varies according to cognition, which cannot be explained by the uptake differences in β-amyloid or tau between CN and MCI subjects. Hence, the CDCA-based scores might be more accurate than the amyloid or tau SUVR for the enrollment in clinical trials of those individuals on the path of cognitive deterioration.

Tau protein spreads through functionally connected neurons in Alzheimer's disease: a combined MEG/PET study

Recent studies on Alzheimer's disease (AD) suggest that tau proteins spread through the brain following neuronal connections. Several mechanisms could be involved in this process: spreading between brain regions that interact strongly (functional connectivity); through the pattern of anatomical connections (structural connectivity); or simple diffusion. Using magnetoencephalography (MEG), we investigated which spreading pathways influence tau protein spreading by modelling the tau propagation process using an epidemic spreading model. We compared the modelled tau depositions with 18F-flortaucipir PET binding potentials at several stages of the AD continuum. In this cross-sectional study, we analysed source-reconstructed MEG data and dynamic 100-min 18F-flortaucipir PET from 57 subjects positive for amyloid-β pathology [preclinical AD (n = 16), mild cognitive impairment (MCI) due to AD (n = 16) and AD dementia (n = 25)]. Cognitively healthy subjects without amyloid-β pathology were included as controls (n = 25). Tau propagation was modelled as an epidemic process (susceptible-infected model) on MEG-based functional networks [in alpha (8-13 Hz) and beta (13-30 Hz) bands], a structural or diffusion network, starting from the middle and inferior temporal lobe. The group-level network of the control group was used as input for the model to predict tau deposition in three stages of the AD continuum. To assess performance, model output was compared to the group-specific tau deposition patterns as measured with 18F-flortaucipir PET. We repeated the analysis by using networks of the preceding disease stage and/or using regions with most observed tau deposition during the preceding stage as seeds. In the preclinical AD stage, the functional networks predicted most of the modelled tau-PET binding potential, with best correlations between model and tau-PET [corrected amplitude envelope correlation (AEC-c) alpha C = 0.584; AEC-c beta C = 0.569], followed by the structural network (C = 0.451) and simple diffusion (C = 0.451). Prediction accuracy declined for the MCI and AD dementia stages, although the correlation between modelled tau and tau-PET binding remained highest for the functional networks (C = 0.384; C = 0.376). Replacing the control-network with the network from the preceding disease stage and/or alternative seeds improved prediction accuracy in MCI but not in the dementia stage. These results suggest that in addition to structural connections, functional connections play an important role in tau spread, and highlight that neuronal dynamics play a key role in promoting this pathological process. Aberrant neuronal communication patterns should be taken into account when identifying targets for future therapy. Our results also suggest that this process is more important in earlier disease stages (preclinical AD/MCI); possibly, in later stages, other processes may be influential.

Influence of Alzheimer's disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex

Neuropathological lesions in the brains of individuals affected with neurodegenerative disorders are hypothesized to trigger molecular and cellular processes that disturb homeostasis of local microenvironments. Here, we applied the 10x Genomics Visium Spatial Proteogenomics (Visium-SPG) platform, which couples spatial gene expression with immunofluorescence protein co-detection, to evaluate its ability to quantify changes in spatial gene expression with respect to amyloid-β (Aβ) and hyperphosphorylated tau (pTau) pathology in post-mortem human brain tissue from individuals with Alzheimer's disease (AD). We identified transcriptomic signatures associated with proximity to Aβ in the human inferior temporal cortex (ITC) during late-stage AD, which we further investigated at cellular resolution with combined immunofluorescence and single molecule fluorescent in situ hybridization (smFISH). The study provides a data analysis workflow for Visium-SPG, and the data represent a proof-of-principal for the power of multi-omic profiling in identifying changes in molecular dynamics that are spatially-associated with pathology in the human brain. We provide the scientific community with web-based, interactive resources to access the datasets of the spatially resolved AD-related transcriptomes at https://research.libd.org/Visium_SPG_AD/.

Interaction of Proteins Involved in Neuronal Proteinopathies

Proteinopathy is characterized by the accumulation of aggregates of a specific protein in a target organ, tissue, or cell. The aggregation of the same protein can cause different pathologies as single protein can adopt various amyloidogenic, disease-specific conformations. The conformation governs the interaction of amyloid aggregates with other proteins that are prone to misfolding and, thus, determines disease-specific spectrum of concomitant pathologies. In this regard, a detailed description of amyloid protein conformation as well as spectrum of its interaction with other proteins become a key point for drafting of precise description of the disease. The majority of clinical cases of neuronal proteinopathies is caused by the aggregation of rather limited range of amyloidogenic proteins. Here, we provided the characterization of pathologies, related to the aggregation of amyloid β peptide, tau protein, α-synuclein, TDP-43, and amylin, giving a short description of pathologies themselves, recent advances in elucidation of misfolded protein conformation, with emphasis on those protein aggregates extracted from biological samples, what is known about the interaction of this proteins, and the influence of this interaction on the progression of underlying disease and comorbidities.

Genetically identical twin-pair difference models support the amyloid cascade hypothesis

The amyloid cascade hypothesis has strongly impacted the Alzheimer's disease research agenda and clinical trial designs over the past decades, but precisely how amyloid-β pathology initiates the aggregation of neocortical tau remains unclear. We cannot exclude the possibility of a shared upstream process driving both amyloid-β and tau in an independent manner instead of there being a causal relationship between amyloid-β and tau. Here, we tested the premise that if a causal relationship exists, then exposure should be associated with outcome both at the individual level as well as within identical twin-pairs, who are strongly matched on genetic, demographic and shared environmental background. Specifically, we tested associations between longitudinal amyloid-β PET and cross-sectional tau PET, neurodegeneration and cognitive decline using genetically identical twin-pair difference models, which provide the unique opportunity of ruling out genetic and shared environmental effects as potential confounders in an association. We included 78 cognitively unimpaired identical twins with [18F]flutemetamol (amyloid-β)-PET, [18F]flortaucipir (tau)-PET, MRI (hippocampal volume) and cognitive data (composite memory). Associations between each modality were tested at the individual level using generalized estimating equation models, and within identical twin-pairs using within-pair difference models. Mediation analyses were performed to test for directionality in the associations as suggested by the amyloid cascade hypothesis. At the individual level, we observed moderate-to-strong associations between amyloid-β, tau, neurodegeneration and cognition. The within-pair difference models replicated results observed at the individual level with comparably strong effect sizes. Within-pair differences in amyloid-β were strongly associated with within-pair differences in tau (β = 0.68, P < 0.001), and moderately associated with within-pair differences in hippocampal volume (β = -0.37, P = 0.03) and memory functioning (β = -0.57, P < 0.001). Within-pair differences in tau were moderately associated with within-pair differences in hippocampal volume (β = -0.53, P < 0.001) and strongly associated with within-pair differences in memory functioning (β = -0.68, P < 0.001). Mediation analyses showed that of the total twin-difference effect of amyloid-β on memory functioning, the proportion mediated through pathways including tau and hippocampal volume was 69.9%, which was largely attributable to the pathway leading from amyloid-β to tau to memory functioning (proportion mediated, 51.6%). Our results indicate that associations between amyloid-β, tau, neurodegeneration and cognition are unbiased by (genetic) confounding. Furthermore, effects of amyloid-β on neurodegeneration and cognitive decline were fully mediated by tau. These novel findings in this unique sample of identical twins are compatible with the amyloid cascade hypothesis and thereby provide important new knowledge for clinical trial designs.

The spatial distribution of coupling between tau and neurodegeneration in amyloid-β positive mild cognitive impairment

Synergies between amyloid-β (Aβ), tau, and neurodegeneration persist along the Alzheimer's disease (AD) continuum. This study aimed to evaluate the extent of spatial coupling between tau and neurodegeneration (atrophy) and its relation to Aβ positivity in mild cognitive impairment (MCI). Data from 409 subjects were included (95 cognitively normal controls, 158 Aβ positive (Aβ+) MCI, and 156 Aβ negative (Aβ-) MCI) Florbetapir PET, Flortaucipir PET, and structural MRI were used as biomarkers for Aβ, tau and atrophy, respectively. Individual correlation matrices for tau load and atrophy were used to layer a multilayer network, with separate layers for tau and atrophy. A measure of coupling between corresponding regions of interest/nodes in the tau and atrophy layers was computed, as a function of Aβ positivity. The extent to which tau-atrophy coupling mediated associations between Aβ burden and cognitive decline was also evaluated. Heightened coupling between tau and atrophy in Aβ+ MCI was found primarily in the entorhinal and hippocampal regions (i.e., in regions corresponding to Braak stages I/II), and to a lesser extent in limbic and neocortical regions (i.e., corresponding to later Braak stages). Coupling strengths in the right middle temporal and inferior temporal gyri mediated the association between Aβ burden and cognition in this sample. Higher coupling between tau and atrophy in Aβ+ MCI is primarily evident in regions corresponding to early Braak stages and relates to overall cognitive decline. Coupling in neocortical regions is more restricted in MCI.

Longitudinal associations between β-amyloid and cortical thickness in mild cognitive impairment

How beta-amyloid accumulation influences brain atrophy in Alzheimer's disease remains contentious with conflicting findings. We aimed to elucidate the correlations of regional longitudinal atrophy with cross-sectional regional and global amyloid in individuals with mild cognitive impairment and no cognitive impairment. We hypothesized that greater cortical thinning over time correlated with greater amyloid deposition, particularly within Alzheimer's disease characteristic regions in mild cognitive impairment, and weaker or no correlations in those with no cognitive impairment. 45 patients with mild cognitive impairment and 12 controls underwent a cross-sectional [¹¹C]-Pittsburgh Compound B PET and two retrospective longitudinal structural imaging (follow-up: 23.65 ± 2.04 months) to assess global/regional amyloid and regional cortical thickness, respectively. Separate linear mixed models were constructed to evaluate relationships of either global or regional amyloid with regional cortical thinning longitudinally. In patients with mild cognitive impairment, regional amyloid in the right banks of the superior temporal sulcus was associated with longitudinal cortical thinning in the right medial orbitofrontal cortex (P = 0.04 after False Discovery Rate correction). In the mild cognitive impairment group, greater right banks amyloid burden and less cortical thickness in the right medial orbitofrontal cortex showed greater visual and verbal memory decline over time, which was not observed in controls. Global amyloid was not associated with longitudinal cortical thinning in any locations in either group. Our findings indicate an increasing influence of amyloid on neurodegeneration and memory along the preclinical to prodromal spectrum. Future multimodal studies that include additional biomarkers will be well-suited to delineate the interplay between various pathological processes and amyloid and memory decline, as well as clarify their additive or independent effects along the disease deterioration.

Evidence against a temporal association between cerebrovascular disease and Alzheimer's disease imaging biomarkers

Whether a relationship exists between cerebrovascular disease and Alzheimer's disease has been a source of controversy. Evaluation of the temporal progression of imaging biomarkers of these disease processes may inform mechanistic associations. We investigate the relationship of disease trajectories of cerebrovascular disease (white matter hyperintensity, WMH, and fractional anisotropy, FA) and Alzheimer's disease (amyloid and tau PET) biomarkers in 2406 Mayo Clinic Study of Aging and Mayo Alzheimer's Disease Research Center participants using accelerated failure time models. The model assumes a common pattern of progression for each biomarker that is shifted earlier or later in time for each individual and represented by a per participant age adjustment. An individual's amyloid and tau PET adjustments show very weak temporal association with WMH and FA adjustments (R = -0.07 to 0.07); early/late amyloid or tau timing explains <1% of the variation in WMH and FA adjustment. Earlier onset of amyloid is associated with earlier onset of tau (R = 0.57, R2 = 32%). These findings support a strong mechanistic relationship between amyloid and tau aggregation, but not between WMH or FA and amyloid or tau PET.

The Adult Neurogenesis Theory of Alzheimer's Disease

Alzheimer's disease starts in neural stem cells (NSCs) in the niches of adult neurogenesis. All primary factors responsible for pathological tau hyperphosphorylation are inherent to adult neurogenesis and migration. However, when amyloid pathology is present, it strongly amplifies tau pathogenesis. Indeed, the progressive accumulation of extracellular amyloid-β deposits in the brain triggers a state of chronic inflammation by microglia. Microglial activation has a significant pro-neurogenic effect that fosters the process of adult neurogenesis and supports neuronal migration. Unfortunately, this "reactive" pro-neurogenic activity ultimately perturbs homeostatic equilibrium in the niches of adult neurogenesis by amplifying tau pathogenesis in AD. This scenario involves NSCs in the subgranular zone of the hippocampal dentate gyrus in late-onset AD (LOAD) and NSCs in the ventricular-subventricular zone along the lateral ventricles in early-onset AD (EOAD), including familial AD (FAD). Neuroblasts carrying the initial seed of tau pathology travel throughout the brain via neuronal migration driven by complex signals and convey the disease from the niches of adult neurogenesis to near (LOAD) or distant (EOAD) brain regions. In these locations, or in close proximity, a focus of degeneration begins to develop. Then, tau pathology spreads from the initial foci to large neuronal networks along neural connections through neuron-to-neuron transmission.

Early tau detection in flortaucipir images: validation in autopsy-confirmed data and implications for disease progression

BACKGROUND

There is an increasing interest in utilizing tau PET to identify patients early in Alzheimer's disease (AD). In this work, a temporal lobe composite (Eτ) volume of interest (VOI) was evaluated in a longitudinal flortaucipir cohort and compared to a previously described global neocortical VOI. In a separate autopsy-confirmed study, the sensitivity of the Eτ VOI for identifying intermediate (B2) neurofibrillary tangle (NFT) pathology was evaluated.

METHODS

A total of 427 subjects received flortaucipir, florbetapir, MRI, and cognitive evaluation at baseline and 18 months. In a separate autopsy study, 67 subjects received ante-mortem flortaucipir scans, and neuropathological findings were recorded according to NIA-AA recommendations by two experts. Two VOIs: Eτ comprising FreeSurfer volumes (bilateral entorhinal cortex, fusiform, parahippocampal, and inferior temporal gyri) transformed to MNI space and a previously published global AD signature-weighted neocortical VOI (AD_signature) (Devous et al., J Nucl Med 59:937-43, 2018), were used to calculate SUVr relative to a white matter reference region (PERSI) (Southekal et al., J Nucl Med Off Publ Soc Nucl Med 59:944-51, 2018). SUVr cutoffs for positivity were determined based on a cohort of young, cognitively normal subjects. Subjects were grouped based on positivity on both VOIs (Eτ+/AD_signature+; Eτ+/AD_signature-; Eτ-/AD_signature-). Groupwise comparisons were performed for baseline SUVr, 18-month changes in SUVr, neurodegeneration, and cognition. For the autopsy study, the sensitivity of Eτ in identifying intermediate Braak pathology (B2) subjects was compared to that of AD signature-weighted neocortical VOI. The average surface maps of subjects in the Eτ+/AD_signature- group and B2 NFT scores were created for visual evaluation of uptake.

RESULTS

Sixty-four out of 390 analyzable subjects were identified as Eτ+/AD_signature-: 84% were Aβ+, 100% were diagnosed as MCI or AD, and 59% were APOE ε4 carriers. Consistent with the hypothesis that Eτ+/AD_signature- status reflects an early stage of AD, Eτ+/AD_signature- subjects deteriorated significantly faster than Eτ-/AD_signature- subjects, but significantly slower than Eτ+/AD_signature+ subjects, on most measures (i.e., change in AD_signature SUVr, Eτ ROI cortical thickness, and MMSE). The AD_signature VOI was selective for subjects who came to autopsy with a B3 NFT score. In the autopsy study, 12/15 B2 subjects (including 10/11 Braak IV) were Eτ+/AD_signature-. Surface maps showed that flortaucipir uptake was largely captured by the Eτ VOI regions in B2 subjects.

CONCLUSION

The Eτ VOI identified subjects with elevated temporal but not global tau (Eτ+/AD_signature-) that were primarily Aβ+, APOE ε4 carriers, and diagnosed as MCI or AD. Eτ+/AD_signature- subjects had greater accumulation of tau, greater atrophy, and higher decline on MMSE in 18 months compared to Eτ-/AD_signature- subjects. Finally, the Eτ VOI identified the majority of the intermediate NFT score subjects in an autopsy-confirmed study. As far as we know, this is the first study that presents a visualization of ante-mortem FTP retention patterns that at a group level agree with the neurofibrillary tangle staging scheme proposed by Braak. These findings suggest that the Eτ VOI may be sensitive for detecting impaired subjects early in the course of Alzheimer's disease.

Synthesis, single crystal characterization and anti-AD activities of a novel complex of Cu(II) with in situ formed protonated chrysin derivative ligand

Alzheimer's disease (AD), the most common form of neurodegeneration disorder in adults, is becoming the overwhelming burden on the healthcare and economic system. In this study, chrysin derivative with the morpholine moiety was designed, synthesized and evaluated based on the multi targets directed ligands strategy for the treatment of AD centered with therapeutic attempts to restore metal homeostasis. It selectively coordinated with the important bio-metal ions related AD, especially Cu²⁺. Notably, single crystals of both 1 and 1-Cu(II) were obtained and the single crystal structures were characterized by X-ray crystal diffraction, which provided a basis to further explore the possible structure-activity relationship at the molecular level. Compound 1 and 1-Cu(II) complex showed potent anti-oxidative activities, with respect to both ·OH and ·O₂^- scavenging properties In addition, 1 had good inhibitory activity on Aβ_1-42 aggregation, and it could target copper dyshomeostasis through extracting Cu²⁺ from the amyloids. The studies in silico showed that 1 had brain availability and peroral bioavailability. Taken together, compound 1, as the derivative of chrysin, might be a promising advanced lead candidate for the development of new anti-AD drugs and it may provide a useful template for studying the structure-activity relationships of biometal-coordinating drugs.

Association between gray matter atrophy, cerebral hypoperfusion, and cognitive impairment in Alzheimer's disease

Background

Alzheimer's disease (AD) is one of the most severe neurodegenerative diseases leading to dementia in the elderly. Cerebral atrophy and hypoperfusion are two important pathophysiological characteristics. However, it is still unknown about the area-specific causal pathways between regional gray matter atrophy, cerebral hypoperfusion, and cognitive impairment in AD patients.

Method

Forty-two qualified AD patients and 49 healthy controls (HC) were recruited in this study. First, we explored voxel-wise inter-group differences in gray matter volume (GMV) and arterial spin labeling (ASL) -derived cerebral blood flow (CBF). Then we explored the voxel-wise associations between GMV and Mini-Mental State Examination (MMSE) score, GMV and CBF, and CBF and MMSE to identify brain targets contributing to cognitive impairment in AD patients. Finally, a mediation analysis was applied to test the causal pathways among atrophied GMV, hypoperfusion, and cognitive impairment in AD.

Results

Voxel-wise permutation test identified that the left middle temporal gyrus (MTG) had both decreased GMV and CBF in the AD. Moreover, the GMV of this region was positively correlated with MMSE and its CBF, and CBF of this region was also positively correlated with MMSE in AD (p < 0.05, corrected). Finally, mediation analysis revealed that gray matter atrophy of left MTG drives cognitive impairment of AD via the mediation of CBF (proportion of mediation = 55.82%, β = 0.242, 95% confidence interval by bias-corrected and accelerated bootstrap: 0.082 to 0.530).

Conclusion

Our findings indicated suggested that left MTG is an important hub linking gray matter atrophy, hypoperfusion, and cognitive impairment for AD, and might be a potential treatment target for AD.

Discriminative accuracy of the A/T/N scheme to identify cognitive impairment due to Alzheimer's disease

Introduction

The optimal combination of amyloid-β/tau/neurodegeneration (A/T/N) biomarker profiles for the diagnosis of Alzheimer's disease (AD) dementia is unclear.

Methods

We examined the discriminative accuracy of A/T/N combinations assessed with neuroimaging biomarkers for the differentiation of AD from cognitively unimpaired (CU) elderly and non-AD neurodegenerative diseases in the TRIAD, BioFINDER-1 and BioFINDER-2 cohorts (total n = 832) using area under the receiver operating characteristic curves (AUC).

Results

For the diagnosis of AD dementia (vs. CU elderly), T biomarkers performed as well as the complete A/T/N system (AUC range: 0.90-0.99). A and T biomarkers in isolation performed as well as the complete A/T/N system in differentiating AD dementia from non-AD neurodegenerative diseases (AUC range; A biomarker: 0.84-1; T biomarker: 0.83-1).

Discussion

In diagnostic settings, the use of A or T neuroimaging biomarkers alone can reduce patient burden and medical costs compared with using their combination, without significantly compromising accuracy.

The nervous system during COVID-19: Caught in the crossfire

SARS-CoV-2, the virus that causes coronavirus disease (COVID)-19, has become a persistent global health threat. Individuals who are symptomatic for COVID-19 frequently exhibit respiratory illness, which is often accompanied by neurological symptoms of anosmia and fatigue. Mounting clinical data also indicate that many COVID-19 patients display long-term neurological disorders postinfection such as cognitive decline, which emphasizes the need to further elucidate the effects of COVID-19 on the central nervous system. In this review article, we summarize an emerging body of literature describing the impact of SARS-CoV-2 infection on central nervous system (CNS) health and highlight important areas of future investigation.

Mapping the association between tau-PET and Aβ-amyloid-PET using deep learning

In Alzheimer’s disease, the molecular pathogenesis of the extracellular Aβ-amyloid (Aβ) instigation of intracellular tau accumulation is poorly understood. We employed a high-resolution PET scanner, with low detection thresholds, to examine the Aβ-tau association using a convolutional neural network (CNN), and compared results to a standard voxel-wise linear analysis. The full range of Aβ Centiloid values was highly predicted by the tau topography using the CNN (training R² = 0.86, validation R² = 0.75, testing R² = 0.72). Linear models based on tau-SUVR identified widespread positive correlations between tau accumulation and Aβ burden throughout the brain. In contrast, CNN analysis identified focal clusters in the bilateral medial temporal lobes, frontal lobes, precuneus, postcentral gyrus and middle cingulate. At low Aβ levels, information from the middle cingulate, frontal lobe and precuneus regions was more predictive of Aβ burden, while at high Aβ levels, the medial temporal regions were more predictive of Aβ burden. The data-driven CNN approach revealed new associations between tau topography and Aβ burden.

Network Tau spreading is vulnerable to the expression gradients of APOE and glutamatergic-related genes

A key hallmark of Alzheimer's disease (AD) pathology is the intracellular accumulation of tau protein in the form of neurofibrillary tangles across large-scale networks of the human brain cortex. Currently, it is still unclear how tau accumulates within specific cortical systems and whether in situ genetic traits play a role in this circuit-based propagation progression. In this study, using two independent cohorts of cognitively normal older participants, we reveal the brain network foundation of tau spreading and its association with using high-resolution transcriptomic genetic data. We observed that specific connectomic and genetic gradients exist along the tau spreading network. In particular, we identified 577 genes whose expression is associated with the spatial spreading of tau. Within this set of genes, APOE and glutamatergic synaptic genes, such as SLC1A2, play a central role. Thus, our study characterizes neurogenetic topological vulnerabilities in distinctive brain circuits of tau spreading and suggests that drug development strategies targeting the gradient expression of this set of genes should be explored to help reduce or prevent pathological tau accumulation.

The impact of subthreshold levels of amyloid deposition on conversion to dementia in patients with amyloid-negative amnestic mild cognitive impairment

BACKGROUND

About 40-50% of patients with amnestic mild cognitive impairment (MCI) are found to have no significant Alzheimer's pathology based on amyloid PET positivity. Notably, conversion to dementia in this population is known to occur much less often than in amyloid-positive MCI. However, the relationship between MCI and brain amyloid deposition remains largely unknown. Therefore, we investigated the influence of subthreshold levels of amyloid deposition on conversion to dementia in amnestic MCI patients with negative amyloid PET scans.

METHODS

This study was a retrospective cohort study of patients with amyloid-negative amnestic MCI who visited the memory clinic of Asan Medical Center. All participants underwent detailed neuropsychological testing, brain magnetic resonance imaging, and [18F]-florbetaben (FBB) positron emission tomography scan (PET). Conversion to dementia was determined by a neurologist based on a clinical interview with a detailed neuropsychological test or a decline in the Korean version of the Mini-Mental State Examination score of more than 4 points per year combined with impaired activities of daily living. Regional cortical amyloid levels were calculated, and a receiver operating characteristic (ROC) curve for conversion to dementia was obtained. To increase the reliability of the results of the study, we analyzed the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset together.

RESULTS

During the follow-up period, 36% (39/107) of patients converted to dementia from amnestic MCI. The dementia converter group displayed increased standardized uptake value ratio (SUVR) values of FBB on PET in the bilateral temporal, parietal, posterior cingulate, occipital, and left precuneus cortices as well as increased global SUVR. Among volume of interests, the left parietal SUVR predicted conversion to dementia with the highest accuracy in the ROC analysis (area under the curve [AUC] = 0.762, P < 0.001). The combination of precuneus, parietal cortex, and FBB composite SUVRs also showed a higher accuracy in predicting conversion to dementia than other models (AUC = 0.763). Of the results of ADNI data, the SUVR of the left precuneus SUVR showed the highest AUC (AUC = 0.596, P = 0.006).

CONCLUSION

Our findings suggest that subthreshold amyloid levels may contribute to conversion to dementia in patients with amyloid-negative amnestic MCI.

Alzheimer’s Disease-Related Genes Identified by Linking Spatial Patterns of Pathology and Gene Expression

Background

Alzheimer’s Disease (AD) is an age-related neurodegenerative disease with a poorly understood etiology, shown to be partly genetic. Glucose hypometabolism, extracellular Amyloid-beta (Aβ) deposition, and intracellular Tau deposition are cardinal features of AD and display characteristic spatial patterns in the brain. We hypothesize that regional differences in underlying gene expression confer either resistance or susceptibility to AD pathogenic processes and are associated with these spatial patterns. Data-driven methods for the identification of genes involved in AD pathogenesis complement hypothesis-driven approaches that reflect current theories about the disease. Here we present a data driven method for the identification of genes involved in AD pathogenesis based on comparing spatial patterns of normal gene expression to Positron Emission Tomography (PET) images of glucose hypometabolism, Aβ deposition, and Tau deposition.

Methods

We performed correlations between the cerebral cortex microarray samples from the six cognitively normal (CN) post-mortem Allen Human Brain Atlas (AHBA) specimens and PET FDG-18, AV-45, and AV-1451 tracer images from AD and CN participants in the Alzheimer’s Disease and Neuroimaging Initiative (ADNI) database. Correlation coefficients for each gene by each ADNI subject were then entered into a partial least squares discriminant analysis (PLS-DA) to determine sets that best classified the AD and CN groups. Pathway analysis via BioPlanet 2019 was then used to infer the function of implicated genes.

Results

We identified distinct sets of genes strongly associated with each PET modality. Pathway analyses implicated novel genes involved in mitochondrial function, and Notch signaling, as well as genes previously associated with AD.

Conclusion

Using an unbiased approach, we derived sets of genes with expression patterns spatially associated with FDG hypometabolism, Aβ deposition, and Tau deposition in AD. This methodology may complement population-based approaches for identifying the genetic underpinnings of AD.

Multiplex Connectome Changes across the Alzheimer’s Disease Spectrum Using Gray Matter and Amyloid Data

The organization of the Alzheimer’s disease (AD) connectome has been studied using graph theory using single neuroimaging modalities such as positron emission tomography (PET) or structural magnetic resonance imaging (MRI). Although these modalities measure distinct pathological processes that occur in different stages in AD, there is evidence that they are not independent from each other. Therefore, to capture their interaction, in this study we integrated amyloid PET and gray matter MRI data into a multiplex connectome and assessed the changes across different AD stages. We included 135 cognitively normal (CN) individuals without amyloid-β pathology (Aβ−) in addition to 67 CN, 179 patients with mild cognitive impairment (MCI) and 132 patients with AD dementia who all had Aβ pathology (Aβ+) from the Alzheimer’s Disease Neuroimaging Initiative. We found widespread changes in the overlapping connectivity strength and the overlapping connections across Aβ-positive groups. Moreover, there was a reorganization of the multiplex communities in MCI Aβ + patients and changes in multiplex brain hubs in both MCI Aβ + and AD Aβ + groups. These findings offer a new insight into the interplay between amyloid-β pathology and brain atrophy over the course of AD that moves beyond traditional graph theory analyses based on single brain networks.

OUP accepted manuscript

Synaptic dysfunction is an early mechanism in Alzheimer’s disease that involves progressively larger areas of the brain over time. However, how it starts and propagates is unknown.

Here we show that amyloid-β released by microglia in association with large extracellular vesicles (Aβ-EVs) alters dendritic spine morphology in vitro, at the site of neuron interaction, and impairs synaptic plasticity both in vitro and in vivo in the entorhinal cortex–dentate gyrus circuitry. One hour after Aβ-EV injection into the mouse entorhinal cortex, long-term potentiation was impaired in the entorhinal cortex but not in the dentate gyrus, its main target region, while 24 h later it was also impaired in the dentate gyrus, revealing a spreading of long-term potentiation deficit between the two regions. Similar results were obtained upon injection of extracellular vesicles carrying Aβ naturally secreted by CHO7PA2 cells, while neither Aβ₄₂ alone nor inflammatory extracellular vesicles devoid of Aβ were able to propagate long-term potentiation impairment. Using optical tweezers combined to time-lapse imaging to study Aβ-EV–neuron interaction, we show that Aβ-EVs move anterogradely at the axon surface and that their motion can be blocked through annexin-V coating. Importantly, when Aβ-EV motility was inhibited, no propagation of long-term potentiation deficit occurred along the entorhinal–hippocampal circuit, implicating large extracellular vesicle motion at the neuron surface in the spreading of long-term potentiation impairment.

Our data indicate the involvement of large microglial extracellular vesicles in the rise and propagation of early synaptic dysfunction in Alzheimer’s disease and suggest a new mechanism controlling the diffusion of large extracellular vesicles and their pathogenic signals in the brain parenchyma, paving the way for novel therapeutic strategies to delay the disease.

Rich-Club Connectivity of the Structural Covariance Network Relates to Memory Processes in Mild Cognitive Impairment and Alzheimer's Disease

BACKGROUND

Though mediotemporal lobe volume changes are well-known features of Alzheimer's disease (AD), grey matter volume changes may be distributed throughout the brain. These distributed changes are not independent due to the underlying network structure and can be described in terms of a structural covariance network (SCN).

OBJECTIVE

To investigate how the cortical brain organization is altered in AD we studied the mutual connectivity of hubs in the SCN, i.e., the rich-club.

METHODS

To construct the SCNs, cortical thickness was obtained from structural MRI for 97 participants (normal cognition, n = 37; mild cognitive impairment, n = 41; Alzheimer-type dementia, n = 19). Subsequently, rich-club coefficients were calculated from the SCN, and related to memory performance and hippocampal volume using linear regression.

RESULTS

Lower rich-club connectivity was related to lower memory performance as well as lower hippocampal volume.

CONCLUSION

Therefore, this study provides novel evidence of reduced connectivity in hub areas in relation to AD-related cognitive impairments and atrophy.

Genetic and environmental factors in Alzheimer's and Parkinson's diseases and promising therapeutic intervention via fecal microbiota transplantation

Neurodegenerative diseases are characterized by neuronal impairment and loss of function, and with the major shared histopathological hallmarks of misfolding and aggregation of specific proteins inside or outside cells. Some genetic and environmental factors contribute to the promotion of the development and progression of neurodegenerative diseases. Currently, there are no effective treatments for neurodegenerative diseases. It has been revealed that bidirectional communication exists between the brain and the gut. The gut microbiota is a changeable and experience-dependent ecosystem and can be modified by genetic and environmental factors. The gut microbiota provides potential therapeutic targets that can be regulated as new interventions for neurodegenerative diseases. In this review, we discuss genetic and environmental risk factors for neurodegenerative diseases, summarize the communication among the components of the microbiota-gut-brain axis, and discuss the treatment strategy of fecal microbiota transplantation (FMT). FMT is a promising treatment for neurodegenerative diseases, and restoration of the gut microbiota to a premorbid state is a novel goal for prevention and treatment strategies.

18F-Flortaucipir PET Associations with Cerebrospinal Fluid, Cognition, and Neuroimaging in Mild Cognitive Impairment due to Alzheimer's Disease

BACKGROUND

Tau positron emission tomography (PET) imaging is used in research, but its relation to cerebrospinal fluid (CSF) tau and other Alzheimer's disease (AD)-related clinical measures is unclear in mild cognitive impairment with AD biomarkers (MCI-AD).

OBJECTIVE

To determine associations between 18F-flortaucipir PET and CSF AD biomarkers, cognitive functioning, and neuroimaging measures in MCI-AD.

METHODS

In 29 participants 50 years or older with MCI-AD, 18F-flortaucipir PET, CSF total tau (T-tau), phosphorylated tau181p (P-tau), amyloid-β (Aβ), structural MRI, and neuropsychological testing were collected as baseline assessments of an ongoing clinical trial. 11C-Pittsburgh compound B PET was simultaneously conducted in 20 participants. Associations between 18F-flortaucipir PET and these measures were assessed by multiple linear regression adjusted for potential confounders and using global, lobar, and voxel-wise standardized uptake value ratio (SUVr).

RESULTS

Whole brain 18F-flortaucipir SUVr was significantly associated with CSF T-tau (r = 0.68, p < 0.001) and P-tau (r = 0.42, p = 0.04) after adjusting for age, sex, race, and education, with strongest associations in the temporal region (T-tau: r = 0.69, p < 0.001; P-tau: r = 0.49, p = 0.02). Voxel-wise analysis confirmed these regional associations. 18F-flortaucipir PET was also associated with CSF Aβ (r = -0.45, p = 0.03), episodic memory (r = -0.61, p = 0.001), visuospatial working memory (r = -0.46, p = 0.02), and brain cortical thickness (r = -0.44, p = 0.03) but not hippocampal volume. In the amyloid PET subset, although 11C-PiB PET associated strongly with 18F-flortaucipir (r = 0.79, p≤0.001), associations were stronger between 11C-PiB and key outcomes, compared to 18F-flortaucipir.

CONCLUSION

18F-flortaucipir PET is moderately associated with CSF AD biomarkers and other AD-related phenotypes. The associations in this MCI-AD sample are stronger than previously described in other populations.

Clinical validity of increased cortical uptake of [18F]flortaucipir on PET as a biomarker for Alzheimer's disease in the context of a structured 5-phase biomarker development framework

PURPOSE

In 2017, the Geneva Alzheimer's disease (AD) Biomarker Roadmap initiative adapted the framework of the systematic validation of oncological diagnostic biomarkers to AD biomarkers, with the aim to accelerate their development and implementation in clinical practice. With this work, we assess the maturity of [18F]flortaucipir PET and define its research priorities.

METHODS

The level of maturity of [18F]flortaucipir was assessed based on the AD Biomarker Roadmap. The framework assesses analytical validity (phases 1-2), clinical validity (phases 3-4), and clinical utility (phase 5).

RESULTS

The main aims of phases 1 (rationale for use) and 2 (discriminative ability) have been achieved. [18F]Flortaucipir binds with high affinity to paired helical filaments of tau and has favorable kinetic properties and excellent discriminative accuracy for AD. The majority of secondary aims of phase 2 were fully achieved. Multiple studies showed high correlations between ante-mortem [18F]flortaucipir PET and post-mortem tau (as assessed by histopathology), and also the effects of covariates on tracer binding are well studied. The aims of phase 3 (early detection ability) were only partially or preliminarily achieved, and the aims of phases 4 and 5 were not achieved.

CONCLUSION

Current literature provides partial evidence for clinical utility of [18F]flortaucipir PET. The aims for phases 1 and 2 were mostly achieved. Phase 3 studies are currently ongoing. Future studies including representative MCI populations and a focus on healthcare outcomes are required to establish full maturity of phases 4 and 5.

KL-VS heterozygosity is associated with lower amyloid-dependent tau accumulation and memory impairment in Alzheimer's disease

Klotho-VS heterozygosity (KL-VS^het) is associated with reduced risk of Alzheimer’s disease (AD). However, whether KL-VS^het is associated with lower levels of pathologic tau, i.e., the key AD pathology driving neurodegeneration and cognitive decline, is unknown. Here, we assessed the interaction between KL-VS^het and levels of beta-amyloid, a key driver of tau pathology, on the levels of PET-assessed neurofibrillary tau in 551 controls and patients across the AD continuum. KL-VS^het showed lower cross-sectional and longitudinal increase in tau-PET per unit increase in amyloid-PET when compared to that of non-carriers. This association of KL-VS^het on tau-PET was stronger in Klotho mRNA-expressing brain regions mapped onto a gene expression atlas. KL-VS^het was related to better memory functions in amyloid-positive participants and this association was mediated by lower tau-PET. Amyloid-PET levels did not differ between KL-VS^het carriers versus non-carriers. Together, our findings provide evidence to suggest a protective role of KL-VS^het against amyloid-related tau pathology and tau-related memory impairments in elderly humans at risk of AD dementia.

The KL-VS haplotype of the Klotho gene has been associated with reduced risk of Alzheimer’s disease and dementia. Here the authors show an association between the KL-VS haplotype and amyloid-dependent tau accumulation using PET data.

Plasma markers predict changes in amyloid, tau, atrophy and cognition in non-demented subjects

It is currently unclear whether plasma biomarkers can be used as independent prognostic tools to predict changes associated with early Alzheimer's disease (AD). In this study we sought to address this question by assessing whether plasma biomarkers can predict changes in amyloid load, tau accumulation, brain atrophy and cognition in non-demented individuals. To achieve this, plasma amyloid-β 42/40 (Aβ42/40), phosphorylated-tau181 (P-tau181), phosphorylated-tau217 (P-tau217) and neurofilament light (NfL) were determined in 159 non-demented individuals, 123 patients with AD dementia and 35 patients with a non-AD dementia from the Swedish BioFINDER-2 study, who underwent longitudinal amyloid (18 F-flutemetamol) and tau (18 F-RO948) positron emission tomography (PET), structural magnetic resonance imaging (T1-weighted) and cognitive testing. Our univariate linear mixed effect models showed there were several significant associations between the plasma biomarkers with imaging and cognitive measures. However, when all biomarkers were included in the same multivariate linear mixed effect models, we found that increased longitudinal amyloid-PET signals were independently predicted by low baseline plasma Aβ42/40 (p = 0.012), whereas increased tau-PET signals, brain atrophy and worse cognition were independently predicted by high plasma P-tau217 (p < 0.004). These biomarkers performed equally well or better than the corresponding biomarkers measured in the cerebrospinal fluid. In addition, they showed a similar performance to binary plasma biomarker values defined using the Youden index, which can be more easily implemented in the clinic. In addition, plasma Aβ42/40 and P-tau217 did not predict longitudinal changes in patients with a non-AD neurodegenerative disorder. In conclusion, our findings indicate that plasma Aβ42/40 and P-tau217 could be useful in clinical practice, research and drug development as prognostic markers of future AD pathology.

Graph Models of Pathology Spread in Alzheimer's Disease: An Alternative to Conventional Graph Theoretic Analysis

Background: Graph theory and connectomics are new techniques for uncovering disease-induced changes in the brain's structural network. Most prior studied have focused on network statistics as biomarkers of disease. However, an emerging body of work involves exploring how the network serves as a conduit for the propagation of disease factors in the brain and has successfully mapped the functional and pathological consequences of disease propagation. In Alzheimer's disease (AD), progressive deposition of misfolded proteins amyloid and tau is well-known to follow fiber projections, under a "prion-like" trans-neuronal transmission mechanism, through which misfolded proteins cascade along neuronal pathways, giving rise to network spread. Methods: In this review, we survey the state of the art in mathematical modeling of connectome-mediated pathology spread in AD. Then we address several open questions that are amenable to mathematically precise parsimonious modeling of pathophysiological processes, extrapolated to the whole brain. We specifically identify current formal models of how misfolded proteins are produced, aggregate, and disseminate in brain circuits, and attempt to understand how this process leads to stereotyped progression in Alzheimer's and other related diseases. Conclusion: This review serves to unify current efforts in modeling of AD progression that together have the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testing in silico. Impact statement Graph theory is a powerful new approach that is transforming the study of brain processes. There do not exist many focused reviews of the subfield of graph modeling of how Alzheimer's and other dementias propagate within the brain network, and how these processes can be mapped mathematically. By providing timely and topical review of this subfield, we fill a critical gap in the community and present a unified view that can serve as an in silico test-bed for future hypothesis generation and testing. We also point to several open and unaddressed questions and controversies that future practitioners can tackle.

Bundle-specific associations between white matter microstructure and Aβ and tau pathology in preclinical Alzheimer's disease

Beta-amyloid (Aβ) and tau proteins, the pathological hallmarks of Alzheimer's disease (AD), are believed to spread through connected regions of the brain. Combining diffusion imaging and positron emission tomography, we investigated associations between white matter microstructure specifically in bundles connecting regions where Aβ or tau accumulates and pathology. We focused on free-water-corrected diffusion measures in the anterior cingulum, posterior cingulum, and uncinate fasciculus in cognitively normal older adults at risk of sporadic AD and presymptomatic mutation carriers of autosomal dominant AD. In Aβ-positive or tau-positive groups, lower tissue fractional anisotropy and higher mean diffusivity related to greater Aβ and tau burden in both cohorts. Associations were found in the posterior cingulum and uncinate fasciculus in preclinical sporadic AD, and in the anterior and posterior cingulum in presymptomatic mutation carriers. These results suggest that microstructural alterations accompany pathological accumulation as early as the preclinical stage of both sporadic and autosomal dominant AD.

PET Neuroimaging of Alzheimer's Disease: Radiotracers and Their Utility in Clinical Research

Alzheimer's Disease (AD), the leading cause of senile dementia, is a progressive neurodegenerative disorder affecting millions of people worldwide and exerting tremendous socioeconomic burden on all societies. Although definitive diagnosis of AD is often made in the presence of clinical manifestations in late stages, it is now universally believed that AD is a continuum of disease commencing from the preclinical stage with typical neuropathological alterations appearing decades prior to its first symptom, to the prodromal stage with slight symptoms of amnesia (amnestic mild cognitive impairment, aMCI), and then to the terminal stage with extensive loss of basic cognitive functions, i.e., AD-dementia. Positron emission tomography (PET) radiotracers have been developed in a search to meet the increasing clinical need of early detection and treatment monitoring for AD, with reference to the pathophysiological targets in Alzheimer's brain. These include the pathological aggregations of misfolded proteins such as β-amyloid (Aβ) plagues and neurofibrillary tangles (NFTs), impaired neurotransmitter system, neuroinflammation, as well as deficient synaptic vesicles and glucose utilization. In this article we survey the various PET radiotracers available for AD imaging and discuss their clinical applications especially in terms of early detection and cognitive relevance.

Network interdigitations of Tau and amyloid-beta deposits define cognitive levels in aging

Amyloid‐beta (Aβ) plaques and tau neurofibrillary tangles are pathological hallmarks of Alzheimer's disease (AD); their contribution to neurodegeneration and clinical manifestations are critical in understanding preclinical AD. At present, the mechanisms related to Aβ and tau pathogenesis leading to cognitive decline in older adults remain largely unknown. Here, we examined graph theory‐based positron emission tomography (PET) analytical approaches, within and between tau and Aβ PET modalities, and tested the effects on cognitive changes in cognitively normal older adults (CN). Particularly, we focused on the network interdigitations of Aβ and tau deposits, along with cognitive test scores in CN at both baseline and 2‐year follow‐up (FU). We found highly significant Aβ‐tau network integrations in AD vulnerable areas, as well as significant associations between those Aβ‐tau interdigitations and general cognitive impairment in CN at baseline and FU. Our findings suggest a distinctive contribution of interlinking network relationships between Aβ and tau deposits in heteromodal areas of the human brain. They support a network‐based interaction between Aβ and tau accumulations as a key factor for cognitive deterioration in CN prior to dementia.

Longitudinal predictive modeling of tau progression along the structural connectome

Tau neurofibrillary tangles, a pathophysiological hallmark of Alzheimer's disease (AD), exhibit a stereotypical spatiotemporal trajectory that is strongly correlated with disease progression and cognitive decline. Personalized prediction of tau progression is, therefore, vital for the early diagnosis and prognosis of AD. Evidence from both animal and human studies is suggestive of tau transmission along the brains preexisting neural connectivity conduits. We present here an analytic graph diffusion framework for individualized predictive modeling of tau progression along the structural connectome. To account for physiological processes that lead to active generation and clearance of tau alongside passive diffusion, our model uses an inhomogenous graph diffusion equation with a source term and provides closed-form solutions to this equation for linear and exponential source functionals. Longitudinal imaging data from two cohorts, the Harvard Aging Brain Study (HABS) and the Alzheimer's Disease Neuroimaging Initiative (ADNI), were used to validate the model. The clinical data used for developing and validating the model include regional tau measures extracted from longitudinal positron emission tomography (PET) scans based on the ¹⁸F-Flortaucipir radiotracer and individual structural connectivity maps computed from diffusion tensor imaging (DTI) by means of tractography and streamline counting. Two-timepoint tau PET scans were used to assess the goodness of model fit. Three-timepoint tau PET scans were used to assess predictive accuracy via comparison of predicted and observed tau measures at the third timepoint. Our results show high consistency between predicted and observed tau and differential tau from region-based analysis. While the prognostic value of this approach needs to be validated in a larger cohort, our preliminary results suggest that our longitudinal predictive model, which offers an in vivo macroscopic perspective on tau progression in the brain, is potentially promising as a personalizable predictive framework for AD.

A Graph Gaussian Embedding Method for Predicting Alzheimer's Disease Progression With MEG Brain Networks

Characterizing the subtle changes of functional brain networks associated with the pathological cascade of Alzheimer's disease (AD) is important for early diagnosis and prediction of disease progression prior to clinical symptoms. We developed a new deep learning method, termed multiple graph Gaussian embedding model (MG2G), which can learn highly informative network features by mapping high-dimensional resting-state brain networks into a low-dimensional latent space. These latent distribution-based embeddings enable a quantitative characterization of subtle and heterogeneous brain connectivity patterns at different regions, and can be used as input to traditional classifiers for various downstream graph analytic tasks, such as AD early stage prediction, and statistical evaluation of between-group significant alterations across brain regions. We used MG2G to detect the intrinsic latent dimensionality of MEG brain networks, predict the progression of patients with mild cognitive impairment (MCI) to AD, and identify brain regions with network alterations related to MCI.

In vitro Characterization of the Regional Binding Distribution of Amyloid PET Tracer Florbetaben and the Glia Tracers Deprenyl and PK11195 in Autopsy Alzheimer's Brain Tissue

BACKGROUND

Emerging evidence indicates a central role of gliosis in Alzheimer's disease (AD) pathophysiology. However, the regional distribution and interaction of astrogliosis and microgliosis in association with amyloid-β (Aβ) still remain uncertain.

OBJECTIVE

Here we studied the pathological profiles in autopsy AD brain by using specific imaging tracers.

METHODS

Autopsy brain tissues of AD (n = 15, age 70.4±8.5 years) and control cases (n = 12, age 76.6±10.9) were examined with homogenate binding assays, autoradiography for Aβ plaques (3H-florbetaben/3H-PIB), astrogliosis (3H-L-deprenyl), and microgliosis (3H-PK11195/3H-FEMPA), as well as immunoassays.

RESULTS

In vitro saturation analysis revealed high-affinity binding sites of 3H-florbetaben, 3H-L-deprenyl, and 3H-PK11195/3H-FEMPA in the frontal cortex of AD cases. In vitro3H-florbetaben binding increased across cortical and subcortical regions of AD compared to control with the highest binding in the frontal and parietal cortices. The in vitro3H-L-deprenyl binding showed highest binding in the hippocampus (dentate gyrus) followed by cortical and subcortical regions of AD while the GFAP expression was upregulated only in the hippocampus compared to control. The in vitro3H-PK11195 binding was solely increased in the parietal cortex and the hippocampus of AD compared to control. The 3H-florbetaben binding positively correlated with the 3H-L-deprenyl binding in the hippocampus and parietal cortex of AD and controls. Similarly, a positive correlation was observed between 3H-florbetaben binding and GFAP expression in hippocampus of AD and control.

CONCLUSION

The use of multi-imaging tracers revealed different regional pattern of changes in autopsy AD brain with respect to amyloid plaque pathology versus astrogliosis and microgliosis.

Diagnostic Classification and Biomarker Identification of Alzheimer's Disease with Random Forest Algorithm

Random Forest (RF) is a bagging ensemble model and has many important advantages, such as robustness to noise, an effective structure for complex multimodal data and parallel computing, and also provides important features that help investigate biomarkers. Despite these benefits, RF is not used actively to predict Alzheimer's disease (AD) with brain MRIs. Recent studies have reported RF's effectiveness in predicting AD, but the test sample sizes were too small to draw any solid conclusions. Thus, it is timely to compare RF with other learning model methods, including deep learning, particularly with large amounts of data. In this study, we tested RF and various machine learning models with regional volumes from 2250 brain MRIs: 687 normal controls (NC), 1094 mild cognitive impairment (MCI), and 469 AD that ADNI (Alzheimer's Disease Neuroimaging Initiative database) provided. Three types of features sets (63, 29, and 22 features) were selected, and classification accuracies were computed with RF, Support vector machine (SVM), Multi-layer perceptron (MLP), and Convolutional neural network (CNN). As a result, RF, MLP, and CNN showed high performances of 90.2%, 89.6%, and 90.5% with 63 features. Interestingly, when 22 features were used, RF showed the smallest decrease in accuracy, -3.8%, and the standard deviation did not change significantly, while MLP and CNN yielded decreases in accuracy of -6.8% and -4.5% with changes in the standard deviation from 3.3% to 4.0% for MLP and 2.1% to 7.0% for CNN, indicating that RF predicts AD more reliably with fewer features. In addition, we investigated the importance of the features that RF provides, and identified the hippocampus, amygdala, and inferior lateral ventricle as the major contributors in classifying NC, MCI, and AD. On average, AD showed smaller hippocampus and amygdala volumes and a larger volume of inferior lateral ventricle than those of MCI and NC.

PET imaging of neural activity, β-amyloid, and tau in normal brain aging

Normal brain aging is commonly associated with neural activity alteration, β-amyloid (Aβ) deposition, and tau aggregation, driving a progressive cognitive decline in normal elderly individuals. Positron emission tomography (PET) with radiotracers targeting these age-related changes has been increasingly employed to clarify the sequence of their occurrence and the evolution of clinically cognitive deficits. Herein, we reviewed recent literature on PET-based imaging of normal human brain aging in terms of neural activity, Aβ, and tau. Neural hypoactivity reflected by decreased glucose utilization with PET imaging has been predominately reported in the frontal, cingulate, and temporal lobes of the normal aging brain. Aβ PET imaging uncovers the pathophysiological association of Aβ deposition with cognitive aging, as well as the potential mechanisms. Tau-associated cognitive changes in normal aging are likely independent of but facilitated by Aβ as indicated by tau and Aβ PET imaging. Future longitudinal studies using multi-radiotracer PET imaging combined with other neuroimaging modalities, such as magnetic resonance imaging (MRI) morphometry, functional MRI, and magnetoencephalography, are essential to elucidate the neuropathological underpinnings and interactions in normal brain aging.

Transfer learning for predicting conversion from mild cognitive impairment to dementia of Alzheimer's type based on a three-dimensional convolutional neural network

Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT is an ongoing challenge in the field. We developed a deep learning model to predict conversion from MCI to DAT. Structural magnetic resonance imaging scans were used as input to a 3-dimensional convolutional neural network. The 3-dimensional convolutional neural network was trained using transfer learning; in the source task, normal control and DAT scans were used to pretrain the model. This pretrained model was then retrained on the target task of classifying which MCI patients converted to DAT. Our model resulted in 82.4% classification accuracy at the target task, outperforming current models in the field. Next, we visualized brain regions that significantly contribute to the prediction of MCI conversion using an occlusion map approach. Contributory regions included the pons, amygdala, and hippocampus. Finally, we showed that the model's prediction value is significantly correlated with rates of change in clinical assessment scores, indicating that the model is able to predict an individual patient's future cognitive decline. This information, in conjunction with the identified anatomical features, will aid in building a personalized therapeutic strategy for individuals with MCI.

Crosstalk between Depression and Dementia with Resting-State fMRI Studies and Its Relationship with Cognitive Functioning

Alzheimer’s disease (AD) is the most common type of dementia, and depression is a risk factor for developing AD. Epidemiological studies provide a clinical correlation between late-life depression (LLD) and AD. Depression patients generally remit with no residual symptoms, but LLD patients demonstrate residual cognitive impairment. Due to the lack of effective treatments, understanding how risk factors affect the course of AD is essential to manage AD. Advances in neuroimaging, including resting-state functional MRI (fMRI), have been used to address neural systems that contribute to clinical symptoms and functional changes across various psychiatric disorders. Resting-state fMRI studies have contributed to understanding each of the two diseases, but the link between LLD and AD has not been fully elucidated. This review focuses on three crucial and well-established networks in AD and LLD and discusses the impacts on cognitive decline, clinical symptoms, and prognosis. Three networks are the (1) default mode network, (2) executive control network, and (3) salience network. The multiple properties emphasized here, relevant for the hypothesis of the linkage between LLD and AD, will be further developed by ongoing future studies.