Functional connectivity associated with tau levels in ageing, Alzheimer's, and small vessel disease

Targeting papez circuit for cognitive dysfunction- insights into deep brain stimulation for Alzheimer's disease

Hippocampus is the most widely studied brain area coupled with impairment of memory in a variety of neurological diseases and Alzheimer's disease (AD). The limbic structures within the Papez circuit have been linked to various aspects of cognition. Unfortunately, the brain regions that include this memory circuit are often ignored in terms of understanding cognitive decline in these diseases. To properly comprehend where cognition problems originate, it is crucial to clarify any aberrant contributions from all components of a specific circuit -on both a local and a global level. The pharmacological treatments currently available are not long lasting. Deep Brain Stimulation (DBS) emerged as a new powerful therapeutic approach for alleviation of the cognitive dysfunctions. Metabolic, functional, electrophysiological, and imaging studies helped to find out the crucial nodes that can be accessible for DBS. Targeting these nodes within the memory circuit produced significant improvement in learning and memory by disrupting abnormal circuit activity and restoring the physiological network. Here, we provide an overview of the neuroanatomy of the circuit of Papez along with the mechanisms and various deep brain stimulation targets of the circuit structures which could be significant for improving cognitive dysfunctions in AD.

Biomarkers of Aging and Relevant Evaluation Techniques: A Comprehensive Review

The risk of developing chronic illnesses and disabilities is increasing with age. To predict and prevent aging, biomarkers relevant to the aging process must be identified. This paper reviews the known molecular, cellular, and physiological biomarkers of aging. Moreover, we discuss the currently available technologies for identifying these biomarkers, and their applications and potential in aging research. We hope that this review will stimulate further research and innovation in this emerging and fast-growing field.

Characterization of tau propagation pattern and cascading hypometabolism from functional connectivity in Alzheimer's disease

Tau pathology and its spatial propagation in Alzheimer's disease (AD) play crucial roles in the neurodegenerative cascade leading to dementia. However, the underlying mechanisms linking tau spreading to glucose metabolism remain elusive. To address this, we aimed to examine the association between pathologic tau aggregation, functional connectivity, and cascading glucose metabolism and further explore the underlying interplay mechanisms. In this prospective cohort study, we enrolled 79 participants with 18F-Florzolotau positron emission tomography (PET), 18F-fluorodeoxyglucose PET, resting-state functional, and anatomical magnetic resonance imaging (MRI) images in the hospital-based Shanghai Memory Study. We employed generalized linear regression and correlation analyses to assess the associations between Florzolotau accumulation, functional connectivity, and glucose metabolism in whole-brain and network-specific manners. Causal mediation analysis was used to evaluate whether functional connectivity mediates the association between pathologic tau and cascading glucose metabolism. We examined 22 normal controls and 57 patients with AD. In the AD group, functional connectivity was associated with Florzolotau covariance (β = .837, r = 0.472, p < .001) and glucose covariance (β = 1.01, r = 0.499, p < .001). Brain regions with higher tau accumulation tend to be connected to other regions with high tau accumulation through functional connectivity or metabolic connectivity. Mediation analyses further suggest that functional connectivity partially modulates the influence of tau accumulation on downstream glucose metabolism (mediation proportion: 49.9%). Pathologic tau may affect functionally connected neurons directly, triggering downstream glucose metabolism changes. This study sheds light on the intricate relationship between tau pathology, functional connectivity, and downstream glucose metabolism, providing critical insights into AD pathophysiology and potential therapeutic targets.

Shaping the future of preclinical development of successful disease-modifying drugs against Alzheimer's disease: a systematic review of tau propagation models

The transcellular propagation of the aberrantly modified protein tau along the functional brain network is a key hallmark of Alzheimer's disease and related tauopathies. Inoculation-based tau propagation models can recapitulate the stereotypical spread of tau and reproduce various types of tau inclusions linked to specific tauopathy, albeit with varying degrees of fidelity. With this systematic review, we underscore the significance of judicious selection and meticulous functional, biochemical, and biophysical characterization of various tau inocula. Furthermore, we highlight the necessity of choosing suitable animal models and inoculation sites, along with the critical need for validation of fibrillary pathology using confirmatory staining, to accurately recapitulate disease-specific inclusions. As a practical guide, we put forth a framework for establishing a benchmark of inoculation-based tau propagation models that holds promise for use in preclinical testing of disease-modifying drugs.

Micromotor-based electrochemical immunoassays for reliable determination of amyloid-β (1-42) in Alzheimer's diagnosed clinical samples

Alzheimer's disease (AD), in addition to being the most common cause of dementia, is very difficult to diagnose, with the 42-amino acid form of Aβ (Aβ-42) being one of the main biomarkers used for this purpose. Despite the enormous efforts made in recent years, the technologies available to determine Aβ-42 in human samples require sophisticated instrumentation, present high complexity, are sample and time-consuming, and are costly, highlighting the urgent need not only to develop new tools to overcome these limitations but to provide an early detection and treatment window for AD, which is a top-challenge. In recent years, micromotor (MM) technology has proven to add a new dimension to clinical biosensing, enabling ultrasensitive detections in short times and microscale environments. To this end, here an electrochemical immunoassay based on polypyrrole (PPy)/nickel (Ni)/platinum nanoparticles (PtNPs) MM is proposed in a pioneering manner for the determination of Aβ-42 in left prefrontal cortex brain tissue, cerebrospinal fluid, and plasma samples from patients with AD. MM combines the high binding capacity of their immunorecognition external layer with self-propulsion through the catalytic generation of oxygen bubbles in the internal layer due to decomposition of hydrogen peroxide as fuel, allowing rapid bio-detection (15 min) of Aβ-42 with excellent selectivity and sensitivity (LOD = 0.06 ng/mL). The application of this disruptive technology to the analysis of just 25 μL of the three types of clinical samples provides values concordant with the clinical values reported, thus confirming the potential of the MM approach to assist in the reliable, simple, fast, and affordable diagnosis of AD by determining Aβ-42.

Examining the relationship between brain activation and proxies of disease severity using quantile regression in individuals at risk of Alzheimer's disease

Previous studies have reported a pattern of hyperactivation in the pre-dementia phase of Alzheimer's disease (AD), followed by hypoactivation in later stages of the disease. This pattern was modeled as an inverse U-shape function between activation and markers of disease severity. In this study, we used quantile regression to model the association between task-related brain activation in AD signature regions and three markers of disease severity (hippocampal volume, cortical thickness, and associative memory). This approach offers distinct advantages over standard regression models as it analyzes the relationship between brain activation and disease severity across various levels of brain activation. Participants were 54 older adults with subjective cognitive decline+ (SCD+) or mild cognitive impairment (MCI) from the CIMA-Q cohort. The analysis revealed an inverse U-shape quadratic function depicting the relationship between disease severity markers and the activation of the left superior parietal region, while a linear relationship was observed for activation of the hippocampal and temporal regions. Quantile differences were observed for temporal and parietal activation, with more pronounced effects observed in the higher quantiles of activation. When comparing quantiles, we found that higher quantile of activation featured a greater number of individuals with SCD+ compared to mild cognitive impairment (MCI). Results are globally consistent with the presence of an inverse-U shape function of activation in relation to disease severity. They study also underscores the utility of employing quantile regression modeling as the modeling approach revealed the presence of non-homogeneous effects across various quantiles.

Deconstructing pathological tau by biological process in early stages of Alzheimer disease: a method for quantifying tau spatial spread in neuroimaging

BACKGROUND

Neuroimaging studies often quantify tau burden in standardized brain regions to assess Alzheimer disease (AD) progression. However, this method ignores another key biological process in which tau spreads to additional brain regions. We have developed a metric for calculating the extent tau pathology has spread throughout the brain and evaluate the relationship between this metric and tau burden across early stages of AD.

METHODS

445 cross-sectional participants (aged ≥ 50) who had MRI, amyloid PET, tau PET, and clinical testing were separated into disease-stage groups based on amyloid positivity and cognitive status (older cognitively normal control, preclinical AD, and symptomatic AD). Tau burden and tau spatial spread were calculated for all participants.

FINDINGS

We found both tau metrics significantly elevated across increasing disease stages (p < 0.0001) and as a function of increasing amyloid burden for participants with preclinical (p < 0.0001, p = 0.0056) and symptomatic (p = 0.010, p = 0.0021) AD. An interaction was found between tau burden and tau spatial spread when predicting amyloid burden (p = 0.00013). Analyses of slope between tau metrics demonstrated more spread than burden in preclinical AD (β = 0.59), but then tau burden elevated relative to spread (β = 0.42) once participants had symptomatic AD, when the tau metrics became highly correlated (R = 0.83).

INTERPRETATION

Tau burden and tau spatial spread are both strong biomarkers for early AD but provide unique information, particularly at the preclinical stage. Tau spatial spread may demonstrate earlier changes than tau burden which could have broad impact in clinical trial design.

FUNDING

This research was supported by the Knight Alzheimer Disease Research Center (Knight ADRC, NIH grants P30AG066444, P01AG026276, P01AG003991), Dominantly Inherited Alzheimer Network (DIAN, NIH grants U01AG042791, U19AG03243808, R01AG052550-01A1, R01AG05255003), and the Barnes-Jewish Hospital Foundation Willman Scholar Fund.

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

It is well known that Aβ and tau proteins are deposited stereotypically in brain regions to cause Alzheimer's disease. The interaction of amyloid and tau in neurodegenerative diseases is a central feature and key to understanding AD pathophysiology. However their mechanisms are controversial, and many aspects do not fit current theories that rely on cell-autonomous factors. While cell culture and animal studies point to various interaction mechanisms between amyloid and tau, their causal direction and mode (local, remote or network-mediated) remain unknown in human subjects. Further, cross-protein interaction is yet to be reconciled with canonical observations that the two species do not co-localize significantly either in space or in time, and do not target the same neuronal populations. To answer these questions quantitatively, in this study we employed a mathematical reaction-diffusion model encoding the biophysical mechanisms underlying self-assembly, trans-neuronal network propagation and enzymtic cross-species coupling of amyloid and tau. We first established that the spatiotemporal evolution of theoretical tau and Aβ correctly predicts empirical patterns of regional Aβ, tau and atrophy. Remarkably, the introduction of a 1-way Aβ→tau interaction was critical to the models' success. In comparison, both the non-interacting and the 2-way interaction models were significantly worse. We also found that network-mediated spread is essential; alternative modes of spread involving proximity or fiber length fare much worse. This mathematical exposition of the "pas de deux" of co-evolving proteins provides crucial quantitative and 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.

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.

Associations between Education Years and Resting-state Functional Connectivity Modulated by APOE ε4 Carrier Status in Cognitively Normal Older Adults

Objective

: Cognitive reserve has emerged as a concept to explain the variable expression of clinical symptoms in the pathology of Alzheimer's disease (AD). The association between years of education, a proxy of cognitive reserve, and resting-state functional connectivity (rFC), a representative intermediate phenotype, has not been explored in the preclinical phase, considering risk factors for AD. We aimed to evaluate whether the relationship between years of education and rFC in cognitively preserved older adults differs depending on amyloid-beta deposition and APOE ε4 carrier status as effect modifiers.

Methods

: A total of 121 participants underwent functional magnetic resonance imaging, [18F] flutemetamol positron emission tomography-computed tomography, APOE genotyping, and a neuropsychological battery. Potential interactions between years of education and AD risk factors for rFC of AD-vulnerable neural networks were assessed with whole-brain voxel-wise analysis.

Results

: We found a significant education years-by-APOE ε4 carrier status interaction for the rFC from the seed region of the central executive (CEN) and dorsal attention networks. Moreover, there was a significant interaction of rFC between right superior occipital gyrus and the CEN seed region by APOE ε4 carrier status for memory performances and overall cognitive function.

Conclusion

: In preclinical APOE ε4 carriers, higher years of education were associated with higher rFC of the AD vulnerable network, but this contributed to lower cognitive function. These results contribute to a deeper understanding of the impact of cognitive reserve on sensitive functional intermediate phenotypic markers in the preclinical phase of AD.

Combined Connectomics, MAPT Gene Expression, and Amyloid Deposition to Explain Regional Tau Deposition in Alzheimer Disease

OBJECTIVE

We aimed to test whether region-specific factors, including spatial expression patterns of the tau-encoding gene MAPT and regional levels of amyloid positron emission tomography (PET), enhance connectivity-based modeling of the spatial variability in tau-PET deposition in the Alzheimer disease (AD) spectrum.

METHODS

We included 685 participants (395 amyloid-positive participants within AD spectrum and 290 amyloid-negative controls) with tau-PET and amyloid-PET from 3 studies (Alzheimer's Disease Neuroimaging Initiative, 18 F-AV-1451-A05, and BioFINDER-1). Resting-state functional magnetic resonance imaging was obtained in healthy controls (n = 1,000) from the Human Connectome Project, and MAPT gene expression from the Allen Human Brain Atlas. Based on a brain-parcellation atlas superimposed onto all modalities, we obtained region of interest (ROI)-to-ROI functional connectivity, ROI-level PET values, and MAPT gene expression. In stepwise regression analyses, we tested connectivity, MAPT gene expression, and amyloid-PET as predictors of group-averaged and individual tau-PET ROI values in amyloid-positive participants.

RESULTS

Connectivity alone explained 21.8 to 39.2% (range across 3 studies) of the variance in tau-PET ROI values averaged across amyloid-positive participants. Stepwise addition of MAPT gene expression and amyloid-PET increased the proportion of explained variance to 30.2 to 46.0% and 45.0 to 49.9%, respectively. Similarly, for the prediction of patient-level tau-PET ROI values, combining all 3 predictors significantly improved the variability explained (mean adjusted R2 range across studies = 0.118-0.148, 0.156-0.196, and 0.251-0.333 for connectivity alone, connectivity plus MAPT expression, and all 3 modalities combined, respectively).

INTERPRETATION

Across 3 study samples, combining the functional connectome and molecular properties substantially enhanced the explanatory power compared to single modalities, providing a valuable tool to explain regional susceptibility to tau deposition in AD. ANN NEUROL 2024;95:274-287.

Edge time series components of functional connectivity and cognitive function in Alzheimer's disease

Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer's disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer's Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer's disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.

Resting-state alterations in behavioral variant frontotemporal dementia are related to the distribution of monoamine and GABA neurotransmitter systems

Background

Aside to clinical changes, behavioral variant frontotemporal dementia (bvFTD) is characterized by progressive structural and functional alterations in frontal and temporal regions. We examined if there is a selective vulnerability of specific neurotransmitter systems in bvFTD by evaluating the link between disease-related functional alterations and the spatial distribution of specific neurotransmitter systems and their underlying gene expression levels.

Methods

Maps of fractional amplitude of low-frequency fluctuations (fALFF) were derived as a measure of local activity from resting-state functional magnetic resonance imaging for 52 bvFTD patients (mean age = 61.5 ± 10.0 years; 14 females) and 22 healthy controls (HC) (mean age = 63.6 ± 11.9 years; 13 females). We tested if alterations of fALFF in patients co-localize with the non-pathological distribution of specific neurotransmitter systems and their coding mRNA gene expression. Furthermore, we evaluated if the strength of co-localization is associated with the observed clinical symptoms.

Results

Patients displayed significantly reduced fALFF in frontotemporal and frontoparietal regions. These alterations co-localized with the distribution of serotonin (5-HT1b and 5-HT2a) and γ-aminobutyric acid type A (GABAa) receptors, the norepinephrine transporter (NET), and their encoding mRNA gene expression. The strength of co-localization with NET was associated with cognitive symptoms and disease severity of bvFTD.

Conclusions

Local brain functional activity reductions in bvFTD followed the distribution of specific neurotransmitter systems indicating a selective vulnerability. These findings provide novel insight into the disease mechanisms underlying functional alterations. Our data-driven method opens the road to generate new hypotheses for pharmacological interventions in neurodegenerative diseases even beyond bvFTD.

Funding

This study has been supported by the German Consortium for Frontotemporal Lobar Degeneration, funded by the German Federal Ministry of Education and Research (BMBF; grant no. FKZ01GI1007A).

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

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

Remote Associations Between Tau and Cortical Amyloid-β Are Stage-Dependent

Background

Histopathologic studies of Alzheimer's disease (AD) suggest that extracellular amyloid-β (Aβ) plaques promote the spread of neurofibrillary tau tangles. However, these two proteinopathies initiate in spatially distinct brain regions, so how they interact during AD progression is unclear.

Objective

In this study, we utilized Aβ and tau positron emission tomography (PET) scans from 572 older subjects (476 healthy controls (HC), 14 with mild cognitive impairment (MCI), 82 with mild AD), at varying stages of the disease, to investigate to what degree tau is associated with cortical Aβ deposition.

Methods

Using multiple linear regression models and a pseudo-longitudinal ordering technique, we investigated remote tau-Aβ associations in four pathologic phases of AD progression based on tau spread: 1) no-tau, 2) pre-acceleration, 3) acceleration, and 4) post-acceleration.

Results

No significant tau-Aβ association was detected in the no-tau phase. In the pre-acceleration phase, the earliest stage of tau deposition, associations emerged between regional tau in medial temporal lobe (MTL) (i.e., entorhinal cortex, parahippocampal gyrus) and cortical Aβ in lateral temporal lobe regions. The strongest tau-Aβ associations were found in the acceleration phase, in which tau in MTL regions was strongly associated with cortical Aβ (i.e., temporal and frontal lobes regions). Strikingly, in the post-acceleration phase, including 96% of symptomatic subjects, tau-Aβ associations were no longer significant.

Conclusions

The results indicate that associations between tau and Aβ are stage-dependent, which could have important implications for understanding the interplay between these two proteinopathies during the progressive stages of AD.

Edge Time Series Components of Functional Connectivity and Cognitive Function in Alzheimer's Disease

Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer's disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer's Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer's disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.

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 trajectory in Alzheimer's disease: Evidence from the connectome-based computational models

Alzheimer's disease (AD) is a progressive neurodegenerative disorder with an impairment of cognition and memory. Current research on connectomics have now related changes in the network organization in AD to the patterns of accumulation and spread of amyloid and tau, providing insights into the neurobiological mechanisms of the disease. In addition, network analysis and modeling focus on particular use of graphs to provide intuition into key organizational principles of brain structure, that stipulate how neural activity propagates along structural connections. The utility of connectome-based computational models aids in early predicting, tracking the progression of biomarker-directed AD neuropathology. In this article, we present a short review of tau trajectory, the connectome changes in tau pathology, and the dependent recent connectome-based computational modelling approaches for tau spreading, reproducing pragmatic findings, and developing significant novel tau targeted therapies.

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.

Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight

Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.

Effect of Alzheimer's Pathology on Task-Related Brain Network Reconfiguration in Aging

Large-scale brain networks undergo widespread changes with older age and in neurodegenerative diseases such as Alzheimer's disease (AD). Research in young adults (YA) suggest that the underlying functional architecture of brain networks remains relatively consistent between rest and task states. However, it remains unclear whether the same is true in aging and to what extent any changes may be related to accumulation of AD pathology such as β-amyloid (Aβ) and tau. Here, we examined age-related differences in functional connectivity (FC) between rest and an object-scene mnemonic discrimination task using fMRI in young and older adults (OA; both females and males). We used an a priori episodic memory network (EMN) parcellation scheme associated with object and scene processing, that included anterior-temporal regions and posterior-medial regions. We also used positron emission topography to measure Aβ and tau in older adults. The correlation between rest and task FC (i.e., FC similarity) was reduced in older compared with younger adults. Older adults with lower FC similarity in EMN had higher levels of tau in the same EMN regions and performed worse during object, but not scene, trials during the fMRI task. These findings link AD pathology, particularly tau, to a less stable functional architecture in memory networks. They also suggest that smaller changes in FC organization between rest and task states may facilitate better performance in older age. Interpretations are limited by methodological factors related to different acquisition directions and durations between rest and task scans.SIGNIFICANCE STATEMENT The brain's large-scale network organization is relatively consistent between rest and task states in young adults (YA). We found that memory networks in older adults (OA) were less correlated between rest and (memory) task states compared with young adults. Older adults with less correlated brain networks also had higher levels of Alzheimer's disease (AD) pathology in the same regions, suggesting that a less stable network architecture may reflect the early evolution of AD. Older adults with less correlated brain networks also performed worse during the memory task suggesting that more similar network organization between rest and task states may facilitate better performance in older age.

Global brain activity and its coupling with cerebrospinal fluid flow is related to tau pathology

Amyloid-β (Aβ) and tau deposition constitute Alzheimer's disease (AD) neuropathology. Cortical tau deposits first in the entorhinal cortex and hippocampus and then propagates to neocortex in an Aβ-dependent manner. Tau also tends to accumulate earlier in higher-order association cortex than in lower-order primary sensory-motor cortex. While previous research has examined the production and spread of tau, little attention has been paid to its clearance. Low-frequency (<0.1 Hz) global brain activity during the resting state is coupled with cerebrospinal fluid (CSF) flow and potentially reflects glymphatic clearance. Here we report that tau deposition in subjects with evaluated Aβ, accompanied by cortical thinning and cognitive decline, is strongly associated with decreased coupling between CSF flow and global brain activity. Substantial modulation of global brain activity is also manifested as propagating waves of brain activation between higher- and lower-order regions, resembling tau spreading. Together, the findings suggest an important role of resting-state global brain activity in AD tau pathology.

Functional network structure supports resilience to memory deficits in cognitively normal older adults with amyloid-β pathology

Older adults may harbor large amounts of amyloid-β (Aβ) pathology, yet still perform at age-normal levels on memory assessments. We tested whether functional brain networks confer resilience or compensatory mechanisms to support memory in the face of Aβ pathology. Sixty-five cognitively normal older adults received high-resolution resting state fMRI to assess functional networks, 18F-florbetapir-PET to measure Aβ, and a memory assessment. We characterized functional networks with graph metrics of local efficiency (information transfer), modularity (specialization of functional modules), and small worldness (balance of integration and segregation). There was no difference in functional network measures between older adults with high Aβ (Aβ+) compared to those with no/low Aβ (Aβ-). However, in Aβ+ older adults, increased local efficiency, modularity, and small worldness were associated with better memory performance, while this relationship did not occur Aβ- older adults. Further, the association between increased local efficiency and better memory performance in Aβ+ older adults was localized to local efficiency of the default mode network and hippocampus, regions vulnerable to Aβ and involved in memory processing. Our results suggest functional networks with modular and efficient structures are associated with resilience to Aβ pathology, providing a functional target for intervention.

Multiplex core of the human brain using structural, functional and metabolic connectivity derived from hybrid PET-MR imaging

With the increasing success of mapping brain networks and availability of multiple MR- and PET-based connectivity measures, the need for novel methodologies to unravel the structure and function of the brain at multiple spatial and temporal scales is emerging. Therefore, in this work, we used hybrid PET-MR data of healthy volunteers (n = 67) to identify multiplex core nodes in the human brain. First, monoplex networks of structural, functional and metabolic connectivity were constructed, and consequently combined into a multiplex SC-FC-MC network by linking the same nodes categorically across layers. Taking into account the multiplex nature using a tensorial approach, we identified a set of core nodes in this multiplex network based on a combination of eigentensor centrality and overlapping degree. We introduced a coreness coefficient, which mitigates the effect of modeling parameters to obtain robust results. The proposed methodology was applied onto young and elderly healthy volunteers, where differences observed in the monoplex networks persisted in the multiplex as well. The multiplex core showed a decreased contribution to the default mode and salience network, while an increased contribution to the dorsal attention and somatosensory network was observed in the elderly population. Moreover, a clear distinction in eigentensor centrality was found between young and elderly healthy volunteers.

Implication of tau propagation on neurodegeneration in Alzheimer's disease

Propagation of tau fibrils correlate closely with neurodegeneration and memory deficits seen during the progression of Alzheimer's disease (AD). Although it is not well-established what drives or attenuates tau spreading, new studies on human brain using positron emission tomography (PET) have shed light on how tau phosphorylation, genetic factors, and the initial epicenter of tau accumulation influence tau accumulation and propagation throughout the brain. Here, we review the latest PET studies performed across the entire AD continuum looking at the impact of amyloid load on tau pathology. We also explore the effects of structural, functional, and proximity connectivity on tau spreading in a stereotypical manner in the brain of AD patients. Since tau propagation can be quite heterogenous between individuals, we then consider how the speed and pattern of propagation are influenced by the starting localization of tau accumulation in connected brain regions. We provide an overview of some genetic variants that were shown to accelerate or slow down tau spreading. Finally, we discuss how phosphorylation of certain tau epitopes affect the spreading of tau fibrils. Since tau pathology is an early event in AD pathogenesis and is one of the best predictors of neurodegeneration and memory impairments, understanding the process by which tau spread from one brain region to another could pave the way to novel therapeutic avenues that are efficient during the early stages of the disease, before neurodegeneration induces permanent brain damage and severe memory loss.

Functional Network Alterations Associated with Cognition in Pre-Clinical Alzheimer's Disease

Objective: Accumulation of cerebral amyloid-β (Aβ) is a risk factor for cognitive decline and defining feature of Alzheimer's disease (AD). Aβ is implicated in brain network disruption, but the extent to which these changes correspond with observable cognitive deficits in pre-clinical AD has not been tested. This study utilized individual-specific functional parcellations to sensitively evaluate the relationship between network connectivity and cognition in adults with and without Aβ deposition. Participants and Methods: Cognitively unimpaired adults ages 45-85 completed amyloid positron emission tomography, resting-state-functional magnetic resonance imaging (fMRI), and neuropsychological tests of episodic memory and executive function (EF). Participants in the upper tertile of mean standard uptake value ratio were considered Aβ+ (n = 50) while others were Aβ- (n = 99). Individualized functional network parcellations were generated from resting-state fMRI data. We examined the effects of group, network, and group-by-network interactions on memory and EF. Results: We observed several interactions such that within the Aβ+ group, preserved network integrity (i.e., greater connectivity within specific networks) was associated with better cognition, whereas network desegregation (i.e., greater connectivity between relative to within networks) was associated with worse cognition. This dissociation was most apparent for cognitive networks (frontoparietal, dorsal and ventral attention, limbic, and default mode), with connectivity relating to EF in the Aβ+ group specifically. Conclusions: Using an innovative approach to constructing individual-specified resting-state functional connectomes, we were able to detect differences in brain-cognition associations in pre-clinical AD. Our findings provide novel insight into specific functional network alterations occurring in the presence of Aβ that relate to cognitive function in asymptomatic individuals. Impact statement Elevated cerebral amyloid-β is a biomarker of pre-clinical Alzheimer's disease (AD). Associations between amyloidosis, functional network disruption, and cognitive impairment are evident in the later stages of AD, but these effects have not been substantiated in pre-clinical AD. Using individual-specific parcellations that maximally localize functional networks, we identify network alterations that relate to cognition in pre-clinical AD that have not been previously reported. We demonstrate that these effects localize to networks implicated in cognition. Our findings suggest that there may be subtle, amyloid-related alterations in the functional connectome that are detectable in pre-clinical AD, with potential implications for cognition in asymptomatic individuals.

In vivo synaptic density loss correlates with impaired functional and related structural connectivity in Alzheimer's disease

Synapse loss has been considered as a major pathological change in Alzheimer's disease (AD). It remains unclear about whether and how synapse loss relates to functional and structural connectivity dysfunction in AD. We measured synaptic vesicle glycoprotein 2 A (SV2A) binding using 18F-SynVesT-1 PET to evaluate synaptic alterations in 33 participants with AD, 31 with mild cognitive impairment (MCI), and 30 controls. We examined the correlation between synaptic density and cognitive function. Functional MRI was performed to analyze functional connectivity in lower synaptic density regions. We tracked the white matter tracts between impaired functional connectivity regions using Diffusion MRI. In AD group, lower synaptic density in bilateral cortex and hippocampus was found when compared with controls. The synaptic density changes in right insular cortex and bilateral caudal middle frontal gyrus (MFG) were correlated with cognitive decline. Among them, right MFG synaptic density was positively associated with right MFG - bilateral superior frontal gyrus (SFG) functional connectivity. AD had lower probability of tract (POT) between right MFG and SFG than controls, which was significantly associated with global cognition. These findings provide evidence supporting synapse loss contributes to functional and related structural connectivity alterations underlying cognitive impairment of AD.

Gray matter hypoperfusion is a late pathological event in the course of Alzheimer's disease

Several studies have shown decreased cerebral blood flow (CBF) in Alzheimer's disease (AD). However, the role of hypoperfusion in the disease pathogenesis remains unclear. Combining arterial spin labeling MRI, PET, and CSF biomarkers, we investigated the associations between gray matter (GM)-CBF and the key mechanisms in AD including amyloid-β (Aβ) and tau pathology, synaptic and axonal degeneration. Further, we applied a disease progression modeling to characterize the temporal sequence of different AD biomarkers. Lower perfusion was observed in temporo-occipito-parietal cortex in the Aβ-positive cognitively impaired compared to both Aβ-negative and Aβ-positive cognitively unimpaired individuals. In participants along the AD spectrum, GM-CBF was associated with tau, synaptic and axonal dysfunction, but not Aβ in similar cortical regions. Axonal degeneration was further associated with hypoperfusion in cognitively unimpaired individuals. Disease progression modeling revealed that GM-CBF disruption Followed the abnormality of biomarkers of Aβ, tau and brain atrophy. These findings indicate that tau tangles and neurodegeneration are more closely connected with GM-CBF changes than Aβ pathology. Although subjected to the sensitivity of the employed neuroimaging techniques and the modeling approach, these findings suggest that hypoperfusion might not be an early event associated with the build-up of Aβ in preclinical phase of AD.

Statistical power in network neuroscience

Network neuroscience has emerged as a leading method to study brain connectivity. The success of these investigations is dependent not only on approaches to accurately map connectivity but also on the ability to detect real effects in the data - that is, statistical power. We review the state of statistical power in the field and discuss sample size, effect size, measurement error, and network topology as key factors that influence the power of brain connectivity investigations. We use the term 'differential power' to describe how power can vary between nodes, edges, and graph metrics, leaving traces in both positive and negative connectome findings. We conclude with strategies for working with, rather than around, power in connectivity studies.

Clear-headed into old age: Resilience and resistance against brain aging-A PET imaging perspective

With the advances in modern medicine and the adaptation towards healthier lifestyles, the average life expectancy has doubled since the 1930s, with individuals born in the millennium years now carrying an estimated life expectancy of around 100 years. And even though many individuals around the globe manage to age successfully, the prevalence of aging-associated neurodegenerative diseases such as sporadic Alzheimer's disease has never been as high as nowadays. The prevalence of Alzheimer's disease is anticipated to triple by 2050, increasing the societal and economic burden tremendously. Despite all efforts, there is still no available treatment defeating the accelerated aging process as seen in this disease. Yet, given the advances in neuroimaging techniques that are discussed in the current Review article, such as in positron emission tomography (PET) or magnetic resonance imaging (MRI), pivotal insights into the heterogenous effects of aging-associated processes and the contribution of distinct lifestyle and risk factors already have and are still being gathered. In particular, the concepts of resilience (i.e. coping with brain pathology) and resistance (i.e. avoiding brain pathology) have more recently been discussed as they relate to mechanisms that are associated with the prolongation and/or even stop of the progressive brain aging process. Better understanding of the underlying mechanisms of resilience and resistance may one day, hopefully, support the identification of defeating mechanism against accelerating aging.

Anterior dorsal attention network tau drives visual attention deficits in posterior cortical atrophy

Posterior cortical atrophy (PCA), usually an atypical clinical syndrome of Alzheimer's disease, has well-characterized patterns of cortical atrophy and tau deposition that are distinct from typical amnestic presentations of Alzheimer's disease. However, the mechanisms underlying the cortical spread of tau in PCA remain unclear. Here, in a sample of 17 biomarker-confirmed (A+/T+/N+) individuals with PCA, we sought to identify functional networks with heightened vulnerability to tau pathology by examining the cortical distribution of elevated tau as measured by 18F-flortaucipir (FTP) PET. We then assessed the relationship between network-specific FTP uptake and visuospatial cognitive task performance. As predicted, we found consistent and prominent localization of tau pathology in the dorsal attention network and visual network of the cerebral cortex. Elevated FTP uptake within the dorsal attention network (particularly the ratio of FTP uptake between the anterior and posterior nodes) was associated with poorer visuospatial attention in PCA; associations were also identified in other functional networks, although to a weaker degree. Furthermore, using functional MRI data collected from each patient at wakeful rest, we found that a greater anterior-to-posterior ratio in FTP uptake was associated with stronger intrinsic functional connectivity between anterior and posterior nodes of the dorsal attention network. Taken together, we conclude that our cross-sectional marker of anterior-to-posterior FTP ratio could indicate tau propagation from posterior to anterior dorsal attention network nodes, and that this anterior progression occurs in relation to intrinsic functional connectivity within this network critical for visuospatial attention. Our findings help to clarify the spatiotemporal pattern of tau propagation in relation to visuospatial cognitive decline and highlight the key role of the dorsal attention network in the disease progression of PCA.

Uncovering the System Vulnerability and Criticality of Human Brain Under Dynamical Neuropathological Events in Alzheimer's Disease

BACKGROUND

Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-β (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive.

OBJECTIVE

To disentangle the massive heterogeneities in Alzheimer's disease (AD) progressions and identify vulnerable/critical brain regions to AD pathology.

METHODS

In this work, we characterized the interaction of AT[N] biomarkers and their propagation across brain networks using a novel bistable reaction-diffusion model, which allows us to establish a new systems biology underpinning of AD progression. We applied our model to large-scale longitudinal neuroimages from the ADNI database and studied the systematic vulnerability and criticality of brains.

RESULTS

Our model yields long term prediction that is statistically significant linear correlated with temporal imaging data, produces clinically consistent risk prediction, and captures the Braak-like spreading pattern of AT[N] biomarkers in AD development.

CONCLUSIONS

Our major findings include (i) tau is a stronger indicator of regional risk compared to amyloid, (ii) temporal lobe exhibits higher vulnerability to AD-related pathologies, (iii) proposed critical brain regions outperform hub nodes in transmitting disease factors across the brain, and (iv) comparing the spread of neuropathological burdens caused by amyloid-β and tau diffusions, disruption of metabolic balance is the most determinant factor contributing to the initiation and progression of AD.

Vascular feature as a modulator of the aging brain

The cerebral functional reorganization and declined cognitive function of aging might associate with altered vascular features. Here, we explored the altered cerebral hierarchical functional network of 2 conditions (task-free and naturalistic stimuli) in older adults and its relationship with vascular features (systemic microvascular and perfusion features, measured by magnetic resonance imaging) and behavior. Using cerebral gradient analysis, we found that compressive gradient of resting-state mainly located on the primary sensory-motor system and transmodal regions in aging, and further compress in these regions under the continuous naturalistic stimuli. Combining cerebral functional gradient, vascular features, and cognitive performance, the more compressive gradient in the resting-state, the worse vascular state, the lower cognitive function in older adults. Further modulation analysis demonstrated that both vascular features can regulate the relationship between gradient scores in the insula and behavior. Interestingly, systemic microvascular oxygenation also can modulate the relationship between cerebral gradient and cerebral perfusion. Furthermore, the less alteration of the compressive gradient with naturalistic stimuli came with lower cognitive function. Our findings demonstrated that the altered cerebral hierarchical functional structure in aging was linked with changed vascular features and behavior, offering a new framework for studying the physiological mechanism of functional connectivity in aging.

Functional network segregation is associated with attenuated tau spreading in Alzheimer's disease

INTRODUCTION

Lower network segregation is associated with accelerated cognitive decline in Alzheimer's disease (AD), yet it is unclear whether less segregated brain networks facilitate connectivity-mediated tau spreading.

METHODS

We combined resting state functional magnetic resonance imaging (fMRI) with longitudinal tau positron emission tomography (PET) in 42 betamyloid-negative controls and 81 amyloid beta positive individuals across the AD spectrum. Network segregation was determined using resting-state fMRI-assessed connectivity among 400 cortical regions belonging to seven networks.

RESULTS

AD subjects with higher network segregation exhibited slower brain-wide tau accumulation relative to their baseline entorhinal tau PET burden (typical onset site of tau pathology). Second, by identifying patient-specific tau epicenters with highest baseline tau PET we found that stronger epicenter segregation was associated with a slower rate of tau accumulation in the rest of the brain in relation to baseline epicenter tau burden.

DISCUSSION

Our results indicate that tau spreading is facilitated by a more diffusely organized connectome, suggesting that brain network topology modulates tau spreading in AD.

HIGHLIGHTS

Higher brain network segregation is associated with attenuated tau pathology accumulation in Alzheimer's disease (AD). A patient-tailored approach allows for the more precise localization of tau epicenters. The functional segregation of subject-specific tau epicenters predicts the rate of future tau accumulation.

Amyloid-associated increases in soluble tau relate to tau aggregation rates and cognitive decline in early Alzheimer's disease

For optimal design of anti-amyloid-β (Aβ) and anti-tau clinical trials, we need to better understand the pathophysiological cascade of Aβ- and tau-related processes. Therefore, we set out to investigate how Aβ and soluble phosphorylated tau (p-tau) relate to the accumulation of tau aggregates assessed with PET and subsequent cognitive decline across the Alzheimer's disease (AD) continuum. Using human cross-sectional and longitudinal neuroimaging and cognitive assessment data, we show that in early stages of AD, increased concentration of soluble CSF p-tau is strongly associated with accumulation of insoluble tau aggregates across the brain, and CSF p-tau levels mediate the effect of Aβ on tau aggregation. Further, higher soluble p-tau concentrations are mainly related to faster accumulation of tau aggregates in the regions with strong functional connectivity to individual tau epicenters. In this early stage, higher soluble p-tau concentrations is associated with cognitive decline, which is mediated by faster increase of tau aggregates. In contrast, in AD dementia, when Aβ fibrils and soluble p-tau levels have plateaued, cognitive decline is related to the accumulation rate of insoluble tau aggregates. Our data suggest that therapeutic approaches reducing soluble p-tau levels might be most favorable in early AD, before widespread insoluble tau aggregates.

Reduction of kinesin I heavy chain decreases tau hyperphosphorylation, aggregation, and memory impairment in Alzheimer's disease and tauopathy models

Many neurodegenerative diseases, such as Alzheimer's disease (AD) and frontotemporal dementia with Parkinsonism linked to chromosome 17, are characterized by tau pathology. Numerous motor proteins, many of which are involved in synaptic transmission, mediate transport in neurons. Dysfunction in motor protein-mediated neuronal transport mechanisms occurs in several neurodegenerative disorders but remains understudied in AD. Kinesins are the most important molecular motor proteins required for microtubule-dependent transport in neurons, and kinesin-1 is crucial for neuronal transport among all kinesins. Although kinesin-1 is required for normal neuronal functions, the dysfunction of these motor domains leading to neurodegenerative diseases is not fully understood. Here, we reported that the kinesin-I heavy chain (KIF5B), a key molecular motor protein, is involved in tau homeostasis in AD cells and animal models. We found that the levels of KIF5B in P301S tau mice are high. We also found that the knockdown and knockout (KO) of KIFf5B significantly decreased the tau stability, and overexpression of KIF5B in KIF5B-KO cells significantly increased the expression of phosphorylated and total tau levels. This suggested that KIF5B might prevent tau accumulation. By conducting experiments on P301S tau mice, we showed that partially reducing KIF5B levels can reduce hyperphosphorylation of the human tau protein, formation of insoluble aggregates, and memory impairment. Collectively, our results suggested that decreasing KIF5B levels is sufficient to prevent and/or slow down abnormal tau behavior of AD and other tauopathies.

Higher levels of myelin are associated with higher resistance against tau pathology in Alzheimer’s disease

Background

In Alzheimer’s disease (AD), fibrillar tau initially occurs locally and progresses preferentially between closely connected regions. However, the underlying sources of regional vulnerability to tau pathology remain unclear. Previous brain-autopsy findings suggest that the myelin levels—which differ substantially between white matter tracts in the brain—are a key modulating factor of region-specific susceptibility to tau deposition. Here, we investigated whether myelination differences between fiber tracts of the human connectome are predictive of the interregional spreading of tau pathology in AD.

Methods

We included two independently recruited samples consisting of amyloid-PET-positive asymptomatic and symptomatic elderly individuals, in whom tau-PET was obtained at baseline (ADNI: n = 275; BioFINDER-1: n = 102) and longitudinally in a subset (ADNI: n = 123, mean FU = 1.53 [0.69–3.95] years; BioFINDER-1: n = 39, mean FU = 1.87 [1.21–2.78] years). We constructed MRI templates of the myelin water fraction (MWF) in 200 gray matter ROIs and connecting fiber tracts obtained from adult cognitively normal participants. Using the same 200 ROI brain-parcellation atlas, we obtained tau-PET ROI values from each individual in ADNI and BioFINDER-1. In a spatial regression analysis, we first tested the association between cortical myelin and group-average tau-PET signal in the amyloid-positive and control groups. Secondly, employing a previously established approach of modeling tau-PET spreading based on functional connectivity between ROIs, we estimated in a linear regression analysis, whether the level of fiber-tract myelin modulates the association between functional connectivity and longitudinal tau-PET spreading (i.e., covariance) between ROIs.

Results

We found that higher myelinated cortical regions show lower tau-PET uptake (ADNI: rho =  − 0.267, p < 0.001; BioFINDER-1: rho =  − 0.175, p = 0.013). Fiber-tract myelin levels modulated the association between functional connectivity and tau-PET spreading, such that at higher levels of fiber-tract myelin, the association between stronger connectivity and higher covariance of tau-PET between the connected ROIs was attenuated (interaction fiber-tract myelin × functional connectivity: ADNI: β =  − 0.185, p < 0.001; BioFINDER-1: β =  − 0.166, p < 0.001).

Conclusion

Higher levels of myelin are associated with lower susceptibility of the connected regions to accumulate fibrillar tau. These results enhance our understanding of brain substrates that explain regional variation in tau accumulation and encourage future studies to investigate potential underlying mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01074-9.

Molecular signatures underlying neurofibrillary tangle susceptibility in Alzheimer's disease

Tau aggregation in neurofibrillary tangles (NFTs) is closely associated with neurodegeneration and cognitive decline in Alzheimer's disease (AD). However, the molecular signatures that distinguish between aggregation-prone and aggregation-resistant cell states are unknown. We developed methods for the high-throughput isolation and transcriptome profiling of single somas with NFTs from the human AD brain, quantified the susceptibility of 20 neocortical subtypes for NFT formation and death, and identified both shared and cell-type-specific signatures. NFT-bearing neurons shared a marked upregulation of synaptic transmission-related genes, including a core set of 63 genes enriched for synaptic vesicle cycling. Oxidative phosphorylation and mitochondrial dysfunction were highly cell-type dependent. Apoptosis was only modestly enriched, and the susceptibilities of NFT-bearing and NFT-free neurons for death were highly similar. Our analysis suggests that NFTs represent cell-type-specific responses to stress and synaptic dysfunction. We provide a resource for biomarker discovery and the investigation of tau-dependent and tau-independent mechanisms of neurodegeneration.

Dynamic network model reveals distinct tau spreading patterns in early- and late-onset Alzheimer disease

BACKGROUND

The clinical features of Alzheimer's disease (AD) vary substantially depending on whether the onset of cognitive deficits is early or late. The amount and distribution patterns of tau pathology are thought to play a key role in the clinical characteristics of AD, which spreads throughout the large-scale brain network. Here, we describe the differences between tau-spreading processes in early- and late-onset symptomatic individuals on the AD spectrum.

METHODS

We divided 74 cognitively unimpaired (CU) and 68 cognitively impaired (CI) patients receiving 18F-flortaucipir positron emission tomography scans into two groups by age and age at onset. Members of each group were arranged in a pseudo-longitudinal order based on baseline tau pathology severity, and potential interregional tau-spreading pathways were defined following the order using longitudinal tau uptake. We detected a multilayer community structure through consecutive tau-spreading networks to identify spatio-temporal changes in the propagation hubs.

RESULTS

In each group, ordered tau-spreading networks revealed the stage-dependent dynamics of tau propagation, supporting distinct tau accumulation patterns. In the young CU/early-onset CI group, tau appears to spread through a combination of three independent communities with partially overlapped territories, whose specific driving regions were the basal temporal regions, left medial and lateral temporal regions, and left parietal regions. For the old CU/late-onset CI group, however, continuation of major communities occurs in line with the appearance of hub regions in the order of bilateral entorhinal cortices, parahippocampal and fusiform gyri, and lateral temporal regions.

CONCLUSION

Longitudinal tau propagation depicts distinct spreading pathways of the early- and late-onset AD spectrum characterized by the specific location and appearance period of several hub regions that dominantly provide tau.

The lateral entorhinal cortex is a hub for local and global dysfunction in early Alzheimer's disease states

Functional network activity alterations are one of the earliest hallmarks of Alzheimer's disease (AD), detected prior to amyloidosis and tauopathy. Better understanding the neuronal underpinnings of such network alterations could offer mechanistic insight into AD progression. Here, we examined a mouse model (3xTgAD mice) recapitulating this early AD stage. We found resting functional connectivity loss within ventral networks, including the entorhinal cortex, aligning with the spatial distribution of tauopathy reported in humans. Unexpectedly, in contrast to decreased connectivity at rest, 3xTgAD mice show enhanced fMRI signal within several projection areas following optogenetic activation of the entorhinal cortex. We corroborate this finding by demonstrating neuronal facilitation within ventral networks and synaptic hyperexcitability in projection targets. 3xTgAD mice, thus, reveal a dichotomic hypo-connected:resting versus hyper-responsive:active phenotype. This strong homotopy between the areas affected supports the translatability of this pathophysiological model to tau-related, early-AD deficits in humans.

Intrinsic connectivity of the human brain provides scaffold for tau aggregation in clinical variants of Alzheimer's disease

Alzheimer's disease (AD) phenotypes might result from differences in selective vulnerability. Evidence from preclinical models suggests that tau pathology has cell-to-cell propagation properties. Therefore, here, we tested the cell-to-cell propagation framework in the amnestic, visuospatial, language, and behavioral/dysexecutive phenotypes of AD. We report that each AD phenotype is associated with a distinct network-specific pattern of tau aggregation, where tau aggregation is concentrated in brain network hubs. In all AD phenotypes, regional tau load could be predicted by connectivity patterns of the human brain. Furthermore, regions with greater connectivity displayed similar rates of longitudinal tau accumulation in an independent cohort. Connectivity-based tau deposition was not restricted to a specific vulnerable network but was rather a general property of brain organization, linking selective vulnerability and transneuronal spreading models of neurodegeneration. Together, this study indicates that intrinsic brain connectivity provides a framework for tau aggregation across diverse phenotypic manifestations of AD.

Methamphetamine induced neurotoxic diseases, molecular mechanism, and current treatment strategies

Methamphetamine (MA) is a extremely addictive psychostimulant drug with a significant abuse potential. Long-term MA exposure can induce neurotoxic effects through oxidative stress, mitochondrial functional impairment, endoplasmic reticulum stress, the activation of astrocytes and microglial cells, axonal transport barriers, autophagy, and apoptosis. However, the molecular and cellular mechanisms underlying MA-induced neurotoxicity remain unclear. MA abuse increases the chances of developing neurotoxic conditions such as Parkinson's disease (PD), Alzheimer's disease (AD) and other neurotoxic diseases. MA increases the risk of PD by increasing the expression of alpha-synuclein (ASYN). Furthermore, MA abuse is linked to high chances of developing AD and subsequent neurodegeneration due to biological variations in the brain region or genetic and epigenetic variations. To date, there is no Food and Drug Administration (FDA)-approved therapy for MA-induced neurotoxicity, although many studies are being conducted to develop effective therapeutic strategies. Most current studies are now focused on developing therapies to diminish the neurotoxic effects of MA, based on the underlying mechanism of neurotoxicity. This review article highlights current research on several therapeutic techniques targeting multiple pathways to reduce the neurotoxic effects of MA in the brain, as well as the putative mechanism of MA-induced neurotoxicity.

Earlier Alzheimer’s disease onset is associated with tau pathology in brain hub regions and facilitated tau spreading

In Alzheimer’s disease (AD), younger symptom onset is associated with accelerated disease progression and tau spreading, yet the mechanisms underlying faster disease manifestation are unknown. To address this, we combined resting-state fMRI and longitudinal tau-PET in two independent samples of controls and biomarker-confirmed AD patients (ADNI/BioFINDER, n = 240/57). Consistent across both samples, we found that younger symptomatic AD patients showed stronger tau-PET in globally connected fronto-parietal hubs, i.e., regions that are critical for maintaining cognition in AD. Stronger tau-PET in hubs predicted faster subsequent tau accumulation, suggesting that tau in globally connected regions facilitates connectivity-mediated tau spreading. Further, stronger tau-PET in hubs mediated the association between younger age and faster tau accumulation in symptomatic AD patients, which predicted faster cognitive decline. These independently validated findings suggest that younger AD symptom onset is associated with stronger tau pathology in brain hubs, and accelerated tau spreading throughout connected brain regions and cognitive decline.

Contrast agent-free state-of-the-art magnetic resonance imaging on cerebral small vessel disease - Part 2: Diffusion tensor imaging and functional magnetic resonance imaging

Cerebral small vessel disease (cSVD) has been widely studied using conventional magnetic resonance imaging (MRI) methods, although the association between MRI findings and clinical features of cSVD is not always concordant. We assessed the additional contribution of contrast agent-free, state-of-the-art MRI techniques, particularly diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI), to understand brain damage and structural and functional connectivity impairment related to cSVD. We performed a review following the PICOS worksheet and Search Strategy, including 152 original papers in English, published from 2000 to 2022. For each MRI method, we extracted information about their contributions regarding the origins, pathology, markers, and clinical outcomes in cSVD. In general, DTI studies have shown that changes in mean, radial, and axial diffusivity measures are related to the presence of cSVD. In addition to the classical deficit in executive functions and processing speed, fMRI studies indicate connectivity dysfunctions in other domains, such as sensorimotor, memory, and attention. Neuroimaging metrics have been correlated with the diagnosis, prognosis, and rehabilitation of patients with cSVD. In short, the application of contrast agent-free, state-of-the-art MRI techniques has provided a complete picture of cSVD markers and tools to explore questions that have not yet been clarified about this clinical condition. Longitudinal studies are desirable to look for causal relationships between image biomarkers and clinical outcomes.

Traumatic brain injury alterations in the functional connectome are associated with neuroinflammation but not tau in a P30IL tauopathy mouse model

INTRODUCTION

Traumatic Brain Injury (TBI) is often associated with long-term cognitive deficits and altered brain networks which have been linked with accumulation of neurofibrillary tau tangles and neuroinflammation. In this work, we investigated the changes in the brain post-TBI in an Alzheimer's disease pR5 tauopathy model and evaluated the contribution of tauopathy and neuroinflammation to connectivity alterations using resting-state functional Magnetic Resonance Imaging (rs-fMRI).

METHOD

26 P301L tau transgenic mice of 8-9 months of age (21-35 g) expressing the human tau isoform carrying the pathogenic P301L mutation were used for the study. Animals were assessed at day 1 and 7 post-injury/craniotomy and were randomly divided into four groups. All animals underwent an MRI scan on a 9.4 T Bruker system where rsfMRI was acquired. Following imaging, brains were stained with pSer (396 + 404), glial fibrillary acidic protein (GFAP), and ionised calcium-binding adaptor molecule-1 (Iba-1). Group-information-guided Independent Component Analysis (GIG-ICA) and region-of-interest (ROI)-based network connectivity approaches were applied. Principal Component Regression was applied to predict connectivity network strength from the corresponding ROIs.

RESULTS

TBI mice showed decreased functional connectivity in the dentate gyrus, thalamus, and other areas compared to sham animals at day 1 post-injury with the majority of changes resolving at day 7. Principal Component Regression showed only the contralateral CA1 network strength was correlated with the CA1's astrocyte and microglia cell density and the ipsilateral thalamus network strength was correlated with the ipsilateral thalamus' astrocyte and microglia cell density.

CONCLUSION

We present the first report on the temporal alterations in functional connectivity in a P30IL mouse model following TBI. Connectivity between key regions known to be affected in Alzheimer's disease were short-term and reversible following injury. Connectivity strength in CA1 and thalamus showed significant correlation with astrocyte and microglial cell density but not tau density.

Identification of Pathogenetic Brain Regions via Neuroimaging Data for Diagnosis of Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a kind of neurodevelopmental disorder that often occurs in children and has a hidden onset. Patients usually have lagged development of communication ability and social behavior and thus suffer an unhealthy physical and mental state. Evidence has indicated that diseases related to ASD have commonalities in brain imaging characteristics. This study aims to study the pathogenesis of ASD based on brain imaging data to locate the ASD-related brain regions. Specifically, we collected the functional magnetic resonance image data of 479 patients with ASD and 478 normal subjects matched in age and gender and used a machine-learning framework named random support vector machine cluster to extract distinctive brain regions from the preprocessed data. According to the experimental results, compared with other existing approaches, the method used in this study can more accurately distinguish patients from normal individuals based on brain imaging data. At the same time, this study found that the development of ASD was highly correlated with certain brain regions, e.g., lingual gyrus, superior frontal gyrus, medial gyrus, insular lobe, and olfactory cortex. This study explores the effectiveness of a novel machine-learning approach in the study of ASD brain imaging and provides a reference brain area for the medical research and clinical treatment of ASD.

Machine Learning Decomposition of the Anatomy of Neuropsychological Deficit in Alzheimer’s Disease and Mild Cognitive Impairment

Objective

Alzheimer’s Disease (AD) is a progressive condition characterized by cognitive decline. AD is often preceded by mild cognitive impairment (MCI), though the diagnosis of both conditions remains a challenge. Early diagnosis of AD, and prediction of MCI progression require data-driven approaches to improve patient selection for treatment. We used a machine learning tool to predict performance in neuropsychological tests in AD and MCI based on functional connectivity using a whole-brain connectome, in an attempt to identify network substrates of cognitive deficits in AD.

Methods

Neuropsychological tests, baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI, and diffusion weighted imaging scans were obtained from 149 MCI, and 85 AD patients; and 140 cognitively unimpaired geriatric participants. A novel machine learning tool, Hollow Tree Super (HoTS) was utilized to extract feature importance from each machine learning model to identify brain regions that were associated with deficit and absence of deficit for 11 neuropsychological tests.

Results

11 models attained an area under the receiver operating curve (AUC-ROC) greater than 0.65, while five models had an AUC-ROC ≥ 0.7. 20 parcels of the Human Connectome Project Multimodal Parcelation Atlas matched to poor performance in at least two neuropsychological tests, while 14 parcels were associated with good performance in at least two tests. At a network level, most parcels predictive of both presence and absence of deficit were affiliated with the Central Executive Network, Default Mode Network, and the Sensorimotor Networks. Segregating predictors by the cognitive domain associated with each test revealed areas of coherent overlap between cognitive domains, with the parcels providing possible markers to screen for cognitive impairment.

Conclusion

Approaches such as ours which incorporate whole-brain functional connectivity and harness feature importance in machine learning models may aid in identifying diagnostic and therapeutic targets in AD.

Functional connectome analysis in Mild Cognitive Impairment: Comparing AD continuum and Suspected Non-Alzheimer Pathology

INTRODUCTION

Research in brain resting-state functional connectivity (FC) analysis in mild cognitive impairment (MCI) has conflicting results. This work intends to find differences in resting-state FC of MCI subjects due to Alzheimer´s disease continuum (MCI-AD) or suspected non-Alzheimer pathology (MCI-SNAP).

METHODS

92 subjects over 55 years old were enrolled. MCI and controls were grouped using clinical dementia rating and neuropsychological data. CSF biomarkers were collected from MCI subjects, resulting in 32 MCI-AD, 25 MCI-SNAP, and 35 controls. A ROI-to-ROI analysis was carried out looking at inter and intranetwork interactions selecting the following networks: default mode (DMN), salience (SN), visuospatial (VN), and executive. Pearson correlation coefficients, converted to Z-scores were compared by T-tests with alpha set to 0.05, FDR corrected.

RESULTS

Groups were similar in age, education and demographic measures, there were no differences in neuropsychological data between the MCI groups. The ROI-to-ROI analysis MCI-AD versus MCI-SNAP showed no differences. MCI-AD versus controls showed decreased FC between ROIs of the SN and between ROIs from SN and VN. MCI-SNAP versus controls showed increased FC between a ROI of DMN and VN.

DISCUSSION

SN, DMN, and VN are multimodal networks with high value/high cost and may be more vulnerable to AD pathogenic processes. SN and VN were affected in the MCI-AD group, with maintained anticorrelation between DMN and VN. This may indicate subthreshold DMN dysfunction. The result in MCI-SNAP, although discrete, reflects a rearrangement of brain FC, as DMN and VN are expected to be anticorrelated. More research is necessary to confirm these findings.