Tau-Atrophy Variability Reveals Phenotypic Heterogeneity in Alzheimer's Disease

Local molecular and connectomic contributions of tau-related neurodegeneration

Neurodegeneration in Alzheimer's disease (AD) is known to be mostly driven by tau neurofibrillary tangles. However, both tau and neurodegeneration exhibit variability in their distribution across the brain and among individuals, and the relationship between tau and neurodegeneration might be influenced by several factors. I aimed to map local molecular and connectivity characteristics that affect the association between tau pathology and neurodegeneration. The current study was conducted on the cross-sectional tau-PET and longitudinal T1-weighted MRI scan data of 186 participants from the ADNI dataset including 71 cognitively unimpaired (CU) and 115 mild cognitive impairment (MCI) individuals. Furthermore, the normative molecular profile of a region was defined using neurotransmitter receptor densities, gene expression, T1w/T2w ratio (myelination), FDG-PET (glycolytic index, glucose metabolism, and oxygen metabolism), and synaptic density. I found that the excitatory-inhibitory (E:I) ratio, myelination, synaptic density, glycolytic index, and functional connectivity are linked with deviation in the relationship between tau and neurodegeneration. Furthermore, there was spatial similarity between tau pathology and glycolytic index, synaptic density, and functional connectivity across brain regions. The current study demonstrates that the regional susceptibility to tau-related neurodegeneration is associated with specific molecular and connectomic characteristics of the affected neural systems. I found that the molecular and connectivity architecture of the human brain is linked to the different effects of tau pathology on downstream neurodegeneration.

A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variables

Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer's disease (AD) research and clinical trials. However, its routine clinical use is limited by cost and accessibility barriers. Here we explore using machine learning (ML) models to predict clinically useful tau-PET composites from low-cost and non-invasive features, e.g., basic clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI). Results demonstrated that models including plasma biomarkers yielded the most accurate predictions of tau-PET burden (best model: R-squared=0.66-0.68), with especially high contribution from plasma P-tau217. In contrast, MRI variables stood out as best predictors (best model: R-squared=0.28-0.42) of asymmetric tau load between the two hemispheres (an example of clinically relevant spatial information). The models showed high generalizability to external test cohorts with data collected at multiple sites. Based on these results, we also propose a proof-of-concept two-step classification workflow, demonstrating how the ML models can be translated to a clinical setting. This study uncovers current potential in predicting tau-PET information from scalable cost-effective variables, which could improve diagnosis and prognosis of AD.

Pilot implementation of the revised criteria for staging of Alzheimer's disease by the Alzheimer's Association Workgroup in a tertiary memory clinic

INTRODUCTION

We aimed to evaluate the feasibility of the 2024 Alzheimer's Association Workgroup's integrated clinical-biological staging scheme in outpatient settings within a tertiary memory clinic.

METHODS

The 2018 syndromal cognitive staging system, coupled with a binary biomarker classification, was implemented for 236 outpatients with cognitive concerns. The 2024 numeric clinical staging framework, incorporating biomarker staging, was specifically applied to 154 individuals within the Alzheimer's disease (AD) continuum.

RESULTS

The 2024 staging scheme accurately classified 95.5% AD. Among these, 56.5% exhibited concordant clinical and biological stages (canonical), 34.7% demonstrated more advanced clinical stages than biologically expected (susceptible), and 8.8% displayed the inverse pattern (resilient). The susceptible group was characterized by a higher burden of neurodegeneration and inflammation than anticipated from tau, whereas the resilient group showed the opposite.

DISCUSSION

The 2024 staging scheme is generally feasible. A discrepancy between clinical and biological stages is relatively frequent among symptomatic patients with AD.

HIGHLIGHTS

The 2024 AA staging scheme is generally feasible in a tertiary memory clinic. A discrepancy between clinical and biological stages is relatively frequent in AD. The mismatch may be influenced by a non-specific pathological process involved in AD. Individual profiles like aging and lifestyles may contribute to such a mismatch. Matched and mismatched cases converge toward similar clinical outcomes.

Evaluation of partial volume correction and analysis of longitudinal [18F]GTP1 tau PET imaging in Alzheimer's disease using linear mixed-effects models

Purpose

We evaluated the impact of partial volume correction (PVC) methods on the quantification of longitudinal [18F]GTP1 tau positron-emission tomography (PET) in Alzheimer's disease and the suitability of describing the tau pathology burden temporal trajectories using linear mixed-effects models (LMEM).

Methods

We applied van Cittert iterative deconvolution (VC), 2-compartment, and 3-compartment, and the geometric transfer matrix plus region-based voxelwise methods to data acquired in an Alzheimer's disease natural history study over 18 months at a single imaging site. We determined the optimal PVC method by comparing the standardized uptake value ratio change (%ΔSUVR) between diagnostic and tau burden-level groups and the longitudinal repeatability derived from the LMEM. The performance of LMEM analysis for calculating %ΔSUVR was evaluated in a natural history study and in a multisite clinical trial of semorinemab in prodromal to mild Alzheimer's disease by comparing results to traditional per-visit estimates.

Results

The VC, 2-compartment, and 3-compartment PVC methods had similar performance, whereas region-based voxelwise overcorrected regions with a higher tau burden. The lowest within-subject variability and acceptable group separation scores were observed without PVC. The LMEM-derived %ΔSUVR values were similar to the per-visit estimates with lower variability.

Conclusion

The results indicate that the tested PVC methods do not offer a clear advantage or improvement over non-PVC images for the quantification of longitudinal [18F]GTP1 PET data. LMEM offers a robust framework for the longitudinal tau PET quantification with low longitudinal test-retest variability.

Clinical trial registration

NCT02640092 and NCT03289143.

Tau-neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer's continuum

INTRODUCTION

Variability in relationship of tau-based neurofibrillary tangles (T) and neurodegeneration (N) in Alzheimer's disease (AD) arises from non-specific nature of N, modulated by non-AD co-pathologies, age-related changes, and resilience factors.

METHODS

We used regional T-N residual patterns to partition 184 patients within the Alzheimer's continuum into data-driven groups. These were compared with groups from 159 non-AD (amyloid "negative") patients partitioned using cortical thickness, and groups in 98 patients with ante mortem MRI and post mortem tissue for measuring N and T, respectively. We applied the initial T-N residual model to classify 71 patients in an independent cohort into predefined groups.

RESULTS

AD groups displayed spatial T-N mismatch patterns resembling neurodegeneration patterns in non-AD groups, similarly associated with non-AD factors and diverging cognitive outcomes. In the autopsy cohort, limbic T-N mismatch correlated with TDP-43 co-pathology.

DISCUSSION

T-N mismatch may provide a personalized approach for determining non-AD factors associated with resilience/vulnerability in AD.

A review of neuroimaging-based data-driven approach for Alzheimer's disease heterogeneity analysis

Alzheimer's disease (AD) is a complex form of dementia and due to its high phenotypic variability, its diagnosis and monitoring can be quite challenging. Biomarkers play a crucial role in AD diagnosis and monitoring, but interpreting these biomarkers can be problematic due to their spatial and temporal heterogeneity. Therefore, researchers are increasingly turning to imaging-based biomarkers that employ data-driven computational approaches to examine the heterogeneity of AD. In this comprehensive review article, we aim to provide health professionals with a comprehensive view of past applications of data-driven computational approaches in studying AD heterogeneity and planning future research directions. We first define and offer basic insights into different categories of heterogeneity analysis, including spatial heterogeneity, temporal heterogeneity, and spatial-temporal heterogeneity. Then, we scrutinize 22 articles relating to spatial heterogeneity, 14 articles relating to temporal heterogeneity, and five articles relating to spatial-temporal heterogeneity, highlighting the strengths and limitations of these strategies. Furthermore, we discuss the importance of understanding spatial heterogeneity in AD subtypes and their clinical manifestations, biomarkers for abnormal orderings and AD stages, the recent advancements in spatial-temporal heterogeneity analysis for AD, and the emerging role of omics data integration in advancing personalized diagnosis and treatment for AD patients. By emphasizing the significance of understanding AD heterogeneity, we hope to stimulate further research in this field to facilitate the development of personalized interventions for AD patients.

Polypathologic Associations with Gray Matter Atrophy in Neurodegenerative Disease

Mixed pathologies are common in neurodegenerative disease; however, antemortem imaging rarely captures copathologic effects on brain atrophy due to a lack of validated biomarkers for non-Alzheimer's pathologies. We leveraged a dataset comprising antemortem MRI and postmortem histopathology to assess polypathologic associations with atrophy in a clinically heterogeneous sample of 125 human dementia patients (41 female, 84 male) with T1-weighted MRI ≤ 5 years before death and postmortem ordinal ratings of amyloid-[Formula: see text], tau, TDP-43, and [Formula: see text]-synuclein. Regional volumes were related to pathology using linear mixed-effects models; approximately 25% of data were held out for testing. We contrasted a polypathologic model comprising independent factors for each proteinopathy with two alternatives: a model that attributed atrophy entirely to the protein(s) associated with the patient's primary diagnosis and a protein-agnostic model based on the sum of ordinal scores for all pathology types. Model fits were evaluated using log-likelihood and correlations between observed and fitted volume scores. Additionally, we performed exploratory analyses relating atrophy to gliosis, neuronal loss, and angiopathy. The polypathologic model provided superior fits in the training and testing datasets. Tau, TDP-43, and [Formula: see text]-synuclein burden were inversely associated with regional volumes, but amyloid-[Formula: see text] was not. Gliosis and neuronal loss explained residual variance in and mediated the effects of tau, TDP-43, and [Formula: see text]-synuclein on atrophy. Regional brain atrophy reflects not only the primary molecular pathology but also co-occurring proteinopathies; inflammatory immune responses may independently contribute to degeneration. Our findings underscore the importance of antemortem biomarkers for detecting mixed pathology.

Traumatic Brain Injury and Post-Traumatic Stress Disorder and Their Influence on Development and Pattern of Alzheimer's Disease Pathology in Later Life

Background

Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are potential risk factors for the development of dementia including Alzheimer's disease (AD) in later life. The findings of studies investigating this question are inconsistent though.

Objective

To investigate if these inconsistencies are caused by the existence of subgroups with different vulnerability for AD pathology and if these subgroups are characterized by atypical tau load/atrophy pattern.

Methods

The MRI and PET data of 89 subjects with or without previous TBI and/or PTSD from the DoD ADNI database were used to calculate an age-corrected gray matter tau mismatch metric (ageN-T mismatch-score and matrix) for each subject. This metric provides a measure to what degree regional tau accumulation drives regional gray matter atrophy (matrix) and can be used to calculate a summary score (score) reflecting the severity of AD pathology in an individual.

Results

The ageN-T mismatch summary score was positively correlated with whole brain beta-amyloid load and general cognitive function but not with PTSD or TBI severity. Hierarchical cluster analysis identified five different spatial patterns of tau-gray matter interactions. These clusters reflected the different stages of the typical AD tau progression pattern. None was exclusively associated with PTSD and/or TBI.

Conclusions

These findings suggest that a) although subsets of patients with PTSD and/or TBI develop AD-pathology, a history of TBI or PTSD alone or both is not associated with a significantly higher risk to develop AD pathology in later life. b) remote TBI or PTSD do not modify the typical AD pathology distribution pattern.

The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022

The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co-pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI-4 aims to address by enrolling a diverse cohort.

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.

Evolving prion-like tau conformers differentially alter postsynaptic proteins in neurons inoculated with distinct isolates of Alzheimer's disease tau

OBJECTIVES

Although accumulation of misfolded tau species has been shown to predict cognitive decline in patients with Alzheimer's disease (AD) and other tauopathies but with the remarkable diversity of clinical manifestations, neuropathology profiles, and time courses of disease progression remaining unexplained by current genetic data. We considered the diversity of misfolded tau conformers present in individual AD cases as an underlying driver of the phenotypic variations of AD and progressive loss of synapses.

METHODS

To model the mechanism of tau propagation and synaptic toxicity of distinct tau conformers, we inoculated wild-type primary mouse neurons with structurally characterized Sarkosyl-insoluble tau isolates from the frontal cortex of six AD cases and monitored the impact for fourteen days. We analyzed the accumulation rate, tau isoform ratio, and conformational characteristics of de novo-induced tau aggregates with conformationally sensitive immunoassays, and the dynamics of synapse formation, maintenance, and their loss using a panel of pre-and post-synaptic markers.

RESULTS

At the same concentrations of tau, the different AD tau isolates induced accumulation of misfolded predominantly 4-repeat tau aggregates at different rates in mature neurons, and demonstrated distinct conformational characteristics corresponding to the original AD brain tau. The time-course of the formation of misfolded tau aggregates and colocalization correlated with significant loss of synapses in tau-inoculated cell cultures and the reduction of synaptic connections implicated the disruption of postsynaptic compartment as an early event.

CONCLUSIONS

The data obtained with mature neurons expressing physiological levels and adult isoforms of tau protein demonstrate markedly different time courses of endogenous tau misfolding and differential patterns of post-synaptic alterations. These and previous biophysical data argue for an ensemble of various misfolded tau aggregates in individual AD brains and template propagation of their homologous conformations in neurons with different rates and primarily postsynaptic interactors. Modeling tau aggregation in mature differentiated neurons provides a platform for investigating divergent molecular mechanisms of tau strain propagation and for identifying common structural features of misfolded tau and critical interactors for new therapeutic targets and approaches in AD.

The complex pathway between amyloid β and cognition: implications for therapy

For decades, the hypothesis that brain deposition of the amyloid β protein initiates Alzheimer's disease has dominated research and clinical trials. Targeting amyloid β is starting to produce therapeutic benefit, although whether amyloid-lowering drugs will be widely and meaningfully effective is still unclear. Despite extensive in-vivo biomarker evidence in humans showing the importance of an amyloid cascade that drives cognitive decline, the amyloid hypothesis does not fully account for the complexity of late-life cognitive impairment. Multiple brain pathological changes, inflammation, and host factors of resilience might also be involved in contributing to the development of dementia. This variability suggests that the benefits of lowering amyloid β might depend on how strongly an amyloid pathway is manifest in an individual in relation to other coexisting pathophysiological processes. A new approach to research and treatment, which fully considers the multiple factors that drive cognitive decline, is necessary.

When Alzheimer's is LATE: Why Does it Matter?

Recent therapeutic advances provide heightened motivation for accurate diagnosis of the underlying biologic causes of dementia. This review focuses on the importance of clinical recognition of limbic-predominant age-related TDP-43 encephalopathy (LATE). LATE affects approximately one-quarter of older adults and produces an amnestic syndrome that is commonly mistaken for Alzheimer's disease (AD). Although AD and LATE often co-occur in the same patients, these diseases differ in the protein aggregates driving neuropathology (Aβ amyloid/tau vs TDP-43). This review discusses signs and symptoms, relevant diagnostic testing, and potential treatment implications for LATE that may be helpful for physicians, patients, and families. ANN NEUROL 2023;94:211-222.

Tau-Neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer's continuum

Variability in the relationship of tau-based neurofibrillary tangles (T) and degree of neurodegeneration (N) in Alzheimer's Disease (AD) is likely attributable to the non-specific nature of N, which is also modulated by such factors as other co-pathologies, age-related changes, and developmental differences. We studied this variability by partitioning patients within the Alzheimer's continuum into data-driven groups based on their regional T-N dissociation, which reflects the residuals after the effect of tau pathology is "removed". We found six groups displaying distinct spatial T-N mismatch and thickness patterns despite similar tau burden. Their T-N patterns resembled the neurodegeneration patterns of non-AD groups partitioned on the basis of z-scores of cortical thickness alone and were similarly associated with surrogates of non-AD factors. In an additional sample of individuals with antemortem imaging and autopsy, T-N mismatch was associated with TDP-43 co-pathology. Finally, T-N mismatch training was then applied to a separate cohort to determine the ability to classify individual patients within these groups. These findings suggest that T-N mismatch may provide a personalized approach for determining non-AD factors associated with resilience/vulnerability to Alzheimer's disease.

The neuroimmune axis of Alzheimer's disease

Alzheimer's disease (AD) is a genetically complex and heterogeneous disorder with multifaceted neuropathological features, including β-amyloid plaques, neurofibrillary tangles, and neuroinflammation. Over the past decade, emerging evidence has implicated both beneficial and pathological roles for innate immune genes and immune cells, including peripheral immune cells such as T cells, which can infiltrate the brain and either ameliorate or exacerbate AD neuropathogenesis. These findings support a neuroimmune axis of AD, in which the interplay of adaptive and innate immune systems inside and outside the brain critically impacts the etiology and pathogenesis of AD. In this review, we discuss the complexities of AD neuropathology at the levels of genetics and cellular physiology, highlighting immune signaling pathways and genes associated with AD risk and interactions among both innate and adaptive immune cells in the AD brain. We emphasize the role of peripheral immune cells in AD and the mechanisms by which immune cells, such as T cells and monocytes, influence AD neuropathology, including microglial clearance of amyloid-β peptide, the key component of β-amyloid plaque cores, pro-inflammatory and cytotoxic activity of microglia, astrogliosis, and their interactions with the brain vasculature. Finally, we review the challenges and outlook for establishing immune-based therapies for treating and preventing AD.

Obesity-Associated Neurodegeneration Pattern Mimics Alzheimer's Disease in an Observational Cohort Study

BACKGROUND

Excess weight in adulthood leads to health complications such as diabetes, hypertension, or dyslipidemia. Recently, excess weight has also been related to brain atrophy and cognitive decline. Reports show that obesity is linked with Alzheimer's disease (AD)-related changes, such as cerebrovascular damage or amyloid-β accumulation. However, to date no research has conducted a direct comparison between brain atrophy patterns in AD and obesity.

OBJECTIVE

Here, we compared patterns of brain atrophy and amyloid-β/tau protein accumulation in obesity and AD using a sample of over 1,300 individuals from four groups: AD patients, healthy controls, obese otherwise healthy individuals, and lean individuals.

METHODS

We age- and sex-matched all groups to the AD-patients group and created cortical thickness maps of AD and obesity. This was done by comparing AD patients with healthy controls, and obese individuals with lean individuals. We then compared the AD and obesity maps using correlation analyses and permutation-based tests that account for spatial autocorrelation. Similarly, we compared obesity brain maps with amyloid-β and tau protein maps from other studies.

RESULTS

Obesity maps were highly correlated with AD maps but were not correlated with amyloid-β/tau protein maps. This effect was not accounted for by the presence of obesity in the AD group.

CONCLUSION

Our research confirms that obesity-related grey matter atrophy resembles that of AD. Excess weight management could lead to improved health outcomes, slow down cognitive decline in aging, and lower the risk for AD.

A Surface-Based Federated Chow Test Model for Integrating APOE Status, Tau Deposition Measure, and Hippocampal Surface Morphometry

BACKGROUND

Alzheimer's disease (AD) is the most common type of age-related dementia, affecting 6.2 million people aged 65 or older according to CDC data. It is commonly agreed that discovering an effective AD diagnosis biomarker could have enormous public health benefits, potentially preventing or delaying up to 40% of dementia cases. Tau neurofibrillary tangles are the primary driver of downstream neurodegeneration and subsequent cognitive impairment in AD, resulting in structural deformations such as hippocampal atrophy that can be observed in magnetic resonance imaging (MRI) scans.

OBJECTIVE

To build a surface-based model to 1) detect differences between APOE subgroups in patterns of tau deposition and hippocampal atrophy, and 2) use the extracted surface-based features to predict cognitive decline.

METHODS

Using data obtained from different institutions, we develop a surface-based federated Chow test model to study the synergistic effects of APOE, a previously reported significant risk factor of AD, and tau on hippocampal surface morphometry.

RESULTS

We illustrate that the APOE-specific morphometry features correlate with AD progression and better predict future AD conversion than other MRI biomarkers. For example, a strong association between atrophy and abnormal tau was identified in hippocampal subregion cornu ammonis 1 (CA1 subfield) and subiculum in e4 homozygote cohort.

CONCLUSION

Our model allows for identifying MRI biomarkers for AD and cognitive decline prediction and may uncover a corner of the neural mechanism of the influence of APOE and tau deposition on hippocampal morphology.

The hippocampal sparing subtype of Alzheimer's disease assessed in neuropathology and in vivo tau positron emission tomography: a systematic review

Neuropathology and neuroimaging studies have identified several subtypes of Alzheimer's disease (AD): hippocampal sparing AD, typical AD, and limbic predominant AD. An unresolved question is whether hippocampal sparing AD cases can present with neurofibrillary tangles (NFT) in association cortices while completely sparing the hippocampus. To address that question, we conducted a systematic review and performed original analyses on tau positron emission tomography (PET) data. We searched EMBASE, PubMed, and Web of Science databases until October 2022. We also implemented several methods for AD subtyping on tau PET to identify hippocampal sparing AD cases. Our findings show that seven out of the eight reviewed neuropathologic studies included cases at Braak stages IV or higher and therefore, could not identify hippocampal sparing cases with NFT completely sparing the hippocampus. In contrast, tau PET did identify AD participants with tracer retention in the association cortex while completely sparing the hippocampus. We conclude that tau PET can identify hippocampal sparing AD cases with NFT completely sparing the hippocampus. Based on the accumulating data, we suggest two possible pathways of tau spread: (1) a canonical pathway with early involvement of transentorhinal cortex and subsequent involvement of limbic regions and association cortices, and (2) a less common pathway that affects association cortices with limbic involvement observed at end stages of the disease or not at all.

Limbic-Predominant Age-Related TDP-43 Encephalopathy: LATE-Breaking Updates in Clinicopathologic Features and Biomarkers

PURPOSE OF REVIEW

Limbic-predominant age-related TDP-43 encephalopathy (LATE) is a recently defined neurodegenerative disease characterized by amnestic phenotype and pathological inclusions of TAR DNA-binding protein 43 (TDP-43). LATE is distinct from rarer forms of TDP-43 diseases such as frontotemporal lobar degeneration with TDP-43 but is also a common copathology with Alzheimer's disease (AD) and cerebrovascular disease and accelerates cognitive decline. LATE contributes to clinicopathologic heterogeneity in neurodegenerative diseases, so it is imperative to distinguish LATE from other etiologies.

RECENT FINDINGS

Novel biomarkers for LATE are being developed with magnetic resonance imaging (MRI) and positron emission tomography (PET). When cooccurring with AD, LATE exhibits identifiable patterns of limbic-predominant atrophy on MRI and hypometabolism on 18F-fluorodeoxyglucose PET that are greater than expected relative to levels of local AD pathology. Efforts are being made to develop TDP-43-specific radiotracers, molecularly specific biofluid measures, and genomic predictors of TDP-43. LATE is a highly prevalent neurodegenerative disease distinct from previously characterized cognitive disorders.

Neuropathology of Dementia Disorders

PURPOSE OF REVIEW

This article provides an overview of the neuropathology of common age-related dementing disorders, focusing on the pathologies that underlie Alzheimer disease (AD) and related dementias, including Lewy body dementias, frontotemporal dementia, vascular dementia, limbic-predominant age-related transactive response DNA-binding protein 43 (TDP-43) encephalopathy (LATE), and mixed-etiology dementias. This article also discusses the underlying proteinopathies of neurodegenerative diseases (eg, amyloid-β, paired helical filament tau, α-synuclein, and TDP-43 pathology) and vascular pathologies, including tissue injury (eg, infarcts, hemorrhages) with or without vessel disease.

RECENT FINDINGS

New criteria for AD pathologic diagnosis highlight amyloid-β as the sine qua non of AD; they require molecular markers of amyloid and establish a minimum threshold of Braak neurofibrillary tangle stage 3. Pathologic diagnosis is separated from clinical disease (ie, pathologic diagnosis no longer requires dementia). TDP-43 pathology, a major pathology in a frontotemporal dementia subtype, was found as a central pathology in LATE, a newly named amnestic disorder. Multiple pathologies (often co-occurring with AD) contribute to dementia and add complexity to the clinical picture. Conversely, Lewy body, LATE, and vascular dementias often have accompanying AD pathology. Pathology and biomarker studies highlight subclinical pathologies in older people without cognitive impairment. This resilience to brain pathology is common and is known as cognitive reserve.

SUMMARY

The pathologies of dementia in aging are most commonly amyloid, tangles, Lewy bodies, TDP-43, hippocampal sclerosis, and vascular pathologies. These pathologies often co-occur (mixed pathologies), which may make specific clinical diagnoses difficult. In addition, dementia-related pathologies are often subclinical, suggesting varying levels of resilience in older people.

Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer's disease

Alzheimer's disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer's Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD.

Imaging Clinical Subtypes and Associated Brain Networks in Alzheimer’s Disease

Alzheimer’s disease (AD) does not present uniform symptoms or a uniform rate of progression in all cases. The classification of subtypes can be based on clinical symptoms or patterns of pathological brain alterations. Imaging techniques may allow for the identification of AD subtypes and their differentiation from other neurodegenerative diseases already at an early stage. In this review, the strengths and weaknesses of current clinical imaging methods are described. These include positron emission tomography (PET) to image cerebral glucose metabolism and pathological amyloid or tau deposits. Magnetic resonance imaging (MRI) is more widely available than PET. It provides information on structural or functional changes in brain networks and their relation to AD subtypes. Amyloid PET provides a very early marker of AD but does not distinguish between AD subtypes. Regional patterns of pathology related to AD subtypes are observed with tau and glucose PET, and eventually as atrophy patterns on MRI. Structural and functional network changes occur early in AD but have not yet provided diagnostic specificity.