Alzheimer's disease is not "brain aging": neuropathological, genetic, and epidemiological human studies

Biomarker-Based Precision Therapy for Alzheimer's Disease: Multidimensional Evidence Leading a New Breakthrough in Personalized Medicine

(1) Background: Alzheimer's disease (AD) is a worldwide neurodegenerative disorder characterized by the buildup of abnormal proteins in the central nervous system and cognitive decline. Since no radical therapy exists, only symptomatic treatments alleviate symptoms temporarily. In this review, we will explore the latest advancements in precision medicine and biomarkers for AD, including their potential to revolutionize the way we diagnose and treat this devastating condition. (2) Methods: A literature search was performed combining the following Medical Subject Heading (MeSH) terms on PubMed: "Alzheimer's disease", "biomarkers", "APOE", "APP", "GWAS", "cerebrospinal fluid", "polygenic risk score", "Aβ42", "τP-181", " p-tau217", "ptau231", "proteomics", "total tau protein", and "precision medicine" using Boolean operators. (3) Results: Genome-wide association studies (GWAS) have identified numerous genetic variants associated with AD risk, while a transcriptomic analysis has revealed dysregulated gene expression patterns in the brains of individuals with AD. The proteomic and metabolomic profiling of biological fluids, such as blood, urine, and CSF, and neuroimaging biomarkers have also yielded potential biomarkers of AD that could be used for the early diagnosis and monitoring of disease progression. (4) Conclusion: By leveraging a combination of the above biomarkers, novel ultrasensitive immunoassays, mass spectrometry methods, and metabolomics, researchers are making significant strides towards personalized healthcare for individuals with AD.

Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup

The National Institute on Aging and the Alzheimer's Association convened three separate work groups in 2011 and single work groups in 2012 and 2018 to create recommendations for the diagnosis and characterization of Alzheimer's disease (AD). The present document updates the 2018 research framework in response to several recent developments. Defining diseases biologically, rather than based on syndromic presentation, has long been standard in many areas of medicine (e.g., oncology), and is becoming a unifying concept common to all neurodegenerative diseases, not just AD. The present document is consistent with this principle. Our intent is to present objective criteria for diagnosis and staging AD, incorporating recent advances in biomarkers, to serve as a bridge between research and clinical care. These criteria are not intended to provide step-by-step clinical practice guidelines for clinical workflow or specific treatment protocols, but rather serve as general principles to inform diagnosis and staging of AD that reflect current science. HIGHLIGHTS: We define Alzheimer's disease (AD) to be a biological process that begins with the appearance of AD neuropathologic change (ADNPC) while people are asymptomatic. Progression of the neuropathologic burden leads to the later appearance and progression of clinical symptoms. Early-changing Core 1 biomarkers (amyloid positron emission tomography [PET], approved cerebrospinal fluid biomarkers, and accurate plasma biomarkers [especially phosphorylated tau 217]) map onto either the amyloid beta or AD tauopathy pathway; however, these reflect the presence of ADNPC more generally (i.e., both neuritic plaques and tangles). An abnormal Core 1 biomarker result is sufficient to establish a diagnosis of AD and to inform clinical decision making throughout the disease continuum. Later-changing Core 2 biomarkers (biofluid and tau PET) can provide prognostic information, and when abnormal, will increase confidence that AD is contributing to symptoms. An integrated biological and clinical staging scheme is described that accommodates the fact that common copathologies, cognitive reserve, and resistance may modify relationships between clinical and biological AD stages.

Essential New Complexity-Based Themes for Patient-Centered Diagnosis and Treatment of Dementia and Predementia in Older People: Multimorbidity and Multilevel Phenomenology

Dementia is a highly prevalent condition with devastating clinical and socioeconomic sequela. It is expected to triple in prevalence by 2050. No treatment is currently known to be effective. Symptomatic late-onset dementia and predementia (SLODP) affects 95% of patients with the syndrome. In contrast to trials of pharmacological prevention, no treatment is suggested to remediate or cure these symptomatic patients. SLODP but not young onset dementia is intensely associated with multimorbidity (MUM), including brain-perturbating conditions (BPCs). Recent studies showed that MUM/BPCs have a major role in the pathogenesis of SLODP. Fortunately, most MUM/BPCs are medically treatable, and thus, their treatment may modify and improve SLODP, relieving suffering and reducing its clinical and socioeconomic threats. Regrettably, the complex system features of SLODP impede the diagnosis and treatment of the potentially remediable conditions (PRCs) associated with them, mainly due to failure of pattern recognition and a flawed diagnostic workup. We suggest incorporating two SLODP-specific conceptual themes into the diagnostic workup: MUM/BPC and multilevel phenomenological themes. By doing so, we were able to improve the diagnostic accuracy of SLODP components and optimize detecting and favorably treating PRCs. These revolutionary concepts and their implications for remediability and other parameters are discussed in the paper.

Neuroglia in cognitive reserve

The concept of cognitive reserve was born to account for the disjunction between the objective extent of brain damage in pathology and its clinical and intellectual outcome. The cognitive reserve comprises structural (brain reserve) and functional (brain maintenance, resilience, compensation) aspects of the nervous tissue reflecting exposome-driven life-long plasticity, which defines the ability of the brain to withstand aging and pathology. The mechanistic background of this concept was primarily focused on adaptive changes in neurones and neuronal networks. We present arguments favoring the more inclusive view, positing that neuroglia are fundamental for defining the cognitive reserve through homeostatic, neuroprotective, and neurodegenerative mechanisms. Neuroglia are critical for the life-long shaping of synaptically connected neuronal circuits as well as the brain connectome thus defining cognitive reserve. Neuroglial homeostatic and protective physiological responses define brain maintenance and resilience, while neuroglia regenerative capabilities are critical for brain compensation in pathology. Targeting neuroglia may represent an untrodden path for prolonging cognitive longevity.

Association of diabetes mellitus with dementia- and non-dementia-related mortality amongst women: a secondary competing risks analysis of the California Teachers Study

BACKGROUND AND PURPOSE

The prevalence of dementia is rapidly increasing. Attempts to further understand modifiable risk factors such as diabetes mellitus (DM) are urgently needed to inform public health policies for prevention. Thus, the objective of the current study was to assess the relationship between DM and risk of dementia and non-dementia mortality amongst women in the California Teachers Study prospective cohort.

METHODS

Women (n = 124,509) aged 22-104 years at baseline were included. DM was ascertained from self-reported questionnaires and hospital-linked records. Dementia-related deaths were ascertained from state and national records. Competing risk regression models were used to estimate cause-specific hazard ratios and 95% confidence intervals for the association of DM with dementia- and non-dementia-related mortality.

RESULTS

There were 10,511 total DM cases and 3625 deaths due to dementia over a mean of 21.3 years of follow-up. Fully adjusted cause-specific hazard ratios of the association with DM were 2.26 (2.01, 2.55) for dementia-related and 1.97 (1.89, 2.05) for the competing risk of non-dementia-related mortality. This association was strongest amongst participants with incident DM, younger age at baseline and higher alcohol consumption or who were overweight.

CONCLUSIONS

In the California Teachers Study, women with DM had increased risk of mortality due to both dementia and non-dementia causes; however, the risk of mortality due to dementia was elevated compared to non-dementia causes only amongst participants with incident DM.

ArcheD, a residual neural network for prediction of cerebrospinal fluid amyloid-beta from amyloid PET images

Detection and measurement of amyloid-beta (Aβ) in the brain is a key factor for early identification and diagnosis of Alzheimer's disease (AD). We aimed to develop a deep learning model to predict Aβ cerebrospinal fluid (CSF) concentration directly from amyloid PET images, independent of tracers, brain reference regions or preselected regions of interest. We used 1870 Aβ PET images and CSF measurements to train and validate a convolutional neural network ("ArcheD"). We evaluated the ArcheD performance in relation to episodic memory and the standardized uptake value ratio (SUVR) of cortical Aβ. We also compared the brain region's relevance for the model's CSF prediction within clinical-based and biological-based classifications. ArcheD-predicted Aβ CSF values correlated with measured Aβ CSF values (r = 0.92; q < 0.01), SUVR (rAV45 = -0.64, rFBB = -0.69; q < 0.01) and episodic memory measures (0.33 < r < 0.44; q < 0.01). For both classifications, cerebral white matter significantly contributed to CSF prediction (q < 0.01), specifically in non-symptomatic and early stages of AD. However, in late-stage disease, the brain stem, subcortical areas, cortical lobes, limbic lobe and basal forebrain made more significant contributions (q < 0.01). Considering cortical grey matter separately, the parietal lobe was the strongest predictor of CSF amyloid levels in those with prodromal or early AD, while the temporal lobe played a more crucial role for those with AD. In summary, ArcheD reliably predicted Aβ CSF concentration from Aβ PET scans, offering potential clinical utility for Aβ level determination.

Limbic-predominant age-related TDP-43 encephalopathy (LATE-NC): Co-pathologies and genetic risk factors provide clues about pathogenesis

Limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) is detectable at autopsy in more than one-third of people beyond age 85 years and is robustly associated with dementia independent of other pathologies. Although LATE-NC has a large impact on public health, there remain uncertainties about the underlying biologic mechanisms. Here, we review the literature from human studies that may shed light on pathogenetic mechanisms. It is increasingly clear that certain combinations of pathologic changes tend to coexist in aging brains. Although "pure" LATE-NC is not rare, LATE-NC often coexists in the same brains with Alzheimer disease neuropathologic change, brain arteriolosclerosis, hippocampal sclerosis of aging, and/or age-related tau astrogliopathy (ARTAG). The patterns of pathologic comorbidities provide circumstantial evidence of mechanistic interactions ("synergies") between the pathologies, and also suggest common upstream influences. As to primary mediators of vulnerability to neuropathologic changes, genetics may play key roles. Genes associated with LATE-NC include TMEM106B, GRN, APOE, SORL1, ABCC9, and others. Although the anatomic distribution of TDP-43 pathology defines the condition, important cofactors for LATE-NC may include Tau pathology, endolysosomal pathways, and blood-brain barrier dysfunction. A review of the human phenomenology offers insights into disease-driving mechanisms, and may provide clues for diagnostic and therapeutic targets.

2024 Alzheimer's disease facts and figures

This article describes the public health impact of Alzheimer's disease (AD), including prevalence and incidence, mortality and morbidity, use and costs of care and the ramifications of AD for family caregivers, the dementia workforce and society. The Special Report discusses the larger health care system for older adults with cognitive issues, focusing on the role of caregivers and non-physician health care professionals. An estimated 6.9 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060, barring the development of medical breakthroughs to prevent or cure AD. Official AD death certificates recorded 119,399 deaths from AD in 2021. In 2020 and 2021, when COVID-19 entered the ranks of the top ten causes of death, Alzheimer's was the seventh-leading cause of death in the United States. Official counts for more recent years are still being compiled. Alzheimer's remains the fifth-leading cause of death among Americans age 65 and older. Between 2000 and 2021, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 140%. More than 11 million family members and other unpaid caregivers provided an estimated 18.4 billion hours of care to people with Alzheimer's or other dementias in 2023. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $346.6 billion in 2023. Its costs, however, extend to unpaid caregivers' increased risk for emotional distress and negative mental and physical health outcomes. Members of the paid health care and broader community-based workforce are involved in diagnosing, treating and caring for people with dementia. However, the United States faces growing shortages across different segments of the dementia care workforce due to a combination of factors, including the absolute increase in the number of people living with dementia. Therefore, targeted programs and care delivery models will be needed to attract, better train and effectively deploy health care and community-based workers to provide dementia care. Average per-person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2024 for health care, long-term care and hospice services for people age 65 and older with dementia are estimated to be $360 billion. The Special Report investigates how caregivers of older adults with cognitive issues interact with the health care system and examines the role non-physician health care professionals play in facilitating clinical care and access to community-based services and supports. It includes surveys of caregivers and health care workers, focusing on their experiences, challenges, awareness and perceptions of dementia care navigation.

Role of Neurocellular Endoplasmic Reticulum Stress Response in Alzheimer's Disease and Related Dementias Risk

Currently, more than 55 million people around the world suffer from dementia, and Alzheimer's Disease and Related Dementias (ADRD) accounts for nearly 60-70% of all those cases. The spread of Alzheimer's Disease (AD) pathology and progressive neurodegeneration in the hippocampus and cerebral cortex is strongly correlated with cognitive decline in AD patients; however, the molecular underpinning of ADRD's causality is still unclear. Studies of postmortem AD brains and animal models of AD suggest that elevated endoplasmic reticulum (ER) stress may have a role in ADRD pathology through altered neurocellular homeostasis in brain regions associated with learning and memory. To study the ER stress-associated neurocellular response and its effects on neurocellular homeostasis and neurogenesis, we modeled an ER stress challenge using thapsigargin (TG), a specific inhibitor of sarco/endoplasmic reticulum Ca2+ ATPase (SERCA), in the induced pluripotent stem cell (iPSC)-derived neural stem cells (NSCs) of two individuals from our Mexican American Family Study (MAFS). High-content screening and transcriptomic analysis of the control and ER stress-challenged NSCs showed that the NSCs' ER stress response resulted in a significant decline in NSC self-renewal and an increase in apoptosis and cellular oxidative stress. A total of 2300 genes were significantly (moderated t statistics FDR-corrected p-value ≤ 0.05 and fold change absolute ≥ 2.0) differentially expressed (DE). The pathway enrichment and gene network analysis of DE genes suggests that all three unfolded protein response (UPR) pathways, protein kinase RNA-like ER kinase (PERK), activating transcription factor-6 (ATF-6), and inositol-requiring enzyme-1 (IRE1), were significantly activated and cooperatively regulated the NSCs' transcriptional response to ER stress. Our results show that IRE1/X-box binding protein 1 (XBP1) mediated transcriptional regulation of the E2F transcription factor 1 (E2F1) gene, and its downstream targets have a dominant role in inducing G1/S-phase cell cycle arrest in ER stress-challenged NSCs. The ER stress-challenged NSCs also showed the activation of C/EBP homologous protein (CHOP)-mediated apoptosis and the dysregulation of synaptic plasticity and neurotransmitter homeostasis-associated genes. Overall, our results suggest that the ER stress-associated attenuation of NSC self-renewal, increased apoptosis, and dysregulated synaptic plasticity and neurotransmitter homeostasis plausibly play a role in the causation of ADRD.

Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.

Update on the role of T cells in cognitive impairment

The central nervous system (CNS) has long been considered an immune-privileged site, with minimal interaction between immune cells, particularly of the adaptive immune system. Previously, the presence of immune cells in this organ was primarily linked to events involving disruption of the blood-brain barrier (BBB) or inflammation. However, current research has shown that immune cells are found patrolling CNS under homeostatic conditions. Specifically, T cells of the adaptive immune system are able to cross the BBB and are associated with ageing and cognitive impairment. In addition, T-cell infiltration has been observed in pathological conditions, where inflammation correlates with poor prognosis. Despite ongoing research, the role of this population in the ageing brain under both physiological and pathological conditions is not yet fully understood. In this review, we provide an overview of the interactions between T cells and other immune and CNS parenchymal cells, and examine the molecular mechanisms by which these interactions may contribute to normal brain function and the scenarios in which disruption of these connections lead to cognitive impairment. A comprehensive understanding of the role of T cells in the ageing brain and the underlying molecular pathways under normal conditions could pave the way for new research to better understand brain disorders. LINKED ARTICLES: This article is part of a themed issue From Alzheimer's Disease to Vascular Dementia: Different Roads Leading to Cognitive Decline. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.6/issuetoc.

3D convolutional neural networks uncover modality-specific brain-imaging predictors for Alzheimer's disease sub-scores

Different aspects of cognitive functions are affected in patients with Alzheimer's disease. To date, little is known about the associations between features from brain-imaging and individual Alzheimer's disease (AD)-related cognitive functional changes. In addition, how these associations differ among different imaging modalities is unclear. Here, we trained and investigated 3D convolutional neural network (CNN) models that predicted sub-scores of the 13-item Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog13) based on MRI and FDG-PET brain-imaging data. Analysis of the trained network showed that each key ADAS-Cog13 sub-score was associated with a specific set of brain features within an imaging modality. Furthermore, different association patterns were observed in MRI and FDG-PET modalities. According to MRI, cognitive sub-scores were typically associated with structural changes of subcortical regions, including amygdala, hippocampus, and putamen. Comparatively, according to FDG-PET, cognitive functions were typically associated with metabolic changes of cortical regions, including the cingulated gyrus, occipital cortex, middle front gyrus, precuneus cortex, and the cerebellum. These findings brought insights into complex AD etiology and emphasized the importance of investigating different brain-imaging modalities.

Pathologic correlates of aging-related tau astrogliopathy: ARTAG is associated with LATE-NC and cerebrovascular pathologies, but not with ADNC

Age-related tau astrogliopathy (ARTAG) is detectable in the brains of over one-third of autopsied persons beyond age 80, but the pathoetiology of ARTAG is poorly understood. Insights can be gained by analyzing risk factors and comorbid pathologies. Here we addressed the question of which prevalent co-pathologies are observed with increased frequency in brains with ARTAG. The study sample was the National Alzheimer's Coordinating Center (NACC) data set, derived from multiple Alzheimer's disease research centers (ADRCs) in the United States. Data from persons with unusual conditions (e.g. frontotemporal dementia) were excluded leaving 504 individual autopsied research participants, clustering from 20 different ADRCs, autopsied since 2020; ARTAG was reported in 222 (44.0%) of included participants. As has been shown previously, ARTAG was increasingly frequent with older age and in males. The presence and severity of other common subtypes of pathology that were previously linked to dementia were analyzed, stratifying for the presence of ARTAG. In logistical regression-based statistical models that included age and sex as covariates, ARTAG was relatively more likely to be found in brains with limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC), and in brains with comorbid cerebrovascular pathology (arteriolosclerosis and/or brain infarcts). However, ARTAG was not associated with severe Alzheimer's disease neuropathologic change (ADNC), or primary age-related tauopathy (PART). In a subset analysis of 167 participants with neurocognitive testing data, there was a marginal trend for ARTAG pathology to be associated with cognitive impairment as assessed with MMSE scores (P = 0.07, adjusting for age, sex, interval between final clinic visit and death, and ADNC severity). A limitation of the study was that there were missing data about ARTAG pathologies, with incomplete operationalization of ARTAG according to anatomic region and pathologic subtypes (e.g., thorn-shaped or granular-fuzzy astrocytes). In summary, ARTAG was not associated with ADNC, whereas prior observations about ARTAG occurring with increased frequency in aging, males, and brains with LATE-NC were replicated. It remains to be determined whether the increased frequency of ARTAG in brains with comorbid cerebrovascular pathology is related to local infarctions or neuroinflammatory signaling, or with some other set of correlated factors including blood-brain barrier dysfunction.

Controversial Past, Splendid Present, Unpredictable Future: A Brief Review of Alzheimer Disease History

Background: The concept of Alzheimer disease (AD)-since its histological discovery by Alzheimer to the present day-has undergone substantial modifications. Methods: We conducted a classical narrative review of this field with a bibliography selection (giving preference to Medline best match). Results: The following subjects are reviewed and discussed: Alzheimer's discovery, Kraepelin's creation of a new disease that was a rare condition until the 1970's, the growing interest and investment in AD as a major killer in a society with a large elderly population in the second half of the 20th century, the consolidation of the AD clinicopathological model, and the modern AD nosology based on the dominant amyloid hypothesis among many others. In the 21st century, the development of AD biomarkers has supported a novel biological definition of AD, although the proposed therapies have failed to cure this disease. The incidence of dementia/AD has shown a decrease in affluent countries (possibly due to control of risk factors), and mixed dementia has been established as the most frequent etiology in the oldest old. Conclusions: The current concept of AD lacks unanimity. Many hypotheses attempt to explain its complex physiopathology entwined with aging, and the dominant amyloid cascade has yielded poor therapeutic results. The reduction in the incidence of dementia/AD appears promising but it should be confirmed in the future. A reevaluation of the AD concept is also necessary.

Creating an Unprotected Class: Addressing Legal Risks in the Era of Biologically-Defined Alzheimer's Disease

Background

Documentation of preclinical biomarker tests for Alzheimer's disease (AD) in the medical record may expose patients to employment and insurance discrimination risks. There is a gap in research describing clinicians' approaches to documenting biomarker results.

Objective

To evaluate discrimination risks faced by patients undergoing biomarker testing for AD through a qualitative analysis of clinician documentation practices.

Methods

Semi-structured interviews using hypothetical patient scenarios. The qualitative analysis focused on interviewees' responses related to documentation and disclosure of results.

Results

We collected and analyzed 17 interviews with dementia experts; and identified three approaches to documenting biomarkers as: an association with active AD, noninformative, and an increased susceptibility for AD. Those who associated biomarkers with active disease were more likely to favor disclosure to employers and insurers, which could increase discrimination risks.

Conclusions

This study demonstrates the variety of documentation and disclosure practices likely to emerge for preclinical AD biomarker tests and highlights a need for guidelines in this area.

HIV and COVID-19: two pandemics with significant (but different) central nervous system complications

Human immunodeficiency virus (HIV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause significant neurologic disease. Central nervous system (CNS) involvement of HIV has been extensively studied, with well-documented invasion of HIV into the brain in the initial stage of infection, while the acute effects of SARS-CoV-2 in the brain are unclear. Neuropathologic features of active HIV infection in the brain are well characterized whereas neuropathologic findings in acute COVID-19 are largely non-specific. On the other hand, neuropathologic substrates of chronic dysfunction in both infections, as HIV-associated neurocognitive disorders (HAND) and post-COVID conditions (PCC)/long COVID are unknown. Thus far, neuropathologic studies on patients with HAND in the era of combined antiretroviral therapy have been inconclusive, and autopsy studies on patients diagnosed with PCC have yet to be published. Further longitudinal, multidisciplinary studies on patients with HAND and PCC and neuropathologic studies in comparison to controls are warranted to help elucidate the mechanisms of CNS dysfunction in both conditions.

Classifying Alzheimer's Disease Neuropathology Using Clinical and MRI Measurements

Background

Computer-aided machine learning models are being actively developed with clinically available biomarkers to diagnose Alzheimer's disease (AD) in living persons. Despite considerable work with cross-sectional in vivo data, many models lack validation against postmortem AD neuropathological data.

Objective

Train machine learning models to classify the presence or absence of autopsy-confirmed severe AD neuropathology using clinically available features.

Methods

AD neuropathological status are assessed at postmortem for participants from the National Alzheimer's Coordinating Center (NACC). Clinically available features are utilized, including demographics, Apolipoprotein E(APOE) genotype, and cortical thicknesses derived from ante-mortem MRI scans encompassing AD meta regions of interest (meta-ROI). Both logistic regression and random forest models are trained to identify linearly and nonlinearly separable features between participants with the presence (N = 91, age-at-MRI = 73.6±9.24, 38 women) or absence (N = 53, age-at-MRI = 68.93±19.69, 24 women) of severe AD neuropathology. The trained models are further validated in an external data set against in vivo amyloid biomarkers derived from PET imaging (amyloid-positive: N = 71, age-at-MRI = 74.17±6.37, 26 women; amyloid-negative: N = 73, age-at-MRI = 71.59±6.80, 41 women).

Results

Our models achieve a cross-validation accuracy of 84.03% in classifying the presence or absence of severe AD neuropathology, and an external-validation accuracy of 70.14% in classifying in vivo amyloid positivity status.

Conclusions

Our models show that clinically accessible features, including APOE genotype and cortical thinning encompassing AD meta-ROIs, are able to classify both postmortem confirmed AD neuropathological status and in vivo amyloid status with reasonable accuracies. These results suggest the potential utility of AD meta-ROIs in determining AD neuropathological status in living persons.

ArcheD, a residual neural network for prediction of cerebrospinal fluid amyloid-beta from amyloid PET images

Detection and measurement of amyloid-beta (Aβ) aggregation in the brain is a key factor for early identification and diagnosis of Alzheimer's disease (AD). We aimed to develop a deep learning model to predict Aβ cerebrospinal fluid (CSF) concentration directly from amyloid PET images, independent of tracers, brain reference regions or preselected regions of interest. We used 1870 Aβ PET images and CSF measurements to train and validate a convolutional neural network ("ArcheD"). We evaluated the ArcheD performance in relation to episodic memory and the standardized uptake value ratio (SUVR) of cortical Aβ. We also compared the brain region's relevance for the model's CSF prediction within clinical-based and biological-based classifications. ArcheD-predicted Aβ CSF values correlated strongly with measured Aβ CSF values ( r =0.81; p <0.001) and showed correlations with SUVR and episodic memory measures in all participants except in those with AD. For both clinical and biological classifications, cerebral white matter significantly contributed to CSF prediction ( q <0.01), specifically in non-symptomatic and early stages of AD. However, in late-stage disease, brain stem, subcortical areas, cortical lobes, limbic lobe, and basal forebrain made more significant contributions (q<0.01). Considering cortical gray matter separately, the parietal lobe was the strongest predictor of CSF amyloid levels in those with prodromal or early AD, while the temporal lobe played a more crucial role for those with AD. In summary, ArcheD reliably predicted Aβ CSF concentration from Aβ PET scans, offering potential clinical utility for Aβ level determination and early AD detection.

Tau positron emission tomography in patients with cognitive impairment and suspected Alzheimer's disease

Alzheimer's disease (AD) is diagnosed by the presence of both amyloid β and tau proteins. Recent advances in molecular PET imaging have made it possible to assess the accumulation of these proteins in the living brain. PET ligands have been developed that bind to 3R/4R tau in AD, but not to 3R tau or 4R tau alone. Of the first-generation PET ligands, 18F-flortaucipir has recently been approved by the Food and Drug Administration. Several second-generation PET probes with less off-target binding have been developed and are being applied clinically. Visual interpretation of tau PET should be based on neuropathological neurofibrillary tangle staging instead of a simple positive or negative classification. Four visual read classifications have been proposed: "no uptake," "medial temporal lobe (MTL) only," "MTL AND," and "outside MTL." As an adjunct to visual interpretation, quantitative analysis has been proposed using MRI-based native space FreeSurfer parcellations. The standardized uptake value ratio of the target area is measured using the cerebellar gray matter as a reference region. In the near future, the Centiloid scale of tau PET is expected to be used as a harmonized value for standardizing each analytical method or PET ligand used, similar to amyloid PET.

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.

Blood-Brain Barrier Dysfunction and Aβ42/40 Ratio Dose-Dependent Modulation with the ApoE Genotype within the ATN Framework

The definition of Alzheimer's disease (AD) now considers the presence of the markers of amyloid (A), tau deposition (T), and neurodegeneration (N) essential for diagnosis. AD patients have been reported to have increased blood-brain barrier (BBB) dysfunction, but that has not been tested within the ATN framework so far. As the field is moving towards the use of blood-based biomarkers, the relationship between BBB disruption and AD-specific biomarkers requires considerable attention. Moreover, other factors have been previously implicated in modulating BBB permeability, including age, gender, and ApoE status. A total of 172 cognitively impaired individuals underwent cerebrospinal fluid (CSF) analysis for AD biomarkers, and data on BBB dysfunction, demographics, and ApoE status were collected. Our data showed that there was no difference in BBB dysfunction across different ATN subtypes, and that BBB damage was not correlated with cognitive impairment. However, patients with BBB disruption, if measured with a high Qalb, had low Aβ40 levels. ApoE status did not affect BBB function but had a dose-dependent effect on the Aβ42/40 ratio. These results might highlight the importance of understanding dynamic changes across the BBB in future studies in patients with AD.

Moving beyond amyloid and tau to capture the biological heterogeneity of Alzheimer's disease

Alzheimer's disease (AD) manifests along a spectrum of cognitive deficits and levels of neuropathology. Genetic studies support a heterogeneous disease mechanism, with around 70 associated loci to date, implicating several biological processes that mediate risk for AD. Despite this heterogeneity, most experimental systems for testing new therapeutics are not designed to capture the genetically complex drivers of AD risk. In this review, we first provide an overview of those aspects of AD that are largely stereotyped and those that are heterogeneous, and we review the evidence supporting the concept that different subtypes of AD are important to consider in the design of agents for the prevention and treatment of the disease. We then dive into the multifaceted biological domains implicated to date in AD risk, highlighting studies of the diverse genetic drivers of disease. Finally, we explore recent efforts to identify biological subtypes of AD, with an emphasis on the experimental systems and data sets available to support progress in this area.

Deep Brain Stimulation beyond the Clinic: Navigating the Future of Parkinson's and Alzheimer's Disease Therapy

Deep brain stimulation (DBS) is a surgical procedure that uses electrical neuromodulation to target specific regions of the brain, showing potential in the treatment of neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD). Despite similarities in disease pathology, DBS is currently only approved for use in PD patients, with limited literature on its effectiveness in AD. While DBS has shown promise in ameliorating brain circuits in PD, further research is needed to determine the optimal parameters for DBS and address any potential side effects. This review emphasizes the need for foundational and clinical research on DBS in different brain regions to treat AD and recommends the development of a classification system for adverse effects. Furthermore, this review suggests the use of either a low-frequency system (LFS) or high-frequency system (HFS) depending on the specific symptoms of the patient for both PD and AD.

Role of microglia autophagy and mitophagy in age-related neurodegenerative diseases

Microglia, characterized by responding to damage, regulating the secretion of soluble inflammatory mediators, and engulfing specific segments in the central nervous system (CNS), function as key immune cells in the CNS. Emerging evidence suggests that microglia coordinate the inflammatory responses in CNS system and play a pivotal role in the pathogenesis of age-related neurodegenerative diseases (NDDs). Remarkably, microglia autophagy participates in the regulation of subcellular substances, which includes the degradation of misfolded proteins and other harmful constituents produced by neurons. Therefore, microglia autophagy regulates neuronal homeostasis maintenance and process of neuroinflammation. In this review, we aimed at highlighting the pivotal role of microglia autophagy in the pathogenesis of age-related NDDs. Besides the mechanistic process and the co-interaction between microglia autophagy and different kinds of NDDs, we also emphasized potential therapeutic agents and approaches that could be utilized at the onset and progression of these diseases through modulating microglia autophagy, including promising nanomedicines. Our review provides a valuable reference for subsequent studies focusing on treatments of neurodegenerative disorders. The exploration of microglia autophagy and the development of nanomedicines greatly enhances current understanding of NDDs.

Docosahexaenoic acid inhibits ischemic stroke to reduce vascular dementia and Alzheimer’s disease

Stroke and dementia are global leading causes of neurological disability and death. The pathology of these diseases is interrelated and they share common, modifiable risk factors. It is suggested that docosahexaenoic acid (DHA) prevents neurological and vascular disorders induced by ischemic stroke and also prevent dementia. The purpose of this study was to review the potential preventative role of DHA against ischemic stroke-induced vascular dementia and Alzheimer's disease. In this review, I analyzed studies on stroke-induced dementia from the PubMed, ScienceDirect, and Web of Science databases as well as studies on the effects of DHA on stroke-induced dementia. As per the results of interventional studies, DHA intake can potentially ameliorate dementia and cognitive function. In particular, DHA derived from foods such as fish oil enters the blood and then migrates to the brain by binding to fatty acid binding protein 5 that is present in cerebral vascular endothelial cells. At this point, the esterified form of DHA produced by lysophosphatidylcholine is preferentially absorbed into the brain instead of free DHA. DHA accumulates in nerve cell membrane and is involved in the prevention of dementia. The antioxidative and anti-inflammatory properties of DHA and DHA metabolites as well as their ability to decrease amyloid beta (Aβ) 42 production were implicated in the improvement of cognitive function. The antioxidant effect of DHA, the inhibition of neuronal cell death by Aβ peptide, improvement in learning ability, and enhancement of synaptic plasticity may contribute to the prevention of dementia induced by ischemic stroke.

2023 Alzheimer's disease facts and figures

This article describes the public health impact of Alzheimer's disease, including prevalence and incidence, mortality and morbidity, use and costs of care, and the overall impact on family caregivers, the dementia workforce and society. The Special Report examines the patient journey from awareness of cognitive changes to potential treatment with drugs that change the underlying biology of Alzheimer's. An estimated 6.7 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060 barring the development of medical breakthroughs to prevent, slow or cure AD. Official death certificates recorded 121,499 deaths from AD in 2019, and Alzheimer's disease was officially listed as the sixth-leading cause of death in the United States. In 2020 and 2021, when COVID-19 entered the ranks of the top ten causes of death, Alzheimer's was the seventh-leading cause of death. Alzheimer's remains the fifth-leading cause of death among Americans age 65 and older. Between 2000 and 2019, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 145%. This trajectory of deaths from AD was likely exacerbated by the COVID-19 pandemic in 2020 and 2021. More than 11 million family members and other unpaid caregivers provided an estimated 18 billion hours of care to people with Alzheimer's or other dementias in 2022. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $339.5 billion in 2022. Its costs, however, extend to family caregivers' increased risk for emotional distress and negative mental and physical health outcomes - costs that have been aggravated by COVID-19. Members of the paid health care workforce are involved in diagnosing, treating and caring for people with dementia. In recent years, however, a shortage of such workers has developed in the United States. This shortage - brought about, in part, by COVID-19 - has occurred at a time when more members of the dementia care workforce are needed. Therefore, programs will be needed to attract workers and better train health care teams. Average per-person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2023 for health care, long-term care and hospice services for people age 65 and older with dementia are estimated to be $345 billion. The Special Report examines whether there will be sufficient numbers of physician specialists to provide Alzheimer's care and treatment now that two drugs are available that change the underlying biology of Alzheimer's disease.

The unique neuropathological vulnerability of the human brain to aging

Alzheimer's disease (AD)-related neurofibrillary tangles (NFT), argyrophilic grain disease (AGD), aging-related tau astrogliopathy (ARTAG), limbic predominant TDP-43 proteinopathy (LATE), and amygdala-predominant Lewy body disease (LBD) are proteinopathies that, together with hippocampal sclerosis, progressively appear in the elderly affecting from 50% to 99% of individuals aged 80 years, depending on the disease. These disorders usually converge on the same subject and associate with additive cognitive impairment. Abnormal Tau, TDP-43, and α-synuclein pathologies progress following a pattern consistent with an active cell-to-cell transmission and abnormal protein processing in the host cell. However, cell vulnerability and transmission pathways are specific for each disorder, albeit abnormal proteins may co-localize in particular neurons. All these alterations are unique or highly prevalent in humans. They all affect, at first, the archicortex and paleocortex to extend at later stages to the neocortex and other regions of the telencephalon. These observations show that the phylogenetically oldest areas of the human cerebral cortex and amygdala are not designed to cope with the lifespan of actual humans. New strategies aimed at reducing the functional overload of the human telencephalon, including optimization of dream repair mechanisms and implementation of artificial circuit devices to surrogate specific brain functions, appear promising.

Diffusion Changes in Hippocampal Cingulum in Early Biologically Defined Alzheimer's Disease

BACKGROUND

Diagnosis of Alzheimer's disease (AD) was recently shifted from clinical to biological construct to reflect underlying neuropathological status, where amyloid deposition designated patients to the Alzheimer's continuum, and additional tau positivity represented AD.

OBJECTIVE

To investigate white matter (WM) alteration in the brain of patients in the Alzheimer's continuum.

METHODS

A total of 236 subjects across the clinical and biological spectra of AD were included and stratified by normal/abnormal (-/+) amyloid (A) and tau (T) status based on positron emission tomography results, yielding five groups: A-T-cognitively normal (CN), A+T-CN, A+T+ CN, A+T+ mild cognitive impairment, and A+T+ AD. WM alteration was measured by diffusion tensor imaging (DTI). Group differences, correlation of DTI measures with amyloid and tau, and diagnostic performance of such measures were evaluated.

RESULTS

Compared with A-T-CN, widespread WM alteration was observed in the Alzheimer's continuum, including hippocampal cingulum (CGH), cingulum of the cingulate gyrus, and uncinate fasciculus. Diffusion changes measured by regional mean fractional anisotropy (FA) in the bilateral CGH were first detected in the A+T+ CN group and associated with tau burden in the Alzheimer's continuum (p < 0.001). For discrimination between A+T+ CN and A-T-CN groups, CGH FA achieved accuracy, sensitivity, and specificity of 74%, 58%, and 78% for right CGH and 57%, 83%, and 47% respectively for left CGH.

CONCLUSION

WM alteration is widespread in the Alzheimer's continuum. Diffusion alteration in CGH occurred early and was correlated with tau pathology, thus may be a promising biomarker in preclinical AD.

Linking the Amyloid, Tau, and Mitochondrial Hypotheses of Alzheimer's Disease and Identifying Promising Drug Targets

Damage or loss of brain cells and impaired neurochemistry, neurogenesis, and synaptic and nonsynaptic plasticity of the brain lead to dementia in neurodegenerative diseases, such as Alzheimer's disease (AD). Injury to synapses and neurons and accumulation of extracellular amyloid plaques and intracellular neurofibrillary tangles are considered the main morphological and neuropathological features of AD. Age, genetic and epigenetic factors, environmental stressors, and lifestyle contribute to the risk of AD onset and progression. These risk factors are associated with structural and functional changes in the brain, leading to cognitive decline. Biomarkers of AD reflect or cause specific changes in brain function, especially changes in pathways associated with neurotransmission, neuroinflammation, bioenergetics, apoptosis, and oxidative and nitrosative stress. Even in the initial stages, AD is associated with Aβ neurotoxicity, mitochondrial dysfunction, and tau neurotoxicity. The integrative amyloid-tau-mitochondrial hypothesis assumes that the primary cause of AD is the neurotoxicity of Aβ oligomers and tau oligomers, mitochondrial dysfunction, and their mutual synergy. For the development of new efficient AD drugs, targeting the elimination of neurotoxicity, mutual potentiation of effects, and unwanted protein interactions of risk factors and biomarkers (mainly Aβ oligomers, tau oligomers, and mitochondrial dysfunction) in the early stage of the disease seems promising.

Amyloid-Tau-Neurodegeneration Profiles and Longitudinal Cognition in Sporadic Young-Onset Dementia

We examined amyloid-tau-neurodegeneration biomarker effects on cognition in a Southeast-Asian cohort of 84 sporadic young-onset dementia (YOD; age-at-onset <65 years) patients. They were stratified into A+N+, A– N+, and A– N– profiles via cerebrospinal fluid amyloid-β1–42 (A), phosphorylated-tau (T), MRI medial temporal atrophy (neurodegeneration– N), and confluent white matter hyperintensities cerebrovascular disease (CVD). A, T, and CVD effects on longitudinal Mini-Mental State Examination (MMSE) were evaluated. A+N+ patients demonstrated steeper MMSE decline than A– N+ (β = 1.53; p = 0.036; CI 0.15:2.92) and A– N– (β = 4.68; p = 0.001; CI 1.98:7.38) over a mean follow-up of 1.24 years. Within A– N+, T– CVD+ patients showed greater MMSE decline compared to T+CVD– patients (β = – 2.37; p = 0.030; CI – 4.41:– 0.39). A+ results in significant cognitive decline, while CVD influences longitudinal cognition in the A– sub-group.

Association of late-life body mass index with the risk of Alzheimer disease: a 10-year nationwide population-based cohort study

Existing data for the association between late-life body mass index (BMI) and the risk of Alzheimer’s disease (AD) in the underweight population are limited with conflicting results. A large population-based cohort study of 148,534 individuals aged ≥ 65 years who participated in the national health screening program from 2002 to 2005 was performed using the Korean National Health Insurance Service-Senior cohort database 2006–2015. The risk of AD according to BMI category (kg/m²) in Asians was evaluated using a multivariable Cox regression model, after adjustments for age, sex, lifestyle, low-income status, and comorbidities. To evaluate the association between BMI and AD risk, the underweight population was further subdivided according to the degree of thinness. During the 10-year follow-up period, 22,279 individuals developed AD. Relative to the normal-weight population, the estimated adjusted hazard ratio (HR) for incident AD in the underweight, overweight, and obese populations was 1.17 (95% confidence interval [CI], 1.09–1.24), 0.90 (0.87–0.93), and 0.83 (0.80–0.85), respectively. In the underweight population, AD risk increased as the degree of thinness increased (p for the trend, < .001). Late-life BMI showed a significant inverse relationship with AD risk, especially in the underweight population. Public health strategies to screen for AD more actively in the underweight population and improve their weight status may help reduce the burden of AD.

Association of Cognition and Dementia With Neuropathologic Changes of Alzheimer Disease and Other Conditions in the Oldest Old

BACKGROUND AND OBJECTIVES

Age is the largest risk factor for dementia. However, dementia is not universal, even among the oldest-old age groups. Following contemporary neuropathologic guidelines, our objectives were to describe the key neuropathologic lesions and their associations with antemortem cognition in oldest-old individuals.

METHODS

Participants were those enrolled in The 90+ Study, a longitudinal, population-based study of aging/dementia in the oldest old, who agreed to postmortem brain examination. All autopsied brains as of December 2020 were evaluated for the prevalence of Alzheimer disease neuropathologic change (ADNC) and non-ADNC neuropathologic comorbidities. Associations between neuropathologic lesions or the total neuropathologic burden score (sum of the individual scores) and cognition were assessed using multinomial logistic regression and multiple linear regression. Separate regression analyses evaluated relationships between limbic-predominant age-related TDP-43 encephalopathy (LATE-NC) and hippocampal sclerosis (HS) or ADNC/primary age-related tauopathy (PART). Resistance, or failure to develop ADNC/PART, and resilience, inferred from higher-than-expected cognitive functioning, were evaluated in the presence or absence of non-ADNC neuropathologic features.

RESULTS

The most common neuropathologic features in the sample (n = 367) were ADNC/PART related. Increased dementia odds were associated with elevated total neuropathologic burden (odds ratio [OR] 1.5, 95% CI 1.3-1.7, p < 0.0001), β-amyloid (OR 1.6, 95% CI 1.2-2.0, p < 0.0001), neurofibrillary tangles (OR 2.6, 95% CI 1.7-4.1, p < 0.0001), and LATE-NC (OR 2.3, 95% CI 1.7-3.1, p < 0.0001), correcting for multiple comparisons. LATE-NC was associated with dementia with (OR 6.1, 95% CI 2.0-18.7, p = 0.002) and without (OR 5.0, 95% CI 2.6-9.7, p < 0.0001) co-occurring HS and increased the odds of dementia among participants with ADNC (OR 5.0, 95% CI 2.7-9.2, p < 0.0001). Resistance to moderate/severe ADNC/PART was rare (3%), but resilience to ADNC/PART was not (55%). Resilience was rarer in the presence of non-ADNC comorbid lesions, particularly LATE-NC. Among those with moderate/severe ADNC/PART, dementia odds increased with each non-ADNC comorbid lesion (e.g., 1 lesion: OR 2.4, 95% CI 1.3-4.5, p < 0.005; 2 lesions: OR 5.9, 95% CI 2.8-12.3, p < 0.0001).

DISCUSSION

These results highlight the importance of non-ADNC neuropathologic comorbidity, predominantly LATE-NC, to cognition in the oldest old. Given the cumulative effects of non-ADNC comorbid neuropathologic abnormalities, reducing their prevalence, especially LATE-NC, will be vital to the ultimate goal of reducing dementia burden in the oldest-old individuals.

Sex differences in early-onset Alzheimer's disease

INTRODUCTION

Sex is believed to drive heterogeneity in Alzheimer's disease (AD), although evidence in early-onset AD (<65 years, EOAD) is scarce.

METHODS

We included 62 EOAD patients and 44 healthy controls (HC) with cerebrospinal fluid (CSF) AD's core biomarkers and neurofilament light chain levels, neuropsychological assessment, and 3T-MRI. We measured cortical thickness (CTh) and hippocampal subfield volumes (HpS) using Freesurfer. Adjusted linear models were used to analyze sex-differences and the relationship between atrophy and cognition.

RESULTS

Compared to same-sex HC, female-EOAD showed greater cognitive impairment and broader atrophy burden than male-EOAD. In a direct female-EOAD and male-EOAD comparison, there were slight differences in temporal CTh, with no differences in cognition or HpS. CSF tau levels were higher in female-EOAD than in male-EOAD. Greater atrophy was associated with worse cognition in female-EOAD.

CONCLUSIONS

At diagnosis, there are sex-differences in the pattern of cognitive impairment, atrophy burden and CSF tau in EOAD, suggesting there is an influence of sex on pathology spreading and susceptibility to the disease in EOAD.

Ketones: potential to achieve brain energy rescue and sustain cognitive health during ageing

Alzheimer’s disease (AD) is the most common major neurocognitive disorder of ageing. Although largely ignored until about a decade ago, accumulating evidence suggests that deteriorating brain energy metabolism plays a key role in the development and/or progression of AD-associated cognitive decline. Brain glucose hypometabolism is a well-established biomarker in AD but was mostly assumed to be a consequence of neuronal dysfunction and death. However, its presence in cognitively asymptomatic populations at higher risk of AD strongly suggests that it is actually a pre-symptomatic component in the development of AD. The question then arises as to whether progressive AD-related cognitive decline could be prevented or slowed down by correcting or bypassing this progressive ‘brain energy gap’. In this review, we provide an overview of research on brain glucose and ketone metabolism in AD and its prodromal condition – mild cognitive impairment (MCI) – to provide a clearer basis for proposing keto-therapeutics as a strategy for brain energy rescue in AD. We also discuss studies using ketogenic interventions and their impact on plasma ketone levels, brain energetics and cognitive performance in MCI and AD. Given that exercise has several overlapping metabolic effects with ketones, we propose that in combination these two approaches might be synergistic for brain health during ageing. As cause-and-effect relationships between the different hallmarks of AD are emerging, further research efforts should focus on optimising the efficacy, acceptability and accessibility of keto-therapeutics in AD and populations at risk of AD.

Six genetically linked mutations in the CD36 gene significantly delay the onset of Alzheimer's disease

The risk of Alzheimer’s disease (AD) has a strong genetic component, also in the case of late-onset AD (LOAD). Attempts to sequence whole genome in large populations of subjects have identified only a few mutations common to most of the patients with AD. Targeting smaller well-characterized groups of subjects where specific genetic variations in selected genes could be related to precisely defined psychological traits typical of dementia is needed to better understand the heritability of AD. More than one thousand participants, categorized according to cognitive deficits, were assessed using 14 psychometric tests evaluating performance in five cognitive domains (attention/working memory, memory, language, executive functions, visuospatial functions). CD36 was selected as a gene previously shown to be implicated in the etiology of AD. A total of 174 polymorphisms were tested for associations with cognition-related traits and other AD-relevant data using the next generation sequencing. Several associations between single nucleotide polymorphisms (SNP’s) and the cognitive deficits have been found (rs12667404 with language performance, rs3211827 and rs41272372 with executive functions, rs137984792 with visuospatial performance). The most prominent association was found between a group of genotypes in six genetically linked and the age at which the AD patients presented with, or developed, a full-blown dementia. The identified alleles appear to be associated with a delay in the onset of LOAD. In silico studies suggested that the SNP’s alter the expression of CD36 thus potentially affecting CD36-related neuroinflammation and other molecular and cellular mechanisms known to be involved in the neuronal loss leading to AD. The main outcome of the study is an identification of a set of six new mutations apparently conferring a distinct protection against AD and delaying the onset by about 8 years. Additional mutations in CD36 associated with certain traits characteristic of the cognitive decline in AD have also been found.

Effect of masupirdine (SUVN-502) on cognition in patients with moderate Alzheimer's disease: A randomized, double-blind, phase 2, proof-of-concept study

Introduction

This study explored the efficacy and safety of a serotonin-6 receptor antagonist, masupirdine, as adjunct treatment in patients with moderate Alzheimer's disease (AD) concomitantly treated with donepezil and memantine.

Methods

The effects of masupirdine were evaluated in patients with moderate AD dementia on background treatment with donepezil and memantine. Five hundred thirty-seven patients were expected to be randomized in a 1:1:1 ratio, using permuted blocked randomization. After a 2- to 4-week screening period, the study consisted of a 26-week double-blind treatment period, and a 4-week washout period. The primary efficacy measure was the 11-item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-Cog 11). Secondary efficacy measures were Clinical Dementia Rating Scale-Sum of Boxes, Mini-Mental State Examination, 23-item Alzheimer's Disease Co-operative Study Activities of Daily Living, and 12-item Neuropsychiatric Inventory. Changes from baseline were analyzed using a mixed effects model for repeated measures (MMRM). A total of 564 patients were randomized to receive either daily masupirdine 50 mg (190 patients), masupirdine 100 mg (185 patients), or placebo (189 patients). The study is registered at ClinicalTrials.gov (NCT02580305).

Results

The MMRM results showed statistically non-significant treatment differences in change from baseline in ADAS-Cog 11 scores at week 26, comparing each masupirdine dose arm to the placebo arm. No significant treatment effects were observed in the secondary evaluations.

Discussion

Masupirdine was generally safe and well tolerated. Possible reasons for the observed trial results are discussed.

Highlights

Masupirdine was evaluated in moderate Alzheimer's disease patients.First trial in class with background treatment of donepezil and memantine.Masupirdine was generally safe and well tolerated.Possible reasons for the observed trial results are discussed.

Lower Posterior Cingulate N-Acetylaspartate to Creatine Level in Early Detection of Biologically Defined Alzheimer's Disease

Alzheimer’s disease (AD) was recently defined as a biological construct to reflect neuropathologic status, and both abnormal amyloid and tau are required for a diagnosis of AD. We aimed to determine the proton MR spectroscopic (1H-MRS) patterns of the posterior cingulate in biologically defined AD. A total of 68 participants were included in this study, comprising 37 controls, 16 early AD, and 15 late AD, who were classified according to their amyloid and tau status and presence of hippocampal atrophy. Compared with controls, early AD showed lower N-acetylaspartate (NAA)/creatine (Cr) (p = 0.003), whereas late AD showed lower NAA/Cr and higher myoInositol (mI)/Cr (all with p < 0.05). Lower NAA/Cr correlated with a greater global amyloid load (r = −0.47, p < 0.001) and tau load (r = −0.51, p < 0.001) and allowed a discrimination of early AD from controls (p < 0.001). Subgroup analysis showed that NAA/Cr also allowed a differentiation of early AD from controls in the cognitively unimpaired subjects, with an area under the receiver operating characteristics curve, sensitivity, and specificity of 0.96, 100%, and 83.8%, respectively. Lower posterior cingulate NAA levels may help to inform underlying neuropathologic changes in the early stage of AD.

Disentangling Alzheimer's disease neurodegeneration from typical brain ageing using machine learning

Neuroimaging biomarkers that distinguish between changes due to typical brain ageing and Alzheimer's disease are valuable for determining how much each contributes to cognitive decline. Supervised machine learning models can derive multivariate patterns of brain change related to the two processes, including the Spatial Patterns of Atrophy for Recognition of Alzheimer's Disease (SPARE-AD) and of Brain Aging (SPARE-BA) scores investigated herein. However, the substantial overlap between brain regions affected in the two processes confounds measuring them independently. We present a methodology, and associated results, towards disentangling the two. T1-weighted MRI scans of 4054 participants (48-95 years) with Alzheimer's disease, mild cognitive impairment (MCI), or cognitively normal (CN) diagnoses from the Imaging-based coordinate SysTem for AGIng and NeurodeGenerative diseases (iSTAGING) consortium were analysed. Multiple sets of SPARE scores were investigated, in order to probe imaging signatures of certain clinically or molecularly defined sub-cohorts. First, a subset of clinical Alzheimer's disease patients (n = 718) and age- and sex-matched CN adults (n = 718) were selected based purely on clinical diagnoses to train SPARE-BA1 (regression of age using CN individuals) and SPARE-AD1 (classification of CN versus Alzheimer's disease) models. Second, analogous groups were selected based on clinical and molecular markers to train SPARE-BA2 and SPARE-AD2 models: amyloid-positive Alzheimer's disease continuum group (n = 718; consisting of amyloid-positive Alzheimer's disease, amyloid-positive MCI, amyloid- and tau-positive CN individuals) and amyloid-negative CN group (n = 718). Finally, the combined group of the Alzheimer's disease continuum and amyloid-negative CN individuals was used to train SPARE-BA3 model, with the intention to estimate brain age regardless of Alzheimer's disease-related brain changes. The disentangled SPARE models, SPARE-AD2 and SPARE-BA3, derived brain patterns that were more specific to the two types of brain changes. The correlation between the SPARE-BA Gap (SPARE-BA minus chronological age) and SPARE-AD was significantly reduced after the decoupling (r = 0.56-0.06). The correlation of disentangled SPARE-AD was non-inferior to amyloid- and tau-related measurements and to the number of APOE ε4 alleles but was lower to Alzheimer's disease-related psychometric test scores, suggesting the contribution of advanced brain ageing to the latter. The disentangled SPARE-BA was consistently less correlated with Alzheimer's disease-related clinical, molecular and genetic variables. By employing conservative molecular diagnoses and introducing Alzheimer's disease continuum cases to the SPARE-BA model training, we achieved more dissociable neuroanatomical biomarkers of typical brain ageing and Alzheimer's disease.

A robust and interpretable machine learning approach using multimodal biological data to predict future pathological tau accumulation

The early stages of Alzheimer’s disease (AD) involve interactions between multiple pathophysiological processes. Although these processes are well studied, we still lack robust tools to predict individualised trajectories of disease progression. Here, we employ a robust and interpretable machine learning approach to combine multimodal biological data and predict future pathological tau accumulation. In particular, we use machine learning to quantify interactions between key pathological markers (β-amyloid, medial temporal lobe  atrophy, tau and APOE 4) at mildly impaired and asymptomatic stages of AD. Using baseline non-tau markers we derive a prognostic index that: (a) stratifies patients based on future pathological tau accumulation, (b) predicts individualised regional future rate of tau accumulation, and (c) translates predictions from deep phenotyping patient cohorts to cognitively normal individuals. Our results propose a robust approach for fine scale stratification and prognostication with translation impact for clinical trial design targeting the earliest stages of AD.

The authors present a machine learning approach that combines baseline multimodal data to accurately predict individualised trajectories of future pathological tau accumulation at asymptomatic and mildly impaired stages of Alzheimer’s disease.

Overview of tau PET molecular imaging

PURPOSE OF REVIEW

This article reviews tau PET imaging with an emphasis on first-generation and second-generation tau radiotracers and their application in neurodegenerative disorders, including Alzheimer's disease and non-Alzheimer's disease tauopathies.

RECENT FINDINGS

Tau is a critical protein, abundant in neurons within the central nervous system, which plays an important role in maintaining microtubules by binding to tubulin in axons. In its abnormal hyperphosphorylated form, accumulation of tau has been linked to a variety of neurodegenerative disorders, collectively referred to as tauopathies, which include Alzheimer's disease and non-Alzheimer's disease tauopathies [e.g., corticobasal degeneration (CBD), argyrophilic grain disease, progressive supranuclear palsy (PSP), and Pick's disease]. A number of first-generation and second-generation tau PET radiotracers have been developed, including the first FDA-approved agent [18F]-flortaucipir, which allow for in-vivo molecular imaging of underlying histopathology antemortem, ultimately guiding disease staging and development of disease-modifying therapeutics.

SUMMARY

Tau PET is an emerging imaging modality in the diagnosis and staging of tauopathies.

Klotho an Autophagy Stimulator as a Potential Therapeutic Target for Alzheimer’s Disease: A Review

Alzheimer’s disease (AD) is an age-associated neurodegenerative disease; it is the most common cause of senile dementia. Klotho, a single-pass transmembrane protein primarily generated in the brain and kidney, is active in a variety of metabolic pathways involved in controlling neurodegeneration and ageing. Recently, many studies have found that the upregulation of Klotho can improve pathological cognitive deficits in an AD mice model and have demonstrated that Klotho plays a role in the induction of autophagy, a major contributing factor for AD. Despite the close association between Klotho and neurodegenerative diseases, such as AD, the underlying mechanism by which Klotho contributes to AD remains poorly understood. In this paper, we will introduce the expression, location and structure of Klotho and its biological functions. Specifically, this review is devoted to the correlation of Klotho protein and the AD phenotype, such as the effect of Klotho in upregulating the amyloid-beta clearance and in inducing autophagy for the clearance of toxic proteins, by regulating the autophagy lysosomal pathway (ALP). In summary, the results of multiple studies point out that targeting Klotho would be a potential therapeutic strategy in AD treatment.

2022 Alzheimer's disease facts and figures

This article describes the public health impact of Alzheimer's disease (AD), including incidence and prevalence, mortality and morbidity, use and costs of care, and the overall impact on family caregivers, the dementia workforce and society. The Special Report discusses consumers' and primary care physicians' perspectives on awareness, diagnosis and treatment of mild cognitive impairment (MCI), including MCI due to Alzheimer's disease. An estimated 6.5 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060 barring the development of medical breakthroughs to prevent, slow or cure AD. Official death certificates recorded 121,499 deaths from AD in 2019, the latest year for which data are available. Alzheimer's disease was officially listed as the sixth-leading cause of death in the United States in 2019 and the seventh-leading cause of death in 2020 and 2021, when COVID-19 entered the ranks of the top ten causes of death. Alzheimer's remains the fifth-leading cause of death among Americans age 65 and older. Between 2000 and 2019, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 145%. More than 11 million family members and other unpaid caregivers provided an estimated 16 billion hours of care to people with Alzheimer's or other dementias in 2021. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $271.6 billion in 2021. Its costs, however, extend to family caregivers' increased risk for emotional distress and negative mental and physical health outcomes - costs that have been aggravated by COVID-19. Members of the dementia care workforce have also been affected by COVID-19. As essential care workers, some have opted to change jobs to protect their own health and the health of their families. However, this occurs at a time when more members of the dementia care workforce are needed. Average per-person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2022 for health care, long-term care and hospice services for people age 65 and older with dementia are estimated to be $321 billion. A recent survey commissioned by the Alzheimer's Association revealed several barriers to consumers' understanding of MCI. The survey showed low awareness of MCI among Americans, a reluctance among Americans to see their doctor after noticing MCI symptoms, and persistent challenges for primary care physicians in diagnosing MCI. Survey results indicate the need to improve MCI awareness and diagnosis, especially in underserved communities, and to encourage greater participation in MCI-related clinical trials.

White matter damage due to vascular, tau, and TDP-43 pathologies and its relevance to cognition

Multi-compartment modelling of white matter microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) can provide information on white matter health through neurite density index and free water measures. We hypothesized that cerebrovascular disease, Alzheimer's disease, and TDP-43 proteinopathy would be associated with distinct NODDI readouts of white matter damage which would be informative for identifying the substrate for cognitive impairment. We identified two independent cohorts with multi-shell diffusion MRI, amyloid and tau PET, and cognitive assessments: specifically, a population-based cohort of 347 elderly randomly sampled from the Olmsted county, Minnesota, population and a clinical research-based cohort of 61 amyloid positive Alzheimer's dementia participants. We observed an increase in free water and decrease in neurite density using NODDI measures in the genu of the corpus callosum associated with vascular risk factors, which we refer to as the vascular white matter component. Tau PET signal reflective of 3R/4R tau deposition was associated with worsening neurite density index in the temporal white matter where we measured parahippocampal cingulum and inferior temporal white matter bundles. Worsening temporal white matter neurite density was associated with (antemortem confirmed) FDG TDP-43 signature. Post-mortem neuropathologic data on a small subset of this sample lend support to our findings. In the community-dwelling cohort where vascular disease was more prevalent, the NODDI vascular white matter component explained variability in global cognition (partial R2 of free water and neurite density = 8.3%) and MMSE performance (8.2%) which was comparable to amyloid PET (7.4% for global cognition and 6.6% for memory). In the AD dementia cohort, tau deposition was the greatest contributor to cognitive performance (9.6%), but there was also a non-trivial contribution of the temporal white matter component (8.5%) to cognitive performance. The differences observed between the two cohorts were reflective of their distinct clinical composition. White matter microstructural damage assessed using advanced diffusion models may add significant value for distinguishing the underlying substrate (whether cerebrovascular disease versus neurodegenerative disease caused by tau deposition or TDP-43 pathology) for cognitive impairment in older adults.

Neuropathology of Alzheimer's Disease

The key pathological hallmarks-extracellular plaques and intracellular neurofibrillary tangles (NFT)-described by Alois Alzheimer in his seminal 1907 article are still central to the postmortem diagnosis of Alzheimer's disease (AD), but major advances in our understanding of the underlying pathophysiology as well as significant progress in clinical diagnosis and therapy have changed the perspective and importance of neuropathologic evaluation of the brain. The notion that the pathological processes underlying AD already start decades before symptoms are apparent in patients has brought a major change reflected in the current neuropathological classification of AD neuropathological changes (ADNC). The predictable progression of beta-amyloid (Aβ) plaque pathology from neocortex, over limbic structures, diencephalon, and basal ganglia, to brainstem and cerebellum is captured in phases described by Thal and colleagues. The progression of NFT pathology from the transentorhinal region to the limbic system and ultimately the neocortex is described in stages proposed by Braak and colleagues. The density of neuritic plaque pathology is determined by criteria defined by the Consortium to establish a registry for Alzheimer's diseases (CERAD). While these changes neuropathologically define AD, it becomes more and more apparent that the majority of patients present with a multitude of additional pathological changes which are possible contributing factors to the clinical presentation and disease progression. The impact of co-existing Lewy body pathology has been well studied, but the importance of more recently described pathologies including limbic-predominant age-related TDP-43 encephalopathy (LATE), chronic traumatic encephalopathy (CTE), and aging-related tau astrogliopathy (ARTAG) still needs to be evaluated in large cohort studies. In addition, it is apparent that vascular pathology plays an important role in the AD patient population, but a lack of standardized reporting criteria has hampered progress in elucidating the importance of these changes for clinical presentation and disease progression. More recently a key role was ascribed to the immune response to pathological protein aggregates, and it will be important to analyze these changes systematically to better understand the temporal and spatial distribution of the immune response in AD and elucidate their importance for the disease process. Advances in digital pathology and technologies such as single cell sequencing and digital spatial profiling have opened novel avenues for improvement of neuropathological diagnosis and advancing our understanding of underlying molecular processes. Finally, major strides in biomarker-based diagnosis of AD and recent advances in targeted therapeutic approaches may have shifted the perspective but also highlight the continuous importance of postmortem analysis of the brain in neurodegenerative diseases.

Dietary Regulation of Gut-Brain Axis in Alzheimer's Disease: Importance of Microbiota Metabolites

Alzheimer's disease (AD) is a neurodegenerative disease that impacts 45 million people worldwide and is ranked as the 6th top cause of death among all adults by the Centers for Disease Control and Prevention. While genetics is an important risk factor for the development of AD, environment and lifestyle are also contributing risk factors. One such environmental factor is diet, which has emerged as a key influencer of AD development/progression as well as cognition. Diets containing large quantities of saturated/trans-fats, refined carbohydrates, limited intake of fiber, and alcohol are associated with cognitive dysfunction while conversely diets low in saturated/trans-fats (i.e., bad fats), high mono/polyunsaturated fats (i.e., good fats), high in fiber and polyphenols are associated with better cognitive function and memory in both humans and animal models. Mechanistically, this could be the direct consequence of dietary components (lipids, vitamins, polyphenols) on the brain, but other mechanisms are also likely to be important. Diet is considered to be the single greatest factor influencing the intestinal microbiome. Diet robustly influences the types and function of micro-organisms (called microbiota) that reside in the gastrointestinal tract. Availability of different types of nutrients (from the diet) will favor or disfavor the abundance and function of certain groups of microbiota. Microbiota are highly metabolically active and produce many metabolites and other factors that can affect the brain including cognition and the development and clinical progression of AD. This review summarizes data to support a model in which microbiota metabolites influence brain function and AD.

Is Amyloid Burden Measured by 18F-Flutemetamol PET Associated with Progression in Clinical Alzheimer's Disease?

Background:

Patients with Alzheimer’s disease (AD) show heterogeneity in clinical progression rate, and we have limited tools to predict prognosis. Amyloid burden from ¹⁸F-Flutemetamol positron emission tomography (PET), as measured by standardized uptake value ratios (SUVR), might provide prognostic information.

Objective:

We investigate whether ¹⁸F-Flutemetamol PET composite or regional SUVRs are associated with trajectories of clinical progression.

Methods:

This observational longitudinal study included 94 patients with clinical AD. PET images were semi-quantified with normalization to pons. Group-based trajectory modeling was applied to identify trajectory groups according to change in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) over time. Multinomial logistic regression models assessed the association of SUVRs with trajectory group membership.

Results:

Three trajectory groups were identified. In the regression models, neither composite nor regional SUVRs were associated with trajectory group membership.

Conclusion:

There were no associations between CDR progression and ¹⁸F-Flutemetamol PET-derived composite SUVRs or regional SUVRs in clinical AD.

Changes in LASSI-L performance over time among older adults with amnestic MCI and amyloid positivity: A preliminary study

There is a pressing need to develop measures that are sensitive to the earliest subtle cognitive changes of Alzheimer's disease (AD) to improve early detection and track disease progression. The Loewenstein-Acevedo Scales of Semantic Interference (LASSI-L) has been shown to successfully discriminate between cognitively unimpaired (CU) older adults and those with amnestic mild cognitive impairment (MCI) and to correlate with total and regional brain amyloid load. The present study investigated how the LASSI-L scores change over time among three distinct diagnostic groups. Eighty-six community-dwelling older adults underwent a baseline evaluation including: a clinical interview, a neuropsychological evaluation, Magnetic Resonance Imaging (MRI), and amyloid Positron Emission Tomography (PET). A follow up evaluation was conducted 12 months later. Initial mean values were calculated using one-way ANOVAs and chi-square analyses. Post-hoc comparisons were conducted using Tukey's Honestly Significant Difference (HSD). A 3 × 2 repeated measures analysis was utilized to examine differences in LASSI-L performance over time. The MCI amyloid positive group demonstrated a significantly greater decline in LASSI-L performance than the MCI amyloid negative and CU groups respectively. The scales that best differentiated the three groups included the Cued A2, which taps into maximum learning capacity, and Cued B2, which assesses the failure to recover from proactive semantic interference. Our findings further support the LASSI-L's discriminative validity.

From Cerebrospinal Fluid Neurochemistry to Clinical Diagnosis of Alzheimer's Disease in the Era of Anti-Amyloid Treatments. Report of Four Patients

Analysis of classical cerebrospinal fluid biomarkers, especially when incorporated in a classification/diagnostic system such as the AT(N), may offer a significant diagnostic tool allowing correct identification of Alzheimer’s disease during life. We describe four patients with more or less atypical or mixed clinical presentation, in which the classical cerebrospinal fluid biomarkers amyloid peptide with 42 and 40 amino acids (Aβ₄₂ and Aβ₄₀, respectively), phospho-tau (τ_P-181) and total tau (τ_Τ) were measured. Despite the unusual clinical presentation, the biomarker profile was compatible with Alzheimer’s disease in all four patients. The measurement of classical biomarkers in the cerebrospinal fluid may be a useful tool in identifying the biochemical fingerprints of Alzheimer’s disease, especially currently, due to the recent approval of the first disease-modifying treatment, allowing not only typical but also atypical cases to be enrolled in trials of such treatments.