Prevalence of Biologically vs Clinically Defined Alzheimer Spectrum Entities Using the National Institute on Aging-Alzheimer's Association Research Framework

Influence of Different Diagnostic Criteria on Alzheimer Disease Clinical Research

BACKGROUND AND OBJECTIVES

Updates in Alzheimer disease (AD) diagnostic guidelines by the National Institute on Aging-Alzheimer's Association (NIA-AA) and the International Working Group (IWG) over the past 11 years may affect clinical diagnoses. We assessed how these guidelines affect clinical AD diagnosis in a cohort of cognitively unimpaired (CU) and cognitively impaired (CI) individuals.

METHODS

We applied clinical and biomarker data in algorithms to classify individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort according to the following diagnostic guidelines for AD: 2011 NIA-AA, 2016 IWG-2, 2018 NIA-AA, and 2021 IWG-3, assigning the following generic diagnostic labels: (1) not AD (nAD), (2) increased risk of developing AD (irAD), and (3) AD. Diagnostic labels were compared according to their frequency, convergence across guidelines, biomarker profiles, and prognostic value. We also evaluated the diagnostic discordance among the criteria.

RESULTS

A total of 1,195 individuals (mean age 73.2 ± 7.2 years, mean education 16.1 ± 2.7, 44.0% female) presented different repartitions of diagnostic labels according to the 2011 NIA-AA (nAD = 37.8%, irAD = 23.0%, AD = 39.2%), 2016 IWG-2 (nAD = 37.7%, irAD = 28.7%, AD = 33.6%), 2018 NIA-AA (nAD = 40.7%, irAD = 9.3%, AD = 50.0%), and 2021 IWG-3 (nAD = 51.2%, irAD = 8.4%, AD = 48.3%) frameworks. Discordant diagnoses across all guidelines were found in 512 participants (42.8%) (138 [91.4%] occurring in only β-amyloid [CU 65.4%, CI 34.6%] and 191 [78.6%] in only tau-positive [CU 71.7%, CI 28.3%] individuals). Differences in predicting cognitive impairment between nAD and irAD groups were observed with the 2011 NIA-AA (hazard ratio [HR] 2.21, 95% CI 1.34-3.65, p = 0.002), 2016 IWG-2 (HR 2.81, 95% CI 1.59-4.96, p < 0.000), and 2021 IWG-3 (HR 3.61, 95% CI 2.09-6.23, p < 0.000), but not with 2018 NIA-AA (HR 1.69, 95% CI 0.87-3.28, p = 0.115).

DISCUSSION

Over 42% of the studied population presented discordant diagnoses when using the different examined AD criteria, mostly in individuals with a single positive biomarker. Except for 2018 NIA-AA, all guidelines identified asymptomatic individuals at risk of cognitive impairment. Our findings highlight important differences between the guidelines, emphasizing the necessity for updated criteria with enhanced staging metrics, considering clinical, research, therapeutic, and trial design aspects.

Exposures and conditions prior to age 16 are associated with dementia status among adults in the United States Health and Retirement Study

Background

Dementia susceptibility likely begins years before symptoms. Early life has not been comprehensively tested for dementia associations.

Method

In the US Health and Retirement Study (normal baseline cognition; n=16,509; 2008-2018 waves), 31 exposures before age 16 were retrospectively assessed with ten-year incident cognitive status (dementia, impaired, normal). Using parallel logistic models, each exposure was tested with incident cognition, adjusting for sex, baseline age, follow-up, race/ethnicity, personal/parental education.

Result

14.5% had incident impairment and 5.3% had dementia. Depression was associated with 1.71 (95%CI:1.28,2.26) times higher odds of incident impairment, relative to normal cognition. Headaches/migraines were associated with 1.63 (95%CI:1.18,2.22) times higher odds of incident impairment. Learning problems were associated with 1.75 (95%CI:1.05,2.79) times higher odds of incident impairment. Childhood self-rated health of fair (1.86, 95%CI:1.27,2.64) and poor (3.39, 95%CI:1.91,5.82) were associated with higher incident dementia odds, relative to excellent.

Conclusion

Early life factors may be important for impairment or dementia, extending the relevant risk window.

The relationship between hippocampal changes in healthy aging and Alzheimer's disease: a systematic literature review

Introduction

Neurobiological changes in the hippocampus are a common consequence of aging. However, there are differences in the rate of decline and overall volume loss in people with no cognitive impairment compared to those with mild cognitive impairment (MCI) and Alzheimer's disease (AD). This systematic literature review was conducted to determine the relationship between hippocampal atrophy and changes in hippocampal volume in the non-cognitively impaired brain and those with MCI or AD.

Methods

This systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The PubMed database was searched up to September 15, 2022, for longitudinal magnetic resonance imaging studies reporting hippocampal atrophy or volume change in cognitively normal aging individuals and patients with MCI and/or AD. Study selection was divided into two steps: (1) identification and retrieval of relevant studies; (2) screening the studies by (a) title/abstract and (b) full text. Two teams, each consisting of two independent reviewers, determined whether the publications met the inclusion criteria for the systematic review. An evidence table was populated with data extracted from eligible publications and inclusion in the final systematic review was confirmed.

Results

The systematic search identified 357 publications that were initially screened by title/abstract, of which, 115 publications were retrieved and reviewed by full text for eligibility. Seventeen publications met the eligibility criteria; however, during data extraction, two studies were determined to not meet the inclusion criteria and were excluded. The remaining 15 studies were included in the systematic review. Overall, the results of these studies demonstrated that the hippocampus and hippocampal subfields change over time, with both decreased hippocampal volume and increased rate of hippocampal atrophy observed. Hippocampal changes in AD were observed to be greater than hippocampal changes in MCI, and changes in MCI were observed to be greater than those in normal aging populations.

Conclusion

Published literature suggests that the rate of hippocampal decline and extent of loss is on a continuum that begins in people without cognitive impairment and continues to MCI and AD, and that differences between no cognitive impairment, MCI, and AD are quantitative rather than qualitative.

Deep learning assisted quantitative analysis of Aβ and microglia in patients with idiopathic normal pressure hydrocephalus in relation to cognitive outcome

Neuropathologic changes of Alzheimer disease (AD) including Aβ accumulation and neuroinflammation are frequently observed in the cerebral cortex of patients with idiopathic normal pressure hydrocephalus (iNPH). We created an automated analysis platform to quantify Aβ load and reactive microglia in the vicinity of Aβ plaques and to evaluate their association with cognitive outcome in cortical biopsies of patients with iNPH obtained at the time of shunting. Aiforia Create deep learning software was used on whole slide images of Iba1/4G8 double immunostained frontal cortical biopsies of 120 shunted iNPH patients to identify Iba1-positive microglia somas and Aβ areas, respectively. Dementia, AD clinical syndrome (ACS), and Clinical Dementia Rating Global score (CDR-GS) were evaluated retrospectively after a median follow-up of 4.4 years. Deep learning artificial intelligence yielded excellent (>95%) precision for tissue, Aβ, and microglia somas. Using an age-adjusted model, higher Aβ coverage predicted the development of dementia, the diagnosis of ACS, and more severe memory impairment by CDR-GS whereas measured microglial densities and Aβ-related microglia did not correlate with cognitive outcome in these patients. Therefore, cognitive outcome seems to be hampered by higher Aβ coverage in cortical biopsies in shunted iNPH patients but is not correlated with densities of surrounding microglia.

Sex and gender differences in cognitive resilience to aging and Alzheimer's disease

Sex and gender-biological and social constructs-significantly impact the prevalence of protective and risk factors, influencing the burden of Alzheimer's disease (AD; amyloid beta and tau) and other pathologies (e.g., cerebrovascular disease) which ultimately shape cognitive trajectories. Understanding the interplay of these factors is central to understanding resilience and resistance mechanisms explaining maintained cognitive function and reduced pathology accumulation in aging and AD. In this narrative review, the ADDRESS! Special Interest Group (Alzheimer's Association) adopted a multidisciplinary approach to provide the foundations and recommendations for future research into sex- and gender-specific drivers of resilience, including a sex/gender-oriented review of risk factors, genetics, AD and non-AD pathologies, brain structure and function, and animal research. We urge the field to adopt a sex/gender-aware approach to resilience to advance our understanding of the intricate interplay of biological and social determinants and consider sex/gender-specific resilience throughout disease stages. HIGHLIGHTS: Sex differences in resilience to cognitive decline vary by age and cognitive status. Initial evidence supports sex-specific distinctions in brain pathology. Findings suggest sex differences in the impact of pathology on cognition. There is a sex-specific change in resilience in the transition to clinical stages. Gender and sex factors warrant study: modifiable, immune, inflammatory, and vascular.

Clinical Application of Blood Biomarkers in Neurodegenerative Diseases-Present and Future Perspectives

Neurodegenerative diseases are a group of complex diseases characterized by a progressive loss of neurons and degeneration in different areas of the nervous system. They share similar mechanisms, such as neuroinflammation, oxidative stress, and mitochondrial injury, resulting in neuronal loss. One of the biggest challenges in diagnosing neurodegenerative diseases is their heterogeneity. Clinical symptoms are usually present in the advanced stages of the disease, thus it is essential to find optimal biomarkers that would allow early diagnosis. Due to the development of ultrasensitive methods analyzing proteins in other fluids, such as blood, huge progress has been made in the field of biomarkers for neurodegenerative diseases. The application of protein biomarker measurement has significantly influenced not only diagnosis but also prognosis, differentiation, and the development of new therapies, as it enables the recognition of early stages of disease in individuals with preclinical stages or with mild symptoms. Additionally, the introduction of biochemical markers into routine clinical practice may improve diagnosis and allow for a stratification group of people with higher risk, as well as an extension of well-being since a treatment could be started early. In this review, we focus on blood biomarkers, which could be potentially useful in the daily medical practice of selected neurodegenerative diseases.

Flortaucipir PET uncovers relationships between tau and amyloid-β in primary age-related tauopathy and Alzheimer's disease

[18F]-Flortaucipir positron emission tomography (PET) is considered a good biomarker of Alzheimer's disease. However, it is unknown how flortaucipir is associated with the distribution of tau across brain regions and how these associations are influenced by amyloid-β. It is also unclear whether flortaucipir can detect tau in definite primary age-related tauopathy (PART). We identified 248 individuals at Mayo Clinic who had undergone [18F]-flortaucipir PET during life, had died, and had undergone an autopsy, 239 cases of which also had amyloid-β PET. We assessed nonlinear relationships between flortaucipir uptake in nine medial temporal and cortical regions, Braak tau stage, and Thal amyloid-β phase using generalized additive models. We found that flortaucipir uptake was greater with increasing tau stage in all regions. Increased uptake at low tau stages in medial temporal regions was only observed in cases with a high amyloid-β phase. Flortaucipir uptake linearly increased with the amyloid-β phase in medial temporal and cortical regions. The highest flortaucipir uptake occurred with high Alzheimer's disease neuropathologic change (ADNC) scores, followed by low-intermediate ADNC scores, then PART, with the entorhinal cortex providing the best differentiation between groups. Flortaucipir PET had limited ability to detect PART, and imaging-defined PART did not correspond with pathologically defined PART. In summary, spatial patterns of flortaucipir mirrored the histopathological tau distribution, were influenced by the amyloid-β phase, and were useful for distinguishing different ADNC scores and PART.

Alkaloids as drug leads in Alzheimer's treatment: Mechanistic and therapeutic insights

Alzheimer's disease (AD) has few effective treatment options and continues to be a major global health concern. AD is a neurodegenerative disease that typically affects elderly people. Alkaloids have potential sources for novel drug discovery due to their diverse chemical structures and pharmacological activities. Alkaloids, natural products with heterocyclic nitrogen-containing structures, are considered potential treatments for AD. This review explores the neuroprotective properties of alkaloids in AD, focusing on their ability to regulate pathways such as amyloid-beta aggregation, oxidative stress, synaptic dysfunction, tau hyperphosphorylation, and neuroinflammation. The FDA has approved alkaloids such as acetylcholinesterase inhibitors like galantamine and rivastigmine. This article explores AD's origins, current market medications, and clinical applications of alkaloids in AD therapy. This review explores the development of alkaloid-based drugs for AD, focusing on pharmacokinetics, blood-brain barrier penetration, and potential adverse effects. Future research should focus on the clinical evaluation of promising alkaloids, developing recently discovered alkaloids, and the ongoing search for novel alkaloids for medical treatment. A pharmaceutical option containing an alkaloid may potentially slow down the progression of AD while enhancing its symptoms. This review highlights the potential of alkaloids as valuable drug leads in treating AD, providing a comprehensive understanding of their mechanisms of action and therapeutic implications.

Integrative Single-Plaque Analysis Reveals Signature Aβ and Lipid Profiles in the Alzheimer's Brain

Cerebral accumulation of amyloid-β (Aβ) initiates molecular and cellular cascades that lead to Alzheimer's disease (AD). However, amyloid deposition does not invariably lead to dementia. Amyloid-positive but cognitively unaffected (AP-CU) individuals present widespread amyloid pathology, suggesting that molecular signatures more complex than the total amyloid burden are required to better differentiate AD from AP-CU cases. Motivated by the essential role of Aβ and the key lipid involvement in AD pathogenesis, we applied multimodal mass spectrometry imaging (MSI) and machine learning (ML) to investigate amyloid plaque heterogeneity, regarding Aβ and lipid composition, in AP-CU versus AD brain samples at the single-plaque level. Instead of focusing on a population mean, our analytical approach allowed the investigation of large populations of plaques at the single-plaque level. We found that different (sub)populations of amyloid plaques, differing in Aβ and lipid composition, coexist in the brain samples studied. The integration of MSI data with ML-based feature extraction further revealed that plaque-associated gangliosides GM2 and GM1, as well as Aβ1-38, but not Aβ1-42, are relevant differentiators between the investigated pathologies. The pinpointed differences may guide further fundamental research investigating the role of amyloid plaque heterogeneity in AD pathogenesis/progression and may provide molecular clues for further development of emerging immunotherapies to effectively target toxic amyloid assemblies in AD therapy. Our study exemplifies how an integrative analytical strategy facilitates the unraveling of complex biochemical phenomena, advancing our understanding of AD from an analytical perspective and offering potential avenues for the refinement of diagnostic tools.

Atypical Alzheimer's disease: new insights into an overlapping spectrum between the language and visual variants

Overlap between language and visual variants of atypical Alzheimer's disease (AD) has been reported. However, the extent, frequency of overlap, and its neuroanatomical underpinnings remain unclear. Eighty-two biomarker-confirmed AD patients who presented with either predominant language (n = 34) or visuospatial/perceptual (n = 48) deficits underwent detailed clinical examinations, MRI, and [18F]flortaucipir-PET. Subgroups were defined based on language/visual testing and patterns of volume loss and tau uptake were assessed. 28% of the language group had visual dysfunction (marked in 8%), and 47% of the visual group had language impairment (marked in 26%). Progressive involvement of the parieto-occipital and frontal lobes was noted with greater visual impairment in the language group, and greater left parieto-temporal and frontal involvement with worsening language impairment in the visual group. Only 25% of our cohort showed a pure language or visual presentation, highlighting the high frequency of syndromic overlap in atypical AD and the diagnostic challenge of categorical phenotyping.

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.

Memory complaint in a middle-income country: a four-year longitudinal study in a cohort with low-education

BACKGROUND

 Memory complaints are frequent in older adults and are associated with higher risk of cognitive decline.

OBJECTIVE

 To investigate the functional outcome of individuals with memory complaints followed up at primary care centers.

METHODS

 Data were collected between 2016 e 2020 in primary health care centers in Brazil. Patients underwent the Brief Cognitive Screening Battery, and the Functional Activities Questionnaire.

RESULTS

 The initial sample (2016) comprised 91 individuals classified into those with subjective cognitive decline (SCD, n = 15), mild cognitive impairment (MCI, n = 45), or dementia (n = 31). During follow-up, 8 individuals (8.8% of the initial sample) died and 26 (28.5% of the initial sample) were not found. Fifty-seven participants underwent clinical reassessment. Of 15 individuals with SCD, 7 were not found (46.7%), 4 (26.7%) progressed to MCI, and 4 (26.7%) remained stable. Of 45 individuals with MCI, 11 were not found (24.4%), 2 (4.4%) died, 6 (13.4%) progressed to dementia, 12 (26.7%) regressed to SCD, and 14 (31.1%) remained stable. Of 31 individuals with dementia, 8 were not found (25.8%), 6 (19.4%) died, 2 (6.5%) regressed to SCD, 7 (22.6%) regressed to MCI, and 8 remained stable (25.8%). Clinical improvement was due to the treatment of reversible causes, such as B12 hypovitaminosis and mood disorders. Older age, lower Mini-Mental State Examination, and higher scores of memory complaint, but not the use of benzodiazepines and of proton pump inhibitors, were predictors of functional status.

CONCLUSION

 Despite their limits (short sample size, missing data), these results support the idea that adequate screening, follow-up, and treatment of reversible causes of dementia in primary care are essential.

Mayo normative studies: regression-based normative data for ages 30-91 years with a focus on the Boston Naming Test, Trail Making Test and Category Fluency

OBJECTIVE

Normative neuropsychological data are essential for interpretation of test performance in the context of demographic factors. The Mayo Normative Studies (MNS) aim to provide updated normative data for neuropsychological measures administered in the Mayo Clinic Study of Aging (MCSA), a population-based study of aging that randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. We examined demographic effects on neuropsychological measures and validated the regression-based norms in comparison to existing normative data developed in a similar sample.

METHOD

The MNS includes cognitively unimpaired adults ≥30 years of age (n = 4,428) participating in the MCSA. Multivariable linear regressions were used to determine demographic effects on test performance. Regression-based normative formulas were developed by first converting raw scores to normalized scaled scores and then regressing on age, age2, sex, and education. Total and sex-stratified base rates of low scores (T < 40) were examined in an older adult validation sample and compared with Mayo's Older Americans Normative Studies (MOANS) norms.

RESULTS

Independent linear regressions revealed variable patterns of linear and/or quadratic effects of age (r2 = 6-27% variance explained), sex (0-13%), and education (2-10%) across measures. MNS norms improved base rates of low performance in the older adult validation sample overall and in sex-specific patterns relative to MOANS.

CONCLUSIONS

Our results demonstrate the need for updated norms that consider complex demographic associations on test performance and that specifically exclude participants with mild cognitive impairment from the normative sample.

Altered structural and functional connectivity in Posterior Cortical Atrophy and Dementia with Lewy bodies

Posterior cortical atrophy (PCA) and dementia with Lewy bodies (DLB) show distinct atrophy and overlapping hypometabolism profiles, but it is unknown how disruptions in structural and functional connectivity compare between these disorders and whether breakdowns in connectivity relate to either atrophy or hypometabolism. Thirty amyloid-positive PCA patients, 24 amyloid-negative DLB patients and 30 amyloid-negative cognitively unimpaired (CU) healthy individuals were recruited at Mayo Clinic, Rochester, MN, and underwent a 3T head MRI, including structural MRI, resting state functional MRI (rsfMRI) and diffusion tensor imaging (DTI) sequences, as well as [18F] fluorodeoxyglucose (FDG) PET. We assessed functional connectivity within and between 12 brain networks using rsfMRI and the CONN functional connectivity toolbox and calculated regional DTI metrics using the Johns Hopkins atlas. Multivariate linear-regression models corrected for multiple comparisons and adjusted for age and sex compared DTI metrics and within-network and between-network functional connectivity across groups. Regional gray-matter volumes and FDG-PET standard uptake value ratios (SUVRs) were calculated and analyzed at the voxel-level using SPM12. We used univariate linear-regression models to investigate the relationship between connectivity measures, gray-matter volume, and FDG-PET SUVR. On DTI, PCA showed degeneration in occipito-parietal white matter, posterior thalamic radiations, splenium of the corpus collosum and sagittal stratum compared to DLB and CU, with greater degeneration in the temporal white matter and the fornix compared to CU. We observed no white-matter degeneration in DLB compared to CU. On rsfMRI, reduced within-network connectivity was present in dorsal and ventral default mode networks (DMN) and the dorsal-attention network in PCA compared to DLB and CU, with reduced within-network connectivity in the visual and sensorimotor networks compared to CU. DLB showed reduced connectivity in the cerebellar network compared to CU. Between-network analysis showed increased connectivity in both cerebellar-to-sensorimotor and cerebellar-to-dorsal attention network connectivity in PCA and DLB. PCA showed reduced anterior DMN-to-cerebellar and dorsal attention-to-sensorimotor connectivity, while DLB showed reduced posterior DMN-to-sensorimotor connectivity compared to CU. PCA showed reduced dorsal DMN-to-visual connectivity compared to DLB. The multimodal analysis revealed weak associations between functional connectivity and volume in PCA, and between functional connectivity and metabolism in DLB. These findings suggest that PCA and DLB have unique connectivity alterations, with PCA showing more widespread disruptions in both structural and functional connectivity; yet some overlap was observed with both disorders showing increased connectivity from the cerebellum.

Combining artificial neural networks and a marginal structural model to predict the progression from depression to Alzheimer's disease

Introduction

Decades of research in population health have established depression as a likely precursor to Alzheimer's disease. A combination of causal estimates and machine learning methods in artificial intelligence could identify internal and external mediating mechanisms that contribute to the likelihood of progression from depression to Alzheimer's disease.

Methods

We developed an integrated predictive model, combining the marginal structural model and an artificial intelligence predictive model, distinguishing between patients likely to progress from depressive states to Alzheimer's disease better than each model alone.

Results

The integrated predictive model achieved substantial clinical relevance when using the area under the curve measure. It performed better than the traditional statistical method or a single artificial intelligence method alone.

Discussion

The integrated predictive model could form a part of a clinical screening tool that identifies patients who are likely to progress from depression to Alzheimer's disease for early behavioral health interventions. Given the high costs of treating Alzheimer's disease, our model could serve as a cost-effective intervention for the early detection of depression before it progresses to Alzheimer's disease.

Biomarker-based staging of Alzheimer disease: rationale and clinical applications

Disease staging, whereby the spatial extent and load of brain pathology are used to estimate the severity of Alzheimer disease (AD), is pivotal to the gold-standard neuropathological diagnosis of AD. Current in vivo diagnostic frameworks for AD are based on abnormal concentrations of amyloid-β and tau in the cerebrospinal fluid or on PET scans, and breakthroughs in molecular imaging have opened up the possibility of in vivo staging of AD. Focusing on the key principles of disease staging shared across several areas of medicine, this Review highlights the potential for in vivo staging of AD to transform our understanding of preclinical AD, refine enrolment criteria for trials of disease-modifying therapies and aid clinical decision-making in the era of anti-amyloid therapeutics. We provide a state-of-the-art review of recent biomarker-based AD staging systems and highlight their contributions to the understanding of the natural history of AD. Furthermore, we outline hypothetical frameworks to stage AD severity using more accessible fluid biomarkers. In addition, by applying amyloid PET-based staging to recently published anti-amyloid therapeutic trials, we highlight how biomarker-based disease staging frameworks could illustrate the numerous pathological changes that have already taken place in individuals with mildly symptomatic AD. Finally, we discuss challenges related to the validation and standardization of disease staging and provide a forward-looking perspective on potential clinical applications.

Alzheimer's Amyloid Hypothesis and Antibody Therapy: Melting Glaciers?

The amyloid cascade hypothesis for Alzheimer's disease is still alive, although heavily challenged. Effective anti-amyloid immunotherapy would confirm the hypothesis' claim that the protein amyloid-beta is the cause of the disease. Two antibodies, aducanumab and lecanemab, have been approved by the U.S. Food and Drug Administration, while a third, donanemab, is under review. The main argument for the FDA approvals is a presumed therapy-induced removal of cerebral amyloid deposits. Lecanemab and donanemab are also thought to cause some statistical delay in the determination of cognitive decline. However, clinical efficacy that is less than with conventional treatment, selection of amyloid-positive trial patients with non-specific amyloid-PET imaging, and uncertain therapy-induced removal of cerebral amyloids in clinical trials cast doubt on this anti-Alzheimer's antibody therapy and hence on the amyloid hypothesis, calling for a more thorough investigation of the negative impact of this type of therapy on the brain.

Diagnosis of Alzheimer's disease: Towards accuracy and accessibility

Alzheimer's disease (AD) is a serious dementia afflicting aging population and is characterized by cognitive decline, amyloid-β plaques, and neurofibrillary tangles. AD substantially impairs the life quality of the victims and poses a heavy burden on the society at large. The number of people with dementia due to AD, prodromal AD, and preclinical AD is estimated to stand at roughly 3.2, 69, and 315 million worldwide, respectively. Current clinical diagnosis is based on clinical symptoms, and clinical research demonstrated that positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers had excellent diagnostic performance. However, the application of CSF biomarker tests and PET are restricted by the invasiveness and high cost. The presence of clinical symptoms means that AD pathology has been progressing for many years, and only a few drugs have been approved for the traetemnt of AD. Therefore, early diagnosis is extremely important for controlling the outcomes caused by AD. In this review, we provided an overview of developing clinical diagnostic criteria, diagnostic strategies under clinical research, developing blood based-biomarker assays, and promising nanotechnologically-based assays.

MSUT2 regulates tau spreading via adenosinergic signaling mediated ASAP1 pathway in neurons

Inclusions comprised of microtubule-associated protein tau (tau) are implicated in a group of neurodegenerative diseases, collectively known as tauopathies, that include Alzheimer's disease (AD). The spreading of misfolded tau "seeds" along neuronal networks is thought to play a crucial role in the progression of tau pathology. Consequently, restricting the release or uptake of tau seeds may inhibit the spread of tau pathology and potentially halt the advancement of the disease. Previous studies have demonstrated that the Mammalian Suppressor of Tauopathy 2 (MSUT2), an RNA binding protein, modulates tau pathogenesis in a transgenic mouse model. In this study, we investigated the impact of MSUT2 on tau pathogenesis using tau seeding models. Our findings indicate that the loss of MSUT2 mitigates human tau seed-induced pathology in neuron cultures and mouse models. In addition, MSUT2 regulates many gene transcripts, including the Adenosine Receptor 1 (A1AR), and we show that down regulation or inhibition of A1AR modulates the activity of the "ArfGAP with SH3 Domain, Ankyrin Repeat, and PH Domain 1 protein" (ASAP1), thereby influencing the internalization of pathogenic tau seeds into neurons resulting in reduction of tau pathology.

Significance of a positive tau PET scan with a negative amyloid PET scan

INTRODUCTION

The implications of positive tau positron emission tomography (T) with negative beta amyloid positron emission tomography (A) are not well understood. We investigated cognitive performance in participants who were T+ but A-.

METHODS

We evaluated 98 participants from the Mayo Clinic who were T+ and A-. Participants were matched 2:1 to A- and T- cognitively unimpaired (CU) controls. Cognitive test scores were compared between different groups.

RESULTS

The A-T+ group demonstrated lower performance than the A-T- group on the Mini-Mental Status Exam (MMSE) (p < 0.001), Wechsler Memory Scale-Revised Logical Memory I (p < 0.001) and Logical Memory II (p < 0.001), Auditory Verbal Learning Test (AVLT) delayed recall (p = 0.004), category fluency (animals p = 0.005; vegetables p = 0.021), Trail Making Test A and B (p < 0.001), and others. There were no significant differences in demographic features or apolipoprotein E (APOE) e4 genotype between CU A-T+ and CI A-T+.

DISCUSSION

A-T+ participants show an association with lower cognitive performance.

Case report: pre-symptomatic clinical and metabolic profile in posterior cortical atrophy and dementia with Lewy bodies

A research participant was monitored over nearly two decades at Mayo Clinic, undergoing annual neurologic assessments, neuropsychological tests, and multimodal imaging. Initially, he was cognitively normal but developed symptoms consistent with Posterior Cortical Atrophy (PCA) during the study. Early tests indicated mild, yet normal-range declines in language and visuospatial skills. FDG-PET scans revealed increased metabolism in posterior brain regions long before symptoms appeared. Advanced analysis using a novel in-house machine-learning tool predicted concurrent Alzheimer's disease and dementia with Lewy bodies. Autopsy confirmed a mixed neurodegenerative condition with significant Alzheimer's pathology and dense neocortical Lewy bodies. This case underscores the value of longitudinal imaging in predicting complex neurodegenerative diseases, offering vital insights into the early neurocognitive changes associated with PCA and dementia with Lewy bodies.

Evaluation of serum neurofilament light chain and glial fibrillary acidic protein in the diagnosis of Alzheimer's disease

Purpose

This study aimed to evaluate the use of serum neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in the diagnosis of Alzheimer's disease (AD) and the differential diagnosis between AD and mild cognitive impairment (MCI).

Methods

From September 2021 to October 2022, we collected venous blood from patients and healthy individuals who visited our hospital's Neurology Department, and we isolated serum to detect NfL and GFAP using direct chemiluminescence. The results were analyzed using one-way analysis of variance (ANOVA) analysis and receiver operating characteristic (ROC) curves.

Results

Pairwise comparisons among the three groups showed that compared with the health checkup (HC) group, serum NfL and GFAP were increased in both AD and MCI (PNfL < 0.05, PGFAP < 0.01). There were significant differences in GFAP between MCI and AD groups, and the level in AD group was higher (p < 0.01), while there was no difference in NfL. Both serum NfL and serum GFAP levels can independently diagnose AD (p < 0.01). The ROC curve showed that GFAP had a higher diagnostic efficacy, with an area under the ROC curve (AUC) of 0.928. The cut-off values of the two serum markers for the diagnosis of AD were NfL > 40.09 pg./mL and GFAP >31.40 pg./mL. Sensitivity and specificity for NfL in the diagnosis of AD were 59.6 and 76.2%, respectively, and for GFAP, they were 90.4 and 82.1%, respectively. The combined diagnosis of GFAP and NfL improved the diagnostic efficiency (AUC = 0.931, sensitivity = 78.8%, specificity = 92.3%). The cut-off value of GFAP for the differential diagnosis of MCI and AD was 46.05 pg./mL.

Conclusion

Both serum NfL and serum GFAP can be used as biomarkers for the diagnosis of AD. Serum GFAP has better diagnostic efficacy and can distinguish AD from MCI. A combined diagnosis can improve diagnostic specificity.

Converged avenues: depression and Alzheimer's disease- shared pathophysiology and novel therapeutics

Depression, a highly prevalent disorder affecting over 280 million people worldwide, is comorbid with many neurological disorders, particularly Alzheimer's disease (AD). Depression and AD share overlapping pathophysiology, and the search for accountable biological substrates made it an essential and intriguing field of research. The paper outlines the neurobiological pathways coinciding with depression and AD, including neurotrophin signalling, the hypothalamic-pituitary-adrenal axis (HPA), cellular apoptosis, neuroinflammation, and other aetiological factors. Understanding overlapping pathways is crucial in identifying common pathophysiological substrates that can be targeted for effective management of disease state. Antidepressants, particularly monoaminergic drugs (first-line therapy), are shown to have modest or no clinical benefits. Regardless of the ineffectiveness of conventional antidepressants, these drugs remain the mainstay for treating depressive symptoms in AD. To overcome the ineffectiveness of traditional pharmacological agents in treating comorbid conditions, a novel therapeutic class has been discussed in the paper. This includes neurotransmitter modulators, glutamatergic system modulators, mitochondrial modulators, antioxidant agents, HPA axis targeted therapy, inflammatory system targeted therapy, neurogenesis targeted therapy, repurposed anti-diabetic agents, and others. The primary clinical challenge is the development of therapeutic agents and the effective diagnosis of the comorbid condition for which no specific diagnosable scale is present. Hence, introducing Artificial Intelligence (AI) into the healthcare system is revolutionary. AI implemented with interdisciplinary strategies (neuroimaging, EEG, molecular biomarkers) bound to have accurate clinical interpretation of symptoms. Moreover, AI has the potential to forecast neurodegenerative and psychiatric illness much in advance before visible/observable clinical symptoms get precipitated.

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.

Behavioral and Neuropsychiatric Differences Across Two Atypical Alzheimer's Disease Variants: Logopenic Progressive Aphasia and Posterior Cortical Atrophy

BACKGROUND

Posterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are two common atypical Alzheimer's disease (AD) variants. Little is known about behavioral and neuropsychiatric symptoms or activities of daily living (ADLs) in PCA and LPA, and whether they differ across syndromes.

OBJECTIVE

To characterize the behavioral and neuropsychiatric profiles and ADLs of PCA and LPA and compare presence/absence and severity of symptoms between syndromes.

METHODS

Seventy-eight atypical AD patients, 46 with PCA and 32 with LPA, completed the Neuropsychiatric Inventory Questionnaire (NPI-Q) and Cambridge Behavioral Inventory-Revised (CBI-R) at baseline and longitudinally over-time. Mann-Whitney U and Fisher's Exact Tests assessed for differences in symptoms between the two syndromes with significance set at p≤0.01. To eliminate demographic differences as confounders the groups were matched, and differences reanalyzed.

RESULTS

PCA were younger at onset (p = 0.006), at time of baseline assessment (p = 0.02) and had longer disease duration (p = 0.01). Neuropsychiatric symptoms were common in PCA and LPA, although more common and severe in PCA. At baseline, PCA had a higher NPI-Q total score (p = 0.01) and depression subscore (p = 0.01) than LPA. Baseline total CBI-R scores were also higher in PCA than LPA (p = 0.001) with PCA having worse scores in all 10 CBI-R categories. Longitudinally, there was no difference between groups on the NPI-Q. However, on the CBI-R, PCA had faster rates of worsening on self-grooming (p = 0.01) and self-dressing (p = 0.01) compared to LPA.

CONCLUSIONS

Behavioral and neuropsychiatric symptoms are common in PCA and LPA although these symptoms are more common and severe in PCA.

Once upon a time, the Amyloid Cascade Hypothesis

Recent trials with monoclonal antibodies targeting amyloid-β (Aβ) in Alzheimer's disease (AD) have sparked a renewed interest in disease-modifying therapies. Despite their promise, these trials leave the issue open and posit some doubts about the validity of the Amyloid Cascade Hypothesis (ACH). While some scores of neurocognitive tests improved upon treatment, real-world clinical benefits were minimal. This Viewpoint discusses additional, often overlooked findings from these trials. We also emphasize the multifactorial nature of AD and the need for a broader research perspective beyond the simplistic disease model provided by the ACH.

Mayo Normative Studies: Amyloid and Neurodegeneration Negative Normative Data for the Auditory Verbal Learning Test and Sex-Specific Sensitivity to Mild Cognitive Impairment/Dementia

Background

Conventional normative samples include individuals with undetected Alzheimer's disease neuropathology, lowering test sensitivity for cognitive impairment.

Objective

We developed Mayo Normative Studies (MNS) norms limited to individuals without elevated amyloid or neurodegeneration (A-N-) for Rey's Auditory Verbal Learning Test (AVLT). We compared these MNS A-N- norms in female, male, and total samples to conventional MNS norms with varying levels of demographic adjustments.

Methods

The A-N- sample included 1,059 Mayo Clinic Study of Aging cognitively unimpaired (CU) participants living in Olmsted County, MN, who are predominantly non-Hispanic White. Using a regression-based approach correcting for age, sex, and education, we derived fully-adjusted T-score formulas for AVLT variables. We validated these A-N- norms in two independent samples of CU (n = 261) and mild cognitive impairment (MCI)/dementia participants (n = 392) > 55 years of age.

Results

Variability associated with age decreased by almost half in the A-N- norm sample relative to the conventional norm sample. Fully-adjusted MNS A-N- norms showed approximately 7- 9% higher sensitivity to MCI/dementia compared to fully-adjusted MNS conventional norms for trials 1- 5 total and sum of trials. Among women, sensitivity to MCI/dementia increased with each normative data refinement. In contrast, age-adjusted conventional MNS norms showed greatest sensitivity to MCI/dementia in men.

Conclusions

A-N- norms show some benefits over conventional normative approaches to MCI/dementia sensitivity, especially for women. We recommend using these MNS A-N- norms alongside MNS conventional norms. Future work is needed to determine if normative samples that are not well characterized clinically show greater benefit from biomarker-refined approaches.

Machine learning analyses identify multi-modal frailty factors that selectively discriminate four cohorts in the Alzheimer's disease spectrum: a COMPASS-ND study

BACKGROUND

Frailty indicators can operate in dynamic amalgamations of disease conditions, clinical symptoms, biomarkers, medical signals, cognitive characteristics, and even health beliefs and practices. This study is the first to evaluate which, among these multiple frailty-related indicators, are important and differential predictors of clinical cohorts that represent progression along an Alzheimer's disease (AD) spectrum. We applied machine-learning technology to such indicators in order to identify the leading predictors of three AD spectrum cohorts; viz., subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and AD. The common benchmark was a cohort of cognitively unimpaired (CU) older adults.

METHODS

The four cohorts were from the cross-sectional Comprehensive Assessment of Neurodegeneration and Dementia dataset. We used random forest analysis (Python 3.7) to simultaneously test the relative importance of 83 multi-modal frailty indicators in discriminating the cohorts. We performed an explainable artificial intelligence method (Tree Shapley Additive exPlanation values) for deep interpretation of prediction effects.

RESULTS

We observed strong concurrent prediction results, with clusters varying across cohorts. The SCI model demonstrated excellent prediction accuracy (AUC = 0.89). Three leading predictors were poorer quality of life ([QoL]; memory), abnormal lymphocyte count, and abnormal neutrophil count. The MCI model demonstrated a similarly high AUC (0.88). Five leading predictors were poorer QoL (memory, leisure), male sex, abnormal lymphocyte count, and poorer self-rated eyesight. The AD model demonstrated outstanding prediction accuracy (AUC = 0.98). Ten leading predictors were poorer QoL (memory), reduced olfaction, male sex, increased dependence in activities of daily living (n = 6), and poorer visual contrast.

CONCLUSIONS

Both convergent and cohort-specific frailty factors discriminated the AD spectrum cohorts. Convergence was observed as all cohorts were marked by lower quality of life (memory), supporting recent research and clinical attention to subjective experiences of memory aging and their potentially broad ramifications. Diversity was displayed in that, of the 14 leading predictors extracted across models, 11 were selectively sensitive to one cohort. A morbidity intensity trend was indicated by an increasing number and diversity of predictors corresponding to clinical severity, especially in AD. Knowledge of differential deficit predictors across AD clinical cohorts may promote precision interventions.

A New Framework for Dementia Nomenclature

Importance

Nomenclature in the field of neurodegenerative diseases presents a challenging problem. Inconsistent use of terms such as Alzheimer disease and dementia has compromised progress in clinical care, research, and development of therapeutics. Dementia-associated stigma further contributes to inconsistent and imprecise language. The result is a lack of clarity that produces confusion with patients and the general public and presents communication challenges among researchers. Therefore, the Advisory Council on Research, Care, and Services of the National Plan to Address Alzheimer's Disease authorized a committee to make recommendations for improvement.

Objective

To establish a systematic neurodegenerative disease framework for information collection and communication to standardize language usage for research, clinical, and public health purposes.

Evidence Review

The Dementia Nomenclature Initiative organized into 3 major stakeholder working groups: clinicians, researchers, and the public (including individuals living with dementia and family caregivers). To inform the work, the initiative completed a narrative literature review of dementia nomenclature evolution over the last century across the PubMed, CINAHL, PsycInfo, and Scopus databases (January 1, 2000, through July 31, 2020). Initiative working groups used the results as a foundation for understanding current challenges with dementia nomenclature and implications for research, clinical practice, and public understanding. The initiative obtained additional input via focus groups with individuals living with dementia and caregivers, with separate groups for race and ethnicity (American Indian or Alaska Native, Asian or Pacific Islander, Black or African American, Hispanic or Latino, and White) as an initial assessment of the meaning of dementia-related terms to these groups.

Findings

From working group deliberations, the literature review, and focus group input, the initiative developed a framework clearly separating the clinical syndromic presentation experienced by affected individuals from possible underlying pathophysiologies. In the framework, domains of clinical impairment, such as cognitive, behavioral, motor, and other neurologic features, are graded by level of impairment between none and severe. Next, biomarker information describes underlying disease processes, explains the syndrome, and identifies possible disease labels: Alzheimer disease, frontotemporal degeneration, dementia with Lewy bodies, or vascular cognitive impairment dementia.

Conclusions and Relevance

The Dementia Nomenclature Initiative established a framework to guide communication about cognitive impairment among older adults. Wider testing and refinement of the framework will subsequently improve the information used in communicating about cognitive impairment and the way in which the information is used in clinical, research, and public settings.

The proteinopenia hypothesis: Loss of Aβ42 and the onset of Alzheimer's Disease

The dominant protein-lowering strategy in Alzheimer's Disease (AD) has failed to provide a clinically-meaningful treatment for patients. We hypothesize that the loss of functional, soluble Aβ42 during the process of aggregation into amyloid is more detrimental to the brain than the corresponding accrual of insoluble amyloid.

Association of AI-determined Kellgren-Lawrence grade with medial meniscus extrusion and cartilage thickness by AI-based 3D MRI analysis in early knee osteoarthritis

The associations among Kellgren-Lawrence (KL) grade, medial meniscus extrusion (MME), and cartilage thickness in knee osteoarthritis (OA) remain insufficiently understood. Our aim was to determine these associations in early to moderate medial tibiofemoral knee OA. We included 469 subjects with no lateral OA from the Kanagawa Knee Study. KL grade was assessed using artificial intelligence (AI) software. The MME was measured by MRI, and the cartilage thickness was evaluated in 18 subregions of the medial femorotibial joint by another AI system. The median MME width was 1.4 mm in KL0, 1.5 mm in KL1, 2.4 mm in KL2, and 6.0 mm in KL3. Cartilage thinning in the medial femur occurred in the anterior central subregion in KL1, expanded inwardly in KL2, and further expanded in KL3. Cartilage thinning in the medial tibia occurred in the anterior and middle external subregions in KL1, expanded into the anterior and middle central subregions in KL2, and further expanded in KL3. The absolute correlation coefficient between MME width and cartilage thickness increased as the KL grade increased in some subregions. This study provides novel insights into the early stages of knee OA and potentially has implications for the development of early intervention strategies.

Deep brain stimulation of thalamic nucleus reuniens promotes neuronal and cognitive resilience in an Alzheimer's disease mouse model

The mechanisms that confer cognitive resilience to Alzheimer's Disease (AD) are not fully understood. Here, we describe a neural circuit mechanism underlying this resilience in a familial AD mouse model. In the prodromal disease stage, interictal epileptiform spikes (IESs) emerge during anesthesia in the CA1 and mPFC regions, leading to working memory disruptions. These IESs are driven by inputs from the thalamic nucleus reuniens (nRE). Indeed, tonic deep brain stimulation of the nRE (tDBS-nRE) effectively suppresses IESs and restores firing rate homeostasis under anesthesia, preventing further impairments in nRE-CA1 synaptic facilitation and working memory. Notably, applying tDBS-nRE during the prodromal phase in young APP/PS1 mice mitigates age-dependent memory decline. The IES rate during anesthesia in young APP/PS1 mice correlates with later working memory impairments. These findings highlight the nRE as a central hub of functional resilience and underscore the clinical promise of DBS in conferring resilience to AD pathology by restoring circuit-level homeostasis.

Amyloid and tau-PET in early-onset AD: Baseline data from the Longitudinal Early-onset Alzheimer's Disease Study (LEADS)

INTRODUCTION

We aimed to describe baseline amyloid-beta (Aβ) and tau-positron emission tomograrphy (PET) from Longitudinal Early-onset Alzheimer's Disease Study (LEADS), a prospective multi-site observational study of sporadic early-onset Alzheimer's disease (EOAD).

METHODS

We analyzed baseline [18F]Florbetaben (Aβ) and [18F]Flortaucipir (tau)-PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aβ+) from EOnonAD (Aβ-) based on the combination of visual read by expert reader and image quantification.

RESULTS

243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid-PET; 231 (95.1%) of them were tau-PET positive (A+T+). Tau-PET signal was elevated across cortical regions with a parietal-predominant pattern, and higher burden was observed in younger and female EOAD participants.

DISCUSSION

LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau-PET binding at baseline might have implications for therapeutic strategies in patients with EOAD.

HIGHLIGHTS

72% of patients with clinical EOAD were positive on both amyloid- and tau-PET. Amyloid-positive patients with EOAD had high tau-PET signal across cortical regions. In EOAD, tau-PET mediated the relationship between amyloid-PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau-PET.

Transcript-Level In Silico Analysis of Alzheimer's Disease-Related Gene Biomarkers and Their Evaluation with Bioactive Flavonoids to Explore Therapeutic Interactions

Alzheimer's disease (AD) is a progressive brain disorder that can significantly affect the quality of life. We used a variety of in silico tools to investigate the transcript-level mutational impact of exonic missense rare variations (single nucleotide polymorphisms, SNPs) on protein function and to identify potential druggable protein cavities that correspond to potential therapeutic targets for the management of AD. According to the NIA-AA (National Institute on Aging-Alzheimer's Association) framework, we selected three AD biomarker genes (APP, NEFL, and MAPT). We systematically screened transcript-level exonic rare SNPs from these genes with a minor allele frequency of 1% in 1KGD (1000 Genomes Project Database) and gnomAD (Genome Aggregation Database). With downstream functional effect predictions, a single variation (rs182024939: K > N) of the MAPT gene with nine transcript SNPs was identified as the most pathogenic variation from the large dataset of mutations. The machine learning consensus classifier predictor categorized these transcript-level SNPs as the most deleterious variations, resulting in a large decrease in protein structural stability (ΔΔG kcal/mol). The bioactive flavonoid library was screened for drug-likeness and toxicity risk. Virtual screening of eligible flavonoids was performed using the MAPT protein. Identification of druggable protein-binding cavities showed VAL305, GLU655, and LYS657 as consensus-interacting residues present in the MAPT-docked top-ranked flavonoid compounds. The MM/PB(GB)SA analysis indicated hesperetin (-5.64 kcal/mol), eriodictyol (-5.63 kcal/mol), and sakuranetin (-5.60 kcal/mol) as the best docked flavonoids with the near-native binding pose. The findings of this study provide important insights into the potential of hesperetin as a promising flavonoid that can be utilized for further rational drug design and lead optimization to open new gateways in the field of AD therapeutics.

Identification ferroptosis-related hub genes and diagnostic model in Alzheimer's disease

Background

Ferroptosis is a newly defined form of programmed cell death and plays an important role in Alzheimer's disease (AD) pathology. This study aimed to integrate bioinformatics techniques to explore biomarkers to support the correlation between ferroptosis and AD. In addition, further investigation of ferroptosis-related biomarkers was conducted on the transcriptome characteristics in the asymptomatic AD (AsymAD).

Methods

The microarray datasets GSE118553, GSE132903, GSE33000, and GSE157239 on AD were downloaded from the GEO database. The list of ferroptosis-related genes was extracted from the FerrDb website. Differentially expressed genes (DEGs) were identified by R "limma" package and used to screen ferroptosis-related hub genes. The random forest algorithm was used to construct the diagnostic model through hub genes. The immune cell infiltration was also analyzed by CIBERSORTx. The miRNet and DGIdb database were used to identify microRNAs (miRNAs) and drugs which targeting hub genes.

Results

We identified 18 ferroptosis-related hub genes anomalously expressed in AD, and consistent expression trends had been observed in both AsymAD The random forest diagnosis model had good prediction results in both training set (AUC = 0.824) and validation set (AUC = 0.734). Immune cell infiltration was analyzed and the results showed that CD4+ T cells resting memory, macrophages M2 and neutrophils were significantly higher in AD. A significant correlation of hub genes with immune infiltration was observed, such as DDIT4 showed strong positive correlation with CD4+ T cells memory resting and AKR1C2 had positive correlation with Macrophages M2. Additionally, the microRNAs (miRNAs) and drugs which targeting hub genes were screened.

Conclusion

These results suggest that ferroptosis-related hub genes we screened played a part in the pathological progression of AD. We explored the potential of these genes as diagnostic markers and their relevance to immune cells which will help in understanding the development of AD. Targeting miRNAs and drugs provides new research clues for preventing the development of AD.

Estimating the prevalence of diagnosed Alzheimer disease in England across deprivation groups using electronic health records: a clinical practice research datalink study

OBJECTIVE

Estimate the prevalence of diagnosed Alzheimer's disease (AD) and early Alzheimer's disease (eAD) overall and stratified by age, sex and deprivation and combinations thereof in England on 1 January 2020.

DESIGN

Cross-sectional.

SETTING

Primary care electronic health record data, the Clinical Practice Research database linked with secondary care data, Hospital Episode Statistics (HES) and patient-level deprivation data, Index of Multiple Deprivation (IMD).

OUTCOME MEASURES

The prevalence per 100 000 of the population and corresponding 95% CIs for both diagnosed AD and eAD overall and stratified by covariates. Sensitivity analyses were conducted to assess the sensitivity of the population definition and look-back period.

RESULTS

There were 448 797 patients identified in the Clinical Practice Research Datalink that satisfied the study inclusion criteria and were eligible for HES and IMD linkage. For the main analysis of AD and eAD, 379 763 patients are eligible for inclusion in the denominator. This resulted in an estimated prevalence of diagnosed AD of 378.39 (95% CI, 359.36 to 398.44) per 100 000 and eAD of 292.81 (95% CI, 276.12 to 310.52) per 100 000. Prevalence estimates across main and sensitivity analyses for the entire AD study population were found to vary widely with estimates ranging from 137.48 (95% CI, 127.05 to 148.76) to 796.55 (95% CI, 768.77 to 825.33). There was significant variation in prevalence of diagnosed eAD when assessing the sensitivity with the look-back periods, as low as 120.54 (95% CI, 110.80 to 131.14) per 100 000, and as high as 519.01 (95% CI, 496.64 to 542.37) per 100 000.

CONCLUSIONS

The study found relatively consistent patterns of prevalence across both AD and eAD populations. Generally, the prevalence of diagnosed AD increased with age and increased with deprivation for each age category. Women had a higher prevalence than men. More granular levels of stratification reduced patient numbers and increased the uncertainty of point prevalence estimates. Despite this, the study found a relationship between deprivation and prevalence of AD.

The amyloid cascade hypothesis: an updated critical review

Results from recent clinical trials of antibodies that target amyloid-β (Aβ) for Alzheimer's disease have created excitement and have been heralded as corroboration of the amyloid cascade hypothesis. However, while Aβ may contribute to disease, genetic, clinical, imaging and biochemical data suggest a more complex aetiology. Here we review the history and weaknesses of the amyloid cascade hypothesis in view of the new evidence obtained from clinical trials of anti-amyloid antibodies. These trials indicate that the treatments have either no or uncertain clinical effect on cognition. Despite the importance of amyloid in the definition of Alzheimer's disease, we argue that the data point to Aβ playing a minor aetiological role. We also discuss data suggesting that the concerted activity of many pathogenic factors contribute to Alzheimer's disease and propose that evolving multi-factor disease models will better underpin the search for more effective strategies to treat the disease.

Nordic diet and its benefits in neurological function: a systematic review of observational and intervention studies

Introduction

Neurological disorders have been considered the major contributors to global long-term disability and lower quality of life. Lifestyle factors, such as dietary patterns, are increasingly recognized as important determinants of neurological function. Some dietary behaviors, such as Nordic diet (ND) were likely to have protective effects on brain function. However, an understanding of the effectiveness of the ND pattern to improve neurological function and brain health is not fully understood. We review the current evidence that supports the ND pattern in various aspects of neurological function and addresses both proven and less established mechanisms of action based on its food ingredients and biochemical compounds.

Methods

In this systematic review, PubMed, Web of Science, and Scopus databases were searched from inception to February 2023. Observational and intervention studies were included.

Results

Of the 627 screened studies, 5 observational studies (including three cohorts and two cross-sectional studies) and 3 intervention studies investigating the association between ND and neurological function. Observational studies investigated the association of ND with the following neurological functions: cognition, stroke, and neuropsychological function. Intervention studies investigated the effects of ND on cognition and depression.

Discussion

Despite the limited literature on ND and its association with neurological function, several aspects of ND may lead to some health benefits suggesting neuroprotective effects. The current state of knowledge attributes the possible effects of characteristic components of the ND to its antioxidant, anti-inflammatory, lipid-lowering, gut-brain-axis modulating, and ligand activities in cell signaling pathways. Based on existing evidence, the ND may be considered a recommended dietary approach for the improvement of neurological function and brain health.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/], identifier [CRD2023451117].

Promise and peril of claims-based dementia ascertainment in causal inference

Festa and colleagues highlight underrecognized factors that may bias research, policy, and population health strategies predicated upon claims-based ascertainment of Alzheimer’s Disease and Related Dementias within the United States.

Neuropathology-based APOE genetic risk score better quantifies Alzheimer's risk

INTRODUCTION

Apolipoprotein E (APOE) ε4-carrier status or ε4 allele count are included in analyses to account for the APOE genetic effect on Alzheimer's disease (AD); however, this does not account for protective effects of APOE ε2 or heterogeneous effect of ε2, ε3, and ε4 haplotypes.

METHODS

We leveraged results from an autopsy-confirmed AD study to generate a weighted risk score for APOE (APOE-npscore). We regressed cerebrospinal fluid (CSF) amyloid and tau biomarkers on APOE variables from the Wisconsin Registry for Alzheimer's Prevention (WRAP), Wisconsin Alzheimer's Disease Research Center (WADRC), and Alzheimer's Disease Neuroimaging Initiative (ADNI).

RESULTS

The APOE-npscore explained more variance and provided a better model fit for all three CSF measures than APOE ε4-carrier status and ε4 allele count. These findings were replicated in ADNI and observed in subsets of cognitively unimpaired (CU) participants.

DISCUSSION

The APOE-npscore reflects the genetic effect on neuropathology and provides an improved method to account for APOE in AD-related analyses.

How Many Alzheimer-Perusini's Atypical Forms Do We Still Have to Discover?

Alzheimer-Perusini's (AD) disease represents the most spread dementia around the world and constitutes a serious problem for public health. It was first described by the two physicians from whom it took its name. Nowadays, we have extensively expanded our knowledge about this disease. Starting from a merely clinical and histopathologic description, we have now reached better molecular comprehension. For instance, we passed from an old conceptualization of the disease based on plaques and tangles to a more modern vision of mixed proteinopathy in a one-to-one relationship with an alteration of specific glial and neuronal phenotypes. However, no disease-modifying therapies are yet available. It is likely that the only way to find a few "magic bullets" is to deepen this aspect more and more until we are able to draw up specific molecular profiles for single AD cases. This review reports the most recent classifications of AD atypical variants in order to summarize all the clinical evidence using several discrimina (for example, post mortem neurofibrillary tangle density, cerebral atrophy, or FDG-PET studies). The better defined four atypical forms are posterior cortical atrophy (PCA), logopenic variant of primary progressive aphasia (LvPPA), behavioral/dysexecutive variant and AD with corticobasal degeneration (CBS). Moreover, we discuss the usefulness of such classifications before outlining the molecular-genetic aspects focusing on microglial activity or, more generally, immune system control of neuroinflammation and neurodegeneration.

FDG-PET versus Amyloid-PET Imaging for Diagnosis and Response Evaluation in Alzheimer's Disease: Benefits and Pitfalls

In June 2021, the US Federal Drug and Food Administration (FDA) granted accelerated approval for the antibody aducanumab and, in January 2023, also for the antibody lecanemab, based on a perceived drug-induced removal of cerebral amyloid-beta as assessed by amyloid-PET and, in the case of lecanemab, also a presumption of limited clinical efficacy. Approval of the antibody donanemab is awaiting further data. However, published trial data indicate few, small and uncertain clinical benefits, below what is considered "clinically meaningful" and similar to the effect of conventional medication. Furthermore, a therapy-related decrease in the amyloid-PET signal may also reflect increased cell damage rather than simply "amyloid removal". This interpretation is more consistent with increased rates of amyloid-related imaging abnormalities and brain volume loss in treated patients, relative to placebo. We also challenge the current diagnostic criteria for AD based on amyloid-PET imaging biomarkers and recommend that future anti-AD therapy trials apply: (1) diagnosis of AD based on the co-occurrence of cognitive decline and decreased cerebral metabolism assessed by FDA-approved FDG-PET, (2) therapy efficacy determined by favorable effect on cognitive ability, cerebral metabolism by FDG-PET, and brain volumes by MRI, and (3) neuropathologic examination of all deaths occurring in these trials.

The Role of Clinical Assessment in the Era of Biomarkers

Hippocratic Medicine revolved around the three main principles of patient, disease, and physician and promoted the systematic observation of patients, rational reasoning, and interpretation of collected information. Although these remain the cardinal features of clinical assessment today, Medicine has evolved from a more physician-centered to a more patient-centered approach. Clinical assessment allows physicians to encounter, observe, evaluate, and connect with patients. This establishes the patient-physician relationship and facilitates a better understanding of the patient-disease relationship, as the ultimate goal is to diagnose, prognosticate, and treat. Biomarkers are at the core of the more disease-centered approach that is currently revolutionizing Medicine as they provide insight into the underlying disease pathomechanisms and biological changes. Genetic, biochemical, radiographic, and clinical biomarkers are currently used. Here, we define a seven-level theoretical construct for the utility of biomarkers in neurodegenerative diseases. Level 1-3 biomarkers are considered supportive of clinical assessment, capable of detecting susceptibility or risk factors, non-specific neurodegeneration or dysfunction, and/or changes at the individual level which help increase clinical diagnostic accuracy and confidence. Level 4-7 biomarkers have the potential to surpass the utility of clinical assessment through detection of early disease stages and prediction of underlying pathology. In neurodegenerative diseases, biomarkers can potentiate, but cannot substitute, clinical assessment. In this current era, aside from adding to the discovery, evaluation/validation, and implementation of more biomarkers, clinical assessment remains crucial to maintaining the personal, humanistic, and sociocultural aspects of patient care. We would argue that clinical assessment is a custom that should never go obsolete.

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

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

Towards a future where Alzheimer's disease pathology is stopped before the onset of dementia

Alzheimer's disease (AD) is a major healthcare challenge with no curative treatment at present. To address this challenge, we need a paradigm shift, where we focus on pre-dementia stages of AD. In this Perspective, we outline a strategy to move towards a future with personalized medicine for AD by preparing for and investing in effective and patient-orchestrated diagnosis, prediction and prevention of the dementia stage. While focusing on AD, this Perspective also discusses studies that do not specify the cause of dementia. Future personalized prevention strategies encompass multiple components, including tailored combinations of disease-modifying interventions and lifestyle. By empowering the public and patients to be more actively engaged in the management of their health and disease and by developing improved strategies for diagnosis, prediction and prevention, we can pave the way for a future with personalized medicine, in which AD pathology is stopped to prevent or delay the onset of dementia.

Neuroimaging in Alzheimer's Disease for Early Diagnosis: A Comprehensive Review

Alzheimer's disease (AD) is the most common cause of dementia in the elderly, affecting roughly half of those over the age of 85. We briefly discussed the risk factors, epidemiology, and treatment options for AD. The development of therapeutic therapies operating very early in the disease cascade has been spurred by the realization that the disease process begins at least a decade or more before the manifestation of symptoms. Thus, the clinical significance of early diagnosis was emphasized. Using various keywords, a literature search was carried out using PubMed and other databases. For inclusion, pertinent articles were chosen and reviewed. This article has reviewed different neuroimaging techniques that are considered advanced tools to aid in establishing a diagnosis and highlighted the advantages as well as disadvantages of those techniques. Besides, the prevalence of several in vivo biomarkers aided in discriminating affected individuals from healthy controls in the early stages of the disease. Each imaging method has its advantages and disadvantages, hence no single imaging approach can be the optimum modality for diagnosis. This article also commented on a better approach to using these techniques to increase the likelihood of an early diagnosis.

A 12-month randomised pilot trial of the Alzheimer's and music therapy study: a feasibility assessment of music therapy and physical activity in patients with mild-to-moderate Alzheimer's disease

BACKGROUND

The Alzheimer's and Music Therapy (ALMUTH) study is the first randomised controlled trial (RCT) design with 12 months of active non-pharmacological therapy (NPT) implementing music therapy (MT) and physical activity (PA) for participants with Alzheimer's disease (AD). The aim of the present article is to retrospectively examine the inclusion of mild-to-moderate Alzheimer's Disease patients into the main ALMUTH study protocol and to determine if continued inclusion of AD patients is warranted.

METHODS

The randomised pilot trial was conducted as a parallel three-arm RCT, reflecting the experimental design of the ALMUTH study. The trial was conducted in Bergen, Norway, and randomisation (1:1:1) was performed by an external researcher. The study was open label and the experimental design features two active NPTs: MT and PA, and a passive control (no intervention, CON) in Norwegian speaking patients with AD who still live at home and could provide informed consent. Sessions were offered once per week (up to 90 min) up to 40 sessions over 12 months. Baseline and follow-up tests included a full neuropsychological test battery and three magnetic resonance imaging (MRI) measurements (structural, functional, and diffusion weighted imaging). Feasibility outcomes were assessed and were determined as feasible if they met the target criteria.

RESULTS

Eighteen participants with a diagnosis of mild-to-moderate AD were screened, randomised, and tested once at baseline and once after 12-months. Participants were divided into three groups: MT (n = 6), PA (n = 6), and CON (n = 6). Results of the study revealed that the ALMUTH protocol in patients with AD was not feasible. The adherence to the study protocol was poor (50% attended sessions), with attrition and retention rates at 50%. The recruitment was costly and there were difficulties acquiring participants who met the inclusion criteria. Issues with study fidelity and problems raised by staff were taken into consideration for the updated study protocol. No adverse events were reported by the patients or their caregivers.

CONCLUSIONS

The pilot trial was not deemed feasible in patients with mild-to-moderate AD. To mitigate this, the ALMUTH study has expanded the recruitment criteria to include participants with milder forms of memory impairment (pre-AD) in addition to expanding the neuropsychological test battery. The ALMUTH study is currently ongoing through 2023.

TRIAL REGISTRATION

Norsk Forskningsråd (NFR) funded. Regional Committees for Medical and Health Research Ethics (REC-WEST: reference number 2018/206).

CLINICALTRIALS

gov: NCT03444181 (registered retrospectively 23 February 2018, https://clinicaltrials.gov/ct2/show/NCT03444181 ).

Rationale and design of the ABOARD project (A Personalized Medicine Approach for Alzheimer's Disease)

The key to stopping Alzheimer's disease (AD) lies in the pre-dementia stages, with the goal to stop AD before dementia has started. We present the rationale and design of the ABOARD (A Personalized Medicine Approach for Alzheimer's Disease) project, which aims to invest in personalized medicine for AD. ABOARD is a Dutch public-private partnership of 32 partners, connecting stakeholders from a scientific, clinical, and societal perspective. The 5-year project is structured into five work packages on (1) diagnosis, (2) prediction, (3) prevention, (4) patient-orchestrated care, and (5) communication and dissemination. ABOARD functions as a network organization in which professionals interact cross-sectorally. ABOARD has a strong junior training program "Juniors On Board." Project results are shared with society through multiple communication resources. By including relevant partners and involving citizens at risk, patients, and their care partners, ABOARD builds toward a future with personalized medicine for AD.

Highlights

ABOARD (A Personalized Medicine Approach for Alzheimer's Disease) is a public-private research project executed by 32 partners that functions as a network organization.Together, the project partners build toward a future with personalized medicine for Alzheimer's disease.Although ABOARD is a Dutch consortium, it has international relevance.ABOARD improves diagnosis, prediction, prevention, and patient-orchestrated care.