A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers

Neuropsychological Performance in Alzheimer's Disease versus Late-Life Depression: A Systematic Review and Meta-Analysis

OBJECTIVE

Despite decades of research, neuropsychological tests (NPTs) that clearly differentiate between Alzheimer's disease (AD) and late-life depression (LLD) have yet to be agreed upon. Given this gap in knowledge and the rapid deployment of disease-modifying drugs for the two disorders, accurate clinical diagnosis using evidence-based assessment is essential. This study aims to systematically examine the literature to identify NPTs that would be able to differentiate AD and LLD.

METHOD

Databases and bibliographies were searched to identify articles for analysis. Two major inclusion criteria were that the studies compared neuropsychological functioning of AD versus LLD using normed NPTs and provided data for effect size calculation. Risk of bias was minimized by having independent coders for all steps in the review.

RESULTS

Forty-one studies met inclusion criteria (N = 2,797) and provided effect sizes for tests that were classified as belonging to 15 domains of functioning. The two groups were well differentiated by tasks of delayed contextual verbal memory as compared to immediate or non-contextual memory, recognition cueing, confrontation naming, visuospatial construction, and conceptualization. Specific NPTs that appear to be useful for differential diagnosis include the Rey Auditory Verbal Learning Test-Delayed Recognition; Boston Naming Test; the Dementia Rating Scale's memory, conceptualization, and construction subscales; and the CERAD Constructional Praxis.

CONCLUSIONS

The NPTs highlighted in this systematic review could be used as a relatively simple and cost-effective method to differentiate between patients with cognitive dysfunction due to AD versus LLD.

Identification of preclinical dementia according to ATN classification for stratified trial recruitment: A machine learning approach

INTRODUCTION

The Amyloid/Tau/Neurodegeneration (ATN) framework was proposed to identify the preclinical biological state of Alzheimer's disease (AD). We investigated whether ATN phenotype can be predicted using routinely collected research cohort data.

METHODS

927 EPAD LCS cohort participants free of dementia or Mild Cognitive Impairment were separated into 5 ATN categories. We used machine learning (ML) methods to identify a set of significant features separating each neurodegeneration-related group from controls (A-T-(N)-). Random Forest and linear-kernel SVM with stratified 5-fold cross validations were used to optimize model whose performance was then tested in the ADNI database.

RESULTS

Our optimal results outperformed ATN cross-validated logistic regression models by between 2.2% and 8.3%. The optimal feature sets were not consistent across the 4 models with the AD pathologic change vs controls set differing the most from the rest. Because of that we have identified a subset of 10 features that yield results very close or identical to the optimal.

DISCUSSION

Our study demonstrates the gains offered by ML in generating ATN risk prediction over logistic regression models among pre-dementia individuals.

Current Challenges in the Diagnosis of Progressive Neurocognitive Disorders: A Critical Review of the Literature and Recommendations for Primary and Secondary Care

Screening for early symptoms of cognitive impairment enables timely interventions for patients and their families. Despite the advances in dementia diagnosis, the current nosography of neurocognitive disorders (NCDs) seems to overlook some clinical manifestations and predictors that could contribute to understanding the conversion from an asymptomatic stage to a very mild one, eventually leading to obvious disease. The present review examines different diagnostic approaches in view of neurophysiological and neuropsychological evidence of NCD progression, which may be subdivided into: (1) preclinical stage; (2) transitional stage; (3) prodromal or mild stage; (4) major NCD. The absence of univocal criteria and the adoption of ambiguous or narrow labels might complicate the diagnostic process. In particular, it should be noted that: (1) only neuropathological hallmarks characterize preclinical NCD; (2) transitional NCD must be assessed through proactive neuropsychological protocols; (3) prodromal/mild NCDs are based on cognitive functional indicators; (4) major NCD requires well-established tools to evaluate its severity stage; (5) insight should be accounted for by both patient and informants. Therefore, the examination of evolving epidemiological and clinical features occurring at each NCD stage may orient primary and secondary care, allowing for more targeted prevention, diagnosis, and/or treatment of both cognitive and functional impairment.

Association of Chronic Pain with Biomarkers of Neurodegeneration, Microglial Activation, and Inflammation in Cerebrospinal Fluid and Impaired Cognitive Function

OBJECTIVE

Debate surrounds the role of chronic pain as a risk factor for cognitive decline and dementia. This study aimed at examining the association of chronic pain with biomarkers of neurodegeneration using data from the Alzheimer's Disease Neuroimaging Initiative.

METHODS

Participants were classified using the ATN (amyloid, tau, neurodegeneration) classification. Chronic pain was defined as persistent or recurrent pain reported at baseline. For each ATN group, analysis of covariance models identified differences in cerebrospinal fluid (CSF) levels of amyloid β1-42 , phosphorylated tau 181 (ptau181 ), total tau (t-tau), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), and cognitive function between chronic pain states. Differences in CSF levels of inflammatory markers between chronic pain states were further analyzed. Linear mixed effect models examined longitudinal changes.

RESULTS

The study included 995 individuals, with 605 (60.81%) reporting chronic pain at baseline. At baseline, individuals with suspected non-Alzheimer pathophysiology and chronic pain showed increased CSF levels of t-tau and sTREM2. Chronic pain was associated with increased tumor necrosis factor α levels, irrespective of the ATN group. Longitudinally, an increase in ptau181 CSF levels was observed in chronic pain patients with negative amyloid and neurodegeneration markers. Amyloid-positive and neurodegeneration-negative chronic pain patients showed higher memory function cross-sectionally. No significant longitudinal decline in cognitive function was observed for any ATN group.

INTERPRETATION

Our study suggests that chronic pain induces neuronal damage and microglial activation in particular subgroups of patients along the AD spectrum. Further studies are needed to confirm these findings. ANN NEUROL 2023.

Assessment of brain-derived extracellular vesicle enrichment for blood biomarker analysis in age-related neurodegenerative diseases: An international overview

INTRODUCTION

Brain-derived extracellular vesicles (BEVs) in blood allows for minimally- invasive investigations of CNS-specific markers of age-related neurodegenerative diseases (NDDs). Polymer-based EV- and immunoprecipitation (IP)-based BEV-enrichment protocols from blood have gained popularity. We systematically investigated protocol consistency across studies, and determined CNS-specificity of proteins associated with these protocols.

METHODS

NDD articles investigating BEVs in blood using polymer-based and/or IP-based BEV enrichment protocols were systematically identified, and protocols compared. Proteins used for BEV-enrichment and/or post-enrichment were assessed for CNS- and brain-cell-type- specificity; extracellular domains (ECD+); and presence in EV-databases.

RESULTS

82.1% of studies used polymer-based (ExoQuick) EV-enrichment, and 92.3% used L1CAM for IP-based BEV-enrichment. Centrifugation times differed across studies. 26.8% of 82 proteins systematically identified were CNS-specific: 50% ECD+, 77.3% were listed in EV- databases.

DISCUSSION

We identified protocol steps requiring standardization, and recommend additional CNS-specific proteins that can be used for BEV-enrichment or as BEV-biomarkers.

Accuracy of plasma Aβ40, Aβ42, and p-tau181 to detect CSF Alzheimer's pathological changes in cognitively unimpaired subjects using the Lumipulse automated platform

BACKGROUND

The arrival of new disease-modifying treatments for Alzheimer's disease (AD) requires the identification of subjects at risk in a simple, inexpensive, and non-invasive way. With tools allowing an adequate screening, it would be possible to optimize the use of these treatments. Plasma markers of AD are very promising, but it is necessary to prove that alterations in their levels are related to alterations in gold standard markers such as cerebrospinal fluid or PET imaging. With this research, we want to evaluate the performance of plasma Aβ40, Aβ42, and p-tau181 to detect the pathological changes in CSF using the automated Lumipulse platform.

METHODS

Both plasma and CSF Aβ40, Aβ42, and p-tau181 have been evaluated in a group of 208 cognitively unimpaired subjects with a 30.3% of ApoE4 carriers. We have correlated plasma and CSF values of each biomarker. Then, we have also assessed the differences in plasma marker values according to amyloid status (A - / +), AD status (considering AD + subjects to those A + plus Tau +), and ATN group defined by CSF. Finally, ROC curves have been performed, and the area under the curve has been measured using amyloid status and AD status as an outcome and different combinations of plasma markers as predictors.

RESULTS

Aβ42, amyloid ratio, p-tau181, and p-tau181/Aβ42 ratio correlated significantly between plasma and CSF. For these markers, the levels were significantly different in the A + / - , AD + / - , and ATN groups. Amyloid ratio predicts amyloid and AD pathology in CSF with an AUC of 0.89.

CONCLUSIONS

Plasma biomarkers of AD using the automated Lumipulse platform show good diagnostic performance in detecting Alzheimer's pathology in cognitively unimpaired subjects.

Clinical trials of new drugs for Alzheimer disease: a 2020-2023 update

Alzheimer's disease (AD) is the leading cause of dementia, presenting a significant unmet medical need worldwide. The pathogenesis of AD involves various pathophysiological events, including the accumulation of amyloid and tau, neuro-inflammation, and neuronal injury. Clinical trials focusing on new drugs for AD were documented in 2020, but subsequent developments have emerged since then. Notably, the US-FDA has approved Aducanumab and Lecanemab, both antibodies targeting amyloid, marking the end of a nearly two-decade period without new AD drugs. In this comprehensive report, we review all trials listed in clinicaltrials.gov, elucidating their underlying mechanisms and study designs. Ongoing clinical trials are investigating numerous promising new drugs for AD. The main trends in these trials involve pathophysiology-based, disease-modifying therapies and the recruitment of participants in earlier stages of the disease. These trends underscore the significance of conducting fundamental research on pathophysiology, prevention, and intervention prior to the occurrence of brain damage caused by AD.

Plasma ATN(I) classification and precision pharmacology in Alzheimer's disease

Evaluating potential therapies for Alzheimer's disease (AD) depends on use of biomarkers for appropriate subject selection and monitoring disease progression. Biomarkers that predict onset of clinical symptoms are particularly important for AD because they enable intervention before irreversible neurodegeneration occurs. The amyloid-β-tau-neurodegeneration (ATN) classification system is currently used as a biological staging model for AD and is based on three classes of biomarkers evaluating amyloid-β (Aβ), tau pathology and neurodegeneration or neuronal injury. Promising blood-based biomarkers for each of these categories have been identified (Aβ42/Aβ40 ratio, phosphorylated tau, neurofilament light chain), and this matrix is now being expanded toward an ATN(I) system, where "I" represents a neuroinflammatory biomarker. The plasma ATN(I) system, together with APOE genotyping, offers a basis for individualized evaluation and a move away from the classic "one size fits all" approach toward a biomarker-driven individualisation of therapy for patients with AD.

The "when" matters: Evidence from memory markers in the clinical continuum of Alzheimer's disease

OBJECTIVE

Cognitive assessment able to detect impairments in the early neuropathological stages of Alzheimer's disease (AD) is urgently needed. The visual short-term memory binding task (VSTMBT) and the Free and Cued Selective Reminding Test (FCSRT) have been recommended by the neurodegenerative disease working group as promising tests to aid in the early detection of AD. In this study, we investigated their complementary value across the clinical stages of the AD continuum.

METHOD

One hundred and seventeen older adults with subjective cognitive complaint (SCC), 79 with mild cognitive impairment (MCI), 31 patients with AD dementia (ADD), and 37 cognitively unimpaired (CU) subjects, underwent assessment with the VSTMBT and the picture version of the Spanish FCSRT.

RESULTS

After controlling for multiple comparisons, significant differences were found across groups. The VSTMBT was the only test that "marginally" differentiated between CU and SCC (d = 0.47, p = .052). Moreover, whereas the FCSRT showed a gradient (CU = SCC) > MCI > ADD, the VSTMBT gradient was CU > SCC > (MCI = ADD) suggesting that conjunctive binding deficits assessed by the latter may be sensitive to the very early stages of the disease.

CONCLUSIONS

Our results suggest that the VSTMBT and the FCSRT are sensitive to the clinical continuum of AD. Whereas the former detects changes in the early prodromal stages, the latter is more sensitive to the advanced prodromal stages of AD. These novel tests can aid in the early detection, monitor disease progression and response to treatment, and thus support drug development programs. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The use of neuroimaging techniques in the early and differential diagnosis of dementia

Dementia is a leading cause of disability and death worldwide. At present there is no disease modifying treatment for any of the most common types of dementia such as Alzheimer's disease (AD), Vascular dementia, Lewy Body Dementia (LBD) and Frontotemporal dementia (FTD). Early and accurate diagnosis of dementia subtype is critical to improving clinical care and developing better treatments. Structural and molecular imaging has contributed to a better understanding of the pathophysiology of neurodegenerative dementias and is increasingly being adopted into clinical practice for early and accurate diagnosis. In this review we summarise the contribution imaging has made with particular focus on multimodal magnetic resonance imaging (MRI) and positron emission tomography imaging (PET). Structural MRI is widely used in clinical practice and can help exclude reversible causes of memory problems but has relatively low sensitivity for the early and differential diagnosis of dementia subtypes. 18F-fluorodeoxyglucose PET has high sensitivity and specificity for AD and FTD, while PET with ligands for amyloid and tau can improve the differential diagnosis of AD and non-AD dementias, including recognition at prodromal stages. Dopaminergic imaging can assist with the diagnosis of LBD. The lack of a validated tracer for α-synuclein or TAR DNA-binding protein 43 (TDP-43) imaging remain notable gaps, though work is ongoing. Emerging PET tracers such as 11C-UCB-J for synaptic imaging may be sensitive early markers but overall larger longitudinal multi-centre cross diagnostic imaging studies are needed.

[Parkinson's and Alzheimer's disease as system-wide neurodegenerative disorders]

BACKGROUND

Parkinson's and Alzheimer's disease (PD/AD) are characterized by cellular pathological changes that precede clinical manifestation and symptom onset by decades (prodromal period) as well as by a heterogeneity of clinical symptoms. Both diseases are recognized as system-wide diseases with organ-transgressing dysregulation and involvement of immunological and neuroinflammatory mechanisms facilitating pathological protein aggregation and neurodegeneration.

OBJECTIVES

Overview of natural course, phenotypes and classification of PD/AD with a focus on underlying (system-wide) immunological and neuroinflammatory mechanisms.

METHODS

Literature research and consideration of expert opinions.

RESULTS

The accumulation of misfolded proteins such as amyloid‑β and synuclein in the course of neurodegenerative processes forms the basis of the current biological classifications, understanding of course and subtypes. Protein aggregation in PD/AD induces an innate immune response by activating microglia and the release of inflammatory mediators such as cytokines and chemokines and leading to further spread of neurodegeneration and accumulation of intracellular neurofibrillary tangles (NFTs). There is also growing evidence that adaptive immune responses involving auto-antibodies or auto-antigen-specific T‑/B-cell reactions involving tau, amyloid‑β or synuclein might be involved in the disease progression or subtypes of PD/AD.

CONCLUSIONS

Both innate and adaptive immune responses seem to be substantially involved in the pathological cascade leading to neurodegeneration in PD/AD and may contribute to disease progression and clinical subtypes. Thus, future targeted interventions should not only focus on protein aggregation but also on neuroinflammatory and immunological mechanisms.

Cross-sectional and longitudinal evaluation of plasma glial fibrillary acidic protein to detect and predict clinical syndromes of Alzheimer's disease

Introduction

This study examined plasma glial fibrillary acidic protein (GFAP) as a biomarker of cognitive impairment due to Alzheimer's disease (AD) with and against plasma neurofilament light chain (NfL), and phosphorylated tau (p-tau)181+231.

Methods

Plasma samples were analyzed using Simoa platform for 567 participants spanning the AD continuum. Cognitive diagnosis, neuropsychological testing, and dementia severity were examined for cross-sectional and longitudinal outcomes.

Results

Plasma GFAP discriminated AD dementia from normal cognition (adjusted mean difference = 0.90 standard deviation [SD]) and mild cognitive impairment (adjusted mean difference = 0.72 SD), and demonstrated superior discrimination compared to alternative plasma biomarkers. Higher GFAP was associated with worse dementia severity and worse performance on 11 of 12 neuropsychological tests. Longitudinally, GFAP predicted decline in memory, but did not predict conversion to mild cognitive impairment or dementia.

Discussion

Plasma GFAP was associated with clinical outcomes related to suspected AD and could be of assistance in a plasma biomarker panel to detect in vivo AD.

MRI-based Deep Learning Assessment of Amyloid, Tau, and Neurodegeneration Biomarker Status across the Alzheimer Disease Spectrum

Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disease, but incurs considerable cost and exposure to ionizing radiation. MRI currently has limited use in characterizing ATN status. Deep learning techniques can detect complex patterns in MRI data and have potential for noninvasive characterization of ATN status. Purpose To use deep learning to predict PET-determined ATN biomarker status using MRI and readily available diagnostic data. Materials and Methods MRI and PET data were retrospectively collected from the Alzheimer's Disease Imaging Initiative. PET scans were paired with MRI scans acquired within 30 days, from August 2005 to September 2020. Pairs were randomly split into subsets as follows: 70% for training, 10% for validation, and 20% for final testing. A bimodal Gaussian mixture model was used to threshold PET scans into positive and negative labels. MRI data were fed into a convolutional neural network to generate imaging features. These features were combined in a logistic regression model with patient demographics, APOE gene status, cognitive scores, hippocampal volumes, and clinical diagnoses to classify each ATN biomarker component as positive or negative. Area under the receiver operating characteristic curve (AUC) analysis was used for model evaluation. Feature importance was derived from model coefficients and gradients. Results There were 2099 amyloid (mean patient age, 75 years ± 10 [SD]; 1110 male), 557 tau (mean patient age, 75 years ± 7; 280 male), and 2768 FDG PET (mean patient age, 75 years ± 7; 1645 male) and MRI pairs. Model AUCs for the test set were as follows: amyloid, 0.79 (95% CI: 0.74, 0.83); tau, 0.73 (95% CI: 0.58, 0.86); and neurodegeneration, 0.86 (95% CI: 0.83, 0.89). Within the networks, high gradients were present in key temporal, parietal, frontal, and occipital cortical regions. Model coefficients for cognitive scores, hippocampal volumes, and APOE status were highest. Conclusion A deep learning algorithm predicted each component of PET-determined ATN status with acceptable to excellent efficacy using MRI and other available diagnostic data. © RSNA, 2023 Supplemental material is available for this article.

How to 19F MRI: applications, technique, and getting started

Magnetic resonance imaging (MRI) plays a significant role in the routine imaging workflow, providing both anatomical and functional information. 19F MRI is an evolving imaging modality where instead of 1H, 19F nuclei are excited. As the signal from endogenous 19F in the body is negligible, exogenous 19F signals obtained by 19F radiofrequency coils are exceptionally specific. Highly fluorinated agents targeting particular biological processes (i.e., the presence of immune cells) have been visualised using 19F MRI, highlighting its potential for non-invasive and longitudinal molecular imaging. This article aims to provide both a broad overview of the various applications of 19F MRI, with cancer imaging as a focus, as well as a practical guide to 19F imaging. We will discuss the essential elements of a 19F system and address common pitfalls during acquisition. Last but not least, we will highlight future perspectives that will enhance the role of this modality. While not an exhaustive exploration of all 19F literature, we endeavour to encapsulate the broad themes of the field and introduce the world of 19F molecular imaging to newcomers. 19F MRI bridges several domains, imaging, physics, chemistry, and biology, necessitating multidisciplinary teams to be able to harness this technology effectively. As further technical developments allow for greater sensitivity, we envision that 19F MRI can help unlock insight into biological processes non-invasively and longitudinally.

Clinical, imaging, and biomarker evidence of amyloid- and tau-related neurodegeneration in late-onset epilepsy of unknown etiology

Accumulating evidence suggests amyloid and tau-related neurodegeneration may play a role in development of late-onset epilepsy of unknown etiology (LOEU). In this article, we review recent evidence that epilepsy may be an initial manifestation of an amyloidopathy or tauopathy that precedes development of Alzheimer's disease (AD). Patients with LOEU demonstrate an increased risk of cognitive decline, and patients with AD have increased prevalence of preceding epilepsy. Moreover, investigations of LOEU that use CSF biomarkers and imaging techniques have identified preclinical neurodegeneration with evidence of amyloid and tau deposition. Overall, findings to date suggest a relationship between acquired, non-lesional late-onset epilepsy and amyloid and tau-related neurodegeneration, which supports that preclinical or prodromal AD is a distinct etiology of late-onset epilepsy. We propose criteria for assessing elevated risk of developing dementia in patients with late-onset epilepsy utilizing clinical features, available imaging techniques, and biomarker measurements. Further research is needed to validate these criteria and assess optimal treatment strategies for patients with probable epileptic preclinical AD and epileptic prodromal AD.

Cryo-EM structure of Alzheimer's disease tau filaments with PET ligand MK-6240

Positron Emission Tomography (PET) ligands have advanced Alzheimer's disease (AD) diagnosis and treatment. Using autoradiography and cryo-EM, we identified AD brain tissue with elevated tau burden, purified filaments, and determined the structure of second-generation high avidity PET ligand MK-6240 at 2.31 Å resolution, which bound at a 1:1 ratio within the cleft of tau paired-helical filament (PHF), engaging with glutamine 351, lysine K353, and isoleucine 360. This information elucidates the basis of MK-6240 PET in quantifying PHF deposits in AD and may facilitate the structure-based design of superior ligands against tau amyloids.

Blood-based biomarkers for Alzheimer's disease: Current state and future use in a transformed global healthcare landscape

Timely detection of the pathophysiological changes and cognitive impairment caused by Alzheimer's disease (AD) is increasingly pressing because of the advent of biomarker-guided targeted therapies that may be most effective when provided early in the disease. Currently, diagnosis and management of early AD are largely guided by clinical symptoms. FDA-approved neuroimaging and cerebrospinal fluid biomarkers can aid detection and diagnosis, but the clinical implementation of these testing modalities is limited because of availability, cost, and perceived invasiveness. Blood-based biomarkers (BBBMs) may enable earlier and faster diagnoses as well as aid in risk assessment, early detection, prognosis, and management. Herein, we review data on BBBMs that are closest to clinical implementation, particularly those based on measures of amyloid-β peptides and phosphorylated tau species. We discuss key parameters and considerations for the development and potential deployment of these BBBMs under different contexts of use and highlight challenges at the methodological, clinical, and regulatory levels.

Prebiotic inulin enhances gut microbial metabolism and anti-inflammation in apolipoprotein E4 mice with sex-specific implications

Gut dysbiosis has been identified as a crucial factor of Alzheimer's disease (AD) development for apolipoprotein E4 (APOE4) carriers. Inulin has shown the potential to mitigate dysbiosis. However, it remains unclear whether the dietary response varies depending on sex. In the study, we fed 4-month-old APOE4 mice with inulin for 16 weeks and performed shotgun metagenomic sequencing to determine changes in microbiome diversity, taxonomy, and functional gene pathways. We also formed the same experiments with APOE3 mice to identify whether there are APOE-genotype dependent responses to inulin. We found that APOE4 female mice fed with inulin had restored alpha diversity, significantly reduced Escherichia coli and inflammation-associated pathway responses. However, compared with APOE4 male mice, they had less metabolic responses, including the levels of short-chain fatty acids-producing bacteria and the associated kinases, especially those related to acetate and Erysipelotrichaceae. These diet- and sex- effects were less pronounced in the APOE3 mice, indicating that different APOE variants also play a significant role. The findings provide insights into the higher susceptibility of APOE4 females to AD, potentially due to inefficient energy production, and imply the importance of considering precision nutrition for mitigating dysbiosis and AD risk in the future.

Amyloid-Beta Co-Pathology Is a Major Determinant of the Elevated Plasma GFAP Values in Amyotrophic Lateral Sclerosis

Recent studies reported increased plasma glial acidic fibrillary protein (GFAP) levels in amyotrophic lateral sclerosis (ALS) patients compared to controls. We expanded these findings in a larger cohort, including 156 ALS patients and 48 controls, and investigated the associations of plasma GFAP with clinical variables and other biofluid biomarkers. Plasma GFAP and Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers were assessed by the single molecule array and the Lumipulse platforms, respectively. In ALS patients, plasma GFAP was higher than in controls (p < 0.001) and associated with measures of cognitive decline. Twenty ALS patients (12.8%) showed a positive amyloid status (A+), of which nine also exhibited tau pathology (A+T+, namely ALS-AD). ALS-AD patients showed higher plasma GFAP than A- ALS participants (p < 0.001) and controls (p < 0.001), whereas the comparison between A- ALS and controls missed statistical significance (p = 0.07). Plasma GFAP distinguished ALS-AD subjects more accurately (area under the curve (AUC) 0.932 ± 0.027) than plasma p-tau181 (AUC 0.692 ± 0.058, p < 0.0001) and plasma neurofilament light chain protein (AUC, 0.548 ± 0.088, p < 0.0001). Cognitive measures differed between ALS-AD and other ALS patients. AD co-pathology deeply affects plasma GFAP values in ALS patients. Plasma GFAP is an accurate biomarker for identifying AD co-pathology in ALS, which can influence the cognitive phenotype.

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

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

Secondary neurodegeneration following Stroke: what can blood biomarkers tell us?

Stroke is one of the leading causes of death and the primary source of disability in adults, resulting in neuronal necrosis of ischemic areas, and in possible secondary degeneration of regions surrounding or distant to the initial damaged area. Secondary neurodegeneration (SNDG) following stroke has been shown to have different pathogenetic origins including inflammation, neurovascular response and cytotoxicity, but can be associated also to regenerative processes. Aside from focal neuronal loss, ipsilateral and contralateral effects distal to the lesion site, disruptions of global functional connectivity and a transcallosal diaschisis have been reported in the chronic stages after stroke. Furthermore, SNDG can be observed in different areas not directly connected to the primary lesion, such as thalamus, hippocampus, amygdala, substantia nigra, corpus callosum, bilateral inferior fronto-occipital fasciculus and superior longitudinal fasciculus, which can be highlighted by neuroimaging techniques. Although the clinical relevance of SNDG following stroke has not been well understood, the identification of specific biomarkers that reflect the brain response to the damage, is of paramount importance to investigate in vivo the different phases of stroke. Actually, brain-derived markers, particularly neurofilament light chain, tau protein, S100b, in post-stroke patients have yielded promising results. This review focuses on cerebral morphological modifications occurring after a stroke, on associated cellular and molecular changes and on state-of-the-art of biomarkers in acute and chronic phase. Finally, we discuss new perspectives regarding the implementation of blood-based biomarkers in clinical practice to improve the rehabilitation approaches and post stroke recovery.

Insulin resistance and body mass index are associated with TSPO PET in cognitively unimpaired elderly

Metabolic risk factors are associated with peripheral low-grade inflammation and an increased risk for dementia. We evaluated if metabolic risk factors i.e. insulin resistance, body mass index (BMI), serum cholesterol values, or high sensitivity C-reactive protein associate with central inflammation or beta-amyloid (Aβ) accumulation in the brain, and if these associations are modulated by APOE4 gene dose. Altogether 60 cognitively unimpaired individuals (mean age 67.7 years (SD 4.7); 63% women; 21 APOE3/3, 20 APOE3/4 and 19 APOE4/4) underwent positron emission tomography with [11C]PK11195 targeting TSPO (18 kDa translocator protein) and [11C]PIB targeting fibrillar Aβ. [11C]PK11195 distribution value ratios and [11C]PIB standardized uptake values were calculated in a cortical composite region of interest typical for Aβ accumulation in Alzheimer's disease. Associations between metabolic risk factors, [11C]PK11195, and [11C]PIB uptake were evaluated with linear models adjusted for age and sex. Higher logarithmic HOMA-IR (standardized beta 0.40, p = 0.002) and BMI (standardized beta 0.27, p = 0.048) were associated with higher TSPO availability. Voxel-wise analyses indicated that this association was mainly seen in the parietal cortex. Higher logarithmic HOMA-IR was associated with higher [11C]PIB (standardized beta 0.44, p = 0.02), but only in APOE4/4 homozygotes. BMI and HOMA-IR seem to influence TSPO availability in the brain.

Biomarker disclosure protocols in prodromal Alzheimer's disease clinical trials

INTRODUCTION

The development of biomarkers for Alzheimer's disease (AD) has allowed researchers to increase sample homogeneity and test candidate treatments earlier in the disease. The integration of biomarker "screening" criteria should be met with a parallel implementation of standardized methods to disclose biomarker testing results to research participants; however, the extent to which protocolized disclosure occurs in trials is unknown.

METHODS

We reviewed the literature to identify prodromal AD trials published in the past 10 years. From these, we quantified the frequency of biomarker disclosure reporting and the depth of descriptions provided.

RESULTS

Of 30 published trials using positron emission tomography or cerebrospinal fluid-based amyloid positivity as an eligibility criterion, only one mentioned disclosure, with no details on methods.

DISCUSSION

Possible reasons for and implications of this information gap are discussed. Recommendations are provided for trialists considering biomarker screening as part of intervention trials focused on prodromal AD.

HIGHLIGHTS

Few prodromal Alzheimer's disease (AD) trial papers discuss biomarker disclosure. Disclosure has implications for participants, family members, and trial success. Disclosure must be consistently integrated and reported in prodromal AD trials. Best practice guidelines and training resources for disclosure are needed.

Cross-sectional associations of CSF tau levels with Rey's AVLT: A recency ratio study

OBJECTIVE

The preeminent in vivo cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are amyloid β 1-42 (Aβ42), phosphorylated Tau (p-tau), and total Tau (t-tau). The goal of this study was to examine how well traditional (total and delayed recall) and process-based (recency ratio [Rr]) measures derived from Rey's Auditory Verbal Learning test (AVLT) were associated with these biomarkers.

METHOD

Data from 235 participants (Mage = 65.5, SD = 6.9), who ranged from cognitively unimpaired to mild cognitive impairment, and for whom CSF values were available, were extracted from the Wisconsin Registry for Alzheimer's Prevention. Bayesian regression analyses were carried out using CSF scores as outcomes, AVLT scores as predictors, and controlling for demographic data and diagnosis.

RESULTS

We found moderate evidence that Rr was associated with both CSF p-tau (Bayesian factor [BFM] = 5.55) and t-tau (BFM = 7.28), above and beyond the control variables, while it did not correlate with CSF Aβ42 levels. In contrast, total and delayed recall scores were not linked with any of the AD biomarkers, in separate analyses. When comparing all memory predictors in a single regression, Rr remained the strongest predictor of CSF t-tau levels (BFM = 3.57).

CONCLUSIONS

Our findings suggest that Rr may be a better cognitive measure than commonly used AVLT scores to assess CSF levels of p-tau and t-tau in nondemented individuals. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Blood-based biomarkers for Alzheimer's disease: a multicenter-based cross-sectional and longitudinal study in China

Discrepancies in diagnostic biomarkers for Alzheimer's Disease (AD) may arise from racial disparities, risk factors, or lifestyle differences. Moreover, there has been a lack of systematic and multicenter studies to evaluate baselines of the AD biomarkers in Chinese populations. Thus, there is an urgent need for research to investigate the effectiveness of blood biomarkers for AD, specifically in the Chinese Han population, using a multicenter approach. In the present multicenter-based cross-sectional and longitudinal study, we evaluated 817 blood samples from 6 different clinical centers. We measured plasma amyloid beta (Aβ)-40, Aβ42, phosphorylated tau 181 (pTau), total tau (tTau), serum neurofilament light (NFL), and glial fibrillary acidic protein (GFAP). Additionally, 18F-florbetapir positron electron tomography and magnetic resonance imaging were also performed. A combination of the APOE genotype with plasma pTau and serum GFAP demonstrated exceptional performance in distinguishing Aβ status. Furthermore, baseline GFAP levels exhibited a strong association with cognitive decline over time and brain atrophy, with higher GFAP levels predicting a faster rate of neurodegeneration. In summary, these results validate the practicality of blood biomarkers in the Chinese Han population, encompassing various regions within China. Additionally, they emphasize the potential of pTau and GFAP as non-invasive methods for detecting and screening AD at an early stage.

A Continuous Extension of Gene Set Enrichment Analysis using the Likelihood Ratio Test Statistics Identifies VEGF as a Candidate Pathway for Alzheimer's disease

Background

Alzheimer's disease involves brain pathologies such as amyloid plaque depositions and hyperphosphorylated tau tangles and is accompanied by cognitive decline. Identifying the biological mechanisms underlying disease onset and progression based on quantifiable phenotypes will help understand the disease etiology and devise therapies.

Objective

Our objective was to identify molecular pathways associated with AD biomarkers (Amyloid-β and tau) and cognitive status (MMSE) accounting for variables such as age, sex, education, and APOE genotype.

Methods

We introduce a novel pathway-based statistical approach, extending the gene set likelihood ratio test to continuous phenotypes. We first analyzed independently each of the three phenotypes (Amyloid-β, tau, cognition), using continuous gene set likelihood ratio tests to account for covariates, including age, sex, education, and APOE genotype. The analysis involved a large sample size with data available for all three phenotypes, allowing for the identification of common pathways.

Results

We identified 14 pathways significantly associated with Amyloid-β, 5 associated with tau, and 174 associated with MMSE. Surprisingly, the MMSE outcome showed a larger number of significant pathways compared to biomarkers. A single pathway, vascular endothelial growth factor receptor binding (VEGF-RB), exhibited significant associations with all three phenotypes.

Conclusions

The study's findings highlight the importance of the VEGF signaling pathway in aging in AD. The complex interactions within the VEGF signaling family offer valuable insights for future therapeutic interventions.

Digit Ratio (2D:4D) Is Not Associated with Alzheimer's Disease in the Elderly

The development of Alzheimer's disease (AD) is influenced by sex hormones-estrogens and androgens in particular. However, the impact of prenatal sex hormone exposure is less clear; very few investigations have examined the relationship between the second-to-fourth digit length ratio (2D:4D), a putative proxy for the ratio of prenatal estrogens to androgens, and AD, with inconsistent results among the few that have. Therefore, we aimed to investigate this relationship using methodologically robust metrics. In a 2 (sex) × 4 (group) MANOVA incorporating 108 participants (30 AD patients, 19 patients with tauopathy but no amyloidopathy, 31 clinical and 28 healthy age- and education-matched controls), the effects of sex and group on the dependent variables right and left 2D:4D were examined. We also explored the association between 2D:4D and the severity of AD symptoms assessed via neuropsychological examination. We did not find any significant differences in the right- and left-hand 2D:4D between patients with AD and the other groups; no significant associations between 2D:4D and neuropsychological task performances were found in the dementia groups. The 2D:4D of healthy women was significantly lower than that of depressed women without AD, i.e., clinical controls, but not significantly different from depressed female patients with AD. This investigation does not support the role of 2D:4D in the development or severity of AD in general, but suggests a potential role of 2D:4D for depression in women. Future studies are warranted to clarify whether 2D:4D can distinguish between early- and late-onset depression in women.

Prospective association of general anesthesia with risk of cognitive decline in a Chinese elderly community population

As life expectancy increases and the population grows, the number of surgeries performed each year is likely to continue to increase. We evaluated whether surgery with general anesthesia increases risk for cognitive impairment in a Chinese elderly community population. The current data was obtained from the China Longitudinal Aging Study (cohort 1) and Shanghai Brain Aging study (cohort 2). Cohort 1 included 1545 elderly people with normal cognitive function, who underwent a screening process that included physical examination, medical history, baseline and 1-year follow-up assessments of cognitive function by a face-to-face interview. Cohort 2 included an additional 194 elderly people with normal cognitive function, all of whom, unlike cohort 1, underwent T1-phase MR imaging scans. In cohort 1, 127 elderly people with normal cognitive function transformed into mild cognitive impairment, 27 into dementia, while 1391 still maintained normal cognitive function. By using Cox regression analysis, we found that surgery with general anesthesia was a risk factor for cognitive impairment (p = 0.013, HR = 1.506, 95% CI 1.091-2.078); In cohort 2, we found that elderly people with a history of surgery with general anesthesia had lower Montreal Cognitive Assessment (MoCA) scores and smaller right amygdala volume (p < 0.05). Through correlation analysis, we found that the volume of the right amygdala was significantly correlated (p = 0.003, r = 0.212) with MoCA. Then by using the linear regression analysis (mediation model), we found that surgery with general anesthesia directly affected the MoCA score by affecting the volume of the right amygdala (B = 1.315, p = 0.036 95% CI 0.088-2.542). We confirm surgery with general anesthesia as a risk factor for cognitive impairment, and its mechanism may be related to its effect on the volume of the right amygdala.

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.

Semantic intrusion errors are associated with plasma Ptau-181 among persons with amnestic mild cognitive impairment who are amyloid positive

Introduction

Semantic intrusion errors (SI) have distinguished between those with amnestic Mild Cognitive Impairment (aMCI) who are amyloid positive (A+) versus negative (A-) on positron emission tomography (PET).

Method

This study examines the association between SI and plasma - based biomarkers. One hundred and twenty-eight participants received SiMoA derived measures of plasma pTau-181, ratio of two amyloid-β peptide fragments (Aβ42/Aβ40), Neurofilament Light protein (NfL), Glial Fibrillary Acidic Protein (GFAP), ApoE genotyping, and amyloid PET imaging.

Results

The aMCI A+ (n = 42) group had a higher percentage of ApoE ɛ4 carriers, and greater levels of pTau-181 and SI, than Cognitively Unimpaired (CU) A- participants (n = 25). CU controls did not differ from aMCI A- (n = 61) on plasma biomarkers or ApoE genotype. Logistic regression indicated that ApoE ɛ4 positivity, pTau-181, and SI were independent differentiating predictors (Correct classification = 82.0%; Sensitivity = 71.4%; Specificity = 90.2%) in identifying A+ from A- aMCI cases.

Discussion

A combination of plasma biomarkers, ApoE positivity and SI had high specificity in identifying A+ from A- aMCI cases.

Protein disulfide isomerases as CSF biomarkers for the neuronal response to tau pathology

INTRODUCTION

Cerebrospinal fluid (CSF) biomarkers for specific cellular disease processes are lacking for tauopathies. In this translational study we aimed to identify CSF biomarkers reflecting early tau pathology-associated unfolded protein response (UPR) activation.

METHODS

We employed mass spectrometry proteomics and targeted immunoanalysis in a combination of biomarker discovery in primary mouse neurons in vitro and validation in patient CSF from two independent large multicentre cohorts (EMIF-AD MBD, n = 310; PRIDE, n = 771).

RESULTS

First, we identify members of the protein disulfide isomerase (PDI) family in the neuronal UPR-activated secretome and validate secretion upon tau aggregation in vitro. Next, we demonstrate that PDIA1 and PDIA3 levels correlate with total- and phosphorylated-tau levels in CSF. PDIA1 levels are increased in CSF from AD patients compared to controls and patients with tau-unrelated frontotemporal and Lewy body dementia (LBD).

HIGHLIGHTS

Neuronal unfolded protein response (UPR) activation induces the secretion of protein disulfide isomerases (PDIs) in vitro. PDIA1 is secreted upon tau aggregation in neurons in vitro. PDIA1 and PDIA3 levels correlate with total and phosphorylated tau levels in CSF. PDIA1 levels are increased in CSF from Alzheimer's disease (AD) patients compared to controls. PDIA1 levels are not increased in CSF from tau-unrelated frontotemporal dementia (FTD) and Lewy body dementia (LBD) patients.

The association between personality and plasma biomarkers of astrogliosis and neuronal injury

Personality traits have been associated with the risk of dementia and Alzheimer's disease neuropathology, including amyloid and tau. This study examines whether personality traits are concurrently related to plasma glial fibrillary acidic protein (GFAP), a marker of astrogliosis, and neurofilament light (NfL), a marker of neuronal injury. Cognitively unimpaired participants from the Baltimore Longitudinal Study on Aging (N = 786; age: 22-95) were assayed for plasma GFAP and NfL and completed the Revised NEO Personality Inventory, which measures 5 domains and 30 facets of personality. Neuroticism (particularly vulnerability to stress, anxiety, and depression) was associated with higher GFAP and NfL. Conscientiousness was associated with lower GFAP. Extraversion (particularly positive emotions, assertiveness, and activity) was related to lower GFAP and NfL. These associations were independent of demographic, behavioral, and health covariates and not moderated by age, sex, or apolipoprotein E genotype. The personality correlates of astrogliosis and neuronal injury tend to be similar, are found in individuals without cognitive impairment, and point to potential neurobiological underpinnings of the association between personality traits and neurodegenerative diseases.

Cortical microstructural changes predict tau accumulation and episodic memory decline in older adults harboring amyloid

INTRODUCTION

Non-invasive diffusion-weighted imaging (DWI) to assess brain microstructural changes via cortical mean diffusivity (cMD) has been shown to be cross-sectionally associated with tau in cognitively normal older adults, suggesting that it might be an early marker of neuronal injury. Here, we investigated how regional cortical microstructural changes measured by cMD are related to the longitudinal accumulation of regional tau as well as to episodic memory decline in cognitively normal individuals harboring amyloid pathology.

METHODS

122 cognitively normal participants from the Harvard Aging Brain Study underwent DWI, T1w-MRI, amyloid and tau PET imaging, and Logical Memory Delayed Recall (LMDR) assessments. We assessed whether the interaction of baseline amyloid status and cMD (in entorhinal and inferior-temporal cortices) was associated with longitudinal regional tau accumulation and with longitudinal LMDR using separate linear mixed-effects models.

RESULTS

We find a significant interaction effect of the amyloid status and baseline cMD in predicting longitudinal tau in the entorhinal cortex (p = 0.044) but not the inferior temporal lobe, such that greater baseline cMD values predicts the accumulation of entorhinal tau in amyloid-positive participants. Moreover, we find a significant interaction effect of the amyloid status and baseline cMD in the entorhinal cortex (but not inferior temporal cMD) in predicting longitudinal LMDR (p < 0.001), such that baseline entorhinal cMD predicts the episodic memory decline in amyloid-positive participants.

CONCLUSIONS

The combination of amyloidosis and elevated cMD in the entorhinal cortex may help identify individuals at short-term risk of tau accumulation and Alzheimer's Disease-related episodic memory decline, suggesting utility in clinical trials.

CSF MTBR-tau243 is a specific biomarker of tau tangle pathology in Alzheimer's disease

Aggregated insoluble tau is one of two defining features of Alzheimer's disease. Because clinical symptoms are strongly correlated with tau aggregates, drug development and clinical diagnosis need cost-effective and accessible specific fluid biomarkers of tau aggregates; however, recent studies suggest that the fluid biomarkers currently available cannot specifically track tau aggregates. We show that the microtubule-binding region (MTBR) of tau containing the residue 243 (MTBR-tau243) is a new cerebrospinal fluid (CSF) biomarker specific for insoluble tau aggregates and compared it to multiple other phosphorylated tau measures (p-tau181, p-tau205, p-tau217 and p-tau231) in two independent cohorts (BioFINDER-2, n = 448; and Knight Alzheimer Disease Research Center, n = 219). MTBR-tau243 was most strongly associated with tau-positron emission tomography (PET) and cognition, whereas showing the lowest association with amyloid-PET. In combination with p-tau205, MTBR-tau243 explained most of the total variance in tau-PET burden (0.58 ≤ R2 ≤ 0.75) and the performance in predicting cognitive measures (0.34 ≤ R2 ≤ 0.48) approached that of tau-PET (0.44 ≤ R2 ≤ 0.52). MTBR-tau243 levels longitudinally increased with insoluble tau aggregates, unlike CSF p-tau species. CSF MTBR-tau243 is a specific biomarker of tau aggregate pathology, which may be utilized in interventional trials and in the diagnosis of patients. Based on these findings, we propose to revise the A/T/(N) criteria to include MTBR-tau243 as representing insoluble tau aggregates ('T').

Computational neurosciences and quantitative systems pharmacology: a powerful combination for supporting drug development in neurodegenerative diseases

Successful clinical development of new therapeutic interventions is notoriously difficult, especially in neurodegenerative diseases, where predictive biomarkers are scarce and functional improvement is often based on patient's perception, captured by structured interviews. As a consequence, mechanistic modeling of the processes relevant to therapeutic interventions in CNS disorders has been lagging behind other disease indications, probably because of the perceived complexity of the brain. However in this report, we develop the argument that a combination of Computational Neurosciences and Quantitative Systems Pharmacology (QSP) modeling of molecular pathways is a powerful simulation tool to enhance the probability of successful drug development for neurodegenerative diseases. Computational Neurosciences aims to predict action potential dynamics and neuronal circuit activation that are ultimately linked to behavioral changes and clinically relevant functional outcomes. These processes can not only be affected by the disease state, but also by common genotype variants on neurotransmitter-related proteins and the psycho-active medications often prescribed in these patient populations. Quantitative Systems Pharmacology (QSP) modeling of molecular pathways allows to simulate key pathological drivers of dementia, such as protein aggregation and neuroinflammatory responses. They often impact neurotransmitter homeostasis and voltage-gated ion-channels or lead to mitochondrial dysfunction, ultimately leading to changes in action potential dynamics and clinical readouts. Combining these two modeling approaches can lead to better actionable understanding of the many non-linear pharmacodynamic processes active in the human diseased brain. Practical applications include a rational selection of the optimal doses in combination therapies, identification of subjects more likely to respond to treatment, a more balanced stratification of treatment arms in terms of comedications, disease status and common genotype variants and re-analysis of small clinical trials to uncover a possible clinical signal. Ultimately this will lead to a higher success rate of bringing new therapeutics to the right patient populations.

ATN profile classification across two independent prospective cohorts

BACKGROUND

The ATN model represents a research framework used to describe in subjects the presence or absence of Alzheimer's disease (AD) pathology through biomarkers. The aim of this study was to describe the prevalence of different ATN profiles using quantitative imaging biomarkers in two independent cohorts, and to evaluate the pertinence of ATN biomarkers to identify comparable populations across independent cohorts.

METHODS

A total of 172 subjects from the Geneva Memory Clinic and 113 volunteers from a study on healthy aging at the University Hospital of Zurich underwent amyloid (A) and tau (T) PET, as well as T1-weigthed MRI scans using site-specific protocols. Subjects were classified by cognition (cognitively unimpaired, CU, or impaired, CI) based on clinical assessment by experts. Amyloid data converted into the standardized centiloid scale, tau PET data normalized to cerebellar uptake, and hippocampal volume expressed as a ratio over total intracranial volume ratio were considered as biomarkers for A, T, and neurodegeneration (N), respectively. Positivity for each biomarker was defined based on previously published thresholds. Subjects were then classified according to the ATN model. Differences among profiles were tested using Kruskal-Wallis ANOVA, and between cohorts using Wilcoxon tests.

RESULTS

Twenty-nine percent of subjects from the Geneva cohorts were classified with a normal (A-T-N-) profile, while the Zurich cohort included 64% of subjects in the same category. Meanwhile, 63% of the Geneva and 16% of the Zurich cohort were classified within the AD continuum (being A+ regardless of other biomarkers' statuses). Within cohorts, ATN profiles were significantly different for age and mini-mental state examination scores, but not for years of education. Age was not significantly different between cohorts. In general, imaging A and T biomarkers were significantly different between cohorts, but they were no longer significantly different when stratifying the cohorts by ATN profile. N was not significantly different between cohorts.

CONCLUSION

Stratifying subjects into ATN profiles provides comparable groups of subjects even when individual recruitment followed different criteria.

Quantification of race/ethnicity representation in Alzheimer's disease neuroimaging research in the USA: a systematic review

BACKGROUND

Racial and ethnic minoritized groups are disproportionately at risk for Alzheimer's Disease (AD), but are not sufficiently recruited in AD neuroimaging research in the United States. This is important as sample composition impacts generalizability of findings, biomarker cutoffs, and treatment effects. No studies have quantified the breadth of race/ethnicity representation in the AD literature.

METHODS

This review identified median race/ethnicity composition of AD neuroimaging US-based research samples available as free full-text articles on PubMed. Two types of published studies were analyzed: studies that directly report race/ethnicity data (i.e., direct studies), and studies that do not report race/ethnicity but used data from a cohort study/database that does report this information (i.e., indirect studies).

RESULTS

Direct studies (n = 719) have median representation of 88.9% white or 87.4% Non-Hispanic white, 7.3% Black/African American, and 3.4% Hispanic/Latino ethnicity, with 0% Asian American, Native Hawaiian/Pacific Islander, and American Indian/Alaska Native, Multiracial, and Other Race participants. Cohort studies/databases (n = 44) from which indirect studies (n = 1745) derived are more diverse, with median representation of 84.2% white, 83.7% Non-Hispanic white, 11.6% Black/African American, 4.7% Hispanic/Latino, and 1.75% Asian American participants. Notably, 94% of indirect studies derive from just 10 cohort studies/databases. Comparisons of two time periods using a median split for publication year, 1994-2017 and 2018-2022, indicate that sample diversity has improved recently, particularly for Black/African American participants (3.39% from 1994-2017 and 8.29% from 2018-2022).

CONCLUSIONS

There is still underrepresentation of all minoritized groups relative to Census data, especially for Hispanic/Latino and Asian American individuals. The AD neuroimaging literature will benefit from increased representative recruitment of ethnic/racial minorities. More transparent reporting of race/ethnicity data is needed.

Alzheimer's Disease and Green Tea: Epigallocatechin-3-Gallate as a Modulator of Inflammation and Oxidative Stress

Alzheimer's disease (AD) is the most common cause of dementia, characterised by a marked decline of both memory and cognition, along with pathophysiological hallmarks including amyloid beta peptide (Aβ) accumulation, tau protein hyperphosphorylation, neuronal loss and inflammation in the brain. Additionally, oxidative stress caused by an imbalance between free radicals and antioxidants is considered one of the main risk factors for AD, since it can result in protein, lipid and nucleic acid damage and exacerbate Aβ and tau pathology. To date, there is a lack of successful pharmacological approaches to cure or even ameliorate the terrible impact of this disease. Due to this, dietary compounds with antioxidative and anti-inflammatory properties acquire special relevance as potential therapeutic agents. In this context, green tea, and its main bioactive compound, epigallocatechin-3-gallate (EGCG), have been targeted as a plausible option for the modulation of AD. Specifically, EGCG acts as an antioxidant by regulating inflammatory processes involved in neurodegeneration such as ferroptosis and microglia-induced cytotoxicity and by inducing signalling pathways related to neuronal survival. Furthermore, it reduces tau hyperphosphorylation and aggregation and promotes the non-amyloidogenic route of APP processing, thus preventing the formation of Aβ and its subsequent accumulation. Taken together, these results suggest that EGCG may be a suitable candidate in the search for potential therapeutic compounds for neurodegenerative disorders involving inflammation and oxidative stress, including Alzheimer's disease.

Novel CSF tau biomarkers can be used for disease staging of sporadic Alzheimer's disease

Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic work-up of dementia in clinical practice and the design of clinical trials. Here, we created a staging model using the Subtype and Stage Inference (SuStaIn) algorithm by evaluating cerebrospinal fluid (CSF) amyloid-β (Aβ) and tau biomarkers in 426 participants from BioFINDER-2, that represent the entire spectrum of AD. The model composition and main analyses were replicated in 222 participants from the Knight ADRC cohort. SuStaIn revealed in the two cohorts that the data was best explained by a single biomarker sequence (one subtype), and that five CSF biomarkers (ordered: Aβ42/40, tau phosphorylation occupancies at the residues 217 and 205 [pT217/T217 and pT205/T205], microtubule-binding region of tau containing the residue 243 [MTBR-tau243], and total tau) were sufficient to create an accurate disease staging model. Increasing CSF stages (0-5) were associated with increased abnormality in other AD-related biomarkers, such as Aβ- and tau-PET, and aligned with different phases of longitudinal biomarker changes consistent with current models of AD progression. Higher CSF stages at baseline were associated with higher hazard ratio of clinical decline. Our findings indicate that a common pathophysiologic molecular pathway develops across all AD patients, and that a single CSF collection is sufficient to reliably indicate the presence of both AD pathologies and the degree and stage of disease progression.

Potential diagnostic value of CSF metabolism-related proteins across the Alzheimer's disease continuum

BACKGROUND

Alzheimer's disease (AD) cerebrospinal fluid (CSF) core biomarkers (Aβ42/40 ratio, p-tau, and t-tau) provide high diagnostic accuracy, even at the earliest stage of disease. However, these markers do not fully reflect the complex AD pathophysiology. Recent large scale CSF proteomic studies revealed several new AD candidate biomarkers related to metabolic pathways. In this study we measured the CSF levels of four metabolism-related proteins not directly linked to amyloid- and tau-pathways (i.e., pyruvate kinase, PKM; aldolase, ALDO; ubiquitin C-terminal hydrolase L1, UCHL1, and fatty acid-binding protein 3, FABP3) across the AD continuum. We aimed at validating the potential value of these proteins as new CSF biomarkers for AD and their possible involvement in AD pathogenesis, with specific interest on the preclinical phase of the disease.

METHODS

CSF PKM and ALDO activities were measured with specific enzyme assays while UCHL1 and FABP3 levels were measured with immunoassays in a cohort of patients composed as follows: preclinical AD (pre-AD, n = 19, cognitively unimpaired), mild cognitive impairment due to AD (MCI-AD, n = 50), dementia due to AD (ADdem, n = 45), and patients with frontotemporal dementia (FTD, n = 37). Individuals with MCI not due to AD (MCI, n = 30) and subjective cognitive decline (SCD, n = 52) with negative CSF AD-profile, were enrolled as control groups.

RESULTS

CSF UCHL1 and FABP3 levels, and PKM activity were significantly increased in AD patients, already at the pre-clinical stage. CSF PKM activity was also increased in FTD patients compared with control groups, being similar between AD and FTD patients. No difference was found in ALDO activity among the groups. UCHL1 showed good performance in discriminating early AD patients (pre-AD and MCI-AD) from controls (AUC ~ 0.83), as assessed by ROC analysis. Similar results were obtained for FABP3. Conversely, PKM provided the best performance when comparing FTD vs. MCI (AUC = 0.80). Combination of PKM, FABP3, and UCHL1 improved the diagnostic accuracy for the detection of patients within the AD continuum when compared with single biomarkers.

CONCLUSIONS

Our study confirmed the potential role of UCHL1 and FABP3 as neurodegenerative biomarkers for AD. Furthermore, our results validated the increase of PKM activity in CSF of AD patients, already at the preclinical phase of the disease. Increased PKM activity was observed also in FTD patients, possibly underlining similar alterations in energy metabolism in AD and FTD.

Precipitating Mechanisms of Falls in Preclinical Alzheimer's Disease

Background

Individuals with Alzheimer's disease (AD) are more than twice as likely to incur a serious fall as the general population of older adults. Although AD is commonly associated with cognitive changes, impairments in other clinical measures such as strength or functional mobility (i.e., gait and balance) may precede symptomatic cognitive impairment in preclinical AD and lead to increased fall risk.

Objective

To examine mechanisms (i.e., functional mobility, cognition, AD biomarkers) associated with increased falls in cognitively normal older adults.

Methods

This 1-year study was part of an ongoing longitudinal cohort study. We examined the relationships among falls, clinical measures of functional mobility and cognition, and neuroimaging AD biomarkers in cognitively normal older adults. We also investigated which domain(s) best predicted fall propensity and severity through multiple regression models.

Results

A total of 182 older adults were included (mean age 75 years, 53% female). A total of 227 falls were reported over the year; falls per person ranged from 0-16 with a median of 1. Measures of functional mobility were the best predictors of fall propensity and severity. Cognition and AD biomarkers were associated with each other but not with the fall outcome measures.

Conclusion

These results suggest that, although subtle changes in cognition may be more closely associated with AD neuropathology, functional mobility indicators better predict falls in cognitively normal older adults. This study adds to our understanding of the mechanisms underlying falls in older adults and could lead to the development of targeted fall prevention strategies.

Proteomics of brain, CSF, and plasma identifies molecular signatures for distinguishing sporadic and genetic Alzheimer's disease

Proteomic studies for Alzheimer's disease (AD) are instrumental in identifying AD pathways but often focus on single tissues and sporadic AD cases. Here, we present a proteomic study analyzing 1305 proteins in brain tissue, cerebrospinal fluid (CSF), and plasma from patients with sporadic AD, TREM2 risk variant carriers, patients with autosomal dominant AD (ADAD), and healthy individuals. We identified 8 brain, 40 CSF, and 9 plasma proteins that were altered in individuals with sporadic AD, and we replicated these findings in several external datasets. We identified a proteomic signature that differentiated TREM2 variant carriers from both individuals with sporadic AD and healthy individuals. The proteins associated with sporadic AD were also altered in patients with ADAD, but with a greater effect size. Brain-derived proteins associated with ADAD were also replicated in additional CSF samples. Enrichment analyses highlighted several pathways, including those implicated in AD (calcineurin and Apo E), Parkinson's disease (α-synuclein and LRRK2), and innate immune responses (SHC1, ERK-1, and SPP1). Our findings suggest that combined proteomics across brain tissue, CSF, and plasma can be used to identify markers for sporadic and genetically defined AD.

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.

Validating blood tests as a possible routine diagnostic assay of Alzheimer's disease

INTRODUCTION

In recent years, exciting developments in disease modifying treatments for Alzheimer's disease (AD) have made accurate and timely diagnosis of this disease a priority. Blood biomarkers (BBMs) for amyloid pathology using improved immunoassay and mass spectrometry techniques have been an area of intense research for the last 10 years and are coming to the fore, as a real prospect to be used in the clinical diagnostics of the disease.

AREAS COVERED

The following review will update and discuss blood biomarkers that will be most useful in diagnosing AD and the context necessary for their implementation.

EXPERT OPINION

It is clear we now have BBMs, and technology to measure them, that are capable of detecting amyloid pathology in AD. The challenge is to validate them across platforms and populations to incorporate them into clinical practice. It is important that implementation comes with education, we need to give clinicians the tools for appropriate use and interpretation. It is feasible that BBMs will be used to screen populations, initially for clinical trial entry but also therapeutic intervention in the foreseeable future. We now need to focus BBM research on other pathologies to ensure we accelerate the development of therapeutics for all neurodegenerative diseases.

Applying Joint Graph Embedding to Study Alzheimer's Neurodegeneration Patterns in Volumetric Data

Neurodegeneration measured through volumetry in MRI is recognized as a potential Alzheimer's Disease (AD) biomarker, but its utility is limited by lack of specificity. Quantifying spatial patterns of neurodegeneration on a whole brain scale rather than locally may help address this. In this work, we turn to network based analyses and extend a graph embedding algorithm to study morphometric connectivity from volume-change correlations measured with structural MRI on the timescale of years. We model our data with the multiple random eigengraphs framework, as well as modify and implement a multigraph embedding algorithm proposed earlier to estimate a low dimensional embedding of the networks. Our version of the algorithm guarantees meaningful finite-sample results and estimates maximum likelihood edge probabilities from population-specific network modes and subject-specific loadings. Furthermore, we propose and implement a novel statistical testing procedure to analyze group differences after accounting for confounders and locate significant structures during AD neurodegeneration. Family-wise error rate is controlled at 5% using permutation testing on the maximum statistic. We show that results from our analysis reveal networks dominated by known structures associated to AD neurodegeneration, indicating the framework has promise for studying AD. Furthermore, we find network-structure tuples that are not found with traditional methods in the field.

Tackling seizures in patients with Alzheimer's disease

INTRODUCTION

In past years, a possible bidirectional link between epilepsy and Alzheimer's disease (AD) has been proposed: if AD patients are more likely to develop epilepsy, people with late-onset epilepsy evidence an increased risk of dementia. Furthermore, current research suggested that subclinical epileptiform discharges may be more frequent in patients with AD and network hyperexcitability may hasten cognitive impairment.

AREAS COVERED

In this narrative review, the authors discuss the recent evidence linking AD and epilepsy as well as seizures semeiology and epileptiform activity observed in patients with AD. Finally, anti-seizure medications (ASMs) and therapeutic trials to tackle seizures and network hyperexcitability in this clinical scenario have been summarized.

EXPERT OPINION

There is growing experimental evidence demonstrating a strong connection between seizures, neuronal hyperexcitability, and AD. Epilepsy in AD has shown a good response to ASMs both at the late and prodromal stages. The new generation ASMs with fewer cognitive adverse effects seem to be a preferable option. Data on the possible effects of network hyperexcitability and ASMs on AD progression are still inconclusive. Further clinical trials are mandatory to identify clear guidelines about treatment of subclinical epileptiform discharges in patients with AD without seizures.

The importance of the dyad: Participant perspectives on sharing biomarker results in Alzheimer's disease research

BACKGROUND

In the asymptomatic "preclinical" phase of Alzheimer's disease (AD), abnormal biomarkers indicate risk for developing cognitive impairment. Biomarker information is increasingly being disclosed to participants in research settings, and biomarker testing and results disclosure will be implemented in clinical settings in the future. Biomarker disclosure has potential psychosocial benefits and harms, impacting affected individuals and their support person(s). Limited data are available about with whom research participants share their results, information that will be necessary to develop disclosure protocols and post-disclosure resources. Additionally, existing research has been conducted in largely White cohorts, limiting applicability to future clinical populations.

METHODS

We enrolled a diverse cohort of 329 adults (184 non-Hispanic White and 145 Black/African American individuals) who previously participated in AD research. After reviewing a vignette describing a hypothetical biomarker research study, participants indicated their anticipated willingness to share biomarker results with loved ones, and what reactions they anticipated from others. Using mixed-methods analysis, we identified responses related to willingness to share results.

RESULTS

A majority (78.7%) were willing to share their results with support persons. Many (59.6%) felt it would not be difficult to share, and most (90.6%) believed their loved ones would be supportive. The most common reasons for sharing were to prepare for possible future AD (41.0% of respondents), while the most common reason for not sharing was to avoid worrying loved ones (4.8% of respondents). A total of 7.3% of respondents related reasons regarding being unsure about sharing.

DISCUSSION

Participants' interest in sharing results supports integrating support persons into AD biomarker research, and may help maximize potential benefits for participants. Communicating with this "dyad" of research participant and support person(s) may improve involvement in research, and help prepare for implementation of clinical biomarker testing by clarifying communication preferences and the influence of support persons on psychosocial outcomes.

Plasma biomarkers for prediction of Alzheimer's disease neuropathologic change

While plasma biomarkers for Alzheimer's disease (AD) are increasingly being evaluated for clinical diagnosis and prognosis, few population-based autopsy studies have evaluated their utility in the context of predicting neuropathological changes. Our goal was to investigate the utility of clinically available plasma markers in predicting Braak staging, neuritic plaque score, Thal phase, and overall AD neuropathological change (ADNC).We utilized a population-based prospective study of 350 participants with autopsy and antemortem plasma biomarker testing using clinically available antibody assay (Quanterix) consisting of Aβ42/40 ratio, p-tau181, GFAP, and NfL. We utilized a variable selection procedure in cross-validated (CV) logistic regression models to identify the best set of plasma predictors along with demographic variables, and a subset of neuropsychological tests comprising the Mayo Clinic Preclinical Alzheimer Cognitive Composite (Mayo-PACC). ADNC was best predicted with plasma GFAP, NfL, p-tau181 biomarkers along with APOE ε4 carrier status and Mayo-PACC cognitive score (CV AUC = 0.798). Braak staging was best predicted using plasma GFAP, p-tau181, and cognitive scores (CV AUC = 0.774). Neuritic plaque score was best predicted using plasma Aβ42/40 ratio, p-tau181, GFAP, and NfL biomarkers (CV AUC = 0.770). Thal phase was best predicted using GFAP, NfL, p-tau181, APOE ε4 carrier status and Mayo-PACC cognitive score (CV AUC = 0.754). We found that GFAP and p-tau provided non-overlapping information on both neuritic plaque and Braak stage scores whereas Aβ42/40 and NfL were mainly useful for prediction of neuritic plaque scores. Separating participants by cognitive status improved predictive performance, particularly when plasma biomarkers were included. Plasma biomarkers can differentially inform about overall ADNC pathology, Braak staging, and neuritic plaque score when combined with demographics and cognitive variables and have significant utility for earlier detection of AD.