Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease

Alzheimer Disease Biomarkers: Moving from CSF to Plasma for Reliable Detection of Amyloid and tau Pathology

BACKGROUND

Development of validated biomarkers to detect early Alzheimer disease (AD) neuropathology is needed for therapeutic AD trials. Abnormal concentrations of "core" AD biomarkers, cerebrospinal fluid (CSF) amyloid beta1-42, total tau, and phosphorylated tau correlate well with neuroimaging biomarkers and autopsy findings. Nevertheless, given the limitations of established CSF and neuroimaging biomarkers, accelerated development of blood-based AD biomarkers is underway.

CONTENT

Here we describe the clinical significance of CSF and plasma AD biomarkers to detect disease pathology throughout the Alzheimer continuum and correlate with imaging biomarkers. Use of the AT(N) classification by CSF and imaging biomarkers provides a more objective biologically based diagnosis of AD than clinical diagnosis alone. Significant progress in measuring CSF AD biomarkers using extensively validated highly automated assay systems has facilitated their transition from research use only to approved in vitro diagnostics tests for clinical use. We summarize development of plasma AD biomarkers as screening tools for enrollment and monitoring participants in therapeutic trials and ultimately in clinical care. Finally, we discuss the challenges for AD biomarkers use in clinical trials and precision medicine, emphasizing the possible ethnocultural differences in the levels of AD biomarkers.

SUMMARY

CSF AD biomarker measurements using fully automated analytical platforms is possible. Building on this experience, validated blood-based biomarker tests are being implemented on highly automated immunoassay and mass spectrometry platforms. The progress made developing analytically and clinically validated plasma AD biomarkers within the AT(N) classification scheme can accelerate use of AD biomarkers in therapeutic trials and routine clinical practice.

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.

Translating blood biomarkers into clinical practice for Alzheimer's disease: Challenges and perspectives

Early and accurate diagnosis of Alzheimer's disease (AD) in clinical practice is urgent with advances in AD treatment. Blood biomarker assays are preferential diagnostic tools for widespread clinical use with the advantages of being less invasive, cost effective, and easily accessible, and they have shown good performance in research cohorts. However, in community-based populations with maximum heterogeneity, great challenges are still faced in diagnosing AD based on blood biomarkers in terms of accuracy and robustness. Here, we analyze these challenges, including the confounding impact of systemic and biological factors, small changes in blood biomarkers, and difficulty in detecting early changes. Furthermore, we provide perspectives on several potential strategies to overcome these challenges for blood biomarkers to bridge the gap from research to clinical practice.

Genetic propensity for cerebral amyloidosis and risk of mild cognitive impairment and Alzheimer's disease within a cognitive reserve framework

INTRODUCTION

We constructed a polygenic risk score (PRS) for β-amyloid (PRSAβ42) to proxy AD pathology and investigated its association with incident Alzheimer's disease (AD)/amnestic mild cognitive impairment (aMCI) and the influence of cognitive reserve (CR), proxied by educational years, on the relationship between PRSAβ42 and AD/aMCI risk.

METHODS

A total of 618 cognitive-normal participants were followed-up for 2.92 years. The association of PRSAβ42 and CR with AD/aMCI incidence was examined with COX models. Then we examined the additive interaction between PRSAβ42 and CR and the CR effect across participants with different PRSAβ42 levels.

RESULTS

Higher PRSAβ42 and CR were associated with a 33.9% higher risk and 8.3% less risk for AD/aMCI, respectively. An additive interaction between PRSAβ42 and CR was observed. High CR was associated with 62.6% less risk of AD/aMCI incidence only in the high-PRSAβ42 group.

DISCUSSION

A super-additive effect of PRSAβ42 and CR on AD/aMCI risk was observed. CR influence was evident in participants with high PRSAβ42.

CSF biomarker concordance with amyloid PET in Phase 3 studies of aducanumab

INTRODUCTION

We assessed the use of cerebrospinal fluid (CSF) biomarkers as an alternative to positron emission tomography (PET) for brain amyloid beta (Aβ) pathology confirmation in the EMERGE and ENGAGE clinical trials.

METHODS

EMERGE and ENGAGE were randomized, placebo-controlled, Phase 3 trials of aducanumab in participants with early Alzheimer's disease. Concordance between CSF biomarkers (Aβ42, Aβ40, phosphorylated tau 181, and total tau) and amyloid PET status (visual read) at screening was examined.

RESULTS

Robust concordance between CSF biomarkers and amyloid PET visual status was observed (for Aβ42/Aβ40, AUC: 0.90; 95% CI: 0.83-0.97; p < 0.0001), confirming CSF biomarkers as a reliable alternative to amyloid PET in these studies. Compared with single CSF biomarkers, CSF biomarker ratios showed better agreement with amyloid PET visual reads, demonstrating high diagnostic accuracy.

DISCUSSION

These analyses add to the growing body of evidence supporting CSF biomarkers as reliable alternatives to amyloid PET imaging for brain Aβ pathology confirmation.

HIGHLIGHTS

CSF biomarkers and amyloid PET concordance were assessed in Ph3 aducanumab trials. Robust concordance between CSF biomarkers and amyloid PET was observed. CSF biomarker ratios increased diagnostic accuracy over single CSF biomarkers. CSF Aβ42/Aβ40 demonstrated high concordance with amyloid PET. Results support CSF biomarker testing as a reliable alternative to amyloid PET.

Pharmacological Inhibition of Ferroptosis as a Therapeutic Target for Neurodegenerative Diseases and Strokes

Emerging evidence suggests that ferroptosis, a unique regulated cell death modality that is morphologically and mechanistically different from other forms of cell death, plays a vital role in the pathophysiological process of neurodegenerative diseases, and strokes. Accumulating evidence supports ferroptosis as a critical factor of neurodegenerative diseases and strokes, and pharmacological inhibition of ferroptosis as a therapeutic target for these diseases. In this review article, the core mechanisms of ferroptosis are overviewed and the roles of ferroptosis in neurodegenerative diseases and strokes are described. Finally, the emerging findings in treating neurodegenerative diseases and strokes through pharmacological inhibition of ferroptosis are described. This review demonstrates that pharmacological inhibition of ferroptosis by bioactive small-molecule compounds (ferroptosis inhibitors) could be effective for treatments of these diseases, and highlights a potential promising therapeutic avenue that could be used to prevent neurodegenerative diseases and strokes. This review article will shed light on developing novel therapeutic regimens by pharmacological inhibition of ferroptosis to slow down the progression of these diseases in the future.

Greater cognitive reserve is related to lower cortical excitability in healthy cognitive aging, but not in early clinical Alzheimer's disease

Objective

To investigate the relationship between cortico-motor excitability and cognitive reserve (CR) in cognitively unimpaired older adults (CU) and in older adults with mild cognitive impairment or mild dementia due to Alzheimer's disease (AD).

Methods

Data were collected and analyzed from 15 CU and 24 amyloid-positive AD participants aged 50-90 years. A cognitive reserve questionnaire score (CRQ) assessed education, occupation, leisure activities, physical activities, and social engagement. Cortical excitability was quantified as the average amplitude of motor evoked potentials (MEP amplitude) elicited with single-pulse transcranial magnetic stimulation delivered to primary motor cortex. A linear model compared MEP amplitudes between groups. A linear model tested for an effect of CRQ on MEP amplitude across all participants. Finally, separate linear models tested for an effect of CRQ on MEP amplitude within each group. Exploratory analyses tested for effect modification of demographics, cognitive scores, atrophy measures, and CSF measures within each group using nested regression analysis.

Results

There was no between-group difference in MEP amplitude after accounting for covariates. The primary model showed a significant interaction term of group*CRQ (R2adj = 0.18, p = 0.013), but no main effect of CRQ. Within the CU group, higher CRQ was significantly associated with lower MEP amplitude (R2adj = 0.45, p = 0.004). There was no association in the AD group.

Conclusion

Lower cortico-motor excitability is related to greater CRQ in CU, but not in AD. Lower MEP amplitudes may reflect greater neural efficiency in cognitively unimpaired older adults. The lack of association seen in AD participants may reflect disruption of the protective effects of CR. Future work is needed to better understand the neurophysiologic mechanisms leading to the protective effects of CR in older adults with and without neurodegenerative disorders.

Sensitive label-free detection of the biomarker phosphorylated tau-217 protein in Alzheimer's disease using a graphene-based solution-gated field effect transistor

Alzheimer's disease (AD) is generally diagnosed using advanced imaging, but recent research suggests early screening using biomarkers in peripheral blood is feasible; among them, plasma tau proteins phosphorylated at threonine 231, threonine 181, and threonine 217 (p-tau217) are potential targets. A recent study indicates that the p-tau217 protein is the most efficacious biomarker. However, a clinical study found a pg/ml threshold for AD screening beyond standard detection methods. A biosensor with high sensitivity and specificity p-tau217 detection has not yet been reported. In this study, we developed a label-free solution-gated field effect transistor (SGFET)-based biosensor featuring a graphene oxide/graphene (GO/G) layered composite. The top layer of bilayer graphene grown using chemical vapor deposition was functionalized with oxidative groups serving as active sites for forming covalent bonds with the biorecognition element (antibodies); the bottom G could act as a transducer to respond to the attachment of the target analytes onto the top GO conjugated with the biorecognition element via π-π interactions between the GO and G layers. With this unique atomically layered G composite, we obtained a good linear electrical response in the Dirac point shift to p-tau217 protein concentrations in the range of 10 fg/ml to 100 pg/ml. The biosensor exhibited a high sensitivity of 18.6 mV/decade with a high linearity of 0.991 in phosphate-buffered saline (PBS); in human serum albumin, it showed approximately 90% of the sensitivity (16.7 mV/decade) in PBS, demonstrating high specificity. High stability of the biosensor was also displayed in this study.

The Role of Iron Metabolism, Lipid Metabolism, and Redox Homeostasis in Alzheimer's Disease: from the Perspective of Ferroptosis

In the development of Alzheimer's disease (AD), cell death is common. Novel cell death form-ferroptosis is discovered in recent years. Ferroptosis is an iron-regulated programmed cell death mechanism and has been identified in AD clinical samples. Typical characteristics of ferroptosis involve the specific changes in cell morphology, iron-dependent aggregation of reactive oxygen species (ROS) and lipid peroxides, loss of glutathione (GSH), inactivation of glutathione peroxidase 4 (GPX4), and a unique group of regulatory genes. Increasing evidence demonstrates that ferroptosis may be associated with neurological dysfunction in AD. However, the underlying mechanisms have not been fully elucidated. This article reviews the potential role of ferroptosis in AD, the involvement of ferroptosis in the pathological progression of AD through the mechanisms of iron metabolism, lipid metabolism, and redox homeostasis, as well as a range of potential therapies targeting ferroptosis for AD. Intervention strategies based on ferroptosis are promising for Alzheimer's disease treatment at present, but further researches are still needed.

Blood biomarkers for Alzheimer's disease in clinical practice and trials

Blood-based biomarkers hold great promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD) in clinical practice. This is very timely, considering the recent development of anti-amyloid-β (Aβ) immunotherapies. Several assays for measuring phosphorylated tau (p-tau) in plasma exhibit high diagnostic accuracy in distinguishing AD from all other neurodegenerative diseases in patients with cognitive impairment. Prognostic models based on plasma p-tau levels can also predict future development of AD dementia in patients with mild cognitive complaints. The use of such high-performing plasma p-tau assays in the clinical practice of specialist memory clinics would reduce the need for more costly investigations involving cerebrospinal fluid samples or positron emission tomography. Indeed, blood-based biomarkers already facilitate identification of individuals with pre-symptomatic AD in the context of clinical trials. Longitudinal measurements of such biomarkers will also improve the detection of relevant disease-modifying effects of new drugs or lifestyle interventions.

Evaluating the feasibility of cognitive impairment detection in Alzheimer's disease screening using a computerized visual dynamic test

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disease without known cure. However, early medical treatment can help control its progression and postpone intellectual decay. Since AD is preceded by a period of cognitive deterioration, the effective assessment of cognitive capabilities is crucial to develop reliable screening procedures. For this purpose, cognitive tests are extensively used to evaluate cognitive areas such as language, attention, or memory.

METHODS

In this work, we analyzed the potential of a visual dynamics evaluation, the rapid serial visual presentation task (RSVP), for the detection of cognitive impairment in AD. We compared this evaluation with two of the most extended brief cognitive tests applied in Spain: the Clock-drawing test (CDT) and the Phototest. For this purpose, we assessed a group of patients (mild AD and mild cognitive impairment) and controls, and we evaluated the ability of the three tests for the discrimination of the two groups.

RESULTS

The preliminary results obtained suggest the RSVP performance is statistically higher for the controls than for the patients (p-value = 0.013). Furthermore, we obtained promising classification results for this test (mean accuracy of 0.91 with 95% confidence interval 0.72, 0.97).

CONCLUSIONS

Since the RSVP is a computerized, auto-scored, and potentially self-administered brief test, it could contribute to speeding-up cognitive impairment screening and to reducing the associated costs. Furthermore, this evaluation could be combined with other tests to augment the efficiency of cognitive impairment screening protocols and to potentially monitor patients under medical treatment.

Cortical microstructural associations with CSF amyloid and pTau

Diffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer's disease (AD) pathology. Few studies have evaluated multi-shell dMRI models, such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI, in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181 and Aβ1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8±6.2 years) from the Alzheimer's Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1-42 and higher pTau181 were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures were more widely associated with Aβ1-42 than pTau181 and better distinguished Aβ+ from Aβ- participants than pTau+/- participants. Conversely, cortical thickness was more tightly linked with pTau181. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI measures sensitive to early AD pathogenesis and microstructural damage may elucidate mechanisms underlying cognitive decline.

Basal forebrain activity predicts functional degeneration in the entorhinal cortex and decreases with Alzheimer's Disease progression

BACKGROUND AND OBJECTIVES

Recent models of Alzheimer's Disease (AD) suggest the nucleus basalis of Meynert (NbM) as the origin of structural degeneration followed by the entorhinal cortex (EC). However, the functional properties of NbM and EC regarding amyloid-β and hyperphosphorylated tau remain unclear.

METHODS

We analyzed resting-state (rs)fMRI data with CSF assays from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n=71) at baseline and two years later.

RESULTS

At baseline, local activity, as quantified by fractional amplitude of low-frequency fluctuations (fALFF), differentiated between normal and abnormal CSF groups in the NbM but not EC. Further, NbM activity linearly decreased as a function of CSF ratio, resembling the disease status. Finally, NbM activity predicted the annual percentage signal change in EC, but not the reverse, independent from CSF ratio.

DISCUSSION

Our findings give novel insights into the pathogenesis of AD by showing that local activity in NbM is affected by proteinopathology and predicts functional degeneration within the EC.

The association between white matter hyperintensities and amyloid and tau deposition

White matter hyperintensities (WMHs) frequently occur in Alzheimer's Disease (AD) and have a contribution from ischemia, though their relationship with β-amyloid and cardiovascular risk factors (CVRFs) is not completely understood. We used AT classification to categorize individuals based on their β-amyloid and tau pathologies, then assessed the effects of β-amyloid and tau on WMH volume and number. We then determined regions in which β-amyloid and WMH accumulation were related. Last, we analyzed the effects of various CVRFs on WMHs. As secondary analyses, we observed effects of age and sex differences, atrophy, cognitive scores, and APOE genotype. PET, MRI, FLAIR, demographic, and cardiovascular health data was collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI-3) (N = 287, 48 % male). Participants were categorized as A + and T + if their Florbetapir SUVR and Flortaucipir SUVR were above 0.79 and 1.25, respectively. WMHs were mapped on MRI using a deep convolutional neural network (Sepehrband et al., 2020). CVRF scores were based on history of hypertension, systolic and diastolic blood pressure, pulse rate, respiration rate, BMI, and a cumulative score with 6 being the maximum score. Regression models and Pearson correlations were used to test associations and correlations between variables, respectively, with age, sex, years of education, and scanner manufacturer as covariates of no interest. WMH volume percent was significantly associated with global β-amyloid (r = 0.28, p < 0.001), but not tau (r = 0.05, p = 0.25). WMH volume percent was higher in individuals with either A + or T + pathology compared to controls, particularly within in the A+/T + group (p = 0.007, Cohen's d = 0.4, t = -2.5). Individual CVRFs nor cumulative CVRF scores were associated with increased WMH volume. Finally, the regions where β-amyloid and WMH count were most positively associated were the middle temporal region in the right hemisphere (r = 0.18, p = 0.002) and the fusiform region in the left hemisphere (r = 0.017, p = 0.005). β-amyloid and WMH have a clear association, though the mechanism facilitating this association is still not fully understood. The associations found between β-amyloid and WMH burden emphasizes the relationship between β-amyloid and vascular lesion formation while factors like CVRFs, age, and sex affect AD development through various mechanisms. These findings highlight potential causes and mechanisms of AD as targets for future preventions and treatments. Going forward, a larger emphasis may be placed on β-amyloid's vascular effects and the implications of impaired brain clearance in AD.

Role of Tau in Various Tauopathies, Treatment Approaches, and Emerging Role of Nanotechnology in Neurodegenerative Disorders

A few protein kinases and phosphatases regulate tau protein phosphorylation and an imbalance in their enzyme activity results in tau hyper-phosphorylation. Aberrant tau phosphorylation causes tau to dissociate from the microtubules and clump together in the cytosol to form neurofibrillary tangles (NFTs), which lead to the progression of neurodegenerative disorders including Alzheimer's disease (AD) and other tauopathies. Hence, targeting hyperphosphorylated tau protein is a restorative approach for treating neurodegenerative tauopathies. The cyclin-dependent kinase (Cdk5) and the glycogen synthase kinase (GSK3β) have both been implicated in aberrant tau hyperphosphorylation. The limited transport of drugs through the blood-brain barrier (BBB) for reaching the central nervous system (CNS) thus represents a significant problem in the development of drugs. Drug delivery systems based on nanocarriers help solve this problem. In this review, we discuss the tau protein, regulation of tau phosphorylation and abnormal hyperphosphorylation, drugs in use or under clinical trials, and treatment strategies for tauopathies based on the critical role of tau hyperphosphorylation in the pathogenesis of the disease. Pathology of neurodegenerative disease due to hyperphosphorylation and various therapeutic approaches including nanotechnology for its treatment.

CSF Aβ42 and Aβ42/Aβ40 Ratio in Alzheimer's Disease and Frontotemporal Dementias

BACKGROUND

Alzheimer's disease dementia (ADD) may manifest with atypical phenotypes, resembling behavioral variant frontotemporal dementia (bvFTD) and corticobasal syndrome (CBS), phenotypes which typically have an underlying frontotemporal lobar degeneration with tau proteinopathy (FTLD-tau), such as Pick's disease, corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), or FTLD with TDP-43 proteinopathy (FTLD-TDP). CSF biomarkers total and phosphorylated tau (τ_T and τ_P-181), and amyloid beta with 42 and 40 amino acids (Aβ₄₂ and Aβ₄₀) are biomarkers of AD pathology. The primary aim of this study was to compare the diagnostic accuracy of Aβ₄₂ to Aβ₄₂/Aβ₄₀ ratio in: (a) differentiating ADD vs. frontotemporal dementias; (b) patients with AD pathology vs. non-AD pathologies; (c) compare biomarker ratios and composite markers to single CSF biomarkers in the differentiation of AD from FTD; Methods: In total, 263 subjects were included (ADD: n = 98; bvFTD: n = 49; PSP: n = 50; CBD: n = 45; controls: n = 21). CSF biomarkers were measured by commercially available ELISAs (EUROIMMUN). Multiple biomarker ratios (Aβ₄₂/Aβ₄₀; τ_T/τ_P-181; τ_T/Aβ₄₂; τ_P-181/Aβ₄₂) and composite markers (t-tau: τ_T/(Aβ₄₂/Aβ40); p-tau: τ_P-181/(Aβ₄₂/Aβ₄₀) were calculated. ROC curve analysis was performed to compare AUCs of Aβ₄₂ and Aβ₄₂/Aβ₄₀ ratio and relevant composite markers between ADD and FTD, as defined clinically. BIOMARKAPD/ABSI criteria (abnormal τ_T, τ_P-181 Aβ₄₂, and Aβ₄₂/Aβ₄₀ ratio) were used to re-classify all patients into AD pathology vs. non-AD pathologies, and ROC curve analysis was repeated to compare Aβ₄₂ and Aβ₄₂/Aβ₄₀; Results: Aβ₄₂ did not differ from Aβ₄₂/Aβ₄₀ ratio in the differentiation of ADD from FTD (AUCs 0.752 and 0.788 respectively; p = 0.212). The τ_T/Aβ₄₂ ratio provided maximal discrimination between ADD and FTD (AUC:0.893; sensitivity 88.8%, specificity 80%). BIOMARKAPD/ABSI criteria classified 60 patients as having AD pathology and 211 as non-AD. A total of 22 had discrepant results and were excluded. Aβ₄₂/Aβ₄₀ ratio was superior to Aβ₄₂ in the differentiation of AD pathology from non-AD pathology (AUCs: 0.939 and 0.831, respectively; p < 0.001). In general, biomarker ratios and composite markers were superior to single CSF biomarkers in both analyses.

CONCLUSIONS

Aβ₄₂/Aβ₄₀ ratio is superior to Aβ₄₂ in identifying AD pathology, irrespective of the clinical phenotype. CSF biomarker ratios and composite markers provide higher diagnostic accuracy compared to single CSF biomarkers.

Distinct spatiotemporal subtypes of amyloid deposition are associated with diverging disease profiles in cognitively normal and mild cognitive impairment individuals

We aimed to investigate the relationship between spatiotemporal changes of amyloid deposition and Alzheimer's disease (AD) profiles in cognitively normal (CN) and those with mild cognitive impairment (MCI). Using a data-driven method and amyloid-PET data, we identified and validated two subtypes in two independent datasets (discovery dataset: N = 548, age = 72.4 ± 6.78, 49% female; validation dataset: N = 348, age = 74.9 ± 8.16, 47% female) from the Alzheimer's Disease Neuroimaging Initiative across a range of individuals who were CN or had MCI. The two subtypes showed distinct regional progression patterns and presented distinct genetic, clinical and biomarker characteristics. The cortex-priority subtype was more likely to show typical clinical syndromes of symptomatic AD and vice versa. Furthermore, the regional progression patterns were associated with clinical and biomarker profiles. In sum, our findings suggest that the spatiotemporal variants of amyloid depositions are in close association with disease trajectories; these findings may provide insight into the disease monitoring and enrollment of therapeutic trials in AD.

Multimodality imaging of neurodegenerative disorders with a focus on multiparametric magnetic resonance and molecular imaging

Neurodegenerative diseases afflict a large number of persons worldwide, with the prevalence and incidence of dementia rapidly increasing. Despite their prevalence, clinical diagnosis of dementia syndromes remains imperfect with limited specificity. Conventional structural-based imaging techniques also lack the accuracy necessary for confident diagnosis. Multiparametric magnetic resonance imaging and molecular imaging provide the promise of improving specificity and sensitivity in the diagnosis of neurodegenerative disease as well as therapeutic monitoring of monoclonal antibody therapy. This educational review will briefly focus on the epidemiology, clinical presentation, and pathologic findings of common and uncommon neurodegenerative diseases. Imaging features of each disease spanning from conventional magnetic resonance sequences to advanced multiparametric methods such as resting-state functional magnetic resonance imaging and arterial spin labeling imaging will be described in detail. Additionally, the review will explore the findings of each diagnosis on molecular imaging including single-photon emission computed tomography and positron emission tomography with a variety of clinically used and experimental radiotracers. The literature and clinical cases provided demonstrate the power of advanced magnetic resonance imaging and molecular techniques in the diagnosis of neurodegenerative diseases and areas of future and ongoing research. With the advent of combined positron emission tomography/magnetic resonance imaging scanners, hybrid protocols utilizing both techniques are an attractive option for improving the evaluation of neurodegenerative diseases.

Diencephalic versus Hippocampal Amnesia in Alzheimer's Disease: The Possible Confabulation-Misidentification Phenotype

BACKGROUND

Alzheimer's disease (AD) is clinically heterogeneous, including the classical-amnesic (CA-) phenotype and some variants.

OBJECTIVE

We aim to describe a further presentation we (re)named confabulation-misidentification (CM-) phenotype.

METHODS

We performed a retrospective longitudinal case-series study of 17 AD outpatients with the possible CM-phenotype (CM-ADs). Then, in a cross-sectional study, we compared the CM-ADs to a sample of 30 AD patients with the CA-phenotype (CA-ADs). The primary outcome was the frequency of cognitive and behavioral features. Data were analyzed as differences in percentage by non-parametric Chi Square and mean differences by parametric T-test.

RESULTS

Anterograde amnesia (100%) with early confabulation (88.2%), disorientation (88.2%) and non-infrequently retrograde amnesia (64.7%) associated with reduced insight (88.2%), moderate prefrontal executive impairment (94.1%) and attention deficits (82.3%) dominated the CM-phenotype. Neuropsychiatric features with striking misidentification (52.9%), other less-structured delusions (70.6%), and brief hallucinations (64.7%) were present. Marked behavioral disturbances were present early in some patients and very common at later stages. At the baseline, the CM-ADs showed more confabulation (p < 0.001), temporal disorientation (p < 0.02), misidentification (p = 0.013), other delusions (p = 0.002), and logorrhea (p = 0.004) than the CA-ADs. In addition, more social disinhibition (p = 0.018), reduction of insight (p = 0.029), and hallucination (p = 0.03) persisted at 12 months from baseline. Both the CA- and CM-ADs showed anterior and medial temporal atrophy. Compared to HCs, the CM-ADs showed more right fronto-insular atrophy, while the CA-ADs showed more dorsal parietal, precuneus, and right parietal atrophy.

CONCLUSION

We described an AD phenotype resembling diencephalic rather than hippocampal amnesia and overlapping the past-century description of presbyophrenia.

The impact of sleep components, quality and patterns on glymphatic system functioning in healthy adults: A systematic review

OBJECTIVE

The glymphatic system is thought to be responsible for waste clearance in the brain. As it is primarily active during sleep, different components of sleep, subjective sleep quality, and sleep patterns may contribute to glymphatic functioning. This systematic review aimed at exploring the effect of sleep components, sleep quality, and sleep patterns on outcomes associated with the glymphatic system in healthy adults.

METHODS

PubMed®, Scopus, and Web of Science were searched for studies published in English until December 2021. Articles subjectively or objectively investigating sleep components (total sleep time, time in bed, sleep efficiency, sleep onset latency, wake-up after sleep onset, sleep stage, awakenings), sleep quality, or sleep pattern in healthy individuals, on outcomes associated with glymphatic system (levels of amyloid-β, tau, α-synuclein; cerebrospinal fluid, perivascular spaces; apolipoprotein E) were selected.

RESULTS

Out of 8359 records screened, 51 studies were included. Overall, contradictory findings were observed according to different sleep assessment method. The most frequently assessed sleep parameters were total sleep time, sleep quality, and sleep efficiency. No association was found between sleep efficiency and amyloid-β, and between slow-wave activity and tau. Most of the studies did not find any correlation between total sleep time and amyloid-β nor tau level. Opposing results correlated sleep quality with amyloid-β and tau.

CONCLUSIONS

This review highlighted inconsistent results across the studies; as such, the specific association between the glymphatic system and sleep parameters in healthy adults remains poorly understood. Due to the heterogeneity of sleep assessment methods and the self-reported data representing the majority of the observations, future studies with universal study design and sleep methodology in healthy individuals are advocated.

Clinical Biomarkers and Novel Drug Targets to Cut Gordian Knots of Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD), the primary cause of dementia, escalating worldwide, has no proper diagnosis or effective treatment. Neuronal cell death and impairment of cognitive abilities, possibly triggered by several brain mechanisms, are the most significant characteristic of this disorder.

METHODS

A multitude of pharmacological targets have been identified for potential drug design against AD. Although many advances in treatment strategies have been made to correct various abnormalities, these often exhibit limited clinical significance because this disease aggressively progresses into different regions of the brain, causing severe deterioration.

RESULTS

These biomarkers can be game-changers for early detection and timely monitoring of such disorders.

CONCLUSION

This review covers clinically significant biomarkers of AD for precise and early monitoring of risk factors and stages of this disease, the potential site of action and novel targets for drugs, and pharmacological approaches to clinical management.

Vascular endothelial-cadherin as a marker of endothelial injury in preclinical Alzheimer disease

OBJECTIVE

Endothelial dysfunction is an early and prevalent pathology in Alzheimer disease (AD). We here investigate the value of vascular endothelial-cadherin (VEC) as a cerebrospinal fluid (CSF) marker of endothelial injury in preclinical AD.

METHODS

Cognitively normal participants (Clinical Dementia Rating [CDR] 0) from the Knight Washington University-ADRC were included in this study (n = 700). Preclinical Alzheimer's Cognitive Composite (PACC) scores, CSF VEC, tau, p-tau181, Aβ42/Aβ40, neurofilament light-chain (NFL) levels, and magnetic resonance imaging (MRI) assessments of white matter injury (WMI) were obtained from all participants. A subset of participants underwent brain amyloid imaging using positron emission tomography (amyloid-PET) (n = 534). Linear regression examined associations of CSF VEC with PACC and individual cognitive scores in preclinical AD. Mediation analyses examined whether CSF VEC mediated effects of CSF amyloid and tau markers on cognition in preclinical AD.

RESULTS

CSF VEC levels significantly correlated with PACC and individual cognitive scores in participants with amyloid (A+T±N±; n = 558) or those with amyloid and tau pathologies (A+T+N±; n = 259), after adjusting for covariates. CSF VEC also correlated with CSF measures of amyloid, tau, and neurodegeneration and global amyloid burden on amyloid-PET scans in our cohort. Importantly, our findings suggest that CSF VEC mediates associations of CSF Aβ42/Aβ40, p-tau181, and global amyloid burden with cognitive outcomes in preclinical AD.

INTERPRETATION

Our results support the utility of CSF VEC as a marker of endothelial injury in AD and highlight the importance of endothelial injury as an early pathology that contributes to cognitive impairment in even the earliest preclinical stages.

Predicting AT(N) pathologies in Alzheimer's disease from blood-based proteomic data using neural networks

BACKGROUND AND OBJECTIVE

Blood-based biomarkers represent a promising approach to help identify early Alzheimer's disease (AD). Previous research has applied traditional machine learning (ML) to analyze plasma omics data and search for potential biomarkers, but the most modern ML methods based on deep learning has however been scarcely explored. In the current study, we aim to harness the power of state-of-the-art deep learning neural networks (NNs) to identify plasma proteins that predict amyloid, tau, and neurodegeneration (AT[N]) pathologies in AD.

METHODS

We measured 3,635 proteins using SOMAscan in 881 participants from the European Medical Information Framework for AD Multimodal Biomarker Discovery study (EMIF-AD MBD). Participants underwent measurements of brain amyloid β (Aβ) burden, phosphorylated tau (p-tau) burden, and total tau (t-tau) burden to determine their AT(N) statuses. We ranked proteins by their association with Aβ, p-tau, t-tau, and AT(N), and fed the top 100 proteins along with age and apolipoprotein E (APOE) status into NN classifiers as input features to predict these four outcomes relevant to AD. We compared NN performance of using proteins, age, and APOE genotype with performance of using age and APOE status alone to identify protein panels that optimally improved the prediction over these main risk factors. Proteins that improved the prediction for each outcome were aggregated and nominated for pathway enrichment and protein-protein interaction enrichment analysis.

RESULTS

Age and APOE alone predicted Aβ, p-tau, t-tau, and AT(N) burden with area under the curve (AUC) scores of 0.748, 0.662, 0.710, and 0.795. The addition of proteins significantly improved AUCs to 0.782, 0.674, 0.734, and 0.831, respectively. The identified proteins were enriched in five clusters of AD-associated pathways including human immunodeficiency virus 1 infection, p53 signaling pathway, and phosphoinositide-3-kinase-protein kinase B/Akt signaling pathway.

CONCLUSION

Combined with age and APOE genotype, the proteins identified have the potential to serve as blood-based biomarkers for AD and await validation in future studies. While the NNs did not achieve better scores than the support vector machine model used in our previous study, their performances were likely limited by small sample size.

Brain 18 F-Florbetapir PET/CT Findings in an Early-onset Alzheimer Disease Patient Carrying Presenilin-1 G378E Mutation

Positron emission tomography (PET) with 18 F-Fluorodeoxyglucose ( 18 F-FDG) plays an outstanding role in the diagnostic work-up of dementia. Amyloid PET imaging is a complementary imaging technique for the early detection of Alzheimer disease (AD). β-amyloid precursor protein ( APP ), Presenilin-1 ( PSEN1 ) and Presenilin-2 ( PSEN2 ) are the 3 main causative genes responsible for autosomal dominant early-onset Alzheimer disease (EOAD). This is the first report of 18 F-Florbetapir amyloid imaging findings in a 35-year-old male patient with EOAD carrying the G378E mutation in PSEN1 gene. Brain computed tomography (CT) and magnetic resonance imaging scans showed remarkable cerebral atrophy with dilatation of the cerebrospinal fluid spaces; furthermore, a 18 F-Florbetapir PET/CT scan demonstrated also widespread remarkable accumulation of the amyloid tracer in the cerebral cortex, with reduction of the normal contrast between white and gray matter and flattening of the external cortical margins. Furthermore, PET/CT showed intense 18 F-florbetapir uptake in the striatum and in the thalamus bilaterally. Our case supports the usefulness of amyloid PET imaging in the diagnostic work-up of EOAD.

A Review of Application of Aβ42/40 Ratio in Diagnosis and Prognosis of Alzheimer’s Disease

The number of patients with Alzheimer’s disease (AD) and non-Alzheimer’s disease (non-AD) has drastically increased over recent decades. The amyloid cascade hypothesis attributes a vital role to amyloid-β protein (Aβ) in the pathogenesis of AD. As the main pathological hallmark of AD, amyloid plaques consist of merely the 42 and 40 amino acid variants of Aβ (Aβ 42 and Aβ 40). The cerebrospinal fluid (CSF) biomarker Aβ 42/40 has been extensively investigated and eventually integrated into important diagnostic tools to support the clinical diagnosis of AD. With the development of highly sensitive assays and technologies, blood-based Aβ 42/40, which was obtained using a minimally invasive and cost-effective method, has been proven to be abnormal in synchrony with CSF biomarker values. This paper presents the recent progress of the CSF Aβ 42/40 ratio and plasma Aβ 42/40 for AD as well as their potential clinical application as diagnostic markers or screening tools for dementia.

A Computational Monte Carlo Simulation Strategy to Determine the Temporal Ordering of Abnormal Age Onset Among Biomarkers of Alzheimer's Disease

To quantitatively determining the temporal ordering of abnormal age onsets (AAO) among various biomarkers for Alzheimer's disease (AD), we introduced a computational Monte-Carlo simulation (CMCS) to statistically examine such ordering of an AAO pair or over all AAOs. The CMCS 1) simulates longitudinal data, estimates AAO for each iteration, and finally assesses the type-I error of an AAO pair or all AAO ordering. Using hippocampus volume (VHC), cerebral glucose hypometabolic convergence index (HCI), plasma neurofilament light (NfL), mini-mental state exam (MMSE), the auditory verbal learning test-long term memory (AVLT-LTM), short term memory (AVLT-STM) and clinical-dementia rating sum of box scale (CDR-SOB) from 382 mild cognitive impairment converters and non-converters, the CMCS estimated type-I error for the earlier AAO of VHC, AVLT_STM and AVLT_LTM each than MMSE was significant (p<0.002). The type-I error for the overall AAO temporal ordering of VHC ≤ AVLT_STM ≤ AVLT_LTM < HCI ≤ MMSE ≤ CDR-SOB ≤ NfL was p = 0.012. These findings showed that our CMCS is capable of providing statistical inferences for quantifying AAO ordering which has important implications in advancing our understanding of AD.

Multi-feature computational framework for combined signatures of dementia in underrepresented settings

Objective.The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD) remains challenging in underrepresented, underdiagnosed groups, including Latinos, as advanced biomarkers are rarely available. Recent guidelines for the study of dementia highlight the critical role of biomarkers. Thus, novel cost-effective complementary approaches are required in clinical settings.Approach. We developed a novel framework based on a gradient boosting machine learning classifier, tuned by Bayesian optimization, on a multi-feature multimodal approach (combining demographic, neuropsychological, magnetic resonance imaging (MRI), and electroencephalography/functional MRI connectivity data) to characterize neurodegeneration using site harmonization and sequential feature selection. We assessed 54 bvFTD and 76 AD patients and 152 healthy controls (HCs) from a Latin American consortium (ReDLat).Main results. The multimodal model yielded high area under the curve classification values (bvFTD patients vs HCs: 0.93 (±0.01); AD patients vs HCs: 0.95 (±0.01); bvFTD vs AD patients: 0.92 (±0.01)). The feature selection approach successfully filtered non-informative multimodal markers (from thousands to dozens).Results. Proved robust against multimodal heterogeneity, sociodemographic variability, and missing data.Significance. The model accurately identified dementia subtypes using measures readily available in underrepresented settings, with a similar performance than advanced biomarkers. This approach, if confirmed and replicated, may potentially complement clinical assessments in developing countries.

Recent advances in pre-clinical diagnosis of Alzheimer's disease

Alzheimer's disease (AD) is the most common dementia with currently no known cures or disease modifying treatments (DMTs), despite much time and effort from the field. Diagnosis and intervention of AD during the early pre-symptomatic phase of the disease is thought to be a more effective strategy. Therefore, the detection of biomarkers has emerged as a critical tool for monitoring the effect of new AD therapies, as well as identifying patients most likely to respond to treatment. The establishment of the amyloid/tau/neurodegeneration (A/T/N) framework in 2018 has codified the contexts of use of AD biomarkers in neuroimaging and bodily fluids for research and diagnostic purposes. Furthermore, a renewed drive for novel AD biomarkers and innovative methods of detection has emerged with the goals of adding additional insight to disease progression and discovery of new therapeutic targets. The use of biomarkers has accelerated the development of AD drugs and will bring new therapies to patients in need. This review highlights recent methods utilized to diagnose antemortem AD.

Using the Montreal cognitive assessment to identify individuals with subtle cognitive decline

OBJECTIVE

Dementia is a devastating neurological disease that may be better managed if diagnosed earlier when subclinical neurodegenerative changes are already present, including subtle cognitive decline and mild cognitive impairment. In this study, we used item-level performance on the Montreal Cognitive Assessment (MoCA) to identify individuals with subtle cognitive decline.

METHOD

Individual MoCA item data from the Alzheimer's Disease Neuroimaging Initiative was grouped using k-modes cluster analysis. These clusters were validated and examined for association with convergent neuropsychological tests. The clusters were then compared and characterized using multinomial logistic regression.

RESULTS

A three-cluster solution had 77.3% precision, with Cluster 1 (high performing) displaying no deficits in performance, Cluster 2 (memory deficits) displaying lower memory performance, and Cluster 3 (compound deficits) displaying lower performance on memory and executive function. Age at MoCA (older in compound deficits), gender (more females in memory deficits), and marital status (fewer married in compound deficits) were significantly different among clusters. Age was not associated with increased odds of membership in the high-performing cluster compared to the others.

CONCLUSIONS

We identified three clusters of individuals classified as cognitively unimpaired using cluster analysis. Individuals in the compound deficits cluster performed lower on the MoCA and were older and less often married than individuals in other clusters. Demographic analyses suggest that cluster identity was due to a combination of both cognitive and clinical factors. Identifying individuals at risk for future cognitive decline using the MoCA could help them receive earlier evidence-based interventions to slow further cognitive decline. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Predictive Scale for Amyloid PET Positivity Based on Clinical and MRI Variables in Patients with Amnestic Mild Cognitive Impairment

The presence of amyloid-β (Aβ) deposition is considered important in patients with amnestic mild cognitive impairment (aMCI), since they can progress to Alzheimer’s disease dementia. Amyloid positron emission tomography (PET) has been used for detecting Aβ deposition, but its high cost is a significant barrier for clinical usage. Therefore, we aimed to develop a new predictive scale for amyloid PET positivity using easily accessible tools. Overall, 161 aMCI patients were recruited from six memory clinics and underwent neuropsychological tests, brain magnetic resonance imaging (MRI), apolipoprotein E (APOE) genotype testing, and amyloid PET. Among the potential predictors, verbal and visual memory tests, medial temporal lobe atrophy, APOE genotype, and age showed significant differences between the Aβ-positive and Aβ-negative groups and were combined to make a model for predicting amyloid PET positivity with the area under the curve (AUC) of 0.856. Based on the best model, we developed the new predictive scale comprising integers, which had an optimal cutoff score ≥ 3. The new predictive scale was validated in another cohort of 98 participants and showed a good performance with AUC of 0.835. This new predictive scale with accessible variables may be useful for predicting Aβ positivity in aMCI patients in clinical practice.

Different Profiles of Spatial Navigation Deficits In Alzheimer’s Disease Biomarker-Positive Versus Biomarker-Negative Older Adults With Amnestic Mild Cognitive Impairment

Background

Spatial navigation impairment is a promising cognitive marker of Alzheimer’s disease (AD) that can reflect the underlying pathology.

Objectives

We assessed spatial navigation performance in AD biomarker positive older adults with amnestic mild cognitive impairment (AD aMCI) vs. those AD biomarker negative (non-AD aMCI), and examined associations between navigation performance, MRI measures of brain atrophy, and cerebrospinal fluid (CSF) biomarkers.

Methods

A total of 122 participants with AD aMCI (n = 33), non-AD aMCI (n = 31), mild AD dementia (n = 28), and 30 cognitively normal older adults (CN) underwent cognitive assessment, brain MRI (n = 100 had high-quality images for volumetric analysis) and three virtual navigation tasks focused on route learning (body-centered navigation), wayfinding (world-centered navigation) and perspective taking/wayfinding. Cognitively impaired participants underwent CSF biomarker assessment [amyloid-β1–42, total tau, and phosphorylated tau181 (p-tau181)] and amyloid PET imaging (n = 47 and n = 45, respectively), with a subset having both (n = 19).

Results

In route learning, AD aMCI performed worse than non-AD aMCI (p &lt; 0.001), who performed similarly to CN. In wayfinding, aMCI participants performed worse than CN (both p ≤ 0.009) and AD aMCI performed worse than non-AD aMCI in the second task session (p = 0.032). In perspective taking/wayfinding, aMCI participants performed worse than CN (both p ≤ 0.001). AD aMCI and non-AD aMCI did not differ in conventional cognitive tests. Route learning was associated with parietal thickness and amyloid-β1–42, wayfinding was associated with posterior medial temporal lobe (MTL) volume and p-tau181 and perspective taking/wayfinding was correlated with MRI measures of several brain regions and all CSF biomarkers.

Conclusion

AD biomarker positive and negative older adults with aMCI had different profiles of spatial navigation deficits that were associated with posterior MTL and parietal atrophy and reflected AD pathology.

The cerebrospinal fluid biomarker ratio Aβ42/40 identifies amyloid positron emission tomography positivity better than Aβ42 alone in a heterogeneous memory clinic cohort

BACKGROUND

Cerebrospinal fluid (CSF) analysis for detecting amyloid positivity may be as reliable as positron emission tomography (PET). We evaluated the performance of the amyloid beta (Aβ)42/40 ratio for predicting amyloid positivity by PET, compared with Aβ42 alone, and phosphorylated tau 181 (pTau181)/Aβ42 and total tau (tTau)/Aβ42 ratios, using fully automated CSF immunoassays (Roche Diagnostics International Ltd, Rotkreuz, Switzerland) in a heterogeneous cohort of patients with a range of cognitive disorders reflecting the typical population of a memory clinic.

METHODS

CSF samples from 103 patients with known amyloid PET status (PET positive = 54; PET negative = 49) were retrospectively selected from one site in Germany; 71 patients were undergoing treatment for mild cognitive impairment (n = 44) or mild-to-moderate dementia (n = 27) due to Alzheimer's disease (AD), and 32 patients were undergoing treatment for non-AD-related cognitive disorders. Aβ42, pTau181, and tTau concentrations were measured in CSF samples using the respective Elecsys® CSF immunoassays modified for use on the cobas e 411 analyzer; Aβ40 concentrations were measured using a non-commercially available robust prototype assay. Sensitivities/specificities for amyloid positivity cut-offs (Youden-derived and pre-defined) were calculated, and receiver operating characteristic analyses determined area under the curve (AUC) versus amyloid PET status. Limitations include a small sample size, use of a pre-analytical protocol not in accordance with the Elecsys CSF immunoassay method sheets, and the lack of a pre-defined cut-off for Aβ42/40.

RESULTS

Point estimates for sensitivity and specificity of CSF biomarkers and biomarker ratios versus amyloid PET were 0.93 and 0.57 for Aβ42, 0.96 and 0.69 for pTau181/Aβ42, 0.92 and 0.69 for tTau/Aβ42, and 0.94 and 0.82 for Aβ42/40. For AUCs, point estimates (95% confidence intervals) versus amyloid PET were 0.78 (0.68-0.88) for Aβ42, 0.88 (0.81-0.95) for pTau181/Aβ42, 0.87 (0.80-0.95) for tTau/Aβ42, and 0.90 (0.83-0.97) for Aβ42/40.

CONCLUSIONS

CSF Aβ42/40 ratio can predict PET amyloid positivity with high accuracy in patients with a range of cognitive disorders when evaluating Aβ pathology independent of tau and neurodegeneration for research purposes. The performance of Aβ42/40 was comparable with pTau181/Aβ42 and tTau/Aβ42 used in clinical practice and better than Aβ42 alone.

Advances in the development of new biomarkers for Alzheimer's disease

Alzheimer's disease (AD) is a complex, heterogeneous, progressive disease and is the most common type of neurodegenerative dementia. The prevalence of AD is expected to increase as the population ages, placing an additional burden on national healthcare systems. There is a large need for new diagnostic tests that can detect AD at an early stage with high specificity at relatively low cost. The development of modern analytical diagnostic tools has made it possible to determine several biomarkers of AD with high specificity, including pathogenic proteins, markers of synaptic dysfunction, and markers of inflammation in the blood. There is a considerable potential in using microRNA (miRNA) as markers of AD, and diagnostic studies based on miRNA panels suggest that AD could potentially be determined with high accuracy for individual patients. Studies of the retina with improved methods of visualization of the fundus are also showing promising results for the potential diagnosis of the disease. This review focuses on the recent developments of blood, plasma, and ocular biomarkers for the diagnosis of AD.

Aducanumab Use in Symptomatic Alzheimer Disease Evidence in Focus: A Report of the AAN Guidelines Subcommittee

OBJECTIVE

To identify the class of evidence for aducanumab use for the treatment of Alzheimer disease and present clinical considerations regarding use.

METHODS

The author panel systematically reviewed available clinical trial data detailing aducanumab use in individuals with early symptomatic Alzheimer disease. Level of evidence statements were assigned in accordance with the American Academy of Neurology's 2017 therapeutic classification of evidence scheme. Safety information, regulatory decisions, and clinical context were also reviewed.

RESULTS

Data were identified from 4 clinical trials, 1 rated Class I and 3 rated Class II. The Class I study showed that single doses of aducanumab up to 30 mg/kg were safe and well tolerated. All 3 Class II studies provided evidence that aducanumab (3-10 mg/kg) decreased amyloid deposition on brain PET at 1 year vs placebo. Efficacy data in the Class II studies varied by dose and outcome, but aducanumab either had no effect on mean change on the Clinical Dementia Rating Sum of Boxes scores or resulted in less worsening (vs placebo) that was of uncertain clinical importance. Adverse amyloid-related imaging abnormalities occurred in approximately 40% of individuals treated with aducanumab vs 10% receiving placebo.

CLINICAL CONTEXT

Administration of aducanumab will require expanded clinical infrastructure. Evidence-based guidance is needed to address key questions (e.g., safety in populations not enrolled in phase 3 studies, expected benefits on daily function, treatment duration) and critical issues relating to access to aducanumab (e.g., coverage, costs, burden of monthly infusions) that will inform shared decision making between patients and providers.

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

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

Waste Clearance in the Brain and Neuroinflammation: A Novel Perspective on Biomarker and Drug Target Discovery in Alzheimer's Disease

Alzheimer’s disease (AD) is a multifactorial disease with a heterogeneous etiology. The pathology of Alzheimer’s disease is characterized by amyloid-beta and hyperphosphorylated tau, which are necessary for disease progression. Many clinical trials on disease-modifying drugs for AD have failed to indicate their clinical benefits. Recent advances in fundamental research have indicated that neuroinflammation plays an important pathological role in AD. Damage- and pathogen-associated molecular patterns in the brain induce neuroinflammation and inflammasome activation, causing caspase-1-dependent glial and neuronal cell death. These waste products in the brain are eliminated by the glymphatic system via perivascular spaces, the blood-brain barrier, and the blood–cerebrospinal fluid barrier. Age-related vascular dysfunction is associated with an impairment of clearance and barrier functions, leading to neuroinflammation. The proteins involved in waste clearance in the brain and peripheral circulation may be potential biomarkers and drug targets in the early stages of cognitive impairment. This short review focuses on waste clearance dysfunction in AD pathobiology and discusses the improvement of waste clearance as an early intervention in prodromal AD and preclinical stages of dementia.

Engineering extracellular vesicles for Alzheimer's disease: An emerging cell-free approach for earlier diagnosis and treatment

Alzheimer's disease (AD) is a debilitating neurodegenerative disorder affecting over five million people globally and has no established cure. Current AD-related treatments only alleviate cognitive and behavioral symptoms and do not address disease onset or progression, underlining the unmet need to create an effective, innovative AD therapeutic. Extracellular vesicles (EVs) have emerged as a new class of nanotherapeutics. These secreted, lipid-bound cellular signaling carriers show promise for potential clinical applications for neurodegenerative diseases like AD. Additionally, analyzing contents and characteristics of patient-derived EVs may address the unmet need for earlier AD diagnostic techniques, informing physicians of altered genetic expression or cellular communications specific to healthy and diseased physiological states. There are numerous recent advances in regenerative medicine using EVs and include bioengineering perspectives to modify EVs, target glial cells in neurodegenerative diseases like AD, and potentially use EVs to diagnose and treat AD earlier. This article is categorized under: Neurological Diseases > Biomedical Engineering Neurological Diseases > Molecular and Cellular Physiology Neurological Diseases > Stem Cells and Development.

Evidence of plasma biomarkers indicating high risk of dementia in cognitively normal subjects

Subjects with comorbidities are at risk for neurodegeneration. There is a lack of a direct relationship between comorbidities and neurodegeneration. In this study, immunomagnetic reduction (IMR) assays were utilized to assay plasma Aβ_1-42 and total tau protein (T-Tau) levels in poststroke (PS, n = 27), family history of Alzheimer's disease (ADFH, n = 35), diabetes (n = 21), end-stage renal disease (ESRD, n = 41), obstructive sleep apnea (OSA, n = 20), Alzheimer's disease (AD, n = 65). Thirty-seven healthy controls (HCs) were enrolled. The measured concentrations of plasma Aβ_1-42 were 14.26 ± 1.42, 15.43 ± 1.76, 15.52 ± 1.60, 16.15 ± 1.05, 16.52 ± 0.59, 15.97 ± 0.54 and 20.06 ± 3.09 pg/mL in HC, PS, ADFH, diabetes, ESRD, OSA and AD groups, respectively. The corresponding concentrations of plasma T-Tau were 15.13 ± 3.62, 19.29 ± 8.01, 17.93 ± 6.26, 19.74 ± 2.92, 21.54 ± 2.72, 20.17 ± 2.77 and 41.24 ± 14.64 pg/mL. The plasma levels of Aβ_1-42 and T-Tau in were significantly higher in the PS, ADFH, diabetes, ESRD and OSA groups than controls (Aβ_1-42 in PS: 15.43 ± 1.76 pg/mL vs. 14.26 ± 1.42 pg/mL, p < 0.005; T-Tau in PS: 19.29 ± 8.01 vs. 15.13 ± 3.62 pg/mL, p < 0.005, Aβ_1-42 in ADFH: 15.52 ± 1.60 pg/mL vs. 14.26 ± 1.42 pg/mL, p < 0.001; T-Tau in ADFH: 17.93 ± 6.26 vs. 15.13 ± 3.62 pg/mL, p < 0.005, Aβ_1-42 in diabetes: 16.15 ± 1.05 pg/mL vs. 14.26 ± 1.42 pg/mL, p < 0.001; T-Tau in diabetes: 19.74 ± 2.92 vs. 15.13 ± 3.62 pg/mL, p < 0.001, Aβ_1-42 in ESRD: 16.52 ± 0.59 pg/mL vs. 14.26 ± 1.42 pg/mL, p < 0.001; T-Tau in ESRD: 21.54 ± 2.72 vs. 15.13 ± 3.62 pg/mL, p < 0.001, Aβ_1-42 in OSA: 15.97 ± 0.54 pg/mL vs. 14.26 ± 1.42 pg/mL, p < 0.001; T-Tau in OSA: 20.17 ± 2.77 vs. 15.13 ± 3.62 pg/mL, p < 0.001). This evidence indicates the high risk for dementia in these groups from the perspective of plasma biomarkers.

Aducanumab: Appropriate Use Recommendations Update

Aducanumab (Aduhelm) is approved in the United States for the treatment of patients with mild cognitive impairment due to Alzheimer's disease or mild AD dementia. Aducanumab Appropriate Use Recommendations (AURs) have been published and have helped guide best practices for use of aducanumab. As real-world use has occurred and more information has accrued, the AURs require refinement. We update the AURs to better inform appropriate patient selection and improve shared decision-making, safety monitoring, and risk mitigation in treated patients. Based on evolving experience we emphasize the importance of detecting past medical conditions that may predispose to amyloid related imaging abnormalities (ARIA) or may increase the likelihood of ARIA complications including autoimmune or inflammatory conditions, seizures, or disorders associated with extensive white matter pathology. The apolipoprotein E ε4 (APOE4) genotype is strongly associated with ARIA and exhibits a gene dose effect. We recommend that clinicians perform APOE genotyping to better inform patient care decisions, discussions regarding risk, and clinician vigilance concerning ARIA. As most ARIA occurs during the titration period of aducanumab, we suggest performing MRI before the 5th, 7th, 9th, and 12th infusions to improve detection. Uncommonly, ARIA may be recurrent or serious; we suggest additional parameters for treatment discontinuation taking these observations into account. It is important to continue to learn from the real-world use of aducanumab and the AURs will continue to evolve as new information becomes available. This AUR update does not address efficacy, price, or insurance coverage and is provided to assist clinicians to establish best practices for use of aducanumab in the treatment of patients with mild cognitive impairment and mild Alzheimer's dementia.

Connecting Cohorts to Diminish Alzheimer's Disease (CONCORD-AD): A Report of an International Research Collaboration Network

Longitudinal observational cohort studies are being conducted worldwide to understand cognition, biomarkers, and the health of the aging population better. Cross-cohort comparisons and networks of registries in Alzheimer's disease (AD) foster scientific exchange, generate insights, and contribute to the evolving clinical science in AD. A scientific working group was convened with invited investigators from established cohort studies in AD, in order to form a research collaboration network as a resource to address important research questions. The Connecting Cohorts to Diminish Alzheimer's Disease (CONCORD-AD) collaboration network was created to bring together global resources and expertise, to generate insights and improve understanding of the natural history of AD, to inform design of clinical trials in all disease stages, and to plan for optimal patient access to disease-modifying therapies once they become available. The network brings together expertise and data insights from 7 cohorts across Australia, Europe, and North America. Notably, the network includes populations recruited through memory clinics as well as population-based cohorts, representing observations from individuals across the AD spectrum. This report aims to introduce the CONCORD-AD network, providing an overview of the cohorts involved, reporting the common assessments used, and describing the key characteristics of the cohort populations. Cohort study designs and baseline population characteristics are compared, and available cognitive, functional, and neuropsychiatric symptom data, as well as the frequency of biomarker assessments, are summarized. Finally, the challenges and opportunities of cross-cohort studies in AD are discussed.

Unravelling the Association Between Amyloid-PET and Cerebrospinal Fluid Biomarkers in the Alzheimer's Disease Spectrum: Who Really Deserves an A+?

BACKGROUND

Association between cerebrospinal fluid (CSF)-amyloid-β (Aβ)42 and amyloid-PET measures is inconstant across the Alzheimer's disease (AD) spectrum. However, they are considered interchangeable, along with Aβ 42/40 ratio, for defining 'Alzheimer's Disease pathologic change' (A+).

OBJECTIVE

Herein, we further characterized the association between amyloid-PET and CSF biomarkers and tested their agreement in a cohort of AD spectrum patients.

METHODS

We include ed 23 patients who underwent amyloid-PET, MRI, and CSF analysis showing reduced levels of Aβ 42 within a 365-days interval. Thresholds used for dichotomization were: Aβ 42 <  640 pg/mL (Aβ 42+); pTau >  61 pg/mL (pTau+); and Aβ 42/40 <  0.069 (ADratio+). Amyloid-PET scans were visually assessed and processed by four pipelines (SPMCL, SPMAAL, FSGM, FSWC).

RESULTS

Different pipelines gave highly inter-correlated standardized uptake value ratios (SUVRs) (rho = 0.93-0.99). The most significant findings were: pTau positive correlation with SPMCL SUVR (rho = 0.56, p = 0.0063) and Aβ 42/40 negative correlation with SPMCL and SPMAAL SUVRs (rho = -0.56, p = 0.0058; rho = -0.52, p = 0.0117 respectively). No correlations between CSF-Aβ 42 and global SUVRs were observed. In subregion analysis, both pTau and Aβ 42/40 values significantly correlated with cingulate SUVRs from any pipeline (R2 = 0.55-0.59, p <  0.0083), with the strongest associations observed for the posterior/isthmus cingulate areas. However, only associations observed for Aβ 42/40 ratio were still significant in linear regression models. Moreover, combining pTau with Aβ 42 or using Aβ 42/40, instead of Aβ 42 alone, increased concordance with amyloid-PET status from 74% to 91% based on visual reads and from 78% to 96% based on Centiloids.

CONCLUSION

We confirmed that, in the AD spectrum, amyloid-PET measures show a stronger association and a better agreement with CSF-Aβ 42/40 and secondarily pTau rather than Aβ 42 levels.

Tau Biomarkers in Dementia: Positron Emission Tomography Radiopharmaceuticals in Tauopathy Assessment and Future Perspective

Abnormal accumulation of Tau protein is closely associated with neurodegeneration and cognitive impairment and it is a biomarker of neurodegeneration in the dementia field, especially in Alzheimer’s disease (AD); therefore, it is crucial to be able to assess the Tau deposits in vivo. Beyond the fluid biomarkers of tauopathy described in this review in relationship with the brain glucose metabolic patterns, this review aims to focus on tauopathy assessment by using Tau PET imaging. In recent years, several first-generation Tau PET tracers have been developed and applied in the dementia field. Common limitations of first-generation tracers include off-target binding and subcortical white-matter uptake; therefore, several institutions are working on developing second-generation Tau tracers. The increasing knowledge about the distribution of first- and second-generation Tau PET tracers in the brain may support physicians with Tau PET data interpretation, both in the research and in the clinical field, but an updated description of differences in distribution patterns among different Tau tracers, and in different clinical conditions, has not been reported yet. We provide an overview of first- and second-generation tracers used in ongoing clinical trials, also describing the differences and the properties of novel tracers, with a special focus on the distribution patterns of different Tau tracers. We also describe the distribution patterns of Tau tracers in AD, in atypical AD, and further neurodegenerative diseases in the dementia field.

Association Between Plasma Amyloid-β and Neuropsychological Performance in Patients With Cognitive Decline

Objective: To investigate the association between plasma amyloid-β (Aβ) levels and neuropsychological performance in patients with cognitive decline using a highly sensitive nano-biosensing platform.

Methods: We prospectively recruited 44 patients with cognitive decline who underwent plasma Aβ analysis, amyloid positron emission tomography (PET) scanning, and detailed neuropsychological tests. Patients were classified into a normal control (NC, n = 25) or Alzheimer’s disease (AD, n = 19) group based on amyloid PET positivity. Multiple linear regression was performed to determine whether plasma Aβ (Aβ₄₀, Aβ₄₂, and Aβ_42/40) levels were associated with neuropsychological test results.

Results: The plasma levels of Aβ_42/40 were significantly different between the NC and AD groups and were the best predictor of amyloid PET positivity by receiver operating characteristic curve analysis [area under the curve of 0.952 (95% confidence interval, 0.892–1.000)]. Although there were significant differences in the neuropsychological performance of cognitive domains (language, visuospatial, verbal/visual memory, and frontal/executive functions) between the NC and AD groups, higher levels of plasma Aβ_42/40 were negatively correlated only with verbal and visual memory performance.

Conclusion: Our results demonstrated that plasma Aβ analysis using a nano-biosensing platform could be a useful tool for diagnosing AD and assessing memory performance in patients with cognitive decline.

Cerebral amyloid load determination in a clinical setting: interpretation of amyloid biomarker discordances aided by tau and neurodegeneration measurements

BACKGROUND

Alzheimer's disease (AD) diagnosis can be hindered by amyloid biomarkers discordances.

OBJECTIVE

We aim to interpret discordances between amyloid positron emission tomography (Amy-PET) and cerebrospinal fluid (CSF) (Aβ₄₂ and Aβ_42/40), using Amy-PET semiquantitative analysis, [¹⁸F]fluorodeoxyglucose (FDG)-PET pattern, and CSF assays.

METHOD

Thirty-six subjects with dementia or mild cognitive impairment, assessed by neuropsychological tests, structural and functional imaging, and CSF assays (Aβ₄₂, Aβ_42/40, p-tau, t-tau), were retrospectively examined. Amy-PET and FDG-PET scans were analyzed by visual assessment and voxel-based analysis. SUVR were calculated on Amy-PET scans.

RESULTS

Groups were defined basing on the agreement among CSF Aβ₄₂ (A), CSF Aβ_42/40 Ratio (R), and Amy-PET (P) dichotomic results ( ±). In discordant groups, CSF assays, Amy-PET semiquantification, and FDG-PET patterns supported the diagnosis suggested by any two agreeing amyloid biomarkers. In groups with discordant CSF Aβ₄₂, the ratio always agrees with Amy-PET results, solving both false-negative and false-positive Aβ₄₂ results, with Aβ₄₂ levels close to the cut-off in A + R-P- subjects. The A + R + P- group presented high amyloid deposition in relevant areas, such as precuneus, posterior cingulate cortex (PCC) and dorsolateral frontal inferior cortex at semiquantitative analysis.

CONCLUSION

The amyloid discordant cases could be overcome by combining CSF Aβ₄₂, CSF ratio, and Amy-PET results. The concordance of any 2 out of the 3 biomarkers seems to reveal the remaining one as a false result. A cut-off point review could avoid CSF Aβ₄₂ false-negative results. The regional semiquantitative Amy-PET analysis in AD areas, such as precuneus and PCC, could increase the accuracy in AD diagnosis.

In Vivo Microdialysis in Mice Captures Changes in Alzheimer's Disease Cerebrospinal Fluid Biomarkers Consistent with Developing Pathology

BACKGROUND

Preclinical models of Alzheimer's disease (AD) can provide valuable insights into the onset and progression of the disease, such as changes in concentrations of amyloid-β (Aβ) and tau in cerebrospinal fluid (CSF). However, such models are currently underutilized due to limited advancement in techniques that allow for longitudinal CSF monitoring.

OBJECTIVE

An elegant way to understand the biochemical environment in the diseased brain is intracerebral microdialysis, a method that has until now been limited to short-term observations, or snapshots, of the brain microenvironment. Here we draw upon patient-based findings to characterize CSF biomarkers in a commonly used preclinical mouse model for AD.

METHODS

Our modified push-pull microdialysis method was first validated ex vivo with human CSF samples, and then in vivo in an AD mouse model, permitting assessment of dynamic changes of CSF Aβ and tau and allowing for better translational understanding of CSF biomarkers.

RESULTS

We demonstrate that CSF biomarker changes in preclinical models capture what is observed in the brain; with a decrease in CSF Aβ observed when plaques are deposited, and an increase in CSF tau once tau pathology is present in the brain parenchyma. We found that a high molecular weight cut-off membrane allowed for simultaneous sampling of Aβ and tau, comparable to CSF collection by lumbar puncture in patients.

CONCLUSION

Our approach can further advance AD and other neurodegenerative research by following evolving neuropathology along the disease cascade via consecutive sampling from the same animal and can additionally be used to administer pharmaceutical compounds and assess their efficacy (Bjorkli, unpublished data).

CSF and Plasma Cholinergic Markers in Patients With Cognitive Impairment

Introduction

Alzheimer’s disease (AD) is the most prevalent form of dementia with symptoms of deteriorating cognitive functions and memory loss, partially as a result of a decrease in cholinergic neurotransmission. The disease is incurable and treatment with cholinesterase inhibitors (ChEIs) is symptomatic. Choline acetyltransferase (ChAT), the enzyme that synthesizes acetylcholine (ACh), has been proven recently to be present in both cerebrospinal fluid (CSF) and plasma. As ChAT plays a role in regulating the extracellular ACh levels, it may have an impact on prognosis and cognitive performance in AD patients.

Objectives

To measure ChAT activity and its protein concentration in CSF and plasma from patients with AD, mild cognitive impairment (MCI), or Subjective cognitive impairment (SCI).

Methods

Plasma and CSF samples were obtained from 21 AD, 32 MCI, and 30 SCI patients. The activity and protein levels of ChAT and acetylcholinesterase (AChE), the enzyme catalyzing the hydrolysis of ACh, were analyzed using an integrated activity and protein concentration ELISA-like assay. A Cholinergic Index was calculated as the ratio of ChAT to AChE activities in CSF. The data were analyzed in relation to dementia biomarkers and cognitive performance of the patients.

Results

The CSF ChAT activity was significantly higher (55–67%) in MCI patients compared to AD and SCI cases. The CSF Cholinergic Index was 41 and 22% lower in AD patients than in MCI and SCI subjects, respectively. This index correlated positively with the Aβ₄₂/p-tau ratio in CSF in SCI but negatively with that in AD and MCI. The ChAT activity and protein levels in plasma exhibited significant differences with the pattern of AD>>MCI>SCI.

Conclusion

This is the first study investigating soluble levels of the key cholinergic enzyme, ChAT, in both plasma and CSF of individuals at different clinical stages of dementia. Although further validation is needed, the overall pattern of the results suggests that in the continuum of AD, the cholinergic signaling exhibits an inverse U-shape dynamic of changes in the brain that greatly differs from the changes observed in the plasma compartment.

Lacsogram: A New EEG Tool to Diagnose Alzheimer's Disease

This work proposes the application of a new electroencephalogram (EEG) signal processing tool - the lacsogram - to characterize the Alzheimer's disease (AD) activity and to assist on its diagnosis at different stages: Mild Cognitive Impairment (MCI), Mild and Moderate AD (ADM) and Advanced AD (ADA). Statistical analyzes are performed to lacstral distances between conventional EEG subbands to find measures capable of discriminating AD in all stages and characterizing the AD activity in each electrode. Cepstral distances are used for comparison. Comparing all AD stages and Controls (C), the most important significances are the lacstral distances between subbands θ and α ( p = 0.0014 0.05). The topographic maps show significant differences in parietal, temporal and frontal regions as AD progresses. Machine learning models with a leave-one-out cross-validation process are applied to lacstral/cepstral distances to develop an automatic method for diagnosing AD. The following classification accuracies are obtained with an artificial neural network: 95.55% for All vs All, 98.06% for C vs MCI, 95.99% for C vs ADM, 93.85% for MCI vs ADM-ADA. In C vs MCI, C vs ADM and MCI vs ADM-ADA, the proposed method outperforms the state-of-art methods by 5%, 1%, and 2%, respectively. In All vs All, it outperforms the state-of-art EEG and non-EEG methods by 6% and 2%, respectively. These results indicate that the proposed method represents an improvement in diagnosing AD.