Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B

Docking for Molecules That Bind in a Symmetric Stack with SymDOCK

Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of great current interest. In recent structures, ligands bind in stacks in the tau fibrils to reflect the rotational and translational symmetry of the fibril itself; in these structures, the ligands make few interactions with the protein but interact extensively with each other. To exploit this symmetry and stacking, we developed SymDOCK, a method to dock molecules that follow the protein's symmetry. For each prospective ligand pose, we apply the symmetry operation of the fibril to generate a self-interacting and fibril-interacting stack, checking that doing so will not cause a clash between the original molecule and its image. Absent a clash, we retain that pose and add the ligand-ligand van der Waals energy to the ligand's docking score (here using DOCK3.8). We can check these geometries and energies using an implementation of ANI, a neural-network-based quantum-mechanical evaluation of the ligand stacking energies. In retrospective calculations, symmetry docking can reproduce the poses of three tau PET tracers whose structures have been determined. More convincingly, in a prospective study, SymDOCK predicted the structure of the PET tracer MK-6240 bound in a symmetrical stack to AD PHF tau before that structure was determined; the docked pose was used to determine how MK-6240 fit the cryo-EM density. In proof-of-concept studies, SymDOCK enriched known ligands over property-matched decoys in retrospective screens without sacrificing docking speed and can address large library screens that seek new symmetrical stackers. Future applications of this approach will be considered.

Biomarkers in Alzheimer's Disease: Are Olfactory Neuronal Precursors Useful for Antemortem Biomarker Research?

Alzheimer's disease (AD), as the main cause of dementia, affects millions of people around the world, whose diagnosis is based mainly on clinical criteria. Unfortunately, the diagnosis is obtained very late, when the neurodegenerative damage is significant for most patients. Therefore, the exhaustive study of biomarkers is indispensable for diagnostic, prognostic, and even follow-up support. AD is a multifactorial disease, and knowing its underlying pathological mechanisms is crucial to propose new and valuable biomarkers. In this review, we summarize some of the main biomarkers described in AD, which have been evaluated mainly by imaging studies in cerebrospinal fluid and blood samples. Furthermore, we describe and propose neuronal precursors derived from the olfactory neuroepithelium as a potential resource to evaluate some of the widely known biomarkers of AD and to gear toward searching for new biomarkers. These neuronal lineage cells, which can be obtained directly from patients through a non-invasive and outpatient procedure, display several characteristics that validate them as a surrogate model to study the central nervous system, allowing the analysis of AD pathophysiological processes. Moreover, the ease of obtaining and harvesting endows them as an accessible and powerful resource to evaluate biomarkers in clinical practice.

Revision of Alzheimer's diagnostic criteria or relocation of the Potemkin village

The recently announced revision of the Alzheimer's disease (AD) diagnostic ATN classification adds to an already existing disregard for clinical assessment the rejection of image-based in vivo assessment of the brain's condition. The revision suggests that the diagnosis of AD should be based solely on the presence of cerebral amyloid-beta and tau, indicated by the "A" and "T". The "N", which stands for neurodegeneration - detected by imaging - should no longer be given importance, except that A+ ± T + = AD with amyloid PET being the main method for demonstrating A+ . We believe this is an artificial and misleading suggestion. It is artificial because it relies on biomarkers whose significance remains obscure and where the detection of "A" is based on a never-validated PET method using a tracer that marks much more than amyloid-beta. It is misleading because many patients without dementia will be falsely classified as having AD, but nonetheless candidates for passive immunotherapy, which may be more harmful than beneficial, and sometimes fatal.

Harmonization of CSF and imaging biomarkers in Alzheimer's disease: Need and practical applications for genetics studies and preclinical classification

In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers, leading to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS results using this approach with currently accepted methods. We also used a generalized mixture model to calculate the threshold for biomarker-positivity. Based on our findings, our normalization approach performed as well as meta-analysis and did not lead to any spurious results. In terms of dichotomization, cutoffs calculated with this approach were very similar to those reported previously. These findings show that the Z-score based harmonization approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.

Imaging Neuroinflammation: Quantification of Astrocytosis in a Multitracer PET Approach

The recent progress in the development of in vivo biomarkers is rapidly changing how neurodegenerative diseases are conceptualized and diagnosed and how clinical trials are designed today. Alzheimer's disease (AD) - the most common neurodegenerative disorder - is characterized by a complex neuropathology involving the deposition of extracellular amyloid-β (Aβ) plaques and intracellular neurofibrillary tangles (NFTs) of hyperphosphorylated tau proteins, accompanied by the activation of glial cells, i.e., astrocytes and microglia, and neuroinflammatory response, leading to neurodegeneration and cognitive dysfunction. An increasing diversity of positron emission tomography (PET) imaging radiotracers is available to selectively target the different pathophysiological processes of AD. Along with the success of Aβ PET and the more recent tau PET imaging, there is a great interest to develop PET tracers to image glial reactivity and neuroinflammation. While most research to date has focused on imaging microgliosis, there is an upsurge of interest in imaging reactive astrocytes in the AD continuum. There is increasing evidence that reactive astrocytes are morphologically and functionally heterogeneous, with different subtypes that express different markers and display various homeostatic or detrimental roles across disease stages. Therefore, multiple biomarkers are desirable to unravel the complex phenomenon of reactive astrocytosis. In the field of in vivo PET imaging in AD, the research concerning reactive astrocytes has predominantly focused on targeting monoamine oxidase B (MAO-B), most often using either 11C-deuterium-L-deprenyl (11C-DED) or 18F-SMBT-1 PET tracers. Additionally, imidazoline2 binding (I2BS) sites have been imaged using 11C-BU99008 PET. Recent studies in our group using 11C-DED PET imaging suggest that astrocytosis may be present from the early stages of disease development in AD. This chapter provides a detailed description of the practical approach used for the analysis of 11C-DED PET imaging data in a multitracer PET paradigm including 11C-Pittsburgh compound B (11C-PiB) and 18F-fluorodeoxyglucose (18F-FDG). The multitracer PET approach allows investigating the comparative regional and temporal patterns of in vivo brain astrocytosis, fibrillar Aβ deposition, glucose metabolism, and brain structural changes. It may also contribute to understanding the potential role of novel plasma biomarkers of reactive astrocytes, in particular the glial fibrillary acidic protein (GFAP), at different stages of disease progression. This chapter attempts to stimulate further research in the field, including the development of novel PET tracers that may allow visualizing different aspects of the complex astrocytic and microglial response in neurodegenerative diseases. Progress in the field will contribute to the incorporation of PET imaging of glial reactivity and neuroinflammation as biomarkers with clinical application and motivate further investigation on glial cells as therapeutic targets in AD and other neurodegenerative diseases.

A Chronic Increase in Blood-Brain Barrier Permeability Facilitates Intraneuronal Deposition of Exogenous Bloodborne Amyloid-Beta1-42 Peptide in the Brain and Leads to Alzheimer's Disease-Relevant Cognitive Changes in a Mouse Model

Background

Increased blood-brain barrier (BBB) permeability and amyloid-β (Aβ) peptides (especially Aβ1-42) (Aβ42) have been linked to Alzheimer's disease (AD) pathogenesis, but the nature of their involvement in AD-related neuropathological changes leading to cognitive changes remains poorly understood.

Objective

To test the hypothesis that chronic extravasation of bloodborne Aβ42 peptide and brain-reactive autoantibodies and their entry into the brain parenchyma via a permeable BBB contribute to AD-related pathological changes and cognitive changes in a mouse model.

Methods

The BBB was rendered chronically permeable through repeated injections of Pertussis toxin (PT), and soluble monomeric, fluorescein isothiocyanate (FITC)-labeled or unlabeled Aβ42 was injected into the tail-vein of 10-month-old male CD1 mice at designated intervals spanning ∼3 months. Acquisition of learned behaviors and long-term retention were assessed via a battery of cognitive and behavioral tests and linked to neuropathological changes.

Results

Mice injected with both PT and Aβ42 demonstrated a preferential deficit in the capacity for long-term retention and an increased susceptibility to interference in selective attention compared to mice exposed to PT or saline only. Immunohistochemical analyses revealed increased BBB permeability and entry of bloodborne Aβ42 and immunoglobulin G (IgG) into the brain parenchyma, selective neuronal binding of IgG and neuronal accumulation of Aβ42 in animals injected with both PT and Aβ42 compared to controls.

Conclusion

Results highlight the potential synergistic role of BBB compromise and the influx of bloodborne Aβ42 into the brain in both the initiation and progression of neuropathologic and cognitive changes associated with AD.

Reducing neonatal Fc receptor binding enhances clearance and brain-to-blood ratio of TfR-delivered bispecific amyloid-β antibody

Recent development of amyloid-β (Aβ)-targeted immunotherapies for Alzheimer's disease (AD) have highlighted the need for accurate diagnostic methods. Antibody-based positron emission tomography (PET) ligands are well suited for this purpose as they can be directed toward the same target as the therapeutic antibody. Bispecific, brain-penetrating antibodies can achieve sufficient brain concentrations, but their slow blood clearance remains a challenge, since it prolongs the time required to achieve a target-specific PET signal. Here, two antibodies were designed based on the Aβ antibody bapineuzumab (Bapi) - one monospecific IgG (Bapi) and one bispecific antibody with an antigen binding fragment (Fab) of the transferrin receptor (TfR) antibody 8D3 fused to one of the heavy chains (Bapi-Fab8D3) for active, TfR-mediated transport into the brain. A variant of each antibody was designed to harbor a mutation to the neonatal Fc receptor (FcRn) binding domain, to increase clearance. Blood and brain pharmacokinetics of radiolabeled antibodies were studied in wildtype (WT) and AD mice (AppNL-G-F). The FcRn mutation substantially reduced blood half-life of both Bapi and Bapi-Fab8D3. Bapi-Fab8D3 showed high brain uptake and the brain-to-blood ratio of its FcRn mutated form was significantly higher in AppNL-G-F mice than in WT mice 12 h after injection and increased further up to 168 h. Ex vivo autoradiography showed specific antibody retention in areas with abundant Aβ pathology. Taken together, these results suggest that reducing FcRn binding of a full-sized bispecific antibody increases the systemic elimination and could thereby drastically reduce the time from injection to in vivo imaging.

Transforming Neurology and Psychiatry: Organ-specific PET Instrumentation and Clinical Applications

PET technology has immense potential for furthering understanding of the brain and associated disorders, including advancements in high-resolution tomographs and hybrid imaging modalities. Novel radiotracers targeting specific neurotransmitter systems and molecular markers provide opportunities to unveil intricate mechanisms underlying neurologic and psychiatric conditions. As PET imaging techniques and analysis methods continue to be refined, the field is poised to make significant contributions to personalized medicine for more targeted and effective interventions. PET instrumentation has advanced the fields of neurology and psychiatry, providing insights into pathophysiology and development of effective treatments.

Where Should I Draw the Line: PET-Driven, Data-Driven, or Manufacturer Cut-Off?

Background

The optimal cut-off for Alzheimer's disease (AD) CSF biomarkers remains controversial.

Objective

To analyze the performance of cut-off points standardized by three methods: one that optimized the agreement between 11C-Pittsburgh compound B PET (a-PET) and CSF biomarkers (Aβ1-42, pTau, tTau, and Aβ1-42/Aβ1-40 ratio) in our population, called PET-driven; an unbiased cut-off using data from a healthy research cohort, called data-driven, and that provided by the manufacturer. We also compare changes in ATN classification.

Methods

CSF biomarkers measured by the LUMIPULSE G600II platform and qualitative visualization of amyloid positron emission tomography (a-PET) were performed in all the patients. We established a cut-off for each single biomarker and Aβ1-42/Aβ1-40 ratio that optimized their agreement with a-PET using ROC curves. Sensitivity, Specificity, and Overall Percent of Agreement are assessed using a-PET or clinical diagnosis as gold standard for every cut-off. Also, we established a data-driven cut-off from our cognitively unimpaired cohort. We then analyzed changes in ATN classification.

Results

One hundred and ten patients were recruited. Sixty-six (60%) were a-PET positive. PET-driven cut-offs were: pTau > 57, tTau > 362.62, Aβ1-42/Aβ1-40 < 0.069. For a single biomarker, pTau showed the highest accuracy (AUC 0.926). New PET-driven cut-offs classified patients similarly to manufacturer cut-offs (only two patients changed). However, 20 patients (18%) changed when data-driven cut-offs were used.

Conclusions

We established our sample's best CSF biomarkers cut-offs using a-PET as the gold standard. These cut-offs categorize better symptomatic subjects than data-driven in ATN classification, but they are very similar to the manufacturer's.

Performance of the Lumipulse plasma Aβ42/40 and pTau181 immunoassays in the detection of amyloid pathology

INTRODUCTION

This study evaluated the performance of the Lumipulse plasma beta-amyloid (Aβ) 42/40 and pTau181 compared to other assays to detect an abnormal amyloid-positron emission tomography (PET).

METHODS

Plasma samples from cognitively unimpaired (N = 179) and MCI/AD dementia (N = 36) individuals were retrospectively evaluated. Plasma Aβ42/40 and pTau181 were measured using the Lumipulse and Simoa immunoassays. An immunoprecipitation mass spectrometry (IP-MS) assay for plasma Aβ42/40 was also evaluated. Amyloid-PET status was the outcome measure.

RESULTS

Lumipulse and IP-MS Aβ42/40 exhibited the highest diagnostic accuracy for detecting an abnormal amyloid-PET (areas under the curve [AUCs] of 0.81 and 0.84, respectively). The Lumipulse and Simoa pTau181 assays exhibited lower performance (AUCs of 0.74 and 0.72, respectively). The Simoa Aβ42/40 assay demonstrated the lowest diagnostic accuracy (AUC 0.57). Combining Aβ42/40 and pTau181 did not significantly improve performance over Aβ42/40 alone for Lumipulse (AUC 0.83) or over pTau181 alone for Simoa (AUC 0.71).

DISCUSSION

The Lumipulse Aβ42/40 assay showed similar performance to the IP-MS Aβ42/40 assay for detection of an abnormal amyloid-PET; and both assays performed better than the two p-tau181 immunoassays. The Simoa Aβ42/Aβ40 assay was the least accurate at predicting an abnormal amyloid-PET status.

Highlights

Lumipulse plasma Aβ42/Aβ40 AUC for abnormal amyloid-PET detection was 0.81.This performance was comparable to previously reported IP-MS and higher than Simoa.Performance of Alzheimer's disease blood biomarkers varies between assays.

High Contrast PET Imaging of Subcortical and Allocortical Amyloid-β in Early Alzheimer's Disease Using [11C]AZD2184

Background

Deposits of amyloid-β (Aβ) appear early in Alzheimer's disease (AD).

Objective

The aim of the present study was to compare the presence of cortical and subcortical Aβ in early AD using positron emission tomography (PET).

Methods

Eight cognitively unimpaired (CU) subjects, 8 with mild cognitive impairment (MCI) and 8 with mild AD were examined with PET and [11C]AZD2184. A data driven cut-point for Aβ positivity was defined by Gaussian mixture model of isocortex binding potential (BPND) values.

Results

Sixteen subjects (3 CU, 5 MCI and 8 AD) were Aβ-positive. BPND was lower in subcortical and allocortical regions compared to isocortex. Fifteen of the 16 Aβ-positive subjects displayed Aβ binding in striatum, 14 in thalamus and 10 in allocortical regions.

Conclusions

Aβ deposits appear to be widespread in early AD. It cannot be excluded that deposits appear simultaneously throughout the whole brain which has implications for improved diagnostics and disease monitoring.

Amyloid-β Deposition Predicts Grocery Shopping Performance in Older Adults Without Cognitive Impairment

Background

A screening tool sensitive to Alzheimer's disease (AD) risk factors, such as amyloid-β (Aβ) deposition, and subtle cognitive changes, best elicited by complex everyday tasks, is needed.

Objective

To determine if grocery shopping performance could differentiate older adults at elevated risk of developing AD (OAer), older adults at low risk of developing AD (OAlr), and young adults (YA), and if amount of Aβ deposition could predict grocery shopping performance in older adults (OA).

Methods

Twenty-one OAer (78±5 years), 33 OAlr (78±5 years), and 28 YA (31±3 years) performed four grocery shopping trials, with the best and worst performances analyzed. Measures included trial time, number of correct items, number of grocery note fixations, and number of fixations and percentage of time fixating on the correct shelving unit, correct brand, and correct shelf. Linear mixed effects models compared measures by performance rank (best, worst) and group (OAer, OAlr, YA), and estimated the effect of Aβ deposition on measures in OA.

Results

Relative to their best performance, OAer and OAlr exhibited more correct shelving unit fixations and correct brand fixations during their worst performance, while YA did not. Within OA's worst performance, greater Aβ deposition was associated with a smaller percentage of time fixating on the correct shelving unit, correct shelf, and correct brand. Within OA, greater Aβ deposition was associated with more grocery note fixations.

Conclusions

OA with elevated Aβ deposition may exhibit subtle working memory impairments and less efficient visual search strategies while performing a cognitively demanding everyday task.

Nicotine Abuse and Neurodegeneration: Novel Pharmacogenetic Targets to Aid Quitting and Reduce the Risk of Dementia

Nicotine dependence has deleterious neurological impacts. Previous studies found an association between cigarette smoking and accelerating age-related thinning of the brain's cortex and subsequent cognitive decline. Smoking is considered the third most common risk factor for dementia, which prompted the inclusion of smoking cessation in dementia prevention strategies. Traditional pharmacologic options for smoking cessation include nicotine transdermal patches, bupropion and varenicline. However, based on smokers' genetic makeup, pharmacogenetics can be used to develop novel therapies to replace these traditional approaches. Genetic variability of cytochrome P450 2A6 has a major impact on smokers' behavior and their response to quitting therapies. Gene polymorphism in nicotinic acetylcholine receptor subunits also has a great influence on the ability to quit smoking. In addition, polymorphism of certain nicotinic acetylcholine receptors was found to affect the risk of dementia and the impact of tobacco smoking on the development of Alzheimer's disease. Nicotine dependence involves the activation of pleasure response through the stimulation of dopamine release. Central dopamine receptors, catechol-o-methyltransferase and the dopamine transporter protein, regulate synaptic dopamine levels. The genes of these molecules are potential targets for novel smoking cessation drugs. Pharmacogenetic studies of smoking cessation also investigated other molecules, such as ANKK1 and dopamine-beta-hydroxylase (DBH). In this perspective article, we aim to highlight the promising role of pharmacogenetics in the development of effective drugs for smoking cessation, which can increase the success rate of smoking quitting plans and ultimately reduce the incidence of neurodegeneration and dementia.

Repurposing of the PET Probe Prototype PiB for Label and Radiation-Free CEST MRI Molecular Imaging of Amyloid

Positron emission tomography (PET) probes are specific and sensitive while suffering from radiation risk. It is worthwhile to explore the chemical emission saturation transfer (CEST) effects of the probe prototypes and repurpose them for CEST imaging to avoid radiation. In this study, we used 11C-PiB as an example of a PET probe for detecting amyloid and tested the feasibility of repurposing this PET probe prototype, PiB, for CEST imaging. After optimizing the parameters through preliminary phantom experiments, we used APP/PS1 transgenic mice and age-matched C57 mice for in vivo CEST magnetic resonance imaging (MRI) of amyloid. Furthermore, the pathological assessment was conducted on the same brain slices to evaluate the correlation between the CEST MRI signal abnormality and β-amyloid deposition detected by immunohistochemical staining. In our results, the Z-spectra revealed an apparent CEST effect that peaked at approximately 6 ppm. APP/PS1 mice as young as 9 months injected with PiB showed a significantly higher CEST effect compared to the control groups. The hyperintense region was correlated with the Aβ deposition shown by pathological staining. In conclusion, repurposing the PET probe prototype for CEST MRI imaging is feasible and enables label- and radiation-free detection of the amyloid while maintaining the sensitivity and specificity of the ligand. This study opens the door to developing CEST probes based on PET probe prototypes.

Coordination Chemistry of Sulfur-Containing Bifunctional Chelators: Toward in Vivo Stabilization of 64Cu PET Imaging Agents for Alzheimer's Disease

The broader utilization of 64Cu positron emission tomography (PET) imaging agents has been hindered by the unproductive demetalation induced by bioreductants. To advance the development of 64Cu-based PET imaging tracers for Alzheimer's Disease (AD), there is a need for novel ligand design strategies. In this study, we developed sulfur-containing dithiapyridinophane (N2S2) bifunctional chelators (BFCs) as well as all nitrogen-based diazapyridinophane (N4) BFCs to compare their abilities to chelate Cu and target Aβ aggregates. Through spectrophotometric titrations and electrochemical measurements, we have demonstrated that the N2S2-based BFCs exhibit >10 orders of magnitude higher binding affinity toward Cu(I) compared to their N4-based counterparts, while both types of BFCs exhibit high stability constants toward Cu(II). Notably, solid state structures for both Cu(II) and Cu(I) complexes supported by the two ligand frameworks were obtained, providing molecular insights into their copper chelating abilities. Aβ binding experiments were conducted to study the structure-affinity relationship, and fluorescence microscopy imaging studies confirmed the selective labeling of the BFCs and their copper complexes. Furthermore, we investigated the potential of these ligands for the 64Cu-based PET imaging of AD through radiolabeling and autoradiography studies. We believe our findings provide molecular insights into the design of bifunctional Cu chelators that can effectively stabilize both Cu(II) and Cu(I) and, thus, can have significant implications for the development of 64Cu PET imaging as a diagnostic tool for AD.

Biological Diagnosis of Alzheimer's Disease Based on Amyloid Status: An Illustration of Confirmation Bias in Medical Research?

Alzheimer's disease (AD) was first characterized by Dr. Alois Alzheimer in 1906 by studying a demented patient and discovering cerebral amyloid plaques and neurofibrillary tangles. Subsequent research highlighted the roles of Aβ peptides and tau proteins, which are the primary constituents of these lesions, which led to the amyloid cascade hypothesis. Technological advances, such as PET scans using Florbetapir, have made it possible to visualize amyloid plaques in living patients, thus improving AD's risk assessment. The National Institute on Aging and the Alzheimer's Association introduced biological diagnostic criteria in 2011, which underlined the amyloid deposits diagnostic value. However, potential confirmation bias may have led researchers to over-rely on amyloid markers independent of AD's symptoms, despite evidence of their limited specificity. This review provides a critical examination of the current research paradigm in AD, including, in particular, the predominant focus on amyloid and tau species in diagnostics. We discuss the potential multifaceted consequences of this approach and propose strategies to mitigate its overemphasis in the development of new biomarkers. Furthermore, our study presents comprehensive guidelines aimed at enhancing the creation of biomarkers for accurately predicting AD dementia onset. These innovations are crucial for refining patient selection processes in clinical trial enrollment and for the optimization of therapeutic strategies. Overcoming confirmation bias is essential to advance the diagnosis and treatment of AD and to move towards precision medicine by incorporating a more nuanced understanding of amyloid biomarkers.

Tau PET burden in Brodmann areas 35 and 36 is associated with individual differences in cognition in non-demented older adults

Introduction

The accumulation of neurofibrillary tau tangles, a neuropathological hallmark of Alzheimer's disease (AD), occurs in medial temporal lobe (MTL) regions early in the disease process, with some of the earliest deposits localized to subregions of the entorhinal cortex. Although functional specialization of entorhinal cortex subregions has been reported, few studies have considered functional associations with localized tau accumulation.

Methods

In this study, stepwise linear regressions were used to examine the contributions of regional tau burden in specific MTL subregions, as measured by 18F-MK6240 PET, to individual variability in cognition. Dependent measures of interest included the Clinical Dementia Rating Sum of Boxes (CDR-SB), Mini Mental State Examination (MMSE), and composite scores of delayed episodic memory and language. Other model variables included age, sex, education, APOE4 status, and global amyloid burden, indexed by 11C-PiB.

Results

Tau burden in right Brodmann area 35 (BA35), left and right Brodmann area 36 (BA36), and age each uniquely contributed to the proportion of explained variance in CDR-SB scores, while right BA36 and age were also significant predictors of MMSE scores, and right BA36 was significantly associated with delayed episodic memory performance. Tau burden in both left and right BA36, along with education, uniquely contributed to the proportion of explained variance in language composite scores. Importantly, the addition of more inclusive ROIs, encompassing less granular segmentation of the entorhinal cortex, did not significantly contribute to explained variance in cognition across any of the models.

Discussion

These findings suggest that the ability to quantify tau burden in more refined MTL subregions may better account for individual differences in cognition, which may improve the identification of non-demented older adults who are on a trajectory of decline due to AD.

Advances in the prevention and treatment of Alzheimer's disease based on oral bacteria

With the global population undergoing demographic shift towards aging, the prevalence of Alzheimer's disease (AD), a prominent neurodegenerative disorder that primarily afflicts individuals aged 65 and above, has increased across various geographical regions. This phenomenon is accompanied by a concomitant decline in immune functionality and oral hygiene capacity among the elderly, precipitating compromised oral functionality and an augmented burden of dental plaque. Accordingly, oral afflictions, including dental caries and periodontal disease, manifest with frequency among the geriatric population worldwide. Recent scientific investigations have unveiled the potential role of oral bacteria in instigating both local and systemic chronic inflammation, thereby delineating a putative nexus between oral health and the genesis and progression of AD. They further proposed the oral microbiome as a potentially modifiable risk factor in AD development, although the precise pathological mechanisms and degree of association have yet to be fully elucidated. This review summarizes current research on the relationship between oral bacteria and AD, describing the epidemiological and pathological mechanisms that may potentially link them. The purpose is to enrich early diagnostic approaches by incorporating emerging biomarkers, offering novel insights for clinicians in the early detection of AD. Additionally, it explores the potential of vaccination strategies and guidance for clinical pharmacotherapy. It proposes the development of maintenance measures specifically targeting oral health in older adults and advocates for guiding elderly patients in adopting healthy lifestyle habits, ultimately aiming to indirectly mitigate the progression of AD while promoting oral health in the elderly.

In vivo three-dimensional brain imaging with chemiluminescence probes in Alzheimer's disease models

Optical three-dimensional (3D) molecular imaging is highly desirable for providing precise distribution of the target-of-interest in disease models. However, such 3D imaging is still far from wide applications in biomedical research; 3D brain optical molecular imaging, in particular, has rarely been reported. In this report, we designed chemiluminescence probes with high quantum yields, relatively long emission wavelengths, and high signal-to-noise ratios to fulfill the requirements for 3D brain imaging in vivo. With assistance from density-function theory (DFT) computation, we designed ADLumin-Xs by locking up the rotation of the double bond via fusing the furan ring to the phenyl ring. Our results showed that ADLumin-5 had a high quantum yield of chemiluminescence and could bind to amyloid beta (Aβ). Remarkably, ADLumin-5's radiance intensity in brain areas could reach 4 × 107 photon/s/cm2/sr, which is probably 100-fold higher than most chemiluminescence probes for in vivo imaging. Because of its strong emission, we demonstrated that ADLumin-5 could be used for in vivo 3D brain imaging in transgenic mouse models of Alzheimer's disease.

Predicting cognitive dysfunction and regional hubs using Braak staging amyloid-beta biomarkers and machine learning

Mild cognitive impairment (MCI) is a transitional stage between normal aging and early Alzheimer's disease (AD). The presence of extracellular amyloid-beta (Aβ) in Braak regions suggests a connection with cognitive dysfunction in MCI/AD. Investigating the multivariate predictive relationships between regional Aβ biomarkers and cognitive function can aid in the early detection and prevention of AD. We introduced machine learning approaches to estimate cognitive dysfunction from regional Aβ biomarkers and identify the Aβ-related dominant brain regions involved with cognitive impairment. We employed Aβ biomarkers and cognitive measurements from the same individuals to train support vector regression (SVR) and artificial neural network (ANN) models and predict cognitive performance solely based on Aβ biomarkers on the test set. To identify Aβ-related dominant brain regions involved in cognitive prediction, we built the local interpretable model-agnostic explanations (LIME) model. We found elevated Aβ in MCI compared to controls and a stronger correlation between Aβ and cognition, particularly in Braak stages III-IV and V-VII (p < 0.05) biomarkers. Both SVR and ANN, especially ANN, showed strong predictive relationships between regional Aβ biomarkers and cognitive impairment (p < 0.05). LIME integrated with ANN showed that the parahippocampal gyrus, inferior temporal gyrus, and hippocampus were the most decisive Braak regions for predicting cognitive decline. Consistent with previous findings, this new approach suggests relationships between Aβ biomarkers and cognitive impairment. The proposed analytical framework can estimate cognitive impairment from Braak staging Aβ biomarkers and delineate the dominant brain regions collectively involved in AD pathophysiology.

An inclusive study of recent advancements in Alzheimer's disease: A comprehensive review

Alzheimer's disease (AD) has remained elusive in revealing its pathophysiology and mechanism of development. In this review paper, we attempt to highlight several theories that abound about the exact pathway of AD development. The number of cases worldwide has prompted a constant flow of research to detect high-risk patients, slow the progression of the disease and discover improved methods of treatment that may prove effective. We shall focus on the two main classes of drugs that are currently in use; and emerging ones with novel mechanisms that are under development. As of late there has also been increased attention towards factors that were previously thought to be unrelated to AD, such as the gut microbiome, lifestyle habits, and diet. Studies have now shown that all these factors make an impact on AD progression, thus bringing to our attention more areas that could hold the key to combating this disease. This paper covers all the aforementioned factors concisely. We also briefly explore the relationship between mental health and AD, both before and after the diagnosis of the disease.

Multistep synthesis of a novel copper complex with potential for Alzheimer's disease diagnosis

Positron emission tomography (PET) imaging of Aβ plaques, is recognized as a tool for the diagnosis of Alzheimer's disease. As a contribution to the development of new strategies for early diagnosis of the disease, using PET medical imaging technique, a new copper complex, the [Cu(TE1PA-ONO)]+ was synthesized in ten steps. The key step of our strategy is the coupling of a monopicolinate-N-alkylated cyclam-based ligand with a moiety capable of recognizing Aβ plaques via a successful and challenging Buchwald-Hartwig coupling reaction. To our knowledge, it is the first time that such a strategy is used to functionalize polyazamacrocyclic derivatives. The thermodynamic stability constants determined in MeOH/H2O solvent indicate that the attachment of this moiety does not weaken the chelating properties of TE1PA-ONO ligand in relation to parent HTE1PA. The novel complex described here is able to recognize amyloid plaques in brain sections from Alzheimer's disease patients and shows low toxicity to human neuronal cells.

A method for the efficient evaluation of substrate-based cholinesterase imaging probes for Alzheimer's disease

Cholinesterase (ChE) enzymes have been identified as diagnostic markers for Alzheimer disease (AD). Substrate-based probes have been synthesised to detect ChEs but they have not detected changes in ChE distribution associated with AD pathology. Probes are typically screened using spectrophotometric methods with pure enzyme for specificity and kinetics. However, the biochemical properties of ChEs associated with AD pathology are altered. The present work was undertaken to determine whether the Karnovsky-Roots (KR) histochemical method could be used to evaluate probes at the site of pathology. Thirty thioesters and esters were synthesised and evaluated using enzyme kinetic and KR methods. Spectrophotometric methods demonstrated all thioesters were ChE substrates, yet only a few provided staining in the brain with the KR method. Esters were ChE substrates with interactions with brain ChEs. These results suggest that the KR method may provide an efficient means to screen compounds as probes for imaging AD-associated ChEs.

Design and feasibility of an Alzheimer's disease blood test study in a diverse community-based population

INTRODUCTION

Alzheimer's disease (AD) blood tests are likely to become increasingly important in clinical practice, but they need to be evaluated in diverse groups before use in the general population.

METHODS

This study enrolled a community-based sample of older adults in the St. Louis, Missouri, USA area. Participants completed a blood draw, Eight-Item Informant Interview to Differentiate Aging and Dementia (AD8® ), Montreal Cognitive Assessment (MoCA), and survey about their perceptions of the blood test. A subset of participants completed additional blood collection, amyloid positron emission tomography (PET), magnetic resonance imaging (MRI), and Clinical Dementia Rating (CDR® ).

RESULTS

Of the 859 participants enrolled in this ongoing study, 20.6% self-identified as Black or African American. The AD8 and MoCA correlated moderately with the CDR. The blood test was well accepted by the cohort, but it was perceived more positively by White and highly educated individuals.

DISCUSSION

Studying an AD blood test in a diverse population is feasible and may accelerate accurate diagnosis and implementation of effective treatments.

HIGHLIGHTS

A diverse group of older adults was recruited to evaluate a blood amyloid test. The enrollment rate was high and the blood test was well accepted by participants. Cognitive impairment screens have moderate performance in a diverse population. Alzheimer's disease blood tests are likely to be feasible for use in real-world settings.

Artificial intelligence for diagnostic and prognostic neuroimaging in dementia: A systematic review

INTRODUCTION

Artificial intelligence (AI) and neuroimaging offer new opportunities for diagnosis and prognosis of dementia.

METHODS

We systematically reviewed studies reporting AI for neuroimaging in diagnosis and/or prognosis of cognitive neurodegenerative diseases.

RESULTS

A total of 255 studies were identified. Most studies relied on the Alzheimer's Disease Neuroimaging Initiative dataset. Algorithmic classifiers were the most commonly used AI method (48%) and discriminative models performed best for differentiating Alzheimer's disease from controls. The accuracy of algorithms varied with the patient cohort, imaging modalities, and stratifiers used. Few studies performed validation in an independent cohort.

DISCUSSION

The literature has several methodological limitations including lack of sufficient algorithm development descriptions and standard definitions. We make recommendations to improve model validation including addressing key clinical questions, providing sufficient description of AI methods and validating findings in independent datasets. Collaborative approaches between experts in AI and medicine will help achieve the promising potential of AI tools in practice.

HIGHLIGHTS

There has been a rapid expansion in the use of machine learning for diagnosis and prognosis in neurodegenerative disease Most studies (71%) relied on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with no other individual dataset used more than five times There has been a recent rise in the use of more complex discriminative models (e.g., neural networks) that performed better than other classifiers for classification of AD vs healthy controls We make recommendations to address methodological considerations, addressing key clinical questions, and validation We also make recommendations for the field more broadly to standardize outcome measures, address gaps in the literature, and monitor sources of bias.

Traumatic brain injury and Alzheimer's Disease biomarkers: A systematic review of findings from amyloid and tau positron emission tomography (PET)

Traumatic brain injury (TBI) has been discussed as a risk factor for Alzheimer's disease (AD) due to its association with dementia risk and earlier cognitive symptom onset. However, the mechanisms behind this relationship are unclear. Some studies have suggested TBI may increase pathological protein deposition in an AD-like pattern; others have failed to find such associations. This review covers literature that uses positron emission tomography (PET) of amyloid-β and/or tau to examine subjects with history of TBI who are at risk for AD due to advanced age. A comprehensive literature search was conducted on January 9, 2023, and 24 resulting citations met inclusion criteria. Common methodological concerns included small samples, limited clinical detail about subjects' TBI, recall bias due to reliance on self-reported TBI, and an inability to establish causation. For both amyloid and tau, results were widespread but inconsistent. The regions which showed the most compelling evidence for increased amyloid deposition were the cingulate gyrus, cuneus/precuneus, and parietal lobe. Evidence for increased tau was strongest in the medial temporal lobe, entorhinal cortex, precuneus, and frontal, temporal, parietal, and occipital lobes. However, conflicting findings across most regions of interest in both amyloid- and tau-PET studies indicate the critical need for future work in expanded samples and with greater clinical detail to offer a clearer picture of the relationship between TBI and protein deposition in older subjects at risk for AD.

Fully automated production of [11C]PiB for clinical use on Trasis-AllinOne synthesizer module

Pittsburgh compound B ([11C]PiB) was the first broadly applied radiotracer with specificity for amyloid-β (Aβ) peptide aggregates in the brain and has since been established as the gold standard for positron emission tomography (PET) employed for clinical in vivo imaging of Aβ plaques, used for imaging applications of Alzheimer's disease (AD), related dementia, and other tauopathies. The use of [11C]PiB for routine PET studies is dependent on the production capabilities of each radiochemistry laboratory, subsequently a continuous effort is made to develop suitable and sustainable methods on a variety of auto synthesis platforms. Here we report a fully automated, multi-step radio synthesis, purification, and reformulation of [11C]PiB for PET imaging using the Trasis AllinOne synthesis unit, a commonly used commercial radiochemistry module. We performed three validation runs to evaluate the reproducibility and to verify that the acceptable criteria were met for the release of clinical-grade [11C]PiB using a Trasis AllinOne auto radiosynthesis unit. Solid phase supported radiolabeling was performed through the capture of precursor (6-OH-BTA-0) on a C18 solid phase extraction (SPE) cartridge and subsequent flushing of gaseous [11C]Methyl triflate(MeOTf) through the Sep-Pak for carbon-11 (11C) N-methylation. Starting with 92.5 GBq [11C]CO2, [11C]PiB synthesis was completed in approximately 25 min after cyclotron end of bombardment with an injectable dose >7.0 GBq at end of the synthesis. The radiopharmaceutical product met all quality control criteria and specifications for use in human studies.

Unveiling the influence of daily dietary patterns on brain cortical structure: insights from bidirectional Mendelian randomization

Cognitive impairment is a significant concern in aging populations. This study utilized Mendelian randomization analysis to explore the impact of dietary habits and macro-nutrients on cortical structure. A bidirectional Mendelian randomization approach was employed, incorporating large-scale genetic data on dietary habits and brain cortical structure. The results did not reveal significant causal relationships between dietary factors and overall cortical structure and thickness. However, specific dietary factors showed associations with cortical structure in certain regions. For instance, fat intake affected six cortical regions, while milk, protein, fruits, and water were associated with changes in specific regions. Reverse analysis suggested that cortical thickness influenced the consumption of alcohol, carbohydrates, coffee, and fish. These findings contribute to understanding the potential mechanisms underlying the role of dietary factors in cognitive function changes and provide evidence supporting the existence of the gut-brain axis.

The RODI mHealth app Insight: Machine-Learning-Driven Identification of Digital Indicators for Neurodegenerative Disorder Detection

Neurocognitive Disorders (NCDs) pose a significant global health concern, and early detection is crucial for optimizing therapeutic outcomes. In parallel, mobile health apps (mHealth apps) have emerged as a promising avenue for assisting individuals with cognitive deficits. Under this perspective, we pioneered the development of the RODI mHealth app, a unique method for detecting aligned with the criteria for NCDs using a series of brief tasks. Utilizing the RODI app, we conducted a study from July to October 2022 involving 182 individuals with NCDs and healthy participants. The study aimed to assess performance differences between healthy older adults and NCD patients, identify significant performance disparities during the initial administration of the RODI app, and determine critical features for outcome prediction. Subsequently, the results underwent machine learning processes to unveil underlying patterns associated with NCDs. We prioritize the tasks within RODI based on their alignment with the criteria for NCDs, thus acting as key digital indicators for the disorder. We achieve this by employing an ensemble strategy that leverages the feature importance mechanism from three contemporary classification algorithms. Our analysis revealed that tasks related to visual working memory were the most significant in distinguishing between healthy individuals and those with an NCD. On the other hand, processes involving mental calculations, executive working memory, and recall were less influential in the detection process. Our study serves as a blueprint for future mHealth apps, offering a guide for enhancing the detection of digital indicators for disorders and related conditions.

Eligibility for Anti-Amyloid Treatment in a Population-Based Study of Cognitive Aging

BACKGROUND AND OBJECTIVES

Treatment options for Alzheimer disease (AD) are limited and have focused mainly on symptomatic therapy and improving quality of life. Recently, lecanemab, an anti-β-amyloid monoclonal antibody (mAb), received accelerated approval by the US Food and Drug Administration for treatment in the early stages of biomarker-confirmed symptomatic AD. An additional anti-β-amyloid mAb, aducanumab, was approved in 2021, and more will potentially become available in the near future. Research on the applicability and generalizability of the anti-β-amyloid mAb eligibility criteria on adults with biomarkers available in the general population has been lacking. The study's primary aim was to apply the clinical trial eligibility criteria for lecanemab treatment to participants with early AD of the population-based Mayo Clinic Study of Aging (MCSA) and assess the generalizability of anti-amyloid treatment. The secondary aim of this study was to apply the clinical trial eligibility criteria for aducanumab treatment in MCSA participants.

METHODS

This cross-sectional study aimed to apply the clinical trial eligibility criteria for lecanemab and aducanumab treatment to participants with early AD of the population-based MCSA and assess the generalizability of anti-amyloid treatment.

RESULTS

Two hundred thirty-seven MCSA participants (mean age [SD] 80.9 [6.3] years, 54.9% male, and 97.5% White) with mild cognitive impairment (MCI) or mild dementia and increased brain amyloid burden by PiB PET comprised the study sample. Lecanemab trial's inclusion criteria reduced the study sample to 112 (47.3% of 237) participants. The trial's exclusion criteria further narrowed the number of potentially eligible participants to 19 (overall 8% of 237). Modifying the eligibility criteria to include all participants with MCI (instead of applying additional cognitive criteria) resulted in 17.4% of participants with MCI being eligible for lecanemab treatment. One hundred four participants (43.9% of 237) fulfilled the aducanumab clinical trial's inclusion criteria. The aducanumab trial's exclusion criteria further reduced the number of available participants, narrowing those eligible to 12 (5.1% of 237). Common exclusions were related to other chronic conditions and neuroimaging findings.

DISCUSSION

Findings estimate the limited eligibility in typical older adults with cognitive impairment for anti-β-amyloid mAbs.

Distinct Heterocyclic Moieties Govern the Selectivity of Thiophene-Vinylene-Based Ligands Towards Aβ or Tau Pathology in Alzheime's Disease

Distinct aggregated proteins are correlated with numerous neurodegenerative diseases and the development of ligands that selectively detect these pathological hallmarks is vital. Recently, the synthesis of thiophene-based optical ligands, denoted bi-thiophene-vinyl-benzothiazoles (bTVBTs), that could be utilized for selective assignment of tau pathology in brain tissue with Alzheime's disease (AD) pathology, was reported. Herein, we investigate the ability of these ligands to selectively distinguish tau deposits from aggregated amyloid-β (Aβ), the second AD associated pathological hallmark, when replacing the terminal thiophene moiety with other heterocyclic motifs. The selectivity for tau pathology was reduced when introducing specific heterocyclic motifs, verifying that specific molecular interactions between the ligands and the aggregates are necessary for selective detection of tau deposits. In addition, ligands having certain heterocyclic moieties attached to the central thiophene-vinylene building block displayed selectivity to aggregated Aβ pathology. Our findings provide chemical insights for the development of ligands that can distinguish between aggregated proteinaceous species consisting of different proteins and might also aid in creating novel agents for clinical imaging of tau pathology in AD.

Blood β-synuclein is related to amyloid PET positivity in memory clinic patients

INTRODUCTION

β-synuclein is an emerging blood biomarker to study synaptic degeneration in Alzheimer´s disease (AD), but its relation to amyloid-β (Αβ) pathology is unclear.

METHODS

We investigated the association of plasma β-synuclein levels with [18F] flutemetamol positron emission tomography (PET) in patients with AD dementia (n = 51), mild cognitive impairment (MCI-Aβ+ n = 18, MCI- Aβ- n = 30), non-AD dementias (n = 22), and non-demented controls (n = 5).

RESULTS

Plasma β-synuclein levels were higher in Aβ+ (AD dementia, MCI-Aβ+) than in Aβ- subjects (non-AD dementias, MCI-Aβ-) with good discrimination of Aβ+ from Aβ- subjects and prediction of Aβ status in MCI individuals. A positive correlation between plasma β-synuclein and Aβ PET was observed in multiple cortical regions across all lobes.

DISCUSSION

Plasma β-synuclein demonstrated discriminative properties for Aβ PET positive and negative subjects. Our data underline that β-synuclein is not a direct marker of Aβ pathology and suggest different longitudinal dynamics of synaptic degeneration versus amyloid deposition across the AD continuum.

HIGHLIGHTS

Blood and CSF β-synuclein levels are higher in Aβ+ than in Aβ- subjects. Blood β-synuclein level correlates with amyloid PET positivity in multiple regions. Blood β-synuclein predicts Aβ status in MCI individuals.

Eye movement patterns during viewing face images with neutral expressions in patients with early-stage Alzheimer's disease and amnestic mild cognitive impairment

BACKGROUND

Alzheimer's disease (AD) neuropathology affects the brain regions responsible for visuospatial skills. Accumulating evidence points to visual difficulties involving face processing in AD and amnestic mild cognitive impairment (aMCI). No study has so far examined eye movement patterns when viewing faces with neutral expressions in patients with AD.

AIM

The objective of this study aimed to examine the eye movements of patients with early-stage AD, aMCI, and healthy controls (HC) during viewing face images.

MATERIALS&METHODS

Thirty-one AD, 37 aMCI, and 33 HC were included in the study. Eye movements in facial stimuli were recorded with the EyeLink 1000 Plus eye-tracker.

RESULTS

Our findings showed that AD patients looked less at the eye area of interest than the nose and mouth areas of interest compared to aMCI and HC. Regardless of the group, all participants looked at the eye and nose areas of interest more and longer in the mouth area of interest. In addition, the first fixation duration to the eye area of interest of all participants was shorter than that of the nose and mouth.

DISCUSSION

Consistent with our study, studies in healthy adults revealed eye movement patterns that focused more on the eyes and nose. AD patients are unable to pay attention to the salient parts of faces, tending to focus instead on the non-informative parts.

CONCLUSION

Our study is the first to reveal eye movement differences in face processing in AD.

Docking for molecules that bind in a symmetric stack with SymDOCK

Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of much current interest. In recent structures, ligands bind in stacks in the tau fibrils to reflect the rotational and translational symmetry of the fibril itself; in these structures the ligands make few interactions with the protein but interact extensively with each other. To exploit this symmetry and stacking, we developed SymDOCK, a method to dock molecules that follow the protein's symmetry. For each prospective ligand pose, we apply the symmetry operation of the fibril to generate a self-interacting and fibril-interacting stack, checking that doing so will not cause a clash between the original molecule and its image. Absent a clash, we retain that pose and add the ligand-ligand van der Waals energy to the ligand's docking score (here using DOCK3.8). We can check these geometries and energies using an implementation of ANI, a neural network-based quantum-mechanical evaluation of the ligand stacking energies. In retrospective calculations, symmetry docking can reproduce the poses of three tau PET tracers whose structures have been determined. More convincingly, in a prospective study SymDOCK predicted the structure of the PET tracer MK-6240 bound in a symmetrical stack to AD PHF tau before that structure was determined; the docked pose was used to determine how MK-6240 fit the cryo-EM density. In proof-of-concept studies, SymDOCK enriched known ligands over property-matched decoys in retrospective screens without sacrificing docking speed, and can address large library screens that seek new symmetrical stackers. Future applications of this approach will be considered.

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

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

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.

Structural mechanism for specific binding of chemical compounds to amyloid fibrils

Amyloid fibril is an important pharmaceutical target for diagnostic and therapeutic treatment of neurodegenerative diseases. However, rational design of chemical compounds that interact with amyloid fibrils is unachievable due to the lack of mechanistic understanding of the ligand-fibril interaction. Here we used cryoelectron microscopy to survey the amyloid fibril-binding mechanism of a series of compounds including classic dyes, (pre)clinical imaging tracers and newly identified binders from high-throughput screening. We obtained clear densities of several compounds in complex with an α-synuclein fibril. These structures unveil the basic mechanism of the ligand-fibril interaction, which exhibits remarkable difference from the canonical ligand-protein interaction. In addition, we discovered a druggable pocket that is also conserved in the ex vivo α-synuclein fibrils from multiple system atrophy. Collectively, these findings expand our knowledge of protein-ligand interaction in the amyloid fibril state, which will enable rational design of amyloid binders in a medicinally beneficial way.

Plasma biomarkers identify older adults at risk of Alzheimer's disease and related dementias in a real-world population-based cohort

INTRODUCTION

Plasma biomarkers-cost effective, non-invasive indicators of Alzheimer's disease (AD) and related disorders (ADRD)-have largely been studied in clinical research settings. Here, we examined plasma biomarker profiles and their associated factors in a population-based cohort to determine whether they could identify an at-risk group, independently of brain and cerebrospinal fluid biomarkers.

METHODS

We measured plasma phosphorylated tau181 (p-tau181), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and amyloid beta (Aβ)42/40 ratio in 847 participants from a population-based cohort in southwestern Pennsylvania.

RESULTS

K-medoids clustering identified two distinct plasma Aβ42/40 modes, further categorizable into three biomarker profile groups: normal, uncertain, and abnormal. In different groups, plasma p-tau181, NfL, and GFAP were inversely correlated with Aβ42/40, Clinical Dementia Rating, and memory composite score, with the strongest associations in the abnormal group.

DISCUSSION

Abnormal plasma Aβ42/40 ratio identified older adult groups with lower memory scores, higher dementia risks, and higher ADRD biomarker levels, with potential implications for population screening.

HIGHLIGHTS

Population-based plasma biomarker studies are lacking, particularly in cohorts without cerebrospinal fluid or neuroimaging data. In the Monongahela-Youghiogheny Healthy Aging Team study (n = 847), plasma biomarkers associated with worse memory and Clinical Dementia Rating (CDR), apolipoprotein E ε4, and greater age. Plasma amyloid beta (Aβ)42/40 ratio levels allowed clustering participants into abnormal, uncertain, and normal groups. Plasma Aβ42/40 correlated differently with neurofilament light chain, glial fibrillary acidic protein, phosphorylated tau181, memory composite, and CDR in each group. Plasma biomarkers can enable relatively affordable and non-invasive community screening for evidence of Alzheimer's disease and related disorders pathophysiology.

Plasma p-tau231 and p-tau217 inform on tau tangles aggregation in cognitively impaired individuals

INTRODUCTION

Phosphorylated tau (p-tau) biomarkers have been recently proposed to represent brain amyloid-β (Aβ) pathology. Here, we evaluated the plasma biomarkers' contribution beyond the information provided by demographics (age and sex) to identify Aβ and tau pathologies in individuals segregated as cognitively unimpaired (CU) and impaired (CI).

METHODS

We assessed 138 CU and 87 CI with available plasma p-tau231, 217+ , and 181, Aβ42/40, GFAP and Aβ- and tau-PET.

RESULTS

In CU, only plasma p-tau231 and p-tau217+ significantly improved the performance of the demographics in detecting Aβ-PET positivity, while no plasma biomarker provided additional information to identify tau-PET positivity. In CI, p-tau217+ and GFAP significantly contributed to demographics to identify both Aβ-PET and tau-PET positivity, while p-tau231 only provided additional information to identify tau-PET positivity.

DISCUSSION

Our results support plasma p-tau231 and p-tau217+ as state markers of early Aβ deposition, but in later disease stages they inform on tau tangle accumulation.

HIGHLIGHTS

It is still unclear how much plasma biomarkers contribute to identification of AD pathology across the AD spectrum beyond the information already provided by demographics (age + sex). Plasma p-tau231 and p-tau217+ contribute to demographic information to identify brain Aβ pathology in preclinical AD. In CI individuals, plasma p-tau231 contributes to age and sex to inform on the accumulation of tau tangles, while p-tau217+ and GFAP inform on both Aβ deposition and tau pathology.

Application of Deep Learning for Prediction of Alzheimer's Disease in PET/MR Imaging

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide. Positron emission tomography/magnetic resonance (PET/MR) imaging is a promising technique that combines the advantages of PET and MR to provide both functional and structural information of the brain. Deep learning (DL) is a subfield of machine learning (ML) and artificial intelligence (AI) that focuses on developing algorithms and models inspired by the structure and function of the human brain's neural networks. DL has been applied to various aspects of PET/MR imaging in AD, such as image segmentation, image reconstruction, diagnosis and prediction, and visualization of pathological features. In this review, we introduce the basic concepts and types of DL algorithms, such as feed forward neural networks, convolutional neural networks, recurrent neural networks, and autoencoders. We then summarize the current applications and challenges of DL in PET/MR imaging in AD, and discuss the future directions and opportunities for automated diagnosis, predictions of models, and personalized medicine. We conclude that DL has great potential to improve the quality and efficiency of PET/MR imaging in AD, and to provide new insights into the pathophysiology and treatment of this devastating disease.

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.

Theranostic in GLP-1R molecular imaging: challenges and emerging opportunities

Theranostic in nuclear medicine combines diagnostic imaging and internal irradiation therapy using different therapeutic nuclear probes for visual diagnosis and precise treatment. GLP-1R is a popular receptor target in endocrine diseases, non-alcoholic steatohepatitis, tumors, and other areas. Likewise, it has also made breakthroughs in the development of molecular imaging. It was recognized that GLP-1R imaging originated from the study of insulinoma and afterwards was expanded in application including islet transplantation, pancreatic β-cell mass measurement, and ATP-dependent potassium channel-related endocrine diseases. Fortunately, GLP-1R molecular imaging has been involved in ischemic cardiomyocytes and neurodegenerative diseases. These signs illustrate the power of GLP-1R molecular imaging in the development of medicine. However, it is still limited to imaging diagnosis research in the current molecular imaging environment. The lack of molecular-targeted therapeutics related report hinders its radiology theranostic. In this article, the current research status, challenges, and emerging opportunities for GLP-1R molecular imaging are discussed in order to open a new path for theranostics and to promote the evolution of molecular medicine.

A Novel Brain PET Radiotracer for Imaging Alpha Synuclein Fibrils in Multiple System Atrophy

Abnormal α-synuclein (α-syn) aggregation characterizes α-synucleinopathies, including Parkinson's disease (PD) and multiple system atrophy (MSA). However, no suitable positron emission tomography (PET) radiotracer for imaging α-syn in PD and MSA exists currently. Our structure-activity relationship studies identified 4-methoxy-N-(4-(3-(pyridin-2-yl)-3,8-diazabicyclo[3.2.1]octan-8-yl)phenyl)benzamide (4i) as a PET radiotracer candidate for imaging α-syn. In vitro assays revealed high binding of 4i to recombinant α-syn fibrils (inhibition constant (Ki) = 6.1 nM) and low affinity for amyloid beta (Aβ) fibrils in Alzheimer's disease (AD) homogenates. However, [3H]4i also exhibited high specific binding to AD, progressive supranuclear palsy, and corticobasal degeneration tissues as well as PD and MSA tissues, suggesting notable affinity to tau. Nevertheless, the specific binding to pathologic α-syn aggregates in MSA post-mortem brain tissues was significantly higher than in PD tissues. This finding demonstrated the potential use of [11C]4i as a PET tracer for imaging α-syn in MSA patients. Nonhuman primate PET studies confirmed good brain uptake and rapid washout for [11C]4i.

Chemical design of radioiodinated probes with a metabolizable linkage for target-selective imaging of systemic amyloidosis

INTRODUCTION

Systemic amyloidosis is a rare disease caused by the deposition of amyloid fibrils in various organs. Amyloid-targeted radiopharmaceuticals have been developed and applied to diagnose systemic amyloidosis peripherally; however, high-contrast imaging has not been achieved because of the high background signals in normal organs. To overcome this problem, we designed an amyloid-targeted radioiodinated probe 1 with a metabolizable linkage (ester bond) to release of radiolabeled metabolites (m-iodohippuric acid) in normal organs that could be rapidly excreted in the urine.

METHODS

Compound 1 was synthesized by conjugating 2-(4-(methylamino)phenyl)benzo[d]thiazol-6-ol, an amyloid-targeting compound, with m-iodohippuric acid. [125I]1 was synthesized via iododestannylation using a tributyltin precursor. Mouse models of amyloid A (AA) amyloidosis, a type of systemic amyloidosis, were prepared by administering amyloid-enhancing factor to mice and used for in vitro autoradiography using organ sections and in vivo evaluation.

RESULTS

[125I]1 was obtained with a radiochemical yield of 59% and radiochemical purity of over 95%. An in vitro autoradiographic study demonstrated that [125I]1 specifically binds to amyloid in the splenic tissue. Upon administration to normal mice, [125I]1 was distributed to organs throughout the body, followed by the rapid excretion of radioactivity in the urine as m-[125I]iodohippuric acid. Furthermore, ex vivo autoradiography showed that [125I]1 bound to the amyloid formed around the follicles in the spleens of AA amyloidosis model mice.

CONCLUSION

These results suggest that the interposition of a metabolizable linkage between an amyloid-targeting moiety and a radiolabeled hippuric acid would be useful in the design of radiopharmaceuticals for high-contrast imaging of systemic amyloidosis.

Chronotype is Associated with Sleep Quality in Older Adults

Introduction

Disrupted sleep is common in individuals with Alzheimer's disease (AD) and may be a marker for AD risk. The timing of sleep or chronotype affects sleep-wake activity and is also associated with AD, but little is known about links between sleep and chronotype in older adults. In this study, we tested if different measures of sleep and chronotype are associated among older adults even after adjusting for multiple potentially confounding variables.

Methods

Participants (N=243) with a mean age of 74 underwent standardized cognitive assessments, measurement of CSF AD biomarkers, and sleep monitoring via single-channel EEG, actigraphy, and self-reported sleep logs. Chronotype was defined as the midpoint of sleep measured by actigraphy.

Results

Later mid-point of sleep (i.e., late chronotype) was associated with African American race and greater night-to-night variability in the sleep mid-point. After controlling for age, race, sex, cognitive status, AD biomarkers, and sleep disorders, a later mid-point of sleep was associated with longer rapid eye movement (REM) onset latency, decreased REM sleep time, lower sleep efficiency, increased sleep onset latency, and more awakenings at night. Late chronotype was also associated with increased <2 Hz non-REM slow-wave activity.

Conclusions

To identify individuals at risk for cognitive impairment before symptoms onset, non-invasive in vivo markers of brain function, such as sleep, are needed to track both future risk of cognitive impairment and response to interventions. Chronotype is a potential modifiable AD risk factor and should also be taken into account when using sleep as a marker for AD risk.

Navigating Early Alzheimer's Diagnosis: A Comprehensive Review of Diagnostic Innovations

The hunt for early Alzheimer's disease detection has created cutting-edge diagnostic instruments with enormous promise. This article examines the many facets of these developments, focusing on how they have revolutionised diagnosis and patient outcomes. These tools make it possible to detect tiny brain changes even before they give birth to clinical symptoms by combining cutting-edge biomarkers, neuroimaging methods, and machine-learning algorithms. A significant opportunity for therapies that can slow the course of the disease exists during this early detection stage. Additionally, these cutting-edge techniques improve diagnostic precision, objectivity, and accessibility. Liquid biopsies and blood-based biomarkers provide non-invasive alternatives, filling accessibility gaps in diagnosis. While issues with standardisation, ethics, and data integration continue, collaboration within research, clinical practice, and policy realms fuels positive developments. As technology advances, the way towards better Alzheimer's diagnosis becomes more evident, giving patients and families dealing with this difficult illness fresh hope. The synergy between scientific advancement and compassionate treatment is crucial for improving Alzheimer's disease diagnosis, as this paper emphasises.

Frontal and temporal lobe correlates of verbal learning and memory in aMCI and suspected Alzheimer's disease dementia

Alzheimer's disease is primarily known for deficits in learning and retaining new information. This has long been associated with pathological changes in the mesial temporal lobes. The role of the frontal lobes in memory in Alzheimer's disease is less well understood. In this study, we examined the role of the frontal lobes in learning, recognition, and retention of new verbal information, as well as the presence of specific errors (i.e., intrusions and false-positive errors). Participants included one hundred sixty-seven patients clinically diagnosed with amnestic mild cognitive impairment or suspected Alzheimer's disease dementia who were administered the California Verbal Learning Test and completed high-resolution MRI. We confirmed the role of the mesial temporal lobes in learning and retention, including the volumes of the hippocampus, entorhinal cortex, and parahippocampal gyrus. In addition, false-positive errors were associated with all volumes of the mesial temporal lobes and widespread areas within the frontal lobes. Errors of intrusion were related to the supplementary motor cortex and hippocampus. Most importantly, the mesial temporal lobes interacted with the frontal lobes for learning, recognition, and memory errors. Lower volumes in both regions explained more performance variance than any single structure. This study supports the interaction of the frontal lobes with the temporal lobes in many aspects of memory in Alzheimer's disease.

Preclinical Evaluation of Novel PET Probes for Dementia

The development of novel PET imaging agents that selectively bind specific dementia-related targets can contribute significantly to accurate, differential and early diagnosis of dementia causing diseases and support the development of therapeutic agents. Consequently, in recent years there has been a growing body of literature describing the development and evaluation of potential new promising PET tracers for dementia. This review article provides a comprehensive overview of novel dementia PET probes under development, classified by their target, and pinpoints their preclinical evaluation pathway, typically involving in silico, in vitro and ex/in vivo evaluation. Specific target-associated challenges and pitfalls, requiring extensive and well-designed preclinical experimental evaluation assays to enable successful clinical translation and avoid shortcomings observed for previously developed 'well-established' dementia PET tracers are highlighted in this review.

The functional role of the precuneus

Recent advancements in computational approaches and neuroimaging techniques have refined our understanding of the precuneus. While previously believed to be largely a visual processing region, the importance of the precuneus in complex cognitive functions has been previously less familiar due to a lack of focal lesions in this deeply seated region, but also a poor understanding of its true underlying anatomy. Fortunately, recent studies have revealed significant information on the structural and functional connectivity of this region, and this data has provided a more detailed mechanistic understanding of the importance of the precuneus in healthy and pathologic states. Through improved resting-state functional MRI analyses, it has become clear that the function of the precuneus can be better understood based on its functional association with large scale brain networks. Dual default mode network systems have been well explained in recent years in supporting episodic memory and theory of mind; however, a novel 'para-cingulate' network, which is a subnetwork of the larger central executive network, with likely significant roles in self-referential processes and related psychiatric symptoms is introduced here and requires further clarification. Importantly, detailed anatomic studies on the precuneus structural connectivity inside and beyond the cingulate cortex has demonstrated the presence of large structural white matter connections, which provide an additional layer of meaning to the structural-functional significance of this region and its association with large scale brain networks. Together, the structural-functional connectivity of the precuneus has provided central elements which can model various neurodegenerative diseases and psychiatric disorders, such as Alzheimer's disease and depression.