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

Apolipoprotein E and Alzheimer's disease pathology in African American older adults

The apolipoprotein-E4 (APOE*4) and apolipoprotein-E2 (APOE*2) alleles are more common in African American versus non-Hispanic white populations, but relationships of both alleles with Alzheimer's disease (AD) pathology among African American individuals are unclear. We measured APOE allele and β-amyloid (Aβ) and tau using blood samples and positron emission tomography (PET) images, respectively. Individual regression models tested associations of each APOE allele with Aβ or tau PET overall, stratified by racialized group, and with a racialized group interaction. We included 358 older adults (42% African American) with Aβ PET, 134 (29% African American) of whom had tau PET. APOE*4 was associated with higher Aβ in non-Hispanic white (P < 0.0001), but not African American (P = 0.64) participants; racialized group modified the association between APOE*4 and Aβ (P < 0.0001). There were no other racialized group differences. These results suggest that the association of APOE*4 and Aβ differs between African American and non-Hispanic white populations. Other drivers of AD pathology in African American populations should be identified as potential therapeutic targets.

Advances in blood biomarkers for Alzheimer disease (AD): A review

Alzheimer disease (AD) and Alzheimer Disease and Related Dementias (AD/ADRD) are growing public health challenges globally affecting millions of older adults, necessitating concerted efforts to advance our understanding and management of these conditions. AD is a progressive neurodegenerative disorder characterized pathologically by amyloid plaques and tau neurofibrillary tangles that are the primary cause of dementia in older individuals. Early and accurate diagnosis of AD dementia is crucial for effective intervention and treatment but has proven challenging to accomplish. Although testing for AD brain pathology with cerebrospinal fluid (CSF) or positron emission tomography (PET) has been available for over 2 decades, most patients never underwent this testing because of inaccessibility, high out-of-pocket costs, perceived risks, and the lack of AD-specific treatments. However, in recent years, rapid progress has been made in developing blood biomarkers for AD/ADRD. Consequently, blood biomarkers have emerged as promising tools for non-invasive and cost-effective diagnosis, prognosis, and monitoring of AD progression. This review presents the evolving landscape of blood biomarkers in AD/ADRD and explores their potential applications in clinical practice for early detection, prognosis, and therapeutic interventions. It covers recent advances in blood biomarkers, including amyloid beta (Aβ) peptides, tau protein, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP). It also discusses their diagnostic and prognostic utility while addressing associated challenges and limitations. Future research directions in this rapidly evolving field are also proposed.

Ligand-based design of [18F]OXD-2314 for PET imaging in non-Alzheimer's disease tauopathies

Positron emission tomography (PET) imaging of tau aggregation in Alzheimer's disease (AD) is helping to map and quantify the in vivo progression of AD pathology. To date, no high-affinity tau-PET radiopharmaceutical has been optimized for imaging non-AD tauopathies. Here we show the properties of analogues of a first-in-class 4R-tau lead, [18F]OXD-2115, using ligand-based design. Over 150 analogues of OXD-2115 were synthesized and screened in post-mortem brain tissue for tau affinity against [3H]OXD-2115, and in silico models were used to predict brain uptake. [18F]OXD-2314 was identified as a selective, high-affinity non-AD tau PET radiotracer with favorable brain uptake, dosimetry, and radiometabolite profiles in rats and non-human primate and is being translated for first-in-human PET studies.

Evaluation of Neurodegenerative Disorders with Amyloid-β, Tau, and Dopaminergic PET Imaging: Interpretation Pitfalls

Antiamyloid therapies for Alzheimer disease recently entered clinical practice, making imaging biomarkers for Alzheimer disease even more relevant to guiding patient management. Amyloid and tau PET are valuable tools that can provide objective evidence of Alzheimer pathophysiology in living patients and will increasingly be used to complement 18F-FDG PET in the diagnostic evaluation of cognitive impairment and dementia. Parkinsonian syndromes, also common causes of dementia, can likewise be evaluated with a PET imaging biomarker,18F-DOPA, allowing in vivo assessment of the presynaptic dopaminergic neurons. Understanding the role of these PET biomarkers will help the nuclear medicine physician contribute to the appropriate diagnosis and management of patients with cognitive impairment and dementia. To successfully evaluate brain PET examinations for neurodegenerative diseases, knowledge of the necessary protocol details for obtaining a reliable imaging study, inherent limitations for each PET radiopharmaceutical, and pitfalls in image interpretation is critical. This review will focus on underlying concepts for interpreting PET examinations, important procedural details, and guidance for avoiding potential interpretive pitfalls for amyloid, tau, and dopaminergic PET examinations.

Redesign of a thioflavin-T-binding protein with a flat β-sheet to evaluate a thioflavin-T-derived photocatalyst with enhanced affinity

Amyloids, proteinous aggregates with β-sheet-rich fibrils, are involved in several neurodegenerative diseases such as Alzheimer's disease; thus, their detection is critically important. The most common fluorescent dye for amyloid detection is thioflavin-T (ThT), which shows on/off fluorescence upon amyloid binding. We previously reported that an engineered globular protein with a flat β-sheet, peptide self-assembly mimic (PSAM), can be used as an amyloid binding model. In this study, we further explored the residue-specific properties of ThT-binding to the flat β-sheet by introducing systematic mutations. We found that site-specific mutations at the ThT-binding channel enhanced affinity. We also evaluated the binding of a ThT-based photocatalyst, which showed the photooxygenation activity on the amyloid fibril upon light radiation. Upon binding of the photocatalyst to the PSAM variant, singlet oxygen-generating activity was observed. The results of this study expand our understanding of the detailed binding mechanism of amyloid-specific molecules.

The Study of Remyelinating Therapies in Multiple Sclerosis: Visual Outcomes as a Window Into Repair

INTRODUCTION

Amelioration of disability in multiple sclerosis requires the development of complementary therapies that target neurodegeneration and promote repair. Remyelination is a promising neuroprotective strategy that may protect axons from damage and subsequent neurodegeneration.

METHODS

A review of key literature plus additional targeted search of PubMed and Google Scholar was conducted.

RESULTS

There has been a rapid expansion of clinical trials studying putative remyelinating candidates, but further growth of the field is limited by the lack of consensus on key aspects of trial design. We have not yet defined the ideal study population, duration of therapy, or the appropriate outcome measures to detect remyelination in humans. The varied natural history of multiple sclerosis, coupled with the short time frame of phase II clinical trials, requires that we develop and validate biomarkers of remyelination that can serve as surrogate endpoints in clinical trials.

CONCLUSIONS

We propose that the visual system may be the most well-suited and validated model for the study potential remyelinating agents. In this review, we discuss the pathophysiology of demyelination and summarize the current clinical trial landscape of remyelinating agents. We present some of the challenges in the study of remyelinating agents and discuss current potential biomarkers of remyelination and repair, emphasizing both established and emerging visual outcome measures.

Atrophy links lower novelty-related locus coeruleus connectivity to cognitive decline in preclinical AD

INTRODUCTION

Animal research has shown that tau pathology in the locus coeruleus (LC) is associated with reduced norepinephrine signaling, lower projection density to the medial temporal lobe (MTL), atrophy, and cognitive impairment. We investigated the contribution of LC-MTL functional connectivity (FCLC-MTL) on cortical atrophy across Braak stage regions and its impact on cognition.

METHODS

We analyzed functional magnetic resonance imaging and amyloid beta (Aβ) positron emission tomography data from 128 cognitively normal participants, associating novelty-related FCLC-MTL with longitudinal atrophy and cognition with and without Aβ moderation.

RESULTS

Cross-sectionally, lower FCLC-MTL was associated with atrophy in Braak stage II regions. Longitudinally, atrophy in Braak stage 2 to 4 regions related to lower baseline FCLC-MTL at elevated levels of Aβ, but not to other regions. Atrophy in Braak stage 2 regions mediated the relation between FCLC-MTL and subsequent cognitive decline.

DISCUSSION

FCLC-MTL is implicated in Aβ-related cortical atrophy, suggesting that LC-MTL connectivity could confer neuroprotective effects in preclinical AD.

HIGHLIGHTS

Novelty-related functional magnetic resonance imaging (fMRI) LC-medial temporal lobe (MTL) connectivity links to longitudinal Aβ-dependent atrophy. This relationship extended to higher Braak stage regions with increasing Aβ burden. Longitudinal MTL atrophy mediated the LC-MTL connectivity-cognition relationship. Our findings mirror the animal data on MTL atrophy following NE signal dysfunction.

The clinical importance of suspected non-Alzheimer disease pathophysiology

The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) - a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP.

Anti-amyloid Antibody Therapies for Alzheimer's Disease

Alzheimer's disease (AD) is the most common cause of dementia, which is characterized by a progressive neurodegenerative disorder that is extremely difficult to treat and severely reduces quality of life. Amyloid beta (Aβ) has been the primary target of experimental therapies owing to the neurotoxicity of Aβ and the brain Aβ load detected in humans by amyloid positron emission tomography (PET) imaging. Recently completed phase 2 and 3 trials of third-generation anti-amyloid immunotherapies indicated clinical efficacy in significantly reducing brain Aβ load and inhibiting the progression of cognitive decline. Anti-amyloid immunotherapies are the first effective disease-modifying therapies for AD, and aducanumab and lecanemab were recently approved through the US Food and Drug Administration's accelerated approval pathway. However, these therapies still exhibit insufficient clinical efficacy and are associated with amyloid-related imaging abnormalities. Further advances in the field of AD therapeutics are required to revolutionize clinical AD treatment, dementia care, and preventive cognitive healthcare.

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

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

Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities in a community-dwelling cohort

INTRODUCTION

We evaluated associations between plasma and neuroimaging-derived biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities.

METHODS

We examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ-positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion-weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N = 299), mild cognitive impairment (MCI; N = 192), or dementia (DEM; N = 65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma-imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]).

RESULTS

Plasma biomarkers differed across diagnostic groups (DEM > MCI > CU), were altered in Aβ-PET-positive individuals, and were associated with poorer brain health and kidney function.

DISCUSSION

eGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers.

HIGHLIGHTS

Plasma biomarkers differ across diagnostic groups (DEM > MCI > CU) and are altered in Aβ-PET-positive individuals. Altered plasma biomarker levels are associated with poorer brain health and kidney function. Plasma and neuroimaging biomarker associations are largely independent of comorbidities.

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.

Patterns of Early Neocortical Amyloid-β Accumulation: A PET Population-Based Study

The widespread deposition of amyloid-β (Aβ) plaques in late-stage Alzheimer disease is well defined and confirmed by in vivo PET. However, there are discrepancies between which regions contribute to the earliest topographic Aβ deposition within the neocortex. Methods: This study investigated Aβ signals in the perithreshold SUV ratio range using Pittsburgh compound B (PiB) PET in a population-based study cross-sectionally and longitudinally. PiB PET scans from 1,088 participants determined the early patterns of PiB loading in the neocortex. Results: Early-stage Aβ loading is seen first in the temporal, cingulate, and occipital regions. Regional early deposition patterns are similar in both apolipoprotein ε4 carriers and noncarriers. Clustering analysis shows groups with different patterns of early amyloid deposition. Conclusion: These findings of initial Aβ deposition patterns may be of significance for diagnostics and understanding the development of Alzheimer disease phenotypes.

Crystal Violet Selectively Detects Aβ Oligomers but Not Fibrils In Vitro and in Alzheimer's Disease Brain Tissue

Deposition of extracellular Amyloid Beta (Aβ) and intracellular tau fibrils in post-mortem brains remains the only way to conclusively confirm cases of Alzheimer's Disease (AD). Substantial evidence, though, implicates small globular oligomers instead of fibrils as relevant biomarkers of, and critical contributors to, the clinical symptoms of AD. Efforts to verify and utilize amyloid oligomers as AD biomarkers in vivo have been limited by the near-exclusive dependence on conformation-selective antibodies for oligomer detection. While antibodies have yielded critical evidence for the role of both Aβ and tau oligomers in AD, they are not suitable for imaging amyloid oligomers in vivo. Therefore, it would be desirable to identify a set of oligomer-selective small molecules for subsequent development into Positron Emission Tomography (PET) probes. Using a kinetics-based screening assay, we confirm that the triarylmethane dye Crystal Violet (CV) is oligomer-selective for Aβ42 oligomers (AβOs) grown under near-physiological solution conditions in vitro. In postmortem brains of an AD mouse model and human AD patients, we demonstrate that A11 antibody-positive oligomers but not Thioflavin S (ThioS)-positive fibrils colocalize with CV staining, confirming in vitro results. Therefore, our kinetic screen represents a robust approach for identifying new classes of small molecules as candidates for oligomer-selective dyes (OSDs). Such OSDs, in turn, provide promising starting points for the development of PET probes for pre-mortem imaging of oligomer deposits in humans.

The AHA/ASA and DSM-V diagnostic criteria for vascular cognitive impairment identify cases with predominant vascular pathology

BACKGROUND

There are major challenges in determining the etiology of vascular cognitive impairment (VCI) clinically, especially in the presence of mixed pathologies, such as vascular and amyloid. Most recently, two criteria (American Heart Association/American Stroke Association (AHA/ASA) and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V)) have been proposed for the clinical diagnosis of VCI but have not as yet been validated using neuroimaging.

AIMS

This study aims to determine whether the AHA/ASA and DSM-V criteria for VCI can distinguish between cases with predominantly vascular pathology and cases with mixed pathology.

METHODS

A total of 186 subjects were recruited from a cross-sectional memory clinic-based study at the National University Hospital, Singapore. All subjects underwent clinical and neuropsychological assessment, magnetic resonance imaging (MRI) and carbon 11-labeled Pittsburgh Compound B ([11C] PiB) positron emission tomography (PET) scans. Diagnosis of the etiological subtypes of VCI (probable vascular mild cognitive impairment (VaMCI), possible VaMCI, non-VaMCI, probable vascular dementia (VaD), possible VaD, non-VaD) were performed following AHA/ASA and DSM-V criteria. Brain amyloid burden was determined for each subject with standardized uptake value ratio (SUVR) values ⩾1.5 classified as amyloid positive.

RESULTS

Using κ statistics, both criteria had excellent agreement for probable VaMCI, probable VaD, and possible VaD (κ = 1.00), and good for possible VaMCI (κ = 0.71). Using the AHA/ASA criteria, the amyloid positivity of probable VaMCI (3.8%) and probable VaD (15%) was significantly lower compared to possible VaMCI (26.7%), non-VaMCI (33.3%), possible VaD (73.3%), and non-VaD (76.2%) (p < 0.001). Similarly, using the DSM-V criteria, the amyloid positivity of probable VaMCI (3.8%) and probable VaD (15%) was significantly lower compared to possible VaMCI (26.3%), non-VaMCI (32.1%), possible VaD (73.3%), and non-VaD (76.2%) (p < 0.001). In both criteria, there was good agreement in differentiating individuals with non-VaD and possible VaD, with significantly higher (p < 0.001) global [11C]-PiB SUVR, from individuals with probable VaMCI and probable VaD, who had predominant vascular pathology.

CONCLUSION

The AHA/ASA and DSM-V criteria for VCI can identify VCI cases with little to no concomitant amyloid pathology, hence supporting the utility of AHA/ASA and DSM-V criteria in diagnosing patients with predominant vascular pathology.

DATA ACCESS STATEMENT

Data supporting this study are available from the Memory Aging and Cognition Center, National University of Singapore. Access to the data is subject to approval and a data sharing agreement due to University policy.

Cancer Immunotherapy and Medical Imaging Research Trends from 2003 to 2023: A Bibliometric Analysis

Purpose

With the rapid development of immunotherapy, cancer treatment has entered a new phase. Medical imaging, as a primary diagnostic method, is closely related to cancer immunotherapy. However, until now, there has been no systematic bibliometric analysis of the state of this field. Therefore, the main purpose of this article is to clarify the past research trajectory, summarize current research hotspots, reveal dynamic scientific developments, and explore future research directions.

Patients and Methods

A comprehensive search was conducted on the Web of Science Core Collection (WoSCC) database to identify publications related to immunotherapy specifically for the medical imaging of carcinoma. The search spanned the period from the year 2003 to 2023. Several analytical tools were employed. These included CiteSpace (6.2.4), and the Microsoft Office Excel (2016).

Results

By searching the database, a total of 704 English articles published between 2003 and 2023 were obtained. We have observed a rapid increase in the number of publications since 2018. The two most active countries are the United States (n=265) and China (n=170). Pittock, Sean J and Abu-sbeih, Hamzah are very concerned about the relationship between cancer immunotherapy and medical images and have published more academic papers (n = 5; n = 4). Among the top 10 co-cited authors, Topalian Sl (n=43) cited ranked first, followed by Graus F (n=40) cited. According to clustering, timeline, and burst word analysis, the results show that the current research focus is on "MRI", "deep learning", "tumor microenvironment" and so on.

Conclusion

Medical imaging and cancer immunotherapy are hot topics. The United States is the country with the most publications and the greatest influence in this field, followed by China. "MRI", "PET/PET-CT", "deep learning", "immune-related adverse events" and "tumor microenvironment" are currently hot research topics and potential targets.

Midpoint of sleep is associated with sleep quality in older adults with and without symptomatic Alzheimer's disease

Introduction

Disrupted sleep is common in individuals with Alzheimer's disease (AD) and may be a marker for AD risk. The timing of sleep affects sleep-wake activity and is also associated with AD, but little is known about links between sleep architecture and the midpoint of sleep in older adults. In this study, we tested if the midpoint of sleep is associated with different measures of sleep architecture, AD biomarkers, and cognitive status among older adults with and without symptomatic AD.

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, a home sleep apnea test, and self-reported sleep logs. The midpoint of sleep was defined by actigraphy.

Results

A later midpoint of sleep was associated with African-American race and greater night-to-night variability in the sleep midpoint. After adjusting for multiple potential confounding factors, a later sleep midpoint was associated with longer rapid-eye movement (REM) onset latency, decreased REM sleep time, more actigraphic awakenings at night, and higher < 2 Hz non-REM slow-wave activity.

Conclusions

Noninvasive in vivo markers of brain function, such as sleep, are needed to track both future risk of cognitive impairment and response to interventions in older adults at risk for AD. Sleep timing is associated with multiple other sleep measures and may affect their utility as markers of AD. The midpoint of sleep may be changed through behavioral intervention and should be taken into account when using sleep as a marker for AD risk.

Thiophene-Based Ligands for Specific Assignment of Distinct Aβ Pathologies in Alzheimer's Disease

Aggregated species of amyloid-β (Aβ) are one of the pathological hallmarks in Alzheimer's disease (AD), and ligands that selectively target different Aβ deposits are of great interest. In this study, fluorescent thiophene-based ligands have been used to illustrate the features of different types of Aβ deposits found in AD brain tissue. A dual-staining protocol based on two ligands, HS-276 and LL-1, with different photophysical and binding properties, was developed and applied on brain tissue sections from patients affected by sporadic AD or familial AD associated with the PSEN1 A431E mutation. When binding to Aβ deposits, the ligands could easily be distinguished for their different fluorescence, and distinct staining patterns were revealed for these two types of AD. In sporadic AD, HS-276 consistently labeled all immunopositive Aβ plaques, whereas LL-1 mainly stained cored and neuritic Aβ deposits. In the PSEN1 A431E cases, each ligand was binding to specific types of Aβ plaques. The ligand-labeled Aβ deposits were localized in distinct cortical layers, and a laminar staining pattern could be seen. Biochemical characterization of the Aβ aggregates in the individual layers also showed that the variation of ligand binding properties was associated with certain Aβ peptide signatures. For the PSEN1 A431E cases, it was concluded that LL-1 was binding to cotton wool plaques, whereas HS-276 mainly stained diffuse Aβ deposits. Overall, our findings showed that a combination of ligands was essential to identify distinct aggregated Aβ species associated with different forms of AD.

Gray matter gamma-hydroxy-butyric acid and glutamate reflect beta-amyloid burden at old age

Gamma-hydroxy-butyric acid (GABA) and glutamate are neurotransmitters with essential importance for cognitive processing. Here, we investigate relationships between GABA, glutamate, and brain ß-amyloid (Aß) burden before clinical manifestation of Alzheimer's disease (AD). Thirty cognitively healthy adults (age 69.9 ± 6 years) received high-resolution atlas-based 1H-magnetic resonance spectroscopic imaging (MRSI) at ultra-high magnetic field strength of 7 Tesla for gray matter-specific assessment of GABA and glutamate. We assessed Aß burden with positron emission tomography and risk factors for AD. Higher gray matter GABA and glutamate related to higher Aß-burden (ß = 0.60, p < 0.05; ß = 0.64, p < 0.02), with positive effect modification by apolipoprotein-E-epsilon-4-allele (APOE4) (p = 0.01-0.03). GABA and glutamate negatively related to longitudinal change in verbal episodic memory performance (ß = -0.48; p = 0.02; ß = -0.50; p = 0.01). In vivo measures of GABA and glutamate reflect early AD pathology at old age, in an APOE4-dependent manner. GABA and glutamate may represent promising biomarkers and potential targets for early therapeutic intervention and prevention.

Highlights

Gray matter-specific metabolic imaging with high-resolution atlas-based MRSI at 7 Tesla.Higher GABA and glutamate relate to ß-amyloid burden, in an APOE4-dependent manner.Gray matter GABA and glutamate identify older adults with high risk of future AD.GABA and glutamate might reflect altered synaptic and neuronal activity at early AD.

Amyloid-β prediction machine learning model using source-based morphometry across neurocognitive disorders

Previous studies have developed and explored magnetic resonance imaging (MRI)-based machine learning models for predicting Alzheimer's disease (AD). However, limited research has focused on models incorporating diverse patient populations. This study aimed to build a clinically useful prediction model for amyloid-beta (Aβ) deposition using source-based morphometry, using a data-driven algorithm based on independent component analyses. Additionally, we assessed how the predictive accuracies varied with the feature combinations. Data from 118 participants clinically diagnosed with various conditions such as AD, mild cognitive impairment, frontotemporal lobar degeneration, corticobasal syndrome, progressive supranuclear palsy, and psychiatric disorders, as well as healthy controls were used for the development of the model. We used structural MR images, cognitive test results, and apolipoprotein E status for feature selection. Three-dimensional T1-weighted images were preprocessed into voxel-based gray matter images and then subjected to source-based morphometry. We used a support vector machine as a classifier. We applied SHapley Additive exPlanations, a game-theoretical approach, to ensure model accountability. The final model that was based on MR-images, cognitive test results, and apolipoprotein E status yielded 89.8% accuracy and a receiver operating characteristic curve of 0.888. The model based on MR-images alone showed 84.7% accuracy. Aβ-positivity was correctly detected in non-AD patients. One of the seven independent components derived from source-based morphometry was considered to represent an AD-related gray matter volume pattern and showed the strongest impact on the model output. Aβ-positivity across neurological and psychiatric disorders was predicted with moderate-to-high accuracy and was associated with a probable AD-related gray matter volume pattern. An MRI-based data-driven machine learning approach can be beneficial as a diagnostic aid.

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

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

Mixture of regressions with multivariate responses for discovering subtypes in Alzheimer's biomarkers with detection limits

There is no gold standard for the diagnosis of Alzheimer's disease (AD), except from autopsies, which motivates the use of unsupervised learning. A mixture of regressions is an unsupervised method that can simultaneously identify clusters from multiple biomarkers while learning within-cluster demographic effects. Cerebrospinal fluid (CSF) biomarkers for AD have detection limits, which create additional challenges. We apply a mixture of regressions with a multivariate truncated Gaussian distribution (also called a censored multivariate Gaussian mixture of regressions or a mixture of multivariate tobit regressions) to over 3,000 participants from the Emory Goizueta Alzheimer's Disease Research Center and Emory Healthy Brain Study to examine amyloid-beta peptide 1-42 (Abeta42), total tau protein and phosphorylated tau protein in CSF with known detection limits. We address three gaps in the literature on mixture of regressions with a truncated multivariate Gaussian distribution: software availability; inference; and clustering accuracy. We discovered three clusters that tend to align with an AD group, a normal control profile and non-AD pathology. The CSF profiles differed by race, gender and the genetic marker ApoE4, highlighting the importance of considering demographic factors in unsupervised learning with detection limits. Notably, African American participants in the AD-like group had significantly lower tau burden.

PET Imaging in Dementia: Mini-Review and Canadian Perspective for Clinical Use

PET imaging is increasingly recognized as an important diagnostic tool to investigate patients with cognitive disturbances of possible neurodegenerative origin. PET with 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG), assessing glucose metabolism, provides a measure of neurodegeneration and allows a precise differential diagnosis among the most common neurodegenerative diseases, such as Alzheimer's disease, frontotemporal dementia or dementia with Lewy bodies. PET tracers specific for the pathological deposits characteristic of different neurodegenerative processes, namely amyloid and tau deposits typical of Alzheimer's Disease, allow the visualization of these aggregates in vivo. [18F]FDG and amyloid PET imaging have reached a high level of clinical validity and are since 2022 investigations that can be offered to patients in standard clinical care in most of Canada.This article will briefly review and summarize the current knowledge on these diagnostic tools, their integration into diagnostic algorithms as well as perspectives for future developments.

Comparison of plasma biomarkers and amyloid PET for predicting memory decline in cognitively unimpaired individuals

BACKGROUND

We compared the ability of several plasma biomarkers versus amyloid positron emission tomography (PET) to predict rates of memory decline among cognitively unimpaired individuals.

METHODS

We studied 645 Mayo Clinic Study of Aging participants. Predictor variables were age, sex, education, apolipoprotein E (APOE) ε4 genotype, amyloid PET, and plasma amyloid beta (Aβ)42/40, phosphorylated tau (p-tau)181, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and p-tau217. The outcome was a change in a memory composite measure.

RESULTS

All plasma biomarkers, except NfL, were associated with mean memory decline in models with individual biomarkers. However, amyloid PET and plasma p-tau217, along with age, were key variables independently associated with mean memory decline in models combining all predictors. Confidence intervals were narrow for estimates of population mean prediction, but person-level prediction intervals were wide.

DISCUSSION

Plasma p-tau217 and amyloid PET provide useful information about predicting rates of future cognitive decline in cognitively unimpaired individuals at the population mean level, but not at the individual person level.

Performance on complex memory tests is associated with β-amyloid in individuals at risk of developing Alzheimer's disease

The pathophysiological development of Alzheimer's disease (AD) begins in the brain years before the onset of clinical symptoms. The accumulation of beta-amyloid (Aβ) is thought to be the first cortical pathology to occur. Carrying one apolipoprotein E (APOE) ε4 allele increases the risk of developing AD at least 2-3 times and is associated with earlier Aβ accumulation. Although it is difficult to identify Aβ-related cognitive impairment in early AD with standard cognitive tests, more sensitive memory tests may be able to do this. We sought to examine associations between Aβ and performance on three tests within three subdomains of memory, verbal, visual, and associative memory, to elucidate which of these tests were sensitive to Aβ-related cognitive impairment in at-risk subjects. 55 APOE ε4 carriers underwent MRI, 11 C-Pittsburgh Compound B (PiB) PET, and cognitive testing. A composite cortical PiB SUVR cut-off score of 1.5 was used to categorise subjects as either APOE ε4 Aβ+ or APOE ε4 Aβ-. Correlations were carried out using cortical surface analysis. In the whole APOE ε4 group, we found significant correlations between Aβ load and performance on verbal, visual, and associative memory tests in widespread cortical areas, the strongest association being with performance on associative memory tests. In the APOE ε4 Aβ+ group, we found significant correlations between Aβ load and performance of verbal and associative, but not visual, memory in localised cortical areas. Performance on verbal and associative memory tests provides sensitive markers of early Aβ-related cognitive impairment in at-risk subjects.

Harmonizing florbetapir and PiB PET measurements of cortical Aβ plaque burden using multiple regions-of-interest and machine learning techniques: An alternative to the Centiloid approach

INTRODUCTION

Machine learning (ML) can optimize amyloid (Aβ) comparability among positron emission tomography (PET) radiotracers. Using multi-regional florbetapir (FBP) measures and ML, we report better Pittsburgh compound-B (PiB)/FBP harmonization of mean-cortical Aβ (mcAβ) than Centiloid.

METHODS

PiB-FBP pairs from 92 subjects in www.oasis-brains.org and 46 in www.gaain.org/centiloid-project were used as the training/testing sets. FreeSurfer-extracted FBP multi-regional Aβ and actual PiB mcAβ in the training set were used to train ML models generating synthetic PiB mcAβ. The correlation coefficient (R) between the synthetic/actual PiB mcAβ in the testing set was assessed.

RESULTS

In the testing set, the synthetic/actual PiB mcAβ correlation R = 0.985 (R2  = 0.970) using artificial neural network was significantly higher (p ≤ 6.6e-4) than the FBP/PiB correlation R = 0.927 (R2  = 0.860), improving total variance percentage (R2 ) from 86% to 97%. Other ML models such as partial least square, ensemble, and relevance vector regressions also improved R (p = 9.677e-05 /0.045/0.0017).

DISCUSSION

ML improved mcAβ comparability. Additional studies are needed for the generalizability to other amyloid tracers, and to tau PET. Highlights Centiloid is a calibration of the amyloid scale, not harmonization. Centiloid unifies the amyloid scale without improving inter-tracer association (R2 ). Machine learning (ML) can harmonize the amyloid scale by improving R2 . ML harmonization maps multi-regional florbetapir SUVRs to PiB mean-cortical SUVR. Artificial neural network ML increases Centiloid R2 from 86% to 97%.

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

Risk of Alzheimer's disease is associated with longitudinal changes in plasma biomarkers in the multi-ethnic Washington Heights-Hamilton Heights-Inwood Columbia Aging Project (WHICAP) cohort

BACKGROUND

Alzheimer's disease (AD) biomarkers can help differentiate cognitively unimpaired (CU) individuals from mild cognitive impairment (MCI) and dementia. The role of AD biomarkers in predicting cognitive impairment and AD needs examination.

METHODS

In 628 CU individuals from a multi-ethnic cohort, amyloid beta (Aβ)42, Aβ40, phosphorylated tau-181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) were measured in plasma.

RESULTS

Higher baseline levels of p-tau181/Aβ42 ratio were associated with an increased risk of incident dementia. A biomarker pattern (with elevated Aβ42/Aβ40 but low p-tau181/Aβ42) was associated with decreased dementia risk. Compared to CU, participants who developed MCI or dementia had a rapid decrease in this protective biomarker pattern reflecting AD-specific pathological change.

DISCUSSION

Elevated levels of AD biomarker p-tau181/Aβ42, by itself or combined with a low Aβ42/Aβ40 level, predicts clinically diagnosed AD. Individuals with a rapid change in these biomarkers may need close monitoring for the potential downward trajectory of cognition.

HIGHLIGHTS

We discuss a multi-ethnic, urban community study of elderly individuals. The study consisted of a longitudinal assessment over 6 years with repeated clinical assessments. The study used blood-based biomarkers as predictors of mild cognitive impairment and Alzheimer's disease.

Unhealthy white matter connectivity, cognition, and racialization in older adults

INTRODUCTION

White matter hyperintensities (WMH) may promote clinical Alzheimer's disease (AD) disparities between Black American (BA) and non-Hispanic White (nHW) populations. Using a novel measurement, unhealthy white matter connectivity (UWMC), we interrogated racialized group differences in associations between WMH in AD pathology-affected regions and cognition.

METHODS

UWMC is the proportion of white matter fibers that pass through WMH for every pair of brain regions. Individual regression models tested associations of UWMC in beta-amyloid (Aβ) or tau pathology-affected regions with cognition overall, stratified by racialized group, and with a racialized group interaction.

RESULTS

In 201 older adults ranging from cognitively unimpaired to AD, BA participants exhibited greater UWMC and worse cognition than nHW participants. UWMC was negatively associated with cognition in 17 and 5 Aβ- and tau-affected regions, respectively. Racialization did not modify these relationships.

DISCUSSION

Differential UWMC burden, not differential UWMC-and-cognition associations, may drive clinical AD disparities between racialized groups.

HIGHLIGHTS

Unhealthy white matter connectivity (UWMC) in Alzheimer's disease (AD) pathology-affected brain regions is associated with cognition. Relationships between UWMC and cognition are similar between Black American (BA) and non-Hispanic White (nHW) individuals. More UWMC may partially drive higher clinical AD burden in BA versus nHW populations. UWMC risk factors, particularly social and environmental, should be identified.

Reduced SV2A and GABAA receptor levels in the brains of type 2 diabetic rats revealed by [18F]SDM-8 and [18F]flumazenil PET

PURPOSE

Type 2 diabetes mellitus (T2DM) is associated with a greater risk of Alzheimer's disease. Synaptic impairment and protein aggregates have been reported in the brains of T2DM models. Here, we assessed whether neurodegenerative changes in synaptic vesicle 2 A (SV2A), γ-aminobutyric acid type A (GABAA) receptor, amyloid-β, tau and receptor for advanced glycosylation end product (RAGE) can be detected in vivo in T2DM rats.

METHODS

Positron emission tomography (PET) using [18F]SDM-8 (SV2A), [18F]flumazenil (GABAA receptor), [18F]florbetapir (amyloid-β), [18F]PM-PBB3 (tau), and [18F]FPS-ZM1 (RAGE) was carried out in 12-month-old diabetic Zucker diabetic fatty (ZDF) and SpragueDawley (SD) rats. Immunofluorescence staining, Thioflavin S staining, proteomic profiling and pathway analysis were performed on the brain tissues of ZDF and SD rats.

RESULTS

Reduced cortical [18F]SDM-8 uptake and cortical and hippocampal [18F]flumazenil uptake were observed in 12-month-old ZDF rats compared to SD rats. The regional uptake of [18F]florbetapir and [18F]PM-PBB3 was comparable in the brains of 12-month-old ZDF and SD rats. Immunofluorescence staining revealed Thioflavin S-negative, phospho-tau-positive inclusions in the cortex and hypothalamus in the brains of ZDF rats and the absence of amyloid-beta deposits. The level of GABAA receptors was lower in the cortex of ZDF rats than SD rats. Proteomic analysis further demonstrated that, compared with SD rats, synaptic-related proteins and pathways were downregulated in the hippocampus of ZDF rats.

CONCLUSION

These findings provide in vivo evidence for regional reductions in SV2A and GABAA receptor levels in the brains of aged T2DM ZDF rats.

Multicenter Experience with Good Manufacturing Practice Production of [11C]PiB for Amyloid Positron Emission Tomography Imaging

Alzheimer's disease (AD) is a neurodegenerative disorder with increasing global prevalence and accounts for over half of all dementia cases. Early diagnosis is paramount for not only the management of the disease, but also for the development of new AD treatments. The current golden standard for diagnosis is performed by positron emission tomography (PET) scans with the tracer [11C]Pittsburg Compound B ([11C]PiB), which targets amyloid beta protein (Aβ) that builds up as plaques in the brain of AD patients. The increasing demand for AD diagnostics is in turn expected to drive an increase in [11C]PiB-PET scans and the setup of new [11C]PiB production lines at PET centers globally. Here, we present the [11C]PiB production setups, experiences, and use from four Danish PET facilities and discuss the challenges and potential pitfalls of [11C]PiB production. We report on the [11C]PiB production performed with the 6-OH-BTA-0 precursor dissolved in either dry acetone or 2-butanone and by using either [11C]CO2 or [11C]CH4 as 11C- precursors on three different commercial synthesis modules: TracerLab FX C Pro, ScanSys, or TracerMaker. It was found that the [11C]CO2 method gives the highest radioactive yield (1.5 to 3.2 GBq vs. 0.8 ± 0.3 GBq), while the highest molar activity (98.0 ± 61.4 GBq/μmol vs. 21.2 to 95.6 GBq/μmol) was achieved using [11C]CH4. [11C]PiB production with [11C]CO2 on a TracerLab FX C Pro offered the most desirable results, with the highest yield of 3.17 ± 1.20 GBq and good molar activity of 95.6 ± 44.2 GBq/μmol. Moreover, all reported methods produced [11C]PiB in quantities suitable for clinical applications, thus providing a foundation for other PET facilities seeking to establish their own [11C]PiB production.

Altered amyloid-β structure markedly reduces gliosis in the brain of mice harboring the Uppsala APP deletion

Deposition of amyloid beta (Aβ) into plaques is a major hallmark of Alzheimer's disease (AD). Different amyloid precursor protein (APP) mutations cause early-onset AD by altering the production or aggregation properties of Aβ. We recently identified the Uppsala APP mutation (APPUpp), which causes Aβ pathology by a triple mechanism: increased β-secretase and altered α-secretase APP cleavage, leading to increased formation of a unique Aβ conformer that rapidly aggregates and deposits in the brain. The aim of this study was to further explore the effects of APPUpp in a transgenic mouse model (tg-UppSwe), expressing human APP with the APPUpp mutation together with the APPSwe mutation. Aβ pathology was studied in tg-UppSwe brains at different ages, using ELISA and immunohistochemistry. In vivo PET imaging with three different PET radioligands was conducted in aged tg-UppSwe mice and two other mouse models; tg-ArcSwe and tg-Swe. Finally, glial responses to Aβ pathology were studied in cell culture models and mouse brain tissue, using ELISA and immunohistochemistry. Tg-UppSwe mice displayed increased β-secretase cleavage and suppressed α-secretase cleavage, resulting in AβUpp42 dominated diffuse plaque pathology appearing from the age of 5-6 months. The γ-secretase cleavage was not affected. Contrary to tg-ArcSwe and tg-Swe mice, tg-UppSwe mice were [11C]PiB-PET negative. Antibody-based PET with the 3D6 ligand visualized Aβ pathology in all models, whereas the Aβ protofibril selective mAb158 ligand did not give any signals in tg-UppSwe mice. Moreover, unlike the other two models, tg-UppSwe mice displayed a very faint glial response to the Aβ pathology. The tg-UppSwe mouse model thus recapitulates several pathological features of the Uppsala APP mutation carriers. The presumed unique structural features of AβUpp42 aggregates were found to affect their interaction with anti-Aβ antibodies and profoundly modify the Aβ-mediated glial response, which may be important aspects to consider for further development of AD therapies.

Recent applications of positron emission tomographic (PET) imaging in psychiatric drug discovery

INTRODUCTION

Psychiatry is one of the medical disciplines that suffers most from a lack of innovation in its therapeutic arsenal. Many failures in drug candidate trials can be explained by pharmacological properties that have been poorly assessed upstream, in terms of brain passage, brain target binding and clinical outcomes. Positron emission tomography can provide pharmacokinetic and pharmacodynamic data to help select candidate-molecules for further clinical trials.

AREAS COVERED

This review aims to explain and discuss the various methods using positron-emitting radiolabeled molecules to trace the cerebral distribution of the drug-candidate or indirectly measure binding to its therapeutic target. More than an exhaustive review of PET studies in psychopharmacology, this article highlights the contributions this technology can make in drug discovery applied to psychiatry.

EXPERT OPINION

PET neuroimaging is the only technological approach that can, in vivo in humans, measure cerebral delivery of a drug candidate, percentage and duration of target binding, and even the pharmacological effects. PET studies in a small number of subjects in the early stages of the development of a psychotropic drug can therefore provide the pharmacokinetic/pharmacodynamic data required for subsequent clinical evaluation. While PET technology is demanding in terms of radiochemical, radiopharmacological and nuclear medicine expertise, its integration into the development process of new drugs for psychiatry has great added value.

Abnormal motor cortical plasticity as a useful neurophysiological biomarker for Alzheimer's disease pathology

OBJECTIVE

Amyloid-beta (Aβ) and tau accumulations impair long-term potentiation (LTP) induction in animal hippocampi. We investigated relationships between motor-cortical plasticity and biomarkers for Alzheimer's disease (AD) diagnosis in subjects with cognitive decline.

METHODS

Twenty-six consecutive subjects who complained of memory problems participated in this study. We applied transcranial quadripuse stimulation with an interstimulus interval of 5 ms (QPS5) to induce LTP-like plasticity. Motor-evoked potentials were recorded from the right first-dorsal interosseous muscle before and after QPS5. Cognitive functions, Aβ42 and tau levels in the cerebrospinal fluid (CSF) were measured. Amyloid positron-emission tomography (PET) with11C-Pittsburg compound-B was also conducted. We studied correlations of QPS5-induced plasticity with cognitive functions or AD-related biomarkers.

RESULTS

QPS5-induced LTP-like plasticity positively correlated with cognitive scores. The degree of LTP-like plasticity negatively correlated with levels of CSF-tau, and the amount of amyloid-PET accumulation at the precuneus, and correlated with the CSF-Aβ42 level positively. In the amyloid-PET positive subjects, non-responder rate of QPS5 was higher than the CSF-tau positive rate.

CONCLUSIONS

Findings suggest that QPS5-induced LTP-like plasticity is a functional biomarker of AD. QPS5 could detect abnormality at earlier stages than CSF-tau in the amyloid-PET positive subjects.

SIGNIFICANCE

Assessing motor-cortical plasticity could be a useful neurophysiological biomarker for AD pathology.

Age and beta amyloid deposition impact gait speed, stride length, and gait smoothness while transitioning from an even to an uneven walking surface in older adults

BACKGROUND

Capturing a measure of movement quality during a complex walking task may indicate the earliest signs of detrimental changes to the brain due to beta amyloid (Aβ) deposition and be a potential differentiator of older adults at elevated and low risk of developing Alzheimer's disease. This study aimed to determine: 1) age-related differences in gait speed, stride length, and gait smoothness while transitioning from an even to an uneven walking surface, by comparing young adults (YA) and older adults (OA), and 2) if gait speed, stride length, and gait smoothness in OA while transitioning from an even to an uneven walking surface is influenced by the amount of Aβ deposition present in an OA's brain.

METHODS

Participants included 56 OA (>70 years of age) and 29 YA (25-35 years of age). In OA, Aβ deposition in the brain was quantified by PET imaging. All participants completed a series of cognitive assessments, a functional mobility assessment, and self-report questionnaires. Then participants performed two sets of walking trials on a custom-built walkway containing a mixture of even and uneven surface sections, including three trials with a grass uneven surface and three trials with a rocks uneven surface. Gait data were recorded using a wireless inertial measurement unit system. Stride length, gait speed, and gait smoothness (i.e., log dimensionless lumbar jerk) in the anteroposterior (AP), mediolateral (ML), and vertical (VT) directions were calculated for each stride. Outcomes were retained for five stride locations immediately surrounding the surface transition.

RESULTS

OA exhibited slower gait (Grass: p < 0.001; Rocks: p = 0.006), shorter strides (Grass: p < 0.001; Rocks: p = 0.008), and smoother gait (Grass AP: p < 0.001; Rocks AP: p = 0.002; Rocks ML: p = 0.02) than YA, but they also exhibited greater reductions in gait speed and stride length than YA while transitioning to the uneven grass and rocks surfaces. Within the OA group, those with greater Aβ deposition exhibited decreases in smoothness with age (Grass AP: p = 0.02; Rocks AP: p = 0.03; Grass ML: p = 0.04; Rocks ML: p = 0.03), while those with lower Aβ deposition exhibited increasing smoothness with age (Grass AP: p = 0.01; Rocks AP: p = 0.02; Grass ML: p = 0.08; Rocks ML: p = 0.07). Better functional mobility was associated with less smooth gait (Grass ML: p = 0.02; Rocks ML: p = 0.05) and with less variable gait smoothness (Grass and Rocks AP: both p = 0.04) in the OA group.

CONCLUSION

These results suggest that, relative to YA, OA may be adopting more cautious, compensatory gait strategies to maintain smoothness when approaching surface transitions. However, OA with greater Aβ deposition may have limited ability to adopt compensatory gait strategies to increase the smoothness of their walking as they get older because of neuropathological changes altering the sensory integration process and causing worse dynamic balance (i.e., jerkier gait). Functional mobility, in addition to age and Aβ deposition, may be an important factor of whether or not an OA chooses to employ compensatory strategies to prioritize smoothness while walking and what type of compensatory strategy an OA chooses.

Advancing Diagnostics and Patient Care: The Role of Biomarkers in Radiology

The integration of biomarkers into medical practice has revolutionized the field of radiology, allowing for enhanced diagnostic accuracy, personalized treatment strategies, and improved patient care outcomes. This review offers radiologists a comprehensive understanding of the diverse applications of biomarkers in medicine. By elucidating the fundamental concepts, challenges, and recent advancements in biomarker utilization, it will serve as a bridge between the disciplines of radiology and epidemiology. Through an exploration of various biomarker types, such as imaging biomarkers, molecular biomarkers, and genetic markers, I outline their roles in disease detection, prognosis prediction, and therapeutic monitoring. I also discuss the significance of robust study designs, blinding, power and sample size calculations, performance metrics, and statistical methodologies in biomarker research. By fostering collaboration between radiologists, statisticians, and epidemiologists, I hope to accelerate the translation of biomarker discoveries into clinical practice, ultimately leading to improved patient care.

Machine Learning Models of Polygenic Risk for Enhanced Prediction of Alzheimer Disease Endophenotypes

Background and Objectives

Alzheimer disease (AD) has a polygenic architecture, for which genome-wide association studies (GWAS) have helped elucidate sequence variants (SVs) influencing susceptibility. Polygenic risk score (PRS) approaches show promise for generating summary measures of inherited risk for clinical AD based on the effects of APOE and other GWAS hits. However, existing PRS approaches, based on traditional regression models, explain only modest variation in AD dementia risk and AD-related endophenotypes. We hypothesized that machine learning (ML) models of polygenic risk (ML-PRS) could outperform standard regression-based PRS methods and therefore have the potential for greater clinical utility.

Methods

We analyzed combined data from the Mayo Clinic Study of Aging (n = 1,791) and the Alzheimer's Disease Neuroimaging Initiative (n = 864). An AD PRS was computed for each participant using the top common SVs obtained from a large AD dementia GWAS. In parallel, ML models were trained using those SV genotypes, with amyloid PET burden as the primary outcome. Secondary outcomes included amyloid PET positivity and clinical diagnosis (cognitively unimpaired vs impaired). We compared performance between ML-PRS and standard PRS across 100 training sessions with different data splits. In each session, data were split into 80% training and 20% testing, and then five-fold cross-validation was used within the training set to ensure the best model was produced for testing. We also applied permutation importance techniques to assess which genetic factors contributed most to outcome prediction.

Results

ML-PRS models outperformed the AD PRS (r2 = 0.28 vs r2 = 0.24 in test set) in explaining variation in amyloid PET burden. Among ML approaches, methods accounting for nonlinear genetic influences were superior to linear methods. ML-PRS models were also more accurate when predicting amyloid PET positivity (area under the curve [AUC] = 0.80 vs AUC = 0.63) and the presence of cognitive impairment (AUC = 0.75 vs AUC = 0.54) compared with the standard PRS.

Discussion

We found that ML-PRS approaches improved upon standard PRS for prediction of AD endophenotypes, partly related to improved accounting for nonlinear effects of genetic susceptibility alleles. Further adaptations of the ML-PRS framework could help to close the gap of remaining unexplained heritability for AD and therefore facilitate more accurate presymptomatic and early-stage risk stratification for clinical decision-making.

The value of FDG combined with PiB PET in the diagnosis of patients with cognitive impairment in a memory clinic

AIMS

To analyze the value of 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with amyloid PET in cognitive impairment diagnosis.

METHODS

A total of 187 patients with dementia or mild cognitive impairment (MCI) who underwent 11 C-Pittsburgh compound B (PiB) and FDG PET scans in a memory clinic were included in the final analysis.

RESULTS

Amyloid-positive and amyloid-negative dementia patient groups showed a significant difference in the proportion of individuals presenting temporoparietal cortex (p < 0.001) and posterior cingulate/precuneus cortex (p < 0.001) hypometabolism. The sensitivity and specificity of this hypometabolic pattern for identifying amyloid pathology were 72.61% and 77.97%, respectively, in patients clinically diagnosed with AD and 60.87% and 76.19%, respectively, in patients with MCI. The initial diagnosis was changed in 32.17% of patients with dementia after considering both PiB and FDG results. There was a significant difference in both the proportion of patients showing the hypometabolic pattern and PiB positivity between dementia conversion patients and patients with a stable diagnosis of MCI (p < 0.05).

CONCLUSION

Temporoparietal and posterior cingulate/precuneus cortex hypometabolism on FDG PET suggested amyloid pathology in patients with cognitive impairment and is helpful in diagnostic decision-making and predicting AD dementia conversion from MCI, particularly when combined with amyloid PET.

The amyloid-β peptide: Guilty as charged?

Recent years have seen both considerable progress and controversy in the Alzheimer's disease (AD) field. After decades of slow to negligible movement towards the development of disease modifying therapies, promising outcomes in recent clinical trials with several monoclonal antibodies targeting various forms of the amyloid-β (Aβ) peptide have at last opened a possible way forward. In fact, at this point multiple anti-Aβ therapeutics are close to receiving (or have already received) regulatory approval. Although these outcomes are not without some degree of divisiveness, the fact remains that targeting amyloid for removal has finally shown at least modest efficacy in slowing the otherwise relentless progression of the disease. Although the validation of the long standing amyloid cascade hypothesis would seem to be at hand, what remains is the puzzling issue of why - if Aβ indeed causes AD - does removing it from the brain not stop the disease entirely.

Modeling the temporal evolution of plasma p-tau in relation to amyloid beta and tau PET

INTRODUCTION

The timing of plasma biomarker changes is not well understood. The goal of this study was to evaluate the temporal co-evolution of plasma and positron emission tomography (PET) Alzheimer's disease (AD) biomarkers.

METHODS

We included 1408 Mayo Clinic Study of Aging and Alzheimer's Disease Research Center participants. An accelerated failure time (AFT) model was fit with amyloid beta (Aβ) PET, tau PET, plasma p-tau217, p-tau181, and glial fibrillary acidic protein (GFAP) as endpoints.

RESULTS

Individual timing of plasma p-tau progression was strongly associated with Aβ PET and GFAP progression. In the population, GFAP became abnormal first, then Aβ PET, plasma p-tau, and tau PET temporal meta-regions of interest when applying cut points based on young, cognitively unimpaired participants.

DISCUSSION

Plasma p-tau is a stronger indicator of a temporally linked response to elevated brain Aβ than of tau pathology. While Aβ deposition and a rise in GFAP are upstream events associated with tau phosphorylation, the temporal link between p-tau and Aβ PET was the strongest.

HIGHLIGHTS

Plasma p-tau progression was more strongly associated with Aβ than tau PET. Progression on plasma p-tau was associated with Aβ PET and GFAP progression. P-tau181 and p-tau217 become abnormal after Aβ PET and before tau PET. GFAP became abnormal first, before plasma p-tau and Aβ PET.

Gray and White Matter Voxel-Based Morphometry of Alzheimer's Disease With and Without Significant Cerebrovascular Pathologies

Alzheimer's disease (AD) is the most common type of dementia, and AD individuals often present significant cerebrovascular disease (CVD) symptomology. AD with significant levels of CVD is frequently labeled mixed dementia (or sometimes AD-CVD), and the differentiation of these two neuropathologies (AD, AD-CVD) from each other is challenging, especially at early stages. In this study, we compared the gray matter (GM) and white matter (WM) volumes in AD (n = 83) and AD-CVD (n = 37) individuals compared with those of cognitively healthy controls (n = 85) using voxel-based morphometry (VBM) of their MRI scans. The control individuals, matched for age and sex with our two dementia groups, were taken from the ADNI. The VBM analysis showed widespread patterns of significantly lower GM and WM volume in both dementia groups compared to the control group (P < .05, family-wise error corrected). While comparing with AD-CVD, the AD group mainly demonstrated a trend of lower volumes in the GM of the left putamen and right hippocampus and WM of the right thalamus (uncorrected P < .005 with cluster threshold, K = 10). The AD-CVD group relative to AD tended to present lower GM and WM volumes, mainly in the cerebellar lobules and right brainstem regions, respectively (uncorrected P < .005 with cluster threshold, K = 10). Although finding a discriminatory feature in structural MRI data between AD and AD-CVD neuropathologies is challenging, these results provide preliminary evidence that demands further investigation in a larger sample size.

Association Between β-Amyloid Accumulation and Incident Dementia in Individuals 80 Years or Older Without Dementia

BACKGROUND AND OBJECTIVES

While the highest prevalence of dementia occurs in individuals older than 80 years, most imaging studies focused on younger populations. The rates of β-amyloid (Aβ) accumulation and the effect of Alzheimer disease (AD) pathology on progression to dementia in this age group remain unexplored. In this study, we examined the relationship between changes in Aβ deposition over time and incident dementia in nondemented individuals followed during a period of 11 years.

METHODS

We examined 94 participants (age 85.9 + 2.8 years) who had up to 5 measurements of Pittsburgh compound-B (PiB)-PET and clinical evaluations from 2009 to 2020. All 94 participants had 2 PiB-PET scans, 76 participants had 3 PiB-PET scans, 18 participants had 4 PiB-PET scans, and 10 participants had 5 PiB-PET scans. The rates of Aβ deposition were compared with 120 nondemented individuals younger than 80 years (69.3 ± 5.4 years) from the Australian Imaging, Biomarker, and Lifestyle (AIBL) study who had 3 or more annual PiB-PET assessments.

RESULTS

By 2020, 49% of the participants developed dementia and 63% were deceased. There was a gradual increase in Aβ deposition in all participants whether they were considered Aβ positive or negative at baseline. In a Cox model controlled for age, sex, education level, APOE-4 allele, baseline Mini-Mental State Examination, and mortality, short-term change in Aβ deposition was not significantly associated with incident dementia (HR 2.19 (0.41-11.73). However, baseline Aβ burden, cortical thickness, and white matter lesions volume were the predictors of incident dementia. Aβ accumulation was faster (p = 0.01) in the older cohort (5.6%/year) when compared with AIBL (4.1%/year). In addition, baseline Aβ deposition was a predictor of short-term change (mean time 1.88 years).

DISCUSSION

There was an accelerated Aβ accumulation in cognitively normal individuals older than 80 years. Baseline Aβ deposition was a determinant of incident dementia and short-term change in Aβ deposition suggesting that an active Aβ pathologic process was present when these participants were cognitively normal. Consequently, age may not be a limiting factor for the use of the emergent anti-Aβ therapies.

Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review

Translational bioinformatics and data science play a crucial role in biomarker discovery as it enables translational research and helps to bridge the gap between the bench research and the bedside clinical applications. Thanks to newer and faster molecular profiling technologies and reducing costs, there are many opportunities for researchers to explore the molecular and physiological mechanisms of diseases. Biomarker discovery enables researchers to better characterize patients, enables early detection and intervention/prevention and predicts treatment responses. Due to increasing prevalence and rising treatment costs, mental health (MH) disorders have become an important venue for biomarker discovery with the goal of improved patient diagnostics, treatment and care. Exploration of underlying biological mechanisms is the key to the understanding of pathogenesis and pathophysiology of MH disorders. In an effort to better understand the underlying mechanisms of MH disorders, we reviewed the major accomplishments in the MH space from a bioinformatics and data science perspective, summarized existing knowledge derived from molecular and cellular data and described challenges and areas of opportunities in this space.

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.