PET molecular imaging for pathophysiological visualization in Alzheimer's disease

AI-driven innovations in Alzheimer's disease: Integrating early diagnosis, personalized treatment, and prognostic modelling

Alzheimer's disease (AD) presents a significant challenge in neurodegenerative research and clinical practice due to its complex etiology and progressive nature. The integration of artificial intelligence (AI) into the diagnosis, treatment, and prognostic modelling of AD holds promising potential to transform the landscape of dementia care. This review explores recent advancements in AI applications across various stages of AD management. In early diagnosis, AI-enhanced neuroimaging techniques, including MRI, PET, and CT scans, enable precise detection of AD biomarkers. Machine learning models analyze these images to identify patterns indicative of early cognitive decline. Additionally, AI algorithms are employed to detect genetic and proteomic biomarkers, facilitating early intervention. Cognitive and behavioral assessments have also benefited from AI, with tools that enhance the accuracy of neuropsychological tests and analyze speech and language patterns for early signs of dementia. Personalized treatment strategies have been revolutionized by AI-driven approaches. In drug discovery, virtual screening and drug repurposing, guided by predictive modelling, accelerate the identification of effective treatments. AI also aids in tailoring therapeutic interventions by predicting individual responses to treatments and monitoring patient progress, allowing for dynamic adjustment of care plans. Prognostic modelling, another critical area, utilizes AI to predict disease progression through longitudinal data analysis and risk prediction models. The integration of multi-modal data, combining clinical, genetic, and imaging information, enhances the accuracy of these predictions. Deep learning techniques are particularly effective in fusing diverse data types to uncover new insights into disease mechanisms and progression. Despite these advancements, challenges remain, including ethical considerations, data privacy, and the need for seamless integration of AI tools into clinical workflows. This review underscores the transformative potential of AI in AD management while highlighting areas for future research and development. By leveraging AI, the healthcare community can improve early diagnosis, personalize treatments, and predict disease outcomes more accurately, ultimately enhancing the quality of life for individuals with AD.

Updates in Alzheimer's disease: from basic research to diagnosis and therapies

Alzheimer's disease (AD) is the most common neurodegenerative disorder, characterized pathologically by extracellular deposition of β-amyloid (Aβ) into senile plaques and intracellular accumulation of hyperphosphorylated tau (pTau) as neurofibrillary tangles. Clinically, AD patients show memory deterioration with varying cognitive dysfunctions. The exact molecular mechanisms underlying AD are still not fully understood, and there are no efficient drugs to stop or reverse the disease progression. In this review, we first provide an update on how the risk factors, including APOE variants, infections and inflammation, contribute to AD; how Aβ and tau become abnormally accumulated and how this accumulation plays a role in AD neurodegeneration. Then we summarize the commonly used experimental models, diagnostic and prediction strategies, and advances in periphery biomarkers from high-risk populations for AD. Finally, we introduce current status of development of disease-modifying drugs, including the newly officially approved Aβ vaccines, as well as novel and promising strategies to target the abnormal pTau. Together, this paper was aimed to update AD research progress from fundamental mechanisms to the clinical diagnosis and therapies.

[Construction and analysis of brain metabolic network in temporal lobe epilepsy patients based on 18F-FDG PET]

The establishment of brain metabolic network is based on 18fluoro-deoxyglucose positron emission computed tomography ( 18F-FDG PET) analysis, which reflect the brain functional network connectivity in normal physiological state or disease state. It is now applied to basic and clinical brain functional network research. In this paper, we constructed a metabolic network for the cerebral cortex firstly according to 18F-FDG PET image data from patients with temporal lobe epilepsy (TLE).Then, a statistical analysis to the network properties of patients with left or right TLE and controls was performed. It is shown that the connectivity of the brain metabolic network is weakened in patients with TLE, the topology of the network is changed and the transmission efficiency of the network is reduced, which means the brain metabolic network connectivity is extensively impaired in patients with TLE. It is confirmed that the brain metabolic network analysis based on 18F-FDG PET can provide a new perspective for the diagnose and therapy of epilepsy by utilizing PET images.

Alzheimer's disease stage recognition from MRI and PET imaging data using Pareto-optimal quantum dynamic optimization

The threat posed by Alzheimer's disease (AD) to human health has grown significantly. However, the precise diagnosis and classification of AD stages remain a challenge. Neuroimaging methods such as structural magnetic resonance imaging (sMRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) have been used to diagnose and categorize AD. However, feature selection approaches that are frequently used to extract additional data from multimodal imaging are prone to errors. This paper suggests using a static pulse-coupled neural network and a Laplacian pyramid to combine sMRI and FDG-PET data. After that, the fused images are used to train the Mobile Vision Transformer (MViT), optimized with Pareto-Optimal Quantum Dynamic Optimization for Neural Architecture Search, while the fused images are augmented to avoid overfitting and then classify unfused MRI and FDG-PET images obtained from the AD Neuroimaging Initiative (ADNI) and Open Access Series of Imaging Studies (OASIS) datasets into various stages of AD. The architectural hyperparameters of MViT are optimized using Quantum Dynamic Optimization, which ensures a Pareto-optimal solution. The Peak Signal-to-Noise Ratio (PSNR), the Mean Squared Error (MSE), and the Structured Similarity Indexing Method (SSIM) are used to measure the quality of the fused image. We found that the fused image was consistent in all metrics, having 0.64 SIMM, 35.60 PSNR, and 0.21 MSE for the FDG-PET image. In the classification of AD vs. cognitive normal (CN), AD vs. mild cognitive impairment (MCI), and CN vs. MCI, the precision of the proposed method is 94.73%, 92.98% and 89.36%, respectively. The sensitivity is 90. 70%, 90. 70%, and 90. 91% while the specificity is 100%, 100%, and 85. 71%, respectively, in the ADNI MRI test data.

Novel β-amyloid PET Imaging Study of [18F]92 in Patients with Cognitive Decline

[18F]-4-((E)-(((E)-4-(2-(2-(2-Fluoroethoxy)ethoxy)ethoxy)benzylidene)-hydrazono)methyl)-N-methylaniline ([18F]92) is a novel positron emission tomography (PET) tracer previously reported to exhibit high binding affinity to aggregated β-amyloid (Aβ). This study aims to report a fully automated radiosynthesis procedure for [18F]92, explore its radioactive distribution in the brains of healthy subjects, and investigate its potential application value in the early diagnosis of Alzheimer's disease (AD). The fully automated radiosynthesis of [18F]92 was performed on the AllinOne module. Thirty one participants were recruited for this study. Dynamic [18F]92 PET imaging was conducted over 0-90 min period to assess time-activity curves (TAC) and standardized uptake value ratio (SUVR) curves in cognitively normal (CN) subjects. All participants were visually classified as either positive (+) or negative (-). Semiquantitative analyses of [18F]92 were performed by calculating SUVRs in different regions of interest. Furthermore, the study analyzed the relationships between global SUVR and plasma AD biomarkers, including Aβ42, Aβ40, P-tau181, and T-tau. The automated radiosynthesis of [18F]92 was completed within 50 min, yielding a radiochemical purity of greater than 95% and a radiochemical yield of 36 ± 3% (nondecay-corrected). Among the participants, 15 were estimated as Aβ (-) and 16 as Aβ (+). TACs indicated that [18F]92 rapidly crossed the blood-brain barrier within 10 min, followed by a rapid decrease, which then slowed down in the last 50-90 min. SUVR curves revealed that SUVR values stabilized around 60-70 min after injection and reached an equilibrium between 70 and 90 min, primarily in the cerebral cortex. SUVRs of Aβ (+) participants were significantly higher than those of Aβ (-) individuals within the cerebral cortex. In addition, Aβ42 and the Aβ42/Aβ40 ratio exhibited negative correlations with global SUVR, while plasma P-tau181 and the P-tau181/T-tau ratio displayed positive correlations with global SUVR. [18F]92 exhibits excellent pharmacokinetic properties in the human brain and can be synthesized automatically on a large scale. [18F]92 is a promising and reliable radiotracer for estimating Aβ pathology accumulation, providing valuable assistance in AD diagnosis and guiding clinical trials of therapeutic drugs.

PET brain imaging in neurological disorders

Brain disorders are a series of conditions with damage or loss of neurons, such as Parkinson's disease (PD), Alzheimer's disease (AD), or drug dependence. These individuals have gradual deterioration of cognitive, motor, and other central nervous system functions affected. This degenerative trajectory is intricately associated with dysregulations in neurotransmitter systems. Positron Emission Tomography (PET) imaging, employing radiopharmaceuticals and molecular imaging techniques, emerges as a crucial tool for detecting brain biomarkers. It offers invaluable insights for early diagnosis and distinguishing brain disorders. This article comprehensively reviews the application and progress of conventional and novel PET imaging agents in diagnosing brain disorders. Furthermore, it conducts a thorough analysis on merits and limitations. The article also provides a forward-looking perspective in the future development directions of PET imaging agents for diagnosing brain disorders and proposes potential innovative strategies. It aims to furnish clinicians and researchers with an all-encompassing overview of the latest advancements and forthcoming trends in the utilization of PET imaging for diagnosing brain disorders.

Exploratory Tau PET/CT with [11C]PBB3 in Patients with Suspected Alzheimer's Disease and Frontotemporal Lobar Degeneration: A Pilot Study on Correlation with PET Imaging and Cerebrospinal Fluid Biomarkers

Accurately diagnosing Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) is challenging due to overlapping symptoms and limitations of current imaging methods. This study investigates the use of [11C]PBB3 PET/CT imaging to visualize tau pathology and improve diagnostic accuracy. Given diagnostic challenges with symptoms and conventional imaging, [11C]PBB3 PET/CT's potential to enhance accuracy was investigated by correlating tau pathology with cerebrospinal fluid (CSF) biomarkers, positron emission tomography (PET), computed tomography (CT), amyloid-beta, and Mini-Mental State Examination (MMSE). We conducted [11C]PBB3 PET/CT imaging on 24 patients with suspected AD or FTLD, alongside [11C]PiB PET/CT (13 patients) and [18F]FDG PET/CT (15 patients). Visual and quantitative assessments of [11C]PBB3 uptake using standardized uptake value ratios (SUV-Rs) and correlation analyses with clinical assessments were performed. The scans revealed distinct tau accumulation patterns; 13 patients had no or faint uptake (PBB3-negative) and 11 had moderate to pronounced uptake (PBB3-positive). Significant inverse correlations were found between [11C]PBB3 SUV-Rs and MMSE scores, but not with CSF-tau or CSF-amyloid-beta levels. Here, we show that [11C]PBB3 PET/CT imaging can reveal distinct tau accumulation patterns and correlate these with cognitive impairment in neurodegenerative diseases. Our study demonstrates the potential of [11C]PBB3-PET imaging for visualizing tau pathology and assessing disease severity, offering a promising tool for enhancing diagnostic accuracy in AD and FTLD. Further research is essential to validate these findings and refine the use of tau-specific PET imaging in clinical practice, ultimately improving patient care and treatment outcomes.

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.

A single-domain antibody for the detection of pathological Tau protein in the early stages of oligomerization

BACKGROUND

Soluble oligomeric forms of Tau protein have emerged as crucial players in the propagation of Tau pathology in Alzheimer's disease (AD). Our objective is to introduce a single-domain antibody (sdAb) named 2C5 as a novel radiotracer for the efficient detection and longitudinal monitoring of oligomeric Tau species in the human brain.

METHODS

The development and production of 2C5 involved llama immunization with the largest human Tau isoform oligomers of different maturation states. Subsequently, 2C5 underwent comprehensive in vitro characterization for affinity and specificity via Enzyme-Linked Immunosorbent Assay and immunohistochemistry on human brain slices. Technetium-99m was employed to radiolabel 2C5, followed by its administration to healthy mice for biodistribution analysis.

RESULTS

2C5 exhibited robust binding affinity towards Tau oligomers (Kd = 6.280 nM ± 0.557) and to Tau fibers (Kd = 5.024 nM ± 0.453), with relatively weaker binding observed for native Tau protein (Kd = 1791 nM ± 8.714) and amyloid peptide (Kd > 10,000 nM). Remarkably, this SdAb facilitated immuno-histological labeling of pathological forms of Tau in neurons and neuritic plaques, yielding a high-contrast outcome in AD patients, closely mirroring the performance of reference antibodies AT8 and T22. Furthermore, 2C5 SdAb was successfully radiolabeled with 99mTc, preserving stability for up to 6 h post-radiolabeling (radiochemical purity > 93%). However, following intravenous injection into healthy mice, the predominant uptake occurred in kidneys, amounting to 115.32 ± 3.67, 97.70 ± 43.14 and 168.20 ± 34.52% of injected dose per gram (% ID/g) at 5, 10 and 45 min respectively. Conversely, brain uptake remained minimal at all measured time points, registering at 0.17 ± 0.03, 0.12 ± 0.07 and 0.02 ± 0.01% ID/g at 5, 10 and 45 min post-injection respectively.

CONCLUSION

2C5 demonstrates excellent affinity and specificity for pathological Tau oligomers, particularly in their early stages of oligomerization. However, the current limitation of insufficient blood-brain barrier penetration necessitates further modifications before considering its application in nuclear medicine imaging for humans.

Unveiling New Strategies Facilitating the Implementation of Artificial Intelligence in Neuroimaging for the Early Detection of Alzheimer's Disease

Alzheimer's disease (AD) is a chronic neurodegenerative disorder with a global impact. The past few decades have witnessed significant strides in comprehending the underlying pathophysiological mechanisms and developing diagnostic methodologies for AD, such as neuroimaging approaches. Neuroimaging techniques, including positron emission tomography and magnetic resonance imaging, have revolutionized the field by providing valuable insights into the structural and functional alterations in the brains of individuals with AD. These imaging modalities enable the detection of early biomarkers such as amyloid-β plaques and tau protein tangles, facilitating early and precise diagnosis. Furthermore, the emerging technologies encompassing blood-based biomarkers and neurochemical profiling exhibit promising results in the identification of specific molecular signatures for AD. The integration of machine learning algorithms and artificial intelligence has enhanced the predictive capacity of these diagnostic tools when analyzing complex datasets. In this review article, we will highlight not only some of the most used diagnostic imaging approaches in neurodegeneration research but focus much more on new tools like artificial intelligence, emphasizing their application in the realm of AD. These advancements hold immense potential for early detection and intervention, thereby paving the way for personalized therapeutic strategies and ultimately augmenting the quality of life for individuals affected by AD.

Utilities of Isolated Nerve Terminals in Ex Vivo Analyses of Protein Translation in (Patho)physiological Brain States: Focus on Alzheimer's Disease

Synapses are the cellular substrates of higher-order brain functions, and their dysfunction is an early and primary pathogenic mechanism across several neurological disorders. In particular, Alzheimer's disease (AD) is categorized by prodromal structural and functional synaptic deficits, prior to the advent of classical behavioral and pathological features. Recent research has shown that the development, maintenance, and plasticity of synapses depend on localized protein translation. Synaptosomes and synaptoneurosomes are biochemically isolated synaptic terminal preparations which have long been used to examine a variety of synaptic processes ex vivo in both healthy and pathological conditions. These ex vivo preparations preserve the mRNA species and the protein translational machinery. Hence, they are excellent in organello tools for the study of alterations in mRNA levels and protein translation in neuropathologies. Evaluation of synapse-specific basal and activity-driven de novo protein translation activity can be conveniently performed in synaptosomal/synaptoneurosomal preparations from both rodent and human brain tissue samples. This review gives a quick overview of the methods for isolating synaptosomes and synaptoneurosomes before discussing the studies that have utilized these preparations to study localized synapse-specific protein translation in (patho)physiological situations, with an emphasis on AD. While the review is not an exhaustive accumulation of all the studies evaluating synaptic protein translation using the synaptosomal model, the aim is to assemble the most relevant studies that have done so. The hope is to provide a suitable research platform to aid neuroscientists to utilize the synaptosomal/synaptoneurosomal models to evaluate the molecular mechanisms of synaptic dysfunction within the specific confines of mRNA localization and protein translation research.

Imaging of brain clearance pathways via MRI assessment of the glymphatic system

Glymphatic clearance dysfunction may play an important role in a variety of neurodegenerative diseases and the progression of ageing. However, in vivo imaging of the glymphatic system is challenging. In this study, we describe an MRI method based on chemical exchange saturation transfer (CEST) of the Angiopep-2 probe to visualize the clearance function of the glymphatic system. We injected rats with Angiopep-2 via the tail vein and performed in vivo MRI at 7 T to track differences in Angiopep-2 signal changes; we then applied the same principles in a bilateral deep cervical lymph node ligation rat model and in ageing rats. We demonstrated the feasibility of Angiopep-2 CEST for visualizing the clearance function of the glymphatic system. Finally, a pathological assessment was performed. Within the model group, the deep cervical lymph node ligation group and the ageing group showed higher CEST signal than the control group. We conclude that this new MRI method can visualize clearance in the glymphatic system.

The Future of (Radio)-Labeled Compounds in Research and Development within the Life Science Industry

In this review the applications of isotopically labeled compounds are discussed and put into the context of their future impact in the life sciences. Especially discussing their use in the pharma and crop science industries to follow their fate in the environment, in vivo or in complex matrices to understand the potential harm of new chemical structures and to increase the safety of human society.

Phenomic Imaging

Human phenomics is defined as the comprehensive collection of observable phenotypes and characteristics influenced by a complex interplay among factors at multiple scales. These factors include genes, epigenetics at the microscopic level, organs, microbiome at the mesoscopic level, and diet and environmental exposures at the macroscopic level. "Phenomic imaging" utilizes various imaging techniques to visualize and measure anatomical structures, biological functions, metabolic processes, and biochemical activities across different scales, both in vivo and ex vivo. Unlike conventional medical imaging focused on disease diagnosis, phenomic imaging captures both normal and abnormal traits, facilitating detailed correlations between macro- and micro-phenotypes. This approach plays a crucial role in deciphering phenomes. This review provides an overview of different phenomic imaging modalities and their applications in human phenomics. Additionally, it explores the associations between phenomic imaging and other omics disciplines, including genomics, transcriptomics, proteomics, immunomics, and metabolomics. By integrating phenomic imaging with other omics data, such as genomics and metabolomics, a comprehensive understanding of biological systems can be achieved. This integration paves the way for the development of new therapeutic approaches and diagnostic tools.

Synthesis and biological evaluation of indane-based fluorescent probes for detection of amyloid-β aggregates in Alzheimer's disease

In this article, the development of fluorescent imaging probes for the detection of Alzheimer's disease (AD)-associated protein aggregates is described. Indane derivatives with a donor-π-acceptor (D-π-A) structure were designed and synthesized. The probes were evaluated for their ability to bind to β-amyloid (Aβ) protein aggregates, which are a key pathological hallmark of AD. The results showed that several probes exhibited significant changes in fluorescence intensity at wavelengths greater than 600 nm when they were bound to Aβ aggregates compared to the Aβ monomeric form. Among the tested probes, four D-π-A type indane derivatives showed promising binding selectivity to Aβ aggregates over non-specific proteins such as bovine serum albumin (BSA). The molecular docking study showed that our compounds were appropriately located along the Aβ fibril axis through the hydrophobic tunnel structure. Further analysis revealed that the most active compound having dimethylaminopyridyl group as an election donor and dicyano group as an electron acceptor could effectively stain Aβ plaques in brain tissue samples from AD transgenic mice. These findings suggest that our indane-based compounds have the potential to serve as fluorescent probes for the detection and monitoring of Aβ aggregation in AD.

Amyloid PET across the cognitive spectrum in former professional and college American football players: findings from the DIAGNOSE CTE Research Project

BACKGROUND

Exposure to repetitive head impacts (RHI) in American football players can lead to cognitive impairment and dementia due to neurodegenerative disease, particularly chronic traumatic encephalopathy (CTE). The pathognomonic lesion of CTE consists of perivascular aggregates of hyper-phosphorylated tau in neurons at the depths of cortical sulci. However, it is unclear whether exposure to RHI accelerates amyloid-β (Aβ) plaque formation and increases the risk for Alzheimer's disease (AD). Although the Aβ neuritic plaques characteristic of AD are observed in a minority of later-stage CTE cases, diffuse plaques are more common. This study examined whether former professional and college American football players, including those with cognitive impairment and dementia, have elevated neuritic Aβ plaque density, as measured by florbetapir PET. Regardless of cognitive and functional status, elevated levels of florbetapir uptake were not expected.

METHODS

We examined 237 men ages 45-74, including 119 former professional (PRO) and 60 former college (COL) football players, with and without cognitive impairment and dementia, and 58 same-age men without a history of contact sports or TBI (unexposed; UE) and who denied cognitive or behavioral symptoms at telephone screening. Former players were categorized into four diagnostic groups: normal cognition, subjective memory impairment, mild cognitive impairment, and dementia. Positive florbetapir PET was defined by cortical-cerebellar average SUVR of ≥ 1.10. Multivariable linear regression and analysis of covariance (ANCOVA) compared florbetapir average SUVR across diagnostic and exposure groups. Multivariable logistic regression compared florbetapir positivity. Race, education, age, and APOE4 were covariates.

RESULTS

There were no diagnostic group differences either in florbetapir average SUVR or the proportion of elevated florbetapir uptake. Average SUVR means also did not differ between exposure groups: PRO-COL (p = 0.94, 95% C.I. = [- 0.033, 0.025]), PRO-UE (p = 0.40, 95% C.I. = [- 0.010, 0.029]), COL-UE (p = 0.36, 95% CI = [0.0004, 0.039]). Florbetapir was not significantly associated with years of football exposure, cognition, or daily functioning.

CONCLUSIONS

Cognitive impairment in former American football players is not associated with PET imaging of neuritic Aβ plaque deposition. These findings are inconsistent with a neuropathological diagnosis of AD in individuals with substantial RHI exposure and have both clinical and medico-legal implications.

TRIAL REGISTRATION

NCT02798185.

Emulsion Technology in Nuclear Medicine: Targeted Radionuclide Therapies, Radiosensitizers, and Imaging Agents

Radiopharmaceuticals serve as a major part of nuclear medicine contributing to both diagnosis and treatment of several diseases, especially cancers. Currently, most radiopharmaceuticals are based on small molecules with targeting ability. However, some concerns over their stability or non-specific interactions leading to off-target localization are among the major challenges that need to be overcome. Emulsion technology has great potential for the fabrication of carrier systems for radiopharmaceuticals. It can be used to create particles with different compositions, structures, sizes, and surface characteristics from a wide range of generally recognized as safe (GRAS) materials, which allows their functionality to be tuned for specific applications. In particular, it is possible to carry out surface modifications to introduce targeting and stealth properties, as well as to control the particle dimensions to manipulate diffusion and penetration properties. Moreover, emulsion preparation methods are usually simple, economic, robust, and scalable, which makes them suitable for medical applications. In this review, we highlight the potential of emulsion technology in nuclear medicine for developing targeted radionuclide therapies, for use as radiosensitizers, and for application in radiotracer delivery in gamma imaging techniques.

Insights into the pathological basis of dementia from population-based neuropathology studies

The epidemiological neuropathology perspective of population and community-based studies allows unbiased assessment of the prevalence of various pathologies and their relationships to late-life dementia. In addition, this approach provides complementary insights to conventional case-control studies, which tend to be more representative of a younger clinical cohort. The Cognitive Function and Ageing Study (CFAS) is a longitudinal study of cognitive impairment and frailty in the general United Kingdom population. In this review, we provide an overview of the major findings from CFAS, alongside other studies, which have demonstrated a high prevalence of pathology in the ageing brain, particularly Alzheimer's disease neuropathological change and vascular pathology. Increasing burdens of these pathologies are the major correlates of dementia, especially neurofibrillary tangles, but there is substantial overlap in pathology between those with and without dementia, particularly at intermediate burdens of pathology and also at the oldest ages. Furthermore, additional pathologies such as limbic-predominant age-related TDP-43 encephalopathy, ageing-related tau astrogliopathy and primary age-related tauopathies contribute to late-life dementia. Findings from ageing population-representative studies have implications for the understanding of dementia pathology in the community. The high prevalence of pathology and variable relationship to dementia status has implications for disease definition and indicate a role for modulating factors on cognitive outcome. The complexity of late-life dementia, with mixed pathologies, indicates a need for a better understanding of these processes across the life-course to direct the best research for reducing risk in later life of avoidable clinical dementia syndromes.

Anti-Amyloid Immunotherapies for Alzheimer's Disease: A 2023 Clinical Update

The amyloid cascade hypothesis is a useful framework for therapeutic development in Alzheimer's disease (AD). Amyloid b1-42 (Aβ) has been the main target of experimental therapies, based on evidence of the neurotoxic effects of Aβ, and of the potential adverse effects of brain Aβ burden detected in humans in vivo by positron emission tomography (PET). Progress on passive anti-amyloid immunotherapy research includes identification of antibodies that facilitate microglial activation, catalytical disaggregation, and increased flow of Aβ from cerebrospinal fluid (CSF) to plasma, thus decreasing the neurotoxic effects of Aβ. Recently completed phase 2 and 3 trials of 3rd generation anti-amyloid immunotherapies are supportive of their clinical efficacy in reducing brain Aβ burden and preventing cognitive decline. Data from recent trials implicate these agents as the first effective disease-modifying therapies against AD and has led to the US Food and Drug Administration (FDA) recent approval of aducanumab and lecanemab, under an accelerated approval pathway. The clinical effects of these agents are modest, however, and associated with amyloid-related imaging abnormalities (ARIA). Testing the effects of anti-Aβ immunotherapies in pre-symptomatic populations and identification of more potent and safer agents is the scope of ongoing and future research. Innovations in clinical trial design will be the key for the efficient and equitable development of novel anti-Aβ immunotherapies. The progress in the field of AD therapeutics will bring new clinical, logistical, and ethical challenges, which pose to revolutionize the practice of neurology, dementia care, and preventive cognitive healthcare.

Development of [18F]Thiazolylacylaminopyridine-Based Glycogen Synthase Kinase-3β Ligands for Positron Emission Tomography Imaging

Glycogen synthase kinase-3β (GSK-3β) regulates numerous of CNS-specific signaling pathways, and is particularly implicated in various pathogenetic mechanisms of Alzheimer's disease (AD). A noninvasive method for detecting GSK-3β in AD brains via positron emission tomography (PET) imaging could enhance the understanding of AD pathogenesis and aid in the development of AD therapeutic drugs. In this study, an array of fluorinated thiazolyl acylaminopyridines (FTAAP) targeting GSK-3β were designed and synthesized. These compounds showed moderate to high affinities (IC₅₀ = 6.0 - 426 nM) for GSK-3β in vitro. A potential GSK-3β tracer, [¹⁸F]8, was successfully radiolabeled. [¹⁸F]8 had unsatisfactory initial brain uptake despite its suitable lipophilicity, molecular size and good stability. Further structural refinement of the lead compound is needed to develop promising [¹⁸F]-labeled radiotracers for the detection of GSK-3β in AD brains.