Amyloid Imaging Research Articles

Amyloid Imaging Update: How the Amyloid Landscape Is Changing in Light of the Recent Food and Drug Administration Approval of Antiamyloid Therapeutics.

It has been some time since the Journal of Nuclear Medicine and Technology has published an article on best practices in amyloid imaging. In light of the recent Food and Drug Administration approval of new antiamyloid therapies (AATs) to decrease amyloid plaques in the brain and slow progression of mild cognitive impairment, and the potential increase in the number of amyloid PET scans being acquired to document amyloid plaques, the Journal of Nuclear Medicine and Technology felt it was a perfect time to publish a refresher on best practices. AATs are administered to help slow progression of mild cognitive impairment, allowing patients to live independently a little longer before having to give up their independence and move in with family or into an assisted living facility. Neurologists prescribing AATs must first document that the patient has amyloid plaques. To do this, amyloid PET can be performed, or a lumbar puncture can be used to look for amyloid plaques in the cerebrospinal fluid. Although the latter is more cost-effective and has no associated radiation exposure, it is highly invasive compared with amyloid PET. High-quality amyloid PET scans interpretated by a trained nuclear medicine physician are the first step and key to providing the dementia expert and patient with accurate information on amyloid status, allowing for the best decisions on patient management.

Positron Emission Tomography/Computed Tomography Imaging in Therapeutic Clinical Trials in Alzheimer's Disease: AnOverview of the Current State of the Artof Research.

The integration of positron emission tomography/computed tomography (PET/CT) has revolutionized the landscape of Alzheimer's disease (AD) research and therapeutic interventions. By combining structural and functional imaging, PET/CT provides a comprehensive understanding of disease pathology and response to treatment assessment. PET/CT, particularly with 2-deoxy-2-[fluorine-18]fluoro-D-glucose (18F-FDG), facilitates the visualization of glucose metabolism in the brain, enabling early diagnosis, staging, and monitoring of neurodegenerative disease progression. The advent of amyloid and tau PET imaging has further propelled the field forward, offering invaluable tools for tracking pathological hallmarks, assessing treatment response, and predicting clinical outcomes. While some therapeutic interventions targeting amyloid plaque load showed promising results with the reduction of cerebral amyloid accumulation over time, others failed to demonstrate a significant impact of anti-amyloid agents for reducing the amyloid plaques burden in AD brains. Tau PET imaging has conversely fueled the advent of disease-modifying therapeutic strategies in AD by supporting the assessment of neurofibrillary tangles of tau pathology deposition over time. Looking ahead, PET imaging holds immense promise for studying additional targets such as neuroinflammation, cholinergic deficit, and synaptic dysfunction. Advances in radiotracer development, dedicated brain PET/CT scanners, and Artificial Intelligence-powered software are poised to enhance the quality, sensitivity, and diagnostic power of molecular neuroimaging. Consequently, PET/CT remains at the forefront of AD research, offering unparalleled opportunities for unravelling the complexities of the disease and advancing therapeutic interventions, although it is not yet enough alone to allow patients' recruitment in therapeutic clinical trials.

Real-Time 3D Imaging and Inhibition Analysis of Human Serum Amyloid A Aggregations Using Quantum Dots.

Serum amyloid A (SAA) is one of the most important precursor amyloid proteins discovered during the study of amyloidosis, but its underlying aggregation mechanism has not yet been well elucidated. Since SAA aggregation is a key step in the pathogenesis of AA amyloidosis, amyloid inhibitors can be used as a tool to study its pathogenesis. Previously, we reported a novel microliter-scale high-throughput screening (MSHTS) system for screening amyloid β (Aβ) aggregation inhibitors based on quantum dot (QD) fluorescence imaging technology. In this study, we report the aggregation of human SAA (hSAA) in phosphate-buffered saline, in which we successfully visualized hSAA aggregation by QD using fluorescence microscopy and confocal microscopy. Two-dimensional and three-dimensional image analyses showed that most aggregations were observed at 40 μM hSAA, which was the optimal aggregation concentration in vitro. The accuracy of this finding was verified by a Thioflavin T assay. The transmission electron microscopy results showed that QD uniformly bound to hSAA aggregation. hSAA aggregation inhibitory activity was also evaluated by rosmarinic acid (RA). The results showed that RA, which is a compound with high inhibitory activity against Aβ aggregation, also exhibited high inhibitory activity against 40 μM hSAA. These results indicate that the MSHTS system is an effective tool for visualizing hSAA aggregation and for screening highly active inhibitors.

Isotope Encoded chemical Imaging Identifies Amyloid Plaque Age Dependent Structural Maturation, Synaptic Loss, and Increased Toxicity.

It is of critical importance to our understanding of Alzheimer's disease (AD) pathology to determine how key pathological factors are interconnected and implicated in nerve cell death, clinical symptoms, and disease progression. The formation of extracellular beta-amyloid (Aβ) plaques is the major pathological hallmark of AD and Aβ has been suggested to be a critical inducer of AD, driving disease pathogenesis. Exactly how Aβ plaque formation begins and how ongoing plaque deposition proceeds and initiates subsequent neurotoxic mechanisms is not well understood. The primary aim of our research is to elucidate the biochemical processes underlying early Aβ plaque formation in brain tissue. We recently introduced a chemical imaging paradigm based on mass spectrometry imaging (MSI) and metabolic isotope labelling to follow stable isotope labelling kinetics (iSILK) in vivo to track the in vivo build-up and deposition of Aβ. Herein, knock-in Aβ mouse models ( App NL-F ) that develop Aβ pathology gradually are metabolically labeled with stable isotopes. This chemical imaging approach timestamps amyloid plaques during the period of initial deposition allowing the fate of aggregating Aβ species from before and during the earliest events of plaque pathology through plaque maturation to be tracked. To identify the molecular and cellular response to plaque maturation, we integrated iSILK with single plaque transcriptomics performed on adjacent tissue sections. This enabled changes in gene expression to be tracked as a function of plaque age (as encoded in the Aβ peptide isotopologue pattern) distinct from changes due to the chronological age or pathological severity. This approach identified that plaque age correlates negatively with gene expression patterns associated with synaptic function as early as in 10-month-old animals but persists into 18 months. Finally, we integrated hyperspectral confocal microscopy into our multiomic approach to image amyloid structural isomers, revealing a positive correlation between plaque age and amyloid structural maturity. This analysis identified three categories of plaques, each with a distinct impact on the surrounding microenvironment. Here, we identified that older, more compact plaques were associated with the most significant synapse loss and toxicity. These data show how isotope-encoded MS imaging can be used to delineate Aβ toxicity dynamics in vivo. Moreover, we show for the first time a functional integration of dynamic MSI, structural plaque imaging and whole genome-wide spatial transcriptomics at the single plaque level. This multiomic approach offers an unprecedented combination of temporal and spatial resolution enabling a description of the earliest events of precipitating amyloid pathology and how Aβ modulates synaptotoxic mechanisms.

Comparison of brief olfactory and cognitive assessments to neuroimaging biomarkers in the prediction of cognitive decline and dementia in the MCSA cohort.

We evaluated impaired odor identification and global cognition as simple, cost-effective alternatives to neuroimaging biomarkers to predict cognitive decline and dementia in the Mayo Clinic Study of Aging. Six hundred forty-seven participants (mean 8.1, standard deviation 3.4 years' follow-up) had the following baseline procedures: modified Blessed Information Memory Concentration Test (BIMCT), 12-item Brief Smell Identification Test (BSIT), structural brain magnetic resonance imaging (MRI), and positron emission tomography (PET) imaging with 11C-Pittsburgh compound B (11C-PiB) and fluorodeoxyglucose (FDG; subset). Cognitive decline developed in 102 participants and dementia in 34 participants. In survival analyses, PiB PET showed robust prediction for cognitive decline. Impaired BSIT, impaired BIMCT, MRI, and FDG measures were also significant predictors. The combination of demographics + BSIT + BIMCT showed strong predictive utility (C-index 0.81), similar to demographics + PiB PET (C-index 0.80). Similar but stronger results were obtained for prediction of dementia. Impairment in both odor identification test and global cognition was comparable to PiB PET for predicting cognitive decline and dementia. In 647 participants in the population-based Mayo Clinic Study of Aging, several clinical markers and biomarkers each predicted cognitive decline or dementia during an average 8 years of follow-up. The combination of the demographic variables of age, sex, and education with a brief odor identification test (BSIT) and a global cognitive test (Blessed Information Memory Concentration Test) showed strong predictive utility (C-index 0.81) for cognitive decline that was similar to the demographic variables combined with Pittsburgh Compound B amyloid imaging (C-index 0.80). Combining a brief odor identification test with a brief cognitive test needs consideration as a simple, cost-effective option in the clinical assessment of individuals at risk of cognitive decline and dementia, as well as a potential tool to identify individuals who may benefit from disease-modifying treatments and to screen participants for prevention trials.

Integrating amyloid imaging and genetics for early risk stratification of Alzheimer's disease.

Alzheimer's disease (AD) initiates years prior to symptoms, underscoring the importance of early detection. While amyloid accumulation starts early, individuals with substantial amyloid burden may remain cognitively normal, implying that amyloid alone is not sufficient for early risk assessment. Given the genetic susceptibility of AD, a multi-factorial pseudotime approach was proposed to integrate amyloid imaging and genotype data for estimating a risk score. Validation involved association with cognitive decline and survival analysis across risk-stratified groups, focusing on patients with mild cognitive impairment (MCI). Our risk score outperformed amyloid composite standardized uptake value ratio in correlation with cognitive scores. MCI subjects with lower pseudotime risk score showed substantial delayed onset of AD and slower cognitive decline. Moreover, pseudotime risk score demonstrated strong capability in risk stratification within traditionally defined subgroups such as early MCI, apolipoprotein E (APOE) ε4+ MCI, APOE ε4- MCI, and amyloid+ MCI. Our risk score holds great potential to improve the precision of early risk assessment. Accurate early risk assessment is critical for the success of clinical trials. A new risk score was built from integrating amyloid imaging and genetic data. Our risk score demonstrated improved capability in early risk stratification.

Tracking the pre-clinical progression of transthyretin amyloid cardiomyopathy using artificial intelligence-enabled electrocardiography and echocardiography.

Diagnosing transthyretin amyloid cardiomyopathy (ATTR-CM) requires advanced imaging, precluding large-scale testing for pre-clinical disease. We examined the application of artificial intelligence (AI) to echocardiography (TTE) and electrocardiography (ECG) as a scalable strategy to quantify pre-clinical trends in ATTR-CM. Across age/sex-matched case-control datasets in the Yale-New Haven Health System (YNHHS) we trained deep learning models to identify ATTR-CM-specific signatures on TTE videos and ECG images (area under the curve of 0.93 and 0.91, respectively). We deployed these across all studies of individuals referred for cardiac nuclear amyloid imaging in an independent population at YNHHS and an external population from the Houston Methodist Hospitals (HMH) to define longitudinal trends in AI-defined probabilities for ATTR-CM using age/sex-adjusted linear mixed models, and describe discrimination metrics during the early pre-clinical stage. Among 984 participants referred for cardiac nuclear amyloid imaging at YNHHS (median age 74 years, 44.3% female) and 806 at HMH (69 years, 34.5% female), 112 (11.4%) and 174 (21.6%) tested positive for ATTR-CM, respectively. Across both cohorts and modalities, AI-defined ATTR-CM probabilities derived from 7,423 TTEs and 32,205 ECGs showed significantly faster progression rates in the years before clinical diagnosis in cases versus controls (p time × group interaction ≤0.004). In the one-to-three-year window before cardiac nuclear amyloid imaging sensitivity/specificity metrics were estimated at 86.2%/44.2% [YNHHS] vs 65.7%/65.5% [HMH] for AI-Echo, and 89.8%/40.6% [YNHHS] vs 88.5%/35.1% [HMH] for AI-ECG. We demonstrate that AI tools for echocardiographic videos and ECG images can enable scalable identification of pre-clinical ATTR-CM, flagging individuals who may benefit from risk-modifying therapies.

Amyloid Imaging With 124I-Evuzamitide Can Detect Temporal Changes in Systemic Amyloid Load and Correlates With Echocardiographic Parameters in Patients With AL or ATTR Amyloidosis

Amyloid Imaging With 124I-Evuzamitide Can Detect Temporal Changes in Systemic Amyloid Load and Correlates With Echocardiographic Parameters in Patients With AL or ATTR Amyloidosis

Stress testing the Centiloid: Precision and variability of PET quantification of amyloid pathology.

Assessing the potential sources of bias and variability of the Centiloid (CL) scale is fundamental for its appropriate clinical application. We included 533 participants from AMYloid imaging to Prevent Alzheimer's Disease (AMYPAD DPMS) and Alzheimer's Disease Neuroimaging Initiative (ADNI) cohorts. Thirty-two CL pipelines were created using different combinations of reference region (RR), RR and target types, and quantification spaces. Generalized estimating equations stratified by amyloid positivity were used to assess the impact of the quantification pipeline, radiotracer, age, brain atrophy, and harmonization status on CL. RR selection and RR type impact CL the most, particularly in amyloid-negative individuals. The standard CL pipeline with the whole cerebellum as RR is robust against brain atrophy and differences in image resolution, with 95% confidence intervals below±3.95 CL for amyloid beta positivity cutoffs (CL<24). The standard CL pipeline is recommended for most scenarios. Confidence intervals should be considered when operationalizing CL cutoffs in clinical and research settings. We developed a framework for evaluating Centiloid (CL) variability to different factors. Reference region selection and delineation had the highest impact on CL values. Whole cerebellum (WCB) and whole cerebellum plus brainstem (WCB+BSTM) as reference regions yielded consistent results across tracers. The standard CL pipeline is robust against atrophy and image resolution variation. Estimated within- and between-pipeline variability (95% confidence interval) in absolute CL units.

Improving the Diagnostic Yield of Amyloid Imaging Using the Jefferson Protocol

Improving the Diagnostic Yield of Amyloid Imaging Using the Jefferson Protocol

Associations of Physical Activity Engagement with Cerebral Amyloid-β and Tau from Midlife.

Higher midlife physical activity engagement has been associated with lower dementia risk in late life. However, the underlying mechanisms contributing to the protective effect remain unclear. The goal of the current study was to evaluate the associations of physical activity with cerebral amyloid-β (Aβ) and tau in a predominately middle-aged community-based cohort, as well as to explore whether the associations differ by sex or age. Participants from the Framingham Heart Study underwent 11C-Pittsburgh Compound B amyloid and 18F-Flortaucipir tau positron emission tomography (PET) imaging. Total physical activity levels were evaluated by self-report using the Physical Activity Index (PAI). Cross-sectional associations between total PAI with regional Aβ and tau PET retention were evaluated using linear regression models adjusted for demographic and cardiovascular risk factors. Interactions with sex and age group were examined and stratified analyses were performed when significant. FDR-correction for multiple comparisons was applied. The sample included 354 participants (mean age 53±8 years, 51% female). Higher total PAI scores were associated with lower entorhinal cortex tau PET binding (β(SE) = -0.021(0.008), p = 0.049). There were significant interactions with sex. In men alone, total PAI inversely associated with entorhinal cortex (β(SE) = -0.035(0.009), p = 0.001), inferior temporal (β(SE) = -0.029(0.010), p = 0.012), and rhinal cortex tau(β(SE) = -0.033(0.010), p = 0.002). The results suggest that higher midlife physical activity engagement may confer resistance to tau pathology. However, the effects may vary based on sex, highlighting the importance of better understanding and tailoring lifestyle interventions to address sex disparities.

Reasons for undergoing amyloid imaging among diverse enrollees in the A4 study.

Understanding attitudes toward participation among diverse preclinical Alzheimer's disease (AD) trial participants could yield insights to instruct future recruitment. Using data from the Anti-Amyloid Treatment in Asymptomatic AD (A4) Study, we examined differences among mutually exclusive racial and ethnic groups in views and perceptions of amyloid imaging (VPAI), a measure of motivations to undergo amyloid biomarker testing in the setting of preclinical AD. We used linear regression to quantify differences at baseline. Compared to non-Hispanic or Latino (NH) White participants, Hispanic or Latino (3.52 points, 95% confidence interval [CI]: [2.61, 4.42]); NH Asian (2.97 points, 95% CI: [1.71, 4.22]); and NH Black participants (2.79 points, 95% CI: [1.96, 3.63]) participants demonstrated higher levels of endorsement of the VPAI items at baseline. Differences may exist among participants from differing ethnic and racial groups in motivations to undergo biomarker testing in the setting of a preclinical AD trial. Representative samples in AD clinical trials are vital to result in generalizability. We assessed motivations to undergo amyloid imaging in a preclinical AD trial. Racial and ethnic minority groups showed higher endorsement of VPAI items. Differences were driven by perceived risk, plan/prepare, and curiosity domains. Few observations among racial and ethnic groups changed after biomarker disclosure.

Associations of cerebral amyloid beta and tau with cognition from midlife.

Understanding early neuropathological changes and their associations with cognition may aid dementia prevention. This study investigated associations of cerebral amyloid and tau positron emission tomography (PET) retention with cognition in a predominately middle-aged community-based cohort and examined factors that may modify these relationships. 11C-Pittsburgh compound B amyloid and 18F-flortaucipir tau PET imaging were performed. Associations of amyloid and tau PET with cognition were evaluated using linear regression. Interactions with age, apolipoprotein E (APOE) ε4 status, and education were examined. Amyloid and tau PET were not associated with cognition in the overall sample (N=423; mean: 57±10 years; 50% female). However, younger age (<55 years) and APOE ε4 were significant effect modifiers, worsening cognition in the presence of higher amyloid and tau. Higher levels of Aβ and tau may have a pernicious effect on cognition among APOE ε4 carriers and younger adults, suggesting a potential role for targeted early interventions. Risk and resilience factors influenced cognitive vulnerability due to Aβ and tau. Higher fusiform tau associated with poorer visuospatial skills in younger adults. APOE ε4 interacted with Aβ and tau to worsen cognition across multiple domains.

Continuous β-Amyloid CSF/PET Imbalance Model to Capture Alzheimer Disease Heterogeneity.

Discordance between CSF and PET biomarkers of β-amyloid (Aβ) might reflect an imbalance between soluble and aggregated species, possibly reflecting disease heterogeneity. Previous studies generally used binary cutoffs to assess discrepancies in CSF/PET biomarkers, resulting in a loss of information on the extent of discordance. In this study, we (1) jointly modeled Aβ-CSF/PET data to derive a continuous measure of the imbalance between soluble and fibrillar pools of Aβ, (2) investigated factors contributing to this imbalance, and (3) examined associations with cognitive trajectories. Across 822 cognitively unimpaired (n = 261) and cognitively impaired (n = 561) Alzheimer's Disease Neuroimaging Initiative individuals (384 [46.7%] females, mean age 73.0 ± 7.4 years), we fitted baseline CSF-Aβ42 and global Aβ-PET to a hyperbolic regression model, deriving a participant-specific Aβ-aggregation score (standardized residuals); negative values represent more soluble relative to aggregated Aβ and positive values more aggregated relative to soluble Aβ. Using linear models, we investigated whether methodological factors, demographics, CSF biomarkers, and vascular burden contributed to Aβ-aggregation scores. With linear mixed models, we assessed whether Aβ-aggregation scores were predictive of cognitive functioning. Analyses were repeated in an early independent validation cohort of 383 Amyloid Imaging to Prevent Alzheimer's Disease Prognostic and Natural History Study individuals (224 [58.5%] females, mean age 65.2 ± 6.9 years). The imbalance model could be fit (pseudo-R2 = 0.94) in both cohorts, across CSF kits and PET tracers. Although no associations were observed with the main methodological factors, lower Aβ-aggregation scores were associated with larger ventricular volume (β = 0.13, p < 0.001), male sex (β = -0.18, p = 0.019), and homozygous APOE-ε4 carriership (β = -0.56, p < 0.001), whereas higher scores were associated with increased uncorrected CSF p-tau (β = 0.17, p < 0.001) and t-tau (β = 0.16, p < 0.001), better baseline executive functioning (β = 0.12, p < 0.001), and slower global cognitive decline (β = 0.14, p = 0.006). In the validation cohort, we replicated the associations with APOE-ε4, CSF t-tau, and, although modestly, with cognition. We propose a novel continuous model of Aβ CSF/PET biomarker imbalance, accurately describing heterogeneity in soluble vs aggregated Aβ pools in 2 independent cohorts across the full Aβ continuum. Aβ-aggregation scores were consistently associated with genetic and AD-associated CSF biomarkers, possibly reflecting disease heterogeneity beyond methodological influences.

Retinal peri-arteriolar versus peri-venular amyloidosis, hippocampal atrophy, and cognitive impairment: exploratory trial

The relationship between amyloidosis and vasculature in cognitive impairment and Alzheimer’s disease (AD) pathogenesis is increasingly acknowledged. We conducted a quantitative and topographic assessment of retinal perivascular amyloid plaque (AP) distribution in individuals with both normal and impaired cognition. Using a retrospective dataset of scanning laser ophthalmoscopy fluorescence images from twenty-eight subjects with varying cognitive states, we developed a novel image processing method to examine retinal peri-arteriolar and peri-venular curcumin-positive AP burden. We further correlated retinal perivascular amyloidosis with neuroimaging measures and neurocognitive scores. Our study unveiled that peri-arteriolar AP counts surpassed peri-venular counts throughout the entire cohort (P < 0.0001), irrespective of the primary, secondary, or tertiary vascular branch location, with a notable increase among cognitively impaired individuals. Moreover, secondary branch peri-venular AP count was elevated in the cognitively impaired (P < 0.01). Significantly, peri-venular AP count, particularly in secondary and tertiary venules, exhibited a strong correlation with clinical dementia rating, Montreal cognitive assessment score, hippocampal volume, and white matter hyperintensity count. In conclusion, our exploratory analysis detected greater peri-arteriolar versus peri-venular amyloidosis and a marked elevation of amyloid deposition in secondary branch peri-venular regions among cognitively impaired subjects. These findings underscore the potential feasibility of retinal perivascular amyloid imaging in predicting cognitive decline and AD progression. Larger longitudinal studies encompassing diverse populations and AD-biomarker confirmation are warranted to delineate the temporal-spatial dynamics of retinal perivascular amyloid deposition in cognitive impairment and the AD continuum.

Evaluation of the feasibility of utilizing the H/CL ratio with HMDP/HDP cardiac amyloid imaging

Evaluation of the feasibility of utilizing the H/CL ratio with HMDP/HDP cardiac amyloid imaging

Generative AI unlocks PET insights: brain amyloid dynamics and quantification.

Studying the spatiotemporal patterns of amyloid accumulation in the brain over time is crucial in understanding Alzheimer's disease (AD). Positron Emission Tomography (PET) imaging plays a pivotal role because it allows for the visualization and quantification of abnormal amyloid beta (Aβ) load in the living brain, providing a powerful tool for tracking disease progression and evaluating the efficacy of anti-amyloid therapies. Generative artificial intelligence (AI) can learn complex data distributions and generate realistic synthetic images. In this study, we demonstrate for the first time the potential of Generative Adversarial Networks (GANs) to build a low-dimensional representation space that effectively describes brain amyloid load and its dynamics. Using a cohort of 1,259 subjects with AV45 PET images from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we develop a 3D GAN model to project images into a latent representation space and generate back synthetic images. Then, we build a progression model on the representation space based on non-parametric ordinary differential equations to study brain amyloid evolution. We found that global SUVR can be accurately predicted with a linear regression model only from the latent representation space (RMSE = 0.08 ± 0.01). We generated synthetic PET trajectories and illustrated predicted Aβ change in four years compared with actual progression. Generative AI can generate rich representations for statistical prediction and progression modeling and simulate evolution in synthetic patients, providing an invaluable tool for understanding AD, assisting in diagnosis, and designing clinical trials. The aim of this study was to illustrate the huge potential that generative AI has in brain amyloid imaging and to encourage its advancement by providing use cases and ideas for future research tracks.

Role of Amyloidogenic and Non-Amyloidogenic Protein Spaces in Neurodegenerative Diseases and their Mitigation Using Theranostic Agents.

Neurodegenerative diseases (NDDs) refer to a complex heterogeneous group of diseases which are associated with the accumulation of amyloid fibrils or plaques in the brain leading to progressive loss of neuronal functions. Alzheimer's disease is one of the major NDD responsible for 60-80 % of all dementia cases. Currently, there are no curative or disease-reversing/modifying molecules for many of the NDDs except a few such as donepezil, rivastigmine, galantamine, carbidopa and levodopa which treat the disease-associated symptoms. Similarly, there are very few FDA-approved tracers such as flortaucipir (Tauvid) for tau fibril imaging and florbetaben (Neuraceq), flutemetamol (Vizamyl), and florbetapir (Amyvid) for amyloid imaging available for diagnosis. Recent advances in the cryogenic electron microscopy reported distinctly different microstructures for tau fibrils associated with different tauopathies highlighting the possibility to develop tauopathy-specific imaging agents and therapeutics. In addition, it is important to identify the proteins that are associated with disease development and progression to know about their 3D structure to develop various diagnostics, therapeutics and theranostic agents. The current article discusses in detail the disease-associated amyloid and non-amyloid proteins along with their structural insights. We comprehensively discussed various novel proteins associated with NDDs and their implications in disease pathology. In addition, we document various emerging chemical compounds developed for diagnosis and therapy of different NDDs with special emphasis on theranostic agents for better management of NDDs.

HPR77 CMS Coverage Lift on PET Beta Amyloid Imaging Impact on mAb Treatment and Beneficiary Out-Of-Pocket Spending

HPR77 CMS Coverage Lift on PET Beta Amyloid Imaging Impact on mAb Treatment and Beneficiary Out-Of-Pocket Spending

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.