Early detection of Alzheimer's disease using PiB and FDG PET

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.

Influence of the Onset of Menopause on the Risk of Developing Alzheimer's Disease

Menopause is a natural phase marked by the permanent cessation of menstrual cycles, occurring when the production of reproductive hormones from the ovaries stops for at least 12 consecutive months. Studies have suggested a potential connection between menopause and a heightened risk of developing Alzheimer's disease (AD), underscoring the significant role of reduced estrogen levels in the development of AD. Estrogen plays a crucial role in brain metabolism, influencing energy metabolism, synaptic plasticity, and cognitive functions. The cognitive benefits associated with hormone replacement therapy (HRT) are believed to be linked to estrogen's neuroprotective effects, either through direct action on the brain or indirectly by improving cardiovascular health. Extensive literature supports the positive impact of estrogen on brain cells. While the physiological effects of estrogen on the brain have not been consistently replicated in clinical trials, further research is crucial to provide more definitive recommendations to menopausal patients regarding the influence of HRT on AD. This review aims to comprehensively explore the interplay between menopause and AD, as well as the potential of HRT to mitigate cognitive decline in post-menopausal individuals.

Cerebral Metabolic Signature of Chronic Benzodiazepine Use in Nondemented Older Adults: An FDG-PET Study in the MEMENTO Cohort

OBJECTIVE

We sought to examine the association between chronic Benzodiazepine (BZD) use and brain metabolism obtained from 2-deoxy-2-fluoro-D-glucose (FDG) positron emission tomography (PET) in the MEMENTO clinical cohort of nondemented older adults with an isolated memory complaint or mild cognitive impairment at baseline.

METHODS

Our analysis focused on 3 levels: (1) the global mean brain standardized uptake value (SUVR), (2) the Alzheimer's disease (AD)-specific regions of interest (ROIs), and (3) the ratio of total SUVR on the brain and different anatomical ROIs. Cerebral metabolism was obtained from 2-deoxy-2-fluoro-D-glucose-FDG-PET and compared between chronic BZD users and nonusers using multiple linear regressions adjusted for age, sex, education, APOE ε 4 copy number, cognitive and neuropsychiatric assessments, history of major depressive episodes and antidepressant use.

RESULTS

We found that the SUVR was significantly higher in chronic BZD users (n = 192) than in nonusers (n = 1,122) in the whole brain (beta = 0.03; p = 0.038) and in the right amygdala (beta = 0.32; p = 0.012). Trends were observed for the half-lives of BZDs (short- and long-acting BZDs) (p = 0.051) and Z-drug hypnotic treatments (p = 0.060) on the SUVR of the right amygdala. We found no significant association in the other ROIs.

CONCLUSION

Our study is the first to find a greater global metabolism in chronic BZD users and a specific greater metabolism in the right amygdala. Because the acute administration of BZDs tends to reduce brain metabolism, these findings may correspond to a compensatory mechanism while the brain adapts with global metabolism upregulation, with a specific focus on the right amygdala.

Basal forebrain volume and metabolism in carriers of the Colombian mutation for autosomal dominant Alzheimer's disease

We aimed to study atrophy and glucose metabolism of the cholinergic basal forebrain in non-demented mutation carriers for autosomal dominant Alzheimer's disease (ADAD). We determined the level of evidence for or against atrophy and impaired metabolism of the basal forebrain in 167 non-demented carriers of the Colombian PSEN1 E280A mutation and 75 age- and sex-matched non-mutation carriers of the same kindred using a Bayesian analysis framework. We analyzed baseline MRI, amyloid PET, and FDG-PET scans of the Alzheimer's Prevention Initiative ADAD Colombia Trial. We found moderate evidence against an association of carrier status with basal forebrain volume (Bayes factor (BF10) = 0.182). We found moderate evidence against a difference of basal forebrain metabolism (BF10 = 0.167). There was only inconclusive evidence for an association between basal forebrain volume and delayed memory and attention (BF10 = 0.884 and 0.184, respectively), and between basal forebrain volume and global amyloid load (BF10 = 2.1). Our results distinguish PSEN1 E280A mutation carriers from sporadic AD cases in which cholinergic involvement of the basal forebrain is already detectable in the preclinical and prodromal stages. This indicates an important difference between ADAD and sporadic AD in terms of pathogenesis and potential treatment targets.

Neuroinflammation is linked to dementia risk in Parkinson's disease

The development of dementia is a devastating aspect of Parkinson's disease (PD), affecting nearly half of patients within 10 years post-diagnosis. For effective therapies to prevent and slow progression to PD dementia (PDD), the key mechanisms that determine why some people with PD develop early dementia, while others remain cognitively unaffected, need to be understood. Neuroinflammation and tau protein accumulation have been demonstrated in post-mortem PD brains, and in many other neurodegenerative disorders leading to dementia. However, whether these processes mediate dementia risk early on in the PD disease course is not established. To this end, we used PET neuroimaging with 11C-PK11195 to index neuroinflammation and 18F-AV-1451 for misfolded tau in early PD patients, stratified according to dementia risk in our 'Neuroinflammation and Tau Accumulation in Parkinson's Disease Dementia' (NET-PDD) study. The NET-PDD study longitudinally assesses newly-diagnosed PD patients in two subgroups at low and high dementia risk (stratified based on pentagon copying, semantic fluency, MAPT genotype), with comparison to age- and sex-matched controls. Non-displaceable binding potential (BPND) in 43 brain regions (Hammers' parcellation) was compared between groups (pairwise t-tests), and associations between BPND of the tracers tested (linear-mixed-effect models). We hypothesized that people with higher dementia risk have greater inflammation and/or tau accumulation in advance of significant cognitive decline. We found significantly elevated neuroinflammation (11C-PK11195 BPND) in multiple subcortical and restricted cortical regions in the high dementia risk group compared with controls, while in the low-risk group this was limited to two cortical areas. The high dementia risk group also showed significantly greater neuroinflammation than the low-risk group concentrated on subcortical and basal ganglia regions. Neuroinflammation in most of these regions was associated with worse cognitive performance (Addenbrooke's Cognitive Examination-III score). Overall neuroinflammation burden also correlated with serum levels of pro-inflammatory cytokines. In contrast, increases in 18F-AV-1451 (tau) BPND in PD versus controls were restricted to subcortical regions where off-target binding is typically seen, with no relationship to cognition found. Whole-brain 18F-AV-1451 burden correlated with serum phosphorylated tau181 levels. Although there was minimal regional tau accumulation in PD, regional neuroinflammation and tau burden correlated in PD participants, with the strongest association in the high dementia risk group, suggesting possible co-localization of these pathologies. In conclusion, our findings suggest that significant regional neuroinflammation in early PD might underpin higher risk for PDD development, indicating neuroinflammation as a putative early modifiable aetiopathological disease factor to prevent or slow dementia development using immunomodulatory strategies.

Brain metabolic network covariance and aging in a mouse model of Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD), the leading cause of dementia worldwide, represents a human and financial impact for which few effective drugs exist to treat the disease. Advances in molecular imaging have enabled assessment of cerebral glycolytic metabolism, and network modeling of brain region have linked to alterations in metabolic activity to AD stage.

METHODS

We performed 18 F-FDG positron emission tomography (PET) imaging in 4-, 6-, and 12-month-old 5XFAD and littermate controls (WT) of both sexes and analyzed region data via brain metabolic covariance analysis.

RESULTS

The 5XFAD model mice showed age-related changes in glucose uptake relative to WT mice. Analysis of community structure of covariance networks was different across age and sex, with a disruption of metabolic coupling in the 5XFAD model.

DISCUSSION

The current study replicates clinical AD findings and indicates that metabolic network covariance modeling provides a translational tool to assess disease progression in AD models.

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

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

PET/CT/MRI in Clinical Trials of Alzheimer's Disease

With the advent of PET imaging in 1976, 2-deoxy-2-[18F]fluoro-D-glucose (FDG)-PET became the preferred method for in vivo investigation of cerebral processes, including regional hypometabolism in Alzheimer's disease. With the emergence of amyloid-PET tracers, [11C]Pittsburgh Compound-B in 2004 and later [18F]florbetapir, [18F]florbetaben, and [18F]flumetamol, amyloid-PET has replaced FDG-PET in Alzheimer's disease anti-amyloid clinical trial treatments to ensure "amyloid positivity" as an entry criterion, and to measure treatment-related decline in cerebral amyloid deposits. MRI has been used to rule out other brain diseases and screen for 'amyloid-related imaging abnormalities' (ARIAs) of two kinds, ARIA-E and ARIA-H, characterized by edema and micro-hemorrhage, respectively, and, to a lesser extent, to measure changes in cerebral volumes. While early immunotherapy trials of Alzheimer's disease showed no clinical effects, newer monoclonal antibody trials reported decreases of 27% to 85% in the cerebral amyloid-PET signal, interpreted by the Food and Drug Administration as amyloid removal expected to result in a reduction in clinical decline. However, due to the lack of diagnostic specificity of amyloid-PET tracers, amyloid positivity cannot prevent the inclusion of non-Alzheimer's patients and even healthy subjects in these clinical trials. Moreover, the "decreasing amyloid accumulation" assessed by amyloid-PET imaging has questionable quantitative value in the presence of treatment-related brain damage (ARIAs). Therefore, future Alzheimer's clinical trials should disregard amyloid-PET imaging and focus instead on assessment of regional brain function by FDG-PET and MRI monitoring of ARIAs and brain volume loss in all trial patients.

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

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

A simulative deep learning model of SNP interactions on chromosome 19 for predicting Alzheimer's disease risk and rates of disease progression

BACKGROUND

Identifying genetic patterns that contribute to Alzheimer's disease (AD) is important not only for pre-symptomatic risk assessment but also for building personalized therapeutic strategies.

METHODS

We implemented a novel simulative deep learning model to chromosome 19 genetic data from the Alzheimer's Disease Neuroimaging Initiative and the Imaging and Genetic Biomarkers of Alzheimer's Disease datasets. The model quantified the contribution of each single nucleotide polymorphism (SNP) and their epistatic impact on the likelihood of AD using the occlusion method. The top 35 AD-risk SNPs in chromosome 19 were identified, and their ability to predict the rate of AD progression was analyzed.

RESULTS

Rs561311966 (APOC1) and rs2229918 (ERCC1/CD3EAP) were recognized as the most powerful factors influencing AD risk. The top 35 chromosome 19 AD-risk SNPs were significant predictors of AD progression.

DISCUSSION

The model successfully estimated the contribution of AD-risk SNPs that account for AD progression at the individual level. This can help in building preventive precision medicine.

Advances in diagnosing mild cognitive impairment and Alzheimer's disease using 11C-PIB- PET/CT and common neuropsychological tests

Alzheimer's disease (AD) is a critical health issue worldwide that has a negative impact on patients' quality of life, as well as on caregivers, society, and the environment. Positron emission tomography (PET)/computed tomography (CT) and neuropsychological scales can be used to identify AD and mild cognitive impairment (MCI) early, provide a differential diagnosis, and offer early therapies to impede the course of the illness. However, there are few reports of large-scale ¹¹C-PIB-PET/CT investigations that focus on the pathology of AD and MCI. Therefore, further research is needed to determine how neuropsychological test scales and PET/CT measurements of disease progression interact.

Brain glucose metabolism and dopamine transporter changes in rats with morphine-induced conditioned place preference

Addiction to morphine is a chronic brain disease leading to compulsive abuse. Drug addiction animal models with and without conditioned place preference (CPP) training have been used to investigate cue-elicited drug craving. We used ¹⁸ F-fluorodeoxyglucose (¹⁸ F-FDG) and ¹¹ C-2-β-carbomethoxy-3-β-(4-fluorophenyl)tropane (¹¹ C-CFT) micro-PET/CT scans to examine the regional changes in brain glucose metabolism and dopamine transporter (DAT) availability to study their relationship underlying drug memory in morphine-treated rat models with and without CPP. Standardized uptake value ratio (SUVr) of ¹⁸ F-FDG significantly decreased in the medial prefrontal cortex (mPFC) and cingulate with short-term morphine administration compared with the baseline condition. Voxelwise analysis indicated glucose metabolism alterations in the somatosensory cortex, hippocampus and cingulate in morphine-treated rats and in the striatum, thalamus, medial prefrontal cortex, primary motor cortex and many regions in the cortex in the CPP group compared with the baseline condition. Alterative glucose metabolism was also observed in the striatum, primary somatosensory cortex and some cortical regions in the CPP group compared with morphine alone group. DAT expression alterations were only observed in the long-term morphine compared with the short-term morphine group. This study shows that cerebral glucose metabolism significantly altered during morphine administration and CPP process mainly in the mPFC, striatum and hippocampus, which indicates that the function of these brain regions is involved in cue-induced craving and memory retrieval.

The oDGal Mouse: A Novel, Physiologically Relevant Rodent Model of Sporadic Alzheimer's Disease

Sporadic Alzheimer's disease (sAD) represents a serious and growing worldwide economic and healthcare burden. Almost 95% of current AD patients are associated with sAD as opposed to patients presenting with well-characterized genetic mutations that lead to AD predisposition, i.e., familial AD (fAD). Presently, the use of transgenic (Tg) animals overexpressing human versions of these causative fAD genes represents the dominant research model for AD therapeutic development. As significant differences in etiology exist between sAD and fAD, it is perhaps more appropriate to develop novel, more sAD-reminiscent experimental models that would expedite the discovery of effective therapies for the majority of AD patients. Here we present the oDGal mouse model, a novel model of sAD that displays a range of AD-like pathologies as well as multiple cognitive deficits reminiscent of AD symptomology. Hippocampal cognitive impairment and pathology were delayed with N-acetyl-cysteine (NaC) treatment, which strongly suggests that reactive oxygen species (ROS) are the drivers of downstream pathologies such as elevated amyloid beta and hyperphosphorylated tau. These features demonstrate a desired pathophenotype that distinguishes our model from current transgenic rodent AD models. A preclinical model that presents a phenotype of non-genetic AD-like pathologies and cognitive deficits would benefit the sAD field, particularly when translating therapeutics from the preclinical to the clinical phase.

Neuroinflammation and amyloid deposition in the progression of mixed Alzheimer and vascular dementia

BACKGROUND

Alzheimer's disease (AD) and vascular contributions to cognitive impairment and dementia (VCID) pathologies coexist in patients with cognitive impairment. Abnormal amyloid beta (Aβ) deposition is the hallmark pathologic biomarker for AD. Neuroinflammation may be a pathophysiological mechanism in both AD and VCID. In this study, we aimed to understand the role of neuroinflammation and Aβ deposition in white matter hyperintensities (WMH) progression and cognitive decline over a decade in patients with mixed AD and VCID pathologies.

METHODS

Twenty-four elderly participants (median [interquartile range] age 78 [64.8, 83] years old, 14 female) were recruited from the Knight Alzheimer Disease Research Center. 11C-PK11195 standard uptake value ratio (SUVR) and 11C-PiB mean cortical binding potential (MCBP) were used to evaluate neuroinflammation and Aβ deposition in-vivo, respectively. Fluid-attenuated inversion recovery MR images were acquired to obtain baseline WMH volume and its progression over 11.5 years. Composite cognitive scores (global, processing speed and memory) were computed at baseline and follow-up over 7.5 years. Multiple linear regression models evaluated the association between PET biomarkers (11C-PK11195 SUVR and 11C-PiB MCBP) and baseline WMH volume and cognitive function. Moreover, linear mixed-effects models evaluated whether PET biomarkers predicted greater WMH progression or cognitive decline over a decade.

RESULTS

Fifteen participants (62.5%) had mixed AD (positive PiB) and VCID (at least one vascular risk factor) pathologies. Elevated 11C-PK11195 SUVR, but not 11C-PiB MCBP, was associated with greater baseline WMH volume and predicted greater WMH progression. Elevated 11C-PiB MCBP was associated with baseline memory and global cognition. Elevated 11C-PK11195 SUVR and elevated 11C-PiB MCBP independently predicted greater global cognition and processing speed declines. No association was found between 11C-PK11195 SUVR and 11C-PiB MCBP.

CONCLUSIONS

Neuroinflammation and Aβ deposition may represent two distinct pathophysiological pathways, and both independently contributed to the progression of cognitive impairment in mixed AD and VCID pathologies. Neuroinflammation, but not Aβ deposition, contributed to WMH volume and progression.

Two Routes to Alzheimer's Disease Based on Differential Structural Changes in Key Brain Regions

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disorder with homogenous disease patterns. Neuropathological changes precede symptoms by up to two decades making neuroimaging biomarkers a prime candidate for early diagnosis, prognosis, and patient stratification.

OBJECTIVE

The goal of the study was to discern intermediate AD stages and their precursors based on neuroanatomical features for stratifying patients on their progression through different stages.

METHODS

Data include grey matter features from 14 brain regions extracted from longitudinal structural MRI and cognitive data obtained from 1,017 healthy controls and AD patients of ADNI. AD progression was modeled with a Hidden Markov Model, whose hidden states signify disease stages derived from the neuroanatomical data. To tie the progression in brain atrophy to a behavioral marker, we analyzed the ADAS-cog sub-scores in the stages.

RESULTS

The optimal model consists of eight states with differentiable neuroanatomical features, forming two routes crossing once at a very early point and merging at the final state. The cortical route is characterized by early and sustained atrophy in cortical regions. The limbic route is characterized by early decrease in limbic regions. Cognitive differences between the two routes are most noticeable in the memory domain with subjects from the limbic route experiencing stronger memory impairments.

CONCLUSION

Our findings corroborate that more than one pattern of grey matter deterioration with several discernable stages can be identified in the progression of AD. These neuroanatomical subtypes are behaviorally meaningful and provide a door into early diagnosis of AD and prognosis of the disease's progression.

Optimal transport- and kernel-based early detection of mild cognitive impairment patients based on magnetic resonance and positron emission tomography images

Background

To help clinicians provide timely treatment and delay disease progression, it is crucial to identify dementia patients during the mild cognitive impairment (MCI) stage and stratify these MCI patients into early and late MCI stages before they progress to Alzheimer’s disease (AD). In the process of diagnosing MCI and AD in living patients, brain scans are collected using neuroimaging technologies such as computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET). These brain scans measure the volume and molecular activity within the brain resulting in a very promising avenue to diagnose patients early in a minimally invasive manner.

Methods

We have developed an optimal transport based transfer learning model to discriminate between early and late MCI. Combing this transfer learning model with bootstrap aggregation strategy, we overcome the overfitting problem and improve model stability and prediction accuracy.

Results

With the transfer learning methods that we have developed, we outperform the current state of the art MCI stage classification frameworks and show that it is crucial to leverage Alzheimer’s disease and normal control subjects to accurately predict early and late stage cognitive impairment.

Conclusions

Our method is the current state of the art based on benchmark comparisons. This method is a necessary technological stepping stone to widespread clinical usage of MRI-based early detection of AD.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13195-021-00915-3).

Learning Cognitive-Test-Based Interpretable Rules for Prediction and Early Diagnosis of Dementia Using Neural Networks

Background: Accurate, cheap, and easy to promote methods for dementia prediction and early diagnosis are urgently needed in low- and middle-income countries. Integrating various cognitive tests using machine learning provides promising solutions. However, most effective machine learning models are black-box models that are hard to understand for doctors and could hide potential biases and risks. Objective: To apply cognitive-test-based machine learning models in practical dementia prediction and diagnosis by ensuring both interpretability and accuracy. Methods: We design a framework adopting Rule-based Representation Learner (RRL) to build interpretable diagnostic rules based on the cognitive tests selected by doctors. According to the visualization and test results, doctors can easily select the final rules after analysis and trade-off. Our framework is verified on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset (n = 606) and Peking Union Medical College Hospital (PUMCH) dataset (n = 375). Results: The predictive or diagnostic rules learned by RRL offer a better trade-off between accuracy and model interpretability than other representative machine learning models. For mild cognitive impairment (MCI) conversion prediction, the cognitive-test-based rules achieve an average area under the curve (AUC) of 0.904 on ADNI. For dementia diagnosis on subjects with a normal Mini-Mental State Exam (MMSE) score, the learned rules achieve an AUC of 0.863 on PUMCH. The visualization analyses also verify the good interpretability of the learned rules. Conclusion: With the help of doctors and RRL, we can obtain predictive and diagnostic rules for dementia with high accuracy and good interpretability even if only cognitive tests are used.

A healthy mind in a healthy body: Effects of arteriosclerosis and other risk factors on cognitive aging and dementia

In this review we start from the assumption that, to fully understand cognitive aging, it is important to embrace a holistic view, integrating changes in bodily, brain, and cognitive functions. This broad view can help explain individual differences in aging trajectories and could ultimately enable prevention and remediation strategies. As the title of this review suggests, we claim that there are not only indirect but also direct effects of various organ systems on the brain, creating cascades of phenomena that strongly contribute to age-related cognitive decline. Here we focus primarily on the cerebrovascular system, because of its direct effects on brain health and close connections with the development and progression of Alzheimer's Disease and other types of dementia. We start by reviewing the main cognitive changes that are often observed in normally aging older adults, as well as the brain systems that support them. Second, we provide a brief overview of the cerebrovascular system and its known effects on brain anatomy and function, with a focus on aging. Third, we review genetic and lifestyle risk factors that may affect the cerebrovascular system and ultimately contribute to cognitive decline. Lastly, we discuss this evidence, review limitations, and point out avenues for additional research and clinical intervention.

Evaluation of 10-minute post-injection 11C-PiB PET and its correlation with 18F-FDG PET in older adults who are cognitively healthy, mildly impaired, or with probable Alzheimer's disease

OBJECTIVE

Positron emission tomography (PET) allows in vivo evaluation of molecular targets in neurodegenerative diseases, such as Alzheimer's disease. Mild cognitive impairment is an intermediate stage between normal cognition and Alzheimer-type dementia. In vivo fibrillar amyloid-beta can be detected in PET using [11C]-labeled Pittsburgh compound B (11C-PiB). In contrast, [18F]fluoro-2-deoxy-d-glucose (18F-FDG) is a neurodegeneration biomarker used to evaluate cerebral glucose metabolism, indicating neuronal injury and synaptic dysfunction. In addition, early cerebral uptake of amyloid-PET tracers can determine regional cerebral blood flow. The present study compared early-phase 11C-PiB and 18F-FDG in older adults without cognitive impairment, amnestic mild cognitive impairment, and clinical diagnosis of probable Alzheimer's disease.

METHODS

We selected 90 older adults, clinically classified as healthy controls, with amnestic mild cognitive impairment, or with probable Alzheimer's disease, who underwent an 18F-FDG PET, early-phase 11C-PiB PET and magnetic resonance imaging. All participants were also classified as amyloid-positive or -negative in late-phase 11C-PiB. The data were analyzed using statistical parametric mapping.

RESULTS

We found that the probable Alzheimer's disease and amnestic mild cognitive impairment group had lower early-phase 11C-PiB uptake in limbic structures than 18F-FDG uptake. The images showed significant interactions between amyloid-beta status (negative or positive). However, early-phase 11C-PiB appears to provide different information from 18F-FDG about neurodegeneration.

CONCLUSIONS

Our study suggests that early-phase 11C-PiB uptake correlates with 18F-FDG, irrespective of the particular amyloid-beta status. In addition, we observed distinct regional distribution patterns between both biomarkers, reinforcing the need for more robust studies to investigate the real clinical value of early-phase amyloid-PET imaging.

Acute inorganic nitrate intake increases regional insulin action in the brain: Results of a double-blind, randomized, controlled cross-over trial with abdominally obese men

AIMS

Improving brain insulin sensitivity may be a promising approach in the prevention and treatment of metabolic and cognitive diseases. Our aim was to investigate acute effects of inorganic nitrate on regional cerebral blood flow (CBF) responses to intranasal insulin in abdominally obese men.

METHODS

Eighteen apparently healthy men, aged 18-60 years and with a waist circumference ≥ 102 cm, participated in a randomized, double-blind, placebo-controlled cross-over trial. The study consisted of two test days separated by at least one week. Men received in random order a drink providing 10 mmol (i.e., 625 mg nitrate) potassium nitrate or an isomolar placebo drink with potassium chloride. Brain insulin action was assessed 120-150 min after the drinks by quantifying acute effects of nasal insulin on regional CBF using arterial spin labeling Magnetic Resonance Imaging. Glucose and insulin concentrations were measured at regular intervals, while blood pressure was determined fasted and at 240 min.

RESULTS

Inorganic nitrate intake increased regional insulin action in five brain clusters. The two largest clusters were located in the right temporal lobe (ΔCBF: 7.0 ± 3.8 mL/100 g/min, volume: 5296 mm³, P < 0.001; and ΔCBF: 6.5 ± 4.3 mL/100 g/min, volume: 3592 mm³, P < 0.001), while two other cortical clusters were part of the right frontal (ΔCBF: 9.0 ± 6.0 mL/100 g/min, volume: 1096 mm³, P = 0.007) and the left parietal lobe (ΔCBF: 6.1 ± 4.3 mL/100 g/min, volume: 1024 mm³, P = 0.012). One subcortical cluster was located in the striatum (ΔCBF: 5.9 ± 3.2 mL/100 g/min, volume: 1792 mm³, P < 0.001). No effects of nitrate were observed on CBF before administration. Following nitrate intake, circulating nitrate plus nitrite concentrations increased over time (P = 0.003), but insulin and glucose concentrations and blood pressure did not change.

CONCLUSION

Acute inorganic nitrate intake may improve regional brain insulin action in abdominally obese men. These regions are involved in the regulation of different metabolic and cognitive processes. The trial was registered on January 6th, 2021 at ClinicalTrials.gov as NCT04700241.

Synthesis of novel benzothiazole derivatives and investigation of their enzyme inhibitory effects against Alzheimer's disease

The use of dual acetylcholinesterase (AChE)-monoamine oxidase B (MAO-B) inhibitors is a new approach in the treatment of Alzheimer disease (AD). In this work, 14 new benzothiazoles (4a-4n) were designed and synthesized. In biological activity studies, the AChE, butyrylcholinesterase (BChE), MAO-A and MAO-B inhibitory potentials of all compounds were evaluated using the in vitro fluorometric method. Additionally, amyloid beta (Aβ)-aggregation inhibitory effects of active compounds were evaluated by means of an in vitro kit-based method. The biological evaluation showed that compounds 4a, 4d, 4f, 4h, 4k and 4m displayed significant activity against AChE and MAO-B enzymes. Compound 4f displayed inhibitory activity against AChE and MAO-B enzyme with IC50 values of 23.4 ± 1.1 nM and 40.3 ± 1.7 nM, respectively. It has been revealed that compound 4f may have the potential to inhibit AChE and MAO-B enzymes, as well as the ability to prevent the formation of beta amyloid plaques accumulated in the brains of patients suffering from AD. In silico studies also support the obtained biological activity findings. Compound 4f provided strong interactions with the active site of both enzymes. In particular, the interaction of compound 4f with flavin adenine dinucleotide (FAD) in the MAO-B enzyme active site is a promising and exciting finding.

Commentary: Aducanumab-Related ARIA: Paean or Lament?

ABSTRACT

Høilund-Carlsen and colleagues raise important issues related to amyloid PET, diagnosis of Alzheimer disease, and recently approved antiamyloid treatment aducanumab. We discuss new developments that may direct us to methods of presymptomatic detection of Alzheimer disease and development of effective prevention and therapy.

Deep-learning prediction of amyloid deposition from early-phase amyloid positron emission tomography imaging

OBJECTIVE

While the use of biomarkers for the detection of early and preclinical Alzheimer's Disease has become essential, the need to wait for over an hour after injection to obtain sufficient image quality can be challenging for patients with suspected dementia and their caregivers. This study aimed to develop an image-based deep-learning technique to generate delayed uptake patterns of amyloid positron emission tomography (PET) images using only early-phase images obtained from 0-20 min after radiotracer injection.

METHODS

We prepared pairs of early and delayed [¹¹C]PiB dynamic images from 253 patients (cognitively normal n = 32, fronto-temporal dementia n = 39, mild cognitive impairment n = 19, Alzheimer's disease n = 163) as a training dataset. The neural network was trained with the early images as the input, and the output was the corresponding delayed image. A U-net convolutional neural network (CNN) and a conditional generative adversarial network (C-GAN) were used for the deep-learning architecture and the data augmentation methods, respectively. Then, an independent test data set consisting of early-phase amyloid PET images (n = 19) was used to generate corresponding delayed images using the trained network. Two nuclear medicine physicians interpreted the actual delayed images and predicted delayed images for amyloid positivity. In addition, the concordance of the actual delayed and predicted delayed images was assessed statistically.

RESULTS

The concordance of amyloid positivity between the actual versus AI-predicted delayed images was 79%(κ = 0.60) and 79% (κ = 0.59) for each physician, respectively. In addition, the physicians' agreement rate was at 89% (κ = 0.79) when the same image was interpreted. And, the actual versus AI-predicted delayed images were not readily distinguishable (correct answer rate, 55% and 47% for each physician, respectively). The statistical comparison of the actual versus the predicted delated images indicated that the peak signal-to-noise ratio (PSNR) was 21.8 dB ± 2.2 dB, and the structural similarity index (SSIM) was 0.45 ± 0.04.

CONCLUSION

This study demonstrates the feasibility of an image-based deep-learning framework to predict delayed patterns of Amyloid PET uptake using only the early phase images. This AI-based image generation method has the potential to reduce scan time for amyloid PET and increase the patient throughput, without sacrificing diagnostic accuracy for amyloid positivity.

Aducanumab-Related Amyloid-Related Imaging Abnormalities: Paean or Lament?

ABSTRACT

When the FDA granted accelerated approval of Biogen's Alzheimer disease drug, aducanumab (marketed as Aduhelm), it deviated from its mission of guaranteeing drug safety and efficacy because the approval was based exclusively on a perceived dose-dependent reduction in brain amyloid deposits and not upon a proven clinical effect. We believe that the amyloid-PET scans, perceived as showing decreasing amyloid deposits, are an expression of increased cerebral cell death due to aducanumab treatment, so that with time one should instead expect a worsening and not an improvement in the treated patients' condition.

Cortical excitability and plasticity in Alzheimer's disease and mild cognitive impairment: A systematic review and meta-analysis of transcranial magnetic stimulation studies

BACKGROUND

Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique. When stimulation is applied over the primary motor cortex and coupled with electromyography measures, TMS can probe functions of cortical excitability and plasticity in vivo. The purpose of this meta-analysis is to evaluate the utility of TMS-derived measures for differentiating patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) from cognitively normal older adults (CN).

METHODS

Databases searched included PubMed, Embase, APA PsycInfo, Medline, and CINAHL Plus from inception to July 2021.

RESULTS

Sixty-one studies with a total of 2728 participants (1454 patients with AD, 163 patients with MCI, and 1111 CN) were included. Patients with AD showed significantly higher cortical excitability, lower cortical inhibition, and impaired cortical plasticity compared to the CN cohorts. Patients with MCI exhibited increased cortical excitability and reduced plasticity compared to the CN cohort. Additionally, lower cognitive performance was significantly associated with higher cortical excitability and lower inhibition. No seizure events due to TMS were reported, and the mild adverse response rate is approximately 3/1000 (i.e., 9/2728).

CONCLUSIONS

Findings of our meta-analysis demonstrate the potential of using TMS-derived cortical excitability and plasticity measures as diagnostic biomarkers and therapeutic targets for AD and MCI.

PET Imaging in Animal Models of Alzheimer’s Disease

The successful development and translation of PET imaging agents targeting β-amyloid plaques and hyperphosphorylated tau tangles have allowed for in vivo detection of these hallmarks of Alzheimer’s disease (AD) antemortem. Amyloid and tau PET have been incorporated into the A/T/N scheme for AD characterization and have become an integral part of ongoing clinical trials to screen patients for enrollment, prove drug action mechanisms, and monitor therapeutic effects. Meanwhile, preclinical PET imaging in animal models of AD can provide supportive information for mechanistic studies. With the recent advancement of gene editing technologies and AD animal model development, preclinical PET imaging in AD models will further facilitate our understanding of AD pathogenesis/progression and the development of novel treatments. In this study, we review the current state-of-the-art in preclinical PET imaging using animal models of AD and suggest future research directions.

Potential role of Drug Repositioning Strategy (DRS) for management of tauopathy

Tauopathy is a term that has been used to represent a pathological condition in which hyperphosphorylated tau protein aggregates in neurons and glia which results in neurodegeneration, synapse loss and dysfunction and cognitive impairments. Recently, drug repositioning strategy (DRS) becomes a promising field and an alternative approach to advancing new treatments from actually developed and FDA approved drugs for an indication other than the indication it was originally intended for. This paradigm provides an advantage because the safety of the candidate compound has already been established, which abolishes the need for further preclinical safety testing and thus substantially reduces the time and cost involved in progressing of clinical trials. In the present review, we focused on correlation between tauopathy and common diseases as type 2 diabetes mellitus and the global virus COVID-19 and how tau pathology can aggravate development of these diseases in addition to how these diseases can be a risk factor for development of tauopathy. Moreover, correlation between COVID-19 and type 2 diabetes mellitus was also discussed. Therefore, repositioning of a drug in the daily clinical practice of patients to manage or prevent two or more diseases at the same time with lower side effects and drug-drug interactions is a promising idea. This review concluded the results of pre-clinical and clinical studies applied on antidiabetics, COVID-19 medications, antihypertensives, antidepressants and cholesterol lowering drugs for possible drug repositioning for management of tauopathy.

Salience network anatomical and molecular markers are linked with cognitive dysfunction in mild cognitive impairment

BACKGROUND AND PURPOSE

Recent studies indicate disrupted functional mechanisms of salience network (SN) regions-right anterior insula, left anterior insula, and anterior cingulate cortex-in mild cognitive impairment (MCI). However, the underlying anatomical and molecular mechanisms in these regions are not clearly understood yet. It is also unknown whether integration of multimodal-anatomical and molecular-markers could predict cognitive impairment better in MCI.

METHODS

Herein we quantified anatomical volumetric markers via structural MRI and molecular amyloid markers via PET with Pittsburgh compound B in SN regions of MCI (n = 33) and healthy controls (n = 27). From these markers, we built support vector machine learning models aiming to estimate cognitive dysfunction in MCI.

RESULTS

We found that anatomical markers are significantly reduced and molecular markers are significantly elevated in SN nodes of MCI compared to healthy controls (p < .05). These altered markers in MCI patients were associated with their worse cognitive performance (p < .05). Our machine learning-based modeling further suggested that the integration of multimodal markers predicts cognitive impairment in MCI superiorly compared to using single modality-specific markers.

CONCLUSIONS

These findings shed light on the underlying anatomical volumetric and molecular amyloid alterations in SN regions and show the significance of multimodal markers integration approach in better predicting cognitive impairment in MCI.

Metabolic Syndrome: Is It Time to Add the Central Nervous System?

Metabolic syndrome (MS) is a set of cardio-metabolic risk factors that includes central obesity, hyperglycemia, hypertension, and dyslipidemias. The syndrome affects 25% of adults worldwide. The definition of MS has evolved over the last 80 years, with various classification systems and criteria, whose limitations and benefits are currently the subject of some controversy. Likewise, hypotheses regarding the etiology of MS add more confusion from clinical and epidemiological points of view. The leading suggestion for the pathophysiology of MS is insulin resistance (IR). IR can affect multiple tissues and organs, from the classic “triumvirate” (myocyte, adipocyte, and hepatocyte) to possible effects on organs considered more recently, such as the central nervous system (CNS). Mild cognitive impairment (MCI) and Alzheimer’s disease (AD) may be clinical expressions of CNS involvement. However, the association between MCI and MS is not understood. The bidirectional relationship that seems to exist between these factors raises the questions of which phenomenon occurs first and whether MCI can be a precursor of MS. This review explores shared pathophysiological mechanisms between MCI and MS and establishes a hypothesis of a possible MCI role in the development of IR and the appearance of MS.

Quantum dots as a theranostic approach in Alzheimer's disease: a systematic review

Aim: Quantum dots (QDs) are nanoparticles that have an emerging application as theranostic agents in several neurodegenerative diseases. The advantage of QDs as nanomedicine is due to their unique optical properties that provide high sensitivity, stability and selectivity at a nanoscale range. Objective: To offer renewed insight into current QD research and elucidate its promising application in Alzheimer's disease (AD) diagnosis and therapy. Methods: A comprehensive literature search was conducted in PubMed and Google Scholar databases that included the following search terms: 'quantum dots', 'blood-brain barrier', 'cytotoxicity', 'toxicity' and 'Alzheimer's disease'; PRISMA guidelines were adhered to. Results: Thirty-four publications were selected to evaluate the ability of QDs to cross the blood-brain barrier, potential toxicity and current AD diagnostic and therapeutic applications. Conclusion: QD's unique optical properties and versatility to conjugate to various biomolecules, while maintaining a nanoscale size, render them a promising theranostic tool in AD.

The Role of Free and Cued Selective Reminding Test in Predicting [18F]Florbetaben PET Results in Mild Cognitive Impairment and Mild Dementia

BACKGROUND

Free and Cued Selective Reminding Test (FCSRT) is a reliable cognitive marker for Alzheimer's disease (AD), and the identification of neuropsychological tests sensitive to the early signs of AD pathology is crucial both in research and clinical practice.

OBJECTIVE

The study aimed to ascertain the ability of FCSRT in predicting the amyloid load as determined from amyloid PET imaging (Amy-PET) in patients with cognitive disorders.

METHODS

For our purpose, 79 patients (71 MCI, 8 mild dementia) underwent a complete workup for dementia, including the FCSRT assessment and a [18F]florbetaben PET scan. FCSRT subitem scores were used as predictors in different binomial regression models.

RESULTS

Immediate free recall and delayed free recall were the best predictors overall in the whole sample; whereas in patients <76 years, all models further improved with immediate total recall (ITR) and Index of Sensitivity of Cueing (ISC) resulting the most accurate in anticipating Amy-PET results, with a likelihood of being Amy-PET positive greater than 85% for ITR and ISC scores of less than 25 and 0.5, respectively.

CONCLUSION

FCSRT proved itself to be a valid tool in dementia diagnosis, also being able to correlate with amyloid pathology. The possibility to predict Amy-PET results through a simple and reliable neuropsychological test might be helpful for clinicians in the dementia field, adding value to a paper and pencil tool compared to most costly biomarkers.

A New Serum Biomarker Set to Detect Mild Cognitive Impairment and Alzheimer's Disease by Peptidome Technology

Background:

Because dementia is an emerging problem in the world, biochemical markers of cerebrospinal fluid (CSF) and radio-isotopic analyses are helpful for diagnosing Alzheimer’s disease (AD). Although blood sample is more feasible and plausible than CSF or radiological biomarkers for screening potential AD, measurements of serum amyloid- β (Aβ), plasma tau, and serum antibodies for Aβ_1 - 42 are not yet well established.

Objective:

We aimed to identify a new serum biomarker to detect mild cognitive impairment (MCI) and AD in comparison to cognitively healthy control by a new peptidome technology.

Methods:

With only 1.5μl of serum, we examined a new target plate “BLOTCHIP^®” plus a matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS) to discriminate control (n = 100), MCI (n = 60), and AD (n = 99). In some subjects, cognitive Mini-Mental State Examination (MMSE) were compared to positron emission tomography (PET) with Pittsburgh compound B (PiB) and the serum probability of dementia (SPD). The mother proteins of candidate serum peptides were examined in autopsied AD brains.

Results:

Apart from Aβ or tau, the present study discovered a new diagnostic 4-peptides-set biomarker for discriminating control, MCI, and AD with 87% of sensitivity and 65% of specificity between control and AD (^***p < 0.001). MMSE score was well correlated to brain Aβ deposition and to SPD of AD. The mother proteins of the four peptides were upregulated for coagulation, complement, and plasticity (three proteins), and was downregulated for anti-inflammation (one protein) in AD brains.

Conclusion:

The present serum biomarker set provides a new, rapid, non-invasive, highly quantitative and low-cost clinical application for dementia screening, and also suggests an alternative pathomechanism of AD for neuroinflammation and neurovascular unit damage.

Amyloid burden quantification depends on PET and MR image processing methodology

Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer's Disease in-vivo. However, quantification can be affected by the image processing methodology applied. This study's goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their Native Space and Standard Space; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature. Intensity-related metrics were not substantially affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in Native Space avoiding non-rigid spatial transformations. For analyses in Standard Space, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in Native Space, while intensity-based metrics are more robust against differences in image processing pipelines.

Metformin attenuates plaque-associated tau pathology and reduces amyloid-β burden in APP/PS1 mice

Background

The neuropathological hallmarks of Alzheimer’s disease (AD) are amyloid-β (Aβ) plaques and neurofibrillary tangles (NFTs). The amyloid cascade theory is the leading hypothesis of AD pathology. Aβ deposition precedes the aggregation of tau pathology and Aβ pathology precipitates tau pathology. Evidence also indicates the reciprocal interactions between amyloid and tau pathology. However, the detailed relationship between amyloid and tau pathology in AD remains elusive. Metformin might have a positive effect on cognitive impairments. However, whether metformin can reduce AD-related pathologies is still unconclusive.

Methods

Brain extracts containing tau aggregates were unilaterally injected into the hippocampus and the overlying cerebral cortex of 9-month-old APPswe/PS1DE9 (APP/PS1) mice and age-matched wild-type (WT) mice. Metformin was administrated in the drinking water for 2 months. Aβ pathology, tau pathology, plaque-associated microgliosis, and autophagy marker were analyzed by immunohistochemical staining and immunofluorescence analysis 2 months after injection of proteopathic tau seeds. The effects of metformin on both pathologies were explored.

Results

We observed tau aggregates in dystrophic neurites surrounding Aβ plaques (NP tau) in the bilateral hippocampi and cortices of tau-injected APP/PS1 mice but not WT mice. Aβ plaques promoted the aggregation of NP tau pathology. Injection of proteopathic tau seeds exacerbated Aβ deposits and decreased the number of microglia around Aβ plaques in the hippocampus and cortex of APP/PS1 mice. Metformin ameliorated the microglial autophagy impairment, increased the number of microglia around Aβ plaques, promoted the phagocytosis of NP tau, and reduced Aβ load and NP tau pathology in APP/PS1 mice.

Conclusion

These findings indicate the existence of the crosstalk between amyloid and NP tau pathology. Metformin promoted the phagocytosis of pathological Aβ and tau proteins by enhancing microglial autophagy capability. It reduced Aβ deposits and limited the spreading of NP tau pathology in APP/PS1 mice, which exerts a beneficial effect on both pathologies.

History in perspective: How Alzheimer's Disease came to be where it is?

Treatment of Alzheimer's Disease (AD) remains an unsolved issue despite the pronounced global attention it has received from researchers over the last four decades. Determining the primary cause of the disease is challenging due to its long prodromal phase and multifactorial etiology. Regardless, academic disagreements amongst the scientific community have helped in making significant advancements in underpinning the molecular basis of disease pathogenesis. Substantial development in fluid and imaging biomarkers for AD led to a sharp turn in defining the disease as a molecular construct, dispensing its clinical definition. With conceptual progress, revisions in the diagnostic criteria of AD were made, culminating into the research framework proposed by National Institute on Aging and Alzheimer's Association in 2018 which unified different stages of the disease continuum, giving a common language of AT(N)¹ classification to researchers. With realization that dementia is the final stage of AD spectrum, its early diagnosis by means of cerebrospinal fluid biomarkers, Positron Emission Tomography and Magnetic Resonance Imaging of the brain holds crucial importance in discovering ways of halting the disease progression. This article maps the insights into the pathogenesis as well as the diagnostic criteria and tests for AD as these have evolved over time. A contextualized timeline of how the understanding of AD has matured with advancing knowledge allows future research to be directed and unexplored avenues to be prioritized.

Case Report: Long-Term Chemotherapy With Hydroxyurea and Prednisolone in a Cat With a Meningioma: Correlation of FDG Uptake and Tumor Grade Assessed by Histopathology and Expression of Ki-67 and p53

A 15.5-year-old, neutered, male, domestic shorthair cat was presented with neurologic dysfunctions. At presentation, an obtunded mental status and vestibular ataxia were identified. On neurologic examination, postural reactions were decreased-to-absent in all four limbs, and pupillary light reflexes showed bilaterally delayed results. Magnetic resonance imaging was performed, and a demarcated lesion was identified in the third ventricle. The cat was tentatively diagnosed with a brain tumor, which was suspected to be a meningioma. The cat was treated with hydroxyurea and prednisolone. Mental status was considered more alert, and ataxia improved following treatment. On the 106th day after the commencement of treatment, a ¹⁸F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) scan was performed. On the PET images, a hypermetabolic region was found in the lesion. The average standardized uptake value of FDG was 2.47, and the tumor-to-normal-tissue ratio was 1.25. The cat died 408 days following the commencement of treatment, and a grade 1 meningioma was confirmed by postmortem histopathology. Immunohistochemistry for Ki-67 and p53 was performed. The labeling indices of Ki-67 and p53 were 2.56 and 0%, respectively. This case shows that chemotherapy with hydroxyurea and prednisolone may be considered in the treatment of feline meningiomas. Furthermore, this is the first case describing the application of FDG-PET to visualize a naturally occurring meningioma in a cat.

Patterns of glucose hypometabolism in Down syndrome resemble sporadic Alzheimer's disease except for the putamen

INTRODUCTION

Adults with Down syndrome (DS) are predisposed to Alzheimer's disease (AD) and the relationship between cognition and glucose metabolism in this population has yet to be evaluated.

METHODS

Adults with DS (N = 90; mean age [standard deviation] = 38.0 [8.30] years) underwent [C-11]Pittsburgh compound B (PiB) and [F-18]fluorodeoxyglucose (FDG) positron emission tomography scans. Associations among amyloid beta (Aβ), FDG, and measures of cognition were explored. Interregional FDG metabolic connectivity was assessed to compare cognitively stable DS and mild cognitive impairment/AD (MCI-DS/AD).

RESULTS

Negative associations between Aβ and FDG were evident in regions affected in sporadic AD. A positive association was observed in the putamen, which is the brain region showing the earliest increases in Aβ deposition. Both Aβ and FDG were associated with measures of cognition, and metabolic connectivity distinguished cases of MCI-DS/AD from cognitively stable DS.

DISCUSSION

Associations among Aβ, FDG, and cognition reveal that neurodegeneration in DS resembles sporadic AD with the exception of the putamen, highlighting the usefulness of FDG in monitoring neurodegeneration in DS.

The Dysregulation of OGT/OGA Cycle Mediates Tau and APP Neuropathology in Down Syndrome

Protein O-GlcNAcylation is a nutrient-related post-translational modification that, since its discovery some 30 years ago, has been associated with the development of neurodegenerative diseases. As reported in Alzheimer's disease (AD), flaws in the cerebral glucose uptake translate into reduced hexosamine biosynthetic pathway flux and subsequently lead to aberrant protein O-GlcNAcylation. Notably, the reduction of O-GlcNAcylated proteins involves also tau and APP, thus promoting their aberrant phosphorylation in AD brain and the onset of AD pathological markers. Down syndrome (DS) individuals are characterized by the early development of AD by the age of 60 and, although the two conditions present the same pathological hallmarks and share the alteration of many molecular mechanisms driving brain degeneration, no evidence has been sought on the implication of O-GlcNAcylation in DS pathology. Our study aimed to unravel for the first time the role of protein O-GlcNacylation in DS brain alterations positing the attention of potential trisomy-related mechanisms triggering the aberrant regulation of OGT/OGA cycle. We demonstrate the disruption of O-GlcNAcylation homeostasis, as an effect of altered OGT and OGA regulatory mechanism, and confirm the relevance of O-GlcNAcylation in the appearance of AD hallmarks in the brain of a murine model of DS. Furthermore, we provide evidence for the neuroprotective effects of brain-targeted OGA inhibition. Indeed, the rescue of OGA activity was able to restore protein O-GlcNAcylation, and reduce AD-related hallmarks and decreased protein nitration, possibly as effect of induced autophagy.

Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation

Multimodal fusion in neuroimaging combines data from multiple imaging modalities to overcome the fundamental limitations of individual modalities. Neuroimaging fusion can achieve higher temporal and spatial resolution, enhance contrast, correct imaging distortions, and bridge physiological and cognitive information. In this study, we analyzed over 450 references from PubMed, Google Scholar, IEEE, ScienceDirect, Web of Science, and various sources published from 1978 to 2020. We provide a review that encompasses (1) an overview of current challenges in multimodal fusion (2) the current medical applications of fusion for specific neurological diseases, (3) strengths and limitations of available imaging modalities, (4) fundamental fusion rules, (5) fusion quality assessment methods, and (6) the applications of fusion for atlas-based segmentation and quantification. Overall, multimodal fusion shows significant benefits in clinical diagnosis and neuroscience research. Widespread education and further research amongst engineers, researchers and clinicians will benefit the field of multimodal neuroimaging.

Brain lipid peroxidation and alzheimer disease: Synergy between the Butterfield and Mattson laboratories

Brains from persons with Alzheimer disease (AD) and its earlier stage, amnestic mild cognitive impairment (MCI), exhibit high levels of oxidative damage, including that to phospholipids. One type of oxidative damage is lipid peroxidation, the most important index of which is protein-bound 4-hydroxy-2-trans-nonenal (HNE). This highly reactive alkenal changes the conformations and lowers the activities of brain proteins to which HNE is covalently bound. Evidence exists that suggests that lipid peroxidation is the first type of oxidative damage associated with amyloid β-peptide (Aβ), a 38-42 amino acid peptide that is highly neurotoxic and critical to the pathophysiology of AD. The Butterfield laboratory is one of, if not the, first research group to show that Aβ42 oligomers led to lipid peroxidation and to demonstrate this modification in brains of subjects with AD and MCI. The Mattson laboratory, particularly when Dr. Mattson was a faculty member at the University of Kentucky, also showed evidence for lipid peroxidation associated with Aβ peptides, mostly in in vitro systems. Consequently, there is synergy between our two laboratories. Since this special tribute issue of Aging Research Reviews is dedicated to the career of Dr. Mattson, a review of some aspects of this synergy of lipid peroxidation and its relevance to AD, as well as the role of lipid peroxidation in the progression of this dementing disorder seems germane. Accordingly, this review outlines some of the individual and/or complementary research on lipid peroxidation related to AD published from our two laboratories either separately or jointly.

Insulin Resistance at the Crossroad of Alzheimer Disease Pathology: A Review

Insulin plays a major neuroprotective and trophic function for cerebral cell population, thus countering apoptosis, beta-amyloid toxicity, and oxidative stress; favoring neuronal survival; and enhancing memory and learning processes. Insulin resistance and impaired cerebral glucose metabolism are invariantly reported in Alzheimer's disease (AD) and other neurodegenerative processes. AD is a fatal neurodegenerative disorder in which progressive glucose hypometabolism parallels to cognitive impairment. Although AD may appear and progress in virtue of multifactorial nosogenic ingredients, multiple interperpetuative and interconnected vicious circles appear to drive disease pathophysiology. The disease is primarily a metabolic/energetic disorder in which amyloid accumulation may appear as a by-product of more proximal events, especially in the late-onset form. As a bridge between AD and type 2 diabetes, activation of c-Jun N-terminal kinase (JNK) pathway with the ensued serine phosphorylation of the insulin response substrate (IRS)-1/2 may be at the crossroads of insulin resistance and its subsequent dysmetabolic consequences. Central insulin axis bankruptcy translates in neuronal vulnerability and demise. As a link in the chain of pathogenic vicious circles, mitochondrial dysfunction, oxidative stress, and peripheral/central immune-inflammation are increasingly advocated as major pathology drivers. Pharmacological interventions addressed to preserve insulin axis physiology, mitochondrial biogenesis-integral functionality, and mitophagy of diseased organelles may attenuate the adjacent spillover of free radicals that further perpetuate mitochondrial damages and catalyze inflammation. Central and/or peripheral inflammation may account for a local flood of proinflammatory cytokines that along with astrogliosis amplify insulin resistance, mitochondrial dysfunction, and oxidative stress. All these elements are endogenous stressor, pro-senescent factors that contribute to JNK activation. Taken together, these evidences incite to identify novel multi-mechanistic approaches to succeed in ameliorating this pandemic affliction.

Advantages and Pitfalls in Fluid Biomarkers for Diagnosis of Alzheimer's Disease

Alzheimer’s disease (AD) is a commonly occurring neurodegenerative disease in the advanced-age population, with a doubling of prevalence for each 5 years of age above 60 years. In the past two decades, there has been a sustained effort to find suitable biomarkers that may not only aide with the diagnosis of AD early in the disease process but also predict the onset of the disease in asymptomatic individuals. Current diagnostic evidence is supportive of some biomarker candidates isolated from cerebrospinal fluid (CSF), including amyloid beta peptide (Aβ), total tau (t-tau), and phosphorylated tau (p-tau) as being involved in the pathophysiology of AD. However, there are a few biomarkers that have been shown to be helpful, such as proteomic, inflammatory, oral, ocular and olfactory in the early detection of AD, especially in the individuals with mild cognitive impairment (MCI). To date, biomarkers are collected through invasive techniques, especially CSF from lumbar puncture; however, non-invasive (radio imaging) methods are used in practice to diagnose AD. In order to reduce invasive testing on the patients, present literature has highlighted the potential importance of biomarkers in blood to assist with diagnosing AD.

Mini Review: Opposing Pathologies in Cancer and Alzheimer's Disease: Does the PI3K/Akt Pathway Provide Clues?

This minireview is a brief overview examining the roles of insulin-like growth factors (IGFs) and the PI3K/Akt pathway in two apparently unconnected diseases: Alzheimer's dementia and cancer. For both, increased age is a major risk factor, and, in accord with the global rise in average life expectancy, their prevalence is also increasing. Cancer, however, involves excessive cell proliferation and metastasis, whereas Alzheimer's disease (AD) involves cell death and tissue destruction. The apparent "inverse" nature of these disease states is examined here, but also some important commonalities in terms of the PI3K/Akt pathway, glucose utilization and cell deregulation/death. The focus here is on four key molecules associated with this pathway; notably, the insulin receptor substrate 1 (IRS-1), cellular tumor antigen p53 (p53), peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1) and low-density lipoprotein receptor-related protein-1 (LRP1), all previously identified as potential therapeutic targets for both diseases. The insulin-resistant state, commonly reported in AD brain, results in neuronal glucose deprivation, due to a dampening down of the PI3K/Akt pathway, including overactivity of the mammalian target of rapamycin 1 (mTORC1) complex, hyperphosphorylation of p53 and neuronal death. This contrasts with cancer, where there is overstimulation of the PI3K/Akt pathway and the suppression of mTORC1 and p53, enabling abundant energy and unrestrained cell proliferation. Although these disease states appear to be diametrically opposed, the same key molecules are controlling pathology and, with differential targeting of therapeutics, may yet provide a beneficial outcome for both.

Association Between Amyloid-β, Small-vessel Disease, and Neurodegeneration Biomarker Positivity, and Progression to Mild Cognitive Impairment in Cognitively Normal Individuals

BACKGROUND

We estimated the prevalence and incidence of amyloid-β deposition (A), small-vessel disease (V), and neurodegeneration (N) biomarker positivity in community-dwelling cognitively normal individuals (CN). We determined the longitudinal association between the respective biomarker indices with progression to all-cause mild cognitive impairment (MCI) and its amnestic and nonamnestic subtypes.

METHODS

CN participants, recruited by advertising, underwent brain [C-11]Pittsburgh Compound-B (PiB)-positron emission tomography (PET), magnetic resonance imaging, and [F-18]fluoro-2-deoxy-glucose (FDG)-PET, and were designated as having high or low amyloid-β (A+/A-), greater or lower white matter hyperintensities burden (V+/V-) and diminished or normal cortical glucose metabolism (N+/N-). MCI was adjudicated using clinical assessments. We examined the association between A, V, and N biomarker positivity at study baseline and endpoint, with progression to MCI using linear regression, Cox proportional hazards and Kaplan-Meier analyses adjusted for age and APOE-ε4 carrier status.

RESULTS

In 98 CN individuals (average age 74 years, 65% female), A+, V+, and N+ prevalence was 26%, 33%, and 8%, respectively. At study endpoint (median: 5.5 years), an A+, but not a V+ or N+ scan, was associated with higher odds of all-cause MCI (Chi-square = 3.9, p = .048, odds ratio, 95% confidence interval = 2.6 [1.01-6.8]). Baseline A+, V+, or N+ were not associated with all-cause MCI, however, baseline A+ (p = .018) and A+N+ (p = .049), and endpoint A+N+ (p = .025) were associated with time to progression to amnestic, not nonamnestic, MCI.

CONCLUSION

Longitudinal assessments clarify the association between amyloid-β and progression to all-cause MCI in CN individuals. The association between biomarker positivity indices of amyloid-β and neurodegeneration, and amnestic MCI reflects the underlying pathology involved in the progression to prodromal Alzheimer's disease.

Hemodynamics Analysis of Patients With Mild Cognitive Impairment During Working Memory Tasks

Diagnosis of dementia in early stage is important to prevent progression of dementia in the aging society. Mild cognitive impairment (MCI) denotes an early stage of Alzheimer disease (AD). In this paper, we aim to classify MCI patients from healthy controls (HC) during working memory tasks using functional near-infrared spectroscopy (fNIRS). To achieve this objective, t-values and correlation coefficients are calculated to find the region of interest (ROI) channels and brain connectivity. From the ROI channels averaged over subjects, features (mean and slope) of hemodynamic responses were extracted for classification. Extracted features were labelled as two classes and classified via two classifiers, linear discriminant analysis (LDA) and support vector machine (SVM). The classification accuracies were 73.08 % with LDA and 71.15 % with SVM. The results show that there are significant differences in the hemodynamic responses (HR) between MCI patients and healthy controls. Therefore, these results suggest a possibility of using fNIRS as a diagnostic tool for MCI patients.

The correlation of neuropsychological evaluation with 11C-PiB and 18F-FC119S amyloid PET in mild cognitive impairment and Alzheimer disease

For the diagnosis of mild cognitive impairment (MCI) and Alzheimer disease (AD), variable neuroimaging and neuropsychological tests have been used. We aimed to evaluate the correlation of neuropsychological domain with new amyloid positron emission tomography (PET) study and to validate the availability of new PET tracer.We enrolled 20 patients who underwent C-PiB-PET/CT, new PET tracer F-FC119S PET/CT from November, 2014 to July, 2015. Among them, 10 patients were diagnosed with AD and 10 patients with MCI. The current version of Seoul Neuropsychological Screening Battery (SNSB) II was performed for cognitive evaluation. Each parameter of SNSB was compared between 2 patient groups. Spearman correlation analysis between value of SNSB domain and standardized uptake value ratio (SUVR) of PET was also performed.The AD group presented significant poor z-score in Korean-Boston Naming Test(K-BNT) (P = .01),copy score of Rey Complex Figure Test (RCFT) (P = .049), immediate (P = .028)and delayed memory of Seoul Verbal Learning Test (SVLT) (P = .028), recognition of RCFT (P = .004), "animal" of Controlled Oral Word Association Test (COWAT) (P = .041), color reading of Korean-Color Word Stroop test (K-CWST) (P = .014), and Digit Symbol Coding (DSC) (P = .007) compared with MCI group. That means, except attention domain, all other cognitive domains were relatively impaired in AD compared with MCI. In correlation analysis, we found that poor performances on copy score of RCFT in MCI groups were associated with great beta amyloid burden in frontal area in both C-PiB-PET/CT and F-FC119S PET/CT. In AD group, F-FC119S PET presented more extensive correlation in each cognitive domain with multiple cortical areas compared with C-PiB-PET.The degree of amyloid burden assessed on F-FC119S PET was significantly correlated with neuropsychological test in AD, and also MCI patients. The combination of neuropsychological evaluation with novel F-FC119S PET/CT can be used for valid biomarker for MCI and AD.

Transport of Glucose by the Plasma Membrane Affects the Removal and Concentration of Ca2+ at Rest in Neurons - Implications of a Condition Prior to Alzheimer's Disease?

Alzheimer's disease (AD) is classically characterized by two major markers: extracellular development of senile plaques and intracellular formation of neurofibrillary tangles. Nonetheless, neuronal glucose hypometabolism and Ca²⁺ deregulation have been separately implied in the genesis and progress of the neurodegenerative process. In this sense, the goal of this study was to investigate if modifications in the glucose transport would influence the cellular viability and would be involved with the activity of Ca²⁺ removal from the neuron. The total levels of plasma membrane Ca²⁺-ATPase (PMCA) and glucose transporters (GLUT1 and 3), as well as glucose entry and intracellular Ca²⁺ dynamics were quantified in neurons maintained at different glucose concentrations or submitted to GLUT3 mRNA interference. The results showed that reduced extracellular glucose impaired neuronal viability from day 8, but didn't change the total protein levels of GLUT1, GLUT3 and PMCA before the onset of the cell death. Conversely, the rate of glucose transport and Ca²⁺ concentration was already altered since the 4th day of external glucose reduction. Interestingly, reduction of GLUT3 on plasma membrane led to lower glucose transport and intracellular Ca²⁺ accumulation. It was observed that the reduction of glucose transport directed the neuron to decrease the removal and increase of intracellular Ca²⁺ at rest. Therefore, we concluded that reduced glucose transport impairs neuronal viability and compromise the activity of Ca²⁺ removal from the neuron. Thus, it is expected that changes in glucose transport may lead to a more susceptible condition or trigger a neurodegenerative condition resulting in accumulation of intracellular Ca²⁺.

Impairment of Glycolysis-Derived l-Serine Production in Astrocytes Contributes to Cognitive Deficits in Alzheimer's Disease

Alteration of brain aerobic glycolysis is often observed early in the course of Alzheimer's disease (AD). Whether and how such metabolic dysregulation contributes to both synaptic plasticity and behavioral deficits in AD is not known. Here, we show that the astrocytic l-serine biosynthesis pathway, which branches from glycolysis, is impaired in young AD mice and in AD patients. l-serine is the precursor of d-serine, a co-agonist of synaptic NMDA receptors (NMDARs) required for synaptic plasticity. Accordingly, AD mice display a lower occupancy of the NMDAR co-agonist site as well as synaptic and behavioral deficits. Similar deficits are observed following inactivation of the l-serine synthetic pathway in hippocampal astrocytes, supporting the key role of astrocytic l-serine. Supplementation with l-serine in the diet prevents both synaptic and behavioral deficits in AD mice. Our findings reveal that astrocytic glycolysis controls cognitive functions and suggest oral l-serine as a ready-to-use therapy for AD.