Comparison between Early-Onset and Late-Onset Alzheimer's Disease Patients with Amnestic Presentation: CSF and (18)F-FDG PET Study

Systematic review and meta-analysis of repetitive transcranial magnetic stimulation (rTMS) for activities of daily living in Alzheimer's disease

OBJECTIVE

This systematic review of randomised controlled trials (RCTs) was conducted to assess the effect of repetitive transcranial magnetic stimulation (rTMS) on activities of daily living (ADLs) in Alzheimer's disease (AD) patients.

DATA SOURCES

Ten databases were retrieved for pertinent Chinese and English literatures published up until January 2024.

REVIEW METHODS

All RCTs of rTMS for ADLs in AD were included in this meta-analysis. Two researchers independently selected the literatures, retrieved the data of included literatures, accessed risk-of-bias of literatures with the Cochrane Collaboration's quality criteria and then cross-checked. Meta-analysis was carried out with Cochrane's Review Manager (RevMan, version 5.4). The PRISMA guidelines were followed in this systematic review.

RESULTS

The 37 literatures involving 2461 patients with AD were included in this study. Compared with the control groups received the interventions such as routine pharmacotherapy, cognitive training, ect., with/without sham-rTMS, the experiment groups received the interventions of the control groups and rTMS. The findings were as follows: ADL scale [mean difference (MD) = -3.92, 95%CI (-4.93, -2.91), P < 0.00001]; Barthel Index (BI) [MD = 9.75, 95% CI (6.66, 12.85), P < 0.00001]; Modified Barthel Index (MBI) [MD = 5.43, 95% CI (3.13, 7.73), P < 0.00001]. The differences were statistically significant for all indicators. In 29 studies, rTMS stimulation sites were located in the dorsolateral prefrontal cortex (DLPFC).

CONCLUSION

The rTMS could improve the ADLs in AD patients, and the DLPFC was a frequently used stimulation site of the rTMS for AD treatment.

Caregivers' Burden on Patients with Dementia Having Multiple Chronic Diseases

Purpose

This study aimed to find the caregiving burden level for patients with dementia who had multiple chronic diseases by simultaneously considering both patient and caregiver factors.

Participants and Methods

A cross-sectional study with 284 patients with dementia having multiple chronic diseases managed by the dementia collaborative care team at Changhua Christian Hospital in Taiwan was conducted. The input variables were from patients, such as age, gender, mood symptoms, and behavioral and psychological symptoms, and caregivers, including age, relation to the patient, caregiver's mood, and caregiving burden. The Apriori algorithm was employed to determine the association between patient and caregiver factors and different caregiving burden levels by setting up the minimum support of 1% and confidence of 90% along with lift >1.

Results

When caring for patients with dementia, twenty scenarios were found for caregivers with a severe burden. In addition, 1936 scenarios were related to caregivers with a moderate-to-severe burden. Specifically, there were eight scenarios for patients with three chronic diseases which could be further categorized into five general rules. Two hundred and fifty scenarios belonging to patients with two chronic diseases could be classified into 16 different combinations from eight chronic diseases of the database.

Conclusion

Caregiver's mood, patients with mild dementia, and patients aged 75-84 years were associated with a severe caregiving burden. College and above education of the caregiver, the patient aged 85 years or more, and at least one of caregiver's moods were the variables to result in a moderate-to-severe burden for caregivers caring for patients with three multiple chronic diseases. Moreover, college and above education of the caregiver, mood symptom, age of the caregiver, and age of the patient were important variables for caregivers who had a moderate-to-severe burden taking care of patients with two chronic diseases.

Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer's disease

Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.

Addressing the Discrepancies Between Animal Models and Human Alzheimer's Disease Pathology: Implications for Translational Research

Animal models, particularly transgenic mice, are extensively used in Alzheimer's disease (AD) research to emulate key disease hallmarks, such as amyloid plaques and neurofibrillary tangles formation. Although these models have contributed to our understanding of AD pathogenesis and can be helpful in testing potential therapeutic interventions, their reliability is dubious. While preclinical studies have shown promise, clinical trials often yield disappointing results, highlighting a notable gap and disparity between animal models and human AD pathology. Existing models frequently overlook early-stage human pathologies and other key AD characteristics, thereby limiting their application in identifying optimal therapeutic interventions. Enhancing model reliability necessitates rigorous study design, comprehensive behavioral evaluations, and biomarker utilization. Overall, a nuanced understanding of each model's neuropathology, its fidelity to human AD, and its limitations is essential for accurate interpretation and successful translation of findings. This article analyzes the discrepancies between animal models and human AD pathology that complicate the translation of findings from preclinical studies to clinical applications. We also delve into AD pathogenesis and attributes to propose a new perspective on this pathology and deliberate over the primary limitations of key experimental models. Additionally, we discuss several fundamental problems that may explain the translational failures and suggest some possible directions for more effective preclinical studies.

Repetitive transcranial magnetic stimulation for apathy in patients with neurodegenerative conditions, cognitive impairment, stroke, and traumatic brain injury: a systematic review

Background

We aimed to determine the effects and tolerability of repetitive transcranial magnetic stimulation (rTMS) on apathy in patients with neurodegenerative conditions, mild cognitive impairment (MCI), stroke, and traumatic brain injury (TBI) via systematic review.

Methods

We conducted a systematic search in major electronic health databases, including PubMed, Scopus, and PsycINFO, covering the period from inception to June 2023. Comparative clinical trials and cohort studies, and studies with before-after designs were considered for inclusion. We used the Cochrane Risk of Bias and the National Institutes of Health (NIH) tools to assess methodological quality.

Results

Out of 258 records identified, 14 studies met our eligibility criteria (11 randomized controlled trials (RCT) and 3 studies utilized before-and-after designs) with a total of 418 patients (overall female-to-male ratio 1:1.17) included in the review. The overall methodological quality of the included studies was assessed to be fair to good. The stimulation parameters used varied considerably across the studies. The summary findings of our review indicate the following observations on the effects of rTMS on apathy: (1) the results of all included studies in Alzheimer's disease investigating the effects of rTMS on apathy have consistently shown a positive impact on apathy; (2) the majority of studies conducted in Parkinson's disease have not found statistically significant results; (3) a single study (RCT) on patients with primary progressive aphasia demonstrated significant beneficial effects of rTMS on apathy; (4) the trials conducted on individuals with MCI yielded varying conclusions; (5) one study (RCT) in chronic stroke suggested that rTMS might have the potential to improve apathy; (6) one study conducted on individuals with mild TBI did not find a significant favorable association on apathy; and (7) the use of different rTMS protocols on the populations described is generally safe.

Conclusion

The feasibility of utilizing rTMS as a treatment for apathy has been suggested in this review. Overall, limited evidence suggests that rTMS intervention may have the potential to modify apathy among patients with AD, PPA, MCI and chronic stroke, but less so in PD and mild TBI. These findings require confirmation by larger, well-designed clinical trials.

Profiling baseline performance on the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) cohort near the midpoint of data collection

OBJECTIVE

The Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) seeks to provide comprehensive understanding of early-onset Alzheimer's disease (EOAD; onset <65 years), with the current study profiling baseline clinical, cognitive, biomarker, and genetic characteristics of the cohort nearing the data-collection mid-point.

METHODS

Data from 371 LEADS participants were compared based on diagnostic group classification (cognitively normal [n = 89], amyloid-positive EOAD [n = 212], and amyloid-negative early-onset non-Alzheimer's disease [EOnonAD; n = 70]).

RESULTS

Cognitive performance was worse for EOAD than other groups, and EOAD participants were apolipoprotein E (APOE) ε4 homozygotes at higher rates. An amnestic presentation was common among impaired participants (81%), with several clinical phenotypes present. LEADS participants generally consented at high rates to optional trial procedures.

CONCLUSIONS

We present the most comprehensive baseline characterization of sporadic EOAD in the United States to date. EOAD presents with widespread cognitive impairment within and across clinical phenotypes, with differences in APOE ε4 allele carrier status appearing to be relevant.

HIGHLIGHTS

Findings represent the most comprehensive baseline characterization of sporadic early-onset Alzheimer's disease (EOAD) to date. Cognitive impairment was widespread for EOAD participants and more severe than other groups. EOAD participants were homozygous apolipoprotein E (APOE) ε4 carriers at higher rates than the EOnonAD group. Amnestic presentation predominated in EOAD and EOnonAD participants, but other clinical phenotypes were present.

CSF biomarkers for early-onset Alzheimer's disease in Chinese population from PUMCH dementia cohort

Introduction

Alzheimer's disease (AD) is one of the highly concerned degenerative disorders in recent decades. Though vast amount of researches has been done in various aspects, early-onset subtype, however, needs more investigation in diagnosis for its atypical manifestations and progression process. Fundamental CSF biomarkers of early-onset AD are explored in PUMCH dementia cohort to depict its laboratory characteristics.

Materials and methods

A total of 125 individuals (age of onset <65 years old) from PUMCH dementia cohort were recruited consecutively and classified into AD, non-AD dementia, and control groups. Levels of amyloid-β 42 (Aβ42), total tau (t-tau) and phosphorylated tau (p-tau) were measured using ELISA INNOTEST (Fujirebio, Ghent, Belgium). Students' t-test or non-parametric test are used to evaluate the differences between groups. Area under curve (AUC) of receiver operating characteristic (ROC) curve was introduced to prove the diagnostic powers of corresponding markers. Logistic regression is used to establish diagnostic model to combine several markers together to promote the diagnostic power.

Results

The average of all three biomarkers and two calculated ratios (t-tau/Aβ42, p-tau/Aβ42) were statistically different in the AD group compared with the other two groups (Ps < 0.01). From our data, we were able to provide cutoff values (Aβ42 < 570.9 pg/mL; p-tau > 56.49 pg/mL; t-tau > 241.6 pg/mL; t-tau/Aβ42 > 0.529; p-tau/Aβ42 > 0.0846) with acceptable diagnostic accuracy compared to other studies. Using a combination of biomarkers and logistic regression (area under curve 0.951), we were able to further improve diagnostic efficacy.

Discussion

Our study supports the diagnostic usefulness of biomarkers and defined cutoff values to diagnose early-onset AD. We showed that the ratios of t-tau/Aβ42 and p-tau/Aβ42 are more sensitive than relying on Aβ42 levels alone, and that we can further improve diagnostic accuracy by combining biomarkers.

Plasma biomarkers and their correlation in adult children of parents with Alzheimer’s disease

Family history (FH) of late-onset Alzheimer’s disease (AD) is associated with changes in several cerebrospinal fluid (CSF) biomarkers in cognitively normal individuals. However, potential changes in plasma biomarkers remain unknown. This study aimed to evaluate potential plasma biomarkers and their correlation in cognitively normal adult children (AC) and to compare this data with their AD parents and unrelated non-demented controls (NC). Participants with dementia due to AD, their AC and NC were recruited. Plasma samples were assessed for amyloid beta (Aβ)_1–42, Aβ_1–40, total tau (T-tau) and phosphorylated tau (P-tau). Kruskal–Wallis test was used for the comparison of this data between the three groups. Spearman rank correlation was used for evaluation of the correlations between Aβ_1–40 and Aβ_1–42, and T-tau and P-tau in the AD and AC groups. A total of 99 subjects completed the assessment (30 had AD; 38 were AC group; and 31 were NC). Compared with the NC group, there were significantly higher levels of Aβ_1–40, P-tau, and P-tau/T-tau ratio, and lower levels of Aβ_1–42 and Aβ_1–42/Aβ_1–40 ratio in the AD and AC groups. The correlation between the level of Aβ_1–42 and Aβ_1–40 and level of T-tau and P-tau was only observed in the AC but not in the AD group. AC of AD parents demonstrate some indicators of AD like their parents. Disruption to the correlation between Aβ and tau in AD may be a biomarker for the development of AD in AC, which should be examined in a longitudinal cohort.

Discerning the Role of Blood Brain Barrier Dysfunction in Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common form of neurodegenerative disease. The predominant characteristics of AD are the accumulation of amyloid-β (Aβ) and hyperphosphorylated tau in the brain. Blood brain barrier (BBB) dysfunction as one of the causative factors of cognitive impairment is increasingly recognized in the last decades. However, the role of BBB dysfunction in AD pathogenesis is still not fully understood. It remains elusive whether BBB dysfunction is a consequence or causative fact of Aβ pathology, tau pathology, neuroinflammation, or other conditions. In this review, we summarized the major findings of BBB dysfunction in AD and the reciprocal relationships between BBB dysfunction, Aβ pathology, tau pathology, and neuroinflammation. In addition, the implications of BBB dysfunction in AD for delivering therapeutic drugs were presented. Finally, we discussed how to better determine the underlying mechanisms between BBB dysfunction and AD, as well as how to explore new therapies for BBB regulation to treat AD in the future.

Longitudinal Analysis of Brain-Predicted Age in Amnestic and Non-amnestic Sporadic Early-Onset Alzheimer's Disease

Objective: Predicted age difference (PAD) is a score computed by subtracting chronological age from "brain" age, which is estimated using neuroimaging data. The goal of this study was to evaluate the PAD as a marker of phenotypic heterogeneity and severity among early-onset Alzheimer's disease (EOAD) patients. Methods: We first used 3D T1-weighted (3D-T1) magnetic resonance images (MRI) of 3,227 healthy subjects aged between 18 and 85 years to train, optimize, and evaluate the brain age model. A total of 123 participants who met the criteria for early-onset (<65 years) sporadic form of probable Alzheimer's disease (AD) and presented with two distinctive clinical presentations [an amnestic form (n = 74) and a non-amnestic form (n = 49)] were included at baseline and followed-up for a maximum period of 4 years. All the participants underwent a work-up at baseline and every year during the follow-up period, which included clinical examination, neuropsychological testing and genotyping, and structural MRI. In addition, cerebrospinal fluid biomarker assay was recorded at baseline. PAD score was calculated by applying brain age model to 3D-T1 images of the EOAD patients and healthy controls, who were matched based on age and sex. At baseline, between-group differences for neuropsychological and PAD scores were assessed using linear models. Regarding longitudinal analysis of neuropsychological and PAD scores, differences between amnestic and non-amnestic participants were analyzed using linear mixed-effects modeling. Results: PAD score was significantly higher for non-amnestic patients (2.35 ± 0.91) when compared to amnestic patients (2.09 ± 0.74) and controls (0.00 ± 1). Moreover, PAD score was linearly correlated with the Mini-Mental State Examination (MMSE) and the Clinical Dementia Rating Sum of Boxes (CDR-SB), for both amnestic and non-amnestic sporadic forms. Longitudinal analyses showed that the gradual development of the disease in patients was accompanied by a significant increase in PAD score over time, for both amnestic and non-amnestic patients. Conclusion: PAD score was able to separate amnestic and non-amnestic sporadic forms. Regardless of the clinical presentation, as PAD score was a way of quantifying an early brain age acceleration, it was an appropriate method to detect the development of AD and follow the evolution of the disease as a marker of severity as MMSE and CDR-SB.

Optimizing Use of Neuroimaging Tools in Evaluation of Prodromal Alzheimer's Disease and Related Disorders

Alzheimer's disease (AD) is the most common neurodegenerative disease and is characterized by preclinical, pre-dementia, and dementia phases. Progression of the disease leads to cognitive decline and is associated with loss of functional independence, personality changes, and behavioral disturbances. Current guidelines for AD diagnosis include the use of neuroimaging tools as biomarkers for identifying and monitoring pathological changes. Various imaging modalities, namely magnetic resonance imaging (MRI), fluorodeoxyglucose-positron emission tomography (FDG-PET) and PET with amyloid-beta tracers are available to facilitate early accurate diagnoses. Enhancing diagnosis in the early stages of the disease can allow for timely interventions that can delay progression of the disease. This paper will discuss the characteristic findings associated with each of the imaging tools for patients with AD, with a focus on FDG-PET due to its established accuracy in assisting with the differential diagnosis of dementia and discussion of other methods including MRI. Diagnostically-relevant features to aid clinicians in making a differential diagnosis will also be pointed out and multimodal imaging will be reviewed. We also discuss the role of quantification software in interpretation of brain imaging. Lastly, to guide evaluation of patients presenting with cognitive deficits, an algorithm for optimal integration of these imaging tools will be shared. Molecular imaging modalities used in dementia evaluations hold promise toward identifying AD-related pathology before symptoms are fully in evidence. The work describes state of the art functional and molecular imaging methods for AD. It will also overview a clinically applicable quantitative method for reproducible assessments of such scans in the early identification of AD.

Associations among education, age, and the dementia with Lewy bodies (DLB) metabolic pattern: A European-DLB consortium project

INTRODUCTION

We assessed the influence of education as a proxy of cognitive reserve and age on the dementia with Lewy bodies (DLB) metabolic pattern.

METHODS

Brain 18F-fluorodeoxyglucose positron emission tomography and clinical/demographic information were available in 169 probable DLB patients included in the European DLB-consortium database. Principal component analysis identified brain regions relevant to local data variance. A linear regression model was applied to generate age- and education-sensitive maps corrected for Mini-Mental State Examination score, sex (and either education or age).

RESULTS

Age negatively covaried with metabolism in bilateral middle and superior frontal cortex, anterior and posterior cingulate, reducing the expression of the DLB-typical cingulate island sign (CIS). Education negatively covaried with metabolism in the left inferior parietal cortex and precuneus (making the CIS more prominent).

DISCUSSION

These findings point out the importance of tailoring interpretation of DLB biomarkers considering the concomitant effect of individual, non-disease-related variables such as age and cognitive reserve.

Quantitative MRI Differences Between Early versus Late Onset Alzheimer's Disease

Investigators report greater parietal tau deposition and alternate frontoparietal network involvement in early onset Alzheimer's Disease (EOAD) with onset <65 years as compared with typical late onset AD (LOAD). To determine whether clinical brain MRI volumes reflect these differences in EOAD compared with LOAD. This study investigated the clinical MRI scans of 45 persons with Clinically Probable AD with onset <65 years, and compared them to 32 with Clinically Probable AD with onset ≥65 years. Brain volumes on their T1 MRI scans were quantified with a volumetric program. Receiver operating curve analyses were performed. Persons with EOAD had significantly smaller parietal lobes (volumetric percentiles) than LOAD. Late onset Alzheimer's Disease had a smaller left putamen and hippocampus. Area Under the Curve was 96.5% with brain region delineation of EOAD compared to LOAD. This study indicates parietal atrophy less than 30% of normal on clinical MRI scans is suggestive of EOAD compared to LOAD.

Could Early Identification of Changes in Olfactory Function Be an Indicator of Preclinical Neurodegenerative Disease? A Systematic Review

INTRODUCTION

Alzheimer's disease (AD) is a debilitating neurodegenerative disease that currently affects 850,000 individuals in the UK with estimates continuing to rise. Diagnosis is only available in the presence of significant neuronal pathology and apparent cognitive decline, meaning that treatment avenues are often limited and carry little to no effect on prognosis. Olfactory function has been shown to have a direct correlation with cognitive function and therefore may serve as a potential diagnostic tool for the detection of preclinical disease. The objective was to examine the current literature to establish the accuracy of olfactory function testing in determining current and future cognitive function.

METHODS

A systematic review was performed via Medline on 17 October 2019 using the search terms and Boolean operators 'Dementia OR Alzheimer's AND olfaction AND cognitive impairment' yielding 111 results. These were then screened using inclusion/exclusion criteria alongside a PICO strategy. After titles, abstracts and full text were screened, nine articles were included in the review and critically appraised using the AXIS and CASP tools.

RESULTS

Significant correlations are demonstrated between olfactory impairment (OI) and cognitive decline. However, there were limitations of many of the studies in that confounders such as head trauma, upper respiratory infection (URTI) and smoking history were not considered. The majority of the studies also used an olfactory screening tool that was not designed for the population being examined.

CONCLUSION

Despite improvements in olfactory testing needing to be implemented, OI is clearly impaired in neurodegenerative disease across a multitude of ages and cultures, offering an early marker of future cognitive decline. As a result of the heterogenous nature of the included studies, there is a further need for future research to ensure the sensitivity, validity and reliability of implementing olfactory testing as an early marker of future cognitive decline.

[18F] FBB cortical uptake is not related to the age of onset of Alzheimer's disease

AIM

To investigate the relationships between amyloid burden in brain and the age of onset of Alzheimer's disease.

MATERIALS AND METHODS

We examined 60 patients with clinical diagnosis of Alzheimer's disease. Of them, 22 were early-onset of Alzheimer's disease and 38 were late-onset of Alzheimer's disease. All of them underwent a brain PET scan 90 minutes after the injection of 4-[(E)-2-[4-[2-[2-(2-fluoranylethoxy)ethoxy]ethoxy]phenyl]ethenyl]-N-methylaniline ([F] FBB); 300 ± 10 MBq). Relationships between amyloid burden in brain and age of onset of Alzheimer's disease were assessed by means of statistical parametric mapping version 12.

RESULTS

There were no significant differences [F] FBB uptake between early-onset of Alzheimer's disease and late-onset of Alzheimer's disease patients.

CONCLUSION

In our study group, the age of onset is not related to brain amyloid burden in Alzheimer's disease patients.

Structural Brain Imaging Phenotypes of Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) Found by Hierarchical Clustering

A hierarchical clustering algorithm was applied to magnetic resonance images (MRI) of a cohort of 751 subjects having a mild cognitive impairment (MCI), 282 subjects having received Alzheimer's disease (AD) diagnosis, and 428 normal controls (NC). MRIs were preprocessed to gray matter density maps and registered to a stereotactic space. By first rendering the gray matter density maps comparable by regressing out age, gender, and years of education, and then performing the hierarchical clustering, we found clusters displaying structural features of typical AD, cortically-driven atypical AD, limbic-predominant AD, and early-onset AD (EOAD). Among these clusters, EOAD subjects displayed marked cortical gray matter atrophy and atrophy of the precuneus. Furthermore, EOAD subjects had the highest progression rates as measured with ADAS slopes during the longitudinal follow-up of 36 months. Striking heterogeneities in brain atrophy patterns were observed with MCI subjects. We found clusters of stable MCI, clusters of diffuse brain atrophy with fast progression, and MCI subjects displaying similar atrophy patterns as the typical or atypical AD subjects. Bidirectional differences in structural phenotypes were found with MCI subjects involving the anterior cerebellum and the frontal cortex. The diversity of the MCI subjects suggests that the structural phenotypes of MCI subjects would deserve a more detailed investigation with a significantly larger cohort. Our results demonstrate that the hierarchical agglomerative clustering method is an efficient tool in dividing a cohort of subjects with gray matter atrophy into coherent clusters manifesting different structural phenotypes.

Positron Emission Tomography (PET) and Neuroimaging in the Personalized Approach to Neurodegenerative Causes of Dementia

Generally, dementia should be considered an acquired syndrome, with multiple possible causes, rather than a specific disease in itself. The leading causes of dementia are neurodegenerative and non-neurodegenerative alterations. Nevertheless, the neurodegenerative group of diseases that lead to cognitive impairment and dementia includes multiple possibilities or mixed pathologies with personalized treatment management for each cause, even if Alzheimer's disease is the most common pathology. Therefore, an accurate differential diagnosis is mandatory in order to select the most appropriate therapy approach. The role of personalized assessment in the treatment of dementia is rapidly growing. Neuroimaging is an essential tool for differential diagnosis of multiple causes of dementia and allows a personalized diagnostic and therapeutic protocol based on risk factors that may improve treatment management, especially in early diagnosis during the prodromal stage. The utility of structural and functional imaging could be increased by standardization of acquisition and analysis methods and by the development of algorithms for automated assessment. The aim of this review is to focus on the most commonly used tracers for differential diagnosis in the dementia field. Particularly, we aim to explore ¹⁸F Fluorodeoxyglucose (FDG) and amyloid positron emission tomography (PET) imaging in Alzheimer's disease and in other neurodegenerative causes of dementia.

The combined effects of microglia activation and brain glucose hypometabolism in early-onset Alzheimer's disease

Background

Early-onset Alzheimer’s disease (EOAD) is characterized by young age of onset (< 65 years), severe neurodegeneration, and rapid disease progression, thus differing significantly from typical late-onset Alzheimer’s disease. Growing evidence suggests a primary role of neuroinflammation in AD pathogenesis. However, the role of microglia activation in EOAD remains a poorly explored field. Investigating microglial activation and its influence on the development of synaptic dysfunction and neuronal loss in EOAD may contribute to the understanding of its pathophysiology and to subject selection in clinical trials. In our study, we aimed to assess the amount of neuroinflammation and neurodegeneration and their relationship in EOAD patients, through positron emission tomography (PET) measures of microglia activation and brain metabolic changes.

Methods

We prospectively enrolled 12 EOAD patients, classified according to standard criteria, who underwent standard neurological and neuropsychological evaluation, CSF analysis, brain MRI, and both [¹⁸F]-FDG PET and [¹¹C]-(R)-PK11195 PET. Healthy controls databases were used for statistical comparison. [¹⁸F]-FDG PET brain metabolism in single subjects and as a group was assessed by an optimized SPM voxel-wise single-subject method. [¹¹C]-PK11195 PET binding potentials were obtained using reference regions selected with an optimized clustering procedure followed by a parametric analysis. We performed a topographic interaction analysis and correlation analysis in AD-signature metabolic dysfunctional regions and regions of microglia activation. A network connectivity analysis was performed using the interaction regions of hypometabolism and [¹¹C]-PK11195 PET BP increases.

Results

EOAD patients showed a significant and extended microglia activation, as [¹¹C]-PK11195 PET binding potential increases, and hypometabolism in typical AD-signature brain regions, i.e., temporo-parietal cortex, with additional variable frontal and occipital hypometabolism in the EOAD variants. There was a spatial concordance in the interaction areas and significant correlations between the two biological changes. The network analysis showed a disruption of frontal connectivity induced by the metabolic/microglia effects.

Conclusion

The severe microglia activation characterizing EOAD and contributing to neurodegeneration may be a marker of rapid disease progression. The coupling between brain glucose hypometabolism and local immune response in AD-signature regions supports their biological interaction.

The Brain Metabolic Correlates of the Main Indices of Neuropsychological Assessment in Alzheimer's Disease

Background: The study aimed to investigate the relationships between F-18 fluorodeoxyglucose (18F)FDG uptake and neuropsychological assessment in Alzheimer’s disease (AD). Methods: We evaluated 116 subjects with AD according to the NINCDS-ADRDA criteria. All the subjects underwent a brain PET/CT with (18F)FDG, cerebrospinal fluid (CSF) assay, mini-mental state examination (MMSE) and further neuropsychological tests: Rey auditory verbal learning test, immediate recall (RAVLT immediate); Rey auditory verbal learning test, delayed recall (RAVLT, delayed); Rey complex figure test, copy (RCFT, copy); Rey complex figure test, delayed recall (RCFT, delayed); Raven’s colored progressive matrices (RCPM); phonological word fluency test (PWF) and Stroop test. We performed the statistical analysis by using statistical parametric mapping (SPM12; Wellcome Department of Cognitive Neurology, London, UK). Results: A significant relationship has been reported between (18F)FDG uptake and RAVLT immediate test in Brodmann area (BA)37 and BA22 and with RCFT, copy in BA40, and BA7. We did not find any significant relationships with other tests. Conclusion: In the AD population, brain (18F)FDG uptake is moderately related to the neuropsychological assessment, suggesting a limited impact on statistical data analysis of glucose brain metabolism.

Early-onset Alzheimer Disease and Its Variants

PURPOSE OF REVIEW

Early-onset Alzheimer disease (AD) is defined as having an age of onset younger than 65 years. While early-onset AD is often overshadowed by the more common late-onset AD, recognition of the differences between early- and late-onset AD is important for clinicians.

RECENT FINDINGS

Early-onset AD comprises about 5% to 6% of cases of AD and includes a substantial percentage of phenotypic variants that differ from the usual amnestic presentation of typical AD. Characteristics of early-onset AD in comparison to late-onset AD include a larger genetic predisposition (familial mutations and summed polygenic risk), more aggressive course, more frequent delay in diagnosis, higher prevalence of traumatic brain injury, less memory impairment and greater involvement of other cognitive domains on presentation, and greater psychosocial difficulties. Neuroimaging features of early-onset AD in comparison to late-onset AD include greater frequency of hippocampal sparing and posterior neocortical atrophy, increased tau burden, and greater connectomic changes affecting frontoparietal networks rather than the default mode network.

SUMMARY

Early-onset AD differs substantially from late-onset AD, with different phenotypic presentations, greater genetic predisposition, and differences in neuropathologic burden and topography. Early-onset AD more often presents with nonamnestic phenotypic variants that spare the hippocampi and with greater tau burden in posterior neocortices. The early-onset AD phenotypic variants involve different neural networks than typical AD. The management of early-onset AD is similar to that of late-onset AD but with special emphasis on targeting specific cognitive areas and more age-appropriate psychosocial support and education.

Neuronal injury biomarkers for assessment of the individual cognitive reserve in clinically suspected Alzheimer's disease

OBJECTIVES

Many predictive or influencing factors have emerged in investigations of the cognitive reserve model of patients with Alzheimer's disease (AD). For example, neuronal injury, which correlates with cognitive decline in AD, can be assessed by [¹⁸F]-fluorodeoxyglucose positron-emission-tomography (FDG-PET), structural magnetic resonance imaging (MRI) and total tau in cerebrospinal fluid (CSF_t-tau), all according to the A/T/N-classification. The aim of this study was to calculate residual cognitive performance based on neuronal injury biomarkers as a surrogate of cognitive reserve, and to test the predictive value of this index for the individual clinical course.

METHODS

110 initially mild cognitive impaired and demented subjects (age 71 ± 8 years) with a final diagnosis of AD dementia were assessed at baseline by clinical mini-mental-state-examination (MMSE), FDG-PET, MRI and CSF_t-tau. All neuronal injury markers were tested for an association with clinical MMSE and the resulting residuals were correlated with years of education. We used multiple regression analysis to calculate the expected MMSE score based on neuronal injury biomarkers and covariates. The residuals of the partial correlation for each biomarker and the predicted residualized memory function were correlated with individual cognitive changes measured during clinical follow-up (27 ± 13 months).

RESULTS

FDG-PET correlated highly with clinical MMSE (R = -0.49, p < .01), whereas hippocampal atrophy to MRI (R = -0.15, p = .14) and CSF_t-tau (R = -0.12, p = .22) showed only weak correlations. Residuals of all neuronal injury biomarker regressions correlated significantly with education level, indicating them to be surrogates of cognitive reserve. A positive residual was associated with faster cognitive deterioration at follow-up for the residuals of stand-alone FDG-PET (R = -0.36, p = .01) and the combined residualized memory function model (R = -0.35, p = .02).

CONCLUSIONS

These findings suggest that subjects with higher cognitive reserve had accumulated more pathology, which subsequently caused a faster cognitive decline over time. Together with previous findings suggesting that higher reserve is associated with slower cognitive decline, we propose a biphasic reserve effect, with an initially protective phase followed by more rapid decompensation once the protection is overwhelmed.

Prognostic value of Alzheimer's biomarkers in mild cognitive impairment: the effect of age at onset

OBJECTIVE

The aim of this study is to assess the impact of age at onset on the prognostic value of Alzheimer's biomarkers in a large sample of patients with mild cognitive impairment (MCI).

METHODS

We measured Aβ42, t-tau, hippocampal volume on magnetic resonance imaging (MRI) and cortical metabolism on fluorodeoxyglucose-positron emission tomography (FDG-PET) in 188 MCI patients followed for at least 1 year. We categorised patients into earlier and later onset (EO/LO). Receiver operating characteristic curves and corresponding areas under the curve (AUCs) were performed to assess and compar the biomarker prognostic performances in EO and LO groups. Linear Model was adopted for estimating the time-to-progression in relation with earlier/later onset MCI groups and biomarkers.

RESULTS

In earlier onset patients, all the assessed biomarkers were able to predict cognitive decline (p < 0.05), with FDG-PET showing the best performance. In later onset patients, all biomarkers but t-tau predicted cognitive decline (p < 0.05). Moreover, FDG-PET alone in earlier onset patients showed a higher prognostic value than the one resulting from the combination of all the biomarkers in later onset patients (earlier onset AUC 0.935 vs later onset AUC 0.753, p < 0.001). Finally, FDG-PET showed a different prognostic value between earlier and later onset patients (p = 0.040) in time-to-progression allowing an estimate of the time free from disease.

DISCUSSION

FDG-PET may represent the most universal tool for the establishment of a prognosis in MCI patients and may be used for obtaining an onset-related estimate of the time free from disease.

Brain metabolic patterns in patients with suspected non-Alzheimer's pathophysiology (SNAP) and Alzheimer's disease (AD): is [18F] FDG a specific biomarker in these patients?

PURPOSE

The present study was conducted to compare the pattern of brain [¹⁸F] FDG uptake in suspected non-Alzheimer's pathophysiology (SNAP), AD, and healthy controls using 2-deoxy-2-[¹⁸F]fluoroglucose ([¹⁸F] FDG) positron emission tomography imaging. Cerebrospinal fluid (CSF) biomarkers amyloid-β1-42 peptide (Aβ1-42) and tau were used in order to differentiate AD from SNAP.

METHODS

The study included 43 newly diagnosed AD patients (female = 23; male = 20) according to the NINCDS-ADRDA criteria, 15 SNAP patients (female = 12; male =3), and a group of 34 healthy subjects that served as the control group (CG), who were found to be normal at neurological evaluation (male = 20; female = 14). A battery of neuropsychological tests was administrated in AD and SNAP subjects; cerebrospinal fluid assay was conducted in both AD and SNAP as well. Brain PET/CT acquisition was started 30 ± 5 min after [¹⁸F] FDG injection in all subjects. SPM12 [statistical parametric mapping] implemented in MATLAB 2018a was used for the analysis of PET scans in this study.

RESULTS

As compared to SNAP, AD subjects showed significant hypometabolism in a wide cortical area involving the right frontal, parietal, and temporal lobes. As compared to CG, AD subjects showed a significant reduction in [¹⁸F] FDG uptake in the parietal, limbic, and frontal cortex, while a more limited reduction in [¹⁸F] FDG uptake in the same areas was found when comparing SNAP to CG.

CONCLUSIONS

SNAP subjects show milder impairment of brain [¹⁸F] FDG uptake as compared to AD. The partial overlap of the metabolic pattern between SNAP and AD limits the use of [¹⁸F] FDG PET/CT in effectively discriminating these clinical entities.

Brain metabolic correlates of CSF Tau protein in a large cohort of Alzheimer's disease patients: A CSF and FDG PET study

AIMS

Physiopathological mechanisms of Alzheimer's disease (AD) are still matter of debate. Especially the role of amyloid β and tau pathology in the development of the disease are still matter of debate. Changes in tau and amyloid β peptide concentration in cerebrospinal fluid (CSF) and hypometabolic patterns at fluorine-18 fluorodeoxyglucose (¹⁸F-FDG) PET scanning are considered as biomarkers of AD. The present study was aimed to evaluate the relationships between the concentrations of CSF total Tau (t-Tau), phosphorilated Tau (p-Tau) and Aβ_1-42 amyloid peptide with ¹⁸F-FDG brain distribution in a group of patients with AD.

MATERIALS AND METHODS

We examined 131 newly diagnosed AD patients according to the NINCDS-ADRDA criteria and 20 healthy controls. The mean (±SD) age of the patients was 70 (±7) years; 57 were male and 74 were female. All patients and controls underwent a complete clinical investigation, including medical history, neurological examination, mini-mental state examination (MMSE), a complete blood screening (including routine exams, thyroid hormones and a complete neuropsychological evaluation). Structural MRI was performed not earlier than 1 month before the ¹⁸F-FDG PET/CT. The following patients were excluded: those with isolated deficits and/or unmodified MMSE (=25/30) on revisit (period of follow-up: 6, 12 and 18 months); patients who had had a clinically manifest acute stroke in the last 6 months with a Hachinsky score greater than 4; and patients with radiological evidence of subcortical lesions. All AD patients were taken off cholinesterase inhibitor treatment throughout the study. We performed lumbar puncture and CSF sampling for diagnostic purposes 2 weeks (±2 days) before the PET/CT scan. The relationship between brain F-FDG uptake and CSF biomarkers was analysed using statistical parametric mapping (SPM8; Wellcome Department of Cognitive Neurology, London, UK) implemented in Matlab R2012b using the MMSE score, sex and age, and other CSF biomarkers as covariates.

RESULTS

t-Tau, p-Tau and Aβ(1-42) in CSF resulted 774 ± 345 pg/ml, 98 ± 64 pg/ml and 348.8 ± 111 pg/ml respectively. SPM analysis showed a significant negative correlation between CSF t-Tau and ¹⁸F FDG uptake in right temporal, parietal and frontal lobe (Brodmann areas, BA, 20, 40 and 8; P fdr and few corr < 0.001, ke 19534). We did not find any significant relationships with other CSF biomarkers.

CONCLUSIONS

t-Tau deposition in brain is related to temporal, parietal and frontal hypometabolism in AD.

18F-FDG PET hypometabolism patterns reflect clinical heterogeneity in sporadic forms of early-onset Alzheimer's disease

Until now, hypometabolic patterns and their correlations with neuropsychological performance have not been assessed as a function of the various presentations of sporadic early-onset Alzheimer's disease (EOAD). Here, we processed and analyzed the patients' metabolic maps at the vertex and voxel levels by using a nonparametric, permutation method that also regressed out the effects of cortical thickness and gray matter volume, respectively. The hypometabolism patterns in several areas of the brain were significantly correlated with the clinical manifestations. These areas included the paralimbic regions for typical presentations of sporadic EOAD. For atypical presentations, the hypometabolic regions included Broca's and Wernicke's areas and the pulvinar in language forms, bilateral primary and higher processing visual regions (with right predominance) in visuospatial forms, and the bilateral prefrontal cortex in executive forms. Similar hypometabolism patterns were also observed in a correlation analysis of the ¹⁸F-FDG PET data versus domain-specific, neuropsychological test scores. These heterogeneities might reflect different underlying pathophysiological processes in particular clinical presentations of sporadic EOAD and should be taken into account in future longitudinal and therapeutic studies.

Cerebrospinal Fluid Aβ43 Is Reduced in Early-Onset Compared to Late-Onset Alzheimer's Disease, But Has Similar Diagnostic Accuracy to Aβ42

Background: Amyloid beta 1-43 (Aβ43) may be a useful additional biomarker for diagnosing Alzheimer's disease (AD). We have investigated cerebrospinal fluid (CSF) levels of Aβ43 in patients with early-onset AD in contrast to levels in late-onset AD. For comparison, in addition to the 'core' biomarkers, several other analytes were also determined [YKL-40, neurofilament light (NF-L), glial fibrillary acidic protein (GFAP), and progranulin]. Material and Methods: Cerebrospinal fluid samples were obtained from patients with early-onset AD (age ≤ 62, n = 66), late-onset AD (age ≥ 68, n = 25), and groups of cognitively intact individuals (age ≤ 62, n = 41, age ≥ 68, n = 39). Core CSF AD biomarkers [amyloid beta 1-42 (Aβ42), total tau, phosphorylated tau] were analyzed, as well as levels of Aβ43 and other analytes, using commercially available enzyme-linked immunosorbent assays. Results: Cerebrospinal fluid Aβ43 was significantly reduced in early-onset AD compared to late-onset AD (14.8 ± 7.3 vs. 21.8 ± 9.4 pg/ml, respectively), whereas the levels of Aβ42 in the two AD groups were not significantly different (474.9 ± 142.0 vs. 539.6 ± 159.9 pg/ml, respectively). Aβ43 and all core biomarkers were significantly altered in patients with AD compared to corresponding controls. NF-L was significantly increased in early-onset AD compared to younger controls, an effect not found between the older groups. Relationships between the Aβ peptides and tau proteins, YKL-40, NF-L, GFAP and progranulin were also investigated without finding marked associations. However, age-associated increases in levels of tau proteins, YKL-40, NF-L and GFAP were found with respect to age in healthy controls. Results for these other analytes were similar to previously published data. Aβ43 did not improve diagnostic accuracy in either AD group compared to Aβ42.

DISCUSSION

Cerebrospinal fluid Aβ43, but not Aβ42 levels, varied significantly with age in patients with AD. If CSF levels of Aβ peptides reflect amyloid deposition in brain, the possibility arises that there is a difference between Aβ43 and Aβ42 deposition in younger compared to older brain. However, the level of Aβ43 in CSF shows no improvement over Aβ42 regarding diagnostic accuracy.

PET Imaging for Early Detection of Alzheimer's Disease: From Pathologic to Physiologic Biomarkers

This article describes the application of various PET imaging agents in the investigation and diagnosis of Alzheimer's disease (AD), including radiotracers for pathologic biomarkers of AD such as β-amyloid deposits and tau protein aggregates, and the neuroinflammation biomarker 18 kDa translocator protein, as well as physiologic biomarkers, such as cholinergic receptors, glucose metabolism, and the synaptic density biomarker synaptic vesicle glycoprotein 2A. Potential of these biomarkers for early AD diagnosis is also assessed.

Early-Onset Alzheimer Disease

Early-onset Alzheimer disease (EOAD), with onset in individuals younger than 65 years, although overshadowed by the more common late-onset AD (LOAD), differs significantly from LOAD. EOAD comprises approximately 5% of AD and is associated with delays in diagnosis, aggressive course, and age-related psychosocial needs. One source of confusion is that a substantial percentage of EOAD are phenotypic variants that differ from the usual memory-disordered presentation of typical AD. The management of EOAD is similar to that for LOAD, but special emphasis should be placed on targeting the specific cognitive areas involved and more age-appropriate psychosocial support and education.