NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14:535-562. [PMID: 29653606 PMCID: PMC5958625 DOI: 10.1016/j.jalz.2018.02.018]

Identifying Changepoints in Biomarkers During the Preclinical Phase of Alzheimer's Disease

Objective: Several models have been proposed for the evolution of Alzheimer's disease (AD) biomarkers. The aim of this study was to identify changepoints in a range of biomarkers during the preclinical phase of AD. Methods: We examined nine measures based on cerebrospinal fluid (CSF), magnetic resonance imaging (MRI) and cognitive testing, obtained from 306 cognitively normal individuals, a subset of whom subsequently progressed to the symptomatic phase of AD. A changepoint model was used to determine which of the measures had a significant change in slope in relation to clinical symptom onset. Results: All nine measures had significant changepoints, all of which preceded symptom onset, however, the timing of these changepoints varied considerably. A single measure, CSF t-tau, had an early changepoint (34 years prior to symptom onset). A group of measures, including the remaining CSF measures (CSF Abeta and phosphorylated tau) and all cognitive tests had changepoints 10-15 years prior to symptom onset. A second group is formed by medial temporal lobe shape composite measures, with a 6-year time difference between the right and left side (respectively nine and 3 years prior to symptom onset). Conclusion: These findings highlight the long period of time prior to symptom onset during which AD pathology is accumulating in the brain. There are several significant findings, including the early changes in cognition and the laterality of the MRI findings. Additional work is needed to clarify their significance.

Seeding selectivity and ultrasensitive detection of tau aggregate conformers of Alzheimer disease

Alzheimer disease (AD) and chronic traumatic encephalopathy (CTE) involve the abnormal accumulation in the brain of filaments composed of both three-repeat (3R) and four-repeat (4R) (3R/4R) tau isoforms. To probe the molecular basis for AD's tau filament propagation and to improve detection of tau aggregates as potential biomarkers, we have exploited the seeded polymerization growth mechanism of tau filaments to develop a highly selective and ultrasensitive cell-free tau seed amplification assay optimized for AD (AD real-time quaking-induced conversion or AD RT-QuIC). The reaction is based on the ability of AD tau aggregates to seed the formation of amyloid fibrils made of certain recombinant tau fragments. AD RT-QuIC detected seeding activity in AD (n = 16) brains at dilutions as extreme as 10⁷-10¹⁰-fold, but was 10²-10⁶-fold less responsive when seeded with brain from most cases of other types of tauopathy with comparable loads of predominant 3R or 4R tau aggregates. For example, AD brains had average seeding activities that were orders of magnitude higher than Pick disease brains with predominant 3R tau deposits, but the opposite was true using our previously described Pick-optimized tau RT-QuIC assay. CTE brains (n = 2) had seed concentrations comparable to the weakest of the AD specimens, and higher than 3 of 4 specimens with 3R/4R primary age-related tauopathy. AD seeds shared properties with the tau filaments found in AD brains, as AD seeds were sarkosyl-insoluble, protease resistant, and reactive with tau antibodies. Moreover, AD RT-QuIC detected as little as 16 fg of pure synthetic tau fibrils. The distinctive seeding activity exhibited by AD and CTE tau filaments compared to other types of tauopathies in these seeded polymerization reactions provides a mechanistic basis for their consistent propagation as specific conformers in patients with 3R/4R tau diseases. Importantly, AD RT-QuIC also provides rapid ultrasensitive quantitation of 3R/4R tau-seeding activity as a biomarker.

The metabolic brain signature of cognitive resilience in the 80+: beyond Alzheimer pathologies

Research into cognitive resilience imaging markers may help determine the clinical significance of Alzheimer's disease pathology among older adults over 80 years (80+). In this study, we aimed to identify a fluorodeoxyglucose (FDG)-PET based imaging marker of cognitive resilience. We identified 457 participants ≥ 80 years old (357 cognitively unimpaired, 118 cognitively impaired at baseline, mean age of 83.5 ± 3.2 years) from the population-based Mayo Clinic Study of Aging (MCSA) with baseline MRI, Pittsburgh compound B-PET and FDG-PET scans and neuropsychological evaluation. We identified a subset of 'resilient' participants (cognitively stable 80+, n = 192) who maintained normal cognition for an average of 5 years (2-10 years). Global PIB ratio, FDG-PET ratio and cortical thickness from Alzheimer's disease signature regions were used as Alzheimer's disease imaging biomarker outcomes and global cognitive z-score was used as a cognitive outcome. First, using voxel-wise multiple regression analysis, we identified the metabolic areas underlying cognitive resilience in cognitively stable 80+ participants, which we call the 'resilience signature'. Second, using multivariate linear regression models, we evaluated the association of risk and protective factors with the resilience signature and its added value for predicting global cognition beyond established Alzheimer's disease imaging biomarkers in the full 80+ sample. Third, we evaluated the utility of the resilience signature in conjunction with amyloidosis in predicting longitudinal cognition using linear mixed effect models. Lastly, we assessed the utility of the resilience signature in an independent cohort using ADNI (n = 358, baseline mean age of 80 ± 3.8). Our main findings were: (i) FDG-PET uptake in the bilateral anterior cingulate cortex and anterior temporal pole was associated with baseline global cognition in cognitively stable 80+ (the resilience signature); (ii) established Alzheimer's disease imaging biomarkers did not predict baseline global cognition in this subset of participants; (iii) in the full MCSA 80+ and ADNI cohorts, amyloid burden and FDG-PET in the resilience signature were the stronger predictors of baseline global cognition; (iv) sex and systemic vascular health predicted FDG-PET in the resilience signature, suggesting vascular health maintenance as a potential pathway to preserve the metabolism of these areas; and (v) the resilience signature provided significant information about global longitudinal cognitive change even when considering amyloid status in both the MCSA and ADNI cohorts. The FDG-PET resilience signature may be able to provide important information in conjunction with other Alzheimer's disease biomarkers for the determination of clinical prognosis. It may also facilitate identification of disease targeting modifiable risk factors such as vascular health maintenance.

EARLY PREDICTION OF ALZHEIMER'S DISEASE DEMENTIA BASED ON BASELINE HIPPOCAMPAL MRI AND 1-YEAR FOLLOW-UP COGNITIVE MEASURES USING DEEP RECURRENT NEURAL NETWORKS

Multi-modal biological, imaging, and neuropsychological markers have demonstrated promising performance for distinguishing Alzheimer's disease (AD) patients from cognitively normal elders. However, it remains difficult to early predict when and which mild cognitive impairment (MCI) individuals will convert to AD dementia. Informed by pattern classification studies which have demonstrated that pattern classifiers built on longitudinal data could achieve better classification performance than those built on cross-sectional data, we develop a deep learning model based on recurrent neural networks (RNNs) to learn informative representation and temporal dynamics of longitudinal cognitive measures of individual subjects and combine them with baseline hippocampal MRI for building a prognostic model of AD dementia progression. Experimental results on a large cohort of MCI subjects have demonstrated that the deep learning model could learn informative measures from longitudinal data for characterizing the progression of MCI subjects to AD dementia, and the prognostic model could early predict AD progression with high accuracy.

Which MCI Patients Should be Included in Prodromal Alzheimer Disease Clinical Trials?

BACKGROUND

Prodromal Alzheimer disease (AD) clinical trials enroll patients with mild cognitive impairment (MCI) meeting biomarker criteria, but specific enrollment criteria vary among trials.

METHODS

We used data from AD Neuroimaging Initiative (ADNI) MCI participants to assess AD biomarker eligibility, variation in trial outcome measures, and statistical power.

RESULTS

Most (65%) participants meet eligibility criteria based on low cerebrospinal fluid amyloid beta (Aβ). Relative to trials enrolling exclusively based on low cerebrospinal fluid Aβ, trials including participants with a high ratio of phosphorylated tau to Aβ would include an additional 15% of participants. Fewer (34% to 62%) participants met criteria for Aβ and tau. Differences in clinical and demographic characteristics of modeled trial samples were minimal. Those with low Aβ and high tau showed the greatest change over time on outcome measures.

CONCLUSIONS

Eligibility rates for prodromal trials vary depending on the specific biomarker criteria, though differences in demographics and the variation associated with outcome measures are minimal. Broadening inclusion criteria beyond amyloid alone may facilitate recruitment but include patients showing slower progression over time. Biomarker criteria selection should be informed by the goal of enrolling individuals most likely to utilize and benefit from the intervention under investigation in a particular setting.

Relevance of the interplay between amyloid and tau for cognitive impairment in early Alzheimer's disease

Amyloid β (Aβ) and tau are key hallmark features of Alzheimer's disease (AD) neuropathology. The interplay of Aβ and tau for cognitive impairment in early AD was examined with cross-sectional analysis, measured by cerebrospinal fluid biomarkers (Aβ_1-42, total tau [t-tau], and phosphorylated tau [p-tau181P]), and on cognitive performance by the repeatable battery for assessment of neuropsychological status (RBANS). Participants (n = 246) included cognitively normal (Aβ-), mild cognitively impaired (Aβ-), preclinical AD (Aβ+), and prodromal AD (Aβ+). Overall, cognitive scores (RBANS total scale score) had a moderate negative correlation to t-tau (n = 246; r = -0.434; p < 0.001) and p-tau181P (r = -0.389; p < 0.001). When classified by Aβ status, this correlation to t-tau was applicable only in Aβ+ participants (n = 139; r = -0.451, p < 0.001) but not Aβ- participants (n = 107; r = 0.137, p = 0.16), with identical findings for p-tau. Both tau (p < 0.0001) and interaction of Aβ_1-42 with tau (p = 0.006) affected RBANS, but not Aβ_1-42 alone. Cognitive/memory performance correlated well with cerebrospinal fluid tau levels across early stages of AD, although the correlation is Aβ dependent.

Design and sample size considerations for Alzheimer's disease prevention trials using multistate models

BACKGROUND/AIMS

Clinical trials for Alzheimer's disease have been aimed primarily at persons who have cognitive symptoms at enrollment. However, researchers are now recognizing that the pathophysiological process of Alzheimer's disease begins years, if not decades, prior to the onset of clinical symptoms. Successful intervention may require intervening early in the disease process. Critical issues arise in designing clinical trials for primary and secondary prevention of Alzheimer's disease including determination of sample sizes and follow-up duration. We address a number of these issues through application of a unifying multistate model for the preclinical course of Alzheimer's disease. A multistate model allows us to specify at which points during the long disease process the intervention exerts its effects.

METHODS

We used a nonhomogeneous Markov multistate model for the progression of Alzheimer's disease through preclinical disease states defined by biomarkers, mild cognitive impairment and Alzheimer's disease dementia. We used transition probabilities based on several published cohort studies. Sample size methods were developed that account for factors including the initial preclinical disease state of trial participants, the primary endpoint, age-dependent transition and mortality rates and specifications of which transition rates are the targets of the intervention.

RESULTS

We find that Alzheimer's disease prevention trials with a clinical primary endpoint of mild cognitive impairment or Alzheimer's disease dementia will require sample sizes of the order many thousands of individuals with at least 5 years of follow-up, which is larger than most Alzheimer's disease therapeutic trials conducted to date. The reasons for the large trial sizes include the long and variable preclinical period that spans decades, high rates of attrition among elderly populations due to mortality and losses to follow-up and potential selection effects, whereby healthier subjects enroll in prevention trials. A web application is available to perform sample size calculations using the methods reported here.

CONCLUSION

Sample sizes based on multistate models can account for the points in the disease process when interventions exert their effects and may lead to more accurate sample size determinations. We will need innovative strategies to help design Alzheimer's disease prevention trials with feasible sample size requirements and durations of follow-up.

Symptom clusters of subjective cognitive decline amongst cognitively normal older persons and their utilities in predicting objective cognitive performance: structural equation modelling

BACKGROUND AND PURPOSE

Prior literature on subjective cognitive decline (SCD) has mostly focused on memory complaints. It is uncertain whether the other non-memory complaints are equally relevant and can be used, alongside memory complaints, to identify populations at high risk of cognitive impairment. How the memory and non-memory complaints of SCD cluster with each other amongst community-dwelling individuals was investigated, and the differential utility of the symptom clusters of SCD in predicting objective cognitive performance was evaluated.

METHODS

This study included 736 participants who were ≥60 years and had normal cognition, using the baseline data of an ongoing cohort study. Participants completed baseline assessments which comprised an SCD scale, a global cognitive measure and neuropsychological tests. Symptom clusters of SCD - as identified from exploratory and confirmatory factor analyses - were included in structural equation models to predict baseline changes in neuropsychological tests.

RESULTS

The symptoms of SCD were split into two distinct factors, of which factor 1 was reported much more frequently than factor 2. Each standard deviation (SD) increment in factor 1 led to a 0.16-0.50 SD increase in global cognition, immediate memory, visuospatial abilities, language, attention and delayed memory (P < 0.05). In contrast, each SD increment in factor 2 worsened some of the cognitive domains by 0.18-0.37 SD.

CONCLUSIONS

The various complaints of SCD can have different implications amongst cognitively normal older persons and may possibly be classified into age-related symptoms and pathological symptoms. The findings highlight the need for caution when selecting SCD measures, and illustrate the potential utility of SCD subtypes to inform on the underlying neurobiology.

Sensitivity of a Preclinical Alzheimer's Cognitive Composite (PACC) to amyloid β load in preclinical Alzheimer's disease

Introduction: Preclinical Alzheimer's disease (AD) is characterized by amyloid-related cognitive decline. Reduction in this decline is used to determine the efficacy of drug therapies designed to forestall the disease in preclinical AD clinical trials, measured by a Preclinical Alzheimer's Cognitive Composite (PACC). Most studies estimate rates of cognitive change by comparing cognitively normal (CN) older adults with abnormally high beta-amyloid (Aβ+) to those with low levels (Aβ-). However, participants of preclinical AD clinical trials must be Aβ+ for entry. Therefore, we estimated the effect of very high amyloid (Aβ++) and Aβ+ on cognitive change over three years measured by different versions of the PACC in individuals with preclinical AD. Method: CN older adults underwent Aβ neuroimaging and neuropsychological assessments over three years as part of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. Three cognitive composite scores were computed: the Alzheimer's Disease Cooperative Study (ADCS)-PACC, the ADCS-PACC with no Mini-Mental State Examination (MMSE), and the z-scores of Attention, Verbal Fluency and Episodic Memory for Nondemented Older Adults (ZAVEN) composite. Results: Compared to the Aβ++ group, the Aβ+ group showed a slower rate of cognitive decline with the largest magnitude of difference reflected by the ADCS-PACC (d = 0.85). The ADCS-PACC excluding the MMSE and the ZAVEN also reflected a moderate to large magnitude of difference between groups (d = 0.62, d = 0.72, respectively). Conclusions: When all individuals have abnormal Aβ, the level of Aβ at baseline is associated with the rate of subsequent decline. The ADCS-PACC was the most sensitive composite score in showing that lower Aβ is associated with a slower rate of cognitive decline; however, there are limitations to the use of the MMSE. These results provide a benchmark of comparison for preclinical AD clinical trials aiming to slow cognitive deterioration.

Amyloid-Negative Dementia in the Elderly is Associated with High Accumulation of Tau in the Temporal Lobes

Background:

We previously reported that among cases clinically diagnosed with Alzheimer’s disease, the proportion of amyloid beta (Aβ) -negative case increases in the elderly population. Tauopathy including Argyrophilic Grain Disease (AGD) and Neurofibrillary Tangle-Predominant Dementia (NFTPD), may be the leading causes of such dementia.

Objective:

To evaluate the involvement of tau, we studied tau accumulation in Amyloid-Negative Dementia Cases in the Elderly (ANDE) with Positron Emission Tomography (PET).

Methods:

Seven cases with slowly progressive dementia who were older than 80 years and were negative for Aβ were studied. In one case, autopsy obtained 2 years after the PET examination revealed neurofibrillary tangles limited around the parahippocampal gyrus. Four cases showed strong laterality in magnetic resonance imaging atrophy (clinical AGD), while the other three cases had no significant laterality in atrophy (clinical NFTPD). Age-corrected PET data of healthy controls (HC; n = 12) were used as control. Tau accumulation was evaluated with [11C]PBB3-PET.

Results:

High accumulation was found in the lateral temporal cortex in ANDE. In autopsy case, scattered neurofibrillary tangles were found in the parahippocampal gyrus. In addition, there was a very high accumulation of PBB3 in the large area of bilateral parietal lobes, although no corresponding tau component was found in the autopsied case.

Conclusion:

Relatively high burden of tau deposition was commonly observed in the lateral temporal cortex and parietal cortex of ANDE, part of which may explain dementia in these subjects. [11C]PBB3 may be useful in detecting tauopathy in ANDE.

CSF level of β-amyloid peptide predicts mortality in Alzheimer's disease

Objective

Alzheimer’s disease (AD) is the sixth leading cause of death, with an average survival estimated between 5 and 10 years after diagnosis. Despite recent advances in diagnostic criteria of AD, few studies have used biomarker-based diagnostics to determine the prognostic factors of AD. We investigate predictors of death and institutionalization in a population of AD patients with high probability of AD physiopathology process assessed by positivity of three CSF biomarkers.

Methods

Three hundred twenty-one AD patients with abnormal values for CSF beta-amyloid peptide (Aβ42), tau, and phosphorylated tau levels were recruited from a memory clinic-based registry between 2008 and 2017 (Lariboisiere hospital, Paris, France) and followed during a median period of 3.9 years. We used multivariable Cox models to estimate the hazard ratio (HR) of death and institutionalization for baseline clinical data, genotype of the apolipoprotein E (APOE), and levels of CSF biomarkers.

Results

A total of 71 (22%) patients were institutionalized and 57 (18%) died during the follow-up. Greater age, male sex, lower MMSE score, and lower CSF Aβ42 level were associated with an increased risk of mortality. One standard deviation lower CSF Aβ42 (135 pg/mL) was associated with a 89% increased risk of death (95% CI = 1.25–2.86; p = 0.002). This association was not modified by age, sex, education, APOE ε4, and disease severity. There was no evidence of an association of tau CSF biomarkers with mortality. None of the CSF biomarkers were associated with institutionalization.

Conclusions

Lower CSF Aβ42 is a strong prognostic marker of mortality in AD patients, independently of age or severity of the disease. Whether drugs targeting beta-amyloid peptide could have an effect on mortality of AD patients should be investigated in future clinical trials.

Fractionating the Rey Auditory Verbal Learning Test: Distinct roles of large-scale cortical networks in prodromal Alzheimer's disease

Successful episodic memory calls upon a number of different cognitive processes that are supported by the coordination of several large-scale cortical networks. Previous work from our group has demonstrated dissociable anatomic substrates at different stages of memory in patients with dementia due to Alzheimer's disease (AD). The aim of the current study was to extend the understanding of brain-behavior associations underlying a commonly administered neuropsychological assessment of verbal episodic memory (Rey Auditory Verbal Learning Test; RAVLT) by determining the cortical network contributions to the performance at early vs. late stages of list learning, delayed recall, and retention, in 235 very mild biomarker positive (A+/T+/N+) individuals diagnosed with amnestic mild cognitive impairment (aMCI; MMSE = 27.7). We measured cortical atrophy in four large-scale cortical networks impacted by AD: default mode (DMN), dorsal attention (DAN), frontoparietal (FPN), and language (LN) networks. We also evaluated the role of hippocampal atrophy at each stage of memory performance. Partial correlation analyses controlling for age, sex, and education and corrected for multiple comparisons revealed that early learning was most strongly associated with cortical thickness in the DAN, while late learning was most strongly associated with hippocampal volume, but also related to cortical thickness in the DAN, FPN, DMN, and LN. Delayed recall was associated most strongly with hippocampal volume, but was also related to cortical thickness in the FPN and DMN, while retention was associated only with hippocampal volume. These findings are consistent with prior models of the neural substrates of different stages of verbal list learning and retrieval, provide new insights into the cortical networks undergoing neurodegeneration even at very mild stages of prodromal AD, and inform our thinking about the networks and regions being interrogated by this kind of neuropsychological assessment of episodic memory.

The effect of ApoE ε4 on longitudinal brain region-specific glucose metabolism in patients with mild cognitive impairment: a FDG-PET study

While the ApoE ε4 allele is a known risk factor for mild cognitive impairment (MCI) and Alzheimer's disease, brain region specific effects remain elusive. In this study, we investigate whether the ApoE ε4 allele exhibits brain region specific effects in longitudinal glucose uptake among patients with MCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed FDG PET images, MRIs, and demographic information were downloaded from the ADNI database. An iterative reblurred Van Cittertiteration method was used for partial volume correction (PVC) on all PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. Longitudinal changes in ROI FDG standardized uptake value ratio (SUVR) relative to cerebellum in 24 ApoE ε4 carriers and 24 age-matched ApoE ε4 non-carriers were measured for up to 84-months (median 72 months, SD = 11.2 months) and compared using a generalized linear mixed effects model controlling for gender, education, baseline age, and follow-up period. Additionally, voxelwise analysis was performed by implementing a paired t-test comparing matched baseline and 72 month FDG SUVR images in ApoE carriers and non-carriers separately. Results with PVC were compared with ones from non-PVC based analysis. After applying PVC, the superior fontal, parietal, lateral temporal, medial temporal, caudate, thalamus, and post-cingulate, and amygdala regions had greater longitudinal decreases in FDG uptake in ApoE ε4 carriers with MCI compared to non-carriers with MCI. Similar forebrain and limbic clusters were found through voxelwise analysis. Compared to the PVC based analysis, fewer significant ApoE-associated regions and clusters were found in the non-PVC based PET analysis. Our findings suggest that the ApoE ε4 genotype is associated with a longitudinal decline in glucose uptake in 8 forebrain and limbic brain regions in the context of MCI. In conclusion, this 84-months longitudinal FDG PET study demonstrates a novel ApoE ε4-associated brain-region specific glucose metabolism pattern in patients with MCI. Partial volume correction improved FDG PET quantification.

How pattern information analyses of semantic brain activity elicited in language comprehension could contribute to the early identification of Alzheimer's Disease

Alzheimer's disease (AD) is associated with a loss of semantic knowledge reflecting brain pathophysiology that begins years before dementia. Identifying early signs of pathophysiology induced dysfunction in the neural systems that access and process words' meaning could therefore help forecast dementia. This article reviews pioneering studies demonstrating that abnormal functional Magnetic Resonance Imaging (fMRI) response patterns elicited in semantic tasks reflect both AD-pathophysiology and the hereditary risk of AD, and also can help forecast cognitive decline. However, to bring current semantic task-based fMRI research up to date with new AD research guidelines the relationship with different types of AD-pathophysiology needs to be more thoroughly examined. We shall argue that new analytic techniques and experimental paradigms will be critical for this. Previous work has relied on specialized tests of specific components of semantic knowledge/processing (e.g. famous name recognition) to reveal coarse AD-related changes in activation across broad brain regions. Recent computational advances now enable more detailed tests of the semantic information that is represented within brain regions during more natural language comprehension. These new methods stand to more directly index how pathophysiology alters neural information processing, whilst using language comprehension as the basis for a more comprehensive examination of semantic brain function. We here connect the semantic pattern information analysis literature up with AD research to raise awareness to potential cross-disciplinary research opportunities.

Plasma Levels of Soluble AβPPβ as a Biomarker for Alzheimer's Disease with Dementia

Cost- and time-effective markers of Alzheimer's disease (AD), reliable and feasible at the population level are urgently needed. Soluble amyloid-β protein precursor β (sAβPPβ) in plasma has attracted scientific attention as a potential AD biomarker candidate. Here we report that plasma sAβPPβ levels in patients with AD dementia and typical for AD cerebrospinal fluid (CSF) biomarker profiles (N = 33) are significantly lower (p < 0.01) than those of cognitively healthy elderly individuals without AD (N = 39), while CSF sAβPPβ levels did not differ between the studied groups. This provides further evidence for the potential of sAβPPβ in plasma as an AD biomarker candidate.

Clinical impact of [18F]flutemetamol PET among memory clinic patients with an unclear diagnosis

Purpose

To investigate the impact of amyloid PET with [¹⁸F]flutemetamol on diagnosis and treatment management in a cohort of patients attending a tertiary memory clinic in whom, despite extensive cognitive assessment including neuropsychological testing, structural imaging, CSF biomarker analysis and in some cases [¹⁸F]FDG PET, the diagnosis remained unclear.

Methods

The study population consisted of 207 patients with a clinical diagnosis prior to [¹⁸F]flutemetamol PET including mild cognitive impairment (MCI; n = 131), Alzheimer’s disease (AD; n = 41), non-AD (n = 10), dementia not otherwise specified (dementia NOS; n = 20) and subjective cognitive decline (SCD; n = 5).

Results

Amyloid positivity was found in 53% of MCI, 68% of AD, 20% of non-AD, 20% of dementia NOS, and 60% of SCD patients. [¹⁸F]Flutemetamol PET led, overall, to a change in diagnosis in 92 of the 207 patients (44%). A high percentage of patients with a change in diagnosis was observed in the MCI group (n = 67, 51%) and in the dementia NOS group (n = 11; 55%), followed by the non-AD and AD (30% and 20%, respectively). A significant increase in cholinesterase inhibitor treatment was observed after [¹⁸F]flutemetamol PET (+218%, 34 patients before and 108 patients after).

Conclusion

The present study lends support to the clinical value of amyloid PET in patients with an uncertain diagnosis in the tertiary memory clinic setting.

Language Performance of Individuals at Risk for Mild Cognitive Impairment

Purpose Evidence exists that changes in language performance may be an early indicator of mild cognitive impairment (MCI), often a harbinger of dementing disease. The purpose of this study was the evaluation of language performance in individuals at risk for MCI by virtue of age and self-concern and its relation to performance on tests of memory, visuospatial function, and mental status. Method Eighty-three individuals 55 years or older were administered the Arizona Battery for Communication Disorders of Dementia ( Bayles & Tomoeda, 1993 ), a standardized battery with normative data from 86 healthy older adults (HOAs) and 86 individuals with Alzheimer's dementia, the most common dementing disease. A performance criterion of 1-1.5 SDs below the mean of HOAs defined MCI, as recommended in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. We hypothesized that (a) the majority of at-risk participants would score 1 SD or more below the mean of HOAs on 1 or more subtests and (b) language performance tests would present a greater challenge than memory, mental status, and visuospatial construction tests. Results Both hypotheses were confirmed. Sixty-two participants (74.6%) met the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria on at least 1 subtest. Moreover, language subtests were those most likely to elicit a performance 1 SD or more below the mean of HOAs. Conclusions Language performance deficits can appear early before impairment in episodic memory, visuospatial construction ability, or mental status in individuals at risk for MCI. Speech-language pathologists are uniquely qualified to identify subtle changes in language, and standardized language tests with normative data should be used when testing for MCI.

Trajectories of the Hippocampal Subfields Atrophy in the Alzheimer's Disease: A Structural Imaging Study

Background

The hippocampus and hippocampal subfields have been found to be diversely affected in Alzheimer's Disease (AD) and early stages of Alzheimer's disease by neuroimaging studies. However, our knowledge is still lacking about the trajectories of the hippocampus and hippocampal subfields atrophy with the progression of Alzheimer's disease.

Objective

To identify which subfields of the hippocampus differ in the trajectories of Alzheimer's disease by magnetic resonance imaging (MRI) and to determine whether individual differences on memory could be explained by structural volumes of hippocampal subfields.

Methods

Four groups of participants including 41 AD patients, 43 amnestic mild cognitive impairment (aMCI) patients, 35 subjective cognitive decline (SCD) patients and 42 normal controls (NC) received their structural MRI brain scans. Structural MR images were processed by the FreeSurfer 6.0 image analysis suite to extract the hippocampus and its subfields. Furthermore, we investigated relationships between hippocampal subfield volumes and memory test variables (AVLT-immediate recall, AVLT-delayed recall, AVLT-recognition) and the regression model analyses were controlled for age, gender, education and eTIV.

Results

CA1, subiculum, presubiculum, molecular layer and fimbria showed the trend toward significant volume reduction among four groups with the progression of Alzheimer's disease. Volume of left subiculum was most strongly and actively correlated with performance across AVLT measures.

Conclusion

The trend changes in the hippocampus subfields and further illustrates that SCD is the preclinical stage of AD earlier than aMCI. Future studies should aim to associate the atrophy of the hippocampal subfields in SCD with possible conversion to aMCI or AD with longitudinal design.

Centiloid cut-off values for optimal agreement between PET and CSF core AD biomarkers

BACKGROUND

The Centiloid scale has been developed to standardize measurements of amyloid PET imaging. Reference cut-off values of this continuous measurement enable the consistent operationalization of decision-making for multicentre research studies and clinical trials. In this study, we aimed at deriving reference Centiloid thresholds that maximize the agreement against core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers in two large independent cohorts.

METHODS

A total of 516 participants of the ALFA+ Study (N = 205) and ADNI (N = 311) underwent amyloid PET imaging ([18F]flutemetamol and [18F]florbetapir, respectively) and core AD CSF biomarker determination using Elecsys® tests. Tracer uptake was quantified in Centiloid units (CL). Optimal Centiloid cut-offs were sought that maximize the agreement between PET and dichotomous determinations based on CSF levels of Aβ42, tTau, pTau, and their ratios, using pre-established reference cut-off values. To this end, a receiver operating characteristic analysis (ROC) was conducted, and Centiloid cut-offs were calculated as those that maximized the Youden's J Index or the overall percentage agreement recorded.

RESULTS

All Centiloid cut-offs fell within the range of 25-35, except for CSF Aβ42 that rendered an optimal cut-off value of 12 CL. As expected, the agreement of tau/Aβ42 ratios was higher than that of CSF Aβ42. Centiloid cut-off robustness was confirmed even when established in an independent cohort and against variations of CSF cut-offs.

CONCLUSIONS

A cut-off of 12 CL matches previously reported values derived against postmortem measures of AD neuropathology. Together with these previous findings, our results flag two relevant inflection points that would serve as boundary of different stages of amyloid pathology: one around 12 CL that marks the transition from the absence of pathology to subtle pathology and another one around 30 CL indicating the presence of established pathology. The derivation of robust and generalizable cut-offs for core AD biomarkers requires cohorts with adequate representation of intermediate levels.

TRIAL REGISTRATION

ALFA+ Study, NCT02485730 ALFA PET Sub-study, NCT02685969.

Amyloid beta in nasal secretions may be a potential biomarker of Alzheimer's disease

We investigated the level of amyloid beta (Aβ) in nasal secretions of patients with Alzheimer’s disease dementia (ADD) using interdigitated microelectrode (IME) biosensors and determined the predictive value of Aβ in nasal secretions for ADD diagnosis. Nasal secretions were obtained from 35 patients with ADD, 18 with cognitive decline associated with other neurological disorders (OND), and 26 cognitively unimpaired (CU) participants. Capacitance changes in IMEs were measured by capturing total Aβ (ΔC_tAβ). After 4-(2-hydroxyethyl)-1-piperazinepropanesulfonic acid (EPPS) was injected, additional capacitance changes due to the smaller molecular weight Aβ oligomers disassembled from the higher molecular weight oligomeric Aβ were determined (ΔC_oAβ). By dividing two values, the capacitance ratio (ΔC_oAβ/ΔC_tAβ) was determined and then normalized to the capacitance change index (CCI). The CCI was higher in the ADD group than in the OND (p = 0.040) and CU groups (p = 0.007). The accuracy of the CCI was fair in separating into the ADD and CU groups (area under the receiver operating characteristic curve = 0.718, 95% confidence interval = 0.591–0.845). These results demonstrate that the level of Aβ in nasal secretions increases in ADD and the detection of Aβ in nasal secretions using IME biosensors may be possible in predicting ADD.

Tetraclinis articulata essential oil mitigates cognitive deficits and brain oxidative stress in an Alzheimer's disease amyloidosis model

BACKGROUND

Tetraclinis articulata is used in traditional medicine and has been reported to possess antibacterial, antifungal, cytotoxic, anti-inflammatory and antioxidant properties.

PURPOSE

This study investigated the effects of T. articulata essential oil on memory and brain oxidative stress in amyloid-β peptide 1-42 (Aβ1-42)-induced an Alzheimer's disease amyloidosis model. Moreover, the underlying mechanism for memory enhancement and antioxidant activity was investigated, thus supporting its traditional use with scientific evidence for further studies.

METHODS

T. articulata essential oil was administered by inhalation to male Wistar rats once daily for 15 min period at doses of 1% and 3% for 21 days after the intracerebroventricular administration of Aβ1-42 right-unilaterally to induce memory deficits. The chemical composition of the essential oil was done by GC-MS and GC-FID. Spatial memory of rats was tested using Y-maze and radial arm maze tests. The possible underlying mechanism for memory improvement exhibited by T. articulata essential oil was investigated by in vivo brain antioxidant effect and acetylcholinesterase (AChE) inhibitory effect. In vitro, experimental evaluations were assessed through DPPH and ABTS tests.

RESULTS

The GC-MS and GC-FID data showed that the essential oil has a high percent of monoterpene hydrocarbons. Also, we demonstrated the essential oil reversed the Aβ1-42-induced decreasing of the spontaneous alternation in the Y-maze test and the Aβ1-42-induced increasing of the working and reference memory errors in the radial arm maze test. Furthermore, the Aβ1-42-decreased the acetylcholinesterase activity and the oxidant-antioxidant status in the rat hippocampus was retrieved by the treatment with the essential oil.

CONCLUSION

The study demonstrates that the essential oil could be a potent pharmacological agent against dementia by modulating cholinergic activity and promoting antioxidant action in the rat hippocampus.

Association of short-term cognitive decline and MCI-to-AD dementia conversion with CSF, MRI, amyloid- and 18F-FDG-PET imaging

Disease-modifying treatment trials are increasingly advanced to the prodromal or preclinical phase of Alzheimer's disease (AD), and inclusion criteria are based on biomarkers rather than clinical symptoms. Therefore, it is of great interest to determine which biomarkers should be combined to accurately predict conversion from mild cognitive impairment (MCI) to AD dementia. However, up to date, only few studies performed a complete A/T/N subject characterization using each of the CSF and imaging markers, or they only investigated long-term (≥ 2 years) prognosis. This study aimed to investigate the association between cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), amyloid- and ¹⁸F-FDG positron emission tomography (PET) measures at baseline, in relation to cognitive changes and conversion to AD dementia over a short-term (12-month) period. We included 13 healthy controls, 49 MCI and 16 AD dementia patients with a clinical-based diagnosis and a complete A/T/N characterization at baseline. Global cortical amyloid-β (Aβ) burden was quantified using the ¹⁸F-AV45 standardized uptake value ratio (SUVR) with two different reference regions (cerebellar grey and subcortical white matter), whereas metabolism was assessed based on ¹⁸F-FDG SUVR. CSF measures included Aβ_1–42, Aβ_1–40, T-tau, P-tau₁₈₁, and their ratios, and MRI markers included hippocampal volumes (HV), white matter hyperintensities, and cortical grey matter volumes. Cognitive functioning was measured by MMSE and RBANS index scores. All statistical analyses were corrected for age, sex, education, and APOE ε4 genotype. As a result, faster cognitive decline was most strongly associated with hypometabolism (posterior cingulate) and smaller hippocampal volume (e.g., Δstory recall: β = +0.43 [p < 0.001] and + 0.37 [p = 0.005], resp.) at baseline. In addition, faster cognitive decline was significantly associated with higher baseline Aβ burden only if SUVR was referenced to the subcortical white matter (e.g., Δstory recall: β = −0.28 [p = 0.020]). Patients with MCI converted to AD dementia at an annual rate of 31%, which could be best predicted by combining neuropsychological testing (visuospatial construction skills) with either MRI-based HV or ¹⁸F-FDG-PET. Combining all three markers resulted in 96% specificity and 92% sensitivity. Neither amyloid-PET nor CSF biomarkers could discriminate short-term converters from non-converters.

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FDG-PET and MRI HV are the strongest predictors of cognitive decline and conversion to AD.

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Combination of visuospatial construction testing with FDG-PET or MRI HV present high predicting power of conversion.

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CSF and amyloid-PET seem less suitable markers of disease progression.

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Increased AV45-PET predicts short-term cognitive decline if SUVR is referenced to WM instead of CB.

Is there a difference in regional read [18F]flutemetamol amyloid patterns between end-of-life subjects and those with amnestic mild cognitive impairment?

PURPOSE

Visual interpretation of PET [¹⁸F]flutemetamol images relies on systematic review of five brain regions and is considered positive when an elevated signal is observed in at least one region. Amnestic mild cognitive impairment (aMCI) is an early clinical presentation of Alzheimer's disease (AD); hence it is of interest to determine if the pattern of visually read regional positivity between end-of-life (EoL) patients with and without dementia and aMCI patients is different.

METHODS

A total of 180 EoL patients with and without dementia (mean age 81 years, range 59 to 95 years) and 232 aMCI patients (mean age 71 years, range 53 to 91 years) were scanned following intravenous administration of 185-370 MBq [¹⁸F]flutemetamol. Images from both studies were read by two groups of five blinded readers who independently classified each of the five regions as either positive or negative. The majority interpretation made by at least three of the five readers was used as the imaging endpoint and compared with a composite standardized uptake value ratio (SUVR) analysis using a predetermined threshold.

RESULTS

Amyloid-positive images from 71 of 106 EoL patients coming to autopsy and from 97 aMCI patients were included. In the images from the EoL patients widespread deposition of amyloid was observed, with 76% of the images positive in all five regions and a further 20% positive in four regions. In the images from the aMCI patients, similar results were observed with 87% of the images positive in five regions and a further 5% positive in four regions. The mean SUVR of these positively read images was 2.24 (range 1.48 to 3.14) and 2.08 (range 1.28 to 3.04) in the autopsy and aMCI groups, respectively. There was 95.3% agreement between the visual reading and SUVR quantitation in the aMCI group and 90.4% agreement in the autopsy group.

CONCLUSION

Patients with aMCI showed a similar distribution of amyloid deposition determined by both visual reading and SUVR to that observed in patients with and without dementia coming to autopsy. Most of the aMCI patients, who are already within the AD continuum, had widespread amyloid deposition in terms of amount and topographical progression. Attempts to observe potential initial signs of amyloid deposition should focus on populations earlier in the dementia spectrum such as patients with subjective cognitive decline or even at-risk subjects with earlier stages of disease.

Diagnostic performance of a fully automated chemiluminescent enzyme immunoassay for Alzheimer's disease diagnosis

The variability of Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers (Aβ42, t-Tau and p-Tau) undermines their full-fledged introduction into routine diagnostics and clinical trials. The introduction of automatic systems can improve the diagnostic performance promoting standardization and reducing the impact of preanalytical and analytical factors. Here we assessed the diagnostic performance of a fully automated chemiluminescent enzyme assay (LUMIPULSE) and compared it with that obtained by using the classical manual enzyme-linked immunosorbent assays (ELISAs). Patients were clinically diagnosed as AD (n = 42) and non-AD (n = 38). Clinical diagnosis was confirmed at follow-up. LUMIPULSE Aβ42 was reduced in AD (969.4 ± 329.6 pg/mL vs. 1625.9 ± 745.9 pg/mL, p <0.001), whereas LUMIPULSE t-Tau was increased in AD (768.2 ± 281.0 pg/mL vs. 337.5 ± 159.1 pg/mL, p < 0.001) compared to non-AD patients. Both LUMIPULSE Aβ42 (AUC = 0.78, spec. = 0.74, sens. = 0.76) and t-Tau (AUC = 0.94, spec. = 0.93, sens. = 0.87) showed good accuracy in distinguish AD from non-AD and a high correlation with the manual ELISAs (r = 0.87, p < 0.001 and r = 0.92, p < 0.001, respectively). LUMIPULSE improves clinical accuracy in AD diagnosis, promoting the use of standardized values for CSF biomarkers with a good correlation with classical manual assays.

Mechanisms of functional compensation, delineated by eigenvector centrality mapping, across the pathophysiological continuum of Alzheimer's disease

Background

Mechanisms of functional compensation throughout the progression of Alzheimer's disease (AD) remain largely underspecified. By investigating functional connectomics in relation to cerebrospinal fluid (CSF) biomarkers across the pathophysiological continuum of AD, we identify disease-stage-specific patterns of functional degradation and functional compensation.

Methods

Data from a sample of 96 participants, comprised of 49 controls, 11 preclinical AD subjects, 21 patients with mild cognitive impairment (MCI) due to AD and 15 patients with mild dementia due to AD, were analyzed. CSF ratio of phosphorylated tau protein over amyloid beta peptide 42 (p-tau/Aβ42) was computed and used as a marker of progression along the AD continuum. Whole-brain, voxel-wise eigenvector centrality mapping (ECM) was computed from resting-state fMRI and regression against p-tau/Aβ42 was performed. Surviving clusters were used as data-derived seeds in functional connectivity analyses and investigated in relation to memory performance scores (delayed free recall and memory alteration) via complementary regression models. To investigate disease-stage-specific effects, the whole-brain connectivity maps of each cluster were compared between progressive groups.

Results

Centrality in BA39-BA19 is negatively correlated with the p-tau/Aβ42 ratio and associated to memory function impairment across the AD continuum. The thalamus, anterior cingulate (ACC), midcingulate (MCC) and posterior cingulate cortex (PCC) show the opposite effect. The MCC shows the highest increase in centrality as memory performance decays. In the asymptomatic preclinical group, MCC shows reduced functional connectivity (FC) with the left hippocampus and stronger FC with the precuneus (PCu). Additionally, BA39-BA19 show reduced FC with the cerebellum, compensated by stronger FC between cerebellum and PCC. In the MCI group, PCC shows reduced FC with PCu, compensated by stronger FC with the left pars orbitalis, insula and temporal pole, as well as by stronger FC of MCC with its anterior and ventral neighboring areas and the cerebellum. In the mild dementia group, extensive functional decoupling occurs across the entire autobiographical memory network and functional resilience ensues in posterior regions and the cerebellum.

Conclusions

Functional decoupling in preclinical AD occurs predominantly in AD-vulnerable regions (e.g. hippocampus, cerebellar lobule VI / Crus I, visual cortex, frontal pole) and coupling between MCC and PCu, as well as between PCC and cerebellum, emerge as intrinsic mechanisms of functional compensation. At the MCI stage, the PCu can no longer compensate for hippocampal decoupling, but the compensatory role of the MCC and PCC ensue into the stage of dementia. These findings shed light on the neural mechanisms of functional compensation across the pathophysiological continuum of AD, highlighting the compensatory roles of several key brain areas.

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BA39-BA19 centrality implicated in Alzheimer's disease.

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Increasing centrality in cingulate and thalamus involved in functional compensation.

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Preclinical functional alterations of hippocampus compensated by precuneus.

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Cerebellar involvement in functional compensation.

Clinical and Biomarker Characteristics According to Clinical Spectrum of Alzheimer's Disease (AD) in the Validation Cohort of Korean Brain Aging Study for the Early Diagnosis and Prediction of AD

We aimed to present the study design of an independent validation cohort from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's disease (AD) (KBASE-V) and to investigate the baseline characteristics of the participants according to the AD clinical spectrum. We recruited 71 cognitively normal (CN) participants, 96 with subjective cognitive decline (SCD), 72 with mild cognitive impairment (MCI), and 56 with AD dementia (ADD). The participants are followed for three years. The Consortium to Establish a Registry for AD scores was significantly different between all of the groups. The logical memory delayed recall scores were significantly different between all groups, except between the MCI and ADD groups. The Mini-Mental State Examination score, hippocampal volume, and cerebrospinal fluid (CSF) amyloid-β42 level were significant difference among the SCD, MCI, and ADD groups. The frequencies of participants with amyloid pathology according to PET or CSF studies were 8.9%, 25.6%, 48.3%, and 90.0% in the CN, SCD, MCI, and ADD groups, respectively. According to ATN classification, A+/T+/N+ or A+/T+/N- was observed in 0%, 15.5%, 31.0%, and 78.3% in the CN, SCD, MCI, and ADD groups, respectively. The KBASE-V showed a clear difference according to the AD clinical spectrum in neuropsychological tests and AD biomarkers.

Amyloid PET and cognitive decline in cognitively normal individuals: the SCIENCe project

We examined the relationships between amyloid-β PET and concurrent and longitudinal cognitive performance in 107 cognitively normal individuals with subjective cognitive decline (age: 64 ± 8 years, 44% female, Mini-Mental State Examination score 29 ± 1). All underwent 90-minute dynamic [¹⁸F]florbetapir PET scanning and longitudinal neuropsychological tests with a mean follow-up of 3.4 ± 3.0 years. Receptor parametric mapping was used to calculate [¹⁸F]florbetapir binding potential (BP_ND), and we performed linear mixed models to assess the relationships between global [¹⁸F]florbetapir BP_ND and neuropsychological performance. Higher [¹⁸F]florbetapir BP_ND was related to lower concurrent Mini-Mental State Examination (β ± SE: -1.69 ± 0.63 p < 0.01) and to steeper rate of decline on tasks capturing memory (Rey Auditory Verbal Learning Task immediate [β ± SE -1.81 ± 0.81, p < 0.05] and delayed recall [β ± SE -1.19 ± 0.34, p < 0.01]), attention/executive functions (Stroop II [color] [β ± SE -0.02 ± 0.01, p < 0.05], Stroop III [word-color] [β ± SE -0.03 ± 0.02, p < 0.05]), and language (category fluency [β ± SE -0.04 ± 0.01, p < 0.01]). These findings suggest that higher amyloid-β load in cognitively normal individuals with subjective cognitive decline from a memory clinic is associated with lower concurrent global cognition and with faster rate of decline in a variety of cognitive domains.

Association of Glucose Fluctuations with Sarcopenia in Older Adults with Type 2 Diabetes Mellitus

Type 2 diabetes mellitus accelerates loss of muscle mass and strength. Patients with Alzheimer’s disease (AD) also show these conditions, even in the early stages of AD. The mechanism linking glucose management with these muscle changes has not been elucidated but has implications for clarifying these associations and developing preventive strategies to maintain functional capacity. This study included 69 type 2 diabetes patients with a diagnosis of cognitive impairment (n = 32) and patients with normal cognition (n = 37). We investigated the prevalence of sarcopenia in diabetes patients with and without cognitive impairment and examined the association of glucose alterations with sarcopenia. Daily glucose levels were evaluated using self-monitoring of blood glucose, and we focused on the effects of glucose fluctuations, postprandial hyperglycemia, and the frequency of hypoglycemia on sarcopenia. Diabetes patients with cognitive impairment displayed a high prevalence of sarcopenia, and glucose fluctuations were independently associated with sarcopenia, even after adjusting for glycated hemoglobin A1c (HbA1c) levels and associated factors. In particular, glucose fluctuations were significantly associated with a low muscle mass, low grip strength, and slow walking speed. Our observation suggests the importance of glucose management by considering glucose fluctuations to prevent the development of disability.

ATN profiles among cognitively normal individuals and longitudinal cognitive outcomes

OBJECTIVE

To examine the long-term cognitive trajectories of individuals with normal cognition at baseline and distinct amyloid/tau/neurodegeneration (ATN) profiles.

METHODS

Pooling data across 4 cohort studies, 814 cognitively normal participants (mean baseline age = 59.6 years) were classified into 8 ATN groups using baseline CSF levels of β-amyloid 1-42 as a measure of amyloid (A), phosphorylated tau 181 as a measure of tau (T), and total tau as a measure of neurodegeneration (N). Cognitive performance was measured using a previously validated global factor score and with the Mini-Mental State Examination. We compared the cognitive trajectories across groups using growth curve models (mean follow-up time = 7 years).

RESULTS

Using different model formulations and cut points for determining biomarker abnormality, only the group with abnormal levels of amyloid, tau, and neurodegeneration (A+T+N+) showed consistently greater cognitive decline than the group with normal levels of all biomarkers (A-T-N-). Replicating prior findings using the 2011 National Institute on Aging-Alzheimer's Association/suspected non-Alzheimer disease pathophysiology schema, only individuals with abnormal levels of both amyloid and phosphorylated tau 181 or total tau (stage 2) showed greater cognitive decline than those with normal biomarker levels (stage 0).

CONCLUSION

The results are consistent with the hypothesis that both elevated brain amyloid and neurofibrillary tangles are necessary to observe accelerated neurodegeneration, which in turn leads to cognitive decline.

[Guideline-conform exact diagnosis and coding of dementia]

All of the currently available guidelines specify a two-stage procedure. The first stage entails performing a comprehensive description, diagnosis and confirmation of the dementia syndrome. The second stage involves the precise etiological classification. Alzheimer's disease represents the most common cause followed by vascular dementia and Parkinson's disease dementia, Lewy body dementia, frontotemporal lobar degeneration and others. Dementia encompasses a variety of underlying conditions. This review gives an overview of the clinically oriented diagnosis according to the updated S3 guidelines in Germany.

Revealing heterogeneity of brain imaging phenotypes in Alzheimer's disease based on unsupervised clustering of blood marker profiles

Alzheimer's disease (AD) affects millions of people and is a major rising problem in health care worldwide. Recent research suggests that AD could have different subtypes, presenting differences in how the disease develops. Characterizing those subtypes could be key to deepen the understanding of this complex disease. In this paper, we used a multivariate, non-supervised clustering method over blood-based markers to find subgroups of patients defined by distinctive blood marker profiles. Our analysis on ADNI database identified 4 possible subgroups, each with a different blood profile. More importantly, we show that subgroups with different profiles have a different relationship between brain phenotypes detected in magnetic resonance imaging and disease condition.

Comparative evaluation of two immunoassays for cerebrospinal fluid β-Amyloid1-42 measurement

AIM OF THE STUDY

Beta-Amyloid 1-42 peptide (βA42) is a cerebro-spinal fluid (CSF) biomarker, key element of the NIA Alzheimer's disease diagnostic criteria. The enzyme-linked immunosorbent assay (ELISA) has been the mainstay method for βA42 measurement on cerebrospinal fluid (CSF). Recently, a new βA42 measurement method in chemiluminescence enzyme immunoassay (CLEIA) is available on Lumipulse G 600 II automatic platform. The aim of the work was to evaluate the concordance of the ELISA and the new method (CLEIA) in the CSF βA42 levels measurement.

MATERIALS AND METHODS

CSF βA42 levels were assayed in 49 samples using the ELISA method (Innotest β- amyloid 1-42, Fujirebio Europe N.V., Gent, Belgium) and CLEIA method on Lumipulse G600II fully automatic platform (Lumipulse G β- amyloid 1-42, Fujirebio Europe N.V., Gent, Belgium). We compared values of the two methods using acceptability interval based on Inherent Combined Imprecision (ICI), the Passing-Bablok regression analysis, the Pearson correlation coefficient (r) and the Bland-Altman plot.

RESULTS

The analysis of the ICI showed that the two methods differ substantially. The regression equation (y = -103.04 + 1.52×) highlighted the presence of proportional systematic difference, without significant deviation from linearity (p = .42). The Pearson correlation coefficient was 0.826. The Bland-Altman plot analysis showed a significant systematic difference in the two methods: ELISA measurements were in average -27.06% (95% CI -31.89 to -22.23%) lower compared to CLEIA ones.

CONCLUSIONS

Our study highlighted a difference between the two methods. Therefore, the cut-off for the normal levels of βA42 should be reviewed in the laboratory report.

Alzheimer's Disease Diagnosis Based on Cortical and Subcortical Features

Alzheimer's disease (AD) is a common neurodegenerative disease with an often seen prodromal mild cognitive impairment (MCI) phase, where memory loss is the main complaint progressively worsening with behavior issues and poor self-care. However, not all patients clinically diagnosed with MCI progress to the AD. Currently, several high-dimensional classification techniques have been developed to automatically distinguish among AD, MCI, and healthy control (HC) patients based on T1-weighted MRI. However, these method features are based on wavelets, contourlets, gray-level co-occurrence matrix, etc., rather than using clinical features which helps doctors to understand the pathological mechanism of the AD. In this study, a new approach is proposed using cortical thickness and subcortical volume for distinguishing binary and tertiary classification of the National Research Center for Dementia dataset (NRCD), which consists of 326 subjects. Five classification experiments are performed: binary classification, i.e., AD vs HC, HC vs mAD (MCI due to the AD), and mAD vs aAD (asymptomatic AD), and tertiary classification, i.e., AD vs HC vs mAD and AD vs HC vs aAD using cortical and subcortical features. Datasets were divided in a 70/30 ratio, and later, 70% were used for training and the remaining 30% were used to get an unbiased estimation performance of the suggested methods. For dimensionality reduction purpose, principal component analysis (PCA) was used. After that, the output of PCA was passed to various types of classifiers, namely, softmax, support vector machine (SVM), k-nearest neighbors, and naïve Bayes (NB) to check the performance of the model. Experiments on the NRCD dataset demonstrated that the softmax classifier is best suited for the AD vs HC classification with an F1 score of 99.06, whereas for other groups, the SVM classifier is best suited for the HC vs mAD, mAD vs aAD, and AD vs HC vs mAD classifications with the F1 scores being 99.51, 97.5, and 99.99, respectively. In addition, for the AD vs HC vs aAD classification, NB performed well with an F1 score of 95.88. In addition, to check our proposed model efficiency, we have also used the OASIS dataset for comparing with 9 state-of-the-art methods.

What are we trying to prevent in Alzheimer disease?

Within aging societies, the number of individuals suffering from Alzheimer disease (AD) is constistently increasing. This is paralleled by intense research aimed at improving treatment options and potentially even fostering effective prevention. The discussion on relevant outcomes of such interventions is ongoing. Here, different types of currently applied outcomes in the treatment of AD at the dementia stage, but also at the pre-dementia stages of mild cognitive impairment (MCI) and asymptomatic preclinical AD are discussed. Regulatory agencies require effects on the clinical measures of cognition and function. In novel disease-modifying therapy trials, biological markers are used as secondary and exploratory outcomes. Additional outcomes of great relevance for the individual patients are neuropsychiatric symptoms, quality of life, and goal attainment. In addition, costs and cost-benefit ratios are of interest for the reimbursement of interventions.

Psychosis in neurodegenerative disorders: recent developments

PURPOSE OF REVIEW

This review presents the latest developments covered in the literature regarding psychosis in neurodegenerative disorders and discusses possible future research directions.

RECENT FINDINGS

Recent findings in the field of psychosis and neurodegenerative disorders revolve around four main themes. The first theme is the impact of sex on the expression of psychosis in neurodegenerative disorders. The second theme focuses on the relationship between psychosis and neurodegenerative disease biomarkers. The third concerns how psychotic symptoms in neurodegenerative disorders may share common mechanisms with other primary psychotic disorders such as schizophrenia. Finally, there have been some promising developments in the area of therapeutics to treat dementia-related psychosis involving both established and novel treatments.

SUMMARY

New findings in the field of neurodegeneration and psychosis parallel new directions in the field of neurodegeneration in general. More specifically, we have seen a shift in focus to issues highlighting the role of sex, biomarkers, translation to other disorders, and therapeutics.

MicroRNAs in Alzheimer's Disease

Alzheimer’s disease (AD) is a progressive and devastating neurodegenerative disorder. It is the leading cause of dementia in the world’s rapidly growing aging population. The characteristics of AD are memory loss and cognitive impairment, meaning patients cannot carry out their daily activities independently. The increase of AD cases poses heavy burdens on families, society and the economy. Despite frequent efforts being made to research the etiology of AD, the causes of AD remain unknown, and no curative treatments are available yet. The pathological hallmarks of AD are amyloid plaques and neurofibrillary tangles in the brain. MicroRNAs are endogenous ∼22 nucleotides non-coding RNAs that could regulate gene expression at a post-transcriptional level by transcript degradation or translation repression. MicroRNAs are involved in many biological processes and diseases, particularly multifactorial diseases, providing an excellent tool with which to research the mechanisms of these diseases. AD is a multifactorial disorder, and accumulating evidence shows that microRNAs play a critical role in the pathogenesis of AD. In this review, we will highlight the effect of microRNAs in different pathological processes throughout AD progression.

Dementia prevention and reserve against neurodegenerative disease

Similar to other complex disorders, the etiology of Alzheimer disease is multifactorial and characterized by an interplay of biological and environmental risk and protective factors. Potentially modifiable risk factors have emerged from epidemiological research and strategies to prevent neurodegeneration and dementia are currently being tested, including multimodal interventions aiming to reduce several risk factors at once. The concept of reserve was developed based on the observation that certain individual characteristics, such as life experiences, lifestyles, and neurobiological parameters, are associated with a higher resilience against neurodegeneration and its symptoms. Coordinated research is required to maximize the use of available human and financial resources to better understand the underlying neurobiological mechanisms of reserve and to translate research findings into effective public health interventions.

Antidiabetic therapies and Alzheimer disease

Given current lack of therapies for dementia, there is substantial interest in identifying potentially modifiable risk factors. Clarifying the potential of these factors to mitigate risk as well as determining the mechanisms that link these factors to dementia is expected to lead to new approaches for both preventing and treating neurodegenerative diseases such as Alzheimer disease. Modifiable factors include cardiovascular risks as well as related lifestyle-centric factors such as diet and physical activity (reviewed in this issue). Given reports that type 2 diabetes and associated features increase the risk for developing dementia, there has been tremendous interest in exploring whether use of antidiabetic medications may impact the risk of dementia, as well as whether antidiabetic medications could be used to prevent or treat dementia, particularly Alzheimer disease. This review will briefly cover the known links between diabetes and risk for dementia, the state of evidence linking antidiabetic treatments with either protection against dementia or possibly increased risk for cognitive dysfunction, and provide a brief overview of what has been learned from clinical trials testing antidiabetic treatments in Alzheimer disease.

When is Alzheimer's not dementia-Cochrane commentary on The National Institute on Ageing and Alzheimer's Association Research Framework for Alzheimer's Disease

Early 2018 saw the release of new diagnostic guidance on Alzheimer's disease from the National Institute on Ageing and the Alzheimer's Association (NIA-AA). This proposed research framework represents a fundamental change in how we think about Alzheimer's disease, moving from diagnosis based on clinical features to diagnosis based solely on biomarkers. These recommendations are contentious and have important implications for patients, clinicians, policy makers and the pharmaceutical industry. In this commentary, we offer a summary of the NIA-AA research framework. We then focus on five key areas: divorcing neuropathology from the clinical syndrome; the emphasis placed on one dementia subtype; validity of available biomarkers; the changing meaning of the term 'Alzheimer's disease'; and the potential for a research framework to influence clinical practice.

Brief cognitive screening instruments for early detection of Alzheimer's disease: a systematic review

OBJECTIVES

The objective of this systematic review was (1) to give an overview of the available short screening instruments for the early detection of Alzheimer's disease (AD) and (2) to review the psychometric properties of these instruments.

METHODS

First, a systematic search of titles and abstracts of PubMed and Web of Science was conducted between February and July 2015 and updated in April 2016 and May 2018. Only papers written in English or Dutch were considered. All full-text papers about cognitive screening instruments for the early detection of AD were included, resulting in the identification of 38 pencil and paper tests and 12 computer tests. In a second step, the psychometric quality of these instruments was evaluated. Therefore, the same databases were searched again to identify papers that described the psychometric properties of the instruments meanwhile applying diagnostic criteria for the diagnostic groups included.

RESULTS

Out of 1454 papers, 96 clearly discussed the psychometric properties of the instruments. Eighty-nine papers discussed pencil and paper tests of which 80 were validated in a memory clinic setting. Based on the number of studies (31 articles) and the sensitivity (84%) and specificity (74%) values, the Montreal Cognitive Assessment (MoCA) seems to be a promising (pencil and paper) screening test for memory clinic testing as well as for population screening. Regarding computer tests, validation studies were only available for 7 out of 12 tests.

CONCLUSIONS

A large number of screening tests for AD are available. However, most tests are only validated in a memory clinic setting and description of the psychometric properties of the instruments is limited. Especially, computer tests require further research. The MoCA is a promising instrument, but the specificity to detect early AD is rather low.

Translational research on reserve against neurodegenerative disease: consensus report of the International Conference on Cognitive Reserve in the Dementias and the Alzheimer's Association Reserve, Resilience and Protective Factors Professional Interest Area working groups

BACKGROUND

The concept of reserve was established to account for the observation that a given degree of neurodegenerative pathology may result in varying degrees of symptoms in different individuals. There is a large amount of evidence on epidemiological risk and protective factors for neurodegenerative diseases and dementia, yet the biological mechanisms that underpin the protective effects of certain lifestyle and physiological variables remain poorly understood, limiting the development of more effective preventive and treatment strategies. Additionally, different definitions and concepts of reserve exist, which hampers the coordination of research and comparison of results across studies.

DISCUSSION

This paper represents the consensus of a multidisciplinary group of experts from different areas of research related to reserve, including clinical, epidemiological and basic sciences. The consensus was developed during meetings of the working groups of the first International Conference on Cognitive Reserve in the Dementias (24-25 November 2017, Munich, Germany) and the Alzheimer's Association Reserve and Resilience Professional Interest Area (25 July 2018, Chicago, USA). The main objective of the present paper is to develop a translational perspective on putative mechanisms underlying reserve against neurodegenerative disease, combining evidence from epidemiological and clinical studies with knowledge from animal and basic research. The potential brain functional and structural basis of reserve in Alzheimer's disease and other brain disorders are discussed, as well as relevant lifestyle and genetic factors assessed in both humans and animal models.

CONCLUSION

There is an urgent need to advance our concept of reserve from a hypothetical model to a more concrete approach that can be used to improve the development of effective interventions aimed at preventing dementia. Our group recommends agreement on a common dictionary of terms referring to different aspects of reserve, the improvement of opportunities for data sharing across individual cohorts, harmonising research approaches across laboratories and groups to reduce heterogeneity associated with human data, global coordination of clinical trials to more effectively explore whether reducing epidemiological risk factors leads to a reduced burden of neurodegenerative diseases in the population, and an increase in our understanding of the appropriateness of animal models for reserve research.

What matters to people with memory problems, healthy volunteers and health and social care professionals in the context of developing treatment to prevent Alzheimer's dementia? A qualitative study

Background

Alzheimer's disease (AD) is recognized as one of the greatest global public health challenges. There is increasing consensus that optimal disease modification using pharmaceuticals may best be achieved earlier in the disease continuum before symptoms occur. However, more needs to be understood about what outcomes are meaningful to potential participants in clinical trials within this preventative paradigm and how people make trade‐offs between risks and benefits. The Electronic Person‐Specific Outcome Measure (ePSOM) programme is developing an app to capture person‐specific outcomes and preferences in clinical trials.

Objective

As one phase in the ePSOM programme, this study explored what matters when developing new treatments to prevent AD and how trade‐offs are made between risks and benefits, from three perspectives.

Design

Focus groups were conducted with people living with memory problems (n = 21) and healthy volunteers (n = 10), and telephone interviews with health and social care professionals (n = 10). Differences and overlap between the three groups were explored.

Results

Outcomes that matter lie in five key domains in relation to what matters in everyday life: Everyday Functioning; Relationships and Social Connections; Enjoying Life; Sense of Identity; and Alleviating  Symptoms. Insights were gained into the significance of reducing the risk of developing dementia with drugs and the processes of weighing up risks versus benefits.

Discussion and conclusions

The key domains identified are being used to inform the next stage of the ePSOM programme which is to develop a survey to be distributed nationally in the UK to explore these issues further.