Emerging β-amyloid pathology and accelerated cortical atrophy

Voxel-wise insights into early Alzheimer's disease pathology progression: the association with APOE and memory decline

Longitudinal investigation of the Apolipoprotein E (APOE) genotype's impact on Alzheimer's disease (AD) biomarker progression, focusing on amyloid beta (Aβ) accumulation and gray matter (GM) atrophy, integrating cognitive decline and baseline levels. Longitudinal florbetapir-PET and T1-weighted MRI data from 100 cognitively normal (CN) and mild cognitive impaired (MCI) participants both with considerable global Aβ accumulation ("high Aβ accumulators") were analyzed using a voxel-wise approach. Associations of APOE genotype and memory decline with Aβ accumulation and GM atrophy were examined separately for each neuroimaging modality, controlling for baseline Aβ levels and diagnosis. Alternatively, the effect of baseline diagnosis, while controlling for memory decline, was investigated. A multimodal analysis evaluated interactions between genotype, memory decline, and GM atrophy on Aβ accumulation. High Aβ accumulators displayed extensive Aβ pathology predominantly in the medial orbito-frontal cortex, cingulate cortex, and precuneus, along with GM atrophy in temporal, occipital, orbito-frontal, and parietal areas. ɛ4 carriers with memory decline exhibited greater Aβ accumulation and GM atrophy in selective regions compared to non-carriers with memory decline, while no genotype difference was observed in individuals without decline. No interaction effect was observed for MCI diagnosis. Regional associations between the two biomarkers were similarly dependent on genotype and memory decline. ɛ4 carriers exhibiting memory decline present an accelerated neurobiological pattern at predementia stages, supporting early ɛ4 carrier monitoring and interventions in this at-risk group. Importantly, memory decline might be more informative than MCI regarding AD pathology progression emphasizing the importance of repeated cognitive assessments.

Amyloid is associated with accelerated atrophy in cognitively unimpaired individuals

INTRODUCTION

This study examined the association of longitudinal atrophy with baseline cerebrospinal fluid (CSF) amyloid beta (Aβ, A) and phosphorylated tau (p-tau, T) biomarkers (Aβ42/40, p-tau181) in 406 cognitively unimpaired (CU) individuals (6.670 years of follow-up on average, up to 13 imaging visits) to assess whether A+ is associated with Alzheimer's disease-like atrophy and whether this depends on p-tau181 levels.

METHODS

An A-T- CU group free from abnormal neurodegeneration (N) was identified using a robust normative approach and used to model normal age-related atrophy via z-scoring. Linear mixed-effects models tested differences in longitudinal atrophy between A+ and A-T-N- individuals and between A/T subgroups.

RESULTS

A+ was associated with worse atrophy within and beyond the medial temporal lobe, even at low levels of p-tau181.

DISCUSSION

Neurodegeneration likely begins soon after the onset of abnormal Aβ pathology. Clinical intervention at the earliest signs of Aβ pathology may be needed to mitigate further neurodegeneration.

Highlights

An A-T-N- control group was identified using a robust normative approachA+ was associated with accelerated atrophy in cognitively unimpaired individualsAtrophy was observed even at low p-tau181 levels.

The relationship between hippocampal changes in healthy aging and Alzheimer's disease: a systematic literature review

Introduction

Neurobiological changes in the hippocampus are a common consequence of aging. However, there are differences in the rate of decline and overall volume loss in people with no cognitive impairment compared to those with mild cognitive impairment (MCI) and Alzheimer's disease (AD). This systematic literature review was conducted to determine the relationship between hippocampal atrophy and changes in hippocampal volume in the non-cognitively impaired brain and those with MCI or AD.

Methods

This systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The PubMed database was searched up to September 15, 2022, for longitudinal magnetic resonance imaging studies reporting hippocampal atrophy or volume change in cognitively normal aging individuals and patients with MCI and/or AD. Study selection was divided into two steps: (1) identification and retrieval of relevant studies; (2) screening the studies by (a) title/abstract and (b) full text. Two teams, each consisting of two independent reviewers, determined whether the publications met the inclusion criteria for the systematic review. An evidence table was populated with data extracted from eligible publications and inclusion in the final systematic review was confirmed.

Results

The systematic search identified 357 publications that were initially screened by title/abstract, of which, 115 publications were retrieved and reviewed by full text for eligibility. Seventeen publications met the eligibility criteria; however, during data extraction, two studies were determined to not meet the inclusion criteria and were excluded. The remaining 15 studies were included in the systematic review. Overall, the results of these studies demonstrated that the hippocampus and hippocampal subfields change over time, with both decreased hippocampal volume and increased rate of hippocampal atrophy observed. Hippocampal changes in AD were observed to be greater than hippocampal changes in MCI, and changes in MCI were observed to be greater than those in normal aging populations.

Conclusion

Published literature suggests that the rate of hippocampal decline and extent of loss is on a continuum that begins in people without cognitive impairment and continues to MCI and AD, and that differences between no cognitive impairment, MCI, and AD are quantitative rather than qualitative.

Diverging Relationships among Amyloid, Tau, and Brain Atrophy in Early-Onset and Late-Onset Alzheimer's Disease

PURPOSE

Alzheimer's disease (AD) dementia may not be a single disease entity. Early-onset AD (EOAD) and late-onset AD (LOAD) have been united under the same eponym of AD until now, but disentangling the heterogeneity according to the age of sonset has been a major tenet in the field of AD research.

MATERIALS AND METHODS

Ninety-nine patients with AD (EOAD, n=54; LOAD, n=45) and 66 cognitively normal controls completed both [18F]THK5351 and [18F]flutemetamol (FLUTE) positron emission tomography scans along with structural magnetic resonance imaging and detailed neuropsychological tests.

RESULTS

EOAD patients had higher THK retention in the precuneus, parietal, and frontal lobe, while LOAD patients had higher THK retention in the medial temporal lobe. Intravoxel correlation analyses revealed that EOAD presented narrower territory of local FLUTE-THK correlation, while LOAD presented broader territory of correlation extending to overall parieto-occipito-temporal regions. EOAD patients had broader brain areas which showed significant negative correlations between cortical thickness and THK retention, whereas in LOAD, only limited brain areas showed significant correlation with THK retention. In EOAD, most of the cognitive test results were correlated with THK retention. However, a few cognitive test results were correlated with THK retention in LOAD.

CONCLUSION

LOAD seemed to show gradual increase in tau and amyloid, and those two pathologies have association to each other. On the other hand, in EOAD, tau and amyloid may develop more abruptly and independently. These findings suggest LOAD and EOAD may have different courses of pathomechanism.

Subjective Cognitive Impairment Can Be Detected from the Decline of Complex Cognition: Findings from the Examination of Remedes 4 Alzheimer's (R4Alz) Structural Validity

R4Alz is utilized for the early detection of minor neurocognitive disorders. It was designed to assess three main dimensions of cognitive-control abilities: working-memory capacity, attentional control, and executive functioning.

OBJECTIVES

To reveal the cognitive-control dimensions that can differentiate between adults and older adults with healthy cognition, people with subjective cognitive impairment, and people diagnosed with mild cognitive impairment by examining the factorial structure of the R4Alz tool.

METHODS

The study comprised 404 participants: (a) healthy adults (n = 192), (b) healthy older adults (n = 29), (c) people with SCI (n = 74), and (d) people diagnosed with MCI (n = 109). The R4Alz battery was administered to all participants, including tests that assess short-term memory storage, information processing, information updating in working memory, and selective, sustained and divided attention), task/rule-switching, inhibitory control, and cognitive flexibility.

RESULTS

A two-factorial structural model was confirmed for R4Alz, with the first factor representing "fluid intelligence (FI)" and the second factor reflecting "executive functions (EF)". Both FI and EFs discriminate among all groups.

CONCLUSIONS

The R4Alz battery presents sound construct validity, evaluating abilities in FI and EF. Both abilities can differentiate very early cognitive impairment (SCI) from healthy cognitive aging and MCI.

Detecting Amyloid Positivity Using Morphometric Magnetic Resonance Imaging

Background

Early detection of amyloid-β (Aβ) positivity is essential for an accurate diagnosis and treatment of Alzheimer's disease (AD), but it is currently costly and/or invasive.

Objective

We aimed to classify Aβ positivity (Aβ+) using morphometric features from magnetic resonance imaging (MRI), a more accessible and non-invasive technique, in two clinical population scenarios: one containing AD, mild cognitive impairment (MCI) and cognitively normal (CN) subjects, and another only cognitively impaired subjects (AD and MCI).

Methods

Demographic, cognitive (Mini-Mental State Examination [MMSE] scores), regional morphometry MRI (volumes, areas, and thicknesses), and derived morphometric graph theory (GT) features from all subjects (302 Aβ+, age: 73.3±7.2, 150 male; 246 Aβ-, age: 71.1±7.1, 131 male) were combined in different feature sets. We implemented a machine learning workflow to find the best Aβ+ classification model.

Results

In an AD+MCI+CN population scenario, the best-performing model selected 120 features (107 GT features, 12 regional morphometric features and the MMSE total score) and achieved a negative predictive value (NPVadj) of 68.4%, and a balanced accuracy (BAC) of 66.9%. In a AD+MCI scenario, the best model obtained NPVadj of 71.6%, and BAC of 70.7%, using 180 regional morphometric features (98 volumes, 52 areas and 29 thicknesses from temporal, parietal, and frontal brain regions).

Conclusions

Although with currently limited clinical applicability, regional MRI morphometric features have clinical usefulness potential for detecting Aβ status, which may be augmented by a combination with cognitive data when cognitively normal subjects make up a substantial part of the population presenting for diagnosis.

Respective influence of beta-amyloid and APOE ε4 genotype on medial temporal lobe subregions in cognitively unimpaired older adults

Medial temporal lobe (MTL) subregions are differentially affected in Alzheimer's disease (AD), with a specific involvement of the entorhinal cortex (ERC), perirhinal cortex and hippocampal cornu ammonis (CA)1. While amyloid (Aβ) and APOEε4 are respectively the first molecular change and the main genetic risk factor in AD, their links with MTL atrophy remain relatively unclear. Our aim was to uncover these effects using baseline data from 130 participants included in the Age-Well study, for whom ultra-high-resolution structural MRI, amyloid-PET and APOEε4 genotype were available. No volume differences were observed between Aβ + (n = 24) and Aβ- (n = 103), nor between APOE4+ (n = 35) and APOE4- (n = 95) participants. However, our analyses showed that both Aβ and APOEε4 status interacted with age on CA1, which is known to be specifically atrophied in early AD. In addition, APOEε4 status moderated the effects of age on other subregions (subiculum, ERC), suggesting a more important contribution of APOEε4 than Aβ to MTL atrophy in cognitively unimpaired population. These results are crucial to develop MRI-based biomarkers to detect early AD.

Directed Functional Brain Connectivity is Altered in Sub-threshold Amyloid-β Accumulation in Cognitively Normal Individuals

Several studies have shown that amyloid-β (Aβ) deposition below the clinically relevant cut-off levels is associated with subtle changes in cognitive function and increases the risk of developing future Alzheimer's disease (AD). Although functional MRI is sensitive to early alterations occurring during AD, sub-threshold changes in Aβ levels have not been linked to functional connectivity measures. This study aimed to apply directed functional connectivity to identify early changes in network function in cognitively unimpaired participants who, at baseline, exhibit Aβ accumulation below the clinically relevant threshold. To this end, we analyzed baseline functional MRI data from 113 cognitively unimpaired participants of the Alzheimer's Disease Neuroimaging Initiative cohort who underwent at least one 18F-florbetapir-PET after the baseline scan. Using the longitudinal PET data, we classified these participants as Aβ negative (Aβ-) non-accumulators (n = 46) and Aβ- accumulators (n = 31). We also included 36 individuals who were amyloid-positive (Aβ+) at baseline and continued to accumulate Aβ (Aβ+ accumulators). For each participant, we calculated whole-brain directed functional connectivity networks using our own anti-symmetric correlation method and evaluated their global and nodal properties using measures of network segregation (clustering coefficient) and integration (global efficiency). When compared to Aβ- non-accumulators, the Aβ- accumulators showed lower global clustering coefficient. Moreover, the Aβ+ accumulator group exhibited reduced global efficiency and clustering coefficient, which at the nodal level mainly affected the superior frontal gyrus, anterior cingulate cortex, and caudate nucleus. In Aβ- accumulators, global measures were associated with lower baseline regional PET uptake values, as well as higher scores on the Modified Preclinical Alzheimer Cognitive Composite. Our findings indicate that directed connectivity network properties are sensitive to subtle changes occurring in individuals who have not yet reached the threshold for Aβ positivity, which makes them a potentially viable marker to detect negative downstream effects of very early Aβ pathology.

R4Alz-Revised: A Tool Able to Strongly Discriminate 'Subjective Cognitive Decline' from Healthy Cognition and 'Minor Neurocognitive Disorder'

BACKGROUND

The diagnosis of the minor neurocognitive diseases in the clinical course of dementia before the clinical symptoms' appearance is the holy grail of neuropsychological research. The R4Alz battery is a novel and valid tool that was designed to assess cognitive control in people with minor cognitive disorders. The aim of the current study is the R4Alz battery's extension (namely R4Alz-R), enhanced by the design and administration of extra episodic memory tasks, as well as extra cognitive control tasks, towards improving the overall R4Alz discriminant validity.

METHODS

The study comprised 80 people: (a) 20 Healthy adults (HC), (b) 29 people with Subjective Cognitive Decline (SCD), and (c) 31 people with Mild Cognitive Impairment (MCI). The groups differed in age and educational level.

RESULTS

Updating, inhibition, attention switching, and cognitive flexibility tasks discriminated SCD from HC (p ≤ 0.003). Updating, switching, cognitive flexibility, and episodic memory tasks discriminated SCD from MCI (p ≤ 0.001). All the R4Alz-R's tasks discriminated HC from MCI (p ≤ 0.001). The R4Alz-R was free of age and educational level effects. The battery discriminated perfectly SCD from HC and HC from MCI (100% sensitivity-95% specificity and 100% sensitivity-90% specificity, respectively), whilst it discriminated excellently SCD from MCI (90.3% sensitivity-82.8% specificity).

CONCLUSION

SCD seems to be stage a of neurodegeneration since it can be objectively evaluated via the R4Alz-R battery, which seems to be a useful tool for early diagnosis.

Impact of Amyloid Pathology in Mild Cognitive Impairment Subjects: The Longitudinal Cognition and Surface Morphometry Data

The amyloid framework forms the central medical theory related to Alzheimer disease (AD), and the in vivo demonstration of amyloid positivity is essential for diagnosing AD. On the basis of a longitudinal cohort design, the study investigated clinical progressive patterns by obtaining cognitive and structural measurements from a group of patients with amnestic mild cognitive impairment (MCI); the measurements were classified by the positivity (Aβ+) or absence (Aβ-) of the amyloid biomarker. We enrolled 185 patients (64 controls, 121 patients with MCI). The patients with MCI were classified into two groups on the basis of their [¹⁸F]flubetaben or [¹⁸F]florbetapir amyloid positron-emission tomography scan (Aβ+ vs. Aβ-, 67 vs. 54 patients) results. Data from annual cognitive measurements and three-dimensional T1 magnetic resonance imaging scans were used for between-group comparisons. To obtain longitudinal cognitive test scores, generalized estimating equations were applied. A linear mixed effects model was used to compare the time effect of cortical thickness degeneration. The cognitive decline trajectory of the Aβ+ group was obvious, whereas the Aβ- and control groups did not exhibit a noticeable decline over time. The group effects of cortical thickness indicated decreased entorhinal cortex in the Aβ+ group and supramarginal gyrus in the Aβ- group. The topology of neurodegeneration in the Aβ- group was emphasized in posterior cortical regions. A comparison of the changes in the Aβ+ and Aβ- groups over time revealed a higher rate of cortical thickness decline in the Aβ+ group than in the Aβ- group in the default mode network. The Aβ+ and Aβ- groups experienced different APOE ε4 effects. For cortical-cognitive correlations, the regions associated with cognitive decline in the Aβ+ group were mainly localized in the perisylvian and anterior cingulate regions. By contrast, the degenerative topography of Aβ- MCI was scattered. The memory learning curves, cognitive decline patterns, and cortical degeneration topographies of the two MCI groups were revealed to be different, suggesting a difference in pathophysiology. Longitudinal analysis may help to differentiate between these two MCI groups if biomarker access is unavailable in clinical settings.

Impact of APOE ε4 Carrier Status on Associations Between Subthreshold, Positive Amyloid-β Deposition, Brain Function, and Cognitive Performance in Cognitively Normal Older Adults: A Prospective Study

Background

A growing body of evidence suggests a deteriorating effect of subthreshold amyloid-beta (Aβ) accumulation on cognition before the onset of clinical symptoms of Alzheimer's disease (AD). Despite the association between the Aβ-dependent pathway and the APOE ε4 allele, the impact of this allele on the progression from the subthreshold Aβ deposits to cognitive function impairment is unclear. Furthermore, the comparative analysis of positive Aβ accumulation in the preclinical phase is lacking.

Objective

This study aimed to explore the differential effect of the APOE ε4 carrier status on the association between Aβ deposition, resting-state brain function, and cognitive performance in cognitively normal (CN) older adults, depending on the Aβ burden status.

Methods

One hundred and eighty-two older CN adults underwent resting-state functional magnetic resonance imaging, [18F] flutemetamol (FMM) positron emission tomography, a neuropsychological battery, and APOE genotyping. We evaluated the resting-state brain function by measuring the local and remote functional connectivity (FC) and measured the remote FC in the default-mode network (DMN), central-executive network (CEN), and salience network (SN). In addition, the subjects were dichotomized into those with subthreshold and positive Aβ deposits using a neocortical standardized uptake value ratio with the cut-off value of 0.62, which was calculated with respect to the pons.

Results

The present result showed that APOE ε4 carrier status moderated the relationship between Aβ deposition, local and remote resting-state brain function, and cognitive performance in each CN subthreshold and positive Aβ group. We observed the following: (i) the APOE ε4 carrier status-Aβ deposition and APOE ε4 carrier status-local FC interaction for the executive and memory function; (ii) the APOE ε4 carrier status-regional Aβ accumulation interaction for the local FC; and (iv) the APOE ε4 carrier status-local FC interaction for the remote inter-network FC between the DMN and CEN, contributing higher cognitive performance in the APOE ε4 carrier with higher inter-network FC. Finally, these results were modulated according to Aβ positivity.

Conclusion

This study is the first attempt to thoroughly examine the influence of the APOE ε4 carrier status from the subthreshold to positive Aβ accumulation during the preclinical phase.

Common variants contribute to intrinsic human brain functional networks

The human brain forms functional networks of correlated activity, which have been linked with both cognitive and clinical outcomes. However, the genetic variants affecting brain function are largely unknown. Here, we used resting-state functional magnetic resonance images from 47,276 individuals to discover and validate common genetic variants influencing intrinsic brain activity. We identified 45 new genetic regions associated with brain functional signatures (P < 2.8 × 10-11), including associations to the central executive, default mode, and salience networks involved in the triple-network model of psychopathology. A number of brain activity-associated loci colocalized with brain disorders (e.g., the APOE ε4 locus with Alzheimer's disease). Variation in brain function was genetically correlated with brain disorders, such as major depressive disorder and schizophrenia. Together, our study provides a step forward in understanding the genetic architecture of brain functional networks and their genetic links to brain-related complex traits and disorders.

AMYQ: An index to standardize quantitative amyloid load across PET tracers

INTRODUCTION

Positron emission tomography (PET) amyloid quantification methods require magnetic resonance imaging (MRI) for spatial registration and a priori reference region to scale the images. Furthermore, different tracers have distinct thresholds for positivity. We propose the AMYQ index, a new measure of amyloid burden, to overcome these limitations.

METHODS

We selected 18F-amyloid scans from ADNI and Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) with the corresponding T1-MRI. A subset also had neuropathological data. PET images were normalized, and the AMYQ was calculated based on an adaptive template. We compared AMYQ with the Centiloid scale on clinical and neuropathological diagnostic performance.

RESULTS

AMYQ was related with amyloid neuropathological burden and had excellent diagnostic performance to discriminate controls from patients with Alzheimer's disease (AD) (area under the curve [AUC] = 0.86). AMYQ had a high agreement with the Centiloid scale (intraclass correlation coefficient [ICC] = 0.88) and AUC between 0.94 and 0.99 to discriminate PET positivity when using different Centiloid cutoffs.

DISCUSSION

AMYQ is a new MRI-independent index for standardizing and quantifying amyloid load across tracers.

Insights into the Pathophysiology of Psychiatric Symptoms in Central Nervous System Disorders: Implications for Early and Differential Diagnosis

Different psychopathological manifestations, such as affective, psychotic, obsessive-compulsive symptoms, and impulse control disturbances, may occur in most central nervous system (CNS) disorders including neurodegenerative and neuroinflammatory diseases. Psychiatric symptoms often represent the clinical onset of such disorders, thus potentially leading to misdiagnosis, delay in treatment, and a worse outcome. In this review, psychiatric symptoms observed along the course of several neurological diseases, namely Alzheimer’s disease, fronto-temporal dementia, Parkinson’s disease, Huntington’s disease, and multiple sclerosis, are discussed, as well as the involved brain circuits and molecular/synaptic alterations. Special attention has been paid to the emerging role of fluid biomarkers in early detection of these neurodegenerative diseases. The frequent occurrence of psychiatric symptoms in neurological diseases, even as the first clinical manifestations, should prompt neurologists and psychiatrists to share a common clinico-biological background and a coordinated diagnostic approach.

Spatial patterns of correlation between cortical amyloid and cortical thickness in a tertiary clinical population with memory deficit

To estimate regional Alzheimer disease (AD) pathology burden clinically, analysis methods that enable tracking brain amyloid or tau positron emission tomography (PET) with magnetic resonance imaging (MRI) measures are needed. We therefore developed a robust MRI analysis method to identify brain regions that correlate linearly with regional amyloid burden in congruent PET images. This method was designed to reduce data variance and improve the sensitivity of the detection of cortical thickness-amyloid correlation by using whole brain modeling, nonlinear image coregistration, and partial volume correction. Using this method, a cross-sectional analysis of 75 tertiary memory clinic AD patients was performed to test our hypothesis that regional amyloid burden and cortical thickness are inversely correlated in medial temporal neocortical regions. Medial temporal cortical thicknesses were not correlated with their regional amyloid burden, whereas cortical thicknesses in the lateral temporal, lateral parietal, and frontal regions were inversely correlated with amyloid burden. This study demonstrates the robustness of our technique combining whole brain modeling, nonlinear image coregistration, and partial volume correction to track the differential correlation between regional amyloid burden and cortical thinning in specific brain regions. This method could be used with amyloid and tau PET to assess corresponding cortical thickness changes.

Amyloid-β Positivity Predicts Cognitive Decline but Cognition Predicts Progression to Amyloid-β Positivity

BACKGROUND

Stage 1 of the National Institute on Aging-Alzheimer's Association's proposed Alzheimer's disease continuum is defined as amyloid-β (Aβ) positive but cognitively normal. Identifying at-risk individuals before Aβ reaches pathological levels could have great benefits for early intervention. Although Aβ levels become abnormal long before severe cognitive impairments appear, increasing evidence suggests that subtle cognitive changes may begin early, potentially before Aβ surpasses the threshold for abnormality. We examined whether baseline cognitive performance would predict progression from normal to abnormal levels of Aβ.

METHODS

We examined the association of baseline cognitive composites (Preclinical Alzheimer Cognitive Composite, Alzheimer's Disease Neuroimaging Initiative (ADNI) memory factor composite) with progression to Aβ positivity in 292 nondemented, Aβ-negative ADNI participants. Additional analyses included continuous cerebrospinal fluid biomarker levels to examine the effects of subthreshold pathology.

RESULTS

Forty participants progressed to Aβ positivity during follow-up. Poorer baseline performance on both cognitive measures was significantly associated with increased odds of progression. More abnormal levels of baseline cerebrospinal fluid phosphorylated tau and subthreshold Aβ were associated with increased odds of progression to Aβ positivity. Nevertheless, baseline ADNI memory factor composite performance predicted progression even after controlling for baseline biomarker levels and APOE genotype (Preclinical Alzheimer Cognitive Composite was trend level). Survival analyses were largely consistent: controlling for baseline biomarker levels, baseline Preclinical Alzheimer Cognitive Composite still significantly predicted progression time to Aβ positivity (ADNI memory factor composite was trend level).

CONCLUSIONS

The possibility of intervening before Aβ reaches pathological levels is of obvious benefit. Low-cost, noninvasive cognitive measures can be informative for determining who is likely to progress to Aβ positivity, even after accounting for baseline subthreshold biomarker levels.

Prediction of rapid amyloid and phosphorylated‐Tau accumulation in cognitively healthy individuals

Objective

To test the hypothesis that among cognitively healthy individuals, distinct groups exist in terms of amyloid and phosphorylated-tau accumulation rates; that if rapid accumulator groups exist, their membership can be predicted by Alzheimer's disease (AD) risk factors, and that time points of significant increase in AD protein accumulation will be evident.

Methods

The analysis reports data from 263 individuals from the BIOCARD and 184 individuals from the Baltimore Longitudinal Study of Aging with repeated cerebrospinal fluid (CSF) and positron emission tomography (PET) sampling, respectively. We used latent class mixed-effect models to identify distinct classes of amyloid (CSF and PET) and p-Tau (CSF) accumulation rates and generalized additive modeling to investigate non-linear changes to AD biomarkers.

Results

For both amyloid and p-Tau latent class models we confirmed the existence of two separate classes: accumulators and non-accumulators. The accumulator and non-accumulator groups differed significantly in terms of baseline AD protein levels and slope of change. APOE ε4 carrier status and episodic memory predicted amyloid class membership. Non-linear models revealed time points of significant increase in the rate of amyloid and p-Tau accumulation whereby APOE ε4 carrier status associated with earlier age at onset of rapid accumulation.

Conclusions

The current analysis demonstrates the existence of distinct classes of amyloid and p-Tau accumulators. Predictors of class membership were identified but the overall accuracy of the models was modest, highlighting the need for additional biomarkers that are sensitive to early disease phenotypes.

Resting State Glucose Utilization and Adult Reading Test Performance

Adult reading tests (ART) have been widely used in both research and clinical settings as a measure of premorbid cognitive abilities or cognitive reserve. However, the neural substrates underlying ART performance are largely unknown. Furthermore, it has not yet been examined whether the neural substrates of ART performance reflect the cortical regions associated with premorbid intelligence or cognitive reserve. The aim of the study is to identify the functional neural correlates of ART performance using 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging in the cognitively normal (CN) middle- and old-aged adults. Voxel-wise analyses revealed positive correlations between glucose metabolism and ART performance in the frontal and primary somatosensory regions, more specifically the lateral frontal cortex, anterior cingulate cortex and postcentral gyrus (PCG). When conducted again only for amyloid-β (Aβ)-negative individuals, the voxel-wise analysis showed significant correlations in broader areas of the frontal and primary somatosensory regions. This is the first neuroimaging study to directly demonstrate the cerebral resting-state glucose utilization associated with ART performance. Our findings provide important evidence at the neural level that ART predicts premorbid general intelligence and cognitive reserve, as brain areas that showed significant correlations with ART performance correspond to regions that have been associated with general intelligence and cognitive reserve.

Rates of age- and amyloid β-associated cortical atrophy in older adults with superior memory performance

INTRODUCTION

Superior cognitive performance in older adults may reflect underlying resistance to age-associated neurodegeneration. While elevated amyloid β (Aβ) deposition (Aβ+) has been associated with increased cortical atrophy, it remains unknown whether "SuperAgers" may be protected from Aβ-associated neurodegeneration.

METHODS

Neuropsychologically defined SuperAgers (n = 172) and cognitively normal for age (n = 172) older adults from the Australian Imaging, Biomarkers and Lifestyle study were case matched. Rates of cortical atrophy over 8 years were examined by SuperAger classification and Aβ status.

RESULTS

Of the case-matched SuperAgers and cognitively normal for age older adults, 40.7% and 40.1%, respectively, were Aβ+. Rates of age- and Aβ-associated atrophy did not differ between the groups on any measure. Aβ- individuals displayed the slowest rates of atrophy.

DISCUSSION

Maintenance of superior memory in late life does not reflect resistance to age- or Aβ-associated atrophy. However, those individuals who reached old age without cognitive impairment nor elevated Aβ deposition (i.e. Aβ-) displayed reduced rates of cortical atrophy.

Improving brain age prediction models: incorporation of amyloid status in Alzheimer's disease

Brain age prediction is a machine learning method that estimates an individual's chronological age from their neuroimaging scans. Brain age indicates whether an individual's brain appears "older" than age-matched healthy peers, suggesting that they may have experienced a higher cumulative exposure to brain insults or were more impacted by those pathological insults. However, contemporary brain age models include older participants with amyloid pathology in their training sets and thus may be confounded when studying Alzheimer's disease (AD). We showed that amyloid status is a critical feature for brain age prediction models. We trained a model on T1-weighted MRI images participants without amyloid pathology. MRI data were processed to estimate gray matter density voxel-wise, which were then used to predict chronological age. Our model performed accurately comparable to previous models. Notably, we demonstrated more significant differences between AD diagnostic groups than other models. In addition, our model was able to delineate significant differences in brain age relative to chronological age between cognitively normal individuals with and without amyloid. Incorporation of amyloid status in brain age prediction models ultimately improves the utility of brain age as a biomarker for AD.

Associations among amyloid status, age, and longitudinal regional brain atrophy in cognitively unimpaired older adults

The goal of this study was to compare regional brain atrophy patterns in cognitively unimpaired (CU) older adults with and without brain accumulation of amyloid-β (Aβ) to elucidate contributions of Aβ, age, and other variables to atrophy rates. In 80 CU participants from the Alzheimer's Disease Neuroimaging Initiative, we determined effects of Aβ and age on longitudinal, regional atrophy rates, while accounting for confounding variables including sex, APOE ε4 genotype, white matter lesions, and cerebrospinal fluid total and phosphorylated tau levels. We not only found overlapping patterns of atrophy in Aβ+ versus Aβ- participants but also identified regions where atrophy pattern differed between the 2 groups. Higher Aβ load was associated with increased longitudinal atrophy in the entorhinal cortex, amygdala, and hippocampus, even when accounting for age and other variables. Age was associated with atrophy in insula, fusiform gyrus, and isthmus cingulate, even when accounting for Aβ. We found age by Aβ interactions in the postcentral gyrus and lateral orbitofrontal cortex. These results elucidate the separate and related effects of age, Aβ, and other important variables on longitudinal brain atrophy rates in CU older adults.

Genome-wide association study identifies CBFA2T3 affecting the rate of CSF Aβ42 decline in non-demented elders

Brain amyloid deposition is an early pathological event in Alzheimer's disease (AD), and abnormally low levels amyloid-β42 peptide (Aβ42) in cerebrospinal fluid (CSF) can be detected in preclinical AD. To identify the genetic determinants that regulate the rate of CSF Aβ42 decline among non-demented elders, we conducted a genome-wide association study involved 321 non-demented elders from Alzheimer's Disease Neuroimaging Initiative (ADNI) 1/GO/2 cohorts restricted to non-Hispanic Caucasians. A novel genome-wide significant association of higher annualized percent decline of CSF Aβ42 in the gene CBFA2T3 (CBFA2/RUNX1 translocation partner 3; rs13333659-T; p = 2.24 × 10-9) was identified. Besides displaying abnormal CSF Aβ42 levels, rs13333659-T carriers were more likely to exhibit a greater longitudinal cognitive decline (p = 0.029, β = 0.097) and hippocampal atrophy (p = 0.029, β = -0.160) in the non-demented elders, especially for the participants who were amyloid-positive at baseline. These findings suggest rs13333659 in CBFA2T3 as a risk locus to modulate the decline rate of CSF Aβ42 preceding the onset of clinical symptoms.

Executive and Language Subjective Cognitive Decline Complaints Discriminate Preclinical Alzheimer's Disease from Normal Aging

BACKGROUND

There is a need to specify the profile of subjective cognitive decline in preclinical Alzheimer's disease (preAD).

OBJECTIVES

To explore specific items of the Subjective Cognitive Decline Questionnaire (SCD-Q) that discriminate preAD from normal aging.

METHODS

68 cognitively normal older adults were classified as controls (n = 52) or preAD (n = 16) according to amyloid-β (Aβ) levels. An exploratory factor analysis and item analysis of the SCD-Q were performed. Informant reports of the SCD-Q were used to corroborate the findings of self-reports. One-year neuropsychological follow-up was available.

RESULTS

Four SCD-Q factors were extracted: EM-factor (episodic memory), A-factor (attention), O-factor (organization), and L-factor (language). PreAD reported a significantly higher decline in L-factor (F(1) = 6.49; p = 0.014) and A-factor (F(1) = 4.04; p = 0.049) compared to controls, and showed a higher frequency of perceived decline in SCD-Q items related with language and executive tasks (Sig-items.) Significant discriminative powers for Aβ-positivity were found for L-factor (AUC = 0.75; p = 0.003) and A-factor (AUC = 0.74; p = 0.004). Informants in the preAD group confirmed significantly higher scores in L-factor and Sig-items. A significant time×group interaction was found in the Semantic Fluency and Stroop tests, with the preAD group showing a decrease in performance at one-year.

CONCLUSIONS

Our results suggest that SCD-Q items related with language and executive decline may help in prediction algorithms to detect preAD. Validation in an independent population is needed.

Amyloid-β and Tau at the Crossroads of Alzheimer's Disease

Alzheimer's disease (AD) is the most common form of dementia characterized neuropathologically by senile plaques and neurofibrillary tangles (NFTs). Early breakthroughs in AD research led to the discovery of amyloid-β as the major component of senile plaques and tau protein as the major component of NFTs. Shortly following the identification of the amyloid-β (Aβ) peptide was the discovery that a genetic mutation in the amyloid precursor protein (APP), a type1 transmembrane protein, can be a cause of autosomal dominant familial AD (fAD). These discoveries, coupled with other breakthroughs in cell biology and human genetics, have led to a theory known as the "amyloid hypothesis", which postulates that amyloid-β is the predominant driving factor in AD development. Nonetheless, more recent advances in imaging analysis, biomarkers and mouse models are now redefining this original hypothesis, as it is likely amyloid-β, tau and other pathophysiological mechanism such as inflammation, come together at a crossroads that ultimately leads to the development of AD.

Brain β-Amyloid and Atrophy in Individuals at Increased Risk of Cognitive Decline

BACKGROUND AND PURPOSE

The relationship between brain β-amyloid and regional atrophy is still incompletely understood in elderly individuals at risk of dementia. Here, we studied the associations between brain β-amyloid load and regional GM and WM volumes in older adults who were clinically evaluated as being at increased risk of cognitive decline based on cardiovascular risk factors.

MATERIALS AND METHODS

Forty subjects (63-81 years of age) were recruited as part of a larger study, the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability. Neuroimaging consisted of PET using ¹¹C Pittsburgh compound-B and T1-weighted 3D MR imaging for the measurement of brain β-amyloid and GM and WM volumes, respectively. All subjects underwent clinical, genetic, and neuropsychological evaluations for the assessment of cognitive function and the identification of cardiovascular risk factors.

RESULTS

Sixteen subjects were visually evaluated as showing cortical β-amyloid (positive for β-amyloid). In the voxel-by-voxel analyses, no significant differences were found in GM and WM volumes between the samples positive and negative for β-amyloid. However, in the sample positive for β-amyloid, increases in ¹¹C Pittsburgh compound-B uptake were associated with reductions in GM volume in the left prefrontal (P = .02) and right temporal lobes (P = .04).

CONCLUSIONS

Our results show a significant association between increases in brain β-amyloid and reductions in regional GM volume in individuals at increased risk of cognitive decline. This evidence is consistent with a model in which increases in β-amyloid incite neurodegeneration in memory systems before cognitive impairment manifests.

MRI predictors of amyloid pathology: results from the EMIF-AD Multimodal Biomarker Discovery study

BACKGROUND

With the shift of research focus towards the pre-dementia stage of Alzheimer's disease (AD), there is an urgent need for reliable, non-invasive biomarkers to predict amyloid pathology. The aim of this study was to assess whether easily obtainable measures from structural MRI, combined with demographic data, cognitive data and apolipoprotein E (APOE) ε4 genotype, can be used to predict amyloid pathology using machine-learning classification.

METHODS

We examined 810 subjects with structural MRI data and amyloid markers from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, including subjects with normal cognition (CN, n = 337, age 66.5 ± 7.2, 50% female, 27% amyloid positive), mild cognitive impairment (MCI, n = 375, age 69.1 ± 7.5, 53% female, 63% amyloid positive) and AD dementia (n = 98, age 67.0 ± 7.7, 48% female, 97% amyloid positive). Structural MRI scans were visually assessed and Freesurfer was used to obtain subcortical volumes, cortical thickness and surface area measures. We first assessed univariate associations between MRI measures and amyloid pathology using mixed models. Next, we developed and tested an automated classifier using demographic, cognitive, MRI and APOE ε4 information to predict amyloid pathology. A support vector machine (SVM) with nested 10-fold cross-validation was applied to identify a set of markers best discriminating between amyloid positive and amyloid negative subjects.

RESULTS

In univariate associations, amyloid pathology was associated with lower subcortical volumes and thinner cortex in AD-signature regions in CN and MCI. The multi-variable SVM classifier provided an area under the curve (AUC) of 0.81 ± 0.07 in MCI and an AUC of 0.74 ± 0.08 in CN. In CN, selected features for the classifier included APOE ε4, age, memory scores and several MRI measures such as hippocampus, amygdala and accumbens volumes and cortical thickness in temporal and parahippocampal regions. In MCI, the classifier including demographic and APOE ε4 information did not improve after additionally adding imaging measures.

CONCLUSIONS

Amyloid pathology is associated with changes in structural MRI measures in CN and MCI. An automated classifier based on clinical, imaging and APOE ε4 data can identify the presence of amyloid pathology with a moderate level of accuracy. These results could be used in clinical trials to pre-screen subjects for anti-amyloid therapies.

Longitudinal decreases in multiple cerebrospinal fluid biomarkers of neuronal injury in symptomatic late onset Alzheimer's disease

INTRODUCTION

Individuals in early stages of Alzheimer's disease are a targeted population for secondary prevention trials aimed at preserving normal cognition. Understanding within-person biomarker(s) change over time is critical for trial enrollment and design.

METHODS

Longitudinal cerebrospinal fluid samples from the Alzheimer's Disease Neuroimaging Initiative were assayed for novel markers of neuronal/synaptic injury (visinin-like protein 1, Ng, and SNAP-25) and neuroinflammation (YKL-40) and compared with β amyloid 42, tau, and phospho-tau181. General linear mixed models were used to compare within-person rates of change in three clinical groups (cognitively normal, mild cognitive impairment, and Alzheimer's disease) further defined by β amyloid status.

RESULTS

Levels of injury markers were highly positively correlated. Despite elevated baseline levels as a function of clinical status and amyloid-positivity, within-person decreases in these measures were observed in the early symptomatic, amyloid-positive Alzheimer's disease group.

DISCUSSION

Knowledge of within-person biomarker change will impact interpretation of biomarker outcomes in clinical trials that are dependent on disease stage.

Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity

It is not known exactly where amyloid-β (Aβ) fibrils begin to accumulate in individuals with Alzheimer’s disease (AD). Recently, we showed that abnormal levels of Aβ42 in cerebrospinal fluid (CSF) can be detected before abnormal amyloid can be detected using PET in individuals with preclinical AD. Using these approaches, here we identify the earliest preclinical AD stage in subjects from the ADNI and BioFINDER cohorts. We show that Aβ accumulation preferentially starts in the precuneus, medial orbitofrontal, and posterior cingulate cortices, i.e., several of the core regions of the default mode network (DMN). This early pattern of Aβ accumulation is already evident in individuals with normal Aβ42 in the CSF and normal amyloid PET who subsequently convert to having abnormal CSF Aβ42. The earliest Aβ accumulation is further associated with hypoconnectivity within the DMN and between the DMN and the frontoparietal network, but not with brain atrophy or glucose hypometabolism. Our results suggest that Aβ fibrils start to accumulate predominantly within certain parts of the DMN in preclinical AD and already then affect brain connectivity.

Abnormal levels of Aβ42 in the cerebrospinal fluid occur prior to a positive amyloid PET scan in the brain of individuals with Alzheimer’s disease and here the authors use this temporal pattern to identify individuals with very early stage AD. They show that Aβ fibrils start to accumulate in some of the regions of the default mode network and affect brain connectivity before neurodegeneration occurs.

Preclinical effects of APOE ε4 on cerebrospinal fluid Aβ42 concentrations

Background

From earlier studies it is known that the APOE ε2/ε3/ε4 polymorphism modulates the concentrations of cerebrospinal fluid (CSF) beta-amyloid_1–42 (Aβ42) in patients with cognitive decline due to Alzheimer’s disease (AD), as well as in cognitively healthy controls. Here, in a large cohort consisting solely of cognitively healthy individuals, we aimed to evaluate how the effect of APOE on CSF Aβ42 varies by age, to understand the association between APOE and the onset of preclinical AD.

Methods

APOE genotype and CSF Aβ42 concentration were determined in a cohort comprising 716 cognitively healthy individuals aged 17–99 from nine different clinical research centers.

Results

CSF concentrations of Aβ42 were lower in APOE ε4 carriers than in noncarriers in a gene dose-dependent manner. The effect of APOE ε4 on CSF Aβ42 was age dependent. The age at which CSF Aβ42 concentrations started to decrease was estimated at 50 years in APOE ε4-negative individuals and 43 years in heterozygous APOE ε4 carriers. Homozygous APOE ε4 carriers showed a steady decline in CSF Aβ42 concentrations with increasing age throughout the examined age span.

Conclusions

People possessing the APOE ε4 allele start to show a decrease in CSF Aβ42 concentration almost a decade before APOE ε4 noncarriers already in early middle age. Homozygous APOE ε4 carriers might deposit Aβ42 throughout the examined age span. These results suggest that there is an APOE ε4-dependent period of early alterations in amyloid homeostasis, when amyloid slowly accumulates, that several years later, together with other downstream pathological events such as tau pathology, translates into cognitive decline.

Time to Amyloid Positivity and Preclinical Changes in Brain Metabolism, Atrophy, and Cognition: Evidence for Emerging Amyloid Pathology in Alzheimer's Disease

Background: Aβ pathology is associated with longitudinal changes of brain metabolism, atrophy, and cognition, in cognitively healthy elders. However, Aβ information is usually measured cross-sectionally and dichotomized to classify subjects as Aβ-positive or Aβ-negative, making it difficult to evaluate when brain and cognitive changes occur with respect to emerging Aβ pathology. In this study, we use longitudinal Aβ information to combine the level and rate of change of Aβ to estimate the time to Aβ-positivity for each subject and test this temporal proximity to significant Aβ pathology for associations with brain structure, metabolism, and cognition. Methods: In 89 cognitively healthy elders with up to 10 years of follow-up, we estimated the points at which rates of fluorodeoxyglucose (FDG) PET, MRI, and cognitive and functional decline begin to accelerate with respect to the time to Aβ-positivity. Points of initial acceleration in rates of decline were estimated using mixed-effects models with penalized regression splines. Results: Acceleration of rates of FDG PET were observed to occur 20+ years before the conventional threshold for Aβ-positivity. Subtle signs of cognitive dysfunction were observed 10+ years before Aβ-positivity. Conclusions: Aβ may have subtle associations with other hallmarks of Alzheimer's disease before Aβ biomarkers reach conventional thresholds for Aβ-positivity. Therefore, we propose that emerging Aβ pathology occurs many years before cognitively healthy elders reach the current threshold for Aβ positivity (preclinical AD). To allow prevention in the earliest disease stages, AD clinical trials may be designed to also include subjects with Aβ biomarkers in the sub-threshold range.

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.

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015.

METHODS

We used standard searches to find publications using ADNI data.

RESULTS

(1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers.

DISCUSSION

Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.

Anti-Correlated Cerebrospinal Fluid Biomarker Trajectories in Preclinical Alzheimer's Disease

BACKGROUND

The earliest stage of preclinical Alzheimer's disease (AD) is defined by low levels of cerebrospinal fluid (CSF) amyloid-β (Aβ42). However, covariance in longitudinal dynamic change of Aβ42 and tau in incipient preclinical AD is poorly understood.

OBJECTIVE

To examine dynamic interrelationships between Aβ42 and tau in preclinical AD.

METHODS

We followed 47 cognitively intact participants (CI) with available CSF data over four years in ADNI. Based on longitudinal Aβ42 levels in CSF, CI were classified into three groups: 1) Aβ42 stable with normal levels of Aβ42 over time (n = 15); 2) Aβ42 declining with normal Aβ42 levels at baseline but showing decline over time (n = 14); and 3) Aβ42 levels consistently abnormal (n = 18).

RESULTS

In the Aβ42 declining group, suggestive of incipient preclinical AD, CSF phosphorylated tau (p-tau) showed a similar longitudinal pattern of increasing abnormality over time (p = 0.0001). Correlation between longitudinal slopes of Aβ42 and p-tau confirmed that both trajectories were anti-correlated (rho = -0.60; p = 0.02). Regression analysis showed that Aβ42 slope (decreasing Aβ42) predicted p-tau slope (increasing p-tau) (R2 = 0.47, p = 0.03). Atrophy in the hippocampus was predicted by the interaction of Aβ42 and p-tau slopes (p <  0.0001) only in this incipient preclinical AD group. In all groups combined, memory decline was predicted by p-tau.

CONCLUSIONS

The evolution of Aβ42 and p-tau CSF biomarkers in CI subjects follows an anti-correlated trajectory, i.e., as Aβ42 declined, p-tau increased, and thus was suggestive of strong temporal coincidence. Rapid pathogenic cross-talk between Aβ42 and p-tau thus may be evident in very early stages of preclinical AD.

Computerized Cognitive Tests Are Associated with Biomarkers of Alzheimer's Disease in Cognitively Normal Individuals 10 Years Prior

OBJECTIVES

Evidence suggests that Alzheimer's disease (AD) biomarkers become abnormal many years before the emergence of clinical symptoms of AD, raising the possibility that biomarker levels measured in cognitively normal individuals would be associated with cognitive performance many years later. This study examined whether performance on computerized cognitive tests is associated with levels of cerebrospinal fluid (CSF) biomarkers of amyloid, tau, and phosphorylated tau (p-tau) obtained approximately 10 years earlier, when individuals were cognitively normal and primarily middle-aged.

METHODS

Individuals from the BIOCARD cohort (mean age at testing=69 years) were tested on two computerized tasks hypothesized to rely on brain regions affected by the early accumulation of AD pathology: (1) a Paired Associates Learning (PAL) task (n=67) and (2) a visual search task (n=86).

RESULTS

In regression analyses, poorer performance on the PAL task was associated with higher levels of CSF p-tau obtained years earlier, whereas worse performance in the visual search task was associated with lower levels of CSF Aβ1-42.

CONCLUSIONS

These findings suggest that AD biomarker levels may be differentially predictive of specific cognitive functions many years later. In line with the pattern of early accumulation of AD pathology, the PAL task, hypothesized to rely on medial temporal lobe function, was associated with CSF p-tau, whereas the visual search task, hypothesized to rely on frontoparietal function, was associated with CSF amyloid. Studies using amyloid and tau PET imaging will be useful in examining these hypothesized relationships further. (JINS, 2016, 22, 968-977).

Cerebrospinal fluid tau, neurogranin, and neurofilament light in Alzheimer's disease

Cerebrospinal fluid (CSF) tau (total tau, T‐tau), neurofilament light (NFL), and neurogranin (Ng) are potential biomarkers for neurodegeneration in Alzheimer's disease (AD). It is unknown whether these biomarkers provide similar or complementary information in AD. We examined 93 patients with AD, 187 patients with mild cognitive impairment, and 109 controls. T‐tau, Ng, and NFL were all predictors of AD diagnosis. Combinations improved the diagnostic accuracy (AUC 85.5% for T‐tau, Ng, and NFL) compared to individual biomarkers (T‐tau 80.8%; Ng 71.4%; NFL 77.7%). T‐tau and Ng were highly correlated (ρ = 0.79, P < 0.001) and strongly associated with β‐amyloid (Aβ) pathology, and with longitudinal deterioration in cognition and brain structure, primarily in people with Aβ pathology. NFL on the other hand was not associated with Aβ pathology and was associated with cognitive decline and brain atrophy independent of Aβ. T‐tau, Ng, and NFL provide partly independent information about neuronal injury and may be combined to improve the diagnostic accuracy for AD. T‐tau and Ng reflect Aβ‐dependent neurodegeneration, while NFL reflects neurodegeneration independently of Aβ pathology.

Progressively Disrupted Intrinsic Functional Connectivity of Basolateral Amygdala in Very Early Alzheimer's Disease

Very early Alzheimer’s disease (AD) – i.e., AD at stages of mild cognitive impairment (MCI) and mild dementia – is characterized by progressive structural and neuropathologic changes, such as atrophy or tangle deposition in medial temporal lobes, including hippocampus and entorhinal cortex and also adjacent amygdala. While progressively disrupted intrinsic connectivity of hippocampus with other brain areas has been demonstrated by many studies, amygdala connectivity was rarely investigated in AD, notwithstanding its known relevance for emotion processing and mood disturbances, which are both important in early AD. Intrinsic functional connectivity (iFC) patterns of hippocampus and amygdala overlap in healthy persons. Thus, we hypothesized that increased alteration of iFC patterns along AD is not limited to the hippocampus but also concerns the amygdala, independent from atrophy. To address this hypothesis, we applied structural and functional resting-state MRI in healthy controls (CON, n = 33) and patients with AD in the stages of MCI (AD-MCI, n = 38) and mild dementia (AD-D, n = 36). Outcome measures were voxel-based morphometry (VBM) values and region-of-interest-based iFC maps of basolateral amygdala, which has extended cortical connectivity. Amygdala VBM values were progressively reduced in patients (CON > AD-MCI and AD-D). Amygdala iFC was progressively reduced along impairment severity (CON > AD-MCI > AD-D), particularly for hippocampus, temporal lobes, and fronto-parietal areas. Notably, decreased iFC was independent of amygdala atrophy. Results demonstrate progressively impaired amygdala intrinsic connectivity in temporal and fronto-parietal lobes independent from increasing amygdala atrophy in very early AD. Data suggest that early AD disrupts intrinsic connectivity of medial temporal lobe key regions, including that of amygdala.

Cognitive and functional changes associated with Aβ pathology and the progression to mild cognitive impairment

Cognitively-normal people with evidence of β-amyloid (Aβ) pathology and subtle cognitive dysfunction are believed to be at high risk for progression to mild cognitive impairment due to Alzheimer's disease (AD). Clinical trials in later stages of AD typically include a coprimary endpoint to demonstrate efficacy on both cognitive and functional assessments. Recent trials focus on cognitively-normal people, but functional decline has not been explored for trial designs in this group. The goal of this study was therefore to characterize cognitive and functional decline in (1) cognitively-normal people converting to mild cognitive impairment (MCI) and (2) cognitively-normal β-amyloid-positive (Aβ+) people. Specifically, we sought to identify and compare the cognitive and functional assessments and their weighted combinations that maximize the longitudinal decline specific to these 2 groups. We studied 68 people who converted from normal cognition to MCI and 70 nonconverters, as well as 137 Aβ+ and 210 β-amyloid-negative cognitively-normal people. We used bootstrap aggregation and cross-validated mixed-models to estimate the distribution of weights applied to cognitive and functional outcomes to form composites. We also evaluated best subset optimization. Using optimized composites, we estimated statistical power for a variety of clinical trial scenarios. Overall, 55.4% of cognitively-normal to MCI converters were Aβ+. Large gains in power estimates were obtained when requiring participants to have both subtle cognitive dysfunction and Aβ pathology compared with requiring Aβ pathology alone. Additional power resulted when including functional as well as cognitive outcomes as part of the composite. Composites formed by applying equal weights to all measures provided the highest estimates of cross-validated power, although similar to both continuous weight optimization and best subset optimization. Using a composite to detect a 30% slowing of decline, 80% power was obtained for predicted Aβ+ converters with 375 completers/arm for a 30-month trial using a combination of cognitive/ functional measures. In the Aβ+ group, power to approach levels suitable for a phase III clinical trial would require considerably larger sample sizes. Composites incorporating both cognitive and functional measures may substantially increase the power of a trial in a preclinical (Aβ+) AD population with subtle evidence of cognitive dysfunction.

Assessing risk for preclinical β-amyloid pathology with APOE, cognitive, and demographic information

INTRODUCTION

Clinical trials in Alzheimer's disease are aimed at early stages of disease, including preclinical Alzheimer's disease. The high cost and time required to screen large numbers of participants for Aβ pathology impede the development of novel drugs. This study's objective was to evaluate the extent to which inexpensive and easily obtainable information can reduce the number of screen failures by increasing the proportion of Aβ+ participants identified for screening.

METHODS

We used random forest models to evaluate the positive predictive value of demographics, APOE, and longitudinal cognitive rates in the prediction of amyloid pathology, measured by florbetapir PET or cerebrospinal fluid.

RESULTS

Predicting Aβ positivity with demographic, APOE, and cognitive information yielded a positive predictive value estimate of 0.65 (95% CI, 0.50-0.96), nearly a 60% increase over the reference Aβ+ prevalence in the cohort of 0.41.

CONCLUSIONS

By incorporating this procedure, clinical trial screening costs of 7500 USD per participant may be reduced by nearly 7 million USD total.

Accelerated decline in white matter integrity in clinically normal individuals at risk for Alzheimer's disease

Prior studies have identified white matter abnormalities in Alzheimer's disease (AD). Yet, cross-sectional studies in normal older individuals show little evidence for an association between markers of AD risk (APOE4 genotype and amyloid deposition), and white matter integrity. Here, 108 normal older adults (age, 66-87) with assessments of apolipoprotein e4 (APOE4) genotype and assessment of amyloid burden by positron emission tomography underwent diffusion tensor imaging scans for measuring white matter integrity at 2 time points, on average 2.6 years apart. Linear mixed-effects models showed that amyloid burden at baseline was associated with steeper decline in fractional anisotropy in the parahippocampal cingulum (p < 0.05). This association was not significant between baseline measures suggesting that longitudinal analyses can provide novel insights that are not detectable in cross-sectional designs. Amyloid-related changes in hippocampus volume did not explain the association between amyloid burden and change in fractional anisotropy. The results suggest that accumulation of cortical amyloid and white matter changes in parahippocampal cingulum are not independent processes in individuals at increased risk for AD.

Epigenetics of dementia: understanding the disease as a transformation rather than a state

Alzheimer's disease and other idiopathic dementias are associated with epigenetic transformations. These transformations connect the environment and genes to pathogenesis, and have led to the investigation of epigenetic-based therapeutic targes for the treatment of these diseases. Epigenetic changes occur over time in response to environmental effects. The epigenome-based latent early-life associated regulation (LEARn) hypothetical model indicates that accumulated environmental hits produce latent epigenetic changes. These hits can alter biochemical pathways until a pathological threshold is reached, which appears clinically as the onset of dementia. The hypotheses posed by LEARn are testable via longitudinal epigenome-wide, envirome-wide, and exposome-wide association studies (LEWAS) of the genome, epigenome, and environment. We posit that the LEWAS design could lead to effective prevention and treatments by identifying potential therapeutic strategies. Epigenetic evidence suggests that dementia is not a suddenly occurring and sharply delineated state, but rather a gradual change in crucial cellular pathways, that transforms an otherwise healthy state, as a result of neurodegeneration, to a dysfunctional state. Evidence from epigenetics could lead to ways to detect, prevent, and reverse such processes before clinical dementia.

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2

INTRODUCTION

Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders.

METHODS

We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3.

RESULTS

Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials.

DISCUSSION

Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future.

Increased CSF Aβ during the very early phase of cerebral Aβ deposition in mouse models

Abnormalities in brains of Alzheimer's disease (AD) patients are thought to start long before the first clinical symptoms emerge. The identification of affected individuals at this ‘preclinical AD’ stage relies on biomarkers such as decreased levels of the amyloid-β peptide (Aβ) in the cerebrospinal fluid (CSF) and positive amyloid positron emission tomography scans. However, there is little information on the longitudinal dynamics of CSF biomarkers, especially in the earliest disease stages when therapeutic interventions are likely most effective. To this end, we have studied CSF Aβ changes in three Aβ precursor protein transgenic mouse models, focusing our analysis on the initial Aβ deposition, which differs significantly among the models studied. Remarkably, while we confirmed the CSF Aβ decrease during the extended course of brain Aβ deposition, a 20–30% increase in CSF Aβ40 and Aβ42 was found around the time of the first Aβ plaque appearance in all models. The biphasic nature of this observed biomarker changes stresses the need for longitudinal biomarker studies in the clinical setting and the search for new ‘preclinical AD’ biomarkers at even earlier disease stages, by using both mice and human samples. Ultimately, our findings may open new perspectives in identifying subjects at risk for AD significantly earlier, and in improving the stratification of patients for preventive treatment strategies.

Mapping 3-year changes in gray matter and metabolism in Aβ-positive nondemented subjects

Gray matter (GM) atrophy and brain glucose hypometabolism are already detected in the predementia stages of Alzheimer's disease (AD), but the regional and longitudinal associations between the two are not well understood. Here, we analyzed the patterns of longitudinal atrophy (magnetic resonance imaging [MRI]) and (18)F-Fluorodeoxyglucose-positron emission tomography ([18F]FDG-PET) metabolism decline in 40 cognitively healthy control (HC) and 52 mildly impaired (mild cognitive impairment [MCI]) subjects during 3 years. Based on cerebrospinal fluid and brain amyloid-PET, the subjects were divided into amyloid-beta (Aβ)- and Aβ+ subgroups. In voxel-based and region of interest analyses, we compared the 3-year rates of change in GM and glucose metabolism between Aβ-subgroups, within each diagnostic group. In joint-independent component analyses, we assessed the patterns of covariation between longitudinal change in GM volume and glucose metabolism. MCI-Aβ+ showed faster atrophy than MCI-Aβ- within the temporal, medial temporal, and medial parietal lobes. HC-Aβ+ showed faster atrophy within the precuneus than HC-Aβ-. For FDG-PET metabolism, MCI-Aβ+ exhibited faster decline than MCI-Aβ- in temporoparietal regions, whereas no differences between HC subgroups were observed. Joint-independent component analysis showed that accelerated atrophy and metabolism decline correlated across distant brain regions for MCI-Aβ+. In conclusion, abnormally increased levels of Aβ in nondemented subjects were associated with accelerated decline in both GM and glucose metabolism, where both types of neurodegeneration progress in spatially divergent patterns.

The transitional association between β-amyloid pathology and regional brain atrophy

INTRODUCTION

Alzheimer's disease (AD) is characterized by the accumulation of β-amyloid (Aβ) associated with brain atrophy and cognitive decline. The functional form to model the association between Aβ and regional brain atrophy has not been well defined. To determine the relationship between Aβ and atrophy, we compared the performance of the usual dichotomization of cerebrospinal fluid (CSF) Aβ to identify subjects as Aβ+ and Aβ- with a trilinear spline model of CSF Aβ.

METHODS

One hundred and eighty-three subjects with mild cognitive impairment and 108 cognitively normal controls with baseline CSF Aβ and up to 4 years of longitudinal magnetic resonance imaging data from the Alzheimer's Disease Neuroimaging Initiative were analyzed using mixed-effects regression. Piecewise-linear splines were used to evaluate the nonlinear nature of the association between CSF Aβ and regional atrophy and to identify points of acceleration of atrophy with respect to Aβ. Several parameterizations of CSF Aβ were compared using likelihood ratio tests and the Akaike information criterion. Periods of acceleration of atrophy in which subjects transition from CSF Aβ negativity to CSF Aβ positivity were estimated from the spline models and tested for significance.

RESULTS

Spline models resulted in better fits for many temporal and parietal regions compared with the dichotomous models. The trilinear model showed that periods of acceleration of atrophy varied greatly by region with early changes seen in the insula, amygdala, precuneus, hippocampus, and other temporal regions, occurring before the clinical threshold for CSF Aβ positivity.

DISCUSSION

The use of piecewise-linear splines provides an improved model of the nonlinear association between CSF Aβ and regional atrophy in regions implicated in the progression of AD. The important biological finding of this work is that some brain regions show periods of accelerated volume loss well before the CSF Aβ42 threshold. This implies that signs of brain atrophy develop before the current conventional definition of "preclinical AD".

Nonlinear cerebral atrophy patterns across the Alzheimer's disease continuum: impact of APOE4 genotype

The progression of Alzheimer's disease (AD) is characterized by complex trajectories of cerebral atrophy that are affected by interactions with age and apolipoprotein E allele ε4 (APOE4) status. In this article, we report the nonlinear volumetric changes in gray matter across the full biological spectrum of the disease, represented by the AD-cerebrospinal fluid (CSF) index. This index reflects the subject's level of pathology and position along the AD continuum. We also evaluated the associated impact of the APOE4 genotype. The atrophy pattern associated with the AD-CSF index was highly symmetrical and corresponded with the typical AD signature. Medial temporal structures showed different atrophy dynamics along the progression of the disease. The bilateral parahippocampal cortices and a parietotemporal region extending from the middle temporal to the supramarginal gyrus presented an initial increase in volume which later reverted. Similarly, a portion of the precuneus presented a rather linear inverse association with the AD-CSF index whereas some other clusters did not show significant atrophy until index values corresponded to positive CSF tau values. APOE4 carriers showed steeper hippocampal volume reductions with AD progression. Overall, the reported atrophy patterns are in close agreement with those mentioned in previous findings. However, the detected nonlinearities suggest that there may be different pathological processes taking place at specific moments during AD progression and reveal the impact of the APOE4 allele.

Neuropsychiatric symptoms in Alzheimer's disease: What might be associated brain circuits?

Neuropsychiatric symptoms (NPS) are very common in Alzheimer's disease (AD), particularly agitation, apathy, depression, and delusions. Brain networks or circuits underlying these symptoms are just starting to be understood, and there is a growing imaging and neurochemical evidence base for understanding potential mechanisms for NPS. We offer a synthetic review of the recent literature and offer hypotheses for potential networks/circuits underlying these NPS, particularly agitation, apathy, and delusions. Agitation in AD appears to be associated with deficits in structure and function of frontal cortex, anterior cingulate cortex, posterior cingulate cortex, amygdala, and hippocampus, and may be associated with mechanisms underlying misinterpretation of threats and affective regulation. Apathy in AD is associated with frontal cortex, anterior cingulate cortex, posterior cingulate cortex, as well as orbitofrontal cortex, and inferior temporal cortex, and may be associated with mechanisms underlying avoidance behaviors.

Brain structure and function as mediators of the effects of amyloid on memory

OBJECTIVE

The objective of this study was to test whether effects of β-amyloid (Aβ) pathology on episodic memory were mediated by metabolism and gray matter volume in the early stages of Alzheimer disease.

METHODS

This was a prospective cohort study. We measured baseline Aβ (using florbetapir-PET), brain function (using fluorodeoxyglucose-PET), and brain structure (using MRI). A mediation analysis was performed to test whether statistical effects of Aβ positivity on cross-sectional and longitudinal episodic memory were mediated by hypometabolism or regional gray matter volume in cognitively healthy controls (CN, n = 280) and mild cognitive impairment (MCI, n = 463).

RESULTS

Lower memory scores were associated with Aβ positivity (CN, mildly; MCI, strongly), smaller gray matter volumes (CN, few regions, including hippocampus; MCI, widespread), and hypometabolism. Smaller volumes and hypometabolism mediated effects of Aβ in MCI but not in CN. The strongest individual regions mediated up to approximately 25%. A combination of brain structure and function mediated up to approximately 40%. In several regions, gray matter atrophy and hypometabolism predicted episodic memory without being associated (at p < 0.05) with Aβ positivity.

CONCLUSIONS

Changes in brain structure and function appear to be, in part, downstream events from Aβ pathology, ultimately resulting in episodic memory deficits. However, Aβ pathology is also strongly related to memory deficits through mechanisms that are not quantified by these imaging measurements, and episodic memory decline is partly caused by Alzheimer disease-like brain changes independently of Aβ pathology.

The evolution of preclinical Alzheimer's disease: implications for prevention trials

As the field begins to test the concept of a "preclinical" stage of neurodegenerative disease, when the pathophysiological process has begun in the brain, but clinical symptoms are not yet manifest, a number of intriguing questions have already arisen. In particular, in preclinical Alzheimer's disease (AD), the temporal relationship of amyloid markers to markers of neurodegeneration and their relative utility in the prediction of cognitive decline among clinically normal older individuals remains to be fully elucidated. Secondary prevention trials in AD have already begun in both genetic at-risk and amyloid at-risk cohorts, with several more trials in the planning stages, and should provide critical answers about whether intervention at this very early stage of disease can truly bend the curve of clinical progression. This review will highlight recent progress in cognitive, imaging, and biomarker outcomes in the field of preclinical AD, and the remaining gaps in knowledge.