The A/T/N biomarker scheme and patterns of brain atrophy assessed in mild cognitive impairment

Biomarkers of neural integrity and immunoglobulin genes influence neurodegeneration in Alzheimer's disease

Compelling evidence has been presented in favor of herpes simplex virus type 1 (HSV1) being one of the causative agents of Alzheimer's disease (AD). The success of HSV1 as a pathogen relates to its sophisticated strategies to evade host immunosurveillance. One strategy involves encoding a decoy Fcγ receptor (FcγR) that thwarts the Fcγ-mediated effector functions, such as antibody-dependent cellular cytotoxicity (ADCC), a potent host immunosurveillance mechanism against virally infected cells. The decoy FcγR binds to antibodies of all IgG subclasses, except IgG3; therefore, IgG3 would be expected to play an important role in viral clearance by neutralization and ADCC, and thus contribute to protection from HSV1-spurred diseases. Previous studies have shown significant association between anti-HSV1 IgG3 antibodies and cortical thinning of the areas of the brain typically altered in AD and also targeted by HSV1. The aim of the present investigation was to determine whether GM (γ marker) 5 and GM 21 allotypes, hereditary allelic determinants expressed on IgG3, together with brain biomarkers of neural integrity, contributed to neurodegeneration-as measured by mini-mental state examination (MMSE) score-in patients with AD. Multiple regression analyses showed that the homozygous GM 5/5 genotype, preserved right hippocampus, and right insula thickness were associated with higher MMSE scores (p < 0.001), whereas the opposite pattern and GM 5/21 genotype were associated with worse clinical profiles. Influence of GM 5/21-expressing IgG3 antibodies on the ADCC of HSV1-infected neurons could, at least partially, explain these results.

Prospective Longitudinal Perfusion in Probable Alzheimer's Disease Correlated with Atrophy in Temporal Lobe

Reduced cerebral blood flow (CBF) in the temporoparietal region and gray matter volumes (GMVs) in the temporal lobe were previously reported in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, the temporal relationship between reductions in CBF and GMVs requires further investigation. This study sought to determine if reduced CBF is associated with reduced GMVs, or vice versa. Data came from 148 volunteers of the Cardiovascular Health Study Cognition Study (CHS-CS), including 58 normal controls (NC), 50 MCI, and 40 AD who had perfusion and structural MRIs during 2002-2003 (Time 2). Sixty-three of the 148 volunteers had follow-up perfusion and structural MRIs (Time 3). Forty out of the 63 volunteers received prior structural MRIs during 1997-1999 (Time 1). The relationships between GMVs and subsequent CBF changes, and between CBF and subsequent GMV changes were investigated. At Time 2, we observed smaller GMVs (p<0.05) in the temporal pole region in AD compared to NC and MCI. We also found associations between: (1) temporal pole GMVs at Time 2 and subsequent declines in CBF in this region (p=0.0014) and in the temporoparietal region (p=0.0032); (2) hippocampal GMVs at Time 2 and subsequent declines in CBF in the temporoparietal region (p=0.012); and (3) temporal pole CBF at Time 2 and subsequent changes in GMV in this region (p = 0.011). Therefore, hypoperfusion in the temporal pole may be an early event driving its atrophy. Perfusion declines in the temporoparietal and temporal pole follow atrophy in this temporal pole region.

Multimodal subtypes identified in Alzheimer's Disease Neuroimaging Initiative participants by missing-data-enabled subtype and stage inference

Alzheimer's disease is a highly heterogeneous disease in which different biomarkers are dynamic over different windows of the decades-long pathophysiological processes, and potentially have distinct involvement in different subgroups. Subtype and Stage Inference is an unsupervised learning algorithm that disentangles the phenotypic heterogeneity and temporal progression of disease biomarkers, providing disease insight and quantitative estimates of individual subtype and stage. However, a key limitation of Subtype and Stage Inference is that it requires a complete set of biomarkers for each subject, reducing the number of datapoints available for model fitting and limiting applications of Subtype and Stage Inference to modalities that are widely collected, e.g. volumetric biomarkers derived from structural MRI. In this study, we adapted the Subtype and Stage Inference algorithm to handle missing data, enabling the application of Subtype and Stage Inference to multimodal data (magnetic resonance imaging, positron emission tomography, cerebrospinal fluid and cognitive tests) from 789 participants in the Alzheimer's Disease Neuroimaging Initiative. Missing-data Subtype and Stage Inference identified five subtypes having distinct progression patterns, which we describe by the earliest unique abnormality as 'Typical AD with Early Tau', 'Typical AD with Late Tau', 'Cortical', 'Cognitive' and 'Subcortical'. These new multimodal subtypes were differentially associated with age, years of education, Apolipoprotein E (APOE4) status, white matter hyperintensity burden and the rate of conversion from mild cognitive impairment to Alzheimer's disease, with the 'Cognitive' subtype showing the fastest clinical progression, and the 'Subcortical' subtype the slowest. Overall, we demonstrate that missing-data Subtype and Stage Inference reveals a finer landscape of Alzheimer's disease subtypes, each of which are associated with different risk factors. Missing-data Subtype and Stage Inference has broad utility, enabling the prediction of progression in a much wider set of individuals, rather than being restricted to those with complete data.

The clinical importance of suspected non-Alzheimer disease pathophysiology

The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) - a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP.

Prediction of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Amyloid PET and Brain MR Imaging Data: A 48-Month Follow-Up Analysis of the Alzheimer's Disease Neuroimaging Initiative Cohort

We developed a novel quantification method named "shape feature" by combining the features of amyloid positron emission tomography (PET) and brain magnetic resonance imaging (MRI) and evaluated its significance in predicting the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. From the ADNI database, 334 patients with MCI were included. The brain amyloid smoothing score (AV45_BASS) and brain atrophy index (MR_BAI) were calculated using the surface area and volume of the region of interest in AV45 PET and MRI. During the 48-month follow-up period, 108 (32.3%) patients converted from MCI to AD. Age, Mini-Mental State Examination (MMSE), cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-cog), apolipoprotein E (APOE), standardized uptake value ratio (SUVR), AV45_BASS, MR_BAI, and shape feature were significantly different between converters and non-converters. Univariate analysis showed that age, MMSE, ADAS-cog, APOE, SUVR, AV45_BASS, MR_BAI, and shape feature were correlated with the conversion to AD. In multivariate analyses, high shape feature, SUVR, and ADAS-cog values were associated with an increased risk of conversion to AD. In patients with MCI in the ADNI cohort, our quantification method was the strongest prognostic factor for predicting their conversion to AD.

Differential response to donepezil in MRI subtypes of mild cognitive impairment

BACKGROUND

Donepezil is an approved therapy for the treatment of Alzheimer's disease (AD). Results across clinical trials have been inconsistent, which may be explained by design-methodological issues, the pathophysiological heterogeneity of AD, and diversity of included study participants. We investigated whether response to donepezil differs in mild cognitive impaired (MCI) individuals demonstrating different magnetic resonance imaging (MRI) subtypes.

METHODS

From the Hippocampus Study double-blind, randomized clinical trial, we included 173 MCI individuals (donepezil = 83; placebo = 90) with structural MRI data, at baseline and at clinical follow-up assessments (6-12-month). Efficacy outcomes were the annualized percentage change (APC) in hippocampal, ventricular, and total grey matter volumes, as well as in the AD cortical thickness signature. Participants were classified into MRI subtypes as typical AD, limbic-predominant, hippocampal-sparing, or minimal atrophy at baseline. We primarily applied a subtyping approach based on continuous scale of two subtyping dimensions. We also used the conventional categorical subtyping approach for comparison.

RESULTS

Donepezil-treated MCI individuals showed slower atrophy rates compared to the placebo group, but only if they belonged to the minimal atrophy or hippocampal-sparing subtypes. Importantly, only the continuous subtyping approach, but not the conventional categorical approach, captured this differential response.

CONCLUSIONS

Our data suggest that individuals with MCI, with hippocampal-sparing or minimal atrophy subtype, may have improved benefit from donepezil, as compared with MCI individuals with typical or limbic-predominant patterns of atrophy. The newly proposed continuous subtyping approach may have advantages compared to the conventional categorical approach. Future research is warranted to demonstrate the potential of subtype stratification for disease prognosis and response to treatment.

TRIAL REGISTRATION

ClinicalTrial.gov NCT00403520. Submission Date: November 21, 2006.

Usefulness of the Visual Cognitive Assessment Test in Detecting Mild Cognitive Impairment in the Community

BACKGROUND

A delay in the detection of mild cognitive impairment (MCI) in the community delays the opportunity for early intervention. Accurate tools to detect MCI in the community are lacking. The Visual Cognitive Assessment Test (VCAT) is a visual based cognitive test useful for multilingual populations without the need for translation.

OBJECTIVE

Here, we evaluate the usefulness of VCAT in detecting MCI in a community population in Singapore.

METHODS

We recruited 301 participants from the community who completed a detailed neuropsychological assessment and 170 of them completed a 3T magnetic resonance imaging (MRI) brain scan. We performed a receiver operating characteristics analysis to test the diagnostic performance of VCAT compared to Montreal Cognitive Assessment (MoCA) in distinguishing MCI from cognitively normal (CN) by measuring area under the curve (AUC). To test for the association of VCAT with structural MRI, we performed a Pearson's correlation analysis for VCAT and MRI variables.

RESULTS

We recruited 39 CN and 262 MCI participants from Dementia Research Centre (Singapore). Mean age of the cohort was 63.64, SD = 9.38, mean education years was 13.59, SD = 3.70 and majority were women (55.8%). VCAT was effective in detecting MCI from CN with an AUC of 0.794 (95% CI 0.723-0.865) which was slightly higher than MoCA 0.699 (95% CI 0.621-0.777). Among subjects with MCI, VCAT was associated with medial temporal lobe atrophy (ρ = -0.265, p = 0.001).

CONCLUSIONS

The VCAT is useful in detecting MCI in the community in Singapore and may be an effective measure of neurodegeneration.

Exploring the ATN classification system using brain morphology

BACKGROUND

The NIA-AA proposed amyloid-tau-neurodegeneration (ATN) as a classification system for AD biomarkers. The amyloid cascade hypothesis (ACH) implies a sequence across ATN groups that patients might undergo during transition from healthy towards AD: A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+. Here we assess the evidence for monotonic brain volume decline for this particular (amyloid-conversion first, tau-conversion second, N-conversion last) and alternative progressions using voxel-based morphometry (VBM) in a large cross-sectional MRI cohort.

METHODS

We used baseline data of the DELCODE cohort of 437 subjects (127 controls, 168 SCD, 87 MCI, 55 AD patients) which underwent lumbar puncture, MRI scanning, and neuropsychological assessment. ATN classification was performed using CSF-Aβ42/Aβ40 (A+/-), CSF phospho-tau (T+/-), and adjusted hippocampal volume or CSF total-tau (N+/-). We compared voxel-wise model evidence for monotonic decline of gray matter volume across various sequences over ATN groups using the Bayesian Information Criterion (including also ROIs of Braak stages). First, face validity of the ACH transition sequence A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+ was compared against biologically less plausible (permuted) sequences among AD continuum ATN groups. Second, we evaluated evidence for 6 monotonic brain volume progressions from A-T-N- towards A+T+N+ including also non-AD continuum ATN groups.

RESULTS

The ACH-based progression A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+ was consistent with cognitive decline and clinical diagnosis. Using hippocampal volume for operationalization of neurodegeneration (N), ACH was most evident in 9% of gray matter predominantly in the medial temporal lobe. Many cortical regions suggested alternative non-monotonic volume progressions over ACH progression groups, which is compatible with an early amyloid-related tissue expansion or sampling effects, e.g., due to brain reserve. Volume decline in 65% of gray matter was consistent with a progression where A status converts before T or N status (i.e., ACH/ANT) when compared to alternative sequences (TAN/TNA/NAT/NTA). Brain regions earlier affected by tau tangle deposition (Braak stage I-IV, MTL, limbic system) present stronger evidence for volume decline than late Braak stage ROIs (V/VI, cortical regions). Similar findings were observed when using CSF total-tau for N instead.

CONCLUSION

Using the ATN classification system, early amyloid status conversion (before tau and neurodegeneration) is associated with brain volume loss observed during AD progression. The ATN system and the ACH are compatible with monotonic progression of MTL atrophy.

TRIAL REGISTRATION

DRKS00007966, 04/05/2015, retrospectively registered.

The Clinical Application of Optimized AT(N) Classification in Alzheimer’s Clinical Syndrome (ACS) and non-ACS Conditions

We aimed to assess the utility of AT(N) classification in clinical practice. We measured the cerebrospinal fluid levels of amyloid-β (Aβ) 42, Aβ40, phosphorylated tau, total tau, and neurofilament light chain (NfL) in samples from 230 patients with Alzheimer's clinical syndrome (ACS) and 328 patients with non-ACS. The concordance of two A-markers (i.e., Aβ42 alone and the Aβ42/Aβ40 ratio) was not significantly different between the ACS (87.4%) and non-ACS (74.1%) groups. However, the frequency of discordant cases with A_Aβ42-alone+/A_Aβ-ratio- was significantly higher in the non-ACS (23.8%) than in the ACS group (7.4%). The concordance of two N-markers (i.e., total tau and NfL) was 40.4% in the ACS group and 24.4% in the non-ACS group. In the ACS samples, the frequency of biological Alzheimer's disease (i.e., A+T+) in N_tau+ cases was 95% while that in N_NfL+ cases was 65%. Reflecting Aβ deposition and neurodegeneration more accurately, we recommend the use of AT(N) classification defined by cerebrospinal fluid A_Aβ-ratioTN_NfL in clinical practice.

Associations between different tau-PET patterns and longitudinal atrophy in the Alzheimer's disease continuum: biological and methodological perspectives from disease heterogeneity

BACKGROUND

Subtypes and patterns are defined using tau-PET (tau pathology) and structural MRI (atrophy) in Alzheimer's disease (AD). However, the relationship between tau pathology and atrophy across these subtypes/patterns remains unclear. Therefore, we investigated the biological association between baseline tau-PET patterns and longitudinal atrophy in the AD continuum; and the methodological characterization of heterogeneity as a continuous phenomenon over the conventional discrete subgrouping.

METHODS

In 366 individuals (amyloid-beta-positive cognitively normal, prodromal AD, AD dementia; amyloid-beta-negative cognitively normal), we examined the association between tau-PET patterns and longitudinal MRI. We modeled tau-PET patterns as a (a) continuous phenomenon with key dimensions: typicality and severity; and (b) discrete phenomenon by categorization into patterns: typical, limbic predominant, cortical predominant and minimal tau. Tau-PET patterns and associated longitudinal atrophy were contextualized within the Amyloid/Tau/Neurodegeneration (A/T/N) biomarker scheme.

RESULTS

Localization and longitudinal atrophy change vary differentially across different tau-PET patterns in the AD continuum. Atrophy, a downstream event, did not always follow a topography akin to the corresponding tau-PET pattern. Further, heterogeneity as a continuous phenomenon offered an alternative and useful characterization, sharing correspondence with the conventional subgrouping. Tau-PET patterns also show differential A/T/N profiles.

CONCLUSIONS

The site and rate of atrophy are different across the tau-PET patterns. Heterogeneity should be treated as a continuous, not discrete, phenomenon for greater sensitivity. Pattern-specific A/T/N profiles highlight differential multimodal interactions underlying heterogeneity. Therefore, tracking multimodal interactions among biomarkers longitudinally, modeling disease heterogeneity as a continuous phenomenon, and examining heterogeneity across the AD continuum could offer avenues for precision medicine.

Criterion Validation of Tau PET Staging Schemes in Relation to Cognitive Outcomes

BACKGROUND

Utilization of NIA-AA Research Framework requires dichotomization of tau pathology. However, due to the novelty of tau-PET imaging, there is no consensus on methods to categorize scans into "positive" or "negative" (T+ or T-). In response, some tau topographical pathologic staging schemes have been developed.

OBJECTIVE

The aim of the current study is to establish criterion validity to support these recently-developed staging schemes.

METHODS

Tau-PET data from 465 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90) were classified as T+ or T- using decision rules for the Temporal-Occipital Classification (TOC), Simplified TOC (STOC), and Lobar Classification (LC) tau pathologic schemes of Schwarz, and Chen staging scheme. Subsequent dichotomization was analyzed in comparison to memory and learning slope performances, and diagnostic accuracy using actuarial diagnostic methods.

RESULTS

Tau positivity was associated with worse cognitive performance across all staging schemes. Cognitive measures were nearly all categorized as having "fair" sensitivity at classifying tau status using TOC, STOC, and LC schemes. Results were comparable between Schwarz schemes, though ease of use and better data fit preferred the STOC and LC schemes. While some evidence was supportive for Chen's scheme, validity lagged behind others-likely due to elevated false positive rates.

CONCLUSIONS

Tau-PET staging schemes appear to be valuable for Alzheimer's disease diagnosis, tracking, and screening for clinical trials. Their validation provides support as options for tau pathologic dichotomization, as necessary for use of NIA-AA Research Framework. Future research should consider other staging schemes and validation with other outcome benchmarks.

Identification of causal effects of neuroanatomy on cognitive decline requires modeling unobserved confounders

INTRODUCTION

Carrying out a randomized controlled trial to estimate the causal effects of regional brain atrophy due to Alzheimer's disease (AD) is impossible. Instead, we must estimate causal effects from observational data. However, this generally requires knowing and having recorded all confounders, which is often unrealistic.

METHODS

We provide an approach that leverages the dependencies among multiple neuroanatomical measures to estimate causal effects from observational neuroimaging data without the need to know and record all confounders.

RESULTS

Our analyses of N = 732 $N=732$ subjects from the Alzheimer's Disease Neuroimaging Initiative demonstrate that using our approach results in biologically meaningful conclusions, whereas ignoring unobserved confounding yields results that conflict with established knowledge on cognitive decline due to AD.

DISCUSSION

The findings provide evidence that the impact of unobserved confounding can be substantial. To ensure trustworthy scientific insights, future AD research can account for unobserved confounding via the proposed approach.

Different AT(N) profiles and clinical progression classified by two different N markers using total tau and neurofilament light chain in cerebrospinal fluid

Background

The AT(N) classification was proposed for categorising individuals according to biomarkers. However, AT(N) profiles may vary depending on the markers chosen and the target population.

Methods

We stratified 177 individuals who participated in the Japanese Alzheimer's Disease Neuroimaging Initiative by AT(N) classification according to cerebrospinal fluid (CSF) biomarkers. We compared the frequency of AT(N) profiles between the classification using total tau and neurofilament light chain (NfL) as N markers (AT(N)_tau and AT(N)_NfL). Baseline characteristics, and longitudinal biological and clinical changes were examined between AT(N) profiles.

Results

We found that 9% of cognitively unimpaired subjects, 49% of subjects with mild cognitive impairment, and 61% of patients with Alzheimer's disease (AD) dementia had the biological AD profile (ie, A+T+) in the cohort. The frequency of AT(N) profiles substantially differed between the AT(N)_tau and AT(N)_NfL classifications. When we used t-tau as the N marker (AT(N)_tau), those who had T- were more frequently assigned to (N)-, whereas those who had T+were more frequently assigned to (N)+ than when we used NfL as the N marker (AT(N)_NfL). During a follow-up, the AD continuum group progressed clinically and biologically compared with the normal biomarker group in both the AT(N)_tau and AT(N)_NfL classifications. More frequent conversion to dementia was observed in the non-AD pathological change group in the AT(N)_tau classification, but not in the AT(N)_NfL classification.

Conclusions

AT(N)_tau and AT(N)_NfL in CSF may capture different aspects of neurodegeneration and provide a different prognostic value. The AT(N) classification aids in understanding the AD continuum biology in various populations.

Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer's disease

Understanding Alzheimer's disease (AD) heterogeneity is important for understanding the underlying pathophysiological mechanisms of AD. However, AD atrophy subtypes may reflect different disease stages or biologically distinct subtypes. Here we use longitudinal magnetic resonance imaging data (891 participants with AD dementia, 305 healthy control participants) from four international cohorts, and longitudinal clustering to estimate differential atrophy trajectories from the age of clinical disease onset. Our findings (in amyloid-β positive AD patients) show five distinct longitudinal patterns of atrophy with different demographical and cognitive characteristics. Some previously reported atrophy subtypes may reflect disease stages rather than distinct subtypes. The heterogeneity in atrophy rates and cognitive decline within the five longitudinal atrophy patterns, potentially expresses a complex combination of protective/risk factors and concomitant non-AD pathologies. By alternating between the cross-sectional and longitudinal understanding of AD subtypes these analyses may allow better understanding of disease heterogeneity.

Cross-Sectional and Longitudinal Hippocampal Atrophy, Not Cortical Thinning, Occurs in Amyloid-Negative, p-Tau-Positive, Older Adults With Non-Amyloid Pathology and Mild Cognitive Impairment

Introduction

Alzheimer's disease (AD) is a degenerative disease characterized by pathological accumulation of amyloid and phosphorylated tau. Typically, the early stage of AD, also called mild cognitive impairment (MCI), shows amyloid pathology. A small but significant number of individuals with MCI do not exhibit amyloid pathology but have elevated phosphorylated tau levels (A-T+ MCI). We used CSF amyloid and phosphorylated tau to identify the individuals with A+T+ and A-T+ MCI as well as cognitively normal (A-T-) controls. To increase the sample size, we leveraged the Global Alzheimer's Association Interactive Network and identified 137 MCI+ and 61 A-T+ MCI participants. We compared baseline and longitudinal, hippocampal, and cortical atrophy between groups.

Methods

We applied ComBat harmonization to minimize site-related variability and used FreeSurfer for all measurements.

Results

Harmonization reduced unwanted variability in cortical thickness by 3.4% and in hippocampal volume measurement by 10.3%. Cross-sectionally, widespread cortical thinning with age was seen in the A+T+ and A-T+ MCI groups (p < 0.0005). A decrease in the hippocampal volume with age was faster in both groups (p < 0.05) than in the controls. Longitudinally also, hippocampal atrophy rates were significant (p < 0.05) when compared with the controls. No longitudinal cortical thinning was observed in A-T+ MCI group.

Discussion

A-T+ MCI participants showed similar baseline cortical thickness patterns with aging and longitudinal hippocampal atrophy rates as participants with A+T+ MCI, but did not show longitudinal cortical atrophy signature.

Hippocampal Atrophy Subtypes of Alzheimer's Disease Using Automatic MRI in a Memory Clinic Cohort: Clinical Implications

INTRODUCTION

One pathological hallmark of Alzheimer's disease (AD) is atrophy of medial temporal brain regions that can be visualized on magnetic resonance imaging (MRI), but not all patients will have atrophy. The aim was to use MRI to categorize patients according to their hippocampal atrophy status and to present prevalence of the subtypes, difference in clinical symptomatology and progression, and factors associated with hippocampal subtypes.

METHODS

We included 215 patients with AD who had been assessed with the clinically available MRI software NeuroQuant (NQ; CorTechs labs/University of California, San Diego, CA, USA). NQ measures the hippocampus volume and calculates a normative percentile. Atrophy was regarded to be present if the percentile was ≤5. Demographics, cognitive measurements, AD phenotypes, apolipoprotein E status, and results from cerebrospinal fluid and amyloid positron emission tomography analyses were included as explanatory variables of the hippocampal subtypes.

RESULTS

Of all, 60% had no hippocampal atrophy. These patients were younger and less cognitively impaired concerning global measures, memory function, and abstraction but impaired concerning executive, visuospatial, and semantic fluency, and more of them had nonamnestic AD, compared to those with hippocampal atrophy. No difference in progression rate was observed between the two groups. In mild cognitive impairment patients, amyloid pathology was associated with the no hippocampal atrophy group.

CONCLUSION

The results have clinical implications. Clinicians should be aware of the large proportion of AD patients presenting without atrophy of the hippocampus as measured with this clinical MRI method in the diagnostic set up and that nonamnestic phenotypes are more common in this group as compared to those with atrophy. Furthermore, the findings are relevant in clinical trials.

Alpha desynchronization during Stroop test unmasks cognitively healthy individuals with abnormal CSF Amyloid/Tau

Synaptic dysfunctions precede cognitive decline in Alzheimer's disease by decades, affect executive functions, and can be detected by quantitative electroencephalography (qEEG). We used quantitative electroencephalography combined with Stroop testing to identify changes of inhibitory controls in cognitively healthy individuals with an abnormal versus normal ratio of cerebrospinal fluid (CSF) amyloid/total-tau. We studied two groups of participants (60-94 years) with either normal (CH-NAT or controls, n = 20) or abnormal (CH-PAT, n = 21) CSF amyloid/tau ratio. We compared: alpha event-related desynchronization (ERD), alpha spectral entropy (SE), and their relationships with estimated cognitive reserve. CH-PATs had more negative occipital alpha ERD, and higher frontal and occipital alpha SE during low load congruent trials, indicating hyperactivity. CH-PATs demonstrated fewer frontal SE changes with higher load, incongruent Stroop testing. Correlations of alpha ERD with estimated cognitive reserve were significant in CH-PATs but not in CH-NATs. These results suggested compensatory hyperactivity in CH-PATs compared to CH-NATs. We did not find differences in alpha ERD comparisons with individual CSF amyloid(A), p-tau(T), total-tau(N) biomarkers.

Brain Atrophy and Clinical Characterization of Adults With Mild Cognitive Impairment and Different Cerebrospinal Fluid Biomarker Profiles According to the AT(N) Research Framework of Alzheimer’s Disease

Introduction

This study aimed to evaluate, in adults with mild cognitive impairment (MCI), the brain atrophy that may distinguish between three AT(N) biomarker-based profiles, and to determine its clinical value.

Methods

Structural MRI (sMRI) was employed to evaluate the volume and cortical thickness differences in MCI patients with different AT(N) profiles, namely, A−T−(N)−: normal AD biomarkers; A+T−(N)−: AD pathologic change; and A+T+(N)+: prodromal AD. Sensitivity and specificity of these changes were also estimated.

Results

An initial atrophy in medial temporal lobe (MTL) areas was found in the A+T−(N)− and A+T+(N)+ groups, spreading toward the parietal and frontal regions in A+T+(N)+ patients. These structural changes allowed distinguishing AT(N) profiles within the AD continuum; however, the profiles and their pattern of neurodegeneration were unsuccessful to determine the current clinical status.

Conclusion

sMRI is useful in the determination of the specific brain structural changes of AT(N) profiles along the AD continuum, allowing differentiation between MCI adults with or without pathological AD biomarkers.

Analysis of Brain Structural Connectivity Networks and White Matter Integrity in Patients With Mild Cognitive Impairment

White matter integrity and structural connectivity may be altered in mild cognitive impairment (MCI), and these changes may closely reflect decline in specific cognitive domains. Multi-shell diffusion data in healthy control (HC, n = 31) and mild cognitive impairment (MCI, n = 19) cohorts were downloaded from the ADNI3 database. The data were analyzed using an advanced approach to assess both white matter microstructural integrity and structural connectivity. Compared with HC, lower intracellular compartment (IC) and higher isotropic (ISO) values were found in MCI. Additionally, significant correlations were found between IC and Montreal Cognitive Assessment (MoCA) scores in the MCI cohort. Network analysis detected structural connectivity differences between the two groups, with lower connectivity in MCI. Additionally, significant differences between HC and MCI were observed for global network efficiency. Our results demonstrate the potential of advanced diffusion MRI biomarkers for understanding brain changes in MCI.

The Outcome of Patients with Amyloid-Negative Amnestic Mild Cognitive Impairment

Background: Patients with amnestic mild cognitive impairment (aMCI) are usually at an initial stage of Alzheimer’s disease (AD). However, some patients with aMCI do not present biomarkers of amyloid pathology characteristic of AD. The significance of amyloid-negative aMCI is not presently clear. Objective: To know the etiology and prognosis of amyloid-negative aMCI. Methods: Patients who fulfilled criteria for aMCI and were amyloid negative were selected from a large cohort of non-demented patients with cognitive complaints and were followed with clinical and neuropsychological assessments. Results: Few amyloid-negative aMCI had evidence of neurodegeneration at the baseline, as reflected in cerebrospinal fluid elevated tau protein levels. About half of the patients remained essentially stable for long periods of time. Others manifested a psychiatric disorder that was not apparent at baseline, namely major depression or bipolar disorder. Remarkably, about a quarter of patients developed neurodegenerative disorders other than AD, mostly frontotemporal dementia or Lewy body disease. Conclusion: Amyloid-negative aMCI is a heterogeneous condition. Many patients remain clinically stable, but others may later manifest psychiatric conditions or evolve to neurodegenerative disorders. Prudence is needed when communicating to the patient and family the results of biomarkers, and clinical follow-up should be advised.

Simple Quantification of Surface Uptake in F-18 Florapronol PET/CT Imaging for the Validation of Alzheimer’s Disease

We developed a novel quantification method named shape feature using F-18 florapronol positron emission tomography–computed tomography (PET/CT) and evaluated its sensitivity and specificity for discriminating between patients with Alzheimer’s disease (AD) and patients with mild cognitive impairment or other precursors dementia (non-AD). We calculated the cerebral amyloid smoothing score (CASS) and brain atrophy index (BAI) using the surface area and volume of the region of interest in PET images. We calculated gray and white matter from trained CT data, prepared using U-net. Shape feature was calculated by multiplying CASS with BAI scores. We measured region-based standard uptake values (SUVr) and performed receiver operating characteristic (ROC) analysis to compare SUVr, shape feature, CASS, and BAI score. We investigated the relationship between shape feature and neuropsychological tests. Fifty subjects (23 with AD and 27 with non-AD) were evaluated. SUVr, shape feature, CASS, and BAI score were significantly higher in patients with AD than in those with non-AD. There was no statistically significant difference between shape feature and SUVr in ROC analysis. Shape feature correlated well with mini-mental state examination scores. Shape feature can effectively quantify beta-amyloid deposition and atrophic changes in the brain. These results suggest that shape feature is useful in the diagnosis of AD.

Prediction of Cognitive Progression in Individuals with Mild Cognitive Impairment Using Radiomics as an Improvement of the ATN System: A Five-Year Follow-Up Study

Objective

To improve the N biomarker in the amyloid/tau/neurodegeneration system by radiomics and study its value for predicting cognitive progression in individuals with mild cognitive impairment (MCI).

Materials and Methods

A group of 147 healthy controls (HCs) (72 male; mean age ± standard deviation, 73.7 ± 6.3 years), 197 patients with MCI (114 male; 72.2 ± 7.1 years), and 128 patients with Alzheimer’s disease (AD) (74 male; 73.7 ± 8.4 years) were included. Optimal A, T, and N biomarkers for discriminating HC and AD were selected using receiver operating characteristic (ROC) curve analysis. A radiomics model containing comprehensive information of the whole cerebral cortex and deep nuclei was established to create a new N biomarker. Cerebrospinal fluid (CSF) biomarkers were evaluated to determine the optimal A or T biomarkers. All MCI patients were followed up until AD conversion or for at least 60 months. The predictive value of A, T, and the radiomics-based N biomarker for cognitive progression of MCI to AD were analyzed using Kaplan-Meier estimates and the log-rank test.

Results

The radiomics-based N biomarker showed an ROC curve area of 0.998 for discriminating between AD and HC. CSF Aβ42 and p-tau proteins were identified as the optimal A and T biomarkers, respectively. For MCI patients on the Alzheimer’s continuum, isolated A+ was an indicator of cognitive stability, while abnormalities of T and N, separately or simultaneously, indicated a high risk of progression. For MCI patients with suspected non-Alzheimer’s disease pathophysiology, isolated T+ indicated cognitive stability, while the appearance of the radiomics-based N+ indicated a high risk of progression to AD.

Conclusion

We proposed a new radiomics-based improved N biomarker that could help identify patients with MCI who are at a higher risk for cognitive progression. In addition, we clarified the value of a single A/T/N biomarker for predicting the cognitive progression of MCI.

The probabilistic model of Alzheimer disease: the amyloid hypothesis revised

The current conceptualization of Alzheimer disease (AD) is driven by the amyloid hypothesis, in which a deterministic chain of events leads from amyloid deposition and then tau deposition to neurodegeneration and progressive cognitive impairment. This model fits autosomal dominant AD but is less applicable to sporadic AD. Owing to emerging information regarding the complex biology of AD and the challenges of developing amyloid-targeting drugs, the amyloid hypothesis needs to be reconsidered. Here we propose a probabilistic model of AD in which three variants of AD (autosomal dominant AD, APOE ε4-related sporadic AD and APOE ε4-unrelated sporadic AD) feature decreasing penetrance and decreasing weight of the amyloid pathophysiological cascade, and increasing weight of stochastic factors (environmental exposures and lower-risk genes). Together, these variants account for a large share of the neuropathological and clinical variability observed in people with AD. The implementation of this model in research might lead to a better understanding of disease pathophysiology, a revision of the current clinical taxonomy and accelerated development of strategies to prevent and treat AD.

Neuroimaging Biomarkers Predicting the Efficacy of Multimodal Rehabilitative Intervention in the Alzheimer's Dementia Continuum Pathology

In this work we aimed to identify neural predictors of the efficacy of multimodal rehabilitative interventions in AD-continuum patients in the attempt to identify ideal candidates to improve the treatment outcome. Subjects in the AD continuum who participated in a multimodal rehabilitative treatment were included in the analysis [n = 82, 38 Males, mean age = 76 ± 5.30, mean education years = 9.09 ± 3.81, Mini Mental State Examination (MMSE) mean score = 23.31 ± 3.81]. All subjects underwent an MRI acquisition (1.5T) at baseline (T0) and a neuropsychological evaluation before (T0) and after intervention (T1). All subjects underwent an intensive multimodal cognitive rehabilitation (8–10 weeks). The MMSE and Neuropsychiatric Inventory (NPI) scores were considered as the main cognitive and behavioral outcome measures, and Delta change scores (T1–T0) were categorized in Improved (ΔMMSE > 0; ΔNPI < 0) and Not Improved (ΔMMSE ≤ 0; ΔNPI ≥ 0). Logistic Regression (LR) and Random Forest classification models were performed including neural markers (Medial Temporal Brain; Posterior Brain (PB); Frontal Brain (FB), Subcortical Brain indexes), neuropsychological (MMSE, NPI, verbal fluencies), and demographical variables (sex, age, education) at baseline. More than 50% of patients showed a positive effect of the treatment (ΔMMSE > 0: 51%, ΔNPI < 0: 52%). LR model on ΔMMSE (Improved vs. Not Improved) indicate a predictive role for MMSE score (p = 0.003) and PB index (p = 0.005), especially the right PB (p = 0.002) at baseline. The Random Forest analysis correctly classified 77% of cognitively improved and not improved AD patients. Concerning the NPI, LR model on ΔNPI (Improved vs. Not Improved) showed a predictive role of sex (p = 0.002), NPI (p = 0.005), PB index (p = 0.006), and FB index (p = 0.039) at baseline. The Random Forest reported a classification accuracy of 86%. Our data indicate that cognitive and behavioral status alone are not sufficient to identify best responders to a multidomain rehabilitation treatment. Increased neural reserve, especially in the parietal areas, is also relevant for the compensatory mechanisms activated by rehabilitative treatment. These data are relevant to support clinical decision by identifying target patients with high probability of success after rehabilitative programs on cognitive and behavioral functioning.

Dorsolateral prefrontal cortex excitability abnormalities in Alzheimer's Dementia: Findings from transcranial magnetic stimulation and electroencephalography study

There is some evidence of cortical hyper-excitability in Alzheimer's Dementia (AD) but its relationship with cognition is not clear. In this study, we assessed dorsolateral prefrontal cortex (DLPFC) excitability and its relationship with cognition in AD. Twenty-four participants with AD (mean [SD] age = 74.1 [7.2] years) and eleven elderly healthy controls (HC) (mean [SD] age = 68.8 [7.3] years) were recruited. Transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) was used to assess cortical excitability. Cortical evoked activity (CEA) between 25 and 80 ms post-TMS stimulus was calculated as the primary measure of cortical excitability. TMS-evoked potential peak (TEP) amplitudes (P30, N45 and P60) were also calculated. Cognition was assessed using Montreal Cognitive Assessment (MoCA), Executive Interview (EXIT) and Cambridge Neuropsychological Test Automated Battery Stockings of Cambridge (SOC). There was no difference in TMS stimulus intensity between the groups. DLPFC-CEA was higher in the AD (mean [SD] = 134.64 [90.22] μV) than the HC group (mean [SD] = 82.65 [40.28] μV; t₃₃ = 2.357, p = 0.025). There were no differences in TEP peak amplitudes between the groups. Further, DLPFC-CEA was inversely associated with MoCA and SOC, and positively associated with EXIT scores in AD. These results suggest increased DLPFC excitability in AD, and its inverse associations with global cognition and executive function. Future studies should examine these findings in larger samples and longitudinally, and could also assess these markers of cortical excitability in relation to other established markers of AD and in response to interventions.

Quantitative Assessment of Cortical Excitability in Alzheimer's Dementia and Its Association with Clinical Symptoms: A Systematic Review and Meta-Analyses

BACKGROUND

Alzheimer's disease (AD) is characterized by cognitive and neuropsychiatric symptoms (NPS) due to underlying neurodegenerative pathology. Some studies using electroencephalography (EEG) have shown increased epileptiform and epileptic activity in AD.

OBJECTIVE

This review and meta-analyses aims to synthesize the existing evidence for quantitative abnormalities of cortical excitability in AD and their relationship with clinical symptoms.

METHODS

We systematically searched and reviewed publications that quantitatively assessed cortical excitability, using transcranial magnetic stimulation (TMS) resting motor threshold (rMT), active motor threshold (aMT), motor evoked potential (MEP) or directly from the cortex using TMS-EEG via TMS-evoked potential (TEP). We meta-analyzed studies that assessed rMT and aMT using random effects model.

RESULTS

We identified 895 publications out of which 37 were included in the qualitative review and 30 studies using rMT or aMT were included in the meta-analyses. The AD group had reduced rMT (Hedges' g = -0.99, 95%CI [-1.29, -0.68], p <  0.00001) and aMT (Hedges' g = -0.87, 95%CI [-1.50, -0.24], p <  0.00001) as compared with control groups, indicative of higher cortical excitability. Qualitative review found some evidence of increased MEP amplitude, whereas findings related to TEP were inconsistent. There was some evidence supporting an inverse association between cortical excitability and global cognition. No publications reported on the relationship between cortical excitability and NPS.

CONCLUSION

There is strong evidence of increased motor cortex excitability in AD and some evidence of an inverse association between excitability and cognition. Future studies should assess cortical excitability from non-motor areas using TMS-EEG and examine its relationship with cognition and NPS.

Association of Vitamin D Receptor Polymorphisms with Amyloid-β Transporters Expression and Risk of Mild Cognitive Impairment in a Chilean Cohort

Background: Amyloid-β peptide (Aβ) deposition in Alzheimer’s disease (AD) is due to an imbalance in its production/clearance rate. Aβ is transported across the blood-brain barrier by LRP1 and P-gp as efflux transporters and RAGE as influx transporter. Vitamin D deficit and polymorphisms of the vitamin D receptor (VDR) gene are associated with high prevalence of mild cognitive impairment (MCI) and AD. Further, vitamin D promotes the expression of LRP1 and P-gp in AD-animal model brains. Objective: To associate VDR polymorphisms Apa I (rs7975232), Taq I (rs731236), and Fok I (rs2228570) with the risk of developing MCI in a Chilean population, and to evaluate the relationship of these polymorphisms to the expression of VDR and Aβ-transporters in peripheral blood mononuclear cells (PBMCs). Methods: VDR polymorphisms Apa I, Taq I, and Fok I were determined in 128 healthy controls (HC) and 66 MCI patients. mRNA levels of VDR and Aβ-transporters were evaluated in subgroups by qPCR. Results: Alleles A of Apa I and C of Taq I were associated with a lower risk of MCI. HC with the Apa I AA genotype had higher mRNA levels of P-gp and LRP1, while the expression of VDR and RAGE were higher in MCI patients and HC. For Fok I, the TC genotype was associated with lower expression levels of Aβ-transporters in both groups. Conclusion: We propose that the response to vitamin D treatment will depend on VDR polymorphisms, being more efficient in carriers of protective alleles of Apa I polymorphism.

A Review of Brain Atrophy Subtypes Definition and Analysis for Alzheimer’s Disease Heterogeneity Studies

Alzheimer’s disease (AD) is a heterogeneous disease with different subtypes. Studying AD subtypes from brain structure, neuropathology, and cognition are of great importance for AD heterogeneity research. Starting from the study of constructing AD subtypes based on the features of T1-weighted structural magnetic resonance imaging, this paper introduces the major connections between the subtype definition and analysis strategies, including brain region-based subtype definition, and their demographic, neuropathological, and neuropsychological characteristics. The advantages and existing problems are analyzed, and reasonable improvement schemes are prospected. Overall, this review offers a more comprehensive view in the field of atrophy subtype in AD, along with their advantages, challenges, and future prospects, and provide a basis for improving individualized AD diagnosis.

The Amyloid, Tau, and Neurodegeneration (A/T/N) Classification Applied to a Clinical Research Cohort with Long-Term Follow-Up

Background:

The unbiased amyloid, tau, and neurodegeneration (A/T/N) classification is designed to characterize individuals in the Alzheimer continuum and is currently little explored in clinical cohorts.

Objective:

A retrospective comparison of the A/T/N classification system with the results of a two-year clinical study, with extended follow-up up to 10 years after inclusion.

Methods:

Patients (n = 102) clinically diagnosed as Alzheimer’s disease (AD) with dementia or amnestic mild cognitive impairment (MCI), and 61 cognitively healthy control individuals were included. Baseline cerebrospinal fluid core biomarkers for AD (Aβ₄₂, phosphorylated tau, and total tau) were applied to the A/T/N classification using the final clinical diagnosis at extended follow-up as the gold standard.

Results:

A + T + N+ was a strong predictor for AD dementia, even among cognitively healthy individuals. Amnestic MCI was heterogenous, considering both clinical outcome and distribution within A/T/N. Some individuals with amnestic MCI progressed to clinical AD dementia within all four major A/T/N groups. The highest proportion of progression was among triple positive cases, but progression was also common in individuals with suspected non-Alzheimer pathophysiology (A-T + N+), and those with triple negative status. A-T-N- individuals who were cognitively healthy overwhelmingly remained cognitively intact over time, but in amnestic MCI the clinical outcome was heterogenous, including AD dementia, other dementias, and recovery.

Conclusion:

The A/T/N framework accentuates biomarkers over clinical status. However, when selecting individuals for research, a combination of the two may be necessary since the prognostic value of the A/T/N framework depends on clinical status.

Brain Atrophy Subtypes and the ATN Classification Scheme in Alzheimer's Disease

INTRODUCTION

We investigated the association between atrophy subtypes of Alzheimer's disease (AD), the ATN classification scheme, and key demographic and clinical factors in 2 cohorts with different source characteristics (a highly selective research-oriented cohort, the Alzheimer's Disease Neuroimaging Initiative [ADNI]; and a naturalistic heterogeneous clinically oriented cohort, Karolinska Imaging Dementia Study [KIDS]).

METHODS

A total of 382 AD patients were included. Factorial analysis of mixed data was used to investigate associations between AD subtypes based on brain atrophy patterns, ATN profiles based on cerebrospinal fluid biomarkers, and age, sex, Mini Mental State Examination (MMSE), cerebrovascular disease (burden of white matter signal abnormalities, WMSAs), and APOE genotype.

RESULTS

Older patients with high WMSA burden, belonging to the typical AD subtype and showing A+T+N+ or A+T+N- profiles clustered together and were mainly from ADNI. Younger patients with low WMSA burden, limbic-predominant or minimal atrophy AD subtypes, and A+T-N- or A+T-N+ profiles clustered together and were mainly from KIDS. APOE ε4 carriers more frequently showed the A+T-N- and A+T+N- profiles.

CONCLUSIONS

Our findings align with the recent framework for biological subtypes of AD: the combination of risk factors, protective factors, and brain pathologies determines belonging of AD patients to distinct subtypes.

Evaluation of the ATN model in a longitudinal memory clinic sample with different underlying disorders

INTRODUCTION

To evaluate the usefulness of the 2018 NIA-AA (National Institute on Aging and Alzheimer's Association) research framework in a longitudinal memory clinic study with different clinical outcomes and underlying disorders.

METHODS

We included 420 patients with mild cognitive impairment or subjective cognitive impairment. During the follow up, 27% of the patients converted to dementia, with the majority converting to Alzheimer's disease (AD) or mixed dementia. Based on the baseline values of the cerebrospinal fluid biomarkers, the patients were classified into one of the eight possible ATN groups (amyloid beta [Aβ] aggregation [A], tau aggregation reflecting neurofibrillary tangles [T], and neurodegeneration [N]).

RESULTS

The majority of the patients converting to AD and mixed dementia were in ATN groups positive for A (71%). The A+T+N+ group was highly overrepresented among converters to AD and mixed dementia. Patients converting to dementias other than AD or mixed dementia were evenly distributed across the ATN groups.

DISCUSSION

Our findings provide support for the usefulness of the ATN system to detect incipient AD or mixed dementia.

Research diagnostic criteria for Alzheimer's disease: findings from the LipiDiDiet randomized controlled trial

Background

To explore the utility of the International Working Group (IWG)-1 criteria in recruitment for Alzheimer’s disease (AD) clinical trials, we applied the more recently proposed research diagnostic criteria to individuals enrolled in a randomized controlled prevention trial (RCT) and assessed their disease progression.

Methods

The multinational LipiDiDiet RCT targeted 311 individuals with IWG-1 defined prodromal AD. Based on centrally analyzed baseline biomarkers, participants were classified according to the IWG-2 and National Institute on Aging–Alzheimer’s Association (NIA-AA) 2011 and 2018 criteria. Linear mixed models were used to investigate the 2-year change in cognitive and functional performance (Neuropsychological Test Battery NTB Z scores, Clinical Dementia Rating-Sum of Boxes CDR-SB) (criteria × time interactions; baseline score, randomization group, sex, Mini-Mental State Examination (MMSE), and age also included in the models). Cox models adjusted for randomization group, MMSE, sex, age, and study site were used to investigate the risk of progression to dementia over 2 years.

Results

In total, 88%, 86%, and 69% of participants had abnormal cerebrospinal fluid (CSF) β-amyloid, total tau, and phosphorylated tau, respectively; 64% had an A+T+N+ profile (CSF available for N = 107). Cognitive-functional decline appeared to be more pronounced in the IWG-2 prodromal AD, NIA-AA 2011 high and intermediate AD likelihood, and NIA-AA 2018 AD groups, but few significant differences were observed between the groups within each set of criteria. Hazard ratio (95% CI) for dementia was 4.6 (1.6–13.7) for IWG-2 prodromal AD (reference group no prodromal AD), 7.4 (1.0–54.7) for NIA-AA 2011 high AD likelihood (reference group suspected non-AD pathology SNAP), and 9.4 (1.2–72.7) for NIA-AA 2018 AD (reference group non-Alzheimer’s pathologic change). Compared with the NIA-AA 2011 high AD likelihood group (abnormal β-amyloid and neuronal injury markers), disease progression was similar in the intermediate AD likelihood group (medial temporal lobe atrophy; no CSF available).

Conclusions

Despite being less restrictive than the other criteria, the IWG-1 criteria reliably identified individuals with AD pathology. More pragmatic and easily applicable selection criteria might be preferred due to feasibility in certain situations, e.g., in multidomain prevention trials that do not specifically target β-amyloid/tau pathologies.

Trial registration

Netherlands Trial Register, NL1620. Registered on 9 March 2009

Personalized Healthcare for Dementia

Dementia is one of the most common health problems affecting older adults, and the population with dementia is growing. Dementia refers to a comprehensive syndrome rather than a specific disease and is characterized by the loss of cognitive abilities. Many factors are related to dementia, such as aging, genetic profile, systemic vascular disease, unhealthy diet, and physical inactivity. As the causes and types of dementia are diverse, personalized healthcare is required. In this review, we first summarize various diagnostic approaches associated with dementia. Particularly, clinical diagnosis methods, biomarkers, neuroimaging, and digital biomarkers based on advances in data science and wearable devices are comprehensively reviewed. We then discuss three effective approaches to treating dementia, including engineering design, exercise, and diet. In the engineering design section, recent advances in monitoring and drug delivery systems for dementia are introduced. Additionally, we describe the effects of exercise on the treatment of dementia, especially focusing on the effects of aerobic and resistance training on cognitive function, and the effects of diets such as the Mediterranean diet and ketogenic diet on dementia.

Mitochondrial Dysfunction in Alzheimer's Disease: A Biomarker of the Future?

Alzheimer's disease (AD) is the most common cause of dementia worldwide and is characterised pathologically by the accumulation of amyloid beta and tau protein aggregates. Currently, there are no approved disease modifying therapies for clearance of either of these proteins from the brain of people with AD. As well as abnormalities in protein aggregation, other pathological changes are seen in this condition. The function of mitochondria in both the nervous system and rest of the body is altered early in this disease, and both amyloid and tau have detrimental effects on mitochondrial function. In this review article, we describe how the function and structure of mitochondria change in AD. This review summarises current imaging techniques that use surrogate markers of mitochondrial function in both research and clinical practice, but also how mitochondrial functions such as ATP production, calcium homeostasis, mitophagy and reactive oxygen species production are affected in AD mitochondria. The evidence reviewed suggests that the measurement of mitochondrial function may be developed into a future biomarker for early AD. Further work with larger cohorts of patients is needed before mitochondrial functional biomarkers are ready for clinical use.

ATN incorporating cerebrospinal fluid neurofilament light chain detects frontotemporal lobar degeneration

INTRODUCTION

The ATN framework provides an in vivo diagnosis of Alzheimer's disease (AD) using cerebrospinal fluid (CSF) biomarkers of pathologic amyloid plaques (A), tangles (T), and neurodegeneration (N). ATN is rarely evaluated in pathologically confirmed patients and its poor sensitivity to suspected non-Alzheimer's pathophysiologies (SNAP), including frontotemporal lobar degeneration (FTLD), leads to misdiagnoses. We compared accuracy of ATN (ATN_TAU ) using CSF total tau (t-tau) to a modified strategy (ATN_NfL ) using CSF neurofilament light chain (NfL) in an autopsy cohort.

METHODS

ATN_TAU and ATN_NfL were trained in an independent sample and validated in autopsy-confirmed AD (n = 67) and FTLD (n = 27).

RESULTS

ATN_NfL more accurately identified FTLD as SNAP (sensitivity = 0.93, specificity = 0.94) than ATN_TAU (sensitivity = 0.44, specificity = 0.97), even in cases with co-occurring AD and FTLD. ATN_NfL misclassified fewer AD and FTLD as "Normal" (2%) than ATN_TAU (14%).

DISCUSSION

ATN_NfL is a promising diagnostic strategy that may accurately identify both AD and FTLD, even when pathologies co-occur.

Comparison of subtyping methods for neuroimaging studies in Alzheimer's disease: a call for harmonization

Biological subtypes in Alzheimer's disease, originally identified on neuropathological data, have been translated to in vivo biomarkers such as structural magnetic resonance imaging and positron emission tomography, to disentangle the heterogeneity within Alzheimer's disease. Although there is methodological variability across studies, comparable characteristics of subtypes are reported at the group level. In this study, we investigated whether group-level similarities translate to individual-level agreement across subtyping methods, in a head-to-head context. We compared five previously published subtyping methods. Firstly, we validated the subtyping methods in 89 amyloid-beta positive Alzheimer's disease dementia patients (reference group: 70 amyloid-beta negative healthy individuals) using structural magnetic resonance imaging. Secondly, we extended and applied the subtyping methods to 53 amyloid-beta positive prodromal Alzheimer's disease and 30 amyloid-beta positive Alzheimer's disease dementia patients (reference group: 200 amyloid-beta negative healthy individuals) using structural magnetic resonance imaging and tau positron emission tomography. Subtyping methods were implemented as outlined in each original study. Group-level and individual-level comparisons across methods were performed. Each individual subtyping method was replicated, and the proof-of-concept was established. At the group level, all methods captured subtypes with similar patterns of demographic and clinical characteristics, and with similar cortical thinning and tau positron emission tomography uptake patterns. However, at the individual level, large disagreements were found in subtype assignments. Although characteristics of subtypes are comparable at the group level, there is a large disagreement at the individual level across subtyping methods. Therefore, there is an urgent need for consensus and harmonization across subtyping methods. We call for the establishment of an open benchmarking framework to overcome this problem.

The AT(N) framework for Alzheimer's disease in adults with Down syndrome

The National Institute on Aging in conjunction with the Alzheimer's Association (NIA-AA) recently proposed a biological framework for defining the Alzheimer's disease (AD) continuum. This new framework is based upon the key AD biomarkers (amyloid, tau, neurodegeneration, AT[N]) instead of clinical symptoms and represents the latest understanding that the pathological processes underlying AD begin decades before the manifestation of symptoms. By using these same biomarkers, individuals with Down syndrome (DS), who are genetically predisposed to developing AD, can also be placed more precisely along the AD continuum. The A/T(N) framework is therefore thought to provide an objective manner by which to select and enrich samples for clinical trials. This new framework is highly flexible and allows the addition of newly confirmed AD biomarkers into the existing AT(N) groups. As biomarkers for other pathological processes are validated, they can also be added to the AT(N) classification scheme, which will allow for better characterization and staging of AD in DS. These biological classifications can then be merged with clinical staging for an examination of factors that impact the biological and clinical progression of the disease. Here, we leverage previously published guidelines for the AT(N) framework to generate such a plan for AD among adults with DS.

Significance of Blood and Cerebrospinal Fluid Biomarkers for Alzheimer's Disease: Sensitivity, Specificity and Potential for Clinical Use

Alzheimer's disease (AD) is the most common type of dementia, affecting more than 5 million Americans, with steadily increasing mortality and incredible socio-economic burden. Not only have therapeutic efforts so far failed to reach significant efficacy, but the real pathogenesis of the disease is still obscure. The current theories are based on pathological findings of amyloid plaques and tau neurofibrillary tangles that accumulate in the brain parenchyma of affected patients. These findings have defined, together with the extensive neurodegeneration, the diagnostic criteria of the disease. The ability to detect changes in the levels of amyloid and tau in cerebrospinal fluid (CSF) first, and more recently in blood, has allowed us to use these biomarkers for the specific in-vivo diagnosis of AD in humans. Furthermore, other pathological elements of AD, such as the loss of neurons, inflammation and metabolic derangement, have translated to the definition of other CSF and blood biomarkers, which are not specific of the disease but, when combined with amyloid and tau, correlate with the progression from mild cognitive impairment to AD dementia, or identify patients who will develop AD pathology. In this review, we discuss the role of current and hypothetical biomarkers of Alzheimer's disease, their specificity, and the caveats of current high-sensitivity platforms for their peripheral detection.

Fluid Biomarkers for Synaptic Dysfunction and Loss

Synapses are the site for brain communication where information is transmitted between neurons and stored for memory formation. Synaptic degeneration is a global and early pathogenic event in neurodegenerative disorders with reduced levels of pre- and postsynaptic proteins being recognized as a core feature of Alzheimer's disease (AD) pathophysiology. Together with AD, other neurodegenerative and neurodevelopmental disorders show altered synaptic homeostasis as an important pathogenic event, and due to that, they are commonly referred to as synaptopathies. The exact mechanisms of synapse dysfunction in the different diseases are not well understood and their study would help understanding the pathogenic role of synaptic degeneration, as well as differences and commonalities among them and highlight candidate synaptic biomarkers for specific disorders. The assessment of synaptic proteins in cerebrospinal fluid (CSF), which can reflect synaptic dysfunction in patients with cognitive disorders, is a keen area of interest. Substantial research efforts are now directed toward the investigation of CSF synaptic pathology to improve the diagnosis of neurodegenerative disorders at an early stage as well as to monitor clinical progression. In this review, we will first summarize the pathological events that lead to synapse loss and then discuss the available data on established (eg, neurogranin, SNAP-25, synaptotagmin-1, GAP-43, and α-syn) and emerging (eg, synaptic vesicle glycoprotein 2A and neuronal pentraxins) CSF biomarkers for synapse dysfunction, while highlighting possible utilities, disease specificity, and technical challenges for their detection.

Diagnostic Stability of Mild Cognitive Impairment, and Predictors of Reversion to Normal Cognitive Functioning

OBJECTIVE

Studies that investigate predictive factors for spontaneous recovery (reversion) from mild cognitive impairment (MCI) are only beginning to emerge, and the long-term course of MCI is not properly understood. We aimed to investigate stability of the MCI diagnosis, predictors for reversion, as well as the trajectory of MCI over the course of 12 years.

MATERIALS AND METHODS

Data were drawn from the Swedish population study: Good Aging in Skåne with MCI defined according to the expanded Mayo Clinic criteria. A total of 331 participants, aged 60-95 years with MCI, were used to investigate 6-year MCI stability and reversion, and 410 participants were used to inspect 12-year MCI trajectory. Predictors for reversion included demographical factors, psychological status, and factors tied to the cognitive testing session and the operationalization of the MCI criteria.

RESULTS

Over half (58%, 95% CI 52.7-63.3) of the participants reverted back to normal cognitive functioning at 6-year follow-up. Of those with stable MCI, 56.5% (95% CI 48.2-64.8) changed subtype. A total of 23.9% (95% CI 13.7-34.1) of the 6-year follow-up reverters re-transitioned back to MCI at 12-year follow-up. ORs for reversion were significantly higher in participants with lower age (60-year-olds: OR 2.19, 95% CI 1.08-4.43, 70-year-olds: OR 3.11, 95% CI 1.27-7.62), better global cognitive functioning (OR 1.15, 95% CI 1.03-1.29), good concentration (OR 2.53, 95% CI 1.06-6.05), and single-domain subtype (OR 2.68, 95% CI 1.51-4.75).

CONCLUSION

Our findings provide further support that MCI reversion to normal cognitive functioning as well as re-transitioning to MCI is fairly common, suggesting that the MCI trajectory does not necessarily lead straight to dementia. Additionally, assessment of factors associated with reversion can aid clinicians to make accurate MCI progression prognosis.

Analysis of MRI Data in Diagnostic Neuroradiology

Magnetic resonance imaging (MRI) is a noninvasive imaging tool for neuroradiological diagnosis. Numerous concepts of automated MRI analysis and the use of machine learning have been proposed to assist diagnosis and prognosis. While these academic innovations have proven effective in principle within controlled environments, their application to clinical practice has faced unmet requirements, such as the ability to perform reliably across a heterogeneous population, to work robustly in the presence of comorbidities, and to be invariant to scanner hardware and image quality. The lack of realistic confidence bounds and the inability to handle missing data have also reduced the application of most of these methods outside of academic studies. Mastering the complex challenges in the diagnostic process may help researchers discover novel biological constructs in multimodal data and improve stratification for clinical trials, paving the way for precision medicine. This review presents the state of the art of computerized brain MRI analysis for diagnostic purposes. We critically evaluate the current clinical usefulness of the methods and highlight challenges and future perspectives of the field.

ATN classification and clinical progression in subjective cognitive decline: The SCIENCe project

Objective

To investigate the relationship between the ATN classification system (amyloid, tau, neurodegeneration) and risk of dementia and cognitive decline in individuals with subjective cognitive decline (SCD).

Methods

We classified 693 participants with SCD (60 ± 9 years, 41% women, Mini-Mental State Examination score 28 ± 2) from the Amsterdam Dementia Cohort and Subjective Cognitive Impairment Cohort (SCIENCe) project according to the ATN model, as determined by amyloid PET or CSF β-amyloid (A), CSF p-tau (T), and MRI-based medial temporal lobe atrophy (N). All underwent extensive neuropsychological assessment. For 342 participants, follow-up was available (3 ± 2 years). As a control population, we included 124 participants without SCD.

Results

Fifty-six (n = 385) participants had normal Alzheimer disease (AD) biomarkers (A–T–N–), 27% (n = 186) had non-AD pathologic change (A–T–N+, A–T+N–, A–T+N+), 18% (n = 122) fell within the Alzheimer continuum (A+T–N–, A+T–N+, A+T+N–, A+T+N+). ATN profiles were unevenly distributed, with A–T+N+, A+T–N+, and A+T+N+ containing very few participants. Cox regression showed that compared to A–T–N–, participants in A+ profiles had a higher risk of dementia with a dose–response pattern for number of biomarkers affected. Linear mixed models showed participants in A+ profiles showed a steeper decline on tests addressing memory, attention, language, and executive functions. In the control group, there was no association between ATN and cognition.

Conclusions

Among individuals presenting with SCD at a memory clinic, those with a biomarker profile A–T+N+, A+T–N–, A+T+N–, and A+T+N+ were at increased risk of dementia, and showed steeper cognitive decline compared to A–T–N– individuals. These results suggest a future where biomarker results could be used for individualized risk profiling in cognitively normal individuals presenting at a memory clinic.

The MemClin project: a prospective multi memory clinics study targeting early stages of cognitive impairment

Background

There remains a lack of large-scale clinical studies of cognitive impairment that aim to increase diagnostic and prognostic accuracy as well as validate previous research findings. The MemClin project will amass large quantities of cross-disciplinary data allowing for the construction of robust models to improve diagnostic accuracy, expand our knowledge on differential diagnostics, strengthen longitudinal prognosis, and harmonise examination protocols across centres. The current article describes the Memory Clinic (MemClin) project’s study-design, materials and methods, and patient characteristics. In addition, we present preliminary descriptive data from the ongoing data collection.

Methods

Nine out of ten memory clinics in the greater Stockholm area, which largely use the same examination methods, are included. The data collection of patients with different stages of cognitive impairment and dementia is coordinated centrally allowing for efficient and secure large-scale database construction. The MemClin project rest directly on the memory clinics examinations with cognitive measures, health parameters, and biomarkers.

Results

Currently, the MemClin project has informed consent from 1543 patients. Herein, we present preliminary data from 835 patients with confirmed cognitive diagnosis and neuropsychological test data available. Of those, 239 had dementia, 487 mild cognitive impairment (MCI), and 104 subjective cognitive impairment (SCI). In addition, we present descriptive data on visual ratings of brain atrophy and cerebrospinal fluid markers.

Conclusions

Based on our current progress and preliminary data, the MemClin project has a high potential to provide a large-scale database of 1200–1500 new patients annually. This coordinated data collection will allow for the construction of improved diagnostic and prognostic models for neurodegenerative disorders and other cognitive conditions in their naturalistic setting.

A Comprehensive Visual Rating Scale for Predicting Progression from Mild Cognitive Impairment to Dementia in Patients with Alzheimer's Pathology or Suspected Non-Alzheimer's Pathology

Background and Purpose

To identify biomarkers for prediction of the progression to dementia in mild cognitive impairment (MCI) patients, evaluation of brain structure changes has been validated by a comprehensive visual grading scale (CVRS) through magnetic resonance imaging (MRI). In this study, we specifically elucidated for the cognitive change of MCI patients classified based on AT(N) pathological status classification during the follow-up period of 3 years through the CVRS.

Methods

The 301 patients with initial MCI visited at least once for follow-up period. The data used in this study were obtained from the Alzheimer's disease (AD) Neuroimaging Initiative study. Brain atrophy was assessed by CVRS using MRI. AT(N) profiles were classified by cerebrospinal fluid abnormality. Based on the AT(N) assessment, all individuals in this study were divided into 3 groups (normal state biomarker, suspected non-Alzheimer's pathology [SNAP], or Alzheimer's continuum). The cox regression was used to analyze the hazard ratios of CVRS for progression to dementia.

Results

Sixty-three progressed and 238 remained stable to dementia and the CVRS (mean±standard deviation) had significant difference between progressive MCI and stable MCI (p<0.001). Univariate and multivariate cox regression results (p<0.001) showed the independence of initial CVRS as a predictor for the progression to dementia. Moreover, comparing the classified AT(N) pathology group, SNAP and AD, effectiveness of CVRS as a predictor was verified only in Alzheimer's continuum.

Conclusions

The initial CVRS score as a predictor of dementia progression was independently validated at the stage of Alzheimer's progression among AT(N) pathologically differentiated MCI.

The A/T/N model applied through imaging biomarkers in a memory clinic

PURPOSE

The A/T/N model is a research framework proposed to investigate Alzheimer's disease (AD) pathological bases (i.e., amyloidosis A, neurofibrillary tangles T, and neurodegeneration N). The application of this system on clinical populations is still limited. The aim of the study is to evaluate the topography of T distribution by 18F-flortaucipir PET in relation to A and N and to describe the A/T/N status through imaging biomarkers in memory clinic patients.

METHODS

Eighty-one patients with subjective and objective cognitive impairment were classified as A+/A- and N+/N- through amyloid PET and structural MRI. Tau deposition was compared across A/N subgroups at voxel level. T status was defined through a global cut point based on A/N subgroups and subjects were categorized following the A/T/N model.

RESULTS

A+N+ and A+N- subgroups showed higher tau burden compared to A-N- group, with A+N- showing significant deposition limited to the medial and lateral temporal regions. Global cut point discriminated A+N+ and A+N- from A-N- subjects. On A/T/N classification, 23% of patients showed a negative biomarker profile, 58% fell within the Alzheimer's continuum, and 19% of the sample was characterized by non-AD pathologic change.

CONCLUSION

Medial and lateral temporal regions represent a site of significant tau accumulation in A+ subjects and possibly a useful marker of early clinical changes. This is the first study in which the A/T/N model is applied using 18F-flortaucipir PET in a memory clinic population. The majority of patients showed a profile consistent with the Alzheimer's continuum, while a minor percentage showed a profile suggestive of possible other neurodegenerative diseases. These results support the applicability of the A/T/N model in clinical practice.

Applying the ATN scheme in a memory clinic population: The ABIDE project

OBJECTIVE

To apply the ATN scheme to memory clinic patients, to assess whether it discriminates patient populations with specific features.

METHODS

We included 305 memory clinic patients (33% subjective cognitive decline [SCD]: 60 ± 9 years, 61% M; 19% mild cognitive impairment [MCI]: 68 ± 9 years, 68% M; 48% dementia: 66 ± 10 years, 58% M) classified for positivity (±) of amyloid (A) ([¹⁸F]Florbetaben PET), tau (T) (CSF p-tau), and neurodegeneration (N) (medial temporal lobe atrophy). We assessed ATN profiles' demographic, clinical, and cognitive features at baseline, and cognitive decline over time.

RESULTS

The proportion of A+T+N+ patients increased with syndrome severity (from 1% in SCD to 14% in MCI and 35% in dementia), while the opposite was true for A-T-N- (from 48% to 19% and 6%). Compared to A-T-N-, patients with the Alzheimer disease profiles (A+T+N- and A+T+N+) were older (both p < 0.05) and had a higher prevalence of APOE ε4 (both p < 0.05) and lower Mini-Mental State Examination (MMSE) (both p < 0.05), memory (both p < 0.05), and visuospatial abilities (both p < 0.05) at baseline. Non-Alzheimer profiles A-T-N+ and A-T+N+ showed more severe white matter hyperintensities (both p < 0.05) and worse language performance (both p < 0.05) than A-T-N-. A linear mixed model showed faster decline on MMSE over time in A+T+N- and A+T+N+ (p = 0.059 and p < 0.001 vs A-T-N-), attributable mainly to patients without dementia.

CONCLUSIONS

The ATN scheme identified different biomarker profiles with overlapping baseline features and patterns of cognitive decline. The large number of profiles, which may have different implications in patients with vs without dementia, poses a challenge to the application of the ATN scheme.

Potential Fluid Biomarkers for the Diagnosis of Mild Cognitive Impairment

Mild cognitive impairment (MCI) is characterized by a level of cognitive impairment that is lower than normal for a person’s age, but a higher function than that that observed in a demented person. MCI represents a transitional state between normal aging and dementia disorders, especially Alzheimer’s disease (AD). Much effort has been made towards determining the prognosis of a person with MCI who will convert to AD. It is now clear that cerebrospinal fluid (CSF) levels of Aβ40, Aβ42, total tau and phosphorylated tau are useful for predicting the risk of progression from MCI to AD. This review highlights the advantages of the current blood-based biomarkers in MCI, and discusses some of these challenges, with an emphasis on recent studies to provide an overview of the current state of MCI.

Subtypes of Alzheimer's Disease Display Distinct Network Abnormalities Extending Beyond Their Pattern of Brain Atrophy

Different subtypes of Alzheimer's disease (AD) with characteristic distributions of neurofibrillary tangles and corresponding brain atrophy patterns have been identified using structural magnetic resonance imaging (MRI). However, the underlying biological mechanisms that determine this differential expression of neurofibrillary tangles are still unknown. Here, we applied graph theoretical analysis to structural MRI data to test the hypothesis that differential network disruption is at the basis of the emergence of these AD subtypes. We studied a total of 175 AD patients and 81 controls. Subtyping was done using the Scheltens' scale for medial temporal lobe atrophy, the Koedam's scale for posterior atrophy, and the Pasquier's global cortical atrophy scale for frontal atrophy. A total of 89 AD patients showed a brain atrophy pattern consistent with typical AD; 30 patients showed a limbic-predominant pattern; 29 patients showed a hippocampal-sparing pattern; and 27 showed minimal atrophy. We built brain structural networks from 68 cortical regions and 14 subcortical gray matter structures for each AD subtype and for the controls, and we compared between-group measures of integration, segregation, and modular organization. At the global level, modularity was increased and differential modular reorganization was detected in the four subtypes. We also found a decrease of transitivity in the typical and hippocampal-sparing subtypes, as well as an increase of average local efficiency in the minimal atrophy and hippocampal-sparing subtypes. We conclude that the AD subtypes have a distinct signature of network disruption associated with their atrophy patterns and further extending to other brain regions, presumably reflecting the differential spread of neurofibrillary tangles. We discuss the hypothetical emergence of these subtypes and possible clinical implications.

Different pattern of CSF glial markers between dementia with Lewy bodies and Alzheimer's disease

The role of innate immunity in dementia with Lewy bodies (DLB) has been little studied. We investigated the levels in cerebrospinal fluid (CSF) of glial proteins YKL-40, soluble TREM2 (sTREM2) and progranulin in DLB and their relationship with Alzheimer's disease (AD) biomarkers. We included patients with DLB (n = 37), prodromal DLB (prodDLB, n = 23), AD dementia (n = 50), prodromal AD (prodAD, n = 53), and cognitively normal subjects (CN, n = 44). We measured levels of YKL-40, sTREM2, progranulin, Aβ1-42, total tau (t-tau) and phosphorylated tau (p-tau) in CSF. We stratified the group DLB according to the ratio t-tau/Aβ1-42 (≥0.52, indicative of AD pathology) and the A/T classification. YKL-40, sTREM2 and progranulin levels did not differ between DLB groups and CN. YKL-40 levels were higher in AD and prodAD compared to CN and to DLB and prodDLB. Patients with DLB with a CSF profile suggestive of AD copathology had higher levels of YKL-40, but not sTREM2 or PGRN, than those without. T+ DLB patients had also higher YKL-40 levels than T-. Of these glial markers, only YKL-40 correlated with t-tau and p-tau in DLB and in prodDLB. In contrast, in prodAD, sTREM2 and PGRN also correlated with t-tau and p-tau. In conclusion, sTREM2 and PGRN are not increased in the CSF of DLB patients. YKL-40 is only increased in DLB patients with an AD biomarker profile, suggesting that the increase is driven by AD-related neurodegeneration. These data suggest a differential glial activation between DLB and AD.

Tau PET Imaging for Staging of Alzheimer's Disease in Down Syndrome

Alzheimer's disease (AD) pathology and early-onset dementia develop almost universally in Down syndrome (DS). AD is defined neuropathologically by the presence of extracellular plaques of aggregated amyloid β protein and intracellular neurofibrillary tangles (NFTs) of aggregated hyperphosphorylated tau protein. The development of radiolabeled positron emission tomography (PET) ligands for amyloid plaques and tau tangles enables the longitudinal assessment of the spatial pattern of their accumulation in relation to symptomatology. Recent work indicates that amyloid pathology develops 15-20 years before neurodegeneration and symptom onset in the sporadic and autosomal dominant forms of AD, while tau pathology correlates more closely with symptomatic stages evidenced by cognitive decline and dementia. Recent work on AD biomarkers in DS illustrates similarities between DS and sporadic AD. It may soon be possible to apply recently developed staging classifications to DS to obtain a more nuanced understanding of the development AD in DS and to provide more accurate diagnosis and prognosis in the clinic.