Associations between Alzheimer disease biomarkers, neurodegeneration, and cognition in cognitively normal older people

MRI-Derived AD Signature of Cortical Thinning and Plasma P-Tau217 for Predicting Alzheimer Dementia Among Community-Dwelling Older Adults

Background and Objectives

Structural brain MRI and blood-based phosphorylated tau (p-tau) measures are among the least invasive and least expensive Alzheimer's disease (AD) biomarkers to date. The extent to which these biomarkers may outperform one another in predicting future Alzheimer dementia diagnosis is poorly understood, however. This study investigated 2 specific AD biomarkers, i.e., a cortical thickness signature of AD (AD-CT) and plasma p-tau217, for predicting Alzheimer dementia.

Methods

Data came from community-dwelling older participants of the Religious Orders Study or the Rush Memory and Aging Project. AD-CT was obtained from 3T MRI scans using a magnetization-prepared rapid acquisition gradient echo sequence and by averaging thickness from previously identified cortical regions implicated in AD. Plasma p-tau217 was quantified using an immunoassay developed by Lilly Research Laboratories on the MSD platform. Both MRI scans and blood specimens were collected at the same visits, and subsequent diagnoses of Alzheimer dementia were determined through annual detailed clinical evaluations. Cox proportional hazards models examined the associations of the 2 biomarkers with incident Alzheimer dementia, and prediction accuracy was assessed using c-statistics.

Results

A total of 198 older adults, on average 84 years of age, were included. Over a mean follow-up of 4 years, 60 (30%) individuals developed Alzheimer dementia. AD-CT (hazard ratio: 1.71, 95% CI 1.26-2.31) and separately plasma p-tau217 (hazard ratio: 2.57, 95% CI 1.83-3.61) were associated with incident Alzheimer dementia. The c-statistic for prediction accuracy was consistently higher for plasma p-tau217 (between 0.74 and 0.81) than AD-CT (between 0.70 and 0.75) across a range of time horizons. Furthermore, with both biomarkers included in the same model, there was only modest improvement in the c-statistic due to AD-CT.

Discussion

Plasma p-tau217 outperforms an imaging-based cortical thickness signature of AD in predicting future Alzheimer dementia diagnosis. Furthermore, the AD cortical thickness signature adds little to the prediction accuracy above and beyond plasma p-tau217.

Seeing beyond the symptoms: biomarkers and brain regions linked to cognitive decline in Alzheimer's disease

Objective

Early Alzheimer's disease (AD) diagnosis remains challenging, necessitating specific biomarkers for timely detection. This study aimed to identify such biomarkers and explore their associations with cognitive decline.

Methods

A cohort of 1759 individuals across cognitive aging stages, including healthy controls (HC), mild cognitive impairment (MCI), and AD, was examined. Utilizing nine biomarkers from structural MRI (sMRI), diffusion tensor imaging (DTI), and positron emission tomography (PET), predictions were made for Mini-Mental State Examination (MMSE), Clinical Dementia Rating Scale Sum of Boxes (CDRSB), and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS). Biomarkers included four sMRI (e.g., average thickness [ATH]), four DTI (e.g., mean diffusivity [MD]), and one PET Amyloid-β (Aβ) measure. Ensemble regression tree (ERT) technique with bagging and random forest approaches were applied in four groups (HC/MCI, HC/AD, MCI/AD, and HC/MCI/AD).

Results

Aβ emerged as a robust predictor of cognitive scores, particularly in late-stage AD. Volumetric measures, notably ATH, consistently correlated with cognitive scores across early and late disease stages. Additionally, ADAS demonstrated links to various neuroimaging biomarkers in all subject groups, highlighting its efficacy in monitoring brain changes throughout disease progression. ERT identified key brain regions associated with cognitive scores, such as the right transverse temporal region for Aβ, left and right entorhinal cortex, left inferior temporal gyrus, and left middle temporal gyrus for ATH, and the left uncinate fasciculus for MD.

Conclusion

This study underscores the importance of an interdisciplinary approach in understanding AD mechanisms, offering potential contributions to early biomarker development.

Lung function and risk of incident dementia: A prospective cohort study of 431,834 individuals

BACKGROUND

Whether lung function prospectively affects cognitive brain health independent of their overlapping factors remains largely unknown. This study aimed to investigate the longitudinal association between decreased lung function and cognitive brain health and to explore underlying biological and brain structural mechanisms.

METHODS

This population-based cohort included 43,1834 non-demented participants with spirometry from the UK Biobank. Cox proportional hazard models were fitted to estimate the risk of incident dementia for individuals with low lung function. Mediation models were regressed to explore the underlying mechanisms driven by inflammatory markers, oxygen-carrying indices, metabolites, and brain structures.

FINDINGS

During a follow-up of 3,736,181 person-years (mean follow-up 8.65 years), 5,622 participants (1.30 %) developed all-cause dementia, which consisted of 2,511 Alzheimer's dementia (AD) and 1,308 Vascular Dementia (VD) cases. Per unit decrease in lung function measure was each associated with increased risk for all-cause dementia (forced expiratory volume in 1 s [liter]: hazard ratio [HR, 95 %CI], 1.24 [1.14-1.34], P = 1.10 × 10^-07; forced vital capacity [liter]: 1.16 [1.08-1.24], P = 2.04 × 10^-05; peak expiratory flow [liter/min]: 1.0013 [1.0010-1.0017], P = 2.73 × 10^-13). Low lung function generated similar hazard estimates for AD and VD risks. As underlying biological mechanisms, systematic inflammatory markers, oxygen-carrying indices, and specific metabolites mediated the effects of lung function on dementia risks. Besides, brain grey and white matter patterns mostly affected in dementia were substantially changed with lung function.

INTERPRETATION

Life-course risk for incident dementia was modulated by individual lung function. Maintaining optimal lung function is useful for healthy aging and dementia prevention.

APOE-ε4 modulates the association between regional amyloid deposition and cognitive performance in cognitively unimpaired middle-aged individuals

PURPOSE

To determine whether the APOE-ε4 allele modulates the relationship between regional β-amyloid (Aβ) accumulation and cognitive change in middle-aged cognitively unimpaired (CU) participants.

METHODS

The 352 CU participants (mean aged 61.1 [4.7] years) included completed two cognitive assessments (average interval 3.34 years), underwent [¹⁸F]flutemetamol Aβ positron emission tomography (PET), T1w magnetic resonance imaging (MRI), as well as APOE genotyping. Global and regional Aβ PET positivity was assessed across five regions-of-interest by visual reading (VR) and regional Centiloids. Linear regression models were developed to examine the interaction between regional and global Aβ PET positivity and APOE-ε4 status on longitudinal cognitive change assessed with the Preclinical Alzheimer's Cognitive Composite (PACC), episodic memory, and executive function, after controlling for age, sex, education, cognitive baseline scores, and hippocampal volume.

RESULTS

In total, 57 participants (16.2%) were VR+ of whom 41 (71.9%) were APOE-ε4 carriers. No significant APOE-ε4*global Aβ PET interactions were associated with cognitive change for any cognitive test. However, APOE-ε4 carriers who were VR+ in temporal areas (n = 19 [9.81%], p = 0.04) and in the striatum (n = 8 [4.14%], p = 0.01) exhibited a higher decline in the PACC. The temporal areas findings were replicated when regional PET positivity was determined with Centiloid values. Regionally, VR+ in the striatum was associated with higher memory decline. As for executive function, interactions between APOE-ε4 and regional VR+ were found in temporal and parietal regions, and in the striatum.

CONCLUSION

CU APOE-ε4 carriers with a positive Aβ PET VR in regions known to accumulate amyloid at later stages of the Alzheimer's disease (AD) continuum exhibited a steeper cognitive decline. This work supports the contention that regional VR of Aβ PET might convey prognostic information about future cognitive decline in individuals at higher risk of developing AD.

CLINICALTRIALS

gov Identifier: NCT02485730. Registered 20 June 2015 https://clinicaltrials.gov/ct2/show/NCT02485730 and ClinicalTrials.gov Identifier:NCT02685969. Registered 19 February 2016 https://clinicaltrials.gov/ct2/show/NCT02685969 .

DeepParcellation: A novel deep learning method for robust brain magnetic resonance imaging parcellation in older East Asians

Accurate parcellation of cortical regions is crucial for distinguishing morphometric changes in aged brains, particularly in degenerative brain diseases. Normal aging and neurodegeneration precipitate brain structural changes, leading to distinct tissue contrast and shape in people aged >60 years. Manual parcellation by trained radiologists can yield a highly accurate outline of the brain; however, analyzing large datasets is laborious and expensive. Alternatively, newly-developed computational models can quickly and accurately conduct brain parcellation, although thus far only for the brains of Caucasian individuals. To develop a computational model for the brain parcellation of older East Asians, we trained magnetic resonance images of dimensions 256 × 256 × 256 on 5,035 brains of older East Asians (Gwangju Alzheimer's and Related Dementia) and 2,535 brains of Caucasians. The novel N-way strategy combining three memory reduction techniques inception blocks, dilated convolutions, and attention gates was adopted for our model to overcome the intrinsic memory requirement problem. Our method proved to be compatible with the commonly used parcellation model for Caucasians and showed higher similarity and robust reliability in older aged and East Asian groups. In addition, several brain regions showing the superiority of the parcellation suggest that DeepParcellation has a great potential for applications in neurodegenerative diseases such as Alzheimer's disease.

Linking Puberty and the Gut Microbiome to the Pathogenesis of Neurodegenerative Disorders

Puberty is a critical period of development marked by the maturation of the central nervous system, immune system, and hypothalamic-pituitary-adrenal axis. Due to the maturation of these fundamental systems, this is a period of development that is particularly sensitive to stressors, increasing susceptibility to neurodevelopmental and neurodegenerative disorders later in life. The gut microbiome plays a critical role in the regulation of stress and immune responses, and gut dysbiosis has been implicated in the development of neurodevelopmental and neurodegenerative disorders. The purpose of this review is to summarize the current knowledge about puberty, neurodegeneration, and the gut microbiome. We also examine the consequences of pubertal exposure to stress and gut dysbiosis on the development of neurodevelopmental and neurodegenerative disorders. Understanding how alterations to the gut microbiome, particularly during critical periods of development (i.e., puberty), influence the pathogenesis of these disorders may allow for the development of therapeutic strategies to prevent them.

The acute effects of antimicrobials and lipopolysaccharide on the cellular mechanisms associated with neurodegeneration in pubertal male and female CD1 mice

Exposure to stressors during puberty can cause enduring effects on brain functioning and behaviours related to neurodegeneration. However, the mechanisms underlying these effects remain unclear. The gut microbiome is a complex and dynamic system that could serve as a possible mechanism through which early life stress may increase the predisposition to neurodegeneration. Therefore, the current study was designed to examine the acute effects of pubertal antimicrobial and lipopolysaccharide (LPS) treatments on the cellular mechanisms associated with neurodegenerative disorders in male and female mice. At five weeks of age, male and female CD-1 mice received 200 μL of broad-spectrum antimicrobials or water, through oral gavage, twice daily for seven days. Mice received an intraperitoneal (i.p.) injection of either saline or LPS at 6 weeks of age (i.e., pubertal period). Sickness behaviours were recorded and mice were euthanized 8 h post-injection. Following euthanasia, brains and blood samples were collected. The results indicated that puberal antimicrobial and LPS treatment induced sex-dependent changes in biomarkers related to sickness behaviour, peripheral inflammation, intestinal permeability, and neurodegeneration. The findings suggest that pubertal LPS and antimicrobial treatment may increase susceptibility to neurodegenerative diseases later in life, particularly in males.

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Pubertal antimicrobial and LPS treatment increase cytokine concentrations.

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Antimicrobial and LPS treatment have sex-specific effects on intestinal permeability.

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They also induce sex-specific changes in neurodegenerative markers.

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Antimicrobial treatment did not potentiate LPS-induced sickness behaviours.

Musical Activity During Life Is Associated With Multi-Domain Cognitive and Brain Benefits in Older Adults

Regular musical activity as a complex multimodal lifestyle activity is proposed to be protective against age-related cognitive decline and Alzheimer’s disease. This cross-sectional study investigated the association and interplay between musical instrument playing during life, multi-domain cognitive abilities and brain morphology in older adults (OA) from the DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) study. Participants reporting having played a musical instrument across three life periods (n = 70) were compared to controls without a history of musical instrument playing (n = 70), well-matched for reserve proxies of education, intelligence, socioeconomic status and physical activity. Participants with musical activity outperformed controls in global cognition, working memory, executive functions, language, and visuospatial abilities, with no effects seen for learning and memory. The musically active group had greater gray matter volume in the somatosensory area, but did not differ from controls in higher-order frontal, temporal, or hippocampal volumes. However, the association between gray matter volume in distributed frontal-to-temporal regions and cognitive abilities was enhanced in participants with musical activity compared to controls. We show that playing a musical instrument during life relates to better late-life cognitive abilities and greater brain capacities in OA. Musical activity may serve as a multimodal enrichment strategy that could help preserve cognitive and brain health in late life. Longitudinal and interventional studies are needed to support this notion.

Multi-Omics-Based Autophagy-Related Untypical Subtypes in Patients with Cerebral Amyloid Pathology

Recent multi-omics analyses paved the way for a comprehensive understanding of pathological processes. However, only few studies have explored Alzheimer's disease (AD) despite the possibility of biological subtypes within these patients. For this study, unsupervised classification of four datasets (genetics, miRNA transcriptomics, proteomics, and blood-based biomarkers) using Multi-Omics Factor Analysis+ (MOFA+), along with systems-biological approaches following various downstream analyses are performed. New subgroups within 170 patients with cerebral amyloid pathology (Aβ+) are revealed and the features of them are identified based on the top-rated targets constructing multi-omics factors of both whole (M-TPAD) and immune-focused models (M-IPAD). The authors explored the characteristics of subtypes and possible key-drivers for AD pathogenesis. Further in-depth studies showed that these subtypes are associated with longitudinal brain changes and autophagy pathways are main contributors. The significance of autophagy or clustering tendency is validated in peripheral blood mononuclear cells (PBMCs; n = 120 including 30 Aβ- and 90 Aβ+), induced pluripotent stem cell-derived human brain organoids/microglia (n = 12 including 5 Aβ-, 5 Aβ+, and CRISPR-Cas9 apolipoprotein isogenic lines), and human brain transcriptome (n = 78). Collectively, this study provides a strategy for precision medicine therapy and drug development for AD using integrative multi-omics analysis and network modelling.

Classification of Alzheimer’s Disease Using Dual-Phase 18F-Florbetaben Image with Rank-Based Feature Selection and Machine Learning

18F-florbetaben (FBB) positron emission tomography is a representative imaging test that observes amyloid deposition in the brain. Compared to delay-phase FBB (dFBB), early-phase FBB shows patterns related to glucose metabolism in 18F-fluorodeoxyglucose perfusion images. The purpose of this study is to prove that classification accuracy is higher when using dual-phase FBB (dual FBB) versus dFBB quantitative analysis by using machine learning and to find an optimal machine learning model suitable for dual FBB quantitative analysis data. The key features of our method are (1) a feature ranking method for each phase of FBB with a cross-validated F1 score and (2) a quantitative diagnostic model based on machine learning methods. We compared four classification models: support vector machine, naïve Bayes, logistic regression, and random forest (RF). In composite standardized uptake value ratio, RF achieved the best performance (F1: 78.06%) with dual FBB, which was 4.83% higher than the result with dFBB. In conclusion, regardless of the two quantitative analysis methods, using the dual FBB has a higher classification accuracy than using the dFBB. The RF model is the machine learning model that best classifies a dual FBB. The regions that have the greatest influence on the classification of dual FBB are the frontal and temporal lobes.

Decreased Cerebral Amyloid-β Depositions in Patients With a Lifetime History of Major Depression With Suspected Non-Alzheimer Pathophysiology

Cerebral amyloid-β (Aβ) depositions in depression in old age are controversial. A substantial proportion of individuals with late-life major depressive disorder (MDD) could be classified as having suspected non-Alzheimer’s disease pathophysiology (SNAP) by a negative test for the biomarker amyloid-β (Aβ−) but positive neurodegeneration (ND+). This study aimed to evaluate subthreshold Aβ loads in amyloid-negative MDD, particularly in SNAP MDD patients. This study included 46 amyloid-negative MDD patients: 23 SNAP (Aβ−/ND+) MDD and 23 Aβ−/ND− MDD, and 22 Aβ−/ND− control subjects. All subjects underwent ¹⁸F-florbetapir PET, FDG-PET, and MRI. Regions of interest (ROIs) and voxel-wise group comparisons were performed with adjustment for age, gender, and level of education. The SNAP MDD patients exhibited significantly deceased ¹⁸F-florbetapir uptakes in most cortical regions but not the parietal and precuneus cortex, as compared with the Aβ−/ND− MDD and control subjects (FDR correction, p < 0.05). No correlations of neuropsychological tests or depression characteristics with global cortical uptakes, but significant positive correlations between cognitive functions and adjusted hippocampal volumes among different groups were observed. The reduced Aβ depositions in the amyloid-negative MDD patients might be attributed mainly to the SNAP MDD patients. Our results indicated that meaningfully low amounts of subclinical Aβ might contain critical information on the non-amyloid-mediated pathogenesis.

CSF markers of AD-related pathology relate specifically to memory impairment in older people with HIV: a pilot study

Given the co-occurrence of memory impairment in HIV-associated neurocognitive disorders (HAND) and amnestic mild cognitive impairment/Alzheimer's disease (aMCI/AD), biomarkers are needed that can disentangle these conditions among people with HIV (PWH). We assessed whether cerebrospinal fluid (CSF) markers of AD could help in this effort by determining their relationship to learning and memory deficits versus cognitive deficits more characteristic of HAND than aMCI/AD (processing speed and complex visual/motor coordination) among 31 older PWH. CSF amyloid-β42 phosphorylated-tau, amyloid-β40/amyloid-β42 and phosphorylated-tau/amyloid-β42 ratio related to learning/memory performance but not HAND-related deficits, suggesting that these biomarkers may have utility in disentangling aMCI/AD from HAND.

China Registry Study on Cognitive Impairment in the Elderly: Protocol of a Prospective Cohort Study

Introduction: To develop appropriate strategies for early diagnosis and intervention of cognitive impairment, the identification of minimally invasive and cost-effective biomarkers for the early diagnosis of cognitive impairment is crucial and desirable. Therefore, the CHina registry study on cOgnitive imPairment in the Elderly (HOPE) study is designed to investigate the natural course of cognitive decline and explore the clinical, imaging, and biochemical markers for the detection and diagnosis of cognitive impairment on its earliest stage.

Methods: Approximately 5,000 Chinese elderly aged more than 50 years were recruited from Sun Yat-sen Memorial Hospital, Sun Yat-sen University in Guangzhou, China by the year 2024. All subjects were invited to complete the clinical assessment, neuropsychological assessment, the biological samples collection (blood and cerebrospinal fluid (CSF)], magnetic resonance imaging (MRI) examination, and optional amyloid and tau PET. The follow-up survey was conducted every 1 year to repeat these assessments for 20 years. To better clarify the relationship between potential risk factors and endpoint events [changes in cognitive score or incidence of mild cognitive impairment (MCI) and/or dementia], appropriate statistical methods were used to analyze the data, including but not limited to, such as linear mixed-effect model, competing risk model, or the least absolute shrinkage and selection operator model.

Significance: The CHina registry study on cOgnitive imPairment in the Elderly study is designed to explore the longitudinal changes in characteristics of participants with cognitive decline and to identify potential plasma and imaging biomarkers with cost-benefit and scalability advantages. The results will enable broader clinical access and efficient population screening and then improve the development of treatment and the quality of life for cognitive impairment at the early stage.

Trial registration number: NCT04360200.

Subtyping of mild cognitive impairment using a deep learning model based on brain atrophy patterns

Trajectories of cognitive decline vary considerably among individuals with mild cognitive impairment (MCI). To address this heterogeneity, subtyping approaches have been developed, with the objective of identifying more homogeneous subgroups. To date, subtyping of MCI has been based primarily on cognitive measures, often resulting in indistinct boundaries between subgroups and limited validity. Here, we introduce a subtyping method for MCI based solely upon brain atrophy. We train a deep learning model to differentiate between Alzheimer’s disease (AD) and cognitively normal (CN) subjects based on whole-brain MRI features. We then deploy the trained model to classify MCI subjects based on whole-brain gray matter resemblance to AD-like or CN-like patterns. We subsequently validate the subtyping approach using cognitive, clinical, fluid biomarker, and molecular imaging data. Overall, the results suggest that atrophy patterns in MCI are sufficiently heterogeneous and can thus be used to subtype individuals into biologically and clinically meaningful subgroups.

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Individuals with mild cognitive impairment (MCI) are subtyped using a deep learning model

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The model is able to subtype MCI based solely on structural brain atrophy patterns

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The model-based subtypes differ in amyloid burden, brain metabolism, and cognition

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The model-based subtyping approach captures marked differences in cognitive decline

Long-term prognosis and educational determinants of brain network decline in older adult individuals

Older adults with lower education are at greater risk for dementia. It is unclear which brain changes lead to these outcomes. Longitudinal imaging-based measures of brain structure and function were examined in adult individuals (baseline age, 45–86 years; two to five visits per participant over 1–9 years). College degree completion differentiates individual-based and neighborhood-based measures of socioeconomic status and disadvantage. Older adults (~65 years and over) without a college degree exhibit a pattern of declining large-scale functional brain network organization (resting-state system segregation) that is less evident in their college-educated peers. Declining brain system segregation predicts impending changes in dementia severity, measured up to 10 years past the last scan date. The prognostic value of brain network change is independent of Alzheimer’s disease (AD)-related genetic risk (APOE status), the presence of AD-associated pathology (cerebrospinal fluid phosphorylated tau, cortical amyloid) and cortical thinning. These results demonstrate that the trajectory of an individual’s brain network organization varies in relation to their educational attainment and, more broadly, is a unique indicator of individual brain health during older age.

Multi-Target-Directed Ligands as an Effective Strategy for the Treatment of Alzheimer's Disease

Alzheimer's disease (AD) is a complex neurological disorder, and multiple pathological factors are believed to be involved in the genesis and progression of the disease. A number of hypotheses, including Acetylcholinesterase, Monoamine oxidase, β-Amyloid, Tau protein, etc., have been proposed for the initiation and progression of the disease. At present, acetylcholine esterase inhibitors and memantine (NMDAR antagonist) are the only approved therapies for the symptomatic management of AD. Most of these single-target drugs have miserably failed in the treatment or halting the progression of the disease. Multi-factorial diseases like AD require complex treatment strategies that involve simultaneous modulation of a network of interacting targets. Since the last few years, Multi-Target-Directed Ligands (MTDLs) strategy, drugs that can simultaneously hit multiple targets, is being explored as an effective therapeutic approach for the treatment of AD. In the current review article, the authors have briefly described various pathogenic pathways associated with AD. The importance of Multi-Target-Directed Ligands and their design strategies in recently reported articles have been discussed in detail. Potent leads are identified through various structure-activity relationship studies, and their drug-like characteristics are described. Recently developed promising compounds have been summarized in the article. Some of these MTDLs with balanced activity profiles against different targets have the potential to be developed as drug candidates for the treatment of AD.

Topographic patterns of white matter hyperintensities are associated with multimodal neuroimaging biomarkers of Alzheimer's disease

Background

White matter hyperintensities (WMH) are frequently found in Alzheimer’s disease (AD). Commonly considered as a marker of cerebrovascular disease, regional WMH may be related to pathological hallmarks of AD, including beta-amyloid (Aβ) plaques and neurodegeneration. The aim of this study was to examine the regional distribution of WMH associated with Aβ burden, glucose hypometabolism, and gray matter volume reduction.

Methods

In a total of 155 participants (IMAP+ cohort) across the cognitive continuum from normal cognition to AD dementia, FLAIR MRI, AV45-PET, FDG-PET, and T1 MRI were acquired. WMH were automatically segmented from FLAIR images. Mean levels of neocortical Aβ deposition (AV45-PET), temporo-parietal glucose metabolism (FDG-PET), and medial-temporal gray matter volume (GMV) were extracted from processed images using established AD meta-signature templates. Associations between AD brain biomarkers and WMH, as assessed in region-of-interest and voxel-wise, were examined, adjusting for age, sex, education, and systolic blood pressure.

Results

There were no significant associations between global Aβ burden and region-specific WMH. Voxel-wise WMH in the splenium of the corpus callosum correlated with greater Aβ deposition at a more liberal threshold. Region- and voxel-based WMH in the posterior corpus callosum, along with parietal, occipital, and frontal areas, were associated with lower temporo-parietal glucose metabolism. Similarly, lower medial-temporal GMV correlated with WMH in the posterior corpus callosum in addition to parietal, occipital, and fontal areas.

Conclusions

This study demonstrates that local white matter damage is correlated with multimodal brain biomarkers of AD. Our results highlight modality-specific topographic patterns of WMH, which converged in the posterior white matter. Overall, these cross-sectional findings corroborate associations of regional WMH with AD-typical Aß deposition and neurodegeneration.

The neuroimaging of neurodegenerative and vascular disease in the secondary prevention of cognitive decline

Structural brain changes indicative of dementia occur up to 20 years before the onset of clinical symptoms. Efforts to modify the disease process after the onset of cognitive symptoms have been unsuccessful in recent years. Thus, future trials must begin during the preclinical phases of the disease before symptom onset. Age related cognitive decline is often the result of two coexisting brain pathologies: Alzheimer’s disease (amyloid, tau, and neurodegeneration) and vascular disease. This review article highlights some of the common neuroimaging techniques used to visualize the accumulation of neurodegenerative and vascular pathologies during the preclinical stages of dementia such as structural magnetic resonance imaging, positron emission tomography, and white matter hyperintensities. We also describe some emerging neuroimaging techniques such as arterial spin labeling, diffusion tensor imaging, and quantitative susceptibility mapping. Recent literature suggests that structural imaging may be the most sensitive and cost-effective marker to detect cognitive decline, while molecular positron emission tomography is primarily useful for detecting disease specific pathology later in the disease process. Currently, the presence of vascular disease on magnetic resonance imaging provides a potential target for optimizing vascular risk reduction strategies, and the presence of vascular disease may be useful when combined with molecular and metabolic markers of neurodegeneration for identifying the risk of cognitive impairment.

Genetic associations of in vivo pathology influence Alzheimer's disease susceptibility

INTRODUCTION

Although the heritability of sporadic Alzheimer's disease (AD) is estimated to be 60-80%, addressing the genetic contribution to AD risk still remains elusive. More specifically, it remains unclear whether genetic variants are able to affect neurodegenerative brain features that can be addressed by in vivo imaging techniques.

METHODS

Targeted sequencing analysis of the coding and UTR regions of 132 AD susceptibility genes was performed. Neuroimaging data using 11C-Pittsburgh Compound B positron emission tomography (PET), 18F-fluorodeoxyglucose PET, and MRI that are available from the KBASE (Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's disease) cohort were acquired. A total of 557 participants consisted of 336 cognitively normal (CN) adults, 137 mild cognitive impairment (MCI), and 84 AD dementia (ADD) groups.

RESULTS

We called 5391 high-quality single nucleotide variants (SNVs) on AD susceptibility genes and selected significant associations between variants and five in vivo AD pathologies: (1) amyloid β (Aβ) deposition, (2) AD-signature region cerebral glucose metabolism (AD-Cm), (3) posterior cingulate cortex (PCC) cerebral glucose metabolism (PCC-Cm), (4) AD-signature region cortical thickness (AD-Ct), and (5) hippocampal volume (Hv). The association analysis for common variants (allele frequency (AF) > 0.05) yielded several novel loci associated with Aβ deposition (PIWIL1-rs10848087), AD-Cm (NME8-rs2722372 and PSEN2-rs75733498), AD-Ct (PSEN1-rs7523) and, Hv (CASS4-rs3746625). Meanwhile, in a gene-based analysis for rare variants (AF < 0.05), cases carrying rare variants in LPL, FERMT2, NFAT5, DSG2, and ITPR1 displayed associations with the neuroimaging features. Exploratory voxel-based brain morphometry between the variant carriers and non-carriers was performed subsequently. Finally, we document a strong association of previously reported APOE variants with the in vivo AD pathologies and demonstrate that the variants exert a causal effect on AD susceptibility via neuroimaging features.

CONCLUSIONS

This study provides novel associations of genetic factors to Aβ accumulation and AD-related neurodegeneration to influence AD susceptibility.

Global Metabolic Shifts in Age and Alzheimer's Disease Mouse Brains Pivot at NAD+/NADH Redox Sites

Age and Alzheimer’s disease (AD) share some common features such as cognitive impairments, memory loss, metabolic disturbances, bioenergetic deficits, and inflammation. Yet little is known on how systematic shifts in metabolic networks depend on age and AD. In this work, we investigated the global metabolomic alterations in non-transgenic (NTg) and triple-transgenic (3xTg-AD) mouse brain hippocampus as a function of age by using untargeted Ultrahigh Performance Liquid Chromatography-tandem Mass Spectroscopy (UPLC-MS/MS). We observed common metabolic patterns with aging in both NTg and 3xTg-AD brains involved in energy-generating pathways, fatty acids oxidation, glutamate, and sphingolipid metabolism. We found age-related downregulation of metabolites from reactions in glycolysis that consumed ATP and in the TCA cycle, especially at NAD⁺/NADH-dependent redox sites, where age- and AD-associated limitations in the free NADH may alter reactions. Conversely, metabolites increased in glycolytic reactions in which ATP is produced. With age, inputs to the TCA cycle were increased including fatty acid β-oxidation and glutamine. Overall age- and AD-related changes were > 2-fold when comparing the declines of upstream metabolites of NAD⁺/NADH-dependent reactions to the increases of downstream metabolites (p = 10^-5, n = 8 redox reactions). Inflammatory metabolites such as ceramides and sphingosine-1-phosphate also increased with age. Age-related decreases in glutamate, GABA, and sphingolipid were seen which worsened with AD genetic load in 3xTg-AD brains, possibly contributing to synaptic, learning- and memory-related deficits. The data support the novel hypothesis that age- and AD-associated metabolic shifts respond to NAD(P)⁺/NAD(P)H redox-dependent reactions, which may contribute to decreased energetic capacity.

Plasma amyloid, tau, and neurodegeneration biomarker profiles predict Alzheimer's disease pathology and clinical progression in older adults without dementia

INTRODUCTION

Plasma markers have been reported to be associated with brain amyloid burden, tau pathology, or neurodegeneration. We aimed to evaluate whether plasma biomarker profiles could predict Alzheimer's disease (AD) pathology and clinical progression in older adults without dementia.

METHODS

Cross-sectional and longitudinal data of participants enrolled in this study were from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Plasma amyloid beta (Aβ)1-42/Aβ1-40 ratio was selected as the marker for amyloid pathology, p-tau181 for tau pathology, and neurofilament light for neurodegeneration. Cut-offs for these plasma markers were calculated with well-established positron emission tomography and structural imaging biomarkers as reference. Older adults without dementia were categorized into eight groups at baseline by plasma amyloid/tau/neurodegeneration (A/T/N) cut-offs. Clinical progression was analyzed using linear mixed-effects models and Cox proportional hazard models.

RESULTS

A total of 183 participants (97 cognitively normal [CN] subjects and 86 patients with mild cognitive impairment [MCI]; mean age 72.6 years, and 48.1% men) were included. Participants with A+ had significantly higher proportions of apolipoprotein E (APOE) gene ɛ4 carriers than those with A-. Brain atrophy was observed in all groups of CN, whereas cognition decline was obvious in the A+T+N+ group. Compared to A-T-N-, MCI patients with A+T+N+ had faster cognition worsening and faster brain atrophy. In the whole cohort, A+T+N+ and A+T+N- participants were at higher risk of clinical progression.

DISCUSSION

Plasma A/T/N biomarker profiles may predict AD pathology and clinical progression, indicating a potential role for plasma biomarkers in clinical trials. More research is warranted to develop a robust plasma AD framework.

Associations of Brain Pathology Cognitive and Physical Markers With Age in Cognitively Normal Individuals Aged 60-102 Years

The prevalence of brain pathologies increases with age and cognitive and physical functions worsen over the lifetime. It is unclear whether these processes show a similar increase with age. We studied the association of markers for brain pathology cognitive and physical functions with age in 288 cognitively normal individuals aged 60-102 years selected from the cross-sectional EMIF-AD PreclinAD and 90+ Study at the Amsterdam UMC. An abnormal score was consistent with a score below the 5th percentile in the 60- to 70-year-old individuals. Prevalence of abnormal scores was estimated using Generalized Estimating Equations (GEE) models. The prevalence of abnormal handgrip strength, the Digit Symbol Substitution Test, and hippocampal volume showed the fastest increase with age and abnormal MMSE score, muscle mass, and amyloid aggregation the lowest. The increase in prevalence of abnormal markers was partly dependent on sex, level of education, and amyloid aggregation. We did not find a consistent pattern in which markers of brain pathology cognitive and physical processes became abnormal with age.

Improving Anti-Neurodegenerative Benefits of Acetylcholinesterase Inhibitors in Alzheimer's Disease: Are Irreversible Inhibitors the Future?

Decades of research have produced no effective method to prevent, delay the onset, or slow the progression of Alzheimer's disease (AD). In contrast to these failures, acetylcholinesterase (AChE, EC 3.1.1.7) inhibitors slow the clinical progression of the disease and randomized, placebo-controlled trials in prodromal and mild to moderate AD patients have shown AChE inhibitor anti-neurodegenerative benefits in the cortex, hippocampus, and basal forebrain. CNS neurodegeneration and atrophy are now recognized as biomarkers of AD according to the National Institute on Aging-Alzheimer's Association (NIA-AA) criteria and recent evidence shows that these markers are among the earliest signs of prodromal AD, before the appearance of amyloid. The current AChE inhibitors (donepezil, rivastigmine, and galantamine) have short-acting mechanisms of action that result in dose-limiting toxicity and inadequate efficacy. Irreversible AChE inhibitors, with a long-acting mechanism of action, are inherently CNS selective and can more than double CNS AChE inhibition possible with short-acting inhibitors. Irreversible AChE inhibitors open the door to high-level CNS AChE inhibition and improved anti-neurodegenerative benefits that may be an important part of future treatments to more effectively prevent, delay the onset, or slow the progression of AD.

Amyloid β influences the relationship between cortical thickness and vascular load

INTRODUCTION

Cortical thickness has been proposed as a biomarker of Alzheimer's disease (AD)- related neurodegeneration, but the nature of its relationship with amyloid beta (Aβ) deposition and white matter hyperintensity volume (WMHV) in cognitively normal adults is unclear.

METHODS

We investigated the influences of Aβ status (negative/positive) and WMHV on cortical thickness in 408 cognitively normal adults aged 69.2 to 71.9 years who underwent 18F-Florbetapir positron emission tomography (PET) and structural magnetic resonance imaging (MRI). Two previously defined Alzheimer's disease (AD) cortical signature regions and the major cortical lobes were selected as regions of interest (ROIs) for cortical thickness.

RESULTS

Higher WMHV, but not Aβ status, predicted lower cortical thickness across all participants, in all ROIs. Conversely, when Aβ-positive participants were considered alone, higher WMHV predicted higher cortical thickness in a temporal AD-signature region.

DISCUSSION

WMHV may differentially influence cortical thickness depending on the presence or absence of Aβ, potentially reflecting different pathological mechanisms.

Morphometric network differences in ageing versus Alzheimer's disease dementia

Age being the main risk factor for Alzheimer's disease, it is particularly challenging to disentangle structural changes related to normal brain ageing from those specific to Alzheimer's disease. Most studies aiming to make this distinction focused on older adults only and on a priori anatomical regions. Drawing on a large, multi-cohort dataset ranging from young adults (n = 468; age range 18-35 years), to older adults with intact cognition (n = 431; age range 55-90 years) and with Alzheimer's disease (n = 50 with late mild cognitive impairment and 71 with Alzheimer's dementia, age range 56-88 years), we investigated grey matter organization and volume differences in ageing and Alzheimer's disease. Using independent component analysis on all participants' structural MRI, we first derived morphometric networks and extracted grey matter volume in each network. We also derived a measure of whole-brain grey matter pattern organization by correlating grey matter volume in all networks across all participants from the same cohort. We used logistic regressions and receiver operating characteristic analyses to evaluate how well grey matter volume in each network and whole-brain pattern could discriminate between ageing and Alzheimer's disease. Because increased heterogeneity is often reported as one of the main features characterizing brain ageing, we also evaluated interindividual heterogeneity within morphometric networks and across the whole-brain organization in ageing and Alzheimer's disease. Finally, to investigate the clinical validity of the different grey matter features, we evaluated whether grey matter volume or whole-brain pattern was related to clinical progression in cognitively normal older adults. Ageing and Alzheimer's disease contributed additive effects on grey matter volume in nearly all networks, except frontal lobe networks, where differences in grey matter were more specific to ageing. While no networks specifically discriminated Alzheimer's disease from ageing, heterogeneity in grey matter volumes across morphometric networks and in the whole-brain grey matter pattern characterized individuals with cognitive impairments. Preservation of the whole-brain grey matter pattern was also related to lower risk of developing cognitive impairment, more so than grey matter volume. These results suggest both ageing and Alzheimer's disease involve widespread atrophy, but that the clinical expression of Alzheimer's disease is uniquely associated with disruption of morphometric organization.

The importance of stroke as a risk factor of cognitive decline in community dwelling older and oldest peoples: the SONIC study

Background

Cognitive impairment is a major health concern among older and oldest people. Moreover, stroke is a relevant contributor for cognitive decline and development of dementia. The study of cognitive decline focused on stroke as the important risk factor by recruiting older and oldest is still lagging behind. Therefore, the aim of this study was to investigate the importance of stroke as a risk factor of cognitive decline during 3 years in community dwelling older and oldest people.

Methods

This study was longitudinal study with a 3-year follow-up in Japan. The participants were 1333 community dwelling older and oldest people (70 years old = 675, 80 years old = 589, and 90 years old = 69). Data collected included basic data (age, sex, and history of stroke), vascular risk factors (hypertension, diabetes mellitus, dyslipidemia, atrial fibrillation, and current smoking), and social factors (educational level, frequency of going outdoors, long-term care (LTC) service used, and residential area). The Japanese version of the Montreal Cognitive Assessment (MoCA-J) was decline of ≥2 points was defined as cognitive decline. Multiple logistic regression analysis was used to investigate the association between stroke and other risk factors with cognitive decline during a 3-year follow-up.

Results

The fit of the hypothesized model by multiple logistic regression showed that a history of stroke, advanced age, and greater MoCA-J score at the baseline were important risk factors, while the presence of dyslipidemia and a higher educational level were protective factors that were significantly correlated with cognitive decline during the 3-year follow-up.

Conclusions

The cognitive decline after the 3-year follow-up was influenced by the history of stroke and advanced age, while greater MoCA-J score at the baseline was positively associated with subsequent 3 years cognitive decline. The protective factors were the presence of dyslipidemia and a higher educational level. Therefore, these factors are considered important and should be taken into consideration when searching for creative solutions to prevent cognitive decline after stroke in community dwelling older and oldest people.

Association of Retinal Nerve Fiber Layer Thinning With Current and Future Cognitive Decline: A Study Using Optical Coherence Tomography

Importance

Identifing potential screening tests for future cognitive decline is a priority for developing treatments for and the prevention of dementia.

Objective

To examine the potential of retinal nerve fiber layer (RNFL) thickness measurement in identifying those at greater risk of cognitive decline in a large community cohort of healthy people.

Design, Setting, and Participants

UK Biobank is a prospective, multicenter, community-based study of UK residents aged 40 to 69 years at enrollment who underwent baseline retinal optical coherence tomography imaging, a physical examination, and a questionnaire. The pilot study phase was conducted from March 2006 to June 2006, and the main cohort underwent examination for baseline measures from April 2007 to October 2010. Four basic cognitive tests were performed at baseline, which were then repeated in a subset of participants approximately 3 years later. We analyzed eyes with high-quality optical coherence tomography images, excluding those with eye disease or vision loss, a history of ocular or neurological disease, or diabetes. We explored associations between RNFL thickness and cognitive function using multivariable logistic regression modeling to control for demographic as well as physiologic and ocular variation.

Main Outcomes and Measures

Odds ratios (ORs) for cognitive performance in the lowest fifth percentile in at least 2 of 4 cognitive tests at baseline, or worsening results on at least 1 cognitive test at follow-up. These analyses were adjusted for age, sex, race/ethnicity, height, refraction, intraocular pressure, education, and socioeconomic status.

Results

A total of 32 038 people were included at baseline testing, for whom the mean age was 56.0 years and of whom 17 172 (53.6%) were women. A thinner RNFL was associated with worse cognitive performance on baseline assessment. A multivariable regression controlling for potential confounders showed that those in the thinnest quintile of RNFL were 11% more likely to fail at least 1 cognitive test (95% CI, 2.0%-2.1%; P = .01). Follow-up cognitive tests were performed for 1251 participants (3.9%). Participants with an RNFL thickness in the 2 thinnest quintiles were almost twice as likely to have at least 1 test score be worse at follow-up cognitive testing (quintile 1: OR, 1.92; 95% CI, 1.29-2.85; P < .001; quintile 2: OR, 2.08; 95% CI, 1.40-3.08; P < .001).

Conclusions and Relevance

A thinner RNFL is associated with worse cognitive function in individuals without a neurodegenerative disease as well as greater likelihood of future cognitive decline. This preclinical observation has implications for future research, prevention, and treatment of dementia.

The mitochondria-targeted antioxidant MitoQ inhibits memory loss, neuropathology, and extends lifespan in aged 3xTg-AD mice

Oxidative stress, likely stemming from dysfunctional mitochondria, occurs before major cognitive deficits and neuropathologies become apparent in Alzheimer's disease (AD) patients and in mouse models of the disease. We previously reported that treating 2- to 7-month-old 3xTg-AD mice with the mitochondria-targeted antioxidant MitoQ (mitoquinone mesylate: [10-(4,5-Dimethoxy-2-methyl-3,6-dioxo-1,4-cyclohexadien-1-yl)decyl](triphenyl)phosphonium methanesulfonate), a period when AD-like pathologies first manifest in them, prevents AD-like symptoms from developing. To elucidate further a role for mitochondria-derived oxidative stress in AD progression, we examined the ability of MitoQ to inhibit AD-like pathologies in these mice at an age in which cognitive and neuropathological symptoms have fully developed. 3xTg-AD female mice received MitoQ in their drinking water for five months beginning at twelve months after birth. Untreated 18-month-old 3xTg-AD mice exhibited significant learning deficits and extensive AD-like neuropathologies. MitoQ-treated mice showed improved memory retention compared to untreated 3xTg-AD mice as well as reduced brain oxidative stress, synapse loss, astrogliosis, microglial cell proliferation, Aβ accumulation, caspase activation, and tau hyperphosphorylation. Additionally, MitoQ treatment significantly increased the abbreviated lifespan of the 3xTg-AD mice. These findings support a role for the involvement of mitochondria-derived oxidative stress in the etiology of AD and suggest that mitochondria-targeted antioxidants may lessen symptoms in AD patients.

Amyloid β Deposition and Suspected Non-Alzheimer Pathophysiology and Cognitive Decline Patterns for 12 Years in Oldest Old Participants Without Dementia

Importance

The prevalence of pathologic conditions of the brain associated with Alzheimer disease increases strongly with age. Little is known about the distribution and clinical significance of preclinical biomarker staging in the oldest old, when most individuals without dementia are likely to have positive biomarkers.

Objective

To compare the patterns of long-term cognitive decline in multiple domains by preclinical biomarker status in the oldest old without dementia.

Design, Setting, and Participants

A longitudinal observational study with a mean (SD) of 12.2 (2.2) years (range 7.2-15.1 years) of follow-up was conducted in an academic medical center from August 24, 2000, to January 14, 2016, including and extending observations from the Ginkgo Evaluation of Memory study. A total of 197 adults who had completed the Ginkgo Evaluation of Memory study, were free of dementia, and were able to undergo magnetic resonance imaging were eligible for a neuroimaging study in 2009. Of these patients, 175 were included in the present analyses; 140 (80%) were cognitively normal and 35 (20%) had mild cognitive impairment.

Main Outcomes and Measures

Biomarker groups included amyloid β negative (Aβ-)/neurodegeneration negative (ND-), amyloid β positive (Aβ+)/ND-, Aβ-/neurodegeneration positive (ND+), and Aβ+/ND+ based on Pittsburgh Compound B retention and hippocampal volume in 2009. Participants completed baseline neuropsychological testing from 2000 to 2002 and annual testing from 2004 to 2016. Domains included memory, executive function, language, visual-spatial reasoning, and attention and psychomotor speed. Slopes of decline were evaluated with linear mixed models adjusted for age, sex, and years of education.

Results

Of the 175 participants (71 women and 104 men), at imaging, mean (SD) age was 86.0 (2.9) years (range, 82-95 years). A total of 42 participants (24.0%) were Aβ-/ND-, 32 (18.3%) were Aβ+/ND-, 35 (20.0%) were Aβ-/ND+, and 66 (37.7%) were Aβ+/ND+. On all cognitive measures, the Aβ+/ND+ group showed the steepest decline. Compared with the Aβ-/ND- group, the amyloid deposition alone (Aβ+/ND-) group showed faster decline on tests of verbal and visual memory (-0.3513; 95% CI, -0.5269 to -0.1756), executive function (0.0158; 95% CI, 0.0013-0.0303), and language (-0.1934; 95% CI, -0.3520 to -0.0348). The Aβ-/ND+ group showed faster visual memory decline than the Aβ-/ND- reference group (-0.3007; 95% CI, -0.4736 to -0.1279).

Conclusions and Relevance

In the oldest old without dementia, presence of either or both Aβ and hippocampal atrophy is typical (>75%). Isolated hippocampal volume atrophy is associated only with greater decline in memory. However, isolated Aβ is associated with decline in memory plus language and executive functions. These findings suggest different underlying pathophysiologic processes in the Aβ+/ND- and Aβ-/ND+ groups.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease

In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

Brain volumes and cortical thickness on MRI in the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER)

Background

The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) was a multicenter randomized controlled trial that reported beneficial effects on cognition for a 2-year multimodal intervention (diet, exercise, cognitive training, vascular risk monitoring) versus control (general health advice). This study reports exploratory analyses of brain MRI measures.

Methods

FINGER targeted 1260 older individuals from the general Finnish population. Participants were 60–77 years old, at increased risk for dementia but without dementia/substantial cognitive impairment. Brain MRI scans were available for 132 participants (68 intervention, 64 control) at baseline and 112 participants (59 intervention, 53 control) at 2 years. MRI measures included regional brain volumes, cortical thickness, and white matter lesion (WML) volume. Cognition was assessed at baseline and 1- and 2-year visits using a comprehensive neuropsychological test battery. We investigated the (1) differences between the intervention and control groups in change in MRI outcomes (FreeSurfer 5.3) and (2) post hoc sub-group analyses of intervention effects on cognition in participants with more versus less pronounced structural brain changes at baseline (mixed-effects regression models, Stata 12).

Results

No significant differences between the intervention and control groups were found on the changes in MRI measures. Beneficial intervention effects on processing speed were more pronounced in individuals with higher baseline cortical thickness in Alzheimer’s disease signature areas (composite measure of entorhinal, inferior and middle temporal, and fusiform regions). The randomization group × time × cortical thickness interaction coefficient was 0.198 (p = 0.021). A similar trend was observed for higher hippocampal volume (group × time × hippocampus volume interaction coefficient 0.1149, p = 0.085).

Conclusions

The FINGER MRI exploratory sub-study did not show significant differences between the intervention and control groups on changes in regional brain volumes, regional cortical thicknesses, or WML volume after 2 years in at-risk elderly without substantial impairment. The cognitive benefits on processing speed of the FINGER intervention may be more pronounced in individuals with fewer structural brain changes on MRI at baseline. This suggests that preventive strategies may be more effective if started early, before the occurrence of more pronounced structural brain changes.

Trial registration

ClinicalTrials.gov, NCT01041989. Registered January 5, 2010.

Cerebral white matter free water: A sensitive biomarker of cognition and function

OBJECTIVE

To determine whether free water (FW) content, initially developed to correct metrics derived from diffusion tensor imaging and recently found to be strongly associated with vascular risk factors, may constitute a sensitive biomarker of white matter (WM) microstructural differences associated with cognitive performance but remains unknown.

METHODS

Five hundred thirty-six cognitively diverse individuals, aged 77 ± 8 years, received yearly comprehensive clinical evaluations and a baseline MRI examination of whom 224 underwent follow-up MRI. WM microstructural measures, including FW, fractional anisotropy, and mean diffusivity corrected for FW and WM hyperintensity burden were computed within WM voxels of each individual. Baseline and change in MRI metrics were then used as independent variables to explain baseline and change in episodic memory (EM), executive function (EF), and Clinical Dementia Rating (CDR) scores using linear, logistic, and Cox proportional-hazards regressions.

RESULTS

Higher baseline FW and WM hyperintensity were associated with lower baseline EM and EF, higher baseline CDR, accelerated EF and EM decline, and higher probability to transition to a more severe CDR stage (p values <0.01). Annual change in FW was also found to be associated with concomitant change in cognitive and functional performance (p values <0.01).

CONCLUSIONS

This study finds cross-sectional and longitudinal associations between FW content and trajectory of cognitive and functional performance in a large sample of cognitively diverse individuals. It supports the need to investigate the pathophysiologic process that manifests increased FW, potentially leading to more severe WM territory injury and promoting cognitive and functional decline.

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

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

Physiological effects of amyloid precursor protein and its derivatives on neural stem cell biology and signaling pathways involved

The pathological implication of amyloid precursor protein (APP) in Alzheimer's disease has been widely documented due to its involvement in the generation of amyloid-β peptide. However, the physiological functions of APP are still poorly understood. APP is considered a multimodal protein due to its role in a wide variety of processes, both in the embryo and in the adult brain. Specifically, APP seems to play a key role in the proliferation, differentiation and maturation of neural stem cells. In addition, APP can be processed through two canonical processing pathways, generating different functionally active fragments: soluble APP-α, soluble APP-β, amyloid-β peptide and the APP intracellular C-terminal domain. These fragments also appear to modulate various functions in neural stem cells, including the processes of proliferation, neurogenesis, gliogenesis or cell death. However, the molecular mechanisms involved in these effects are still unclear. In this review, we summarize the physiological functions of APP and its main proteolytic derivatives in neural stem cells, as well as the possible signaling pathways that could be implicated in these effects. The knowledge of these functions and signaling pathways involved in the onset or during the development of Alzheimer's disease is essential to advance the understanding of the pathogenesis of Alzheimer's disease, and in the search for potential therapeutic targets.

The 12-Word Philadelphia Verbal Learning Test Performances in Older Adults: Brain MRI and Cerebrospinal Fluid Correlates and Regression-Based Normative Data

Background/Aims

This study evaluated neuroimaging and biological correlates, psychometric properties, and regression-based normative data of the 12-word Philadelphia Verbal Learning Test (PVLT), a list-learning test.

Methods

Vanderbilt Memory and Aging Project participants free of clinical dementia and stroke (n = 230, aged 73 ± 7 years) completed a neuropsychological protocol and brain MRI. A subset (n = 111) underwent lumbar puncture for analysis of Alzheimer's disease (AD) and axonal integrity cerebrospinal fluid (CSF) biomarkers. Regression models related PVLT indices to MRI and CSF biomarkers adjusting for age, sex, race/ethnicity, education, APOE-ε4 carrier status, cognitive status, and intracranial volume (MRI models). Secondary analyses were restricted to participants with normal cognition (NC; n = 127), from which regression-based normative data were generated.

Results

Lower PVLT performances were associated with smaller medial temporal lobe volumes (p < 0.05) and higher CSF tau concentrations (p < 0.04). Among NC, PVLT indices were associated with white matter hyperintensities on MRI and an axonal injury biomarker (CSF neurofilament light; p < 0.03).

Conclusion

The PVLT appears sensitive to markers of neurodegeneration, including temporal regions affected by AD. Conversely, in cognitively normal older adults, PVLT performance seems to relate to white matter disease and axonal injury, perhaps reflecting non-AD pathways to cognitive change. Enhanced normative data enrich the clinical utility of this tool.

Secondary prevention of Alzheimer's dementia: neuroimaging contributions

BACKGROUND

In Alzheimer's disease (AD), pathological changes may arise up to 20 years before the onset of dementia. This pre-dementia window provides a unique opportunity for secondary prevention. However, exposing non-demented subjects to putative therapies requires reliable biomarkers for subject selection, stratification, and monitoring of treatment. Neuroimaging allows the detection of early pathological changes, and longitudinal imaging can assess the effect of interventions on markers of molecular pathology and rates of neurodegeneration. This is of particular importance in pre-dementia AD trials, where clinical outcomes have a limited ability to detect treatment effects within the typical time frame of a clinical trial. We review available evidence for the use of neuroimaging in clinical trials in pre-dementia AD. We appraise currently available imaging markers for subject selection, stratification, outcome measures, and safety in the context of such populations.

MAIN BODY

Amyloid positron emission tomography (PET) is a validated in-vivo marker of fibrillar amyloid plaques. It is appropriate for inclusion in trials targeting the amyloid pathway, as well as to monitor treatment target engagement. Amyloid PET, however, has limited ability to stage the disease and does not perform well as a prognostic marker within the time frame of a pre-dementia AD trial. Structural magnetic resonance imaging (MRI), providing markers of neurodegeneration, can improve the identification of subjects at risk of imminent decline and hence play a role in subject inclusion. Atrophy rates (either hippocampal or whole brain), which can be reliably derived from structural MRI, are useful in tracking disease progression and have the potential to serve as outcome measures. MRI can also be used to assess comorbid vascular pathology and define homogeneous groups for inclusion or for subject stratification. Finally, MRI also plays an important role in trial safety monitoring, particularly the identification of amyloid-related imaging abnormalities (ARIA). Tau PET to measure neurofibrillary tangle burden is currently under development. Evidence to support the use of advanced MRI markers such as resting-state functional MRI, arterial spin labelling, and diffusion tensor imaging in pre-dementia AD is preliminary and requires further validation.

CONCLUSION

We propose a strategy for longitudinal imaging to track early signs of AD including quantitative amyloid PET and yearly multiparametric MRI.

Functional connectivity in cognitive control networks mitigates the impact of white matter lesions in the elderly

BACKGROUND

Cerebrovascular pathology, quantified by white matter lesions (WML), is known to affect cognition in aging, and is associated with an increased risk of dementia. The present study aimed to investigate whether higher functional connectivity in cognitive control networks mitigates the detrimental effect of WML on cognition.

METHODS

Nondemented older participants (≥ 50 years; n = 230) underwent cognitive evaluation, fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI), and resting state functional magnetic resonance imaging (fMRI). Total WML volumes were quantified algorithmically. Functional connectivity was assessed in preselected higher-order resting state networks, namely the fronto-parietal, the salience, and the default mode network, using global and local measures. Latent moderated structural equations modeling examined direct and interactive relationships between WML volumes, functional connectivity, and cognition.

RESULTS

Larger WML volumes were associated with worse cognition, having a greater impact on executive functions (β = -0.37, p < 0.01) than on memory (β = -0.22, p < 0.01). Higher global functional connectivity in the fronto-parietal network and higher local connectivity between the salience network and medial frontal cortex significantly mitigated the impact of WML on executive functions, (unstandardized coefficients: b = 2.39, p = 0.01; b = 3.92, p = 0.01) but not on memory (b = -5.01, p = 0.51, b = 2.01, p = 0.07, respectively). No such effects were detected for the default mode network.

CONCLUSION

Higher functional connectivity in fronto-parietal and salience networks may protect against detrimental effects of WML on executive functions, the cognitive domain that was predominantly affected by cerebrovascular pathology. These results highlight the crucial role of cognitive control networks as a neural substrate of cognitive reserve in older individuals.

A 'Comprehensive Visual Rating Scale' for predicting progression to dementia in patients with mild cognitive impairment

Background

Numerous efforts have been made to identify biomarkers for predicting the progression of dementia in patients with mild cognitive impairment (MCI), and recently, a comprehensive visual rating scale (CVRS) based on magnetic resonance imaging (MRI) has been validated to assess structural changes in the brain of elderly patients. Based on this, the present study investigated the use of CVRS for predicting dementia and elucidated its association with cognitive change in patients with MCI over a three-year follow-up.

Methods

We included 340 patients with MCI with more than one follow-up visit. Data were obtained from the Alzheimer’s disease Neuroimaging Initiative study. We assessed all the patients using CVRS and determined their progression to dementia during a follow-up period of over 3 years. The cox proportional hazards model was used to analyze hazard ratios (HRs) of CVRS for disease progression. Further, multiple cognitive measures of the patients over time were fitted using the random effect model to assess the effect of initial CVRS score on subsequent cognitive changes.

Results

Of 340 patients, 69 (20.2%) progressed to dementia and the median baseline score (interquartile range) of CVRS significantly differed between stable MCI and progressive MCI (9 (5–13) vs 13 (8–17), p<0.001). The initial CVRS score was independently associated with an increased risk of progression to dementia (HR 1.123, 95% confidence interval [CI] 1.059–1.192). From 12 to 24 months, the effect of the interaction between CVRS and interval of follow-up visit on cognitive performance achieved significance (p<0.001).

Conclusions

Baseline CVRS predicted the progression to dementia in patients with MCI, and was independently associated with longitudinal cognitive decline.

Temporal Order of Alzheimer's Disease-Related Cognitive Marker Changes in BLSA and WRAP Longitudinal Studies

Investigation of the temporal trajectories of currently used neuropsychological tests is critical to identifying earliest changing measures on the path to dementia due to Alzheimer's disease (AD). We used the Progression Score (PS) method to characterize the temporal trajectories of measures of verbal memory, executive function, attention, processing speed, language, and mental status using data spanning normal cognition, mild cognitive impairment, and AD from 1,661 participants with a total of 7,839 visits (age at last visit 77.6 SD 9.2) in the Baltimore Longitudinal Study of Aging (BLSA) and 1510 participants with a total of 3,473 visits (age at last visit 59.5 SD 7.4) in the Wisconsin Registry for Alzheimer's Prevention (WRAP). This method aligns individuals in time based on the similarity of their longitudinal measurements to reveal temporal trajectories. As a validation of our methodology, we explored the associations between the individualized cognitive progression scores (Cog-PS) computed by our method and clinical diagnosis. Digit span tests were the first to show declines in both data sets, and were detected mainly among cognitively normal individuals. These were followed by tests of verbal memory, which were in turn followed by Trail Making Tests, Boston Naming Test, and Mini-Mental State Examination. Differences in Cog-PS across the clinical diagnosis and APOEɛ4 groups were statistically significant, highlighting the potential use of Cog-PS as individualized indicators of disease progression. Identifying cognitive measures that are changing in preclinical AD can lead to the development of novel cognitive tests that are finely tuned to detecting earliest changes.

Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease

Alzheimer's disease (AD) is a major neurodegenerative disease and the most common cause of dementia. Currently, no treatment exists to slow down or stop the progression of AD. There is converging belief that disease-modifying treatments should focus on early stages of the disease, that is, the mild cognitive impairment (MCI) and preclinical stages. Making a diagnosis of AD and offering a prognosis (likelihood of converting to AD) at these early stages are challenging tasks but possible with the help of multimodality imaging, such as magnetic resonance imaging (MRI), fluorodeoxyglucose (FDG)-positron emission topography (PET), amyloid-PET, and recently introduced tau-PET, which provides different but complementary information. This article is a focused review of existing research in the recent decade that used statistical machine learning and artificial intelligence methods to perform quantitative analysis of multimodality image data for diagnosis and prognosis of AD at the MCI or preclinical stages. We review the existing work in 3 subareas: diagnosis, prognosis, and methods for handling modality-wise missing data-a commonly encountered problem when using multimodality imaging for prediction or classification. Factors contributing to missing data include lack of imaging equipment, cost, difficulty of obtaining patient consent, and patient drop-off (in longitudinal studies). Finally, we summarize our major findings and provide some recommendations for potential future research directions.

Thiamine diphosphate reduction strongly correlates with brain glucose hypometabolism in Alzheimer's disease, whereas amyloid deposition does not

Background

The underlying mechanism of brain glucose hypometabolism, an invariant neurodegenerative feature that tightly correlates with cognitive impairment and disease progression of Alzheimer’s disease (AD), remains elusive.

Methods

Positron emission tomography with 2-[¹⁸F]fluoro-2-deoxy-d-glucose (FDG-PET) was used to evaluate brain glucose metabolism, presented as the rate of 2-[¹⁸F]fluoro-2-deoxy-d-glucose standardized uptake value ratio (FDG SUVR) in patients with AD or control subjects and in mice with or without thiamine deficiency induced by a thiamine-deprived diet. Brain amyloid-β (Aβ) deposition in patients with clinically diagnosed AD was quantified by performing assays using ¹¹C-Pittsburgh compound B PET. The levels of thiamine metabolites in blood samples of patients with AD and control subjects, as well as in blood and brain samples of mice, were detected by high-performance liquid chromatography with fluorescence detection.

Results

FDG SUVRs in frontal, temporal, and parietal cortices of patients with AD were closely correlated with the levels of blood thiamine diphosphate (TDP) and cognitive abilities, but not with brain Aβ deposition. Mice on a thiamine-deprived diet manifested a significant decline of FDG SUVRs in multiple brain regions as compared with those in control mice, with magnitudes highly correlating with both brain and blood TDP levels. There were no significant differences in the changes of FDG SUVRs in observed brain regions between amyloid precursor protein/presenilin-1 and wild-type mice following thiamine deficiency.

Conclusions

We demonstrate, for the first time to our knowledge, in vivo that TDP reduction strongly correlates with brain glucose hypometabolism, whereas amyloid deposition does not. Our study provides new insight into the pathogenesis and therapeutic strategy for AD.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0354-2) contains supplementary material, which is available to authorized users.

Regionally specific changes in the hippocampal circuitry accompany progression of cerebrospinal fluid biomarkers in preclinical Alzheimer's disease

Neuropathological and in vivo brain imaging studies agree that the cornu ammonis 1 and subiculum subfields of the hippocampus are most vulnerable to atrophy in the prodromal phases of Alzheimer's disease (AD). However, there has been limited investigation of the structural integrity of the components of the hippocampal circuit, including subfields and extra-hippocampal white matter structure, in relation to the progression of well-accepted cerebrospinal fluid (CSF) biomarkers of AD, amyloid-β 1-42 (Aβ) and total-tau (tau). We investigated these relationships in 88 aging asymptomatic individuals with a parental or multiple-sibling familial history of AD. Apolipoprotein (APOE) ɛ4 risk allele carriers were identified, and all participants underwent cognitive testing, structural magnetic resonance imaging, and lumbar puncture for CSF assays of tau, phosphorylated-tau (p-tau) and Aβ. Individuals with a reduction in CSF Aβ levels (an indicator of amyloid accretion into neuritic plaques) as well as evident tau pathology (believed to be linked to neurodegeneration) exhibited lower subiculum volume, lower fornix microstructural integrity, and a trend towards lower cognitive score than individuals who showed only reduction in CSF Aβ. In contrast, persons with normal levels of tau showed an increase in structural MR markers in relation to declining levels of CSF Aβ. These results suggest that hippocampal subfield volume and extra-hippocampal white matter microstructure demonstrate a complex pattern where an initial volume increase is followed by decline among asymptomatic individuals who, in some instances, may be a decade or more away from onset of cognitive or functional impairment.

Moderate decline in select synaptic markers in the prefrontal cortex (BA9) of patients with Alzheimer's disease at various cognitive stages

Synaptic loss, plaques and neurofibrillary tangles are viewed as hallmarks of Alzheimer's disease (AD). This study investigated synaptic markers in neocortical Brodmann area 9 (BA9) samples from 171 subjects with and without AD at different levels of cognitive impairment. The expression levels of vesicular glutamate transporters (VGLUT1&2), glutamate uptake site (EAAT2), post-synaptic density protein of 95 kD (PSD95), vesicular GABA/glycine transporter (VIAAT), somatostatin (som), synaptophysin and choline acetyl transferase (ChAT) were evaluated. VGLUT2 and EAAT2 were unaffected by dementia. The VGLUT1, PSD95, VIAAT, som, ChAT and synaptophysin expression levels significantly decreased as dementia progressed. The maximal decrease varied between 12% (synaptophysin) and 42% (som). VGLUT1 was more strongly correlated with dementia than all of the other markers (polyserial correlation = -0.41). Principal component analysis using these markers was unable to differentiate the CDR groups from one another. Therefore, the status of the major synaptic markers in BA9 does not seem to be linked to the cognitive status of AD patients. The findings of this study suggest that the loss of synaptic markers in BA9 is a late event that is only weakly related to AD dementia.

AMPA Receptor Trafficking in Natural and Pathological Aging

α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) enable most excitatory transmission in the brain and are crucial for mediating basal synaptic strength and plasticity. Because of the importance of their function, AMPAR dynamics, activity and subunit composition undergo a tight regulation which begins as early as prenatal development and continues through adulthood. Accumulating evidence suggests that the precise regulatory mechanisms involved in orchestrating AMPAR trafficking are challenged in the aging brain. In turn dysregulation of AMPARs can be linked to most neurological and neurodegenerative disorders. Understanding the mechanisms that govern AMPAR signaling during natural and pathological cognitive decline will guide the efforts to develop most effective ways to tackle neurodegenerative diseases which are one of the primary burdens afflicting an increasingly aging population. In this review, I provide a brief overview of the molecular mechanisms involved in AMPAR trafficking highlighting what is currently known about how these processes change with age and disease. As a particularly well-studied example of AMPAR dysfunction in pathological aging I focus in Alzheimer’s disease (AD) with special emphasis in how the production of neurofibrillary tangles (NFTs) and amyloid-β plaques may contribute to disruption in AMPAR function.

27-Hydroxycholesterol impairs neuronal glucose uptake through an IRAP/GLUT4 system dysregulation

Ismail et al. show that 27-hydroxycholesterol, a peripheral cholesterol metabolite capable of passing the blood–brain barrier, reduces brain glucose uptake by upregulating the renin-angiotensin system and inhibiting GLUT4. This alteration affects memory processes and is likely to have implications on neurodegenerative diseases.

Hypercholesterolemia is associated with cognitively deteriorated states. Here, we show that excess 27-hydroxycholesterol (27-OH), a cholesterol metabolite passing from the circulation into the brain, reduced in vivo brain glucose uptake, GLUT4 expression, and spatial memory. Furthermore, patients exhibiting higher 27-OH levels had reduced ¹⁸F-fluorodeoxyglucose uptake. This interplay between 27-OH and glucose uptake revealed the engagement of the insulin-regulated aminopeptidase (IRAP). 27-OH increased the levels and activity of IRAP, countered the IRAP antagonist angiotensin IV (AngIV)–mediated glucose uptake, and enhanced the levels of the AngIV-degrading enzyme aminopeptidase N (AP-N). These effects were mediated by liver X receptors. Our results reveal a molecular link between cholesterol, brain glucose, and the brain renin-angiotensin system, all of which are affected in some neurodegenerative diseases. Thus, reducing 27-OH levels or inhibiting AP-N maybe a useful strategy in the prevention of the altered glucose metabolism and memory decline in these disorders.

Independent value added by diffusion MRI for prediction of cognitive function in older adults

The purpose of this study was to determine whether white matter microstructure measured by diffusion magnetic resonance imaging (dMRI) provides independent information about baseline level or change in executive function (EF) or memory (MEM) in older adults with and without cognitive impairment. Longitudinal data was acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study from phases GO and 2 (2009–2015). ADNI participants included were diagnosed as cognitively normal (n = 46), early mild cognitive impairment (MCI) (n = 48), late MCI (n = 29), and dementia (n = 39) at baseline. We modeled the association between dMRI-based global white matter mean diffusivity (MD) and baseline level and change in EF and MEM composite scores, in models controlling for baseline bilateral hippocampal volume, regional cerebral FDG PET metabolism and global cerebral AV45 PET uptake. EF and MEM composite scores were measured at baseline, 6, 12, 24 and 36 months. In the baseline late MCI and dementia groups, greater global MD was associated with lesser baseline EF, but not EF change nor MEM baseline or change. As expected, lesser hippocampal volume and lesser FDG PET metabolism was associated with greater rates of EF and MEM decline. In ADNI-GO/2 participants, white matter integrity provided independent information about current executive function, but was not sensitive to future cognitive change. Since individuals experiencing executive function declines progress to dementia more rapidly than those with only memory impairment, better biomarkers of future executive function decline are needed.

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In the ADNI cohort, MRI and PET predictors of baseline and change in executive function were tested.

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Global mean diffusivity was associated with baseline, but not change in, executive function.

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Diffusion MRI provides independent information on current executive function in older adults.

Heterogeneity in Suspected Non-Alzheimer Disease Pathophysiology Among Clinically Normal Older Individuals

IMPORTANCE

A substantial proportion of clinically normal (CN) older individuals are classified as having suspected non-Alzheimer disease pathophysiology (SNAP), defined as biomarker negative for β-amyloid (Aβ-) but positive for neurodegeneration (ND+). The etiology of SNAP in this population remains unclear.

OBJECTIVE

To determine whether CN individuals with SNAP show evidence of early Alzheimer disease (AD) processes (ie, elevated tau levels and/or increased risk for cognitive decline).

DESIGN, SETTING, AND PARTICIPANTS

This longitudinal observational study performed in an academic medical center included 247 CN participants from the Harvard Aging Brain Study. Participants were classified into preclinical AD stages using measures of Aβ (Pittsburgh Compound B [PIB]-labeled positron emission tomography) and ND (hippocampal volume or cortical glucose metabolism from AD-vulnerable regions). Classifications included stages 0 (Aβ-/ND-), 1 (Aβ+/ND-), and 2 (Aβ+/ND+) and SNAP (Aβ-/ND+). Continuous levels of PiB and ND, tau levels in the medial and inferior temporal lobes, and longitudinal cognition were examined. Data collection began in 2010 and is ongoing. Data were analyzed from 2015 to 2016.

MAIN OUTCOMES AND MEASURES

Evidence of amyloid-independent tau deposition and/or cognitive decline.

RESULTS

Of the 247 participants (142 women [57.5%]; 105 men [42.5%]; mean age, 74 [range, 63-90] years), 64 (25.9%) were classified as having SNAP. Compared with the stage 0 group, the SNAP group was not more likely to have subthreshold PiB values (higher values within the Aβ- range), suggesting that misclassification due to the PiB cutoff was not a prominent contributor to this group (mean [SD] distribution volume ratio, 1.08 [0.05] for the SNAP group; 1.09 [0.05] for the stage 1 group). Tau levels in the medial and inferior temporal lobes were indistinguishable between the SNAP and stage 0 groups (entorhinal cortex, β = -0.005 [SE, 0.036]; parahippocampal gyrus, β = -0.001 [SE, 0.027]; and inferior temporal lobe, β = -0.004 [SE, 0.027]; P ≥ .88) and were lower in the SNAP group compared with the stage 2 group (entorhinal cortex, β = -0.125 [SE, 0.041]; parahippocampal gyrus, β = -0.074 [SE, 0.030]; and inferior temporal lobe, β = -0.083 [SE, 0.031]; P ≤ .02). The stage 2 group demonstrated greater cognitive decline compared with all other groups (stage 0, β = -0.239 [SE, 0.042]; stage 1, β = -0.242 [SE, 0.051]; and SNAP, β = -0.157 [SE, 0.044]; P ≤ .001), whereas the SNAP group showed a diminished practice effect over time compared with the stage 0 group (β = -0.082 [SE, 0.037]; P = .03).

CONCLUSIONS AND RELEVANCE

In this study, clinically normal adults with SNAP did not exhibit evidence of elevated tau levels, which suggests that this biomarker construct does not represent amyloid-independent tauopathy. At the group level, individuals with SNAP did not show cognitive decline but did show a diminished practice effect. SNAP is likely heterogeneous, with a subset of this group at elevated risk for short-term decline. Future refinement of biomarkers will be necessary to subclassify this group and determine the biological correlates of ND markers among Aβ- CN individuals.

A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers

Biomarkers have become an essential component of Alzheimer disease (AD) research and because of the pervasiveness of AD pathology in the elderly, the same biomarkers are used in cognitive aging research. A number of current issues suggest that an unbiased descriptive classification scheme for these biomarkers would be useful. We propose the "A/T/N" system in which 7 major AD biomarkers are divided into 3 binary categories based on the nature of the pathophysiology that each measures. "A" refers to the value of a β-amyloid biomarker (amyloid PET or CSF Aβ42); "T," the value of a tau biomarker (CSF phospho tau, or tau PET); and "N," biomarkers of neurodegeneration or neuronal injury ([(18)F]-fluorodeoxyglucose-PET, structural MRI, or CSF total tau). Each biomarker category is rated as positive or negative. An individual score might appear as A+/T+/N-, or A+/T-/N-, etc. The A/T/N system includes the new modality tau PET. It is agnostic to the temporal ordering of mechanisms underlying AD pathogenesis. It includes all individuals in any population regardless of the mix of biomarker findings and therefore is suited to population studies of cognitive aging. It does not specify disease labels and thus is not a diagnostic classification system. It is a descriptive system for categorizing multidomain biomarker findings at the individual person level in a format that is easy to understand and use. Given the present lack of consensus among AD specialists on terminology across the clinically normal to dementia spectrum, a biomarker classification scheme will have broadest acceptance if it is independent from any one clinically defined diagnostic scheme.

"New Old Pathologies": AD, PART, and Cerebral Age-Related TDP-43 With Sclerosis (CARTS)

The pathology-based classification of Alzheimer's disease (AD) and other neurodegenerative diseases is a work in progress that is important for both clinicians and basic scientists. Analyses of large autopsy series, biomarker studies, and genomics analyses have provided important insights about AD and shed light on previously unrecognized conditions, enabling a deeper understanding of neurodegenerative diseases in general. After demonstrating the importance of correct disease classification for AD and primary age-related tauopathy, we emphasize the public health impact of an underappreciated AD "mimic," which has been termed "hippocampal sclerosis of aging" or "hippocampal sclerosis dementia." This pathology affects >20% of individuals older than 85 years and is strongly associated with cognitive impairment. In this review, we provide an overview of current hypotheses about how genetic risk factors (GRN, TMEM106B, ABCC9, and KCNMB2), and other pathogenetic influences contribute to TDP-43 pathology and hippocampal sclerosis. Because hippocampal sclerosis of aging affects the "oldest-old" with arteriolosclerosis and TDP-43 pathologies that extend well beyond the hippocampus, more appropriate terminology for this disease is required. We recommend "cerebral age-related TDP-43 and sclerosis" (CARTS). A detailed case report is presented, which includes neuroimaging and longitudinal neurocognitive data. Finally, we suggest a neuropathology-based diagnostic rubric for CARTS.