Time course of brain volume changes in the preclinical phase of Alzheimer's disease

Revealing heterogeneity in mild cognitive impairment based on individualized structural covariance network

BACKGROUND

Mild cognitive impairment (MCI) is a heterogeneous disorder with significant individual variabilities in clinical and biological features. Abnormal inter-regional structural covariance suggests disruption of the brain structural network in MCI. Most studies have examined group-level structural covariance alterations while ignoring individual-level differences. Hence, we aimed to investigate the heterogeneity of MCI using individual differential structural covariance network (IDSCN) analysis.

METHODS

T1-weighted images of 596 MCI patients and 309 cognitively normal (CN) were collected from the ADNI database as discovery dataset, and 122 MCI and 117 CN from the OASIS-3 dataset as validation cohort. We constructed each patient's IDSCN using regional gray matter volume and applied K-means clustering analysis to identify MCI subtypes based on significantly altered covariance edges. Then, clinical features, brain structure, and gene expression profiles were evaluated for each subtype.

RESULTS

In the ADNI dataset, MCI patients exhibited significant alterations in structural covariance edges, mainly involving the hippocampus, parahippocampal gyrus, and amygdala. Two robust MCI subtypes were identified. Subtype 1 showed faster disease progression relative to subtype 2, which was validated in the independent OASIS-3 dataset. Significant differences between two subtypes were found in clinical cognition and biomarkers, cerebral atrophy patterns, and enriched genes for metal ion transport and neuron projection development. Finally, correlation analysis and functional annotation further revealed that the affected edges were related to cognitive performance and implicated in memory and emotion terms.

CONCLUSIONS

In summary, these findings offer new perspectives into understanding the heterogeneity of MCI and facilitate strategies for future precision medicine.

Age-related disturbances in rest-activity rhythms and integrity of the hippocampal network: An exploratory study

To better understand the relationship between the rest-activity rhythms and cognitive impairments during aging, we assessed the longitudinal changes in the rest-activity rhythms in an elderly population and their possible detrimental effect on the hippocampal network. This was done longitudinally in a rural cohort with two actigraphic assessments and brain imaging examinations, seven years apart. A segmentation of the hippocampus and its related structures was used to assess volumes and functional connectivity in this network based on anatomical and resting state functional data. Regression models were carried out to investigate the potential association of the evolution of sleep and rest-activity rhythms parameters with the structural and functional integrity of the hippocampal network. Our sample was composed of 33 subjects aged 75.2 ± 2.4 years old at the first time point with 40% of women. After seven years, the sleep of our participants did not change but their rest-activity rhythms did (p < 0.05), with a decrease in relative amplitude (∂RA = -0.021) and stability (∂IS = -0.044) as well as an increase in fragmentation (∂IV = +0.072). The deterioration of rest-activity rhythms was correlated with a lower anterior hippocampal volume (p corrected <0.05) while no correlation with functional connectivity was observed. These findings suggest that a degradation of rest-activity rhythms in people over 70 years old could constitute a factor of hippocampal vulnerability. Preventive interventions should consider rest-activity rhythms in the oldest-old population.

Neuroanatomical and clinical factors predicting future cognitive impairment

Identifying cognitively normal (CN) older adults who will convert to cognitive impairment (CI) due to Alzheimer's disease is crucial for early intervention. Clinical and neuroimaging measures were acquired from 301 CN adults who converted to CI within 15 years of baseline, and 294 who did not. Regional volumes and brain age measures were extracted from T1-weighted magnetic resonance images. Linear discriminant analysis compared non-converters' characteristics against those of short-, mid-, and long-term converters. Conversion was associated with clinical measures such as hearing impairment and self-reported memory decline. Converters' brain volumes were smaller than non-converters' across 48 frontal, temporal, and subcortical structures. Brain age measures of 12 structures were correlated with shorter times to conversion. Conversion prediction accuracy increased from 81.5% to 90.5% as time to conversion decreased. Proximity to CI conversion is foreshadowed by anatomic features of brain aging that enhance the accuracy of predicting conversion.

Non-Linear Association of Dietary Polyamines with the Risk of Incident Dementia: Results from Population-Based Cohort of the UK Biobank

Natural polyamines, including spermidine (SPD), spermine (SPM) and putrescine (PUT), are evolutionarily conserved endogenous molecules crucially involved in central cellular processes. Their physiological importance may extend to the maintenance of cognitive function during aging. However, limited population-based epidemiological studies have explored the link between dietary polyamines and dementia risk. This study was a prospective analysis of 77,092 UK Biobank participants aged ≥ 60 years without dementia at baseline. We used Cox proportional hazard regression models to explore the associations between dietary polyamines and the risk of dementia, and restricted cubic splines to test the non-linear relationships. During a median follow-up of 12 years, 1087 incidents of all-cause dementia cases occurred, including 450 Alzheimer's disease (AD) cases and 206 vascular dementia (VD) cases. The fully adjusted hazard ratios (HRs) for the upper fourth quintile of dietary SPD, in comparison with the lowest quintile of intake, were 0.68 (95% confidence interval [95% CI]: 0.66-0.83) for the risk of all-cause dementia, 0.62 (95% CI: 0.45-0.85) for AD and 0.56 (95% CI: 0.36-0.88) for VD, respectively. A 26% reduction in dementia risk [HR: 0.74, (95% CI: 0.61-0.89)] and a 47% reduction in AD [HR: 0.53, (95%CI: 0.39-0.72)] were observed comparing the third with the lowest quintiles of dietary SPM. Dietary PUT was only associated with a reduced risk of all-cause dementia in the fourth quintile [HR (95% CI): 0.82 (0.68-0.99)]. Reduced risk was not found to be significant across all quintiles. There were 'U'-shaped relationships found between dietary polyamines and all-cause dementia, AD and VD. Stratification by genetic predisposition showed no significant effect modification. Optimal intake of polyamines was linked to a decreased risk of dementia, with no modification by genetic risk. This potentially suggests cognitive benefits of dietary natural polyamines in humans.

Emergence of the brain-border immune niches and their contribution to the development of neurodegenerative diseases

Historically, the central nervous system (CNS) was regarded as 'immune-privileged', possessing its own distinct immune cell population. This immune privilege was thought to be established by a tight blood-brain barrier (BBB) and blood-cerebrospinal-fluid barrier (BCSFB), which prevented the crossing of peripheral immune cells and their secreted factors into the CNS parenchyma. However, recent studies have revealed the presence of peripheral immune cells in proximity to various brain-border niches such as the choroid plexus, cranial bone marrow (CBM), meninges, and perivascular spaces. Furthermore, emerging evidence suggests that peripheral immune cells may be able to infiltrate the brain through these sites and play significant roles in driving neuronal cell death and pathology progression in neurodegenerative disease. Thus, in this review, we explore how the brain-border immune niches may contribute to the pathogenesis of neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS). We then discuss several emerging options for harnessing the neuroimmune potential of these niches to improve the prognosis and treatment of these debilitative disorders using novel insights from recent studies.

The prevalence of mild cognitive impairment in Gulf War veterans: a follow-up study

Introduction

Gulf War Illness (GWI), also called Chronic Multisymptom Illness (CMI), is a multi-faceted condition that plagues an estimated 250,000 Gulf War (GW) veterans. Symptoms of GWI/CMI include fatigue, pain, and cognitive dysfunction. We previously reported that 12% of a convenience sample of middle aged (median age 52 years) GW veterans met criteria for mild cognitive impairment (MCI), a clinical syndrome most prevalent in older adults (e.g., ≥70 years). The current study sought to replicate and extend this finding.

Methods

We used the actuarial neuropsychological criteria and the Montreal Cognitive Assessment (MoCA) to assess the cognitive status of 952 GW veterans. We also examined regional brain volumes in a subset of GW veterans (n = 368) who had three Tesla magnetic resonance images (MRIs).

Results

We replicated our previous finding of a greater than 10% rate of MCI in four additional cohorts of GW veterans. In the combined sample of 952 GW veterans (median age 51 years at time of cognitive testing), 17% met criteria for MCI. Veterans classified as MCI were more likely to have CMI, history of depression, and prolonged (≥31 days) deployment-related exposures to smoke from oil well fires and chemical nerve agents compared to veterans with unimpaired and intermediate cognitive status. We also replicated our previous finding of hippocampal atrophy in veterans with MCI, and found significant group differences in lateral ventricle volumes.

Discussion

Because MCI increases the risk for late-life dementia and impacts quality of life, it may be prudent to counsel GW veterans with cognitive dysfunction, CMI, history of depression, and high levels of exposures to deployment-related toxicants to adopt lifestyle habits that have been associated with lowering dementia risk. With the Food and Drug Administration's recent approval of and the VA's decision to cover the cost for anti-amyloid β (Aβ) therapies, a logical next step for this research is to determine if GW veterans with MCI have elevated Aβ in their brains.

The Association of Retinal Microvasculature With Gray Matter Changes and Structural Covariance Network: A Voxel-Based Morphometry Study

Purpose

Increasing evidence suggests that retinal microvasculature may reflect global cerebral atrophy. However, little is known about the relation of retinal microvasculature with specific brain regions and brain networks. Therefore, we aimed to unravel the association of retinal microvasculature with gray matter changes and structural covariance network using a voxel-based morphometry (VBM) analysis.

Methods

One hundred and forty-four volunteers without previously known neurological diseases were recruited from West China Hospital, Sichuan University between April 1, 2021, and December 31, 2021. Retinal microvasculature of superficial vascular plexus (SVP), intermediate capillary plexus (ICP), and deep capillary plexus (DCP) were measured by optical coherence tomography angiography using an automatic segmentation. The VBM and structural covariance network analyses were applied to process brain magnetic resonance imaging (MRI) images. The associations of retinal microvasculature with voxel-wise gray matter volumes and structural covariance network were assessed by linear regression models.

Results

In the study, 137 participants (mean age = 59.72 years, 37.2% men) were included for the final analysis. Reduced perfusion in SVP was significantly associated with reduced voxel-wise gray matter volumes of the brain regions including the insula, putamen, occipital, frontal, and temporal lobes, all of which were located in the anterior part of the brain supplied by internal carotid artery, except the occipital lobe. In addition, these regions were also involved in visual processing and cognitive impairment (such as left inferior occipital gyrus, left lingual gyrus, and right parahippocampal gyrus). In regard to the structural covariance, the perfusions in SVP were positively related to the structural covariance of the left lingual gyrus seed with the left middle occipital gyrus, the right middle occipital gyrus, and the left middle frontal gyrus.

Conclusions

Poor perfusion in SVP was correlated with reduced voxel-wise gray matter volumes and structural covariance networks in regions related to visual processing and cognitive impairment. It suggests that retinal microvasculature may offer a window to identify aging related cerebral alterations.

Association of white matter lesions and brain atrophy with the development of dementia in a community: the Hisayama Study

AIM

To investigate the association of white matter lesions volume (WMLV) levels with dementia risk and the association between dementia risk and the combined measures of WMLV and either total brain atrophy or dementia-related gray matter atrophy in a general older population.

METHODS

One thousand one hundred fifty-eight Japanese dementia-free community-residents aged ≥65 years who underwent brain magnetic resonance imaging were followed for 5.0 years. WMLV were segmented using the Lesion Segmentation Toolbox. Total brain volume (TBV) and regional gray matter volume were estimated by voxel-based morphometry. The WMLV-to-intracranial brain volume ratio (WMLV/ICV) was calculated, and its association with dementia risk was estimated using Cox proportional hazard models. Total brain atrophy, defined as the TBV-to-ICV ratio (TBV/ICV), and dementia-related regional brain atrophy defined based on our previous report were calculated. The association between dementia risk and the combined measures of WMLV/ICV and either total brain atrophy or the number of atrophied regions was also tested.

RESULTS

During the follow-up, 113 participants developed dementia. The risks of dementia increased significantly with higher WMLV/ICV levels. In addition, dementia risk increased additively both in participants with higher WMLV/ICV levels and lower TBV/ICV levels and in those with higher WMLV/ICV levels and a higher number of dementia-related brain regional atrophy.

CONCLUSION

The risk of dementia increased significantly with higher WMLV/ICV levels. An additive increment in dementia risk was observed with higher WMLV/ICV levels and lower TBV/ICV levels or a higher number of dementia-related brain regional atrophy, suggesting the importance of prevention or control of cardiovascular risk factors.

Effects of risk factors on longitudinal changes in brain structure and function in the progression of AD

INTRODUCTION

Past research on Alzheimer's disease (AD) has focused on biomarkers, cognition, and neuroimaging as primary predictors of its progression, albeit additional ones have recently gained attention. When turning to the prediction of the progression from one stage to another, one could benefit from the joint assessment of imaging-based biomarkers and risk/protective factors.

METHODS

We included 86 studies that fulfilled our inclusion criteria.

RESULTS

Our review summarizes and discusses the results of 30 years of longitudinal research on brain changes assessed with neuroimaging and the risk/protective factors and their effect on AD progression. We group results into four sections: genetic, demographic, cognitive and cardiovascular, and lifestyle factors.

DISCUSSION

Given the complex nature of AD, including risk factors could prove invaluable for a better understanding of AD progression. Some of these risk factors are modifiable and could be targeted by potential future treatments.

Impact of age on the cerebrospinal fluid spaces: high-convexity and medial subarachnoid spaces decrease with age

Background

Impaired cerebrospinal fluid (CSF) dynamics may contribute to the pathophysiology of neurodegenerative diseases, and play a crucial role in brain health in older people; nonetheless, such age-related changes have not been well elucidated. Disproportionately enlarged subarachnoid-space hydrocephalus (DESH) is a neuroimaging phenotype of idiopathic normal-pressure hydrocephalus, originating from impaired CSF dynamics, and closely associated with aging. This study aimed to investigate the pathophysiology of DESH and determine age-related changes in CSF dynamics.

Methods

Using magnetic resonance imaging, we investigated the pathophysiology of DESH by quantitatively evaluating the volumes of DESH-related regions (ventricles [VS], Sylvian fissure [SF], and subarachnoid spaces at high convexity and midline [SHM]) and brain parenchyma in community-dwelling individuals aged  ≥ 65 years. DESH-related regions were assessed using a visual rating scale, and volumes measured using voxel-based morphometry. Brain parenchyma volumes were measured using FreeSurfer software.

Results

Data from 1,356 individuals were analyzed, and 25 (1.8%) individuals had DESH. Regarding the relationships between the volume of each CSF space and age, VS and SF volumes increased with age, whereas SHM volume did not increase. VS and SF volumes increased as the whole brain volume decreased, whereas SHM volume did not increase even if the whole brain volume decreased; that is, SHM did not expand even if brain atrophy progressed. Moreover, lower Mini-Mental State Examination scores were significantly associated with lower SHM volume and higher VS volume. These associations remained significant even when individuals with DESH were excluded.

Conclusions

This study showed that the volume of high-convexity and medial subarachnoid spaces did not expand and tended to decrease with age; the human brain continuously progresses toward a “DESH-like” morphology with aging in community-dwelling older persons (i.e., DESH might be an “accelerated aging stage” rather than an “age-related disorder”). Our results indicated that brain atrophy may be associated with the development of “DESH-like” morphology. In addition, this morphological change, as well as brain atrophy, is an important condition associated with cognitive decline in older adults. Our findings highlight the importance of investigating the aging process of CSF dynamics in the human brain to preserve brain health in older people.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12987-022-00381-5.

Evaluation of functional MRI-based human brain parcellation: a review

Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can significantly affect the outcome of the analysis. In recent years, several novel approaches for constructing MRI-based brain parcellations have been developed with promising results. In the absence of ground truth, several evaluation approaches have been used to evaluate currently available brain parcellations. In this article, we review and critique methods used for evaluating functional brain parcellations constructed using fMRI data sets. We also describe how some of these evaluation methods have been used to estimate the optimal parcellation granularity. We provide a critical discussion of the current approach to the problem of identifying the optimal brain parcellation that is suited for a given neuroimaging study. We argue that the criteria for an optimal brain parcellation must depend on the application the parcellation is intended for. We describe a teleological approach to the evaluation of brain parcellations, where brain parcellations are evaluated in different contexts and optimal brain parcellations for each context are identified separately. We conclude by discussing several directions for further research that would result in improved evaluation strategies.

Multiple-region grey matter atrophy as a predictor for the development of dementia in a community: the Hisayama Study

OBJECTIVE

To assess the association of regional grey matter atrophy with dementia risk in a general older Japanese population.

METHODS

We followed 1158 dementia-free Japanese residents aged ≥65 years for 5.0 years. Regional grey matter volume (GMV) at baseline was estimated by applying voxel-based morphometry methods. The GMV-to-total brain volume ratio (GMV/TBV) was calculated, and its association with dementia risk was estimated using Cox proportional hazard models. We assessed whether the predictive ability of a model based on known dementia risk factors could be improved by adding the total number of regions with grey matter atrophy among dementia-related brain regions, where the cut-off value for grey matter atrophy in each region was determined by receiver operating characteristic curves.

RESULTS

During the follow-up, 113 participants developed all-cause dementia, including 83 with Alzheimer's disease (AD). Lower GMV/TBV of the medial temporal lobe, insula, hippocampus and amygdala were significantly/marginally associated with higher risk of all-cause dementia and AD (all p for trend ≤0.08). The risks of all-cause dementia and AD increased significantly with increasing total number of brain regions exhibiting grey matter atrophy (both p for trend <0.01). Adding the total number of regions with grey matter atrophy into a model consisting of known risk factors significantly improved the predictive ability for AD (Harrell's c-statistics: 0.765-0.802; p=0.02).

CONCLUSIONS

Our findings suggest that the total number of regions with grey matter atrophy among the medial temporal lobe, insula, hippocampus and amygdala is a significant predictor for developing dementia, especially AD, in the general older population.

Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes

BACKGROUND

Hippocampal atrophy is a well-known biomarker of neurodegeneration, such as that observed in Alzheimer's disease (AD). Although distributions of hippocampal volume trajectories for asymptomatic individuals often reveal substantial heterogeneity, it is unclear whether interpretable trajectory classes can be objectively detected and used for prediction analyses.

OBJECTIVE

To detect and predict hippocampal trajectory classes in a computationally competitive context using established AD-related risk factors/biomarkers.

METHODS

We used biomarker/risk factor and longitudinal MRI data in asymptomatic adults from the AD Neuroimaging Initiative (n = 351; Mean = 75 years; 48.7% female). First, we applied latent class growth analyses to left (LHC) and right (RHC) hippocampal trajectory distributions to identify distinct classes. Second, using random forest analyses, we tested 38 multi-modal biomarkers/risk factors for their relative importance in discriminating the lower (potentially elevated atrophy risk) from the higher (potentially reduced risk) class.

RESULTS

For both LHC and RHC trajectory distribution analyses, we observed three distinct trajectory classes. Three biomarkers/risk factors predicted membership in LHC and RHC lower classes: male sex, higher education, and lower plasma Aβ1-42. Four additional factors selectively predicted membership in the lower LHC class: lower plasma tau and Aβ1-40, higher depressive symptomology, and lower body mass index.

CONCLUSION

Data-driven analyses of LHC and RHC trajectories detected three classes underlying the heterogeneous distributions. Machine learning analyses determined three common and four unique biomarkers/risk factors discriminating the higher and lower LHC/RHC classes. Our sequential analytic approach produced evidence that the dynamics of preclinical hippocampal trajectories can be predicted by AD-related biomarkers/risk factors from multiple modalities.

Biomarkers for Alzheimer's Disease Early Diagnosis

Alzheimer's disease (AD) is the most common cause of dementia, affecting the central nervous system (CNS) through the accumulation of intraneuronal neurofibrillary tau tangles (NFTs) and β-amyloid plaques. By the time AD is clinically diagnosed, neuronal loss has already occurred in many brain and retinal regions. Therefore, the availability of early and reliable diagnosis markers of the disease would allow its detection and taking preventive measures to avoid neuronal loss. Current diagnostic tools in the brain, such as magnetic resonance imaging (MRI), positron emission tomography (PET) imaging, and cerebrospinal fluid (CSF) biomarkers (Aβ and tau) detection are invasive and expensive. Brain-secreted extracellular vesicles (BEVs) isolated from peripheral blood have emerged as novel strategies in the study of AD, with enormous potential as a diagnostic evaluation of therapeutics and treatment tools. In addition; similar mechanisms of neurodegeneration have been demonstrated in the brain and the eyes of AD patients. Since the eyes are more accessible than the brain, several eye tests that detect cellular and vascular changes in the retina have also been proposed as potential screening biomarkers. The aim of this study is to summarize and discuss several potential markers in the brain, eye, blood, and other accessible biofluids like saliva and urine, and correlate them with earlier diagnosis and prognosis to identify individuals with mild symptoms prior to dementia.

Association of impaired fasting glucose and Type 2 Diabetes Mellitus with brain volume changes in Alzheimer's Disease patients analyzed by MRI: a retrospective study

Objectives

Alzheimer’s disease (AD), impaired fasting glucose (IFG), and Type 2 diabetes mellitus (T2DM) were reported associated with smaller brain volumes. Nevertheless, the association of hyperglycemia with brain volume changes in AD patients remains unclear. To investigate this issue, structural magnetic resonance imaging was used to compare brain volumes among AD patients with different fasting glucose levels.

Methods

Eighty-five AD patients were divided into three groups based on their fasting glucose level as suggested by the American Diabetes Association: normal fasting glucose group (AD_NFG, n = 45), AD_IFG group (n = 15), and AD_T2DM group (n = 25). Sagittal 3D T1-weighted images were obtained to calculate the brain volume. Brain parenchyma and 33 brain structures were automatically segmented. Each regional volume was analyzed among groups. For regions with statistical significance, partial correlation analysis was used to evaluate their relationships with fasting glucose level, corrected for Mini-Mental State Examination score, age, education level, cholesterol, triglyceride, and blood pressure.

Results

Compared with the AD_IFG and AD_NFG groups, the volume of pons in AD_T2DM group was significantly smaller. Fasting glucose was negatively correlated with pontine volume.

Conclusions

T2DM may exacerbate pontine atrophy in AD patients, and fasting glucose level is associated with pontine volume.

Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

BACKGROUND

Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year.

OBJECTIVES

To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI.

SEARCH METHODS

On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches.

SELECTION CRITERIA

We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter.

DATA COLLECTION AND ANALYSIS

Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available.

MAIN RESULTS

We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate.

AUTHORS' CONCLUSIONS

The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.

Spatial navigation ability predicts progression of dementia symptomatology

INTRODUCTION

Spatial navigation deficits are observed in Alzheimer's disease cross-sectionally, but prediction of longitudinal clinical decline has been less examined.

METHODS

Cognitive mapping (CM) was assessed in 95 participants and route learning (RL) was assessed in 65 participants at baseline. Clinical progression over an average of 4 to 5 years was assessed using the clinical dementia rating (CDR) scale. Relative predictive ability was compared to episodic memory, hippocampus, and cerebrospinal fluid biomarkers (phosphorylated tau/amyloid β 42 (ptau₁₈₁ /Aβ₄₂ ) ratio).

RESULTS

CM and RL were predictors of clinical progression (P's < 0.032). All measures, except RL-Learning remained predictors with episodic memory in models (P's < 0.048). Only RL-Retrieval remained a predictor when ptau₁₈₁ /Aβ₄₂ was included (P < 0.001). CM interacted with hippocampus and ptau₁₈₁ /Aβ₄₂ in prediction (P's < 0.013). CM, RL, and episodic memory evidenced strong diagnostic accuracy (area under the curve (AUC) = 0.894, 0.794, and 0.735, respectively); CM tended to perform better than episodic memory (P = 0.056).

DISCUSSION

Baseline spatial navigation performance may be appropriate for assessing risk of clinical progression.

Determinants of mesial temporal lobe volume loss in older individuals with preserved cognition: a longitudinal PET amyloid study

Mesial temporal lobe (MTL) is prominently affected in normal aging and associated with neurodegeneration in AD. Whether or not MTL atrophy is dependent on increasing amyloid load before the emergence of cognitive deficits is still disputed. We performed a 4.5-year longitudinal study in 75 older community dwellers (48 women, mean age: 79.3 years) including magnetic resonance imaging at baseline and follow-up, positron emission tomography amyloid during follow-up, neuropsychological assessment at 18 and 55 months, and APOE genotyping. Linear regression models were used to identify predictors of the MTL volume loss. Amyloid load was negatively associated with bilateral MTL volume at baseline explaining almost 10.5% of its variability. In multivariate models including time of follow-up and demographic variables (older age, male gender), this percentage exceeded 35%. The APOE4 allele independently contributed another 6%. Cognitive changes had a modest but still significant negative association with MTL volume loss. Our data support a multifactorial model including amyloid deposition, older age, male gender, APOE4 allele, and slight decline of cognitive abilities as independent predictors of MTL volume loss in brain aging.

Plasmalogen deficiency and neuropathology in Alzheimer's disease: Causation or coincidence?

Causation of Alzheimer's disease (AD) is not well understood. It is necessary to look beyond neuropathology to identify the underlying causes of AD and many other common neurological diseases. Lipid abnormalities are well documented in the preclinical phases of many neurological diseases including AD. Here, we use AD as an example to examine the role of lipid abnormalities as an underlying cause of neurodegeneration. Role of lipids, particularly phospholipids, in the optimal function of the nervous system, impact of the aberrations of phospholipid metabolism on β-amyloid deposition and cholinergic neuronal function, epidemiological evidence on the association of phospholipids with AD, and preliminary data on the possible modulation of risk factors of AD by phospholipids are examined. Implications of these findings on diagnosis and prevention are also discussed.

Lifespan Changes of the Human Brain In Alzheimer's Disease

Brain imaging studies have shown that slow and progressive cerebral atrophy characterized the development of Alzheimer's Disease (AD). Despite a large number of studies dedicated to AD, key questions about the lifespan evolution of AD biomarkers remain open. When does the AD model diverge from the normal aging model? What is the lifespan trajectory of imaging biomarkers for AD? How do the trajectories of biomarkers in AD differ from normal aging? To answer these questions, we proposed an innovative way by inferring brain structure model across the entire lifespan using a massive number of MRI (N = 4329). We compared the normal model based on 2944 control subjects with the pathological model based on 3262 patients (AD + Mild cognitive Impaired subjects) older than 55 years and controls younger than 55 years. Our study provides evidences of early divergence of the AD models from the normal aging trajectory before 40 years for the hippocampus, followed by the lateral ventricles and the amygdala around 40 years. Moreover, our lifespan model reveals the evolution of these biomarkers and suggests close abnormality evolution for the hippocampus and the amygdala, whereas trajectory of ventricular enlargement appears to follow an inverted U-shape. Finally, our models indicate that medial temporal lobe atrophy and ventricular enlargement are two mid-life physiopathological events characterizing AD brain.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Relationship Between DTI Metrics and Cognitive Function in Alzheimer's Disease

Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder with a clinical presentation characterized by memory impairment and executive dysfunction. Our group previously demonstrated significant alterations in white matter microstructural metrics in AD compared to healthy older adults. We aimed to further investigate the relationship between white matter microstructure in AD and cognitive function, including memory and executive function. Methods: Diffusion tensor imaging (DTI) and neuropsychological data were downloaded from the AD Neuroimaging Initiative database for 49 individuals with AD and 48 matched healthy older adults. The relationship between whole-brain fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AxD), radial diffusivity (RD), and composite scores of memory and executive function was examined. We also considered voxel-wise relationships using Tract-Based Spatial Statistics. Results: As expected, individuals with AD had lower composite scores on tests of memory and executive function, as well as disrupted white matter integrity (low FA, high MD, AxD, and RD) relative to healthy older adults in widespread regions, including the hippocampus. When the AD and healthy older adult groups were combined, we found significant relationships between DTI metrics (FA/MD/AxD/RD) and memory scores across widespread regions of the brain, including the medial temporal regions. We also found significant relationships between DTI metrics (FA/MD/AxD/RD) and executive function in widespread regions, including the frontal areas in the combined group. However, when the groups were examined separately, no significant relationships were found between DTI metrics (FA/MD/AxD/RD) and memory performance for either group. Further, we did not find any significant relationships between DTI metrics (FA/MD/AxD/RD) and executive function in the AD group, but we did observe significant relationships between FA/RD, and executive function in healthy older adults. Conclusion: White matter integrity is disrupted in AD. In a mixed sample of AD and healthy elderly persons, associations between measures of white matter microstructure and memory and executive cognitive test performance were evident. However, no significant linear relationship between the degree of white matter disruption and level of cognitive functioning (memory and executive abilities) was found in those with AD. Future longitudinal studies of the relations between DTI metrics and cognitive function in AD are required to determine whether DTI has potential to measure progression of AD and/or treatment efficacy.

Association of Retinal Nerve Fiber Layer Thickness With Brain Alterations in the Visual and Limbic Networks in Elderly Adults Without Dementia

IMPORTANCE

The eye is a sensory organ that is easily accessible for imaging techniques, allowing the measurement of the retinal nerve fiber layer (RNFL) thickness. The eye is part of the central nervous system, and its neurons may be susceptible to degeneration; therefore, changes in the RNFL thickness may reflect microstructural and volume alterations in the brain.

OBJECTIVE

To explore the association between the peripapillary RNFL thickness and brain alterations in the visual and limbic networks in elderly people without dementia.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional analysis of the Three-City/Antioxydants, Lipides Essentiels, Nutrition et Maladies Oculaires (Alienor) Study cohort (April 2009 to December 2010). The dates of analysis were July 2017 to August 2018. The setting was a population-based study in France. The brain volume analysis included 104 participants, and the diffusion tensor imaging analysis included 79 participants.

MAIN OUTCOMES AND MEASURES

Global RNFL was assessed by spectral-domain optical coherence tomography. Brain volumes were assessed via T1-weighted magnetic resonance imaging by measurement of the global white and gray matter fractions and the hippocampal fraction. Brain microstructural alterations were assessed with diffusion tensor imaging at the level of the posterior thalamic radiations, the limbic system tracts (the fornix and cingulum bundles), and the posterior limb of the internal capsule (control region). Linear regression models adjusted for several confounders were performed.

RESULTS

Among a total of 104 participants, the mean (SD) age was 80.8 (3.9) years, and the cohort was 56.7% women (n = 59). The mean (SD) global RNFL thickness was 89.3 (12.9) µm. A thicker RNFL was associated with a greater hippocampal fraction (quantity of increase β = 0.013; 95% CI, 0.001-0.025 per 10-μm increase in the RNFL thickness) and better diffusion tensor imaging variables in the global cingulum (mean diffusivity β = -0.007; 95% CI, -0.015 to -0.000) and the hippocampal part of the cingulum (mean diffusivity β = -0.009; 95% CI, -0.016 to -0.002 and radial diffusivity β = -0.010; 95% CI, -0.018 to -0.002) and the posterior thalamic radiations (fractional anisotropy β = 0.008; 95% CI, 0.000-0.017). No significant associations were found with other magnetic resonance imaging volumes or with other diffusion tensor imaging variables. In particular, there was no significant association with the control region of interest.

CONCLUSIONS AND RELEVANCE

Results of this study suggest that in elderly individuals without dementia, a thicker RNFL was associated with better magnetic resonance imaging variables both in a region that included the visual pathways and in regions particularly involved in the neurodegenerative processes of Alzheimer disease.

Near-Term Decrease in Brain Volume following Mild Traumatic Injury Is Detectible in the Context of Preinjury Volumetric Stability: Neurobiologic Insights from Analysis of Historical Imaging Examinations

BACKGROUND AND PURPOSE

Neurodegeneration after mild traumatic brain injury may manifest as decreasing regional brain volume that evolves from months to years following mild traumatic brain injury and is associated with worse clinical outcomes. We hypothesized that quantitative brain volume derived from CT of the head, performed for clinical indications during routine care, would change with time and provide insights into the putative neuroinflammatory response to mild traumatic brain injury.

MATERIALS AND METHODS

We searched the electronic medical record of our institution for NCCTs of the head performed in patients with mild traumatic brain injury and included those who also underwent NCCTs of the head 1 month to 1 year before and after mild traumatic brain injury for an indication unrelated to trauma. Controls underwent 3 sequential NCCTs of the head with indications unrelated to trauma. The whole-brain and intracranial volume groups were computed using ITK-SNAP. Brain volumes normalized to intracranial volumes were compared across time points using the Wilcoxon signed-rank test.

RESULTS

We identified 48 patients from 2005 to 2015 who underwent NCCTs of the head in the emergency department for mild traumatic brain injury and had NCCTs of the head performed both before and after mild traumatic brain injury. Median normalized brain volumes significantly decreased on the follow-up study post-mild traumatic brain injury (0.86 versus 0.84, P < .001) and were similar compared with pre-mild traumatic brain injury studies (0.87 versus 0.86, P = .927). There was no significant difference between normalized brain volumes in the 48 controls.

CONCLUSIONS

A decrease in brain volume following mild traumatic brain injury is detectable on CT and is not seen in similar patients with non-mild traumatic brain injury during a similar timeframe. Given the stability of brain volume before mild traumatic brain injury, CT volume loss may represent the subtle effects of neurodegeneration.

A Systematic Review of Longitudinal Studies Which Measure Alzheimer's Disease Biomarkers

Alzheimer’s disease (AD) is a progressive and fatal neurodegenerative disease, with no effective treatment or cure. A gold standard therapy would be treatment to slow or halt disease progression; however, knowledge of causation in the early stages of AD is very limited. In order to determine effective endpoints for possible therapies, a number of quantitative surrogate markers of disease progression have been suggested, including biochemical and imaging biomarkers. The dynamics of these various surrogate markers over time, particularly in relation to disease development, are, however, not well characterized. We reviewed the literature for studies that measured cerebrospinal fluid or plasma amyloid-β and tau, or took magnetic resonance image or fluorodeoxyglucose/Pittsburgh compound B-positron electron tomography scans, in longitudinal cohort studies. We summarized the properties of the major cohort studies in various countries, commonly used diagnosis methods and study designs. We have concluded that additional studies with repeat measures over time in a representative population cohort are needed to address the gap in knowledge of AD progression. Based on our analysis, we suggest directions in which research could move in order to advance our understanding of this complex disease, including repeat biomarker measurements, standardization and increased sample sizes.

In Vivo Detection of Gray Matter Neuropathology in the 3xTg Mouse Model of Alzheimer's Disease with Diffusion Tensor Imaging

A diagnosis of Alzheimer's disease (AD), a neurodegenerative disorder accompanied by severe functional and cognitive decline, is based on clinical findings, with final confirmation of the disease at autopsy by the presence of amyloid-β (Aβ) plaques and neurofibrillary tangles. Given that microstructural brain alterations occur years prior to clinical symptoms, efforts to detect brain changes early could significantly enhance our ability to diagnose AD sooner. Diffusion tensor imaging (DTI), a type of MRI that characterizes the magnitude, orientation, and anisotropy of the diffusion of water in tissues, has been used to infer neuropathological changes in vivo. Its utility in AD, however, is still under investigation. The current study used DTI to examine brain regions susceptible to AD-related pathology; the cerebral cortex, entorhinal cortex, and hippocampus, in 12-14-month-old 3xTg AD mice that possess both Aβ plaques and neurofibrillary tangles. Mean diffusivity did not differ between 3xTg and control mice in any region. Decreased fractional anisotropy (p < 0.01) and axial diffusivity (p < 0.05) were detected only in the hippocampus, in which both congophilic Aβ plaques and hyperphosphorylated tau accumulation, consistent with neurofibrillary tangle formation, were detected. Pathological tau accumulation was seen in the cortex. The entorhinal cortex was largely spared from AD-related neuropathology. This is the first study to demonstrate DTI abnormalities in gray matter in a mouse model of AD in which both pathological hallmarks are present, suggesting the feasibility of DTI as a non-invasive means of detecting brain pathology in vivo in early-stage AD.

The Rationale Behind the New Alzheimer's Disease Conceptualization: Lessons Learned During the Last Decades

In the last decades, progress in neuroimaging techniques and cerebrospinal fluid assays has enabled the characterization of several Alzheimer's disease (AD) biomarkers. This knowledge has shifted the conceptualization of AD from a clinical-pathological construct, where its diagnosis required the presence of dementia with distinct pathologic features, toward a clinical-biological one that recognizes AD as a pathological continuum with a clinical picture that ranges from normal cognition to a dementia stage. Specifically, AD is now divided into three stages: preclinical (abnormal biomarkers and no or only subtle cognitive impairment), mild cognitive impairment or prodromal AD (abnormal pathophysiological biomarkers and episodic memory impairment), and dementia (abnormal biomarkers and clear cognitive and functional impairment). The possibility of assessing AD pathophysiology in vivo before the onset of clinical symptoms in the preclinical stage provides the unprecedented opportunity to intervene at earlier stages of the continuum in secondary prevention trials. Currently, large cohort studies of cognitively healthy participants are undergoing with the main aim of disentangling the natural history of AD to identify individuals with an increased risk of developing AD in the near future to be recruited in these clinical trials. In this paper, we review how the concept of AD has changed over the years as well as discuss the implications of this conceptual change.

Total Brain and Hippocampal Volumes and Cognition in Older American Indians: The Strong Heart Study

BACKGROUND

Estimates of hippocampal volume by magnetic resonance imaging have clinical and cognitive correlations and can assist in early Alzheimer disease diagnosis. However, little is known about the relationship between global or regional brain volumes and cognitive test performance in American Indians.

MATERIALS AND METHODS

American Indian participants (N=698; median age, 72 y) recruited for the Cerebrovascular Disease and its Consequences in American Indians study, an ancillary study of the Strong Heart Study cohort, were enrolled. Linear regression models assessed the relationship between magnetic resonance imaging brain volumes (total brain and hippocampi) and cognitive measures of verbal learning and recall, processing speed, verbal fluency, and global cognition.

RESULTS

After controlling for demographic and clinical factors, all volumetric measurements were positively associated with processing speed. Total brain volume was also positively associated with verbal learning, but not with verbal recall. Conversely, left hippocampal volume was associated with both verbal learning and recall. The relationship between hippocampal volume and recall performance was more pronounced among those with lower scores on a global cognitive measure. Controlling for APOE ε4 did not substantively affect the associations.

CONCLUSIONS

These results support further investigation into the relationship between structural Alzheimer disease biomarkers, cognition, genetics, and vascular risk factors in aging American Indians.

Peripapillary Retinal Nerve Fiber Layer Thickness and the Evolution of Cognitive Performance in an Elderly Population

Retinal nerve fiber layer (RNFL) thickness is reduced in Alzheimer’s patients. However, whether it is associated with early evolution of cognitive function is unknown. Within 427 participants from the Three-City-Alienor longitudinal population-based cohort, we explored the relationship between peripapillary RNFL thicknesses and the evolution of cognitive performance. RNFL was assessed at baseline by spectral domain optical coherence tomography; cognitive performances were assessed at baseline and at 2 years, with the Mini–Mental State Examination, the Isaacs’ set test, and the Free and Cued Selective Reminding Test (FCSRT). Multivariate linear mixed models were performed. The RNFL was not associated with initial cognitive performance. Nevertheless, a thicker RNFL was significantly associated with a better cognitive evolution over time in the free delayed recall (p = 0.0037) and free + cued delayed recall (p = 0.0043) scores of the FCSRT, particularly in the temporal, superotemporal, and inferotemporal segments. No associations were found with other cognitive tests. The RNFL was associated with changes in scores that assess episodic memory. RNFL thickness could reflect a higher risk of developing cognitive impairment over time.

The Biological Function of the Prion Protein: A Cell Surface Scaffold of Signaling Modules

The prion glycoprotein (PrP^C) is mostly located at the cell surface, tethered to the plasma membrane through a glycosyl-phosphatydil inositol (GPI) anchor. Misfolding of PrP^C is associated with the transmissible spongiform encephalopathies (TSEs), whereas its normal conformer serves as a receptor for oligomers of the β-amyloid peptide, which play a major role in the pathogenesis of Alzheimer’s Disease (AD). PrP^C is highly expressed in both the nervous and immune systems, as well as in other organs, but its functions are controversial. Extensive experimental work disclosed multiple physiological roles of PrP^C at the molecular, cellular and systemic levels, affecting the homeostasis of copper, neuroprotection, stem cell renewal and memory mechanisms, among others. Often each such process has been heralded as the bona fide function of PrP^C, despite restricted attention paid to a selected phenotypic trait, associated with either modulation of gene expression or to the engagement of PrP^C with a single ligand. In contrast, the GPI-anchored prion protein was shown to bind several extracellular and transmembrane ligands, which are required to endow that protein with the ability to play various roles in transmembrane signal transduction. In addition, differing sets of those ligands are available in cell type- and context-dependent scenarios. To account for such properties, we proposed that PrP^C serves as a dynamic platform for the assembly of signaling modules at the cell surface, with widespread consequences for both physiology and behavior. The current review advances the hypothesis that the biological function of the prion protein is that of a cell surface scaffold protein, based on the striking similarities of its functional properties with those of scaffold proteins involved in the organization of intracellular signal transduction pathways. Those properties are: the ability to recruit spatially restricted sets of binding molecules involved in specific signaling; mediation of the crosstalk of signaling pathways; reciprocal allosteric regulation with binding partners; compartmentalized responses; dependence of signaling properties upon posttranslational modification; and stoichiometric requirements and/or oligomerization-dependent impact on signaling. The scaffold concept may contribute to novel approaches to the development of effective treatments to hitherto incurable neurodegenerative diseases, through informed modulation of prion protein-ligand interactions.

Neuropsychological Markers of Medial Perirhinal and Entorhinal Cortex Functioning are Impaired Twelve Years Preceding Diagnosis of Alzheimer's Dementia

Neurofibrillary pathology in Alzheimer's dementia (AD) is associated with cognitive impairments and cortical thinning, and begins in medial perirhinal cortex (mPRC) before entering entorhinal cortex (ERC). Thus, mPRC dysfunction (e.g., semantic object memory impairments) may predate or accompany ERC (i.e., episodic memory) dysfunction in the preclinical course of typical AD. We developed formulae estimating mPRC and ERC integrity (i.e., cortical thickness) using common neuropsychological tests in 31 healthy individuals and 58 early AD patients. These formulae estimated the longitudinal courses of mPRC and ERC functioning in independent groups of 28 optimally healthy individuals who developed AD (NC-AD) over 2.8-13.4 years and 28 pairwise-matched, stable, healthy individuals (NC-NC). Mixed models demonstrated significantly worse NC-AD than NC-NC estimated mPRC and ERC functioning at the earliest observation, 12 years preceding diagnosis, and a significant decline 4 years preceding the AD diagnosis. These findings demonstrate that specific neuropsychological impairments occur early in the course of preclinical AD and that tasks measuring mPRC functioning may serve as additional, powerful markers of preclinical AD.

Cognitive dysfunction in major depression and Alzheimer's disease is associated with hippocampal-prefrontal cortex dysconnectivity

Cognitive dysfunction is prevalent in psychiatric disorders. Deficits are observed in multiple domains, including working memory, executive function, attention, and information processing. Disability caused by cognitive dysfunction is frequently as debilitating as the prominent emotional disturbances. Interactions between the hippocampus and the prefrontal cortex are increasingly appreciated as an important link between cognition and emotion. Recent developments in optogenetics, imaging, and connectomics can enable the investigation of this circuit in a manner that is relevant to disease pathophysiology. The goal of this review is to shed light on the contributions of this circuit to cognitive dysfunction in neuropsychiatric disorders, focusing on Alzheimer's disease and depression.

Homotaurine Effects on Hippocampal Volume Loss and Episodic Memory in Amnestic Mild Cognitive Impairment

Homotaurine supplementation may have a positive effect on early Alzheimer's disease. Here, we investigated its potential neuroprotective effect on the hippocampus structure and episodic memory performances in amnestic mild cognitive impairment (aMCI). Neuropsychological, clinical, and neuroimaging assessment in 11 treated and 22 untreated patients were performed at baseline and after 1 year. Magnetic resonance data were analyzed using voxel-based morphometry to explore significant differences (Family Wise Error corrected) between the two groups over time. Patients treated with homotaurine showed decreased volume loss in the left and right hippocampal tail, left and right fusiform gyrus, and right inferior temporal cortex which was associated with improved short-term episodic memory performance as measured by the recency effect of the Rey 15-word list learning test immediate recall. Thus, homotaurine supplementation in individuals with aMCI has a positive effect on hippocampus atrophy and episodic memory loss. Future studies should further clarify the mechanisms of its effects on brain morphometry.

Neuroimaging in Alzheimer's disease: preclinical challenges toward clinical efficacy

The scope of this review focuses on recent applications in preclinical and clinical magnetic resonance imaging (MRI) toward accomplishing the goals of early detection and responses to therapy in animal models of Alzheimer's disease (AD). Driven by the outstanding efforts of the Alzheimer's Disease Neuroimaging Initiative (ADNI), a truly invaluable resource, the initial use of MRI in AD imaging has been to assess changes in brain anatomy, specifically assessing brain shrinkage and regional changes in white matter tractography using diffusion tensor imaging. However, advances in MRI have led to multiple efforts toward imaging amyloid beta plaques first without and then with the use of MRI contrast agents. These technological advancements have met with limited success and are not yet appropriate for the clinic. Recent developments in molecular imaging inclusive of high-power liposomal-based MRI contrast agents as well as fluorine 19 ((19)F) MRI and manganese enhanced MRI have begun to propel promising advances toward not only plaque imaging but also using MRI to detect perturbations in subcellular processes occurring within the neuron. This review concludes with a discussion about the necessity for the development of novel preclinical models of AD that better recapitulate human AD for the imaging to truly be meaningful and for substantive progress to be made toward understanding and effectively treating AD. Furthermore, the continued support of outstanding programs such as ADNI as well as the development of novel molecular imaging agents and MRI fast scanning sequences will also be requisite to effectively translate preclinical findings to the clinic.

Structural Magnetic Resonance Imaging Markers of Alzheimer's Disease and Its Retranslation to Rodent Models

The importance of imaging biomarkers has been acknowledged in the diagnosis and in the follow-up of Alzheimer's disease (AD), one of the major causes of dementia. Next to the molecular biomarkers and PET imaging investigations, structural MRI approaches provide important information about the disease progression and about the pathomechanism. Furthermore,a growing body of literature retranslates these imaging biomarkers to various rodent models of the disease. The goal of this review is to provide an overview of the macro- and microstructural imaging biomarkers of AD, concentrating on atrophy measures and diffusion MRI alterations. A survey is also given of the imaging approaches used in rodent models of dementias that can promote drug development.

Brain imaging of neurovascular dysfunction in Alzheimer's disease

Neurovascular dysfunction, including blood-brain barrier (BBB) breakdown and cerebral blood flow (CBF) dysregulation and reduction, are increasingly recognized to contribute to Alzheimer's disease (AD). The spatial and temporal relationships between different pathophysiological events during preclinical stages of AD, including cerebrovascular dysfunction and pathology, amyloid and tau pathology, and brain structural and functional changes remain, however, still unclear. Recent advances in neuroimaging techniques, i.e., magnetic resonance imaging (MRI) and positron emission tomography (PET), offer new possibilities to understand how the human brain works in health and disease. This includes methods to detect subtle regional changes in the cerebrovascular system integrity. Here, we focus on the neurovascular imaging techniques to evaluate regional BBB permeability (dynamic contrast-enhanced MRI), regional CBF changes (arterial spin labeling- and functional-MRI), vascular pathology (structural MRI), and cerebral metabolism (PET) in the living human brain, and examine how they can inform about neurovascular dysfunction and vascular pathophysiology in dementia and AD. Altogether, these neuroimaging approaches will continue to elucidate the spatio-temporal progression of vascular and neurodegenerative processes in dementia and AD and how they relate to each other.

Role of β-Amyloidosis and Neurodegeneration in Subsequent Imaging Changes in Mild Cognitive Impairment

IMPORTANCE

To understand how a model of Alzheimer disease pathophysiology based on β-amyloidosis and neurodegeneration predicts the regional anatomic expansion of hypometabolism and atrophy in persons with mild cognitive impairment (MCI).

OBJECTIVE

To define the role of β-amyloidosis and neurodegeneration in the subsequent progression of topographic cortical structural and metabolic changes in MCI.

DESIGN, SETTING, AND PARTICIPANTS

Longitudinal, observational study with serial brain imaging conducted from March 28, 2006, to January 6, 2015, using a population-based cohort. A total of 96 participants with MCI (all aged >70 years) with serial imaging biomarkers from the Mayo Clinic Study of Aging or Mayo Alzheimer's Disease Research Center were included. Participants were characterized initially as having elevated or not elevated brain β-amyloidosis (A+ or A-) based on 11C-Pittsburgh compound B positron emission tomography. They were further characterized initially by the presence or absence of neurodegeneration (N+ or N-), where the presence of neurodegeneration was defined by abnormally low hippocampal volume or hypometabolism in an Alzheimer disease-like pattern on 18fluorodeoxyglucose (FDG)-positron emission tomography.

MAIN OUTCOMES AND MEASURES

Regional FDG standardized uptake value ratio (SUVR) and gray matter volumes in medial temporal, lateral temporal, lateral parietal, and medial parietal regions.

RESULTS

In the primary regions of interest (ROI), the A+N+ group (n = 45) had lower FDG SUVR at baseline compared with the A+N- group (n = 17) (all 4 ROIs; P < .001). The A+N+ group also had lower FDG SUVR at baseline (all 4 ROIs; P < .01) compared with the A-N- group (n = 12). The A+N+ group had lower medial temporal gray matter volume at baseline (P < .001) compared with either the A+N- group or A-N- group. The A+N+ group showed large longitudinal declines in FDG SUVR (P < .05 for medial temporal, lateral temporal, and medial parietal regions) and gray matter volumes (P < .05 for medial temporal and lateral temporal regions) compared with the A-N+ group (n = 22). The A+N+ group also showed large longitudinal declines compared with the A-N- group on FDG SUVR (P < .05 for medial temporal and lateral parietal regions) and gray matter volumes (all 4 ROIs; P < .05) compared with the A+N- group. The A-N+ group did not show declines in FDG SUVR or gray matter volume compared with the A+N- or A-N- groups.

CONCLUSIONS AND RELEVANCE

Persons with MCI who were A+N+ demonstrated volumetric and metabolic worsening in temporal and parietal association areas, consistent with the expectation that the MCI stage in the Alzheimer pathway heralds incipient isocortical involvement. The A-N+ group, those with suspected non-Alzheimer pathophysiology, lacked a distinctive longitudinal volumetric or metabolic profile.

The ALFA project: A research platform to identify early pathophysiological features of Alzheimer's disease

Introduction

The preclinical phase of Alzheimer's disease (AD) is optimal for identifying early pathophysiological events and developing prevention programs, which are shared aims of the ALFA project, including the ALFA registry and parent cohort and the nested ALFA+ cohort study.

Methods

The ALFA parent cohort baseline visit included full cognitive evaluation, lifestyle habits questionnaires, DNA extraction, and MRI. The nested ALFA+ study adds wet and imaging biomarkers for deeper phenotyping.

Results

A total of 2743 participants aged 45 to 74 years were included in the ALFA parent cohort. We show that this cohort, mostly composed of cognitively normal offspring of AD patients, is enriched for AD genetic risk factors.

Discussion

The ALFA project represents a valuable infrastructure that will leverage with different studies and trials to prevent AD. The longitudinal ALFA+ cohort will serve to untangle the natural history of the disease and to model the preclinical stages to develop successful trials.

Risk of dementia and death in the long-term follow-up of the Pittsburgh Cardiovascular Health Study-Cognition Study

INTRODUCTION

Increasing life expectancy has resulted in a larger population of older individuals at risk of dementia.

METHODS

The Cardiovascular Health Study-Cognition Study followed 532 participants from 1998-99 (mean age 79) to 2013 (mean age 93) for death and dementia.

RESULTS

Risk of death was determined by extent of coronary artery calcium, high-sensitivity cardiac troponin, brain natriuretic peptide, and white matter grade. Significant predictors of dementia were age, apolipoprotein-E4, vocabulary raw score, hippocampal volume, ventricular size, cognitive performance, and number of blocks walked. By 2013, 160 of 532 were alive, including 19 cognitively normal. Those with normal cognition had higher grade education, better cognition test scores, greater hippocampal volume, faster gait speed, and number of blocks walked as compared with survivors who were demented.

DISCUSSION

Few survived free of dementia and disability. Prevention and delay of cognitive decline for this older population is an imperative.

Neuroimaging of hippocampal atrophy in early recognition of Alzheimer's disease--a critical appraisal after two decades of research

As a characteristic feature of Alzheimer's disease (AD) hippocampal atrophy (HA) can be demonstrated in the majority of patients by using neuroimaging techniques in particular magnetic resonance imaging (MRI). Hippocampal atrophy is associated with declarative memory deficits and can also be associated with changes of adjacent medial temporal substructures such as the parahippocampal gyrus or the the entorhinal cortex. Similar findings are present in patients with mild cognitive impairment (MCI) albeit to a lesser extent. While these finding facilitate the diagnostic process in patients with clinical suspicious AD, the metric properties of hippocampal atrophy for delineating healthy aging from MCI and mild AD still appear to be rather limited; as such it is not sufficient to establish the diagnosis of AD (and even more so of MCI). This limitation partly refers to methodological issues and partly to the fact that hippocampal tissue integrity is subject to various pathogenetic influences other than AD. Moreover,the effects of hippocampal atrophy on the behavioral level (e.g. cognitive deficits) are modulated by the individual's cognitive reserve. From a clinical standpoint these observations are in line with the hypothesis that the onset and course of AD is influenced by a number of peristatic factors which are partly conceptualized in the concepts of brain and/or cognitive reserve. These complex interactions have to be considered when using the presence of hippocampal atrophy in the routine diagnostic procedure of AD.

[Successful aging: what can neurology and geriatrics contribute?]

The relative proportion of elderly persons in Western societies is rapidly growing, leading to an increasing frequency of age-related neurological diseases (e.g. dementia) and functional impairments (e.g. immobility). This article argues that this development should prompt a new focus in medical care. The key questions should not only be how can we improve treatment of age-related disorders but also how can we prevent age-related disorders in the first place or at least substantially delay their onset? These questions touch on an even more profound question: how can successful aging be accomplished? That is, which factors and processes characterize successful aging both on a system and on a molecular level? Thus, the crucial societal, scientific and medical challenges for Western societies are to develop and implement measures of primary prevention of dysfunctional aging. The disease-centered framework which currently determines most clinical thinking, scientific research and third party funding has to be supplemented by a novel framework of successful aging. This article defines dysfunctional aging as a convergent downstream result of multiple interacting system processes. Each of these detrimental system processes must be targeted by specific measures of geriatric primary prevention. This, in turn, implies that geriatrics does not start in the elderly or with the onset of particular geriatric disorders. Instead, it starts in the daily practice of neurology and other medical disciplines taking care of persons aged 20-40 years who are largely healthy and in the middle of their professional and personal career. Or, in a nutshell, geriatrics starts right in the middle of medical care.

Detection of Alzheimer's disease signature in MR images seven years before conversion to dementia: Toward an early individual prognosis

Finding very early biomarkers of Alzheimer's Disease (AD) to aid in individual prognosis is of major interest to accelerate the development of new therapies. Among the potential biomarkers, neurodegeneration measurements from MRI are considered as good candidates but have so far not been effective at the early stages of the pathology. Our objective is to investigate the efficiency of a new MR-based hippocampal grading score to detect incident dementia in cognitively intact patients. This new score is based on a pattern recognition strategy, providing a grading measure that reflects the similarity of the anatomical patterns of the subject under study with dataset composed of healthy subjects and patients with AD. Hippocampal grading was evaluated on subjects from the Three-City cohort, with a followup period of 12 years. Experiments demonstrate that hippocampal grading yields prediction accuracy up to 72.5% (P < 0.0001) 7 years before conversion to AD, better than both hippocampal volume (58.1%, P = 0.04) and MMSE score (56.9%, P = 0.08). The area under the ROC curve (AUC) supports the efficiency of imaging biomarkers with a gain of 8.4 percentage points for hippocampal grade (73.0%) over hippocampal volume (64.6%). Adaptation of the proposed framework to clinical score estimation is also presented. Compared with previous studies investigating new biomarkers for AD prediction over much shorter periods, the very long followup of the Three-City cohort demonstrates the important clinical potential of the proposed imaging biomarker. The high accuracy obtained with this new imaging biomarker paves the way for computer-based prognostic aides to help the clinician identify cognitively intact subjects that are at high risk to develop AD.

Mapping the Relationship of Contributing Factors for Preclinical Alzheimer's Disease

While detecting and validating correlations among the contributing factors to the preclinical phase of Alzheimer’s disease (pAD) has been a focus, a potent meta-analysis method to integrate current findings is essential. The entity-relationship diagram with nodes as entities and edges as relationships is a graphical representation that summarizes the relationships among multiple factors in an intuitive manner. Based on this concept, a new meta-analysis approach with this type of diagram is proposed to summarize research about contributing factors of pAD and their interactions. To utilize the information for enriched visualization, width and color of the edges are encoded with reporting times, number of pAD subjects, correlation coefficient, and study design (cross-sectional or longitudinal). The proposed Probabilistic Entity-Relationship Diagram (PERD) demonstrated its effectiveness in this research for studying pAD. Another kind of diagram with occurrence order for some factors was also proposed to provide sequential information of the factors. In addition, PERD could potentially develop into an online application named PERD-online, which would help researchers to pool findings on the same relationships and guide further tests to validate uncertain relationships in PERD. PERD as a generic graphical meta-analysis tool can also be applied in studying other multifactorial diseases.

Biomarkers in the diagnosis and management of Alzheimer's disease

Traditionally Alzheimer's disease (AD) has been diagnosed and its course followed based on clinical observations and cognitive testing, and confirmed postmortem by demonstrating amyloid plaques and neurofibrillary tangles in the brain. But the growing recognition that the disease process is ongoing, damaging the brain long before clinical findings appear, has intensified a search for biomarkers that might allow its very early diagnosis and the objective assessment of its responses to putative treatments. At present at least eight biochemical measurements or scanning procedures are used as biomarkers, usually in panels, by neurologists and others. The biochemical measurements are principally of amyloid proteins and their A-beta precursors, or of tau proteins. Brain atrophy can be assessed by means of structural magnetic resonance imaging (sMRI), and decreased blood flow and metabolism can be estimated by functional magnetic resonance imaging (fMRI). [18F]fluorodeoxyglucose-positron emission tomography (FDG-PET) is used to measure the brain's energy utilization and to infer synaptic number. Impaired connectivity between brain regions is indicated by diffusion tensor imaging (DTI), while magnetic resonance spectroscopy (MRS) provides metabolic markers of diminished cell number. Additional proposed biomarkers utilize electroencephalography (EEG) and magnetoencephalography (MEG) for quantifying impairments in connectivity. Genetic analyses illustrate the heterogeneity of disease processes that can cause cognitive impairment syndromes. Recent observations awaiting confirmation suggest that levels of some plasma phospholipids can also be biomarkers of AD and that reductions in these levels can enable the accurate prediction that a cognitively normal individual will go on to develop MCI or AD within 2 years.

Atherosclerosis in epilepsy: its causes and implications

Evidence from epidemiological, longitudinal, prospective, double-blinded clinical trials as well as case reports documents age-accelerated atherosclerosis with increased carotid artery intima media thickness (CA-IMT) in patients with epilepsy. These findings raise concern regarding their implications for age-accelerated cognitive and behavioral changes in midlife and risk of later age-related cognitive disorders including neurodegenerative processes such as Alzheimer's disease (AD). Chronic epilepsy, cerebral atherosclerosis, and age-related cognitive disorders including AD share many clinical manifestations (e.g. characteristic cognitive deficits), risk factors, and structural and pathological brain abnormalities. These shared risk factors include increased CA-IMT, hyperhomocysteinemia (HHcy), lipid abnormalities, weight gain and obesity, insulin resistance (IR), and high levels of inflammatory and oxidative stresses. The resulting brain structural and pathological abnormalities include decreased volume of the hippocampus, increased cortical thinning of the frontal lobe, ventricular expansion and increased white matter ischemic disease, total brain atrophy, and β-amyloid protein deposition in the brain. The knowledge that age-accelerated atherosclerosis may contribute to age-accelerated cognitive and behavioral abnormalities and structural brain pathologies in patients with chronic epilepsy represents an important research path to pursue future clinical and management considerations.

Brain region's relative proximity as marker for Alzheimer's disease based on structural MRI

BACKGROUND

Alzheimer's disease (AD) is a progressive, incurable neurodegenerative disease and the most common type of dementia. It cannot be prevented, cured or drastically slowed, even though AD research has increased in the past 5-10 years. Instead of focusing on the brain volume or on the single brain structures like hippocampus, this paper investigates the relationship and proximity between regions in the brain and uses this information as a novel way of classifying normal control (NC), mild cognitive impaired (MCI), and AD subjects.

METHODS

A longitudinal cohort of 528 subjects (170 NC, 240 MCI, and 114 AD) from ADNI at baseline and month 12 was studied. We investigated a marker based on Procrustes aligned center of masses and the percentile surface connectivity between regions. These markers were classified using a linear discriminant analysis in a cross validation setting and compared to whole brain and hippocampus volume.

RESULTS

We found that both our markers was able to significantly classify the subjects. The surface connectivity marker showed the best results with an area under the curve (AUC) at 0.877 (p<0.001), 0.784 (p<0.001), 0,766 (p<0.001) for NC-AD, NC-MCI, and MCI-AD, respectively, for the functional regions in the brain. The surface connectivity marker was able to classify MCI-converters with an AUC of 0.599 (p<0.05) for the 1-year period.

CONCLUSION

Our results show that our relative proximity markers include more information than whole brain and hippocampus volume. Our results demonstrate that our proximity markers have the potential to assist in early diagnosis of AD.