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

Brain morphology mediating the effects of common genetic risk variants on Alzheimer's disease

Background

Late-onset Alzheimer's disease (LOAD) has been associated with alterations in the morphology of multiple brain structures, and it is likely that disease mechanisms differ between brain regions. Coupling genetic determinants of LOAD with measures of brain morphology could localize and identify primary causal neurobiological pathways.

Objective

To determine causal pathways from genetic risk variants of LOAD via brain morphology to LOAD.

Methods

Mediation and Mendelian randomization (MR) analysis were performed using common genetic variation, T1 MRI and clinical data collected by UK Biobank and Alzheimer's Disease Neuroimaging Initiative.

Results

Thickness of the entorhinal cortex and the volumes of the hippocampus, amygdala and inferior lateral ventricle mediated the effect of APOE ε4 on LOAD. MR showed that a thinner entorhinal cortex, a smaller hippocampus and amygdala, and a larger volume of the inferior lateral ventricles, increased the risk of LOAD as well as vice versa.

Conclusions

Combining neuroimaging and genetic data can give insight into the causal neuropathological pathways of LOAD.

Genetic polymorphism in β-site amyloid precursor protein-cleaving enzyme 1 affects the structure of medial temporal lobe and cognition in Alzheimer's disease: an exploratory study

The β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) gene polymorphism (rs638405) has been widely reported to be associated with Alzheimer's disease (AD) risk. However, studies on the relationship between BACE1 gene polymorphism (rs638405), brain volume, and cognition in AD patients remain scarce. To investigate the effect of genetic polymorphism in BACE1 on gray matter volume (GMV) and cognition in AD, this study recruited 111 cognitively unimpaired (CU) controls and 144 AD patients. The effect of BACE1 rs638405 polymorphism on cognition was explored in CU and AD groups. Then the interaction effect of the diagnosis and BACE1 rs638405 polymorphism on GMV was performed, following the post-hoc analysis of regions of interest (ROIs) in interaction analysis. Mediation analysis was used to elucidate the relationship among genotypes, ROIs and cognition. BACE1 rs638405 G carriers (BACE1 G+) showed significantly lower scores in global cognition and memory function than noncarriers (BACE1 G-) in AD group. Genotypes (G+/G-) and diagnosis (CU/AD) have interaction on GMV of medial temporal lobe (MTL) including the left parahippocampus and right hippocampus. Post-hoc analysis revealed that BACE1 G+ exhibited significantly lower GMV in ROIs compared to BACE1 G- in AD. Finally, mediation analysis further demonstrated that the GMV of ROIs mediated the effect of BACE1 rs638405 polymorphism on cognition in AD. Our results emphasize the BACE1 rs638405 gene polymorphisms may affect the GMV of MTL and cognition in AD, deepening the understanding of AD pathogenesis.

Genetic architecture of hippocampus subfields volumes in Alzheimer's disease

BACKGROUND

The hippocampus is a heterogeneous structure, comprising histologically and functionally distinguishable hippocampal subfields. The volume reductions in hippocampal subfields have been demonstrated to be linked with Alzheimer's disease (AD). The aim of our study is to investigate the hippocampal subfields' genetic architecture based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) data set.

METHODS

After preprocessing the downloaded genetic variants and imaging data from the ADNI database, a co-sparse reduced rank regression model was applied to analyze the genetic architecture of hippocampal subfields volumes. Homology modeling, docking, molecular dynamics simulations, and Co-IP experiments for protein-protein interactions were used to verify the function of target protein on hippocampal subfields successively. After that, the association analysis between the candidated genes on the hippocampal subfields volume and clinical scales were performed.

RESULTS

The results of the association analysis revealed five unique genetic variants (e.g., ubiquitin-specific protease 10 [USP10]) changed in nine hippocampal subfields (e.g., the granule cell and molecular layer of the dentate gyrus [GC-ML-DG]). Among five genetic variants, USP10 had the strongest interaction effect with BACE1, which affected hippocampal subfields verified by MD and Co-IP experiments. The results of association analysis between the candidated genes on the hippocampal subfields volume and clinical scales showed that candidated genes influenced the volume and function of hippocampal subfields.

CONCLUSIONS

Current evidence suggests that hippocampal subfields have partly distinct genetic architecture and may improve the sensitivity of the detection of AD.

The Hippocampal Subfield Volume Reduction and Plasma Biomarker Changes in Mild Cognitive Impairment and Alzheimer's Disease

Background

The hippocampus consists of histologically and functionally distinct subfields, which shows differential vulnerabilities to Alzheimer's disease (AD)-associated pathological changes.

Objective

To investigate the atrophy patterns of the main hippocampal subfields in patients with mild cognitive impairment (MCI) and AD and the relationships among the hippocampal subfield volumes, plasma biomarkers and cognitive performance.

Methods

This cross-sectional study included 119 patients stratified into three categories: normal cognition (CN; N = 40), MCI (N = 39), and AD (N = 40). AD-related plasma biomarkers were measured, including amyloid-β (Aβ)42, Aβ40, Aβ42/Aβ40 ratio, p-tau181, and p-tau217, and the hippocampal subfield volumes were calculated using automated segmentation and volumetric procedures implemented in FreeSurfer.

Results

The subiculum body, cornu ammonis (CA) 1-head, CA1-body, CA4-body, molecular_layer_HP-head, molecular_layer_HP-body, and GC-ML-DG-body volumes were smaller in the MCI group than in the CN group. The subiculum body and CA1-body volumes accurately distinguished MCI from CN (area under the curve [AUC] = 0.647-0.657). The subiculum-body, GC-ML-DG-body, CA4-body, and molecular_layer_HP-body volumes accurately distinguished AD from MCI (AUC = 0.822-0.833) and AD from CN (AUC = 0.903-0.905). The p-tau 217 level served as the best plasma indicator of AD and correlated with broader hippocampal subfield volumes. Moreover, mediation analysis demonstrated that the subiculum-body volume mediated the associations between the p-tau217 and p-tau181 levels, and the Montreal Cognitive Assessment and Auditory Verbal Learning Test recognition scores.

Conclusions

Hippocampal subfields with distinctive atrophy patterns may mediate the effects of tau pathology on cognitive function. The subiculum-body may be the most clinically meaningful hippocampal subfield, which could be an effective target region for assessing disease progression.

Effects of amyloid beta and dopaminergic depletion on perfusion and clinical symptoms

INTRODUCTION

Although mixed pathologies are common in Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), the effects of amyloid beta and dopaminergic depletion on brain perfusion and clinical symptoms have not been elucidated.

METHODS

In 99 cognitive impairment patients due to AD and/or DLB and 32 controls, 18F-florbetaben (FBB) and dual-phase dopamine transporter (DAT) positron emission tomography (PET) were performed to measure the FBB standardized uptake value ratio (SUVR), striatal DAT uptakes, and brain perfusion.

RESULTS

Higher FBB-SUVR and lower ventral striatal DAT uptake were intercorrelated and, respectively, associated with left entorhinal/temporo-parietal-centered hypoperfusion and vermis/hippocampal-centered hyperperfusion, whereas regional perfusion mediated clinical symptoms and cognition.

DISCUSSION

Amyloid beta deposition and striatal dopaminergic depletion contribute to regional perfusion changes, clinical symptoms, and cognition in the spectrum of normal aging and cognitive impairment due to AD and/or LBD.

HIGHLIGHTS

Amyloid beta (Aβ) deposition was associated with ventral striatal dopaminergic depletion. Aβ deposition and dopaminergic depletion correlated with perfusion. Aβ deposition correlated with hypoperfusion centered in the left entorhinal cortex. Dopaminergic depletion correlated with hyperperfusion centered in the vermis. Perfusion mediated the Aβ deposition/dopaminergic depletion's effects on cognition.

Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer's disease?

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of in vivo gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome.

Bilateral Hippocampal Volume Mediated the Relationship Between Plasma BACE1 Concentration and Memory Function in the Early Stage of Alzheimer's Disease: A Cross-Sectional Study

BACKGROUND

β-site amyloid precursor protein cleaving enzyme 1 (BACE1) is a key enzyme in the formation of amyloid-β (Aβ) protein. Increasing evidence suggests that BACE1 concentration is a potential biomarker for Alzheimer's disease (AD).

OBJECTIVE

To evaluate the correlations between plasma BACE1 concentration, cognition, and hippocampal volume at different stages of the AD continuum.

METHODS

Plasma BACE1 concentrations were measured in 32 patients with probable dementia due to AD (ADD), 48 patients with mild cognitive impairment (MCI) due to AD, and 40 cognitively unimpaired (CU) individuals. Memory function was evaluated using the auditory verbal learning test (AVLT), and voxel-based morphometry was used to analyze bilateral hippocampal volumes. Correlation and mediation analyses were performed to investigate the associations between plasma BACE1 concentration, cognition, and hippocampal atrophy.

RESULTS

The MCI and ADD groups exhibited elevated BACE1 concentrations compared with the CU group after adjusting for age, sex, and apolipoprotein E (APOE) genotype. Increased BACE1 concentration was found in AD continuum patients who were APOE ɛ4 carriers (p < 0.05). BACE1 concentration was negatively associated with the scores of the subitems of the AVLT and hippocampal volume (p < 0.05, false discovery rate correction) in the MCI group. Moreover, bilateral hippocampal volume mediated the relationship between BACE1 concentration and recognition in the MCI group.

CONCLUSION

BACE1 expression increased in the AD continuum, and bilateral hippocampal volume mediated the effect of BACE1 concentration on memory function in patients with MCI. Research has indicated that the plasma BACE1 concentration might be a biomarker at the early stage of AD.

Brain Gray Matter Volume Mediated the Correlation Between Plasma P-Tau and Cognitive Function of Early Alzheimer's Disease in China: A Cross-Sectional Observational Study

BACKGROUND

The primary manifestations of Alzheimer's disease (AD) include cognitive decline and brain gray matter volume (GMV) atrophy. Recent studies have found that plasma phosphorylated-tau (p-tau) concentrations perform better in diagnosing, differentiating, and monitoring the progression of AD. However, the correlation between plasma p-tau, GMV, and cognition remains unclear.

OBJECTIVE

To investigate whether GMV plays a mediating role in the association between plasma p-tau concentrations and cognition.

METHODS

In total, 99 participants (47 patients with AD and 52 cognitively unimpaired [CU] individuals) were included. All participants underwent neuropsychological assessments, laboratory examinations, and magnetic resonance imaging scans. Plasma p-tau217 and p-tau181 concentrations were measured using an enzyme-linked immunosorbent assay kit. Voxel-based morphometry was performed to assess participants' brain GMV. Partial correlation and mediation analyses were conducted in AD group.

RESULTS

Plasma p-tau concentrations were significantly higher in the AD group than in the CU group. Patients with AD had significant brain GMV atrophy in the right hippocampus, bilateral middle temporal gyrus, and right inferior temporal gyrus. In the AD group, there were significant correlations between plasma p-tau217 concentrations, GMV, and Mini-Mental State Examination (MMSE) scores. Brain GMV of the right hippocampus mediated the association between plasma p-tau217 concentrations and MMSE scores. A significant correlation between plasma p-tau181 and MMSE scores was not identified.

CONCLUSION

The findings indicate that p-tau217 is a promising biomarker for central processes affecting brain GMV and cognitive function. This may provide potential targets for future intervention and treatment of tau-targeting therapies in the early stages of AD.

Can hippocampal subfield measures supply information that could be used to improve the diagnosis of Alzheimer's disease?

The diagnosis of Alzheimer's disease (AD) needs to be improved. We investigated if hippocampal subfield volume measured by structural imaging, could supply information, so that the diagnosis of AD could be improved. In this study, subjects were classified based on clinical, neuropsychological, and amyloid positivity or negativity using PET scans. Data from 478 elderly Korean subjects grouped as cognitively unimpaired β-amyloid-negative (NC), cognitively unimpaired β-amyloid-positive (aAD), mild cognitively impaired β-amyloid-positive (pAD), mild cognitively impaired-specific variations not due to dementia β-amyloid-negative (CIND), severe cognitive impairment β-amyloid-positive (ADD+) and severe cognitive impairment β-amyloid-negative (ADD-) were used. NC and aAD groups did not show significant volume differences in any subfields. The CIND did not show significant volume differences when compared with either the NC or the aAD (except L-HATA). However, pAD showed significant volume differences in Sub, PrS, ML, Tail, GCMLDG, CA1, CA4, HATA, and CA3 when compared with the NC and aAD. The pAD group also showed significant differences in the hippocampal tail, CA1, CA4, molecular layer, granule cells/molecular layer/dentate gyrus, and CA3 when compared with the CIND group. The ADD- group had significantly larger volumes than the ADD+ group in the bilateral tail, SUB, PrS, and left ML. The results suggest that early amyloid depositions in cognitive normal stages are not accompanied by significant bilateral subfield volume atrophy. There might be intense and accelerated subfield volume atrophy in the later stages associated with the cognitive impairment in the pAD stage, which subsequently could drive the progression to AD dementia. Early subfield volume atrophy associated with the β-amyloid burden may be characterized by more symmetrical atrophy in CA regions than in other subfields. We conclude that the hippocampal subfield volumetric differences from structural imaging show promise for improving the diagnosis of Alzheimer's disease.

Stage-dependent differential influence of metabolic and structural networks on memory across Alzheimer's disease continuum

Background

Large-scale neuronal network breakdown underlies memory impairment in Alzheimer's disease (AD). However, the differential trajectories of the relationships between network organisation and memory across pathology and cognitive stages in AD remain elusive. We determined whether and how the influences of individual-level structural and metabolic covariance network integrity on memory varied with amyloid pathology across clinical stages without assuming a constant relationship.

Methods

Seven hundred and eight participants from the Alzheimer's Disease Neuroimaging Initiative were studied. Individual-level structural and metabolic covariance scores in higher-level cognitive and hippocampal networks were derived from magnetic resonance imaging and [18F] fluorodeoxyglucose positron emission tomography using seed-based partial least square analyses. The non-linear associations between network scores and memory across cognitive stages in each pathology group were examined using sparse varying coefficient modelling.

Results

We showed that the associations of memory with structural and metabolic networks in the hippocampal and default mode regions exhibited pathology-dependent differential trajectories across cognitive stages using sparse varying coefficient modelling. In amyloid pathology group, there was an early influence of hippocampal structural network deterioration on memory impairment in the preclinical stage, and a biphasic influence of the angular gyrus-seeded default mode metabolic network on memory in both preclinical and dementia stages. In non-amyloid pathology groups, in contrast, the trajectory of the hippocampus-memory association was opposite and weaker overall, while no metabolism covariance networks were related to memory. Key findings were replicated in a larger cohort of 1280 participants.

Conclusions

Our findings highlight potential windows of early intervention targeting network breakdown at the preclinical AD stage.

Funding

Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). We also acknowledge the funding support from the Duke NUS/Khoo Bridge Funding Award (KBrFA/2019-0020) and NMRC Open Fund Large Collaborative Grant (OFLCG09May0035).

Deep transfer learning of structural magnetic resonance imaging fused with blood parameters improves brain age prediction

Machine learning has been applied to neuroimaging data for estimating brain age and capturing early cognitive impairment in neurodegenerative diseases. Blood parameters like neurofilament light chain are associated with aging. In order to improve brain age predictive accuracy, we constructed a model based on both brain structural magnetic resonance imaging (sMRI) and blood parameters. Healthy subjects (n = 93; 37 males; aged 50-85 years) were recruited. A deep learning network was firstly pretrained on a large set of MRI scans (n = 1,481; 659 males; aged 50-85 years) downloaded from multiple open-source datasets, to provide weights on our recruited dataset. Evaluating the network on the recruited dataset resulted in mean absolute error (MAE) of 4.91 years and a high correlation (r = .67, p <.001) against chronological age. The sMRI data were then combined with five blood biochemical indicators including GLU, TG, TC, ApoA1 and ApoB, and 9 dementia-associated biomarkers including ApoE genotype, HCY, NFL, TREM2, Aβ40, Aβ42, T-tau, TIMP1, and VLDLR to construct a bilinear fusion model, which achieved a more accurate prediction of brain age (MAE, 3.96 years; r = .76, p <.001). Notably, the fusion model achieved better improvement in the group of older subjects (70-85 years). Extracted attention maps of the network showed that amygdala, pallidum, and olfactory were effective for age estimation. Mediation analysis further showed that brain structural features and blood parameters provided independent and significant impact. The constructed age prediction model may have promising potential in evaluation of brain health based on MRI and blood parameters.

P-tau and neurodegeneration mediate the effect of β-amyloid on cognition in non-demented elders

BACKGROUND

There are many pathological changes in the brains of Alzheimer's disease (AD) patients. For many years, the mainstream view on the pathogenesis of AD believes that β-amyloid (Aβ) usually acts independently in addition to triggering functions. However, the evidence now accumulating indicates another case that these pathological types have synergies. The objective of this study was to investigate whether effects of Aβ pathology on cognition were mediated by AD pathologies, including tau-related pathology (p-tau), neurodegeneration (t-tau, MRI measurements), axonal injury (NFL), synaptic dysfunction (neurogranin), and neuroinflammation (sTREM2, YKL-40).

METHODS

Three hundred seventy normal controls (CN) and 623 MCI patients from the ADNI (Alzheimer's Disease Neuroimaging Initiative) database were recruited in this research. Linear mixed-effects models were used to evaluate the associations of baseline Aβ with cognitive decline and biomarkers of several pathophysiological pathways. Causal mediation analyses with 10,000 bootstrapped iterations were conducted to explore the mediation effects of AD pathologies on cognition.

RESULTS

Tau-related pathology, neurodegeneration, neuroinflammation are correlated with the concentration of Aβ, even in CN participants. The results show that age, gender, and APOE ε4 carrier status have a moderating influence on some of these relationships. There is a stronger association of Aβ with biomarkers and cognitive changes in the elderly and females. In CN group, Aβ pathology is directly related to poor cognition and has no mediating effect (p < 0.05). In mild cognitive impairment, tau-related pathology (26.15% of total effect) and neurodegeneration (14.8% to 47.0% of total effect) mediate the impact of Aβ on cognition.

CONCLUSIONS

In conclusion, early Aβ accumulation has an independent effect on cognitive decline in CN and a tau, neurodegeneration-dependent effect in the subsequent cognitive decline in MCI patients.

Age-related episodic memory decline and the role of amyloid-β: a systematic review

Aging has been associated with the functional decline of episodic memory (EM). Unanswered questions are whether the decline of EM occurs even during healthy aging and whether this decline is related to amyloid-β (Aβ) deposition in the hippocampus.

Objective

The main purpose of this study was to investigate data on the relationship between the age-related EM decline and Aβ deposition.

Methods

We searched the Cochrane, MEDLINE, Scopus, and Web of Science databases and reference lists of retrieved articles that were published in the past 10 years. The initial literature search identified 517 studies. After screening the title, abstract, key words, and reference lists, 56 studies met the inclusion criteria.

Results

The overall results revealed that increases in Aβ are related to lower hippocampal volume and worse performance on EM tests. The results of this systematic review revealed that high levels of Aβ may be related to EM deficits and the progression to Alzheimer's disease.

Conclusions

We discussed the strengths and pitfalls of various tests and techniques used for investigating EM and Aβ deposition, methodological issues, and potential directions for future research.

Predicting future rates of tau accumulation on PET

Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitively impaired. All 337 participants had: a baseline study visit with MRI, amyloid PET, and tau PET exams, at least one follow-up tau PET exam; and met clinical criteria for membership in one of two clinical diagnostic groups: cognitively unimpaired (n = 203); or cognitively impaired (n = 134, a combined group of participants with either mild cognitive impairment or dementia with Alzheimer's clinical syndrome). Our primary analyses were in these two clinical groups; however, we also evaluated subgroups dividing the unimpaired group by normal/abnormal amyloid PET and the impaired group by clinical phenotype (mild cognitive impairment, amnestic dementia, and non-amnestic dementia). Linear mixed effects models were used to estimate associations between age, sex, education, APOE genotype, amyloid and tau PET standardized uptake value ratio (SUVR), cognitive performance, cortical thickness, and white matter hyperintensity volume at baseline, and the rate of subsequent tau PET accumulation. Log-transformed tau PET SUVR was used as the response and rates were summarized as annual per cent change. A temporal lobe tau PET meta-region of interest was used. In the cognitively unimpaired group, only higher baseline amyloid PET was a significant independent predictor of higher tau accumulation rates (P < 0.001). Higher rates of tau accumulation were associated with faster rates of cognitive decline in the cognitively unimpaired subgroup with abnormal amyloid PET (P = 0.03), but among the subgroup with normal amyloid PET. In the cognitively impaired group, younger age (P = 0.02), higher baseline amyloid PET (P = 0.05), APOE ε4 (P = 0.05), and better cognitive performance (P = 0.05) were significant independent predictors of higher tau accumulation rates. Among impaired individuals, faster cognitive decline was associated with faster rates of tau accumulation (P = 0.01). While we examined many possible predictor variables, our results indicate that screening of unimpaired individuals for potential inclusion in anti-tau trials may be straightforward because the only independent predictor of high tau rates was amyloidosis. In cognitively impaired individuals, imaging and clinical variables consistent with early onset Alzheimer's disease phenotype were associated with higher rates of tau PET accumulation suggesting this may be a highly advantageous group in which to conduct proof-of-concept clinical trials that target tau-related mechanisms. The nature of the dementia phenotype (amnestic versus non-amnestic) did not affect this conclusion.

Ketones improves Apolipoprotein E4-related memory deficiency via sirtuin 3

Background: Apolipoprotein E4 (ApoE4) is the major genetic risk factor of Alzheimer’s disease (AD). ApoE4 carriers have cerebral hypometabolism which is thought as a harbinger of AD. Our previous studies indicated ketones improved mitochondria energy metabolism via sirtuin 3 (Sirt3). However, it is unclear whether ketones upregulate Sirt3 and improve ApoE4-related learning and memory deficits.

Results: Ketones improved learning and memory abilities of ApoE4 mice but not ApoE3 mice. Sirt3, synaptic proteins, the NAD⁺/ NADH ratio, and ATP production were significantly increased in the hippocampus and the cortex from ketone treatment.

Methods: Human ApoE3 and ApoE4 transgenic mice (9-month-old) were treated with either ketones or normal saline by daily subcutaneous injections for 3 months (ketones, beta-hydroxybutyrate (BHB): 600 mg/kg/day; acetoacetate (ACA): 150 mg/kg/day). Learning and memory ability of these mice were assessed. Sirt3 protein, synaptic proteins (PSD95, Synaptophysin), the NAD⁺/ NADH ratio, and ATP levels were measured in the hippocampus and the cortex.

Conclusion: Our current studies suggest that ketones improve learning and memory abilities of ApoE4 transgenic mice. Sirt3 may mediate the neuroprotection of ketones by increasing neuronal energy metabolism in ApoE4 transgenic mice. This provides the foundation for Sirt3’s potential role in the prevention and treatment of AD.

Mild Cognitive Impairment Staging Yields Genetic Susceptibility, Biomarker, and Neuroimaging Differences

INTRODUCTION

While Alzheimer's disease (AD) is divided into severity stages, mild cognitive impairment (MCI) remains a solitary construct despite clinical and prognostic heterogeneity. This study aimed to characterize differences in genetic, cerebrospinal fluid (CSF), neuroimaging, and neuropsychological markers across clinician-derived MCI stages.

METHODS

Vanderbilt Memory & Aging Project participants with MCI were categorized into 3 severity subtypes at screening based on neuropsychological assessment, functional assessment, and Clinical Dementia Rating interview, including mild (n = 18, 75 ± 8 years), moderate (n = 89 72 ± 7 years), and severe subtypes (n = 18, 78 ± 8 years). At enrollment, participants underwent neuropsychological testing, 3T brain magnetic resonance imaging (MRI), and optional fasting lumbar puncture to obtain CSF. Neuropsychological testing and MRI were repeated at 18-months, 3-years, and 5-years with a mean follow-up time of 3.3 years. Ordinary least square regressions examined cross-sectional associations between MCI severity and apolipoprotein E (APOE)-ε4 status, CSF biomarkers of amyloid beta (Aβ), phosphorylated tau, total tau, and synaptic dysfunction (neurogranin), baseline neuroimaging biomarkers, and baseline neuropsychological performance. Longitudinal associations between baseline MCI severity and neuroimaging and neuropsychological trajectory were assessed using linear mixed effects models with random intercepts and slopes and a follow-up time interaction. Analyses adjusted for baseline age, sex, race/ethnicity, education, and intracranial volume for MRI models.

RESULTS

Stages differed at baseline on APOE-ε4 status (early < middle = late; p-values < 0.03) and CSF Aβ (early > middle = late), phosphorylated and total tau (early = middle < late; p-values < 0.05), and neurogranin concentrations (early = middle < late; p-values < 0.05). MCI stage related to greater longitudinal cognitive decline, hippocampal atrophy, and inferior lateral ventricle dilation (early < late; p-values < 0.03).

DISCUSSION

Clinician staging of MCI severity yielded longitudinal cognitive trajectory and structural neuroimaging differences in regions susceptible to AD neuropathology and neurodegeneration. As expected, participants with more severe MCI symptoms at study entry had greater cognitive decline and gray matter atrophy over time. Differences are likely attributable to baseline differences in amyloidosis, tau, and synaptic dysfunction. MCI staging may provide insight into underlying pathology, prognosis, and therapeutic targets.

Dynamic association between AT(N) profile and cognition mediated by cortical thickness in Alzheimer's continuum

BACKGROUND

The recently-proposed National Institute on Aging and Alzheimer's Association research framework organizes Alzheimer's disease (AD) biomarkers based on amyloid/tau/neurodegeneration (AT(N)). This study investigated the mediating effect of structural change in brain MRI on changes in cognitive function according to initial AT(N) profiles.

METHODS

We included 576 subjects (cognitively unimpaired (N = 136), mild cognitive impairment (N = 294), dementia (N = 146)) from the Alzheimer's disease Neuroimaging Initiative study. The parallel-process latent growth curve model was applied to test the mediational effect of cortical thickness growth trajectory between the initial AT(N) profiles and cognitive growth trajectory.

RESULTS

In Alzheimer's continuum, only the A + T + (N)+ profile showed a mediational effect of the cortical thickness growth trajectory. A + T - (N)- was not sufficient to induce direct or indirect effects on cognitive dysfunction, and A + T + (N)- showed a significant direct path from an altered cortical thickness to cognitive decline.

CONCLUSION

The sequential effect between changes in brain MRI and cognition varied by baseline AT(N) profile, suggesting the dynamic changes in the relationships among biomarkers in the current cascade model.

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.

Is Sleep Disruption a Cause or Consequence of Alzheimer's Disease? Reviewing Its Possible Role as a Biomarker

In recent years, the idea that sleep is critical for cognitive processing has gained strength. Alzheimer's disease (AD) is the most common form of dementia worldwide and presents a high prevalence of sleep disturbances. However, it is difficult to establish causal relations, since a vicious circle emerges between different aspects of the disease. Nowadays, we know that sleep is crucial to consolidate memory and to remove the excess of beta-amyloid and hyperphosphorilated tau accumulated in AD patients' brains. In this review, we discuss how sleep disturbances often precede in years some pathological traits, as well as cognitive decline, in AD. We describe the relevance of sleep to memory consolidation, focusing on changes in sleep patterns in AD in contrast to normal aging. We also analyze whether sleep alterations could be useful biomarkers to predict the risk of developing AD and we compile some sleep-related proposed biomarkers. The relevance of the analysis of the sleep microstructure is highlighted to detect specific oscillatory patterns that could be useful as AD biomarkers.

Sirtuin 3 attenuates amyloid-β induced neuronal hypometabolism

Alzheimer’s disease (AD) is manifested by regional cerebral hypometabolism. Sirtuin 3 (Sirt3) is localized in mitochondria and regulates cellular metabolism, but the role of Sirt3 in AD-related hypometabolism remains elusive. We used expression profiling and weighted gene co-expression network analysis (WGCNA) to analyze cortical neurons from a transgenic mouse model of AD (APPSwInd). Based on WGCNA results, we measured NAD⁺ level, NAD⁺/ NADH ratio, Sirt3 protein level and its deacetylation activity, and ATP production across both in vivo and in vitro models. To investigate the effect of Sirt3 on amyloid-β (Aβ)-induced mitochondria damage, we knocked down and over-expressed Sirt3 in hippocampal cells. WGCNA revealed Sirt3 as a key player in Aβ-related hypometabolism. In APP mice, the NAD⁺ level, NAD⁺/ NADH ratio, Sirt3 protein level and activity, and ATP production were all reduced compared to the control. As a result, learning and memory performance were impaired in 9-month-old APP mice compared to wild type controls. Using hippocampal HT22 cells model, Sirt3 overexpression increased Sirt3 deacetylation activity, rescued mitochondria function, and salvaged ATP production, which were damaged by Aβ. Sirt3 plays an important role in regulating Aβ-induced cerebral hypometabolism. This study suggests a potential direction for AD therapy.

Hippocampal subfield volumes and pre-clinical Alzheimer's disease in 408 cognitively normal adults born in 1946

BACKGROUND

The human hippocampus comprises a number of interconnected histologically and functionally distinct subfields, which may be differentially influenced by cerebral pathology. Automated techniques are now available that estimate hippocampal subfield volumes using in vivo structural MRI data. To date, research investigating the influence of cerebral β-amyloid deposition-one of the earliest hypothesised changes in the pathophysiological continuum of Alzheimer's disease-on hippocampal subfield volumes in cognitively normal older individuals, has been limited.

METHODS

Using cross-sectional data from 408 cognitively normal individuals born in mainland Britain (age range at time of assessment = 69.2-71.9 years) who underwent cognitive assessment, 18F-Florbetapir PET and structural MRI on the same 3 Tesla PET/MR unit (spatial resolution 1.1 x 1.1 x 1.1. mm), we investigated the influences of β-amyloid status, age at scan, and global white matter hyperintensity volume on: CA1, CA2/3, CA4, dentate gyrus, presubiculum and subiculum volumes, adjusting for sex and total intracranial volume.

RESULTS

Compared to β-amyloid negative participants (n = 334), β-amyloid positive participants (n = 74) had lower volume of the presubiculum (3.4% smaller, p = 0.012). Despite an age range at scanning of just 2.7 years, older age at time of scanning was associated with lower CA1 (p = 0.007), CA4 (p = 0.004), dentate gyrus (p = 0.002), and subiculum (p = 0.035) volumes. There was no evidence that white matter hyperintensity volume was associated with any subfield volumes.

CONCLUSION

These data provide evidence of differential associations in cognitively normal older adults between hippocampal subfield volumes and β-amyloid deposition and, increasing age at time of scan. The relatively selective effect of lower presubiculum volume in the β-amyloid positive group potentially suggest that the presubiculum may be an area of early and relatively specific volume loss in the pathophysiological continuum of Alzheimer's disease. Future work using higher resolution imaging will be key to exploring these findings further.

β-amyloid pathology and hippocampal atrophy are independently associated with memory function in cognitively healthy elderly

The independent effects of different brain pathologies on age-dependent cognitive decline are unclear. We examined this in 300 cognitively unimpaired elderly individuals from the BioFINDER study. Using cognition as outcome we studied the effects of cerebrospinal fluid biomarkers for amyloid-β (Aβ42/40), neuroinflammation (YKL-40), and neurodegeneration and tau pathology (T-tau and P-tau) as well as MRI measures of white-matter lesions, hippocampal volume (HV), and regional cortical thickness. We found that Aβ positivity and HV were independently associated with memory. Results differed depending on age, with memory being associated with HV (but not Aβ) in older participants (73.3–88.4 years), and with Aβ (but not HV) in relatively younger participants (65.2–73.2 years). This indicates that Aβ and atrophy are independent contributors to memory variability in cognitively healthy elderly and that Aβ mainly affects memory in younger elderly individuals. With advancing age, the effect of brain atrophy overshadows the effect of Aβ on memory function.

AD molecular: PET amyloid imaging across the Alzheimer's disease spectrum: From disease mechanisms to prevention

The advent of amyloid-beta (Aβ) positron emission tomography (PET) imaging has transformed the field of Alzheimer's disease (AD) by enabling the quantification of cortical Aβ accumulation and propagation in vivo. This revolutionary tool has made it possible to measure direct associations between Aβ and other AD biomarkers, to identify factors that influence Aβ accumulation and to redefine entry criteria into clinical trials as well as measure drug target engagement. This chapter summarizes the main findings on the associations of Aβ with other biomarkers of disease progression across the AD spectrum. It discusses investigations of the timing at which Aβ pathology starts to accumulate, demonstrates the clinical utility of Aβ PET imaging and discusses some ethical implications. Finally, it presents genetic and potentially modifiable lifestyle factors that might influence Aβ accumulation and therefore be targets for AD prevention.

White matter microstructural abnormalities and default network degeneration are associated with early memory deficit in Alzheimer's disease continuum

Instead of assuming a constant relationship between brain abnormalities and memory impairment, we aimed to examine the stage-dependent contributions of multimodal brain structural and functional deterioration to memory impairment in the Alzheimer’s disease (AD) continuum. We assessed grey matter volume, white matter (WM) microstructural measures (free-water (FW) and FW-corrected fractional anisotropy), and functional connectivity of the default mode network (DMN) in 54 amnestic mild cognitive impairment (aMCI) and 46 AD. We employed a novel sparse varying coefficient model to investigate how the associations between abnormal brain measures and memory impairment varied throughout disease continuum. We found lower functional connectivity in the DMN was related to worse memory across AD continuum. Higher widespread white matter FW and lower fractional anisotropy in the fornix showed a stronger association with memory impairment in the early aMCI stage; such WM-memory associations then decreased with increased dementia severity. Notably, the effect of the DMN atrophy occurred in early aMCI stage, while the effect of the medial temporal atrophy occurred in the AD stage. Our study provided evidence to support the hypothetical progression models underlying memory dysfunction in AD cascade and underscored the importance of FW increases and DMN degeneration in early stage of memory deficit.

Predicting diagnosis and cognition with 18F-AV-1451 tau PET and structural MRI in Alzheimer's disease

INTRODUCTION

The relative importance of structural magnetic resonance imaging (MRI) and tau positron emission tomography (PET) to predict diagnosis and cognition in Alzheimer's disease (AD) is unclear.

METHODS

We tested 56 cognitively unimpaired controls (including 27 preclinical AD), 32 patients with prodromal AD, and 39 patients with AD dementia. Optimal classifiers were constructed using the least absolute shrinkage and selection operator with ¹⁸F-AV-1451 (tau) PET and structural MRI data (regional cortical thickness and subcortical volumes).

RESULTS

¹⁸F-AV-1451 in the amygdala, entorhinal cortex, parahippocampal gyrus, fusiform, and inferior parietal lobule had 93% diagnostic accuracy for AD (prodromal or dementia). The MRI classifier involved partly the same regions plus the hippocampus, with 83% accuracy, but did not improve upon the tau classifier. ¹⁸F-AV-1451 retention and MRI were independently associated with cognition.

DISCUSSION

Optimized tau PET classifiers may diagnose AD with high accuracy, but both tau PET and structural brain MRI capture partly unique information relevant for the clinical deterioration in AD.

Cerebrospinal Fluid Amyloid-β 42, Total Tau and Phosphorylated Tau are Low in Patients with Normal Pressure Hydrocephalus: Analogies and Differences with Alzheimer's Disease

Co-existence of Alzheimer's disease (AD) in normal pressure hydrocephalus (NPH) is a frequent finding, thus a common pathophysiological basis between AD and NPH has been postulated. We measured CSF amyloid-β 42 (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau) concentrations in a sample of 294 patients with different types of dementia and 32 subjects without dementia. We then compared scores on neuropsychological tests of NPH patients with pathological and normal CSF Aβ42 values. Aβ42 levels were significantly lower in NPH than in control patients, with no significant differences between AD and NPH. On the contrary, t-tau and p-tau levels were significantly lower in NPH than in AD, with no differences between NPH and controls. NPH patients with pathological Aβ42 levels did not perform worse than NPH patients with normal Aβ42 levels in any cognitive domains. Our data seem to support the hypothesis of amyloid accumulation in brains of NPH patients. Nevertheless, amyloid does not seem to play a pathogenetic role in the development of cognitive deficits in NPH.

Joint associations of β-amyloidosis and cortical thickness with cognition

In 1164 cognitively unimpaired persons, aged 50-95 years, from the population-based Mayo Clinic Study of Aging, we examined the relationships of baseline cognition and cognitive changes across the full range of cortical thickness of an Alzheimer signature region of interest and global β-amyloid levels measured by Pittsburgh compound B positron emission tomography (PIB PET) standardized uptake value ratio (SUVR). In machine-learning models accounting for both biomarkers simultaneously, worsening biomarker values were additive and associated with lower baseline global cognition and greater subsequent decline in global cognition. Associations between Alzheimer's disease signature cortical thickness or PIB PET β-amyloid SUVR and baseline cognition were mainly linear. Lower Alzheimer's disease signature cortical thickness values across the entire range of thickness predicted future decline in global cognitive scores, demonstrating its close relationship to cognitive functioning. PIB PET β-amyloid SUVR also predicted cognitive decline across its full range, even when cortical thickness was accounted for. PIB PET β-amyloid's relationship to cognitive decline was nonlinear, more prominent at lower β-amyloid levels and less prominent at higher β-amyloid levels.

Staging of amyloid β, t-tau, regional atrophy rates, and cognitive change in a nondemented cohort: Results of serial mediation analyses

INTRODUCTION

Current models posit a sequence of amyloid β (Aβ), tau, atrophy, and cognitive change leading to Alzheimer's disease, but ambiguities remain. We examined these sequences via serial mediations.

METHODS

We studied normal controls, early mild cognitive impairment, and late mild cognitive impairment individuals from the Alzheimer's Disease Neuroimaging Initiative 2 database for the mediation of baseline cerebrospinal fluid Aβ effects on 2-year cognitive change via regional longitudinal atrophy rate (AR) alone or AR and tau.

RESULTS

In normal controls, Aβ correlated directly with regional ARs and memory loss, with no mediations. In early mild cognitive impairment, tau and lateral temporal ARs serially mediated the influence of Aβ on memory while Aβ affected memory via hippocampal AR. Late mild cognitive impairment consistently showed serial mediations of tau followed by atrophy. However, Aβ effects on memory also continued to be specifically mediated by medial temporal ARs without intermediate tau.

DISCUSSION

Biomarker sequences vary by region and disease state, suggesting the need to refine current cascade models.

18F PET with florbetapir for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)

BACKGROUND

¹⁸F-florbetapir uptake by brain tissue measured by positron emission tomography (PET) is accepted by regulatory agencies like the Food and Drug Administration (FDA) and the European Medicine Agencies (EMA) for assessing amyloid load in people with dementia. Its added value is mainly demonstrated by excluding Alzheimer's pathology in an established dementia diagnosis. However, the National Institute on Aging and Alzheimer's Association (NIA-AA) revised the diagnostic criteria for Alzheimer's disease and confidence in the diagnosis of mild cognitive impairment (MCI) due to Alzheimer's disease may be increased when using amyloid biomarkers tests like ¹⁸F-florbetapir. These tests, added to the MCI core clinical criteria, might increase the diagnostic test accuracy (DTA) of a testing strategy. However, the DTA of ¹⁸F-florbetapir to predict the progression from MCI to Alzheimer's disease dementia (ADD) or other dementias has not yet been systematically evaluated.

OBJECTIVES

To determine the DTA of the ¹⁸F-florbetapir PET scan for detecting people with MCI at time of performing the test who will clinically progress to ADD, other forms of dementia (non-ADD), or any form of dementia at follow-up.

SEARCH METHODS

This review is current to May 2017. We searched MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), BIOSIS Citation Index (Thomson Reuters Web of Science), Web of Science Core Collection, including the Science Citation Index (Thomson Reuters Web of Science) and the Conference Proceedings Citation Index (Thomson Reuters Web of Science), LILACS (BIREME), CINAHL (EBSCOhost), ClinicalTrials.gov (https://clinicaltrials.gov), and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (http://www.who.int/ictrp/search/en/). We also searched ALOIS, the Cochrane Dementia & Cognitive Improvement Group's specialised register of dementia studies (http://www.medicine.ox.ac.uk/alois/). We checked the reference lists of any relevant studies and systematic reviews, and performed citation tracking using the Science Citation Index to identify any additional relevant studies. No language or date restrictions were applied to the electronic searches.

SELECTION CRITERIA

We included studies that had prospectively defined cohorts with any accepted definition of MCI at time of performing the test and the use of ¹⁸F-florbetapir scan to evaluate the DTA of the progression from MCI to ADD or other forms of dementia. In addition, we only selected studies that applied a reference standard for Alzheimer's dementia diagnosis, for example, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) or Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria.

DATA COLLECTION AND ANALYSIS

We screened all titles and abstracts identified in electronic-database searches. Two review authors independently selected studies for inclusion and extracted data to create two-by-two tables, showing the binary test results cross-classified with the binary reference standard. We used these data to calculate sensitivities, specificities, and their 95% confidence intervals. Two independent assessors performed quality assessment using the QUADAS-2 tool plus some additional items to assess the methodological quality of the included studies.

MAIN RESULTS

We included three studies, two of which evaluated the progression from MCI to ADD, and one evaluated the progression from MCI to any form of dementia.Progression from MCI to ADD was evaluated in 448 participants. The studies reported data on 401 participants with 1.6 years of follow-up and in 47 participants with three years of follow-up. Sixty-one (15.2%) participants converted at 1.6 years follow-up; nine (19.1%) participants converted at three years of follow-up.Progression from MCI to any form of dementia was evaluated in five participants with 1.5 years of follow-up, with three (60%) participants converting to any form of dementia.There were concerns regarding applicability in the reference standard in all three studies. Regarding the domain of flow and timing, two studies were considered at high risk of bias. MCI to ADD;Progression from MCI to ADD in those with a follow-up between two to less than four years had a sensitivity of 67% (95% CI 30 to 93) and a specificity of 71% (95% CI 54 to 85) by visual assessment (n = 47, 1 study).Progression from MCI to ADD in those with a follow-up between one to less than two years had a sensitivity of 89% (95% CI 78 to 95) and a specificity of 58% (95% CI 53 to 64) by visual assessment, and a sensitivity of 87% (95% CI 76 to 94) and a specificity of 51% (95% CI 45 to 56) by quantitative assessment by the standardised uptake value ratio (SUVR)(n = 401, 1 study). MCI to any form of dementia;Progression from MCI to any form of dementia in those with a follow-up between one to less than two years had a sensitivity of 67% (95% CI 9 to 99) and a specificity of 50% (95% CI 1 to 99) by visual assessment (n = 5, 1 study). MCI to any other forms of dementia (non-ADD);There was no information regarding the progression from MCI to any other form of dementia (non-ADD).

AUTHORS' CONCLUSIONS

Although sensitivity was good in one included study, considering the poor specificity and the limited data available in the literature, we cannot recommend routine use of ¹⁸F-florbetapir PET in clinical practice to predict the progression from MCI to ADD.Because of the poor sensitivity and specificity, limited number of included participants, and the limited data available in the literature, we cannot recommend its routine use in clinical practice to predict the progression from MCI to any form of dementia.Because of the high financial costs of ¹⁸F-florbetapir, clearly demonstrating the DTA and standardising the process of this modality are important prior to its wider use.

Aberrant interhemispheric functional and structural connectivity in heroin-dependent individuals

Models of heroin addiction emphasize the role of disrupted frontostriatal circuitry supporting cognitive control processes. However, heroin addiction-related alterations in functional and structural interactions among brain regions, especially between the cerebral hemispheres, are rarely examined directly. Resting-state functional magnetic resonance imaging (fMRI) approaches, which reveal patterns of coherent spontaneous fluctuations in the fMRI signal, offer a means to quantify directly functional interactions between the hemispheres. The corpus callosum (CC), which connects homologous regions of the cortex, is the major conduit for information transfer between the cerebral hemispheres and represents a structural connectivity index between hemispheres. We compared interhemispheric voxel-mirrored homotopic connectivity (VMHC) and CC volume between 45 heroin dependent-individuals (HDIs) and 35 non-addict individuals. We observed significant reduction of VMHC in a number of regions, particularly the striatum/limbic system regions, and significant decrease in splenium and genu sub-regions of CC in HDI. Importantly, within HDI, VMHC in the dorsal lateral prefrontal cortex (DLPFC) correlated with genu CC volume, VMHC in the putamen, VMHC in the DLPFC and genu CC volume and splenium CC volume were negatively correlated with heroin duration and impulsivity traits. Further analyses demonstrated that impairment of VMHC of bilateral DLPFC partially mediated the association between genu CC volumes decreased and increased impulsivity in HDI. Our results reveal a substantial impairment of interhemispheric coordination in the HDI. Further, interhemispheric connectivity correlated with the duration of heroin abuse and higher impulsivity behavior in HDI. Our findings provide insight into a heroin addicts' related pathophysiology and reinforce an integrative view of the interhemispheric cerebral functional and structural organization.

Cortical amyloid accumulation is associated with alterations of structural integrity in older people with subjective memory complaints

We determined the effect of cortical amyloid load using ¹⁸F-florbetapir PET on cognitive performance and gray matter structural integrity derived from MRI in 318 cognitively normally performing older people with subjective memory impairment from the INSIGHT-preAD cohort using multivariate partial least squares regression. Amyloid uptake was associated with reduced gray matter structural integrity in hippocampus, entorhinal and cingulate cortex, middle temporal gyrus, prefrontal cortex, and lentiform nucleus (p < 0.01, permutation test). Higher amyloid load was associated with poorer global cognitive performance, delayed recall and attention (p < 0.05), independently of its effects on gray matter connectivity. These findings agree with the assumption of a two-stage effect of amyloid on cognition, (1) an early direct effect in the preclinical stages of Alzheimer's disease and (2) a delayed effect mediated by downstream effects of amyloid accumulation, such as gray matter connectivity decline.

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

INTRODUCTION

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

METHODS

We used standard searches to find publications using ADNI data.

RESULTS

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

DISCUSSION

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

Inter-hemispheric functional dysconnectivity mediates the association of corpus callosum degeneration with memory impairment in AD and amnestic MCI

Evidences suggested that both corpus callosum (CC) degeneration and alternations of homotopic inter-hemispheric functional connectivity (FC) are present in Alzheimer's disease (AD). However, the associations between region-specific CC degeneration and homotopic inter-hemispheric FC and their relationships with memory deficits in AD remain uncharacterized. We hypothesized that selective CC degeneration is associated with memory impairment in AD and amnestic mild cognitive impairment (aMCI), which is mediated by homotopic inter-hemispheric functional dysconnectivity. Using structural magnetic resonance imaging (MRI) and task-free functional MRI, we assessed the CC volume and inter-hemispheric FC in 66 healthy controls, 41 aMCI and 41 AD. As expected, AD had CC degeneration and attenuated inter-hemispheric homotopic FC. Nevertheless, aMCI had relatively less severe CC degeneration (mainly in mid-anterior, central, and mid-posterior) and no reduction in inter-hemispheric homotopic FC. The degeneration of each CC sub-region was associated with specific inter-hemispheric homotopic functional disconnections in AD and aMCI. More importantly, impairment of inter-hemispheric homotopic FC partially mediated the association between CC (particularly the central and posterior parts) degeneration and memory deficit. Notably, these results remained after controlling for hippocampal volume. Our findings shed light on how CC degeneration and the related inter-hemispheric FC impact memory impairment in early stage of AD.

Sleep: A Novel Mechanistic Pathway, Biomarker, and Treatment Target in the Pathology of Alzheimer's Disease?

Sleep disruption appears to be a core component of Alzheimer's disease (AD) and its pathophysiology. Signature abnormalities of sleep emerge before clinical onset of AD. Moreover, insufficient sleep facilitates accumulation of amyloid-β (Aβ), potentially triggering earlier cognitive decline and conversion to AD. Building on such findings, this review has four goals: evaluating (i) associations and plausible mechanisms linking non-rapid-eye-movement (NREM) sleep disruption, Aβ, and AD; (ii) a role for NREM sleep disruption as a novel factor linking cortical Aβ to impaired hippocampus-dependent memory consolidation; (iii) the potential diagnostic utility of NREM sleep disruption as a new biomarker of AD; and (iv) the possibility of sleep as a new treatment target in aging, affording preventative and therapeutic benefits.

Relative impact of amyloid-β, lacunes, and downstream imaging markers on cognitive trajectories

SEE COHEN DOI101093/AWW183 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Amyloid-β and cerebral small vessel disease are the two major causes of cognitive impairment in the elderly. However, the underlying mechanisms responsible for precisely how amyloid-β and cerebral small vessel disease affect cognitive impairment remain unclear. We investigated the effects of amyloid-β and lacunes on downstream imaging markers including structural network and cortical thickness, further analysing their relative impact on cognitive trajectories. We prospectively recruited a pool of 117 mild cognitive impairment patients (45 amnestic type and 72 subcortical vascular type), from which 83 patients received annual follow-up with neuropsychological tests and brain magnetic resonance imaging for 3 years, and 87 patients received a second Pittsburgh compound B positron emission tomography analysis. Structural networks based on diffusion tensor imaging and cortical thickness were analysed. We used linear mixed effect regression models to evaluate the effects of imaging markers on cognitive decline. Time-varying Pittsburgh compound B uptake was associated with temporoparietal thinning, which correlated with memory decline (verbal memory test, unstandardized β = -0.79, P < 0.001; visual memory test, unstandardized β = -2.84, P = 0.009). Time-varying lacune number was associated with the degree of frontoparietal network disruption or thinning, which further affected frontal-executive function decline (Digit span backward test, unstandardized β = -0.05, P = 0.002; Stroop colour test, unstandardized β = -0.94, P = 0.008). Of the multiple imaging markers analysed, Pittsburgh compound B uptake and the number of lacunes had the greatest association with memory decline and frontal-executive function decline, respectively: Time-varying Pittsburgh compound B uptake (standardized β = -0.25, P = 0.010) showed the strongest effect on visual memory test, followed by time-varying temporoparietal thickness (standardized β = 0.21, P = 0.010) and time-varying nodal efficiency (standardized β = 0.17, P = 0.024). Time-varying lacune number (standardized β = -0.25, P = 0.014) showed the strongest effect on time-varying digit span backward test followed by time-varying nodal efficiency (standardized β = 0.17, P = 0.021). Finally, time-varying lacune number (β = -0.22, P = 0.034) showed the strongest effect on time-varying Stroop colour test followed by time-varying frontal thickness (standardized β = 0.19, P = 0.026). Our multimodal imaging analyses suggest that cognitive trajectories related to amyloid-β and lacunes have distinct paths, and that amyloid-β or lacunes have greatest impact on cognitive decline. Our results provide rationale for the targeting of amyloid-β and lacunes in therapeutic strategies aimed at ameliorating cognitive decline.

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2

INTRODUCTION

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

METHODS

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

RESULTS

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

DISCUSSION

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

Neuroplasticity in response to cognitive behavior therapy for social anxiety disorder

Patients with anxiety disorders exhibit excessive neural reactivity in the amygdala, which can be normalized by effective treatment like cognitive behavior therapy (CBT). Mechanisms underlying the brain's adaptation to anxiolytic treatments are likely related both to structural plasticity and functional response alterations, but multimodal neuroimaging studies addressing structure-function interactions are currently missing. Here, we examined treatment-related changes in brain structure (gray matter (GM) volume) and function (blood-oxygen level dependent, BOLD response to self-referential criticism) in 26 participants with social anxiety disorder randomly assigned either to CBT or an attention bias modification control treatment. Also, 26 matched healthy controls were included. Significant time × treatment interactions were found in the amygdala with decreases both in GM volume (family-wise error (FWE) corrected P(FWE) = 0.02) and BOLD responsivity (P(FWE) = 0.01) after successful CBT. Before treatment, amygdala GM volume correlated positively with anticipatory speech anxiety (P(FWE)=0.04), and CBT-induced reduction of amygdala GM volume (pre-post) correlated positively with reduced anticipatory anxiety after treatment (P(FWE) ⩽ 0.05). In addition, we observed greater amygdala neural responsivity to self-referential criticism in socially anxious participants, as compared with controls (P(FWE) = 0.029), before but not after CBT. Further analysis indicated that diminished amygdala GM volume mediated the relationship between decreased neural responsivity and reduced social anxiety after treatment (P=0.007). Thus, our results suggest that improvement-related structural plasticity impacts neural responsiveness within the amygdala, which could be essential for achieving anxiety reduction with CBT.

Is amyloid-β harmful to the brain? Insights from human imaging studies

Although the amyloid-β protein associated with the Alzheimer's disease plaque has been detectable in living people for over a decade, its importance in the pathogenesis of Alzheimer's disease is still debated. The frequent presence of amyloid-β in the brains of cognitively healthy older people has been interpreted as evidence against a causative role. If amyloid-β is crucial to the development of Alzheimer's disease, it should be associated with other Alzheimer's disease-like neurological changes. This review examines whether amyloid-β is associated with other biomarkers indicative of early Alzheimer's disease in normal older people. The preponderance of evidence links amyloid-β to functional change, progressive brain atrophy, and cognitive decline. Individuals at greatest risk of decline seem to be those with evidence of both amyloid-β and findings suggestive of neurodegeneration. The crucial question is thus how amyloid-β is related to brain degeneration and how these two processes interact to cause cognitive decline and dementia.