Automated mapping of hippocampal atrophy in 1-year repeat MRI data from 490 subjects with Alzheimer's disease, mild cognitive impairment, and elderly controls

Postmortem imaging reveals patterns of medial temporal lobe vulnerability to tau pathology in Alzheimer's disease

Our current understanding of the spread and neurodegenerative effects of tau neurofibrillary tangles (NFTs) within the medial temporal lobe (MTL) during the early stages of Alzheimer's Disease (AD) is limited by the presence of confounding non-AD pathologies and the two-dimensional (2-D) nature of conventional histology studies. Here, we combine ex vivo MRI and serial histological imaging from 25 human MTL specimens to present a detailed, 3-D characterization of quantitative NFT burden measures in the space of a high-resolution, ex vivo atlas with cytoarchitecturally-defined subregion labels, that can be used to inform future in vivo neuroimaging studies. Average maps show a clear anterior to poster gradient in NFT distribution and a precise, spatial pattern with highest levels of NFTs found not just within the transentorhinal region but also the cornu ammonis (CA1) subfield. Additionally, we identify granular MTL regions where measures of neurodegeneration are likely to be linked to NFTs specifically, and thus potentially more sensitive as early AD biomarkers.

A Review of PARP-1 Inhibitors: Assessing Emerging Prospects and Tailoring Therapeutic Strategies

Eukaryotic organisms contain an enzyme family called poly (ADP-ribose) polymerases (PARPs), which is responsible for the poly (ADP-ribosylation) of DNA-binding proteins. PARPs are members of the cell signaling enzyme class. PARP-1, the most common isoform of the PARP family, is responsible for more than 90% of the tasks carried out by the PARP family as a whole. A superfamily consisting of 18 PARPs has been found. In order to synthesize polymers of ADP-ribose (PAR) and nicotinamide, the DNA damage nick monitor PARP-1 requires NAD+ as a substrate. The capability of PARP-1 activation to boost the transcription of proinflammatory genes, its ability to deplete cellular energy pools, which leads to cell malfunction and necrosis, and its involvement as a component in the process of DNA repair are the three consequences of PARP-1 activation that are of particular significance in the process of developing new drugs. As a result, the pharmacological reduction of PARP-1 may result in an increase in the cytotoxicity toward cancer cells.

MR-based spatiotemporal anisotropic atrophy evaluation of hippocampus in Alzheimer's disease progression by multiscale skeletal representation

Increasing evidence has shown a higher sensitivity of Alzheimer's disease (AD) progression by local hippocampal atrophy rather than the whole volume. However, existing morphological methods based on subfield-volume or surface in imaging studies are not capable to describe the comprehensive process of hippocampal atrophy as sensitive as histological findings. To map histological distinctive measurements onto medical magnetic resonance (MR) images, we propose a multiscale skeletal representation (m-s-rep) to quantify focal hippocampal atrophy during AD progression in longitudinal cohorts from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The m-s-rep captures large-to-small-scale hippocampal morphology by spoke interpolation over label projection on skeletal models. To enhance morphological correspondence within subjects, we align the longitudinal m-s-reps by surface-based transformations from baseline to subsequent timepoints. Cross-sectional and longitudinal measurements derived from m-s-rep are statistically analyzed to comprehensively evaluate the bilateral hippocampal atrophy. Our findings reveal that during the early AD progression, atrophy primarily affects the lateral-medial extent of the hippocampus, with a difference of 1.8 mm in lateral-medial width in 2 years preceding conversion (p < .001), and the medial head exhibits a maximum difference of 3.05%/year in local atrophy rate (p = .011) compared to controls. Moreover, progressive mild cognitive impairment (pMCI) exhibits more severe and widespread atrophy in the head and body compared to stable mild cognitive impairment (sMCI), with a maximum difference of 1.21 mm in thickness in the medial head 1 year preceding conversion (p = .012). In summary, our proposed method can quantitatively measure the hippocampal morphological changes on 3T MR images, potentially assisting the pre-diagnosis and prognosis of AD.

Classification of Alzheimer's disease based on hippocampal multivariate morphometry statistics

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive cognitive decline, and mild cognitive impairment (MCI) is associated with a high risk of developing AD. Hippocampal morphometry analysis is believed to be the most robust magnetic resonance imaging (MRI) markers for AD and MCI. Multivariate morphometry statistics (MMS), a quantitative method of surface deformations analysis, is confirmed to have strong statistical power for evaluating hippocampus.

AIMS

We aimed to test whether surface deformation features in hippocampus can be employed for early classification of AD, MCI, and healthy controls (HC).

METHODS

We first explored the differences in hippocampus surface deformation among these three groups by using MMS analysis. Additionally, the hippocampal MMS features of selective patches and support vector machine (SVM) were used for the binary classification and triple classification.

RESULTS

By the results, we identified significant hippocampal deformation among the three groups, especially in hippocampal CA1. In addition, the binary classification of AD/HC, MCI/HC, AD/MCI showed good performances, and area under curve (AUC) of triple-classification model achieved 0.85. Finally, positive correlations were found between the hippocampus MMS features and cognitive performances.

CONCLUSIONS

The study revealed significant hippocampal deformation among AD, MCI, and HC. Additionally, we confirmed that hippocampal MMS can be used as a sensitive imaging biomarker for the early diagnosis of AD at the individual level.

A Tutorial for Speech-Language Pathologists: Physical Activity and Social Engagement to Prevent or Slow Cognitive Decline in Older Adults

PURPOSE

This tutorial provides an overview of two behavioral approaches, physical activity and social engagement, to prevent or slow cognitive decline in older adults and to increase awareness in the field of speech-language pathology of the important role that speech-language pathologists (SLPs) play in an interprofessional team working with this population.

METHOD

A review of exercise science, neuroscience, and social science literature was used to synthesize evidence and to outline the impact of physical activity and social engagement on cognition. The following topics were explored: How do exercise and social engagement support cognition? What are modifiable risk factors of dementia? What is the impact of inactivity and isolation on cognition? What is the potential role of the SLP on an interprofessional team focusing on preventive measures for cognitive decline? What is the impact of physical exercise and social engagement on nursing home residents?

RESULTS

Research increasingly points to the critical importance of physical activity and social engagement to prevent cognitive decline in normal aging and to slow cognitive decline associated with mild cognitive impairment and dementia. Research suggests that physical activity maintains or improves memory, attention, executive function, visuospatial function, speed of processing, and general cognitive function. Social engagement has been found to maintain and improve general cognitive function.

CONCLUSIONS

Behavioral interventions are an effective strategy to prevent or slow cognitive decline in the older adult population. SLPs have a role to play on an interprofessional team that works to prevent cognitive decline. By considering factors that play a role in the prevention of cognitive decline, such as physical activity and social engagement, the quality of life and overall health of older adults can be improved. Areas of improvement include memory, attention, executive function, visuospatial function, speed of processing, and general cognitive function.

Association Between Hippocampal Volume and African Neuropsychology Memory Tests in Adult Individuals with Probable Alzheimer's Disease in Democratic Republic of Congo

BACKGROUND

Western studies indicate potential associations between hippocampal volume and memory in the trajectory of Alzheimer's disease (AD). However, limited availability of neuroimaging technology and neuropsychological tests appropriate for sub-Saharan African (SSA) countries makes it difficult to establish neuroanatomical associations of hippocampus and memory in this locale.

OBJECTIVE

This study examined hippocampal volumes and memory in healthy control (HC) and probable AD groups in the Democratic Republic of Congo (DRC).

METHODS

Forty-six subjects with probable AD and 29 HC subjects were screened using the Community Instrument for Dementia and the Alzheimer Questionnaire. Participants underwent neuroimaging in Kinshasa, DRC, and memory was evaluated using the African Neuropsychology Battery (ANB). Multiple linear regression was used to determine associations between hippocampal volumes and memory.

RESULTS

Patients with probable AD performed significantly worse than HCs on ANB memory measures, and exhibited greater cerebral atrophy, which was significantly pronounced in the medial temporal lobe region (hippocampus, entorhinal cortex). Both AD and HC subjects exhibited high rates of white matter hyperintensities compared to international base rate prevalence, which was significantly worse for probable AD. Both also exhibited elevated rates of microhemorrhages. Regression analysis demonstrated a significant association between hippocampal volume and ANB memory tests. Hippocampal atrophy discriminated probable AD from the HC group.

CONCLUSIONS

This study establishes the feasibility of conducting neuroimaging research in the SSA, demonstrates many known neuroimaging findings in probable AD patients hold up using culturally appropriate memory tasks, and suggest cardiovascular problems are a greater issue in SSA than in Western countries.

Sub-mm resolution tomographic imaging in turbid media by an ultra-high density multichannel approach

We demonstrate an ultra-high-density source-detector (SD) diffuse optical tomography system scalable to thousands of combinatorial SD pairs per cm3 of total voxel volume. We demonstrate the imaging of dynamic targets (including phantom arteries) with 100 um resolution at over 10 Hz frame rate within turbid media (> 60 MFP). Further, as a step toward a wearable mobile imager, we introduce monolithic mm-size dense semiconductor laser array chips as sources for potential unobtrusive epidermal tomographic use.

LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures

Over the past 30 years, magnetic resonance imaging has become a ubiquitous tool for accurately visualizing the change and development of the brain's subcortical structures (e.g., hippocampus). Although subcortical structures act as information hubs of the nervous system, their quantification is still in its infancy due to many challenges in shape extraction, representation, and modeling. Here, we develop a simple and efficient framework of longitudinal elastic shape analysis (LESA) for subcortical structures. Integrating ideas from elastic shape analysis of static surfaces and statistical modeling of sparse longitudinal data, LESA provides a set of tools for systematically quantifying changes of longitudinal subcortical surface shapes from raw structure MRI data. The key novelties of LESA include: (i) it can efficiently represent complex subcortical structures using a small number of basis functions and (ii) it can accurately delineate the spatiotemporal shape changes of the human subcortical structures. We applied LESA to analyze three longitudinal neuroimaging data sets and showcase its wide applications in estimating continuous shape trajectories, building life-span growth patterns, and comparing shape differences among different groups. In particular, with the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, we found that the Alzheimer's Disease (AD) can significantly speed the shape change of ventricle and hippocampus from 60 to 75 years old compared with normal aging.

Automated High-Definition MRI Processing Routine Robustly Detects Longitudinal Morphometry Changes in Alzheimer's Disease Patients

Longitudinal MRI studies are of increasing importance to document the time course of neurodegenerative diseases as well as neuroprotective effects of a drug candidate in clinical trials. However, manual longitudinal image assessments are time consuming and conventional assessment routines often deliver unsatisfying study outcomes. Here, we propose a profound analysis pipeline that consists of the following coordinated steps: (1) an automated and highly precise image processing stream including voxel and surface based morphometry using latest highly detailed brain atlases such as the HCP MMP 1.0 atlas with 360 cortical ROIs; (2) a profound statistical assessment using a multiplicative model of annual percent change (APC); and (3) a multiple testing correction adopted from genome-wide association studies that is optimally suited for longitudinal neuroimaging studies. We tested this analysis pipeline with 25 Alzheimer's disease patients against 25 age-matched cognitively normal subjects with a baseline and a 1-year follow-up conventional MRI scan from the ADNI-3 study. Even in this small cohort, we were able to report 22 significant measurements after multiple testing correction from SBM (including cortical volume, area and thickness) complementing only three statistically significant volume changes (left/right hippocampus and left amygdala) found by VBM. A 1-year decrease in brain morphometry coincided with an increasing clinical disability and cognitive decline in patients measured by MMSE, CDR GLOBAL, FAQ TOTAL and NPI TOTAL scores. This work shows that highly precise image assessments, APC computation and an adequate multiple testing correction can produce a significant study outcome even for small study sizes. With this, automated MRI processing is now available and reliable for routine use and clinical trials.

Sex Modifies the Associations of APOEɛ4 with Neuropsychiatric Symptom Burden in Both At-Risk and Clinical Cohorts of Alzheimer's Disease

BACKGROUND

Recent work suggests that APOEɛ4/4 females with Alzheimer's disease (AD) are more susceptible to developing neuropsychiatric symptoms (NPS).

OBJECTIVE

To examine the interaction of sex and APOEɛ4 status on NPS burden using two independent cohorts: 1) patients at risk for AD with mild cognitive impairment and/or major depressive disorder (n = 252) and 2) patients with probable AD (n = 7,261).

METHODS

Regression models examined the interactive effects of sex and APOEɛ4 on the number of NPS experienced and NPS Severity. APOEɛ3/4 and APOEɛ4/4 were pooled in the at-risk cohort due to the sample size.

RESULTS

In the at-risk cohort, there was a significant sex*APOEɛ4 interaction (p = 0.007) such that the association of APOEɛ4 with NPS was greater in females than in males (incident rate ratio (IRR) = 2.0). APOEɛ4/4 females had the most NPS (mean = 1.9) and the highest severity scores (mean = 3.5) of any subgroup. In the clinical cohort, APOEɛ4/4 females had significantly more NPS (IRR = 1.1, p = 0.001, mean = 3.1) and higher severity scores (b = 0.31, p = 0.015, mean = 3.7) than APOEɛ3/3 females (meanNPS = 2.9, meanSeverity = 3.3). No association was found in males.

CONCLUSION

Our study suggests that sex modifies the association of APOEɛ4 on NPS burden. APOEɛ4/4 females may be particularly susceptible to increased NPS burden among individuals with AD and among individuals at risk for AD. Further investigation into the mechanisms behind these associations are needed.

Studying APOE ɛ4 Allele Dose Effects with a Univariate Morphometry Biomarker

BACKGROUND

A univariate neurodegeneration biomarker (UNB) based on MRI with strong statistical discrimination power would be highly desirable for studying hippocampal surface morphological changes associated with APOE ɛ4 genetic risk for AD in the cognitively unimpaired (CU) population. However, existing UNB work either fails to model large group variances or does not capture AD induced changes.

OBJECTIVE

We proposed a subspace decomposition method capable of exploiting a UNB to represent the hippocampal morphological changes related to the APOE ɛ4 dose effects among the longitudinal APOE ɛ4 homozygotes (HM, N = 30), heterozygotes (HT, N = 49) and non-carriers (NC, N = 61).

METHODS

Rank minimization mechanism combined with sparse constraint considering the local continuity of the hippocampal atrophy regions is used to extract group common structures. Based on the group common structures of amyloid-β (Aβ) positive AD patients and Aβ negative CU subjects, we identified the regions-of-interest (ROI), which reflect significant morphometry changes caused by the AD development. Then univariate morphometry index (UMI) is constructed from these ROIs.

RESULTS

The proposed UMI demonstrates a more substantial statistical discrimination power to distinguish the longitudinal groups with different APOE ɛ4 genotypes than the hippocampal volume measurements. And different APOE ɛ4 allele load affects the shrinkage rate of the hippocampus, i.e., HM genotype will cause the largest atrophy rate, followed by HT, and the smallest is NC.

CONCLUSION

The UMIs may capture the APOE ɛ4 risk allele-induced brain morphometry abnormalities and reveal the dose effects of APOE ɛ4 on the hippocampal morphology in cognitively normal individuals.

The association between hippocampal volume and memory in pathological aging is mediated by functional redundancy

Hippocampal neurodegeneration, a primary component of Alzheimer's disease pathology, relates to poor cognition; however, the mechanisms underlying this relationship are not well understood. Using a sample of cognitively normal older adults and individuals with mild cognitive impairment, this study aims to determine the topological properties of functional networks accompanying hippocampal atrophy in aging, along with their association to cognition and clinical progression. We considered two conceptually differing topological properties: redundancy (the existence of alternative channels of functional commutation) and local efficiency (the efficiency of local information exchange). Hippocampal redundancy, but not local efficiency, mediated the association between low hippocampal volume and low memory in both the whole sample and in ß-amyloid positive participants. Additionally, participants with high hippocampal volume, redundancy, and memory clustered separately from those with low values on all three measures, with the latter group showing higher conversion rates to dementia within three years. Together, these results demonstrate that reduced hippocampal redundancy is one mechanism through which hippocampal atrophy associates with memory impairment in healthy and pathological aging.

Hippocampal single-voxel MR spectroscopy with a long echo time at 3 T using semi-LASER sequence

The hippocampus is one of the most challenging brain regions for proton MR spectroscopy (MRS) applications. Moreover, quantification of J-coupled species such as myo-inositol (m-Ins) and glutamate + glutamine (Glx) is affected by the presence of macromolecular background. While long echo time (TE) MRS eliminates the macromolecules, it also decreases the m-Ins and Glx signal and, as a result, these metabolites are studied mainly with short TE. Here, we investigate the feasibility of reproducibly measuring their concentrations at a long TE of 120 ms, using a semi-adiabatic localization by adiabatic selective refocusing (sLASER) sequence, as this sequence was recently recommended as a standard for clinical MRS. Gradient offset-independent adiabatic refocusing pulses were implemented, and an optimal long TE for the detection of m-Ins and Glx was determined using the T2 relaxation times of macromolecules. Metabolite concentrations and their coefficients of variation (CVs) were obtained for a 3.4-mL voxel centered on the left hippocampus on 3-T MR systems at two different sites with three healthy subjects (aged 32.5 ± 10.2 years [mean ± standard deviation]) per site, with each subject scanned over two sessions, and with each session comprising three scans. Concentrations of m-Ins, choline, creatine, Glx and N-acetyl-aspartate were 5.4 ± 1.5, 1.7 ± 0.2, 5.8 ± 0.3, 11.6 ± 1.2 and 5.9 ± 0.4 mM (mean ± standard deviation), respectively. Their respective mean within-session CVs were 14.5% ± 5.9%, 6.5% ± 5.3%, 6.0% ± 3.4%, 10.6% ± 6.2% and 3.5% ± 1.4%, and their mean within-subject CVs were 17.8% ± 18.2%, 7.5% ± 6.3%, 7.4% ± 6.4%, 12.4% ± 5.3% and 4.8% ± 3.0%. The between-subject CVs were 25.0%, 12.3%, 5.3%, 10.7% and 6.4%, respectively. Hippocampal long-TE sLASER single voxel spectroscopy can provide macromolecule-independent assessment of all major metabolites including Glx and m-Ins.

Early Detection of Alzheimer's Disease Based on Clinical Trials, Three-Dimensional Imaging Data, and Personal Information Using Autoencoders

Background:

A timely diagnosis of Alzheimer's disease (AD) is crucial to obtain more practical treatments. In this article, a novel approach using Auto-Encoder Neural Networks (AENN) for early detection of AD was proposed.

Method:

The proposed method mainly deals with the classification of multimodal data and the imputation of missing data. The data under study involve the MiniMental State Examination, magnetic resonance imaging, positron emission tomography, cerebrospinal fluid data, and personal information. Natural logarithm was used for normalizing the data. The Auto-Encoder Neural Networks was used for imputing missing data. Principal component analysis algorithm was used for reducing dimensionality of data. Support Vector Machine (SVM) was used as classifier. The proposed method was evaluated using Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Then, 10fold crossvalidation was used to audit the detection accuracy of the method.

Results:

The effectiveness of the proposed approach was studied under several scenarios considering 705 cases of ADNI database. In three binary classification problems, that is AD vs. normal controls (NCs), mild cognitive impairment (MCI) vs. NC, and MCI vs. AD, we obtained the accuracies of 95.57%, 83.01%, and 78.67%, respectively.

Conclusion:

Experimental results revealed that the proposed method significantly outperformed most of the stateoftheart methods.

Early Stage Longitudinal Subcortical Volumetric Changes following Mild Traumatic Brain Injury

Objective: To investigate early brain volumetric changes from acute to 6 months following mild traumatic brain injury (mTBI) in deep gray matter regions and their association with patient 6-month outcome.Methods: Fifty-six patients with mTBI underwent MRI and behavioral evaluation at acute (<10 days) and approximately 1 and 6 months post injury. Regional volume changes were investigated in key gray matter regions: thalamus, hippocampus, putamen, caudate, pallidum, and amygdala, and compared with volumes from 34 healthy control subjects. In patients with mTBI, we further assessed associations between longitudinal regional volume changes with patient outcome measures at 6 months including post-concussive symptoms, cognitive performance, and overall satisfaction with life.Results: Reduction in thalamic and hippocampal volumes was observed at 1 month among patients with mTBI. Such volume reduction persisted in the thalamus until 6 months. Changes in thalamic volumes also correlated with multiple symptom and functional outcome measures in patients at 6 months.Conclusion: Our results indicate that the thalamus may be differentially affected among patients with mTBI, resulting in both structural and functional deficits with subsequent post-concussive sequelae and may serve as a biomarker for the assessment of efficacy of novel therapeutic interventions.

Reduced Hippocampal Glutamate and Posterior Cingulate N-Acetyl Aspartate in Mild Cognitive Impairment and Alzheimer's Disease Is Associated with Episodic Memory Performance and White Matter Integrity in the Cingulum: A Pilot Study

Identification of biological changes underlying the early symptoms of Alzheimer's disease (AD) will help to identify and stage individuals prior to symptom onset. The limbic system, which supports episodic memory and is impaired early in AD, is a primary target. In this study, brain metabolism and microstructure evaluated by high field (7 Tesla) proton magnetic resonance spectroscopy (1H-MRS) and diffusion tensor imaging (DTI) were evaluated in the limbic system of eight individuals with mild cognitive impairment (MCI), nine with AD, and sixteen normal elderly controls (NEC). Left hippocampal glutamate and posterior cingulate N-acetyl aspartate concentrations were reduced in MCI and AD compared to NEC. Differences in DTI metrics indicated volume and white matter loss along the cingulum in AD compared to NEC. Metabolic and microstructural changes were associated with episodic memory performance assessed using Craft Story 21 Recall and Benson Complex Figure Copy. The current study suggests that metabolite concentrations measured using 1H-MRS may provide insight into the underlying metabolic and microstructural processes of episodic memory impairment.

Longitudinal trajectories of hippocampal volume in middle to older age community dwelling individuals

Understanding heterogeneity in brain aging trajectories is important to estimate the extent to which aging outcomes can be optimized. Although brain changes in late life are well-characterized, brain changes in middle age are not well understood. In this study, we investigated hippocampal change in a generally healthy community-living population of middle (n = 421, mean age 47.2 years) and older age (n = 411, mean age 63.0 years) individuals, over a follow-up of up to 12 years. Manually traced hippocampal volumes were analyzed using multilevel models and latent class analysis to investigate longitudinal aging trajectories and laterality and sex effects, and to identify subgroups that follow different aging trajectories. Hippocampal volumes decreased on average by 0.18%/year in middle age and 0.3%/year in older age. Men tended to experience steeper declines than women in middle age only. Three subgroups of individuals following different trajectories were identified in middle age and 2 in older age. Contrary to expectations, the subgroup containing two-thirds of older age participants maintained stable hippocampal volumes across the follow-up.

Nonlinear interaction between APOE ε4 allele load and age in the hippocampal surface of cognitively intact individuals

The ε4 allele of the gene Apolipoprotein E is the major genetic risk factor for Alzheimer's Disease. APOE ε4 has been associated with changes in brain structure in cognitively impaired and unimpaired subjects, including atrophy of the hippocampus, which is one of the brain structures that is early affected by AD. In this work we analyzed the impact of APOE ε4 gene dose and its association with age, on hippocampal shape assessed with multivariate surface analysis, in a ε4‐enriched cohort of n = 479 cognitively healthy individuals. Furthermore, we sought to replicate our findings on an independent dataset of n = 969 individuals covering the entire AD spectrum. We segmented the hippocampus of the subjects with a multi‐atlas‐based approach, obtaining high‐dimensional meshes that can be analyzed in a multivariate way. We analyzed the effects of different factors including APOE, sex, and age (in both cohorts) as well as clinical diagnosis on the local 3D hippocampal surface changes. We found specific regions on the hippocampal surface where the effect is modulated by significant APOE ε4 linear and quadratic interactions with age. We compared between APOE and diagnosis effects from both cohorts, finding similarities between APOE ε4 and AD effects on specific regions, and suggesting that age may modulate the effect of APOE ε4 and AD in a similar way.

Longitudinal atrophy in early Braak regions in preclinical Alzheimer's disease

A major focus of Alzheimer's disease (AD) research has been finding sensitive outcome measures to disease progression in preclinical AD, as intervention studies begin to target this population. We hypothesize that tailored measures of longitudinal change of the medial temporal lobe (MTL) subregions (the sites of earliest cortical tangle pathology) are more sensitive to disease progression in preclinical AD compared to standard cognitive and plasma NfL measures. Longitudinal T1-weighted MRI of 337 participants were included, divided into amyloid-β negative (Aβ-) controls, cerebral spinal fluid p-tau positive (T+) and negative (T-) preclinical AD (Aβ+ controls), and early prodromal AD. Anterior/posterior hippocampus, entorhinal cortex, Brodmann areas (BA) 35 and 36, and parahippocampal cortex were segmented in baseline MRI using a novel pipeline. Unbiased change rates of subregions were estimated using MRI scans within a 2-year-follow-up period. Experimental results showed that longitudinal atrophy rates of all MTL subregions were significantly higher for T+ preclinical AD and early prodromal AD than controls, but not for T- preclinical AD. Posterior hippocampus and BA35 demonstrated the largest group differences among hippocampus and MTL cortex respectively. None of the cross-sectional MTL measures, longitudinal cognitive measures (PACC, ADAS-Cog) and cross-sectional or longitudinal plasma NfL reached significance in preclinical AD. In conclusion, longitudinal atrophy measurements reflect active neurodegeneration and thus are more directly linked to active disease progression than cross-sectional measurements. Moreover, accelerated atrophy in preclinical AD seems to occur only in the presence of concomitant tau pathology. The proposed longitudinal measurements may serve as efficient outcome measures in clinical trials.

Anti-inflammatories in Alzheimer's disease-potential therapy or spurious correlate?

Epidemiological evidence suggests non-steroidal anti-inflammatory drugs reduce the risk of Alzheimer’s disease. However, clinical trials have found no evidence of non-steroidal anti-inflammatory drug efficacy. This incongruence may be due to the wrong non-steroidal anti-inflammatory drugs being tested in robust clinical trials or the epidemiological findings being caused by confounding factors. Therefore, this study used logistic regression and the innovative approach of negative binomial generalized linear mixed modelling to investigate both prevalence and cognitive decline, respectively, in the Alzheimer’s Disease Neuroimaging dataset for each commonly used non-steroidal anti-inflammatory drug and paracetamol. Use of most non-steroidal anti-inflammatories was associated with reduced Alzheimer’s disease prevalence yet no effect on cognitive decline was observed. Paracetamol had a similar effect on prevalence to these non-steroidal anti-inflammatory drugs suggesting this association is independent of the anti-inflammatory effects and that previous results may be due to spurious associations. Interestingly, diclofenac use was significantly associated with both reduce incidence and slower cognitive decline warranting further research into the potential therapeutic effects of diclofenac in Alzheimer’s disease.

Brain structure changes over time in normal and mildly impaired aged persons

Structural brain changes in aging are known to occur even in the absence of dementia, but the magnitudes and regions involved vary between studies. To further characterize these changes, we analyzed paired MRI images acquired with identical protocols and scanner over a median 5.8-year interval. The normal study group comprised 78 elders (25M 53F, baseline age range 70–78 years) who underwent an annual standardized expert assessment of cognition and health and who maintained normal cognition for the duration of the study. We found a longitudinal grey matter (GM) loss rate of 2.56 ± 0.07 ml/year (0.20 ± 0.04%/year) and a cerebrospinal fluid (CSF) expansion rate of 2.97 ± 0.07 ml/year (0.22 ± 0.04%/year). Hippocampal volume loss rate was higher than the GM and CSF global rates, 0.0114 ± 0.0004 ml/year (0.49 ± 0.04%/year). Regions of greatest GM loss were posterior inferior frontal lobe, medial parietal lobe and dorsal cerebellum. Rates of GM loss and CSF expansion were on the low end of the range of other published values, perhaps due to the relatively good health of the elder volunteers in this study. An additional smaller group of 6 subjects diagnosed with MCI at baseline were followed as well, and comparisons were made with the normal group in terms of both global and regional GM loss and CSF expansion rates. An increased rate of GM loss was found in the hippocampus bilaterally for the MCI group.

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.

Emphasis Learning, Features Repetition in Width Instead of Length to Improve Classification Performance: Case Study-Alzheimer's Disease Diagnosis

In the past decade, many studies have been conducted to advance computer-aided systems for Alzheimer's disease (AD) diagnosis. Most of them have recently developed systems concentrated on extracting and combining features from MRI, PET, and CSF. For the most part, they have obtained very high performance. However, improving the performance of a classification problem is complicated, specifically when the model's accuracy or other performance measurements are higher than 90%. In this study, a novel methodology is proposed to address this problem, specifically in Alzheimer's disease diagnosis classification. This methodology is the first of its kind in the literature, based on the notion of replication on the feature space instead of the traditional sample space. Briefly, the main steps of the proposed method include extracting, embedding, and exploring the best subset of features. For feature extraction, we adopt VBM-SPM; for embedding features, a concatenation strategy is used on the features to ultimately create one feature vector for each subject. Principal component analysis is applied to extract new features, forming a low-dimensional compact space. A novel process is applied by replicating selected components, assessing the classification model, and repeating the replication until performance divergence or convergence. The proposed method aims to explore most significant features and highest-preforming model at the same time, to classify normal subjects from AD and mild cognitive impairment (MCI) patients. In each epoch, a small subset of candidate features is assessed by support vector machine (SVM) classifier. This repeating procedure is continued until the highest performance is achieved. Experimental results reveal the highest performance reported in the literature for this specific classification problem. We obtained a model with accuracies of 98.81%, 81.61%, and 81.40% for AD vs. normal control (NC), MCI vs. NC, and AD vs. MCI classification, respectively.

The Specific Impact of Apolipoprotein E Epsilon 2 on Cognition and Brain Function in Cognitively Normal Elders and Mild Cognitive Impairment Patients

Variants in the apolipoprotein E (APOE) gene play an important role in the development of Alzheimer’s disease (AD). Specifically, the APOE ε4 allele is an established genetic risk factor for AD, while the APOE ε2 allele is a protective factor against AD. However, the mechanism underlying this impact of APOE genotype on the pathogenesis of AD remain unclear. This study sought to investigate the influence of APOE genotype on cognition and neuroimaging features in cognitively normal (CN) elderly individuals and patients with mild cognitive impairment (MCI). A total of 177 participants were selected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, including 101 MCI patients and 76 CN individuals. A 2 × 3 (consisting of two groups and three APOE genotypes) analysis of covariance was carried out to measure the influences of diagnosis and APOE genotype on cognition and brain features, assessed based on global functional connectivity density (gFCD) and hippocampal volume. In addition, a mediation analysis was carried out to investigate the indirect influence of neuroimaging features on the relationship between APOE genotype and cognitive performance in the MCI group. This analysis revealed that APOE genotype had an influence on brain function in the bilateral precentral gyrus, right thalamus, and posterior cingulate cortex (PCC). In addition, an interactive influence between diagnosis and APOE genotype was found on general cognition, immediate memory, executive function, hippocampal volume, and gFCD in the right dorsolateral prefrontal cortex and medial prefrontal cortex (MPFC). Finally, this mediation analysis revealed that hippocampal volume and gFCD in the thalamus may mediate the relationship between APOE genotype and cognitive performance in the MCI group. Taken together, our findings provide novel insights into the neural mechanisms underlying the genetically guided pathogenic mechanisms of AD.

Identifying Morphological Patterns of Hippocampal Atrophy in Patients With Mesial Temporal Lobe Epilepsy and Alzheimer Disease

Purpose: Mesial temporal lobe epilepsy (MTLE) and Alzheimer's disease (AD) are two distinct neurological disorders associated with hippocampal atrophy. Our goal is to analyze the morphologic patterns of hippocampal atrophy to better understand the underlying pathological and clinical characteristics of the two conditions.

Methods: Twenty-five patients with AD and 20 healthy controls with matched age and gender were recruited into the AD group. Twenty-three MTLE patients and 28 healthy controls with matched age and gender were recruited into the MTLE group. All subjects were scanned on 3T-MRI scanner. Automated volumetric analysis was applied to measure and compare the hippocampal volume of the two respective groups. Vertex-based morphologic analysis was applied to characterize the morphologic patterns of hippocampal atrophy within and between groups, and a correlation analysis was performed.

Results: Volumetric analysis revealed significantly decreased hippocampal volume in both AD and MTLE patients compared to the controls. In the patients with AD, the mean total hippocampal volume was 32.70% smaller than that of healthy controls, without a significant difference between the left and the right hippocampus (p < 0.05). In patients with MTLE, a significant reduction in unilateral hippocampal volume was observed, with a mean volume reduction of 28.38% as compared with healthy controls (p < 0.05). Vertex-based morphologic analysis revealed a generalized shrinkage of the hippocampi in AD patients, especially in bilateral medial and lateral regions. In MTLE group, atrophy was seen in the ipsilateral head, ipsilateral lateral body and slightly contralateral tail of the hippocampus (FWE-corrected, p < 0.05).

Conclusions: MTLE and AD have distinctive morphologic patterns of hippocampal atrophy, which provide new insight into the radiology-pathology correlation in these diseases.

Electrophysiological Processes on Motor Imagery Mediate the Association Between Increased Gray Matter Volume and Cognition in Amnestic Mild Cognitive Impairment

Motor imagery is considered as an ideal window to observe neural processes of action representations. Behavioral evidence has indicated an alteration of motor imagery in amnestic mild cognitive impairment (aMCI). However, it still remains unclear on the altered neurophysiological processing mechanism of motor imagery and whether this mechanism links the abnormal biological basis of motor imagery with impaired cognition in aMCI. This study was to investigate the altered neurophysiological processing mechanism of motor imagery and to examine the relationships between this knowledge and the altered structural basis of motor imagery with impaired cognition in aMCI. A hand mental rotation paradigm was used to manipulate the processing of motor imagery while event-related brain potentials (ERPs) were recorded and gray matter (GM) voxel-based morphometry was performed in 20 aMCI and 29 healthy controls. Compared with controls, aMCI exhibited lower ERP amplitudes in parietal cortex and higher ERP amplitudes in frontal cortex during motor imagery. In addition, aMCI showed reduced GM volumes in cerebellum posterior lobe, insula and hippocampus/parahippocampal gyrus, and increased GM volumes in middle cingulate gyrus and superior frontal gyrus. Most importantly, increased ERP amplitude significantly mediated the association between increased GM and cognition. This study provided a novel evidence for the relationships between the electrophysiological processing mechanism and structural basis of motor imagery with impaired cognition in aMCI. It suggests that improving neural activity by stimulating the frontal lobe can potentially contribute to acquire motor imagery skills for neurological rehabilitation in aMCI subjects.

Cognitive Correlates of Hippocampal Atrophy and Ventricular Enlargement in Adults with or without Mild Cognitive Impairment

We analyzed structural magnetic resonance imaging data from 58 cognitively normal and 101 mild cognitive impairment subjects. We used a general linear regression model to study the association between cognitive performance with hippocampal atrophy and ventricular enlargement using the radial distance method. Bilateral hippocampal atrophy was associated with baseline and longitudinal memory performance. Left hippocampal atrophy predicted longitudinal decline in visuospatial function. The multidomain ventricular analysis did not reveal any significant predictors.

Spatially Regularized Shape Analysis of the Hippocampus Using P-Spline Based Shape Regression

Shape analysis is increasingly becoming important to study changes in brain structures in relation to clinical neurological outcomes. This is a challenging task due to the high dimensionality of shape representations and the often limited number of available shapes. Current techniques counter the poor ratio between dimensions and sample size by using regularization in shape space, but do not take into account the spatial relations within the shapes. This can lead to models that are biologically implausible and difficult to interpret. We propose to use P-spline based regression, which combines a generalized linear model (GLM) with the coefficients described as B-splines and a penalty term that constrains the regression coefficients to be spatially smooth. Owing to the GLM, this method can naturally predict both continuous and discrete outcomes and can include non-spatial covariates without penalization. We evaluated our method on hippocampus shapes extracted from magnetic resonance (MR) images of 510 non-demented, elderly people. We related the hippocampal shape to age, memory score, and sex. The proposed method retained the good performance of current techniques, such as ridge regression, but produced smoother coefficient fields that are easier to interpret.

Applying surface-based hippocampal morphometry to study APOE-E4 allele dose effects in cognitively unimpaired subjects

Apolipoprotein E (APOE) e4 is the major genetic risk factor for late-onset Alzheimer's disease (AD). The dose-dependent impact of this allele on hippocampal volumes has been documented, but its influence on general hippocampal morphology in cognitively unimpaired individuals is still elusive. Capitalizing on the study of a large number of cognitively unimpaired late middle aged and older adults with two, one and no APOE-e4 alleles, the current study aims to characterize the ability of our automated surface-based hippocampal morphometry algorithm to distinguish between these three levels of genetic risk for AD and demonstrate its superiority to a commonly used hippocampal volume measurement. We examined the APOE-e4 dose effect on cross-sectional hippocampal morphology analysis in a magnetic resonance imaging (MRI) database of 117 cognitively unimpaired subjects aged between 50 and 85 years (mean = 57.4, SD = 6.3), including 36 heterozygotes (e3/e4), 37 homozygotes (e4/e4) and 44 non-carriers (e3/e3). The proposed automated framework includes hippocampal surface segmentation and reconstruction, higher-order hippocampal surface correspondence computation, and hippocampal surface deformation analysis with multivariate statistics. In our experiments, the surface-based method identified APOE-e4 dose effects on the left hippocampal morphology. Compared to the widely-used hippocampal volume measure, our hippocampal morphometry statistics showed greater statistical power by distinguishing cognitively unimpaired subjects with two, one, and no APOE-e4 alleles. Our findings mirrored previous studies showing that APOE-e4 has a dose effect on the acceleration of brain structure deformities. The results indicated that the proposed surface-based hippocampal morphometry measure is a potential preclinical AD imaging biomarker for cognitively unimpaired individuals.

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Applied surface-based hippocampal morphometry on cognitively unimpaired subjects.

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Our study identified APOE-e4 dose effects on cognitively unimpaired subjects.

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Surface-based hippocampal morphometry outperformed the hippocampal volume measure.

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Surface-based hippocampal morphometry may be a potential preclinical AD biomarker.

Reduced Gray Matter Volume of the Thalamus and Hippocampal Region in Elderly Healthy Adults with no Impact of APOE ɛ4: A Longitudinal Voxel-Based Morphometry Study

BACKGROUND

Many cross-sectional voxel-based morphometry (VBM) investigations have shown significant inverse correlations between chronological age and gray matter (GM) volume in several brain regions in healthy humans. However, few VBM studies have documented GM decrements in the healthy elderly with repeated MRI measurements obtained in the same subjects. Also, the extent to which the APOE ɛ4 allele influences longitudinal findings of GM reduction in the healthy elderly is unclear.

OBJECTIVE

Verify whether regional GM changes are associated with significant decrements in cognitive performance taking in account the presence of the APOE ɛ4 allele.

METHODS

Using structural MRI datasets acquired in 55 cognitively intact elderly subjects at two time-points separated by approximately three years, we searched for voxels showing significant GM reductions taking into account differences in APOE genotype.

RESULTS

We found global GM reductions as well as regional GM decrements in the right thalamus and left parahippocampal gyrus (p < 0.05, family-wise error corrected for multiple comparisons over the whole brain). These findings were not affected by APOE ɛ4.

CONCLUSIONS

Irrespective of APOE ɛ4, longitudinal VBM analyses show that the hippocampal region and thalamus are critical sites where GM shrinkage is greater than the degree of global volume reduction in healthy elderly subjects.

Biomarkers in Neurodegenerative Diseases

The past decade has seen tremendous efforts in biomarker discovery and validation for neurodegenerative diseases. The source and type of biomarkers has continued to grow for central nervous system diseases, from biofluid-based biomarkers (blood or cerebrospinal fluid (CSF)), to nucleic acids, tissue, and imaging. While DNA remains a predominant biomarker used to identify familial forms of neurodegenerative diseases, various types of RNA have more recently been linked to familial and sporadic forms of neurodegenerative diseases during the past few years. Imaging approaches continue to evolve and are making major contributions to target engagement and early diagnostic biomarkers. Incorporation of biomarkers into drug development and clinical trials for neurodegenerative diseases promises to aid in the development and demonstration of target engagement and drug efficacy for neurologic disorders. This review will focus on recent advancements in developing biomarkers for clinical utility in Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS).

Automated and manual hippocampal segmentation techniques: Comparison of results, reproducibility and clinical applicability

BACKGROUND

Imaging techniques used to measure hippocampal atrophy are key to understanding the clinical progression of Alzheimer's disease (AD). Various semi-automated hippocampal segmentation techniques are available and require human expert input to learn how to accurately segment new data. Our goal was to compare 1) the performance of our automated hippocampal segmentation technique relative to manual segmentations, and 2) the performance of our automated technique when provided with a training set from two different raters. We also explored the ability of hippocampal volumes obtained using manual and automated hippocampal segmentations to predict conversion from MCI to AD.

METHODS

We analyzed 161 1.5 T T1-weighted brain magnetic resonance images (MRI) from the ADCS Donepezil/Vitamin E clinical study. All subjects carried a diagnosis of mild cognitive impairment (MCI). Three different segmentation outputs (one produced by manual tracing and two produced by a semi-automated algorithm trained with training sets developed by two raters) were compared using single measure intraclass correlation statistics (smICC). The radial distance method was used to assess each segmentation technique's ability to detect hippocampal atrophy in 3D. We then compared how well each segmentation method detected baseline hippocampal differences between MCI subjects who remained stable (MCInc) and those who converted to AD (MCIc) during the trial. Our statistical maps were corrected for multiple comparisons using permutation-based statistics with a threshold of p < .01.

RESULTS

Our smICC analyses showed significant agreement between the manual and automated hippocampal segmentations from rater 1 [right smICC = 0.78 (95%CI 0.72-0.84); left smICC = 0.79 (95%CI 0.72-0.85)], the manual segmentations from rater 1 versus the automated segmentations from rater 2 [right smICC = 0.78 (95%CI 0.7-0.84); left smICC = 0.78 (95%CI 0.71-0.84)], and the automated segmentations of rater 1 versus rater 2 [right smICC = 0.97 (95%CI 0.96-0.98); left smICC = 0.97 (95%CI 0.96-0.98)]. All three segmentation methods detected significant CA1 and subicular atrophy in MCIc compared to MCInc at baseline (manual: right pcorrected = 0.0112, left pcorrected = 0.0006; automated rater 1: right pcorrected = 0.0318, left pcorrected = 0.0302; automated rater 2: right pcorrected = 0.0029, left pcorrected = 0.0166).

CONCLUSIONS

The hippocampal volumes obtained with a fast semi-automated segmentation method were highly comparable to the ones obtained with the labor-intensive manual segmentation method. The AdaBoost automated hippocampal segmentation technique is highly reliable allowing the efficient analysis of large data sets.

Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease (Review)

Alzheimer's disease (AD) is a complex and multifactorial disease. In order to understand the genetic influence in the progression of AD, and to identify novel pharmaceutical agents and their associated targets, the present study discusses computational modeling and biomarker evaluation approaches. Based on mechanistic signaling pathway approaches, various computational models, including biochemical and morphological models, are discussed to explore the strategies that may be used to target AD treatment. Different biomarkers are interpreted on the basis of morphological and functional features of amyloid β plaques and unstable microtubule‑associated tau protein, which is involved in neurodegeneration. Furthermore, imaging and cerebrospinal fluids are also considered to be key methods in the identification of novel markers for AD. In conclusion, the present study reviews various biochemical and morphological computational models and biomarkers to interpret novel targets and agonists for the treatment of AD. This review also highlights several therapeutic targets and their associated signaling pathways in AD, which may have potential to be used in the development of novel pharmacological agents for the treatment of patients with AD. Computational modeling approaches may aid the quest for the development of AD treatments with enhanced therapeutic efficacy and reduced toxicity.

Ethnoracial differences in brain structure change and cognitive change

OBJECTIVE

The purpose of this study was to examine longitudinal associations between structural MRI and cognition in a diverse sample.

METHOD

Older adults (n = 444; Mage = 74.5)-121 African Americans, 212 Whites, and 111 Hispanics-underwent an average of 5.3 annual study visits. Approximately half were cognitively normal at baseline (global Clinical Dementia Rating M = 0.5). Of the patients with dementia, most (79%) were diagnosed with Alzheimer's disease (AD). MRI measures of gray matter volume (baseline and change), and hippocampal and white matter hyperintensity (WMH) volumes (baseline), were used to predict change in global cognition. Multilevel latent variable modeling was used to test the hypothesis that brain effects on cognitive change differed across ethnoracial groups.

RESULTS

In a multivariable model, global gray matter change was the strongest predictor of cognitive decline in Whites and African Americans and specific temporal lobe change added incremental explanatory power in Whites. Baseline WMH volume was the strongest predictor of cognitive decline in Hispanics and made an incremental contribution in Whites.

CONCLUSIONS

We found ethnoracial group differences in associations of brain variables with cognitive decline. The unique patterns in Whites appeared to suggest a greater influence of AD in this group. In contrast, cognitive decline in African Americans and Hispanics was most uniquely attributable to global gray matter change and baseline WMH, respectively. Brain changes underlying cognitive decline in older adults are heterogeneous and depend on fixed and modifiable risk factors that differ based on ethnicity and race. (PsycINFO Database Record

Longitudinal brain imaging in preclinical Alzheimer disease: impact of APOE ε4 genotype

While prior work reliably demonstrates that the APOE ɛ4 allele has deleterious group level effects on Alzheimer disease pathology, the homogeneity of its influence across the lifespan and spatially in the brain remains unknown. Further it is unclear what combinations of factors at an individual level lead to observed group level effects of APOE genotype. To evaluate the impact of the APOE genotype on disease trajectories, we examined longitudinal MRI and PET imaging in a cohort of 497 cognitively normal middle and older aged participants. A whole-brain regional approach was used to evaluate the spatial effects of genotype on longitudinal change of amyloid-β pathology and cortical atrophy. Carriers of the ɛ4 allele had increased longitudinal accumulation of amyloid-β pathology diffusely through the cortex, but the emergence of this effect across the lifespan differed greatly by region (e.g. age 49 in precuneus, but 65 in the visual cortex) with the detrimental influence already being evident in some regions in middle age. This increased group level effect on accumulation was due to a greater proportion of ɛ4 carriers developing amyloid-β pathology, on average doing so at an earlier age, and having faster amyloid-β accumulation even after accounting for baseline amyloid-β levels. APOE ɛ4 carriers displayed faster rates of structural loss in primarily constrained to the medial temporal lobe structures at around 50 years, although this increase was modest and proportional to the elevated disease severity in APOE ɛ4 carriers. This work indicates that influence of the APOE gene on pathology can be detected starting in middle age.

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.

Perinatal stress and human hippocampal volume: Findings from typically developing young adults

The main objective of this study was to investigate the impact of prenatal and early postnatal stress on hippocampal volume in young adulthood. In sharp contrast to numerous results in animal models, our data from a neuroimaging follow-up (n = 131) of a community-based birth cohort from the Czech Republic (European Longitudinal Study of Pregnancy and Childhood) showed that in typically developing young adults, hippocampal volume was not associated with birth weight, stressful life events during the prenatal or early postnatal period, or dysregulated mood and wellbeing in the mother during the early postnatal period. Interestingly, mother’s anxiety/co-dependence during the first weeks after birth did show long-lasting effects on the hippocampal volume in young adult offspring irrespective of sex. Further analyses revealed that these effects were subfield-specific; present in CA1, CA2/3, CA4, GC-DG, subiculum, molecular layer, and HATA, hippocampal subfields identified by translational research as most stress- and glucocorticoid-sensitive, but not in the remaining subfields. Our findings provide evidence that the type of early stress is critical when studying its effects on the human brain.

A Multi-Cohort Study of ApoE ɛ4 and Amyloid-β Effects on the Hippocampus in Alzheimer's Disease

The apolipoprotein E (APOE) gene has been consistently shown to modulate the risk of Alzheimer’s disease (AD). Here, using an AD and normal aging dataset primarily consisting of three AD multi-center studies (n = 1,781), we compared the effect of APOE and amyloid-β (Aβ) on baseline hippocampal volumes in AD patients, mild cognitive impairment (MCI) subjects, and healthy controls. A large sample of healthy adolescents (n = 1,387) was also used to compare hippocampal volumes between APOE groups. Subjects had undergone a magnetic resonance imaging (MRI) scan and APOE genotyping. Hippocampal volumes were processed using FreeSurfer. In the AD and normal aging dataset, hippocampal comparisons were performed in each APOE group and in ɛ4 carriers with positron emission tomography (PET) Aβ who were dichotomized (Aβ+/Aβ–) using previous cut-offs. We found a linear reduction in hippocampal volumes with ɛ4 carriers possessing the smallest volumes, ɛ3 carriers possessing intermediate volumes, and ɛ2 carriers possessing the largest volumes. Moreover, AD and MCI ɛ4 carriers possessed the smallest hippocampal volumes and control ɛ2 carriers possessed the largest hippocampal volumes. Subjects with both APOE ɛ4 and Aβ positivity had the lowest hippocampal volumes when compared to Aβ- ɛ4 carriers, suggesting a synergistic relationship between APOE ɛ4 and Aβ. However, we found no hippocampal volume differences between APOE groups in healthy 14-year-old adolescents. Our findings suggest that the strongest neuroanatomic effect of APOE ɛ4 on the hippocampus is observed in AD and groups most at risk of developing the disease, whereas hippocampi of old and young healthy individuals remain unaffected.

Quantitative MRI Brain Studies in Mild Cognitive Impairment and Alzheimer's Disease: A Methodological Review

Classifying and predicting Alzheimer's disease (AD) in individuals with memory disorders through clinical and psychometric assessment is challenging, especially in mild cognitive impairment (MCI) subjects. Quantitative structural magnetic resonance imaging acquisition methods in combination with computer-aided diagnosis are currently being used for the assessment of AD. These acquisitions methods include voxel-based morphometry, volumetric measurements in specific regions of interest (ROIs), cortical thickness measurements, shape analysis, and texture analysis. This review evaluates the aforementioned methods in the classification of cases into one of the following three groups: normal controls, MCI, and AD subjects. Furthermore, the performance of the methods is assessed on the prediction of conversion from MCI to AD. In parallel, it is also assessed which ROIs are preferred in both classification and prognosis through the different states of the disease. Structural changes in the early stages of the disease are more pronounced in the medial temporal lobe, especially in the entorhinal cortex, whereas with disease progression, both entorhinal cortex and hippocampus offer similar discriminative power. However, for the conversion from MCI subjects to AD, entorhinal cortex provides better predictive accuracies rather than other structures, such as the hippocampus.

The identification of high potential archers based on fitness and motor ability variables: A Support Vector Machine approach

Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. The present study classified and predicted high and low-potential archers from a set of fitness and motor ability variables trained on different SVMs kernel algorithms. 50 youth archers with the mean age and standard deviation of 17.0 ± 0.6 years drawn from various archery programmes completed a six arrows shooting score test. Standard fitness and ability measurements namely hand grip, vertical jump, standing broad jump, static balance, upper muscle strength and the core muscle strength were also recorded. Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. SVM models with linear, quadratic, cubic, fine RBF, medium RBF, as well as the coarse RBF kernel functions, were trained based on the measured performance variables. The HACA clustered the archers into high-potential archers (HPA) and low-potential archers (LPA), respectively. The linear, quadratic, cubic, as well as the medium RBF kernel functions models, demonstrated reasonably excellent classification accuracy of 97.5% and 2.5% error rate for the prediction of the HPA and the LPA. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from a combination of the selected few measured fitness and motor ability performance variables examined which would consequently save cost, time and effort during talent identification programme.

Beyond symptomatic effects: potential of donepezil as a neuroprotective agent and disease modifier in Alzheimer's disease

Alzheimer's disease (AD) is associated with neurodegenerative changes resulting clinically in progressive cognitive and functional deficits. The only therapies are the cholinesterase inhibitors donepezil, galantamine and rivastigmine and the N-methyl-D-aspartate-receptor antagonist memantine. Donepezil acts primarily on the cholinergic system as a symptomatic treatment, but it also has potential for disease modification and may reduce the rate of progression of AD. This review explores the potential for disease modifying effects of donepezil. Several neuroprotective mechanisms that are independent of cholinesterase inhibition, are suggested. Donepezil has demonstrated a range of effects, including protecting against amyloid β, ischaemia and glutamate toxicity; slowing of progression of hippocampal atrophy; and up-regulation of nicotinic acetylcholine receptors. Clinically, early and continuous treatment with donepezil is considered to preserve cognitive function more effectively than delayed treatment. The possible neuroprotective effects of donepezil and the potential for disease pathway modification highlight the importance of early diagnosis and treatment initiation in AD.

An acute bout of aerobic or strength exercise specifically modifies circulating exerkine levels and neurocognitive functions in elderly individuals with mild cognitive impairment

Although exercise is an effective way to decrease the risk of developing Alzheimer's disease, the biological basis for such benefits from the different exercise modes remains elusive. The present study thus aimed (i) to investigate the effects of acute aerobic or resistance exercise on neurocognitive performances and molecular markers when performing a cognitive task involving executive functioning in older adults with amnestic mild cognitive impairment (aMCI), and (ii) to explore relationships of acute exercise-induced neurocognitive changes with changes in circulating levels of neuroprotective growth factors (e.g., BDNF, IGF-1, VEGF, and FGF-2, collectively termed 'exerkines'), elicited by different acute exercise modes. Sixty-six older adults with aMCI were recruited and randomly assigned to an aerobic exercise (AE) group, a resistance exercise (RE) group, or a non-exercise-intervention (control) group. The behavioral [i.e., accuracy rate (AR) and reaction time (RT)] and electrophysiological [i.e., event-related potential (ERP) P3 latency and amplitude collected from the Fz, Cz, and Pz electrodes] indices were simultaneously measured when participants performed a Flanker task at baseline and after either an acute bout of 30 min of moderate-intensity AE, RE or a control period. Blood samples were taken at three time points, one at baseline (T1) and two after an acute exercise intervention (T2 and T3: before and after cognitive task test, respectively). The results showed that the acute AE and RE not only improved behavioral (i.e., RTs) performance but also increased the ERP P3 amplitudes in the older adults with aMCI. Serum FGF-2 levels did not change with acute aerobic or resistance exercise. However, an acute bout of aerobic exercise significantly increased serum levels of BDNF and IGF-1 and tended to increase serum levels of VEGF in elderly aMCI individuals. Acute resistance exercise increased only serum IGF-1 levels. However, the exercise-induced elevated levels of these molecular markers returned almost to baseline levels in T3 (about 20 min after acute exercise). In addition, changes in the levels of neurotrophic and angiogenic factors were not correlated with changes in RTs and P3 amplitudes. The present findings of changes in neuroprotective growth factors and neurocognitive performances through acute AE or RE suggest that molecular and neural prerequisites for exercise-dependent plasticity are preserved in elderly aMCI individuals. However, the distinct pattern of changes in circulating molecular biomarkers induced by two different exercise modes in aMCI elderly individuals and the potentially interactive mechanisms of the effects of BDNF, IGF-1, and VEGF on amyloid-β provide a basis for future long-term exercise intervention to investigate whether AE relative to RE might be more effective in prevention/treatment of an early stage neurodegenerative disease.

The bumps under the hippocampus

Shown in every neuroanatomy textbook, a key morphological feature is the bumpy ridges, which we refer to as hippocampal dentation, on the inferior aspect of the hippocampus. Like the folding of the cerebral cortex, hippocampal dentation allows for greater surface area in a confined space. However, examining numerous approaches to hippocampal segmentation and morphology analysis, virtually all published 3D renderings of the hippocampus show the inferior surface to be quite smooth or mildly irregular; we have rarely seen the characteristic bumpy structure on reconstructed 3D surfaces. The only exception is a 9.4T postmortem study (Yushkevich et al. [2009]: NeuroImage 44:385-398). An apparent question is, does this indicate that this specific morphological signature can only be captured using ultra high-resolution techniques? Or, is such information buried in the data we commonly acquire, awaiting a computation technique that can extract and render it clearly? In this study, we propose an automatic and robust super-resolution technique that captures the fine scale morphometric features of the hippocampus based on common 3T MR images. The method is validated on 9.4T ultra-high field images and then applied on 3T data sets. This method opens possibilities of future research on the hippocampus and other sub-cortical structural morphometry correlating the degree of dentation with a range of diseases including epilepsy, Alzheimer's disease, and schizophrenia. Hum Brain Mapp 39:472-490, 2018. © 2017 Wiley Periodicals, Inc.

Atrophy of the Posterior Subiculum Is Associated with Memory Impairment, Tau- and Aβ Pathology in Non-demented Individuals

Alzheimer’s disease (AD) is associated with atrophy of the cornu ammonis (CA) 1 and the subiculum subfield of the hippocampus (HC), and with deficits in episodic memory and spatial orientation. These deficits are mainly associated with the functionality of the posterior HC. We therefore hypothesized that key AD pathologies, i.e., β-amyloid and tau pathology would be particularly associated with the volume of the posterior subiculum in non-demented individuals. In our study we included 302 cognitively normal elderly participants (CN), 183 patients with subjective cognitive decline (SCD) and 171 patients with amnestic mild cognitive impairment (MCI), all of whom underwent 3T magnetic resonance images (MRI). The subicular subfield was segmented using Freesurfer 5.3 and divided into 10 volumetric segments moving from the most posterior (segment 1) to the most anterior part along the axis of the hippocampal head and body (segment 10). Cerebrospinal fluid (CSF) Aβ₄₂ and phosphorylated tau (P-tau) were quantified using ELISA and were used as biomarkers for β-amyloid and tau pathology, respectively. In the total sample, tau-pathology and Aβ-pathology and (measured by elevated P-tau and low Aβ₄₂ levels in CSF) and mild memory dysfunction were mostly associated with the volume changes of the posterior subiculum. Both SCD and MCI patients with elevated P-tau or low Aβ₄₂ levels displayed predominantly posterior subicular atrophy in comparisons to control subjects with normal CSF biomarker levels. Finally, there was no main effect of Aβ₄₂ or P-tau when comparing SCD with abnormal P-tau or Aβ₄₂ with SCD with normal levels of these CSF-biomarkers. However, in the left subiculum there was a significant interaction revealing atrophy in the left posterior but not the anterior subiculum in participants with low Aβ₄₂ levels. The same pattern was observed on the contralateral side in participants with elevated P-tau levels. In conclusion, AD pathologies and mild memory dysfunction are mainly associated with atrophy of the posterior parts of the subicular subfields of the HC in non-demented individuals. In light of these findings we suggest that segmentation of the HC subfields may benefit from considering the volume of the different anterior-posterior subsections of each subfield.

The ethanol extract of Aquilariae Lignum ameliorates hippocampal oxidative stress in a repeated restraint stress mouse model

Background

Chronic stress contributes to the development of brain disorders, such as neurodegenerative and psychiatric diseases. Oxidative damage is well known as a causative factor for pathogenic process in brain tissues. The aim of this study is to evaluate the neuroprotective effect of a 30% ethanol extract of Aquilariae Lignum (ALE) in repeated stress-induced hippocampal oxidative injury.

Methods

Fifty BALB/c male mice (12 weeks old) were randomly divided into five groups (n = 10). For 11 consecutive days, each group was orally administered with distilled water, ALE (20 or 80 mg/kg) or N-acetylcysteine (NAC; 100 mg/kg), and then all mice (except unstressed group) were subjected to restraint stress for 6 h. On the final day, brain tissues and sera were isolated, and stress hormones and hippocampal oxidative alterations were examined. We also treated lipopolysaccharide (LPS, 1 μg/mL)-stimulated BV2 microglial cells with ALE (1 and 5 μg/mL) or NAC (10 μM) to investigate the pharmacological mechanism.

Results

Restraint stress considerably increased the serum levels of corticosterone and adrenaline and the hippocampal levels of reactive oxygen species (ROS), nitric oxide (NO), and malondialdehyde (MDA). ALE administration significantly attenuated the above abnormalities. ALE also significantly normalized the stress-induced activation of astrocytes and microglial cells in the hippocampus as well as the elevation of pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α) and interleukin-1 beta (IL-1β). The in vitro assay outcome supplemented ALE could dramatically block NF-κB activation in microglia. The anti-oxidative stress effects of ALE were supported by the results of antioxidant components, 4-hydroxynonenal (4-HNE), NADPH oxidase 2 (NOX2), inducible nitric oxide synthase (iNOS) and NFE2L2 (Nrf2) in the hippocampal tissues.

Conclusions

We firstly demonstrated the neuroprotective potentials of A. Lignum against hippocampal oxidative injury in repeated restraint stress. The corresponding mechanisms might involve modulations in the release of ROS, pro-inflammatory cytokines and stress hormones.

Cerebral PET glucose hypometabolism in subjects with mild cognitive impairment and higher EEG high-alpha/low-alpha frequency power ratio

In Alzheimer's disease (AD) research, both 2-deoxy-2-(¹⁸F)fluoro-D-glucose (FDG) positron emission tomography (PET) and electroencephalography (EEG) are reliable investigational modalities. The aim of this study was to investigate the associations between EEG High-alpha/Low-alpha (H-alpha/L-alpha) power ratio and cortical glucose metabolism. A total of 23 subjects with mild cognitive impairment (MCI) underwent FDG-PET and EEG examinations. H-alpha/L-alpha power ratio was computed for each subject and 2 groups were obtained based on the increase of the power ratio. The subjects with higher H-alpha/L-alpha power ratio showed a decrease in glucose metabolism in the hub brain areas previously identified as typically affected by AD pathology. In subjects with higher H-alpha/L-alpha ratio and lower metabolism, a "double alpha peak" was identified in the EEG spectrum and a U-shaped correlation between glucose metabolism and increase of H-alpha/L-alpha power ratio has been found. Moreover, in this group, a conversion rate of 62.5% at 24 months was detected, significantly different from the chance percentage expected. The neurophysiological meaning of the interplay between alpha oscillations and glucose metabolism and the possible interest of the H-alpha/L-alpha power ratio as a clinical biomarker in AD have been discussed.