Hippocampal volume and asymmetry in mild cognitive impairment and Alzheimer's disease: Meta-analyses of MRI studies

Effect of 3-Month Aerobic Dance on Hippocampal Volume and Cognition in Elderly People With Amnestic Mild Cognitive Impairment: A Randomized Controlled Trial

As an intermediate state between normal aging and dementia, mild cognitive impairment (MCI), especially amnestic MCI (aMCI), is a key stage in the prevention and intervention of Alzheimer’s disease (AD). Whether dancing could increase the hippocampal volume of seniors with aMCI remains debatable. The aim of this study was to investigate the influence of aerobic dance on hippocampal volume and cognition after 3 months of aerobic dance in older adults with aMCI. In this randomized controlled trial, 68 elderly people with aMCI were randomized to either the aerobic dance group or the control group using a 1:1 allocation ratio. Ultimately, 62 of 68 participants completed this study, and the MRI data of 54 participants were included. A specially designed aerobic dance routine was performed by the dance group three times per week for 3 months, and all participants received monthly healthcare education after inclusion. MRI with a 3.0T MRI scanner and cognitive assessments were performed before and after intervention. High-resolution three-dimensional (3D) T1-weighted anatomical images were acquired for the analysis of hippocampal volume. A total of 35 participants (mean age: 71.51 ± 6.62 years) were randomized into the aerobic dance group and 33 participants (mean age: 69.82 ± 7.74 years) into the control group. A multiple linear regression model was used to detect the association between intervention and the difference of hippocampal volumes as well as the change of cognitive scores at baseline and after 3 months. The intervention group showed greater right hippocampal volume (β [95% CI]: 0.379 [0.117, 0.488], p = 0.002) and total hippocampal volume (β [95% CI]: 0.344 [0.082, 0.446], p = 0.005) compared to the control group. No significant association of age or gender was found with unilateral or global hippocampal volume. There was a correlation between episodic memory and intervention, as the intervention group showed a higher Wechsler Memory Scale-Revised Logical Memory (WMS-RLM) score (β [95% CI]: 0.326 [1.005, 6.773], p = 0.009). Furthermore, an increase in age may cause a decrease in the Mini-Mental State Examination (MMSE) score (β [95% CI]: −0.366 [−0.151, −0.034], p = 0.002). In conclusion, 3 months of aerobic dance could increase the right and total hippocampal volumes and improve episodic memory in elderly persons with aMCI.

Clinical Trial Registration: This study was registered on the Chinese Clinical Trial Registry [www.chictr.org.cn], identifier [ChiCTR-INR-15007420].

Spousal caregiving, widowhood, and cognition: A systematic review and a biopsychosocial framework for understanding the relationship between interpersonal losses and dementia risk in older adulthood

Accumulating research suggests that stressful life events, especially those that threaten close intimate bonds, are associated with an increased risk of dementia. Grieving the loss of a spouse, whether in the form of caregiving or after the death, ranks among 'life's most significant stressors', evoking intense psychological and physiological distress. Despite numerous studies reporting elevated dementia risk or poorer cognition among spousal caregivers and widow(er)s compared to controls, no review has summarized findings across cognitive outcomes (i.e., dementia incidence, cognitive impairment rates, cognitive performance) or proposed a theoretical model for understanding the links between partner loss and abnormal cognitive decline. The current systematic review summarizes findings across 64 empirical studies. Overall, both cross-sectional and longitudinal studies revealed an adverse association between partner loss and cognitive outcomes. In turn, we propose a biopsychosocial model of cognitive decline that explains how caregiving and bereavement may position some to develop cognitive impairment or Alzheimer's disease and related dementias. More longitudinal studies that focus on the biopsychosocial context of caregivers and widow(er)s are needed.

MRI biomarkers for Alzheimer's disease: the impact of functional connectivity in the default mode network and structural connectivity between lobes on diagnostic accuracy

Background

At present, clinical use of MRI in Alzheimer's disease (AD) is mostly focused on the assessment of brain atrophy, namely in the hippocampal region. Despite this, multiple biomarkers reflecting structural and functional brain connectivity changes have shown promising results in the assessment of AD. To help identify the most relevant ones that may stand a chance of being used in clinical practice, we compared multiple biomarker in terms of their value to discriminate AD from healthy controls and analyzed their age dependency.

Methods

20 AD patients and 20 matched controls underwent MRI-scanning (3T GE), including T1-weighted, diffusion-MRI, and resting-state-fMRI (rsfMRI). Whole brain, white matter, gray matter, cortical gray matter and hippocampi volumes were measured using icobrain. rsfMRI between regions of the default-mode-network (DMN) was assessed using group independent-component-analysis. Median diffusivity and kurtosis were determined in gray and white-matter. DTI data was used to evaluate pairwise structural connectivity between lobar regions and the hippocampi.

Logistic-Regression and Random-Forest models were trained to classify AD-status based on, respectively different isolated features and age, and feature-groups combined with age.

Results

Hippocampal features, features reflecting the functional connectivity between the medial-Pre-Frontal-Cortex (mPFC) and the posterior regions of the DMN, and structural interhemispheric frontal connectivity showed the strongest differences between AD-patients and controls. Structural interhemispheric parietal connectivity, structural connectivity between the parietal lobe and hippocampus in the right hemisphere, and mPFC-DMN-features, showed only an association with AD-status (p < 0.05) but not with age. Hippocampi volumes showed an association both with age and AD-status (p < 0.05).

Smallest-hippocampus-volume was the most discriminative feature. The best performance (accuracy:0.74, sensitivity:0.74, specificity:0.74) was obtained with an RF-model combining the best feature from each feature-group (smallest hippocampus volume, WM volume, median GM MD, lTPJ-mPFC connectivity and structural interhemispheric frontal connectivity) and age.

Conclusions

Brain connectivity changes caused by AD are reflected in multiple MRI-biomarkers. Decline in both the functional DMN-connectivity and the parietal interhemispheric structural connectivity may assist sepparating healthy-aging driven changes from AD, complementing hippocampal volumes which are affected by both aging and AD.

Pulsed Arterial Spin Labeling and Segmented Brain Volumetry in the Diagnostic Evaluation of Frontotemporal Dementia, Alzheimer’s Disease and Mild Cognitive Impairment

Background: Previous studies suggest that brain atrophy can not only be defined by its morphological extent, but also by the cerebral blood flow (CBF) within a certain area of the brain, including white and gray matter. The aim of this study is to investigate known atrophy patterns in different forms of dementia and to compare segmented brain volumetrics and pulsed arterial spin labeling (pASL) data to explore the correlation between brain maps with atrophy and this non-contrast-enhanced brain-perfusion method. Methods: Our study comprised 17 patients with diagnosed cognitive impairment (five Alzheimer’s disease = AD, five frontotemporal dementia = FTD, seven mild cognitive impairment = MCI) and 19 healthy control subjects (CO). All patients and controls underwent 4D-pASL brain-perfusion MR imaging and T1w MPRAGE. The data were assessed regarding relative brain volume on the basis of 286 brain regions, and absolute and relative cerebral blood flow (CBF/rCBF) were derived from pASL data in the corresponding brain regions. Mini-Mental State Examination (MMSE) was performed to assess cognitive functions. Results: FTD patients demonstrated significant brain atrophy in 43 brain regions compared to CO. Patients with MCI showed significant brain atrophy in 18 brain regions compared to CO, whereas AD patients only showed six brain regions with significant brain atrophy compared to CO. There was good correlation of brain atrophy and pASL perfusion data in five brain regions of patients with diagnosed FTD, especially in the superior temporal gyrus (r = 0.900, p = 0.037), the inferior frontal white matter (pars orbitalis; r = 0.968, p = 0.007) and the thalami (r = 0.810, p = 0.015). Patients with MCI demonstrated a correlation in one brain region (left inferior fronto-occipital fasciculus; r = 0.786, p = 0.036), whereas patients with diagnosed AD revealed no correlation. Conclusions: pASL can detect affected brain regions in cognitive impairment and corresponds with brain atrophy, especially for patients suffering from FTD and MCI. However, there was no correlation of perfusion alterations and brain atrophy in AD. pASL perfusion might thus represent a promising tool for noninvasive brain-perfusion evaluation in specific dementia subtypes as a complimentary imaging-based bio marker in addition to brain volumetry.

Hippocampal volume reduction is associated with direct measure of insulin resistance in adults

Hippocampal integrity is highly susceptible to metabolic dysfunction, yet its mechanisms are not well defined. We studied 126 healthy individuals aged 23-61 years. Insulin resistance (IR) was quantified by measuring steady-state plasma glucose (SSPG) concentration during the insulin suppression test. Body mass index (BMI), adiposity, fasting insulin, glucose, leptin as well as structural neuroimaing with automatic hippocampal subfield segmentation were performed. Data analysis using unsupervised machine learning (k-means clustering) identified two subgroups reflecting a pattern of more pronounced hippocampal volume reduction being concurrently associated with greater adiposity and insulin resistance; the hippocampal volume reductions were uniform across subfields. Individuals in the most deviant subgroup were predominantly women (79 versus 42 %) with higher BMI [27.9 (2.5) versus 30.5 (4.6) kg/m²], IR (SSPG concentration, [156 (61) versus 123 (70) mg/dL] and leptinemia [21.7 (17.0) versus 44.5 (30.4) μg/L]. The use of person-based modeling in healthy individuals suggests that adiposity, insulin resistance and compromised structural hippocampal integrity behave as a composite phenotype; female sex emerged as risk factor for this phenotype.

Multi-label, multi-domain learning identifies compounding effects of HIV and cognitive impairment

Older individuals infected by Human Immunodeficiency Virus (HIV) are at risk for developing HIV-Associated Neurocognitive Disorder (HAND), i.e., from reduced cognitive functioning similar to HIV-negative individuals with Mild Cognitive Impairment (MCI) or to Alzheimer's Disease (AD) if more severely affected. Incompletely understood is how brain structure can serve to differentiate cognitive impairment (CI) in the HIV-positive (i.e., HAND) from the HIV-negative cohort (i.e., MCI and AD). To that end, we designed a multi-label classifier that labels the structural magnetic resonance images (MRI) of individuals by their HIV and CI status via two binary variables. Proper training of such an approach traditionally requires well-curated datasets containing large number of samples for each of the corresponding four cohorts (healthy controls, CI HIV-negative adults a.k.a. CI-only, HIV-positive patients without CI a.k.a. HIV-only, and HAND). Because of the rarity of such datasets, we proposed to improve training of the multi-label classifier via a multi-domain learning scheme that also incorporates domain-specific classifiers on auxiliary single-label datasets specific to either binary label. Specifically, we complement the training dataset of MRIs of the four cohorts (Control: 156, CI-only: 335, HIV-only: 37, HAND: 145) acquired by the Memory and Aging Center at the University of California - San Francisco with a CI-specific dataset only containing MRIs of HIV-negative subjects (Controls: 229, CI-only: 397) from the Alzheimer's Disease Neuroimaging Initiative and an HIV-specific dataset (Controls: 75, HIV-only: 75) provided by SRI International. Based on cross-validation on the UCSF dataset, the multi-domain and multi-label learning strategy leads to superior classification accuracy compared with one-domain or multi-class learning approaches, specifically for the undersampled HIV-only cohort. The 'prediction logits' of CI computed by the multi-label formulation also successfully stratify motor performance among the HIV-positive subjects (including HAND). Finally, brain patterns driving the subject-level predictions across all four cohorts characterize the independent and compounding effects of HIV and CI in the HAND cohort.

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

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

Longitudinal Effects of Physical Activity Change on Hippocampal Volumes over up to 12 Years in Middle and Older Age Community-Dwelling Individuals

The objectives of this study were to investigate the long-term associations between changes in physical activity levels and hippocampal volumes over time, while considering the influence of age, sex, and APOE-ε4 genotype. We investigated the effects of change in physical activity on hippocampal volumes in 411 middle age (mean age = 47.2 years) and 375 older age (mean age = 63.1 years) adults followed up to 12 years. An annual volume decrease was observed in the left (middle age: 0.46%; older age: 0.51%) but not in the right hippocampus. Each additional 10 metabolic equivalents (METs, ~2 h of moderate exercise) increase in weekly physical activity was associated with 0.33% larger hippocampal volume in middle age (equivalent to ~1 year of typical aging). In older age, each additional MET was associated with 0.05% larger hippocampal volume; however, the effects declined with time by 0.005% per year. For older age APOE-ε4 carriers, each additional MET was associated with a 0.10% increase in hippocampal volume. No sex effects of physical activity change were found. Increasing physical activity has long-term positive effects on hippocampal volumes and appears especially beneficial for older APOE-ε4 carriers. To optimize healthy brain aging, physical activity programs should focus on creating long-term exercise habits.

Distinct Atrophy Pattern of Hippocampal Subfields in Patients with Progressive and Stable Mild Cognitive Impairment: A Longitudinal MRI Study

BACKGROUND

Predicting the prognosis of mild cognitive impairment (MCI) has outstanding clinical value, and the hippocampal volume is a reliable imaging biomarker of AD diagnosis.

OBJECTIVE

We aimed to longitudinally assess hippocampal sub-regional difference (volume and asymmetry) among progressive MCI (pMCI), stable MCI (sMCI) patients, and normal elderly.

METHODS

We identified 29 pMCI, 52 sMCI, and 102 normal controls (NC) from the ADNI database. All participants underwent neuropsychological assessment and 3T MRI scans three times. The time interval between consecutive MRI sessions was about 1 year. Volumes of hippocampal subfield were measured by Freesurfer. Based on the analysis of variance, repeated measures analyses, and receiver operating characteristic curves, we compared cross-sectional and longitudinal alteration sub-regional volume and asymmetry index.

RESULTS

Compared to NC, both MCI groups showed significant atrophy in all subfields. At baseline, pMCI have a smaller volume than sMCI in the bilateral subiculum, molecular layer (ML), the molecular and granule cell layers of the dentate gyrus, cornu ammonis 4, and right tail. Furthermore, repeated measures analyses revealed that pMCI patients showed a faster volume loss than sMCI in bilateral subiculum and ML. After controlling for age, gender, and education, most results remained unchanged. However, none of the hippocampal sub-regional volumes performed better than the whole hippocampus in ROC analyses, and no asymmetric difference between pMCI and sMCI was found.

CONCLUSION

The faster volume loss in subiculum and ML suggest a higher risk of disease progression in MCI patients. The hippocampal asymmetry may have smaller value in predicting the MCI prognosis.

The Association Between Hippocampal Volume and Level of Attention in Children and Adolescents

The hippocampus, which engages in the process of consolidating long-term memories and learning, shows active development during childhood and adolescence. The hippocampus also functionally influences attention. Based on the influence of hippocampal function on attention, it was expected that the volume of the hippocampus would be associated with the difference in attention during childhood and adolescence, in which the brain develops actively. Thus, this study examined the association between hippocampal volume and attention metrics measured by the continuous performance test (CPT) in 115 children and adolescents (mean age = 12.43 ± 3.0, 63 male and 52 female). In association studies with both auditory and visual attention, we found that the bilateral hippocampal volumes showed negative relationships with auditory omission errors. A smaller volume of the left hippocampus also led to a longer auditory response time. However, visual attention did not show any significant relationship with the hippocampal volume. These findings were consistent even after adjusting for the effects of the related covariates (e.g., age, insomnia, and depression). Taken together, this study suggested that the increase in hippocampal volume during childhood and adolescence was associated significantly with better auditory attention.

Microstructural Plasticity in the Hippocampus of Healthy Older Adults after Acute Exercise

INTRODUCTION

The hippocampus experiences structural and functional decline with age and is a critical region for memory and many cognitive processes. Exercise is beneficial for the aging brain and shows preferential benefits for hippocampal volume, activation, and memory-related cognitive processes. However, research thus far has primarily focused on the effects of exercise on long-term volumetric changes in the hippocampus using structural magnetic resonance imaging. Critically, microstructural alterations within the hippocampus over short time intervals are associated with neuroplasticity and cognitive changes that do not alter its volume but are still functionally relevant. However, it is not yet known if microstructural neuroplasticity occurs in the hippocampus in response to a single session of exercise.

METHODS

We used a within-subject design to determine if a 30-min bout of moderate-intensity aerobic exercise altered bilateral hippocampal diffusion tensor imaging measures in healthy older adults (n = 30) compared with a seated rest control condition.

RESULTS

Significantly lower fractional anisotropy and higher mean diffusivity were found after exercise relative to seated rest within the bilateral hippocampus, and this effect was driven by higher radial diffusivity. No significant differences in axial diffusivity were observed.

CONCLUSIONS

These findings suggest that a single exercise session can lead to microstructural alterations in the hippocampus of healthy older adults. These differences may be associated with changes in the extracellular space and glial, synaptic, and dendritic processes within the hippocampus. Repeated microstructural alterations resulting from acute bouts of exercise may accumulate and precede larger volumetric and functional improvements in the hippocampus.

Amyloid-Beta Influences Memory via Functional Connectivity During Memory Retrieval in Alzheimer's Disease

Objective: Amnesia in Alzheimer's disease (AD) appears early and could be caused by encoding deficiency, consolidation dysfunction, and/or impairment in the retrieval of stored memory information. The relationship between AD pathology biomarker β-amyloid and memory dysfunction is unclear. Method: The memory task functional MRI and amyloid PET were simultaneously performed to investigate the relationship between memory performance, memory phase-related functional connectivity, and cortical β-amyloid deposition. We clustered functional networks during memory maintenance and compared network connectivity between groups in each memory phase. Mediation analysis was performed to investigate the mediator between β-amyloid and related cognitive performance. Results: Alzheimer's disease was primarily characterized by decreased functional connectivity in a data-driven network composed of an a priori default mode network, limbic network, and frontoparietal network during the memory maintenance (0.205 vs. 0.236, p = 0.04) and retrieval phase (0.159 vs. 0.183, p = 0.017). Within the network, AD had more regions with reduced connectivity during the retrieval than the maintenance and encoding phases (chi-square p = 0.01 and < 0.001). Furthermore, the global cortical β-amyloid negatively correlated with network connectivity during the memory retrieval phase (R = - 0.247, p = 0.032), with this relationship mediating the effect of cortical β-amyloid on memory performance (average causal mediation effect = - 0.05, p = 0.035). Conclusion: We demonstrated that AD had decreased connectivity in specific networks during the memory retrieval phase. Impaired functional connectivity during memory retrieval mediated the adverse effect of β-amyloid on memory. These findings help to elucidate the involvement of cortical β-amyloid (Aβ) in the memory performance in the early stages of AD.

The reduced left hippocampal volume related to the delayed P300 latency in amnestic mild cognitive impairment

BACKGROUND

Amnestic mild cognitive impairment (aMCI) is characterized by delayed P300 latency and reduced grey matter (GM) volume, respectively. The relationship between the features in aMCI is unclear. This study was to investigate the relationship between the altered P300 latency and the GM volume in aMCI.

METHODS

Thirty-four aMCI and 34 well-matched normal controls (NC) were studied using electroencephalogram during a visual oddball task and scanned with MRI. Both tests were finished in the same day.

RESULTS

As compared with the NC group, the aMCI group exhibited delayed P300 latency in parietal cortex and reduced GM volumes in bilateral temporal pole and left hippocampus/parahippocampal gyrus. A remarkable negative correlation was found between delayed P300 latency and reduced left hippocampal volume only in the aMCI group. Interestingly, the mediating analysis found P300 latency significantly mediated the association between right supramarginal gyrus volume and information processing speed indicated by Stroop Color and Word Test A scores.

CONCLUSIONS

The association between delayed P300 latency and reduced left hippocampal volume in aMCI subjects suggests that reduced left hippocampal volume may be the potential structural basis of delayed P300 latency.

Joint super-resolution and synthesis of 1 mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast

Most existing algorithms for automatic 3D morphometry of human brain MRI scans are designed for data with near-isotropic voxels at approximately 1 mm resolution, and frequently have contrast constraints as well-typically requiring T1-weighted images (e.g., MP-RAGE scans). This limitation prevents the analysis of millions of MRI scans acquired with large inter-slice spacing in clinical settings every year. In turn, the inability to quantitatively analyze these scans hinders the adoption of quantitative neuro imaging in healthcare, and also precludes research studies that could attain huge sample sizes and hence greatly improve our understanding of the human brain. Recent advances in convolutional neural networks (CNNs) are producing outstanding results in super-resolution and contrast synthesis of MRI. However, these approaches are very sensitive to the specific combination of contrast, resolution and orientation of the input images, and thus do not generalize to diverse clinical acquisition protocols - even within sites. In this article, we present SynthSR, a method to train a CNN that receives one or more scans with spaced slices, acquired with different contrast, resolution and orientation, and produces an isotropic scan of canonical contrast (typically a 1 mm MP-RAGE). The presented method does not require any preprocessing, beyond rigid coregistration of the input scans. Crucially, SynthSR trains on synthetic input images generated from 3D segmentations, and can thus be used to train CNNs for any combination of contrasts, resolutions and orientations without high-resolution real images of the input contrasts. We test the images generated with SynthSR in an array of common downstream analyses, and show that they can be reliably used for subcortical segmentation and volumetry, image registration (e.g., for tensor-based morphometry), and, if some image quality requirements are met, even cortical thickness morphometry. The source code is publicly available at https://github.com/BBillot/SynthSR.

Differential Role for Hippocampal Subfields in Alzheimer's Disease Progression Revealed with Deep Learning

Mild cognitive impairment (MCI) is often considered the precursor of Alzheimer's disease. However, MCI is associated with substantially variable progression rates, which are not well understood. Attempts to identify the mechanisms that underlie MCI progression have often focused on the hippocampus but have mostly overlooked its intricate structure and subdivisions. Here, we utilized deep learning to delineate the contribution of hippocampal subfields to MCI progression. We propose a dense convolutional neural network architecture that differentiates stable and progressive MCI based on hippocampal morphometry with an accuracy of 75.85%. A novel implementation of occlusion analysis revealed marked differences in the contribution of hippocampal subfields to the performance of the model, with presubiculum, CA1, subiculum, and molecular layer showing the most central role. Moreover, the analysis reveals that 10.5% of the volume of the hippocampus was redundant in the differentiation between stable and progressive MCI.

Diagnostic Performance of Automated MRI Volumetry by icobrain dm for Alzheimer's Disease in a Clinical Setting: A REMEMBER Study

Background:

Magnetic resonance imaging (MRI) has become important in the diagnostic work-up of neurodegenerative diseases. icobrain dm, a CE-labeled and FDA-cleared automated brain volumetry software, has shown potential in differentiating cognitively healthy controls (HC) from Alzheimer’s disease (AD) dementia (ADD) patients in selected research cohorts.

Objective:

This study examines the diagnostic value of icobrain dm for AD in routine clinical practice, including a comparison to the widely used FreeSurfer software, and investigates if combined brain volumes contribute to establish an AD diagnosis.

Methods:

The study population included HC (n = 90), subjective cognitive decline (SCD, n = 93), mild cognitive impairment (MCI, n = 357), and ADD (n = 280) patients. Through automated volumetric analyses of global, cortical, and subcortical brain structures on clinical brain MRI T1w (n = 820) images from a retrospective, multi-center study (REMEMBER), icobrain dm’s (v.4.4.0) ability to differentiate disease stages via ROC analysis was compared to FreeSurfer (v.6.0). Stepwise backward regression models were constructed to investigate if combined brain volumes can differentiate between AD stages.

Results:

icobrain dm outperformed FreeSurfer in processing time (15–30 min versus 9–32 h), robustness (0 versus 67 failures), and diagnostic performance for whole brain, hippocampal volumes, and lateral ventricles between HC and ADD patients. Stepwise backward regression showed improved diagnostic accuracy for pairwise group differentiations, with highest performance obtained for distinguishing HC from ADD (AUC = 0.914; Specificity 83.0%; Sensitivity 86.3%).

Conclusion:

Automated volumetry has a diagnostic value for ADD diagnosis in routine clinical practice. Our findings indicate that combined brain volumes improve diagnostic accuracy, using real-world imaging data from a clinical setting.

Association of Tau Pathology With Clinical Symptoms in the Subfields of Hippocampal Formation

Objective: To delineate the relationship between clinical symptoms and tauopathy of the hippocampal subfields under different amyloid statuses. Methods: One hundred and forty-three subjects were obtained from the ADNI project, including 87 individuals with normal cognition, 46 with mild cognitive impairment, and 10 with Alzheimer's disease (AD). All subjects underwent the tau PET, amyloid PET, T1W, and high-resolution T2W scans. Clinical symptoms were assessed by the Neuropsychiatric Inventory (NPI) total score and Alzheimer's Disease Assessment Scale cognition 13 (ADAS-cog-13) total score, comprising memory and executive function scores. The hippocampal subfields including Cornu Ammonis (CA1-3), subiculum (Sub), and dentate gyrus (DG), as well as the adjacent para-hippocampus (PHC) and entorhinal cortex (ERC), were segmented automatically using the Automatic Segmentation of Hippocampal Subfields (ASHS) software. The relationship between tauopathy/volume of the hippocampal subfields and assessment scores was calculated using partial correlation analysis under different amyloid status, by controlling age, gender, education, apolipoprotein E (APOE) allele ɛ4 carrier status, and, time interval between the acquisition time of tau PET and amyloid PET scans. Results: Compared with amyloid negative (A-) group, individuals from amyloid positive (A+) group are more impaired based on the Mini-mental State Examination (MMSE; p = 3.82e-05), memory (p = 6.30e-04), executive function (p = 0.0016), and ADAS-cog-13 scores (p = 5.11e-04). Significant decrease of volume (CA1, DG, and Sub) and increase of tau deposition (CA1, Sub, ERC, and PHC) of the hippocampal subfields of both hemispheres were observed for the A+ group compared to the A- group. Tauopathy of ERC is significantly associated with memory score for the A- group, and the associated regions spread into Sub and PHC for the A+ group. The relationship between the impairment of behavior or executive function and tauopathy of the hippocampal subfield was discovered within the A+ group. Leftward asymmetry was observed with the association between assessment scores and tauopathy of the hippocampal subfield, which is more prominent for the NPI score for the A+ group. Conclusion: The associations of tauopathy/volume of the hippocampal subfields with clinical symptoms provide additional insight into the understanding of local changes of the human HF during the AD continuum and can be used as a reference for future studies.

Asymmetric Amyloid Deposition as an Early Sign of Progression in Mild Cognitive Impairment Due to Alzheimer Disease

PURPOSE

In typical Alzheimer disease with dementia (ADD), amyloid pathologies affect both cerebral hemispheres symmetrically. However, the spatial distribution of amyloid-β (Aβ) in the early stage of ADD or over the course of disease has not been investigated. Therefore, we explored asymmetric pattern of Aβ deposition in both hemispheres according to the ADD continuum using 18F-florbetaben PET.

METHODS

Sixty-eight subjects, including 15 Aβ-negative normal controls, 28 Aβ-positive mild cognitive impairment (Aβ+ MCI), and 25 Aβ-positive ADD (Aβ+ ADD) subjects, were enrolled. Differences in the asymmetry index and SUV ratio in each of the 6 target regions (4 cortical lobes, cingulate, precuneus) plus composite region between groups were explored.

RESULTS

The composite and target regional asymmetry indices were significantly different between groups and was highest in Aβ+ MCI (composite, occipital, and temporal, P < 0.001; frontal, P = 0.004). The composite and target regional SUV ratios were significantly different according to 3 groups with gradual increase and were highest in Aβ+ ADD (composite and all target regions, P < 0.001).

CONCLUSIONS

The asymmetric pattern of amyloid deposition was distinct between Aβ-negative normal controls and Aβ+ MCI. This pattern disappeared as the disease progressed. These data indicate that asymmetric amyloid deposition may be an early sign of MCI over the course of ADD.

Rare CASP6N73T variant associated with hippocampal volume exhibits decreased proteolytic activity, synaptic transmission defect, and neurodegeneration

Caspase-6 (Casp6) is implicated in Alzheimer disease (AD) cognitive impairment and pathology. Hippocampal atrophy is associated with cognitive impairment in AD. Here, a rare functional exonic missense CASP6 single nucleotide polymorphism (SNP), causing the substitution of asparagine with threonine at amino acid 73 in Casp6 (Casp6N73T), was associated with hippocampal subfield CA1 volume preservation. Compared to wild type Casp6 (Casp6WT), recombinant Casp6N73T altered Casp6 proteolysis of natural substrates Lamin A/C and α-Tubulin, but did not alter cleavage of the Ac-VEID-AFC Casp6 peptide substrate. Casp6N73T-transfected HEK293T cells showed elevated Casp6 mRNA levels similar to Casp6WT-transfected cells, but, in contrast to Casp6WT, did not accumulate active Casp6 subunits nor show increased Casp6 enzymatic activity. Electrophysiological and morphological assessments showed that Casp6N73T recombinant protein caused less neurofunctional damage and neurodegeneration in hippocampal CA1 pyramidal neurons than Casp6WT. Lastly, CASP6 mRNA levels were increased in several AD brain regions confirming the implication of Casp6 in AD. These studies suggest that the rare Casp6N73T variant may protect against hippocampal atrophy due to its altered catalysis of natural protein substrates and intracellular instability thus leading to less Casp6-mediated damage to neuronal structure and function.

Structural Changes in Thalamic Nuclei Across Prodromal and Clinical Alzheimer's Disease

BACKGROUND

Increasing evidence suggests that thalamic nuclei may atrophy in Alzheimer's disease (AD). We hypothesized that there will be significant atrophy of limbic thalamic nuclei associated with declining memory and cognition across the AD continuum.

OBJECTIVE

The objective of this work was to characterize volume differences in thalamic nuclei in subjects with early and late mild cognitive impairment (MCI) as well as AD when compared to healthy control (HC) subjects using a novel MRI-based thalamic segmentation technique (THOMAS).

METHODS

MPRAGE data from the ADNI database were used in this study (n = 540). Healthy control (n = 125), early MCI (n = 212), late MCI (n = 114), and AD subjects (n = 89) were selected, and their MRI data were parcellated to determine the volumes of 11 thalamic nuclei for each subject. Volumes across the different clinical subgroups were compared using ANCOVA.

RESULTS

There were significant differences in thalamic nuclei volumes between HC, late MCI, and AD subjects. The anteroventral, mediodorsal, pulvinar, medial geniculate, and centromedian nuclei were significantly smaller in subjects with late MCI and AD when compared to HC subjects. Furthermore, the mediodorsal, pulvinar, and medial geniculate nuclei were significantly smaller in early MCI when compared to HC subjects.

CONCLUSION

This work highlights nucleus specific atrophy within the thalamus in subjects with early and late MCI and AD. This is consistent with the hypothesis that memory and cognitive changes in AD are mediated by damage to a large-scale integrated neural network that extends beyond the medial temporal lobes.

Aberrant Hippocampal Functional Connectivity Is Associated with Fornix White Matter Integrity in Alzheimer's Disease and Mild Cognitive Impairment

BACKGROUND

Alzheimer's disease (AD) is the most common cause of dementia in older individuals, and amnestic mild cognitive impairment (aMCI) is currently considered the prodromal stage of AD. The hippocampus and fornix interact functionally and structurally, with the fornix being the major efferent white matter tract from the hippocampus.

OBJECTIVE

The main aim of this study was to examine the impairments present in subjects with AD or aMCI and the relationship of these impairments with the microstructure of the fornix and the functional connectivity (FC) and gray matter volume of the hippocampus.

METHODS

Forty-four AD, 34 aMCI, and 41 age- and gender-matched normal controls (NCs) underwent neuropsychological assessments and multimode MRI. We chose the bilateral hippocampi as the region of interest in which gray matter alterations and FC with the whole brain were assessed and the fornix body as the region of interest in which the microstructural integrity of the white matter was observed. We also evaluated the relationship among gray matter alterations, the abnormal FC of the hippocampus and the integrity of the fornix in AD/aMCIResults:Compared to the NC group, the AD and aMCI groups demonstrated decreased gray matter volume, reduced FC between the bilateral hippocampi and several brain regions in the default mode network and control network, and damaged integrity of the fornix body (decreased fractional anisotropy and increased diffusivity). We also found that left hippocampal FC with some regions, the integrity of the fornix body, and cognition ability were significantly correlated. Therefore, our findings suggest that damage to white matter integrity may partially explain the reduced resting-state FC of the hippocampus in AD and aMCI.

CONCLUSION

AD and aMCI are diseases of disconnectivity including not only functional but also structural disconnectivity. Damage to white matter integrity may partially explain the reduced resting-state FC in AD and aMCI. These findings have significant implications for diagnostics and modeling and provide insights for understanding the disconnection syndrome in AD.

In vivo MRI Structural and PET Metabolic Connectivity Study of Dopamine Pathways in Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is characterized by an involvement of brain dopamine (DA) circuitry, the presence of which has been associated with emergence of both neuropsychiatric symptoms and cognitive deficits.

OBJECTIVE

In order to investigate whether and how the DA pathways are involved in the pathophysiology of AD, we assessed by in vivo neuroimaging the structural and metabolic alterations of subcortical and cortical DA pathways and targets.

METHODS

We included 54 healthy control participants, 53 amyloid-positive subjects with mild cognitive impairment due to AD (MCI-AD), and 60 amyloid-positive patients with probable dementia due to AD (ADD), all with structural 3T MRI and 18F-FDG-PET scans. We assessed MRI-based gray matter reductions in the MCI-AD and ADD groups within an anatomical a priori-defined Nigrostriatal and Mesocorticolimbic DA pathways, followed by 18F-FDG-PET metabolic connectivity analyses to evaluate network-level metabolic connectivity changes.

RESULTS

We found significant tissue loss in the Mesocorticolimbic over the Nigrostriatal pathway. Atrophy was evident in the ventral striatum, orbitofrontal cortex, and medial temporal lobe structures, and already plateaued in the MCI-AD stage. Degree of atrophy in Mesocorticolimbic regions positively correlated with the severity of depression, anxiety, and apathy in MCI-AD and ADD subgroups. Additionally, we observed significant alterations of metabolic connectivity between the ventral striatum and fronto-cingulate regions in ADD, but not in MCI-AD. There were no metabolic connectivity changes within the Nigrostriatal pathway.

CONCLUSION

Our cross-sectional data support a clinically-meaningful, yet stage-dependent, involvement of the Mesocorticolimbic system in AD. Longitudinal and clinical correlation studies are needed to further establish the relevance of DA system involvement in AD.

Brainstem atrophy in the early stage of Alzheimer's disease: a voxel-based morphometry study

Postmortem studies on patients with Alzheimer's disease (AD) have confirmed that the dorsal raphe nucleus (DRN) in the brainstem is the first brain structure affected in the earliest stage of AD. The present study examined the brainstem in the early stage of AD using magnetic resonance (MR) imaging. T1-weighted MR images of the brains of 81 subjects were obtained from the publicly available Open Access Series of Imaging Studies (OASIS) database, including 27 normal control (NC) subjects, 27 patients with very mild AD (AD-VM) and 27 patients with mild AD (AD-M). The brainstem was interactively segmented from the MR images using ITK-SNAP. The present voxel-based morphometry (VBM) study was designed to investigate the brainstem differences between the AD-VM/AD-M groups and the NC group. The results showed bilateral loss in the pons and the left part of the midbrain in the AD-M group compared to the NC group. The AD-M group showed greater loss in the left midbrain than the AD-VM group (P_FWEcorrected < 0.05). The results revealed that brainstem atrophy occurs in the early stages of AD (Clinical Dementia Rating = 0.5 and 1.0). Most of these findings were also investigated in a multicenter dataset. This is the first VBM study that provides evidence of brainstem alterations in the early stage of AD.

A predictive framework based on brain volume trajectories enabling early detection of Alzheimer's disease

We present a framework for constructing predictive models of cognitive decline from longitudinal MRI examinations, based on mixed effects models and machine learning. We apply the framework to detect conversion from cognitively normal (CN) to mild cognitive impairment (MCI) and from MCI to Alzheimer's disease (AD), using a large collection of subjects sourced from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Aging (AIBL). We extract subcortical segmentation and cortical parcellation from corresponding T1-weighted images using FreeSurfer v.6.0, select bilateral 3D regions of interest relevant to neurodegeneration/dementia, and fit their longitudinal volume trajectories using linear mixed effects models. Features describing these model-based trajectories are then used to train an ensemble of machine learning classifiers to distinguish stable CN from converters to MCI, and stable MCI from converters to AD. On separate test sets the models achieved an average of accuracy/precision/recall score of 69/73/60% for converted to MCI and 75/74/77% for converted to AD, illustrating the framework's ability to extract predictive imaging-based biomarkers from routine T1-weighted MRI acquisitions.

Hippocampal Subfield Volumes in Major Depressive Disorder Adolescents with a History of Suicide Attempt

Suicidal behavior is a leading cause of death and often commences during adolescence/young adulthood (15~29 years old). The hippocampus, which consists of multiple functionally specialized subfields, may contribute to the pathophysiology of depression and suicidal behavior. We aimed to investigate the differences of hippocampal subfield volume between major depressive disorder (MDD) patients with and without suicide attempts and healthy controls in adolescents and young adults. A total of 40 MDD suicide attempters (MDD+SA), 27 MDD patients without suicide attempt (MDD-SA), and 37 healthy controls (HC) were recruited. High-resolution T1 MRI images were analyzed with the automated hippocampal substructure module in FreeSurfer 6.0. Volume differences among the groups were analyzed by a generalized linear model controlling for intracranial cavity volume (ICV). The relationship between hippocampal subfield volumes and clinical characteristics (HAM-D and SSI scores) was assessed using two-tailed partial correlation controlling for ICV in MDD+SA and MDD-SA. We found that MDD-SA had significantly smaller bilateral hippocampal fissure volume than HC and MDD+SA. No significant correlation was observed between hippocampal subfield volume and clinical characteristics (HAM-D and SSI scores) in MDD+SA and MDD-SA. Adolescent/young adult suicide attempters with MDD suicide attempters have larger bilateral hippocampal fissures than depressed patients without suicide attempts, independently from clinical characteristics. Within the heterogeneous syndrome of major depressive disorder that holds a risk for suicidality for subgroups, hippocampal morphology may help to explain or possibly predict such risk, yet longitudinal and functional studies are needed for understanding the biological mechanisms underlying.

Gauging the role and impact of drug interactions and repurposing in neurodegenerative disorders

Neurodegenerative diseases (ND) are of vast origin which are characterized by gradual progressive loss of neurons in the brain region. ND can be classified according to the clinical symptoms present (e.g. Cognitive decline, hyperkinetic, and hypokinetic movements disorder) or by the pathological protein deposited (e.g., Amyloid, tau, Alpha-synuclein, TDP-43). Alzheimer's disease preceded by Parkinson's is the most prevalent form of ND world-wide. Multiple factors like aging, genetic mutations, environmental factors, gut microbiota, blood-brain barrier microvascular complication, etc. may increase the predisposition towards ND. Genetic mutation is a major contributor in increasing the susceptibility towards ND, the concept of one disease-one gene is obsolete and now multiple genes are considered to be involved in causing one particular disease. Also, the involvement of multiple pathological mechanisms like oxidative stress, neuroinflammation, mitochondrial dysfunction, etc. contributes to the complexity and makes them difficult to be treated by traditional mono-targeted ligands. In this aspect, the Poly-pharmacological drug approach which targets multiple pathological pathways at the same time provides the best way to treat such complex networked CNS diseases. In this review, we have provided an overview of ND and their pathological origin, along with a brief description of various genes associated with multiple diseases like Alzheimer's, Parkinson's, Multiple sclerosis (MS), Amyotrophic Lateral Sclerosis (ALS), Huntington's and a comprehensive detail about the Poly-pharmacology approach (MTDLs and Fixed-dose combinations) along with their merits over the traditional single-targeted drug is provided. This review also provides insights into current repurposing strategies along with its regulatory considerations.

Bridging Scales in Alzheimer's Disease: Biological Framework for Brain Simulation With The Virtual Brain

Despite the acceleration of knowledge and data accumulation in neuroscience over the last years, the highly prevalent neurodegenerative disease of AD remains a growing problem. Alzheimer's Disease (AD) is the most common cause of dementia and represents the most prevalent neurodegenerative disease. For AD, disease-modifying treatments are presently lacking, and the understanding of disease mechanisms continues to be incomplete. In the present review, we discuss candidate contributing factors leading to AD, and evaluate novel computational brain simulation methods to further disentangle their potential roles. We first present an overview of existing computational models for AD that aim to provide a mechanistic understanding of the disease. Next, we outline the potential to link molecular aspects of neurodegeneration in AD with large-scale brain network modeling using The Virtual Brain (www.thevirtualbrain.org), an open-source, multiscale, whole-brain simulation neuroinformatics platform. Finally, we discuss how this methodological approach may contribute to the understanding, improved diagnostics, and treatment optimization of AD.

Gray Matter Atrophy in Amnestic Mild Cognitive Impairment: A Voxel-Based Meta-Analysis

Background: Voxel-based morphometry (VBM) has been widely used to investigate structural alterations in amnesia mild cognitive impairment (aMCI). However, inconsistent results have hindered our understanding of the exact neuropathology related to aMCI. Objectives: Our aim was to systematically review the literature reporting VBM on aMCI to elucidate consistent gray matter alterations, their functional characterization, and corresponding co-activation patterns. Methods: The PubMed, Web of Science, and EMBASE databases were searched for VBM studies on aMCI published from inception up to June 2020. Peak coordinates were extracted from clusters that showed significant gray matter differences between aMCI patients and healthy controls (HC). Meta-analysis was performed using seed-based d mapping with the permutation of subject images (SDM-PSI), a newly improved meta-analytic method. Functional characterization and task-based co-activation patterns using the BrainMap database were performed on significant clusters to explore their functional roles. Finally, VBM was performed based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to further support the findings. Results: A total of 31 studies with 681 aMCI patients and 837 HC were included in this systematic review. The aMCI group showed significant gray matter atrophy in the left amygdala and right hippocampus, which was consistent with results from the ADNI dataset. Functional characterization revealed that these regions were mainly associated with emotion, cognition, and perception. Further, meta-regression analysis demonstrated that gray matter atrophy in the left inferior frontal gyrus and the left angular gyrus was significantly associated with cognitive impairment in the aMCI group. Conclusions: The findings of gray matter atrophy in the left amygdala and right hippocampus are highly consistent and robust, and not only offer a better understanding of the underlying neuropathology but also provide accurate potential biomarkers for aMCI.

Atrophic Pattern of Hippocampal Subfields in Post-Stroke Demented Patient

BACKGROUND

Previous studies have demonstrated that hippocampal atrophy is a hallmark of dementia and can be used to predict the outcome of post-stroke demented (PSD) patients. The hippocampus consists of several subfields but their involvement in the pathophysiology of the PSD remains unclear.

OBJECTIVE

The present study aimed to investigate volumetric alterations of hippocampal subfields in patients with PSD.

METHODS

High-resolution T1-weighted images were collected from 27 PSD and 28 post-stroke nondemented (PSND) patients who recovered from ischemic stroke, and 17 age-matched normal control (NC). We estimated the volumes of the hippocampal subfields using FreeSurfer 6.0 which segmented the hippocampus into 12 subfields in each hemisphere. The volumetric differences between the groups were evaluated by the two-sample tests after regressing out the age, sex, education, and total intracranial volume.

RESULTS

Compared with NC group, PSD group showed smaller volumes in the entire hippocampus and its subfields, and such differences were not found in PSND group. Moreover, we found the dementia-specific atrophy in the left granule cell layer of dentate gyrus (GC-DG) and CA4 in the PSD patients compared with NC and PSND. Regression analysis showed positive correlations between the changes of cognitive performance and the asymmetry index in the CA3/4 and GC-DG of the PSD group. Furthermore, we found that the volumes of hippocampal subfields provided a better classification performance than the entire hippocampus.

CONCLUSION

Our findings suggest that the hippocampus is reduced in the PSD patients and it presents a selective subfield involvement.

Association between Sour Taste SNP KCNJ2-rs236514, Diet Quality and Mild Cognitive Impairment in an Elderly Cohort

Differences in sour-taste thresholds have been identified in cognition-related diseases. Diet is a modulator of cognitive health, and taste perception influences dietary preferences and habits. Heritable genetics and polymorphisms in the KCNJ2 gene involved in the transduction of sour taste have been linked to variations in sour taste and non-gustatory functions. However, relationships between sour taste genetics, mild cognitive impairment, and diet quality are yet to be elucidated. This study investigated the associations between the presence of the KCNJ2-rs236514 variant (A) allele, diet quality indices, and mild cognitive impairment evaluated by the Mini-Mental State Examination (MMSE), in a secondary cross-sectional analysis of data from the Retirement Health & Lifestyle Study. Data from 524 elderly Australians (≥65y) were analyzed, using standard least squares regression and nominal logistic regression modeling, with demographic adjustments applied. Results showed that the presence of the KCNJ2-A allele is associated with increased proportions of participants scoring in the range indicative of mild or more severe cognitive impairment (MMSE score of ≤26) in the total cohort, and males. These associations remained statistically significant after adjusting for age, sex, and diet quality indices. The absence of association between the KCNJ2-A allele and cognitive impairment in women may be related to their higher diet quality scores in all indices. The potential link between sour taste genotype and cognitive impairment scores may be due to both oral and extra-oral functions of sour taste receptors. Further studies are required on the role and relationship of neurotransmitters, sour taste genotypes and sour taste receptors in the brain, and dietary implications, to identify potential risk groups or avenues for therapeutic or prophylactic interventions.

Cerebral amyloid accumulation is associated with distinct structural and functional alterations in the brain of depressed elders with mild cognitive impairment

BACKGROUND

Elderly patients with late-life depression (LLD) often report mild cognitive impairment (MCI), so Alzheimer's disease (AD) is hard to identify in these patients. We aimed to identify the structural and functional differences between prodromal AD and LLD-related MCI.

METHODS

We performed voxel-based morphometry and functional connectivity (FC) analyses in elderly patients with both LLD and MCI to compare alterations between those with cerebral amyloidopathy and those without. We subdivided patients into subthreshold depression (STD) and major depressive disorder (MDD) groups. Using florbetaben positron emission tomography (PET), we compared volume and connectivity between healthy controls and four STD and MDD groups with or without amyloid deposition(A): STD-MCI-A(+), MDD-MCI-A(+), STD-MCI-A(-), and MDD-MCI-A(-).

RESULTS

Subjects with MDD or amyloid deposition showed greater volume reduction in the left middle temporal gyrus. MDD groups had lower FC than STD groups in the frontal, cortical, and limbic areas. The STD-MCI-A(+) group showed greater FC reduction than the MDD-MCI-A(-) and STD-MCI-A(-) groups, particularly in the hippocampus, parahippocampus, and frontal and temporal cortices. The functional differences associated with amyloid plaques were more evident in the STD group than in the MDD group.

LIMITATIONS

Limitations include disproportional sex ratios, inability to determine the longitudinal effects of amyloidopathy in large populations.

CONCLUSIONS

Regional gray matter loss and alterations in brain networks may reflect impairments caused by amyloid deposition and depression. Such changes may facilitate the detection of prodromal AD in elderly patients with both depression and cognitive dysfunction, allowing earlier intervention and more appropriate treatment.

Detection Gap of Right-Asymmetric Neuronal Degeneration by CERAD Test Battery in Alzheimer's Disease

Objectives: Asymmetric disease characteristics on neuroimaging are common in structural and functional imaging of neurodegenerative diseases, particularly in Alzheimer‘s disease (AD). However, a standardized clinical evaluation of asymmetric neuronal degeneration and its impact on clinical findings has only sporadically been investigated for F-18-fluorodeoxyglucose positron emission tomography (F-18-FDG-PET). This study aimed to evaluate the impact of lateralized neuronal degeneration on the detection of AD by detailed clinical testing. Furthermore, we compared associations between clinical evaluation and lateralized neuronal degeneration between FDG-PET hypometabolism and hippocampal atrophy. Finally, we investigated if specific subtests show associations with lateralized neuronal degeneration.

Methods: One-hundred and forty-six patients with a clinical diagnosis of AD (age 71 ± 8) were investigated by FDG-PET and the “Consortium to Establish a Registry for Alzheimer’s disease” (CERAD) test battery. For assessment of neuronal degeneration, FDG-PET hypometabolism in brain regions typically affected in AD were graded by visual (3D-surface projections) and semiquantitative analysis. Asymmetry of the hippocampus (left-right) in magnetic resonance tomography (MRI) was rated visually by the Scheltens scale. Measures of asymmetry were calculated to quantify lateralized neuronal degeneration and asymmetry scores were subsequently correlated with CERAD.

Results: Asymmetry with left-dominant neuronal degeneration to FDG-PET was an independent predictor of cognitive impairment (visual: β = −0.288, p < 0.001; semiquantitative: β = −0.451, p < 0.001) when controlled for age, gender, years of education and total burden of neuronal degeneration, whereas hippocampal asymmetry to MRI was not (β = −0.034; p = 0.731). Direct comparison of CERAD-PET associations in cases with right- and left-lateralized neuronal degeneration estimated a detection gap of 2.7 years for right-lateralized cases. Left-hemispheric neuronal degeneration was significantly associated with the total CERAD score and multiple subscores, whereas only MMSE (semiquantitative: β = 0.429, p < 0.001) and constructional praxis (semiquantitative: β = 0.292, p = 0.008) showed significant associations with right-hemispheric neuronal degeneration.

Conclusions: Asymmetry of deteriorated cerebral glucose metabolism has a significant impact on the coupling between neuronal degeneration and cognitive function. Right dominant neuronal degeneration shows a delayed detection by global CERAD testing and requires evaluation of specific subdomains of cognitive testing.

Hippocampal shape and asymmetry analysis by cascaded convolutional neural networks for Alzheimer's disease diagnosis

Hippocampal atrophy is often considered as one of the important biomarkers for early diagnosis of Alzheimer's disease (AD), which is an irreversible neurodegenerative disorder. Traditional methods for hippocampus analysis usually computed the shape and volume features from structural Magnetic Resonance Image (sMRI) for the computer-aided diagnosis of AD as well as its prodromal stage, i.e., mild cognitive impairment (MCI). Motivated by the success of deep learning, this paper proposes a deep learning method with the multi-channel cascaded convolutional neural networks (CNNs) to gradually learn the combined hierarchical representations of hippocampal shapes and asymmetries from the binary hippocampal masks for AD classification. First, image segmentation is performed to generate the bilateral hippocampus binary masks for each subject and the mask difference is obtained by subtracting them. Second, multi-channel 3D CNNs are individually constructed on the hippocampus masks and mask differences to extract features of hippocampal shapes and asymmetries for classification. Third, a 2D CNN is cascaded on the 3D CNNs to learn high-level correlation features. Finally, the features learned by multi-channel and cascaded CNNs are combined with a fully connected layer followed by a softmax classifier for disease classification. The proposed method can gradually learn the combined hierarchical features of hippocampal shapes and asymmetries to enhance the classification. Our method is verified on the baseline sMRIs from 807 subjects including 194 AD patients, 397 MCI (164 progressive MCI (pMCI) + 233 stable MCI (sMCI)), and 216 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Experimental results demonstrate that the proposed method achieves an AUC (Area Under the ROC Curve) of 88.4%, 74.6% and 71.9% for AD vs. NC, MCI vs. NC and pMCI vs. sMCI classifications, respectively. It proves the promising classification performance and also shows that both hippocampal shape and asymmetry are helpful for AD diagnosis.

Incomplete hippocampal inversion in schizophrenia: prevalence, severity, and impact on hippocampal structure

Incomplete hippocampal inversion (IHI) is an anatomical variant of the human brain resulting from an arrest in brain development, especially prevalent in the left hemisphere. We hypothesized that IHI is more common in schizophrenia and contributes to the well-known hippocampal structural differences. We studied 199 schizophrenia patients and 161 healthy control participants with 3 T MRI to establish IHI prevalence and the relationship of IHI with hippocampal volume and asymmetry. IHI was more prevalent (left hemisphere: 15% of healthy control participants, 27% of schizophrenia patients; right hemisphere: 4% of healthy control participants, 10% of schizophrenia patients) and more severe in schizophrenia patients compared to healthy control participants. Severe IHI cases were associated with a higher rate of automated segmentation failure. IHI contributed to smaller hippocampal volume and increased R > L volume asymmetry in schizophrenia. The increased prevalence and severity of IHI supports the neurodevelopmental model of schizophrenia. The impact of this developmental variant deserves further exploration in studies of the hippocampus in schizophrenia.

The effects of cognitive training on the topological properties of brain structural network among community-dwelling older adults

Increased number of neuroimaging studies has revealed association between age-related cognitive decline and alterations in the architecture of brain networks, while trials consistently confirmed benefits following cognitive training in the elderly. As a consequence, the present study aimed to investigate the potential moderating role of topological properties in brain structural network on training benefits. Among 32 community-dwelling older adults, 18 were randomly assigned to the training group to receive 24 sessions of multi-domain cognitive training (MDCT) over 12 weeks, and 14 to the control group. At baseline and 12-month follow-up, diffusion tensor imaging was acquired to construct the brain structural network, and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the Visual Reasoning Test (VRT) were performed to assess cognitive functions. Compared with controls, participants received MDCT achieved significant larger gain in terms of delayed memory with a trend of better global cognitive function. In addition, Sigma coefficient of small-worldness were reduced in the MDCT group relative to the control group. Correlation between changes in Sigma and in delayed memory index were found among controls, however, not among older adults received MDCT. Our results demonstrated the modulating effects of cognitive training on the small-world architecture of brain structural network. And the present study suggested a trade-off mechanism underlying the benefits of cognitive training among aged people, where brain sacrificed its cost-effectiveness of network wiring for better cognitive functions.

Age-Related Structural and Functional Changes of the Hippocampus and the Relationship with Inhibitory Control

Aging is associated with structural and functional changes in the hippocampus, and hippocampal dysfunction represents a risk marker of Alzheimer’s disease. Previously, we demonstrated age-related changes in reactive and proactive control in the stop signal task, each quantified by the stop signal reaction time (SSRT) and sequential effect computed as the correlation between the estimated stop signal probability and go trial reaction time. Age was positively correlated with the SSRT, but not with the sequential effect. Here, we explored hippocampal gray matter volume (GMV) and activation to response inhibition and to p(Stop) in healthy adults 18 to 72 years of age. The results showed age-related reduction of right anterior hippocampal activation during stop success vs. go trials, and the hippocampal activities correlated negatively with the SSRT. In contrast, the right posterior hippocampus showed higher age-related responses to p(Stop), but the activities did not correlate with the sequential effect. Further, we observed diminished GMVs of the anterior and posterior hippocampus. However, the GMVs were not related to behavioral performance or regional activities. Together, these findings suggest that hippocampal GMVs and regional activities represent distinct neural markers of cognitive aging, and distinguish the roles of the anterior and posterior hippocampus in age-related changes in cognitive control.

Exercise interventions preserve hippocampal volume: A meta-analysis

Hippocampal volume is a marker of brain health and is reduced with aging and neurological disease. Exercise may be effective at increasing and preserving hippocampal volume, potentially serving as a treatment for conditions associated with hippocampal atrophy (e.g., dementia). This meta-analysis aimed to identify whether exercise training has a positive effect on hippocampal volume and how population characteristics and exercise parameters moderate this effect. Studies met the following criteria: (a) controlled trials; (b) interventions of physical exercise; (c) included at least one time-point of hippocampal volume data before the intervention and one after; (d) assessed hippocampal volume using either manual or automated segmentation algorithms. Animal studies, voxel-based morphometry analyses, and multi-modal interventions (e.g., cognitive training or meditation) were excluded. The primary analysis in n = 23 interventions from 22 published studies revealed a significant positive effect of exercise on total hippocampal volume. The overall effect was significant in older samples (65 years of age or older) and in interventions that lasted over 24 weeks and had less than 150 min per week of exercise. These findings suggest that moderate amounts of exercise for interventions greater than 6 months have a positive effect on hippocampal volume including in older populations vulnerable to hippocampal atrophy.

Relationship between inflammatory biomarker galectin-3 and hippocampal volume in a community study

Galectin-3 (Gal3) is expressed by microglia and performs functions including adhesion; activation of macrophages and fibroblasts, and mediates inflammatory responses in the hippocampus. The present study examined whether serum Gal3 levels predict hippocampal volume in a multi-ethnic, community-based sample. Results of a multiple linear regression (controlling for depression, serum creatinine level, age, BMI, total brain volume, MoCA score, sex, ethnicity, smoking status, history of diabetes) showed that Gal3 levels significantly predicted left (p = .027) but not right hippocampal volume. The relationship was stronger in men than women. Findings suggest this novel inflammatory biomarker is associated with human hippocampal volume.

Contributions of Hippocampal Volume to Cognition in Healthy Older Adults

Objective: The association between hippocampal volume and memory is continuing to be characterized in healthy older adults. Prior research suggests smaller hippocampal volume in healthy older adults is associated with poorer episodic memory and processing speed, as well as working memory, verbal learning, and executive functioning as measured by the NIH Toolbox Fluid (Fluid Cognition Composite, FCC) and Crystalized Cognition Composites (CCC). This study aimed to replicate these findings and to evaluate the association between: (1) hippocampal asymmetry index and cognition; and (2) independent contributions of the left and right hippocampal volume and cognition in a large sample of healthy older adults. Participants and Methods: One-hundred and eighty-three healthy older adults (M age = 71.72, SD = 5.3) received a T1-weighted sequence on a 3T scanner. Hippocampal subfields were extracted using FreeSurfer 6.0 and combined to provide left, right, and total hippocampal volumes. FCC subtests include Dimensional Change Card Sort, Flanker Inhibitory Control and Attention, List Sorting, Picture Sequence Memory, and Pattern Comparison. CCC subtests include Picture Vocabulary and Oral Reading Recognition. Multiple linear regressions were performed predicting cognition composites from the total, left and right, and asymmetry of hippocampal volume, controlling for sex, education, scanner, and total intracranial volume. Multiple comparisons in primary analyses were corrected using a false discovery rate (FDR) of p < 0.05. Results: FCC scores were positively associated with total (β = 0.226, FDR q = 0.044) and left (β = 0.257, FDR q = 0.024) hippocampal volume. Within FCC, Picture Sequence Memory scores positively associated with total (β = 0.284, p = 0.001) and left (β = 0.98, p = 0.001) hippocampal volume. List Sorting scores were also positively associated with left hippocampal volume (β = 0.189, p = 0.029). Conclusions: These results confirm previous research suggesting that bilateral hippocampal volume is associated with FCC, namely episodic memory. The present study also suggests the left hippocampal volume may be more broadly associated with both episodic and working memory. Studies should continue to investigate lateralized hippocampal contributions to aging processes to better identify predictors of cognitive decline.

Does the Right Focal Variant of Alzheimer's Disease Really Exist? A Literature Analysis

BACKGROUND

Alzheimer's disease (AD) is a clinically heterogeneous disease. Multiple atypical syndromes, distinct from the usual amnesic phenotype, have been described. In this context, the existence of a right variant of AD (RAD), characterized by enduring visuospatial impairment associated with right-sided asymmetric brain damage, has been proposed. However, to date, this phenotype remains controversial. In particular, its peculiar characteristics and the independence from more prevalent cases (especially the posterior cortical atrophy syndrome) have to be demonstrated.

OBJECTIVE

To explore the existence of focal RAD on the basis of existing literature.

METHODS

We performed a literature search for the description of atypical AD presentations, potentially evoking cases of focal RAD. To be considered as affected by RAD, the described cases had to present: 1) well documented right-sided asymmetry at neuroimaging; 2) predominant cognitive deficits localizable on the right hemisphere; 3) no specific diagnosis of a known variant of AD.

RESULTS

Twenty-one cases were found in the literature, but some of them were subsequently excluded because some features of a different clinical syndrome were overlapped with the clinical features of RAD. Thirteen positive cases, three of them with pathologically confirmed AD, remained. A common right clinical-radiological syndrome, characterized by memory and visuospatial impairment with temporal and parietal involvement, consistently emerged. However, the heterogeneity among the reports prevented a definitive and univocal description of the syndrome.

CONCLUSION

Even if sporadic observations strongly support the existence of a focal RAD, no definitive conclusions can still be drawn about it as an independent condition.

Long-Term Ambient Air Pollution Exposures and Brain Imaging Markers in Korean Adults: The Environmental Pollution-Induced Neurological EFfects (EPINEF) Study

BACKGROUND

Only a limited number of neuroimaging studies have explored the effects of ambient air pollution in adults. The prior studies have investigated only cortical volume, and they have reported mixed findings, particularly for gray matter. Furthermore, the association between nitrogen dioxide (NO2) and neuroimaging markers has been little studied in adults.

OBJECTIVES

We investigated the association between long-term exposure to air pollutants (NO2, particulate matter (PM) with aerodynamic diameters of ≤10μm (PM10) and ≤2.5μm (PM2.5), and neuroimaging markers.

METHODS

The study included 427 men and 530 women dwelling in four cities in the Republic of Korea. Long-term concentrations of PM10, NO2, and PM2.5 at residential addresses were estimated. Neuroimaging markers (cortical thickness and subcortical volume) were obtained from brain magnetic resonance images. A generalized linear model was used, adjusting for potential confounders.

RESULTS

A 10-μg/m3 increase in PM10 was associated with reduced thicknesses in the frontal [-0.02mm (95% CI: -0.03, -0.01)] and temporal lobes [-0.06mm (95% CI: -0.07, -0.04)]. A 10-μg/m3 increase in PM2.5 was associated with a thinner temporal cortex [-0.18mm (95% CI: -0.27, -0.08)]. A 10-ppb increase in NO2 was associated with reduced thicknesses in the global [-0.01mm (95% CI: -0.01, 0.00)], frontal [-0.02mm (95% CI: -0.03, -0.01)], parietal [-0.02mm (95% CI: -0.03, -0.01)], temporal [-0.04mm (95% CI: -0.05, -0.03)], and insular lobes [-0.01mm (95% CI: -0.02, 0.00)]. The air pollutants were also associated with increased thicknesses in the occipital and cingulate lobes. Subcortical structures associated with the air pollutants included the thalamus, caudate, pallidum, hippocampus, amygdala, and nucleus accumbens.

DISCUSSION

The findings suggest that long-term exposure to high ambient air pollution may lead to cortical thinning and reduced subcortical volume in adults. https://doi.org/10.1289/EHP7133.

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.

Sex differences in cortisol and memory following acute social stress in amnestic mild cognitive impairment

OBJECTIVE

Older adults with amnestic mild cognitive impairment (aMCI) develop Alzheimer's type dementia approximately 10 times faster annually than the normal population. Adrenal hormones are associated with aging and cognition. We investigated the relationship between acute stress, cortisol, and memory function in aMCI with an exploratory analysis of sex.

METHOD

Salivary cortisol was sampled diurnally and during two test sessions, one session with the Trier Social Stress Test (TSST), to explore differences in the relationship between cortisol and memory function in age-normal cognition (NA) and aMCI. Participants with aMCI (n = 6 women, 9 men; mean age = 75) or similarly aged NA (n = 9 women, 7 men, mean age = 75) were given tests of episodic, associative, and spatial working memory with a psychosocial stressor (TSST) in the second session.

RESULTS

The aMCI group performed worse on the memory tests than NA as expected, and males with aMCI had elevated cortisol levels on test days. Immediate episodic memory was enhanced by social stress in NA but not in the aMCI group, indicating that stress-induced alterations in memory are different in individuals with aMCI. High cortisol was associated with impaired performance on episodic memory in aMCI males only. Cortisol in Session 1 moderated the relationship with spatial working memory, whereby higher cortisol was associated with worse performance in NA, but better spatial working memory in aMCI. In addition, effects of aMCI on perceived anxiety in response to stress exposure were moderated by stress-induced cortisol in a sex-specific manner.

CONCLUSIONS

We show effects of aMCI on Test Session cortisol levels and effects on perceived anxiety, and stress-induced impairments in memory in males with aMCI in our exploratory sample. Future studies should explore sex as a biological variable as our findings suggest that effects at the confluence of aMCI and stress can be obfuscated without sex as a consideration.

Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images from ADNI, AIBL, OASIS, and MIRIAD databases

Biomarkers for dementia of Alzheimer's type (DAT) are sought to facilitate accurate prediction of the disease onset, ideally predating the onset of cognitive deterioration. T1-weighted magnetic resonance imaging (MRI) is a commonly used neuroimaging modality for measuring brain structure in vivo, potentially providing information enabling the design of biomarkers for DAT. We propose a novel biomarker using structural MRI volume-based features to compute a similarity score for the individual's structural patterns relative to those observed in the DAT group. We employed ensemble-learning framework that combines structural features in most discriminative ROIs to create an aggregate measure of neurodegeneration in the brain. This classifier is trained on 423 stable normal control (NC) and 330 DAT subjects, where clinical diagnosis is likely to have the highest certainty. Independent validation on 8,834 unseen images from ADNI, AIBL, OASIS, and MIRIAD Alzheimer's disease (AD) databases showed promising potential to predict the development of DAT depending on the time-to-conversion (TTC). Classification performance on stable versus progressive mild cognitive impairment (MCI) groups achieved an AUC of 0.81 for TTC of 6 months and 0.73 for TTC of up to 7 years, achieving state-of-the-art results. The output score, indicating similarity to patterns seen in DAT, provides an intuitive measure of how closely the individual's brain features resemble the DAT group. This score can be used for assessing the presence of AD structural atrophy patterns in normal aging and MCI stages, as well as monitoring the progression of the individual's brain along with the disease course.

Atrophy associated with tau pathology precedes overt cell death in a mouse model of progressive tauopathy

Tau pathology in Alzheimer's disease (AD) first develops in the entorhinal cortex (EC), then spreads to the hippocampus, followed by the neocortex. Overall, tau pathology correlates well with neurodegeneration and cell loss, but the spatial and temporal association between tau pathology and overt volume loss (atrophy) associated with structural changes or cell loss is unclear. Using in vivo magnetic resonance imaging (MRI) with tensor-based morphometry (TBM), we mapped the spatiotemporal pattern of structural changes in a mouse model of AD-like progressive tauopathy. A novel, coregistered in vivo MRI atlas was then applied to identify regions in the medial temporal lobe that had a significant volume reduction. Our study shows that in a mouse model of tauopathy spread, the propagation of tau pathology from the EC to the hippocampus is associated with TBM-related atrophy, but atrophy in the dentate gyrus and subiculum precedes overt cell loss.

Aberrant White Matter Microstructure as a Potential Diagnostic Marker in Alzheimer's Disease by Automated Fiber Quantification

Neuroimaging evidence has suggested white matter microstructure are heavily affected in Alzheimer's disease (AD). However, whether white matter dysfunction is localized at the specific regions of fiber tracts and whether they would be a potential biomarker for AD remain unclear. By automated fiber quantification (AFQ), we applied diffusion tensor images from 25 healthy controls (HC), 24 amnestic mild cognitive impairment (aMCI) patients and 18 AD patients to create tract profiles along 16 major white matter fibers. We compared diffusion metrics [Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR)] between groups. To assess the diagnostic value, we applied a random forest (RF) classifier, a type of machine learning method. In the global tract level, we found that aMCI and AD patients showed higher MD, DA, and DR values in some fiber tracts mostly in the left hemisphere compared to HC. In the point-wise level, widespread disruption were distributed on specific locations of different tracts. The point-wise MD measurements presented the best classification performance with respect to differentiating AD from HC. The two most important variables were localized in the prefrontal potion of left uncinate fasciculus and anterior thalamic radiation. In addition, the point-wise DA in the posterior component of the left cingulum cingulate displayed the most robust discriminative ability to identify AD from aMCI. Our findings provide evidence that white matter abnormalities based on the AFQ method could be as a diagnostic biomarker in AD.