Frequency of hippocampal formation atrophy in normal aging and Alzheimer's disease

Alterations in driving ability and their relationship with morphometric magnetic resonance imaging indicators in patients with amnestic mild cognitive impairment and Alzheimer's disease

BACKGROUND

Drivers with dementia are at a higher risk of motor vehicle accidents. The characteristics of driving behaviour of patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) have not been fully elucidated. We investigated driving ability and its relationship with cognitive function and magnetic resonance imaging (MRI) morphometry indicators.

METHODS

The driving abilities of 19 patients with AD and 11 with amnestic MCI (aMCI) were evaluated using a driving simulator. The association between each driving ability parameter and the Mini-Mental State Examination (MMSE) score or voxel-based specific regional analysis system for AD (VSRAD) was assessed.

RESULTS

Patients with AD made a significantly higher number of operational errors than those with aMCI in attention allocation in the complex task test (P = 0.0008). The number of operational errors in attention allocation in the complex task test significantly and negatively correlated with MMSE scores in all participants (r = -0.4354, P = 0.0162). The decision time in the selective reaction test significantly and positively correlated with the severity and extent of medial temporal structural atrophy (r = 0.4807, P = 0.0372; r = 0.4862, P = 0.0348; respectively).

CONCLUSION

An increase in the operational errors for attention allocation in the complex task test could be a potential indicator of progression from aMCI to AD. Atrophy of the medial temporal structures could be a potential predictor of impaired judgement in driving performance in aMCI and AD. A driving simulator could be useful for evaluating the driving abilities of individuals with aMCI and AD.

Hippocampal microstructure, but not macrostructure, mediates age differences in episodic memory

Introduction

Separate unimodal magnetic resonance imaging (MRI) literatures have shown that hippocampal gray matter macrostructure (volume) and microstructure (diffusion) decline with age and relate to episodic memory performance, with multimodal MRI studies reporting that episodic memory may be better explained by a combination of these metrics. However, these effects are often assessed independent of age or only within older adults and therefore do not address whether these distinct modalities explain variance in (i.e, mediate) the effect of age on episodic memory.

Methods

Here, we simultaneously examined the unique and joint contribution of hippocampal volume and diffusion to age-related differences in episodic memory in 83 younger and 61 older adults who underwent a T1- and diffusion-weighted MRI and completed the Rey Auditory Verbal Learning Test.

Results

As expected, older age was significantly related to smaller volume and higher diffusion (intracellular, dispersion, and free) in bilateral hippocampus and to worse episodic memory performance (immediate and delayed free recall, recognition). Structural equation modelling revealed that the age-memory relationship was significantly mediated by hippocampal diffusion, but not volume. A non-significant influential indirect effect further revealed that the structural metrics did not jointly mediate the age-memory relationship.

Discussion

Together, these findings indicate that hippocampal microstructure uniquely contributes to age-related differences in episodic memory and suggest that volume and diffusion capture distinct neurobiological properties of hippocampal gray matter.

Clinical trials of new drugs for Alzheimer disease: a 2020-2023 update

Alzheimer's disease (AD) is the leading cause of dementia, presenting a significant unmet medical need worldwide. The pathogenesis of AD involves various pathophysiological events, including the accumulation of amyloid and tau, neuro-inflammation, and neuronal injury. Clinical trials focusing on new drugs for AD were documented in 2020, but subsequent developments have emerged since then. Notably, the US-FDA has approved Aducanumab and Lecanemab, both antibodies targeting amyloid, marking the end of a nearly two-decade period without new AD drugs. In this comprehensive report, we review all trials listed in clinicaltrials.gov, elucidating their underlying mechanisms and study designs. Ongoing clinical trials are investigating numerous promising new drugs for AD. The main trends in these trials involve pathophysiology-based, disease-modifying therapies and the recruitment of participants in earlier stages of the disease. These trends underscore the significance of conducting fundamental research on pathophysiology, prevention, and intervention prior to the occurrence of brain damage caused by AD.

The major TMEM106B dementia risk allele affects TMEM106B protein levels, fibril formation, and myelin lipid homeostasis in the ageing human hippocampus

BACKGROUND

The risk for dementia increases exponentially from the seventh decade of life. Identifying and understanding the biochemical changes that sensitize the ageing brain to neurodegeneration will provide new opportunities for dementia prevention and treatment. This study aimed to determine how ageing and major genetic risk factors for dementia affect the hippocampal proteome and lipidome of neurologically-normal humans over the age of 65. The hippocampus was chosen as it is highly susceptible to atrophy with ageing and in several neurodegenerative diseases.

METHODS

Mass spectrometry-based proteomic and lipidomic analysis of CA1 hippocampus samples from 74 neurologically normal human donors, aged 66-104, was used in combination with multiple regression models and gene set enrichment analysis to identify age-dependent changes in the proteome and lipidome. ANOVA was used to test the effect of major dementia risk alleles in the TMEM106B and APOE genes on the hippocampal proteome and lipidome, adjusting for age, gender, and post-mortem interval. Fibrillar C-terminal TMEM106B fragments were isolated using sarkosyl fractionation and quantified by immunoblotting.

RESULTS

Forty proteins were associated with age at false discovery rate-corrected P < 0.05, including proteins that regulate cell adhesion, the cytoskeleton, amino acid and lipid metabolism, and ribosomal subunits. TMEM106B, a regulator of lysosomal and oligodendrocyte function, was regulated with greatest effect size. The increase in TMEM106B levels with ageing was specific to carriers of the rs1990622-A allele in the TMEM106B gene that increases risk for frontotemporal dementia, Alzheimer's disease, Parkinson's disease, and hippocampal sclerosis with ageing. Rs1990622-A was also associated with higher TMEM106B fibril content. Hippocampal lipids were not significantly affected by APOE genotype, however levels of myelin-enriched sulfatides and hexosylceramides were significantly lower, and polyunsaturated phospholipids were higher, in rs1990622-A carriers after controlling for APOE genotype.

CONCLUSIONS

Our study demonstrates that TMEM106B protein abundance is increased with brain ageing in humans, establishes that dementia risk allele rs1990622-A predisposes to TMEM106B fibril formation in the hippocampus, and provides the first evidence that rs1990622-A affects brain lipid homeostasis, particularly myelin lipids. Our data suggests that TMEM106B is one of a growing list of major dementia risk genes that affect glial lipid metabolism.

Changes in the Mitochondria in the Aging Process-Can α-Tocopherol Affect Them?

Aerobic organisms use molecular oxygen in several reactions, including those in which the oxidation of substrate molecules is coupled to oxygen reduction to produce large amounts of metabolic energy. The utilization of oxygen is associated with the production of ROS, which can damage biological macromolecules but also act as signaling molecules, regulating numerous cellular processes. Mitochondria are the cellular sites where most of the metabolic energy is produced and perform numerous physiological functions by acting as regulatory hubs of cellular metabolism. They retain the remnants of their bacterial ancestors, including an independent genome that encodes part of their protein equipment; they have an accurate quality control system; and control of cellular functions also depends on communication with the nucleus. During aging, mitochondria can undergo dysfunctions, some of which are mediated by ROS. In this review, after a description of how aging affects the mitochondrial quality and quality control system and the involvement of mitochondria in inflammation, we report information on how vitamin E, the main fat-soluble antioxidant, can protect mitochondria from age-related changes. The information in this regard is scarce and limited to some tissues and some aspects of mitochondrial alterations in aging. Improving knowledge of the effects of vitamin E on aging is essential to defining an optimal strategy for healthy aging.

Whole-brain structure-function coupling abnormalities in mild cognitive impairment: a study combining amplitude of low-frequency fluctuations and voxel-based morphometry

Alzheimer's disease (AD), one of the leading diseases of the nervous system, is accompanied by symptoms such as loss of memory, thinking and language skills. Both mild cognitive impairment (MCI) and very mild cognitive impairment (VMCI) are the transitional pathological stages between normal aging and AD. While the changes in whole-brain structural and functional information have been extensively investigated in AD, The impaired structure-function coupling remains unknown. The current study employed the OASIS-3 dataset, which includes 53 MCI, 90 VMCI, and 100 Age-, gender-, and education-matched normal controls (NC). Several structural and functional parameters, such as the amplitude of low-frequency fluctuations (ALFF), voxel-based morphometry (VBM), and The ALFF/VBM ratio, were used To estimate The whole-brain neuroimaging changes In MCI, VMCI, and NC. As disease symptoms became more severe, these regions, distributed in the frontal-inf-orb, putamen, and paracentral lobule in the white matter (WM), exhibited progressively increasing ALFF (ALFFNC < ALFFVMCI < ALFFMCI), which was similar to the tendency for The cerebellum and putamen in the gray matter (GM). Additionally, as symptoms worsened in AD, the cuneus/frontal lobe in the WM and the parahippocampal gyrus/hippocampus in the GM showed progressively decreasing structure-function coupling. As the typical focal areas in AD, The parahippocampal gyrus and hippocampus showed significant positive correlations with the severity of cognitive impairment, suggesting the important applications of the ALFF/VBM ratio in brain disorders. On the other hand, these findings from WM functional signals provided a novel perspective for understanding the pathophysiological mechanisms involved In cognitive decline in AD.

Default mode network failure and neurodegeneration across aging and amnestic and dysexecutive Alzheimer's disease

From a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer's disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals (N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer's disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic (N = 8) or dysexecutive (N = 10) Alzheimer's disease from the normative cohort at the patient level, as well as between Alzheimer's disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer's disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer's disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer's disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer's disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer's disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer's disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials.

MOG antibody-associated encephalitis in adult: clinical phenotypes and outcomes

BACKGROUND

We investigated the clinical characteristics and outcomes of myelin oligodendrocyte glycoprotein (MOG) antibody-associated autoimmune encephalitis (MOGAE) in adult patients.

METHODS

From an institutional cohort, we analysed adult patients with MOGAE followed-up for more than 1 year. Disease severity was assessed using the modified Rankin scale (mRS) and Clinical Assessment Scale in Autoimmune Encephalitis scores. Immunotherapy profiles, outcomes and disease relapses were evaluated along with serial brain MRI data.

RESULTS

A total of 40 patients were enrolled and categorised into cortical encephalitis (18 patients), limbic encephalitis (LE, 5 patients) and acute disseminated encephalomyelitis (ADEM, 17 patients). 80.0% of patients achieved good clinical outcomes (mRS 0‒2) and 40.0% relapsed. The LE subtype was associated with an older onset age (p=0.004) and poor clinical outcomes (p=0.014) than the other subtypes but with a low rate of relapse (0.0%). 21/25 (84.0%) relapse attacks were associated with an absence or short (≤6 months) immunotherapy maintenance. On MRI, the development of either diffuse cerebral or medial temporal atrophy within the first 6 month was correlated with poor outcomes. MOG-antibody (MOG-Ab) was copresent with anti-N-methyl-D-aspartate receptor (NMDAR)-antibody in 13 patients, in whom atypical clinical presentation (cortical encephalitis or ADEM, p<0.001) and disease relapse (46.2% vs 0.0%, p<0.001) were more frequent compared with conventional NMDAR encephalitis without MOG-Ab.

CONCLUSIONS

Outcomes are different according to the three phenotypes in MOGAE. Short immunotherapy maintenance is associated with relapse, and brain atrophy was associated with poor outcomes. Patients with dual antibodies of NMDAR and MOG have a high relapse rate.

The major TMEM106B dementia risk allele affects TMEM106B protein levels and myelin lipid homeostasis in the ageing human hippocampus

Background The risk for dementia increases exponentially from the seventh decade of life. Identifying and understanding the biochemical changes that sensitize the ageing brain to neurodegeneration will provide new opportunities for dementia prevention and treatment. This study aimed to determine how ageing and major genetic risk factors for dementia affect the hippocampal proteome and lipidome of neurologically-normal humans over the age of 65. The hippocampus was chosen as it is highly susceptible to atrophy with ageing and in several neurodegenerative diseases. Methods Mass spectrometry-based proteomic and lipidomic analysis of CA1 hippocampus samples from 74 neurologically normal human donors, aged 66-104, was used in combination with multiple regression models and gene set enrichment analysis to identify age-dependent changes in the proteome and lipidome. ANOVA was used to test the effect of major dementia risk alleles in the TMEM106B and APOE genes on the hippocampal proteome and lipidome, adjusting for age, gender, and post-mortem interval. Results Forty proteins were associated with age at false discovery rate-corrected P < 0.05, including proteins that regulate cell adhesion, the cytoskeleton, amino acid and lipid metabolism, and ribosomal subunits. Transmembrane protein 106B (TMEM106B), a regulator of lysosomal and oligodendrocyte function, was regulated with greatest effect size. The increase in TMEM106B levels with age was specific to carriers of the rs1990622-A allele in the TMEM106B gene that is associated with increased risk for frontotemporal dementia, Alzheimer's disease, Parkinson's disease, and hippocampal sclerosis with ageing. Hippocampal lipids were not significantly affected by APOE genotype, however levels of myelin-enriched sulfatides and hexosylceramides were significantly lower, and polyunsaturated phospholipids were higher, in rs1990622-A carriers after controlling for APOE genotype. Conclusions Our study provides the first evidence that TMEM106B protein abundance is increased with brain ageing in humans, and the first evidence that the major TMEM106B dementia risk allele affects brain lipid homeostasis, with a clear effect on myelin lipid content. Our data implies that TMEM106B is one of a growing list of major dementia risk genes that affect glial lipid metabolism.

Cannabinoids in neuroinflammatory disorders: Focusing on multiple sclerosis, Parkinsons, and Alzheimers diseases

The medicinal properties of cannabis and cannabinoid-derivative are entirely investigated and known. In addition, the identification of psychotropic plant cannabinoids has led to more studies regarding the cannabinoid system and its therapeutic features in the treatment and management of clinical symptoms of neuroinflammatory disorders, such as multiple sclerosis (MS), Parkinsons disease (PD), and Alzheimers disease (AD). In fact, cannabinoid agonists are able to control and regulate inflammatory responses. In contrast to the cannabinoid receptor type 1 (CB1) and its unwanted adverse effects, the cannabinoid receptor type 2 (CB2) and its ligands hold promise for new and effective therapeutic approaches. So far, some successes have been achieved in this field. This review will discuss an outline of the endocannabinoid system's involvement in neuroinflammatory disorders. Moreover, the pharmacological efficacy of different natural and synthetic preparations of phytocannabinoids acting on cannabinoid receptors, particularly in MS, PD, and AD, will be updated. Also, the reasons for targeting CB2 for neurodegeneration will be explained.

Seronegative autoimmune encephalitis: clinical characteristics and factors associated with outcomes

Seronegative autoimmune encephalitis is autoimmune encephalitis without any identifiable pathogenic antibody. Although it is a major subtype of autoimmune encephalitis, many unmet clinical needs exist in terms of clinical characteristics, treatments and prognosis. In this institutional cohort study, patients diagnosed with seronegative autoimmune encephalitis with available 2-year outcomes were analysed for the disease course, 2-year outcome prediction system, effect of immunotherapy, necessity of further immunotherapy at 6 or 12 months and pattern of brain atrophy. Seronegative autoimmune encephalitis was subcategorized into antibody-negative probable autoimmune encephalitis, autoimmune limbic encephalitis and acute disseminated encephalomyelitis. Poor 2-year outcome was defined by modified Rankin scale scores 3-6, and the 2-year serial data of Clinical Assessment Scales in Autoimmune Encephalitis score was used for longitudinal data analyses. A total of 147 patients were included. The frequency of achieving a good 2-year outcome (modified Rankin scale 0-2) was 56.5%. The antibody-negative probable autoimmune encephalitis subtype exhibited the poorest outcomes, although the baseline severity was similar among the subtypes. The RAPID score, consisting of five early usable clinical factors, refractory status epilepticus, age of onset ≥60 years, probable autoimmune encephalitis (antibody-negative probable autoimmune encephalitis subtype), infratentorial involvement and delay of immunotherapy ≥1 month, was associated with poorer 2-year outcomes. Any immunotherapy was associated with clinical improvement in the patients with low risk for poor 2-year outcomes (RAPID scores 0-1), and the combination immunotherapy of steroid, immunoglobulin, rituximab and tocilizumab was associated with better outcomes in the patients with high risk for poor 2-year outcomes (RAPID scores 2-5). In patients with persistent disease at 6 months, continuing immunotherapy was associated with more improvement, while the effect of continuing immunotherapy for more than 12 months was unclear. In the longitudinal analysis of MRI, the development of cerebellar atrophy indicated poor outcomes, while the absence of diffuse cerebral atrophy or medial temporal atrophy indicated the possibility of a good outcome. This study provides information about the clinical characteristics and courses, the effect of immunotherapy and its duration, and prognostic factors in seronegative autoimmune encephalitis.

Neuropathology and cholinesterase expression in the brains of octogenarians and older

A subset of octogenarians and older maintain normal cognitive function (CNOO) despite high prevalence and incidence of cognitive decline attributed to neurodegeneration or aging in the population. The rostral prefrontal cortex (rPFC) and hippocampal formation are brain regions integral to cognition, namely attention and memory, facilitated in part by cholinergic innervation. We hypothesized that preserved cholinergic neurotransmission in these regions contributes to intact cognition in the CNOO. To test this, we evaluated the burden of neuropathological and cholinesterase-associated protein aggregates in the rPFC and hippocampal formation. Tissues from age- and sex-matched CNOO and Alzheimer's disease (AD) rPFC and hippocampal formation were stained for β-amyloid (Aβ), tau, α-synuclein, phosphorylated TAR DNA-binding protein 43 (pTDP-43), acetylcholinesterase (AChE), and butyrylcholinesterase (BChE). The relative abundance of neuropathological aggregates was semi-quantitatively scored. Deposition of Aβ plaques, tau neurofibrillary tangles (NFT) and pTDP-43 inclusions were comparable between CNOO and AD cases. Intraneuronal Aβ and tau-positive thorny astrocytes consistent with aging-related tau astrogliopathy, were also noted in the rPFC. Abundance of BChE-positive plaque pathology was significantly higher in AD than in CNOO cases in most regions of interest, followed closely by abundance of AChE-positive plaque pathology. BChE- and AChE-activities were also associated with varied NFT morphologies. CNOO cases maintained cognition despite a high neuropathological burden in the rPFC and hippocampal formation. BChE-positive and, to a lesser extent, AChE-positive pathologies were significantly lower in most regions in the CNOO compared to AD. This suggests a specificity of cholinesterase-associated neuropathology with AD. We conclude that while CNOO have cholinesterase-associated neuropathology in the rPFC and hippocampal formation, abundance in this population is significantly lower compared to AD which may contribute to their intact cognition.

Effect of self-imagination on memory for older adults and aMCI patients

Imagining an event from a personal perspective has been found to be able to enhance memory for words and sentences for healthy younger adults and brain-injured patients. However, little is known about how people with amnestic mild cognitive impairment (aMCI) respond to self-imagination, in comparison to healthy older adults. In the current study, participants were asked to process a group of objects using either a self-imagination approach or a baseline strategy in which the self was not heavily involved. Self-imagination shows a mnemonic advantage over the control strategy, though this pattern emerged more clearly for healthy older adults. Furthermore, suggestive evidence indicates that cognitive ability supports self-reference benefits for healthy older adults, but not aMCI patients. These findings extended previous research to reveal the effectiveness of self-imagination for older adults using pictorial stimuli and supported the viewpoint that aMCI could qualitatively change the way that cognitive resources are engaged.

The association of basal cortisol levels with episodic memory in older adults is mediated by executive function

Elevated basal cortisol levels in elderly may indicate dysregulation of the internal stress-related system, as well as dysfunction and structural alterations in brain structures necessary for cognition, such as hippocampus and prefrontal cortex. Because of the close relation of executive functions and episodic memory processing, in this study we explored whether the association of elevated cortisol levels on episodic memory could be partly attributed to cortisol effects on executive functions. In this cross-sectional study we analyzed data from a sample of 236 community-dwelling older adults from the Cretan Aging Cohort aged 75.56 ± 7.21 years [53 with dementia due to probable Alzheimer's disease, 99 with Mild Cognitive Impairment (MCI) and 84 cognitively non-impaired participants (NI)]. Morning serum cortisol levels were higher in the probable AD as compared to the NI group (p = .031). Mediated regression models in the total sample supported the hypothesis that the negative association of basal cortisol levels with delayed memory was fully mediated by the relation of basal cortisol levels with executive functions and immediate memory (adjusted for age and self-reported depression symptoms). Moderated mediation regression models revealed that the direct effect of cortisol on executive function and the effect of executive function on delayed memory performance were statistically significant among participants diagnosed with MCI, while the immediate memory effect on delayed memory was more pronounced in AD patients, as compared to the NI group. The current findings corroborate neuroimaging research highlighting cortisol effects on executive functions and immediate memory and further suggest that dysregulation of systems involved in these functions may account for the purported detrimental long-term effects of high cortisol levels on delayed memory.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Cortical Correlates of Impulsive Aggressive Behavior in Pediatric Bipolar Disorder

Background: Impulsive aggression represents a frequent characteristic of pediatric bipolar disorder (PBD). Cortical alterations associated with impulsive aggression and its multiple facets have not been investigated yet in youth with bipolar disorder. Aim: To investigate the relationship between cortical thickness and facets of impulsive aggression in youth with PBD. Materials and Methods: Twenty-three youth with PBD and 23 healthy controls (HC) were administered the aggression questionnaire (AQ) and underwent 3T magnetic resonance imaging scan. Cortical thickness was assessed with FreeSurfer. Canonical correlation analyses were used to investigate the relationship between AQ total and subscale scores and cortical thickness in youth with PBD. Results: Youth with PBD had increased scores in the subscales of AQ-anger and AQ-hostility and cortical thinning in in areas belonging to the affective network (AN), frontoparietal network (FPN) and cingulo-opercular network (CON), i.e., right rostral anterior cingulate, right caudal anterior cingulate, right lateral orbitofrontal, right medial orbitofrontal, left and right inferior parietal, left posterior cingulate, left and right supramarginal left lingual cortices. Greater thickness in these networks positively correlated with the AQ-hostility subscale and negatively correlated with AQ-anger subscale. Conclusions: The opposite patterns observed between areas belonging to AN, FPN, CON, and the two facets of IA, namely anger and hostility, corroborate clinical findings supporting the different nature of these two constructs.

Imaging Genetics Study Based on a Temporal Group Sparse Regression and Additive Model for Biomarker Detection of Alzheimer's Disease

Imaging genetics is an effective tool used to detect potential biomarkers of Alzheimer's disease (AD) in imaging and genetic data. Most existing imaging genetics methods analyze the association between brain imaging quantitative traits (QTs) and genetic data [e.g., single nucleotide polymorphism (SNP)] by using a linear model, ignoring correlations between a set of QTs and SNP groups, and disregarding the varied associations between longitudinal imaging QTs and SNPs. To solve these problems, we propose a novel temporal group sparsity regression and additive model (T-GSRAM) to identify associations between longitudinal imaging QTs and SNPs for detection of potential AD biomarkers. We first construct a nonparametric regression model to analyze the nonlinear association between QTs and SNPs, which can accurately model the complex influence of SNPs on QTs. We then use longitudinal QTs to identify the trajectory of imaging genetic patterns over time. Moreover, the SNP information of group and individual levels are incorporated into the proposed method to boost the power of biomarker detection. Finally, we propose an efficient algorithm to solve the whole T-GSRAM model. We evaluated our method using simulation data and real data obtained from AD neuroimaging initiative. Experimental results show that our proposed method outperforms several state-of-the-art methods in terms of the receiver operating characteristic curves and area under the curve. Moreover, the detection of AD-related genes and QTs has been confirmed in previous studies, thereby further verifying the effectiveness of our approach and helping understand the genetic basis over time during disease progression.

An Overview of ICA/BSS-Based Application to Alzheimer's Brain Signal Processing

Alzheimer's disease (AD) is by far the most common cause of dementia associated with aging. Early and accurate diagnosis of AD and ability to track progression of the disease is increasingly important as potential disease-modifying therapies move through clinical trials. With the advent of biomedical techniques, such as computerized tomography (CT), electroencephalography (EEG), magnetoencephalography (MEG), positron emission tomography (PET), magnetic resonance imaging (MRI), and functional magnetic resonance imaging (fMRI), large amounts of data from Alzheimer's patients have been acquired and processed from which AD-related information or "signals" can be assessed for AD diagnosis. It remains unknown how best to mine complex information from these brain signals to aid in early diagnosis of AD. An increasingly popular technique for processing brain signals is independent component analysis or blind source separation (ICA/BSS) that separates blindly observed signals into original signals that are as independent as possible. This overview focuses on ICA/BSS-based applications to AD brain signal processing.

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.

Hippocampal atrophy based Alzheimer's disease diagnosis via machine learning methods

Alzheimer's disease is the most common form of dementia and is a serious health problem. The disease is expected to increase further in the upcoming years with the increase of the elderly population. Developing new treatments and diagnostic methods is getting more important. In this study, we focused on the early diagnosis of dementia in Alzheimer's disease via analysis of neuroimages. We analyzed the data diagnosed by the Alzheimer's Disease Neuroimaging Initiative (ADNI) protocol. The analyzed data were T1-weighted magnetic resonance images of 159 patients with Alzheimer's disease, 217 patients with mild cognitive impairment and 109 cognitively healthy older people. In this study, we propose that the volumetric reduction in the hippocampus is the most important indicator of Alzheimer's disease. There is not much research about the relationship between the volumetric reduction in the hippocampus and Alzheimer's disease. This volume information was calculated through semi-automatic segmentation software ITK-SNAP and a data set was created based on age, gender, diagnosis, and right and left hippocampal volume values. The diagnosis via hippocampal volume information was made by using machine learning techniques. By using this approach, we conclude that brain MRIs can be used to distinguish the patients with Alzheimer's Disease (AD), Mild Cognitive Impairment (MCI) and Cognitive Normal (CN) from each other; while most of the studies were only able to distinguish AD from CN. Our results have revealed that our approach improves the performance of the computer-aided diagnosis of Alzheimer's disease.

Clinical trials of new drugs for Alzheimer disease

Alzheimer disease (AD) accounts for 60-70% of dementia cases. Given the seriousness of the disease and continual increase in patient numbers, developing effective therapies to treat AD has become urgent. Presently, the drugs available for AD treatment, including cholinesterase inhibitors and an antagonist of the N-methyl-D-aspartate receptor, can only inhibit dementia symptoms for a limited period of time but cannot stop or reverse disease progression. On the basis of the amyloid hypothesis, many global drug companies have conducted many clinical trials on amyloid clearing therapy but without success. Thus, the amyloid hypothesis may not be completely feasible. The number of anti-amyloid trials decreased in 2019, which might be a turning point. An in-depth and comprehensive understanding of the contribution of amyloid beta and other factors of AD is crucial for developing novel pharmacotherapies.In ongoing clinical trials, researchers have developed and are testing several possible interventions aimed at various targets, including anti-amyloid and anti-tau interventions, neurotransmitter modification, anti-neuroinflammation and neuroprotection interventions, and cognitive enhancement, and interventions to relieve behavioral psychological symptoms. In this article, we present the current state of clinical trials for AD at clinicaltrials.gov. We reviewed the underlying mechanisms of these trials, tried to understand the reason why prior clinical trials failed, and analyzed the future trend of AD clinical trials.

Cerebrospinal Fluid and MRI Biomarkers in Neurodegenerative Diseases: A Retrospective Memory Clinic-Based Study

BACKGROUND

Cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) biomarkers of neurodegenerative diseases are relatively sensitive and specific in highly curated research cohorts, but proper validation for clinical use is mostly missing.

OBJECTIVE

We studied these biomarkers in a novel memory clinic cohort with a variety of different neurodegenerative diseases.

METHODS

This study consisted of 191 patients with subjective or objective cognitive impairment who underwent neurological, CSF biomarker (Aβ42, p-tau, and tau) and T1-weighted MRI examinations at Kuopio University Hospital. We assessed CSF and imaging biomarkers, including structural MRI focused on volumetric and cortical thickness analyses, across groups stratified based on different clinical diagnoses, including Alzheimer's disease (AD), frontotemporal dementia, dementia with Lewy bodies, Parkinson's disease, vascular dementia, and mild cognitive impairment (MCI), and subjects with no evidence of neurodegenerative disease underlying the cognitive symptoms. Imaging biomarkers were also studied by profiling subjects according to the novel amyloid, tau, and, neurodegeneration (AT(N)) classification.

RESULTS

Numerous imaging variables differed by clinical diagnosis, including hippocampal, amygdalar and inferior lateral ventricular volumes and entorhinal, lingual, inferior parietal and isthmus cingulate cortical thicknesses, at a false discovery rate (FDR)-corrected threshold for significance (analysis of covariance; p < 0.005). In volumetric comparisons by AT(N) profile, hippocampal volume significantly differed (p < 0.001) between patients with normal AD biomarkers and patients with amyloid pathology.

CONCLUSION

Our analysis suggests that CSF and MRI biomarkers function well also in clinical practice across multiple clinical diagnostic groups in addition to AD, MCI, and cognitively normal groups.

Influence of self-referential mode on memory for aMCI patients

One's concept of the self can act as a schema, in some cases facilitating memory performance but in other cases making memory more prone to errors. In this study, we attempted to induce long-lasting self-reference effects through an autobiographical mode in younger and older adults, as well as patients with amnestic mild cognitive impairment (aMCI), predicting that a self-referential mode of thought would benefit memory. Participants first either recalled autobiographical memories or described three neutral photographs in a narrative condition. This was followed by a conventional self-referencing task. At retrieval, participants completed a recognition task. Contrary to our prediction, the self-referencing benefit emerged consistently under autobiographical and narrative modes across all groups. Although our findings indicate that self-referencing can benefit memory, it carries the risk of increasing false alarm rates when induced through an autobiographical mode and consequently the strategy should be utilized with caution.

Psychological Stress and Mitochondria: A Conceptual Framework

BACKGROUND

The integration of biological, psychological, and social factors in medicine has benefited from increasingly precise stress response biomarkers. Mitochondria, a subcellular organelle with its own genome, produce the energy required for life and generate signals that enable stress adaptation. An emerging concept proposes that mitochondria sense, integrate, and transduce psychosocial and behavioral factors into cellular and molecular modifications. Mitochondrial signaling might in turn contribute to the biological embedding of psychological states.

METHODS

A narrative literature review was conducted to evaluate evidence supporting this model implicating mitochondria in the stress response, and its implementation in behavioral and psychosomatic medicine.

RESULTS

Chronically, psychological stress induces metabolic and neuroendocrine mediators that cause structural and functional recalibrations of mitochondria, which constitutes mitochondrial allostatic load. Clinically, primary mitochondrial defects affect the brain, the endocrine system, and the immune systems that play a role in psychosomatic processes, suggesting a shared underlying mechanistic basis. Mitochondrial function and dysfunction also contribute to systemic physiological regulation through the release of mitokines and other metabolites. At the cellular level, mitochondrial signaling influences gene expression and epigenetic modifications, and modulates the rate of cellular aging.

CONCLUSIONS

This evidence suggests that mitochondrial allostatic load represents a potential subcellular mechanism for transducing psychosocial experiences and the resulting emotional responses-both adverse and positive-into clinically meaningful biological and physiological changes. The associated article in this issue of Psychosomatic Medicine presents a systematic review of the effects of psychological stress on mitochondria. Integrating mitochondria into biobehavioral and psychosomatic research opens new possibilities to investigate how psychosocial factors influence human health and well-being across the life-span.

Post-Mortem MRI and Histopathology in Neurologic Disease: A Translational Approach

In this review, combined post-mortem brain magnetic resonance imaging (MRI) and histology studies are highlighted, illustrating the relevance of translational approaches to define novel MRI signatures of neuropathological lesions in neuroinflammatory and neurodegenerative disorders. Initial studies combining post-mortem MRI and histology have validated various MRI sequences, assessing their sensitivity and specificity as diagnostic biomarkers in neurologic disease. More recent studies have focused on defining new radiological (bio)markers and implementing them in the clinical (research) setting. By combining neurological and neuroanatomical expertise with radiological development and pathological validation, a cycle emerges that allows for the discovery of novel MRI biomarkers to be implemented in vivo. Examples of this cycle are presented for multiple sclerosis, Alzheimer's disease, Parkinson's disease, and traumatic brain injury. Some applications have been shown to be successful, while others require further validation. In conclusion, there is much to explore with post-mortem MRI and histology studies, which can eventually be of high relevance for clinical practice.

Coupled changes in hippocampal structure and cognitive ability in later life

Introduction

The hippocampus plays an important role in cognitive abilities which often decline with advancing age.

Methods

In a longitudinal study of community-dwelling adults, we investigated whether there were coupled changes in hippocampal structure and verbal memory, working memory, and processing speed between the ages of 73 (N = 655) and 76 years (N = 469). Hippocampal structure was indexed by hippocampal volume, hippocampal volume as a percentage of intracranial volume (H_ICV), fractional anisotropy (FA), mean diffusivity (MD), and longitudinal relaxation time (T1).

Results

Mean levels of hippocampal volume, H_ICV, FA, T1, and all three cognitive abilities domains decreased, whereas MD increased, from age 73 to 76. At baseline, higher hippocampal volume was associated with better working memory and verbal memory, but none of these correlations survived correction for multiple comparisons. Higher FA, lower MD, and lower T1 at baseline were associated with better cognitive abilities in all three domains; only the correlation between baseline hippocampal MD and T1, and change in the three cognitive domains, survived correction for multiple comparisons. Individuals with higher hippocampal MD at age 73 experienced a greater decline in all three cognitive abilities between ages 73 and 76. However, no significant associations with changes in cognitive abilities were found with hippocampal volume, FA, and T1 measures at baseline. Similarly, no significant associations were found between cognitive abilities at age 73 and changes in the hippocampal MRI biomarkers between ages 73 and 76.

Conclusion

Our results provide evidence to better understand how the hippocampus ages in healthy adults in relation to the cognitive domains in which it is involved, suggesting that better hippocampal MD at age 73 predicts less relative decline in three important cognitive domains across the next 3 years. It can potentially assist in diagnosing early stages of aging-related neuropathologies, because in some cases, accelerated decline could predict pathologies.

A preclinical perspective on the enhanced vulnerability to Alzheimer's disease after early-life stress

Stress experienced early in life (ES), in the form of childhood maltreatment, maternal neglect or trauma, enhances the risk for cognitive decline in later life. Several epidemiological studies have now shown that environmental and adult life style factors influence AD incidence or age-of-onset and early-life environmental conditions have attracted attention in this respect. There is now emerging interest in understanding whether ES impacts the risk to develop age-related neurodegenerative disorders, and their severity, such as in Alzheimer's disease (AD), which is characterized by cognitive decline and extensive (hippocampal) neuropathology. While this might be relevant for the identification of individuals at risk and preventive strategies, this topic and its possible underlying mechanisms have been poorly studied to date. In this review, we discuss the role of ES in modulating AD risk and progression, primarily from a preclinical perspective. We focus on the possible involvement of stress-related, neuro-inflammatory and metabolic factors in mediating ES-induced effects on later neuropathology and the associated impairments in neuroplasticity. The available studies suggest that the age of onset and progression of AD-related neuropathology and cognitive decline can be affected by ES, and may aggravate the progression of AD neuropathology. These relevant changes in AD pathology after ES exposure in animal models call for future clinical studies to elucidate whether stress exposure during the early-life period in humans modulates later vulnerability for AD.

The distribution of the alpha7 nicotinic acetylcholine receptor in healthy aging: An in vivo positron emission tomography study with [18F]ASEM

Altered function of the alpha7 nicotinic acetylcholine receptor (α7-nAChR) is implicated in several neuropsychiatric diseases. Nevertheless, studies of the human cerebral α7-nAChR even in healthy aging are limited in number and to postmortem tissue.

METHODS

The distribution of the cerebral α7-nAChR was estimated in nine brain regions in 25 healthy volunteers (ages 21-86 years; median 57 years, interquartile range 52 years) using [18F]ASEM with positron emission tomography (PET) imaging. Regional total distribution volume (VT) measurements were calculated using the Logan method from each subject's 90 min dynamic PET data and their metabolite-corrected plasma input function. Spearman's rank or Pearson's correlation analysis was used depending on the normality of the data. Correlation between age and regional 1) volume relative to intracranial volume (volume ratio) and 2) [18F]ASEM VT was tested. Correlation between regional volume ratio and [18F]ASEM VT was also evaluated. Finally, the relationship between [18F]ASEM VT and neuropsychological measures was investigated in a subpopulation of 15 elderly healthy participants (those 50 years of age and older). Bonferroni correction for multiple comparisons was applied to statistical analyses.

RESULTS

A negative correlation between tissue volume ratio and age was observed in six of the nine brain regions including striatum and five cortical (temporal, occipital, cingulate, frontal, or parietal) regions. A positive correlation between [18F]ASEM VT and age was observed in all nine brain regions of interest (ROIs). There was no correlation between [18F]ASEM VT and volume ratio in any ROI after controlling for age. Regional [18F]ASEM VT and neuropsychological performance on each of eight representative subtests were not correlated among the well-performing subpopulation of elderly healthy participants.

CONCLUSIONS

Our results suggest an increase in cerebral α7-nAChR distribution over the course of healthy aging that should be tested in future longitudinal studies. The preservation of the α7-nAChR in the aging human brain supports the development of therapeutic agents that target this receptor for use in the elderly. Further study of the relationship between α7-nAChR availability and cognitive impairment over aging is needed.

Targeting Adult Neurogenesis to Optimize Hippocampal Circuits in Aging

Millions of individuals suffer from age-related cognitive decline, defined by impaired memory precision. Increased understanding of hippocampal circuit mechanisms underlying memory formation suggests a role for computational processes such as pattern separation and pattern completion in memory precision. We describe evidence implicating the dentate gyrus-CA3 circuit in pattern separation and completion, and examine alterations in dentate gyrus-CA3 circuit structure and function with aging. We discuss the role of adult hippocampal neurogenesis in memory precision in adulthood and aging, as well as the circuit mechanisms underlying the integration and encoding functions of adult-born dentate granule cells. We posit that understanding these circuit mechanisms will permit generation of circuit-based endophenotypes that will edify new therapeutic strategies to optimize hippocampal encoding during aging.

Perceptual and memory inhibition deficits in clinically healthy older adults are associated with region-specific, doubly dissociable patterns of cortical thinning

Converging evidence suggests that the cognitive control processes that enable the inhibition of irrelevant information on a perceptual versus a memorial basis are qualitatively different and are underlain by unique neural systems that may be affected differentially in aging. In the current study, we investigated whether individual differences in performance on these 2 types of inhibitory processes were attributable to region-specific patterns of cortical thinning. Clinically healthy older adults completed a pair of behavioral memory and perceptual inhibition tasks and then underwent structural brain imaging. We found that worse memory inhibition was associated with reduced cortical thickness in the left ventral lateral prefrontal cortex (VLPFC), an area that has been functionally associated with memory inhibition, but not in either the right or left superior parietal lobule (SPL), areas that have been functionally associated with perceptual inhibition. On the contrary, while impaired perceptual inhibition was associated with cortical thinning in the right SPL, it was not associated with cortical thickness in either the left VLPFC or SPL. These results suggest a double dissociation between performance on 2 types of inhibitory control tasks and cortical thinning in specific brain areas, previously shown to be uniquely associated with functional activation of each these 2 types of cognitive tasks. (PsycINFO Database Record

Structural MR Imaging in the Diagnosis of Alzheimer's Disease and Other Neurodegenerative Dementia: Current Imaging Approach and Future Perspectives

With the rise of aging population, clinical concern and research attention has shifted towards neuroimaging of dementia. The advent of 3T, magnetic resonance imaging (MRI) has permitted the anatomical imaging of neurodegenerative disease, specifically dementia, with improved resolution. Furthermore, more powerful techniques such as diffusion tensor imaging, quantitative susceptibility mapping, and magnetic transfer imaging have successfully emerged for the detection of micro-structural abnormalities. In the present review article, we provide a brief overview of Alzheimer's disease and explore recent neuroimaging developments in the field of dementia with an emphasis on structural MR imaging in order to propose a simple and easily applicable systematic approach to the imaging diagnosis of dementia.

Prediction of Memory Impairment with MRI Data: A Longitudinal Study of Alzheimer's Disease

Alzheimer's Disease (AD), a severe type of neurodegenerative disorder with progressive impairment of learning and memory, has threatened the health of millions of people. How to recognize AD at early stage is crucial. Multiple models have been presented to predict cognitive impairments by means of neuroimaging data. However, traditional models did not employ the valuable longitudinal information along the progression of the disease. In this paper, we proposed a novel longitudinal feature learning model to simultaneously uncover the interrelations among different cognitive measures at different time points and utilize such interrelated structures to enhance the learning of associations between imaging features and prediction tasks. Moreover, we adopted Schatten p-norm to identify the interrelation structures existing in the low-rank subspace. Empirical results on the ADNI cohort demonstrated promising performance of our model.

Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades

The default mode network (DMN) is a set of regions that is tonically engaged during the resting state and exhibits task-related deactivation that is readily reproducible across a wide range of paradigms and modalities. The DMN has been implicated in numerous disorders of cognition and, in particular, in disorders exhibiting age-related cognitive decline. Despite these observations, investigations of the DMN in normal aging are scant. Here, we used blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) acquired during rest to investigate age-related changes in functional connectivity of the DMN in 120 healthy normal volunteers comprising six, 20-subject, decade cohorts (from 20–29 to 70–79). Structural equation modeling (SEM) was used to assess age-related changes in inter-regional connectivity within the DMN. SEM was applied both using a previously published, meta-analytically derived, node-and-edge model, and using exploratory modeling searching for connections that optimized model fit improvement. Although the two models were highly similar (only 3 of 13 paths differed), the sample demonstrated significantly better fit with the exploratory model. For this reason, the exploratory model was used to assess age-related changes across the decade cohorts. Progressive, highly significant changes in path weights were found in 8 (of 13) paths: four rising, and four falling (most changes were significant by the third or fourth decade). In all cases, rising paths and falling paths projected in pairs onto the same nodes, suggesting compensatory increases associated with age-related decreases. This study demonstrates that age-related changes in DMN physiology (inter-regional connectivity) are bidirectional, progressive, of early onset and part of normal aging.

Perceived Stress Is Differentially Related to Hippocampal Subfield Volumes among Older Adults

INTRODUCTION

Chronic exposure to stress has been shown to impact a wide range of health-related outcomes in older adults. Despite extensive animal literature revealing deleterious effects of biological markers of stress on the dentate gyrus subfield of the hippocampus, links between hippocampal subfields and psychological stress have not been studied in humans. This study examined the relationship between perceived stress and hippocampal subfield volumes among racially/ethnically diverse older adults.

METHODS AND MATERIALS

Between July 2011 and March 2014, 116 nondemented participants were consecutively drawn from the Einstein Aging Study, an ongoing community-based sample of individuals over the age of 70 residing in Bronx, New York. All participants completed the Perceived Stress Scale, Geriatric Depression Scale, and underwent 3.0 T MRI. FreeSurfer was used to derive total hippocampal volume, hippocampal subfield volumes (CA1, CA2/CA3, CA4/Dentate Gyrus (CA4/DG), and subiculum), entorhinal cortex volume, whole brain volume, and total intracranial volume.

RESULTS

Linear regression analyses revealed that higher levels of perceived stress were associated with smaller total hippocampal volume (β = -0.20, t = -2.40, p = 0.02), smaller CA2/CA3 volumes (β = -0.18, t = -2.24, p = 0.03) and smaller CA4/DG volumes (β = -0.19, t = -2.28, p = 0.03) after controlling for total intracranial volume, age, gender, and race. These findings remained unchanged after removal of individuals with clinically significant symptoms of depression.

DISCUSSION

Our findings provide evidence of a relationship between a direct indicator of psychological stress and specific hippocampal subfield volumes in elderly individuals. These results highlight the importance of clinical screening for chronic stress in otherwise healthy older adults.

Mammillary Bodies in Alzheimer's Disease: A Golgi and Electron Microscope Study

Alzheimer's disease (AD) is a progressive neurodegenerative disorder, characterized by irreversible memory decline, concerning no rarely spatial memory and orientation, alterations of the mood and personality, gradual loss of motor skills, and substantial loss of capacities obtained by previous long education. We attempted to describe the morphological findings of the mammillary bodies in early cases of AD. Samples were processed for electron microscopy and silver impregnation techniques. The nuclei of the mammillary bodies demonstrated a substantial decrease in the neuronal population and marked abbreviation of dendritic arbors. Decrease in spine density and morphological abnormalities of dendritic spines was also seen. Synaptic alterations were prominent. Alzheimer's pathology, such as deposits of amyloid-β peptide and neurofibrillary degeneration, was minimal. Electron microscopy revealed mitochondrial alterations and fragmentation of Golgi apparatus, associated frequently with synaptic pathology.

The brain on stress: Insight from studies using the Visible Burrow System

The discovery of adrenal steroid receptors outside of the hypothalamus in the hippocampus and other forebrain regions catalyzed research on the effects of stress upon cognitive function, emotions and self-regulatory behaviors as well as the molecular, cellular and neuroanatomical mechanisms underlying acute and chronic stress effects on the brain. Indeed, this work has shown that the brain is a plastic and vulnerable organ in the face of acute and chronic stress. The insight that Bob and Caroline Blanchard had in developing and interpreting findings using the Visible Burrow System model made an enormous contribution to the current view that the human brain is very sensitive to the social environment and to agonistic interactions between individuals. Their collaboration with Sakai and McEwen at The Rockefeller University extended application of the Visible Burrow System model to demonstrate that it also was a unique and highly relevant neuroethological model with which to study stress and adaptation to stressors. Those studies focused on the brain and systemic organ responses to stress and, in turn, described that the brain is also very responsive to changes in systemic physiology.

Alzheimer Disease

PURPOSE OF REVIEW

This article discusses the recent advances in the diagnosis and treatment of Alzheimer disease (AD).

RECENT FINDINGS

In recent years, significant advances have been made in the fields of genetics, neuroimaging, clinical diagnosis, and staging of AD. One of the most important recent advances in AD is our ability to visualize amyloid pathology in the living human brain. The newly revised criteria for diagnosis of AD dementia embrace the use for biomarkers as supportive evidence for the underlying pathology. Guidelines for the responsible use of amyloid positron emission tomography (PET) have been developed, and the clinical and economic implications of amyloid PET imaging are actively being explored.

SUMMARY

Our improved understanding of the clinical onset, progression, neuroimaging, pathologic features, genetics, and other risk factors for AD impacts the approaches to clinical diagnosis and future therapeutic interventions.

Aging is associated with dimerization and inactivation of the brain-enriched tyrosine phosphatase STEP

The STriatal-Enriched tyrosine Phosphatase (STEP) is involved in the etiology of several age-associated neurologic disorders linked to oxidative stress and is also known to play a role in neuroprotection by modulating glutamatergic transmission. However, the possible effect of aging on STEP level and activity in the brain is still unclear. In this study, using young (1 month), adult (4 months), and aged (18 months) rats, we show that aging is associated with increase in dimerization and loss of activity of STEP. Increased dimerization of STEP is primarily observed in the cortex and hippocampus and is associated with depletion of both reduced and total glutathione levels, suggesting an increase in oxidative stress. Consistent with this interpretation, studies in cell culture models of glutathione depletion and oxidative stress also demonstrate formation of dimers and higher order oligomers of STEP that involve intermolecular disulfide bond formation between multiple cysteine residues. Conversely, administration of N-acetyl cysteine, a major antioxidant that enhances glutathione biosynthesis, attenuates STEP dimerization both in the cortex and hippocampus. The findings indicate that loss of this intrinsic protective response pathway with age-dependent increase in oxidative stress may be a contributing factor for the susceptibility of the brain to age-associated neurologic disorders.

Alterations of the volatile metabolome in mouse models of Alzheimer's disease

In the present study, we tested whether the volatile metabolome was altered by mutations of the Alzheimer's disease (AD)-implicated amyloid precursor protein gene (APP) and comprehensively examined urinary volatiles that may potentially serve as candidate biomarkers of AD. Establishing additional biomarkers in screening populations for AD will provide enhanced diagnostic specificity and will be critical in evaluating disease-modifying therapies. Having strong evidence of gross changes in the volatile metabolome of one line of APP mice, we utilized three unique mouse lines which over-express human mutations of the APP gene and their respective non-transgenic litter-mates (NTg). Head-space gas chromatography/mass spectrometry (GC/MS) of urinary volatiles uncovered several aberrant chromatographic peak responses. We later employed linear discrimination analysis and found that the GC/MS peak responses provide accurate (>84%) genotype classification of urinary samples. These initial data in animal models show that mutant APP gene expression entails a uniquely identifiable urinary odor, which if uncovered in clinical AD populations, may serve as an additional biomarker for the disease.

Inflammation as a mediator of the relationship between cortical thickness and metabolic syndrome

Metabolic Syndrome (MetS), the clustering of obesity, high blood pressure, and disordered glucose and lipid/lipoprotein metabolism within a single individual, is associated with poorer cognitive function. It has been hypothesized that cognitive impairment in MetS occurs primarily within the context of inflammation. MetS risk factors are also associated with thinning of the cerebral cortex. However, the mechanisms by which MetS and inflammation affect the brain are poorly understood. The present study used statistical mediation to examine the relationship between MetS risk factors, cortical thickness in a priori regions of interest (ROIs) and inflammation. ROIs were chosen from the previous literature. Forty-three adults between the ages of 40 and 60 years underwent a health screen, neuropsychological testing and structural magnetic resonance imaging. Serum levels of pro-inflammatory markers (interleukin 1, interleukin 2, interleukin 6 and C-Reactive Protein) were measured using enzyme-linked immunosorbent assays. A higher number of MetS risk factors were associated with thinning in the inferior frontal ROI (β = -0.35, p = 0.019) as well as higher levels of serum interleukin 2 (β = 0.31, p = 0.04). A higher level of serum interleukin 2 was also associated with reduced thickness in the inferior frontal gyrus (β = -0.41, p = 0.013). After accounting for the effects of interleukin 2, the number of MetS risk factors was no longer associated with cortical thickness in the inferior frontal gyrus indicating successful statistical mediation. The results indicate a potentially important role for inflammation in linking MetS to cortical thinning and cognitive vulnerability.

BFLCRM: A BAYESIAN FUNCTIONAL LINEAR COX REGRESSION MODEL FOR PREDICTING TIME TO CONVERSION TO ALZHEIMER'S DISEASE

The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer's disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM.

Using visual rating to diagnose dementia: a critical evaluation of MRI atrophy scales

Visual rating scales, developed to assess atrophy in patients with cognitive impairment, offer a cost-effective diagnostic tool that is ideally suited for implementation in clinical practice. By focusing attention on brain regions susceptible to change in dementia and enforcing structured reporting of these findings, visual rating can improve the sensitivity, reliability and diagnostic value of radiological image interpretation. Brain imaging is recommended in all current diagnostic guidelines relating to dementia, and recent guidelines have also recommended the application of medial temporal lobe atrophy rating. Despite these recommendations, and the ease with which rating scales can be applied, there is still relatively low uptake in routine clinical assessments. Careful consideration of atrophy rating scales is needed to verify their diagnostic potential and encourage uptake among clinicians. Determining the added value of combining scores from visual rating in different brain regions may also increase the diagnostic value of these tools.

Structural brain aging and speech production: a surface-based brain morphometry study

While there has been a growing number of studies examining the neurofunctional correlates of speech production over the past decade, the neurostructural correlates of this immensely important human behaviour remain less well understood, despite the fact that previous studies have established links between brain structure and behaviour, including speech and language. In the present study, we thus examined, for the first time, the relationship between surface-based cortical thickness (CT) and three different behavioural indexes of sublexical speech production: response duration, reaction times and articulatory accuracy, in healthy young and older adults during the production of simple and complex meaningless sequences of syllables (e.g., /pa-pa-pa/ vs. /pa-ta-ka/). The results show that each behavioural speech measure was sensitive to the complexity of the sequences, as indicated by slower reaction times, longer response durations and decreased articulatory accuracy in both groups for the complex sequences. Older adults produced longer speech responses, particularly during the production of complex sequence. Unique age-independent and age-dependent relationships between brain structure and each of these behavioural measures were found in several cortical and subcortical regions known for their involvement in speech production, including the bilateral anterior insula, the left primary motor area, the rostral supramarginal gyrus, the right inferior frontal sulcus, the bilateral putamen and caudate, and in some region less typically associated with speech production, such as the posterior cingulate cortex.

Metabolic Alterations Associated to Brain Dysfunction in Diabetes

From epidemiological studies it is known that diabetes patients display increased risk of developing dementia. Moreover, cognitive impairment and Alzheimer's disease (AD) are also accompanied by impaired glucose homeostasis and insulin signalling. Although there is plenty of evidence for a connection between insulin-resistant diabetes and AD, definitive linking mechanisms remain elusive. Cerebrovascular complications of diabetes, alterations in glucose homeostasis and insulin signalling, as well as recurrent hypoglycaemia are the factors that most likely affect brain function and structure. While difficult to study in patients, the mechanisms by which diabetes leads to brain dysfunction have been investigated in experimental models that display phenotypes of the disease. The present article reviews the impact of diabetes and AD on brain structure and function, and discusses recent findings from translational studies in animal models that link insulin resistance to metabolic alterations that underlie brain dysfunction. Such modifications of brain metabolism are likely to occur at early stages of neurodegeneration and impact regional neurochemical profiles and constitute non-invasive biomarkers detectable by magnetic resonance spectroscopy (MRS).

Practical cut-offs for visual rating scales of medial temporal, frontal and posterior atrophy in Alzheimer's disease and mild cognitive impairment

BACKGROUND

Atrophy in the medial temporal lobe, frontal lobe and posterior cortex can be measured with visual rating scales such as the medial temporal atrophy (MTA), global cortical atrophy - frontal subscale (GCA-F) and posterior atrophy (PA) scales, respectively. However, practical cut-offs are urgently needed, especially now that different presentations of Alzheimer's disease (AD) are included in the revised diagnostic criteria.

AIMS

The aim of this study was to generate a list of practical cut-offs for the MTA, GCA-F and PA scales, for both diagnosis of AD and determining prognosis in mild cognitive impairment (MCI), and to evaluate the influence of key demographic and clinical factors on these cut-offs.

METHODS

AddNeuroMed and ADNI cohorts were combined giving a total of 1147 participants (322 patients with AD, 480 patients with MCI and 345 control subjects). The MTA, GCA-F and PA scales were applied and a broad range of cut-offs was evaluated.

RESULTS

The MTA scale showed better diagnostic and predictive performances than the GCA-F and PA scales. Age, apolipoprotein E (ApoE) ε4 status and age at disease onset influenced all three scales. For the age ranges 45-64, 65-74, 75-84 and 85-94 years, the following cut-offs should be used. MTA: ≥1.5, ≥1.5, ≥2 and ≥2.5; GCA-F, ≥1, ≥1, ≥1 and ≥1; and PA, ≥1, ≥1, ≥1 and ≥1, respectively, with an adjustment for early-onset ApoE ε4 noncarrier AD patients (MTA: ≥2, ≥2, ≥3 and ≥3; and GCA-F: ≥1, ≥1, ≥2 and ≥2, respectively).

CONCLUSIONS

If successfully validated in clinical settings, the list of practical cut-offs proposed here might be useful in clinical practice. Their use might also (i) promote research on atrophy subtypes, (ii) increase the understanding of different presentations of AD, (iii) improve diagnosis and prognosis and (iv) aid population selection and enrichment for clinical trials.

Hippocampal atrophy varies by neuropsychologically defined MCI among men in their 50s

OBJECTIVE

In an effort to address earliest detection of mild cognitive impairment (MCI), we examined hippocampal volumes and atrophy in middle-aged men to explore neuroanatomical support for different neuropsychological definitions of MCI.

METHODS

460 men aged 51-60 years underwent neuropsychological testing and MRI. MCI was defined according to five criteria sets. MRI-derived hippocampal volume and hippocampal occupancy (HOC) were obtained via FreeSurfer. Statistical analyses were performed using linear mixed models.

RESULTS

Differences in HOC between normal cognitive functioning, amnestic, and non-amnestic MCI were observed using MCI criteria that required one impaired (>1.5 SD) cognitive measure in a given cognitive domain or a cognitive composite score method with a cut-point 2 SD below the mean. Differences in standard hippocampal volume were only found between normal and amnestic presentations and only when using the composite score method.

CONCLUSION

Results provide empirical support for detection of pre-MCI in younger cohorts. Convergence of neuropsychological and neuroanatomical data, particularly HOC (as opposed to standard cross-sectional volume), supports early identification of MCI as defined by some neuropsychological criteria.