Associations among amyloid status, age, and longitudinal regional brain atrophy in cognitively unimpaired older adults

Cross-sectional and longitudinal relationships among blood-brain barrier disruption, Alzheimer's disease biomarkers, and cognition in cognitively normal older adults

Blood-brain barrier disruption (BBBd) occurs in aging, particularly in regions vulnerable to Alzheimer's disease (AD) pathology. However, its relationship to pathological protein accumulation, neurodegeneration, and cognitive impairment in normal aging is unclear. We used dynamic contrast-enhanced MRI (DCE-MRI) and positron emission tomography (PET) imaging in cognitively normal older adults to explore how BBBd correlates with brain atrophy and cognitive function, and whether these relationships are influenced by Aβ or tau. We found that greater BBBd in the hippocampus (HC) and an averaged BBBd-susceptible ROI were linked to worse episodic memory, with interactions between BBBd and atrophy influencing this relationship, independent of Aβ and tau. However, there were no significant relationships between BBBd and non-memory cognitive performance. In participants with longitudinal AD biomarker and cognitive data acquired prior to DCE-MRI, faster longitudinal entorhinal cortex (EC) tau accumulation and episodic memory decline were associated with greater HC BBBd, independent of global Aβ changes and regional atrophy. These findings enhance our understanding of the complex relationships between AD biomarkers, cognitive decline, and BBBd.

Preserved brain youthfulness: longitudinal evidence of slower brain aging in superagers

BACKGROUND

Superagers, older adults with exceptional cognitive abilities, show preserved brain structure compared to typical older adults. We investigated whether superagers have biologically younger brains based on their structural integrity.

METHODS

A cohort of 153 older adults (aged 61-93) was recruited, with 63 classified as superagers based on superior episodic memory and 90 as typical older adults, of whom 64 were followed up after two years. A deep learning model for brain age prediction, trained on 899 diverse-aged adults (aged 31-100), was adapted to the older adult cohort via transfer learning. Brain age gap (BAG), a metric based on brain structural patterns, defined as the difference between predicted and chronological age, and its annual rate of change were calculated to assess brain aging status and speed, respectively, and compared among subgroups.

RESULTS

Lower BAGs correlated with more favorable cognitive status in memory and general cognitive function. Superagers exhibited a lower BAG than typical older adults at both baseline and follow-up. Individuals who maintained or attained superager status at follow-up showed a slower annual rate of change in BAG compared to those who remained or became typical older adults.

CONCLUSIONS

Superaging brains manifested maintained neurobiological youthfulness in terms of a more youthful brain aging status and a reduced speed of brain aging. These findings suggest that cognitive resilience, and potentially broader functional resilience, exhibited by superagers during the aging process may be attributable to their younger brains.

Heterogeneity of cerebral atrophic rate in mild cognitive impairment and its interactive association with proteins related to microglia activity on longitudinal cognitive changes

BACKGROUND

Heterogeneity of cerebral atrophic rate commonly exists in mild cognitive impairment (MCI), which may be associated with microglia-involved neuropathology and have an influence on cognitive outcomes.

OBJECTIVE

We aim to explore the heterogeneity of cerebral atrophic rate among MCI and its association with plasma proteins related to microglia activity, with further investigation of their interaction effects on long-term cognition.

SUBJECTS

A total of 630 MCI subjects in the ADNI database were included, of which 260 subjects were available with baseline data on plasma proteins.

METHODS

Group-based multi-trajectory modeling (GBMT) was used to identify the latent classes with heterogeneous cerebral atrophic rates. Associations between latent classes and plasma proteins related to microglia activity were investigated with generalized linear models. Linear mixed effect models (LME) were implemented to explore the interaction effects between proteins related to microglia activity and identified latent classes on longitudinal cognitive changes.

RESULTS

Two latent classes were identified and labeled as the slow-atrophy class and the fast-atrophy class. Associations were found between such heterogeneity of atrophic rates and plasma proteins related to microglia activity, especially AXL receptor tyrosine kinase (AXL), CD40 antigen (CD40), and tumor necrosis factor receptor-like 2 (TNF-R2). Interaction effects on longitudinal cognitive changes showed that higher CD40 was associated with faster cognitive decline in the slow-atrophy class and higher AXL or TNF-R2 was associated with slower cognitive decline in the fast-atrophy class.

CONCLUSIONS

Heterogeneity of atrophic rates at the MCI stage is associated with several plasma proteins related to microglia activity, which show either protective or adverse effects on long-term cognition depending on the variability of atrophic rates.

The characteristics of brain atrophy prior to the onset of Alzheimer's disease: a longitudinal study

Objective

We aimed to use the onset time of Alzheimer's disease (AD) as the reference time to longitudinally investigate the atrophic characteristics of brain structures prior to the onset of AD.

Materials and methods

A total of 328 participants from the ADNI database with clear onset of AD and structural imaging data were included in our study. The time before the onset of AD (abbreviated as BAD) was calculated. We investigated the longitudinal brain changes in 97 regions using multivariate linear mixed effects regression models.

Results

The average BAD was -28.15 months, with a range from -156 to 0 months. The 54 brain regions showed significant atrophy prior to the onset of AD, and these regions were mainly distributed in the frontal and temporal lobes. The parietal and occipital lobe exhibited relatively less atrophy than the other brain lobes. Sex, age, and magnetic field strength had greater direct impacts on structural indicators than APOE genotype and education. The analysis of interaction effects revealed that the APOE ε4 mutation carriers exhibited more severe structural changes in specific brain regions as the BAD increased. However, sex, age, and education had minimal regulatory influence on the structural changes associated with BAD.

Conclusion

Longitudinal analysis, with the onset time point of AD as the reference, can accurately describe the features of structural changes preceding the onset of AD and provide a comprehensive understanding of AD development.

Association of Triglyceride-Glucose Index With Cognitive Function and Brain Atrophy: A Population-Based Study

OBJECTIVE

To investigate the associations of triglyceride-glucose (TyG) index, a reliable surrogate marker for insulin resistance, with the function of various cognitive domains and brain structures among older adults.

DESIGN

A population-based cross-sectional study.

SETTING

Older adults living in the rural communities in China.

PARTICIPANTS

About 4,541 rural-dwelling dementia-free participants (age ≥65 years; 56.37% women) undertook examinations in March-September 2018 for MIND-China.

MEASUREMENTS

TyG index was calculated as ln[fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. A neuropsychological test battery was used to assess memory, attention, verbal fluency, and executive function. Volumetric brain measures were assessed on magnetic resonance imaging (MRI) in a subsample (n = 1,019). Data were analyzed with restricted cubic spline and multivariable general linear models.

RESULTS

An inverted J-shaped association was observed between TyG index and z-scores of multiple cognitive domains, such that among individuals with TyG index ≥8.57 (median), a higher TyG index was significantly associated with lower z-scores of memory, attention, verbal fluency, executive function, and global cognition (all p < 0.05); among people with TyG index <8.57, a higher TyG index was significantly associated with a higher executive function z-score (p < 0.05), but not with any of the other examined cognitive domains. In the MRI subsample, a higher TyG index was significantly associated with lower volumes of total brain tissue, gray matter, and white matter as well as greater cerebrospinal fluid volume (p < 0.05), but not with white matter hyperintensity volume.

CONCLUSIONS

Insulin resistance, as indicated by a high TyG index, was associated with poor function in multiple cognitive domains and global brain atrophy.

Atrophy of specific amygdala subfields in subjects converting to mild cognitive impairment

Introduction

Accumulating evidence indicates that the amygdala exhibits early signs of Alzheimer's disease (AD) pathology. However, it is still unknown whether the atrophy of distinct subfields of the amygdala also participates in the transition from healthy cognition to mild cognitive impairment (MCI).

Methods

Our sample was derived from the AD Neuroimaging Initiative 3 and consisted of 97 cognitively healthy (HC) individuals, sorted into two groups based on their clinical follow-up: 75 who remained stable (s-HC) and 22 who converted to MCI within 48 months (c-HC). Anatomical magnetic resonance (MR) images were analyzed using a semi-automatic approach that combines probabilistic methods and a priori information from ex vivo MR images and histology to segment and obtain quantitative structural metrics for different amygdala subfields in each participant. Spearman's correlations were performed between MR measures and baseline and longitudinal neuropsychological measures. We also included anatomical measurements of the whole amygdala, the hippocampus, a key target of AD-related pathology, and the whole cortical thickness as a test of spatial specificity.

Results

Compared with s-HC individuals, c-HC subjects showed a reduced right amygdala volume, whereas no significant difference was observed for hippocampal volumes or changes in cortical thickness. In the amygdala subfields, we observed selected atrophy patterns in the basolateral nuclear complex, anterior amygdala area, and transitional area. Macro-structural alterations in these subfields correlated with variations of global indices of cognitive performance (measured at baseline and the 48-month follow-up), suggesting that amygdala changes shape the cognitive progression to MCI.

Discussion

Our results provide anatomical evidence for the early involvement of the amygdala in the preclinical stages of AD.

Highlights

Amygdala's atrophy marks elderly progression to mild cognitive impairment (MCI).Amygdala's was observed within the basolateral and amygdaloid complexes.Macro-structural alterations were associated with cognitive decline.No atrophy was found in the hippocampus and cortex.

Respective influence of beta-amyloid and APOE ε4 genotype on medial temporal lobe subregions in cognitively unimpaired older adults

Medial temporal lobe (MTL) subregions are differentially affected in Alzheimer's disease (AD), with a specific involvement of the entorhinal cortex (ERC), perirhinal cortex and hippocampal cornu ammonis (CA)1. While amyloid (Aβ) and APOEε4 are respectively the first molecular change and the main genetic risk factor in AD, their links with MTL atrophy remain relatively unclear. Our aim was to uncover these effects using baseline data from 130 participants included in the Age-Well study, for whom ultra-high-resolution structural MRI, amyloid-PET and APOEε4 genotype were available. No volume differences were observed between Aβ + (n = 24) and Aβ- (n = 103), nor between APOE4+ (n = 35) and APOE4- (n = 95) participants. However, our analyses showed that both Aβ and APOEε4 status interacted with age on CA1, which is known to be specifically atrophied in early AD. In addition, APOEε4 status moderated the effects of age on other subregions (subiculum, ERC), suggesting a more important contribution of APOEε4 than Aβ to MTL atrophy in cognitively unimpaired population. These results are crucial to develop MRI-based biomarkers to detect early AD.

Associations Between Sub-Threshold Amyloid-β Deposition, Cortical Volume, and Cognitive Function Modulated by APOE ɛ4 Carrier Status in Cognitively Normal Older Adults

Background:

There has been renewed interest in the deteriorating effects of sub-threshold amyloid-β (Aβ) accumulation in Alzheimer’s disease (AD). Despite evidence suggesting a synergistic interaction between the APOE ɛ4 allele and Aβ deposition in neurodegeneration, few studies have investigated the modulatory role of this allele in sub-threshold Aβ deposition during the preclinical phase.

Objective:

We aimed to explore the differential effect of the APOE ɛ4 carrier status on the association between sub-threshold Aβ deposition, cortical volume, and cognitive performance in cognitively normal older adults (CN).

Methods:

A total of 112 CN with sub-threshold Aβ deposition was included in the study. Participants underwent structural magnetic resonance imaging, [¹⁸F] flutemetamol PET-CT, and a neuropsychological battery. Potential interactions between APOE ɛ4 carrier status, Aβ accumulation, and cognitive function for cortical volume were assessed with whole-brain voxel-wise analysis.

Results:

We found that greater cortical volume was observed with higher regional Aβ deposition in the APOE ɛ4 carriers, which could be attributed to an interaction between the APOE ɛ4 carrier status and regional Aβ deposition in the posterior cingulate cortex/precuneus. Finally, the APOE ɛ4 carrier status-neuropsychological test score interaction demonstrated a significant effect on the gray matter volume of the left middle occipital gyrus.

Conclusion:

There might be a compensatory response to initiating Aβ in APOE ɛ4 carriers during the earliest AD stage. Despite its exploratory nature, this study offers some insight into recent interests concerning probabilistic AD modeling, focusing on the modulating role of the APOE ɛ4 carrier status during the preclinical period.

Physical exercise promotes brain remodeling by regulating epigenetics, neuroplasticity and neurotrophins

Exercise has been shown to have beneficial effects on brain functions in humans and animals. Exercise can improve memory and learning in age-related neurodegenerative diseases. In animal models, physical exercise regulates epigenetics, promotes synaptic plasticity and hippocampal neurogenesis, regulates the expression levels of neurotrophic factors, and improves cognitive function. Therefore, exercise is very important for brain rehabilitation and remodeling. The purpose of this review is to explore the mechanisms by which exercise exerts positive effects on brain function. This knowledge implies that physical exercise can be used as a non-drug therapy for neurological diseases.

Predicting amyloid status using self-report information from an online research and recruitment registry: The Brain Health Registry

INTRODUCTION

This study aimed to predict brain amyloid beta (Aβ) status in older adults using collected information from an online registry focused on cognitive aging.

METHODS

Aβ positron emission tomography (PET) was obtained from multiple in-clinic studies. Using logistic regression, we predicted Aβ using self-report variables collected in the Brain Health Registry in 634 participants, as well as a subsample (N = 533) identified as either cognitively unimpaired (CU) or mild cognitive impairment (MCI). Cross-validated area under the curve (cAUC) evaluated the predictive performance.

RESULTS

The best prediction model included age, sex, education, subjective memory concern, family history of Alzheimer's disease, Geriatric Depression Scale Short-Form, self-reported Everyday Cognition, and self-reported cognitive impairment. The cross-validated AUCs ranged from 0.62 to 0.66. This online model could help reduce between 15.2% and 23.7% of unnecessary Aβ PET scans in CU and MCI populations.

DISUCSSION

The findings suggest that a novel, online approach could aid in Aβ prediction.