Hippocampal and Parahippocampal Gray Matter Structural Integrity Assessed by Multimodal Imaging Is Associated with Episodic Memory in Old Age

Temporo-frontoparietal hypoconnectivity as a biomarker for isolated language impairment in mild cognitive impairment: A cross-cohort comparison

INTRODUCTION

Whether brain functional connectivity (FC) is consistently disrupted in individuals with mild cognitive impairment (MCI) with isolated language impairment (ilMCI), and its potential to differentiate between MCI subtypes remains uncertain.

METHODS

Cross-sectional data from 404 participants in two cohorts (the Chinese Preclinical Alzheimer's Disease Study and the Alzheimer's Disease Neuroimaging Initiative) were analyzed, including neuropsychological tests, resting-state functional magnetic resonance imaging (fMRI), cerebral amyloid positivity, and apolipoprotein E (APOE) status.

RESULTS

Temporo-frontoparietal FC, particularly between the bilateral superior temporal pole and the left inferior frontal/supramarginal gyri, was consistently decreased in ilMCI compared to amnestic MCI (aMCI) and normal controls, which was correlated with semantic impairment. Using mean temporo-frontoparietal FC as a classifier could improve accuracy in identifying ilMCI subgroups with positive cerebral amyloid deposition and APOE risk alleles.

DISCUSSION

Temporal-frontoparietal hypoconnectivity was observed in individuals with ilMCI, which may reflect semantic impairment and serve as a valuable biomarker to indicate potential mechanisms of underlying neuropathology.

HIGHLIGHTS

Temporo-frontoparietal hypoconnectivity was observed in impaired language mild cognitive impairment (ilMCI). Temporo-frontoparietal hypoconnectivity may reflect semantic impairment. Temporo-frontoparietal functional connectivity can classify ilMCI subtypes.

Grey-matter structure in cortical and limbic regions correlates with general cognitive ability in old age

According to the maintenance hypothesis (Nyberg et al., 2012), structural integrity of the brain's grey matter helps to preserve cognitive functioning into old age. A corollary of this hypothesis that can be tested in cross-sectional data is that grey-matter structural integrity and general cognitive ability are positively associated in old age. Building on Köhncke et al. (2021), who found that region-specific latent factors of grey-matter integrity are positively associated with episodic memory ability among older adults, we examine associations between general factors of grey-matter integrity and a general factor of cognitive ability in a cross-sectional sample of 1466 participants aged 60-88 years, 319 of whom contributed imaging data. Indicator variables based on T1-weighted images (voxel-based morphometry, VBM), magnetization-transfer imaging (MT), and diffusion tensor imaging-derived mean diffusivity (MD) had sufficient portions of variance in common to establish latent factors of grey-matter structure for a comprehensive set of regions of interest (ROI). Individual differences in grey-matter factors were positively correlated across neocortical and limbic areas, allowing for the definition of second-order, general factors for neocortical and limbic ROI, respectively. Both general grey-matter factors were positively correlated with general cognitive ability. For the basal ganglia, the three modality-specific indicators showed heterogenous loading patterns, and no reliable associations of the general grey-matter factor to general cognitive ability were found. To provide more direct tests of the maintenance hypothesis, we recommend applying the present structural modeling approach to longitudinal data, thereby enhancing the physiological validity of latent constructs of brain structure.

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.

Retinal ganglion cell-inner plexiform layer, white matter hyperintensities, and their interaction with cognition in older adults

Purpose

We explored the interaction of optical coherence tomography (OCT) parameters and white matter hyperintensities with cognitive measures in our older adult cohort.

Methods

This observational study enrolled participants who underwent a comprehensive neuropsychological battery, structural 3-T brain magnetic resonance imaging (MRI), visual acuity examination, and OCT imaging. Cerebral small vessel disease (CSVD) markers were read on MR images; lacune, cerebral microbleeds (CMB), white matter hyperintensities (WMH), and enlarged perivascular spaces (EPVS), were defined according to the STRIVE standards. Retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thicknesses (μm) were measured on the OCT tool.

Results

Older adults with cognitive impairment (CI) showed lower RNFL (p = 0.001), GCIPL (p = 0.009) thicknesses, and lower hippocampal volume (p = 0.004) when compared to non-cognitively impaired (NCI). RNFL (p = 0.006) and GCIPL thicknesses (p = 0.032) correlated with MoCA scores. GCIPL thickness (p = 0.037), total WMH (p = 0.003), PWMH (p = 0.041), and DWMH (p = 0.001) correlated with hippocampal volume in our older adults after adjusting for covariates. With hippocampal volume as the outcome, a significant interaction (p < 0.05) between GCIPL and PWMH and total WMH was observed in our older adults.

Conclusion

Both GCIPL thinning and higher WMH burden (especially PWMH) are associated with hippocampal volume and older adults with both pathologies are more susceptible to subclinical cognitive decline.

The integrity of dopaminergic and noradrenergic brain regions is associated with different aspects of late-life memory performance

Changes in dopaminergic neuromodulation play a key role in adult memory decline. Recent research has also implicated noradrenaline in shaping late-life memory. However, it is unclear whether these two neuromodulators have distinct roles in age-related cognitive changes. Here, combining longitudinal MRI of the dopaminergic substantia nigra-ventral tegmental area (SN-VTA) and noradrenergic locus coeruleus (LC) in younger (n = 69) and older (n = 251) adults, we found that dopaminergic and noradrenergic integrity are differentially associated with memory performance. While LC integrity was related to better episodic memory across several tasks, SN-VTA integrity was linked to working memory. Longitudinally, we found that older age was associated with more negative change in SN-VTA and LC integrity. Notably, changes in LC integrity reliably predicted future episodic memory. These differential associations of dopaminergic and noradrenergic nuclei with late-life cognitive decline have potential clinical utility, given their degeneration in several age-associated diseases.

The use of hippocampal grading as a biomarker for preclinical and prodromal Alzheimer's disease

Hippocampal changes are associated with increased age and cognitive decline due to mild cognitive impairment (MCI) and Alzheimer's disease (AD). These associations are often observed only in the later stages of decline. This study examined if hippocampal grading, a method measuring local morphological similarity of the hippocampus to cognitively normal controls (NCs) and AD participants, is associated with cognition in NCs, subjective cognitive decline (SCD), early (eMCI), late (lMCI), and AD. A total of 1620 Alzheimer's Disease Neuroimaging Initiative participants were examined (495 NC, 262 eMCI, 545 lMCI, and 318 AD) because they had baseline MRIs and Alzheimer's disease Assessment Scale (ADAS-13) and Clinical Dementia Rating-Sum of Boxes (CDR-SB) scores. In a sub-analysis, NCs with episodic memory scores (as measured by Rey Auditory Verbal Learning Test, RAVLT) were divided into those with subjective cognitive decline (SCD+; 103) and those without (SCD-; 390). Linear regressions evaluated the influence of hippocampal grading on cognition in preclinical and prodromal AD. Lower global cognition, as measured by increased ADAS-13, was associated with hippocampal grading: NC (p < .001), eMCI (p < .05), lMCI (p < .05), and AD (p = .01). Lower global cognition as measured increased CDR-SB was associated with hippocampal grading in lMCI (p < .05) and AD (p < .001). Lower RAVLT performance was associated with hippocampal grading in SCD- (p < .05) and SCD+ (p < .05). These findings suggest that hippocampal grading is associated with global cognition in NC, eMCI, lMCI, and AD. Early changes in episodic memory during pre-clinical AD are associated with changes in hippocampal grading. Hippocampal grading may be sensitive to progressive changes early in the disease course.

Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models

We present generalized additive latent and mixed models (GALAMMs) for analysis of clustered data with responses and latent variables depending smoothly on observed variables. A scalable maximum likelihood estimation algorithm is proposed, utilizing the Laplace approximation, sparse matrix computation, and automatic differentiation. Mixed response types, heteroscedasticity, and crossed random effects are naturally incorporated into the framework. The models developed were motivated by applications in cognitive neuroscience, and two case studies are presented. First, we show how GALAMMs can jointly model the complex lifespan trajectories of episodic memory, working memory, and speed/executive function, measured by the California Verbal Learning Test (CVLT), digit span tests, and Stroop tests, respectively. Next, we study the effect of socioeconomic status on brain structure, using data on education and income together with hippocampal volumes estimated by magnetic resonance imaging. By combining semiparametric estimation with latent variable modeling, GALAMMs allow a more realistic representation of how brain and cognition vary across the lifespan, while simultaneously estimating latent traits from measured items. Simulation experiments suggest that model estimates are accurate even with moderate sample sizes.

Mental and physical health pathways linking insomnia symptoms to cognitive performance 14 years later

STUDY OBJECTIVES

Insomnia may be a modifiable risk factor for later-life cognitive impairment. We investigated: (1) which insomnia symptoms are associated with subsequent cognitive functioning across domains; (2) whether insomnia-cognition associations are mediated by mental and physical health; and (3) whether these associations are modified by gender.

METHODS

Participants included 2595 adults ages 51-88 at baseline (Mage=64.00 ± 6.66, 64.5% women) in the Health and Retirement Study. The frequency of insomnia symptoms (difficulty initiating sleep, night time awakenings, early awakenings, and feeling unrested upon awakening) at baseline (2002) were quantified using a modified Jenkins Sleep Questionnaire. Cognition was assessed in 2016 via the Harmonized Cognitive Assessment Protocol and operationalized with factor scores corresponding to five domains. Depressive symptoms and vascular conditions in 2014 were assessed via self-report. Structural equation models estimated total, indirect, and direct effects of insomnia symptoms on subsequent cognition through depressive symptoms and vascular diseases, controlling for baseline sociodemographic and global cognition.

RESULTS

Frequent difficulty initiating sleep was associated with poorer episodic memory, executive function, language, visuoconstruction, and processing speed 14 years later (-0.06 ≤ β ≤ -0.04; equivalent to 2.2-3.4 years of aging). Depressive symptoms explained 12.3%-19.5% of these associations and vascular disease explained 6.3%-14.6% of non-memory associations. No other insomnia symptoms were associated with cognition, and no associations were modified by gender.

CONCLUSIONS

Difficulty initiating sleep in later life may predict future cognitive impairment through multiple pathways. Future research with longitudinal assessments of insomnia, insomnia treatments, and cognition is needed to evaluate insomnia as a potential intervention target to optimize cognitive aging.

Graph Analysis of Functional Brain Topology Using Minimum Spanning Tree in Subjective Cognitive Decline

BACKGROUND

Subjects with subjective cognitive decline (SCD) are proposed as a potential population to screen for Alzheimer's disease (AD).

OBJECTIVE

Investigating brain topologies would help to mine the neuromechanisms of SCD and provide new insights into the pathogenesis of AD.

METHODS

Objectively cognitively unimpaired subjects from communities who underwent resting-state BOLD-fMRI and clinical assessments were included. The subjects were categorized into SCD and normal control (NC) groups according to whether they exhibited self-perceived cognitive decline and were worried about it. The minimum spanning tree (MST) of the functional brain network was calculated for each subject, based on which the efficiency and centrality of the brain network organization were explored. Hippocampal/parahippocampal volumes were also detected to reveal whether the early neurodegeneration of AD could be seen in SCD.

RESULTS

A total of 49 subjects in NC and 95 subjects in SCD group were included in this study. We found the efficiency and centrality of brain network organization, as well as the hippocampal/parahippocampal volume were preserved in SCD. Besides, SCD exhibited normal cognitions, including memory, language, and execution, but increased depressive and anxious levels. Interestingly, language and execution, instead of memory, showed a significant positive correlation with the maximum betweenness centrality of the functional brain organization and hippocampal/parahippocampal volume. Neither depressive nor anxious scales exhibited correlations with the brain functional topologies or hippocampal/parahippocampal volume.

CONCLUSION

SCD exhibited preserved efficiency and centrality of brain organization. In clinical practice, language and execution as well as depression and anxiety should be paid attention in SCD.

Cognitive reserve and risk of mobility impairment in older adults

BACKGROUND

Cognitive reserve (CR) protects against cognitive decline and dementia but its relation to mobility impairment has not been established. To address this important gap in the literature, we conducted a longitudinal investigation to test the hypothesis that higher baseline CR was associated with a lower risk of developing mobility impairment in older adults.

METHODS

Participants were dementia-free older adults who received brain magnetic resonance imaging and had gait speed assessments during follow-up. Using the residuals approach, CR was computed as the variance in the Modified Mini-Mental Status Examination total score, that was left after accounting for structural brain integrity, education, and race. Mobility impairment was defined using a validated cutoff score in gait speed of 0.8 m/s. Logistic regression models using general estimating equations were utilized to examine longitudinal associations between baseline CR and the risk of developing mobility impairment across repeated assessments.

RESULTS

Of the participants (n = 237; mean age = 82 years; %female = 56%) who were free of mobility impairment at baseline, 103 developed mobility impairment during follow-up (mean = 3.1 years). Higher CR at baseline was associated with a lower risk of developing incident mobility impairment-odds ratio (OR) = 0.819, 0.67-0.98, p = 0.038 (unadjusted); OR = 0.815, 0.67-0.99, p = 0.04 (adjusted for socio-demographic variables and depression); OR = 0.819, 0.68-0.88, p = 0.035 (adjusted for illness history); OR = 0.824, 0.68-0.99, p = 0.045 (adjusted for white matter hyperintensities); OR = 0.795, 0.65-0.95, p = 0.016 (adjusted for falls history).

CONCLUSION

Higher CR at baseline was protective against developing incident mobility impairment during follow-up among community-residing older adults.

Higher-order multi-shell diffusion measures complement tensor metrics and volume in gray matter when predicting age and cognition

Recent advances in diffusion-weighted imaging have enabled us to probe the microstructure of even gray matter non-invasively. However, these advanced multi-shell protocols are often not included in large-scale studies as they significantly increase scan time. In this study, we investigated whether one set of multi-shell diffusion metrics commonly used in gray matter (as derived from Neurite Orientation Dispersion and Density Imaging, NODDI) provide enough additional information over typical tensor and volume metrics to justify the increased acquisition time, using the cognitive aging framework in the human hippocampus as a testbed. We first demonstrated that NODDI metrics are robust and reliable by replicating previous findings from our lab in a larger population of 79 younger (20.41 ± 1.89 years, 46 females) and 75 older (73.56 ± 6.26 years, 45 females) adults, showing that these metrics in the hippocampal subfields are sensitive to age and memory performance. We then asked how these subfield specific hippocampal NODDI metrics compared with standard tensor metrics and volume in predicting age and memory ability. We discovered that both NODDI and tensor measures separately predicted age and cognition in comparable capacities. However, integrating these modalities together considerably increased the predictive power of our logistic models, indicating that NODDI and tensor measures may be capturing independent microstructural information. We use these findings to encourage neuroimaging data collection consortiums to include a multi-shell diffusion sequence in their protocols since existing NODDI measures (and potential future multi-shell measures) may be able to capture microstructural variance that is missed by traditional approaches, even in studies exclusively examining gray matter.

Change in Latent Gray-Matter Structural Integrity Is Associated With Change in Cardiovascular Fitness in Older Adults Who Engage in At-Home Aerobic Exercise

In aging humans, aerobic exercise interventions have been found to be associated with more positive or less negative changes in frontal and temporal brain areas, such as the anterior cingulate cortex (ACC) and hippocampus, relative to no-exercise control conditions. However, individual measures such as gray-matter (GM) probability may afford less reliable and valid conclusions about maintenance or losses in structural brain integrity than a latent construct based on multiple indicators. Here, we established a latent factor of GM structural integrity based on GM probability assessed by voxel-based morphometry, magnetization transfer saturation, and mean diffusivity. Based on this latent factor, we investigated changes in structural brain integrity during a six-month exercise intervention in brain regions previously reported in studies using volumetric approaches. Seventy-five healthy, previously sedentary older adults aged 63-76 years completed an at-home intervention study in either an exercise group (EG; n = 40) or in an active control group (ACG; n = 35). Measures of peak oxygen uptake (VO2peak) taken before and after the intervention revealed a time-by-group interaction, with positive average change in the EG and no reliable mean change in the ACG. Significant group differences in structural brain integrity changes were observed in the right and left ACC, right posterior cingulate cortex (PCC), and left juxtapositional lobule cortex (JLC). In all instances, average changes in the EG did not differ reliably from zero, whereas average changes in the ACG were negative, pointing to maintenance of structural brain integrity in the EG, and to losses in the ACG. Significant individual differences in change were observed for right ACC and left JLC. Following up on these differences, we found that exercising participants with greater fitness gains also showed more positive changes in structural integrity. We discuss the benefits and limitations of a latent-factor approach to changes in structural brain integrity, and conclude that aerobic fitness interventions are likely to contribute to brain maintenance in old age.

A robust brain signature region approach for episodic memory performance in older adults

This scientific commentary refers to ‘A robust brain signature region approach for episodic memory performance in older adults’ by Fletcher et al. (doi:10.1093/brain/awab007).

A knowledge-based multivariate statistical method for examining gene-brain-behavioral/cognitive relationships: Imaging genetics generalized structured component analysis

With advances in neuroimaging and genetics, imaging genetics is a naturally emerging field that combines genetic and neuroimaging data with behavioral or cognitive outcomes to examine genetic influence on altered brain functions associated with behavioral or cognitive variation. We propose a statistical approach, termed imaging genetics generalized structured component analysis (IG-GSCA), which allows researchers to investigate such gene-brain-behavior/cognitive associations, taking into account well-documented biological characteristics (e.g., genetic pathways, gene-environment interactions, etc.) and methodological complexities (e.g., multicollinearity) in imaging genetic studies. We begin by describing the conceptual and technical underpinnings of IG-GSCA. We then apply the approach for investigating how nine depression-related genes and their interactions with an environmental variable (experience of potentially traumatic events) influence the thickness variations of 53 brain regions, which in turn affect depression severity in a sample of Korean participants. Our analysis shows that a dopamine receptor gene and an interaction between a serotonin transporter gene and the environment variable have statistically significant effects on a few brain regions' variations that have statistically significant negative impacts on depression severity. These relationships are largely supported by previous studies. We also conduct a simulation study to safeguard whether IG-GSCA can recover parameters as expected in a similar situation.