Associations between cognitive and brain volume changes in cognitively normal older adults

Influence of cognitive reserve on cognitive and motor function in α-synucleinopathies: A systematic review and multilevel meta-analysis

Cognitive reserve has shown promise as a justification for neuropathologically unexplainable clinical outcomes in Alzheimer's disease. Recent evidence suggests this effect may be replicated in conditions like Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. However, the relationships between cognitive reserve and different cognitive abilities, as well as motor outcomes, are still poorly understood in these conditions. Additionally, it is unclear whether the reported effects are confounded by medication. This review analysed studies investigating the relationship between cognitive reserve and clinical outcomes in these α-synucleinopathy cohorts, identified from MEDLINE, Scopus, psycINFO, CINAHL, and Web of Science. 85 records, containing 176 cognition and 31 motor function effect sizes, were pooled using multilevel meta-analysis. There was a significant, positive association between higher cognitive reserve and both better cognition and motor function. Cognition effect sizes differed by disease subtype, cognitive reserve measure, and outcome type; however, no moderators significantly impacted motor function. Review findings highlight the clinical implications of cognitive reserve and importance of engaging in reserve-building behaviours.

Age-related enhancement of the association between episodic memory and gray matter volume in medial temporal and frontal lobes

BACKGROUND

Episodic memory (EM) deteriorates as a result of normal aging as well as Alzheimer's disease. The neural underpinnings of such age-related memory impairments in older individuals are not well-understood. Although previous research has unveiled the association between gray matter volume (GMV) and EM in the elderly population, such findings exhibit variances across distinct age cohorts. Consequently, an investigation into the dynamic evolution of this relationship with advancing age is imperative.

RESULT

The present study utilized a sliding window approach to examine how the correlation between EM and GMV varied with age in a cross-sectional sample of 926 Chinese older adults. We found that both verbal EM (VEM) and spatial EM (SEM) exhibited positive correlations with GMV in extensive areas primarily in the temporal and frontal lobes and that these correlations typically became stronger with older age. Moreover, there were variations in the strength of the correlation between EM and GMV with age, which differed based on sex and the specific type of EM. Specifically, the association between VEM and GMVs in the insula and parietal regions became stronger with age for females but not for males, whereas the association between SEM and GMVs in the parietal and occipital regions became stronger for males but not for females. At the brain system level, there is a significant age-related increase in the correlations between both types of EM and the GMV of both the anterior temporal (AT) system and the posterior medial (PM) system in male group. In females, both types of EM show stronger age-related correlations with the GMV of the AT system compared to males.

CONCLUSIONS

Our study revealed a significant positive correlation between GMV in most regions associated with EM and age, particularly in the frontal and temporal lobes. This discovery offers new insights into the connection between brain structure and the diminishing episodic memory function among older individuals.

Total-Body Irradiation Alters White Matter Volume and Microstructural Integrity in Rhesus Macaques

PURPOSE

Long-term survivors of brain irradiation can experience irreversible injury and cognitive impairment. T1-weighted and diffusion tensor magnetic resonance imaging (MRI) are used to evaluate brain volume and white matter (WM) microstructure in neurodevelopmental and neurodegenerative conditions. The goal of this study was to evaluate the long-term effects of single-dose total-body irradiation (TBI) or TBI with 5% partial-body sparing on brain volumetrics and WM integrity in macaques.

METHODS AND MATERIALS

We used MRI scans from a cohort of male rhesus macaques (age range, 3.6-22.8 years) to compare global and regional brain volumes and WM diffusion in survivors of TBI (T1-weighted, n = 137; diffusion tensor imaging, n = 121; dose range, 3.5-10 Gy) with unirradiated controls (T1-weighted, n = 48; diffusion tensor imaging, n = 38).

RESULTS

In all regions of interest, radiation affected age-related changes in fractional anisotropy, which tended to increase across age in both groups but to a lesser extent in the irradiated group (interaction P < .01). Depending on the region of interest, mean diffusivity decreased or remained the same across age in unirradiated animals, whereas it increased or did not change in irradiated animals. The increases in mean diffusivity were driven by changes in radial diffusivity, which followed similar trends across age. Axial diffusivity did not differ by irradiation status. Age-related changes in relative volumes in controls reflected normal trends in humans, with increasing WM and decreasing gray matter until middle age. Cerebrospinal fluid (CSF) volume did not differ across age in controls. WM volume was lower and CSF volume was higher in young irradiated macaques. WM volume was similar between groups, and CSF volume lower in older irradiated macaques. Gray matter volume was unaffected by radiation.

CONCLUSIONS

TBI results in delayed WM expansion and long-term disruption of WM integrity. Diffusion changes suggest that myelin injury in WM is a hallmark of late-delayed radiation-induced brain injury.

Cross-sectional associations between multisensory impairment and brain volumes in older adults: Baltimore Longitudinal Study of Aging

Sensory impairment and brain atrophy is common among older adults, increasing the risk of dementia. Yet, the degree to which multiple co-occurring sensory impairments (MSI across vision, proprioception, vestibular function, olfactory, and hearing) are associated with brain morphometry remain unexplored. Data were from 208 cognitively unimpaired participants (mean age 72 ± 10 years; 59% women) enrolled in the Baltimore Longitudinal Study of Aging. Multiple linear regression models were used to estimate cross-sectional associations between MSI and regional brain imaging volumes. For each additional sensory impairment, there were associated lower orbitofrontal gyrus and entorhinal cortex volumes but higher caudate and putamen volumes. Participants with MSI had lower mean volumes in the superior frontal gyrus, orbitofrontal gyrus, superior parietal lobe, and precuneus compared to participants with < 2 impairments. While MSI was largely associated with lower brain volumes, our results suggest the possibility that MSI was associated with higher basal ganglia volumes. Longitudinal analyses are needed to evaluate the temporality and directionality of these associations.

Uncorking the limitation-improving dual tasking using transcranial electrical stimulation and task training in the elderly: a systematic review

Introduction

With aging, dual task (DT) ability declines and is more cognitively demanding than single tasks. Rapidly declining DT performance is regarded as a predictor of neurodegenerative disease. Task training and non-invasive transcranial electrical stimulation (tES) are methods applied to optimize the DT ability of the elderly.

Methods

A systematic search was carried out in the PUBMED, TDCS (transcranial direct current stimulation) databases, as well as Web of Science, and a qualitative analysis was conducted in 56 included studies. Aiming to summarize the results of studies that implemented tES, task training, or the combination for improving DT ability and related performance changes in healthy elderly and geriatric patients. For different approaches, the training procedures, parameters, as well as outcomes were discussed.

Results

Task training, particularly cognitive-motor DT training, has more notable effects on improving DT performance in the elderly when compared to the neuromodulation method.

Discussion

Anodal transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (L-DLPFC), or its combination with task training could be promising tools. However, additional evidence is required from aged healthy people and patients, as well as further exploration of electrode montage.

Discontinuity of deep medullary veins in SWI is associated with deep white matter hyperintensity volume and cognitive impairment in cerebral small vessel disease

BACKGROUND

Discontinuation of the deep medullary veins (DMVs) may be an early imaging marker for identifying cognitive impairment caused by cerebral small vessel disease (CSVD). However, this method lacks mechanistic exploration. We aimed to investigate whether the DMV score is related to CSVD imaging markers and cognitive impairment in patients with CSVD.

METHODS

This retrospective study included patients with CSVD who completed DMV score and cognition (e.g., MMSE, MoCA) assessments, and underwent MRI scanning (T2-FLAIR for white matter hyperintensities (WMH) volume, T1-weighted MRI for brain parenchymal fractions (BPF) analysis, and SWI for assessment of DMV score). The CSVD imaging markers were quantitatively assessed using the AccuBrain® system. We assessed the diagnostic value of neuroimaging biomarkers for detecting CSVD-related cognitive impairment. In addition, we explored the relationship between the DMV score, CSVD imaging markers, and cognition using mediation analysis.

RESULTS

Ninety-four patients with CSVD were divided into a cognitive impairment group (n = 39) and a non-cognitive impairment group (n = 55). Higher DMV scores, larger WMH volumes, and smaller BPF were observed in the cognitive impairment group than those in the non-cognitive impairment group. Receiver operating characteristics (ROC) analysis revealed that the discovery value of the integration of patient age, BPF, whole WMH volume, and DMV score for cognitive impairment was 0.742, with a sensitivity and specificity of 79.5 % and 61.5 %, respectively. Mediation analysis showed mediation by WMH and BPF in the relationship between DMV score and cognitive impairment (all P < 0.05).

LIMITATIONS

This study did not evaluate the DMV score in subregions according to DMV anatomy.

CONCLUSIONS

The DMV score is significantly associated with cognitive impairment in patients with CSVD, and this association is mediated through WMH and BPF.

Residual Partial Least Squares Learning: Brain Cortical Thickness Simultaneously Predicts Eight Non-pairwise-correlated Behavioural and Disease Outcomes in Alzheimer's Disease

Alzheimer's Disease (AD) is the leading cause of dementia. It results in cortical thickness changes and is associated with a decline in cognition and behaviour. Such decline affects multiple important day-to-day functions, including memory, language, orientation, judgment and problem-solving. Recent research has made important progress in identifying brain regions associated with single outcomes, such as individual AD status and general cognitive decline. The complex projection from multiple brain areas to multiple AD outcomes, however, remains poorly understood. This makes the assessment and especially the prediction of multiple AD outcomes - each of which may unveil an integral yet different aspect of the disease - challenging, particularly when some are not strongly correlated. Here, uniting residual learning, partial least squares (PLS), and predictive modelling, we develop an explainable, generalisable, and reproducible method called the Residual Partial Least Squares Learning (the re-PLS Learning) to (1) chart the pathways between large-scale multivariate brain cortical thickness data (inputs) and multivariate disease and behaviour data (outcomes); (2) simultaneously predict multiple, non-pairwise-correlated outcomes; (3) control for confounding variables (e.g., age and gender) affecting both inputs and outcomes and the pathways in-between; (4) perform longitudinal AD disease status classification and disease severity prediction. We evaluate the performance of the proposed method against a variety of alternatives on data from AD patients, subjects with mild cognitive impairment (MCI), and cognitively normal individuals ( n = 1,196 ) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Our results unveil pockets of brain areas in the temporal, frontal, sensorimotor, and cingulate areas whose cortical thickness may be respectively associated with declines in different cognitive and behavioural subdomains in AD. Finally, we characterise re-PLS' geometric interpretation and mathematical support for delivering meaningful neurobiological insights and provide an open software package (re-PLS) available at https://github.com/thanhvd18/rePLS.

Associations between vascular health, brain stiffness and global cognitive function

Vascular brain injury results in loss of structural and functional connectivity and leads to cognitive impairment. Its various manifestations, including microinfarcts, microhaemorrhages and white matter hyperintensities, result in microstructural tissue integrity loss and secondary neurodegeneration. Among these, tissue microstructural alteration is a relatively early event compared with atrophy along the aging and neurodegeneration continuum. Understanding its association with cognition may provide the opportunity to further elucidate the relationship between vascular health and clinical outcomes. Magnetic resonance elastography offers a non-invasive approach to evaluate tissue mechanical properties, providing a window into the microstructural integrity of the brain. This retrospective study evaluated brain stiffness as a potential biomarker for vascular brain injury and its role in mediating the impact of vascular dysfunction on cognitive impairment. Seventy-five participants from the Mayo Clinic Study of Aging underwent brain imaging using a 3T MR imager with a spin-echo echo-planar imaging sequence for magnetic resonance elastography and T1- and T2-weighted pulse sequences. This study evaluated the effects of vascular biomarkers (white matter hyperintensities and cardiometabolic condition score) on brain stiffness using voxelwise analysis. Partial correlation analysis explored associations between brain stiffness, white matter hyperintensities, cardiometabolic condition and global cognition. Mediation analysis determined the role of stiffness in mediating the relationship between vascular biomarkers and cognitive performance. Statistical significance was set at P-values < 0.05. Diagnostic accuracy of magnetic resonance elastography stiffness for white matter hyperintensities and cardiometabolic condition was evaluated using receiver operator characteristic curves. Voxelwise linear regression analysis indicated white matter hyperintensities negatively correlate with brain stiffness, specifically in periventricular regions with high white matter hyperintensity levels. A negative association between cardiovascular risk factors and stiffness was also observed across the brain. No significant patterns of stiffness changes were associated with amyloid load. Global stiffness (µ) negatively correlated with both white matter hyperintensities and cardiometabolic condition when all other covariables including amyloid load were controlled. The positive correlation between white matter hyperintensities and cardiometabolic condition weakened and became statistically insignificant when controlling for other covariables. Brain stiffness and global cognition were positively correlated, maintaining statistical significance after adjusting for all covariables. These findings suggest mechanical alterations are associated with cognitive dysfunction and vascular brain injury. Brain stiffness significantly mediated the indirect effects of white matter hyperintensities and cardiometabolic condition on global cognition. Local cerebrovascular diseases (assessed by white matter hyperintensities) and systemic vascular risk factors (assessed by cardiometabolic condition) impact brain stiffness with spatially and statistically distinct effects. Global brain stiffness is a significant mediator between vascular disease measures and cognitive function, highlighting the value of magnetic resonance elastography-based mechanical assessments in understanding this relationship.

Prediction of cognitive performance differences in older age from multimodal neuroimaging data

Differences in brain structure and functional and structural network architecture have been found to partly explain cognitive performance differences in older ages. Thus, they may serve as potential markers for these differences. Initial unimodal studies, however, have reported mixed prediction results of selective cognitive variables based on these brain features using machine learning (ML). Thus, the aim of the current study was to investigate the general validity of cognitive performance prediction from imaging data in healthy older adults. In particular, the focus was with examining whether (1) multimodal information, i.e., region-wise grey matter volume (GMV), resting-state functional connectivity (RSFC), and structural connectivity (SC) estimates, may improve predictability of cognitive targets, (2) predictability differences arise for global cognition and distinct cognitive profiles, and (3) results generalize across different ML approaches in 594 healthy older adults (age range: 55-85 years) from the 1000BRAINS study. Prediction potential was examined for each modality and all multimodal combinations, with and without confound (i.e., age, education, and sex) regression across different analytic options, i.e., variations in algorithms, feature sets, and multimodal approaches (i.e., concatenation vs. stacking). Results showed that prediction performance differed considerably between deconfounding strategies. In the absence of demographic confounder control, successful prediction of cognitive performance could be observed across analytic choices. Combination of different modalities tended to marginally improve predictability of cognitive performance compared to single modalities. Importantly, all previously described effects vanished in the strict confounder control condition. Despite a small trend for a multimodal benefit, developing a biomarker for cognitive aging remains challenging.

Development of Efficient Brain Age Estimation Method Based on Regional Brain Volume From Structural Magnetic Resonance Imaging

OBJECTIVE

We aimed to create an efficient and valid predicting model which can estimate individuals' brain age by quantifying their regional brain volumes.

METHODS

A total of 2,560 structural brain magnetic resonance imaging (MRI) scans, along with demographic and clinical data, were obtained. Pretrained deep-learning models were employed to automatically segment the MRI data, which enabled fast calculation of regional brain volumes. Brain age gaps for each subject were estimated using volumetric values from predefined 12 regions of interest (ROIs): bilateral frontal, parietal, occipital, and temporal lobes, as well as bilateral hippocampus and lateral ventricles. A larger weight was given to the ROIs having a larger mean volumetric difference between the cognitively unimpaired (CU) and cognitively impaired group including mild cognitive impairment (MCI), and dementia groups. The brain age was predicted by adding or subtracting the brain age gap to the chronological age according to the presence or absence of the atrophy region.

RESULTS

The study showed significant differences in brain age gaps among CU, MCI, and dementia groups. Furthermore, the brain age gaps exhibited significant correlations with education level and measures of cognitive function, including the clinical dementia rating sum-of-boxes and the Korean version of the Mini-Mental State Examination.

CONCLUSION

The brain age that we developed enabled fast and efficient brain age calculations, and it also reflected individual's cognitive function and cognitive reserve. Thus, our study suggested that the brain age might be an important marker of brain health that can be used effectively in real clinical settings.

Visual Functions Are Associated with Biomarker Changes in Alzheimer's Disease

Background

While various biomarkers of Alzheimer's disease (AD) have been associated with general cognitive function, their association to visual-perceptive function across the AD spectrum warrant more attention due to its significant impact on quality of life. Thus, this study explores how AD biomarkers are associated with decline in this cognitive domain.

Objective

To explore associations between various fluid and imaging biomarkers and visual-based cognitive assessments in participants across the AD spectrum.

Methods

Data from participants (N = 1,460) in the Alzheimer's Disease Neuroimaging Initiative were analyzed, including fluid and imaging biomarkers. Along with the Mini-Mental State Examination (MMSE), three specific visual-based cognitive tests were investigated: Trail Making Test (TMT) A and TMT B, and the Boston Naming Test (BNT). Locally estimated scatterplot smoothing curves and Pearson correlation coefficients were used to examine associations.

Results

MMSE showed the strongest correlations with most biomarkers, followed by TMT-B. The p-tau181/Aβ1-42 ratio, along with the volume of the hippocampus and entorhinal cortex, had the strongest associations among the biomarkers.

Conclusions

Several biomarkers are associated with visual processing across the disease spectrum, emphasizing their potential in assessing disease severity and contributing to progression models of visual function and cognition.

Alzheimer's Related Neurodegeneration Mediates Air Pollution Effects on Medial Temporal Lobe Atrophy

Exposure to ambient air pollution, especially particulate matter with aerodynamic diameter <2.5 μm (PM2.5) and nitrogen dioxide (NO2), are environmental risk factors for Alzheimer's disease and related dementia. The medial temporal lobe (MTL) is an important brain region subserving episodic memory that atrophies with age, during the Alzheimer's disease continuum, and is vulnerable to the effects of cerebrovascular disease. Despite the importance of air pollution it is unclear whether exposure leads to atrophy of the MTL and by what pathways. Here we conducted a longitudinal study examining associations between ambient air pollution exposure and MTL atrophy and whether putative air pollution exposure effects resembled Alzheimer's disease-related neurodegeneration or cerebrovascular disease-related neurodegeneration. Participants included older women (n = 627; aged 71-87) who underwent two structural brain MRI scans (MRI-1: 2005-6; MRI-2: 2009-10) as part of the Women's Health Initiative Memory Study of Magnetic Resonance Imaging. Regionalized universal kriging was used to estimate annual concentrations of PM2.5 and NO2 at residential locations aggregated to 3-year averages prior to MRI-1. The outcome was 5-year standardized change in MTL volumes. Mediators included voxel-based MRI measures of the spatial pattern of neurodegeneration of Alzheimer's disease (Alzheimer's disease pattern similarity scores [AD-PS]) and whole-brain white matter small-vessel ischemic disease (WM-SVID) volume as a proxy of global cerebrovascular damage. Structural equation models were constructed to examine whether the associations between exposures with MTL atrophy were mediated by the initial level or concurrent change in AD-PS score or WM-SVID while adjusting for sociodemographic, lifestyle, clinical characteristics, and intracranial volume. Living in locations with higher PM2.5 (per interquartile range [IQR]=3.17μg/m3) or NO2 (per IQR=6.63ppb) was associated with greater MTL atrophy (βPM2.5 = -0.29, 95% confidence interval [CI]=[-0.41,-0.18]; βNO2 =-0.12, 95%CI=[-0.23,-0.02]). Greater PM2.5 was associated with larger increases in AD-PS (βPM2.5 = 0.23, 95%CI=[0.12,0.33]) over time, which partially mediated associations with MTL atrophy (indirect effect= -0.10; 95%CI=[-0.15, -0.05]), explaining approximately 32% of the total effect. NO2 was positively associated with AD-PS at MRI-1 (βNO2=0.13, 95%CI=[0.03,0.24]), which partially mediated the association with MTL atrophy (indirect effect= -0.01, 95% CI=[-0.03,-0.001]). Global WM-SVID at MRI-1 or concurrent change were not significant mediators between exposures and MTL atrophy. Findings support the mediating role of Alzheimer's disease-related neurodegeneration contributing to MTL atrophy associated with late-life exposures to air pollutants. Alzheimer's disease-related neurodegeneration only partially explained associations between exposure and MTL atrophy suggesting the role of multiple neuropathological processes underlying air pollution neurotoxicity on brain aging.

Perirhinal cortex is associated with fine-grained discrimination of conceptually confusable objects in Alzheimer's disease

The perirhinal cortex (PrC) stands among the first brain areas to deteriorate in Alzheimer's disease (AD). This study tests to what extent the PrC is involved in representing and discriminating confusable objects based on the conjunction of their perceptual and conceptual features. To this aim, AD patients and control counterparts performed 3 tasks: a naming, a recognition memory, and a conceptual matching task, where we manipulated conceptual and perceptual confusability. A structural MRI of the antero-lateral parahippocampal subregions was obtained for each participant. We found that the sensitivity to conceptual confusability was associated with the left PrC volume in both AD patients and control participants for the recognition memory task, while it was specifically associated with the volume of the left PrC in AD patients for the conceptual matching task. This suggests that a decreased volume of the PrC is related to the ability to disambiguate conceptually confusable items. Therefore, testing recognition memory or conceptual matching of easily conceptually confusable items can provide a potential cognitive marker of PrC atrophy.

Brain volumetric changes in menopausal women and its association with cognitive function: a structured review

The menopausal transition has been proposed to put women at risk for undesirable neurological symptoms, including cognitive decline. Previous studies suggest that alterations in the hormonal milieu modulate brain structures associated with cognitive function. This structured review provides an overview of the relevant studies that have utilized MRI to report volumetric differences in the brain following menopause, and its correlations with the evaluated cognitive functions. We performed an electronic literature search using Medline (Ovid) and Scopus to identify studies that assessed the influence of menopause on brain structure with MRI. Fourteen studies met the inclusion criteria. Brain volumetric differences have been reported most frequently in the frontal and temporal cortices as well as the hippocampus. These regions are important for higher cognitive tasks and memory. Additionally, the deficit in verbal and visuospatial memory in postmenopausal women has been associated with smaller regional brain volumes. Nevertheless, the limited number of eligible studies and cross-sectional study designs warrant further research to draw more robust conclusions.

Differential effects of ageing on the neural processing of speech and singing production

Background

Understanding healthy brain ageing has become vital as populations are ageing rapidly and age-related brain diseases are becoming more common. In normal brain ageing, speech processing undergoes functional reorganisation involving reductions of hemispheric asymmetry and overactivation in the prefrontal regions. However, little is known about how these changes generalise to other vocal production, such as singing, and how they are affected by associated cognitive demands.

Methods

The present cross-sectional fMRI study systematically maps the neural correlates of vocal production across adulthood (N=100, age 21-88 years) using a balanced 2x3 design where tasks varied in modality (speech: proverbs / singing: song phrases) and cognitive demand (repetition / completion from memory / improvisation).

Results

In speech production, ageing was associated with decreased left pre- and postcentral activation across tasks and increased bilateral angular and right inferior temporal and fusiform activation in the improvisation task. In singing production, ageing was associated with increased activation in medial and bilateral prefrontal and parietal regions in the completion task, whereas other tasks showed no ageing effects. Direct comparisons between the modalities showed larger age-related activation changes in speech than singing across tasks, including a larger left-to-right shift in lateral prefrontal regions in the improvisation task.

Conclusion

The present results suggest that the brains' singing network undergoes differential functional reorganisation in normal ageing compared to the speech network, particularly during a task with high executive demand. These findings are relevant for understanding the effects of ageing on vocal production as well as how singing can support communication in healthy ageing and neurological rehabilitation.

The influence of age and sex on the absolute cell numbers of the human brain cerebral cortex

The human cerebral cortex is one of the most evolved regions of the brain, responsible for most higher-order neural functions. Since nerve cells (together with synapses) are the processing units underlying cortical physiology and morphology, we studied how the human neocortex is composed regarding the number of cells as a function of sex and age. We used the isotropic fractionator for cell quantification of immunocytochemically labeled nuclei from the cerebral cortex donated by 43 cognitively healthy subjects aged 25-87 years old. In addition to previously reported sexual dimorphism in the medial temporal lobe, we found more neurons in the occipital lobe of men, higher neuronal density in women's frontal lobe, but no sex differences in the number and density of cells in the other lobes and the whole neocortex. On average, the neocortex has ~10.2 billion neurons, 34% in the frontal lobe and the remaining 66% uniformly distributed among the other 3 lobes. Along typical aging, there is a loss of non-neuronal cells in the frontal lobe and the preservation of the number of neurons in the cortex. Our study made possible to determine the different degrees of modulation that sex and age evoke on cortical cellularity.

Combination of Paper and Electronic Trail Making Tests for Automatic Analysis of Cognitive Impairment: Development and Validation Study

BACKGROUND

Computer-aided detection, used in the screening and diagnosing of cognitive impairment, provides an objective, valid, and convenient assessment. Particularly, digital sensor technology is a promising detection method.

OBJECTIVE

This study aimed to develop and validate a novel Trail Making Test (TMT) using a combination of paper and electronic devices.

METHODS

This study included community-dwelling older adult individuals (n=297), who were classified into (1) cognitively healthy controls (HC; n=100 participants), (2) participants diagnosed with mild cognitive impairment (MCI; n=98 participants), and (3) participants with Alzheimer disease (AD; n=99 participants). An electromagnetic tablet was used to record each participant's hand-drawn stroke. A sheet of A4 paper was placed on top of the tablet to maintain the traditional interaction style for participants who were not familiar or comfortable with electronic devices (such as touchscreens). In this way, all participants were instructed to perform the TMT-square and circle. Furthermore, we developed an efficient and interpretable cognitive impairment-screening model to automatically analyze cognitive impairment levels that were dependent on demographic characteristics and time-, pressure-, jerk-, and template-related features. Among these features, novel template-based features were based on a vector quantization algorithm. First, the model identified a candidate trajectory as the standard answer (template) from the HC group. The distance between the recorded trajectories and reference was computed as an important evaluation index. To verify the effectiveness of our method, we compared the performance of a well-trained machine learning model using the extracted evaluation index with conventional demographic characteristics and time-related features. The well-trained model was validated using follow-up data (HC group: n=38; MCI group: n=32; and AD group: n=22).

RESULTS

We compared 5 candidate machine learning methods and selected random forest as the ideal model with the best performance (accuracy: 0.726 for HC vs MCI, 0.929 for HC vs AD, and 0.815 for AD vs MCI). Meanwhile, the well-trained classifier achieved better performance than the conventional assessment method, with high stability and accuracy of the follow-up data.

CONCLUSIONS

The study demonstrated that a model combining both paper and electronic TMTs increases the accuracy of evaluating participants' cognitive impairment compared to conventional paper-based feature assessment.

Reevaluating the role of the hippocampus in memory: A meta-analysis of neurotoxic lesion studies in nonhuman primates

The hippocampus and perirhinal cortex are both broadly implicated in memory; nevertheless, their relative contributions to visual item recognition and location memory remain disputed. Neuropsychological studies in nonhuman primates that examine memory function after selective damage to medial temporal lobe structures report various levels of memory impairment-ranging from minor deficits to profound amnesia. The discrepancies in published findings have complicated efforts to determine the exact magnitude of visual item recognition and location memory impairments following damage to the hippocampus and/or perirhinal cortex. To provide the most accurate estimate to date of the overall effect size, we use meta-analytic techniques on data aggregated from 26 publications that assessed visual item recognition and/or location memory in nonhuman primates with and without selective neurotoxic lesions of the hippocampus or perirhinal cortex. We estimated the overall effect size, evaluated the relation between lesion extent and effect size, and investigated factors that may account for between-study variation. Grouping studies by lesion target and testing method, separate meta-analyses were conducted. One meta-analysis indicated that impairments on tests of visual item recognition were larger after lesions of perirhinal cortex than after lesions of the hippocampus. A separate meta-analysis showed that performance on tests of location memory was severely impaired by lesions of the hippocampus. For the most part, meta-regressions indicated that greater impairment corresponds with greater lesion extent; paradoxically, however, more extensive hippocampal lesions predicted smaller impairments on tests of visual item recognition. We conclude the perirhinal cortex makes a larger contribution than the hippocampus to visual item recognition, and the hippocampus predominately contributes to spatial navigation.

Superficial white matter across development, young adulthood, and aging: volume, thickness, and relationship with cortical features

Superficial white matter (SWM) represents a significantly understudied part of the human brain, despite comprising a large portion of brain volume and making up a majority of cortico-cortical white matter connections. Using multiple, high-quality datasets with large sample sizes (N = 2421, age range 5-100) in combination with methodological advances in tractography, we quantified features of SWM volume and thickness across the brain and across development, young adulthood, and aging. We had four primary aims: (1) characterize SWM thickness across brain regions (2) describe associations between SWM volume and age (3) describe associations between SWM thickness and age, and (4) quantify relationships between SWM thickness and cortical features. Our main findings are that (1) SWM thickness varies across the brain, with patterns robust across individuals and across the population at the region-level and vertex-level; (2) SWM volume shows unique volumetric trajectories with age that are distinct from gray matter and other white matter trajectories; (3) SWM thickness shows nonlinear cross-sectional changes across the lifespan that vary across regions; and (4) SWM thickness is associated with features of cortical thickness and curvature. For the first time, we show that SWM volume follows a similar trend as overall white matter volume, peaking at a similar time in adolescence, leveling off throughout adulthood, and decreasing with age thereafter. Notably, the relative fraction of total brain volume of SWM continuously increases with age, and consequently takes up a larger proportion of total white matter volume, unlike the other tissue types that decrease with respect to total brain volume. This study represents the first characterization of SWM features across the large portion of the lifespan and provides the background for characterizing normal aging and insight into the mechanisms associated with SWM development and decline.

Age-dependent changes in brain iron deposition and volume in deep gray matter nuclei using quantitative susceptibility mapping

BACKGROUND

Microstructural changes in deep gray matter (DGM) nuclei are related to physiological behavior, cognition, and memory. Therefore, it is critical to study age-dependent trajectories of biomarkers in DGM nuclei for understanding brain development and aging, as well as predicting cognitive or neurodegenerative diseases.

OBJECTIVES

We aimed to (1) characterize age-dependent trajectories of mean susceptibility, adjusted volume, and total iron content simultaneously in DGM nuclei using quantitative susceptibility mapping (QSM); (2) examine potential contributions of sex related effects to the different age-dependence trajectories of volume and iron deposition; and (3) evaluate the ability of brain age prediction by combining mean magnetic susceptibility and volume of DGM nuclei.

METHODS

Magnetic susceptibilities and volumetric values of DGM nuclei were obtained from 220 healthy participants (aged 10-70 years) scanned on a 3T MRI system. Regions of interest (ROIs) were drawn manually on the QSM images. Univariate regression analysis between age and each of the MRI measurements in a single ROI was performed. Pearson correlation coefficients were calculated between magnetic susceptibility and adjusted volume in a single ROI. The statistical significance of sex differences in age-dependent trajectories of magnetic susceptibilities and adjusted volumes were determined using one-way ANCOVA. Multiple regression analysis was used to evaluate the ability to estimate brain age using a combination of the mean susceptibilities and adjusted volumes in multiple DGM nuclei.

RESULTS

Mean susceptibility and total iron content increased linearly, quadratically, or exponentially with age in all six DGM nuclei. Negative linear correlation was observed between adjusted volume and age in the head of the caudate nucleus (CN; R² = 0.196, p < 0.001). Quadratic relationships were found between adjusted volume and age in the putamen (PUT; R² = 0.335, p < 0.001), globus pallidus (GP; R² = 0.062, p = 0.001), and dentate nucleus (DN; R² = 0.077, p < 0.001). Males had higher mean magnetic susceptibility than females in the PUT (p = 0.001), red nucleus (RN; p = 0.002), and substantia nigra (SN; p < 0.001). Adjusted volumes of the CN (p < 0.001), PUT (p = 0.030), GP (p = 0.007), SN (p = 0.021), and DN (p < 0.001) were higher in females than those in males throughout the entire age range (10-70 years old). The total iron content of females was higher than that of males in the CN (p < 0.001), but lower than that of males in the PUT (p = 0.014) and RN (p = 0.043) throughout the entire age range (10-70 years old). Multiple regression analyses revealed that the combination of the mean susceptibility value of the PUT, and the volumes of the CN and PUT had the strongest associations with brain age (R² = 0.586).

CONCLUSIONS

QSM can be used to simultaneously investigate age- and sex- dependent changes in magnetic susceptibility and volume of DGM nuclei, thus enabling a comprehensive understanding of the developmental trajectories of iron accumulation and volume in DGM nuclei during brain development and aging.

Plasma proteins related to inflammatory diet predict future cognitive impairment

Dysregulation of the immune system and dietary patterns that increase inflammation can increase the risk for cognitive decline, but the mechanisms by which inflammatory nutritional habits may affect the development of cognitive impairment in aging are not well understood. To determine whether plasma proteins linked to inflammatory diet predict future cognitive impairment, we applied high-throughput proteomic assays to plasma samples from a subset (n = 1528) of Women's Health Initiative Memory Study (WHIMS) participants (mean [SD] baseline age, 71.3 [SD 3.8] years). Results provide insights into how inflammatory nutritional patterns are associated with an immune-related proteome and identify a group of proteins (CXCL10, CCL3, HGF, OPG, CDCP1, NFATC3, ITGA11) related to future cognitive impairment over a 14-year follow-up period. Several of these inflammatory diet proteins were also associated with dementia risk across two external cohorts (ARIC, ESTHER), correlated with plasma biomarkers of Alzheimer's disease (AD) pathology (Aβ42/40) and/or neurodegeneration (NfL), and related to an MRI-defined index of neurodegenerative brain atrophy in a separate cohort (BLSA). In addition to evaluating their biological relevance, assessing their potential role in AD, and characterizing their immune-tissue/cell-specific expression, we leveraged published RNA-seq results to examine how the in vitro regulation of genes encoding these candidate proteins might be altered in response to an immune challenge. Our findings indicate how dietary patterns with higher inflammatory potential relate to plasma levels of immunologically relevant proteins and highlight the molecular mediators which predict subsequent risk for age-related cognitive impairment.

Neuroimaging and verbal memory assessment in healthy aging adults using a portable low-field MRI scanner and a web-based platform: results from a proof-of-concept population-based cross-section study

Consumer wearables and health monitors, internet-based health and cognitive assessments, and at-home biosample (e.g., saliva and capillary blood) collection kits are increasingly used by public health researchers for large population-based studies without requiring intensive in-person visits. Alongside reduced participant time burden, remote and virtual data collection allows the participation of individuals who live long distances from hospital or university research centers, or who lack access to transportation. Unfortunately, studies that include magnetic resonance neuroimaging are challenging to perform remotely given the infrastructure requirements of MRI scanners, and, as a result, they often omit socially, economically, and educationally disadvantaged individuals. Lower field strength systems (< 100 mT) offer the potential to perform neuroimaging at a participant's home, enabling more accessible and equitable research. Here we report the first use of a low-field MRI "scan van" with an online assessment of paired-associate learning (PAL) to examine associations between brain morphometry and verbal memory performance. In a sample of 67 individuals, 18-93 years of age, imaged at or near their home, we show expected white and gray matter volume trends with age and find significant (p < 0.05 FWE) associations between PAL performance and hippocampus, amygdala, caudate, and thalamic volumes. High-quality data were acquired in 93% of individuals, and at-home scanning was preferred by all individuals with prior MRI at a hospital or research setting. Results demonstrate the feasibility of remote neuroimaging and cognitive data collection, with important implications for engaging traditionally under-represented communities in neuroimaging research.

The Mediating Role of Biomarkers in the Association Between Subjective Aging and Episodic Memory

OBJECTIVES

Subjective aging, indexed by subjective age and self-perceptions of aging (SPA), is consistently related to cognition in adulthood. The present study examined whether blood biomarkers mediate the longitudinal associations between subjective aging indices and memory.

METHODS

Data of 5,369 individuals aged 50-94 years (mean = 66.89 years, SD = 9.22; 60% women) were drawn from the Health and Retirement Study (HRS). Subjective age, SPA, and demographic factors were assessed in 2012/2014. Interleukin-6, C-reactive protein, albumin, cystatin C, N-terminal pro B-type natriuretic peptide (NT-proBNP), fasting glucose, Vitamin D, hemoglobin, red cells distribution width, and epigenetic aging were assessed as part of the HRS Venuous Blood Study in 2016. Memory was measured in 2018. The mediators (except for epigenetic aging, which was assessed in a subsample) were tested simultaneously in models that accounted for demographic covariates.

RESULTS

An older subjective age was related to worse memory partially through higher fasting glucose, higher cystatin C, higher NT-proBNP, and accelerated epigenetic aging. Negative SPA was related to worse memory through lower Vitamin D3, higher fasting glucose, higher cystatin C, higher NT-proBNP, and accelerated epigenetic aging. The biomarkers explained between 2% and 10% of subjective age and between 1% and 8% of SPA associations with memory. Additional analysis revealed that biomarkers continued to be significant mediators when physical inactivity and depressive symptoms were included as additional mediators.

CONCLUSION

The present study adds to existing research on the association between subjective aging and memory by providing new evidence on the biological mediators of this association.

Evolutionary and genomic perspectives of brain aging and neurodegenerative diseases

This chapter utilizes genomic concepts and evolutionary perspectives to further understand the possible links between typical brain aging and neurodegenerative diseases, focusing on the two most prevalent of these: Alzheimer's disease and Parkinson's disease. Aging is the major risk factor for these neurodegenerative diseases. Researching the evolutionary and molecular underpinnings of aging helps to reveal elements of the typical aging process that leave individuals more vulnerable to neurodegenerative pathologies. Very little is known about the prevalence and susceptibility of neurodegenerative diseases in nonhuman species, as only a few individuals have been observed with these neuropathologies. However, several studies have investigated the evolution of lifespan, which is closely connected with brain size in mammals, and insights can be drawn from these to enrich our understanding of neurodegeneration. This chapter explores the relationship between the typical aging process and the events in neurodegeneration. First, we examined how age-related processes can increase susceptibility to neurodegenerative diseases. Second, we assessed to what extent neurodegeneration is an accelerated form of aging. We found that while at the phenotypic level both neurodegenerative diseases and the typical aging process share some characteristics, at the molecular level they show some distinctions in their profiles, such as variation in genes and gene expression. Furthermore, neurodegeneration of the brain is associated with an earlier onset of cellular, molecular, and structural age-related changes. In conclusion, a more integrative view of the aging process, both from a molecular and an evolutionary perspective, may increase our understanding of neurodegenerative diseases.

Additive cortical gray matter deficits in people living with HIV who use cocaine

Cocaine use, which is disproportionately common in people living with HIV (PWH), is known to have neurotoxic effects that may exacerbate HIV neuropathogenesis. While both cocaine use and HIV disease are independently associated with deficits in gray matter (GM) volume, the additive effect of cocaine use to HIV disease on GM volume has not been explored. Here, we investigated subcortical and cortical brain volume differences between four groups of individuals with and without HIV disease and/or cocaine use. Participants also completed a comprehensive neuropsychological testing battery, and HIV disease characteristics were recorded. Within subcortical regions, cocaine use was independently associated with higher volume in the dorsal striatum and pallidum, while HIV disease was associated with lower volume in the nucleus accumbens and thalamus. For cortical regions, there was an additive effect of cocaine use on HIV disease in parietal and occipital lobe volume with PWH who used cocaine displaying the lowest GM volume. Within regions that differed between groups, higher neurocognitive function was positively associated with thalamic, nucleus accumbens, dorsal striatum, and occipital lobe volume. For regions that showed a significant main effect of HIV disease, lower nadir CD4 + T cell count was associated with lower nucleus accumbens and occipital lobe volume. Lower current CD4 + T cell count was associated with lower occipital lobe volume. These results suggest that PWH who use cocaine are at greater risk for cortical atrophy than cocaine use or HIV disease alone.

Short superficial white matter and aging: a longitudinal multi-site study of 1293 subjects and 2711 sessions

It is estimated that short association fibers running immediately beneath the cortex may make up as much as 60% of the total white matter volume. However, these have been understudied relative to the long-range association, projection, and commissural fibers of the brain. This is largely because of limitations of diffusion MRI fiber tractography, which is the primary methodology used to non-invasively study the white matter connections. Inspired by recent anatomical considerations and methodological improvements in superficial white matter (SWM) tractography, we aim to characterize changes in these fiber systems in cognitively normal aging, which provide insight into the biological foundation of age-related cognitive changes, and a better understanding of how age-related pathology differs from healthy aging. To do this, we used three large, longitudinal and cross-sectional datasets (N = 1293 subjects, 2711 sessions) to quantify microstructural features and length/volume features of several SWM systems. We find that axial, radial, and mean diffusivities show positive associations with age, while fractional anisotropy has negative associations with age in SWM throughout the entire brain. These associations were most pronounced in the frontal, temporal, and temporoparietal regions. Moreover, measures of SWM volume and length decrease with age in a heterogenous manner across the brain, with different rates of change in inter-gyri and intra-gyri SWM, and at slower rates than well-studied long-range white matter pathways. These features, and their variations with age, provide the background for characterizing normal aging, and, in combination with larger association pathways and gray matter microstructural features, may provide insight into fundamental mechanisms associated with aging and cognition.

Neighborhood Beauty and the Brain in Older Japanese Adults

People have a preference for, and feel better in, beautiful natural environments. However, there are no epidemiological studies on the association between neighborhood beauty and neuroimaging measures. We aimed to determine association between neighborhood beauty and regional brain volume. Participants were 476 community-dwelling older adults from the Neuron to Environmental Impact across Generations (NEIGE) study. Subjective neighborhood beauty was assessed through participants’ perception of beautiful scenery within 1 km of their home. Objective measures of neighborhood indicators (green spaces, blue spaces, and plant diversity) within 1 km of participants’ homes were obtained using a geographic information system. Volumes of brain regions associated with experience of beauty were measured using magnetic resonance imaging. We estimated associations between neighborhood beauty and regional brain volume using linear regression. Of the participants, 42% rated their neighborhoods as very beautiful, and 17% rated them as not at all beautiful. Higher subjective neighborhood beauty was associated with larger bilateral medial orbitofrontal cortex and insula volumes (all p for trend < 0.01). Brain volume was not associated with objective neighborhood measures. Subjective neighborhood beauty was associated with brain regions related to rewards and decision making, suggesting that these brain regions underpin the perception of neighborhood beauty.

Association between Long-Term Air Pollution, Chronic Traffic Noise, and Resting-State Functional Connectivity in the 1000BRAINS Study

BACKGROUND

Older adults show a high variability in cognitive performance that cannot be explained by aging alone. Although research has linked air pollution and noise to cognitive impairment and structural brain alterations, the potential impact of air pollution and noise on functional brain organization is unknown.

OBJECTIVE

This study examined the associations between long-term air pollution and traffic noise with measures of functional brain organization in older adults. We hypothesize that exposures to high air pollution and noise levels are associated with age-like changes in functional brain organization, shown by less segregated brain networks.

METHODS

Data from 574 participants (44.1% female, 56-85 years of age) in the German 1000BRAINS study (2011-2015) were analyzed. Exposure to particulate matter (PM10, PM2.5, and PM2.5 absorbance), accumulation mode particle number (PNAM), and nitrogen dioxide (NO2) was estimated applying land-use regression and chemistry transport models. Noise exposures were assessed as weighted 24-h (Lden) and nighttime (Lnight) means. Functional brain organization of seven established brain networks (visual, sensorimotor, dorsal and ventral attention, limbic, frontoparietal and default network) was assessed using resting-state functional brain imaging data. To assess functional brain organization, we determined the degree of segregation between networks by comparing the strength of functional connections within and between networks. We estimated associations between air pollution and noise exposure with network segregation, applying multiple linear regression models adjusted for age, sex, socioeconomic status, and lifestyle variables.

RESULTS

Overall, small associations of high exposures with lesser segregated networks were visible. For the sensorimotor networks, we observed small associations between high air pollution and noise and lower network segregation, which had a similar effect size as a 1-y increase in age [e.g., in sensorimotor network, -0.006 (95% CI: -0.021, 0.009) per 0.3 ×10-5/m increase in PM2.5 absorbance and -0.004 (95% CI: -0.006, -0.002) per 1-y age increase].

CONCLUSION

High exposure to air pollution and noise was associated with less segregated functional brain networks. https://doi.org/10.1289/EHP9737.

The emerging neuroprotective roles of exerkines in Alzheimer’s disease

Despite the extensive knowledge of the beneficial effects of physical exercise, a sedentary lifestyle is still a predominant harm in our society. Sedentarism is one of the major modifiable risk factors for metabolic diseases such as diabetes mellitus, obesity and neurological disorders, including Alzheimer’s disease (AD)–characterized by synaptic failure, amyloid protein deposition and memory loss. Physical exercise promotes neuroprotective effects through molecules released in circulation and mediates the physiological crosstalk between the periphery and the brain. This literature review summarizes the current understanding of the roles of exerkines, molecules released during physical exercise, as systemic and central factors that mediate the beneficial effects of physical exercise on cognition. We highlight the neuroprotective role of irisin—a myokine released from the proteolytic cleavage of fibronectin type III domain-containing protein 5 (FNDC5) transmembrane protein. Lastly, we review evidence pointing to physical exercise as a potential preventative and interventional strategy against cognitive decline in AD.

The impact of age-related hearing loss on structural neuroanatomy: A meta-analysis

This meta-analysis investigated the association between age-related hearing loss and structural neuroanatomy, specifically changes to gray matter volume. Hearing loss is associated with increased risk of cognitive decline. Hence, understanding the effects of hearing loss in older age on brain health is essential. We reviewed studies which compared older participants with hearing loss (age-related hearing loss: ARHL) to older adults without clinical hearing loss (no-ARHL), on neuroanatomical outcomes, specifically gray matter (GM) volume as measured by magnetic resonance imaging. A total of five studies met the inclusion criteria, three of which were included in an analysis of whole-brain gray matter volume (ARHL group n = 113; no-ARHL group n = 138), and three were included in analyses of lobe-wise gray matter volume (ARHL group n = 139; no-ARHL group n = 162). Effect-size seed-based d mapping software was employed for whole-brain and lobe-wise analysis of gray matter volume. The analysis indicated there was no significant difference between adults with ARHL compared to those with no-ARHL in whole-brain gray matter volume. Due to lacking stereotactic coordinates, the level of gray matter in specific neuroanatomical locations could only be observed at lobe-level. These data indicate that adults with ARHL show increased gray matter atrophy in the temporal lobe only (not in occipital, parietal, or frontal), compared to adults with no-ARHL. The implications for theoretical frameworks of the hearing loss and cognitive decline relationship are discussed in relation to the results. This meta-analysis was pre-registered on PROSPERO (CRD42021265375).

Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=265375, PROSPERO CRD42021265375.

Lower White Matter Volume and Worse Executive Functioning Reflected in Higher Levels of Plasma GFAP among Older Adults with and Without Cognitive Impairment

OBJECTIVE

There are minimal data directly comparing plasma neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) in aging and neurodegenerative disease research. We evaluated associations of plasma NfL and plasma GFAP with brain volume and cognition in two independent cohorts of older adults diagnosed as clinically normal (CN), mild cognitive impairment (MCI), or Alzheimer's dementia.

METHODS

We studied 121 total participants (Cohort 1: n = 50, age 71.6 ± 6.9 years, 78% CN, 22% MCI; Cohort 2: n = 71, age 72.2 ± 9.2 years, 45% CN, 25% MCI, 30% dementia). Gray and white matter volumes were obtained for total brain and broad subregions of interest (ROIs). Neuropsychological testing evaluated memory, executive functioning, language, and visuospatial abilities. Plasma samples were analyzed in duplicate for NfL and GFAP using single molecule array assays (Quanterix Simoa). Linear regression models with structural MRI and cognitive outcomes included plasma NfL and GFAP simultaneously along with relevant covariates.

RESULTS

Higher plasma GFAP was associated with lower white matter volume in both cohorts for temporal (Cohort 1: β = -0.33, p = .002; Cohort 2: β = -0.36, p = .03) and parietal ROIs (Cohort 1: β = -0.31, p = .01; Cohort 2: β = -0.35, p = .04). No consistent findings emerged for gray matter volumes. Higher plasma GFAP was associated with lower executive function scores (Cohort 1: β = -0.38, p = .01; Cohort 2: β = -0.36, p = .007). Plasma NfL was not associated with gray or white matter volumes, or cognition after adjusting for plasma GFAP.

CONCLUSIONS

Plasma GFAP may be more sensitive to white matter and cognitive changes than plasma NfL. Biomarkers reflecting astroglial pathophysiology may capture complex dynamics of aging and neurodegenerative disease.

On The 3D VR Simulated Rubik’s Cube Game for Smart Pads

In this study, interface designs of a VR 3D-simulated Rubik’s Cube game were developed and evaluated. A 2 × 2 × 2 mixed-design ANOVA was executed, with age (younger adult/older adult), interface (arrow/intuitive), and task complexity (easy, a single symmetrical task/difficult, a bio-symmetrical task) experimental design. The first three factors were between-subject designs while the latter was a within-subject design. The dependent variable was the percentage of the task performance and wayfinding questionnaire. The collected experimental data were analyzed by regression method to clarify the correlation among age, interface, task complexity, and wayfinding strategy. There were 96 subjects in the experiment, including 48 younger adults (aged from 18~22) and 48 older adults (aged from 60~85). The experimental results and statistical analysis showed that the task difficulty had a significant effect on task performance in the 3D VR Rubik’s Cube game. For the smart pad, the arrow interface was significantly more effective than the intuitive interface. The theoretical model regression analysis of the task complexity, interface, and wayfinding strategy was shown to be significant. Results showed that users may be affected either positively or negatively by the wayfinding strategy, as a higher score on familiarity indicates better VR game task performance, whereas for the usual spatial behavior wayfinding strategy, the opposite result was found for memory. These results can be used to assess VR game interface designs, taking into consideration age difference, task complexity, experiential self-report on 3D VR games, and including VR rotation navigational

Analysis of Clinical Traits Associated With Cardiovascular Health, Genomic Profiles, and Neuroimaging Markers of Brain Health in Adults Without Stroke or Dementia

IMPORTANCE

The American Heart Association (AHA) Life's Simple 7 (LS7) score captures 7 biological and lifestyle factors associated with promoting cardiovascular health.

OBJECTIVES

To test whether healthier LS7 profiles are associated with significant brain health benefits in persons without stroke or dementia, and to evaluate whether genomic information can recapitulate the observed LS7.

DESIGN, SETTING, AND PARTICIPANTS

This genetic association study was a nested neuroimaging study within the UK Biobank, a large population-based cohort study in the United Kingdom. Between March 2006 and October 2010, the UK Biobank enrolled 502 480 community-dwelling persons aged 40 to 69 years at recruitment. This study focused on a subset of 35 914 participants without stroke or dementia who completed research brain magnetic resonance imaging (MRI) and had available genome-wide data. All analyses were conducted between March 2021 and March 2022.

EXPOSURES

The LS7 (blood pressure, low-density lipoprotein cholesterol, hemoglobin A1c, smoking, exercise, diet, and body mass index) profiles were ascertained clinically and genomically. Independent genetic variants known to influence each of the traits included in the LS7 were assessed. The total LS7 score ranges from 0 (worst) to 14 (best) and was categorized as poor (≤4), average (>4 to 9) and optimal (>9).

MAIN OUTCOMES AND MEASURES

The outcomes of interest were 2 neuroimaging markers of brain health: white matter hyperintensity (WMH) volume and brain volume (BV).

RESULTS

The final analytical sample included 35 914 participants (mean [SD] age 64.1 [7.6] years; 18 830 [52.4%] women). For WMH, compared with persons with poor observed LS7 profiles, those with average profiles had 16% (β = -0.18; SE, 0.03; P < .001) lower mean volume and those with optimal profiles had 39% (β = -0.39; SE, 0.03; P < .001) lower mean volume. Similar results were obtained using the genomic LS7 for WMH (average LS7 profile: β = -0.06; SE, 0.014; P < .001; optimal LS7 profile: β = -0.08; SE, 0.018; P < .001). For BV, compared with persons with poor observed LS7 profiles, those with average LS7 profiles had 0.55% (β = 0.09; SE, 0.02; P < .001) higher volume, and those with optimal LS7 profiles had 1.9% (β = 0.14; SE, 0.02; P < .001) higher volume. The genomic LS7 profiles were not associated with BV.

CONCLUSIONS AND RELEVANCE

These findings suggest that healthier LS7 profiles were associated with better profiles of 2 neuroimaging markers of brain health in persons without stroke or dementia, indicating that cardiovascular health optimization was associated with improved brain health in asymptomatic persons. Genomic information appropriately recapitulated 1 of these associations, confirming the feasibility of modeling the LS7 genomically and pointing to an important role of genetic predisposition in the observed association among cardiometabolic and lifestyle factors and brain health.

Comparison and aggregation of event sequences across ten cohorts to describe the consensus biomarker evolution in Alzheimer's disease

BACKGROUND

Previous models of Alzheimer's disease (AD) progression were primarily hypothetical or based on data originating from single cohort studies. However, cohort datasets are subject to specific inclusion and exclusion criteria that influence the signals observed in their collected data. Furthermore, each study measures only a subset of AD-relevant variables. To gain a comprehensive understanding of AD progression, the heterogeneity and robustness of estimated progression patterns must be understood, and complementary information contained in cohort datasets be leveraged.

METHODS

We compared ten event-based models that we fit to ten independent AD cohort datasets. Additionally, we designed and applied a novel rank aggregation algorithm that combines partially overlapping, individual event sequences into a meta-sequence containing the complementary information from each cohort.

RESULTS

We observed overall consistency across the ten event-based model sequences (average pairwise Kendall's tau correlation coefficient of 0.69 ± 0.28), despite variance in the positioning of mainly imaging variables. The changes described in the aggregated meta-sequence are broadly consistent with the current understanding of AD progression, starting with cerebrospinal fluid amyloid beta, followed by tauopathy, memory impairment, FDG-PET, and ultimately brain deterioration and impairment of visual memory.

CONCLUSION

Overall, the event-based models demonstrated similar and robust disease cascades across independent AD cohorts. Aggregation of data-driven results can combine complementary strengths and information of patient-level datasets. Accordingly, the derived meta-sequence draws a more complete picture of AD pathology compared to models relying on single cohorts.

Episodic Memory and Executive Function Are Differentially Affected by Retests but Similarly Affected by Age in a Longitudinal Study of Normally-Aging Older Adults

Episodic memory and executive function are two cognitive domains that have been studied extensively in older adults and have been shown to decline in normally-aging older individuals. However, one of the problems with characterizing cognitive changes in longitudinal studies has been separating effects attributable to normal aging from effects created by repeated testing or practice. In the present study, 166 people aged 65 and older were enrolled over several years and tested at least 3 times at variable intervals (M = 3.2 yrs). The cognitive measures were composite scores. Each composite was made up of five neuropsychological tests, previously identified through factor analysis. For one pair of composite scores, variance attributable to age was removed from each subtest through regression analyses before z-scores were computed, creating two age-corrected composites. A second pair of composites were not age-corrected. Using linear mixed-effects models, we first explored retest effects for each cognitive domain, independent of age, using the age-corrected composites. We then modeled aging effects using the age-uncorrected composites after subtracting out retest effects. Results indicated significant retest effects for memory but not for executive function, such that memory performance improved across the three testing sessions. When these practice effects were removed from the age-uncorrected data, effects of aging were evident for both executive and memory function with significant declines over time. We also explored several individual difference variables including sex, IQ, and age at the initial testing session and across time. Although sex and IQ affected performance on both cognitive factors at the initial test, neither was related to practice effects, although young-older adults tended to benefit from practice to a greater extent than old-older adults. In addition, people with higher IQs showed slower age-related declines in memory, but no advantages in executive function. These findings suggest that (a) aging affects both memory and executive function similarly, (b) higher IQ, possibly reflecting cognitive reserve, may slow age-related declines in memory, and (c) practice through repeated testing enhances performance in memory particularly in younger-older adults, and may therefore mask aging effects if not taken into account.

Accelerated decline in white matter microstructure in subsequently impaired older adults and its relationship with cognitive decline

Little is known about a longitudinal decline in white matter microstructure and its associations with cognition in preclinical dementia. Longitudinal diffusion tensor imaging and neuropsychological testing were performed in 50 older adults who subsequently developed mild cognitive impairment or dementia (subsequently impaired) and 200 cognitively normal controls. Rates of white matter microstructural decline were compared between groups using voxel-wise linear mixed-effects models. Associations between change in white matter microstructure and cognition were examined. Subsequently impaired individuals had a faster decline in fractional anisotropy in the right inferior fronto-occipital fasciculus and bilateral splenium of the corpus callosum. A decline in right inferior fronto-occipital fasciculus fractional anisotropy was related to a decline in verbal memory, visuospatial ability, processing speed and mini-mental state examination. A decline in bilateral splenium fractional anisotropy was related to a decline in verbal fluency, processing speed and mini-mental state examination. Accelerated regional white matter microstructural decline is evident during the preclinical phase of mild cognitive impairment/dementia and is related to domain-specific cognitive decline.

Fornix volumetric increase and microglia morphology contribute to spatial and recognition-like memory decline in ageing male mice

Ageing displays a low-grade pro-inflammatory profile in blood and the brain. Accumulation of pro-inflammatory cytokines, microglia activation and volumetric changes in the brain correlate with cognitive decline in ageing models. However, the interplay between them is not totally understood. Here, we aimed to globally identify an age-dependent pro-inflammatory profile and microglia morphological plasticity that favors major volume changes in the brain associated with cognitive decline. Cluster analysis of behavioral data obtained from 2-,12- and 20-month-old male C57BL/6 mice revealed age-dependent cognitive decline after the Y-maze, Barnes maze, object recognition (NORT) and object location tests (OLT). Global magnetic resonance imageing (MRI) analysis by deformation-based morphometry (DBM) in the brain identified a volume increase in the fornix and a decrease in the left medial entorhinal cortex (MEntC) during ageing. Notably, the fornix shows an increase in the accumulation of pro-inflammatory cytokines, whereas the left MEntC displays a decrease. Morphological assessment of microglia also confirms an active and dystrophic phenotype in the fornix and a surveillance phenotype in the left MEntC. Finally, biological modeling revealed that age-related volume increase in the fornix was associated with dystrophic microglia and cognitive impairment, as evidenced by failure on tasks examining memory of object location and novelty. Our results propose that the morphological plasticity of microglia might contribute to volumetric changes in brain regions associated with cognitive decline during physiological ageing.

Cognitive Training Modulates Brain Hypersynchrony in a Population at Risk for Alzheimer's Disease

BACKGROUND

Recent studies demonstrated that brain hypersynchrony is an early sign of dysfunction in Alzheimer's disease (AD) that can represent a proxy for clinical progression. Conversely, non-pharmacological interventions, such as cognitive training (COGTR), are associated with cognitive gains that may be underpinned by a neuroprotective effect on brain synchrony.

OBJECTIVE

To study the potential of COGTR to modulate brain synchrony and to eventually revert the hypersynchrony phenomenon that characterizes preclinical AD.

METHODS

The effect of COGTR was examined in a sample of healthy controls (HC, n = 41, 22 trained) and individuals with subjective cognitive decline (SCD, n = 49, 24 trained). Magnetoencephalographic (MEG) activity and neuropsychological scores were acquired before and after a ten-week COGTR intervention aimed at improving cognitive function and daily living performance. Functional connectivity (FC) was analyzed using the phase-locking value. A mixed-effects ANOVA model with factors time (pre-intervention/post-intervention), training (trained/non-trained), and diagnosis (HC/SCD) was used to investigate significant changes in FC.

RESULTS

We found an average increase in alpha-band FC over time, but the effect was different in each group (trained and non-trained). In the trained group (HC and SCD), we report a reduction in the increase in FC within temporo-parietal and temporo-occipital connections. In the trained SCD group, this reduction was stronger and showed a tentative correlation with improved performance in different cognitive tests.

CONCLUSION

COGTR interventions could mitigate aberrant increases in FC in preclinical AD, promoting brain synchrony normalization in groups at a higher risk of developing dementia.

Regional age-related atrophy after screening for preclinical alzheimer disease

Brain atrophy occurs in aging even in the absence of dementia, but it is unclear to what extent this is due to undetected preclinical Alzheimer disease. Here we examine a cross-sectional cohort (ages 18-88) free from confounding influence of preclinical Alzheimer disease, as determined by amyloid PET scans and three years of clinical evaluation post-imaging. We determine the regional strength of age-related atrophy using linear modeling of brain volumes and cortical thicknesses with age. Age-related atrophy was seen in nearly all regions, with greatest effects in the temporal lobe and subcortical regions. When modeling age with the estimated derivative of smoothed aging curves, we found that the temporal lobe declined linearly with age, subcortical regions declined faster at later ages, and frontal regions declined slower at later ages than during midlife. This age-derivative pattern was distinct from the linear measure of age-related atrophy and significantly associated with a measure of myelin. Atrophy did not detectably differ from a preclinical Alzheimer disease cohort when age ranges were matched.

The association between blood lymphocyte NMDAR, group I mGluRs and cognitive function changes in occupationally aluminum-exposed workers and verification in rats

BACKGROUND

Many studies have shown that occupational aluminum (Al) exposure could affect the cognitive functions of workers and cause mild cognitive impairment (MCI). Glutamate receptors (GluRs) play an important role in learning and memory functions.

METHODS

352 workers in a large Al production enterprise were investigated in this research. MMSE, CDT, DST, VFT, FOM were used to evaluate the cognitive functions of workers. Plasma Al levels as exposure indices were measured by Graphite Furnace Atomic Absorption Method (GFAAS). The expression of GluRs was measured by ELISA. Cognitive function comprehensive scores were obtained through factor analysis. Then a rat model of chronic AlCl₃ exposure was established. The detection method of Al levels and protein expression were the same as mentioned-above.

RESULTS

Compared with the Q1 group, the DST, VFT, and comprehensive cognitive function scores of the Q4 group were lower(P < 0.05). For every 1μg/L increase in plasma Al concentration, the risk of cognitive impairment increases 1.051 times (95 %CI:1.031,1.072). Both NMDAR1 and NMDAR2A protein expression level of Q1 group were higher than those of Q2, Q3, Q4 group (all P < 0.05). The mediating effect ratio of NMDAR1 between plasma Al levels and cognitive function comprehensive scores was a1*b1/c=11.30 %, and the mediating effect ratio of NMDAR2A was |a2*b2/c|=21.77 %. Compared with control group, the escape latency of rats in the high Al dose group was longer day by day (P < 0.05). With the increase of Al dose, the relative expression of NMDAR1, NMDAR2A, NMDAR2B, GluR1 and mGluR5 in cerebral cortex and lymphocytes of rats were decreased (P < 0.05). The result of correlation analysis on NMDAR1 protein expression between brain cortex and lymphocyte showed that the correlation coefficient is r = 0.646(P < 0.05).

CONCLUSION

Taking together the results from both Al exposed workers and animal, there is a certain correlation between NMDAR1 protein contents of brain cortex and peripheral lymphocytes. We propose that lymphocyte NMDAR1 could be considered as a peripheral potential marker of cognitive impairment for further observation.

Bayesian inference and dynamic prediction of multivariate joint model with functional data: An application to Alzheimer's disease

Alzheimer's disease (AD) is a severe neurodegenerative disorder impairing multiple domains, for example, cognition and behavior. Assessing the risk of AD progression and initiating timely interventions at early stages are critical to improve the quality of life for AD patients. Due to the heterogeneous nature and complex mechanisms of AD, one single longitudinal outcome is insufficient to assess AD severity and disease progression. Therefore, AD studies collect multiple longitudinal outcomes, including cognitive and behavioral measurements, as well as structural brain images such as magnetic resonance imaging (MRI). How to utilize the multivariate longitudinal outcomes and MRI data to make efficient statistical inference and prediction is an open question. In this article, we propose a multivariate joint model with functional data (MJM-FD) framework that relates multiple correlated longitudinal outcomes to a survival outcome, and use the scalar-on-function regression method to include voxel-based whole-brain MRI data as functional predictors in both longitudinal and survival models. We adopt a Bayesian paradigm to make statistical inference and develop a dynamic prediction framework to predict an individual's future longitudinal outcomes and risk of a survival event. We validate the MJM-FD framework through extensive simulation studies and apply it to the motivating Alzheimer's Disease Neuroimaging Initiative (ADNI) study.

The prognostic utility of CSF neurogranin in predicting future cognitive decline in the Alzheimer's disease continuum: A systematic review and meta-analysis with narrative synthesis

Core cerebrospinal fluid (CSF) biomarkers (Aβ42, T-tau, P-tau) were included as supporting diagnostic criteria for Alzheimer's Disease (AD), but they lack the power to predict AD progression. On the other hand, a new biomarker CSF Neurogranin (Ng) has been shown to predict cognitive decline. This systematic review aims to synthesise the prognostic utility of CSF Ng in predicting cognitive decline in the AD continuum. Seven databases were searched systematically from inception to 30 September 2020. Participants were 55 years or older, who had baseline and at least one follow-up cognitive assessments. Risk of bias was assessed using the Quality in Prognosis Studies tool. Meta-analysis was conducted by pooling standardised beta coefficients and adjusted hazard ratios. Thirteen studies were included and high-quality evidence suggests that CSF Ng predicts Mini-Mental State Examination (MMSE) decline in Aβ⁺ mild cognitive impairment (MCI). Moderate quality evidence showed that CSF Ng could predict the decline of memory and executive function in MCI. Narrative synthesis found that CSF Ng/Aβ42 was also likely to predict cognitive decline. More studies are required to validate the use of CSF Ng as an AD prognostic marker and its application in future development of drug treatment and diagnosis.

Brain-predicted age difference is associated with cognitive processing in later-life

Brain age is a neuroimaging-based biomarker of aging. This study examined whether the difference between brain age and chronological age (brain-PAD) is associated with cognitive function at baseline and longitudinally. Participants were relatively healthy, predominantly white community-dwelling older adults (n = 531, aged ≥70 years), with high educational attainment (61% ≥12 years) and socioeconomic status (59% ≥75th percentile). Brain age was estimated from T1-weighted magnetic resonance images using an algorithm by Cole et al., 2018. After controlling for age, gender, education, depression and body mass index, brain-PAD was negatively associated with psychomotor speed (Symbol Digit Modalities Test) at baseline (Bonferroni p < 0.006), but was not associated with baseline verbal fluency (Controlled Oral Word Association Test), delayed recall (Hopkins Learning Test Revised), or general cognitive status (Mini-Mental State Examination). Baseline brain-PAD was not associated with 3-year change in cognition (Bonferroni p > 0.006). These findings indicate that even in relatively healthy older people, accelerated brain aging is associated with worse psychomotor speed, but future longitudinal research into changes in brain-PAD is needed.

Age-related decline in the brain: a longitudinal study on inter-individual variability of cortical thickness, area, volume, and cognition

Magnetic Resonance Imaging (MRI) studies have shown that cortical volume declines with age. Although volume is a multiplicative measure consisting of thickness and area, few studies have focused on both its components. Information on decline variability and associations between person-specific changes of different brain metrics, brain regions, and cognition is sparse. In addition, the estimates have often been biased by the measurement error, because three repeated measures are minimally required to separate the measurement error from person-specific changes. With a sample size of N = 231, five repeated measures, and an observational time span of seven years, this study explores the associations between changes of different brain metrics, brain regions, and cognitive abilities in aging. Person-specific changes were obtained by latent growth curve models using Bayesian estimation. Our data indicate that both thickness and area are important contributors to volumetric changes. In most brain regions, area clearly declined on average over the years, while thickness showed only little decline. However, there was also substantial variation around the average slope in thickness and area. The correlation pattern of changes in thickness between brain regions was strong and largely homogenous. The pattern for changes in area was similar but weaker, indicating that factors affecting area may be more region-specific. Changes in thickness and volume were substantially correlated with changes in cognition. In some brain regions, changes in area were also related to changes in cognition. Overall, studying the associations between the trajectories of brain regions in different brain metrics provides insights into the regional heterogeneity of structural changes. SIGNIFICANCE STATEMENT: Many studies have described volumetric brain changes in aging. Few studies have focused on both its individual components: area and thickness. Longitudinal studies with three or more time points are highly needed, because they provide more precise average change estimates and, more importantly, allow us to quantify the associations between changes in the different brain metrics, brain regions, and other variables (e.g. cognitive abilities). Studying these associations is important because they can provide information regarding possible underlying factors of these changes. Our study, with a large sample size, five repeated measures, and an observational time span of seven years, provides new insights about the associations between person-specific changes in thickness, area, volume, and cognitive abilities.