Early prevention of cognitive impairment in the community population: The Beijing Aging Brain Rejuvenation Initiative

The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

Leisure activities as reserve mediators of the relationship between loneliness and cognition in aging

Previous studies have found that loneliness affects cognitive functions in older persons. However, the influence of loneliness on different cognitive fields and the internal mechanism of the relationship are unclear. A total of 4772 older persons aged above 50 years (Mean = 65.31, SD = 6.96, 57.7% female) were included in this study. All the participants completed the characteristics scale, as well as the loneliness scale, leisure activity scale, and cognitive function tests in six domains. The results showed that 17.6% of participants had high loneliness, while 16.7% of participants had low loneliness. Associations were observed between higher levels of loneliness and lower scores in general cognitive ability, memory, and executive functions. Mediation analysis suggested that leisure activities, encompassing mental, physical, and social activities, were associated with cognitive functions in the context of loneliness. These results indicate that leisure activities may play a significant role in the relationship between loneliness and cognitive functions in older adults. The study highlights the importance of considering leisure activities in this demographic to potentially mitigate the adverse cognitive effects associated with loneliness.

Pathophysiology characterization of Alzheimer's disease in South China's aging population: for the Greater-Bay-Area Healthy Aging Brain Study (GHABS)

INTRODUCTION

The Guangdong-Hong Kong-Macao Greater-Bay-Area of South China has an 86 million population and faces a significant challenge of Alzheimer's disease (AD). However, the characteristics and prevalence of AD in this area are still unclear due to the rarely available community-based neuroimaging AD cohort.

METHODS

Following the standard protocols of the Alzheimer's Disease Neuroimaging Initiative, the Greater-Bay-Area Healthy Aging Brain Study (GHABS) was initiated in 2021. GHABS participants completed clinical assessments, plasma biomarkers, genotyping, magnetic resonance imaging (MRI), β-amyloid (Aβ) positron emission tomography (PET) imaging, and tau PET imaging. The GHABS cohort focuses on pathophysiology characterization and early AD detection in the Guangdong-Hong Kong-Macao Greater Bay Area. In this study, we analyzed plasma Aβ42/Aβ40 (A), p-Tau181 (T), neurofilament light, and GFAP by Simoa in 470 Chinese older adults, and 301, 195, and 70 had MRI, Aβ PET, and tau PET, respectively. Plasma biomarkers, Aβ PET, tau PET, hippocampal volume, and temporal-metaROI cortical thickness were compared between normal control (NC), subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia groups, controlling for age, sex, and APOE-ε4. The prevalence of plasma A/T profiles and Aβ PET positivity were also determined in different diagnostic groups.

RESULTS

The aims, study design, data collection, and potential applications of GHABS are summarized. SCD individuals had significantly higher plasma p-Tau181 and plasma GFAP than the NC individuals. MCI and dementia patients showed more abnormal changes in all the plasma and neuroimaging biomarkers than NC and SCD individuals. The frequencies of plasma A+/T+ (NC; 5.9%, SCD: 8.2%, MCI: 25.3%, dementia: 64.9%) and Aβ PET positivity (NC: 25.6%, SCD: 22.5%, MCI: 47.7%, dementia: 89.3%) were reported.

DISCUSSION

The GHABS cohort may provide helpful guidance toward designing standard AD community cohorts in South China. This study, for the first time, reported the pathophysiology characterization of plasma biomarkers, Aβ PET, tau PET, hippocampal atrophy, and AD-signature cortical thinning, as well as the prevalence of Aβ PET positivity in the Guangdong-Hong Kong-Macao Greater Bay Area of China. These findings provide novel insights into understanding the characteristics of abnormal AD pathological changes in South China's older population.

Effect of the duration of hypertension on white matter structure and its link with cognition

The relation between hypertension (HTN) and cognition has been reported inclusive results, which may be affected by disease duration. Our study aimed to examine the influence of HTN duration on cognition and its underlying white matter (WM) changes including macrostructural WM hyperintensities (WMH) and microstructural WM integrity. A total of 1218 patients aged ≥55 years with neuropsychological assessment and a subgroup of 233 people with imaging data were recruited and divided into 3 groups (short duration: <5 years, medium duration: 5-20 years, long duration: >20 years). We found that greater HTN duration was preferentially related to worse executive function (EF), processing speed (PS), and more severe WMH, which became more significant during long duration stage. The reductions in WM integrity were evident at the early stage especially in long-range association fibers and then scattered through the whole brain. Increasing WMH and decreasing integrity of specific tracts consistently undermined EF. Furthermore, free water imaging method greatly enhanced the sensitivity in detecting HTN-related WM alterations. These findings supported that the neurological damaging effects of HTN is cumulative and neuroimaging markers of WM at macro- and microstructural level underlie the progressive effect of HTN on cognition.

Cortical thickness reveals sex differences in verbal and visuospatial memory

Although previous studies have reported the sex differences in behavior/cognition and the brain, the sex difference in the relationship between memory abilities and the underlying neural basis in the aging process remains unclear. In this study, we used a machine learning model to estimate the association between cortical thickness and verbal/visuospatial memory in females and males and then explored the sex difference of these associations based on a community-elderly cohort (n = 1153, age ranged from 50.42 to 86.67 years). We validated that females outperformed males in verbal memory, while males outperformed females in visuospatial memory. The key regions related to verbal memory in females include the medial temporal cortex, orbitofrontal cortex, and some regions around the insula. Further, those regions are more located in limbic, dorsal attention, and default-model networks, and are associated with face recognition and perception. The key regions related to visuospatial memory include the lateral prefrontal cortex, anterior cingulate gyrus, and some occipital regions. They overlapped more with dorsal attention, frontoparietal and visual networks, and were associated with object recognition. These findings imply the memory performance advantage of females and males might be related to the different memory processing tendencies and their associated network.

DCP: A pipeline toolbox for diffusion connectome

The brain structural network derived from diffusion magnetic resonance imaging (dMRI) reflects the white matter connections between brain regions, which can quantitatively describe the anatomical connection pattern of the entire brain. The development of structural brain connectome leads to the emergence of a large number of dMRI processing packages and network analysis toolboxes. However, the fully automated network analysis based on dMRI data remains challenging. In this study, we developed a cross-platform MATLAB toolbox named "Diffusion Connectome Pipeline" (DCP) for automatically constructing brain structural networks and calculating topological attributes of the networks. The toolbox integrates a few developed packages, including FSL, Diffusion Toolkit, SPM, Camino, MRtrix3, and MRIcron. It can process raw dMRI data collected from any number of participants, and it is also compatible with preprocessed files from public datasets such as HCP and UK Biobank. Moreover, a friendly graphical user interface allows users to configure their processing pipeline without any programming. To prove the capacity and validity of the DCP, two tests were conducted with using DCP. The results showed that DCP can reproduce the findings in our previous studies. However, there are some limitations of DCP, such as relying on MATLAB and being unable to fixel-based metrics weighted network. Despite these limitations, overall, the DCP software provides a standardized, fully automated computational workflow for white matter network construction and analysis, which is beneficial for advancing future human brain connectomics application research.

Joint contributions from brain activity and activity-independent functional connectivity to working memory aging

Working memory (WM) impairment has been well characterized in normal aging. Various studies have explored changes in either the regional activity or the interregional connectivity underlying the aging process of WM. We proposed that brain activity and connectivity would independently alter with aging and affect WM performance. WM was assessed with a classical N-back task during functional magnetic resonance imaging in a community-based sample comprising 168 elderly subjects (aged 55-86 years old). Following the rationale of background functional connectivity, we assessed age-related alterations in brain activity and seed-based interregional connectivity independently. Analyses revealed age-related decrease in positive activity of the inferior parietal lobule (IPL) and an increase in the negative activity of the ventral anterior cingulate cortex (ACC), and the local functional dysfunctions were accompanied by alterations in their connectivity to other cortical regions. Importantly, regional activity impairments in the IPL and ACC could mediate age-related effects on accuracy rate and reaction time, respectively, and those effects were further counterbalanced by enhancement of their background functional connectivity. We thus claimed that age-induced alterations in regional activity and interregional connectivity occurred independently and contributed to WM changes in aging. Our findings presented the way brain activity and functional connectivity interact in the late adulthood, thus providing a new perspective for understanding WM and cognitive aging.

Vascular Risk Factors and Brain Health in Aging: Insights from a Community-Based Cohort Study

Background

The aging population and high rates of Alzheimer's disease (AD) create significant medical burdens, prompting a need for early prevention. Targeting modifiable risk factors like vascular risk factors (VRFs), closely linked to AD, may provide a promising strategy for intervention.

Objective

This study investigates how VRFs influence cognitive performance and brain structures in a community-based cohort.

Methods

In this cross-sectional study, 4,667 participants over 50 years old, drawn from the Beijing Ageing Brain Rejuvenation Initiative project, were meticulously examined. Cognitive function and VRFs (diabetes mellitus, hypertension, hyperlipidemia, obesity, and smoking), were comprehensively assessed through one-to-one interviews. Additionally, a subset of participants (n = 719) underwent MRI, encompassing T1-weighted and diffusion-weighted scans, to elucidate gray matter volume and white matter structural network organization.

Results

The findings unveil diabetes as a potent detriment to memory, manifesting in atrophy within the right supramarginal gyrus and diminished nodal efficiency and degree centrality in the right inferior parietal lobe. Hypertension solely impaired memory without significant structural changes. Intriguingly, individuals with comorbid diabetes and hypertension exhibited the most pronounced deficits in both brain structure and cognitive performance. Remarkably, hyperlipidemia emerged as a factor associated with enhanced cognition, and preservation of brain structure.

Conclusions

This study illuminates the intricate associations between VRFs and the varied patterns of cognitive and brain structural damage. Notably, the synergistic effect of diabetes and hypertension emerges as particularly deleterious. These findings underscore the imperative to tailor interventions for patients with distinct VRF comorbidities, especially when addressing cognitive decline and structural brain changes.

Association of Age with Dual-Task Objective Cognitive Indicators and Gait Parameters in Older Adults

Background

Early recognition of dementia like Alzheimer's disease is crucial for disease diagnosis and treatment, and existing objective tools for early screening of cognitive impairment are limited.

Objective

To investigate age-related behavioral indicators of dual-task cognitive performance and gait parameters and to explore potential objective markers of early cognitive decline.

Methods

The community-based cognitive screening data was analyzed. Hierarchical cluster analysis and Pearson correlation analysis were performed on the 9-item subjective cognitive decline (SCD-9) scores, walking-cognitive dual-task performance, walking speed, and gait parameters of 152 participants. The significant differences of indicators that may related to cognitive decline were statistically analyzed across six age groups. A mathematical model with age as the independent variable and motor cognition composite score as the dependent variable was established to observe the trend of motor cognition dual-task performance with age.

Results

Strong correlation was found between motor cognitive scores and SCD and age. Gait parameters like the mean value of ankle angle, the left-right difference rate of ankle angle and knee angle and the coefficient of variation of gait cycle showed an excellent correlation with age. Motor cognition scores showed a decreasing trend with age. The slope of motor cognition scores with age after 50 years (k = -1.06) was six times higher than that before 50 years (k = -0.18).

Conclusions

Cognitive performance and gait parameters in the walking-cognitive dual-task state are promising objective markers that could characterize age-related cognitive decline.

Multi-domain cognition dysfunction accompanies frontoparietal and temporal amyloid accumulation in the elderly

It is helpful to understand the pathology of Alzheimer's disease by exploring the relationship between amyloid-β accumulation and cognition. The study explored the relationship between regional amyloid-β accumulation and multiple cognitions and study their application value in the Alzheimer's disease diagnosis. 135 participants completed 18F-florbetapir Positron Emission Tomography (PET), structural MRI, and a cognitive battery. Partial correlation was used to examine the relationship between global and regional amyloid-β accumulation and cognitions. Then, a support vector machine was applied to determine whether cognition-related accumulation regions can adequately distinguish the cognitively normal controls (76 participants) and mild cognitive impairment (30 participants) groups or mild cognitive impairment and Alzheimer's disease (29 participants) groups. The result showed that amyloid-β accumulation regions were mainly located in the frontoparietal cortex, calcarine fissure, and surrounding cortex and temporal pole regions. Episodic memory-related regions included the frontoparietal cortices; executive function-related regions included the frontoparietal, temporal, and occipital cortices; and processing speed-related regions included the frontal and occipital cortices. Support vector machine analysis showed that only episodic memory-related amyloid-β accumulation regions had better classification performance during the progression of Alzheimer's disease. Assessing regional changes in amyloid, particularly in frontoparietal regions, can aid in the early detection of amyloid-related decline in cognitive function.

Differences in resting-state brain networks and gray matter between APOE ε2 and APOE ε4 carriers in non-dementia elderly

Background

Apolipoprotein E (APOE) ε2 and APOE ε4 are the most distinct alleles among the three APOE alleles, both structurally and functionally. However, differences in cognition, brain function, and brain structure between the two alleles have not been comprehensively reported in the literature, especially in non-demented elderly individuals.

Methods

A neuropsychological test battery was used to evaluate the differences in cognitive performance in five cognitive domains. Independent component analysis (ICA) and voxel-based morphometry (VBM) were used separately to analyze resting-state functional magnetic resonance imaging (rs-fMRI) data and the structure MRI data between the two groups. Finally, correlations between differential brain regions and neuropsychological tests were calculated.

Results

APOE ε2 carriers had better cognitive performance in general cognitive, memory, attention, and executive function than APOE ε4 carriers (all p < 0.05). In ICA analyses of rs-fMRI data, the difference in the resting-state functional connectivity (rsFC) between two groups is shown in 7 brain networks. In addition, VBM analyses of the T1-weighted image revealed that APOE ε2 carriers had a larger thalamus and right postcentral gyrus volume and a smaller bilateral putamen volume than APOE ε4 carriers. Finally, differences in brain function and structure may be might be the reason that APOE ε2 carriers are better than APOE ε4 carriers in cognitive performance.

Conclusion

These findings suggest that there are significant differences in brain function and structure between APOE ε2 carriers and APOE ε4 carriers, and these significant differences are closely related to their cognitive performance.

Absent in melanoma 2 mediates aging-related cognitive dysfunction by acting on complement-dependent microglial phagocytosis

Pattern separation (PS) dysfunction is a type of cognitive impairment that presents early during the aging process, and this deficit has been attributed to structural and functional alterations in the dentate gyrus (DG) of the hippocampus. Absent in melanoma 2 (AIM2) is an essential component of the inflammasome. However, whether AIM2 plays a role in aging-associated cognitive dysfunction remains unclear. Here, we found that PS function was impaired in aging mice and was accompanied by marked synaptic loss and increased expression of AIM2 in the DG. Subsequently, we used an AIM2 overexpression virus and mice with AIM2 deletion to investigate the role of AIM2 in regulating PS function and synaptic plasticity and the mechanisms involved. Our study revealed that AIM2 regulates microglial activation during synaptic pruning in the DG region via the complement pathway, leading to impaired synaptic plasticity and PS function in aging mice. These results suggest a critical role for AIM2 in regulating synaptic plasticity and PS function and provide a new direction for ameliorating aging-associated cognitive dysfunction.

SORL1 rs1699102 Moderates the Effect of Sex on Language Network

BACKGROUND

Language ability differs between the sexes. However, it is unclear how this sex difference is moderated by genetic factors and how the brain interacts with genetics to support this specific language capacity. Previous studies have demonstrated that the sorting protein-related receptor (SORL1) polymorphism influences cognitive function and brain structure differently in males and females and is associated with Alzheimer's disease risk.

OBJECTIVE

The aim of this study was to investigate the effects of sex and the SORL1 rs1699102 (CC versus T carriers) genotype on language.

METHODS

103 non-demented Chinese older adults from Beijing Aging Brain Rejuvenation Initiative (BABRI) database were included in this study. Participants completed language tests, T1-weighted structural magnetic resonance imaging (MRI) and resting-state functional MRI. Language test performance, gray matter volume, and network connections were compared between genotype and sex groups.

RESULTS

The rs1699102 polymorphism moderated the effects of sex on language performance, with the female having reversed language advantages in T carriers. The T allele carriers had lower gray matter volume in the left precentral gyrus. The effect of sex on language network connections was moderated by rs1699102; male CC homozygotes and female T carriers had higher internetwork connections, which were negatively correlated with language performance.

CONCLUSION

These results suggest that SORL1 moderates the effects of sex on language, with T being a risk allele, especially in females. Our findings underscore the importance of considering the influence of genetic factors when examining sex effects.

The characteristics of glucose metabolism and functional connectivity in posterior default network during nondemented aging: relationship with executive function performance

BACKGROUND

Understanding the characteristics of intrinsic connectivity networks (ICNs) in terms of both glucose metabolism and functional connectivity (FC) is important for revealing cognitive aging and neurodegeneration, but the relationships between these two aspects during aging has not been well established in older adults.

OBJECTIVE

This study is to assess the relationship between age-related glucose metabolism and FC in key ICNs, and their direct or indirect effects on cognitive deficits in older adults.

METHODS

We estimated the individual-level standard uptake value ratio (SUVr) and FC of eleven ICNs in 59 cognitively unimpaired older adults, then analyzed the associations of SUVr and FC of each ICN and their relationships with cognitive performance.

RESULTS

The results showed both the SUVr and FC in the posterior default mode network (pDMN) had a significant decline with age, and the association between them was also significant. Moreover, both decline of metabolism and FC in the pDMN were significantly correlated with executive function decline. Finally, mediation analysis revealed the glucose metabolism mediated the FC decline with age and FC mediated the executive function deficits.

CONCLUSIONS

Our findings indicated that covariance between glucose metabolism and FC in the pDMN is one of the main routes that contributes to age-related executive function decline.

Altered functional coupling between the cerebellum and cerebrum in patients with amnestic mild cognitive impairment

Cognitive processing relies on the functional coupling between the cerebrum and cerebellum. However, it remains unclear how the 2 collaborate in amnestic mild cognitive impairment (aMCI) patients. With functional magnetic resonance imaging techniques, we compared cerebrocerebellar functional connectivity during the resting state (rsFC) between the aMCI and healthy control (HC) groups. Additionally, we distinguished coupling between functionally corresponding and noncorresponding areas across the cerebrum and cerebellum. The results demonstrated decreased rsFC between both functionally corresponding and noncorresponding areas, suggesting distributed deficits of cerebrocerebellar connections in aMCI patients. Increased rsFC was also observed, which were between functionally noncorresponding areas. Moreover, the increased rsFC was positively correlated with attentional scores in the aMCI group, and this effect was absent in the HC group, supporting that there exists a compensatory mechanism in patients. The current study contributes to illustrating how the cerebellum adjusts its coupling with the cerebrum in individuals with cognitive impairment.

Hippocampus-centred grey matter covariance networks predict the development and reversion of mild cognitive impairment

BACKGROUND

Mild cognitive impairment (MCI) has been thought of as the transitional stage between normal ageing and Alzheimer's disease, involving substantial changes in brain grey matter structures. As most previous studies have focused on single regions (e.g. the hippocampus) and their changes during MCI development and reversion, the relationship between grey matter covariance among distributed brain regions and clinical development and reversion of MCI remains unclear.

METHODS

With samples from two independent studies (155 from the Beijing Aging Brain Rejuvenation Initiative and 286 from the Alzheimer's Disease Neuroimaging Initiative), grey matter covariance of default, frontoparietal, and hippocampal networks were identified by seed-based partial least square analyses, and random forest models were applied to predict the progression from normal cognition to MCI (N-t-M) and the reversion from MCI to normal cognition (M-t-N).

RESULTS

With varying degrees, the grey matter covariance in the three networks could predict N-t-M progression (AUC = 0.692-0.792) and M-t-N reversion (AUC = 0.701-0.809). Further analyses indicated that the hippocampus has emerged as an important region in reversion prediction within all three brain networks, and even though the hippocampus itself could predict the clinical reversion of M-t-N, the grey matter covariance showed higher prediction accuracy for early progression of N-t-M.

CONCLUSIONS

Our findings are the first to report grey matter covariance changes in MCI development and reversion and highlight the necessity of including grey matter covariance changes along with hippocampal degeneration in the early detection of MCI and Alzheimer's disease.

Tau as a biomarker of cognitive impairment and neuropsychiatric symptom in Alzheimer's disease

The A/T/N research framework has been proposed for the diagnosis and prognosis of Alzheimer's disease (AD). However, the spatial distribution of ATN biomarkers and their relationship with cognitive impairment and neuropsychiatric symptoms (NPS) need further clarification in patients with AD. We scanned 83 AD patients and 38 cognitively normal controls who independently completed the mini-mental state examination and Neuropsychiatric Inventory scales. Tau, Aβ, and hypometabolism spatial patterns were characterized using Statistical Parametric Mapping together with [18F]flortaucipir, [18F]florbetapir, and [18F]FDG positron emission tomography. Piecewise linear regression, two-sample t-tests, and support vector machine algorithms were used to explore the relationship between tau, Aβ, and hypometabolism and cognition, NPS, and AD diagnosis. The results showed that regions with tau deposition are region-specific and mainly occurred in inferior temporal lobes in AD, which extensively overlaps with the hypometabolic regions. While the deposition regions of Aβ were unique and the regions affected by hypometabolism were widely distributed. Unlike Aβ, tau and hypometabolism build up monotonically with increasing cognitive impairment in the late stages of AD. In addition, NPS in AD were associated with tau deposition closely, followed by hypometabolism, but not with Aβ. Finally, hypometabolism and tau had higher accuracy in differentiating the AD patients from controls (accuracy = 0.88, accuracy = 0.85) than Aβ (accuracy = 0.81), and the combined three were the highest (accuracy = 0.95). These findings suggest tau pathology is superior over Aβ and glucose metabolism to identify cognitive impairment and NPS. Its results support tau accumulation can be used as a biomarker of clinical impairment in AD.

Temperature variability and common diseases of the elderly in China: a national cross-sectional study

BACKGROUND

In the context of climate change, it has been well observed that short-term temperature variability (TV) could increase the overall and cause-specific mortality and morbidity. However, the association between long-term TV and a broader spectrum of diseases is not yet well understood, especially in the elderly.

METHODS

Our study used data from the fourth Urban and Rural Elderly Population (UREP) study. Long-term TV was calculated from the standard deviation (SD) of daily minimum and maximum temperatures within the study periods (2010-2014, 2011-2014, 2012-2014, 2013-2014, and 2014). Ten self-reported diseases and conditions were collected by questionnaire, including cataract, hypertension, diabetes, cardio-cerebrovascular diseases, stomach diseases, arthritis, chronic lung disease, asthma, cancer, and reproductive diseases. The province-stratified logistic regression model was used to quantify the association between long-term TV and the prevalence of each disease.

RESULTS

A total of 184,047 participants were included in our study. In general, there were significant associations between TV and the prevalence of most diseases at the national level. Cardio-cerebrovascular disease (OR: 1.16, 95% CI: 1.13, 1.20) generated the highest estimates, followed by stomach diseases (OR: 1.15, 95% CI: 1.10, 1.19), asthma (OR: 1.14, 95% CI: 1.06, 1.22), chronic lung diseases (OR: 1.08, 95% CI: 1.03, 1.13), arthritis (OR: 1.08, 95% CI: 1.05, 1.11), and cataract (OR: 1.06, 95% CI: 1.02, 1.10). Moreover, the associations varied by geographical regions and across subgroups stratified by sex, household income, physical activity, and education.

CONCLUSIONS

Our study showed that long-term exposure to TV was associated with the prevalence of main diseases in the elderly. More attention should be paid to the elderly and targeted strategies should be implemented, such as an early warning system.

An Overview

Nowadays, China has rapidly progressed into an aging society and is faced with huge challenges on public health. Aging is accompanied by the structural and functional alterations in the brain, which leads to the cognitive decline in the elderly and acts as the primary risk factor for dementia. However, the aging brain has not been well understood at a systemic level. This chapter presents the definition of brain health, the aging situation in China, an overview of the BABRI, the purpose of writing this book, and the introductions of the chapters, respectively, which will contribute to knowledge of the underlying mechanisms of healthy and pathological aging of the brain.

Contributions of early-life cognitive reserve and late-life leisure activity to successful and pathological cognitive aging

BACKGROUND

The identification of factors that specifically influence pathological and successful cognitive aging is a prerequisite for implementing disease prevention and promoting successful aging. However, multi-domain behavioral factors that characterize the difference between successful and pathological cognitive aging are not clear yet.

METHODS

A group of community-dwelling older adults (N = 1347, aged 70-88 years) in Beijing was recruited in this cross-sectional study, and a sub-cohort was further divided into successful cognitive aging (SCA, N = 154), mild cognitive impairment (MCI, N = 256), and cognitively normal control (CNC, N = 173) groups. Analyses of variance, regression models with the Shapley value algorithm, and structural equation model (SEM) analyses were conducted to determine specific influencing factors and to evaluate their relative importance and interacting relationships in altering cognitive performance.

RESULTS

We found that abundant early-life cognitive reserve (ECR, including the level of education and occupational attainment) and reduced late-life leisure activity (LLA, including mental, physical, and social activities) were distinct characteristics of SCA and MCI, respectively. The level of education, age, mental activity, and occupational attainment were the top four important factors that explained 31.6% of cognitive variability. By SEM analyses, we firstly found that LLA partially mediated the relationship between ECR and cognition; and further multi-group SEM analyses showed ECR played a more direct role in the SCA group than in the MCI group: in the SCA group, only the direct effect of ECR on cognition was significant, and in the MCI group, direct effects between ECR, LLA and cognition were all significant.

CONCLUSIONS

Results of this large-sample community-based study suggest it is important for older adults to have an abundant ECR for SCA, and to keep a high level of LLA to prevent cognitive impairment. This study clarifies the important rankings of behavioral characteristics of cognitive aging, and the relationship that ECR has a long-lasting effect on LLA and finally on cognition, providing efficient guidance for older adults to improve their cognitive function and new evidence to explain the heterogeneity of cognitive aging.

Risk scores of incident mild cognitive impairment in a Beijing community-based older cohort

Objective: It is very important to identify individuals who are at greatest risk for mild cognitive impairment (MCI) to potentially mitigate or minimize risk factors early in its course. We created a practical MCI risk scoring system and provided individualized estimates of MCI risk.

Methods: Using data from 9,000 older adults recruited for the Beijing Ageing Brain Rejuvenation Initiative, we investigated the association of the baseline demographic, medical history, lifestyle and cognitive data with MCI status based on logistic modeling and established risk score (RS) models 1 and 2 for MCI. We evaluated model performance by computing the area under the receiver operating characteristic (ROC) curve (AUC). Finally, RS model 3 was further confirmed and improved based on longitudinal outcome data from the progression of MCI in a sub-cohort who had an average 3-year follow-up.

Results: A total of 1,174 subjects (19.8%) were diagnosed with MCI at baseline, and 72 (7.8%) of 849 developed MCI in the follow-up. The AUC values of RS models 1 and 2 were between 0.64 and 0.70 based on baseline age, education, cerebrovascular disease, intelligence and physical activities. Adding baseline memory and language performance, the AUC of RS model 3 more accurately predicted MCI conversion (AUC = 0.785).

Conclusion: A combination of risk factors is predictive of the likelihood of MCI. Identifying the RSs may be useful to clinicians as they evaluate their patients and to researchers as they design trials to study possible early non-pharmaceutical interventions to reduce the risk of MCI and dementia.

Methodological evaluation of individual cognitive prediction based on the brain white matter structural connectome

An emerging trend is to use regression‐based machine learning approaches to predict cognitive functions at the individual level from neuroimaging data. However, individual prediction models are inherently influenced by the vast options for network construction and model selection in machine learning pipelines. In particular, the brain white matter (WM) structural connectome lacks a systematic evaluation of the effects of different options in the pipeline on predictive performance. Here, we focused on the methodological evaluation of brain structural connectome‐based predictions. For network construction, we considered two parcellation schemes for defining nodes and seven strategies for defining edges. For the regression algorithms, we used eight regression models. Four cognitive domains and brain age were targeted as predictive tasks based on two independent datasets (Beijing Aging Brain Rejuvenation Initiative [BABRI]: 633 healthy older adults; Human Connectome Projects in Aging [HCP‐A]: 560 healthy older adults). Based on the results, the WM structural connectome provided a satisfying predictive ability for individual age and cognitive functions, especially for executive function and attention. Second, different parcellation schemes induce a significant difference in predictive performance. Third, prediction results from different data sets showed that dMRI with distinct acquisition parameters may plausibly result in a preference for proper fiber reconstruction algorithms and different weighting options. Finally, deep learning and Elastic‐Net models are more accurate and robust in connectome‐based predictions. Together, significant effects of different options in WM network construction and regression algorithms on the predictive performances are identified in this study, which may provide important references and guidelines to select suitable options for future studies in this field.

The Effect of APOE ɛ4 on the Functional Connectivity in Frontoparietal Network in Hypertensive Patients

Allele 4 of the apolipoprotein E gene (APOE ε4) and hypertension are considered risk factors for Alzheimer’s Disease (AD). The detection of differences in cognitive function and brain networks between hypertensive patients who are APOE ε4 carriers and non-carriers may help in understanding how hypertension and risk genes cumulatively impair brain function, which could provide critical insights into the genetic mechanism by which hypertension serves as a potential risk factor for cognitive decline and even AD. Using behavioral data from 233 elderly hypertensive patients and neuroimaging data from 38 of them from Beijing, China; the study aimed to assess the effects of APOE ε4 on cognition and to explore related changes in functional connectivity. Cognitively, the patients with APOE ε4 showed decreased executive function, memory and language. In the MRI sub-cohort, the frontoparietal networks in the APOE ε4 carrier group exhibited an altered pattern, mainly in the left precentral regions, inferior frontal lobe and angular gyrus. More importantly, the decline of cognitive function was correlated with abnormal FC in the left precentral regions in APOE ε4 carriers. APOE ε4 aggravated the dysfunction in frontal and parietal regions in hypertensive patients. This highlights the importance of brain protection in hypertensive patients, especially those with a genetic risk of AD.

Neuroimaging brain growth charts: A road to mental health

Mental disorders are common health concerns and contribute to a heavy global burden on our modern society. It is challenging to identify and treat them timely. Neuroimaging evidence suggests the incidence of various psychiatric and behavioral disorders is closely related to the atypical development of brain structure and function. The identification and understanding of atypical brain development provide chances for clinicians to detect mental disorders earlier, perhaps even prior to onset, and treat them more precisely. An invaluable and necessary method in identifying and monitoring atypical brain development are growth charts of typically developing individuals in the population. The brain growth charts can offer a series of standard references on typical neurodevelopment, representing an important resource for the scientific and medical communities. In the present paper, we review the relationship between mental disorders and atypical brain development from a perspective of normative brain development by surveying the recent progress in the development of brain growth charts, including four aspects on growth chart utility: 1) cohorts, 2) measures, 3) mechanisms, and 4) clinical translations. In doing so, we seek to clarify the challenges and opportunities in charting brain growth, and to promote the application of brain growth charts in clinical practice.

Decline in the integration of top-down and bottom-up attentional control in older adults with mild cognitive impairment

Individuals with mild cognitive impairment (MCI) have deficits in goal-directed top-down and stimulus-driven bottom-up attentional control. However, it remains unclear whether and how the interaction between the two processes is altered in individuals with MCI. We collected electroencephalography (EEG) data from 30 older adults with MCI and 30 demographically matched healthy controls (HCs) when they were performing a perceptual decision-making task, in which we manipulated the cognitive load involved in task-relevant top-down processing and the surprise level involved in task-irrelevant bottom-up processing. We found the significant group difference in the interaction between top-down and bottom-up processes. HCs showed enlarged P3 and strengthened event-related microstate C on high (vs. low) surprise level trials under high cognitive load, while there was no such surprise effect suggesting distraction under low cognitive load. In contrast, participants with MCI showed increased P2 and P3 amplitudes and strengthened microstates C and D on high (vs. low) surprise level trials under low cognitive load yet no surprise effect under high load. These results suggested that participants with MCI were distracted by task-irrelevant information under low cognitive load, while under high load, they might experience a passive inhibition on the task-irrelevant bottom-up processing because of the exhaustion of attentional resources; in addition, this altered interaction observed in the MCI group occurred at the stages of selective attention and uncertainty reduction.