When functional blurring becomes deleterious: Reduced system segregation is associated with less white matter integrity and cognitive decline in aging

The Interaction Effects of Sex, Age, APOE and Common Health Risk Factors on Human Brain Functions

Importance

Nonlinear changes in brain function during aging are shaped by a complex interplay of factors, including sex, age, genetics, and modifiable health risk factors. However, the combined effects and underlying mechanisms of these factors on brain functional connectivity remain poorly understood.

Objective

To comprehensively investigate the combined associations of sex, age, APOE genotypes, and ten common modifiable health risk factors with brain functional connectivities during aging.

Design Setting and Participants

This analysis used data from 36,630 UK Biobank participants, aged 44-81, who were assessed for sex, age, APOE genotypes, 10 health risk factors, and brain functional connectivities through resting-state functional magnetic resonance imaging.

Main Outcomes and Measures

Brain functional connectivities were evaluated through within- and between-network functional connectivities and connectivity strength. Associations between risk factors and brain functional connectivities, including their interaction effects, were analyzed.

Results

Hypertension, BMI, and education were the top three influential factors. Sex-specific effects were also observed in interactions involving APOE4 gene, smoking, alcohol consumption, diabetes, BMI, and education. Notably, a negative sex-excessive alcohol interaction showed a stronger negative effect on functional connectivities in males, particularly between the dorsal attention network and the language network, while moderate alcohol consumption appeared to have protective effects. A significant negative interaction between sex and APOE4 revealed a greater reduction in functional connectivity between the cingulo-opercular network and the posterior multimodal network in male APOE4 carriers. Additional findings included a negative age-BMI interaction between the visual and dorsal attention networks, and a positive age-hypertension interaction between the frontoparietal and default mode networks.

Conclusions and Relevance

The findings highlight significant sex disparities in the associations between age, the APOE-ε4 gene, modifiable health risk factors, and brain functional connectivity, emphasizing the necessity of jointly considering these factors to gain a deeper understanding of the complex processes underlying brain aging.

Age-related differences in resting-state, task-related, and structural brain connectivity: graph theoretical analyses and visual search performance

Previous magnetic resonance imaging (MRI) research suggests that aging is associated with a decrease in the functional interconnections within and between groups of locally organized brain regions (modules). Further, this age-related decrease in the segregation of modules appears to be more pronounced for a task, relative to a resting state, reflecting the integration of functional modules and attentional allocation necessary to support task performance. Here, using graph-theoretical analyses, we investigated age-related differences in a whole-brain measure of module connectivity, system segregation, for 68 healthy, community-dwelling individuals 18-78 years of age. We obtained resting-state, task-related (visual search), and structural (diffusion-weighted) MRI data. Using a parcellation of modules derived from the participants' resting-state functional MRI data, we demonstrated that the decrease in system segregation from rest to task (i.e., reconfiguration) increased with age, suggesting an age-related increase in the integration of modules required by the attentional demands of visual search. Structural system segregation increased with age, reflecting weaker connectivity both within and between modules. Functional and structural system segregation had qualitatively different influences on age-related decline in visual search performance. Functional system segregation (and reconfiguration) influenced age-related decline in the rate of visual evidence accumulation (drift rate), whereas structural system segregation contributed to age-related slowing of encoding and response processes (nondecision time). The age-related differences in the functional system segregation measures, however, were relatively independent of those associated with structural connectivity.

Cross-sectional and Longitudinal Age-related Disintegration in Functional Connectivity: Reference Ability Neural Network Cohort

Some theories of aging have linked age-related cognitive decline to a reduction in distinctiveness of neural processing. Observed age-related correlation increases among disparate cognitive tasks have supported the dedifferentiation hypothesis. We previously showed cross-sectional evidence for age-related correlation decreases instead, supporting an alternative disintegration hypothesis. In the current study, we extended our previous research to a longitudinal sample. We tested 135 participants (20-80 years) at two time points-baseline and 5-year follow-up-on a battery of 12 in-scanner tests, each tapping one of four reference abilities. We performed between-tasks correlations within domain (convergent) and between domain (discriminant) at both the behavioral and neural level, calculating a single measure of construct validity (convergent - discriminant). Cross-sectionally, behavioral construct validity was significantly different from chance at each time point, but longitudinal change was not significant. Analysis by median age split revealed that older adults showed higher behavioral validity, driven by higher discriminant validity (lower between-tasks correlations). Participant-level neural validity decreased over time, with convergent validity consistently greater than discriminant validity; this finding was also observed at the cross-sectional level. In addition, a disproportionate decrease in neural validity with age remained significant after controlling for demographic factors. Factors predicting longitudinal changes in global cognition (mean performance across all 12 tasks) included age, change in neural validity, education, and National Adult Reading Test (premorbid intelligence). Change in neural validity partially mediated the effect of age on change in global cognition. Our findings support the theory of age-related disintegration, linking cognitive decline to changes in neural representations over time.

Resting state brain network segregation is associated with walking speed and working memory in older adults

Older adults exhibit larger individual differences in walking ability and cognitive function than young adults. Characterizing intrinsic brain connectivity differences in older adults across a wide walking performance spectrum may provide insight into the mechanisms of functional decline in some older adults and resilience in others. Thus, the objectives of this study were to: (1) determine whether young adults and high- and low-functioning older adults show group differences in brain network segregation, and (2) determine whether network segregation is associated with working memory and walking function in these groups. The analysis included 21 young adults and 81 older adults. Older adults were further categorized according to their physical function using a standardized assessment; 54 older adults had low physical function while 27 were considered high functioning. Structural and functional resting state magnetic resonance images were collected using a Siemens Prisma 3T scanner. Working memory was assessed with the NIH Toolbox list sorting test. Walking speed was assessed with a 400 m-walk test at participants' self-selected speed. We found that network segregation in mobility-related networks (sensorimotor, vestibular, and visual networks) was higher in younger adults compared to older adults. There were no group differences in laterality effects on network segregation. We found multivariate associations between working memory and walking speed with network segregation scores. Higher right anterior cingulate cortex network segregation was associated with higher working memory function. Higher right sensorimotor, right vestibular, right anterior cingulate cortex, and lower left anterior cingulate cortex network segregation was associated with faster walking speed. These results are unique and significant because they demonstrate higher network segregation is largely related to higher physical function and not age alone.

Increased functional integration of emotional control network in late adulthood

Across the adult lifespan, there are changes in how emotions are perceived and regulated. As individuals age, there is an observed improvement in emotion regulation and overall quicker recovery from negative emotions. While previous studies have shown differences in emotion processing in late adulthood, the corresponding differences in large-scale brain networks remain largely underexplored. By utilizing large-scale datasets such as the Human Connectome Project (HCP-Aging, N = 621 ) and Cambridge Centre for Ageing and Neuroscience (Cam-CAN, N = 333 ), we were able to investigate how emotion regulation networks' functional topography differs across the entire adult lifespan. Based on previous meta-analytic work that identified four large-scale functional brain networks involved in emotion generation and regulation, we found an increase in the functional integration of the emotional control network among older adults. Additionally, confirming through the nonlinear model, individuals around the age of 70 showed a steadier decline in integration of a network mediating emotion generation and regulation via interoception. Furthermore, the analyses revealed a negative association between age and perceived stress and loneliness that could be attributed to differences in large-scale emotion regulation networks. Our study highlights the importance of identifying topological changes in the functional emotion network architecture across the lifespan, as it allows for a better understanding of emotional aging and psychological well-being in late adulthood.

Elevating understanding: Linking high-altitude hypoxia to brain aging through EEG functional connectivity and spectral analyses

High-altitude hypoxia triggers brain function changes reminiscent of those in healthy aging and Alzheimer's disease, compromising cognition and executive functions. Our study sought to validate high-altitude hypoxia as a model for assessing brain activity disruptions akin to aging. We collected EEG data from 16 healthy volunteers during acute high-altitude hypoxia (at 4,000 masl) and at sea level, focusing on relative changes in power and aperiodic slope of the EEG spectrum due to hypoxia. Additionally, we examined functional connectivity using wPLI, and functional segregation and integration using graph theory tools. High altitude led to slower brain oscillations, that is, increased δ and reduced α power, and flattened the 1/f aperiodic slope, indicating higher electrophysiological noise, akin to healthy aging. Notably, functional integration strengthened in the θ band, exhibiting unique topographical patterns at the subnetwork level, including increased frontocentral and reduced occipitoparietal integration. Moreover, we discovered significant correlations between subjects' age, 1/f slope, θ band integration, and observed robust effects of hypoxia after adjusting for age. Our findings shed light on how reduced oxygen levels at high altitudes influence brain activity patterns resembling those in neurodegenerative disorders and aging, making high-altitude hypoxia a promising model for comprehending the brain in health and disease.

The 'middle-aging' brain

Middle age has historically been an understudied period of life compared to older age, when cognitive and brain health decline are most pronounced, but the scope for intervention may be limited. However, recent research suggests that middle age could mark a shift in brain aging. We review emerging evidence on multiple levels of analysis indicating that midlife is a period defined by unique central and peripheral processes that shape future cognitive trajectories and brain health. Informed by recent developments in aging research and lifespan studies in humans and animal models, we highlight the utility of modeling non-linear changes in study samples with wide subject age ranges to distinguish life stage-specific processes from those acting linearly throughout the lifespan.

Modeling the neurocognitive dynamics of language across the lifespan

Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed between language comprehension and language production (LP). Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this variability. At the cognitive level, our findings suggest that LP is not an isolated function but is modulated throughout the lifespan by the extent of inter-cognitive synergy between semantic and domain-general processes. At the cerebral level, we show that default mode network (DMN) suppression coupled with fronto-parietal network (FPN) integration is the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related decline in LP. Relatedly, reduced DMN suppression in midlife could compromise the ability to manage the cost of FPN integration. This may prompt older adults to adopt a more cost-efficient compensatory strategy that maintains global homeostasis at the expense of LP performances. Taken together, we propose that midlife represents a critical neurocognitive juncture that signifies the onset of LP decline, as older adults gradually lose control over semantic representations. We summarize our findings in a novel synergistic, economical, nonlinear, emergent, cognitive aging model, integrating connectomic and cognitive dimensions within a complex system perspective.

Revised Temperament and Character Inventory factors predict neuropsychiatric symptoms and aging-related cognitive decline across 25 years

Introduction

Personality traits and neuropsychiatric symptoms such as neuroticism and depression share genetic overlap and have both been identified as risks factors for development of aging-related neurocognitive decline and Alzheimer's disease (AD). This study aimed to examine revised personality factors derived from the Temperament and Character Inventory, previously shown to be associated with psychiatric disorders, as predictors of neuropsychiatric, cognitive, and brain trajectories of participants from a population-based aging study.

Methods

Mixed-effect linear regression analyses were conducted on data for the full sample (Nmax = 1,286), and a healthy subsample not converting to AD-dementia during 25-year follow-up (Nmax = 1,145), complemented with Cox proportional regression models to determine risk factors for conversion to clinical AD.

Results

Two personality factors, Closeness to Experience (CE: avoidance of new stimuli, high anxiety, pessimistic anticipation, low reward seeking) and Tendence to Liabilities (TL: inability to change, low autonomy, unaware of the value of their existence) were associated with higher levels of depressive symptoms, stress (CE), sleep disturbance (TL), as well as greater decline in memory, vocabulary and verbal fluency in the full sample. Higher CE was additionally associated with greater memory decline across 25 years in the healthy subsample, and faster right hippocampal volume reduction across 8 years in a neuroimaging subsample (N = 216). Most, but not all, personality-cognition associations persisted after controlling for diabetes, hypertension and cardiovascular disease. Concerning risks for conversion to AD, higher age, and APOE-ε4, but none of the personality measures, were significant predictors.

Conclusion

The results indicate that personality traits associated with psychiatric symptoms predict accelerated age-related neurocognitive declines even in the absence of neurodegenerative disease. The attenuation of some personality effects on cognition after adjustment for health indicators suggests that those effects may be partly mediated by somatic health. Taken together, the results further emphasize the importance of personality traits in neurocognitive aging and underscore the need for an integrative (biopsychosocial) perspective of normal and pathological age-related cognitive decline.

Longitudinal monitoring of the mouse brain reveals heterogenous network trajectories during aging

The human aging brain is characterized by changes in network efficiency that are currently best captured through longitudinal resting-state functional MRI (rs-fMRI). These studies however are challenging due to the long human lifespan. Here we show that the mouse animal model with a much shorter lifespan allows us to follow the functional network organization over most of the animal's adult lifetime. We used a longitudinal study of the functional connectivity of different brain regions with rs-fMRI under anesthesia. Our analysis uncovers network modules similar to those reported in younger mice and in humans (i.e., prefrontal/default mode network (DMN), somatomotor and somatosensory networks). Statistical analysis reveals different patterns of network reorganization during aging. Female mice showed a pattern akin to human aging, with de-differentiation of the connectome, mainly due to increases in connectivity of the prefrontal/DMN cortical networks to other modules. Our male cohorts revealed heterogenous aging patterns with only one group confirming the de- differentiation, while the majority showed an increase in connectivity of the somatomotor cortex to the Nucleus accumbens. In summary, in line with human work, our analysis in mice supports the concept of de-differentiation in the aging mammalian brain and reveals additional trajectories in aging mice networks.

Association of structural connectivity with functional brain network segregation in a middle-aged to elderly population

Introduction

The deterioration of white matter pathways is one of the hallmarks of the ageing brain. In theory, this decrease in structural integrity leads to disconnection between regions of brain networks and thus to altered functional connectivity and a decrease in cognitive abilities. However, in many studies, associations between structural and functional connectivity are rather weak or not observed at all. System segregation, defined as the extent of partitioning between different resting state networks has increasingly gained attention in recent years as a new metric for functional changes in the aging brain. Yet there is a shortage of previous reports describing the association of structural integrity and functional segregation.

Methods

Therefore, we used a large a large sample of 2,657 participants from the Hamburg City Health Study, a prospective population-based study including participants aged 46-78 years from the metropolitan region Hamburg, Germany. We reconstructed structural and functional connectomes to analyze whether there is an association between age-related differences in structural connectivity and functional segregation, and whether this association is stronger than between structural connectivity and functional connectivity. In a second step, we investigated the relationship between functional segregation and executive cognitive function and tested whether this association is stronger than that between functional connectivity and executive cognitive function.

Results

We found a significant age-independent association between decreasing structural connectivity and decreasing functional segregation across the brain. In addition, decreasing functional segregation showed an association with decreasing executive cognitive function. On the contrary, no such association was observed between functional connectivity and structural connectivity or executive function.

Discussion

These results indicate that the segregation metric is a more sensitive biomarker of cognitive ageing than functional connectivity at the global level and offers a unique and more complementary network-based explanation.

Does functional system segregation mediate the effects of lifestyle on cognition in older adults?

Healthy aging is typically accompanied by cognitive decline. Previous work has shown that engaging in multiple, non-work activities during midlife can have a protective effect on cognition several decades later, rendering it less dependent on brain structural health; the definition of "cognitive reserve". Other work has shown that increasing age is associated with reduced segregation of large-scale brain functional networks. Here we tested the hypothesis that functional segregation (SyS) mediates this effect of middle-aged lifestyle on late-life cognition. We used fMRI data from three tasks in the CamCAN dataset, together with cognitive data on fluid intelligence, episodic memory, and retrospective lifestyle data from the Lifetime of Experiences Questionnaire (LEQ). In all three tasks, we showed that SyS related to fluid intelligence even after adjusting for the (nonlinear) age effects. However, we found no evidence that SyS in late-life mediated the relationship between non-specific (non-occupation) midlife activities and either measure of cognition in late-life. Thus, the brain correlates of cognitive reserve arising from mid-life activities remain to be discovered.

Measures of resting-state brain network segregation and integration vary in relation to data quantity: implications for within and between subject comparisons of functional brain network organization

Measures of functional brain network segregation and integration vary with an individual's age, cognitive ability, and health status. Based on these relationships, these measures are frequently examined to study and quantify large-scale patterns of network organization in both basic and applied research settings. However, there is limited information on the stability and reliability of the network measures as applied to functional time-series; these measurement properties are critical to understand if the measures are to be used for individualized characterization of brain networks. We examine measurement reliability using several human datasets (Midnight Scan Club and Human Connectome Project [both Young Adult and Aging]). These datasets include participants with multiple scanning sessions, and collectively include individuals spanning a broad age range of the adult lifespan. The measurement and reliability of measures of resting-state network segregation and integration vary in relation to data quantity for a given participant's scan session; notably, both properties asymptote when estimated using adequate amounts of clean data. We demonstrate how this source of variability can systematically bias interpretation of differences and changes in brain network organization if appropriate safeguards are not included. These observations have important implications for cross-sectional, longitudinal, and interventional comparisons of functional brain network organization.

Age-related differences in structural and resting-state functional brain network organization across the adult lifespan: A cross-sectional study

We investigated age-related trends in the topology and hierarchical organization of brain structural and functional networks using diffusion-weighted imaging and resting-state fMRI data from a large cohort of healthy aging adults. At the cross-modal level, we explored age-related patterns in the RC involvement of different functional subsystems using a high-resolution functional parcellation. We further assessed age-related differences in the structure-function coupling as well as the network vulnerability to damage to rich club connectivity. Regardless of age, the structural and functional brain networks exhibited a rich club organization and small-world topology. In older individuals, we observed reduced integration and segregation within the frontal-occipital regions and the cerebellum along the brain's medial axis. Additionally, functional brain networks displayed decreased integration and increased segregation in the prefrontal, centrotemporal, and occipital regions, and the cerebellum. In older subjects, structural networks also exhibited decreased within-network and increased between-network RC connectivity. Furthermore, both within-network and between-network RC connectivity decreased in functional networks with age. An age-related decline in structure-function coupling was observed within sensory-motor, cognitive, and subcortical networks. The structural network exhibited greater vulnerability to damage to RC connectivity within the language-auditory, visual, and subcortical networks. Similarly, for functional networks, increased vulnerability was observed with damage to RC connectivity in the cerebellum, language-auditory, and sensory-motor networks. Overall, the network vulnerability decreased significantly in subjects older than 70 in both networks. Our findings underscore significant age-related differences in both brain functional and structural RC connectivity, with distinct patterns observed across the adult lifespan.

Association of executive function with suicidality based on resting-state functional connectivity in young adults with subthreshold depression

Subthreshold depression (StD) is associated an increased risk of developing major depressive disorder (MDD) and suicidality. Suicidality could be linked to distress intolerance and use of context-dependent strategies. We identified neural correlates of executive functioning among the hubs in the resting-state functional connectome (rs-FCN) and examined associations with recent suicidality in StD and MDD. In total, 79 young adults [27 StD, 30 MDD, and 23 healthy controls (HC)] were scanned using magnetic resonance imaging. Neurocognitive measures of the mean latency to correct five moves in the One Touch Stockings of Cambridge (OTSMLC5), spatial working memory between errors (SWMBE), rapid visual information processing A' (RVPA'), and the stop signal reaction time in the stop signal test (SSTSSRT) were obtained. Global graph metrics were calculated to measure the network integration, segregation, and their balance in the rs-FCN. Regional graph metrics reflecting the number of neighbors (degree centrality; DC), participation in the shortcuts (betweenness centrality; BC), and accessibility to intersections (eigenvector centrality; EC) in the rs-FCN defined group-level hubs for StD, HC, and MDD, separately. Global network metrics were comparable among the groups (all P > 0.05). Among the group-level hubs, regional graph metrics of left dorsal anterior insula (dAI), right dorsomedial prefrontal cortex (dmPFC), right rostral temporal thalamus, right precuneus, and left postcentral/middle temporal/anterior subgenual cingulate cortices were different among the groups. Further, significant associations with neurocognitive measures were found in the right dmPFC with SWMBE, and left dAI with SSTSSRT and RVPA'. Shorter OTSMLC5 was related to the lower centralities of right thalamus and suffer of recent 1-year suicidal ideation (all Ps < 0.05 in ≥ 2 centralities out of DC, BC, and EC). Collectively, salience and thalamic networks underlie spatial strategy and planning, response inhibition, and suicidality in StD and MDD. Anti-suicidal therapies targeting executive function and modulation of salience-thalamic network in StD and MDD are required.

Dissociable Effects of Alzheimer's Disease-Related Cognitive Dysfunction and Aging on Functional Brain Network Segregation

Alzheimer's disease (AD) is associated with changes in large-scale functional brain network organization. Individuals with AD exhibit less segregated resting-state brain networks compared with individuals without dementia. However, declines in brain network segregation are also evident as adult individuals grow older. Determining whether these observations reflect unique or overlapping alterations on the functional connectome of the brain is essential for understanding the impact of AD on network organization and incorporating measures of functional brain network organization toward AD characterization. Relationships between AD dementia severity and participant's age on resting-state brain system segregation were examined in 326 cognitively healthy and 275 cognitively impaired human individuals recruited through the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 601; age range, 55-96 years; 320 females). Greater dementia severity and increasing age were independently associated with lower brain system segregation. Further, dementia versus age relationships with brain network organization varied according to the processing roles of brain systems and types of network interactions. Aging was associated with alterations to association systems, primarily among within-system relationships. Conversely, dementia severity was associated with alterations that included both association systems and sensory-motor systems and was most prominent among cross-system interactions. Dementia-related network alterations were evident regardless of the presence of cortical amyloid burden, revealing that the measures of functional network organization are unique from this marker of AD-related pathology. Collectively, these observations demonstrate the specific and widespread alterations in the topological organization of large-scale brain networks that accompany AD and highlight functionally dissociable brain network vulnerabilities associated with AD-related cognitive dysfunction versus aging.SIGNIFICANCE STATEMENT Alzheimer's disease (AD)-associated cognitive dysfunction is hypothesized to be a consequence of brain network damage. It is unclear exactly how brain network alterations vary with dementia severity and whether they are distinct from alterations associated with aging. We evaluated functional brain network organization measured at rest among individuals who varied in age and dementia status. AD and aging exerted dissociable impacts on the brain's functional connectome. AD-associated brain network alterations were widespread and involved systems that subserve not only higher-order cognitive operations, but also sensory and motor operations. Notably, AD-related network alterations were independent of amyloid pathology. The research furthers our understanding of AD-related brain dysfunction and motivates refining existing frameworks of dementia characterization with measures of functional network organization.

Reduced Segregation of Brain Networks in Spatial Neglect After Stroke

Background/Purpose: To investigate the association between the degree of spatial neglect and the changes of brain system segregation (SyS; i.e., the ratio of the extent to which brain networks interact internally and with each other) after stroke. Methods: A cohort of 20 patients with right hemisphere lesion was submitted to neuropsychological assessment as well as to resting-state functional magnetic resonance imaging session at acute stage after stroke. The severity of spatial neglect was quantified using the Center of Cancellation (CoC) scores of the Bells cancellation test. For each patient, resting-state functional connectivity (FC) matrices were assessed by implementing a brain parcellation of nine networks that included the visual network, dorsal attention network (DAN), ventral attention network (VAN), sensorimotor network (SMN), auditory network, cingulo-opercular network, language network, frontoparietal network, and default mode network (DMN). For each patient and each network, we then computed the SyS derived by subtracting the between-network FC from the within-network FC (normalized by the within-network FC). Finally, for each network, the CoC scores were correlated with the SyS. Results: The correlational analyses indicated a negative association between CoC and SyS in the DAN, VAN, SMN, and DMN (q < 0.05 false discovery rate [FDR]-corrected). Patients with more severe spatial neglect exhibited lower SyS and vice versa. Conclusion: The loss of segregation in multiple and specific networks provides a functional framework for the deficits in spatial and nonspatial attention and motor/exploratory ability observed in neglect patients.

Cerebrovascular integrity affects gradients of aging-related dopamine D1 differences in the striatum

Extant research suggest aging-related losses of different dopaminergic markers, including presynaptic dopamine transporters as well as post-synaptic DA receptors. Given the central role of DA in neurocognitive functions, maintenance of a healthy DA system may be a key to mitigate age-related cognitive decline. Mechanisms behind DA losses in aging are however largely uncharted. Past research documented an association between dopaminergic integrity and cerebrovascular health (via white matter lesion volumes). However, it remains unclear whether proximity to lesions affected the spatial patterns of age-related D1DR differences within the striatum, and whether such differences are related to mnemonic function. Here, a large cohort of middle-aged to older healthy participants (age = 40-80 years, n = 119, 50 % women) was assessed for D1-receptor (D1DR) availability with positron emission tomography using [11C]SCH23390, and for white matter lesions using FLAIR-MRI. We found evidence for variations in degree of age-related differences along the ventro-dorsal axis, with more pronounced differences in the dorsal caudate. Further analyses revealed an association between distance to lesions and extent of D1DR losses in the caudate. Furthermore, D1DR differences in dorsal caudate (proximal to lesions) was more strongly associated with memory performance. In conclusion, the present findings suggest that maintenance of cerebrovascular health may be a key factor in promoting successful dopaminergic and memory aging.

Dopamine D1-signaling modulates maintenance of functional network segregation in aging

Past research has shown that as individuals age, there are decreases in within-network connectivity and increases in between-network connectivity, a pattern known as functional dedifferentiation. While the mechanisms behind reduced network segregation are not fully understood, evidence suggests that age-related differences in the dopamine (DA) system may play a key role. The DA D1-receptor (D1DR) is the most abundant and age-sensitive receptor subtype in the dopaminergic system, known to modulate synaptic activity and enhance the specificity of the neuronal signals. In this study from the DyNAMiC project (N = 180, 20-79y), we set out to investigate the interplay among age, functional connectivity, and dopamine D1DR availability. Using a novel application of multivariate Partial Least squares (PLS), we found that older age, and lower D1DR availability, were simultaneously associated with a pattern of decreased within-network and increased between-network connectivity. Individuals who expressed greater distinctiveness of large-scale networks exhibited more efficient working memory. In line with the maintenance hypotheses, we found that older individuals with greater D1DR in caudate exhibited less dedifferentiation of the connectome, and greater working memory, compared to their age-matched counterparts with less D1DR. These findings suggest that dopaminergic neurotransmission plays an important role in functional dedifferentiation in aging with consequences for working memory function at older age.

Synaptic resilience is associated with maintained cognition during ageing

INTRODUCTION

It remains unclear why age increases risk of Alzheimer's disease and why some people experience age-related cognitive decline in the absence of dementia. Here we test the hypothesis that resilience to molecular changes in synapses contribute to healthy cognitive ageing.

METHODS

We examined post-mortem brain tissue from people in mid-life (n = 15), healthy ageing with either maintained cognition (n = 9) or lifetime cognitive decline (n = 8), and Alzheimer's disease (n = 13). Synapses were examined with high resolution imaging, proteomics, and RNA sequencing. Stem cell-derived neurons were challenged with Alzheimer's brain homogenate.

RESULTS

Synaptic pathology increased, and expression of genes involved in synaptic signaling decreased between mid-life, healthy ageing and Alzheimer's. In contrast, brain tissue and neurons from people with maintained cognition during ageing exhibited decreases in synaptic signaling genes compared to people with cognitive decline.

DISCUSSION

Efficient synaptic networks without pathological protein accumulation may contribute to maintained cognition during ageing.

The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large-scale resting-state functional brain networks in aging

The literature on large-scale resting-state functional brain networks across the adult lifespan was systematically reviewed. Studies published between 1986 and July 2021 were retrieved from PubMed. After reviewing 2938 records, 144 studies were included. Results on 11 network measures were summarized and assessed for certainty of the evidence using a modified GRADE method. The evidence provides high certainty that older adults display reduced within-network and increased between-network functional connectivity. Older adults also show lower segregation, modularity, efficiency and hub function, and decreased lateralization and a posterior to anterior shift at rest. Higher-order functional networks reliably showed age differences, whereas primary sensory and motor networks showed more variable results. The inflection point for network changes is often the third or fourth decade of life. Age effects were found with moderate certainty for within- and between-network altered patterns and speed of dynamic connectivity. Research on within-subject bold variability and connectivity using glucose uptake provides low certainty of age differences but warrants further study. Taken together, these age-related changes may contribute to the cognitive decline often seen in older adults.

25 years of neurocognitive aging theories: What have we learned?

The past 25 years have provided a rich discovery of at least four fundamental patterns that represent structural and functional brain aging across multiple cognitive domains. Of the many potential patterns of brain aging, few are ever examined simultaneously in a given study, leading one to question their mutual exclusivity. Moreover, more studies are emerging that note failures to replicate some brain aging patterns, thereby questioning the universality and prevalence of these patterns. Although some attempts have been made to create unifying theories incorporating many of these age-related brain patterns, we propose that the field’s understanding of the aging brain has been hindered due to a large number of influential models with little crosstalk between them. We briefly review these brain patterns, the influential domain-general theories of neurocognitive aging that attempt to explain them, and provide examples of recent challenges to these theories. Lastly, we elaborate on improvements that can be made to lead the field to more comprehensive and robust models of neurocognitive aging.

DyNAMiC: A prospective longitudinal study of dopamine and brain connectomes: A new window into cognitive aging

Concomitant exploration of structural, functional, and neurochemical brain mechanisms underlying age-related cognitive decline is crucial in promoting healthy aging. Here, we present the DopamiNe, Age, connectoMe, and Cognition (DyNAMiC) project, a multimodal, prospective 5-year longitudinal study spanning the adult human lifespan. DyNAMiC examines age-related changes in the brain's structural and functional connectome in relation to changes in dopamine D1 receptor availability (D1DR), and their associations to cognitive decline. Critically, due to the complete lack of longitudinal D1DR data, the true trajectory of one of the most age-sensitive dopamine systems remains unknown. The first DyNAMiC wave included 180 healthy participants (20-80 years). Brain imaging included magnetic resonance imaging assessing brain structure (white matter, gray matter, iron), perfusion, and function (during rest and task), and positron emission tomography (PET) with the [11 C]SCH23390 radioligand. A subsample (n = 20, >65 years) was additionally scanned with [11 C]raclopride PET measuring D2DR. Age-related variation was evident for multiple modalities, such as D1DR; D2DR, and performance across the domains of episodic memory, working memory, and perceptual speed. Initial analyses demonstrated an inverted u-shaped association between D1DR and resting-state functional connectivity across cortical network nodes, such that regions with intermediate D1DR levels showed the highest levels of nodal strength. Evident within each age group, this is the first observation of such an association across the adult lifespan, suggesting that emergent functional architecture depends on underlying D1DR systems. Taken together, DyNAMiC is the largest D1DR study worldwide, and will enable a comprehensive examination of brain mechanisms underlying age-related cognitive decline.

White-Matter Integrity and Working Memory: Links to Aging and Dopamine-Related Genes

Working memory, a core function underlying many higher-level cognitive processes, requires cooperation of multiple brain regions. White matter refers to myelinated axons, which are critical to interregional brain communication. Past studies on the association between white-matter integrity and working memory have yielded mixed findings. Using voxelwise tract-based spatial statistics analysis, we investigated this relationship in a sample of 328 healthy adults from 25 to 80 years of age. Given the important role of dopamine (DA) in working-memory functioning and white matter, we also analyzed the effects of dopamine-related genes on them. There were associations between white-matter integrity and working memory in multiple tracts, indicating that working-memory functioning relies on global connections between different brain areas across the adult life span. Moreover, a mediation analysis suggested that white-matter integrity contributes to age-related differences in working memory. Finally, there was an effect of the COMT Val158Met polymorphism on white-matter integrity, such that Val/Val carriers had lower fractional anisotropy values than any Met carriers in the internal capsule, corona radiata, and posterior thalamic radiation. As this polymorphism has been associated with dopaminergic tone in the prefrontal cortex, this result provides evidence for a link between DA neurotransmission and white matter. Together, the results support a link between white-matter integrity and working memory, and provide evidence for its interplay with age- and DA-related genes.

Association of APOE ɛ4 and Plasma p-tau181 with Preclinical Alzheimer’s Disease and Longitudinal Change in Hippocampus Function

Background: The Apolipoprotein E (APOE) ɛ4 allele has been linked to increased tau phosphorylation and tangle formation. APOE ɛ4 carriers with elevated tau might be at the higher risk for AD progression. Previous studies showed that tau pathology begins early in areas of the medial temporal lobe. Similarly, APOE ɛ4 carriers showed altered hippocampal functional integrity. However, it remains unknown whether elevated tau accumulation on hippocampal functional changes would be more pronounced for APOE ɛ4 carriers. Objective: We related ɛ4 carriage to levels of plasma phosphorylated tau (p-tau181) up to 15 years prior to AD onset. Furthermore, elevated p-tau181 was explored in relation to longitudinal changes in hippocampal function and connectivity. Methods: Longitudinal population-based study. Plasma p-tau181 was analyzed in 142 clinically defined Alzheimer’s disease (AD) cases and 126 controls. The longitudinal analysis involved 87 non-demented individuals with two waves of plasma samples and three waves of functional magnetic resonance imaging during rest and memory encoding. Results: Increased p-tau181 was observed for both ɛ4 carriers and non-carriers close to AD, but exclusively for ɛ4 carriers in the early preclinical groups (7- and 13-years pre-AD). In ɛ4 carriers, longitudinal p-tau181 increase was paralleled by elevated local hippocampal connectivity at rest and subsequent reduction of hippocampus encoding-related activity. Conclusion: Our findings support an association of APOE ɛ4 and p-tau181 with preclinical AD and hippocampus functioning.