Age-related Changes In Brain Structure Research Articles

Dataset factors associated with age-related changes in brain structure and function in neurodevelopmental conditions.

With brain structure and function undergoing complex changes throughout childhood and adolescence, age is a critical consideration in neuroimaging studies, particularly for those of individuals with neurodevelopmental conditions. However, despite the increasing use of large, consortium-based datasets to examine brain structure and function in neurotypical and neurodivergent populations, it is unclear whether age-related changes are consistent between datasets and whether inconsistencies related to differences in sample characteristics, such as demographics and phenotypic features, exist. To address this, we built models of age-related changes of brain structure (regional cortical thickness and regional surface area; N = 1218) and function (resting-state functional connectivity strength; N = 1254) in two neurodiverse datasets: the Province of Ontario Neurodevelopmental Network and the Healthy Brain Network. We examined whether deviations from these models differed between the datasets, and explored whether these deviations were associated with demographic and clinical variables. We found significant differences between the two datasets for measures of cortical surface area and functional connectivity strength throughout the brain. For regional measures of cortical surface area, the patterns of differences were associated with race/ethnicity, while for functional connectivity strength, positive associations were observed with head motion. Our findings highlight that patterns of age-related changes in the brain may be influenced by demographic and phenotypic characteristics, and thus future studies should consider these when examining or controlling for age effects in analyses.

Superagers Resist Typical Age-Related White Matter Structural Changes.

Superagers are elderly individuals with the memory ability of people 30 years younger and provide evidence that age-related cognitive decline is not inevitable. In a sample of 64 superagers (mean age, 81.9; 59% women) and 55 typical older adults (mean age, 82.4; 64% women) from the Vallecas Project, we studied, cross-sectionally and longitudinally over 5 years with yearly follow-ups, the global cerebral white matter status as well as region-specific white matter microstructure assessment derived from diffusivity measures. Superagers and typical older adults showed no difference in global white matter health (total white matter volume, Fazekas score, and lesions volume) cross-sectionally or longitudinally. However, analyses of diffusion parameters revealed the better white matter microstructure in superagers than in typical older adults. Cross-sectional differences showed higher fractional anisotropy (FA) in superagers mostly in frontal fibers and lower mean diffusivity (MD) in most white matter tracts, expressed as an anteroposterior gradient with greater group differences in anterior tracts. FA decrease over time is slower in superagers than in typical older adults in all white matter tracts assessed, which is mirrored by MD increases over time being slower in superagers than in typical older adults in all white matter tracts except for the corticospinal tract, the uncinate fasciculus, and the forceps minor. The better preservation of white matter microstructure in superagers relative to typical older adults supports resistance to age-related brain structural changes as a mechanism underpinning the remarkable memory capacity of superagers, while their regional aging pattern is in line with the last-in-first-out hypothesis.

Structural MRI analysis of age-related changes and sex differences in marmoset brain volume

The field of aging biology, which aims to extend healthy lifespans and prevent age-related diseases, has turned its focus to the Callithrix jacchus (common marmoset) to understand the aging process better. This study utilized magnetic resonance imaging (MRI) to non-invasively analyze the brains of 216 marmosets, investigating age-related changes in brain structure; the relationship between body weight and brain volume; and potential differences between males and females. The key findings revealed that, similar to humans, Callithrix jacchus experiences a reduction in total intracranial volume, cortex, subcortex, thalamus, and cingulate volumes as they age, highlighting site-dependent changes in brain tissue. Notably, the study also uncovered sex differences in cerebellar volume. These insights into the structural connectivity and volumetric changes in the marmoset brain throughout aging contribute to accumulating valuable knowledge in the field, promising to inform future aging research and interventions for enhancing healthspan.

Does the Relationship between Age and Brain Structure Differ in Youth with Conduct Disorder?

Conduct disorder (CD) is characterised by persistent antisocial and aggressive behaviour and typically emerges in childhood or adolescence. Although several authors have proposed that CD is a neurodevelopmental disorder, very little evidence is available about brain development in this condition. Structural brain alterations have been observed in CD, and some indirect evidence for delayed brain maturation has been reported. However, no detailed analysis of age-related changes in brain structure in youth with CD has been conducted. Using cross-sectional MRI data, this study aimed to explore differences in brain maturation in youth with CD versus healthy controls to provide further understanding of the neurodevelopmental processes underlying CD. 291 CD cases (153 males) and 379 healthy controls (160 males) aged 9–18 years (Mage = 14.4) were selected from the European multisite FemNAT-CD study. Structural MRI scans were analysed using surface-based morphometry followed by application of the ENIGMA quality control protocols. An atlas-based approach was used to investigate group differences and test for group-by-age and group-by-age-by-sex interactions in cortical thickness, surface area and subcortical volumes. Relative to healthy controls, the CD group showed lower surface area across frontal, temporal and parietal regions as well as lower total surface area. No significant group-by-age or group-by-age-by-sex interactions were observed on any brain structure measure. These findings suggest that CD is associated with lower surface area across multiple cortical regions, but do not support the idea that CD is associated with delayed brain maturation, at least within the age bracket considered here.

A joint ventricle and WMH segmentation from MRI for evaluation of healthy and pathological changes in the aging brain.

Age-related changes in brain structure include atrophy of the brain parenchyma and white matter changes of presumed vascular origin. Enlargement of the ventricles may occur due to atrophy or impaired cerebrospinal fluid (CSF) circulation. The co-occurrence of these changes in neurodegenerative diseases and in aging brains often requires investigators to take both into account when studying the brain, however, automated segmentation of enlarged ventricles and white matter hyperintensities (WMHs) can be a challenging task. Here, we present a hybrid multi-atlas segmentation and convolutional autoencoder approach for joint ventricle parcellation and WMH segmentation from magnetic resonance images (MRIs). Our fully automated approach uses a convolutional autoencoder to generate a standardized image of grey matter, white matter, CSF, and WMHs, which, in conjunction with labels generated by a multi-atlas segmentation approach, is then fed into a convolutional neural network to parcellate the ventricular system. Hence, our approach does not depend on manually delineated training data for new data sets. The segmentation pipeline was validated on both healthy elderly subjects and subjects with normal pressure hydrocephalus using ground truth manual labels and compared with state-of-the-art segmentation methods. We then applied the method to a cohort of 2401 elderly brains to investigate associations of ventricle volume and WMH load with various demographics and clinical biomarkers, using a multiple regression model. Our results indicate that the ventricle volume and WMH load are both highly variable in a cohort of elderly subjects and there is an independent association between the two, which highlights the importance of taking both the possibility of enlarged ventricles and WMHs into account when studying the aging brain.

Brain age and cognitive functioning in first-episode bipolar disorder.

There is significant heterogeneity in cognitive function in patients with bipolar I disorder (BDI); however, there is a dearth of research into biological mechanisms that might underlie cognitive heterogeneity, especially at disease onset. To this end, this study investigated the association between accelerated or delayed age-related brain structural changes and cognition in early-stage BDI. First episode patients with BDI (n = 80) underwent cognitive assessment to yield demographically normed composite global and domain-specific scores in verbal memory, non-verbal memory, working memory, processing speed, attention, and executive functioning. Structural magnetic resonance imaging data were also collected from all participants and subjected to machine learning to compute the brain-predicted age difference (brainPAD), calculated by subtracting chronological age from age predicted by neuroimaging data (positive brainPAD values indicating age-related acceleration in brain structural changes and negative values indicating delay). Patients were divided into tertiles based on brainPAD values, and cognitive performance compared amongst tertiles with ANCOVA. Patients in the lowest (delayed) tertile of brainPAD values (brainPAD range -17.9 to -6.5 years) had significantly lower global cognitive scores (p = 0.025) compared to patients in the age-congruent tertile (brainPAD range -5.3 to 2.4 yrs), and significantly lower verbal memory scores (p = 0.001) compared to the age-congruent and accelerated (brainPAD range 2.8 to 16.1 yrs) tertiles. These results provide evidence linking cognitive dysfunction in the early stage of BDI to apparent delay in typical age-related brain changes. Further studies are required to assess how age-related brain changes and cognitive functioning evolve over time.

P85. Sex Differences in Regional Patterns of Brain-Age-Gap Estimates

Neuroimaging studies have been instrumental in identifying sex-differences in brain structure, and there is robust evidence for age-related changes in brain structure throughout the lifespan. However, the literature on sex-differences in regional patterns of age-related changes in young adulthood remains limited. To address this, we availed of a machine learning model to obtain local brain-age-gap estimates (L-brainAGE), which reflect voxel-wise differences between an individual’s chronological and biological brain age.

P169. Brain Age and Cognitive Functioning in First Episode Bipolar Disorder

Cognitive deficits are detectable from illness onset in bipolar I disorder (BDI). There is significant heterogeneity in cognitive functioning in this cohort, suggesting potential differences in underlying biological mechanisms. This study investigated whether accelerated or delayed age-related brain structural changes are associated with cognitive functioning in first episode BDI.

The regulatory mechanisms of behavioral and cognitive aging.

With the increase of life expectancy, the world's population is aging rapidly. Previous work in the field of aging greatly increases our understanding of biological mechanisms underlying longevity. Researchers have unraveled a number of longevity pathways conserved from yeast to mammals. However, recent evidence shows that mechanisms regulating the life span and those regulating age-related behavioral decline could be dissociated. The regulatory mechanisms underlying behavioral and cognitive aging is largely unknown. Previous work has described a significant age-related decline in cognitive behaviors including episodic memory, working memory, processing speed, as well as motor function deterioration and circadian dysfunction. With the advance of neuroscience and technology, more and more studies have focused on the age-related changes in structure and function of the brain. In this review, we briefly describe the deterioration of cognitive function and other behaviors in the aging process, and survey the role of age-related changes in brain structure and network, neuron morphology and function, transcriptome in brain and some conserved biological pathways on age-related cognitive and behavioral decline. Further studies on the mechanisms underpinning age-related cognitive and behavioral decline may provide clues not only for improving the quality of life for the ageing population, but also for developing intervention approaches for neurodegenerative diseases.

Two-Year Follow-Up Study of the Relationship Between Brain Structure and Cognitive Control Function Across the Adult Lifespan.

Age-related decline in cognitive control and general slowing are prominent phenomena in aging research. These declines in cognitive functions have been shown to also involve age-related decline in brain structure. However, most evidence in support of these associations is based on cross-sectional data. Therefore, the aim of this study is to contrast cross-sectional and longitudinal analyses to re-examine if the relationship between age-related brain structure and cognitive function are similar between the two approaches. One hundred and two participants completed two sessions with an average interval of 2 years. All participants were assessed by questionnaires, a series of cognitive tasks, and they all underwent neuroimaging acquisition. The main results of this study show that the majority of the conclusions regarding age effect in cognitive control function and processing speed in the literature can be replicated based on the cross-sectional data. Conversely, when we followed up individuals over an average interval of 2 years, then we found much fewer significant relationships between age-related change in gray matter structure of the cognitive control network and age-related change in cognitive control function. Furthermore, there was no “initial age” effect in the relationships between age-related changes in brain structure and cognitive function. This finding suggests that the “aging” relationship between brain structure and cognitive function over a short period of time are independent of “initial age” difference at time point 1. The result of this study warrants the importance of longitudinal research for aging studies to elucidate actual aging processes on cognitive control function.

Generalizing Longitudinal Age Effects on Brain Structure - A Two-Study Comparison Approach.

Cross-sectional studies indicate that normal aging is accompanied by decreases in brain structure. Longitudinal studies, however, are relatively rare and inconsistent regarding their outcomes. Particularly the heterogeneity of methods, sample characteristics and the high inter-individual variability in older adults prevent the deduction of general trends. Therefore, the current study aimed to compare longitudinal age-related changes in brain structure (measured through cortical thickness) in two large independent samples of healthy older adults (n = 161 each); the Longitudinal Healthy Aging Brain (LHAB) database project at the University of Zurich, Switzerland, and 1000BRAINS at the Research Center Juelich, Germany. Annual percentage changes in the two samples revealed stable to slight decreases in cortical thickness over time. After correction for major covariates, i.e., baseline age, sex, education, and image quality, sample differences were only marginally present. Results suggest that general trends across time might be generalizable over independent samples, assuming the same methodology is used, and similar sample characteristics are present.

Brain structure and parasympathetic function during rest and stress in young adult women.

Heart rate variability (HRV) is an important biomarker for parasympathetic function and future health outcomes. The present study examined how the structure of regions in a neural network thought to maintain top-down control of parasympathetic function is associated with HRV during both rest and social stress. Participants were 127 young women (90 Black American), who completed a structural MRI scan and the Trier Social Stress Test (TSST), during which heart rate was recorded. Regression analyses were used to evaluate associations between cortical thickness in five regions of the Central Autonomic Network (CAN; anterior midcingulate cortex [aMCC], pregenual and subgenual anterior cingulate cortex [pgACC, sgACC], orbitofrontal cortex [OFC], and anterior insula) and high-frequency HRV during rest and stress. Results indicated that cortical thickness in CAN regions did not predict average HRV during rest or stress. Greater cortical thickness in the right pgACC was associated with greater peak HRV reactivity during the TSST, and survived correction for multiple comparisons, but not sensitivity analyses with outliers removed. The positive association between cortical thickness in the pgACC and peak HRV reactivity is consistent with the direction of previous findings from studies that examined tonic HRV in adolescents, but inconsistent with findings in adults, which suggests a possible neurodevelopmental shift in the relation between brain structure and autonomic function with age. Future research on age-related changes in brain structure and autonomic function would allow a more thorough understanding of how brain structure may contribute to parasympathetic function across neurodevelopment.

Single-neuron dynamical effects of dendritic pruning implicated in aging and neurodegeneration: towards a measure of neuronal reserve

Aging is a main risk factor for neurodegenerative disorders including Alzheimer's disease. It is often accompanied by reduced cognitive functions, gray-matter volume, and dendritic integrity. Although age-related brain structural changes have been observed across multiple scales, their functional implications remain largely unknown. Here we simulate the aging effects on neuronal morphology as dendritic pruning and characterize its dynamical implications. Utilizing a detailed computational modeling approach, we simulate the dynamics of digitally reconstructed neurons obtained from Neuromorpho.org. We show that dendritic pruning affects neuronal integrity: firing rate is reduced, causing a reduction in energy consumption, energy efficiency, and dynamic range. Pruned neurons require less energy but their function is often impaired, which can explain the diminished ability to distinguish between similar experiences (pattern separation) in older people. Our measures indicate that the resilience of neuronal dynamics is neuron-specific, heterogeneous, and strongly affected by dendritic topology and the position of the soma. Based on the emergent neuronal dynamics, we propose to classify the effects of dendritic deterioration, and put forward a topological measure of “neuronal reserve” that quantifies the resilience of neuronal dynamics to dendritic pruning. Moreover, our findings suggest that increasing dendritic excitability could partially mitigate the dynamical effects of aging.

CHILDHOOD SES AND AGE-RELATED BRAIN CHANGES RACIALLY-ETHNICALLY DIVERSE OLDER ADULTS

Socioeconomic disadvantages in childhood has been linked to dementia in late life. However, the underlying pathways through which childhood socioeconomic status (CSES) affects health in old age is unclear. CSES has been linked to age-related differences in regions affected by Alzheimer’s disease (AD; e.g., hippocampus). CSES varies across race/ethnicity; It is critical to examine the relationship between CSES and age-related brain structural changes across diverse aging populations. We used an established proxy for CSES, number of siblings (i.e., sibship size), to examine whether CSES buffered age-related changes in hippocampal volume in a community-based sample of racially/ethnically diverse older adults. Sibship size moderated age-related differences in hippocampal volume in Whites (β=-5.61[-11.09,-0.12]), but not in Blacks and Hispanics. Results indicate that Whites with no sibling (vs. Whites with siblings) show less age-related difference in hippocampal volume. Future analyses will examine other CSES factors (i.e., parental education/occupation) on age-related structural changes across race/ethnicity.

Corticosteroids and Regional Variations in Thickness of the Human Cerebral Cortex across the Lifespan.

Exposures to life stressors accumulate across the lifespan, with possible impact on brain health. Little is known, however, about the mechanisms mediating age-related changes in brain structure. We use a lifespan sample of participants (n = 21 251; 4–97 years) to investigate the relationship between the thickness of cerebral cortex and the expression of the glucocorticoid- and the mineralocorticoid-receptor genes (NR3C1 and NR3C2, respectively), obtained from the Allen Human Brain Atlas. In all participants, cortical thickness correlated negatively with the expression of both NR3C1 and NR3C2 across 34 cortical regions. The magnitude of this correlation varied across the lifespan. From childhood through early adulthood, the profile similarity (between NR3C1/NR3C2 expression and thickness) increased with age. Conversely, both profile similarities decreased with age in late life. These variations do not reflect age-related changes in NR3C1 and NR3C2 expression, as observed in 5 databases of gene expression in the human cerebral cortex (502 donors). Based on the co-expression of NR3C1 (and NR3C2) with genes specific to neural cell types, we determine the potential involvement of microglia, astrocytes, and CA1 pyramidal cells in mediating the relationship between corticosteroid exposure and cortical thickness. Therefore, corticosteroids may influence brain structure to a variable degree throughout life.

Identifying predictors of within-person variance in MRI-based brain volume estimates

Adequate reliability of measurement is a precondition for investigating individual differences and age-related changes in brain structure. One approach to improve reliability is to identify and control for variables that are predictive of within-person variance. To this end, we applied both classical statistical methods and machine-learning-inspired approaches to structural magnetic resonance imaging (sMRI) data of six participants aged 24–31 years gathered at 40–50 occasions distributed over 6–8 months from the Day2day study. We explored the within-person associations between 21 variables covering physiological, affective, social, and environmental factors and global measures of brain volume estimated by VBM8 and FreeSurfer. Time since the first scan was reliably associated with Freesurfer estimates of grey matter volume and total cortex volume, in line with a rate of annual brain volume shrinkage of about 1 percent. For the same two structural measures, time of day also emerged as a reliable predictor with an estimated diurnal volume decrease of, again, about 1 percent. Furthermore, we found weak predictive evidence for the number of steps taken on the previous day and testosterone levels. The results suggest a need to control for time-of-day effects in sMRI research. In particular, we recommend that researchers interested in assessing longitudinal change in the context of intervention studies or longitudinal panels make sure that, at each measurement occasion, (a) a given participant is measured at the same time of day; (b) all participants are measured at about the same time of day. Furthermore, the potential effects of physical activity, including moderate amounts of aerobic exercise, and testosterone levels on MRI-based measures of brain structure deserve further investigation.

Erasure of striatal chondroitin sulfate proteoglycan-associated extracellular matrix rescues aging-dependent decline of motor learning.

Cognitive decline is a feature of aging. Accumulating evidence suggests that the brain extracellular matrix (ECM) is involved in the process of aging-dependent cognitive impairment and neurodegeneration by regulating synaptic neurotransmission and affecting neuroplasticity. Age-related changes in brain structure and cognition are not uniform across the whole brain. Being one of the most vulnerable brain regions to aging-dependent alterations, striatum is integral to several central nervous system functions, such as motor, cognition, and affective control. However, the striatal ECM is largely understudied. We first describe 2 major types of chondroitin sulfate proteoglycan (CSPG)-associated ECM in striatum: perineuronal nets and diffusive ECM. Both types of ECM accumulate in an aging-dependent manner. The accumulation of CSPG-associated ECM correlates with aging-dependent decline in striatum-related cognitive functions, including motor learning and working memory. Enzymatic depletion of CSPG-associated ECM in aged mice via chondroitinase ABC significantly improves motor learning, suggesting that changes in neural ECM CSPGs regulate striatal plasticity. Our study provides a greater understanding of the role of neural ECM underlying striatal plasticity, which is an important precursor to design appropriate therapeutic strategies for normal and pathologic aging.

Localizing Age-Related Changes in Brain Structure Using Voxel-Based Morphometry.

Aim. We report the dynamic anatomical sequence of human cortical gray matter development from late childhood to young adults using VBM and ROI-based methods. Method. The structural MRI of 91 normal individuals ranging in age from 6 to 26 years was obtained and the GMV for each region was measured. Results. Our results showed that the earliest loss of GMV occurred in left olfactory, right precuneus, caudate, left putamen, pallidum, and left middle temporal gyrus. In addition, the trajectory of maturational and aging showed a linear decline in GMV on both cortical lobes and subcortical regions. The most loss of gray matter was observed in the parietal lobe and basal ganglia, whereas the less loss occurred in the temporal lobe and hippocampus, especially in the left middle temporal pole, which showed no decline until 26 years old. Moreover, the volumes of GM, WM, and CSF were also assessed for linear age effects, showing a significant linear decline in GM with age and a significant linear increase in both WM and CSF with age. Interpretation. Overall, our findings lend support to previous findings of the normal brain development of regional cortex, and they may help in understanding of neurodevelopmental disorders.

Gender-Specific Degeneration of Dementia-Related Subcortical Structures Throughout the Lifespan.

Age-related changes in brain structure are a question of interest to a broad field of research. Structural decline has been consistently, but not unambiguously, linked to functional consequences, including cognitive impairment and dementia. One of the areas considered of crucial importance throughout this process is the medial temporal lobe, and primarily the hippocampal region. Gender also has a considerable effect on volume deterioration of subcortical grey matter (GM) structures, such as the hippocampus. The influence of age×gender interaction on disproportionate GM volume changes might be mediated by hormonal effects on the brain. Hippocampal volume loss appears to become accelerated in the postmenopausal period. This decline might have significant influences on neuroplasticity in the CA1 region of the hippocampus highly vulnerable to pathological influences. Additionally, menopause has been associated with critical pathobiochemical changes involved in neurodegeneration. The micro- and macrostructural alterations and consequent functional deterioration of critical hippocampal regions might result in clinical cognitive impairment-especially if there already is a decline in the cognitive reserve capacity. Several lines of potential vulnerability factors appear to interact in the menopausal period eventually leading to cognitive decline, mild cognitive impairment, or Alzheimer's disease. This focused review aims to delineate the influence of unmodifiable risk factors of neurodegenerative processes, i.e., age and gender, on critical subcortical GM structures in the light of brain derived estrogen effects. The menopausal period appears to be of key importance for the risk of cognitive decline representing a time of special vulnerability for molecular, structural, and functional influences and offering only a narrow window for potential protective effects.

The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample

This paper describes the data repository for the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) initial study cohort. The Cam-CAN Stage 2 repository contains multi-modal (MRI, MEG, and cognitive-behavioural) data from a large (approximately N=700), cross-sectional adult lifespan (18–87years old) population-based sample. The study is designed to characterise age-related changes in cognition and brain structure and function, and to uncover the neurocognitive mechanisms that support healthy cognitive ageing. The database contains raw and preprocessed structural MRI, functional MRI (active tasks and resting state), and MEG data (active tasks and resting state), as well as derived scores from cognitive behavioural experiments spanning five broad domains (attention, emotion, action, language, and memory), and demographic and neuropsychological data. The dataset thus provides a depth of neurocognitive phenotyping that is currently unparalleled, enabling integrative analyses of age-related changes in brain structure, brain function, and cognition, and providing a testbed for novel analyses of multi-modal neuroimaging data.