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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.

Radiomics has made considerable progress in neurodegenerative diseases. However, previous studies only explored the feasibility of radiomics in clinical applications. Therefore, the objective of this study was to obtain the most relevant radiomics features with the aging changes of myelin proteins and compare their diagnostic performances with the diffusion tensor imaging (DTI) parameters to identify the reliability of these features as imaging biomarkers for assessing brain aging. Thirty middle-aged and thirty old-aged mice were assigned to the training set to explore the most relevant features of myelin proteins and their diagnostic performances. Ten middle-aged and ten old-aged mice were assigned to the testing set to further validate the reproducibility of the features. T2-weighted imaging and DTI were conducted to obtain white matter radiomics features and DTI parameters. Myelin proteins, including proteolipid protein (PLP) and myelin basic protein (MBP), were examined by immunofluorescence staining in the regions of the whole brain, cortex, corpus callosum, striatum, and anterior commissure. The Pearson correlation analysis was used to observe the correlations between radiomics features and myelin proteins. The four most relevant features with the top four correlation coefficients were selected to compare their diagnostic performances with the DTI parameters, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AxD), and radial diffusivity (RD). Wavelet-HLL_glszm_ZoneEntropy, wavelet-HLL_gldm_DependenceEntropy, wavelet-LHL_glszm_ZoneEntropy, and log-sigma-2-0-mm-3D_gldm_DependenceEntropy were the four most relevant features, which had moderately significant correlations with PLP. The area under the receiver operating characteristic curves (AUC) of the four features were 0.940, 0.917, 0.831, and 0.964 in the training set, and 0.880, 0.840, 0.860, and 0.880 in the testing set. The AUCs of FA, MD, AxD, and RD were 0.864, 0.743, 0.673, and 0.778 in the training set, and 0.780, 0.710, 0.670, and 0.730 in the testing set. These results demonstrated that radiomics features of white matter displayed significant correlations with myelin proteins and their performances were comparable or even superior to DTI parameters, which ensured their reliability as non-invasive imaging biomarkers for evaluating brain aging.

Background: Aging is associated with multiple neurodegenerative conditions that severely limit quality of life and can shorten lifespan. Studies in rodents indicate that in addition to extending lifespan, the ketogenic diet (KD) improves cognitive function in aged animals, yet long term adherence to KD in Humans is poor. Objectives: To broadly investigate what mechanisms might be activated in the brain in response to ketogenic diet. Methods: We conducted transcriptome wide analysis on whole brain samples from 13-month-old mice, 13-month-old mice fed a ketogenic diet for 1 month, 26-month-old mice, and 26-month-old mice fed a ketogenic diet for 14 months. Results: As expected, analysis of differently expressed genes between the old (26 month) vs younger mice (13 month) showed clear activation of inflammation and complement system pathways with aging. Analysis between the 26-month-old animals fed ketogenic diet for 14 months with 26-month-old animals fed control diet indicate that long-term KD resulted in activation of LRP, TCF7L2 (WNT pathway), and IGF1 signaling. There was also a significant increase in the expression of SOX2-dependent oligodendrocyte/myelination markers, though TCF7L2 and SOX2 dependent gene sets were largely overlapping. Remarkably, the effect of 1 month of ketogenic diet was minimal and there was no congruence between gene expression effects of short-term KD vs long-term KD. Conclusions: This work informs target identification efforts for aging and neurodegenerative disorder therapeutics discovery while also establishing differential effects of short-term vs long-term KD on gene expression in the brain.

Background: : Preventing or reducing the risk of cognitive decline and dementia is of great public health interest. Longitudinal data from diverse samples are needed to properly inform clinicians, researchers, and policy makers. CAN-PROTECT is a recently launched online observational cohort study that assesses factors contributing to both risk for incident cognitive decline and dementia and resilience against brain aging, in participants across the lifespan. Methods: : Measures of cognition, behaviour, and quality of life administered to both participants and study partners were compared using partial Spearman correlations adjusted for participant and study partner age, sex, and education. In participants, relationships between cognition, behaviour, function, and quality of life were examined using adjusted multivariable linear and negative binomial regression models. Results: : In the first three-month window, 2150 participants spanning all Canadian provinces enrolled; 637 nominated study partners had already completed assessments. Engagement with the study was excellent, with many optional assessments completed. Initial analyses demonstrated relationships between cognition, behaviour, function, and quality of life. Discussion: : These preliminary results speak to the utility and feasibility of CAN-PROTECT to obtain data relevant to brain health, highlighting the public interest in participating in studies on cognition. The online portal facilitated participation of a geographically diverse sample. This group is ideal to study brain aging, dementia prevention, and early detection of neurodegenerative disease. Longitudinal data will provide additional insights. Several features of CAN-PROTECT are important to consider in terms of assessing risk and resilience in Canadians, and for further development and recruitment of a research-ready cohort.

As people live longer, the burden of aging-related brain diseases, especially dementia, is increasing. Brain aging increases the risk of cognitive impairment, which manifests as a progressive loss of neuron function caused by the impairment of synaptic plasticity via disrupting lipid homeostasis. Therefore, supplemental dietary lipids have the potential to prevent brain aging. This review summarizes the important roles of dietary lipids in brain function from both structure and mechanism perspectives. Epidemiological and animal studies have provided evidence of the functions of polyunsaturated fatty acids (PUFAs) in brain health. The results of interventions indicate that phospholipids—including phosphatidylcholine, phosphatidylserine, and plasmalogen—are efficient in alleviating cognitive impairment during aging, with plasmalogen exhibiting higher efficacy than phosphatidylserine. Plasmalogen is a recognized nutrient used in clinical trials due to its special vinyl ether bonds and abundance in the postsynaptic membrane of neurons. Future research should determine the dose-dependent effects of plasmalogen in alleviating brain-aging diseases and should develop extraction and storage procedures for its clinical application.

White matter (WM) development has been studied extensively, but most studies used cross-sectional data, and to the best of our knowledge, none of them considered the possible effects of biological (vs. chronological) age. Therefore, we conducted a longitudinal multimodal study of WM development and studied changes in fractional anisotropy (FA) in the different WM tracts and their relationship with cortical thickness-based measures of brain aging in young adulthood. A total of 105 participants from the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) prenatal birth cohort underwent magnetic resonance imaging (MRI) at the age of 23-24, and the age of 28-30 years. At both time points, FA in the different WM tracts was extracted using the JHU atlas, and brain age gap estimate (BrainAGE) was calculated using the Neuroanatomical Age Prediction using R (NAPR) model based on cortical thickness maps. Changes in FA and the speed of cortical brain aging were calculated as the difference between the respective variables in the late vs. early 20s. We demonstrated tract-specific increases as well as decreases in FA, which indicate that the WM microstructure continues to develop in the third decade of life. Moreover, the significant interaction between the speed of cortical brain aging, tract, and sex on mean FA revealed that a greater speed of cortical brain aging in young adulthood predicted greater decreases in FA in the bilateral cingulum and left superior longitudinal fasciculus in young adult men. Overall, these changes in FA in the WM tracts in young adulthood point out the protracted development of WM microstructure, particularly in men.

As an important biomarker of neural aging, the brain age reflects the integrity and health of the human brain. Accurate prediction of brain age could help to understand the underlying mechanism of neural aging. In this study, a cross-stratified ensemble learning algorithm with staking strategy was proposed to obtain brain age and the derived predicted age difference (PAD) using T1-weighted magnetic resonance imaging (MRI) data. The approach was characterized as by implementing two modules: one was three base learners of 3D-DenseNet, 3D-ResNeXt, 3D-Inception-v4; another was 14 secondary learners of liner regressions. To evaluate performance, our method was compared with single base learners, regular ensemble learning algorithms, and state-of-the-art (SOTA) methods. The results demonstrated that our proposed model outperformed others models, with three metrics of mean absolute error (MAE), root mean-squared error (RMSE), and coefficient of determination (R2) of 2.9405 years, 3.9458 years, and 0.9597, respectively. Furthermore, there existed significant differences in PAD among the three groups of normal control (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD), with an increased trend across NC, MCI, and AD. It was concluded that the proposed algorithm could be effectively used in computing brain aging and PAD, and offering potential for early diagnosis and assessment of normal brain aging and AD.

During aging, the brain is subject to greater oxidative stress (OS), which is thought to play a critical role in cognitive impairment. Glutathione (GSH), as a major antioxidant in the brain, can be used to combat OS. However, how brain GSH levels vary with age and their associations with cognitive function is unclear. In this study, we combined point-resolved spectroscopy and edited spectroscopy sequences to investigate extended and closed forms GSH levels in the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and occipital cortex (OC) of 276 healthy participants (extended form, 166 females, age range 20–70 years) and 15 healthy participants (closed form, 7 females, age range 26–56 years), and examined their relationships with age and cognitive function. The results revealed decreased extended form GSH levels with age in the PCC among 276 participants. Notably, the timecourse of extended form GSH level changes in the PCC and ACC differed between males and females. Additionally, positive correlations were observed between extended form GSH levels in the PCC and OC and visuospatial memory. Additionally, a decreased trend of closed form GSH levels with age was also observed in the PCC among 15 participants. Taken together, these findings enhance our understanding of the brain both closed and extended form GSH time course during normal aging and associations with sex and memory, which is an essential first step for understanding the neurochemical underpinnings of healthy aging.

The brain is a complex, dynamic organ that shows differences in the same subject at various periods. Understanding how brain activity changes across age as a function of the brain networks has been greatly abetted by fMRI. Canonical analysis consists of determining how alterations in connectivity patterns (CPs) of certain regions are affected. An alternative approach is taken here by not considering connectivity but rather features computed from recordings at the regions of interest (ROIs). Using machine learning (ML) we assess how neural signals are altered by and prospectively predictive of age and sex via a methodology that is novel in drawing upon pairwise classification across six decades of subjects’ chronological ages. ML is used to answer the equally important questions of what properties of the computed features are most predictive as well as which brain networks are most affected by aging. It was found that there is decreased differentiation among the neural signals of older subjects that are separated in age by the same number of years as younger subjects. Furthermore, the burstiness of the signals change at different rates between males and females. The findings provide insight into brain aging via an ROI-based analysis, the consideration of several feature groups, and a novel classification-based ML pipeline. There is also a contribution to understanding the effects of data aggregated from different recording centers on the conclusions of fMRI studies.

Background: Age-related changes in brain structure may constitute the starting point for cerebral function alteration. Physical activity (PA) demonstrated favorable associations with total brain volume, but its relationship with cortical thickness (CT) remains unclear. We investigated the cross-sectional associations between PA level and CT in community-dwelling people aged 70 years and older. Methods: A total of 403 older adults aged 74.8 ± 4.0 years (mean ± SD) who underwent a baseline magnetic resonance imaging examination and who had data on PA and confounders were included. PA was assessed with a questionnaire. Participants were categorized according to PA levels. Multiple linear regressions were used to compare the brain CT (mm) of the inactive group (no PA at all) with 6 active groups (growing PA levels) in 34 regions of interest. Results: Compared with inactive persons, people who achieved PA at a level of 1500−1999 metabolic equivalent task-min/week (i.e., about 6−7 h of brisk walking for exercise and those who achieved it at 2000−2999 metabolic equivalent task-min/week (i.e., 8−11 h of brisk walking for exercise) had higher CT in the fusiform gyrus and the temporal pole. Additionally, dose−response associations between PA and CT were found in the fusiform gyrus (B = 0.011, SE = 0.004, adj. p = 0.035), the temporal pole (B = 0.026, SE = 0.009, adj. p = 0.048), and the caudal middle frontal gyrus, the entorhinal, medial orbitofrontal, lateral occipital, and insular cortices. Conclusion: This study demonstrates a positive association between PA level and CT in temporal areas such as the fusiform gyrus, a brain region often associated to Alzheimer's disease in people aged 70 years and older. Future investigations focusing on PA type may help to fulfil remaining knowledge gaps in this field.

The brain undergoes many changes at pathological and functional levels in healthy aging. This study employed a longitudinal and multimodal imaging dataset from the OASIS-3 study (n = 300) and explored possible relationships between amyloid beta (Aβ) accumulation and functional brain organization over time in healthy aging. We used positron emission tomography (PET) with Pittsburgh compound-B (PIB) to quantify the Aβ accumulation in the brain and resting-state functional MRI (rs-fMRI) to measure functional connectivity (FC) among brain regions. Each participant had at least 2 to 3 follow-up visits. A linear mixed-effect model was used to examine longitudinal changes of Aβ accumulation and FC throughout the whole brain. We found that the limbic and frontoparietal networks had a greater annual Aβ accumulation and a slower decline in FC in aging. Additionally, the amount of the Aβ deposition in the amygdala network at baseline slowed down the decline in its FC in aging. Furthermore, the functional connectivity of the limbic, default mode network (DMN), and frontoparietal networks accelerated the Aβ propagation across their functionally highly connected regions. The functional connectivity of the somatomotor and visual networks accelerated the Aβ propagation across the brain regions in the limbic, frontoparietal, and DMN networks. These findings suggested that the slower decline in the functional connectivity of the functional hubs may compensate for their greater Aβ accumulation in aging. The Aβ propagation from one brain region to the other may depend on their functional connectivity strength.

Oxidative stress, a state of disrupted redox signaling, reactive oxygen species (ROS) overproduction, and oxidative cell damage, accompanies numerous brain pathologies, including aging-related dementia and Alzheimer's disease, the most common neurodegenerative disorder of the elderly population. However, a causative role of neuronal oxidative stress in the development of aging-related cognitive decline and neurodegeneration remains elusive because of the lack of approaches for modeling isolated oxidative injury in the brain. Here, we present a chemogenetic approach based on the yeast flavoprotein d-amino acid oxidase (DAAO) for the generation of intraneuronal hydrogen peroxide (H2O2). To validate this chemogenetic tool, DAAO and HyPer7, an ultrasensitive genetically encoded H2O2 biosensor, were targeted to neurons. Changes in the fluorescence of HyPer7 upon treatment of neurons expressing DAAO with d-norvaline (D-Nva), a DAAO substrate, confirmed chemogenetically induced production of intraneuornal H2O2. Then, using the verified chemogenetic tool, we emulated isolated intraneuronal oxidative stress in acute brain slices and, using electrophysiological recordings, revealed that it does not alter basal synaptic transmission and the probability of neurotransmitter release from presynaptic terminals but reduces long-term potentiation (LTP). Moreover, treating neurons expressing DAAO with D-Nva via the patch pipette also decreases LTP. This observation indicates that isolated oxidative stress affects synaptic plasticity at single cell level. Our results broaden the toolset for studying normal redox regulation in the brain and elucidating the role of oxidative stress to the pathogenesis of cognitive aging and the early stages of aging-related neurodegenerative diseases. The proposed approach is useful for identification of early markers of neuronal oxidative stress and may be used in screens of potential antioxidants effective against neuronal oxidative injury.

Background: Studies in rodents and humans have indicated that inflammation outside CNS (systemic inflammation) affects brain homeostasis contributing to neurodevelopmental disorders. Itis becoming increasingly evident that such early insults may also belinked to neurodegenerative diseases like late-onset Alzheimer's disease (AD). Importantly, lifestyle and stress, such as viral or bacterial infection causing chronic inflammation, may contribute to neurodegenerative dementia. Systemic inflammatory response triggers a cascade of neuroinflammatory responses, altering brain transcriptome, cell death characteristic of AD, and vascular dementia. Our study aimed to assess the temporal evolution of the pathological impact of systemic inflammation evoked by prenatal and early postnatal peripheral exposure of viral mimetic Polyinosinic:polycytidylic acid (PolyI:C) and compare the hippocampal transcriptomic changes with the profiles of human post-mortem AD and vascular dementia brain specimens. Methods: We have engineered the PolyI:C sterile infection model in wildtype C57BL6 mice to achieve chronic low-grade systemic inflammation. We have conducted a cross-sectional analysis of aging PolyI:C and Saline control mice (3 months, 6 months, 9 months, and 16 months), taking the hippocampus as a reference brain region, and compared the brain aging phenotype to AD progression in humans with mild AD, severe AD, and Controls (CTL), in parallel to Vascular dementia (VaD) patients’ specimens. Results: We found that PolyI:C mice display both peripheral and central inflammation with a peak at 6 months, associated with memory deficits. The hippocampus is characterized by a pronounced and progressive tauopathy. In PolyI:C brains, microglia undergo aging-dependent morphological shifts progressively adopting a phagocytic phenotype. Transcriptomic analysis reveals a profound change in gene expression throughout aging, with a peak in differential expression at 9 months. We show that the proinflammatory marker Lcn2 is one of the genes with the strongest upregulation in PolyI:C mice upon aging. Validation in brains from patients with increasing severity of AD and VaD shows the reproducibility of some gene targets in vascular dementia specimens as compared to AD ones. Conclusions: The PolyI:C model of sterile infection demonstrates that peripheral chronic inflammation causes progressive tau hyperphosphorylation, changes in microglia morphology, astrogliosis and gene reprogramming reflecting increased neuroinflammation, vascular remodeling, and the loss of neuronal functionality seen to some extent in human AD and Vascular dementia suggesting early immune insults could be crucial in neurodegenerative diseases.

Background: Conventional metrics such as the apnea-hypopnea index (AHI) may not fully capture the diverse clinical manifestations of obstructive sleep apnea (OSA). This study aims to establish a novel OSA subtype classification based on the patterns of apneic and hypopneic hypoxic burden (HB), a potential biomarker that more accurately reflects the severity and duration of respiratory events. We further examined the associations of these HB-based subtypes with cardiometabolic risk and brain health outcomes., Methods: We retrospectively analyzed polysomnography data from 1000 participants including normal, mild, moderate, and severe OSA patients. We performed hierarchical clustering based on apneic and hypopneic HB to identify OSA subtypes. We then compared the prevalence of cardiometabolic syndrome (CMS) and brain health outcomes using the brain age index (BAI) among these subtypes., Results: Five distinct subtypes were identified: 'good sleepers' (subtype 1), 'light hypopneic HB' (subtype 2), 'mild HB' (subtype 3), 'moderate HB' (subtype 4), and 'severe HB with marked apneic HB' (subtype 5). The prevalence of CMS (particularly hypertension) was significantly higher in subtypes 2-5 (p < 0.001) compared to subtype 1. BAI was higher in subtypes 4 (3.2 years, p < 0.0001) and 5 (11.1 years, p < 0001) compared to subtype 1. Greater daytime sleepiness was observed in HB-based subtypes 2 and 5 compared to subtype 1 (p < 0.001), whereas no significant differences were found among groups classified by OSA severity using AHI., Conclusion: Our study demonstrates that the HB-based subtypes of OSA are significantly associated with various clinical features and outcomes. These insights could be utilized to improve risk stratification and guide the design of future OSA studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Healthy aging is associated with cognitive decline across multiple domains, including executive function, memory, and attention. These cognitive changes can often influence an individual's ability to function and quality of life. However, the degree to which individuals experience cognitive decline, as well as the trajectory of these changes, exhibits wide variability across people. These cognitive abilities are thought to depend on the coordinated activity of large-scale networks. Like behavioral effects, large variation can be seen in brain structure and function with aging, including in large-scale functional networks. However, tracking this variation requires methods that reliably measure individual brain networks and their changes over time. Here, we review the literature on age-related cognitive decline and on age-related differences in brain structure and function. We focus particularly on functional networks and the individual variation that exists in these measures. We propose that novel individual-centered fMRI approaches can shed new light on patterns of inter- and intra-individual variability in aging. These approaches may be instrumental in understanding the neural bases of cognitive decline., Competing Interests: Declaration of Competing Interest The authors have no conflict of interest to declare., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The human brain remains an endless source of wonder and represents an intruiging scientific frontier. Multiphysics approaches naturally lend themselves to combine our extensive knowledge about the neurobiology of aging and diseases with mechanics to better capture the multiscale behavior of the brain. Our group uses experimental methods, medical image analysis, and constitutive modeling to develop better disease models with the long-term goal to improve diagnosis, treatment, and ultimately enable prevention of many prevalent age- and disease-related brain changes. In the present perspective, we outline on-going work related to neurodevelopment, aging, and neurodegenerative disease.

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

Aging is a natural process in organisms with its underlying mechanisms remaining unknown. Brain aging is accompanied by cognitive deficits and movement disorders, which signify the importance of elaborating its main mechanisms. In this study, oxidative stress biomarkers for lipid peroxidation and thiol redox state were assessed in different brain areas in male mice, categorised in respect to aging as young (three months), middle (eleven months) and elder aged (twenty-three months). Senescence was associated with an increase of lipid peroxidation and a decrease of reduced and oxidized glutathione. In some brain areas, reduced cysteine and oxidized protein thiols were increased with aging. Results support the theory that aging is associated with oxidative stress in the brain of mice and provide an insight in the biochemical aspect of aging in reference to thiol redox status as a potential marker for aging.

Background: Transcranial laser stimulation is a novel method of noninvasive brain stimulation found safe and effective for improving prefrontal cortex neurocognitive functions in healthy young adults. This method is different from electric and magnetic stimulation because it causes the photonic oxidation of cytochrome-c-oxidase, the rate-limiting enzyme for oxygen consumption and the major intracellular acceptor of photons from near-infrared light. This photobiomodulation effect promotes mitochondrial respiration, cerebrovascular oxygenation and neurocognitive function. Pilot studies suggest that transcranial photobiomodulation may also induce beneficial effects in aging individuals. Objectives: Randomized, sham-controlled study to test photobiomodulation effects caused by laser stimulation on cytochrome-c-oxidase oxidation and hemoglobin oxygenation in the prefrontal cortex of 68 healthy younger and older adults, ages 18–85. Methods: Broadband near-infrared spectroscopy was used for the noninvasive quantification of bilateral cortical changes in oxidized cytochrome-c-oxidase and hemoglobin oxygenation before, during and after 1064-nm wavelength laser (IR-A laser, area: 13.6 cm2, power density: 250 mW/cm2) or sham stimulation of the right anterior prefrontal cortex (Brodmann Area 10). Results: As compared to sham control, there was a significant laser-induced increase in oxidized cytochrome-c-oxidase during laser stimulation, followed by a significant post-stimulation increase in oxygenated hemoglobin and a decrease in deoxygenated hemoglobin. Furthermore, there was a greater laser-induced effect on cytochrome-c-oxidase with increasing age, while laser-induced effects on cerebral hemodynamics decreased with increasing age. No adverse laser effects were found. Conclusion: The findings support the use of transcranial photobiomodulation for cerebral oxygenation and alleviation of age-related decline in mitochondrial respiration. They justify further research on its therapeutic potential in neurologic and psychiatric diseases.

“Brain-predicted age” quantifies apparent brain age compared to normative neuroimaging trajectories. Advanced brain-predicted age has been well established in symptomatic Alzheimer disease (AD), but is underexplored in preclinical AD. Prior brain-predicted age studies have typically used structural MRI, but resting-state functional connectivity (FC) remains underexplored. Our model predicted age from FC in 391 cognitively normal, amyloid-negative controls (ages 18–89). We applied the trained model to 145 amyloid-negative, 151 preclinical AD, and 156 symptomatic AD participants to test group differences. The model accurately predicted age in the training set. FC-predicted brain age gaps (FC-BAG) were significantly older in symptomatic AD and significantly younger in preclinical AD compared to controls. There was minimal correspondence between networks predictive of age and AD. Elevated FC-BAG may reflect network disruption during symptomatic AD. Reduced FC-BAG in preclinical AD was opposite to the expected direction, and may reflect a biphasic response to preclinical AD pathology or may be driven by inconsistency between age-related vs. AD-related networks. Overall, FC-predicted brain age may be a sensitive AD biomarker.

Objective: To observe the effect of Wuweizi syrup on brain aging mice model induced by d-galactose in mice. Methods: 72 mice were randomly divided into blank group, model group, naokangling group and low, middle and high dose Wuweizi syrup group. After 3 days of adaptive feeding, except for the blank group, the rest mice were subcutaneously (sc) injected with d-galactose 1.25 g/kg at neck back to replicate the aging model. Sc injection was given for 40 consecutive days, and corresponding drugs were given by gavage on the 11th day of modeling. On the 39th day, the dark experiment was carried out to measure the learning ability of mice. After the last administration for 2 h, brain, liver, thymus and spleen were taken and weighed to calculate the organ index. Blood was taken and CAT, GSH and SOD levels in whole blood were determined. Some brain and liver tissues were taken to prepare homogenates, and MDA levels in tissue homogenates and plasma were measured. Brain, liver, thymus and spleen were stained with HE, and pathological sections were made for observation under light microscope. Results: Compared with the blank group, in the model group, the incubation period of mice was significantly reduced and the number of shuttle back and forth was significantly increased (P

Drosophila NF-κB transcription factor Dif has been well known for its function in innate immunity, and recent study also reveals its role in neuronal cells. However, the underlying mechanisms of Dif in the brain remain elusive. In this study, we aim to investigate the function of Dif in Drosophila brain development and how Dif regulates structure and plasticity of the brain to affect aging and behaviors. Based on the analysis of differentially expressed genes, we identified key genes associated with cell division, development and aging in the brain of Dif 1 loss of function mutant. In Dif 1 larvae, we found that the metamorphosis and brain development were delayed, and cell division was decreased. In Dif 1 adults, the number of neuron cells was reduced in the brain, the lifespan and locomotor activity were decreased, protein markers associated with aging-related neurodegenerative diseases in the brain were altered in abundance or activity. Our results indicated that Dif plays a crucial role in brain plasticity and neurogenesis, dysfunction of Dif delays larval brain development and impacts proliferation of neuronal cells, resulting in aging adult brain by regulating expression of key genes in multiple signaling pathways involved in cell division, neurogenesis and aging., Competing Interests: Declaration of competing interest The authors have declared that no competing interests exist., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Immune system hypersensitivity is believed to contribute to mental frailty in the elderly. Solid evidence indicates NOD-like receptor pyrin domain containing-3 (NLRP3)-inflammasome activation intimately connects aging-associated chronic inflammation (inflammaging) to senile cognitive decline. Thioredoxin interacting protein (TXNIP), an inducible protein involved in oxidative stress, is essential for NLRP3 inflammasome activity. This study aims to find whether TXNIP/NLRP3 inflammasome pathway is involved in senile dementia. According to our studies on sex-matched mice, TXNIP was significantly upregulated in aged animals, paralleled by the NLRP3-inflammasome over-activity leading to enhanced caspase-1 cleavage and IL-1β maturation, in both sexes. This was closely associated with depletion of the anti-aging and cognition enhancing protein klotho, in aged males. Txnip knockout reversed age-related NLRP3-hyperactivity and enhanced thioredoxin (TRX) levels. Further, TXNIP inhibition along with verapamil replicated TXNIP/NLRP3-inflammasome downregulation in aged animals, with FOXO-1 and mTOR upregulation. These alterations concurred with substantial improvements in both cognitive and sensorimotor abilities. Together, these findings substantiate the pivotal role of TXNIP to drive inflammaging in parallel with klotho depletion and functional decline, and delineate thioredoxin system as a potential target to decelerate senile dementia.

Brain aging is a complex process, entailing alterations at the most diverse levels of brain structure and functioning. On the macroscopical scale, gray matter atrophy is one of its most prominent markers, but it remains to be elucidated why some regions are more affected by it than others. In this work, we aimed to explore how age affects the morphometry of cortical structures, and specially the relationship between atrophy and the initial state of regions. To this end, anatomical T1-weighted images from 612 subjects aged 18–85 years were employed. Atlas-based cortical morphometric estimates were obtained. Our results show that, whilst there is no obvious shared pattern between the initial surface area of cortical regions at eighteen years and their yearly rate of decay, for cortical thickness there is enough evidence to suggest thicker regions at eighteen years of age also present higher yearly rates of thinning, although yearly percentages are proportionately smaller. Our analyses reveal that neocortical regions tend to conform to this trend, where agranular cortices experience higher atrophy levels than granular cortices, contrasting a few non-pure neocortical regions that do not follow this trend, highlighting parallels between brain evolution and brain aging.

Brain age prediction studies aim at reliably estimating the difference between the chronological age of an individual and their predicted age based on neuroimaging data, which has been proposed as an informative measure of disease and cognitive decline. As most previous studies relied exclusively on magnetic resonance imaging (MRI) data, we hereby investigate whether combining structural MRI with functional magnetoencephalography (MEG) information improves age prediction using a large cohort of healthy subjects (N = 613, age 18–88 years) from the Cam-CAN repository. To this end, we examined the performance of dimensionality reduction and multivariate associative techniques, namely Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA), to tackle the high dimensionality of neuroimaging data. Using MEG features (mean absolute error (MAE) of 9.60 years) yielded worse performance when compared to using MRI features (MAE of 5.33 years), but a stacking model combining both feature sets improved age prediction performance (MAE of 4.88 years). Furthermore, we found that PCA resulted in inferior performance, whereas CCA in conjunction with Gaussian process regression models yielded the best prediction performance. Notably, CCA allowed us to visualize the features that significantly contributed to brain age prediction. We found that MRI features from subcortical structures were more reliable age predictors than cortical features, and that spectral MEG measures were more reliable than connectivity metrics. Our results provide an insight into the underlying processes that are reflective of brain aging, yielding promise for the identification of reliable biomarkers of neurodegenerative diseases that emerge later during the lifespan.

Summary: Mitochondrial function declines during brain aging and is suspected to play a key role in age-induced cognitive decline and neurodegeneration. Supplementing levels of spermidine, a body-endogenous metabolite, has been shown to promote mitochondrial respiration and delay aspects of brain aging. Spermidine serves as the amino-butyl group donor for the synthesis of hypusine (Nε-[4-amino-2-hydroxybutyl]-lysine) at a specific lysine residue of the eukaryotic translation initiation factor 5A (eIF5A). Here, we show that in the Drosophila brain, hypusinated eIF5A levels decline with age but can be boosted by dietary spermidine. Several genetic regimes of attenuating eIF5A hypusination all similarly affect brain mitochondrial respiration resembling age-typical mitochondrial decay and also provoke a premature aging of locomotion and memory formation in adult Drosophilae. eIF5A hypusination, conserved through all eukaryotes as an obviously critical effector of spermidine, might thus be an important diagnostic and therapeutic avenue in aspects of brain aging provoked by mitochondrial decline.

Background: A dramatic increase in aging populations and low birth rates rapidly drive aging societies and increase aging-associated neurodegenerative diseases. However, functional food or medicinal formulations to prevent geriatric brain disorders are not readily available. Panax ginseng is a candidate, since ginseng has long-been consumed as a rejuvenating agent. However, the underlying molecular mechanisms and the components of ginseng that are responsible for brain rejuvenation and human longevity are unknown. Accumulating evidence shows that gintonin is a candidate for the anti-aging ingredient of ginseng, especially in brain senescence. Methods: Gintonin, a glycolipoprotein complex, contains three lipid-derived G protein-coupled receptor ligands: lysophosphatidic acids (LPAs), lysophosphatidylinositols (LPIs), and linoleic acid (LA). LPA, LPI, and LA act on six LPA receptor subtypes, GPR55, and GPR40, respectively. These G protein-coupled receptors are distributed within the nervous and non-nervous systems of the human body. Results: Gintonin-enriched fraction (GEF) exhibits anti-brain senescence and effects against disorders such as Alzheimer's disease (AD), Huntington's disease (HD), and Parkinson's disease (PD). Oral administration of gintonin in animal models of d-galactose-induced brain aging, AD, HD, and PD restored cognitive and motor functions. The underlying molecular mechanisms of gintonin-mediated anti-brain aging and anti-neurodegenerative diseases include neurogenesis, autophagy stimulation, anti-apoptosis, anti-oxidative stress, and anti-inflammatory activities. This review describes the characteristics of gintonin and GEF, and how gintonin exerts its effects on brain aging and brain associated-neurodegenerative diseases. Conclusion: Finally, we describe how GEF can be applied to improve the quality of life of senior citizens in aging societies.

Brain biological age, which measures the aging process in the brain using neuroimaging data, has been used to assess advanced brain aging in neurodegenerative diseases, including Parkinson disease (PD). However, assuming that whole brain degeneration is uniform may not be sufficient for assessing the complex neurodegenerative processes in PD. In this study we constructed a multiscale brain age prediction models based on structural MRI of 1240 healthy participants. To assess the brain aging patterns using the brain age prediction model, 93 PD patients and 91 healthy controls matching for sex and age were included. We found increased global and regional brain age in PD patients. The advanced aging regions were predominantly noted in the frontal and temporal cortices, limbic system, basal ganglia, thalamus, and cerebellum. Furthermore, region-level rather than global brain age in PD patients was associated with disease severity. Our multiscale brain age prediction model could aid in the development of objective image-based biomarkers to detect advanced brain aging in neurodegenerative diseases., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Maintaining high levels of daily activity and physical capability have been proposed as important constituents to promote healthy brain and cognitive aging. Studies investigating the associations between brain health and physical activity in late life have, however, mainly been based on self-reported data or measures designed for clinical populations. In the current study, we examined cross-sectional associations between physical activity, recorded by an ankle-positioned accelerometer for seven days, physical capability (grip strength, postural control, and walking speed), and neuroimaging based surrogate markers of brain health in 122 healthy older adults aged 65–88 years. We used a multimodal brain imaging approach offering complementary structural MRI based indicators of brain health: global white matter fractional anisotropy (FA) and mean diffusivity (MD) based on diffusion tensor imaging, and subcortical and global brain age based on brain morphology inferred from T1-weighted MRI data. In addition, based on the results from the main analysis, follow-up regression analysis was performed to test for association between the volume of key subcortical regions of interest (hippocampus, caudate, thalamus and cerebellum) and daily steps, and a follow-up voxelwise analysis to test for associations between walking speed and FA across the white matter Tract-Based Spatial Statistics (TBSS) skeleton. The analyses revealed a significant association between global FA and walking speed, indicating higher white matter integrity in people with higher pace. Voxelwise analysis supported widespread significant associations. We also found a significant interaction between sex and subcortical brain age on number of daily steps, indicating younger-appearing brains in more physically active women, with no significant associations among men. These results provide insight into the intricate associations between different measures of brain and physical health in old age, and corroborate established public health advice promoting physical activity.

Emerging evidence suggests that Alzheimer’s Disease (AD) risk factors may differentially contribute to disease trajectory in women than men. Determining the effect of AD risk factors on brain aging in women, compared to men, is critical for understanding whether there are sex differences in the pathways towards AD in cognitively intact but at-risk adults. Brain Age Gap (BAG) is a concept used increasingly as a measure of brain health; BAG is defined as the difference between predicted age (based on structural MRI) and chronological age, with negative values reflecting preserved brain health with age. Using BAG, we investigated whether there were sex differences in the brain effects of AD risk factors (i.e., family history of AD, and carrying an apolipoprotein E ε4 allele [+APOE4]) in cognitively intact adults, and if this relationship was moderated by modifiable factors (i.e. body mass index [BMI], blood pressure and physical activity). We undertook a cross-sectional study of structural MRIs from 1067 cognitively normal adults across four neuroimaging datasets. An elastic net regression model found that women with a family history of AD and +APOE4 genotype had more advanced brain aging than their male counterparts. In a sub-cohort of women with those risk factors, higher BMI was associated with less brain aging whereas lower BMI was not. In a sub-cohort of women and men with +APOE4, engaging in physical activity was more beneficial to men’s brain aging than women’s. Our results demonstrate that AD risk factors are associated with greater brain aging in women than men, although there may be more unexplored modifiable factors that influence this relationship. These findings suggest that the complex interplay between unmodifiable and modifiable AD risk factors can potentially protect against brain aging in women and men.

Both normal ageing and neurodegenerative diseases cause morphological changes to the brain. Age-related brain changes are subtle, nonlinear, and spatially and temporally heterogenous, both within a subject and across a population. Machine learning models are particularly suited to capture these patterns and can produce a model that is sensitive to changes of interest, despite the large variety in healthy brain appearance. In this paper, the power of convolutional neural networks (CNNs) and the rich UK Biobank dataset, the largest database currently available, are harnessed to address the problem of predicting brain age. We developed a 3D CNN architecture to predict chronological age, using a training dataset of 12,802 T1-weighted MRI images and a further 6,885 images for testing. The proposed method shows competitive performance on age prediction, but, most importantly, the CNN prediction errors ΔBrainAge=AgePredicted−AgeTrue correlated significantly with many clinical measurements from the UK Biobank in the female and male groups. In addition, having used images from only one imaging modality in this experiment, we examined the relationship between ΔBrainAge and the image-derived phenotypes (IDPs) from all other imaging modalities in the UK Biobank, showing correlations consistent with known patterns of ageing. Furthermore, we show that the use of nonlinearly registered images to train CNNs can lead to the network being driven by artefacts of the registration process and missing subtle indicators of ageing, limiting the clinical relevance. Due to the longitudinal aspect of the UK Biobank study, in the future it will be possible to explore whether the ΔBrainAge from models such as this network were predictive of any health outcomes.

Investigation of relationships between age-related changes in regional brain volumes and changes in domain-specific cognition could provide insights into the neural underpinnings of individual differences in cognitive aging. Domain-specific cognition (memory, verbal fluency, visuospatial ability) and tests of executive function and attention (Trail-Making Test Part A and B) and 47 brain volumes of interest (VOIs) were assessed in 836 Baltimore Longitudinal Study of Aging participants with mean follow-up of 4.1 years (maximum 23.1 years). To examine the correlation between changes in domain-specific cognition and changes in brain volumes, we used bivariate linear mixed effects models with unstructured variance-covariance structure to estimate longitudinal trajectories for each variable of interest and correlations among the random effects of these measures. Higher annual rates of memory decline were associated with greater volume loss in 14 VOIs primarily within the temporal and occipital lobes. Verbal fluency decline was associated with greater ventricular enlargement and volume loss in 24 VOIs within the frontal, temporal, and parietal lobes. Decline in visuospatial ability was associated with volume loss in 3 temporal and parietal VOIs. Declines on the attentional test were associated with volume loss in 4 VOIs located within temporal and parietal lobes. Greater declines on the executive function test were associated with greater ventricular enlargement and volume loss in 10 frontal, parietal, and temporal VOIs. Our findings highlight domain-specific patterns of regional brain atrophy that may contribute to individual differences in cognitive aging.

Oxidative stress is closely associated with aging and age-related neurodegenerative diseases and plays a vital function in their initiation and progression. Selenium-enriched peptides from Cardamine violifolia (CSP) had excellent antioxidant function in vitro, however, whether it has an effect on aging is still unknown. In this study, the results revealed that CSP supplementation could ameliorate d-galactose (d-gal) induced metabolism disorder, memory dysfunction, and neuron damage in the hippocampus. Moreover, CSP alleviated ROS and MDA levels by increasing the activities of SOD, GSH-Px, CAT, and TAOC, and activate the Nrf2/HO-1/NQO1 pathway, which probably represents an anti-aging mechanism of CSP. Furthermore, CSP reduced the neuro-inflammation by inhibiting the NF-κB pathway in d-gal induced aging rats and suppressed RAGE and P-JNK signaling pathway. Altogether, the study firstly demonstrated the favorable effects of CSP against brain aging, which can be further developed as a promising strategy to prevent or treat age-related neurodegenerative diseases.

Normal aging incurs functional and anatomical alterations in the brain. Cortical thinning, age-related alterations in resting-state functional connectivity (RSFC) and reductions in fractional amplitude of low frequency fluctuations (fALFF) are key components of brain aging that can be studied by neuroimaging. However, the level of association between these processes has not been fully established. We performed an analysis at multiple-levels, i.e. region or connection and modality, to investigate whether the evidence for the effect of aging on fALFF, RSFC and cortical thickness are associated in a large cohort. Our results show that there is a positive association between the level of evidence of age-related effects in all three in the brain. We also demonstrate that on a regional basis the association between RSFC alterations and cortical atrophy may be either positive or negative, which may relate to compensatory mechanisms predicted by the Scaffolding Theory of Aging and Cognition (STAC).

Our understanding of human neurocognitive aging, its developmental roots, and life course influences has been transformed by brain imaging technologies, increasing availability of longitudinal data sets, and analytic advances. The Scaffolding Theory of Aging and Cognition is a life course model, proposed originally in 2009, featuring adaptivity and compensatory potential as lifelong mechanisms for meeting neurocognitive challenges posed by the environment and by developing or declining brain circuitry. Here, we review the scaffolding theory in relation to new evidence addressing when during the life course potentially enriching and depleting factors exert their effects on brain health and scaffolding, and we consider the implications for separable, and potentially reciprocal, influences on the level of cognitive function and the rate of decline in later life., Competing Interests: Declaration of competing interest The author declares no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Brain functional and structural changes lead to cognitive decline during aging, but a high level of cognitive stimulation during life can improve cognitive performances in the older adults, forming the cognitive reserve. Noradrenaline has been proposed as a molecular link between environmental stimulation and constitution of the cognitive reserve. Taking advantage of the ability of olfactory stimulation to activate noradrenergic neurons of the locus coeruleus, we used repeated olfactory enrichment sessions over the mouse lifespan to enable the cognitive reserve buildup. Mice submitted to olfactory enrichment, whether started in early or late adulthood, displayed improved olfactory discrimination at late ages and interestingly, improved spatial memory and cognitive flexibility. Moreover, olfactory and non-olfactory cognitive performances correlated with increased noradrenergic innervation in the olfactory bulb and dorsal hippocampus. Finally, c-Fos mapping and connectivity analysis revealed task-specific remodeling of functional neural networks in enriched older mice. Long-term olfactory enrichment thus triggers structural noradrenergic plasticity and network remodeling associated with better cognitive aging and thereby forms a promising mouse model of the cognitive reserve buildup., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The transition from childhood to adolescence is characterized by enhanced neural plasticity and a consequent susceptibility to both beneficial and adverse aspects of one's milieu., Methods: To understand the implications of the interplay between protective and risk-enhancing factors, we analyzed longitudinal data from the Adolescent Brain Cognitive Development (ABCD) Study (n = 834; 394 female). We probed the maturational correlates of positive lifestyle variables (friendships, parental warmth, school engagement, physical exercise, healthy nutrition) and genetic vulnerability to neuropsychiatric disorders (major depressive disorder, Alzheimer's disease, anxiety disorders, bipolar disorder, schizophrenia) and sought to further elucidate their implications for psychological well-being., Results: Genetic risk factors and lifestyle buffers showed divergent relationships with later attentional and interpersonal problems. These effects were mediated by distinguishable functional neurodevelopmental deviations spanning the limbic, default mode, visual, and control systems. More specifically, greater genetic vulnerability was associated with alterations in the normative maturation of areas rich in dopamine (D 2 ), glutamate, and serotonin receptors and of areas with stronger expression of astrocytic and microglial genes, a molecular signature implicated in the brain disorders discussed here. Greater availability of lifestyle buffers predicted deviations in the normative functional development of higher density GABAergic (gamma-aminobutyric acidergic) receptor regions. The two profiles of neurodevelopmental alterations showed complementary roles in protection against psychopathology, which varied with environmental stress levels., Conclusions: Our results underscore the importance of educational involvement and healthy nutrition in attenuating the neurodevelopmental sequelae of genetic risk factors. They also underscore the importance of characterizing early-life biomarkers associated with adult-onset pathologies., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Lipids are essential components of brain structure and shown to affect brain function. Previous studies have shown that aging men undergo greater brain atrophy than women, but whether the associations between lipids and brain atrophy differ by sex is unclear. We examined sex differences in the associations between circulating lipids by liquid chromatography-tandem mass spectrometry and the progression of MRI-derived brain atrophy index Spatial Patterns of Atrophy for Recognition of Brain Aging (SPARE-BA) over an average of 4.7 (SD = 2.3) years in 214 men and 261 women aged 60 or older who were initially cognitively normal using multivariable linear regression, adjusted for age, race, education, and baseline SPARE-BA. We found significant sex interactions for beta-oxidation rate, short-chain acylcarnitines, long-chain ceramides, and very long-chain triglycerides. Lower beta-oxidation rate and short-chain acylcarnitines in women and higher long-chain ceramides and very long-chain triglycerides in men were associated with faster increases in SPARE-BA (accelerated brain aging). Circulating lipid profiles of accelerated brain aging are sex-specific and vary by lipid classes and structure. Mechanisms underlying these sex-specific lipid profiles of brain aging warrant further investigation., (Published by Elsevier Inc.)

The cognitive reserve (CR) hypothesis is reinforced by negative moderating effects, suggesting that those with higher CR are less reliant on brain structure for cognitive function. Previous research on CR's moderating effects yielded inconsistent results, motivating our 3 studies using UK Biobank data. Study I examined five CR proxies' moderating effects on global, lobar, and regional brain-cognition models; study II extended study I by using a larger sample size; and study III investigated age-related moderating effects on the hippocampal regions. In study I, most moderating effects were negative and none survived the multiple comparison correction, but study II identified 13 global-level models with significant negative moderating effects that survived correction. Study III showed age influenced CR proxies' moderating effects in hippocampal regions. Our findings suggest that the effects of CR proxies on brain integrity and cognition varied depending on the proxy used, brain integrity indicators, cognitive domain, and age group. This study offers significant insights regarding the importance of CR for brain integrity and cognitive outcomes., Competing Interests: Disclosure statement The authors report no conflict of interest., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Ischemic heart disease (IHD) has been linked with poor brain outcomes. The brain magnetic resonance imaging-derived difference between predicted brain age and actual chronological age (brain-age delta in years, positive for accelerated brain aging) may serve as an effective means of communicating brain health to patients to promote healthier lifestyles., Objectives: The authors investigated the impact of prevalent IHD on brain aging, potential underlying mechanisms, and its relationship with dementia risk, vascular risk factors, cardiovascular structure, and function., Methods: Brain age was estimated in subjects with prevalent IHD (n = 1,341) using a Bayesian ridge regression model with 25 structural (volumetric) brain magnetic resonance imaging features and built using UK Biobank participants with no prevalent IHD (n = 35,237)., Results: Prevalent IHD was linked to significantly accelerated brain aging (P < 0.001) that was not fully mediated by microvascular injury. Brain aging (positive brain-age delta) was associated with increased risk of dementia (OR: 1.13 [95% CI: 1.04-1.22]; P = 0.002), vascular risk factors (such as diabetes), and high adiposity. In the absence of IHD, brain aging was also associated with cardiovascular structural and functional changes typically observed in aging hearts. However, such alterations were not linked with risk of dementia., Conclusions: Prevalent IHD and coexisting vascular risk factors are associated with accelerated brain aging and risk of dementia. Positive brain-age delta representing accelerated brain aging may serve as an effective communication tool to show the impact of modifiable risk factors and disease supporting preventative strategies., Competing Interests: Funding Support and Author Disclosures Barts Charity (G-002346) contributed to fees required to access UK Biobank data (access application #2964). Drs Rauseo and Petersen have received grants from the London Medical Imaging and Artificial Intelligence Centre for Value Based Healthcare (AI4VBH), which is funded from the Data to Early Diagnosis and Precision Medicine strand of the government’s Industrial Strategy Challenge Fund, managed and delivered by Innovate UK on behalf of UK Research and Innovation (UKRI). Mr Salih is supported by INVITE program co-financed by the European Union within the Horizon 2020 Programme and by the Regione del Veneto. Dr Raisi-Estebragh has received grants from the National Institute for Health Research (NIHR) Integrated Academic Training programme which supports her Academic Clinical Lectureship post; she has also received grants from the British Heart Foundation Clinical Research Training Fellowship (No. FS/17/81/33318). Dr Aung has received grants from the NIHR Integrated Academic Training programme which supports his Academic Clinical Lectureship post, and the Academy of Medical Sciences Starter Grant for Clinical Lecturers (SGL024∖1024). Dr Slabaugh has received consulting fees from MindRank AI. Dr Marshall has received grants from Barts Charity; and has received personal fees from Biogen and GE Healthcare. Dr Neubauer has received grants from the Oxford NIHR Biomedical Research Centre. Drs Galazzo and Menegaz have received grants from the Fondazione CariVerona (EDIPO project—reference number 2018.0855.2019). Dr Petersen has received grants from the NIHR Biomedical Research Centre at Barts, and from the British Heart Foundation for funding the manual analysis to create a cardiovascular magnetic resonance imaging reference standard for the UK Biobank imaging resource in 5,000 CMR scans (www.bhf.org.uk; PG/14/89/31194), and from the SmartHeart EPSRC programme grant (www.nihr.ac.uk; EP/P001009/1); and has received consulting fees from Circle Cardiovascular Imaging Inc, Calgary, Alberta, Canada. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The processes involved with β-amyloid (Aβ) degradation and clearance in human brain are not well understood. We hypothesized that the distribution of oxidatively modified Aβ, as determined by an affinity-purified antibody in the entorhinal and frontal cortices of Alzheimer's disease (AD), Down syndrome (DS), nondemented elderly control cases, and canine brain, would provide insight into the mechanisms of Aβ accumulation. Based upon plaque counts, oxidized Aβ was present within 46–48% of diffuse and primitive plaques and 98% of cored plaques. Dense punctate deposits of oxidized Aβ were distributed throughout the neuropil in AD and DS brains but were also present within controls with mild neuropathology and isolated cognitive impairments. Confocal studies indicate that punctate oxidized Aβ deposits were within activated microglia. Oxidatively modified Aβ may reflect the efforts of microglial cells to take up and degrade Aβ. Oxidative modification of Aβ may be an early event in Aβ pathogenesis and may be important for plaque biogenesis.

The relationship between brain microstructure and aging has been the subject of intense study, with diffusion MRI perhaps the most effective modality for elucidating these associations. Here, we used the mean apparent propagator (MAP)-MRI framework, which is suitable to characterize complex microstructure, to investigate age-related cerebral differences in a cohort of cognitively unimpaired participants and compared the results to those derived using diffusion tensor imaging. We studied MAP-MRI metrics, among them the non-Gaussianity (NG) and propagator anisotropy (PA), and established an opposing pattern in white matter of higher NG alongside lower PA among older adults, likely indicative of axonal degradation. In gray matter, however, these two indices were consistent with one another, and exhibited regional pattern heterogeneity compared to other microstructural parameters, which could indicate fewer neuronal projections across cortical layers along with an increased glial concentration. In addition, we report regional variations in the magnitude of age-related microstructural differences consistent with the posterior-anterior shift in aging paradigm. These results encourage further investigations in cognitive impairments and neurodegeneration., (Published by Elsevier Inc.)

Background and Purpose: Brain structure and function change with age. Both educational attainments, a proxy for cognitive reserve, and intracranial volume (ICV), a proxy for brain reserve, could contribute to resilience against degenerative change in the brain with aging. Whether the effect of educational attainment on regional brain volume in adults is mediated by ICV is yet unclear. We aimed to investigate the direct and indirect effects (mediated through ICV) of education in early life on regional brain volume in later life., Materials and Method: We investigated the association between ICV and education level and regional brain volume in adults using magnetic resonance imaging scans of 1,731 individuals from multicenter studies. The mediation effect of ICV was analyzed to determine the association between educational attainment at an earlier age and regional brain volume in adults., Results: Our results showed that the effect of education on regional brain volume was significantly mediated by ICV in both men and women. The indirect (mediated via ICV) effect of education on brain volume amounted to 75% of the total effect in the hippocampus (p < 0.001) and 100% in the frontal and insular gray matter (p < 0.001)., Conclusion: Our study demonstrated that the association between educational attainment in early life and regional brain volume in later life was largely mediated by ICV. Attention should be given to the effect of educational attainment and ICV on regional brain size in adults as a measurable resilience effect in brain aging., Competing Interests: Declaration of Competing Interest Authors RK, ML, and DK were employed by NEUROPHET INC. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest., (Copyright © 2023. Published by Elsevier B.V.)

The current study characterized the combating memory impairment effect of seabuckthorn seed protein (SSP) and the arginine (Arg)-enriched peptides (SSPP) on d-galactose-induced brain aging in mice. The Arg content in SSP and SSPP were 10.11 and 17.82 g/100 g, respectively. Seven Arg peptides (Ile/Leu-Arg, Arg-Glu, Asp-Arg-Pro, Arg-Try-Ala, Glu-Arg-Ser, Val-Gly-Arg-Pro, and Lys-Thr-Glu-Arg) were identified from SSPP. The animal experiments of the Morris water maze and the step-down test indicated that the oral administration of SSP (0.25, 0.5, 1.0 mg/g·d) and SSPP (0.25, 0.5, 1.0 mg/g·d) significantly (p < 0.05) reversed the learning and memory impairment symptoms. The activation of endothelial nitric oxide (NO) synthase and neuronal NO synthase were increased, and inducible NO synthase decreased after SSP and SSPP in the hippocampus compared to the model group, with the SSPP being quite effective. Moreover, the treatment significantly exhibited the ability to normalize the serum inflammatory cytokine levels (NF-ĸB, TNF-α, IL-6) and suppress the Arg-inducible nitric oxide (Arg-iNO) pathway. Therefore, SSP and SSPP ingestion reversed the behavioral learning and memory impairment symptoms possibly associated with the anti-inflammation and Arg-iNO pathway. Consumption of SSP and SSPP diets can be beneficial to memory impairment., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023. Published by Elsevier B.V.)

Apolipoprotein E4 (apoE4) is a risk factor for Alzheimer's disease (AD). Here, we investigated brain amyloid-β (Aβ) accumulation throughout the aging process in an amyloid precursor protein (APP) knock-in (KI) mouse model of AD that expresses human APP NL-G-F with or without human apoE4 or apoE3. Brain Aβ42 levels were significantly lower in 9-month-old mice that express human isoforms of apoE than in age-matched APP-KI control mice. Linear accumulation of Aβ42 began in 5-month-old apoE4 mice, and a strong increase in Aβ42 levels was observed in 21-month-old apoE3 mice. Aβ42 levels in cerebroventricular fluid were higher in apoE3 than in apoE4 mice at 6-7 months of age, suggesting that apoE3 is more efficient at clearing Aβ42 than apoE4 at these ages. However, apoE3 protein levels were lower than apoE4 protein levels in the brains of 21-month-old apoE3 and apoE4 mice, respectively, which may explain the rapid increase in brain Aβ42 burden in apoE3 mice. We identified genes that were downregulated in a human apoE-dependent (apoE4 > apoE3) and age-dependent (apoE3 = apoE4) manner, which may regulate brain Aβ burden and/or AD progression. Analysis of gene expression in AD mouse models helps identify molecular mechanisms of pleiotropy by the human APOE gene during aging., Competing Interests: Disclosure statement All authors report no conflict of interest., (Copyright © 2022 Elsevier Inc. All rights reserved.)