Aging is a multifactorial process affects different tissues and organs and is modulated by genetic and environmental factors. In aging, the frequency of DNA repair errors and genomic instability are augmented. Depletion of endogenous antioxidant capacity during aging promotes the development of oxidative stress which triggers oxidative stress-induced DNA injury. Brain aging is manifested by cognitive impairment and memory disorders. Development of neuronal senescence is the major pathway in the progression of brain aging. Silent information regulator sirtuin 1 (SIRT1) is a class III histone deacetylase plays a critical role in genomic stability during aging. SIRT1 is highly expressed in specific brain regions involved in energy expenditure and metabolic activity that is necessary for brain development and control of brain senescence. Therefore, SIRT1 may have neuroprotective effects against brain aging and related neurodegenerative diseases. This narrative review aims to critically evaluate the role of SIRT1 in brain aging and to summarize current evidence on compounds that directly or indirectly modulate SIRT1 activity, with a focus on their mechanistic pathways and potential therapeutic implications. Findings of the present review highlighted that SIRT1 activators such as resveratrol, metformin and statins have neuroprotective effects against brain aging by regulating inflammatory and oxidative stress disorders through modulation of downstream signaling pathways.
Brain maturation varies between individuals, particularly during dynamic developmental periods such as adolescence. Directly assessing the differences in longitudinal trajectories can reveal deviations from normative patterns. To ascertain the association of longitudinal change in brain volumes with birth weight, gestational age, and longitudinal changes in psychopathology. In this cohort study, cross-sectional and longitudinal normative models were developed for brain volumes from the first 2 neuroimaging data collection time points (baseline: 2016-2018; follow-up: 2019-2021) of the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing community-based longitudinal cohort study at 21 US sites. Longitudinal models indexed an individual's expected brain volume at follow-up, conditioned on their baseline measurement, and thus were conditional-longitudinal models. Split-half subsets on demographically matched samples were used to fit the models. ABCD Study participants were recruited through the US school systems. Exclusion criteria included severe medical conditions that interfered with the study protocols. The present analysis further excluded the sample based on imaging quality flags and missing data. Data analysis was performed between May 2024 and August 2025. Birth weight and gestational age derived from parent-reported questionnaires. General psychopathology and subfactor scores were calculated using a bifactor model. Brain volumes and change in volume between time points 1 (baseline) and 2 (follow-up). Cross-sectional and longitudinal centiles were used to quantify deviations in volumes. The sample included 10 830 ABCD Study participants with neuroimaging data collected at baseline (mean [SD] age, 9.9 [0.62] years; 5609 males [51.8%]) and 7262 with data collected at follow-up (mean [SD] age, 12.0 [0.65] years; 3875 males [53.4%]). Longitudinal centiles were sensitive to individual-specific changes in brain volumes. Lower birth weight was associated with lower longitudinal centiles, suggesting larger decreases in brain volumes over time (n = 27 regions, β range = 0.030-0.083). Lower longitudinal centiles were associated with greater increases in psychopathology, suggesting decreasing brain volumes with increasing psychopathology scores (n = 37 regions, β range = -0.061 to -0.031). Changes in psychopathology were not associated with brain volumes at either time point when indexed by cross-sectional centiles. In this cohort study, conditional-longitudinal models captured individual-level deviations from expected growth trajectories, providing information beyond static positions on a growth curve to assess differences in maturation. Robust associations were observed between individual trajectory deviations, birth weight, and longitudinally assessed mental health symptoms. Conditional-longitudinal models hold promise for applications across psychiatric neuroscience, from development to aging.
Most existing DNA methylation (DNAm) studies have used peripheral surrogate tissues to research molecular mechanisms underlying brain disorders and diseases. Initial studies comparing brain to blood primarily at the individual CpG level analysis have generally pointed to a limited overlap of epigenetic patterns, consistent with DNAm being largely tissue- and even cell type-specific. Expanding on these studies, we employed a more complex analysis strategy aimed to 1) identify single DNAm sites associated with deconvolution-estimated brain cell type proportions, the principal measure in this study, in both the frontal brain and peripheral blood, 2) combine blood DNAm sites to predict brain cell type proportions through multivariate models, and 3) examine the association of blood DNAm, age, and epigenetic age acceleration (EAA) on brain cell type proportions. Epigenome-wide association studies for seven brain cell type proportions in matched frontal brain and peripheral blood samples (n = 104) revealed that ∼10% of brain cell type-associated DNAm sites had correlating DNAm levels in peripheral blood (p < 0.05). However, only three peripheral blood DNAm sites were significantly associated with endothelial and stromal brain cell type proportions (adjusted p < 0.05). Brain cell type proportion predictions trained with machine learning approaches using peripheral blood DNAm showed the strongest, although still modest correlations with microglia proportions estimated through cell deconvolution using brain DNAm. Further, deconvolution-estimated blood immune cell type proportions showed a nominally significant association with estimated brain stromal cell proportions, driven primarily by NK cells; however, this association was dependent on chronological age and did not survive age-residualization. Lastly, brain EAA was not associated with brain and blood cell type proportions (adjusted p < 0.05). Collectively, these results suggested that in the context of broad tissue-specificity of DNAm patterns, DNAm levels in peripheral blood might actually inform on some immune brain cell type proportions. The correlations between DNAm profiles specific to immune cell types in blood and brain were consistent with a potential link between peripheral immune and central nervous system immune functions.
Although evidence suggests that psychosocial stress is a risk factor for cognitive decline in aging adults, potential mechanisms for this association are not well understood. This cross-sectional study examined associations of two measures of self-reported psychosocial stress, including the perceived stress scale (PSS) and a stressful life events (SLE) questionnaire, with functional connectivity in four large-scale, nonoverlapping brain networks derived from resting-state functional magnetic resonance imaging (rs-fMRI). Analyses included 426 late middle-aged and older participants from the Healthy Minds for Life study of the Precision Aging® Network (M (SD) age = 64.5 (7.8) years, 71% female, 33% from underrepresented racial/ethnic groups). Higher SLE scores were associated with lower functional connectivity in the default mode, salience/ventral attention, and dorsal attention networks. Higher SLE scores were additionally associated with lower cognitive performance. Patterns of results were similar when individuals with possible cognitive impairment were excluded. These findings indicate that higher levels of psychosocial stress, particularly stressful life events, are associated with lower connectivity in several large-scale functional brain networks and suggest one mechanism by which everyday experiences may shape the aging brain.
Age-related decline in neurovascular integrity is an increasingly recognized contributor to cognitive impairment and neurodegenerative vulnerability. A central feature is blood-brain barrier (BBB) dysfunction arising from endothelial senescence, altered barrier regulation, and chronic low-grade inflammation. In parallel, aging remodels the gut microbiota, with reduced diversity, loss of short-chain fatty acid-producing commensals, and expansion of pro-inflammatory taxa. Converging evidence indicates that age-related shifts in the gut microbiota alter microbiome function and can modulate BBB physiology through microbial metabolites, immune-endothelial signaling, and systemic metabolic pathways. These data position the gut-brain axis as an important, but not sole, modulator of neurovascular aging. Preclinical and emerging human data suggest that dysbiosis lowers the threshold for BBB dysfunction, and microbiome-targeted interventions in experimental models can improve barrier-relevant features. Notably, no human trial has yet demonstrated that microbiome modulation prevents or reverses BBB impairment using validated neuroimaging or fluid biomarkers. This review synthesizes mechanisms of microbiota-BBB crosstalk in aging, distinguishes correlation from causation, and outlines translational opportunities and limitations of dietary, probiotic, and fecal microbiota-based strategies for preserving neurovascular health in older adults.
Neuroinflammation, a key factor in aging and neurodegeneration, is characterized by the increased activation of microglia, the brain's resident immune cells. Microglia play a central role in maintaining brain homeostasis, and their dysregulation during aging is increasingly implicated in the onset and progression of Alzheimer's disease (AD). However, the molecular mechanisms underlying microglial state transitions across physiological and pathological aging remain poorly understood. To address this gap, we conducted an in silico comparative transcriptomic study using publicly available datasets from two murine bulk RNA-seq including wild-type (WT) and APP/PS1 transgenic (Tg) mice at multiple ages, one human scRNA-seq dataset with multiple ages, and data obtained from SCAD-Brain. Our analyses revealed that physiological microglial aging is characterized by dynamic, non-linear gene expression trajectories, whereby genes involved in mitochondrial function, lysosomal degradation, and immune response follow a mirror-like pattern across aging. This mirror-like behavior was conserved in human microglial data across ages. In contrast, this adaptive pattern was disrupted at late-stage pathological aging in Tg mice, where sustained alterations in inflammatory, mitochondrial, and lysosomal pathways became more pronounced. Consistent with these findings, genes dysregulated in Tg mice showed similar expression trends in AD patients in the SCAD-Brain database. These results suggest that middle age may represent a critical transition stage preceding neuroinflammation and neurodegeneration, making it an attractive window to identify preventive or therapeutic targets in early AD. Collectively, this study identifies candidate pathways and genes that warrant further experimental validation in the context of AD and age-related neurodegeneration.
Cognitive aging is shaped by genetic variation, environmental factors, and health-related conditions. Until now, it is largely unclear why some individuals maintain their cognitive function, and others show progressive cognitive decline. This study uncovered determinants of distinct cognitive aging trajectories in the older population. To approach the inter-individual variability in cognitive aging, we clustered n = 696 dementia-free individuals from the prospective TREND study based on their longitudinal changes in comprehensive cognitive testing every 2 years over 13 years on average. Identified subgroups of cognitive aging were tested for differences in general physical health, motor function, mental and neuropsychological health, personality, lifestyle, diet, and genetic and biofluid markers as observed at the phenotypes' initial records. Comparing the best- and lowest-performing subgroups of cognitive aging, we found that individuals who maintain high cognitive function compared to those with low baseline and progressive cognitive decline showed significant faster gait speed, higher health-related quality of life, did sports and cognitive stimulating activities more frequently, and reported higher plant-based foods intake. Although there are fewer phenotypic differences involving the intermediate subgroups of cognitive aging, the best-performing subgroup compared to all other subgroups showed higher plant-based foods intake. Overall, this study identifies distinct, data-driven subgroups of long-term cognitive aging trajectories and reveals factors associated with these divergent paths using deeply phenotyped data. The findings highlight the substantial heterogeneity of cognitive aging and suggest that favorable trajectories are linked to modifiable behavioral and health-related characteristics, providing a foundation for future multidisciplinary strategies to promote healthy cognitive aging.
The brain continuously integrates signals from the external environment along with internal bodily cues to support adaptive cognition and homeostasis. Among these, multiple visceral rhythms, such as respiration, circadian fluctuations, and cardiac activity, contribute to the organization of intrinsic brain dynamics. The present study focuses on cardiac signals, as the heartbeat provides a continuous, quasi-periodic physiological rhythm that enables precise time-locking of neural responses and offers a tractable model for investigating brain-body interactions at rest. Interoceptive processing is influenced by factors, including arousal, emotional state, and aging, and is known to be altered in neurological conditions such as Parkinson's disease and dementia. Here, we investigated how the cortical representation of cardiac signals changes across the adult lifespan and the mechanisms underlying this reorganization. Using a large human cohort (N = 620, aged 18-88 years) with simultaneous resting-state MEG and ECG, the study found that cortical heartbeat-evoked responses (HERs) showed distinct amplitude changes in the 180-320 ms window post the heartbeat including a systematic reduction in amplitude with age. Cardiac signals modulated the phase of ongoing theta-band neural oscillations rather than altering overall power, and this phase-resetting effect became more consolidated in older adults. Source analysis revealed that resting-state HERs originated primarily from fronto-temporal regions, including orbitofrontal, frontal, and temporal pole areas, and exhibited a clear age-related shift from predominantly frontal to more temporal generators. Directed connectivity analyses revealed an age-related shift in heart-brain communication, characterized by increased heart-to-brain and decreased brain-to-heart Granger causality. Together, these findings demonstrate that cardiac processing undergoes systematic age-related reorganization, characterized by changes in response amplitude, phase dynamics, and heart-brain interactions. These alterations may contribute to broader age-related differences in cognitive functions such as attention, emotions, and time perception.
Dementia arises from multifactorial neurodegenerative processes, with growing evidence implicating blood-brain barrier dysfunction, neuroinflammation, and vascular injury as contributors to progressive brain tissue damage. Because decline in white matter microstructural integrity is a prominent feature of brain aging, biomarkers that capture this process may improve dementia risk stratification beyond conventional clinical factors. Fractional anisotropy (FA), derived from diffusion tensor imaging, reflects white matter microstructural integrity and may provide a sensitive marker of downstream injury associated with chronic vascular and barrier dysfunction. We conducted a retrospective single-center study of 528 participants, including individuals with dementia (n = 176), age-matched cognitively normal older adults (n = 176), and a young healthy reference cohort (n = 176), all of whom underwent standardized 3-Tesla diffusion MRI. Dementia prediction was evaluated using elastic net-regularized logistic regression with nested tenfold cross-validation, incorporating 16 prespecified clinical and imaging predictors. Corpus callosum FA showed the largest standardized coefficient within the penalized model, exceeding all demographic and clinical variables. The model demonstrated strong discrimination between dementia and age-matched controls (area under the receiver operating characteristic curve [AUC] = 0.970; sensitivity = 90.9%; specificity = 93.2%). FA also declined stepwise from young adults to cognitively normal older adults to participants with dementia, consistent with progressive white matter microstructural injury across the aging-dementia continuum. These findings indicate that corpus callosum FA provides additional predictive value beyond conventional risk factors and support diffusion MRI as a potentially scalable biomarker of age-related white matter microstructural injury with potential utility for dementia risk stratification and biologically informed prevention strategies.
Age- and disease-related declines in brain health contribute to impairments in physical function, yet effective approaches to lessen these declines remain limited. Overall health is governed by a network of interdependent organ systems, such that dysfunction in one system can propagate across others. Although the brain has been viewed as a top-down regulator of vital functions, evidence indicates that cognition is affected by signals from peripheral organs. This interorgan communication likely explains the coexistence of Alzheimer's disease and related dementias with cardiovascular and metabolic disorders characterized by overlapping pathophysiology. Skeletal muscle and the peripheral vasculature are key contributors to this and represent modifiable systems that can alter brain structure and function. Skeletal muscle regulates myokine release through motor neuron function, contractile activity, and metabolic perturbations, thereby influencing neuroplasticity, mitochondrial function, and inflammatory signaling, and may affect measures of peripheral vascular function, like reactive hyperemia. Other properties of the vasculature, including arterial stiffness, directly affect cerebral perfusion and blood-brain barrier permeability. These systems form a muscle-vascular-brain axis that contributes to brain health and impacts the risk of cognitive impairment. Therefore, our aim was to synthesize the current understanding of interactions among skeletal muscle, the peripheral vasculature, and the brain, and their collective role in maintaining cognitive health. We also highlight recent clinical trials and emerging strategies affecting interorgan crosstalk. These conclusions support a model in which lifestyle interventions targeting peripheral systems, such as resistance training, may preserve brain health across all populations, offering scalable approaches applicable across the lifespan.
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Blood-brain barrier (BBB) integrity naturally declines with age. Brain endothelial cells (ECs) and pericytes (PCs) form the BBB, and aging impairs tight junctions, likely via altered PC-to-EC signaling. However, the molecular mechanisms underlying this impairment remain unclear. Using single-cell RNA sequencing, we profiled 68,316 brain ECs expressing 15,564 genes from young and old mice. Unsupervised clustering and annotation revealed five distinct EC subtypes-Capillary EC1, Capillary EC2, Arterial EC, Venous EC1, and Venous EC2-defined by marker genes Mfsd2a, Plvap, Bmx, Nr2f2, and Vcam1, respectively. Aging shifted EC subtype distribution, with reduced Capillary EC1 (45% vs. 57%) and increased Arterial (33% vs. 16%) and Venous ECs (12% vs. 2%) compared with young mice. Mio analysis further showed that Capillary EC1 and Venous EC2 neighborhoods were less abundant in aged brains. Biotin metabolism was decreased in old vs. young mice, particularly within Capillary EC1, Capillary EC2, and Arterial EC. Although widespread gene downregulation was observed across EC subsets, overall expression trends were largely consistent among clusters. Key genes-Ramp2, Hbb-bs, Ly6c1, Calm1-were less abundant, whereas Rasgrf2 was uniquely enriched in aged mice. Immunohistochemistry confirmed reduced LY6C and RAMP2 and elevated RASGRF2 in aged mouse and human brains. Cell-cell interaction analyses revealed age-associated remodeling of ligand-receptor signaling. Enrichment analyses implicated pathways involved in neurovascular integrity, inflammation, amyloid processing, and vascular remodeling. Collectively, these findings show that aging reprograms EC subtype composition, gene expression, and metabolism, thereby contributing to BBB disruption and neurovascular dysfunction.
Electroencephalography (EEG) research systematically excludes participants with textured hair, limiting generalizability. While inclusive hardware offers a solution, it remains unvalidated in dynamic settings. This study bridges this ecological gap by determining if equitable data quality is achievable across racial groups during a complex Mobile Brain/Body Imaging (MoBI) paradigm. We recruited 17 older adults from racially and ethnically underrepresented groups (REUG) and 17 age-and-sex-matched White older adults. Participants completed an auditory oddball task while sitting and during active standing. EEG was recorded using a dry-brush-electrode system paired with culturally sensitive procedures. The primary outcome was event-related potential (ERP) data quality, quantified using the Standardized Measurement Error (SME) for P3 amplitude and latency. Total data loss was comparable between White (8.29%) and REUG participants (9.88%), with no group differences (p = 0.91) or group×condition interactions (p = 0.82). We found no significant main effects of group or group-by-condition interactions on any SME measure (all p > 0.05), and equivalence testing confirmed that SME for P3 amplitude and latency was statistically equivalent in 16 of 18 stimulus × postural comparisons. A sensitivity analysis restricting the REUG group to participants with textured hair (REUG-T, n = 9) yielded a near-identical pattern (15 of 18 comparisons). Signal‑to‑noise ratio at Fz for frequent stimuli increased from sitting to standing (F = 10.33, p = 0.002, adjusted p = 0.036). Behavioral performance was similar across groups. This study provides the first evidence that equitable ERP data quality is achievable across racial groups during active MoBI by combining inclusive hardware with culturally sensitive protocols. These findings confirm that the technological incompatibility underlying historical underrepresentation is surmountable when paired with culturally sensitive protocols, enabling more inclusive and generalizable cognitive neuroscience.
Chronic aerobic exercise is known to protect against brain and cognitive aging in animals, but it remains unclear whether these benefits are consistent across the span of older adulthood. Using time-varying effect modeling (TVEM) analysis, this study investigated how the associations between changes in cognition and brain network functional connectivity (FC), induced by a 6-month aerobic exercise intervention, vary with age among older adults aged 55 to 80 (n = 107). Participants were divided into two groups based on exercise intensity: moderate-to-vigorous (ModVig group) and light-intensity (Light group). Before and after the intervention, participants completed cognitive tasks measuring executive function (EF) and processing speed (PS) and underwent resting-state fMRI sessions. FC was assessed across large-scale brain networks, including the frontoparietal control (FPCN), default mode (DMN), dorsal attention (DAN), limbic (LN), salience (SN), somatomotor (SMN), and visual network (VN). Change scores for each cognitive task and FC network were calculated by subtracting pre-intervention scores from post-intervention scores. Older adults in the ModVig group demonstrated improved PS performance at ages 58 to 65 and increased FC at ages 67 to 69 in the DAN. When individuals were exposed to ModVig intensity exercise, increases in FC within the FPCN, DMN, and SN were associated with improved EF and PS performance in those in their mid-60s to mid-70s. These findings support the importance of targeting higher moderate-to-vigorous aerobic exercise intensity for interventions, particularly in this age group, to enhance brain and cognitive health.
The emergence of agentic artificial intelligence (AI), such as Anthropic's Claude Mythos, challenges the conventional understanding of human agency. This paper explores differences between computational intelligence and human aging and discusses how advanced AI can intersect with the lived experience and mental health of older adults. Unlike the data-driven, simulation-based, nonconscious functions of AI, consciousness is embodied, relational, and historically evolved. Aging changes the brain, the body, and the body-brain communication. Despite cognitive compensation by recruitment of supplemental neural networks, neural aging changes human experience. Along with neurobiology, consciousness is shaped by the older person's identity, which integrates experiences of successes, reversals, love, loss, suffering, and mortality into a coherent life story. Applying the frameworks of poetic naturalism and "hybrid reason," this paper discusses the possibility of a symbiotic AI-human relationship. In this paradigm, AI manages analytical tasks and offers cognitive support (the "how"), while the aging individual provides intentionality, ethical boundaries, and historical perspective (the "why"). Appropriately managed, the human-AI interaction will be a relationship not of subordination but of mutual optimization. As the natural advocates for older adults, geriatric mental health professionals must steward the integration of AI in aging care, ensuring a synergy in which technology scaffolds and augments human function while it preserves the person's agency and dignity. Advocacy should focus both on minimizing the AI risks of manipulation, over-dependence, and privacy loss and on promoting user-centered designs that can make technology accessible and welcoming for older adults.
Normal aging is accompanied by cognitive decline, structural and functional brain changes. Cognitive training is a potentially effective intervention for cognitive improvement. Transfer of training gains to untrained tasks is the ultimate goal of cognitive training. However, the neural mechanisms underlying successful transfer remain underinvestigated. To examine the predictive role of resting-state functional connectivity in the transfer of training gains. We analyzed resting-state fMRI and cognitive data of 181 healthy older adults (mean age: 68 years) who underwent a 4-week cognitive training at three study sites. The control group consisted of 54 older adults. Participants underwent neuropsychological assessments before and directly after the training, as well as 12 weeks after. We used aggregate scores representing working memory, memory and executive functions to assess transfer effects. Baseline resting-state fMRI was used to investigate functional connectivity. We used a seed-based and an independent component analysis approach to examine brain network activity. The majority of our participants transferred cognitive training gains successfully over a three-month period. Baseline resting-state functional connectivity within the default mode network and the central executive network did not predict transfer of training gains. Baseline resting-state functional connectivity of large-scale networks does not appear to predict who will benefit from cognitive training in healthy older adults. These findings contribute to a better understanding of the functional brain mechanisms underlying transfer of training gains and highlight the need for larger, multi-modal neuroimaging studies to identify reliable neural predictors of cognitive training outcomes.
Emerging evidence has reported associations between more negative views on aging and poorer performance on cognitive tasks. However, findings have been inconsistent. Gender differences and the cognitive status of participants may help explain these discrepancies. This study therefore investigated (a) the associations of gender, presence of mild cognitive impairment (MCI), and their interaction with expectations regarding aging (ERA, a measure assessing views on aging); and (b) the associations between subjective and objective cognitive measures and ERA in cognitively normal (CN) individuals and those with MCI. We report cross-sectional data from the Personality and Total Health Through Life Project (PATH), comprising 1,562 participants (48% females, M age = 75.06 (SD = 1.50), age range = 72-79). ERA were assessed using the 12-item ERA scale, covering global ERA and domain-specific expectations related to physical health, mental health, and cognitive function. Objectively-assessed global cognition, memory, working memory, and processing speed, and subjective memory complaints were assessed using standardized neuropsychological test batteries. Multiple linear regression models were estimated. Among CN participants, women reported more positive ERA than men (β = 4.42, p < .001). Participants with MCI exhibited lower ERA than CN individuals (β = -6.05, p < .001). Subjective memory complaints were associated with lower ERA both in CN (β = -5.38, p < .001) and MCI (β = -8.85, p < .01) participants. Findings support an association between greater current cognition and more positive ERA. Interventions promoting brain health could benefit from a component fostering positive ERA. For individuals experiencing cognitive decline, future research may evaluate strategies that encourage the maintenance of realistic, yet optimistic aging perceptions.
Physical activity (PA) is often proposed as a modifiable strategy to reduce cognitive decline and dementia risk, particularly among individuals at elevated genetic risk for Alzheimer's disease (AD). However, it remains unclear whether the existing literature tests PA at the disease stage and in the populations most likely to show benefit. This umbrella review evaluated whether associations between PA and cognitive, fluid biomarker, neuroimaging, and vascular/metabolic outcomes differ by apolipoprotein E ε4 (APOE ε4) genotype across stages of cognitive aging, with particular attention to how study design and baseline cognitive status shape interpretation of the evidence. Systematic reviews and meta-analyses were screened for primary studies examining PA in adults classified by baseline cognitive status as cognitively unimpaired, mild cognitive impairment (MCI), or dementia. Primary studies reporting APOE ε4-stratified outcomes were extracted and qualitatively synthesized by outcome domain, cognitive stage, and study design. Of 2,100 records identified, seven systematic reviews met inclusion criteria, yielding 68 unique primary studies. Favorable associations between PA and cognitive, biomarker, neuroimaging, and vascular/metabolic outcomes were most often reported in observational studies of younger or cognitively unimpaired adults. Several studies suggested stronger associations among APOE ε4 carriers, including midlife cognitive associations, neuroimaging markers, and vascular/metabolic outcomes such as lipid profiles. In contrast, randomized controlled trials were few, generally enrolled older adults with MCI or dementia, included small APOE ε4 subgroups, and reported largely null or mixed genotype-specific effects. The current evidence does not establish a definitive APOE ε4-specific preventive effect of PA. Future studies may be most informative if they target earlier-stage, low-active, or metabolically at-risk APOE ε4 carriers using objective PA measures and proximal vascular, metabolic, imaging, or blood-based biomarker outcomes.
Semantic memory decline is increasingly recognized as an early feature of Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI), yet the neural dynamics supporting automatic and controlled semantic retrieval in healthy aging remain poorly defined. This study examined task-evoked oscillatory activity during audiovisual object recognition in young adults (YA; N = 27), healthy older adults (OA; N = 33), and individuals with amnestic MCI (N = 21). Participants judged object orientation while viewing living and nonliving images paired with congruent or incongruent characteristic sounds, allowing semantic relationships to be manipulated under implicit retrieval demands. Accuracy was high across groups, although participants with MCI showed reduced performance under the more perceptually challenging inverted conditions. Reaction times were slower in OA than YA and further slowed in MCI, with group differences varying by object animacy and semantic congruency. Event-related spectral perturbation analyses revealed distinct group-related patterns. Healthy older adults showed reduced early and increased late theta activity in frontocentral and parieto-occipital regions, consistent with delayed recruitment of control-related and perceptual-attentional processes. In contrast, MCI participants showed elevated and less condition-sensitive posterior alpha power, together with task- and condition-specific differences in frontocentral theta. The principal pattern of delayed theta recruitment in healthy aging and elevated posterior alpha in MCI was also observed in a supplementary task requiring explicit audiovisual semantic judgments. These findings provide preliminary evidence that healthy aging and amnestic MCI are associated with partly distinct patterns of task-evoked oscillatory activity during audiovisual semantic processing.
To better understand HIV and cardiovascular disease (CVD) effects on brain white matter during HIV infection, advanced diffusion imaging and comprehensive predictor analyses are essential. Prospective observational cohort study. 84 virally suppressed people with HIV infection (PWH) and 48 uninfected controls underwent T1-weighted, FLAIR, and diffusion MRI at baseline and 24 months later (75 PWH and 40 controls). White Matter Hyperintensity (WMH) volumes were derived from structural scans. Fixel-based analysis tract-based metrics included fibre density (FD), fibre cross-section (FC) and fibre density and cross-section (FDC). Relative to controls, mixed models showed significant reductions (p<.05 - p<.01) of FC, and lower FDC to a lesser extent, in multiple long cortical association tracts, and within striatal- and thalamic-frontoparietal connections in PWH at both time points. Higher CVD risk was associated with reduced FC in the arcuate fasciculus and FDC in the cingulate gyrus (p<.05). In PWH, more severe cognitive impairment and longer duration of HIV disease was associated with worse FDC across multiple tracts (p<.03 - p<.001). Lower baseline CD4 counts was associated with lower FD in the frontal association tracts (p<.05 - p<.005). Higher WMH volume was associated with higher CVD risk (periventricular p<.001, deep p<.03), but not HIV status. Major brain white matter tracts are impacted by HIV status, HIV duration, cognitive impairment, baseline CD4, and CVD risk to a lesser extent, despite equal WMH burden between infection groups. Our study provides further evidence of active immuno-vascular underpinning of HIV neuropathogenesis on fine white matter structure despite controlled HIV.