Frontiers in Aging Neuroscience最新文献

Introduction: Age-related changes in brain signal complexity are associated with cognitive decline and reduced neural adaptivity in older adults. Exergaming offers a promising prophylactic intervention combining physical and cognitive training. The aim of the present study was to assess how exergaming alters the temporal trajectory of brain signal complexity at rest and during gameplay in older adults.

Methods: Twenty-eight healthy older adults participated in a 4-week exergaming intervention. Electroencephalography was recorded using 64 electrodes at rest (pre- and post-intervention) and during exergaming (pre-, mid-, and post-intervention). Brain signal complexity was quantified using multiscale entropy across 64 time scales on preprocessed signals.

Results: Post-intervention resting-state analysis revealed significant reductions at fine and increases at coarse scales in frontal, central, and posterior entropy. During gameplay, entropy declined widespread by mid-intervention, particularly at coarse scales over frontal, central and temporal regions. From mid- to post-intervention, the decline narrowed leaving a net pre-to-post reduction concentrated at coarse scales in these regions.

Discussion: Resting-state changes indicated a shift toward a younger brain profile, characterized by a transition from age-related increases in local processing to enhanced distributed processing, which may potentially mitigate the rise in neural modularity associated with aging. During gameplay, brain signal complexity decreased in week 2, followed by a modest change by week 4, consistent with the framework in which complexity initially streamlines and then adjusts toward a task-specific optimum. These findings suggest that exergaming can beneficially modulate brain complexity in older adults, offering the potential to reduce age-related neural decline and support healthy brain aging.

Aging is associated with changes in sensorimotor control that contribute to functional decline, mobility limitations, and increased fall risk. Traditional motor assessments often rely on subjective measures, highlighting the need for objective, quantitative tools. We developed three robot-based tasks using the vBOT planar manipulandum to evaluate sensorimotor performance in healthy young (<35 years) and older (>60 years) adults. These tasks uniquely combined bimanual control and altered dynamic conditions to assess age-related differences. The first task required bimanual coordination to control a virtual 2D arm over 400 center-out and return trials, targeting de novo motor learning. The second task involved unimanual reaching with the dominant hand, consisting of 200 trials in a null-field condition followed by 200 trials with object-like dynamic forces. The third task similarly began with 200 null-field trials and then introduced a viscous force field in the final 200 trials, with fast movements rewarded to encourage peak performance. This task also enabled comparison between dominant and non-dominant arms. All tasks detected age-related performance differences, with the viscous resistance task proving most sensitive to declines in movement speed, force generation, and response onset time. Scoring mechanisms that encouraged brisk performance amplified these effects. Across tasks, older adults generally moved more slowly, took longer to complete tasks, exerted lower peak forces, and had longer response onset times. However, some older participants performed comparably to younger individuals. In the third task, dominant arm performance consistently exceeded that of the non-dominant arm. These results demonstrate that robot-based tasks can sensitively quantify age-related sensorimotor decline and may offer valuable metrics for clinical assessment and monitoring.

Background: Psychosis, including delusions and hallucinations, is a significant neuropsychiatric symptom in Alzheimer's disease (AD) associated with poor prognosis. The relationship between psychosis and AD pathology remains controversial. This study investigates the role of AD pathology in mediating the association between psychosis and cognitive impairment.

Methods: Data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We included individuals with a Clinical Dementia Rating (CDR) score of 0.5 or higher. Among a total of 833 individuals, 96 individuals with psychosis were matched to 192 individuals without psychosis using propensity scores based on age, sex, education level, and follow-up duration. Baseline cognitive performance was assessed using composite memory scores (ADNI-MEM) and executive function scores (ADNI-EF). AD pathology was measured using baseline cerebralspinal fluid (CSF) levels of β-amyloid_1-42 (Aβ_1-42), hyperphosphorylated-tau₁₈₁ (p-tau₁₈₁), and total tau. Logistic regression was performed to evaluate the association of psychosis with baseline cognitive performance and CSF biomarkers. Mediation analysis was conducted to assess whether AD biomarkers mediate the relationship between cognitive impairment and psychosis.

Results: Psychosis was significantly associated with worse ADNI MEM score (β = -0.622, p = 0.013) and worse ADNI EF score (β = -0.516, p = 0.003), and lower CSF Aβ_1-42 levels (β = -0.009, p = 0.007). No significant associations were found with p-tau₁₈₁ or total tau levels. Mediation analysis revealed that low CSF Aβ_1-42 levels mediated the relationship between cognitive impairment and psychosis.

Conclusion: These findings suggest that amyloid pathology may mediate the effect of baseline cognitive impairment on psychosis during disease in AD, highlighting a potential pathological link between cognitive decline and psychotic symptoms.

Introduction: Perioperative neurocognitive disorder (PND) describes a range of cognitive impairments associated with surgery and anaesthesia, often driven by neuroinflammation. This study explored a novel adult mouse model, in which preoperative subclinical infection, induced by low-dose lipopolysaccharide (LPS) in combination with surgery, led to cognitive dysfunction in adult mice.

Methods: Adult male C57BL/6J mice were treated with 0.75 mg/kg LPS two hours before undergoing tibial fracture fixation or appendicectomy. Spontaneous activity and anxiety-like behaviours were tested by open field test. Cognitive outcomes were evaluated using the novel object recognition test and morris water maze. Inflammatory markers and synaptic proteins in the hippocampus were analysed through ELISA, RT-qPCR, and Western blot, while proteomics provided deeper insights into molecular changes.

Results: We found that preoperative LPS sensitised the immune system, leading to heightened neuroinflammation and microglial activation after surgery. This was accompanied by memory and learning impairments. Key synaptic proteins, including PSD-95, GAP-43, SYN and mature BDNF, were significantly reduced, indicating disrupted synaptic function. Proteomics revealed changes in pathways related to immune responses, synaptic organisation, and energy metabolism, providing a potential molecular basis for these cognitive deficits.

Discussion: This study provided a practical adult mouse model for PND, demonstrating that low-dose LPS followed by surgery induced an inflammatory response, leading to postoperative impairments in learning and memory.

Purpose: To explore neurodynamic bases underlying subjective cognitive decline (SCD) based on edge-centric functional network.

Methods: 211 SCD patients and 210 healthy controls (HC) were recruited from the Alzheimer's Disease Neuroimaging Initiative. Edge time series (ETS) were obtained based on resting-state functional magnetic resonance data. The top 10% co-fluctuation signals of all time points in ETS were extracted to construct the high-amplitude frame networks, and the co-fluctuation signals from the remaining time points were used to construct the low-amplitude frame networks. In both network states, the graph theory and network-based statistics (NBS) analyses were used to compare SCD and HC. The correlation of the imaging indicators with cognitive scores and apolipoprotein E (APOE) ε4 genes was performed by Spearman correlation analysis.

Results: SCD exhibited lower peak amplitude and longer trough-to-trough duration (TTD) compared to HC. In both network states, the normalized clustering coefficient, normalized characteristic path length, small-worldness, and global efficiency of SCD were significantly reduced, and the altered nodal centralities of SCD predominantly exhibited a decreasing trend. However, the high-amplitude frame network identified more altered brain regions compared to the low-amplitude frame network. Furthermore, a SCD-related subnetwork was found in the high-amplitude frame network, which was composed of 11 brain regions and 13 edges. TTD was positively related to the number of APOE ε4 genes; the normalized characteristic path length, the betweenness centrality of right postcentral gyrus, and the connection between bilateral angular gyrus were correlated with cognitive scores.

Conclusion: Our findings demonstrate that the edge-centric network framework reveals details of brain network alterations in SCD through different perspectives, and these alterations hold potential as novel biomarkers for SCD.

Alzheimer's disease (AD), characterized by progressive cognitive decline, memory impairment and behavioral disturbances, is the most common form of dementia, and no disease-modifying treatments are available to halt or slow its progression. Amyloid-beta (Aβ) is suggested to play a pivotal role in the pathogenesis of AD, and enhancing the clearance of Aβ from the brain has emerged as a major research direction. As the primary receptor for Aβ clearance at the blood-brain barrier (BBB), low-density lipoprotein receptor-related protein 1 (LRP1) plays a crucial role in regulating Aβ transport and metabolism. Understanding the mechanisms through which LRP1 functions, as well as the factors that influence its activity is essential for enhancing Aβ clearance from the brain and developing targeted therapeutic strategies for Alzheimer's disease. In this review, we introduce the transport of Aβ across the BBB, followed by a discussion of the basic structure and function of LRP1 and its role in AD progression. Then, we summarize factors affecting LRP1 function and current advances in LRP1-targeted therapies. Finally, we explore the potential of LRP1 as a therapeutic target for AD. So, LRP1 may be a central modulator of Aβ dynamics and a clinically actionable target for treatment of Alzheimer's disease.

Introduction: Previous studies have illuminated a significant genetic component in motor neuron disease (MND) pathogenesis, with several causative genes identified. However, a substantial proportion of MND cases remain genetically unexplained, particularly regarding the comprehensive contribution of rare, high-impact variants across the exome.

Methods: Leveraging whole-exome sequencing data from nearly half a million UK Biobank participants, we systematically investigated the association between high-confidence protein-truncating variants (HC PTVs) and MND risk in a Caucasian subset. Our large-scale gene-based association analysis utilized REGENIE software and LOFTEE-defined HC PTVs.

Results: We identified significant preliminary associations between HC PTVs in 14 genes and an increased risk of MND. Notably, while NEK1 has been previously implicated in ALS, the remaining 13 genes (BLVRB, KLHL32, RIMS2, DYDC2, DCBLD1, ANXA4, COMP, TRIM42, ANO4, NFX1, CFAP206, CKAP2L, and ANGPTL4) show preliminary associations as novel candidate loci for the disease. Functional enrichment analyses further indicated that these genes are significantly involved in critical biological pathways, including collagen-containing extracellular matrix organization and ciliary function. Furthermore, tissue specificity analysis highlighted a strong enrichment of these genes' expression in brain regions, with the hypothalamus showing the highest specificity.

Discussion: These findings suggest a potential expansion of the known genetic landscape of MND, and highlight novel biological pathways implicated in its pathogenesis. This study underscores the power of large-scale population genetics in uncovering critical disease mechanisms and offers new avenues for mechanistic research and therapeutic development for MND, pending independent validation.

Background: The rising global burden of Parkinson's disease (PD) is often related to cognitive decline. Exploring neuroimaging biomarkers is crucial for early diagnosis.

Methods: The purpose of the exploratory research was to look at the differences in cortical activation and functional connectivity between PD patients and healthy controls (HC), as well as among cognitive subgroups of PD, using multichannel functional near-infrared spectroscopy (fNIRS) during a verbal fluency task. A total of 39 PD patients and 20 age-matched HC were assessed.

Results: Results showed significantly reduced oxygenated hemoglobin (oxy-Hb) concentrations in PD patients, particularly in the right temporal lobe, compared to HC. Among PD cognitive subgroups, patients with Parkinson's disease dementia (PDD) displayed notably lower oxy-Hb levels in key brain regions compared to PD with normal cognition (PD-NC) and PD with mild cognitive impairment (PD-MCI). The analysis among the four groups showed that the HC group and the PDD group had the most differences in activation. Functional connectivity analyses between PD subgroups revealed that PD-NC patients had stronger connectivity between prefrontal regions than PD-MCI and PDD groups.

Conclusion: Our findings generate the hypothesis that PD is associated with altered neurovascular responses and disrupted cortical network organization in the frontal and temporal lobes, especially in cognitively impaired subgroups. These results support the potential utility of fNIRS for characterizing cognition-related neural alterations in PD and provide a basis for future hypothesis-driven and longitudinal investigations.