The impact of amnestic mild cognitive impairment (aMCI) on cerebral oxygenation and cardiovascular responses to mental and physical challenges in elderly adults is unclear. This study compared the responses to mental (serial sevens test) and physical (isometric handgrip) challenges in older adults with vs. without aMCI.

Thirty-one aMCI (71.5 ± 1.1 years old) and 30 cognitively normal (70.8 ± 1.1 years old) adults participated in the study. Heart rate (HR), mean arterial pressure (MAP), systemic arterial oxygen saturation (SaO2), prefrontal cortical oxyhemoglobin (O2Hb) and deoxyhemoglobin (HHb) contents, and tissue oxygen saturation (ScO2) were continuously monitored during 2-min serial sevens mental arithmetic test and 1-min isometric handgrip at 30% of maximal voluntary contraction. Test results in the aMCI vs. non-MCI subjects were compared by two-factor ANOVA.

Cardiovascular and tissue oxygenation responses to testing were similar in the two groups. Although MAP increased similarly during the mental and physical challenges, increases in HR (P = 0.020), SaO2 (P < 0.001), ScO2 (P = 0.001) and O2Hb (P = 0.022) were greater during the mental vs. physical challenges in both aMCI and cognitively normal subjects.

The mental arithmetic challenge increased the metabolic demand of the prefrontal cortex to a greater extent than the physical task. Cerebral O2 content increased more appreciably during the mental vs. physical challenges, in parallel with greater increases in HR. However, aMCI did not alter these physiological responses to mental or physical challenges.

The number of people living with dementia and/or cognitive impairment worldwide is rising with a negative effect on quality of life for many older adults. This study aims to examine the factors associated with cognitive function among older adults in Kuwait.

This cross-sectional study recruited 253 older adults ≥ 60 years from a Geriatric outpatient unit in Kuwait. Cognitive function (dependent variable) was assessed using the Arabic version of the Mini-Mental State Examination (MMSE) with scores < 24 indicative of cognitive impairment. Biochemical, nutritional, clinical, lifestyle, anthropometric, and sociodemographic independent variables were included.

A normal MMSE score was reported for 51.0% (n = 129) of the sample, with 34.7% and 14.2% of participants having mild and moderate/severe cognitive impairment, respectively. Multivariate ordinal logistic regression analysis indicated that Type 2 diabetes was associated with more than double the odds of cognitive impairment (OR = 2.15, 95% CI: 1.19-3.94; P = 0.01). Each additional level of education was associated with a lower likelihood of cognitive impairment (OR = 0.34, 95% CI: 0.26-0.43; P < 0.001).

This study identifies key risk factors associated with cognitive impairment in older Kuwaiti adults. These findings underscore the need for targeted interventions to mitigate cognitive decline in aging populations and provide context-specific data to support policy decisions.

CRISPR/Cas9 technology has revolutionized genetic and biomedical research in recent years. It enables editing and modulation of gene function with an unparalleled precision and effectiveness. Among the various applications and prospects of this technology, the opportunities it offers in unraveling the molecular underpinnings of a myriad of central nervous system diseases, including neurodegenerative disorders, psychiatric conditions, and developmental abnormalities, are unprecedented. In this review, we highlight the applications of CRISPR/Cas9-based therapeutics as a promising strategy for management of Alzheimer's disease and transformative impact of this technology on AD research. Further, we emphasize the role of CRISPR/Cas9 in generating accurate AD models for identification of novel therapeutic targets, besides the role of CRISPR-based therapies aimed at correcting AD-associated mutations and modulating the neurodegenerative processes. Furthermore, various delivery systems are reviewed and potential of the non-viral nanotechnology-based carriers for overcoming the critical limitations of effective delivery systems for CRISPR/Cas9 is discussed. Overall, this review highlights the promise and prospects of CRISPR/Cas9 technology for unraveling the intricate molecular processes underlying the development of AD, discusses its limitations, ethical concerns and several challenges including efficient delivery across the BBB, ensuring specificity, avoiding off-target effects. This article can be helpful in better understanding the applications of CRISPR/Cas9 based therapeutic approaches and the way forward utilizing enormous potential of this technology in targeted, gene-specific treatments that could change the trajectory of this debilitating and incurable illness.

Epidemiological characteristics of cerebral small vessel disease (cSVD) in the general population, especially among rural older adults, are poorly defined. Here, we reported the prevalence, distribution, and associated factors of cSVD in a rural-dwelling older population in China. This population-based cross-sectional study included 1272 older adults (age ≥60 years; mean age 69.43 years; 58.57% women) who underwent structural brain MRI scans (3.0T) in 2018-2020. MRI markers of cSVD were assessed following the Standards for Reporting Vascular Changes on Neuroimaging-1 criteria. We performed descriptive and regression analyses. The overall prevalence was 20.31% for cerebral microbleeds (CMBs), 26.87% for lacunes, 60.06% for basal ganglia perivascular spaces (PVS), 76.31% for centrum semiovale PVS, 95.74% for deep white matter hyperintensities (WMHs), and 94.17% for periventricular WMHs. The prevalence increased with advancing age for all cSVD markers, except PVS in the centrum semiovale. The prevalence of moderate-to-severe deep WMHs was higher in women than in men (P = 0.005). Older age and hypertension were associated with increased likelihoods of all cSVD markers. A higher body mass index was linked to more WMHs. Coronary heart disease (CHD) was associated with WMHs, CMBs, and lacunes. Our study suggests that cSVD, especially WMHs and PVS, was highly prevalent among rural Chinese older adults. Older age, hypertension, and CHD are associated with distinct cSVD. Future prospective cohort studies are warranted to determine incidence and major risk factors of cSVD, which could facilitate preventive interventions to reduce the burden of cSVD in resource-limited settings.

Until now, it has been challenging to examine what are the causes of the cognitive decline associated with hypertension and to understand the predictive variables that indicate the development of cognitive impairment in people with hypertension. This work is aimed to understand the interplay between heart rate variability and blood pressure and whether their combination can predict cognitive performance. This cross-sectional observational study involved patients with fifty-two adults with essential hypertension and a control group of 41 healthy adults without hypertension. Except for the diagnosis of hypertension the same inclusion criteria were adopted to balance the groups. The overall sample was divided based on HRV metrics. A complete neuropsychological battery was administered and resting heart rate variability in individuals with and without hypertension was measured. Hypertensive patients with altered HRV had worse cognitive performance, particularly in the executive domain. Low HRV and hypertension have interdependent and combined association with cognitive impairment. Our results indicate that the association between hypertension and cognitive performance is affected by HRV. For neuroscientists, it's time to look beyond the brain. And clinicians who treat the body can't assume that the brain is above involvement.

The impact of amnestic mild cognitive impairment (aMCI) on short-term memory (STM) and learning performance assessed with different memory modalities was unknown. This study examined differences in STM and learning ability between verbal and visuospatial memory-modalities in older adults with aMCI.

Thirty-nine aMCI subjects (71.5 ± 6.0 yrs) and 33 non-MCI (control) subjects (71.1 ± 5.7 yrs) of similar age and educational attainment consented to participate in the study. Short-term memory was assessed using Digit-Span-Test (DST), California-Verbal-Learning-Test-2nd edition - short-form (CVLT-II), and Brief-Visuospatial-Memory-Test-Revised (BVMT-R); CVLT-II and BVMT-R assessed verbal-and visuospatial-learning, respectively.

DST-Backward (p = 0.016) and DST-Sequencing (p < 0.001) scores were significantly lower in the aMCI vs. control subjects (Student's t-test), but DST-Forward scores did not differ (p = 0.237). Immediate and delayed free-recall scores in both CVLT-II (p < 0.001) and BVMT-R (p < 0.001) were lower in the aMCI subjects. The immediate free-recall scores in both tests improved with repeated trials (two-factor ANOVA: p < 0.001 for trial factor) to similar extents in the aMCI and control groups with no significant interaction of the trial and group factors (p = 0.266 in CVLT-II and p = 0.239 in BVMT-R).

Amnestic MCI subjects have diminished STM but intact learning ability. Differences in STM of older adults with vs. without aMCI are more readily distinguished by word-verbal memory and/or visuospatial memory testing than digit-verbal memory testing.

Research in aging, impairment, and Alzheimer's disease (AD) often requires powerful computational models for discriminating between clinical cohorts and identifying early biomarkers and key risk or protective factors. Machine Learning (ML) approaches represent a diverse set of data-driven tools for performing such tasks in big or complex datasets. We present systematic demonstration analyses to compare seven frequently used ML classifier models and two eXplainable Artificial Intelligence (XAI) techniques on multiple performance metrics for a common neurodegenerative disease dataset. The aim is to identify and characterize the best performing ML and XAI algorithms for the present data.

We accessed a Canadian Consortium on Neurodegeneration in Aging dataset featuring four well-characterized cohorts: Cognitively Unimpaired (CU), Subjective Cognitive Impairment (SCI), Mild Cognitive Impairment (MCI), and AD (N = 255). All participants contributed 102 multi-modal biomarkers and risk factors. Seven ML algorithms were compared along six performance metrics in discriminating between cohorts. Two XAI algorithms were compared using five performance and five similarity metrics.

Although all ML models performed relatively well in the extreme-cohort comparison (CU/AD), the Super Learner (SL), Random Forest (RF) and Gradient-Boosted trees (GB) algorithms excelled in the challenging near-cohort comparisons (CU/SCI). For the XAI interpretation comparison, SHapley Additive exPlanations (SHAP) generally outperformed Local Interpretable Model agnostic Explanation (LIME) in key performance properties.

The ML results indicate that two tree-based methods (RF and GB) are reliable and effective as initial models for classification tasks involving discrete clinical aging and neurodegeneration data. In the XAI phase, SHAP performed better than LIME due to lower computational time (when applied to RF and GB) and incorporation of feature interactions, leading to more reliable results.

This study assessed the effectiveness of three digital screening tools in detecting cognitive impairment (CI) in a large cohort of community-dwelling elderly individuals and investigated the relationship between key digital features and plasma p-tau217 levels.

This community-based cohort study included 1,083 participants aged 65 years or older, with 337 diagnosed with CI and 746 classified as normal controls (NC). We utilized two screening approaches: traditional methods (AD8, MMSE scale, and APOE genotyping) and digital tools (drawing, gait, and eye tracking). LightGBM-based machine learning models were developed for each digital screening tool and their combination, and their performance was evaluated. The correlation between key digital features and plasma p-tau217 levels was analyzed as well.

A total of 21 drawing, 71 gait, and 35 eye-tracking parameters showed significant differences between the two groups (all p < 0.05). The area under the curve (AUC) values for the drawing, gait, and eye-tracking models in distinguishing CI from NC were 0.860, 0.848, and 0.895, respectively. The combination of eye-tracking and drawing achieved the highest classification effectiveness, with an AUC of 0.958, and accuracy, sensitivity, and specificity all exceeded 85%. The fusion model achieved an AUC of 0.928 in distinguishing mild cognitive impairment (MCI) from NC. Additionally, several digital features (including two drawing, ten gait, and one eye-tracking parameters) were significantly correlated with plasma p-tau217 levels (all |r| > 0.3, p < 0.001).

Digital screening tools offer objective, accurate, and efficient alternatives for detecting CI in community settings, with the fusion of drawing and eye-tracking providing the best performance (AUC = 0.958).

Hypertension is one of the most common diseases in the world, impacting global life expectancy and associated with an increased risk of cognitive impairment.

This study aimed to develop a nomogram that accurately predicts the risk of cognitive impairment in hypertensive patients using the National Health and Nutrition Examination Study (NHANES).

A total of 1517 hypertensive patients from NHANES 2011-2014 were included in this study. The population was divided into two groups: 1065 cases (70 %) in the train set and 452 cases (30 %) in the test set. Lasso regression model and multivariate logistic regression analyses identified predictors significantly associated with cognitive impairment, and the nomogram was constructed using these predictors. The performance of the model was assessed using metrics such as area under the curve (AUC) of receiver operating characteristic (ROC), calibration curves, and decision curve analysis (DCA).

The nomogram identified seven predictors, including sex, age, education, poverty income ratio (PIR), depression, vigorous work activity, and creatinine. A web-based dynamic nomogram (https://cognitive-impairment-in-hypertension.shinyapps.io/DynNomapp/) was constructed based on these factors. The AUC of the train set was 0.802 and the AUC of the test set was 0.756, indicating that the model had excellent discriminative ability. The calibration curve showed that the model was well-calibrated. The DCA indicated that early intervention for those at risk would result in a net benefit.

The model performed well and was clinically predictive, making it easy for clinicians to use and screen for possible cognitive impairment in elderly hypertensive patients.

Age-related cognitive decline is a complex phenomenon that is influenced by various neurobiological processes at the molecular, cellular, and tissue levels. The extent of this decline varies between individuals and the underlying determinants of these differences are not fully understood. Two of the most prominent signs of cognitive decline in aging are the deterioration of episodic memory, which is a hallmark of Alzheimer's disease (AD), and the nearly always accompanying atrophy of the medial temporal lobe. Both cross-sectional and longitudinal studies have consistently demonstrated the strong relationship between these two, however, recent advanced imaging techniques have shown promise for predicting cognitive decline earlier than atrophy measures. In this study, we investigate the value of brain biomechanical properties, specifically in the medial temporal lobe, for predicting global cognitive decline along the normal aging and AD spectrum. Our results indicate that the medial temporal stiffness significantly predicts future cognitive decline beyond that achieved by measures of atrophy and amyloidosis. Measures of brain biomechanical properties may provide valuable prognostic information to enable more efficient study design and evaluation of potential interventions.

We examined whether total joint arthroplasty (TJA) is associated with increased metal accumulation in the brain and histopathologic changes of Alzheimer's disease. We measured ultra-trace metal concentrations (aluminum, chromium, cobalt, manganese, molybdenum, nickel, titanium, and vanadium) on postmortem frozen tissues of the occipital lobe of 177 subjects (89 non-TJA and 88 TJA) using a triple-quadrupole inductively coupled plasma mass spectrometry and correlated elemental concentrations to the degree of Alzheimer's disease neuropathic change (ADNC). To effectively assess the relationship between TJA and brain metal concentrations, subjects with and without TJA were matched for baseline clinical characteristics and showed no difference in postmortem Alzheimer's disease neuropathic change. TJA subjects had increased concentrations of cobalt and titanium and both metals were associated with increased amyloid plaques. In both the TJA and non-TJA subjects, increased concentrations of cobalt, titanium, manganese, and molybdenum were associated with increased odds of neuritic and diffuse plaques. Lastly, the brain's inter-metal correlations were altered in the presence of increased neuritic plaques and/or implantable artificial joints. These findings suggest that metal concentrations and homeostasis vary in presence of TJA.

Cognitive reserve (CR), typically measured through socio-behavioral proxies, can partially explain better cognitive performance despite underlying brain aging or neuropathology.

To examine the associations of CR with mild cognitive impairment (MCI) and cognitive function while considering Alzheimer's disease (AD)-related plasma biomarkers.

This population-based cross-sectional study included 4706 dementia-free individuals from MIND-China. Data on AD-related plasma biomarkers were available for 1204 individuals. A composite CR score was generated by integrating education, occupational complexity, mental activity, and social support, using structural equation modeling. A neuropsychological test battery was used to assess the function of episodic memory, executive function, attention, and verbal fluency. MCI and subtypes of MCI were defined according to the Petersen's criteria. Data were analyzed using general linear and logistic regression models.

Controlling for AD-related plasma biomarkers, higher educational attainment was associated with better performance in all four examined cognitive domains (p < 0.001) and with lower likelihoods of MCI, amnestic MCI (aMCI), and non-aMCI (p < 0.05); late-life mental activity was significantly related to lower likelihoods of MCI and aMCI (p < 0.05). Midlife occupation and late-life social support were not significantly associated with MCI or subtypes (p > 0.05). Higher composite CR scores were related to better performance in all the examined cognitive domains as well as lower likelihoods of MCI, aMCI, and non-aMCI (p < 0.05).

Greater composite CR, derived from the CR indicators across different stages of the lifespan, is associated with better cognitive function independent of AD-related plasma biomarkers, driven mainly by early-life educational attainment.

We evaluated impaired odor identification and global cognition as simple, cost-effective alternatives to neuroimaging biomarkers to predict cognitive decline and dementia in the Mayo Clinic Study of Aging.

Six hundred forty-seven participants (mean 8.1, standard deviation 3.4 years' follow-up) had the following baseline procedures: modified Blessed Information Memory Concentration Test (BIMCT), 12-item Brief Smell Identification Test (BSIT), structural brain magnetic resonance imaging (MRI), and positron emission tomography (PET) imaging with 11C-Pittsburgh compound B (11C-PiB) and fluorodeoxyglucose (FDG; subset).

Cognitive decline developed in 102 participants and dementia in 34 participants. In survival analyses, PiB PET showed robust prediction for cognitive decline. Impaired BSIT, impaired BIMCT, MRI, and FDG measures were also significant predictors. The combination of demographics + BSIT + BIMCT showed strong predictive utility (C-index 0.81), similar to demographics + PiB PET (C-index 0.80). Similar but stronger results were obtained for prediction of dementia.

Impairment in both odor identification test and global cognition was comparable to PiB PET for predicting cognitive decline and dementia.

In 647 participants in the population-based Mayo Clinic Study of Aging, several clinical markers and biomarkers each predicted cognitive decline or dementia during an average 8 years of follow-up. The combination of the demographic variables of age, sex, and education with a brief odor identification test (BSIT) and a global cognitive test (Blessed Information Memory Concentration Test) showed strong predictive utility (C-index 0.81) for cognitive decline that was similar to the demographic variables combined with Pittsburgh Compound B amyloid imaging (C-index 0.80). Combining a brief odor identification test with a brief cognitive test needs consideration as a simple, cost-effective option in the clinical assessment of individuals at risk of cognitive decline and dementia, as well as a potential tool to identify individuals who may benefit from disease-modifying treatments and to screen participants for prevention trials.

Excessive alcohol use is associated with an increased risk of cognitive impairment. Since increased amyloid plaque burden exacerbates cognitive decline, we sought to assess the potential impact of alcohol use disorder (AUD) on cognition, memory, and amyloid burden corresponding with age.

We conducted the retrospective analysis with 6036 subjects, including 269 AUD+ subjects. A four-item CAGE (C-Cutting Down, A-Annoyance by Criticism, G-Guilty Feeling, E-Eye-openers) alcohol questionnaire was given during the recruitment to determine AUD in each participant. We assessed cognitive function, focusing on memory using neuropsychological testing. For 1038 participants, including 57 AUD+ subjects, we measured amyloid burden using the 11C Pittsburgh Compound B tracer-based positron emission tomography imaging.

AUD+ was significantly associated with lower scores of cognition and memory function relative to AUD- individuals. No significant association was found with AUD and elevated brain amyloid under the age of 65. However, further analysis showed that those aged ≥65 showed greater odds for abnormal amyloid in AUD+ compared to AUD- participants.

Our results underscore AUD as a risk factor for cognitive decline and diminished memory, particularly in aging populations. The role of AUD in brain amyloid accumulation requires further study.

Mild cognitive impairment (MCI) may lead to difficulty maintaining postural stability and balance during locomotion. This heightened susceptibility to falls is particularly evident during tasks such as obstacle negotiation, which demands efficient motor planning and reallocation of attentional resources. This study proposed a multi-objective optimal control (MOOC) technique to assess the changes in motor control strategies during obstacle negotiation in older people affected by amnestic MCI.

Motion data from 12 older adults with MCI and 12 controls when crossing obstacles were measured using a motion capture system, and used to obtain the control strategy of obstacle-crossing as the best compromise between the conflicting objectives of the MOOC problem, i.e., minimising mechanical energy expenditure and maximising foot-obstacle clearance. Comparisons of the weighting sets between groups and obstacle heights were performed using a two-way analysis of variance with a significance level of 0.05.

Compared to the controls, the MCI group showed significantly lower best-compromise weightings for mechanical energy expenditure but greater best-compromise weightings for both heel- and toe-obstacle clearances. This altered strategy involved a trade-off, prioritising maximising foot-obstacle clearance at the expense of increased mechanical energy expenditure. The MCI group could successfully navigate obstacles with a normal foot-obstacle clearance but at the cost of higher mechanical energy expenditure.

MCI alters the best-compromise strategy between minimising mechanical energy expenditure and maximising foot-obstacle clearances for obstacle-crossing in older people. These findings provide valuable insights into how MCI impacts motor tasks and offer potential strategies for mitigating fall risks in individuals with MCI. Moreover, this approach could serve as an assessment tool for early diagnosis and a more precise evaluation of disease progression. It may also have applications for individuals with impairments in other cognitive domains.

Mild cognitive impairment (MCI) is characterized by a noticeable decline in cognitive abilities that is not severe enough to significantly interfere with daily life or independent functioning. Recent research highlights the important role of exercise in managing and improving cognitive function in patients with MCI. This scoping review examines the benefits of different forms of exercise in improving cognitive function. Recommendations for exercise, including frequency, consistency, and individualized programs, are discussed in this review, with an emphasis on the importance of safety and regular monitoring. The integration of physical and cognitive training is also suggested to maximize benefits. Regular physical exercise is a promising intervention for mitigating cognitive decline and improving the overall quality of life in patients with MCI.

With the rapid increase in China's aging population, cognitive impairment in the elderly has become a significant public health issue.

In this study we performed a cross-sectional analysis to comprehensively investigate the relationship between cognitive function and emotion, sleep, frailty, nutrition, and clinical variables in hospitalized geriatric patients according to age group and sex. We determined the most important risk factors for cognitive impairment.

A total of 1121 inpatients were recruited from the Department of Gerontology at the Fifth Affiliated Hospital of Sun Yat-sen University, China, from August 2023 to April 2024. Cognitive assessment was performed using the Mini-Mental State Examination scale and Montreal Cognitive Assessment. The sleep quality was evaluated based on the Pittsburgh Sleep Quality Index, and anxiety and depression were evaluated based on the Hamilton Anxiety Scale and Hamilton Depression Scale.

Sex and age differences existed with respect to cognition, emotion, and sleep quality. After full adjustment, age, education level, working status, hemoglobin level, activities of daily living, Hamilton Depression Scale, and Pittsburgh Sleep Quality Index scores were significantly and independently associated with cognitive impairment.

Geriatric patients with a better mood, sleep and nutrition status, higher education level, and more social engagement performance had superior cognitive function. Interventions, such as valuing education, improving sleep, relaxing emotions, preventing anemia, and adjusting lifestyle, may help prevent the development of cognitive deficits. Elderly and female patients required special attention.

Various factors were shown to contribute to maintenance of cognitive function.

The structural brain alterations for subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are poorly defined. We sought to characterize grey matter volume (GMV) and cortical thickness associated with SCD and MCI among rural-dwelling older adults in China.

This population-based cross-sectional study included 1072 dementia-free participants from the brain MRI sub-study of MIND-China (2018-2020). We defined MCI following the Petersen's criteria, and SCD as the self-rated Ascertain Dementia 8-item Questionnaire score ≥ 2. Data were analyzed using voxel-based morphometry (VBM), surface-based morphometry analysis (SBM), and logistic regression models.

SCD was defined in 243 persons and MCI in 246 individuals. The VBM analysis showed that MCI (vs. normal cognition) was significantly associated with reduced GMV in brain regions such as the bilateral parahippocampus, bilateral hippocampus, and bilateral fusiform (P < 0.05), but SCD exhibited no significant differences with normal cognition in GMV (P > 0.05). The ROI-wise SBM analysis revealed that SCD was significantly associated with cortical thinning in the right paracentral sulcus, left caudal middle frontal gyrus, and left entorhinal cortex (P < 0.05) and that MCI was significantly associated with cortical thinning in the left temporal lobe, left frontal lobe, bilateral parietal lobe and bilateral fusiform (P < 0.05).

The brain regions with reduced GMV or cortical thickness in older adults gradually expand from normal cognition through SCD to MCI, suggesting that characterizing structural brain alterations may help define the cognitive spectrum at the pre-dementia phase. These findings have potential implications for understanding the neuropathological process of cognitive deterioration in aging.

Obstructive sleep apnoea (OSA) is associated with an increased risk for cognitive impairment and dementia, which likely involves Alzheimer's disease pathology. Non-rapid eye movement slow-wave activity (SWA) has been implicated in amyloid clearance, but it has not been studied in the context of longitudinal amyloid accumulation in OSA. This longitudinal retrospective study aims to investigate the relationship between polysomnographic and electrophysiological SWA features and amyloid accumulation. From the Mayo Clinic Study of Aging cohort, we identified 71 participants ≥60 years old with OSA (mean baseline age = 72.9 ± 7.5 years, 60.6% male, 93% cognitively unimpaired) who had at least 2 consecutive Amyloid Pittsburgh Compound B (PiB)-PET scans and a polysomnographic study within 5 years of the baseline scan and before the second scan. Annualized PiB-PET accumulation [global ΔPiB(log)/year] was estimated by the difference between the second and first log-transformed global PiB-PET uptake estimations divided by the interval between scans (years). Sixty-four participants were included in SWA analysis. SWA was characterized by the mean relative spectral power density (%) in slow oscillation (SO: 0.5-0.9 Hz) and delta (1-3.9 Hz) frequency bands and by their downslopes (SO-slope and delta-slope, respectively) during the diagnostic portion of polysomnography. We fit linear regression models to test for associations among global ΔPiB(log)/year, SWA features (mean SO% and delta% or mean SO-slope and delta-slope), and OSA severity markers, after adjusting for age at baseline PiB-PET, APOE ɛ4 and baseline amyloid positivity. For 1 SD increase in SO% and SO-slope, global ΔPiB(log)/year increased by 0.0033 (95% CI: 0.0001; 0.0064, P = 0.042) and 0.0069 (95% CI: 0.0009; 0.0129, P = 0.026), which were comparable to 32% and 59% of the effect size associated with baseline amyloid positivity, respectively. Delta-slope was associated with a reduction in global ΔPiB(log)/year by -0.0082 (95% CI: -0.0143; -0.0021, P = 0.009). Sleep apnoea severity was not associated with amyloid accumulation. Regional associations were stronger in the pre-frontal region. Both slow-wave slopes had more significant and widespread regional associations. Annualized PiB-PET accumulation was positively associated with SO and SO-slope, which may reflect altered sleep homeostasis due to increased homeostatic pressure in the setting of unmet sleep needs, increased synaptic strength, and/or hyper-excitability in OSA. Delta-slope was inversely associated with PiB-PET accumulation, suggesting it may represent residual physiological activity. Further investigation of SWA dynamics in the presence of sleep disorders before and after treatment is necessary for understanding the relationship between amyloid accumulation and SWA physiology.

CD33 rs3865444 and hypertension (HTN) are related to cognitive impairment, individually. However, little is known about their combined effects on cognitive function in older adults.

This population-based study included 4368 dementia-free participants (age ≥65 years) in the Multimodal Interventions to Delay Dementia and Disability in Rural China (MIND-China), with data available in 1044 persons for gray matter volume and 85 persons for cerebral blood flow (CBF). We used general linear regression and mediation models to examine the associations of rs3865444 and HTN with cognition, brain atrophy, and CBF.

Among rs3865444 CC carriers, HTN and late-life HTN were significantly associated with impaired cognition. Midlife and late-life HTN were correlated with brain atrophy. CD33 rs3865444 CC moderated the mediation effect of gray matter volume on the association between HTN and global cognition. HTN was correlated with low CBF in rs3865444 CC carriers.

There are synergistic associations of CD33 rs3865444 and HTN with brain and cognitive aging in dementia-free older adults.

Mental and cognitive health is crucial to ensure well-being in older age. However, prolonged periods of stress, grief, and bereavement might compromise mental health balance, leading to profound changes. This study investigated the sex-stratified associations between midlife bereavement experiences (e.g. sibling loss, spousal loss, and multiple losses) and late-life depression (LLD) and cognitive impairment.

Linked data from the Swedish Level-of-Living Survey and the Swedish Panel Study of Living Conditions of the Oldest Old (SWEOLD) were used. Multiple logistic regressions were performed to examine the associations between midlife bereavement and LLD (n = 1078) and cognitive impairment (n = 995), separately.

Sibling loss and multiple losses in midlife were associated with lower odds of LLD, especially among women. Among men, sibling loss in midlife was associated with lower odds of cognitive impairment, while the experience of two losses among women suggested an increased (but non-significant) risk of cognitive impairment. Interaction analyses did not show significant effects between bereavement and gender on LLD and cognitive impairment.

Midlife bereavement might have gendered implications on LLD and cognitive impairment, but associations need to be confirmed by well-powered studies. Further research is warranted to elucidate the association between multiple midlife losses and reduced LLD risk.

The effects and underlying mechanisms of adolescent exposure to combined environmental hazards on cognitive function remain unclear. Here, using a combined exposure model, we found significant cognitive decline, hippocampal neuronal damage, and neuronal senescence in mice exposed to cadmium (Cd) and high-fat diet (HFD) during adolescence. Furthermore, we observed a significant downregulation of Sirtuin 6 (SIRT6) expression in the hippocampi of co-exposed mice. UBCS039, a specific SIRT6 activator, markedly reversed the above adverse effects. Further investigation revealed that co-exposure obviously reduced the levels of La ribonucleoprotein 7 (LARP7), disrupted the interaction between LARP7 and SIRT6, ultimately decreasing SIRT6 expression in mouse hippocampal neuronal cells. Overexpression of Larp7 reversed the combined exposure-induced SIRT6 decrease and senescence in mouse hippocampal neuronal cells. Additionally, the results showed notably elevated levels of Larp7 m6A and YTH domain family protein 2 (YTHDF2) in mouse hippocampal neuronal cells treated with the combined hazards. Ythdf2 short interfering RNA, RNA immunoprecipitation, and RNA stability assays further demonstrated that YTHDF2 mediated the degradation of Larp7 mRNA under combined exposure. Collectively, adolescent co-exposure to Cd and HFD causes hippocampal senescence and cognitive decline in mice by inhibiting LARP7-mediated SIRT6 expression in an m6A-dependent manner.

Mild Cognitive Impairment (MCI) is a neurological disorder at the transition between normal cognitive decline and dementia. Despite the potential role of neuroinflammation in the pathogenesis of MCI, infectious triggers remain mostly unknown. Infection with Bartonella spp., a zoonotic bacterium, has recently been associated with diffuse neurological and psychiatric symptoms. Given the preferential endothelial localization of Bartonella spp. and the role of vascular changes in neurocognitive decline, we hypothesized that there is an association between Bartonella spp. infection and pathologically accelerated decline in cognitive function in aging. To test this hypothesis, we collected serological and molecular markers of past and present Bartonella spp. infection in a sample of older people with and without MCI. Samples were processed in a blinded way to exclude laboratory biases. Contrary to our hypothesis, people with MCI were not more likely than people without MCI to have an active Bartonella spp. infection as measured by droplet digital PCR (p = 0.735) and quantitative PCR (p = 1). In addition, there was no significant difference in positive serological results between cases and controls (p = 0.461). Overall, higher-than-expected active Bartonella spp. infection (37% by ddPCR) and seroreactivity (71% by indirect fluorescent antibody assay) were found in people without MCI. Conclusions require caution, as our study was limited by the small number of cases with MCI. Overall, our results identified a higher than previously recognized rate of exposure and infection with Bartonella spp. in this older study population but does not support a specific role for such infection in MCI.

Sex and gender-biological and social constructs-significantly impact the prevalence of protective and risk factors, influencing the burden of Alzheimer's disease (AD; amyloid beta and tau) and other pathologies (e.g., cerebrovascular disease) which ultimately shape cognitive trajectories. Understanding the interplay of these factors is central to understanding resilience and resistance mechanisms explaining maintained cognitive function and reduced pathology accumulation in aging and AD. In this narrative review, the ADDRESS! Special Interest Group (Alzheimer's Association) adopted a multidisciplinary approach to provide the foundations and recommendations for future research into sex- and gender-specific drivers of resilience, including a sex/gender-oriented review of risk factors, genetics, AD and non-AD pathologies, brain structure and function, and animal research. We urge the field to adopt a sex/gender-aware approach to resilience to advance our understanding of the intricate interplay of biological and social determinants and consider sex/gender-specific resilience throughout disease stages. HIGHLIGHTS: Sex differences in resilience to cognitive decline vary by age and cognitive status. Initial evidence supports sex-specific distinctions in brain pathology. Findings suggest sex differences in the impact of pathology on cognition. There is a sex-specific change in resilience in the transition to clinical stages. Gender and sex factors warrant study: modifiable, immune, inflammatory, and vascular.

Previous studies found that visual impairment (VI) is associated with higher risk of cognitive impairment, but the molecular basis of these conditions is unknown.

We aim to compare the metabolite associations of VI and cognitive impairment.

The study population with comprehensive measurements was derived from the UK Biobank study. Visual acuity worse than 0.3 logMAR units were defined as VI. Failure in one or more of the four cognitive tests was defined as cognitive impairment. A panel of 249 metabolites was measured using a nuclear magnetic resonance metabolites profiling platform. Logistic regression models were applied to compare metabolite associations with VI and cognitive impairment.

23,775 participants with complete data on visual acuity, cognitive tests and metabolomics, and without a history of neurological disorders at baseline were included. After adjusting for confounding factors, VI was significantly associated with cognitive impairment (odds ratio[OR] = 1.49, 95% confidence interval [CI]: 1.27-1.74, p < 0.001). After multiple testing correction (p < 9×10-4), five metabolites including the ratio of omega-6 to omega-3 fatty acids (FAs) (OR = 1.18[1.10-1.27]), ratio of omega-3 to total FAs (OR = 0.84[0.77-0.91]), ratio of docosahexaenoic acid (DHA) to total FAs (OR = 0.86[0.80-0.94]), DHA (OR = 0.85[0.78-0.92]), and omega-3 FAs (OR = 0.84[0.77-0.91]) were uniquely associated with VI. Glycoprotein acetyls (OR = 1.06[1.03-1.10]) and alanine (OR = 0.95[0.92-0.98]) were exclusively associated with cognitive impairment. Albumin was identified as the common metabolite shared by the two phenotypes (OR = 0.90[0.85-0.95] for VI, and 0.95[0.92-0.98]) for cognitive impairment).

We identified distinct and overlapping metabolites associated with VI and cognitive impairment, unveiling their distinct metabolic profiles and potential common pathophysiology.

Exergames are an innovative method that can promote neuroplasticity and improve the cognitive abilities of the elderly. This study aimed to compare the effects of single-task and multi-task exergames on the cognitive ability of the elderly with mild cognitive impairment (MCI).

Computerized literature search was performed using PubMed, Web of Science, EBSCO, Elsevier, ProQuest, China National Knowledge Infrastructure (CNKI), Wanfang and VIP database to identify relevant articles from the establishment of the database from inception to April 1, 2024. The inclusion criteria were: (i) participants aged 60 or older diagnosed with mild cognitive impairment, regardless of gender; (ii) use of randomized controlled trials (RCTs); (iii) interventions involving exergames with physical activity or as the primary variable; and (iv) outcome measures using standardized neuropsychological instruments to assess cognitive function, including statistical data on sample size, mean, and standard deviation. Finally, the included study comprised a total of 526 participants. Mean difference (MD) and 95% confidence interval (CI) were used to synthesize the effect size in the data.

11 studies were included. Due to the differences in the intervention methods, subgroup analysis was performed on the included research. Compared with the control group assessed by the Montreal Cognitive Assessment Scale, the single-task intervention improved the cognitive ability of the elderly with MCI (MD 3.40, 95% CI 2.43-4.37), the Mini-Mental State Examination Scale (MD 2.38, 95% CI -2.03 to 2.72), the Trail Making Test (MD -3.89, 95% CI -6.45 to -1.33), and the Digit Span Forward test (MD 1.16, 95% CI 0.73-1.60).

This meta-analysis supports that exergames could be an effective cognitive rehabilitation method for MCI patients. Our study recommends that patients implement a customized exergames program and adhere to it for a long time. It is necessary to pay attention to the exercise guidelines and provide evidence from clinicians.

(1) This meta-analysis supports that exergames could be an effective cognitive rehabilitation method for MCI patients. Our study recommends that patients implement a customized exergames program and adhere to it for a long time. It is necessary to pay attention to the exercise guidelines and provide evidence from clinicians. (2) This research provides preliminary evidence for the clinical utility of VR tasks developed for mild cognitive impairment. (3) In this paper, only relevant studies in Chinese and English were searched, and no studies in other languages were searched.

The prevalence of mild cognitive impairment (MCI) is steadily increasing among elderly people with type 2 diabetes (T2DM). This study aimed to create and validate a predictive model based on a nomogram.

This cross-sectional study collected sociodemographic characteristics, T2DM-related factors, depression, and levels of social support from 530 older adults with T2DM. We used LASSO regression and multifactorial logistic regression to determine the predictors of the model. The performance of the nomogram was evaluated using calibration curves, receiver operating characteristics (ROC), and decision curve analysis (DCA).

The nomogram comprised age, smoking, physical activity, social support, depression, living alone, and glycosylated hemoglobin. The AUC for the training and validation sets were 0.914 and 0.859. The DCA showed good clinical applicability.

This predictive nomogram has satisfactory accuracy and discrimination. Therefore, the nomogram can be intuitively and easily used to detect MCI in elderly adults with T2DM.

Age-related and Alzheimer's disease (AD) dementia-related neurodegeneration impact brain health. While morphometric measures from T1-weighted scans are established biomarkers, they may be less sensitive to earlier changes. Neurite orientation dispersion and density imaging (NODDI), offering biologically meaningful interpretation of tissue microstructure, may be an advanced brain health biomarker.

We contrasted regional gray matter NODDI and morphometric evaluations concerning their correlation with (1) age, (2) clinical diagnosis stage, and (3) tau pathology as assessed by AV1451 positron emission tomography.

Our study hypothesizes that NODDI measures are more sensitive to aging and early AD changes than morphometric measures. One NODDI output, free water fraction (FWF), showed higher sensitivity to age-related changes, generally better effect sizes in separating mild cognitively impaired from cognitively unimpaired participants, and stronger associations with regional tau deposition than morphometric measures.

These findings underscore NODDI's utility in capturing early neurodegenerative changes and enhancing our understanding of aging and AD.

Neurite orientation dispersion and density imaging can serve as an effective brain health biomarker for aging and early Alzheimer's disease (AD).Free water fraction has higher sensitivity to normal brain aging.Free water fraction has stronger associations with early AD and regional tau deposition.