Forecasting the prevalence of preclinical and clinical Alzheimer's disease in the United States

Encapsulation of trabecular meshwork mesenchymal stem cell using microfluidic system for differentiation into neuron-like cells

OBJECTIVE

Neurodegenerative diseases are a class of nervous system disorders characterized by progressive neuronal degeneration and loss of function. Among emerging therapeutic approaches, microfluidic-enabled stem cell encapsulation and transplantation has gained recognition as a promising strategy for mitigating neuronal damage. In this work, human mesenchymal stem cells (MSCs), isolated from trabecular meshwork (TM) tissue, were successfully encapsulated and differentiated into neural-like cells via a microfluidic platform to demonstrate their potential for neural repair applications.

MATERIALS AND METHODS

The isolated mesenchymal stem cells were cultured on a microfluidic system (fabricated by soft lithography methods) and treated with medium containing DMEM supplemented with RA, IBMX, and forskolin for 7 days. Quantitative PCR (qPCR) were used to analyze differentiated TM-MSC and their expression of neural-like specific markers such as Nestin and b-tubulin 3.

RESULTS

qPCR analysis revealed the presence of genes characteristic of neural cells (Nestin and β-tubulin 3) in cells differentiated both within a microfluidic system and on traditional tissue culture plates (TCPS). qPCR result showed that cells on 1.5% alginate showed higher expression of β-tubulin 3 compared to those on 1% alginate, 2% alginate, and TCPS (p < 0.0001). In contrast, Nestin expression showed no statistically significant differences across all pairwise comparisons (p > 0.05 for all groups).

CONCLUSION

The findings indicate that mesenchymal stem cells derived from the trabecular meshwork (TM-MSCs) may serve as promising candidates for cell-based therapeutic strategies. Furthermore, the microfluidic platform implemented in this study exhibits potential utility as a delivery vehicle for TM-MSCs in therapeutic interventions targeting neurological disorders.

Risk Factors Associated With Late-Onset Epilepsy in Dementia and Mild Cognitive Impairment

Importance

The risk of developing epilepsy substantially increases after the age of 60 years (late-onset epilepsy [LOE]), particularly in people with cognitive decline ([PWCD] ie, dementia and/or mild cognitive impairment). Epilepsy is associated with worse cognitive and mortality outcomes in PWCD. Identifying PWCD at risk for developing LOE can facilitate early screening and treatment of epilepsy.

Objective

To investigate factors associated with LOE in PWCD.

Design, Setting, and Participants

This longitudinal, multicenter study is based on participants from 39 US Alzheimer's Disease Research Centers from September 2005 through December 2021. Of 44 713 participants, 25 119 PWCD were identified. Of these, 14 685 were included who did not have epilepsy at enrollment, had 2 or more visits, and were 60 years or older at the most recent follow-up.

Exposure

The association between various factors and LOE development in PWCD was investigated.

Main Outcomes and Measures

The primary outcome was LOE, defined as seizures starting at or after 60 years of age. Those who did not develop LOE but were 60 years or older at follow-up served as controls. A multivariable Cox regression analysis assessed the association between various factors and LOE. Independent variables included age, sex, and socioeconomic factors (education, race, ethnicity), cardiovascular risks (hypertension, diabetes, hyperlipidemia), cerebrovascular disease (stroke or history of transient ischemic attack [TIA]), other neurologic comorbidities (Parkinson disease [PD], traumatic brain injury), cognition (age at dementia onset, dementia severity, type of dementia [Alzheimer disease (AD) vs non-AD]), genetics (apolipoprotein E4 [APOE4] status), lifestyle (alcohol misuse, smoking), and depression.

Results

Of the 14 685 participants (7355 female [50%] and 7330 male [50%]; mean [SD] age, 73.8 [8.5] years) who met the inclusion criteria, 221 participants (1.5%) developed LOE during follow-up. After adjusting for demographics, cardiovascular risks, neurologic comorbidities, genetics, cognitive factors, and depression, the following were associated with a higher risk of developing LOE: APOE4 allele (adjusted hazard ratio [aHR], 1.39; 95% CI, 1.04-1.86; P = .03), dementia onset before age 60 years (aHR, 2.46; 95% CI, 1.53-3.95; P < .001), worse cognition (aHR, 2.35; 95% CI, 1.97-2.79; P < .001), AD dementia subtype (aHR, 1.68; 95% CI, 1.13-2.49; P = .01), stroke/TIA (aHR, 2.03; 95% CI, 1.37-3.01; P < .001), and PD (aHR, 2.53; 95% CI, 1.08-5.95; P = .03). In sensitivity analysis, using an alternative LOE definition of epilepsy onset after age 65 years revealed the same factors associated with LOE.

Conclusion and Relevance

This study showed that the APOE4 allele, dementia onset before age 60 years, AD dementia subtype, worse cognition, stroke/TIA, and PD are associated with LOE development in PWCD. PWCD with these risk factors may be considered for routine screening with an electroencephalogram for early identification of LOE.

Proof-of-concept for integrating multimodal digital health assessments into lifestyle interventions for older adults with dementia risk factors

Multimodal digital health assessments overcome the limitations of patient-reported outcomes by allowing for continuous and passive monitoring but remain underutilized in older adult lifestyle interventions for brain health. Therefore, we aim to (1) report ecological momentary assessment (EMA) and ActiGraph adherence among older adults during a lifestyle intervention; and (2) use dynamic data collected via EMA and ActiGraph to examine person-specific patterns of mindfulness, steps, and sleep throughout the intervention. We analyzed EMA and ActiGraph data from a pilot study of the 8-week My Healthy Brain program (N = 10) lifestyle group for older adults (60+) with subjective cognitive decline. EMA adherence metrics included proportion of EMA completed and the proportion of days with at least 10 mindfulness minutes. ActiGraph GT9X adherence metrics included the number of valid wear days (≥ 7 h) and the number of days participants achieved their step goal. We used linear mixed-effects models to examine person-specific patterns of step count, sleep efficiency, and mindfulness practice. On average, participants completed 39 of the 49 possible EMAs (80%) during the program. ActiGraph adherence was slightly higher than EMA (M = 61.40 days, 87.71%). Participants achieved the daily mindfulness goal (10 min/day) and step goal on 46.32% and 55.10% of days, respectively. Dynamic data revealed that on average, participant step counts increased by approximately 16.5 steps per day (b = 16.495, p = 0.002). However, some participants exhibited no changes while improvements made by other participants returned to baseline levels of activity. There was substantial heterogeneity in trajectories of mindfulness practice and sleep efficiency. EMA and ActiGraph are feasible for older adults enrolled in dementia risk reduction lifestyle interventions. Future studies are needed to better understand how mechanisms of lifestyle behaviors captured by EMA and ActiGraph are related to cognitive outcomes in older adults.

Application of Network Pharmacology in the Treatment of Neurodegenerative Diseases with Traditional Chinese Medicine

In recent years, the incidence of neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis, has exhibited a steadily rising trend, which has posed a major challenge to the global public health. Traditional Chinese medicine, with its multicomponent and multitarget characteristics, offers a promising approach to treating neurodegenerative diseases. However, comprehensively elucidating the complex mechanisms underlying traditional Chinese medicine formulations remains challenging. As an emerging systems biology method, network pharmacology has provided a vital tool for revealing the multitarget mechanisms of traditional Chinese medicine through high-throughput technologies, molecular docking, and network analysis. This paper reviews the advancements in the application of network pharmacology in treating neurodegenerative diseases using traditional Chinese medicine, analyzes the current status of relevant databases and technological methods, discusses the limitations, and proposes future directions to promote the modernization of traditional Chinese medicine and the development of precision medicine.

Effects of exercise versus usual care on older adults with amnestic mild cognitive impairment: EXERT versus ADNI

INTRODUCTION

EXERT was a multisite randomized controlled trial (RCT) examining the effects of moderate-high intensity aerobic training (AX) versus lower-intensity stretching/balance/range of motion (SBR) on cognitive trajectories in older adults with amnestic mild cognitive impairment (aMCI).

METHODS

Preplanned post-hoc analyses were conducted to compare each arm to a propensity-matched usual care (no intervention) group from Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) selected for similarity across key characteristics. Differences in 12-month trajectories in the primary endpoint (ADAS-Cog-Exec) and magnetic resonance imaging (MRI) volumes in prespecified brain regions were compared.

RESULTS

AX and SBR showed significantly less 12-month cognitive decline than ADNI-1 (AX:n = 109, β = 0.169, 95% confidence interval [CI] 0.011-0.328; SBR:n = 105, β = 0.181, 95% CI 0.007-0.354). There were trends of less prefrontal cortex volume loss for both EXERT groups and less AD signature region volume loss for SBR relative to ADNI-1 over 12 months.

DISCUSSION

Moderate-high intensity aerobic or low-intensity flexibility exercise for 12 months in participants with aMCI may provide protection against decline relative to usual care.

CLINICAL TRIAL REGISTRATION

The EXERT clinical trial is registered at clinicaltrials.gov (NCT02814526).

HIGHLIGHTS

EXERT was a randomized controlled trial in sedentary older adults with aMCI. EXERT arms were propensity-matched to a usual care (no intervention) group (Alzheimer's Disease Neuroimaging Initiative 1 [ADNI-1]). High and low-intensity exercise arms had less 12-mo cognitive decline than ADNI-1. There were trends of less prefrontal cortex volume loss for each arm versus ADNI-1.

Genetic colocalization of cathepsins H, D, and L1 with Alzheimer's disease: Implications for biomarker and therapeutic target discovery

BackgroundCathepsins, a family of lysosomal proteases, have been implicated in Alzheimer's disease (AD) pathogenesis through their involvement in amyloid-β protein precursor processing and neuroinflammation. However, the specific roles of different cathepsins in AD remain unclear.ObjectiveThis study aimed to investigate the genetic associations and potential causal relationships between cathepsins and AD, using Mendelian randomization (MR) to explore their roles as biomarkers and therapeutic targets.MethodsA two-sample MR analysis was conducted using genome-wide association study data for AD and cathepsins. Genetic variants associated with cathepsin expression were used as instrumental variables. Forward MR assessed the causal effect of cathepsins on AD, while reverse MR explored the impact of AD on cathepsin levels. Colocalization analysis was performed to identify shared genetic variants between cathepsins and AD.ResultsCathepsin H was significantly associated with an increased risk of AD (p = 0.0034, OR = 1.04), with consistent results across multiple MR methods. Colocalization analysis revealed a significant genetic overlap between Cathepsin L1 and AD (PP.H4 = 100%), suggesting a shared genetic basis.ConclusionsCathepsin H may be a potential risk factor for AD, while Cathepsin L1 shows promise as a therapeutic target and biomarker due to its genetic overlap with AD. Further research is needed to explore the mechanisms by which these cathepsins influence AD progression and to assess their therapeutic potential in diverse populations.

Inspiring Undergraduate Student Training in Alzheimer's Research (USTAR): Training the Next Generation of Aging Scientists

Inspiring Undergraduate Student Training in Alzheimer's Research (USTAR) aims to provide Underrepresented Minority (URM) undergraduate students with mentored didactic, clinical, and research experiences to stimulate interest in research related to Alzheimer's Disease and Related Dementias (ADRD). USTAR specifically focuses on social determinants of health (SDOH) as risk factors for ADRD minoritized populations. USTAR's scientific rationale is that URM undergraduates are less likely to enter the biomedical workforce. Addressing this disparity is important since minorities are disproportionally affected by ADRD, and URM scientists may deeply appreciate the sociocultural forces that create racial health disparities. USTAR unites faculty expertise from Thomas Jefferson University (TJU) and Delaware State University (DSU), a Historically Black College and University (HBCU). The faculty's work spans the full spectrum of ADRD research and care, including neuroscience, biology, gerontology, geriatrics, neurology, and geriatric psychiatry. The 20-month USTAR program will train two cohorts of 10 students. Across all USTAR activities, we emphasize the relationship between SDOH and cognition. USTAR's goals are to: (1) provide interdisciplinary ADRD-related research, educational, clinical, and community experiences; (2) enhance research skills via group research projects; (3) facilitate transition from undergraduate to graduate studies in science; and (4) evaluate USTAR's effectiveness. USTAR has the potential to increase diversity in the national workforce that conducts health disparities research pertaining to ADRD. This goal aligns with the National Institute on Aging's (NIA) mission to meet the nation's biomedical, behavioral, and clinical research needs and to ensure health equity for all Americans.

Resting-State EEG Power Spectral Density Analysis Between Healthy and Cognitively Impaired Subjects

Background/Objectives: This study evaluates the potential of electroencephalography (EEG) as a noninvasive tool for distinguishing between healthy individuals (n = 79), those with mild cognitive impairment (MCI; n = 36), and dementia patients (n = 7). Methods: Using a 14-channel Emotiv EPOC-X headset, we analyzed power spectral density during a 2-min eyes-closed resting state. Results: Our results demonstrated that while EEG effectively differentiated dementia patients from healthy controls, it did not show significant differences between MCI and healthy controls. This indicates that EEG holds promise for identifying advanced cognitive decline but faces challenges in early-stage detection. Conclusions: The study contributes to the growing body of literature by highlighting EEG's potential as a cost-effective alternative to invasive diagnostic methods while also identifying the need for larger sample sizes and task-oriented approaches to improve its diagnostic precision.

Childhood adversity and late-life cognitive and brain health in a diverse cohort

INTRODUCTION

Childhood adversity harms neurodevelopment. Literature on late-life brain health is limited, and findings on late-life cognition are mixed.

METHODS

Pooling data from Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) and Study of Healthy Aging in African Americans (STAR) cohorts, we assessed the impact of childhood adversity (factor score from seven self-reported items) on (a) executive function and verbal memory decline using linear mixed effects models (n = 2447), (b) structural magnetic resonance imaging (MRI) using linear regression (n = 618), and (c) amyloid positron emission tomography (PET) using generalized linear models (n = 331), all adjusting for early-life demographic and socioeconomic confounders.

RESULTS

Childhood adversity was not associated with cognition except for a slightly faster decline in verbal memory (β ̂ $\hat \beta $  = -0.013 SD/year, 95% confidence interval [-0.025, -0.001]). Among neuroimaging outcomes, childhood adversity was associated with only larger temporal lobe volumes (β ̂ $\hat \beta $  = 0.092 SD [0.012, 0.173]).

DISCUSSION

More research evaluating sources of resilience, heterogeneity, and bias is needed to explain inconsistent findings across studies.

HIGHLIGHTS

We developed measurement models to capture childhood adversity in a diverse cohort. Childhood adversity was associated with a slightly faster verbal memory decline. We examined childhood adversity's effect on structural MRI and amyloid PET measures. Higher childhood adversity was associated with larger temporal lobe volumes.

Feasibility of assessing cognitive impairment via distributed camera network and privacy-preserving edge computing

INTRODUCTION

Mild cognitive impairment (MCI) involves cognitive decline beyond normal age and education expectations. It correlates with decreased socialization and increased aimless motion. We aim to automate detection of these behaviors for improved longitudinal monitoring.

METHODS

We used a privacy-preserving distributed camera network to collect data from MCI patients in an indoor space. Movement and social interaction features were developed using this data to train machine learning algorithms to differentiate between higher and lower cognitive functioning MCI groups.

RESULTS

A Wilcoxon rank-sum test showed significant differences between high- and low-functioning cohorts in the movement and social interaction features. Despite the absence of data linking each person's identity to their specific level of cognitive decline, a machine learning model using key features achieved 71% accuracy.

DISCUSSION

We show that an edge computing-based privacy-preserving camera network can differentiate between levels of cognitive impairment based on movements and social interactions during group activities.

Highlights

Movement and social interaction features showed significant differences in high- and low-functioning cohorts.Significant features included linear path lengths, walking speed, direction change and velocity entropies, and number of group formations, among others.Differences were observed despite the presence of healthy individuals and the lack of individual identifiers.Data were collected using a 39-camera privacy-preserving edge computing network covering a 1700-m2 indoor space.

Alzheimer's disease plasma biomarkers and physical functioning in a diverse sample of adults

INTRODUCTION

The relationship between Alzheimer's disease (AD) plasma biomarkers, and physical functioning (PF) across diverse races and ethnicities remains unclear. This study aims to explore this association in an ethno-racially diverse sample of cognitively unimpaired community-dwelling adults.

METHODS

Data clinical examinations, neuropsychological tests, blood draws, and PF exams (Timed Up and Go [TUG] and Short Physical Performance Battery [SPPB]) were analyzed. Multivariable linear regressions assessed the association between PF and AD plasma biomarkers (amyloid beta [Aβ]40, Aβ42, total tau [t-tau], neurofiliament light chain [NfL]).

RESULTS

The sample (n = 2358; mean age 64.7 years; 65.9% female), was 20% African American, 41.9% non-Hispanic White, and 38.1% Hispanic. Findings indicate that worse PF is linked to higher biomarker levels (p < 0.05). Associations differed by race and ethnicity group. TUG time was associated (p < 0.05) with Aβ40, Aβ42, and tau among non-Hispanic Whites, whereas SPPB scores were associated (p < 0.05) with t-tau and NfL among African Americans.

DISCUSSION

PF, ethnic/racial, and plasma AD biomarker data should be used to aid in developing risk profiles for neurodegenerative diseases.

HIGHLIGHTS

Alzheimer's disease (AD) biomarkers are associated with physical functioning (PF) Ethno-racial variation exists in AD biomarker and PF associations Race and ethnicity should considered when assessing neurodegenerative disease risk.

The double life of glucose metabolism: brain health, glycemic homeostasis, and your patients with type 2 diabetes

The maintenance of cognitive function is essential for quality of life and health outcomes in later years. Cognitive impairment, however, remains an undervalued long-term complication of type 2 diabetes by patients and providers alike. The burden of sustained hyperglycemia includes not only cognitive deficits but also the onset and progression of dementia-related conditions, including Alzheimer's disease (AD). Recent research has shown that the brain maintains an independent glucose "microsystem"-evolved to ensure the availability of fuel for brain neurons without interruption by transient hypoglycemia. When this milieu is perturbed, brain hyperglycemia, brain glucotoxicity, and brain insulin resistance can ensue and interfere with insulin signaling, a key pathway to cognitive function and neuronal integrity. This newly understood brain homeostatic system operates semi-autonomously from the systemic glucoregulatory apparatus. Large-scale clinical studies have shown that systemic dysglycemia is also strongly associated with poorer cognitive outcomes, which can be mitigated through appropriate clinical management of plasma glucose levels. Moreover, these studies demonstrated that glucose-lowering agents are not equally effective at preventing cognitive dysfunction. Glucagon-like peptide-1 (GLP-1) receptor analogs and sodium glucose cotransporter 2 inhibitors (SGLT2is) appear to afford the greatest protection; metformin and dipeptidyl peptidase 4 inhibitors (DPP-4is) also significantly improved cognitive outcomes. Sulfonylureas (SUs) and exogenous insulin, on the other hand, do not provide the same protection and may actually worsen cognitive outcomes. In the creation of a treatment plan, comorbid cognitive conditions should be considered. These efficacious treatments create a new gold standard of managing hyperglycemia-one which is consistent with the "complication-centric prescribing" mandates issued in type 2 diabetes treatment guidelines. The increasing longevity enjoyed by our populace places the onus on clinical care to play the "long game" in using targeted treatments for glucose control in patients with, or at risk for, cognitive decline to maintain cognitive wellness later in life. This article reviews critical emerging data for scientists and trialists and translates new enhancements in patient care for practitioners.

The neural basis of neuropsychiatric symptoms in Alzheimer's disease

Neuropsychiatric symptoms (NPS) such as depression, anxiety, apathy and aggression affect up to 90% of Alzheimer's disease (AD) patients. These symptoms significantly increase caregiver stress and institutionalization rates, and more importantly they are correlated with faster cognitive decline. However, the neuronal basis of NPS in AD remains largely unknown. Here, we review current understanding of NPS and related pathology in studies of AD patients and AD mouse models. Clinical studies indicate that NPS prevalence and severity vary across different AD stages and types. Neuroimaging and postmortem studies have suggested that pathological changes in the anterior cingulate cortex, hippocampus, prefrontal cortex, and amygdala are linked to NPS, although the precise mechanisms remain unclear. Studies of AD mouse models have indicated that amyloid-beta and tau-related neurodegeneration in the hippocampus, prefrontal cortex, and anterior cingulate cortex are correlated with NPS-like behavioral deficits. A better understanding of the NPS phenotypes and related pathological changes will pave the way for developing a better management strategy for NPS in AD patients.

Advances in Research on Meningeal Lymphatic Vessels in Central Nervous System Diseases

Meningeal lymphatic vessels (mLVs), located around the dural sinuses, are considered significant participants in cerebrospinal fluid (CSF) circulation. Meningeal lymphatic vessels not only drain fluids and metabolic waste from the brain into deep cervical lymph nodes (dCLNs) but also transport immune cells from the brain to dCLNs, thus regulating the interaction between the central and peripheral immune systems. These vessels play a crucial role in maintaining normal physiological functions of the central nervous system (CNS). Meningeal lymphatic vessels are involved in the pathophysiological processes of various CNS diseases, including neurodegenerative diseases, cerebrovascular diseases, and brain tumors. In aging and various CNS diseases, damage and dysfunction of mLVs have been observed, leading to the abnormal accumulation of toxic substances and exacerbating neural damage. By transporting antigen-presenting cells that have taken up antigens within the brain to dCLNs, mLVs modulate the activation of peripheral immune cells and their migration and infiltration into brain lesions. Certain drug interventions or physical therapies can modulate the drainage function of mLVs, effectively improving the prognosis of CNS diseases. This review provides a detailed introduction to the anatomic structure, physiological roles, and research advances of mLVs in CNS diseases. In addition, we propose new strategies for targeting mLVs in the treatment of CNS diseases.

Early-Life Parental Affection, Social Relationships in Adulthood, and Later-Life Cognitive Function

OBJECTIVE

Although research has demonstrated the long-term health consequences of childhood adversities, less is known about the long-term impact of positive childhood experiences, such as parental affection.

METHOD

Using longitudinal data (1995-2014) from the Midlife in the United States (MIDUS) study, we analyze structural equation models estimating direct and indirect pathways from early-life parental affection to changes in later-life cognitive function through relationship quality in adulthood among Black and White older adults (N = 1983).

RESULTS

Analyses revealed significant indirect effects of parental affection on better cognitive function through higher levels of social support (both average social support and family social support) in adulthood in the full sample and among Black respondents. Indirect pathways through relationship strain and through friend support were not significant.

DISCUSSION

This work elevates the importance of promoting positive parental relationships during childhood, with implications for better social relationships in adulthood and cognitive function in later life.

Neuroprotective role of curcumin on the hippocampus against the oxidative stress and inflammation of streptozotocin-induced diabetes in rats

In recent years, it has gained importance to determine the effects of diabetes on central nervous system complications. This study aimed to assess the neuroprotective properties of curcumin against neuronal damage in the rat hippocampus caused by diabetes. In accordance with this purpose, we investigated the effects of curcumin on oxidative/antioxidative parameters and pro-inflammatory cytokines in the hippocampal tissue of diabetic Wistar rats. For this purpose, 32 adults, male and healthy Wistar Albino rats were used. Animals were randomly divided into four separate groups: control (C), curcumin(Cu), diabetes (D) and Diabetes + Curcumin (DCu)-treated groups. 60 mg/kg STZ i.p. A single dose was administered to D and DCu groups. Cu and DCu groups were given 50 mg/kg/day curcumin by gavage. After four weeks of treatment, the animals were decapitated under anesthesia and tissue samples were taken for analyses of the parameters (TNF-α, IL-6, IL-1, IL-10, MDA, SOD, catalase, and GSH activities) in the hippocampal tissue. TNF-α, IL-6, IL-1, and MDA levels were increased significantly (p < 0.05) in rats with diabetes compared to the other three groups. TNF-α, IL-6, IL-1, and MDA levels were lower in DCu group animals compared to the D group. It was determined that IL-10, SOD, Catalase, and GSH levels, which were significantly decreased in the D group, increased in the curcumin-supplemented diabetic group (DCu). The relevant sentence has been changed as follows. In conclusion, our findings from this study prove the protective effect of curcumin against diabetes-induced neuropathy in the hippocampus in rats with STZ-induced diabetes.

The Cerebrovascular Side of Plasticity: Microvascular Architecture across Health and Neurodegenerative and Vascular Diseases

The delivery of nutrients to the brain is provided by a 600 km network of capillaries and microvessels. Indeed, the brain is highly energy demanding and, among a total amount of 100 billion neurons, each neuron is located just 10-20 μm from a capillary. This vascular network also forms part of the blood-brain barrier (BBB), which maintains the brain's stable environment by regulating chemical balance, immune cell transport, and blocking toxins. Typically, brain microvascular endothelial cells (BMECs) have low turnover, indicating a stable cerebrovascular structure. However, this structure can adapt significantly due to development, aging, injury, or disease. Temporary neural activity changes are managed by the expansion or contraction of arterioles and capillaries. Hypoxia leads to significant remodeling of the cerebrovascular architecture and pathological changes have been documented in aging and in vascular and neurodegenerative conditions. These changes often involve BMEC proliferation and the remodeling of capillary segments, often linked with local neuronal changes and cognitive function. Cerebrovascular plasticity, especially in arterioles, capillaries, and venules, varies over different time scales in development, health, aging, and diseases. Rapid changes in cerebral blood flow (CBF) occur within seconds due to increased neural activity. Prolonged changes in vascular structure, influenced by consistent environmental factors, take weeks. Development and aging bring changes over months to years, with aging-associated plasticity often improved by exercise. Injuries cause rapid damage but can be repaired over weeks to months, while neurodegenerative diseases cause slow, varied changes over months to years. In addition, if animal models may provide useful and dynamic in vivo information about vascular plasticity, humans are more complex to investigate and the hypothesis of glymphatic system together with Magnetic Resonance Imaging (MRI) techniques could provide useful clues in the future.

The role of lipid species in Alzheimer's disease onset: A comprehensive Mendelian randomization analysis

BACKGROUND

Alzheimer's disease (AD) remains a significant global health challenge, with its etiology intricately linked to a variety of genetic and environmental factors. Among these, lipid metabolism has been hypothesized to play a crucial role, though the causal pathways remain inadequately elucidated. This study aims to employ Mendelian Randomization (MR) to unravel the potential causal relationships between a comprehensive array of lipid species and the risk of developing AD.

METHODS

Utilizing a two-sample MR framework, we analyzed data from genome-wide association studies (GWAS) encompassing 487,511 individuals of European descent. A total of 179 lipid species across 13 lipid categories were investigated for their causal association with AD. Genetic variants serving as instrumental variables (IVs) were carefully selected based on stringent criteria to ensure validity. The statistical analyses, including inverse variance weighting (IVW), weighted median-based estimation, and sensitivity analyses, were conducted using the R software environment.

RESULTS

Our findings reveal a significant causal relationship between ten specific lipid species and the risk of AD. Notably, certain lipids such as Sterol ester (27:1/15:0) and Phosphatidylcholine (16:0_22:4) exhibited a protective effect against AD, as evidenced by their inverse correlation with the disease's risk. Additionally, a reciprocal analysis suggested a negative causal impact of AD on the levels of certain Triacylglycerol species. The integrity of our results was reinforced by sensitivity analyses, including the MR Egger intercept test, indicating the absence of horizontal pleiotropy and confirming the reliability of our findings.

CONCLUSIONS

This study substantiates the causal link between specific lipid species and Alzheimer's disease, highlighting the complex interplay between lipid metabolism and AD pathogenesis. The identified lipid biomarkers offer new insights into the disease's etiology and potential therapeutic targets. Furthermore, our rigorous methodological approach demonstrates the utility of MR in disentangling the causal relationships in complex diseases.

Synthesis and Evaluation of Chloride-Substituted Ramalin Derivatives for Alzheimer's Disease Treatment

Alzheimer's disease (AD) is a progressive neurodegenerative disorder marked by the accumulation of amyloid-beta plaques and hyperphosphorylated tau proteins, leading to cognitive decline and neuronal death. However, despite extensive research, there are still no effective treatments for this condition. In this study, a series of chloride-substituted Ramalin derivatives is synthesized to optimize their antioxidant, anti-inflammatory, and their potential to target key pathological features of Alzheimer's disease. The effect of the chloride position on these properties is investigated, specifically examining the potential of these derivatives to inhibit tau aggregation and beta-site amyloid precursor protein cleaving enzyme 1 (BACE-1) activity. Our findings demonstrate that several derivatives, particularly RA-3Cl, RA-4Cl, RA-26Cl, RA-34Cl, and RA-35Cl, significantly inhibit tau aggregation with inhibition rates of approximately 50%. For BACE-1 inhibition, Ramalin and RA-4Cl also significantly decrease BACE-1 expression in N2a cells by 40% and 38%, respectively, while RA-23Cl and RA-24Cl showed inhibition rates of 30% and 35% in SH-SY5Y cells. These results suggest that chloride-substituted Ramalin derivatives possess promising multifunctional properties for AD treatment, warranting further investigation and optimization for clinical applications.

Effect of early menopause on cognition and brain morphology in an Urban Indian Cohort

BACKGROUND

Evidence for the effect of early menopause on cognition among older women is not consistent and is scant among the Indian population.

METHODS

We aimed to examine the effect of early menopause (≤45 years) on cognitive performance and brain morphology among older dementia-free females of the TLSA cohort using a multiple linear regression analysis.

RESULTS

In a sample of 528 women, 144 (27%) had early menopause. The linear regression analysis showed that women with early menopause performed poorly in cognition and had lesser total gray matter volume [β = -11973.94, p = 0.033], left middle frontal [β = -353.14, p = 0.033], and left superior frontal [β = -460.97, p < 0.026] volume.

CONCLUSION

Dementia-free women with early menopause had poorer cognition, lower total gray matter, and frontal lobe. More research is needed to explore the link between earlier menopause and cognitive decline and develop ways to address it.

HIGHLIGHTS

Evidence on the effect of early menopause on brain morphology is inconsistent and scant in low and middle-income countries, such as India. In a cohort of dementia-free individuals in urban Bangalore, we observed that participants with early menopause had significantly lower cognitive performance and lower total gray matter and frontal lobe volume. We recommend increasing awareness of this fact among the medical community and the general public. There is an urgent need to explore the underlying biological mechanism and to discover effective interventions to mitigate the effect.

Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers

BACKGROUND

Early signs of Alzheimer disease (AD) are difficult to detect, causing diagnoses to be significantly delayed to time points when brain damage has already occurred and current experimental treatments have little effect on slowing disease progression. Tracking cognitive decline at early stages is critical for patients to make lifestyle changes and consider new and experimental therapies. Frequently studied biomarkers are invasive and costly and are limited for predicting conversion from normal to mild cognitive impairment (MCI).

OBJECTIVE

This study aimed to use data collected from fitness trackers to predict MCI status.

METHODS

In this pilot study, fitness trackers were worn by 20 participants: 12 patients with MCI and 8 age-matched controls. We collected physical activity, heart rate, and sleep data from each participant for up to 1 month and further developed a machine learning model to predict MCI status.

RESULTS

Our machine learning model was able to perfectly separate between MCI and controls (area under the curve=1.0). The top predictive features from the model included peak, cardio, and fat burn heart rate zones; resting heart rate; average deep sleep time; and total light activity time.

CONCLUSIONS

Our results suggest that a longitudinal digital biomarker differentiates between controls and patients with MCI in a very cost-effective and noninvasive way and hence may be very useful for identifying patients with very early AD who can benefit from clinical trials and new, disease-modifying therapies.

Age-associated dementia among older people aging with HIV in the United States: a modeling study

OBJECTIVE

Almost 400 000 people with HIV (PWH) in the United States are over age 55 years and at risk for age-associated dementias (AAD), including Alzheimer's disease and vascular contributions to cognitive impairment and dementia (VCID). We projected the cumulative incidence and mortality associated with AAD among PWH at least 60 years in the United States compared with the general population.

DESIGN/METHODS

Integrating the CEPAC and AgeD-Pol models, we simulated two cohorts of 60-year-old male and female individuals: PWH, and the general US population. We estimated AAD incidence and AAD-associated mortality rates. Projected outcomes included AAD cumulative incidence, life expectancy, and quality-adjusted life-years (QALYs). We performed sensitivity and scenario analyses on AAD-specific (e.g. incidence) and HIV-specific (e.g. disengagement from HIV care) parameters, as well as premature aging among PWH.

RESULTS

We projected that 22.1%/16.3% of 60-year-old male individuals/female individuals with HIV would develop AAD by 80 years compared with 15.9%/13.3% of male individuals/female individuals in the general population. Accounting for age-associated and dementia-associated quality of life, 60-year-old PWH would have a lower life expectancy (QALYs): 17.4 years (14.1 QALYs) and 16.8 years (13.4 QALYs) for male and female individuals, respectively, compared with the general population [male individuals, 21.7 years (18.4 QALYs); female individuals, 24.7 years (20.2 QALYs)]. AAD cumulative incidence was most sensitive to non-HIV-related mortality, engagement in HIV care, and AAD incidence rates.

CONCLUSION

Projected estimates of AAD-associated morbidity, mortality, and quality of life can inform decision-makers and health systems planning as the population of PWH ages. Improved AAD prevention, treatment, and supportive care planning are critical for people aging with HIV.

Characterization of African-American Super-Agers in the National Alzheimer's Coordinating Center cohort

BACKGROUND

"Super-agers" are adults aged ≥80 with cognitive performance similar to persons two to three decades younger. Characteristics such as larger hippocampal volume, APOE-ε4 allele absence, higher educational attainment, female sex, and lifelong cognitive stimulation are associated with cognitive performance compatible with super-aging. These findings are based on predominantly white research samples. Limited data are available on African-American super-agers. To fill this gap, we explored potential factors associated with super-aging in older African-American adults.

METHODS

Data from African-American participants aged ≥80 in the National Alzheimer's Coordinating Center (NACC) dataset were analyzed. Using global Clinical Dementia Rating (CDR) scores, participants were first categorized as impaired (score ≥0.5) or non-impaired/normal cognition (NC) (score = 0). From the NC group, super-agers were identified using NACC-data-driven cutoffs. Participants were considered super-agers if their memory performance was similar to persons aged 50-60 with NC, and their performance on other domains was within one standard deviation of the mean for persons aged ≥80. We examined group characteristics (NC, super-ager, impaired) using chi-square and ANOVA with pairwise comparisons. Multinomial logistic regression, adjusted for sex and education, evaluated correlates of super-ager group assignment.

RESULTS

Data for 1285 African-American participants aged ≥80 were analyzed. We identified 24.7% (n = 316) NC, 4.8% (n = 61) super-agers, and 70.6% (n = 905) impaired. Super-agers were mostly female and more educated, had similar vascular comorbidities as the other groups, and had less sleep disorders, depression, and alcohol use. After adjusting for sex and education, super-ager group assignment was associated with less sleep disorders, less depression, and moderate alcohol use.

CONCLUSIONS

Participants with controlled vascular risk, mental health, alcohol use, and sleep disorders tended to be in the super-ager group. These factors may be important focus areas in clinical practice to support cognitive resilience with aging in older African-American adults.

2024 Alzheimer's disease facts and figures

This article describes the public health impact of Alzheimer's disease (AD), including prevalence and incidence, mortality and morbidity, use and costs of care and the ramifications of AD for family caregivers, the dementia workforce and society. The Special Report discusses the larger health care system for older adults with cognitive issues, focusing on the role of caregivers and non-physician health care professionals. An estimated 6.9 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060, barring the development of medical breakthroughs to prevent or cure AD. Official AD death certificates recorded 119,399 deaths from AD in 2021. In 2020 and 2021, when COVID-19 entered the ranks of the top ten causes of death, Alzheimer's was the seventh-leading cause of death in the United States. Official counts for more recent years are still being compiled. Alzheimer's remains the fifth-leading cause of death among Americans age 65 and older. Between 2000 and 2021, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 140%. More than 11 million family members and other unpaid caregivers provided an estimated 18.4 billion hours of care to people with Alzheimer's or other dementias in 2023. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $346.6 billion in 2023. Its costs, however, extend to unpaid caregivers' increased risk for emotional distress and negative mental and physical health outcomes. Members of the paid health care and broader community-based workforce are involved in diagnosing, treating and caring for people with dementia. However, the United States faces growing shortages across different segments of the dementia care workforce due to a combination of factors, including the absolute increase in the number of people living with dementia. Therefore, targeted programs and care delivery models will be needed to attract, better train and effectively deploy health care and community-based workers to provide dementia care. Average per-person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2024 for health care, long-term care and hospice services for people age 65 and older with dementia are estimated to be $360 billion. The Special Report investigates how caregivers of older adults with cognitive issues interact with the health care system and examines the role non-physician health care professionals play in facilitating clinical care and access to community-based services and supports. It includes surveys of caregivers and health care workers, focusing on their experiences, challenges, awareness and perceptions of dementia care navigation.

The effect of the apolipoprotein E ε4 allele and olfactory function on odor identification networks

INTRODUCTION

The combination of apolipoprotein E ε4 (ApoE ε4) status, odor identification, and odor familiarity predicts conversion to mild cognitive impairment (MCI) and Alzheimer's disease (AD).

METHODS

To further understand olfactory disturbances and AD risk, ApoE ε4 carrier (mean age 76.38 ± 5.21) and ε4 non-carrier (mean age 76.8 ± 3.35) adults were given odor familiarity and identification tests and performed an odor identification task during fMRI scanning. Five task-related functional networks were detected using independent components analysis. Main and interaction effects of mean odor familiarity ratings, odor identification scores, and ε4 status on network activation and task-modulation of network functional connectivity (FC) during correct and incorrect odor identification (hits and misses), controlling for age and sex, were explored using multiple linear regression.

RESULTS

Findings suggested that sensory-olfactory network activation was positively associated with odor identification scores in ε4 carriers with intact odor familiarity. The FC of sensory-olfactory, multisensory-semantic integration, and occipitoparietal networks was altered in ε4 carriers with poorer odor familiarity and identification. In ε4 carriers with poorer familiarity, connectivity between superior frontal areas and the sensory-olfactory network was negatively associated with odor identification scores.

CONCLUSIONS

The results contribute to the clarification of the neurocognitive structure of odor identification processing and suggest that poorer odor familiarity and identification in ε4 carriers may signal multi-network dysfunction. Odor familiarity and identification assessment in ε4 carriers may contribute to the predictive value of risk for MCI and AD due to the breakdown of sensory-cognitive network integration. Additional research on olfactory processing in those at risk for AD is warranted.

Association of vitamin B1 intake with geriatric cognitive function: An analysis of the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2014

BACKGROUND

The association between dietary vitamin B1 intake and cognitive performance in the noninstitutionalized older adult population of the United States remains unclear.

PURPOSE

This study aimed to investigate the association between vitamin B1 intake and cognitive performance in older adults in the United States.

METHODS

Vitamin B1 intake was assessed through two 24-h dietary recalls. Weighted logistic regression was used to evaluate the association between vitamin B1 intake and three cognitive scores (immediate recall test [IRT], animal fluency test [AFT], and digit symbol substitution test [DSST]). Cognitive performance was measured by these three tests, and individuals scoring below the lowest quartile were categorized as cognitive impairment. Sensitivity analysis, including dose-response curves, subgroup analyses, interaction effects, per 1 SD, and quartiles, were performed to ensure the accuracy of the conclusion.

RESULTS

A total of 2896 participants over the age of 60 were included in this study. In the adjusted final model, the association between vitamin B1 intake and low cognitive performance in old age was statistically significant, with the following odds ratios (ORs) and 95% confidence intervals (CIs): IRT, 0.75 (0.57, 0.97), P = 0.018; AFT, 0.68 (0.50, 0.92), P = 0.007; DSST, 0.71 (0.54, 0.92), P = 0.005. Subgroup analyses showed that this association was statistically significant among males, white, low-education, and no memory impairment. The results of the sensitivity analyses confirmed the association between VB1 and cognitive function in old age and the absence of interactions in the final calibrated model.

CONCLUSION

Dietary vitamin B1 intake is negatively associated with cognitive performance in older adults.

Physical Exercise Alters Egress Pathways for Intrinsic CSF Outflow: An Investigation Performed with Spin-labeling MR Imaging

PURPOSE

Cerebrospinal fluid (CSF) clearance is essential for maintaining a healthy brain and cognition by removal of metabolic waste from the central nervous system. Physical exercise has been shown to improve human health; however, the effect of physical exercise on intrinsic CSF outflow in humans remains unexplored. The purpose of this study was to investigate intrinsic CSF outflow pathways and quantitative metrics of healthy individuals with active and sedentary lifestyles. In addition, the effect of exercise was investigated among the sedentary subjects before and after 3 weeks of physical activity.

METHODS

This study was performed on 18 healthy adults with informed consent, using a clinical 3-Tesla MRI scanner. We classified participants into two groups based on reported time spent sitting per day (active group: < 7 hours sitting per day and sedentary group: ≥ 7 hours sitting per day). To elucidate the effect of exercise, sedentary individuals increased their activity to 3.5 hours for 3 weeks.

RESULTS

We show that there are two intrinsic CSF egress pathways of the dura mater and lower parasagittal dura (PSD). The adults with an active lifestyle had greater intrinsic CSF outflow metrics than adults with a more sedentary lifestyle. However, after increased physical activity, the sedentary group showed improved CSF outflow metrics. This improvement was particularly notable at the lower PSD, where outflow metrics were highest among the active group.

CONCLUSION

Our findings describe the relationship between physical activity and intrinsic CSF outflow and show a potential selective outflow pathway with increasing physical activity in the lower PSD pathway, potentially from the perivascular space or cortical venous subpial space.

Differential DNA methylation in the brain as potential mediator of the association between traffic-related PM2.5 and neuropathology markers of Alzheimer's disease

INTRODUCTION

Growing evidence indicates that fine particulate matter (PM2.5) is a risk factor for Alzheimer's disease (AD), but the underlying mechanisms have been insufficiently investigated. We hypothesized differential DNA methylation (DNAm) in brain tissue as a potential mediator of this association.

METHODS

We assessed genome-wide DNAm (Illumina EPIC BeadChips) in prefrontal cortex tissue and three AD-related neuropathological markers (Braak stage, CERAD, ABC score) for 159 donors, and estimated donors' residential traffic-related PM2.5 exposure 1, 3, and 5 years prior to death. We used a combination of the Meet-in-the-Middle approach, high-dimensional mediation analysis, and causal mediation analysis to identify potential mediating CpGs.

RESULTS

PM2.5 was significantly associated with differential DNAm at cg25433380 and cg10495669. Twenty-four CpG sites were identified as mediators of the association between PM2.5 exposure and neuropathology markers, several located in genes related to neuroinflammation.

DISCUSSION

Our findings suggest differential DNAm related to neuroinflammation mediates the association between traffic-related PM2.5 and AD.

HIGHLIGHTS

First study to evaluate the potential mediation effect of DNA methylation for the association between PM2.5 exposure and neuropathological changes of Alzheimer's disease. Study was based on brain tissues rarely investigated in previous air pollution research. Cg10495669, assigned to RBCK1 gene playing a role in inflammation, was associated consistently with 1-year, 3-year, and 5-year traffic-related PM2.5 exposures prior to death. Meet-in-the-middle approach and high-dimensional mediation analysis were used simultaneously to increase the potential of identifying the differentially methylated CpGs. Differential DNAm related to neuroinflammation was found to mediate the association between traffic-related PM2.5 and Alzheimer's disease.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Longitudinal Associations of Diet, Food Insecurity, and Supplemental Nutrition Assistance Program Use with Global Cognitive Performance in Middle-Aged and Older Adults

BACKGROUND

Diet quality, food access, and food assistance policies may be key modifiable factors related to cognitive decline.

OBJECTIVE

We aimed to evaluate whether diet quality, food insecurity, and Supplemental Nutrition Assistance Program (SNAP) use are associated with longitudinal changes in cognition among older adults in the United States.

METHODS

Food intake data from the Health Care and Nutrition Study were linked with longitudinal health information from 5 waves of the Health and Retirement Study (2012-2020). The analytic sample (n = 6968) included community-dwelling United States adults aged ≥51 y without cognitive impairment. Global cognition was measured using a telephone-based cognitive status interview (range: 0-27). Diet quality was measured with the Healthy Eating Index, using participants' average intake of 13 dietary components. Questions regarding food access and affordability were used to determine food insecurity and use of SNAP benefits. Linear mixed-effects regression models were used to estimate longitudinal associations between diet-related factors and cognitive score changes.

RESULTS

Poorer diets [β: -0.24; 95% confidence interval (CI): -0.33, -0.15], food insecurity (β: -1.08; 95% CI: -1.31, -0.85), and SNAP use (β: -0.57; 95% CI: -0.82, -0.32) were associated with lower baseline cognitive scores. Poorer diets (β: -0.17; 95% CI: -0.29, -0.05) and food insecurity (β: -0.23; 95% CI: -0.47, -0.01) were associated with significantly steeper declines in cognitive scores over time, after 8 and 2 y of follow-up, respectively; however, SNAP use was not significantly associated with the rate of cognitive decline over time. Estimates were qualitatively similar when restricting the sample to participants aged ≥65 y.

CONCLUSIONS

Results suggest that food access and adherence to healthy diet recommendations may be important elements to maintain cognitive health in aging. SNAP benefits may be insufficient to prevent negative cognitive effects of poor diet and limited access to nutritious foods.

Exploring Alzheimer's disease: a comprehensive brain connectome-based survey

Dementia is an escalating global health challenge, with Alzheimer's disease (AD) at its forefront. Substantial evidence highlights the accumulation of AD-related pathological proteins in specific brain regions and their subsequent dissemination throughout the broader area along the brain network, leading to disruptions in both individual brain regions and their interconnections. Although a comprehensive understanding of the neurodegeneration-brain network link is lacking, it is undeniable that brain networks play a pivotal role in the development and progression of AD. To thoroughly elucidate the intricate network of elements and connections constituting the human brain, the concept of the brain connectome was introduced. Research based on the connectome holds immense potential for revealing the mechanisms underlying disease development, and it has become a prominent topic that has attracted the attention of numerous researchers. In this review, we aim to systematically summarize studies on brain networks within the context of AD, critically analyze the strengths and weaknesses of existing methodologies, and offer novel perspectives and insights, intending to serve as inspiration for future research.

In Silico Identification of a Potential TNF-Alpha Binder Using a Structural Similarity: A Potential Drug Repurposing Approach to the Management of Alzheimer's Disease

Introduction

Alzheimer's disease (AD) is a neurodegenerative disorder with no conclusive remedy. Yohimbine, found in Rauwolfia vomitoria, may reduce brain inflammation by targeting tumour necrosis factor-alpha (TNFα), implicated in AD pathogenesis. Metoserpate, a synthetic compound, may inhibit TNFα. The study is aimed at assessing the potential utility of repurposing metoserpate for TNFα inhibition to reduce neuronal damage and inflammation in AD. The development of safe and effective treatments for AD is crucial to address the growing burden of the disease, which is projected to double over the next two decades.

Methods

Our study repurposed an FDA-approved drug as TNFα inhibitor for AD management using structural similarity studies, molecular docking, and molecular dynamics simulations. Yohimbine was used as a reference compound. Molecular docking used SeeSAR, and molecular dynamics simulation used GROMACS.

Results

Metoserpate was selected from 10 compounds similar to yohimbine based on pharmacokinetic properties and FDA approval status. Molecular docking and simulation studies showed a stable interaction between metoserpate and TNFα over 100 ns (100000 ps). This suggests a reliable and robust interaction between the protein and ligand, supporting the potential utility of repurposing metoserpate for TNFα inhibition in AD treatment.

Conclusion

Our study has identified metoserpate, a previously FDA-approved antihypertensive agent, as a promising candidate for inhibiting TNFα in the management of AD.

Optimizing the Implementation of a Lifestyle Dementia Prevention Intervention for Older Patients in an Academic Healthcare System

Background

Interventions that promote healthy lifestyles are critical for the prevention of Alzheimer's disease and Alzheimer's disease related dementias (AD/ADRD). However, knowledge of the best practices for implementing AD/ADRD prevention in healthcare settings remains limited.

Objective

We aimed to qualitatively identify barriers and facilitators to implementing a clinical trial of a novel lifestyle intervention (My Healthy Brain) in our medical center for older patients with subjective cognitive decline who are at-risk for AD/ADRD.

Methods

We conducted focus groups with 26 healthcare professionals (e.g., physicians, psychology, nursing) from 5 clinics that treat older patients (e.g., memory care, psychiatry). Our qualitative analysis integrated two implementation frameworks to systematically capture barriers and facilitators to AD/ADRD prevention (Consolidated Framework for Implementation Science Research) that impact implementation outcomes of acceptability, appropriateness, and feasibility (Proctor's framework).

Results

We found widespread support for an RCT of My Healthy Brain and AD/ADRD prevention. Participants identified barriers related to patients (stigma, technological skills), providers (dismissiveness of "worried well," doubting capacity for behavior change), clinics (limited time and resources), and the larger healthcare system (underemphasis on prevention). Implementation strategies guided by Expert Recommendations for Implementing Change (ERIC) included: developing tailored materials, training staff, obtaining buy-in from leadership, addressing stigmatized language and practices, identifying "champions," and integrating with workflows and resources.

Conclusions

The results will inform our recruitment, enrollment, and retention procedures to implement the first randomized clinical trial of My Healthy Brain. Our study provides a blueprint for addressing multi-level barriers to the implementation of AD/ADRD prevention for older patients in medical settings.

Bibliometric Analysis of Alzheimer's Disease and Depression

BACKGROUND

The link between Alzheimer's disease and depression has been confirmed by clinical and epidemiological research. Therefore, our study examined the literary landscape and prevalent themes in depression-related research works on Alzheimer's disease through bibliometric analysis.

METHODS

Relevant literature was identified from the Web of Science core collection. Bibliometric parameters were extracted, and the major contributors were defined in terms of countries, institutions, authors, and articles using Microsoft Excel 2019 and VOSviewer. VOSviewer and CiteSpace were employed to visualize the scientific networks and seminal topics.

RESULTS

The analysis of literature utilised 10,553 articles published from 1991 until 2023. The three countries or regions with the most publications were spread across the United States, China, and England. The University of Toronto and the University of Pittsburgh were the major contributors to the institutions. Lyketsos, Constantine G., Cummings, JL were found to make outstanding contributions. Journal of Alzheimer's Disease was identified as the most productive journal. Furthermore, "Alzheimer's", "depression", "dementia", and "mild cognitive decline" were the main topics of discussion during this period.

LIMITATIONS

Data were searched from a single database to become compatible with VOSviewer and CiteSpace, leading to a selection bias. Manuscripts in English were considered, leading to a language bias.

CONCLUSION

Articles on "Alzheimer's" and "depression" displayed an upward trend. The prevalent themes addressed were the mechanisms of depression-associated Alzheimer's disease, the identification of depression and cognitive decline in the early stages of Alzheimer's, alleviating depression and improving life quality in Alzheimer's patients and their caregivers, and diagnosing and treating neuropsychiatric symptoms in Alzheimer. Future research on these hot topics would promote understanding in this field.

Association Between Reduced Posterior Occlusal Contact and Alzheimer's Disease Onset in Older Japanese Adults: Results from the LIFE Study

BACKGROUND

An association between poor oral health and cognitive decline has been reported. Most of these studies have considered the number of teeth as a criterion, only a few studies have analyzed the relationship between occlusal status and Alzheimer's disease (AD).

OBJECTIVE

To elucidate whether posterior occlusal contact is associated with AD, focusing on the Eichner classification, among an older population aged 65 years or older in Japan.

METHODS

This study used monthly claims data of National Health Insurance in Japan from April 2017 to March 2020. The outcome was newly diagnosed AD defined according to ICD-10 code G30. The number of teeth was estimated by dental code data, and occlusal contact was divided into three categories, namely A, B, and C, according to the Eichner classification. Multivariate Cox proportional hazards models were used to analyze the association between a new diagnosis of AD and the Eichner classification.

RESULTS

A total of 22,687 participants were included, 560 of whom had newly diagnosed AD during a mean follow-up period of 12.2 months. The AD participants had a lower proportion of Eichner A and a higher proportion of Eichner C. After adjusting for covariates, hazard ratios (95% confidence intervals) with Eichner B and C were 1.34 (1.01-1.77) and 1.54 (1.03-2.30), respectively.

CONCLUSION

In older people aged≥65 years old, reduced posterior occlusal contact as well as tooth loss have an impact on AD. This study emphasizes the importance of paying attention to occlusal contacts to reduce the risk of AD.

Projecting the Likely Impact of COVID-19 Infections on the Prevalence of Dementia in the United States

Background

The association between COVID-19 infection and the onset of dementia among adults 65 years and older has the potential to increase the burden of dementia worldwide significantly. Our research, which focuses on understanding the likely increase in the burden of dementia due to COVID-19 infection in the USA, has crucial public policy implications. By providing these insights, we aim to empower policymakers, healthcare professionals, researchers, and public health officials to make informed decisions and plan for the future.

Objective

Project the prevalence of dementia in the United States while accounting for the impact of COVID-19 infection on the onset of dementia.

Methods

A dynamic multi-state population model was developed. The model was initialized with USA demographic data and estimates of age, gender, and race-specific transition rates from the Health and Retirement Study (HRS).

Results

The projected increase in the burden of dementia among Americans 65 years and older is a staggering 14.838 million by 2050. However, due to the COVID-19 pandemic, we anticipate an additional 265,000 to 677,000 older adults 65 years and older will be affected by dementia. This will escalate the burden of dementia to a potential 15.103 million to 15.515 million by 2050, a significant human toll that we must be prepared for.

Conclusions

The projected dementia numbers underscore the urgent need for policy and intervention in social care services and healthcare needs planning. This includes providing robust support systems for caregivers and ensuring the healthcare staff is adequately trained to meet the healthcare needs of dementia patients and their families.

Pre-Randomization Predictors of Study Discontinuation in a Preclinical Alzheimer's Disease Randomized Controlled Trial

BACKGROUND

Participant discontinuation from study treatment in a clinical trial can leave a trial underpowered, produce bias in statistical analysis, and limit interpretability of study results. Retaining participants in clinical trials for the full study duration is therefore as important as participant recruitment.

OBJECTIVE

This analysis aims to identify associations of pre-randomization characteristics of participants with premature discontinuation during the blinded phase of the Anti-Amyloid treatment in Asymptomatic AD (A4) Study.

DESIGN

All A4 trial randomized participants were classified as having prematurely discontinued study during the blinded period of the study for any reason (dropouts) or completed the blinded phase of the study on treatment (completers).

SETTING

The trial was conducted across 67 study sites in the United States, Canada, Japan and Australia through the global COVID-19 pandemic.

PARTICIPANTS

The sample consisted of all 1169 A4 trial randomized participants.

MEASUREMENTS

Pre-randomization demographic, clinical, amyloid PET and genetic predictors of study discontinuation were evaluated using a univariate generalized linear mixed model (GLMM), with discontinuation status as the binary outcome, each predictor as a fixed effect, and site as a random effect to account for differences among study sites in the trial. Characteristics significant at p<0.10 were then included in a multivariable GLMM.

RESULTS

Among randomized participants, 339 (29%) discontinued the study during the blinded period (median follow-up time in trial: 759 days). From the multivariable analysis, the two main predictors of study discontinuation were screening State-Trait Anxiety Inventory (STAI) scores (OR = 1.07 [95%CI = 1.02; 1.12]; p=0.002) and age (OR = 1.06 [95%CI = 1.03; 1.09]; p<0.001). Participants with a family history of dementia (OR = 0.75 [95%CI = 0.55; 1.01]; p=0.063) and APOE ε4 carriers (OR = 0.79 [95%CI = 0.6; 1.04]; p=0.094) were less likely to discontinue from the study, with the association being marginally significant. In these analyses, sex, race and ethnicity, cognitive scores and amyloid/tau PET scores were not associated with study dropout.

CONCLUSIONS

In the A4 trial, older participants and those with higher levels of anxiety at baseline as measured by the STAI were more likely to discontinue while those who had a family history of dementia or were APOE ε4 carriers were less likely to drop out. These findings have direct implications for future preclinical trial design and selection processes to identify those individuals at greatest risk of dropout and provide information to the study team to develop effective selection and retention strategies in AD prevention studies.

Research Progress on Effects of Ginsenoside Rg2 and Rh1 on Nervous System and Related Mechanisms

Neurological-related disorders are diseases that affect the body's neurons or peripheral nerve tissue, such as Parkinson's disease (PD) and Alzheimer's disease (AD). The development of neurological disorders can cause serious harm to the quality of life and functioning of the patient. The use of traditional therapeutic agents such as dopamine-promoting drugs, anticholinergic drugs, cholinesterase inhibitors, and NMDA receptor antagonists is often accompanied by a series of side effects such as drug resistance, cardiac arrhythmia, liver function abnormalities, and blurred vision. Therefore, there is an urgent need to find a therapeutic drug with a high safety profile and few side effects. Herbal medicines are rich in active ingredients that are natural macromolecules. Ginsenoside is the main active ingredient of ginseng, which has a variety of pharmacological effects and is considered to have potential value in the treatment of human diseases. Modern pharmacological studies have shown that ginsenosides Rg2 and Rh1 have strong pharmacological activities in the nervous system, with protective effects on nerve cells, improved resistance to neuronal injury, modulation of neural activity, resistance to cerebral ischemia/reperfusion injury, improvement of brain damage after eclampsia hemorrhage, improvement of memory and cognitive deficits, treatment of AD and vascular dementia, alleviation of anxiety, pain, and inhibition of ionic-like behavior. In this article, we searched the pharmacological research literature of Rg2 and Rh1 in the field of neurological diseases, summarized the latest research progress of the two ginsenosides, and reviewed the pharmacological effects and mechanisms of Rg2 and Rh1, which provided a new way of thinking for the research of the active ingredients in ginseng anti-neurological diseases and the development of new drugs.

Alzheimer`s disease mortality in the United States: Cross-sectional analysis of county-level socio-environmental factors

BACKGROUND

Geographical disparities in mortality among Alzheimer`s disease (AD) patients have been reported and complex sociodemographic and environmental determinants of health (SEDH) may be contributing to this variation. Therefore, we aimed to explore high-risk SEDH factors possibly associated with all-cause mortality in AD across US counties using machine learning (ML) methods.

METHODS

We performed a cross-sectional analysis of individuals ≥65 years with any underlying cause of death but with AD in the multiple causes of death certificate (ICD-10,G30) between 2016 and 2020. Outcomes were defined as age-adjusted all-cause mortality rates (per 100,000 people). We analyzed 50 county-level SEDH and Classification and Regression Trees (CART) was used to identify specific county-level clusters. Random Forest, another ML technique, evaluated variable importance. CART`s performance was validated using a "hold-out" set of counties.

RESULTS

Overall, 714,568 individuals with AD died due to any cause across 2,409 counties during 2016-2020. CART identified 9 county clusters associated with an 80.1% relative increase of mortality across the spectrum. Furthermore, 7 SEDH variables were identified by CART to drive the categorization of clusters, including High School Completion (%), annual Particulate Matter 2.5 Level in Air, live births with Low Birthweight (%), Population under 18 years (%), annual Median Household Income in US dollars ($), population with Food Insecurity (%), and houses with Severe Housing Cost Burden (%).

CONCLUSION

ML can aid in the assimilation of intricate SEDH exposures associated with mortality among older population with AD, providing opportunities for optimized interventions and resource allocation to reduce mortality among this population.

Alzheimer's Targeted Treatments: Focus on Amyloid and Inflammation

Alzheimer's disease (AD) is the major cause of dementia that is now threatening the lives of billions of elderly people on the globe, and recent progress in the elucidation of the pathomechanism of AD is now opening venue to tackle the disease by developing and implementing "disease-modifying therapies" that directly act on the pathophysiology and slow down the progression of neurodegeneration. A recent example is the success of clinical trials of anti-amyloid b antibody drugs, whereas other therapeutic targets, e.g., inflammation and tau, are being actively investigated. In this dual perspective session, we plan to have speakers from leading pharmas in the field representing distinct investments in the AD space, which will be followed by the comment from scientific leadership of the Alzheimer's Association who will speak on behalf of all stakeholders. Neuroscientists participating in the Society for Neuroscience may be able to gain insights into the cutting edge of the therapeutic approaches to AD and neurodegenerative disorders, and discuss future contribution of neuroscience to this field.

Lecanemab: Looking Before We Leap

Lecanemab, a novel amyloid-sequestering agent, recently received accelerated Food and Drug Administration approval for the treatment of mild dementia due to Alzheimer disease (AD) and mild cognitive impairment (MCI). Approval was based on a large phase 3 trial, Clarity, which demonstrated reductions in amyloid plaque burden and cognitive decline with lecanemab. Three major concerns should give us pause before adopting this medication: Its beneficial effects are small, its harms are substantial, and its potential costs are unprecedented. Although lecanemab has a clear and statistically significant effect on cognition, its effect size is small and may not be clinically significant. The magnitude of lecanemab's cognitive effect is smaller than independent estimates of the minimally important clinical difference, implying that the effect may be imperceptible to a majority of patients and caregivers. Lecanemab's cognitive effects were numerically smaller than the effect of cholinesterase inhibitors and may be much smaller. The main argument in lecanemab's favor is that it may lead to greater cognitive benefit over time. Although plausible, there is a lack of evidence to support this conclusion. Lecanemab's harms are substantial. In Clarity, it caused symptomatic brain edema in 11% and symptomatic intracranial bleeding in 0.5% of participants. These estimates likely significantly underestimate these risks in general practice for 3 reasons: (1) Lecanemab likely interacts with other medications that increase bleeding, an effect minimized in Clarity. (2) The Clarity population is much younger than the real-world population with mild AD dementia and MCI (age 71 years vs 85 years) and bleeding risk increases with age. (3) Bleeding rates in trials are typically much lower than in clinical practice. Lecanemab's costs are unprecedented. Its proposed price of $26,500 is based on cost-effectiveness analyses with tenuous assumptions. However, even if cost-effective, it is likely to result in higher expenditures than any other medication. If its entire target population were treated, the aggregate medication expenditures would be $120 billion US dollars per year-more than is currently spent on all medications in Medicare Part D. Before adopting lecanemab, we need to know that lecanemab is not less effective, vastly more harmful, and 100× more costly than donepezil.

Understanding the role of psychiatrists in the diagnosis and management of mild cognitive impairment and mild Alzheimer's disease dementia: a cross-sectional survey

BACKGROUND

Alzheimer's disease (AD) is a progressive neurological disorder and the most common cause of dementia. The clinical continuum of AD ranges from asymptomatic disease to mild cognitive impairment (MCI), followed by AD dementia, categorized as mild, moderate, or severe. Almost one-third of patients suspected of having MCI or mild AD dementia are referred to specialists including psychiatrists. We sought to better understand the role that psychiatrists play in the diagnosis, treatment, and management of patients with all-cause MCI or mild AD dementia.

METHODS

We conducted an anonymous, online survey among physicians in the United States between February 4, 2021, and March 1, 2021. We surveyed psychiatrists, primary care physicians (PCPs), geriatricians, and neurologists who treat patients with all-cause MCI or mild AD dementia.

RESULTS

A total of 301 physicians participated in the survey, 50 of whom were psychiatrists. Of their patients with all-cause MCI or mild AD dementia, psychiatrists reported personally diagnosing two-thirds (67%). Psychiatrists used various methods to diagnose MCI or mild AD dementia including mental status testing (94%), review of patient medical history (86%), and neurological exams (61%). Upon diagnosis, psychiatrists reported most commonly discussing treatments (86%), management strategies (80%), disease progression (72%), and etiology of MCI or mild AD dementia (72%) with their patients. Most psychiatrists surveyed (82%) reported receiving advanced formal training in MCI and AD dementia care, primarily via residency training (38%), continuing medical education (22%) or fellowship (18%). Additionally, almost all psychiatrists (92%) reported receiving referrals for ongoing management of patients with MCI or mild AD dementia, primarily from PCPs or neurologists. However, only 46% of psychiatrists viewed themselves as the coordinator of care for their patients with MCI or mild AD dementia.

CONCLUSIONS

Many psychiatrists indicated that they were well-informed about MCI and AD dementia and have a strong interest in providing care for these patients. They can provide timely and accurate diagnosis of clinical MCI and mild AD dementia and develop optimal treatment plans for patients. Although many psychiatrists consider other physicians to be the care coordinators for patients with MCI and mild AD dementia, psychiatrists can play a key role in diagnosing and managing patients with MCI and mild AD dementia.

Longitudinal changes in metabolic network activity in early Alzheimer's disease

INTRODUCTION

The progression of Alzheimer's disease (AD) has been linked to two metabolic networks, the AD-related pattern (ADRP) and the default mode network (DMN).

METHODS

Converting and clinically stable cognitively normal subjects (n = 47) and individuals with mild cognitive impairment (n = 96) underwent 2-[18 F]fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) three or more times over 6 years (nscans  = 705). Expression levels for ADRP and DMN were measured in each subject and time point, and the resulting changes were correlated with cognitive performance. The role of network expression in predicting conversion to dementia was also evaluated.

RESULTS

Longitudinal increases in ADRP expression were observed in converters, while age-related DMN loss was seen in converters and nonconverters. Cognitive decline correlated with increases in ADRP and declines in DMN, but conversion to dementia was predicted only by baseline ADRP levels.

DISCUSSION

The results point to the potential utility of ADRP as an imaging biomarker of AD progression.

Assessing out-of-pocket expenses and indirect costs for the Alzheimer disease continuum in the United States

BACKGROUND: The societal costs of Alzheimer disease (AD) are considerable. Cost data stratified by cost category (direct and indirect) and AD severity in the United States are limited. OBJECTIVE: To describe out-of-pocket (OOP) expenses and indirect costs from unpaid caregiving and work impairment among patients with AD by severity and among patients with mild cognitive impairment (MCI) in a representative sample of the US population. METHODS: Data from the Health and Retirement Study (HRS) were used. HRS respondents were included if they reported an AD diagnosis or were considered as having MCI based on their cognitive performance. MCI and AD severity staging was performed using a crosswalk from results of the modified Telephone Interview of Cognitive Status to the Mini-Mental State Examination. OOP expenses were assessed along with indirect costs (costs to caregivers from providing unpaid help and costs to employers). Sensitivity analyses were performed by varying assumptions of caregiver employment, missed workdays, and early retirement. Patients with AD were stratified by nursing home status, type of insurance, and income level. All cost calculations applied sampling weights. RESULTS: A total of 18,786 patients were analyzed. Patients with MCI (n = 17,885) and AD (n = 901) were aged 67.8 ± 10.7 and 80.9 ± 9.3 years, were 55.7% and 63.3% female, and were 28.3% and 0.9% employed, respectively. OOP expenses per patient per month increased with AD severity, ranging from $420 in mild to $903 in severe AD but were higher in MCI ($554) than in mild AD. Indirect costs to employers were similar across the AD continuum ($197-$242). Costs from unpaid caregiving generally increased by disease severity, from $72 (MCI) to $1,298 (severe AD). Total OOP and indirect costs increased by disease severity, from $869 (MCI) to $2,398 (severe AD). Sensitivity analysis assuming nonworking caregivers and zero costs to employers decreased the total OOP and indirect costs by 32%-53%. OOP expenses were higher for patients with AD who had private insurance (P < 0.01), had higher incomes (P < 0.01), or were in nursing homes (P < 0.01). Indirect costs to caregivers were lower for patients with AD in nursing homes ($600 vs $1,372, P < 0.01). Total indirect costs were higher for patients with AD with lower incomes ($1,498 vs $1,136, P < 0.01) and for those not in nursing homes ($1,571 vs $799, P < 0.01). CONCLUSIONS: This study shows that OOP expenses and indirect costs increase with AD severity, OOP expenses increase with higher income, subscription of private insurance, and nursing home residency, and total indirect costs decrease with higher income and nursing home residency in the United States. DISCLOSURES This study was financially sponsored by Eisai. Drs Zhang and Tahami are employees of Eisai. Drs Chandak, Khachatryan, and Hummel are employees of Certara; Certara is a paid consultant to Eisai. The views expressed here are those of the authors and are not to be attributed to their respective affiliations. Laura De Benedetti, BSc, provided medical writing support to the manuscript; she is an employee of Certara.

The epidemiology of mild cognitive impairment, Alzheimer's disease and related dementia in U.S. veterans

INTRODUCTION

US veterans have a unique dementia risk profile that may be evolving over time.

METHODS

Age-standardized incidence and prevalence of Alzheimer's disease (AD), AD and related dementias (ADRD), and mild cognitive impairment (MCI) was estimated from electronic health records (EHR) data for all veterans aged 50 years and older receiving Veterans Health Administration (VHA) care from 2000 to 2019.

RESULTS

The annual prevalence and incidence of AD declined, as did ADRD incidence. ADRD prevalence increased from 1.07% in 2000 to 1.50% in 2019, primarily due to an increase in the prevalence of dementia not otherwise specified. The prevalence and incidence of MCI increased sharply, especially after 2010. The prevalence and incidence of AD, ADRD, and MCI were highest in the oldest veterans, in female veterans, and in African American and Hispanic veterans.

DISCUSSION

We observed 20-year trends of declining prevalence and incidence of AD, increasing prevalence of ADRD, and sharply increasing prevalence and incidence of MCI.

Cognitive-motor dual-task interference in Alzheimer's disease, Parkinson's disease, and prodromal neurodegeneration: A scoping review

BACKGROUND

Cognitive-motor interference (CMI) is a common deficit in Alzheimer's (AD) disease and Parkinson's disease (PD) and may have utility in identification of prodromal neurodegeneration. There is lack of consensus regarding measurement of CMI resulting from dual task paradigms.

RESEARCH QUESTION

How are individuals with AD, PD, and prodromal neurodegeneration impacted by CMI as measured by dual-task (DT) performance?

METHODS

A systematic literature search was performed in six datasets using the PRISMA guidelines. Studies were included if they had samples of participants with AD, PD, or prodromal neurodegeneration and reported at least one measure of cognitive-motor DT performance.

RESULTS

4741 articles were screened and 95 included as part of this scoping review. Articles were divided into three non-mutually exclusive groups based on diagnoses, with 26 articles in AD, 56 articles in PD, and 29 articles in prodromal neurodegeneration, and results presented accordingly.

SIGNIFICANCE

Individuals with AD and PD are both impacted by CMI, though the impact is likely different for each disease. We found a robust body of evidence regarding the utility of measures of DT performance in the detection of subtle deficits in prodromal AD and some signals of utility in prodromal PD. There are several key methodological challenges related to DT paradigms for the measurement of CMI in neurodegeneration. Overall, DT paradigms show good potential as a clinical method to probe specific brain regions, networks, and function; however, task selection and effect measurement should be carefully considered.

Association between choline supplementation and Alzheimer's disease risk: a systematic review protocol

Background and aims

There is growing evidence suggesting choline intake might have beneficial effects on cognitive function in the elderly. However, some studies report no relationship between choline intake and cognitive function or improvement in Alzheimer's disease patients. This protocol is for a systematic review of choline intake and Alzheimer's disease that aims to assess the comparative clinical effectiveness of choline supplementation on Alzheimer's disease risk.

Methods and analysis

literature search will be performed in PubMed, MEDLINE, EMBASE, CINAHL, Scopus, Cochrane, and the Web of Science electronic databases from inception until October 2023. We will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies will be included if they compared two different time points of choline biomarkers measures in men or women (65+) with Alzheimer's Disease. The risk of bias in the included studies will be assessed within the Covidence data-management software.

Results

This review will summarize the clinical trial and quasi-experimental evidence of choline intake on Alzheimer's disease risk for adults aged 65+. The results from all eligible studies included in the analysis will be presented in tables, text, and figures. A descriptive synthesis will present the characteristics of included studies (e.g., age, sex of participants, type, length of intervention and comparator, and outcome measures), critical appraisal results, and descriptions of the main findings.

Discussion

This systematic review will summarize the existing evidence on the association between Choline intake and AD and to make recommendations if appropriate. The results of this review will be considered with respect to whether there is enough evidence of benefit to merit a more definitive randomized controlled trial. The results will be disseminated through peer-reviewed journals population.

Conclusion

This protocol outlines the methodology for a systematic review of choline intake and AD. The resulting systematic review from this protocol will form an evidence-based foundation to advance nutrition care for individuals with AD or poor cognitive function.

Systematic review registration

http://www.crd.york.ac.uk/PROSPERO, identifier CRD42023395004.

Precipitating Mechanisms of Falls in Preclinical Alzheimer's Disease

Background

Individuals with Alzheimer's disease (AD) are more than twice as likely to incur a serious fall as the general population of older adults. Although AD is commonly associated with cognitive changes, impairments in other clinical measures such as strength or functional mobility (i.e., gait and balance) may precede symptomatic cognitive impairment in preclinical AD and lead to increased fall risk.

Objective

To examine mechanisms (i.e., functional mobility, cognition, AD biomarkers) associated with increased falls in cognitively normal older adults.

Methods

This 1-year study was part of an ongoing longitudinal cohort study. We examined the relationships among falls, clinical measures of functional mobility and cognition, and neuroimaging AD biomarkers in cognitively normal older adults. We also investigated which domain(s) best predicted fall propensity and severity through multiple regression models.

Results

A total of 182 older adults were included (mean age 75 years, 53% female). A total of 227 falls were reported over the year; falls per person ranged from 0-16 with a median of 1. Measures of functional mobility were the best predictors of fall propensity and severity. Cognition and AD biomarkers were associated with each other but not with the fall outcome measures.

Conclusion

These results suggest that, although subtle changes in cognition may be more closely associated with AD neuropathology, functional mobility indicators better predict falls in cognitively normal older adults. This study adds to our understanding of the mechanisms underlying falls in older adults and could lead to the development of targeted fall prevention strategies.

A Pilot Randomized Trial of a Purposeful and Stimulating Volunteer Opportunity: Program Satisfaction and Potential Impacts on Perceived Cognitive Change in a Neurologically Mixed Sample of Older Adults

BACKGROUND

Purposeful social interactions are important for healthy aging. We conducted a pilot trial of SPEAK! (Seniors Promoting English Acquisition and Knowledge), an intervention providing older volunteers with a safe, accessible opportunity to converse via webcam with English-language learners.

METHODS

A neurologically mixed sample of older adults was randomized to 8 weekly, webcam conversations with English-language learners or a waitlist control. Outcomes included the Cognitive Change Index (CCI) and surveys of program satisfaction. Here, we report on session completion, intervention satisfaction, and follow-up CCI scores. Exploratory analyses of CCI intervention effects controlled for baseline CCI scores and the interaction between group and baseline CCI.

RESULTS

Participants (N=38) were on average 70.8 years of age, 28/38 were White, and 16/38 demonstrated possible cognitive impairment on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Pairs completed 115/136 sessions (85%) and all volunteers said they would recommend the program. Controlling for the interaction between baseline CCI and randomization group, SPEAK! volunteers had better follow-up CCI scores than controls (P=0.018). Improvements in CCI were greater among participants with fewer baseline memory problems.

CONCLUSIONS

SPEAK! was feasible and appreciated by older adults with and without cognitive impairment. Larger studies should confirm benefits for memory and other determinants of quality of life.