Disease Dementia Research Articles

Perceived partner responsiveness alters the association between marital distress and well-being in dementia spousal caregivers

Caregivers for spouses with Alzheimer's disease and related dementias (ADRD) experience drastic changes in the marital relationship that may put them at risk for worsening well-being. Perceived partner responsiveness, or feeling cared for, understood, and appreciated by one's spouse, may help mitigate these effects. In this study, we investigated the associations between marital distress, perceived partner responsiveness, and psychological and physiological well-being indicators among ADRD spousal caregivers. MethodA sample of 161 caregivers provided blood samples and completed self-report measures of marital distress, perceived partner responsiveness, and depressive symptoms. We tested hypotheses in our sample cross-sectionally based on two theoretical frameworks. ResultsTesting the marital discord model of depression, caregivers who reported greater marital distress also reported more depressive symptoms, and this association was stronger as participants reported lower perceived partner responsiveness. Caregivers who reported greater marital distress exhibited elevated proinflammatory cytokine production by in vitro lipopolysaccharide (LPS)-stimulated peripheral blood leukocytes at low levels of perceived partner responsiveness, but not mean or high levels. Testing the vulnerability-stress-adaptation model, caregivers who reported more depressive symptoms also reported greater marital distress. Further, caregivers who exhibited elevated LPS-stimulated proinflammatory cytokine production reported greater marital distress at mean and high levels of perceived partner responsiveness, but not low levels. These patterns of results held even when accounting for the dementia stage and reported hours of caregiving per day. DiscussionThis study's findings contribute to the body of research examining interpersonal factors that shape health and well-being among the caregiver population.

The Diagnostic Challenges of Late-onset Neuropsychiatric Symptoms and Early-onset Dementia: A Clinical and Neuropathological Case Study

The emergence of new-onset neuropsychiatric symptoms in middle age presents a diagnostic challenge, particularly when differentiating between a primary psychiatric disorder and an early neurodegenerative disease. The discrepancy between bedside clinical diagnosis and subsequent neuropathological findings in such cases further highlights the difficulty of accurately predicting pathology, especially when there are no evident focal lesions or changes in brain volume. Here we present the case of a 59-year-old woman with inconclusive neuroimaging who exhibited pronounced neuropsychiatric and behavioral symptoms initially suggestive of a mood disorder, then of behavioral variant frontotemporal dementia. However, upon autopsy, we identified coexisting Lewy body disease pathology and tau-related changes, including argyrophilic grain disease and primary age–related tauopathy. This case illustrates the challenges encountered when diagnosing late-onset neuropsychiatric symptoms, emphasizes the link between such symptoms and early-onset dementia and argyrophilic grain disease, and contributes to our understanding of the impact of mixed neuropathology in this population. Accurate diagnosis is essential for the development of molecular-specific therapies and, as well as for accurate prognosis and enrollment in clinical trials.

The gut microbiota-brain axis role in neurodegenerative diseases and implications according to the sex

Recent advancements in neurodegenerative research have embraced a multisystemic approach, emphasizing the role of the gut microbiota and its interactions with various systems, including the central nervous system. This review explores the interactions between the gut-brain axis and neurological illnesses associated with ageing, with a particular focus on the potential influence of sex. Despite increased life expectancy, the chronological ceiling of human well-being remains unchanged, implying that conditions such as dementia and Parkinson's disease will continue to affect individuals for extended periods as lifespans increase. Understanding the microbiota-gut-brain axis in relation to neurodegenerative diseases may pave the way for novel therapeutic approaches. Additionally, emerging research suggests that sex-related variations in gut microbiota and the influence of sex hormones may impact the manifestation of several neurodegenerative conditions, including those related to mental health. This review updates the current knowledge on age-related neurodegenerative diseases, such as dementia, Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and dementia with Lewy bodies. Future research should focus on exploring microbial therapeutics for the treatment and prevention of age-related neurodegenerative disorders, as well as gender-specific variations in gut microbiota. In this context, the EU-funded project MEMOIR will investigate the impact of a healthy diet on gut microbiota and the progression of Mild Cognitive Impairment.

Single Nuclei Transcriptomics Reveals Obesity-Induced Endothelial and Neurovascular Dysfunction: Implications for Cognitive Decline.

Obesity confers risk for cardiovascular disease and vascular dementia. However, genomic alterations modulated by obesity in endothelial cells in the brain and their relationship to other neurovascular unit (NVU) cells are unknown. We performed single nuclei RNA sequencing (snRNAseq) of the NVU (endothelial cells, astrocytes, microglia, and neurons) from the hippocampus of obese (ob/ob) and wild-type (WT) male mice to characterize obesity-induced transcriptomic changes in a key brain memory center and assessed blood-brain barrier permeability (BBB) by gadolinium-enhanced magnetic resonance imaging (MRI). Ob/ob mice displayed obesity, hyperinsulinemia, and impaired glucose tolerance. snRNAseq profiled 14 distinct cell types and 32 clusters within the hippocampus of ob/ob and WT mice and uncovered differentially expressed genes (DEGs) in all NVU cell types, namely, 4462 in neurons, 1386 in astrocytes, 125 in endothelial cells, and 154 in microglia. Gene ontology analysis identified important biological processes such as angiogenesis in endothelial cells and synaptic trafficking in neurons. Cellular pathway analysis included focal adhesion and insulin signaling, which were common to all NVU cell types. Correlation analysis revealed significant positive correlations between endothelial cells and other NVU cell types. Differentially expressed long non-coding RNAs (lncRNAs) were observed in cells of the NVU-affecting pathways such as TNF and mTOR. BBB permeability showed a trend toward increased signal intensity in ob/ob mice. Taken together, our study provides in-depth insight into the molecular mechanisms underlying cognitive dysfunction in obesity and may have implications for therapeutic gene targeting.

Feasibility of Using a Novel, Multimodal Motor Function Assessment Platform With Machine Learning to Identify Individuals With Mild Cognitive Impairment.

Early identification of clinical conditions associated with Alzheimer disease and related dementias (ADRD) is vital for intervention. One promising early detection method is the use of instrumented assessment to identify subtle motor declines associated with ADRD. This pilot study sought to establish the feasibility of building a machine learning model to identify individuals with mild cognitive impairment (MCI) using motor function data obtained from an inexpensive, portable device. Our novel, multimodal motor function assessment platform integrates a depth camera, forceplate, and interface board. Healthy older adults (n=28) and older adults with MCI (n=19) were assessed during static balance, gait, and sit-to-stand activities in both single- and dual-task conditions. Three machine learning models (ie, support vector machine, decision trees, and logistic regression) were trained and tested with the goal of classification of MCI. Our best model was decision trees, which demonstrated an accuracy of 83%, a sensitivity of 0.83, a specificity of 1.00, and an F1 score of 0.83. The top features were extracted and ranked on importance. This study demonstrates the feasibility of building a machine learning model capable of identifying individuals with mild cognitive impairment using motor function data obtained with a portable, inexpensive, multimodal device.

Knowledge, perceptions, and feelings associated with Alzheimer’s disease and related dementias: a qualitative study among middle-aged latinas residing in an underserved agricultural community in California

BackgroundMiddle age is increasingly acknowledged as a critical window for prevention of Alzheimer’s disease and related dementia (ADRD) since research has shown that AD develops in the course of 20–30 years (1) but we know very little about middle-aged individuals’ perspectives on ADRD. Knowledge gaps are particularly large for Latinas living in regions typically underrepresented in ADRD research, such as rural and/or agricultural regions. This is important given that over the next 40 years Latinos are projected to have the largest increase in ADRD cases in the U.S. Therefore, this study aims to assess knowledge, perceptions, and feelings associated with ADRD among a sample of middle-age, Spanish-speaking Latina women.MethodUsing qualitative methods involving semi-structured interviews, we examined knowledge, perceptions, and feelings associated with ADRD among a subsample of the Center for Health Assessment of Mothers and Children of Salinas (CHAMACOS) study. Participants are Latina women residing in an underserved agricultural community entering mid-life (mean = 46.5 years old). Interviews were conducted with 20 women and data was analyzed with inductive thematic content analysis.ResultsWe identified themes regarding perceptions, knowledge, and feelings. First, participants perceive ADRD as involving (1) Loss of memory, (2) Getting lost; (3) Losing the person they once were. With regard to knowledge about ADRD, participants reported: (1) Some knowledge about protective and risk factors for ADRD, (2) No awareness of the links between cardiovascular risk factors and ADRD; (3) A desire to learn prevention methods alongside signs and symptoms of ADRD. Themes related to feelings about ADRD were: (1) Fear of developing ADRD and not being aware of reality or who they are; (2) Worry about losing relationships with loved ones and caretaking if diagnosed with ADRD; (3) Sadness about forgetting one’s family and depending on others if diagnosed with ADRD.ConclusionThe knowledge gaps and negative feelings associated with ADRD highlighted in this study underscore the need for ADRD interventions to include CVD prevention, particularly for mid-life Latino populations residing in rural regions.

Using Deep Learning Neural Networks to Improve Dementia Detection: Automating Coding of the Clock-Drawing Test.

Alzheimer's disease and related dementias (ADRD) is a growing public health concern. The clock-drawing test (CDT), where subjects draw a clock, typically with hands showing 11:10, has been widely used for ADRD-screening. A limitation of including CDT in large-scale studies is that the CDT requires manual coding, which could result in biases if coders interpret and implement coding rules differently. This study created and evaluated an intelligent CDT Clock Scoring system built with Deep Learning Neural Networks (DLNN) to automatically code CDT images. We used a large, publicly available repository of CDT images from the 2011-2019 National Health and Aging Trends Study (NHATS) and compared three advanced DLNN methods - ResNet101, EfficientNet and Vision Transformers (ViT) in coding CDT into binary and ordinal (0 to 5) scores. We extended beyond the traditional nominal classification approach (which does not recognize order) by introducing structured ordering into the coding system and compared DLNN-coded CDT images with manual coding. Results suggest that ViT outperforms ResNet101 and EfficientNet, as well as manual coding. The ordinal coding system has the ability to allow researchers to minimize either under- or over-estimation errors. Starting in 2022, our developed ViT-coding system has been used in NHATS' annual CDT-coding.

Cognitive Trajectories and Associated Social and Behavioral Determinants Among Racial/Ethnic Minority Older Adults in the United States.

Despite higher risks of developing Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) among racial/ethnic minority populations, some maintain good cognition until old age. This study aimed to investigate heterogeneous cognitive trajectories among non-Hispanic Black and Hispanic older adults, examine cognitive impairment prevalence across trajectory classes, and identify associated social and behavioral determinants. Using 11 waves of data from the Health and Retirement Study (1996-2016), 1,322 non-Hispanic Black and 747 Hispanic adults aged 50 + with normal cognition in 1996 were included. Latent class growth modeling and multinomial logistic regressions were performed to examine cognitive trajectories and associated determinants. For both racial/ethnic groups, three trajectory classes were identified: high, medium, and low cognition. In the low cognition class, 87% and 100% of non-Hispanic Black and Hispanic participants developed cognitive impairment. For both racial/ethnic groups, older age and living in rural areas during school time increased the likelihood of being in the low cognition class, while more education was associated with a lower likelihood. Unique risk and protective determinants for non-Hispanic Black and Hispanic participants were also identified. This study reveals the heterogeneity of cognitive trajectories among racial/ethnic minority older adults and various associated social and behavioral determinants. More prevention interventions and accessible, affordable diagnosis and treatment should be provided to older racial/ethnic minorities with these characteristics to reduce disparities. More research is needed to further explore associations between unique determinants and cognition in racial/ethnic minority populations to better inform interventions.

Structure-based computer-aided drug design to identify potential lead molecules for Asparaginyl Endopeptidase inhibitors.

The enzyme Asparaginyl Endopeptidase (AEP) is associated with proteinopathy-related pathologies such as Alzheimer's disease (AD) and Frontal Temporal Dementia (FTD). The onset of pathologies by AEP is due to cleaved fragments forming protein aggregates resulting in neurodegeneration. Unfortunately, there are no clinically approved small molecule inhibitors for AEP, and therefore, it serves as an unmet medical need for the design and development of potential novel small molecules. In developing potential inhibitors for proteolytic activity, a structured approach utilizing structure-based computer-aided drug design (SB-CADD) parameters was employed. This involved virtual high throughput screening (vHTS) across various CNS-focused databases enriched with diverse functionality. We identified the top sixty ligands based on the glide XP-docking score out of 10 million ligands. The free binding energy was then calculated using MM-GBSA for all top selected molecules which resulted in discovering that AEPI-1 to AEPI-6 (Asparaginyl Endopeptidase inhibitors) displayed high affinity towards the catalytic triad. Further investigation determined that all top six hits form stable complexes during 50 ns molecular dynamic simulations. We also observed that AEPI-2 demonstrated the highest stability within the binding pockets. Post-MD analyses such as DCCM, PCA, PDF, and ADMET properties were also evaluated. By bridging all the observations, we observed these six molecules occupy the active site of the β-helix (β1, β3, and β4) of the S1 pocket and additional binding sites in α1 and β5, suggesting its suitability as a potential candidate for drug discovery against Asparaginyl Endopeptidase.

The Relationship between Framingham Stroke Risk Profile on Incident Dementia and Alzheimer's Disease: A 40-Year Follow-Up Study Highlighting Female Vulnerability.

Sex differences in the association between cardiovascular risk factors and the incident all-cause dementia and the subtype Alzheimer's disease (AD) risk are unclear. Framingham Heart Study (FHS) participants (n = 4,171, 54% women, aged 55 to 69 years) were included at baseline and followed up to 40 years. The Framingham Stroke Risk Profile (FSRP) was dichotomized into 2 levels (cutoff: 75th percentile of the FSRP z-scores). Cause-specific hazard models, with death as a competing event, and restricted mean survival time (RMST) model were used to analyze the association between FSRP levels and incident all-cause dementia and AD. Interactions between FSRP and sex were estimated, followed by a sex-stratified analysis to examine the sex modification effect. High FSRP was significantly associated with all-cause dementia (hazard ratio [HR] = 1.25, robust 95% confidence interval [CI] = 1.21 to 1.29, p < 0.001) and AD (HR = 1.58, robust 95% CI = 1.57 to 1.59, p < 0.001) in cause-specific hazard models. High FSRP was significantly associated with incident dementia (HR = 2.81, robust 95% CI = 2.75 to 2.87, p < 0.001) and AD (HR = 2.96, robust 95% CI = 2.36 to 3.71, p < 0.001) in women, but not in men. Results were consistent in the RMST models. Current diabetes and high systolic blood pressure as FSRP components were significantly associated with dementia and AD in women but not in men. High FSRP in mid- to early late life is a critical risk factor for all-cause dementia and AD, particularly in women. Sex-specific interventions and further research to elucidate underlying mechanisms are warranted. ANN NEUROL 2024.

Rural Roads to Cognitive Resilience (RRR): A prospective cohort study protocol.

Ambient air pollution, detrimental built and social environments, social isolation (SI), low socioeconomic status (SES), and rural (versus urban) residence have been associated with cognitive decline and risk of Alzheimer's disease and related dementias (ADRD). Research is needed to investigate the influence of ambient air pollution and built and social environments on SI and cognitive decline among rural, disadvantaged, ethnic minority communities. To address this gap, this cohort study will recruit an ethnoracially diverse, rural Florida sample in geographic proximity to seasonal agricultural burning. We will (1) examine contributions of smoke-related fine particulate matter (PM2.5) exposures to SI and cognitive function; (2) determine effects of built and social environments on SI and cognitive function; and (3) contextualize SI and cognitive function among residents from different ethnoracial groups during burn and non-burn seasons. Methods: We will recruit 1,087 community-dwelling, dementia-free, >=45-year-olds from five communities in Florida's Lake Okeechobee region. Over 36 months, participants will complete baseline visits to collect demographics, health history, and health measurements (e.g., blood pressure, body mass index) and 6-month follow-ups assessing cognitive function and social isolation at each visit. A subsample of 120 participants representative of each community will wear smartwatches to collect sensor data (e.g., heart rate) and daily routine and predefined activities (e.g., GPS-captured travel, frequent destinations) over two months. Ecological momentary assessments (EMA) (e.g., whether smoke has bothered participant in last 30 minutes) will occur over two months during agricultural burning and non-burning months. PurpleAir monitors (36 total) will be installed in each community to continuously monitor outdoor PM2.5 levels. Ethics and expected impact: This study received Florida Atlantic University's Institutional Review Board approval and will require participant informed consent. We expect to identify individual- and community-level factors that increase the risk for SI and cognitive decline in a vulnerable rural population.

External validation of dementia prediction models in Black or African American and White older adults: A longitudinal population-based study in the United States.

Identifying people at high risk of Alzheimer's disease (AD) dementia allows for timely intervention, which, if successful, will result in preventing or delaying the onset of the disease. Utilizing data from the Chicago Health and Aging Project (CHAP; n=2130), we externally evaluated four risk-prediction models for AD dementia, including Cardiovascular Risk Factors, Aging, and Dementia (CAIDE), Australian National University Alzheimer's Disease Risk Index (ANU-ADRI), Brief Dementia Screening Indicator (BDSI), and Dementia Risk Score (DRS), in Black or African American and White adults. BDSI had the highest discriminate abilities for AD dementia (c-statistics of 0.79 in Black and 0.77 in White adults), followed by ANU-ADRI, within the age range and follow-up period of the original development cohort. CAIDE had the lowest discriminating power (c-statistic≤0.55). With increasing follow-up periods (i.e., 10-15 years), the discrimination abilities for all models declined. Because of racial disparities in AD dementia and longer preclinical and prodromal stages of disease development, race-specific models are needed to predict AD risk over 10 years. Utilizing risk-prediction models to identify individuals at higher risk of Alzheimer's disease (AD) dementia could benefit clinicians, patients, and policymakers. Clinicians could enroll high-risk individuals in clinical trials to test new risk-modifiable treatments or initiate lifestyle modifications, which, if successful, would slow cognitive decline and delay the onset of the disease. Current risk-prediction models had good discriminative power during the first 6 years of follow-up but decreased with longer follow-up time. Acknowledging the longer preclinical phase of AD dementia development and racial differences in dementia risk, there is a need to develop race-specific risk-prediction models that can predict 10 or 20 years of risk for AD and related dementias.

Optimal cutoff scores of the Montreal Cognitive Assessment to detect mild cognitive impairment and dementia in Costa Rican older adults

ABSTRACT Background The burden of Alzheimer’s disease and related dementias (AD/ADRD) in Costa Rica is expected to become one of the highest in the region. Early detection will help optimize resources and improve primary care interventions. The Montreal Cognitive Assessment (MoCA) has shown good sensitivity for detecting mild cognitive impairment (MCI), but specificity varies depending on the population. This motivated the analysis of different cutoffs to minimize false-positive classifications in a Costa Rican sample for its use in clinical settings. Methods Data was analyzed from 516 memory clinic outpatients (148 cognitively normal, 260 MCI, 108 mild AD/ADRD; mean age 66.3 ± 10.8 years) who underwent complete neurological and neuropsychological assessment and were diagnosed by consensus. Optimal MoCA cutoff scores were identified using a multiple cutoff approach. Results Overall, a cutoff score of ≥ 23 showed better accuracy to distinguish between normal cognition (NC) and MCI (sensitivity 73%, specificity 83%). When analyzed by educational levels, a cutoff score of ≥ 21 showed better accuracy for ≤ 6 years (sensitivity 80%, specificity 76%), ≥23 for 7–12 years (sensitivity 86%, specificity 76%) and ≥ 24 for > 12 years (sensitivity 70%, specificity 85%). For distinguishing MCI from mild AD/ADRD, the optimal overall cutoff score was ≥ 15 (sensitivity 66%, specificity 85%). When stratified by years of education, cutoff scores of ≥ 14 showed better accuracy for ≤ 6 years (sensitivity 70%, specificity 88%), ≥15 for 7–12 years (sensitivity 46%, specificity 95%) and ≥ 17 for > 12 years (sensitivity 67%, specificity 93%). Conclusions A MoCA cutoff score of ≥ 23 in the Costa Rican population showed better diagnostic accuracy for detecting MCI and may reduce the false positive rate. Our findings may be helpful for primary care clinical settings and further referral criteria.

Lactobacillus Eats Amyloid Plaque and Post-Biotically Attenuates Senescence Due to Repeat Expansion Disorder and Alzheimer's Disease.

Patients with Alzheimer's disease and related dementia (ADRD) are faced with a formidable challenge of focal amyloid deposits and cerebral amyloid angiopathy (CAA). The treatment of amyloid deposits in ADRD by targeting only oxidative stress, inflammation and hyperlipidemia has not yielded significant positive clinical outcomes. The chronic high-fat diet (HFD), or gut dysbiosis, is one of the major contributors of ADRD in part by disrupted transport, epigenetic DNMT1 and the folate 1-carbon metabolism (FOCM) cycle, i.e., rhythmic methylation/de-methylation on DNA, an active part of epigenetic memory during genes turning off and on by the gene writer (DNMT1) and eraser (TET2/FTO) and the transsulfuration pathway by mitochondrial 3-mercaptopyruvate sulfur transferase (3MST)-producing H2S. The repeat CAG expansion and m6A disorder causes senescence and AD. We aim to target the paradigm-shift pathway of the gut-brain microbiome axis that selectively inhibits amyloid deposits and increases mitochondrial transsulfuration and H2S. We have observed an increase in DNMT1 and decreased FTO levels in the cortex of the brain of AD mice. Interestingly, we also observed that probiotic lactobacillus-producing post-biotic folate and lactone/ketone effectively prevented FOCM-associated gut dysbiosis and amyloid deposits. The s-adenosine-methionine (SAM) transporter (SLC25A) was increased by hyperhomocysteinemia (HHcy). Thus, we hypothesize that chronic gut dysbiosis induces SLC25A, the gene writer, and HHcy, and decreases the gene eraser, leading to a decrease in SLC7A and mitochondrial transsulfuration H2S production and bioenergetics. Lactobacillus engulfs lipids/cholesterol and a tri-directional post-biotic, folic acid (an antioxidant and inhibitor of beta amyloid deposits; reduces Hcy levels), and the lactate ketone body (fuel for mitochondria) producer increases SLC7A and H2S (an antioxidant, potent vasodilator and neurotransmitter gas) production and inhibits amyloid deposits. Therefore, it is important to discuss whether lactobacillus downregulates SLC25A and DNMT1 and upregulates TET2/FTO, inhibiting β-amyloid deposits by lowering homocysteine. It is also important to discuss whether lactobacillus upregulates SLC7A and inhibits β-amyloid deposits by increasing the mitochondrial transsulfuration of H2S production.

Perceptions of brain health and aging among middle-aged latinos: A qualitative paper

ObjectivesLatinos living in the US are disproportionately impacted by Alzheimer’s disease and related dementias (ADRD). To develop culturally-informed interventions, a first step is engaging with key stakeholders. The present study aimed to explore perspectives on brain health and aging among middle-aged Latinos living in Chicago, IL. MethodsIndividual, semi-structured interviews were conducted with 30 English- or Spanish-speaking Latinos between 35 to 64 years old. Questions from a previously used interview guide were leveraged and addressed knowledge about the brain, perceptions of healthy and unhealthy aging, ideas of how to care for the brain, where knowledge was acquired, and suggestions for disseminating brain health education. Responses were analyzed using thematic analysis. ResultsThe following themes were identified: (1) Understanding of the brain is varied (including cognitive, behavioral, anatomical, and psychological descriptions); (2) Perceptions surrounding healthy aging are broad and demonstrate a depth of understanding (e.g., physical and cognitive abilities, independence, positive emotions, and sociability), yet understanding of signs of an unhealthy brain is somewhat limited (e.g., focus on memory); (3) Brain health promotion is largely viewed as actionable (spanning physical health, cognitively stimulating activities, emotional wellbeing, medical self-management, and social connectedness); (4) Suggestions for disseminating education included media, clinics, churches, libraries, and community centers, with consideration of possible barriers and facilitators to behavior change (e.g., finances, prioritizing family). ConclusionsResults showed significant heterogeneity in understanding of the brain, albeit with promising attitudes that actions can be taken to protect one’s brain from ADRD. Practice ImplicationsTakeaways include the need for increasing education on normative versus nonnormative memory loss and signs of ADRD beyond memory impairment. Messaging may benefit from utilizing analogies, considering familism and spirituality, and highlighting lifestyle changes that do not carry a financial burden or place blame on individuals.

Neuronal BAG3 attenuates tau hyperphosphorylation, synaptic dysfunction, and cognitive deficits induced by traumatic brain injury via the regulation of autophagy-lysosome pathway

Growing evidence supports that early- or middle-life traumatic brain injury (TBI) is a risk factor for developing Alzheimer’s disease (AD) and AD-related dementia (ADRD). Nevertheless, the molecular mechanisms underlying TBI-induced AD-like pathology and cognitive deficits remain unclear. In this study, we found that a single TBI (induced by controlled cortical impact) reduced the expression of BCL2-associated athanogene 3 (BAG3) in neurons and oligodendrocytes, which is associated with decreased proteins related to the autophagy-lysosome pathway (ALP) and increased hyperphosphorylated tau (ptau) accumulation in excitatory neurons and oligodendrocytes, gliosis, synaptic dysfunction, and cognitive deficits in wild-type (WT) and human tau knock-in (hTKI) mice. These pathological changes were also found in human cases with a TBI history and exaggerated in human AD cases with TBI. The knockdown of BAG3 significantly inhibited autophagic flux, while overexpression of BAG3 significantly increased it in vitro. Specific overexpression of neuronal BAG3 in the hippocampus attenuated AD-like pathology and cognitive deficits induced by TBI in hTKI mice, which is associated with increased ALP-related proteins. Our data suggest that targeting neuronal BAG3 may be a therapeutic strategy for preventing or reducing AD-like pathology and cognitive deficits induced by TBI.

Investigating the effects of indoor lighting on measures of brain health in older adults: protocol for a cross-over randomized controlled trial

BackgroundThe worldwide number of adults aged 60 years and older is expected to double from 1 billion in 2019 to 2.1 billion by 2050. As the population lives longer, the rising incidence of chronic diseases, cognitive disorders, and behavioral health issues threaten older adults’ health span. Exercising, getting sufficient sleep, and staying mentally and socially active can improve quality of life, increase independence, and potentially lower the risk for Alzheimer’s disease or other dementias. Nonpharmacological approaches might help promote such behaviors. Indoor lighting may impact sleep quality, physical activity, and cognitive function. Dynamically changing indoor lighting brightness and color throughout the day has positive effects on sleep, cognitive function, and physical activity of its occupants. The aim of this study is to investigate how different indoor lighting conditions affect such health measures to promote healthier aging.MethodsThis protocol is a randomized, cross-over, single-site trial followed by an exploratory third intervention. Up to 70 older adults in independent living residences at a senior living facility will be recruited. During this 16-week study, participants will experience three lighting conditions. Two cohorts will first experience a static and a dynamic lighting condition in a cluster-randomized cross-over design. The static condition lighting will have fixed brightness and color to match lighting typically provided in the facility. For the dynamic condition, brightness and color will change throughout the day with increased brightness in the morning. After the cross-over, both cohorts will experience another dynamic lighting condition with increased morning brightness to determine if there is a saturation effect between light exposure and health-related measures. Light intake, sleep quality, and physical activity will be measured using wearable devices. Sleep, cognitive function, mood, and social engagement will be assessed using surveys and cognitive assessments.DiscussionWe hypothesize participants will have better sleep quality and greater physical activity during the dynamic lighting compared to the static lighting condition. Additionally, we hypothesize there is a maximal threshold at which health-outcomes improve based on light exposure. Study findings may identify optimal indoor lighting solutions to promote healthy aging for older adults.Trial registrationClinicalTrials.gov Identifier: NCT05978934.

The impact of cardiovascular and cerebrovascular disease on the risk of dementia in rheumatoid arthritis: A mediation analysis

ObjectiveTo examine the role of cardiovascular disease (CVD) as a mediator in the pathway between rheumatoid arthritis (RA) and Alzheimer's disease and related dementias (ADRD). MethodsThis retrospective population-based study included patients over 50 years of age with incident RA, who met the 1987 ACR criteria in 1980–2014. This cohort was matched 1:1 on age, sex and index year to comparators without RA. Information on CVD events was manually extracted from electronic health records. The relationships between RA, CVD and ADRD were examined using Cox proportional hazard models. Time dependent mediation analysis was used to examine the role of CVD as a mediator between RA and ADRD. Results1754 individuals were included (877 persons with RA and 877 comparators without RA). During follow-up, 105 patients with RA and 102 individuals without RA developed ADRD; 444 patients with RA and 375 individuals without RA developed CVD. There was a non-significant association between RA and ADRD both without (aHR 1.27, 95 % CI 0.96, 1.69) and with (aHR 1.27, 95 % CI 0.95,1.68) CVD as a time dependent mediator. The mediation effect of any CVD on ADRD risk was not significant (p = 0.84). We found a significant interaction between RA and CVD on the risk of ADRD (aHR 1.95, 95 % CI 1.11, 3.42; p = 0.021). ConclusionsThe risk of ADRD in RA appears to be increased mainly in the presence of CVD. CVD was not a significant mediator on the risk of ADRD in RA. There was a significant synergistic effect of RA and CVD on ADRD risk.

Intervention for the Management of Neuropsychiatric Symptoms to Reduce Caregiver Stress: Protocol for the Mindful and Self-Compassion Care Intervention for Caregivers of Persons Living With Dementia.

Stress related to Alzheimer disease and related dementias (ADRD) is common, particularly among those who care for persons with challenging behaviors and personality or mood changes. Mindfulness and self-compassion programs are efficacious for managing stress. The skills of mindfulness and self-compassion, however, must be integrated with behavioral management skills in order to effectively improve caregiver stress. In this study, we aimed to describe the development of the Mindful and Self-Compassionate Care (MASC) program, the first program that combines mindfulness and self-compassion with behavioral management skills to decrease caregiver stress, and its evaluation in the Supporting Our Caregivers in ADRD Learning (SOCIAL) study. Using the National Institutes of Health (NIH) stage model, we describe 3 phases of work encompassing NIH Stages 1A and 1B. In phase 1, we conducted 5 focus groups (N=28) of stressed individuals caring for persons with ADRD and challenging behaviors. Rapid data analysis informed the development of a 6-week online intervention. Phase 2 (NIH stage 1A) includes an open pilot (N>10) with optional exit interviews. Phase 3 (NIH stage 1B) is a feasibility randomized controlled trial of the intervention versus the Health Education Program control. Primary outcomes focus on feasibility with secondary outcomes encompassing acceptability, credibility, fidelity, and signals of preliminary efficacy. Phase 1 follows traditional recommendations for qualitative analyses (at the point of thematic saturation) which was achieved after 5 focus groups (N=28). For the phase 2 open pilot, up to 12 participants will be recruited. For the phase 3 feasibility study, recruitment of 80 caregivers will allow the assessment of feasibility benchmarks. Data for phase 1 included 5 focus groups. In phases 2 and 3, data collection will occur through REDCap (Research Electronic Data Capture; Vanderbilt University) surveys and an optional qualitative exit interview. Analyses will include hybrid inductive-deductive analyses for qualitative data and assessment of changes in our intervention targets and outcomes using t tests and correlation analyses. In phase 1, caregivers reported interest in a brief, online stress management program. Participants held misconceptions about mindfulness and self-compassion, but after detailed explanation thoughts, these skills could be helpful when directly linked to implementation during caregiving routines. Phases 2 and 3 will be completed by the end of 2025. We describe the protocol for the Supporting Our Caregivers in ADRD Learning study, as well as the development and feasibility testing of the Mindful and Self-Compassionate Care intervention. Future work will include a fully powered efficacy-effectiveness randomized controlled trial. ClinicalTrials NCT05847153; https://clinicaltrials.gov/study/NCT05847153; and ClinicalTrials.gov NCT06276023; https://clinicaltrials.gov/study/NCT06276023. DERR1-10.2196/58356.

Association between allostatic load and accelerated white matter brain aging: findings from the UK biobank.

White matter (WM) brain age, a neuroimaging-derived biomarker indicating WM microstructural changes, helps predict dementia and neurodegenerative disorder risks. The cumulative effect of chronic stress on WM brain aging remains unknown. In this study, we assessed cumulative stress using a multi-system composite allostatic load (AL) index based on inflammatory, anthropometric, respiratory, lipidemia, and glucose metabolism measures, and investigated its association with WM brain age gap (BAG), computed from diffusion tensor imaging data using a machine learning model, among 22 951 European ancestries aged 40 to 69 (51.40% women) from UK Biobank. Linear regression, Mendelian randomization, along with inverse probability weighting and doubly robust methods, were used to evaluate the impact of AL on WM BAG adjusting for age, sex, socioeconomic, and lifestyle behaviors. We found increasing one AL score unit significantly increased WM BAG by 0.29years in association analysis and by 0.33years in Mendelian analysis. The age- and sex-stratified analysis showed consistent results among participants 45-54 and 55-64years old, with no significant sex difference. This study demonstrated that higher chronic stress was significantly associated with accelerated brain aging, highlighting the importance of stress management in reducing dementia and neurodegenerative disease risks.