Alzheimer's Disease Dementia Research Articles

The Alzheimer's Disease Neuroimaging Initiative-4 (ADNI-4) Engagement Core: A culturally informed, community-engaged research (CI-CER) model to advance brain health equity.

The Alzheimer's Disease Neuroimaging Initiative-4 (ADNI-4) Engagement Core was launched to advance Alzheimer's disease (AD) and AD-related dementia (ADRD) health equity research in underrepresented populations (URPs). We describe our evidence-based, scalable culturally informed, community-engaged research (CI-CER) model and demonstrate its preliminary success in increasing URP enrollment. URPs include ethnoculturally minoritized, lower education (≤ 12 years), and rural populations. The CI-CER model includes: (1) culturally informed methodology (e.g., less restrictive inclusion/exclusion criteria, sociocultural measures, financial compensation, results disclosure, Spanish Language Capacity Workgroup) and (2) inclusive engagement methods (e.g., the Engagement Core team; Hub Sites; Community-Science Partnership Board). As of April 2024, 60% of ADNI-4 new in-clinic enrollees were from ethnoculturally or educationally URPs. This exceeds ADNI-4's≥50% URP representation goal for new enrollees but may not represent final enrollment. Findings show a CI-CER model increases URP enrollment in AD/ADRD clinical research and has important implications for clinical trials to advance health equity. The Alzheimer's Disease Neuroimaging Initiative-4 (ADNI-4) uses a culturally informed, community-engaged research (CI-CER) approach. The CI-CER approach is scalable and sustainable for broad, multisite implementation. ADNI-4 is currently exceeding its inclusion goals for underrepresented populations.

Assessing clinical progression measures in Alzheimer's disease trials: A systematic review and meta-analysis.

Assessing treatments for Alzheimer's disease (AD) relies on reliable tools for measuring AD progression. In this analysis, we evaluate the sensitivity of clinical progression measures in AD within randomized controlled trials (RCTs) with confirmed positive amyloid (Aβ+) status prior to trial enrollment. Excluding trials targeting non-cognitive symptoms, we conducted meta-analyses on progression measures from 25 selected RCTs using R version 4.2.0, along with the metafor and emmeans libraries. The Functional Activities Questionnaire (FAQ) demonstrated the greatest sensitivity over 12weeks. Other cognitive measures demonstrated lower sensitivity. The integrated Alzheimer's Disease Rating Scale (iADRS) and Clinical Dementia Rating-Sum of Boxes (CDR-SB) seemed more effective than their individual cognitive components. Neuropsychiatric measures were the least sensitive in measuring progression. Functional measures generally outperformed other measure categories. Purely cognitive domain-based measures were suboptimal for tracking early AD progression. Ideally, future measures should incorporate both cognitive and functional components to enhance sensitivity. Concerns remain regarding the limitations of current outcome measures used in AD clinical trials, particularly their sensitivity in the early and preclinical stages of the disease, which hampers their reliability as indicators of AD progression. The Functional Activities Questionnaire (FAQ) demonstrated the most substantial weighted mean change over 12weeks, followed by the Mini-Mental State Examination (MMSE). Functional measures outperformed other measure categories. Composite scores of integrated Alzheimer's Disease Rating Scale and Clinical Dementia Rating-Sum of Boxes are more sensitive to change than their individual cognitive components, possibly driven by the functional components of the score. Neuropsychiatric measures analyzed in this study appeared to be the least sensitive in measuring progression.

SGLT2 Inhibitor Use and Risk of Dementia and Parkinson Disease Among Patients With Type 2 Diabetes.

Despite the mechanistic potential of sodium-glucose cotransporter 2 inhibitor (SGLT2i) to improve neurologic outcomes, the efficacy of SGLT2i in neurodegenerative disorders among patients with type 2 diabetes is not well established. This population-based cohort study aimed to investigate the association of SGLT2i use with risks of incident dementia and Parkinson disease (PD) in patients with type 2 diabetes. This was a retrospective examination of data from a cohort of 1,348,362 participants with type 2 diabetes (≥40 years), who started antidiabetic drugs from 2014 to 2019, evaluated using the Korean National Health Insurance Service Database. Propensity score matching (1:1; SGLT2i to other oral antidiabetic drugs [OADs]) produced a cohort of 358,862 participants. Primary outcomes were the individual incidence of Alzheimer disease (AD), vascular dementia (VaD), and PD. Secondary outcomes were all-cause dementia (AD, VaD, and other dementia) and a composite of all-cause dementia and PD. Cox proportional hazards models were used to investigate the association between SGLT2i use and the risks of dementia and PD. From the 358,862 participants analyzed (mean [SD] age, 57.8 [9.6] years; 58.0% male), 6,837 incident dementia or PD events occurred. Regarding the individual endpoints, SGLT2i use was associated with reduced risks of AD (adjusted hazard ratio [aHR] 0.81, 95% CI 0.76-0.87), VaD (aHR 0.69, 95% CI 0.60-0.78), and PD (aHR 0.80, 95% CI 0.69-0.91) with a 6-month drug use lag period. In addition, use of SGLT2i was associated with a 21% lower risk of all-cause dementia (aHR 0.79, 95% CI 0.69-0.90) and a 22% lower risk of all-cause dementia and PD than use of other OADs (aHR 0.78, 95% CI 0.73-0.83). The association between the use of SGLT2i and the lowered risk of these neurodegenerative disorders was not affected by sex, Charlson Comorbidity Index, diabetic complications, comorbidities, and medications. Sensitivity analysis further adjusting for bioclinical variables from health screening tests, including blood pressure, glucose, lipid profiles, and kidney function, yielded generally consistent results. In this nationwide population-based study, SGLT2i use significantly reduced the risks of neurodegenerative disorders in patients with type 2 diabetes independent of various factors including comorbidities and bioclinical parameters. This study provides Class II evidence that SGLT2 antidiabetic drugs decrease the risk of dementia and PD in people with diabetes.

Arc mediates intercellular tau transmission via extracellular vesicles.

Intracellular neurofibrillary tangles that consist of misfolded tau protein 1 cause neurodegeneration in Alzheimer's disease (AD) and frontotemporal dementia (FTD). Tau pathology spreads cell-to-cell 2 but the exact mechanisms of tau release and intercellular transmission remain poorly defined. Tau is released from neurons as free protein or in extracellular vesicles (EVs) 3-5 but the role of these different release mechanisms in intercellular tau transmission is unclear. Here, we show that the neuronal gene Arc is critical for packaging tau into EVs. Brain EVs purified from human tau (hTau) transgenic rTg4510 mice (rTg WT ) contain high levels of hTau that are capable of seeding tau pathology. In contrast, EVs purified from rTg WT crossed with Arc knock-out mice (rTg Arc KO ) have significantly less hTau and cannot seed tau aggregation. Arc facilitates the release of hTau in EVs produced via the I-BAR protein IRSp53, but not free tau. Arc protein directly binds hTau to form a fuzzy complex that we identified in both mouse and human brain tissue. We find that pathological intracellular hTau accumulates in neurons in rTg Arc KO mice, which correlates with accelerated neuron loss in the hippocampus. Finally, we find that intercellular tau transmission is significantly abrogated in Arc KO mice. We conclude that Arc-dependent release of tau in EVs plays a significant role in intracellular tau elimination and intercellular tau transmission.

Associations between people experiencing homelessness (PEH) and neurodegenerative disorders (NDDs): A systematic review and meta-analysis.

Homelessness represents a widespread social issue globally, yet the risk of neurodegenerative diseases (NDDs) associated with people experiencing homelessness (PEH) has not received sufficient attention. Therefore, this study aimed to explore the risk of NDDs among PEH and its variation across countries and regions through meta-analysis and systematic review. Searching from databases such as PubMed and Web of Science, relevant research articles on PEH and NDDs were identified. After multiple screening, eight articles were selected for meta-analysis. Statistical methods and models were used to evaluate the association between PEH and NDDs, stratified by disease type and country. We found that PEH had a 51% higher risk of NDDs (OR = 1.51 (95% CI: 1.21, 1.89)) compared with those with stable housing. Specifically, PEH had a significantly higher risk of developing multiple sclerosis (OR = 4.64 (95% CI: 1.96, 10.98)). Alzheimer's disease and related dementias (ADRD) (OR = 1.93 (95% CI: 1.34, 2.77)), dementia (OR = 1.69 (95% CI: 1.26, 2.27)), and cognitive impairment (OR = 1.07 (95% CI: 0.98, 1.16)) were all at higher risk. Furthermore, country and regional differences were observed, with countries such as Iran (OR = 4.64 (95% CI: 1.96, 10.98)), the Netherlands (OR = 2.14 (95% CI: 1.23, 3.73)), the United States (OR = 1.66 (95% CI: 1.25, 2.22)), and Canada (OR = 1.06 (95% CI: 1.01, 1.10)) showing a higher risk of NDDs among the PEH. The study emphasizes the significant NDD risks among PEH, providing novel perspectives on this issue and shedding light on national disparities influenced by variations in healthcare systems and social environments. This will be beneficial for academia and government to prioritize the health of PEH with NDDs, aiming to mitigate disease incidence and economic burdens while preserving social stability and upholding basic human rights.

Correlations between Cerebrospinal Fluid Biomarkers and Gray Matter Atrophy in Alzheimer's and Behavioural Variant Frontotemporal Dementia.

Distinguishing between frontotemporal dementia (FTD) and Alzheimer's disease (AD) in their early stages remains a significant clinical challenge. Cerebrospinal fluid (CSF) biomarkers (total Tau, phosphorylated Tau, and beta-amyloid) are promising candidates for identifying early differences between these conditions. This study investigates the relationship between grey matter density and CSF markers in the behavioural variant of frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). CSF and 3D T1-weighted magnetic resonance (MR) images were acquired from 14 bvFTD patients, 15 AD patients, and 13 cognitively normal (CN) matched subjects. The CSF markers and their relative ratios (total Tau/beta-amyloid, phosphorylated Tau/beta-amyloid) were compared across the three groups. Voxel-based morphometry (VBM) was performed to characterize the anatomical changes in bvFTD and AD patients compared to CN subjects. Grey matter density maps were obtained by automatic segmentation of 3.0 Tesla 3D T1-Weighted MR Images, and their correlation with CSF markers and relative ratios was investigated. Results demonstrated that, as compared to CN subjects, AD patients are characterised by higher CSF total Tau levels and lower beta-amyloid levels; however, beta-amyloid and relative ratios discriminated AD from bvFTD. In addition, AD and bvFTD patients showed different patterns of atrophy, with AD exhibiting more central (temporal areas) and bvFTD more anterior (frontal areas) atrophy. A correlation was found between grey matter density maps and CSF marker concentrations in the AD group, with total Tau and phosphorylated Tau levels showing a high association with low grey matter density in the left superior temporal gyrus. The study concludes that while bvFTD lacks a CSF marker profile, CSF beta-amyloid levels are useful for differentiating AD from bvFTD. Furthermore, MR structural imaging can contribute significantly to distinguishing between the two pathologies.

Nasal lymphatic obstruction of CSF drainage as a possible cause of Alzheimer's disease and dementia.

Alzheimer's disease, the most common form of dementia among older adults, slowly destroys memory and thinking skills. In recent years, scientists have made tremendous progress in understanding Alzheimer's disease, still, they do not yet fully understand what causes the disease. This article proposes a novel etiology for Alzheimer's disease. Our hypothesis developed from a review of nuclear medicine scans, in which the authors observed a significant increase in nasal turbinate vasodilation and blood pooling in patients with hypertension, sleep apnea, diabetes and/or obesity, all risk factors for Alzheimer's disease. The authors propose that nasal turbinate vasodilation and resultant blood pooling lead to the obstruction of normal nasal lymphatic clearance of cerebrospinal fluid and its waste products from the brain. The nasal turbinate vasodilation, due to increased parasympathetic activity, occurs alongside the well-established increased sympathetic activity of the cardiovascular system as seen in patients with hypertension. The increased parasympathetic activity is likely due to an autonomic imbalance secondary to the increase in worldwide consumption of highly processed food associated with dysregulation of the glucose regulatory system. The authors' hypothesis offers a novel mechanism and a new paradigm for the etiology of Alzheimer's disease and helps explain the rapid worldwide rise in the disease and other dementias which are expected to double in the next 20 years. This new paradigm provides compelling evidence for the modulation of the parasympathetic nervous system as a novel treatment strategy for Alzheimer's disease and other degenerative brain diseases, specifically targeting nasal turbinate lymphatic flow.

High-Risk Medications in Persons Living With Dementia

Individuals with Alzheimer disease (AD) and Alzheimer disease-related dementias (ADRD) may be at increased risk for adverse outcomes relating to inappropriate prescribing of certain high-risk medications, including antipsychotics, sedative-hypnotics, and strong anticholinergic agents. To evaluate the effect of a patient/caregiver and prescriber-mailed educational intervention on potentially inappropriate prescribing to patients with AD or ADRD. This prospective, open-label, pragmatic randomized clinical trial, embedded in 2 large national health plans, was conducted from April 2022 to June 2023. The trial included patients with AD or ADRD and use of any of 3 drug classes targeted for deprescribing (antipsychotics, sedative-hypnotics, or strong anticholinergics). Patients were randomized to 1 of 3 arms: (1) a mailing of educational materials specific to the medication targeted for deprescribing to both the patient and their prescribing clinician; (2) a mailing to the prescribing clinician only; or (3) a usual care arm. Analysis was performed using a modified intention-to-treat approach. The primary study outcome was the dispensing of the medication targeted for deprescribing during a 6-month study observation period. Secondary outcomes included changes in medication-specific mean daily dose and health service utilization. Among 12 787 patients included in the modified intention-to-treat analysis, 8742 (68.4%) were female, and the mean (SD) age was 77.3 (9.4) years. The cumulative incidence of being dispensed a medication targeted for deprescribing was 76.7% (95% CI, 75.4-78.0) in the patient and prescriber mailing group, 77.9% (95% CI, 76.5-79.1) in the prescriber mailing only group, and 77.5% (95% CI, 76.2-78.8) in the usual care group. Hazard ratios were 0.99 (95% CI, 0.94-1.04) for the patient and prescriber group and 1.00 (95% CI, 0.96-1.06) for the prescriber only group compared with the usual care group. There were no differences between the groups for secondary outcomes. These findings suggest medication-specific educational mailings targeting patients with AD or ADRD and their clinicians are not effective in reducing the use of high-risk medications. ClinicalTrials.gov Identifier: NCT05147428.

Blood‐based biomarkers of Alzheimer's disease: Standardization and comprehensiveness

AbstractPopulation aging is sweeping across the globe, resulting in a striking prevalence of Alzheimer's disease (AD) and dementia and a heavy economic burden. Given the time window of 10–20 years from pathological initiation to clinically detected cognitive impairment, early detection can significantly impact the prevention and control of AD. The invasiveness and high cost of cerebrospinal fluid biomarkers and positron emission tomography‐computed tomography imaging limit large‐scale disease screening. However, blood‐based biomarkers (BBMs) lack these disadvantages, shedding light on their usefulness in the large‐scale identification and prevention of AD. Prominent advancement has recently been made regarding BBMs of AD co‐pathology (amyloid β, tau protein, neurofilament light polypeptide, and glial fibrillary acidic protein) to improve their accuracy as clinical diagnostics of AD to a level comparable to that of canonical methods, facilitating the large‐scale clinical implementation of diagnostic tests with higher precision. To briefly summarize, the prospects of AD BBMs rely on standardization and comprehensiveness. Calibrating the sample collection procedure and clarifying the boundaries for indices and abnormalities are beneficial for constructing a canonical diagnostic assay. The comprehensive assembly of heterogeneous clinical evidence guarantees the accuracy of diagnosis and improves the workflow for early identification.

CMS121, a Novel Drug Candidate for the Treatment of Alzheimer's Disease and Age-Related Dementia.

Old age is the major risk factor for sporadic Alzheimer's disease (AD). However, old age-related changes in brain physiology have generally not been taken into consideration in developing drug candidates for the treatment of AD. This is at least partly because the role of these age-related processes in the development and progression of AD are still not well understood. Nevertheless, we and others have described an association between the oxytosis/ferroptosis non-apoptotic regulated cell death pathway and aging. Based on this association, we incorporated protection against this pathway as part of a cell-based phenotypic screening approach to identify novel drug candidates for the treatment of AD. Using this approach, we identified the fisetin derivative CMS121 as a potent neuroprotective molecule that is able to maintain cognitive function in multiple pre-clinical models of AD. Furthermore, we identified a key target of CMS121 as fatty acid synthase, a protein which had not been previously considered in the context of AD. Herein, we provide a comprehensive description of the development of CMS121, its preclinical activities, and the results of the toxicology testing that led to its IND approval.

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.

Illuminating the dark kinome: utilizing multiplex peptide activity arrays to functionally annotate understudied kinases

Protein kinases are critical components of a myriad biological processes and strongly associated with various diseases. While kinase research has been a point of focus in biomedical research for several decades, a large portion of the kinome is still considered understudied or “dark,” because prior research is targeted towards a subset of kinases with well-established roles in cellular processes. We present an empirical and in-silico hybrid workflow to extend the functional knowledge of understudied kinases. Utilizing multiplex peptide activity arrays and robust in-silico analyses, we extended the functional knowledge of five dark tyrosine kinases (AATK, EPHA6, INSRR, LTK, TNK1) and explored their roles in schizophrenia, Alzheimer’s dementia (AD), and major depressive disorder (MDD). Using this hybrid approach, we identified 195 novel kinase-substrate interactions with variable degrees of affinity and linked extended functional networks for these kinases to biological processes that are impaired in psychiatric and neurological disorders. Biochemical assays and mass spectrometry were used to confirm a putative substrate of EPHA6, an understudied dark tyrosine kinase. We examined the EPHA6 network and knowledgebase in schizophrenia using reporter peptides identified and validated from the multi-plex array with high affinity for phosphorylation by EPHA6. Identification and confirmation of putative substrates for understudied kinases provides a wealth of actionable information for the development of new drug treatments as well as exploration of the pathophysiology of disease states using signaling network approaches.

HIV-Associated Neurocognitive Disorder (HAND) and Alzheimer's Disease Pathogenesis: Future Directions for Diagnosis and Treatment.

HIV-associated neurocognitive disorder (HAND) and Alzheimer's disease (AD) are two neurocognitive disorders with overlapping clinical presentations and pathophysiology. The two have been thought to be two separate entities. However, the introduction and widespread use of antiretroviral therapy (ART) has altered the clinical manifestations of HAND, shifting from a pattern of subcortical dementia to one more akin to cortical dementia, resembling AD. Thus, the line between the two disease entities is not clear-cut. In this review, we discuss the concept of Alzheimer's disease-like dementia (ADLD) in HIV, which describes this phenomenon. While the mechanisms of HIV-associated ADLD remain to be elucidated, potential mechanisms include HIV-specific pathways, including epigenetic imprinting from initial viral infection, persistent and low viral load (which can only be detected by ultra-sensitive PCR), HIV-related inflammation, and putative pathways underlying traditional AD risk factors. Importantly, we have shown that HIV-specific microRNAs (miRs) encapsulated in extracellular vesicles (EV-miRs) play an important role in mediating the detrimental effects in the cardiovascular system. A useful preclinical model to study ADLD would be to expose AD mice to HIV-positive EVs to identify candidate EV-miRs that mediate the HIV-specific effects underlying ADLD. Characterization of the candidate EV-miRs may provide novel therapeutic armamentaria for ADLD.

Intervention Development for Tailored Education for Aging and Cognitive Health (TEACH) for Dementia Prevention in Midlife Adults: Protocol for a Randomized Controlled Trial.

A total of 12 modifiable risk factors account for 40% of dementia cases globally, yet population adherence to health behaviors associated with these factors is low. Midlife is a critical window for dementia prevention, as brain pathology often begins to accumulate years or decades before the onset of symptoms. Although multidomain behavioral interventions have been efficacious in reducing the risk of cognitive decline, adherence is low. Intrapersonal factors, such as health beliefs, are known mediators of the relationship between knowledge and health behavior. In keeping with stage I of the National Institutes of Health (NIH) Stage Model for Behavioral Intervention Development, this study will use mixed methods to (1) develop an enhanced health education intervention, including an explanatory method for communicating information about dementia risk and personal health beliefs, and (2) conduct a pilot randomized controlled trial (n=20 per intervention arm) over 8 weeks to assess the feasibility of delivering the enhanced intervention versus basic health education alone. Phase 1 will involve focus groups and individual qualitative interviews. Focus groups will be analyzed using (1) a descriptive framework matrix analysis and (2) interpretive data review by the research team. Individual qualitative interviews will be coded using applied thematic analysis using a phenomenographic approach. Phase 2 will involve a pilot randomized controlled trial. Proximal outcomes (measured at baseline, 4 weeks, and 8 weeks) include the perceived threat of Alzheimer disease, dementia awareness, and self-efficacy. This project was funded in August 2022. Data collection began in 2023 and is projected to be completed in 2025. Study findings will reveal the feasibility of delivering an 8-week multidomain health education intervention for primary prevention of dementia in midlife and will provide preliminary evidence of mechanisms of change. ClinicalTrials.gov NCT05599425; https://clinicaltrials.gov/study/NCT05599425. DERR1-10.2196/60395.

Plasma lipidomic signatures of dementia with Lewy bodies revealed by machine learning, and compared to Alzheimer's disease

BackgroundDementia with Lewy Bodies (DLB) is a complex neurodegenerative disorder that often overlaps clinically with Alzheimer’s disease (AD), presenting challenges in accurate diagnosis and underscoring the need for novel biomarkers. Lipidomic emerges as a promising avenue for uncovering disease-specific metabolic alterations and potential biomarkers, particularly as the lipidomics landscape of DLB has not been previously explored. We aim to identify potential diagnostic biomarkers and elucidate the disease's pathophysiological mechanisms.MethodsThis study conducted a lipidomic analysis of plasma samples from patients with DLB, AD, and healthy controls (HCs) at Xuanwu Hospital. Untargeted plasma lipidomic profiling was conducted via liquid chromatography coupled with mass spectrometry. Machine learning methods were employed to discern lipidomic signatures specific to DLB and to differentiate it from AD.ResultsThe study enrolled 159 participants, including 57 with AD, 48 with DLB, and 54 HCs. Significant differences in lipid profiles were observed between the DLB and HC groups, particularly in the classes of sphingolipids and phospholipids. A total of 55 differentially expressed lipid species were identified between DLB and HCs, and 17 between DLB and AD. Correlations were observed linking these lipidomic profiles to clinical parameters like Unified Parkinson’s Disease Rating Scale III (UPDRS III) and cognitive scores. Machine learning models demonstrated to be highly effective in distinguishing DLB from both HCs and AD, achieving substantial accuracy through the utilization of specific lipidomic signatures. These include PC(15:0_18:2), PC(15:0_20:5), and SPH(d16:0) for differentiation between DLB and HCs; and a panel includes 13 lipid molecules: four PCs, two PEs, three SPHs, two Cers, and two Hex1Cers for distinguishing DLB from AD.ConclusionsThis study presents a novel and comprehensive lipidomic profile of DLB, distinguishing it from AD and HCs. Predominantly, sphingolipids (e.g., ceramides and SPHs) and phospholipids (e.g., PE and PC) were the most dysregulated lipids in relation to DLB patients. The lipidomics panels identified through machine learning may serve as effective plasma biomarkers for diagnosing DLB and differentiating it from AD dementia.

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.

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.