Alzheimer's Disease Research Research Articles

Developing and applying potentially scalable recruitment strategies to accelerate ADRD research participation of Black adults.

More than 2 million older Americans from underrepresented racial and ethnic minority groups (URGs) have early-stage Alzheimer's disease and related dementias (ADRD). There are very few scalable recruitment strategies, particularly for Black older adults, to accelerate participation in ADRD research. The Indiana Alzheimer's Disease Research Center (IADRC) and its Community Advisory Board developed and implemented the innovative RAAISE-D Framework. This Framework informed the creation of community-first recruitment strategies designed to accelerate participation of Black older adults in ADRD research. Preliminary outcomes from its implementation included the doubling of Black adult enrollment (46, 13.4% to 101, 26.9%) from April 2020 to April 2024. Black adults were more likely to have normal cognition, be female, and ≤12 years of education than non-Hispanic White adults. The RAAISE-D Framework identified key concepts for URG focused recruitment strategies which successfully accelerated enrollment of Black adults in ADRD research and could be generalized to other URGs. HIGHLIGHTS: RAAISE-D Framework provides adaptable URG recruitment strategies. IADRC CAB-researcher partnership was the foundation of community-first methodology. RAAISE-D Framework doubled the Black enrollment in the IADRC in 4 years.

The analysis of whether CRISPR-Cas9 is the way forward for Alzheimers disease treatment

Alzheimer's disease (AD) is a progressive and irreversible neurological condition which according to WHO affects more than 55 million individuals globally and is the leading cause of dementia and thereby poses a significant burden on healthcare systems worldwide. AD progresses through stages of mild cognitive impairment to severe dementia and is characterised by the accumulation of extracellular amyloid-beta plaques and neurofibrillary tangles concentrated with tau proteins in neocortical structures and the temporal lobe. Gene-editing technology such as the most prevalent CRISPR-Cas9 provides prospects for the treatment of AD by enabling precise modifications of the genetic mutations associated with the disease. This review explores the potential of CRISPR-Cas9 to revolutionise treatment by targeting and rectifying mutated genes but also examines the current state of Alzheimers treatment. This paper examines recent advancements in preclinical studies and highlights the successes in reducing amyloid-beta plaques and tau neurofibrillary tangles, the pathological features of AD. By evaluating current CRISPR-Cas9 research and other treatments for AD, I aim to provide insight into its potential as a transformative gene therapy approach whilst evaluating its limitations.

The Aβ42:Aβ40 ratio modulates aggregation in beta-amyloid oligomers and drives metabolic changes and cellular dysfunction

The pathophysiological role of Aβ42 oligomers in the onset of Alzheimer’s disease (AD) is heavily disputed, pivoting research toward investigating mixed oligomers composed of Aβ42 and Aβ40, which is more abundant but less aggregation-prone. This study investigates Aβ42:Aβ40 oligomers in different ratios, examining their adverse effects on endothelial cells, neurons, astroglia, and microglia, as well as in a human blood–brain barrier (BBB) model. Combining label-free Raman microscopy with complementary imaging techniques and biochemical assays, we show the prominent impact of Aβ40 on Aβ42 fibrillation, suggesting an inhibitory effect on aggregation. Mixed oligomers, especially with low proportions of Aβ42, were equally detrimental as pure Aβ42 oligomers regarding cell viability, functionality, and metabolism. They also differentially affected lipid droplet metabolism in BBB-associated microglia, indicating distinct pathophysiological responses. Our findings demonstrate the overarching significance of the Aβ42:Aβ40 ratio in Aβ oligomers, challenging the traditional focus on Aβ42 in AD research.

Neuroimaging techniques, gene therapy, and gut microbiota: frontier advances and integrated applications in Alzheimer's Disease research.

Alzheimer's Disease (AD) is a neurodegenerative disorder marked by cognitive decline, for which effective treatments remain elusive due to complex pathogenesis. Recent advances in neuroimaging, gene therapy, and gut microbiota research offer new insights and potential intervention strategies. Neuroimaging enables early detection and staging of AD through visualization of biomarkers, aiding diagnosis and tracking of disease progression. Gene therapy presents a promising approach for modifying AD-related genetic expressions, targeting amyloid and tau pathology, and potentially repairing neuronal damage. Furthermore, emerging evidence suggests that the gut microbiota influences AD pathology through the gut-brain axis, impacting inflammation, immune response, and amyloid metabolism. However, each of these technologies faces significant challenges, including concerns about safety, efficacy, and ethical considerations. This article reviews the applications, advantages, and limitations of neuroimaging, gene therapy, and gut microbiota research in AD, with a particular focus on their combined potential for early diagnosis, mechanistic insights, and therapeutic interventions. We propose an integrated approach that leverages these tools to provide a multi-dimensional framework for advancing AD diagnosis, treatment, and prevention.

Recent Progress in Nanomedicine for the Diagnosis and Treatment of Alzheimer's Diseases.

Alzheimer's disease (AD) is a neurodegenerative disease that causes memory loss and progressive and permanent deterioration of cognitive function. The most challenging issue in combating AD is its complicated pathogenesis, which includes the deposition of amyloid β (Aβ) plaques, intracellular hyperphosphorylated tau protein, neurofibrillary tangles (NFT), etc. Despite rapid advancements in mechanistic research and drug development for AD, the currently developed drugs only improve cognitive ability and temporarily relieve symptoms but cannot prevent the development of AD. Moreover, the blood-brain barrier (BBB) creates a huge barrier to drug delivery in the brain. Therefore, effective diagnostic tools and treatments are urgently needed. In recent years, nanomedicine has provided opportunities to overcome the challenges and limitations associated with traditional diagnostics or treatments. Various types of nanoparticles (NPs) play an essential role in nanomedicine for the diagnosis and treatment of AD, acting as drug carriers to improve targeting and bioavailability across/bypass the BBB or acting as drugs directly on AD lesions. This review categorizes different types of NPs and summarizes their applications in nanomedicine for the diagnosis and treatment of AD. It also discusses the challenges associated with clinical applications and explores the latest developments and prospects of nanomedicine for AD.

Bibliometric analysis of rehabilitation in Alzheimer's disease (2000-2023): trends, hotspots and prospects.

Alzheimer's disease (AD) is a complex neurodegenerative disease that leads to insidious deterioration of brain functions and is considered the sixth leading cause of death in the world. Multiple studies have shown that rehabilitation therapy is becoming an important field of AD research in recent years. We opted for bibliometric analysis to comprehensively summarize the advancements in the study of AD rehabilitation treatment, aiming to provide researchers with current trends and future research directions. All articles and reviews pertaining to rehabilitation treatment in Alzheimer's disease from 2000 to 2023 were downloaded through Web of Science Core Collection. The results were subjected to bibliometric analysis using Microsoft Excel (2019 version), CiteSpace (6.3 R1 Advanced) and VOSviewer 1.6.20. Overall, 1,284 publications were included. The number of publications was increasing yearly. The United States has published the most publications. University of Toronto has published the most papers of all institutions. NEUROPSYCHOLOGICAL REHABILITATION and ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION were the journals with the most studies and the most commonly cited, respectively. Clare L is the author with the highest productivity and co-citation. After analysis, the most common keywords are mild cognitive impairment, cognitive, impairment memory and executive function indicates that cognitive impairment is the main focus of research. Transcranial magnetic stimulation, cognitive rehabilitation, and physical activity/exercise are the hotspots of research at the present stage and are likely to continue. Distinguishing non pharmacological treatments at different stages of development is a research hotspot in AD rehabilitation; Sports intervention, brain functional imaging techniques represented by brain functional connectivity, virtual reality, and quality of life are research directions that need attention.

Upregulated excitatory amino acid transporter 1 (EAAT1) expression in the human medial temporal lobe in Alzheimer's disease.

Alzheimer's disease (AD) is a growing health problem worldwide, particularly in the developed world due to an ageing population. Glutamate excitotoxicity plays a major role in the pathophysiology of AD, and glutamate re-uptake is controlled by excitatory amino acid transporters (EAATs). The EAAT2 isoform is the predominant transporter involved in glutamate reuptake, therefore EAAT1 has not been the focus of AD research. We investigated the layer-specific expression of EAAT1 in human medial temporal lobe regions such as the hippocampus, subiculum, entorhinal cortex and superior temporal gyrus, using fluorescent immunohistochemistry and laser scanning confocal microscopy in human post-mortem tissue. We observed low EAAT1 immunoreactivity in control cases, but upregulated labeling in AD across several brain regions of the medial temporal lobe. Significantly higher integrated density in AD cases was observed in the str. oriens and str. radiatum of the CA2 region, the str. pyramidale of CA3, and the str. moleculare and str. granulosum of the DG. Labeling of EAAT1 appeared astrocytic in nature, showing close association with astrocytic processes in AD cases. We also report that a higher EAAT1 density was positively correlated with the age of AD cases, but this relationship was not observed in control cases. Overall, our results indicate an upregulation of EAAT1 across several hippocampal subregions and layers in AD cases, indicating a potential physiological role for this transporter that needs further investigation.

The Consortium for Clarity in ADRD Research Through Imaging (CLARiTI).

The presence of multiple pathologies is the largest predictor of dementia. A major gap in the field is the in vivo detection of mixed pathologies and their antecedents. The Alzheimer's Disease Research Centers (ADRCs) are uniquely positioned to address this gap. The ADRCs longitudinally follow ≈ 17,000 participants, ranging from cognitively unimpaired to dementia, arising from Alzheimer's disease (AD) and related dementias (ADRD; e.g., AD, Lewy body disorders, vascular). Motivated by the Alzheimer's Disease Neuroimaging Initiative's (ADNI) impact, the ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) was formed. Leveraging existing ADRC infrastructure, CLARiTI will integrate standardized imaging and plasma collection to characterize mixed pathologies and use community-engaged research methods to ensure that≥ 25% of the sample is from underrepresented populations (e.g., ethnoculturally minoritized, low education). The resulting ADRD profiles, within a more diverse sample, will provide key resources for ADRCs and an unprecedented, more generalizable publicly available imaging-plasma dataset. HIGHLIGHTS: In vivo detection of mixed pathologies is critical for Alzheimer's disease and related dementias research. The Alzheimer's Disease Research Centers (ADRCs) are uniquely positioned to address gaps related to mixed pathologies. The ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) will enhance this national program by adding standardized imaging and plasma collection to existing ADRC infrastructure. This effort will provide key resources for ADRCs and an unprecedented publicly available imaging-plasma-neuropath dataset.

Exploring the feasibility of using mice as a substitute model for investigating microglia in aging and Alzheimer's disease though single cell analysis.

To guide animal experiments, we investigated the similarities and differences between humans and mice in aging and Alzheimer's disease (AD) at the single-nucleus RNA sequencing (snRNA-seq) or single-cell RNA sequencing (scRNA-seq) level. Microglia cells were extracted from dataset GSE198323 of human post-mortem hippocampus. The distributions and proportions of microglia subpopulation cell numbers related to AD or age were compared. This comparison was done between GSE198323 for humans and GSE127892 for mice, respectively. The Seurat R package and harmony R package were used for data analysis and batch effect correction. Differentially expressed genes (DEGs) were identified by FindMarkers function with MAST test. Comparative analyses were conducted on shared genes in DEGs associated with age and AD. The analyses were done between human and mouse using various bioinformatics techniques. The analysis of genes in DEGs related to age was conducted. Similarly, the analysis of genes in DEGs related to AD was performed. Cross-species analyses were conducted using orthologous genes. Comparative analyses of pseudotime between humans and mice were performed using Monocle2. (1) Similarities: The proportion of microglial subpopulation Cell_APOE/Apoe shows consistent trends, whether in AD or normal control (NC) groups in both humans and mice. The proportion of Cell_CX3CR1/Cx3cr1, representing homeostatic microglia, remains stable with age in NC groups across species. Tuberculosis and Fc gamma R-mediated phagocytosis pathways are shared in microglia responses to age and AD across species, respectively. (2) Differences: IL1RAPL1 and SPP1 as marker genes are more identifiable in human microglia compared to their mouse counterparts. Most genes of DEGs associated with age or AD exhibit different trends between humans and mice. Pseudotime analyses demonstrate varying cell density trends in microglial subpopulations, depending on age or AD across species. Mouse Apoe and Cell_Apoe maybe serve as proxies for studying human AD, while Cx3cr1 and Cell_Cx3cr1 are suitable for human aging studies. However, AD mouse models (App_NL_G_F) have limitations in studying human genes like IL1RAPL1 and SPP1 related to AD. Thus, mouse models cannot fully replace human samples for AD and aging research.

Construction of A Dataset for All Expressed Transcripts for Alzheimer’s Disease Research

Accurate identification and functional annotation of splicing isoforms and non-coding RNAs (lncRNAs), alongside full-length protein-encoding transcripts, are critical for understanding gene (mis)regulation and metabolic reprogramming in Alzheimer’s disease (AD). This study aims to provide a comprehensive and accurate transcriptome resource to improve existing AD transcript databases. Background/Objectives: Gene mis-regulation and metabolic reprogramming play a key role in AD, yet existing transcript databases lack accurate and comprehensive identification of splicing isoforms and lncRNAs. This study aims to generate a refined transcriptome dataset, expanding the understanding of AD onset and progression. Methods: Publicly available RNA-seq data from pre-AD and AD tissues were utilized. Advanced bioinformatics tools were applied to assemble and annotate full-length transcripts, including splicing isoforms and lncRNAs, with an emphasis on correcting errors and enhancing annotation accuracy. Results: A significantly improved transcriptome dataset was generated, which includes detailed annotations of splicing isoforms and lncRNAs. This dataset expands the scope of existing AD transcript databases and provides new insights into the molecular mechanisms underlying AD. The findings demonstrate that the refined dataset captures more relevant details about AD progression compared to publicly available data. Conclusions: The newly developed transcriptome resource and the associated analysis tools offer a valuable contribution to AD research, providing deeper insights into the disease's molecular mechanisms. This work supports future research into gene regulation and metabolic reprogramming in AD and serves as a foundation for exploring novel therapeutic targets.

Benchmarking of a multi-biomarker low-volume panel for Alzheimer's disease and related dementia research.

In the research setting, obtaining accurate established biomarker measurements and maximizing use of the precious samples is key. Accurate technologies are available for Alzheimer's disease (AD), but no platform can measure all the established and emerging biomarkers in one run. The NUcleic acid Linked Immuno-Sandwich Assay (NULISA) is a technology that requires 15µL of sample to measure more than 100 analytes. We compared AD-relevant biomarkers included in the NULISA against validated assays in cerebrospinal fluid (CSF) and plasma. CSF measures of amyloid beta 42/40, and phosphorylated tau (p-tau)217 are highly correlated when measured by immunoassay, mass spectrometry, or NULISA. In plasma, p-tau217 performance is similar to that reported with other technologies when predicting amyloidosis. Other biomarkers show a wide range of correlation values depending on the fluid and the platform. The NULISA multiplexed platform produces reliable results for established biomarkers in CSF that are useful in research settings, with the advantage of measuring additional biomarkers using minimal sample volume. We tested the novel technology NUcleic acid Linked Immuno-Sandwich Assay (NULISA) in the dementia research setting. NULISA multiplexed platform produces reliable results for established and emerging biomarkers using minimal sample volume. Cerebrospinal fluid measures of amyloid beta 42/40, and phosphorylated tau (p-tau)217 are highly correlated when measured by immunoassay, mass spectrometry, or NULISA. In plasma, p-tau217 performance is similar to that reported with other technologies when predicting amyloidosis. NULISA measures are useful in research settings, with the advantage of measuring additional biomarkers using minimal sample volume.

Biological validation of peak-width of skeletonized mean diffusivity as a VCID biomarker: The MarkVCID Consortium.

Peak-width of skeletonized mean diffusivity (PSMD), a neuroimaging marker of cerebral small vessel disease (SVD), has shown excellent instrumental properties. Here, we extend our work to perform a biological validation of PSMD. We included 396 participants from the Biomarkers for Vascular Contributions to Cognitive Impairment and Dementia (MarkVCID-1) Consortium and three replication samples (Cohorts for Heart and Aging Research in Genomic Epidemiology =6172, Rush University Medical Center =287, University of California Davis Alzheimer's Disease Research Center =567). PSMD was derived from diffusion tensor imaging using an automated algorithm. We related PSMD to a composite measure of general cognitive function using linear regression models adjusting for confounders. Higher PSMD was associated with lower general cognition in MarkVCID-1 independent of age, sex, education, and intracranial volume (Beta [95% confidence interval], -0.8 [-1.2, -0.4], P<0.001). These findings were replicated in independent samples. Furthermore, PSMD explained cognitive status above and beyond white matter hyperintensities. Our biological validation work supports the pursuit of larger clinical validation studies evaluating PSMD as a susceptibility/risk biomarker of small vessel disease contributing to cognitive impairment and dementia. Peak-width of skeletonized mean diffusivity (PSMD) is a novel small vessel disease neuroimaging biomarker. A prior instrumental validation study demonstrated that PSMD is a robust biomarker. This biological validation study shows that high PSMD relates to worse cognition. PSMD explains cognitive function above and beyond white matter hyperintensities. Future clinical validation will assess PSMD as a vascular contribution to cognitive impairment and dementia biomarker in clinical trials.

Unraveling the Mysteries of Alzheimer's Disease Using Artificial Intelligence.

Alzheimer's disease (AD) is a multidimensional, complex condition that affects individuals all over the world. Despite decades of experimental and clinical research that has revealed various processes, many concerns concerning the origin of Alzheimer's disease remain unresolved. Despite the notion that there isn't a complete set of jigsaw pieces, the growing number of public data-sharing initiatives that collect biological, clinical, and lifestyle data from those suffering from Alzheimer's disease has resulted in virtually endless volumes of knowledge about the disorder, far beyond what humans can comprehend. Furthermore, combining Big Data from multi- -omics research gives a chance to investigate the pathophysiological processes underlying the whole biological spectrum of Alzheimer's disease. To improve knowledge on the subject of Alzheimer's disease, Artificial Intelligence (AI) offers a wide variety of approaches for evaluating complex and significant data. The introduction of next-generation sequencing and microarray technologies has resulted in significant growth in genetic data research. When it comes to assessing such complex projects, AI technology beats conventional statistical techniques of data processing. This review focuses on current research and potential challenges for AI in Alzheimer's disease research. This article, in particular, examines how AI may assist healthcare practitioners with patient stratification, estimating an individual's chance of AD conversion, and diagnosing AD using computer-aided diagnostic methodologies. Ultimately, scientists want to develop individualized, efficient medicines.

Conversion to Alzheimer's disease dementia from normal cognition directly or with the intermediate mild cognitive impairment stage.

Progression to Alzheimer's disease (AD) dementia from normal cognition (NC) can follow different trajectories, with most progressing through a recognizable mild cognitive impairment stage (NC-MCI-AD), while some individuals transition quickly from NC to AD dementia (NC-AD). We compared demographic characteristics, health factors, and cognitive and functional assessments across three time points: the first NC visit, the last NC visit, and the first AD dementia visit. The NC-MCI-AD group showed greater impairment in cognitive and functional scores at AD dementia diagnosis, despite maintaining better cognitive function during the NC stage. Analysis of yearly changes revealed negligible differences during NC. However, the yearly change during the AD dementia stage suggested potentially more rapid functional decline in the NC-AD group. These findings highlight the heterogeneity in AD disease progression and emphasize the importance of considering diverse progression patterns in AD research and clinical practice. We investigated the disease progression difference between patients who converted to Alzheimer's disease (AD) dementia from normal cognition (NC) directly or through the mild cognitive impairment (MCI) stage. We found that the NC-MCI-AD group showed greater impairment in cognitive and functional scores at AD dementia diagnosis. We discovered that the NC-AD group had rapid functional decline once patients were confirmed with AD onset.

Visual read of [F-18]florquinitau PET that includes and extends beyond the mesial temporal lobe is associated with increased plasma pTau217 and cognitive decline in a cohort that is enriched with risk for Alzheimer's disease.

Patterns of signal from tau positron emission tomography (tau-PET) confined to the medial temporal lobe (MTL) or extended into the neocortex may be relevant for Alzheimer's disease (AD) research if they are linked to differential biomarker levels and cognitive decline. Visual assessment of Tau-PET [F-18]florquinitau (FQT) exams from 728 initially non-demented older adults yielded four uptake groups: tau-negative (T-), MTL-only (T+MTL), neocortex-only (T+Neo), or both (T+MTL&Neo). Mixed effects models assessed group differences in retrospective cognitive and plasma pTau217 trajectories. T+MTL&Neo was the most common T+ group (n=97; 93% A+) and exhibited the sharpest worsening in cognitive and pTau217 trajectories before tau PET. The T+MTL&Neo category represents an intermediate to advanced stage of AD preceded by rising ptau217 and progressive cognitive decline. The pTau217 finding suggests that A+, T+ in MTL or neocortex could represent early AD stages, with a higher likelihood of progressing to more advanced stages. Visual assessments of Tau-PET FQT revealed four distinct uptake groups: tau-negative (T-), MTL-only (T+MTL), neocortex-only (T+Neo), or both (T+MTL&Neo). Amyloid positive participants in the T+MTL and T+MTL&Neo categories showed a retrospectively faster decline in their cognitive trajectories, and a sharper increase in pTau217 levels in plasma, compared to T-. The T+MTL&Neo group displayed sharper trajectories compared with the other Tau positive groups in both their cognitive scores and pTau217 plasma levels. Our results suggest that participants with Tau present in both MTL and neocortex represent an intermediate to advanced stage of AD, whereas participants with signals confined to either MTL or neocortex could represent earlier AD stages.

Theory-Based Message Design for Recruitment of Underrepresented Racial/Ethnic Groups Into Alzheimer's-Focused Research Registries.

Alzheimer's disease (AD)-focused recruitment research registries can help identify eligible participants for AD studies, but registry participation is limited among racial and ethnic groups most at risk for AD. Using the Reasoned Action Approach (RAA), this study is part of a larger project to design theory-based persuasive recruitment messages that would encourage registry enrollment among underrepresented racial and ethnic groups. National survey data were collected in May/June 2021 from adults aged 50-80 years old living in the United States (n = 1,501) with oversamples of non-Hispanic Black (n = 334) and Hispanic (n = 309) adults for group comparisons. Regression analysis was used to estimate the relationship of the attitudes, norms, and perceived behavioral control on intention to sign up for an AD-focused research registry for each racial/ethnic and sex group (i.e., Black women, Black men, Hispanic female, Hispanic men, non-Hispanic White women, and non-Hispanic White men), followed by an audience segmentation analysis based on intender status. Across almost all target groups, attitudes were an important determinant of intention, and norms and capacity were secondary determinants for Black and Hispanic adults, respectively. There was considerable overlap in attitudinal beliefs most salient to the behavior which focused on benefits to society in some way, either generally (i.e., "helping others in the future"; "advancing science") or more specifically (i.e., "helping others like you"). Differences between groups were more apparent regarding norms and capacity. Targeted recruitment messages based on beliefs that were common across the groups could be an efficient way of recruiting people of color into AD research registries.

Exploring the Perspectives of Older Adults on a Digital Brain Health Platform Using Natural Language Processing: Cohort Study.

Although digital technology represents a growing field aiming to revolutionize early Alzheimer disease risk prediction and monitoring, the perspectives of older adults on an integrated digital brain health platform have not been investigated. This study aims to understand the perspectives of older adults on a digital brain health platform by conducting semistructured interviews and analyzing their transcriptions by natural language processing. The study included 28 participants from the Boston University Alzheimer's Disease Research Center, all of whom engaged with a digital brain health platform over an initial assessment period of 14 days. Semistructured interviews were conducted to collect data on participants' experiences with the digital brain health platform. The transcripts generated from these interviews were analyzed using natural language processing techniques. The frequency of positive and negative terms was evaluated through word count analysis. A sentiment analysis was used to measure the emotional tone and subjective perceptions of the participants toward the digital platform. Word count analysis revealed a generally positive sentiment toward the digital platform, with "like," "well," and "good" being the most frequently mentioned positive terms. However, terms such as "problem" and "hard" indicated certain challenges faced by participants. Sentiment analysis showed a slightly positive attitude with a median polarity score of 0.13 (IQR 0.08-0.15), ranging from -1 (completely negative) to 1 (completely positive), and a median subjectivity score of 0.51 (IQR 0.47-0.53), ranging from 0 (completely objective) to 1 (completely subjective). These results suggested an overall positive attitude among the study cohort. The study highlights the importance of understanding older adults' attitudes toward digital health platforms amid the comprehensive evolution of the digitalization era. Future research should focus on refining digital solutions to meet the specific needs of older adults, fostering a more personalized approach to brain health.

Predictors of Decisional Capacity in Alzheimer's Disease Biomarker Test Candidates.

Deciding to learn one's Alzheimer's disease (AD) biomarker status is a high-stakes endeavor that requires comprehending and deliberating about complex and nuanced information. Assessing capacity to consent to AD biomarker testing and disclosure is further complicated when candidates have cognitive impairment and present with family care partners. The objective of this analysis was to identify predictors of decisional capacity for an amyloid Positron Emission Tomography (PET) disclosure study among persons with mild cognitive impairment (MCI) and their family care partners. This analysis used an analytical correlational design, using baseline data from a randomized controlled trial of amyloid PET results disclosure. Simple linear regression was used to examine predictors of decisional capacity. Focusing on persons with MCI, the predictor variables of interest were sociodemographic characteristics, level of knowledge of MCI/AD, global cognition, and neuropsychological tests of language and executive functioning. Dyadic analyses were conducted with data from 82 dyads of persons with MCI and care providers using the Actor Partner Interdependence Model to assess for presence of actor and partner effects among key variables. Capacity to consent scores demonstrated sufficient capacity for all participants to consent to the study. For persons with MCI, lower age, higher mental status scores, MCI/AD knowledge scores, and better performance on measures of language and executive functioning were predictors of decisional capacity. The model revealed positive actor relations for MCI/AD knowledge with decisional capacity for both persons with MCI and family care partners and negative partner relationships for family care partners MCI/AD knowledge with the decisional capacity of persons with MCI. Assessment of decisional capacity is imperative when considering participation in AD research, including studies with high-stakes procedures like biomarker results disclosure. Our findings highlight that not only do individual characteristics put persons with MCI at risk for lower decisional capacity, but dyadic effects from family care partners may also be present.

EEG and brain network analysis in the early diagnosis of Alzheimer's disease

Abstract. The early diagnosis of Alzheimers Disease (AD) is critical for effective intervention and improved patient outcomes. This paper explores the role of electroencephalography (EEG) and brain network analysis in the early detection of AD, with a particular focus on neurofeedback training as a therapeutic intervention. We review the characteristic changes in EEG signals, such as decreased alpha power and increased theta power, and their implications for identifying early cognitive decline. Functional connectivity analysis using coherence and phase synchronization methods reveals disruptions in key brain networks, providing valuable biomarkers for early AD. We also discuss quantitative EEG (qEEG) techniques, including power spectral density and fractal dimension, which enhance diagnostic accuracy. Additionally, mathematical models like the Kuramoto model offer insights into network dynamics and predict disease progression. Integrating EEG with other diagnostic tools, such as MRI and PET, creates a comprehensive multimodal approach. This integrative framework enhances early diagnosis and informs personalized treatment strategies, representing a significant advancement in the field of AD research and clinical practice.

Gaps in biomedical research in frontotemporal dementia: A call for diversity and disparities focused research.

Frontotemporal dementia (FTD) is one of the leading causes of young-onset dementia before age 65, typically manifesting as abnormal behavior (in behavioral variant FTD) or language impairment (in primary progressive aphasia). Although FTD affects all populations across the globe, knowledge regarding the pathophysiology and genetics derives primarily from studies conducted in North America and Western Europe. Globally, biomedical research for FTD is hindered by variable access to diagnosis, discussed in this group's earlier article, and by reduced access to expertise, funding, and infrastructure. This perspective paper was produced by two professional interest areas of the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART) and discusses the field's current status on the cross-cultural aspects of basic and translational research in FTD (including that focused on epidemiology, genetics, biomarkers, and treatment). It subsequently provides a summary of gaps and needs to address the disparities and advance global FTD biomedical research.