bluuebunny/crossref_metadata_2025 huggingface dataset:
Does cultural and linguistic diversity impact timeliness of dementia diagnosis? Findings from the Australian Dementia Network Registry
Authors: Ahern Susannah , Lin Xiaoping , Honardoost Mohammad Amin , Wallis Kasey , Brodaty Henry , Ward Stephanie Alison ,   ADNetT Registry Steering Committee
Published: January 2025

Background

The Australian Dementia Network (ADNeT) is a collaboration of dementia researchers and clinicians established in 2018. It includes a clinical quality registry that reports on diagnosis and early management of people with dementia or Mild Cognitive Impairment (MCI) across public, private, metropolitan and rural settings. Australia is multicultural and the registry collects information regarding cultural and linguistic diversity (CALD). The aim of this study was to determine if CALD status was associated with time to dementia diagnosis.

Methods

ADNeT registry data from March 2020 – Sept 2023 were analysed. Primary endpoint was time to diagnosis for three groups based on CALD status and preferred spoken language: non‐CALD; English‐speaking CALD; and non‐English‐speaking CALD. Descriptive statistics, univariate and multivariate regression analysis were undertaken for five outcome measures: (1) time from referral to diagnosis (2) time from referral to first appointment, (3) time from first appointment to diagnosis (4) age at referral, and (5) diagnostic outcome (dementia vs MCI).

Results

Of 3,634 participants, 2,817 (78%) were non‐CALD; 451 (12%) were English‐speaking CALD and 366 (10%) were non‐English speaking CALD. Overall median times were 131 days from referral to diagnosis, 75 days from referral to first appointment, and 28 days from first appointment to diagnosis. Both English and non‐English‐speaking CALD background were associated with longer time from referral to diagnosis (154/158 days vs 123 days for non‐CALD), and longer time from first appointment to diagnosis (46/70 days vs 18 days) (p<0.001), remaining significant after adjusting for demographic/health factors. There was no association between CALD and time from referral to first appointment. Non‐English‐speaking CALD background was also associated with older age at referral (80 years vs 78/77 years) and a higher likelihood of dementia diagnosis (75% vs 63/65%), although these differences disappeared after adjustment.

Conclusion

This large national study shows that cultural and linguistic diversity is associated with delayed diagnosis of dementia, with further research required regarding underlying causes. This has important implications for equity of care as it may preclude people from CALD backgrounds accessing novel disease modifying treatments. People from CALD backgrounds may specifically benefit from dementia diagnostic biomarkers to facilitate earlier diagnosis.
FTD Disorders Registry (FTDDR) Participants: Understanding Social Risk Factors in Research Participation
Authors: Reddy Sweatha , Reinecker Robert , Milliard Carrie , Heuer Hilary W. , Forsberg Leah K. , Boxer Adam L. , Rosen Howard J. , Boeve Brad F.
Published: January 2025

Background

Frontotemporal degeneration (FTD) is an umbrella term encompassing a range of rare neurodegenerative disorders that cause progressive changes to behavior, personality, language, and movement with onset typically before age 60. Currently, several potential FTD therapies are under investigation, underscoring the need for increased diversity in research participation. Two validated scores describe socioeconomic and geographic factors that may impact willingness to participate in research. The Area Deprivation Index (ADI) assesses socioeconomic disadvantages and captures social determinants of health. The Rural‐Urban Commuting Area Codes (RUCA) measures population density, urbanization, and daily commuting to determine individuals living in urban versus rural communities. FTDDR is a compliant, web‐based registry to facilitate FTD research. ADI and RUCA analyses of FTDDR participants can provide insight into current participants’ demographics and areas for recruitment prioritization.

Method

FTDDR participants living in the United States were divided into two cohorts: (1‐FTDDR) enrolled in FTDDR only and (2‐ALLFTD) enrolled in FTDDR through ALLFTD, a longitudinal natural history study. ADI was calculated from self‐reported zip codes for 1392 participants in cohort 1 and 983 participants in cohort 2. RUCA scores were generated using self‐reported zip codes for 4565 participants from cohort 1 and 1174 participants from cohort 2.

Result

ADI analysis showed a low percentage (6.9% FTDDR, 5.7% ALLFTD) of participants lived in highly disadvantageous communities. 40.5% of FTDDR cohort and 49.3% of ALLFTD cohort lived in communities considered “low disadvantage,” suggesting they may have fewer socioeconomic risk factors or impediments to research participation. Most participants in both cohorts lived in urban areas (87.9% FTDDR, 85.8% ALLFD); only 3.2% of both cohorts lived in rural communities.

Conclusion

Socioeconomic and geographic factors may play a role in accurate diagnosis, access to medical centers, and ability to participate in research. ADI and RUCA analyses indicate that the majority of FTDDR participants, including those actively enrolled in FTD research, live in less disadvantageous neighborhoods and in urban areas, highlighting the need for outreach to more disadvantaged and rural communities. FTDDR prioritizing an engagement strategy to identify, recruit, and retain diverse individuals willing to participate in research could accelerate advancements in FTD research.
Koreans Invested in Making Caregivers Health Important (KIMCHI): A National Community‐based Project to Enhance Knowledge, Attitudes, and Behaviors about Dementia for the Korean American Community
Authors: Nam Bora , Huang Daren , Yun Stacy W , Shin Hye‐Won , Lee Eun Jeong , Phan Nicole , Park Van Ta
Published: January 2025

Background

The Korean American older adult population is rapidly growing, with most being foreign‐born individuals with limited English proficiency, and who experience significant health disparities. The Koreans Invested in Making Caregivers Health Important (KIMCHI) project is a national, culturally tailored, bilingual (English/Korean) initiative focused on community‐based research dissemination to empower Korean Americans with insights into healthy cognitive aging and dementia caregiving.

Method

From the community partnership with Somang Society and AARIN, a total of 211 participants, predominantly older adults (aged 24‐ 90 years; M = 69; SD = 12.1), mostly female (70.1%), and foreign‐born (96.2%) with limited English proficiency (61.6%), engaged in the project. Paired‐sample t‐tests were employed to assess mean (M) changes in participants’ knowledge, attitudes, and behaviors regarding Alzheimer’s disease and related dementias (ADRD) pre‐ and post‐test (before and after participating in the KIMCHI presentations).

Result

From the community partnership with Somang Society and AARIN, a total of 211 participants, Significant improvements were observed in post‐test ADRD knowledge (M = 11.51), attitudes (M = 7.13), and behaviors (M = 8.88) compared to pre‐test scores (M = 10.34, M = 6.33, M = 8.11, respectively), t(210) = 1.17, p<.05, t(210) = 0.8, p<.05, and t(210) = 0.76, p<.05, respectively. Moreover, 93.8% of participants expressed satisfaction about KIMCHI, 89.4% learned something new about ADRD, 93.8% found the presentations culturally relevant and applicable, and 89% expressed interest to learn more about ADRD training.redominantly older adults (aged 24‐ 90 years; M = 69; SD = 12.1), mostly female (70.1%), and foreign‐born (96.2%) with limited English proficiency (61.6%), engaged in the project. Paired‐sample t‐tests were employed to assess mean (M) changes in participants’ knowledge, attitudes, and behaviors regarding Alzheimer’s disease and related dementias (ADRD) pre‐ and post‐test (before and after participating in the KIMCHI presentations).

Conclusion

Findings indicate that a community‐based research dissemination project (i.e., KIMCHI) can positively influence ADRD knowledge, attitudes, behaviors, and satisfaction among Korean Americans. Future studies should explore additional culturally tailored interventions, including real‐life case examples, to enhance health‐related outcomes and ensure greater representation in research studies for the Korean American community.
Delivery of incretin receptor agonists to the brain
Authors: Rhea Elizabeth
Published: January 2025

Background

Incretin receptor agonists (IRAs) are synthetic peptides that have beneficial effects within the brain. We investigated IRA brain uptake following two routes of delivery: across the blood‐brain barrier (BBB) and following intranasal (IN) delivery.

Method

Radiolabeled IRAs were delivered intravenously or intranasally into CD‐1 mice and uptake by or distribution throughout the brain was assessed. Additionally, distribution following IN delivery was assessed in APP/PS1 and wild‐type male and female mice.

Result

We identified many, but not all, IRAs are able to cross the BBB, and some have faster transport rates than others. We also identified IRAs can be delivered intranasally and that distribution does not majorly differ in a mouse model of Alzheimer’s disease (AD).

Conclusion

The ability for IRAs to access the brain directly shows promise for AD therapeutics and will advance the design of future therapeutics. The IRAs that have a greater brain uptake should be taken into consideration for testing as AD as they would have the ability to act quickly and directly within the brain.
The use of a testimonial video featuring diverse ADRC participants to change research attitudes in the elderly community
Authors: Sewell Margaret , Neugroschl Judith A. , Umpierre Mari , Chin Shehan , Nunez Jade , Martinez Scarline , Fernandez Paulette , Inoa Vielka , Sano Mary
Published: January 2025

Background

Black, Latinx, and Asian community elders remain underrepresented in dementia research. This study explored whether a video created to promote diversity in research by featuring underrepresented ADRC participants would change attitudes about research generally (e.g., that it is safe, that it will find cures), as well as change attitudes about participation in specific types of research (e.g., involving imaging or blood draws).

Method

We created a testimonial format 4‐minute video featuring three ADRC participants (Chinese, Black, Hispanic). They discussed the importance of diversity in research and the vignettes illustrated participation in blood draws, imaging, and cognitive testing. Attitudes were measured by the 7‐item Research Attitude Questionnaire, before and after watching the video. Additionally, four Likert‐style questions were asked regarding the importance of diversity participation in research and willingness to participate in studies involving imaging, blood draws, or cognitive testing.

Result

The video was presented at 6 senior centers in NYC with 91 attendees (age 52‐90). 79% female, 59% Black, 39% Hispanic/Latino, and 8% other. Regarding education, 30% < high school, 35% high school graduates, and 35% ≥ some college. Spanish was the primary language for 44%. The RAQ item “Participating in medical research is generally safe” had the greatest pre/post video delta, with a 14% increase (62% to 76%) endorsing Agree/Strongly Agree. Other RAQ items that were relevant to the video vignettes (e.g., “We all have some responsibility to help others by volunteering in research” had a more modest (5% to 7%) increase in Agree/Strongly Agree. Concerning the additional questions, the greatest increases were seen concerning the need for diversity (66% to 81% Agree/Strongly Agree), and willingness to consider imaging studies (52% to 62%). The greatest trepidation was regarding participating in studies with blood draws (46% initially endorsed Agree/Strongly Agree) which only increased to 49% after the video.

Conclusion

We demonstrate here how testimonial videos with peers may impact interest in research. Future work will explore how improved attitudes toward research may increase research enrollment.
Polytreatment in a very old patient. What’s better for safe prescribing?
Authors: Gareri Pietro , Gareri Ilaria , Covello Luciana Barbara , Ammendola Manuela
Published: January 2025

Background

Prescription for inappropriate drugs can be dangerous to very old people, due to the increased risk of adverse drug reactions.

Case report

We report the consequences of inappropriate prescriptions in a 99‐year‐old woman. She had a clinical history of vascular dementia, diabetes, hypothyroidism, heart failure, osteoarthritis, chronic renal failure, and hypoacusia, and was admitted to our attention for asthenia and loss of appetite. She was hospitalized two months before for third‐degree atrioventricular block, and underwent pacemaker implantation. She had a moderate cognitive impairment, and functional dependence. Pharmacological history was collected by nurses through a video‐call and revealed that she was taking bisoprolol, furosemide, acetylsalicylic acid, L‐thyroxine, valsartan, gliclazide, folate, and digoxin (0.0625 mg/day). She had been suffering from nausea and loss of appetite for one month. On geriatric consultation, she had a heart frequency of 60 bpm. Vesicular murmur was normal, the abdomen was soft on palpation, and peripheral pulses were normal. Blood pressure was 130/80 mm Hg. Electrocardiography confirmed the presence of pacemaker rhythm. Echocardiography documented a mildly depressed ejection fraction of 45%. In the suspicion of digoxin intoxication, digoxin was soon interrupted. She started citicoline 1 g intramuscularly for the first ten days and then 1 g orally. Blood exams showed renal failure (ClCR 21.4 ml/min/m2), mild anemia, digoxin 2.7 ng/ml. A couple of days after digoxin interruption she started to feed again and felt much better.

Conclusions

The present case report shows the need for wise prescriptions in very old people. Drug‐induced symptoms are the second most frequent medical problem that geriatricians encounter and collaboration with nurses can help to optimize pharmacotherapy by deprescribing inappropriate agents.
Utilizing 7 Tesla QSM to evaluate the relationship between cerebral small veins and microbleeds in Alzheimer’s Disease
Authors: Ashouri Laya
Published: January 2025

Background

Cerebral microbleeds (CMBs) are small hypointense round lesions that indicate leakage of blood products from cerebral vessels damaged by β‐amyloid‐40 (Aβ) and typically are detected by T2*‐weighted and susceptibility weighted imaging (SWI) on MRI. They are indicators of cerebral small vessel diseases, especially cerebral amyloid angiopathy (CAA), affecting cortical small arteries. Quantitative susceptibility mapping (QSM) is an advanced MRI imaging technique used to quantify the magnetic susceptibility of tissues in the human body. In this study, we utilized the QSM technique to analyze venous structures at ultra‐high resolution in a cohort of patients with AD and age‐matched control subjects using 7T MRI. Our aim is to evaluate the feasibility of using ultra‐high resolution QSM at 7T MRI to find a link between small veins and CMBs in individuals with AD.

Method

In‐vivo human imaging was performed using a 7T MRI scanner and were analyzed by two neuroradiologists. CMBs were defined as hyperintense, round lesions in the QSM images. For verification, their appearance was matched on the SWI images, where CMBs are hypointense and associated with. CMBs with an immediate adjacent to a vein were assessed in the QSM images. They were defined as CMBs with small veins connection.

Result

This high‐resolution 7T neuroimaging study investigated whether a spatial relationship between small veins and CMBs could be detected in a cohort of AD patients. QSM enabled depiction of cerebral CMBs with a direct connection to a vein and their localization. Our data support the notion that CMBs relate anatomically to veins. Understanding the role of vein pathology in CAA and its role in neurodegenerative pathologies might open novel insights in the pathophysiology of AD.

Conclusion

A key strength of our study lies in the utilization of high‐resolution QSM at 7T MRI. High‐resolution MRI enhances the visibility of small structures, and when maintained at the same resolution, imaging at a higher field MRI increases the signal‐to‐noise ratio. QSM elevates CMB detection sensitivity while facilitating precise visualization of the brain's venous vasculature. Notably, the postprocessing algorithm ensures a high level of specificity for venous blood susceptibilities, minimizing the likelihood of measuring arterioles or slow‐flow small arteries.
Trajectories in Care Among Veterans with Alzheimer’s Disease in the United States
Authors: Palacios Natalia , Xia Weiming , Reisman Joel , Wang Ying , Morin Peter J , Berlowitz Dan , Monfared Amir Abbas Tahami , Zhang Quanwu , Aguilar Byron J. , Zhang Raymond
Published: January 2025

Objective

Few studies have investigated trajectories in care among patients with Alzheimer’s Disease (AD), especially Veterans who experience a unique set of AD risk factors and challenges in access to AD immunotherapy in the Veterans Affairs Healthcare System (VAHS) of the United States.

Methods

We analyzed trajectories in care based on electronic health records (EHR) among Veterans who were assessed for AD based on ICD‐10 coding within the VAHS between Oct 2015 and Jan 2024. Among Veterans with an ICD‐10 code for AD in the VAHS, we examined frequency distributions of clinical visits by physician specialty (primary care, neurologist, geriatrician, psychiatrist, and other specialties) where the initial AD ICD‐10 coding was recorded. Transition to the specialist care or visit to a dementia clinic was calculated during the year after the initial ICD‐10 coding for AD from the initial visit to a primary care physician. Distribution of the transition to specialist care was examined across non‐Hispanic Black, non‐Hispanic White, Hispanic, and other race/ethnicity groups.

Results

A total of 110,836 Veterans were identified by ≥1 ICD‐10 code for AD with a subsample of 71,666 seen by a clinician with known specialty. Mean age was 80.7 years, 97.3% were male, 11.6% non‐Hispanic Black, 8.2% Hispanic, and 70.7% non‐Hispanic White. More than 41% of the initial AD coding was assigned in the primary care physician, 9% in neurologist, 8% geriatrician, and 12% psychiatrist. In the subsample of 71,666 Veterans within one year, 26.4% had a subsequent visit to a neurologist office or Dementia clinic. Among Veterans initially seen in primary care for AD, 31.7% non‐Hispanic Black (p<0.01) and 25.3% Hispanic (p = 0.22), relative to 23.9% non‐Hispanic White, were subsequently visited a neurologist or a dementia clinic.

Conclusions

Over 40% more Veterans were initially evaluated for AD by a primary care clinician than by an AD specialist including neurologists, psychiatrists, and geriatricians. Non‐Hispanic Black Veterans were more likely to follow up with a neurologist or at a dementia clinic compared to Hispanic or non‐Hispanic White Veterans during the year after the initial AD assessment. The findings suggest a need for further enhancement of AD care trajectory.
LGI‐1 Encephalitis: A Comprehensive Multidisciplinary Paradigm for Diagnosis and Management
Authors: Tavakoli Emytis , Fishman Keera , Elmi Sarah
Published: January 2025

Introduction

Leucine‐rich glioma‐inactivated 1 (LGI‐1) antibody encephalitis is a rare subtype of autoimmune limb encephalitis (ALE), which is marked by rapid neuropsychiatric decline. This report details a comprehensive approach to its diagnosis and management.

Assessment

In this case, a 68‐year‐old man presented with aggressive behaviors, cognitive decline, and seizure‐like episodes. Initial assessments suggested major neurocognitive disorder, with MMSE and MOCA scores of 20 and 17, respectively, indicating cognitive impairment. EEG confirmed episodes of facio‐brachial dystonic seizures. Further evaluation revealed hyponatremia, temporal lobe atrophy on MRI, and LGI1‐antibodies in the CSF.

Treatment

Initial treatments included steroids and IVIG, which did not result in significant improvement. However, after receiving two Rituximab trials, improvements in cognitive and behavioural outcomes were observed. Cognitive predictors of poor outcomes included older age, non‐response to initial therapies, and clinical relapses.

Discussion

This case underscores the complex presentation of LGI‐1 encephalitis, emphasizing the importance of thorough diagnostic evaluations and a multimodal treatment approach. The patient’s cognitive and behavioral improvements post‐treatment highlight the significance of timely and targeted interventions in managing this challenging autoimmune encephalitis. Long‐term follow‐up revealed sustained improvements, reinforcing the potential efficacy of a multidisciplinary treatment strategy.
Advanced circadian rhythms in older adults are associated with higher amyloid‐β and tau PET burden and poorer short‐term memory
Authors: Eckhardt Joanna L , Isenberg A. Lisette , Stradford Joy , Aslanyan Vahan , Fenton Laura E. , Monreal Teresa , Pa Judy
Published: January 2025

Background

Several studies link circadian rhythm disturbances to Alzheimer's disease. However, little is known about circadian rhythm involvement with Alzheimer’s pathology in early stages of the disease. The current study investigates the relationship between circadian rhythms, Aβ and tau PET, and short‐term memory, and explores how circadian rhythms vary between age, sex, and APOE4 status.

Method

This research utilizes baseline data from the Lifestyle Enriching Activities for Research in Neuroscience Intervention Trial. Sixty‐eight older adults ages 55‐80 experiencing early cognitive changes wore a GENEActiv accelerometer for ∼30 days. Accelerometer data was processed using the R package GGIR (v3.0‐1), and circadian rhythm measures were extracted using nparACT (v0.8) and ActCR (v0.3.0). Circadian rhythm variables include interdaily stability (IS) (rhythm synchronization), intradaily variability (IV) (fragmentation), and acrotime (peak activity time). Up‐MESOR and Down‐MESOR signify timing of activity increasing above or below mean activity level, respectively, with lower values indicative of advanced (earlier) circadian phase. Participant Aβ and tau SUVr were measured using PET imaging. Short‐term memory is measured with the California Verbal Learning Test‐II Short Delay Free Recall Total Score. Linear regression models were conducted to test associations between circadian rhythms, Aβ, tau, and short‐term memory, and were adjusted for age, sex, APOE4 status, and years of education. Pearson’s correlation was conducted between circadian rhythms and age. Wilcoxon Rank Sum tests were used to assess differences in circadian rhythms between sex and APOE4 status.

Result

Participant demographics are summarized in Table 1. Regression results are summarized in Table 2. Acrotime and Down‐MESOR were associated with Aβ Composite. Acrotime and Up‐MESOR were associated with tau across multiple Braak regions of interest. Notably, IV was significantly associated with Braak stage III/IV. Both acrotime and Up‐MESOR were associated with Short Delay Free Recall Score. Acrotime (r =‐0.25, p=0.04) and Down‐MESOR (r=‐0.26, p=0.04) were moderately correlated with age. IS (W=368, p=0.03) and IV (W=694, p=0.05) differed by sex, and Up‐MESOR differed by APOE4 status (W=599, p=0.03) (Figure 1).

Conclusion

Participants with advanced (earlier) circadian rhythms demonstrate higher Aβ and tau PET burden and poorer short‐term memory. Circadian rhythm measures vary with age, sex, and APOE4 status.
Sleep Encephalography‐Based Brain Age Index as a Potential Biomarker for Incident Cognitive Impairment in Community‐Dwelling Older Men
Authors: Sun Haoqi , Milton Sasha , Thomas Robert J , Westover M. Brandon , Stone Katie L , Yaffe Kristine , Leng Yue
Published: January 2025

Background

Individuals with dementia frequently exhibit disturbed sleep electroencephalography (EEG) microstructures, including spindles and slow oscillations. We have previously developed a sleep EEG‐based brain age index (BAI), which integrates multiple sleep EEG microstructures and has been associated with prevalent dementia in clinical populations. Here, we aim to determine if BAI is associated with incident cognitive impairment (CI) in a community population of older men, and its discrimination capability as a digital biomarker.

Method

This longitudinal study included men older than 65 years who completed overnight polysomnography (PSG) between 2003 and 2005 and had incident CI followed until 2016, as part of the Osteoporotic Fractures in Men study (MrOS). BAI was based on a model trained on participants without neurological or psychiatric diseases. Incident CI was defined as self‐reported dementia, dementia medication use, Modified Mini‐Mental State Examination (3MS)<80, or a decline in 3MS from baseline to any following visit ≥1.5 standard deviations below the mean. We fit logistic regression to assess the associations between quintiles of BAI and incident CI.

Result

There were 2,609 men without dementia at baseline (mean age [sd] = 76.0 [5.3] years), of whom 416 developed incident CI during a maximum follow‐up of 11 years. After adjustment for demographics, education, baseline cognition, medication use, comorbidities, and lifestyle, the highest quintile of BAI (BAI>+2.3 years) was associated with incident CI with an odds ratio of 1.66 (95% confidence interval 1.17–2.38, p=0.0051) when compared to the lowest quintile (BAI<‐6.7 years). Other quintiles were not significantly associated with incident CI. BAI showed a cross‐validated accuracy of 60%, sensitivity of 66%, specificity of 55%, and area under the receiver operative curve of 61% for incident CI. When looking at the brain age itself, the brain age performed better than chronological age in predicting incident CI, since the model with brain age achieved lower (i.e., better) Bayesian Information Criterion than another model with age, together with other covariates.

Conclusion

Higher BAI was associated with incident CI in community‐dwelling older men. These results highlight the potential of BAI as a digital biomarker of future CI in older men.
Psychosocial Well‐Being Factors and Adherence as Predictors of a Working Memory Game’s Outcomes in Older Adults
Authors: Andreo Micaela Noelle , Sierra Francisco J , Skolasinska Paulina , Smith Evan T. , Basak Chandramallika
Published: January 2025

Background

Preventative interventions for cognitive decline are crucial as the number of individuals with Dementia is projected to reach 78 million by 2030. Cognitive Training can be a promising solution for the maintenance and improvement of neurocognitive functioning and has the potential to delay the onset of AD. This study utilizes a home‐based gamified cognitive training, the Bird Watch Game Unity (BWGU), where participants engage aspects of cognitive control to focus on predictable and unpredictable probe‐cue sequences of novel visual stimuli – pictures of birds. This game trains skills such as updating, focus switching, and working memory capacity.

Method

Fifty‐six healthy older adults (>65 years) played the BWGU for approximately 15.25 hours on average. Adherence is defined as frequency (the average lagged days between sessions) and duration (total hours trained). This study’s purpose is to determine if fluctuations in daily well‐being measures such as sleep, mood, stress, wellness, and busy‐ness influence a participant’s adherence. Predictive relationships between an individual’s psychosocial well‐being to adherence and their game learning outcomes will also be discussed. Autoregressive Integrated Moving Average (ARIMA) models are used to forecast a participant’s training adherence from day‐to‐day, using their previous days’ relationship with well‐being measures. Secondly, the well‐being and adherence measures are used to predict changes in cognition between pre‐ and post‐training visits at the group level via multiple regression. The cognitive battery being compared at pre‐ and post‐ include RAVLT, RBMT, WAIS‐V, and DSST. Lastly, we will explore the relationship between adherence to the BWGU and well‐being measures to determine if the BWGU has a significant impact on older adult’s well‐being, in addition to the cognitive benefits.

Result

For approximately 30% of participants, the ARIMA models of well‐being and adherence predicted daily average scores. For some individuals, well‐being measures were sufficient alone, and for others the addition of adherence improved their model’s prediction of game outcomes.

Conclusion

Overall, these findings provide valuable insight into psychosocial factors of learning and adherence to cognitive training, which in turn would help determine both who would benefit the most from training, and the necessary changes to improve future cognitive training interventions.
Exploring the Role of Fatty Acid Supplementation in Persons with Alzheimer’s Disease: A Scoping Review
Authors: Basra Mahi , Patel Saajan , Shah Kriya , Caballero Joshua
Published: January 2025

Background

Lipids are key modulators in the pathogenesis of Alzheimer’s disease (AD). Dysregulation of lipid homeostasis may disrupt the blood brain barrier, alter myelination, disturb cellular signaling and cause abnormal processing of the amyloid precursor protein. The purpose of this scoping review was to evaluate fatty acid supplementation in patients with AD.

Method

A literature search was completed using PubMed, EMBASE and Medline identifying peer‐reviewed articles published between January 2015 and November 2023. Randomized controlled trials, correlational studies, clinical trials, and case studies were considered, while meta‐analyses, systematic reviews, scoping reviews, animal studies, and non‐English literature were excluded. The search strategy involved key terms such as “Alzheimer,” “Alzheimer’s Disease,” “AD,” “neuroinflammation,” “fatty acids,” “fat,” and “lipids.” The PRISMA guidelines guided the inclusion/exclusion process.

Result

Of the 392 articles initially identified, five met inclusion criteria and were evaluated. Omega‐3 polyunsaturated fatty acid (i.e., fish oil), docosahexaenoic/eicosapentaenoic acid (DEA/EPA), medium‐chain triglycerides (MCT), and a combination product made of docosahexaenoic acid (DHA), EPA, uridine monophosphate, choline, phospholipids, selenium, B/C/E vitamins, and folic acid (Souvenaid®) were used in people with AD. A small study using fish oil (0.45 g of EPA with 1 g of DHA) over one year, showed decreased levels of carbonyl groups and hydroperoxides, but clinical effects were not evaluated. A study using DEA/EPA supplementation showed a decrease in fatty acid metabolism products and prevented deterioration in MMSE scores after 6 months. Additionally, the effect of MCT on cognitive ability in 53 patients with mild to moderate AD suggested APOE4‐/‐ patients with mild to moderate AD may have benefited from the MCT intervention with improved cognitive ability (ADAS‐Cog score) compared to placebo. Other studies evaluating Souvenaid® in combination with acetylcholinesterase inhibitors suggested improvements in behavioral tasks, cognitive function, and increase in hippocampal volume.

Conclusion

Preliminary trials suggested mild improvements in persons with AD with fatty acid supplementation. Souvenaid® and MCTs seem promising, highlighting potential clinical benefits. However, there is a need for additional extensive studies to validate these findings and establish clinical significance in AD.
Integrating Connectomics Constraints in Event‐Based Modeling of Alzheimer's Disease Progression: An Analysis of ADNI PET Data
Authors: Vahdatian Mahdieh , Zhao Yuji , Kurmukov Anvar , Gutman Boris A
Published: January 2025

Background

Alzheimer's Disease (AD) presents a major health challenge, with complex and variable neurodegenerative progression. Traditional neuroimaging falls short in fully capturing this heterogeneity. Our study addresses this gap by applying an Event‐Based Model (EBM) to Alzheimer's Disease Neuroimaging Initiative (ADNI) Positron Emission Tomography (PET) data, enriched with connectomics data. This innovative approach promises a more individualized understanding of AD progression, combining PET imaging with insights into brain connectivity from connectomics. Our work aims to enhance early diagnosis and personalized treatment strategies in AD research.

Method

Our study applied an Event‐Based Model (EBM) to Alzheimer's Disease Neuroimaging Initiative (ADNI) datasets across ADNI1, ADNI2, and ADNI3. We analyzed a diverse cohort including Alzheimer's Disease (AD), Mild Cognitive Impairment (MCI), Late MCI (LMCI), Early MCI (EMCI), and cognitively normal (CN) groups, using Amyloid (AMY), Fluorodeoxyglucose (FDG), and Tau PET scans. The methodology integrated connectomics data and employed Monte Carlo Markov Chain (MCMC) techniques for enhanced modeling precision. This approach provided an in‐depth understanding of AD progression, combining advanced statistical analysis with diverse neuroimaging data.

Result

Optimal order of neurodegenerative events ‐ stages of disease progression as measured by changes in metabolic signature (FDG) or Amyloid accumulation ‐ largely followed previously published results. Earliest regions of Amyloid accumulation mirrored the default mode network (Figure 1). Metabolic changes, notably reduction in FDG SUVR, occurred earliest in the same top 10 regions. Also Z‐test statistic (‐4.78): Indicates a significant difference between the average stages of AD and MCI patients, with AD stages being lower than those of MCI.

P‐value (∼0.00000177): Implies an extremely low probability that the observed difference in stages occurred by chance, strongly suggesting a true difference between the groups.

Conclusion

We have presented a novel connectome‐informed progression model of amyloid‐beta accumulation and metabolic changes in the brain. The model discriminates well between stages of cognitive decline and suggests that amyloid accumulation and metabolic changes both follow a similar early of pattern conditioned on white‐matter connectivity
Evaluating the Effects of LDL Cholesterol Levels on Tau Visualization in [F‐18]flortaucipir PET Scans
Authors: Virdi Jaipal , Silverman Daniel H.
Published: January 2025

Background

Alzheimer's Disease and other neurodegenerative diseases are characterized by abnormal tau protein accumulation in the brain. PET imaging utilizing the [F‐18]flortaucipir tracer is a widely used method for visualizing such conditions, yet its effectiveness can be compromised by off‐target binding. To shed light on this issue, our study focuses on how elevated cholesterol concentrations of low‐density lipoproteins (LDL) and standard uptake values (SUVR) from corresponding tau‐PET scans may influence the efficacy of [F‐18]flortaucipir.

Method

Demographic, metabolic, and imaging data were sourced from the Alzheimer's Disease Neuroimaging Initiative for 56 subjects at varying cognitive statuses (CN, n=24; SMC, n=4; MCI, n=25, and AD, n=3). This included t1‐weighted MRI scans and tau‐PET scans acquired with [F‐18]flortauicipir. Cholesterol levels were calculated using the ratio of cholesterol to total lipids in the LDL. Image processing was conducted using Clinica software, with volumes of interest mapped using SUVR from the Hammers atlas.

Result

Our analysis revealed significant correlations between LDL cholesterol levels and radiotracer uptake in the right & left caudate and accumbens nuclei (r=0.45, p=0.00046; r=0.45, p=0.00049; r=0.28, p=0.032, and r=0.26 p=0.05 respectively). When subjects were stratified with respect to the presence (n=27) or absence (n=29) of the APOE4 allele, some interaction was observed for the right caudate nucleus, which became somewhat more tightly correlated to the LDL parameter among those with the ε4 genotype (r=0.53, p=0.003).

Conclusion

A plausible mechanism explaining the correlations found and [F‐18]flortaucipir off‐targeting binding as a whole may be that oxidized low‐density lipoproteins (oxLDL), which proliferate as concentrations rise, could prompt microglia to transform into lipid‐laden foam cells. These cells could then create hydrophobic pockets that slow the radiotracer washout, with this effect being localized to the basal ganglia. This aligns with other research that has identified heightened oxLDL levels to specifically affect the perivascular spaces in the basal ganglia. Furthermore, our findings are consistent with previous studies that have shown increased microglial inflammation associated with the APOE4 genotype.
Microglial Activation Captured by Diffusion‐Weighted MRI and sTREM2 in Alzheimer’s Disease
Authors: Zavradyan Gohar , Bennett Ilana J , Padmanaban Sneha , Kang Seerat , Kuncharapu Sindhuja
Published: January 2025

Background

Alzheimer’s Disease (AD) is characterized by the accumulation of beta‐amyloid plaques and tau protein tangles and neurodegeneration, with growing interest in the role of neuroinflammation. The neuroinflammatory response to an insult is modulated by microglia, which transition from a resting state marked by ramified, branching processes to an activated stated in which they proliferate, migrate, and swell (processes shorten, somas enlarge). Animal studies have shown that diffusion‐weighted magnetic resonance imaging (MRI) is sensitive to these morphological differences in microglia, with higher diffusion in brain regions experiencing inflammation.

Method

The current study examined the sensitivity of diffusion‐weighted MRI to neuroinflammation in older adults diagnosed with AD, and its relation to an established CSF‐based biomarker of microglial activation (soluble Triggering Receptor Expressed on Myeloid cells 2, sTREM2), using data from the Alzheimer’s Disease Neuroimaging Initiative.

Result

Results reveal significantly higher diffusion (mean diffusivity, MD) in the hippocampus and basal ganglia and higher sTREM2 levels in the AD group relative to the older adults diagnosed with mild cognitive impairment or with no cognitive deficits. In addition, higher MD in the basal ganglia (caudate), but not the hippocampus, was significantly related to sTREM2 levels in the AD group.

Conclusion

These findings are consistent with microglia modulating a neuroinflammatory response in AD and indicate that diffusion‐weighted MRI is sensitive to the swollen morphology of activated microglia.
Age‐related variations in diffuse axonal injury following mild traumatic brain injury
Authors: Criado‐Marrero Marangelie , Ravi Sakthivel , Bhaskar Ekta , Febo Marcelo , Abisambra Jose F. F
Published: January 2025

Background

Repetitive mild traumatic brain injury (rmTBI) represents a substantial health challenge, urging a more thorough investigation into its early effects and possible interventions. The collective consequences of rmTBI encompass various neurobiological and neuropsychological impairments, increasing susceptibility to diseases like Alzheimer's and related dementias. Employing the Closed‐Head Impact Model of Engineered Rotational Acceleration (CHIMERA) approach for TBI induction, our prior study revealed connectivity alterations within 53% of regions in young and aged wild‐type mice five days post‐injury.

Method

Given rmTBI's potential for causing diffuse axonal injury, the current study utilized advanced neuroimaging techniques—Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI)—to detect white matter damage in 36 regions of the brain.

Result

Major age‐dependent disruptions were observed in the corticospinal tract, hippocampal commissure, anterior cingulate, and optic tract. Surprisingly, mean diffusivity (MD), a reflection of overall water diffusion, showed unique age‐related effects. Three main regions were affected by injury in young mice: the entorhinal cortex, anterior cingulate, and optic tract. Regardless of injuries, aged animals exhibited an inverse correlation between fractional anisotropy (FA) and radial diffusivity (RD) in the secondary motor area, corticospinal tract, and hippocampal commissure.

Conclusion

Our discoveries are significant for revealing age‐specific changes and understanding the intricate connection between age and injury, shaping brain tissue integrity, particularly in the context of aging research.
Depressive Symptoms and Cognitive Function in Older Adults with Subjective Cognitive Decline: Longitudinal Findings From 2010 to 2020
Authors: Huang Jing , Perrin Nancy , Li Junxin
Published: January 2025

Background

Subjective cognitive decline (SCD) is increasingly recognized as a symptom of preclinical Alzheimer’s disease (AD), characterized by self‐perceived cognitive worsening without objective cognitive deficits. Depressive symptoms have been linked to elevated risks of cognitive decline, yet research on depression’s role in SCD progression is still limited and inconsistent. Therefore, this study aims to examine the longitudinal association between depressive symptoms and cognitive function in older adults with SCD over a 10‐year period.

Method

Using six waves of biennial data from the Health and Retirement Study (2010‐2020), we selected older adults aged 50+ with SCD in 2010. SCD was defined by self‐reported memory decline compared with 2 years ago, absence of objective cognitive deficits (Modified Telephone Interview for Cognitive Status [TICS‐M]>11), and no self‐reported AD or dementia. Linear mixed models estimated the association between baseline depressive symptoms and cognitive function change from 2010 to 2020. Time, depression, and the time by depression interaction predicted cognitive function, measured by TICS‐M. Depressive symptoms were assessed by the eight‐item Center for Epidemiologic Studies Depression Scale (CESD‐8). CESD‐8 scores (0 – 8) were dichotomized into with and without depression using a cutoff of 3. Covariates included age, sex, race, education, marital status, poverty level, smoking, drinking, sleep disturbance, and number of chronic conditions.

Result

3058 older adults with SCD were identified (65.8 ± 10.5 years, 65.3% females). The baseline CESD score averaged 2.03 (SD = 2.32), and 31% were categorized as having probable depression. The mean TICS‐M score was 16.07 (SD = 3.00) in 2010, declining to 14.71 (SD = 4.28) in 2020. Compared with individuals without depression, those with depression at baseline exhibited a significantly greater decline in cognitive function over time when controlling for covariates (p = 0.001). Those with depression showed an average 0.14 greater decline in cognitive function at each biennial wave compared to those without depression (depression × time coefficient = ‐0.14, 95% CI = ‐0.22, ‐0.06).

Conclusion

This study provides longitudinal evidence that depressive symptoms contribute to cognitive decline in SCD above other known factors. Addressing depressive symptoms may be pivotal in slowing further cognitive deterioration in older adults with SCD.
Pursuing dementia detection for better prevalence estimation with artificial intelligence and traditional modelling techniques in electronic health data
Authors: Collyer Taya , Liu Ming , Beare Richard , Andrew Nadine , Ilomaki Jenni , Bell Simon , Rocca Walter A. , St. Sauver Jennifer , Thrift Amanda G , Ung David , Lu Alicia , Siostrom Kristy , Moran Chris , Roberts Helene , Le Elizabeth , Kennedy John Clark , Srikanth Velandai K
Published: January 2025

Background

Population dementia prevalence is traditionally estimated using cohort studies, surveys, routinely‐collected administrative data, and registries. Hospital Electronic Health Records (EHRs) are comprised of rich structured and unstructured (text) clinical data that are underutilised for this purpose.

We aimed to develop a suite of algorithms using routinely‐collected EHR data to reliably identify cases of dementia, as a key step towards incorporating such data in prevalence estimation. Towards this, we developed a novel predictive framework integrating data‐science and biostatistical methods.

Method

Training data were sourced via the National Centre for Healthy Ageing (NCHA) Data Platform, a linked, curated, EHR‐derived data warehouse. Individuals within the platform catchment aged >60 years with confirmed dementia were identified through hospital specialist dementia clinics. A comparison group of individuals aged >60years with EHR records without dementia was recruited from the community.

A panel of clinical experts (Neurology, Geriatric Medicine) informed variable and concept selection and guided data cleaning efforts within both streams. Algorithms were developed via two work‐streams; a traditional biostatistical approach to fit logistic regression models using structured data elements, and a data science stream used Natural Language Processing (NLP) to fit models to the unstructured (text) parts of the EHR, for the same individuals.

Result

Of 568 individuals (362 with dementia), 434 had clinical notes available. In the data science stream using unstructured data, among a range of NLP derived models, the Random Forest classifier performed best in assigning dementia status, with Area Under the Curve (AUC) 0.95, specificity 90.2% and sensitivity 88.4%. In the biostatistics stream, 15 structured variables were included in the final model, covering demographics, health service attendance, medications, and ICD‐10 Codes, with AUC 0.94, specificity 85.9% and sensitivity 85.6%.

Conclusion

Artificial intelligence techniques applied to unstructured electronic health data and guided by human clinical expertise may be powerful tools in capturing the presence of dementia, at least comparable to traditional techniques using structured data, and conferring practical and scientific advantages for dementia prevalence estimation. Future validation is required in less crisply delineated real‐world settings.
Investigations of reported plasma amyloid b peptides and total tau protein assayed with immunomagnetic reduction in cognitively normal controls and patients with amnestic mild cognitive impairment and Alzheimer’s disease dementia
Authors: Yang Charles S.Y.
Published: January 2025

Background

Since 2012, many groups have been using immunomagnetic reduction (IMR) for assaying plasma amyloid β 1‐40 (Aβ1‐40) peptide, Aβ1‐42 peptide and total tau protein (T‐Tau) in cognitively normal controls (NC) and patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease dementia (ADD). Tremendous results have been independently reported. In this work, we summarize the reported levels of plasma Aβ1‐40, Aβ1‐42 and T‐Tau to investigate the consistence among studies.

Method

Results of thirty studies were analyzed, including twenty‐five studies published in papers, two studies presented at conferences and three unpublished studies.

Result

The coefficient of variation (CV) in reported mean values of biomarker concentrations among studies are 8.1% for Aβ1‐40, 4.1% for Aβ1‐42 and 19.4% for T‐Tau in NC, 10.7% for Aβ1‐40, 8.4% for Aβ1‐42 and 15.0% for T‐Tau in aMCI, 10.6% for Aβ1‐40, 19.1% for Aβ1‐42 and 28.7% for T‐Tau in ADD. In the thirty studies, there are 1189 subjects of NC, 543 aMCI patients and 853 ADD patients. The averaged level of plasma Aβ1‐40 of subjects was found to significantly decrease from NC (59.72 pg/ml) to aMCI (45.92 pg/ml, p < 0.0001), which showed non‐significant difference from ADD (48.34 pg/ml, p > 0.05). The averaged level of plasma Aβ1‐42 significantly increased from NC (15.72 pg/ml) to aMCI (17.66 pg/ml, p < 0.0001), which was not significantly different from ADD (19.39 pg/ml, p > 0.05). However, the averaged level of plasma T‐Tau significantly increased from NC (17.92 pg/ml) to aMCI (28.26 pg/ml, p < 0.0001), further significantly increased to ADD (35.51 pg/ml, p < 0.001). The summarized results reveal important impacts to clinical utilities of plasma biomarkers in AD.

Conclusion

The measured concentrations of plasma Aβ1‐40, Aβ1‐42 and T‐Tau with IMR are consistent and reliable among studies. Furthermore, the plasma Aβ1‐40, Aβ1‐42 and T‐Tau levels are able to discriminate NC from patients with aMCI and ADD. Plasma T‐Tau levels are disease‐severity dependent.