bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding Challenges of Recruiting African Americans for Genomic Studies in Alzheimer’s Disease Beyond Trust
Authors: Starks Takiyah D. , Caban‐Holt Allison M , Terrell Kristy A. , Crawford Jesseca , Gregory Ashley , Adams Larry D. , Cuccaro Michael L. , Haines Jonathan L. , Reitz Christiane , Vance Jeffery M. , Pericak‐Vance Margaret A , Byrd Goldie S.
Published: January 2025

Background

Black/African Americans (B/AAs) remain underrepresented in Alzheimer’s disease (AD) research and clinical trials. As a part of understanding genetics and genomics of AD, four U.S sites are recruiting 4,000 African Americans over age 60 for research participation. We identify challenges and propose solutions for recruiting AA’s using community based and grass roots efforts.

Method

An important strategy for recruiting B/AAs for research is to engage researchers and staff in face‐to‐face interactions outside of the medical/academic campus. We analyzed steps required to move individuals from initial research interest to their enrolling in the study, over a 6‐month period. During community outreach activities, interested individuals provided basic demographic data, and level of interest in AD research. Research staff followed‐up by telephone up to three times, within 48 ‐72 hours, to answer questions and schedule a home visit. Scheduled participants were also contacted one week before the study appointment, and a confirmation letter was sent. Participants were called the day before and the day of the home visit to assure participant availability, creating up to eight touch points prior to enrollment.

Result

We enrolled 67 of the 129 B/AAs scheduled over a 6‐month period. Thirty three of the 67 interested participants (49%) were scheduled on the first attempt, n = 26 (39%) on the second attempt and n = 8 (12%) on the third attempt. All enrollees (100%) were called a week before the appointment and a confirmation email was sent. Thirteen (10%) of scheduled appointments were cancelled due to: 1) inability to reach them (62%), 2) no longer interested (15%), 3) feared the blood draw (15%) and 4) time constraints (8%).

Conclusion

Despite using culturally sensitive research teams, materials and advertisements, reliability of recruiting B/AAs for genetic research studies using grass roots methods remains elusive. Appointment cancellations due to fear of blood draws, family issues and time limitations are key factors, but understanding reasons for loss of contact and interest should be further investigated. Closing gaps between B/AAs’ research interest and their actual enrollment will require multiple and simultaneous recruitment strategies that might require more than trust.
Undetected dementia in Brazil
Authors: Miguel Andrew Christopher , Barbosa Matheus Ghossain , Brucki Sonia , Caramelli Paulo , Laks Jerson , Nitrini Ricardo , Suemoto Claudia Kimie , Ferri Cleusa P
Published: January 2025

Background

Despite the increasing number of people with dementia, it remains underdetected worldwide, even in high‐income countries. In Brazil, the number of people with dementia is expected to triple by 2050 and diagnosis can be challenging, contributing to high and growing rates of underdiagnosis. At the moment, there is no national estimate of undetected dementia.

Methods

We estimate the proportion of people with dementia (PWD) who are not diagnosed in relation to the total number of PWD estimated by a recent Delphi Consensus. Diagnosed individuals were estimated through the dispensation of anticholinesterases drugs (AChE) in the Unified Health System (SUS), in 2022, for mild and moderate stages of Alzheimer’s Disease (AD), obtained at ftp://ftp.datasus.gov.br, which follows the Ministry of Health national clinical protocol. National literature was consulted for: (i) the proportion of people with mild and moderate AD.; (ii) the proportion of those who obtain AChE from SUS, from the private sector or from both; (iii) the proportion of those who do not take AChE; and (iv) the proportion of AD related to other dementias. We assumed that the underdetection rates of AD would be similar to other dementias and that 70% of the diagnosed individuals with AD obtain AChE from SUS.

Results

More than 80% of the PWD 60+ are undetected (80,2%). Regionally, the North has the highest rates (95,6%), followed by Northeast (90,0%), Midwest (88,6%), South (74,8%) and Southeast (72,9%). Underdiagnosis was higher among men than women (82,2% versus 78,1%) and among the youngest age groups: 60‐64 years (90,7%), decreasing between 65‐69 years (86,9%), 70‐74 years (81,8%) and increasing again in the oldest group 90+ (84,5%).

Conclusion

The underdiagnosis of dementia in Brazil is among the highest in the world. Populational aging trends and higher rates in younger individuals are of concern due to the importance of timely diagnosis. Gender and regional disparities also need to be considered in specific health policies, to increase not only diagnosis rates, but provide adequate support to PWD and their families.
Democratising Early Career Researcher (ECR) Training for Dementia Research
Authors: Bauermeister Sarah
Published: January 2025

Background

Training programmes and workshops for Early Career Researchers (ECR) in dementia research are frequently expensive and inaccessible. This means that under resourced institutions, researchers and countries (LMIC) are unable to provide adequate training facilities for researchers focused on analyses for dementia outcomes. The result is that only elite institutions are provided high level training facilities for their researchers and those who are not represented in these institutions are underrepresented. Dementias Platform UK (DPUK) provides free and affordable training opportunities for all academic and industry researchers across the world.

Method

The DPUK training programme includes:

1. Datathon workshops which enable researchers from across the world to access large cohort datasets on the DPUK Data Portal and work alongside other global researchers on a dementia‐focused research question.

2. Academies for both elementary and advanced longitudinal data analysis are conducted twice a year.

3. A 12‐week mentoring programme is provided after the Datathon workshop ‐ led by DPUK and aimed at producing a publishable output from their Datathon attendance.

Result

Over 200 researchers across 11 countries have attended the DPUK Training events over the last 5 years.

Conclusion

Providing affordable or free training for the current and next generation of ECRs is possible by using the resources provided by a Trusted Research Environment (TRE) such as DPUK.
Sex differences in risk of developing Alzheimer Disease and cognitive outcomes
Authors: Robinson Carling G. , Morris John C. , Hassenstab Jason J. , Cruchaga Carlos , Belloy Michael E. , Gordon Brian A.
Published: January 2025

Background

The prevalence of Alzheimer disease (AD) is growing rapidly within the aging population with over five million people currently affected in the United States. Of these 5 million people, approximately two‐thirds are females. Prior investigations have demonstrated that females have a higher likelihood of developing AD when compared to men. The present study sought to investigate participants from the Charles F. and Joanne Knight Alzheimer Disease Research Center (ADRC) to determine if sex impacts an individual’s risk of developing dementia.

Method

3231 prospectively recruited participants from were classified as demented or non‐demented based on scores on the Clinical Dementia Rating ® (CDR®). Of the 3231 participants, 58.4 percent were female. Cox proportional hazards models were utilized to compare the rate of developing dementia as a function of self‐reported sex. Models additionally determine if apolipoprotein ε4 (APOE) carriers were at a greater risk of developing dementia. We further evaluated the interaction between sex and APOE status and the likelihood of developing dementia. Baseline age was included as an additional covariate.

Results

Participants had mean of 5.92 years of longitudinal cognitive follow‐up. Females did not demonstrate an increased risk of developing dementia compared to males (Hazard ratio = 0.874, p = 0.149). Age at baseline was a significant predictor of conversion to dementia (Hazard ratio = 1.100, p≤0.001), as was ε4 carriers status (Hazard ratio = 1.64, p≤0.001). The interaction between female sex and APOE status was not a significant predictor of conversion to dementia (Hazard ratio = 1.034, p = 0.863).

Conclusion

Female participants did not demonstrate an increased risk of developing all cause dementia compared to male participants.
The Association Between Plasma P‐tau181 and Cardiovascular Disease in the Framingham Heart Study
Authors: Tanner Jeremy A. , Wiedner Crystal , Aparicio Hugo J. , Gonzales Mitzi M. , Himali Dibya , Kautz Tiffany F. , McGrath Emer R , Parker Alicia S. , Ramos‐Cejudo Jaime , Satizabal Claudia L , Beiser Alexa S , Tracy Russell P. , Vasan Ramachandran S , Himali Jayandra J. , Seshadri Sudha
Published: January 2025

Background

Plasma p‐tau biomarkers are promising diagnostic tools for widespread clinical use. However, recent studies have raised concerns regarding the effect of common medical comorbidities, such as cardiovascular disease (CVD), on plasma p‐tau specificity. These influences must be better understood to enable appropriate clinical use of p‐tau181. We sought to evaluate the association between p‐tau181 and CVD outcomes in the Framingham Heart Study (FHS), a population‐based prospective cohort with deep‐phenotyping of CVD.

Method

FHS Offspring and Omni 1 Cohort participants have been followed through quadrennial exams with detailed CVD assessment. Plasma p‐tau181 was measured from samples of 2543 participants collected in 2011‐2014 using Quanterix Simoa, and analyzed as a binary predictor (highest quintile vs remainder). CVD outcomes (binary:yes/no) included overall CVD, congestive heart failure(CHF), coronary heart disease(CHD), stroke/TIA, and peripheral arterial disease(PAD). Multivariate logistic regressions were performed to assess the association between p‐tau181 and each prevalent CVD outcome adjusting for age, sex, cohort in base models, and additionally for eGFR, and BMI in adjusted models. Cox regression models were performed to assess the association between p‐tau181 and incident CVD outcomes adjusting for similar covariates after a median survival time of 7.0 years [5.9‐7.6]).

Result

Participant characteristics are displayed in Table 1. Elevated p‐tau181 was associated with 74% higher odds of prevalent CHF (OR 1.74; 95%CI[1.02‐2.98], p=0.04) in adjusted models (Table 2). Elevated p‐tau181 was associated with 41% higher risk of incident overall CVD (HR 1.41[1.03‐1.93], p=0.03) and 55% higher risk of incident CHF (1.55[1.03‐2.34], p=0.04) in adjusted models (Table 3). There was no association between p‐tau181 levels and other CVD outcomes in cross‐sectional or longitudinal analyses.

Conclusion

Elevated plasma p‐tau181 is associated with prevalent and incident CHF and with overall CVD in a community‐based population. This aligns with growing evidence of a possible bidirectional relationship between CHF and AD. P‐tau levels should be interpreted with caution in patients with CHF until the link between p‐tau181 and CHF can be further clarified. Studies to understand systemic diseases that influence plasma AD biomarkers are necessary prior to widespread clinical use, and can reveal new relationships between AD and systemic diseases.
Examining How Cognition, Neighborhood Characteristics, and Physical Function are Associated with Outdoor Frequency Among United States Community‐Dwelling Medicare Beneficiaries
Authors: Sefcik Justine S. , Coates Martha C , Petrovsky Darina , Glasofer Amy , Okoye Safiyyah , Vader Daniel T , Moore Renee H , Baker Zachary G , Ma Kris Pui Kwan , Rahemi Zahra , Bacsu Juanita‐Dawne R , Smith Matthew Lee , DiMaria‐Ghalili Rose Ann
Published: January 2025

Background

A large body of research supports the benefits of older adults engaging in physical activity outdoors. However, a paucity of research explores factors associated with the frequency of older adults going outdoors. The aim of this study was to explore how factors including cognition, neighborhood characteristics, and physical ability were associated with community‐dwelling older adults’ outdoor frequency.

Method

This cross‐sectional study used National Health and Aging Trends Study data to investigate determinants of outdoor frequency among Medicare beneficiaries aged 65 and older. We descriptively characterized the distribution of outdoor frequency by participant demographic, health, and neighborhood characteristics using counts and percentages, and estimated odds ratios of relationships between key characteristics (including cognitive status, neighborhood characteristics, and physical ability) and outdoor frequency using survey ordinal logistic regression.

Result

The final sample included 3,368 participants, ages 65 and older (57% female). Most participants went outside every day (60.4%) and few went outside rarely or never (3.5%). Compared to those who went outside daily, individuals who went outside rarely or never were more likely to have probable dementia, live in neighborhoods with street disorder and continuous sidewalks, and have physical limitations requiring assistive devices and help to go outside.

Conclusion

Older adults with dementia and physical limitations may be less likely to experience the benefits of outdoor activity. Neighborhood characteristics may contribute to going outdoors. More research is needed to understand the experiences of people living with dementia and physical limitations in order to develop interventions and age‐friendly neighborhoods promoting outdoor activity.
Harmonisation of neuropsychological assessment for Alzheimer’s disease diagnosis across diverse African settings: A Pilot Study from the African Dementia Consortium (AfDC)
Authors: Paddick Stella‐Maria , Cuccaro Michael L. , Damas Andrea , Baiyewu Olusegun , Farombi Temitope Hannah , Elugbadebo Olufisayo Oluyinka , Okubadejo Njideka U. , Ojo Oluwadamilola , Zaman Andrew F. , McInerney Katalina F. , Akpalu Albert Kwaku , Laryea Ruth , Sarfo Fred Stephen , Osei Shadrack , Obiako Reginald , Ndetei David , Musyimi Christine W. , Damasceno Albertino , Adoukonou Thierry , Ayele Biniyam A. , Mena Pedro R. , Walker Richard , Kalaria Rajesh N , Vance Jeffery M. , Ogunniyi Adesola , Pericak‐Vance Margaret A. , Akinyemi Rufus O. ,   African Dementia Consortium
Published: January 2025

Background

Majority of people living worldwide live in low‐ and middle‐ income countries, including sub‐Saharan Africa (SSA). Most cognitive assessment batteries for Alzheimer’s Disease(AD), are developed in high income countries (HICs), where most international dementia collaborations and data originate. The African Dementia Consortium (AfDC) is a new scientific collaboration network currently participating in the Recruitment and Retention for Alzheimer’s Disease Diversity Genetic Cohorts in the Alzheimer’s Disease Sequencing Project (READD‐ADSP). This pilot study investigated essential adaptations and pilot of cognitive measures from the US Uniform Data Set Version 3 (UDS3) alongside SSA specific measures where these exist, in diverse cultural contexts of the AfDC.

Method

A minimum of 24 individuals (12 with >12 years education, 12 with < 12 years education) aged over 60 years were recruited in Nigeria (3 sites), Tanzania, Kenya, Ghana, Mozambique, Benin and Ethiopia, using convenience sampling. Tests were administered according to a culturally adapted protocol. Feasibility data included time taken for completion, proportion of ‘complete failure’ on individual items, language and translation challenges.

Result

Data were available from 10 sites across 7 countries. Mean scores on some US measures (MINT, Benson figure copy, word list recall) with minor adaptations, were similar to US norms. In contrast, other tests appeared highly challenging (e.g., Trail Making Test, Craft Story) with median scores well outside the HIC range and a high rate of ‘total failure’ (Trails B). Cultural adaptations were necessary and unexpectedly challenging including sound selection and categorical conceptualisation for verbal fluency tasks and protocolising for bilingualism. Median scores varied by site and education, highlighting the need for appropriate local normative values. All adaptations and modifications were carefully documented and will be used by the ADSP‐Phenotype Harmonization Consortium to integrate AfDC cognitive test data with other ADSP cohort data.

Conclusion

Further work should outline required steps for cross cultural harmonisation across countries, especially in SSA as a guideline for other collaborations. The publication of normative values for frequently used AD cognitive measures specific to diverse SSA sociocultural contexts of SSA is needed.
Evaluating Sociodemographic Bias in an Artificial Intelligence Algorithm to Detect Cognitive Impairment in Electronic Health Records
Authors: Magdamo Colin G. , He Yignan , Dickson John R. , Tyagi Tanish , Westover M. Brandon , Mukerji Shibani , Ritchie Christine S. , Hyman Bradley T. T. , Blacker Deborah , Das Sudeshna
Published: January 2025

Background

Underdiagnosis of Alzheimer’s disease and related dementias (ADRD) leads to lost opportunities for timely intervention, increased healthcare costs, and underestimation of the true burden of disease. To address this problem, we developed an AI algorithm, Decipher‐AI (DEtection of Cognitive Impairment PHenotypes in EHR), to screen primary care patients for undiagnosed cognitive impairment (CI). We evaluated performance across sociodemographic groups using 3 years of EHR data before the first diagnosis or most recent visit.

Method

Decipher‐AI employs a two‐level hierarchical model, consisting of a large language model (LLM) to generate latent representations from unstructured clinical text and a patient‐level model that combines these representations with structured EHR data to predict the probability of CI (AUC: 0.98, 95% CI: 0.94, 1.00). Decipher‐AI was evaluated on a test set comprising 22,000 Mass General Brigham primary care patients aged 65 years or older. The selection process involved stratified random sampling across distinct racial/ethnic strata to ensure representation of diverse sociodemographic factors (Table 1). Cognitive status labels were determined based on the presence of dementia‐related diagnosis codes, while sociodemographic status was measured using the Area Deprivation Index (ADI).

Result

The AUC on the validation dataset was 0.80 [95% CI: 0.79, 0.81]; sensitivity was 0.75 [0.74, 0.77] and specificity 0.68 [0.67, 0.69], at the threshold of maximum accuracy. There were no significant differences in AUCs across sex or race/ethnic subgroups, but AUC was lower for patients under 75 years. (Figure 1A). Notably, Decipher‐AI exhibited diminished performance in patients from more disadvantaged neighborhoods (Figure 1B). Further analysis revealed that these disparities were associated with fewer encounters, outpatient visits, and notes containing cognition‐related keywords in patients from disadvantaged neighborhoods (Table 2).

Conclusion

Our study highlights the potential of Decipher‐AI for screening undiagnosed cognitive impairment in primary care. Nevertheless, disparities in algorithm performance underscore the importance of addressing sociodemographic inequities in EHR data. In the future, systematic tailored screening in primary care via standardized questionnaires coupled with AI‐assisted chart reviews, has the potential to address the underdiagnosis of ADRD in an equitable manner.
Association between Medical Comorbidities and White Matter Hyperintensity Volume in Diverse Populations: A HABS‐HD Study
Authors: Trammell Antoine R , Lah James J. , Parker Monica W , Goldstein Felicia , Hales Chadwick M , Davis Crystal P , Dorbin Cornelya D , Saleh Sabria , Murphy‐Tchivzhel Elizabeth , Rose Alecia Michella , Osborne Amber , Ahmad Adiva , Al‐Amin Jahmila , O'Bryant Sid E.
Published: January 2025

Background

Older African American (AA) and Hispanic American (HA) adults have a higher risk for Alzheimer’s disease and related dementias (ADRD) compared to non‐Hispanic white (NHW) adults. AA and HA persons may also develop disease at younger ages with more rapid progression. Vascular disease, including cerebral small vessels, manifest by white matter hyperintensity (WMH) lesions, is more prevalent in AA and HA. Evidence suggests that vascular disease and WMH lesions may influence ADRD risk. This study explores WMH volume and vascular health conditions in a diverse research sample.

Method

We obtained demographic, clinical history, laboratory, and brain magnetic resonance imaging data collected from Health and Aging Brain Study: Health Disparities baseline visits. Using ANOVA and chi‐square, we compared conditions with ADRD risk (depression, hypertension, diabetes, hyperlipidemia, stroke), blood pressure, body mass index (BMI), and labs by self‐reported race (NHW, AA, HA). We performed linear regression adjusted for age, education, and sex to evaluate associations between WMH volume and clinical conditions.

Result

Data from 3,035 participants was analyzed (mean age: 65.2; female: 62.3%; impaired: 20.1%). AA were younger (NHW: 68.6, AA: 62.9, HA: 62.3. p<.0001) and had higher BMI (NHW: 29.1, AA: 32.5, HA: 30.9, p<.0001). Among conditions, HA had more hypertension (NHW: 18.2%, AA: 15.3%, HA: 19.9%, p<.0001), diabetes (NHW: 4.68%, AA: 4.71%, HA:12.4%, p<.0001), higher A1c (NHW: 5.57, AA: 6.02, HA: 6.43, p<.0001), and higher triglycerides (NHW:120, AA: 99.2, HA: 152, p<.0001). NHW had more depression (NHW:10.4%, AA: 4.88%, HA: 8.76%, p=0.006). AA had the highest WMH volume (NHW: 4.16, AA: 18.4, HA: 3.18, p<.0001). Regression showed higher WMH volume was associated with BMI in AA (β=.33, p=.007) and HA (β=1.84, p=.001). In AA, higher WMH volume was associated with diabetes (β=23.7, p=.02) and HbA1c (β=8.32, p=.02). In NHW, higher WMH volume was associated with stroke (β=4.76, p<.0001) and depression (β=1.18, p=.007).

Conclusion

Study findings show associations between WMH burden and medical conditions, labs, and physical measures. Results also show that cerebral small vessel disease and cognitive impairment risk factors may vary by race. Study findings highlight the benefit of diverse research samples in gaining further insights into ADRD risk, pathogenesis, and disease progression.
Extracellular Vesicles for The Diagnosis of Alzheimer's Disease and Related Dementias: A Diagnostic Accuracy Meta‐analysis
Authors: Taha Hash Brown , Yacoub Fatemah , Morris Alanna , Birnbaum Allison
Published: January 2025

Background

Alzheimer’s disease, along with other cognitive disorders such as frontotemporal dementia (FTD), dementia with Lewy body (DLB) Parkinson’s disease dementia (PDD), and vascular cognitive impairment and dementia (VCD), comprise a range of conditions with similar cognitive symptoms but different pathophysiology. Currently, there is no biomarkers to distinguish them before death. The pathophysiological mechanisms differ significantly across these disorders, which implies a varied response to potential treatments. Furthermore, MCI often acts as an early phase, frequently leading to dementia, especially AD. Here, we assessed the diagnostic accuracy of biomarkers in general extracellular vesicles (EVs) and speculative CNS‐enriched EVs using the receiver operating characteristic (ROC) models to discriminate each disorder from one another or from healthy controls (HCs).

Method

We conducted a PRISMA‐guided meta‐analysis on 49 studies to evaluate the diagnostic accuracy of biomarkers in general and speculative CNS‐enriched EVs for AD, FTD, DLB, PDD, VCD, MCI, and HCs, using hierarchical bivariate modeling of ROC statistics. Sub analyses were performed across EV types, mediums (e.g., CSF, plasma, serum, urine, saliva), isolation methods, among others. We also assessed publication bias and the potential number of missing studies with the trim‐and‐fill method and other robust statistical methods.

Results

The analyses reveal that biomarkers derived from general EVs exhibit better diagnostic accuracy and less heterogeneity, variance, and publication bias than speculative CNS‐enriched EVs for all disease comparisons.

Conclusion

These findings suggest that the usage of biomarkers derived from general EVs is superior to those from speculative CNS‐enriched EVs for the diagnosis of dementia.
VCAM is associated with impairment in individuals with amyloid and tau pathology
Authors: Vidor Pedro Rodrigues , Schlickmann Thomas Hugentobler , Machado Luiza Santos , da Rocha Andreia Silva , Ferrari‐Souza João Pedro , Zimmer Eduardo R.
Published: January 2025

Background

Alzheimer's disease (AD) has been known for more than a century, but its complex pathophysiology remains unclear. Previous studies have been suggesting a potential role of neuroinflammation and cerebral vascular changes in AD progression. Part of the immune response relies on the role of Vascular Cell Adhesion Molecule (VCAM) in cell transit through the endothelium. However, there is little information about the impact of VCAM in AD‐related impairment. Here, we investigated the association of plasma VCAM levels with biological and clinical AD markers.

Method

We assessed 357 individuals from the Alzheimer's Disease Neuroimaging Initiative cohort with plasma VCAM and medical data available. Statistical analyses were performed using R Studio. Association with diagnosis was evaluated by a linear regression between VCAM and clinical diagnosis, with adjustments for age, sex, APOEε4 status and years of education. Regressions analysis was also used to assess the association of VCAM with Clinical Dementia Rating Scale ‐ Sum of Boxes (CDR‐SB), adjusting for age, sex, APOEε4 status and years of education, as well as cerebrospinal fluid Aβ42 and p‐Tau181.

Result

The group of individuals with dementia had higher blood VCAM levels (p=0.005) than both CN and MCI (p=0.003) groups, but there was no statistical significance between CN and MCI (Figure 1). VCAM showed a positive association (p = 0.018, Figure 2) with greater impairment as measured by CDR‐SB when adjustments for Aβ42 and p‐Tau181 were included.

Conclusion

Our results suggest differential effects of vascular factors in biological and clinical AD. Further studies are needed to assess whether these relations include causality and whether targeting VCAM can lead to improvements in neuroinflammatory or vascular‐related changes.
Relationship between cognitive impairment and hand grip strength in a population‐based cohort of older Nigerians: Data from the VALIANT Study
Authors: Akinyemi Rufus O. , Olalusi Oludotun V , Akinyemi Tolulope O , Ogunde Gabriel O , Yaria Joseph O , Cadmus Eniola O , Popoola Femi O , Akinyemi Joshua O. , Owolabi Mayowa O , Romero‐Ortuno Roman , Ogunniyi Adesola , Lawlor Brian
Published: January 2025

Background

By 2050, the prevalence of dementia is projected to triple with the greatest increases anticipated in Africa and Asia – largely attributable to population growth and cardiometabolic disorder. Hand‐grip strength (HGS) is a known predictor of cardiometabolic and cognitive health. The relationship between HGS and cognitive impairment (CI) among elderly West Africans is not known. We examined the relationship between HGS and cognitive impairment among older adults in a rural community in Ibadan, South West Nigeria.

Method

The Vascular heAlth, fraiLty and cognition in Ageing Nigerians (VALIANT) Study is an ongoing longitudinal community‐based cohort study aimed at exploring the association between cardiovascular health, cognition and frailty in Nigeria. One thousand participants have been recruited via a multistage, stratified cluster random sampling method recruited from a rural community in Ibadan and taken through a battery of cardiovascular, cognitive and frailty assessment tools. Data on HGS, obtained using a digital hand dynamometer, was available for 480 men and women aged≥50years. The Relationship between cognitive impairment (using MoCA <18) and HGS was examined using a multivariable adjusted logistic regression analysis. All associations were reported as ORs with the corresponding 95% confidence intervals (CI).

Result

The mean age of study participants was 64.5 (11.8) with predominant females (65%). Most participants (62.2%) were hypertensivewhile 22.9% were obese. The mean MOCA score in males and females were 22.155.7 and 17.82 6.6 respectively. Approximately 36% had moderate‐severe CI (MoCA<18), 43% had mild CI (MoCA 18‐25), 21% were normal (>25). There was a significant positive correlation between HGS and MoCA 0.45 (p <0.001). The independent determinants of moderate‐severe cognitive impairment in descending order of aOR (95%CI) were age 1.07 (1.03‐ 1.11), higher HGS 0.94 (0.90 ‐0.98), attainment of primary education 0.14 (0.07 – 0.29), secondary education 0.06 (0.02 – 0.16) and tertiary education 0.01 (0.01 – 0.14)

Conclusion

Besides older age and attainment of any form of education, higher HGS was independently associated with moderate‐severe cognitive impairment among elderly Nigerians. Further exploration of the link between HGS and early clinical/neuroimaging biomarkers of dementia is desirable.
Conversion to dementia up to the fourth annual follow‐up assessment and from a Brazilian cohort of older adults
Authors: Engelmann Gabriela Tomé Oliveira , Vieira Carolina Portugal , Burgos Ivonne Carolina Bolaños , Moro Giovanna Correia Pereira , Borges João Marcos Silva , Costa Julia Cardoso Costa Cardoso , Graciano Guilherme Fonseca , de Souza Aline Siqueira , Saldanha Marcelle Ferreira , Hansen Erika de Oliveira , Romano‐Silva Marco Aurélio , de Miranda Debora Marques , de Marco Luiz Armando Cunha , de Ávila Rafaela Teixeira , Viana Bernardo de Mattos , Bicalho Maria Aparecida Camargos
Published: January 2025

Background

Studies comprising cohorts of cognitively unimpaired older adults or with mild cognitive impairment (MCI) that assesses clinical and biological characteristics to conversion to dementia are scarce in Brazil.

Method

To determine the median conversion time to dementia in a cohort of Brazilian older adults with low educational levels. In the cohort, participants undergo an annual comprehensive clinical and neuropsychological evaluation, complemented by neuroimaging and laboratory assessments to determine the diagnosis. Data from 225 older adults from the Cog‐Aging cohort was assessed and the first confirmed diagnosis was selected for this analysis: 67 Normal Cognition (NC) and 158 with MCI. Descriptive statistics were carried out according to normality tests. The time to conversion to dementia for participants with normal cognition (NC), Mild Cognitive Impairment (MCI) was assessed using the Kaplan‐Meier survival analysis. Only p<0.05 were considered. This study was approved by UFMG’s ethics committee.

Result

The median age at the beginning of the study was 73 years (IQR = 9.19) for NC group, and 77 years for MCI (IQR = 10.58). The median years for education was 4 years for both the NC (IQR = 4.50) and MCI (IQR = 2.00) groups. At the fourth annual follow‐up, 66 patients with NC remained stable, while 21 with MCI remitted to NC. The cumulative proportion surviving of MCI patients was 68,7% (SE .054) at 36 months, with 31 conversions to dementia and 37 remaining cases. At 36 months, no NC had converted to dementia. This occurred at 50 months. The median survival time was 42.74 months (SE 2.92; Lower Bound 37.01; Upper 48.48). In other terms, this means that 50% of MCI conversions to dementia occurrs up to 3.56 years. These differences were statistically significant with Log Rank (Mantel‐cox), Breslow (Generalized Wilcoxon) and Tarone‐Ware p≤ .001.

Conclusion

At the fourth annual follow‐up assessment, patients with NC tend to remain stable, while 50% of participants with MCI convert to dementia up to 3.56 years. MCI poses a greater risk for conversion to dementia in the first’s three years of follow‐up in this sample, however more studies are still needed to assess other confounding variables.
Revolutionizing Dementia Care: Enhancing Talk Therapy with Fine‐Tuned Large Language Models Using GPT Self‐Generated Data
Authors: Xu Jia , Wei Tianyi , Hou Bojian , Demiris George , Shen Li
Published: January 2025

Background

It has been validated that dementia can be alleviated by talk therapy. While general large language models (LLMs) have the potential for talk therapy and dementia treatment, customized LLMs resembling a mental‐health therapist can be more professional and powerful. We introduced an LLM solution designed for tailored mental health support for future dementia care. By employing GPT self‐generated data, encompassing a diverse range of mental health scenarios, we've significantly enhanced the model’s ability to understand and engage with complex emotional and psychological queries from patients. This advancement in LLMs paves the way for more efficient and effective delivery of talk therapy, shedding light for future dementia care and treatment.

Method

We fine‐tuned five open‐source LLMs to enhance their capabilities in the context of mental health counseling. The fine‐tuning process was conducted using the quantized Low‐Rank Adapters (QLoRA) method on an A40 GPU. We generated 10,000 question‐answer pairs as the training data using GPT‐3.5‐Turbo, designed to simulate interactions between mental health counselors and patients. This dataset encompassed a broad spectrum of mental health issues, including but not limited to depression, anxiety, and sleep disorders. Post fine‐tuning, the performance of these models in test data gathered from the Mental Health Forum and Quora (Fig. 2) was judged comprehensively by GPT‐4 Turbo. This evaluation was structured around six mental health metrics (Fig. 1) to ensure precise and relevant assessment in the context of mental health therapy.

Result

The top‐performing model, “Mixtral‐8×7B‐v0.1‐qlora,” achieved a remarkable average score of 7.83 (Tab. 1), highlighting its superior capability over the base model in handling complex mental health interactions. Other fine‐tuned models, such as “Zephyr‐7b‐gpt” and “Vicuna‐7b‐gpt,” also showcased exceptional performance over their base models, scoring 7.82 and 7.78 respectively. These results underscore the efficacy of fine‐tuning in enhancing the empathetic and contextual responsiveness of LLMs in mental health settings, particularly in dementia care.

Conclusion

The study’s results showcased the effectiveness of fine‐tuned large language models (LLMs) suffixed by “QLoRA” in enhancing talk therapy. The leading model, “Mistral‐7B‐Instruct‐v0.2‐QLoRA,” demonstrated superior empathy and understanding over the base model in complex dementia interactions by leveraging domain‐specific data.
A web‐based tool for early prediction of Alzheimer’s disease dementia based on magnetic resonance imaging data
Authors: Fan Yong
Published: January 2025

Background

Recent studies have demonstrated that deep learning of magnetic resonance imaging (MRI) brain scans can accurately predict Alzheimer’s disease (AD) dementia and cognitive decline. However, the translational potential of this technique remains unfulfilled, as the underlying deep learning techniques are not yet available for immediate clinical use. To address this issue, we develop a web‐based tool to facilitate real‐time imaging data visualization and analyses, including brain image segmentation, cortical surface reconstruction, and early prediction of Alzheimer’s disease dementia based on structural MRI data.

Method

A webapp has been developed to load and visualize imaging data with a browser‐based viewer and achieve fast imaging data processing and predictive modeling with a cloud‐computing backend. The browser‐based viewer provides a webpage‐based interface for communicating with the cloud‐computing backend and visualizing imaging data and analysis results. The cloud‐computing backend integrates state‐of‐the‐art deep learning algorithms to carry out real‐time brain image segmentation, cortical surface reconstruction, and early prediction of Alzheimer’s disease dementia based on structural MRI data. All the image processing and prediction results are automatically sent back to the browser‐based viewer for visualizing the results. This webapp supports imaging data in both DICOM and NIFTI formats and all identity information of imaging files are removed automatically before the imaging data being sent to the cloud‐computing backend for computing.

Result

This webapp is compatible across widely used web browsers, allowing real‐time image analysis without installing any software. It can load and visualize MRI images with drag‐and‐drop and achieve brain image segmentation, cortical surface reconstruction, and prediction of progression of Alzheimer’s disease dementia and cognitive decline within seconds. Validation results on large imaging datasets, including ADNI and AIBL, have shown that this tool can achieve fast and accurate prediction of Alzheimer’s disease dementia and cognitive decline.

Conclusion

The webapp turns deep learning methods for MRI data analysis into a clinically usable tool, illustrating the feasibility of real‐time predictive modeling of Alzheimer’s disease dementia based on MRI data. Ongoing development will further increase its capacity to facilitate predictive modeling of diverse neurodegenerative diseases based on imaging data.
The Good Life program for healthy brain aging is a new standard of care in California
Authors: Johnson David K
Published: January 2025

Background

In 2022, The Good Life program for healthy brain aging (TGL) was recognized by Governor Newsom and his Task Force on Alzheimer’s Prevention and Preparedness as a new Standard of Care for Alzheimer’s disease preventive medicine in California. TGL is a large geriatric focused public health initiative that promotes healthy lifestyles to older adults from all walks of life. It is made up of a series of three lifestyle intervention (LSI) classes that are produced and delivered on a video conferencing platform. The Let’s Get Moving (LGM) series is a live, virtual exercise and fitness class delivered to seniors several times per week by a certified fitness trainer using the Exercise is Medicine curriculum of the American College of Sports Medicine. The Let’s Get Cooking (LGC) series delivers virtual healthy cooking classes to seniors in their own home by our staff trained in the 18 Reasons cooking curriculum, an empirically validated nutrition program that uses hands on kitchen training to promote caloric restriction and healthier meal replacement. The peer‐to‐peer mental health TGL program applies a group therapy‐like formatted virtual meeting series to promote mindfulness and emotional literacy.

Method

TGL implemented a 2‐arm pragmatic clinical trial (without random assignment) to test if high versus low levels of Perceived Social Support, Perceived Positive Health Change, and Anxiety symptoms affect attendance in TGL’s intervention over an 18‐week repeated measures follow up. The study is in its 2nd year and will run over 4 years with quarterly assessments of the 3 co‐primary outcomes. Each participant is observed up to 18 months, yielding up to 6 repeated measures of these outcomes per individual.

Result

TGL is very successful at engaging BA and LA in healthy lifestyle classes. TGL has over 2,000 older adult members (approximately 70% of our membership are either BA or LA older adults).

Conclusion

TGL’s success strongly indicates that virtual classes, which eliminates the burdens for older adults to attend in‐person classes, are effective in increasing adoption of healthy lifestyle behaviors.
Navigating the Complexities of Alzheimer’s Clinical Trials: The Perils of Small Molecule Studies and the Risk of Fraudulent Practices
Authors: O'Keefe Patrick P , Hendrix Suzanne B. , Zhang Jeffery , Hendrix Kent , Wang Lixia , Dickson Samuel P.
Published: January 2025

Background

Alzheimer’s disease (AD) presents unique challenges in clinical trials involving small molecules. Multifaceted issues plague such trials, emphasizing susceptibility to fraud from clinical sites and “professional patients”. The relative ease of simulating Alzheimer’s diagnosis, coupled with inadequate oversight by Contract Research Organizations (CROs), creates fertile ground for deceptive practices. Poor rater quality and the simplicity of falsifying data exacerbate concerns.

A core difficulty is the diagnostic ambiguity of AD, where symptomatic overlap with other cognitive disorders often leads to misdiagnosis or feigned conditions by professional patients. This issue is intensified in small molecule studies, which are easier to replicate or substitute than biologics, increasing the temptation and feasibility of fraudulent activities. Lax monitoring and control by CROs contribute to these vulnerabilities, allowing unnoticed data manipulation and deceitful conduct. It is particularly alarming that sites most prone to deceitful practices include predominantly underrepresented populations, thwarting inclusion efforts.

Method

We critically analyze the inefficacy of regulatory audits in detecting and preventing fraud as clinical sites adeptly prepare regulatory documents to mask misconduct. We evaluate methods for detecting fraudulent practices based on the clinical data and clinical operations metrics.

Result

The absence of medical expertise among auditors limits their ability to discern data integrity issues and the nuances of AD symptomatology. Traditional data management review and statistical analysis methods fail to identify these types of issues.

Conclusion

We call for a reevaluation of current methodologies in AD clinical trials. We advocate for enhanced CRO oversight, improved rater training, and incorporation of medical expertise in audits. Targeted, blinded statistical data review can identify problematic sites. Addressing these challenges can safeguard AD research integrity, accelerate development of effective therapeutics, and protect and benefit vulnerable populations.
Determinants of hand grip strength among community dwelling older adults in southwestern Nigeria: Data from the VALIANT Study
Authors: Akinyemi Rufus O. , Olalusi Oludotun V , Akinyemi Tolulope O , Yaria Joseph O , Ogunde Gabriel O , Akinyemi Joshua O. , Lawlor Brian , Ogunniyi Adesola
Published: January 2025

Background

Hand‐grip strength (HGS) is known to be a surrogate marker of not only fitness and frailty, but of cognitive and cardiometabolic health. It is cheap, readily deployed and can be a valuable tool in resource‐limited settings. Little however is known about the determinants and correlates of HGS in sub‐Saharan Africa, where stroke and vascular cognitive disorders are projected to exponentially increase. We examined the determinants of HGS among older adults in a rural community in Ibadan, South West Nigeria.

Method

Vascular heAlth, fraiLty and cognition in Ageing Nigerians (VALIANT) Study is an ongoing longitudinal community‐based cohort study aimed at exploring the association between cardiovascular health, cognition and frailty in Nigeria. One thousand (1000) participants have so far been recruited (via a multistage, stratified cluster random sampling method) and have been taken through a battery of cardiovascular, cognitive and frailty assessment tools. Data on HGS, obtained using a digital hand dynamometer, was available for 480 men and women aged ≥50years. A multivariable adjusted linear regression analysis was used to assess the determinants of HGS. All associations were reported as coefficients with 95% confidence intervals (CI)

Result

The mean age was 64.5 (11.8) with 35% males. The mean HGS was higher among males (22.86 10.1) than in females (16.26 6.1) (p<0.001) and decreased with increasing age and in the left hand. Using the Rockwood frailty scale, 66 (13.8%) of the study participants were vulnerable to frail while 80% had cognitive impairment (MoCA <26). In the multivariable linear regression analysis, the independent determinants of hand grip strength with corresponding beta coefficients (95%CI) were attainment of tertiary/postgraduate education 5.19 (1.70; 8.68), being a widow/widower ‐2.75 (‐5.47; ‐0.03), lower MoCA score<19 ‐2.50 (‐4.42; ‐0.59) and higher IDEA‐IADL score 0.23 (0.02, 0.44)

Conclusion

Amongst older adults in rural Nigeria, attainment of tertiary/postgraduate education was independently associated with higher HGS; while being a widow/widower and presence of low cognitive reserve were independently associated with lower HGS. This study has identified unique determinants of HGS among West Africans.
Patterns of Association of Tau Across Cortical Regions Differ Between [18F]MK6240 and [18F]Flortaucipir
Authors: Hosseini Seyyed Ali , Rahmouni Nesrine , Therriault Joseph , Servaes Stijn , Tissot Cécile , Aumont Etienne , Arias Jaime Fernandez , Macedo Arthur C. , Wang Yi‐Ting , Stevenson Jenna , Lussier Firoza Z , Chan Tevy , Zheng Yansheng , Trudel Lydia , Gauthier Serge , Baker Suzanne L. , Pascoal Tharick A. , Rosa‐Neto Pedro
Published: January 2025

Background

This study aims to investigate the differential patterns of association in tau protein imaging across cortical regions using two distinct Tau imaging agents: [18F]MK6240 and [18F]Flortaucipir. The underlying hypothesis posits that variations in the properties of these tracers, such as affinity and off‐target effects, influence the observed patterns of association in neuroimaging.

Method

To test this hypothesis, a comprehensive study was conducted involving 104 subjects part of the HEAD study at McGill University: 53 cognitively normal (CN), 19 with mild cognitive impairment (MCI), 9 with Alzheimer's Disease (AD) and 23 non‐AD. A key methodological aspect of the study was the selection of seed cortical regions based on the highest standardized uptake value ratios (SUVR) obtained in population average images. These regions included the trans‐entorhinal area, parietal, posterior cingulate cortices, and two off‐target binding regions: the choroid plexus and substantial nigra. This approach allowed for a nuanced analysis of tracer associations in both target and off‐target regions.

Result

The results revealed notable differences between the two tracers. Specifically, [18F]MK6240 exhibited higher associations between cortical regions, with similar slopes in these associations across different areas. In contrast, the associations between the off‐target binding regions (Choroid Plexus and Substantia Nigra) and the established Braak regions were found to be non‐significant. This finding is particularly revealing, as it underscores the differential binding affinity and specificity of the two tracers.

Conclusion

In conclusion, the study substantiates the initial hypothesis by demonstrating that distinct tau tracers exhibit unique patterns of cortical associations, which can be attributed to their specific properties. This insight has significant implications for the interpretation of tau imaging in neurodegenerative diseases, particularly in AD. It highlights the necessity of considering tracer‐specific characteristics when analyzing neuroimaging data and suggests that a one‐size‐fits‐all approach may not be appropriate in the nuanced field of neuroimaging. The findings of this study pave the way for more refined and accurate diagnostic practices in neurology, particularly in the context of neurodegenerative diseases where tau protein plays a pivotal role.