bluuebunny/crossref_metadata_2025 huggingface dataset:
Sex‐Differences in the Association of 24‐h Blood Pressure Level and Variability with Subclinical Markers of Cerebral Small Vessel Disease
Authors: Garza Shana B , Charisis Sokratis , Patil Dhrumil , Vatcheva Kristina P. , Mejia‐Arango Silvia , Mena Luis Javier , Alliey‐Rodriguez Ney , Satizabal Claudia L , Chavez Carlos A , Gaona Ciro , Silva Egle , Lee Joseph H. , Terwilliger Joseph D. , Gutierrez Jose , Seshadri Sudha , Maestre Gladys E. , Melgarejo Jesus D
Published: January 2025

Background

High blood pressure (BP) level and variability has been linked to stroke, cerebral small vessel disease (CSVD), cognitive decline, and dementia. However, it is unclear whether sex/gender influences the association of BP level and variability with CSVD. Therefore, we aimed to examine sex‐differences in the association of CSVD with 24‐h BP level and variability.

Methods

We used 374 participants aged ≥40y from the Maracaibo Aging Study (women, 73.5%; mean age, 59.1y) who underwent 24‐h ambulatory BP monitoring and brain magnetic resonance imaging (MRI) scans. The 24‐h systolic BP variability was quantified as the average real variability (ARV) index. Markers of CSVD were visualized on MRI scans and included log‐transformed white matter hyperintensities (log‐WMH) volume, and the presence (yes/no) of lacunes, cerebral microbleeds (CMB), or enlarged perivascular spaces (EPVS). The association of 24‐h systolic BP level and variability with markers of CSVD was analyzed using adjusted logistic and linear regression separately for men and women.

Results

Overall, men had greater log‐WMH volume (median, 2.9 vs. 2.5 cm3) and higher proportion of lacunes (18.2% vs. 8.7%) than women (P≤0.011). The proportion of CMB and EPVS was similar between women and men (P≥0.522). A higher 24‐h systolic BP level was associated with log‐WMH in men (adjusted β‐coefficient, 0.37; 95% CI 0.08, 0.21) and women (adjusted β‐coefficient, 0.16; 95% CI, 0.01, 0.09) as well as the presence of lacunes in both groups (the OR for men was 2.31 [95% CI, 1.08‐4.95] and for women was 1.55 [95% CI, 1.02‐2.37]). Only in women, a higher 24‐h ARV systolic BP was associated with log‐WMH (adjusted β‐coefficient, 0.19; 95% CI, 0.02, 0.10), lacunes (OR, 1.81; 95% CI, 1.15‐2.84), and EPVS (OR, 1.67; 95% CI, 1.07‐2.60).

Conclusions

We found sex‐differences in the association 24‐h BP level and variability with markers of CSVD. In men, high 24‐h BP level had a greater impact on the burden of WMH and lacunes than in women whereas high 24‐h BP variability seems to be a risk for CSVD only in women. These results suggest the potential influence of sex in the relationship between vascular risk factors and CSVD.
Impacts of sex and ethnic background on the relationship between stress and hippocampal volumes
Authors: Stypulkowski Katie , Kaplan Nikki L , Levine Taylor F , Caldwell Jessica ZK
Published: January 2025

Background

Stress is known to have a negative impact on hippocampal volume (HCV) and convey higher risk for development of Alzheimer’s disease (AD). Previous research has established differences among older adults by racial/ethnic background in levels of stress (Brown, Mitchell, & Ailshire, 2020) and HCV (Bygrave et al., 2022). Further, women have been shown to retain brain volumes longer compared to men in the presence of other risk factors for AD (e.g., Cieri et al., 2022), but this research is primarily in non‐Hispanic White individuals (NHW). The purpose of this study was to examine the relationship between stress and HCV across a multiethnic cohort, with the hypothesis that sex would moderate the relationship.

Methods

Data from the Health & Aging Brain Study ‐ Health Disparities was used, including African American (AA; n = 482), NHW (n = 817), and Mexican American (MA; n = 727) older adults. Prior to statistical analyses, HCVs were corrected via proportion of total intracranial volume. Six moderation regression analyses were employed to examine effects of chronic stress on HCVs. The Chronic Stress Scale total score was the independent variable, right and left HCVs were dependent variables, and sex was the moderator. Age and education were covariates.

Results

There was a significant interaction between chronic stress and sex on right (t(711) = 2.53, p = .01) and left HCVs (t(719) = 2.57, p = .01) among MAs, such that MA men showed lower HCVs as chronic stress increased, while MA women showed no relationship, suggesting HCV resilience in the context of chronic stress. Sex did not moderate the relationship between stress and HCVs in NHW or AA groups.

Conclusions

Sex was found to moderate the relationship between stress and HCV among MAs, but not AAs or NHWs. MA men’s HCVs decreased as chronic stress increased, while MA women’s HCVs remained robust to high stress levels. MA men may be more vulnerable to the impacts of chronic stress in older age, suggesting chronic stress may be an important modifiable risk factor for AD in this group. Further work is needed to understand the impacts of stress as a risk for AD across various demographic groups.
The association of coronary artery calcium progression and cognitive function in midlife ‐ The Coronary Artery Risk Development In Young Adults (CARDIA) Study
Authors: Teramoto Masayuki , Hoang Tina D , Sidney Stephen , Terry James G. , Pletcher Mark J , Marcus Gregory M , Hoffman Thomas , Yaffe Kristine
Published: January 2025

Background

Little is known about the impact of coronary artery calcium (CAC) and its progression on cognitive function in midlife, a time of importance for cognitive aging.

Methods

In CARDIA, CAC was measured using computed tomography at years 15 (baseline), 20 and 25. CAC progression was defined as: (1) CAC>0 at follow‐up among participants with baseline CAC = 0; (2) an annualized change of ≥10 units at follow‐up among those with 0<baseline CAC<100; or (3) an annualized percent change (annualized change in CAC score divided by baseline CAC score) ≥10% among those with baseline CAC≥100. Cognitive function was measured with Digit Symbol Substitution Test (DSST), Rey Auditory Verbal Learning Test (RAVLT), Stroop Interference, Montreal Cognitive Assessment (MoCA) and Verbal Fluency (Letter and Category Fluency) at year 35. We used linear regression to estimate the difference between marginal means with 95% confidence intervals (CIs) of each cognitive test by CAC score (0 vs >0) and CAC progression.

Results

Among 2,341 participants (mean age 40.3 ± 3.6 years, 56% female, 43% Black at baseline), higher CAC score and CAC progression were associated with significantly lower cognitive performance in all cognitive tests. After adjustment for demographics, the association remained for CAC progression, compared to no progression, for most test scores: DSST (‐2.70 95% CI: ‐4.05 to ‐1.36, p < 0.001), MoCA (‐0.44 95% CI: ‐0.74 to ‐0.13, p = 0.005) and verbal fluency (‐0.85 95% CI: ‐1.57 to ‐0.12, p = 0.02). Similar associations were observed for higher CAC score (>0 vs 0): DSST (‐3.11 95% CI: ‐5.16 to ‐1.06, p = 0.003), MoCA (‐0.81 95% CI: ‐1.28 to ‐0.34, p = 0.001) and RAVLT (‐0.67 95% CI: ‐1.12 to ‐0.23, p = 0.003). Additional adjustment for physical activity, depressive symptoms, and APOE, and mutually for baseline CAC score and progression did not materially change the association.

Conclusions

CAC score and progression were associated with lower cognitive function in midlife. CAC progression may be an independent risk factor for early cognitive aging, independent of baseline CAC score and other risk factors.
Providing In‐Home Helmet‐Based 40 Hz Light Therapy for Alzheimer’s Patients in Memory Care Facilities in Detroit, MI: A Proposal for a Feasibility Study to Expand Early Efficacy Data
Authors: Bart Jacob A , Attar Zechariah
Published: January 2025

Introduction

Alzheimer’s disease is the most common and costly neurodegenerative disease worldwide. Early studies of helmet‐based 40 Hz light therapy have demonstrated safety and early efficacy in targeting the pathophysiologic characteristics of Alzheimer’s disease. This intervention has shown slowing and even reversal of disease progression. An extensive literature review has demonstrated this therapy to be cost‐effective and user‐friendly with minimal side effects. Implementation of this therapy has been limited by barriers to access, illustrated by small sample sizes and poor compliance in numerous studies. Further research with larger sample sizes is essential to accelerate the rate of translation from bench to bedside by addressing implementation barriers to access, thereby optimizing patient adherence.

Hypothesis

We hypothesize that offering helmet‐based 40 Hz light therapy in a home setting will result in increased enrollment of eligible patients and compliance by providing convenience to patients and their caregivers. This approach will develop implementation guidelines while expanding on existing efficacy data.

Objective

To explore our hypothesis, we plan to conduct a feasibility study by recruiting through, and providing care at, memory care facilities in Detroit, Michigan. Changing the location of care may be an easily adaptable implementation strategy that can be applied nationally. We’ve identified 50 memory care facilities that house Alzheimer’s patients, with capacity for over 400 residents in Detroit alone.

Methods

We plan to assemble a mobile team of research‐clinicians to administer helmet‐based 40 Hz light therapy. Scheduled weekly appointments can be facilitated at the convenience of the patients and their care providers across all facilities that allow this therapy for their residents. These participants will be recruited via rolling admission and outcomes will be evaluated using standardized neurocognitive assessments.

In summary, helmet‐based 40 Hz therapy has already been shown to be safe and effective. Studying the feasibility of implementing it in the patient’s home is an important next step in making this care accessible to those that need it most.
A Scoping Review of the Use of Non‐Fatty Acid Nutraceuticals for Chronic Inflammation in Persons with Alzheimer’s Disease
Authors: Patel Saajan , Basra Mahi , Shah Kriya , Caballero Joshua
Published: January 2025

Background

Reducing chronic inflammation has been linked to anti‐inflammatory foods and may be implicated in treating Alzheimer’s disease (AD). Plants produce antioxidants, such as phytochemicals, that appear to reduce the incidence of chronic inflammatory diseases. Phytochemicals may include active substances like polyphenols. Nutraceutical formulations may offer the advantage of combining specific types of phytochemicals with other nutrients to provide optimal efficacy while reducing adverse effects from consuming individual phytochemicals. The purpose of this scoping review was to assess the use of non‐fatty acid nutraceuticals on persons with AD.

Method

A literature search was performed using the databases PubMed, EMBASE and Medline 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”, “anti‐inflammatory diet”, “fiber”, “plant extract”, and “supplement”. The PRISMA guidelines guided the inclusion/exclusion process.

Result

After applying the inclusion/exclusion criteria, four out of 49 articles were identified and evaluated. Among nutraceuticals, selenium, carotenoid, combined metabolic activators, and boswellic acid have been studied in randomized controlled trials. Data using selenium (average dose: 0.32 mg tid) over 24 weeks increased selenate cerebrospinal concentrations but did not result in significant cognitive differences compared to placebo. A six‐month study with carotenoid supplementation showed 1‐palmitoyl‐2(5'‐oxo‐valeryl)‐sn‐glycero‐3‐phosphocholine (POVPC) levels, an oxidation marker, did not improve compared to placebo in patients with AD. A study using boswellic showed patients with AD had lower levels of plasma Aβ40 and suggested improved MMSE scores. Another study evaluating combined metabolic activators (CMAs) in AD patients showed the administration of CMAs suggested improvement in cognitive function. Limitations among the studies may include patient selection, short duration of trial, determining clinical significance, and assessing costs associated with using these products.

Conclusion

Overall, small, limited studies suggest mild improvements in cognitive function using non‐fatty acid nutraceuticals in persons with AD. Boswellic acid and CMAs may show the most promise. However, larger trials are warranted to confirm preliminary results.
Molecular chemiluminescence imaging of misfolded proteins with a versatile and highly sensitive probe in neurodegenerative disease models
Authors: Ran Chongzhao , Zhu Biyue
Published: January 2025

Background

Protein misfolding is a key pathological phenomenon driving neurodegenerative diseases that affect millions of people. Visualizing this misfolding process with smart imaging probes would greatly facilitate early diagnosis, etiology elucidation, disease progression monitoring, and drug discovery of neurodegeneration. Although numerous probes have been reported, several unmet needs still exist.

Method

In this study, we demonstrated that both generic and precise visualization of misfoldons could be achieved with a highly sensitive chemiluminescence probe, ADLumin‐1.

Result

For the generic aspect, we demonstrated that ADLumin‐1 was highly responsive when interacting with various misfoldons, including beta‐amyloid peptides, tau proteins, alpha‐synucleins, and TDP‐43, showing up to 128‐fold higher signal to noise ratio compared to gold standard dye Thioflavin T. Next, we explore the binding and the activating mechanism by molecular docking and proved ADLumin‐1 could non‐invasively visualize cerebral biomarker in transgenic mice models of Parkinson’s disease (PD), Alzheimer’s disease(AD) and amyotrophic lateral sclerosis (ALS). For the precise aspect, we explore the precise diagnostic value of ADLumin‐1 by using α‐synuclein, a key biomarker in PD. By combining with protein misfolding cyclic amplification (PMCA) technology, ADLumin‐1 enables selective detection of α‐synuclein in CSF at the femtomolar level. Finally, we showcased that ADLumin‐1 enables in situ monitoring of α‐synuclein misfoldons in transgenic mice by employing the bio‐orthogonal ChRET concept.

Conclusion

Taking the advantages of dual facets of generality and precision, our findings could be broadly applied in the preclinical and clinical studies of neurodegenerative diseases.
Visual Search Assessed with the Rowan Digital Cancellation Protocol
Authors: De Anda‐Duran Ileana , Bazzano Lydia , Urbina Elaine M. , Woo Jessica , Baliga Ganesh , Libon David J.
Published: January 2025

Background

With the advent of monoclonal antibody therapy to treat mild cognitive impairment and mild dementia due to Alzheimer’s disease (AD) there is a need to develop tests to screen for neurocognitive difficulty that are reliable and easily deployed.

Method

The Rowan Digital Cancellation Tests (RDCT) is comprised of three tests administered using an iPad Pro. Each test was preceded by a practice trial. During practice and test trials a buzzer sounded when commission errors were made. For each test, participants worked for 180 sec. Sixteen targets were located in each quadrant. Target items were embedded within a random array modeled after Weintraub (2000). The Digital Letter Cancellation Test asked participants to circle the letter “A”. The target for the Digital Symbol Cancellation was a geometric symbol. On the Digital Letter/Symbol Switching Cancellation test participants alternated first circling a specific letter, then a specific symbol. Five outcome variables were compiled including correct hits (range 0‐64), distance per correct hit; mean non‐motor/‘think’ time/hit; mean Apple pencil touch; and mean commission errors.

Result

A group of 21 community‐dwelling participants were assessed (age = 51.9±7.2; education = 14.9±2.0; White = 66%, female = 91.5%). A graded pattern of performance was seen for most outcome variables (Table 1) such that more targets were identified for letter>symbol>letter/symbol (p< 0.003), and mean distance traveled per target was less for letter<letter/symbol and symbol< letter/symbol (p< 0.001). Non‐motor/‘think’ time and mean Apple pencil touch increased contingent on task complexity letter<symbol<letter/symbol (p< 0.016, & p< 0.004, respectively). More commission errors emerged on the letter/symbol vs letter test condition (p< 0.002).

Conclusion

Among this sample of community dwelling, generally healthy participants, the RDCT was well‐tolerated. Preliminary data generally yielded graded pattern of performance based on test complexity. When brought to scale these tests could provide a reliable method to screen for neurocognitive decline among patients with neurodegenerative illness.
Engaging Sexual and Gender Minority Caregivers of Alzheimer’s and Related Dementias: The RISE Project
Authors: Flatt Jason D. , Anderson Joel G , Klenczar Brittany , Yamada Cody , Hancock Kari A. , Kittle Krystal R. , Wharton Whitney
Published: January 2025

Background

More than 6 million people in the U.S. are currently living with Alzheimer’s disease and related dementias (ADRD), and informal caregivers provide them with more than $270 billion annually in unpaid care. Few studies on ADRD caregiving have engaged caregivers from diverse sexual and gender minorities (SGM), or lesbian, gay, bisexual, transgender, queer, intersex, asexual, and/or another identity.

Methods

This study explores ways to engage and recruit diverse SGM ADRD caregivers into ADRD and aging‐related clinical research. We conducted focus groups and individual interviews with 25 SGM adults who were current, past, or prospective ADRD caregivers. Interviews explored barriers and facilitators to research participation, innovative recruitment strategies, SGM‐specific caregiver needs, and awareness of diverse types of aging and ADRD‐related research. We used thematic analysis to identify key themes.

Results

Caregivers’ ages ranged from 18‐78 years. In terms of race/ethnicity, 48% identified as White, 48% African American, 4% American Indian or Alaska Native, and 10% Hispanic/Latino. For relationships to their care recipients, most reported caring for a parent (47%), followed by a friend (18%), partner/spouse (12%), other relative (12%), or another relationship (11%). The majority provided care for more than a year (52%), followed by 17% providing care for less than a year and 30% expecting to provide care within the next year. We identified five initial themes around recruitment and engagement of SGM ADRD caregivers into research: (1) ensuring inclusion of those from diverse racial/ethnic backgrounds, (2) developing trust through relationship building, (3) safety and privacy measures necessary for SGM identity disclosure, (4) novel recruitment and engagement efforts (media, arts, entertainment), and (5) emphasizing how participating in research supports SGM progress toward equity.

Conclusions

We identified novel ways to recruit and engage diverse SGM ADRD caregivers into research. Future research should explore and test strategies to engage and enhance inclusion of racially/ethnically diverse SGM ADRD caregivers in ADRD research. There is also a need for additional novel strategies to effectively recruit and engage diverse SGM ADRD into research and identify solutions for addressing their health challenges and caregiving needs.
An Innovative Community‐led Education and Recruitment Program to increase Clinical Research Participation Among Black Americans
Authors: Niknejad Bahar , Gibson Ethlyn McQueen , Brown‐Hughes Travonia , McDonough Katie , Andrews Ebony , Hudson Deborah , Okhravi Hamid
Published: January 2025

Background

Previous studies attest to a lack of awareness about Alzheimer’s Disease (AD) and limited participation of Black Americans in AD clinical trials. The AHEAD Study is a multicenter trial focused on preventing AD by evaluating the effectiveness and safety of Lecanemab in individuals with preclinical AD. The study aims to recruit at least 15% from underrepresented populations, including Black Americans. To achieve this goal, our study site utilizes a community‐based participatory research (CBPR) approach and developed a Community Education and Recruitment Program (CERP) designed to increase the participation of Black individuals in the AHEAD Study.

Method

In a collaborative partnership between researchers at Eastern Virginia Medical School, Hampton University, a Historically Black College University (HBCU) and the Alzheimer’s Association of Southeastern Virginia, a Community Advisory Board and Ministerial Alliance, comprised of Black community leaders in Hampton Roads, Virginia was formed. The board has directed the development of our CERP. Two Black community health workers (CHW) were trained using an educational toolkit centered on increasing AD awareness and community recruitment for the AHEAD Study. Within our CERP, our team, comprised of faculties, Alzheimer’s Association trained volunteers and CHWs, conducted educational programs at various Black community venues, including senior centers, health fairs, civics events, fraternities/sororities, and church events like Purple Sunday programs. Study outcomes metrics include: attendance at outreach events, the number of attendees who signed up for the study, the number of participants prescreened, and the number of participants randomized into the AHEAD Study.

Result

As of January 2024, we have presented our program at 63 community events with over 6,300 attendees. We have held Purple Sunday luncheons and talks at over 18 Black churches in urban and rural localities in Hampton Roads. A total of 334 participants have signed up for the study, 180 have been prescreened, and 101 have passed the first phase of screening and 6 have been randomized in the AHEAD Study.

Conclusion

Partnering with key community stakeholders thru a community‐led education and recruitment program has proven to be highly effective in circumventing sociocultural barriers to research participation by members of underrepresented groups.
Behavioral estimates of recognition memory in Veterans with mild TBI at risk of Neurodegeneration
Authors: Morreale Kristina , Karaca Meltem , Chadalavada Myna , Waskow Emily , Hagan Brenna , DeCaro Renée , Anderson Natalie , Budson Andrew E. , Turk Katherine W.
Published: January 2025

Background

Loss of recognition memory has been hypothesized to be a potential behavioral marker of neurodegenerative disease given decreases in both recollection and familiarity reported in both MCI (Mild Cognitive Impairment) and AD (Alzheimer’s Disease). Stage III CTE (Chronic Traumatic Encephalopathy) involves p‐tau deposition in the medial temporal lobe, impacting memory. Decreases of both familiarity and recollection are promising potential markers of CTE related neurodegeneration following TBI (Traumatic Brain Injury). Decreases in recollection may act as an early marker of neurodegeneration following TBI in CTE, whereas familiarity may act as a later stage indicator of neurodegeneration.

Method

We collected behavioral data including memory measures, neuropsychological measures, head injury exposure, and standardized questionnaires. Veteran participants were recruited from VA Boston Healthcare System, N = 45.

Result

We analyzed initial behavioral data with specific focus on group levels of memory using receiver operator characteristics curves (see Figure 1). Pearson correlations were performed on groups with TBIs across their lifetimes to assess the linear relationship between a.) number of TBIs and familiarity r (43) = ‐.107, p < .001, b.) years since last TBI and recollection r (43) = ‐.107, p < .001, and c.) years since last TBI and familiarity r (43) = ‐.139, p < .001. A one‐way ANOVA was preformed to examine if groups differed in measures of recollection, familiarity, number of TBIs and years since last TBI. MCI + OTBI a.) group showed the worst recollection compared to young adults with TBI F(2,41) = 3.33, p = .046, b.) highest number of TBIs than older adults with TBI F( 2,41) = 3.65, p = .036, and c.) have more years elapsed as compared to all head injury groups F( 2,41) = 8.12, p = .001.

Conclusion

Our results reveal worsened memory in those with TBIs. Among all Veterans with TBI, increased number of TBIs were associated with worse familiarity performance. Participants with greater years since last TBI had worse familiarity and recollection performance. Between groups, the MCI participants with TBI (MCI+OTBI) exhibited the worst familiarity performance, highest number of TBIs, and longest time since head injury.
Cognitive Rehabilitation and Physical Activity for Early Dementia ‐ A Randomized Clinical Trial
Authors: Mandeep   , Khurana Dheeraj , Ray Sucharita , Arun Priti , Mishra Jyoti , Kaur Manreet , Kumar Ashok
Published: January 2025

Background‐

An estimated 8.8 million Indians older than 60 years have dementia. The increase in number of people living with dementia is causing difficultly to meet the need for care and support, particularly people with early‐stage dementia. Pharmacological treatments for dementia might not be effective or tolerated by all due to its possible side effects. Cognitive rehabilitation and physical activity may help preventing or slowing progression of dementia

Objective‐

To find efficacy of combined cognitive and physical intervention in improving the cognition in people with Mild Cognitive Impairment (MCI) and Early Dementia.

Methods‐

A randomised clinical trial was conducted among 60 patients with MCI and early dementia. The Intervention arm received Cognitive Rehabilitation and Physical Activity intervention along with Standard Care (n = 30) and Control arm received standard care (n = 30). Follow‐ up assessments were conducted at 1 month and 3 months. The primary outcome measure were attention, memory and executive functions. ADLs and IQCODE were the secondary outcomes. Descriptive statistics was used for statistical analysis using SPSS‐22 software.

Results

Among 60 randomized participants (mean age, 62.5 years; 70% male) 22 (73%) of intervention arm completed the cognitive retraining worksheets. At 1 month and 3 months, Intervention arm showed significant improvement in TMTB‐A, Category fluency, Phonemic fluency, Total learning and Spatial recall (mean difference ‐98.455, P = 0.00; 16.40, P = 0.00; 15.80, P = 0.00; 6.59, P = 0.00; 2.79, P = 0.002 at Fup 1 and ‐150.36, P = 0.00; 16.49 P = 0.00; 14.7, P = 0.00; 6.86, P = 0.00; 3.26, P = 0.002 at Fup 2). No statistically significant difference as fount in IADL and OQCODE.

Conclusions‐

In patients with MCI and early Dementia, Combined Cognitive and Physical Intervention in addition to Standard of Care may show improvement Attention, Memory and Executive Functioning.
Integrating Noninvasive Radiofrequency Monitoring Technology Into Clinical Decision‐Making
Authors: Bolstad Britni A , Johnson Brian B
Published: January 2025

Background

Across a broad range of physical and cognitive outcomes in gerontology and geriatric practice, it is fundamentally important to establish systems for clinical decision‐making. Current technological solutions include sensors for monitoring movement activity, however many of these methods are complex, invasive, and dependent on factors such as compliance, context, and idyllic conditions. An alternative approach to monitoring is through continuously active, noninvasive radiofrequency (NRF) sensors. Our hypothesis is that NRF sensors can be used to detect clinically relevant changes and support clinical decision‐making because they provide a more accurate and reliable method for monitoring movement activity than camera‐based systems and wearable sensors, thus the identification and progression of physical and cognitive decline could be measured through movement data and enhance the care management of older adults.

Method

NRF sensors are highly suited to optimizing supportive actions by clinicians and healthcare organizations. However, despite the interest in NRF systems, it is mostly absent from clinical context aside from research initiatives. Commercial technologies and technologies developed in research initiatives are often developed without a proper understanding of the specific needs of older adults or what clinicians consider useful. Our approach is to use NRF sensors and an algorithm library to identify changes in movement activity and inform clinical decision‐making thereby facilitating care management based on individual needs.

Result

Initial lab tests at the University of Minnesota showed the NRF sensor to be effective for monitoring falls in real‐time, movement activity, and resting states. These results suggest that NRF sensors could be used to measure clinically relevant changes among the older adult population.

Conclusion

NRF sensors may provide clinicians with pertinent data that would otherwise be inaccessible and help them to develop an individualized plan of care. With movement data, clinicians could further assess risk factors, monitor for adverse events, and detect physical or cognitive decline to improve care management. NRF monitoring technology is conceptualized as a means of better fulfilling the needs of older adults. Further research questions seek to evaluate the impact of using NRF sensors for quantitative monitoring, particularly within healthcare organizations.
A Decade‐Long Analysis of Dementia Incidence in Argentina: Insights from a Public Registry Study
Authors: Calandri Ismael Luis , Suemoto Claudia Kimie , Allegri Ricardo ,   Equipo de Estadística e Investigación social, Agencia Nacional de Discapacidad, Argentina
Published: January 2025

Background

Argentina is the second‐largest country in Latin America, home to 9% of the world’s Latino population. Like the rest of Latin America, it is grappling with the aging of its population and an increase in risk factors. Despite this, there are currently no studies on the incidence of dementia in the national territory. This study aims to present the current incidence rates and changes over the past decade for dementia in Argentina. Additionally, we explore sex‐specific and early‐onset dementia trends.

Methods

Utilizing 10‐year data from the “National Disability Registry,” a comprehensive national database offering specialized health coverage, we identified cases certified by an interdisciplinary board. Dementia subjects were defined as those with mental disability onset post‐18 years, with etiological diagnosis as per the ICD‐10 code for dementia causes. We calculated age‐standardized incidence rates per 100,000 inhabitants using population projections based on the 2010 and 2022 national censuses. To explore incidence time trends, we fitted linear models to predict incidence, considering time and sex as covariates.

Results

In 2023, Argentina exhibited an age‐standardized incidence of 25.3 new dementia cases per 100,000 inhabitants (19.1 for men and 31.1 for women). (Table 1, Figure 1) A significant increase in incidence (p = 0.029) was observed over the 10 years (yearly effect: beta = 0.14, 95% CI [0.02, 0.26]) (Figure 2), with no significant sex‐specific impact on incidence evolution (p = 0.8). Early‐onset dementia reported an incidence of 5 per 100,000, contrasting with late‐onset dementia at 26.1. Late‐onset dementia displayed significant growth compared to early‐onset cases (p = 0.07).

Conclusion

The increasing dementia incidence in Argentina emphasizes the urgent need for targeted interventions. Although there is no differential growth in incidence between men and women, women consistently exhibit a higher occurrence. Early‐onset dementia, traditionally associated with genetic predisposition, has remained stable. In contrast, late‐onset dementia has surged recently, likely due to the aging of the population and the rise in modifiable risk factors reported by other regional studies. These findings serve as a call to action, emphasizing significant regional prevention potential.
Plasma and MRI biomarkers predict post‐mortem tau pathology
Authors: Hu Mingzhao , Moloney Christina M. , Przybelski Scott A. , Algeciras‐Schimnich Alicia , Fought Angela J. , Rothberg Darren M. , Nguyen Aivi T. , Reichard Ross R. , Dickson Dennis W. , Knopman David S. , Jack Clifford R. , Petersen Ronald C. , Mielke Michelle M. , Graff‐Radford Jonathan , Murray Melissa E. , Vemuri Prashanthi
Published: January 2025

Background

Imaging and plasma markers are used as key indicators of disease for Alzheimer’s disease (AD) but their usefulness in predicting regional tau pathology is relatively understudied. Our objective was to construct predictive models for regional tau pathology measured on postmortem brain tissue using multiple ante‐mortem AD biomarkers. We focused on hippocampal and parietal regions that were immunostained with AT8 and 2E9 that reflect early and advanced aspects of tangle maturity, respectively.

Methods

Using autopsy data from 63 participants enrolled in the Mayo Clinic Study of Aging (MCSA) where the last clinical visit is within three years of death, we analyzed three ante‐mortem plasma markers ‐ phosphorylated tau protein at the threonine 181 residue, glial fibrillary acidic protein, total β‐amyloid Aβ42 relative to Aβ40 ratio (Quanterix Simoa HD‐X Analyzer), and three regional MRI markers computed using SPM12 ‐ parietal thickness, parietal volume relative to total intracranial volume ratio, and hippocampal volume adjusted for total intracranial volume. Based on eight separate cross‐sectional linear regression models weighted by the inverse of time from last visit to death, we estimated the multiple and partial R2 predicting post‐mortem pathology measures, including AT8 and 2E9 in both the hippocampal and parietal regions. All models were adjusted for age, sex, and cardiovascular and metabolic conditions score.

Results

The MRI models (R2 of 0.26‐0.53) had greater predictive power compared to the plasma models (R2 of 0.17‐0.26). The best multiple R2 was 0.53 for prediction of hippocampal AT8 using antemortem hippocampal volume adjusted for total intracranial volume followed by R2 of 0.43 for prediction of hippocampal 2E9 using hippocampal volume adjusted for total intracranial volume. Though the model prediction of parietal AT8 and 2E9 measurements was low (R2 of 0.21‐0.26), parietal thickness exhibited better predictive performance than parietal volume relative to total intracranial volume ratio.

Conclusions

The data we presented here may be utilized to validate biomarkers using regional pathology. Our results support that regional MRI is sensitive to tau pathology. Newer MRI methods should be tested to examine the specificity of newer quantitative measurements to tau pathology.
Identification of cross‐diagnostic protein signatures and subtypes of neurodegenerative diseases using multi‐task deep learning on the UK Biobank proteomics dataset
Authors: Gargas Tomasz , Hou Liping , Wrzesinski Tomasz , Wojtowicz Konrad , Kowalska Marta , Kamuda Malgorzata , Jetka Tomasz , Whelan Christopher D , Smets Bart
Published: January 2025

Background

Neurodegenerative diseases are a heterogeneous group of illnesses. Differences across patients exist in the underlying biological drivers of disease. Furthermore, cross‐diagnostic disease mechanisms exist, and different pathologies often co‐occur in the brain. Clinical symptoms fail to capture this heterogeneity. Molecular biomarker‐driven approaches are needed to improve patient identification & stratification with the aim of moving towards more targeted patient treatment strategies.

Method

The UK Biobank Pharma Proteomics Project has generated a proteomics dataset of unprecedented size. It consists of plasma proteomic profiles measured using the Olink 3k protein panel from over 54,000 individuals, complemented with broad phenotypic & genetic information. It is a unique resource to explore the biological correlation between neurodegenerative diseases as well as with other indications. We applied a multi‐task deep learning (MTL) approach to generate models that predict disease status based on plasma proteomics profiles for a broad range of indications, including neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. The MTL approach first learns fundamental biological patterns by knowledge sharing between diseases in the initial segment of the network. Subsequently, understanding of a specific indication is refined with dedicated training. This improves model generalizability and statistical power. The neural network also produces low‐dimensional embeddings of proteomic profiles that can be used for sample clustering and to derive insights about disease‐associated processes.

Result

The average precision‐recall area‐under‐the‐curve (PR‐AUC) of the MTL models across all diseases is 0.72 vs. 0.67 for the baseline single task logistic regression models. For Alzheimer’s disease, the MTL classifier has a PR‐AUC of 0.76. Feature importance scores were calculated using the SHAP method. Top features for Alzheimer’s disease included several known biomarkers (e.g., GFAP, NPTXR). A UMAP projection of all diseases using the feature importance scores clusters diseases by disease category. Sample clustering revealed biologically interpretable patient subgroups, such as a Parkinson’s cluster linked to lysosomal biology.

Conclusion

High performance of the MTL approach signifies good characterization of cross‐disease biology. This is corroborated by the model’s capability to produce meaningful low‐dimensional representations of plasma proteomics profiles that can be used for identification of cross‐diagnostic protein signatures and subtypes of neurodegenerative diseases.

UKB application number 65851.
Prediction of amyloid and tau status in nondemented older adults using tree‐based ensemble models
Authors: Seo Younghoon , Oh Hwamee
Published: January 2025

Background

Predicting amyloid and tau status in nondemented older adults with AD pathologies using more affordable and accessible measures can facilitate clinical trials by reducing the screen failure rate. The goal of the present study was to develop tree‐based ensemble models to predict PET‐based amyloid and tau burden using non‐invasive measures.

Method

Two datasets, amyloid (Aβ; n = 1062) and tau (n = 410), from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were used to predict the biomarker load in the subjects with normal cognition and mild cognitive impairment. Amyloid PET with the [18F]Florbetapir tracer was used as the gold‐standard measure for binary amyloid status classification), while tau PET with the [18F]Flortaucipir tracer was used for the three‐stage (low, intermediate, and high) determination. We trained random forest (RF), extreme gradient boosting machine (XGBoost), and light gradient boosting machine (lightGBM) models using different combinations of demographic, neuropsychological, APOE genotype, and volumetric MRI data, and measured the model performance using area under the receiver operating curve (AUROC).

Result

The performance of baseline model with demographics showed modest performance for Aβ (RF = 0.665, XGB = 0.650, LGBM = 0.659). Subsequent additions of features improved the predictive performance, with the model using demographic data, cognitive data, and volumetric MRI measures demonstrating the highest performance (RF = 0.762, XGB = 0.763, LGBM = 0.761). Meanwhile, the baseline model achieved modest performance for the three‐stage tau classification (RF = 0.643, XGB = 0.654, LGBM = 0.643), and the further addition of features improved the performance, with the feature combination of demographic data, cognitive, volumetric MRI measures, and continuous Aβ PET SUVRs achieving very good performance (RF = 0.799, XGB = 0.801, LGBM = 0.800). SHAP summary plots showed that age, entorhinal cortex volume, and neuropsychological and functional measures were important for Aβ classification, while Aβ load, high global cognition scores, hippocampal and middle temporal gyrus volume were shown to predict tau status.

Conclusion

Without using amyloid and tau PET, tree‐based ensemble machine learning models predict amyloid and tau status among nondemented older adults with modest to very good performance and could be incorporated for future clinical trials.
Analysis of Lifestyle‐Related Risk Factors in Stroke Patients
Authors: Nam Sanghun , Lim Young Myoung , Kim Ah‐Ram , Lim Seungju , Park Ji‐Hyuk
Published: January 2025

Background

Previous research has predominantly examined life satisfaction in stroke patients as a singular variable, overlooking its multidimensional nature encompassing health, income, spouse, and child satisfaction. To address this research gap, our longitudinal study utilizes survival analysis to investigate how various aspects of life satisfaction are influenced by diverse lifestyle factors.

Method

We employed data from the Korean Longitudinal Study of Aging (2010‐2020), specifically focusing on stroke patients who survived from 2010 to 2020. Dependent variables included health, income, spouse, and child satisfaction. Lifestyle factors encompassed health behavior, health status, and social interactions, while Cox regression analysis incorporated control variables such as age, sex, education, and residential area.

Result

Exercise demonstrated the highest hazard ratio (HR) in child satisfaction (HR = 2.111, CI = 1.04‐4.31), while health screening exhibited the highest HR in health satisfaction (HR = 1.489). Depression had the highest HR in child satisfaction (HR = 6.343, CI = 2.67‐14.98). The lowest HR in child satisfaction was observed for BMI (HR = 0.500, CI = 0.27‐0.94), whereas diabetes showed the highest HR (HR = 1.800, CI = 1.05‐3.08). Employment status had the highest HR in health satisfaction (HR = 1.678, CI = 1.68‐1.01), with no significant differences in other variables.

Conclusion

Our study delves into the complex dynamics of the relationship between lifestyle factors and the various dimensions of life satisfaction among stroke patients. Through meticulous examination, we unravel the intricate connections that exist within this association.
Association between brain tau deposition and default mode network connectivity in cognitively normal older adults
Authors: Cha Woo‐Jin , Yi Dahyun , Chumin Evgeny J. , Byun Min Soo , Jung Joon Hyung , Ahn Hyejin , Kim Yu Kyeong , Lee Yun‐Sang , Kang Koung Mi , Sohn Chul‐Ho , Risacher Shannon L. , Sporns Olaf , Nho Kwangsik , Saykin Andrew J. , Lee Dong Young ,   KBASE Research Group
Published: January 2025

Background

Alzheimer’s disease (AD) pathology occurs in the brain before manifestation of significant cognitive decline. Growing evidence suggests that brain networks such as default mode network (DMN) or salience network, identified through resting‐state functional magnetic resonance imaging (MRI), are affected by AD pathology. In this study, we investigated the relationship between network segregation and the key in vivo AD pathologies including beta‐amyloid (Aβ) and tau deposition in old adults with no cognitive impairment.

Method

A total 283 older adults with normal cognition aging from 55 to 87 were recruited from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s Disease (KBASE) cohort. The participants underwent comprehensive clinical and neuropsychological assessment, [11C] Pittsburgh Compound B PET for measuring Aβ deposition, [18F] AV‐1451 PET for measuring tau deposition, structural MRI, and resting‐state functional MRI for measuring functional connectivity (FC). For PET scans, standard uptake value ratio (SUVR) was used for the analyses; combined regions of inferior cerebellum and pons were used as the reference region when obtaining SUVRs. For FC, segregation values (ratios between median z‐transformed Pearson correlation of within‐ and between‐network connectivity) for overall and the seven individual resting state networks were computed (Table). The relationships between Aβ or tau deposition and network connectivity segregation were examined through cross‐sectional approach using multiple regression analyses. In the analyses, Aβ or tau deposition was used as an independent variable and segregation values of the networks were used as dependent variables.

Result

Tau deposition had a significant negative association with the DMN segregation (β = ‐0.249, p = 0.007); but, tau had no relationships with any other networks (Table). Aβ deposition was not associated with any segregation values for the seven brain networks (Table).

Conclusion

Our finding suggests that impaired functional connectivity of DMN is closely linked to tau deposition even in cognitively unimpaired older individuals.
Assessment of AI‐generated digital twin (DT) methodology on reduction of treatment effect variance and potential clinical trial sample size saving using a Phase 2 trial dataset from patients with Alzheimer’s disease (AD)
Authors: Wang Deli , Florian Hana , Yu Lynch Shau , Robieson Weining Z , Wang Li , Zhong Sheng , Xing Yunzhao , Zhuang Run , Kusiak Coco , Millar Stefanie , Turner Michelle , Ross Jess , Walsh Jonathan R. , Begany Katelyn , Graff Ole
Published: January 2025

Background

In Alzheimer’s Disease (AD) trials, clinical scales are used to assess treatment effect in patients. Minimizing statistical uncertainty of trial outcomes is an important consideration to increase statistical power. Machine learning models can leverage baseline data to create AI‐generated digital twins – individualized predictions (or prognostic scores) of how each patient’s clinical outcomes may change during a trial assuming they received placebo. Incorporating prognostic scores into trial design and analysis as a covariate increases statistical power, or reduces sample size, in Phase 2 and 3 trials (Figures 1/2). We assessed these properties using data from a Phase 2 clinical trial of tilavonemab in patients diagnosed with early AD (NCT02880956) and digital twin (DT) methodology (PROCOVATM).

Method

In a double‐blind, Phase 2 trial (AWARE), 453 patients aged 55‐85 years with early AD (met NIA‐AA clinical criteria for mild cognitive impairment or probable AD), were randomized to receive placebo or 1 of 3 doses of tilavonemab (1:1:1:1 ratio) over a 96‐week treatment period. Prognostic scores were produced for the change from baseline (Δ) in Clinical Dementia Rating Scale Sum of Boxes (CDR‐SB) and the Δ in AD Assessment Scale‐Cognitive Subscale 14 (ADAS‐Cog 14). Sample size savings were calculated from partial Pearson correlations (controlled for treatment) between prognostic scores and trial outcomes. Variability reductions were assessed using a covariance modelling approach that adjusts for the prognostic score (PROCOVATM).

Result

For Δ CDR‐SB and Δ ADAS‐Cog 14 at Week 96, standard deviations of the prognostic scores were lower than the trial’s outcomes. Partial correlation coefficients were moderate for both Δ CDR‐SB (p = 0.360) and Δ ADAS‐Cog 14 (p = 0.305) at Week 96. Total residual variance for both outcomes was reduced by ∼11% with DT methodology compared to an unadjusted model.

Conclusion

Depending on correlations between prognostic scores and actual trial outcomes, a potential overall sample size reduction of 5‐10% could be achieved using DT methodology (PROCOVATM) while maintaining statistical power, based on Δ CDR‐SB and Δ ADAS‐Cog 14 in the AWARE study. Sample size savings could enable shortening of the recruitment period and reduce the number of patients on placebo, encouraging greater patient participation.