bluuebunny/crossref_metadata_2025 huggingface dataset:
Drug Substitution as a Potential Unintended Consequence of Antipsychotic Deprescribing in Long‐Term Care: A Retrospective Cohort Study in Ontario, Canada
Authors: Kirkham Julia G , Harris Daniel A , Nguyen Paul , Bronskill Susan E , Maxwell Colleen J , Iaboni Andrea , Chowdhury Mohammad Z I , Seitz Dallas
Published: January 2025

Background

The overuse of antipsychotics in persons with dementia in long‐term care (LTC) has been a source of clinical concern, public attention, and policy intervention for over 30 years. Targeted quality improvement, broader awareness of risks, and other initiatives have resulted in substantial reductions in antipsychotic use in LTC settings in North America and elsewhere. Limited evidence suggests that reductions in antipsychotic use may be resulting in unintended consequences, such as substitution with alternate, but similarly harmful, psychotropic medications.

Methods

We used a retrospective, matched cohort study design using linked population‐based health care databases held at ICES. LTC residents 66 years or older with dementia who were prescribed an inappropriate (i.e., without an indication aligning with the definition of appropriate antipsychotic use in LTC, including schizophrenia, Huntington’s disorder, hallucinations, delusions, or end‐of‐life care) antipsychotic medication with at least 6‐months of continuous use were identified over a 10‐year period (2008‐18). Antipsychotic users who subsequently discontinued an antipsychotic medication were matched 1:1 to persistent users on key variables and followed for up to 1‐year following antipsychotic discontinuation for new prescriptions of one or more psychotropic medications and clinical outcomes.

Results

Among 26,092 LTC residents with dementia (mean age of 84 years) who were prescribed an inappropriate antipsychotic medication, 5,854 (22%) discontinued during the follow‐up period. After adjusting for key variables, new psychotropic medication prescription was not more common among antipsychotic discontinuers in the 6‐months following antipsychotic discontinuation compared to those who continued an antipsychotic medication (hazard ratio (HR) 0.90; 95% CI, 0.70‐1.15). Mortality was similar between the two groups (HR 1.01; 95% CI 0.90‐1.15) at up to 1‐year following antipsychotic discontinuation.

Conclusion

Antipsychotic discontinuation in this study was not associated with medication substitution. These results supports other studies indicating that antipsychotic discontinuation in dementia can be safe but has questionable effect on mortality. While medication use trends in LTC have shown increases in other psychotropic medication use alongside antipsychotic reductions, this study suggests that this may be driven by factors other than substitution, such as increasing complexity of LTC residents, including higher prevalence of mental health disorders other than dementia.
Association of Polysomnography‐Assessed Sleep Parameters with Alzheimer’s Disease Biomarkers in Older Adults
Authors: Chen Jiong , Cavaillès Clémence , Jin Jiangli , Stankeviciute Laura , Winer Joseph R. , Gao Song , Peng Dantao , Leng Yue , Milton Sasha
Published: January 2025

Background

over the past decade, a bi‐directional relationship between sleep and Alzheimer’s disease (AD) has been increasingly recognized, with several studies suggesting a link between self‐reported sleep disturbances and AD biomarkers. However, the association between polysomnography (PSG)‐assessed sleep parameters and AD biomarkers remains unknown.

Method

We examined 128 participants [mean age 70.9 (±9.7) years, 43.8% of men; 23 healthy controls (HC), 41 with mild cognitive impairment (MCI), and 64 with AD] from an outpatient memory clinic. Sleep features were derived from overnight PSG and were categorized by tertiles. Four AD biomarkers were measured, including tau‐181, Brain‐Derived Neurotrophic Factor (BDNF), and neurofilament light (NFL) obtained from blood samples, and Aβ levels measured from amyloid positron emission tomography scans. We used multivariable linear regression models to examine the associations between sleep parameters and AD biomarkers.

Result

After adjustment for age, sex, APOE4 status, diabetes, smoking habits, and body mass index, participants in the highest tertile of rapid eye movement (REM) latency (>192.7 minutes) had higher tau‐181 (β = 0.25, 95% confidence interval (CI) = 0.01;0.55) and Aβ (β = 0.15, 95% CI = 0.06;0.26) levels, and lower BDNF (β = ‐0.51, 95% CI = ‐0.70;‐0.20) compared to the lowest tertile (< 98.2 minutes). Moreover, participants in the middle slow wave sleep (SWS) percentage tertile (2.5‐10.2%) had lower tau‐181 levels (β = ‐0.18, 95% CI = ‐0.34;‐0.02) compared to those in the lowest tertile (< 2.5%). We did not find any association between AD biomarkers and sleep duration, efficiency, latency, or other sleep macro‐architecture features. The association between sleep and AD biomarkers did not differ by cognitive diagnoses (i.e., NC, MCI, or AD).

Conclusion

Longer REM latency was associated with higher levels of AD biomarkers in older adults with and without cognitive impairment. Future research is needed to examine the longitudinal association between sleep architecture and AD biomarkers and clarify underlying mechanisms.
The Associations of Self‐perception and Personality with Incident Dementia: The Health and Retirement Study, 2010‐2020
Authors: Wei Jingkai , Lohman Matthew , Zhang Yanan , Yang Chih‐Hsiang , Merchant Anwar T , Friedman Daniela B.
Published: January 2025

Background

Self‐perception and personality may play an important role in the development of dementia through lifestyle modification, social engagement, and mental well‐being. However, evidence regarding the associations of self‐perception and personality with incident dementia has not been well established.

Method

A total of 14,099 participants aged 50 years and older in the Health and Retirement Study (7,335 in 2010 and 6,764 in 2012) were included. They were measured for characteristics of self‐perception and personality using a validated self‐administered questionnaire. This included assessments of anxiety, anger (including anger‐in and anger‐out), five personality traits (neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness), self‐perception of aging, positive and negative affect, sense of control (including perceived constraints and personal mastery), loneliness, hopelessness, optimism and pessimism, cynical hostility, and life satisfaction. Incident dementia through 2020 was self‐reported via questionnaire. Proportional hazards models were used to examine the associations of each component of self‐perception and personality with incident dementia, adjusted for age, sex, race, education, smoking status (current, former, never), physical activity (≥1 time of moderate and/or vigorous physical activity per week), body mass index, depressive symptoms, and prevalent diseases (hypertension, diabetes, heart disease, stroke). Death was considered a competing risk. Subgroup analyses were conducted by sex and race.

Result

After an average follow‐up of 6.9±3.1 years, a total of 590 (4.5%) incident dementia cases occurred. Higher levels of anxiety, anger‐out, neuroticism, negative affect, sense of constraints, loneliness, hopelessness, pessimism, and hostility were associated with a higher risk of dementia. In contrast, higher levels of conscientiousness, openness, positive self‐perception of aging, positive affect, sense of mastery, optimism, and life satisfaction were associated with a lower risk of dementia. Modification of some factors was observed across different subgroups based on race and/or sex (Table 1).

Conclusion

Self‐perception and personality are predictive of incident dementia. Individuals with unfavorable self‐perception and personality profile, indicating a higher risk of dementia, may be monitored for risk reduction.
AI‐based dementia risk prediction using voice digial biomarkers: A web‐based platform
Authors: Ko Hyunwoong , Park Nayoung , Kwon Sukbong
Published: January 2025

Background

Dementia is a major public health problem affecting millions of people worldwide. Early diagnosis and intervention are essential to improve quality of life and reduce the burden of dementia. Recently, voice digital biomarkers have emerged as a promising approach for the early detection of dementia owing to its clinical utility and accessibility.

Method

In this study, we present a voice biomarker‐based dementia prediction system using a Korean dataset from the AI hub entitled cognitive disorder diagnostic speech/dialogue. A total of 5,769 voice recordings were obtained, of which 2,424 were from CN, 1,611 from MCI, and 1,734 from AD, and were recorded during the administration of cognitive tests. We first extracted dementia‐related speech biomarkers using signal processing and speech activity detection. The extracted speech biomarkers were then used to predict the Clinical Dementia Rating (CDR) to discriminate the severity of dementia from the dataset using ML/DL framework. We also developed an automated engine to extract the voice biomarkers and predict the CDR. The engine was deployed using Docker containers and a web service was implemented using the Flutter framework.

Result

The results showed that the proposed system achieved a CDR prediction accuracy of 83.6% and precision of 0.872. This is comparable to the accuracy of other voice biomarker‐based dementia prediction systems developed using Western datasets. A Flutter‐based web service is shown in the attached figure.

Conclusion

The proposed system is a promising new approach for early detection of dementia. It is easy to use, accessible and inexpensive, making it a potential tool for widespread use. The system could be used to screen large numbers of people for dementia, potentially leading to earlier diagnosis and intervention. In addition, the use of a low‐language digital voice biomarker makes the system more accessible to people from different linguistic backgrounds. This could help to reduce inequalities in dementia detection and care. In the future, we plan to add a variety of predictive models, including depression and Parkinson's disease. More detailed information, including a published web site, will be released through the AAIC 2024 poster session.
How well does the RAQ measure up? Assessing attitudes toward research in a diverse community sample
Authors: Gooding Diane Carol , Boykin C. Malik , Bouges Shenikqua , Van Hulle Carol A. , Lewis Jordan P. , Zuelsdorff Megan L. , Carter Fabu P. , Gleason Carey E.
Published: January 2025

Background

Individuals’ attitudes toward research predict recruitment, engagement, and retention. The Research Attitudes Questionnaire (RAQ), developed to predict individuals’ willingness to participate, is often used in AD research. It can be used to identify strategies to mitigate individuals’ reluctance to engage in research. To date, there are mixed findings regarding diverse groups’ willingness to engage in AD research. Between‐group comparisons are only meaningful and valid when the measures being used reflect true group differences in the construct i.e., measurement invariance (MI). One of the prerequisites for meaningful comparisons across diverse groups is to have measurement invariance. The study goal was to examine the suitability of the RAQ across age and ethno‐racialized identities.

Methods

We explored the MI of the 7‐item RAQ using Confirmatory Factor Analysis (CFA) via Mplus in a community‐derived sample of 457 younger and 594 older African American, 307 younger and 339 older American Indian/Alaska Native, and 173 younger and 679 older Non‐Hispanic White male and female individuals. CFA evaluated the one‐factor model across the groups. Subsequently, loadings, means, and residuals were consecutively constrained to equality. We examined whether the increased restrictions produced significant changes in the data‐model fit to determine whether conditions were met to demonstrate varying levels of measurement invariance.

Results

Table 1 summarizes sample demographics and provides mean total RAQ scores. The RAQ showed good internal consistency across age and ethno‐racialized groups (Cronbach’s a ranging from 0.78 to .85). A one‐factor model showed acceptable fit across the groups (Table 2). The results of the cross‐sample invariance tests are provided in Table 3. We found evidence of configural invariance; comparisons of successive models supported metric invariance, and scalar invariance. Strict invariance was not supported.

Conclusions

These data suggest that across the 6 groups, who differed in terms of age and ethno‐racial identity, the strengths of associations between the specific scale items and the latent construct being assessed by the RAQ are the same. However, the groups may differ in the extent to which they are characterized by the latent variable. This finding supports the suitability of the RAQ for cross‐cultural comparisons of willingness to engage in research.
Does six months of structured group exercise improve physical activity, sedentary behavior, and sleep in people living with dementia? A pilot randomized controlled trial
Authors: Oke Olabamibo , Dong Yanbin , Zhu Haidong , Soares Andre , Patel Charmi , Hergott Colleen , Waller Jennifer L , Young Lufei , Robinson‐Johnson Dawnchelle , Sams Richard , Hamrick Mark , Jehu Deborah A
Published: January 2025

Background

People living with dementia (PWD) often have inactivity‐induced muscle atrophy, increased sedentary behavior, and circadian rhythm disorders. Exercise may improve physical activity, sedentary behavior, and sleep in PWD, but further research is needed. The purpose of this pilot randomized controlled trial (RCT) was to examine whether a structured exercise program improves physical activity, sedentary behavior, and sleep in PWD.

Method

PWD were randomized (1:1) to exercise (n = 21) or usual care (n = 21) at two residential care facilities (NCT05488951; age = 82.1±8.05 years; Montreal Cognitive Assessment (MOCA) = 10.2 points; female = 35.7%; mobility device = 61.9%). Participants wore an actigraphy monitor on their non‐dominant wrist for 7 days (minimum of 4 days to be included in the analysis) at baseline and 6 months. The adapted Otago Exercise Program involved a physical therapist‐led strength, balance, and walking program for 1 hour, 3x/week for 6 months in groups of 5‐7. We controlled for age, race, sex, and the MOCA in the intent‐to‐treat (ITT; n = 42) and per protocol analyses (PPA; n = 21 usual care; n = 9 exercisers with 2/3 adherence).

Result

The ITT analysis revealed that the exercise group (pre = 78.8%, post = 83.7%) had a greater percentage of sedentary activity than the usual care group (pre = 68.2%, post = 67.7%) at 6 months (p = 0.01). The PPA disclosed that the average length of sedentary bouts decreased in the usual care group (pre = 22.2, post = 20.1 minutes) compared to exercise group (pre = 46.9, post = 54.1 minutes) from baseline to 6 months (p = 0.01). Adherence to wearing the actigraphy monitor for ≥4 days was poor (pre: n = 25/42 PWD, post: n = 13/42 PWD).

Conclusion

This RCT provides insufficient evidence to suggest that exercise impacts physical activity, sedentary behavior, or sleep among PWD. The results suggesting that usual care improves sedentary behavior over exercise should be interpreted with caution because this is a pilot RCT and adherence to wearing the actigraphy monitor was poor in both groups due to cognitive impairment. Future work is still needed to determine the effects of exercise on physical activity, sedentary behavior, and sleep, and should consider alternative placements of the actigraphy monitors, such as the back or lower leg, to increase adherence.
Decision‐Making Competence in Health Behavior Among Rural Older Adults with Cognitive Decline
Authors: Park Myonghwa , Kim Heejung , Kim Jinju , Seo Eunkyung , An Wonmi
Published: January 2025

Background

The aging population in rural areas is a unique health challenge. Older adults with cognitive decline are particularly vulnerable due to limited access to medical resources and health‐related information, a disparity more pronounced in rural compared to urban settings. This study investigates key factors influencing perceived decision‐making competence for health behavior in this demographic.

Method

This study was conducted as a secondary analysis of data from a larger health promotion project in a rural area of South Korea. The data of 170 older adults, aged 60 and above was analyzed. These individuals were identified as having suspected cognitive impairments based on the 10‐item cognitive function screening test. The study focused on assessing various factors such as cognitive function, social support, quality of life, and perceived decision‐making competence for health behaviors.

Result

The assessment of decision‐making competence for health behavior was conducted using a scale ranging from 1 to 5, with the mean score being 3.03 ± 0.66. Detailed analysis showed varying levels of competence across different health behaviors: regular exercise (2.54±1.13), healthy diet (2.92±1.05), brushing teeth (2.87±1.19), regular health checkup (3.05±1.09), infection prevention (3.48±1.10), social activity (3.45±1.11), and health education participation (2.91±1.01). This revealed a pattern where participants showed lower competence in areas requiring more active engagement, like regular exercise, and higher competence in more passive or socially facilitated behaviors like infection prevention and social activity. Furthermore, a positive correlation was observed between the levels of social support, the quality of life (as measured by the EQ‐5D), and the decision‐making competence for health behaviors.

Conclusion

The study’s findings highlight significant variations in decision‐making competence among rural older adults with cognitive decline, influenced by the type of health behavior and the level of social support and quality of life. These insights emphasize the need for tailored health promotion strategies that consider these variables. Future research should aim to deepen the understanding of these relationships, particularly by comparing this group with older adults without cognitive impairments or in urban area. and exploring the causal factors behind different levels of decision‐making competence.
Mortality associated with seizures in dementia
Authors: Zawar Ifrah
Published: January 2025

Background

Seizures are a common co‐morbidity of dementia and are associated with accelerated cognitive decline. However, the impact of recurrent versus remote seizures on mortality outcomes in people with dementia (PWD) has not been studied. The purpose of our study is to fill this knowledge gap.

Method

This longitudinal, multicenter study is based on participants recruited from 39 Alzheimer’s disease Centers in the US from 9/2005 –12/2021. The effect of recurrent or active seizures (over the preceding 12 months and/or requiring active treatment), remote seizures (history of seizures but no seizures over the preceding 12 months) and no history of seizures (controls) were assessed on mortality outcomes in people with dementia.

Result

Among 26,598 cognitively impaired, 664 had recurrent seizures and 567 had remote seizures. Early onset of cognitive decline (p<0.001), dominant AD mutation (p = 0.002), Parkinson’s disease (PD, p = 0.055), traumatic brain injury (TBI, p<0.001), active depression (p<0.001) and stroke or TIA were associated with active or remote seizures. Patients with active seizures performed worse on Clinical dementia rating (P<0.001), and functional assessment scale (p<0.001) compared to those without seizures.

Analysis of longitudinal mortality data showed that a higher proportion of active seizure patients had died compared to remote seizures and controls (35.86 vs 28.62 vs 19.11% respectively, p < 0.0001), and they were younger at death (74.88 vs 76.53 vs 79.81 years, p < 0.001). To examine mortality further, a Cox regression model was conducted to study age at death and seizure status. We adjusted the model for sex, race, ethnicity, age, severity of dementia, hypertension, diabetes, stroke, TIA, TBI, PD, depression, education, alcohol use and dominant AD mutation. Despite adjustment, patients with active seizures were at a higher risk of dying at a younger age (adjusted hazard ratio: aHR: 1.79, CI: 1.52‐2.10, p<0.001) but those with remote seizures were not (aHR: 1.05, CI:0.90‐1.24, p0.52).

Conclusion

Our research findings suggest that PWD with active or recurrent seizures have higher mortality rates at a younger age compared to PWD with remote or no seizures. Our findings highlight the need for more aggressive control of seizures in PWD.
Impact of multimodal intervention on cognitive function and nutritional status in older adults with oral frailty: Post‐hoc sub‐group analyses of the J‐MINT study
Authors: Nakamura Junya , Uchida Kazuaki , Sugimoto Taiki , Matsuo Koichiro , Sakurai Takashi , Arai Hidenori
Published: January 2025

Background

In Japan, effective interventions to prevent low nutrition in older people with oral frailty have not been well established. This post‐hoc sub‐group analysis of the Japan‐multimodal intervention trial for the prevention of dementia (J‐MINT) aimed to examine the efficacy of the multidomain intervention in older adults with and without oral frailty.

Methods

J‐MINT was an 18‐month randomized controlled trial in which participants aged 65‐85 years with mild cognitive impairment were randomized to a multimodal intervention group (physical exercise, nutrition counseling, cognitive training, and vascular risk factor management) and a control group. This study included the participants in J‐MINT who had undergone the intervention program and follow‐up evaluation at least once. Oral frailty was defined as oral frailty (Oral Frailty Index‐8 ≥ 4 points) at baseline assessment. Outcomes were the change from baseline to 18‐month assessment in cognitive function (the composite scores of eight neuropsychological tests), Body Mass Index (BMI), nutritional status (Mini Nutritional Assessment Short‐Form), fat‐free mass, fat mass, food diversity, and appetite (Council on Nutrition Appetite Questionnaire). A mixed model for the repeated measure was used to calculate the mean difference (MD) of outcome between the intervention and control groups.

Results

Of 531 participants enrolled in J‐MINT, 433 participants were included (mean age: 74.4±4.9; women, 226; intervention group: 215), and 152 participants had oral frailty at baseline assessment. In older adults with oral frailty, although no significant mean difference in cognitive function was observed (MD [95%CI] = 0.099 [‐0.019‐0.217]), significant intervention effect in nutritional status (0.548 [0.034‐1.062]), fat‐free mass (0.842 [0.216‐1.468]), fat mass (‐0.962 [‐1.890–0.038]), food diversity (1.263 [0.374‐2.150]), and appetite (1.315 [0.524‐2.110]) were observed. However, in older adults without oral frailty, there is a significant intervention effect in only food diversity (1.454 [0.808‐2.100]).

Conclusion

The results of this study suggest the effectiveness of multimodal interventions on nutritional indicators for older adults with oral frailty. Oral frailty may be an effective target for multimodal intervention.
37‐year secular trends in prevalence, incidence, and survival rate of dementia in a Japanese community: the Hisayama Study
Authors: Ohara Tomoyuki , Minohara Toshifumi , Nakazawa Taro , Hata Jun , Shibata Mao , Ninomiya Toshiharu
Published: January 2025

Background

Few population‐based prospective studies have investigated whether the prevalence, incidence, and survival rate of dementia in a community have changed since the 2010s.

Method

Seven cross‐sectional surveys of dementia were conducted among residents of a Japanese community, aged ≥65 years, in 1985, 1992, 1998, 2005, 2012, 2017, and 2022. We also established three cohorts consisting of the residents of this age group without dementia in 1988 (n = 803), 2002 (n = 1,231), and 2012 (n = 1,521) and each was followed for 10 years. Trends in the prevalence of dementia were tested by using the logistic regression model. The age‐ and sex‐adjusted incidence and survival rate of dementia were compared between cohorts using the Cox proportional hazards model.

Result

The crude prevalence of dementia increased with time from 1985 to 2012 (6.7% in 1985, 5.7% in 1992, 7.1% in 1998, 12.5% in 2005, and 17.9% in 2012, p for trend <0.01), while the crude prevalence of dementia decreased with time from 2012 to 2022 (17.9% in 2012, 15.6% in 2017, and 11.9% in 2022, p for trend <0.01). These secular changes did not change even after standardizing by age. The age‐ and sex‐adjusted incidence of dementia significantly increased from the 1988 cohort to the 2002 cohort (adjusted hazard ratio [aHR] = 1.7, 95% confidence intervals [CI] = 1.4‐2.1). However, the age‐ and sex‐adjusted incidence of dementia significantly decreased from the 2002 cohort to 2012 cohort (aHR = 0.6, 95% CI = 0.5‐0.7). The age‐ and sex‐adjusted 5‐year survival rate of dementia significantly improved from the 1988 cohort to the 2002 cohort (47.3% to 65.2%, p<0.01), while no secular change was observed from the 2002 cohort to the 2012 cohort (65.2% to 58.3%, p = 0.39).

Conclusion

The decreasing trends in the prevalence and incidence of dementia were observed since 2012 in the Japanese older population. The decline in the incidence of dementia may be due to prevention of lifestyle‐related diseases, such as hypertension and diabetes, and improvement of proper management of the disease, as well as awareness and promotion of healthy lifestyle behaviors.
Analysis of performance structures of activities of daily living affecting the sleep using social network analysis
Authors: Son Sungmin , Hwang Mose , Shim Aeri , Lee Hyeyoung , Jeong Kyuho , Nam Yeonjoo , Kim Taehui
Published: January 2025

Background

Sleep directly affects daily life, and lack of sleep affects cognitive function and mental health. So, this study analyzed the performance structures of daily activities affecting sleep using social network analysis.

Methods

The subjects were 313 people over 50 years old. The performance structures of daily activities were analyzed by social network analysis, and network characteristics, centrality, and cohesion structures were analyzed. Daily activities were analyzed by categorizing into pre‐sleep daytime activities, sleep preparation activities, and post‐sleep daytime activities. Data collection utilized a structured survey. Subjects were allowed to describe up to five activities to affect sleep. Intensity was assessed using a 5‐point scale.

Results

The analysis of network characteristics showed that the number of activities performed in the daytime was the most performed. However, during sleep preparation, due to the decrease in the number of activities, the density increased, and the values of degree and eigenvector centrality showed high. The results of network centrality showed that, before sleep, bathing/showering, physical activities, and job performance and maintenance influence sleep. During sleep preparation, turning off lights was the most affecting activity on sleep. After sleep, eating and swallowing was the most affected activity by the results of sleep. The results of cohesion analysis showed that, before sleep, job performance and maintenance formed the structures associated with socializing with others. Eating and swallowing, and physical activities formed the structures associated with the self‐management activities performed. In preparing for sleep, turning off lights formed the structure associated with organizing the environment for sleep. After sleep, eating and swallowing formed the structures associated with the basic daily activities related to self‐management.

Conclusions

This study analyzed the interaction between sleep and daily activities. Based on these, key interventions for optimizing sleep include reinforcing bathing/showering and physical activities, as well as regulating job performance and maintenance before sleep. Organizing the environmental factors affecting to sleep and encouraging basic daily activities post‐sleep are needed. The findings can be used as important information to enhance sleep‐related activities of daily living.
Subclinical thyroid dysfunctions and the risk of dementia in the oldest old: the Monzino 80‐plus population‐based study
Authors: Lucca Ugo , Tettamanti Mauro , Forloni Gianluigi , Galbussera Alessia A.
Published: January 2025

Background

Overt hyperthyroidism and hypothyroidism are regarded as possible causes of reversible dementia. Evidence on the risk of dementia associated with subclinical thyroid dysfunctions is limited and barely existent in the very old, while findings are conflicting. Objective: To cross‐sectionally and longitudinally investigate the association of subclinical‐hyperthyroidism and subclinical‐hypothyroidism with dementia in a prospective population‐based study of 80‐years or older residents in Varese province, Italy (Monzino 80‐plus Study).

Method

TSH, FT4, and FT3 concentrations were determined by immunofluorescence ELFA. According to laboratory reference values of concentration, euthyroidism was defined as a THS between 0.25 and 5.00 mUI/mL, subclinical‐hypothyroidism as a TSH >5.00 mUI/mL and an FT4 within reference range, subclinical‐hyperthyroidism as a TSH <0.25 mUI/mL and an FT4 within reference range. Diagnosis of dementia fulfilled DSM‐IV criteria. Covariates entered in the adjusted logistic regression and Cox proportional hazard models: age, sex, education, alcohol consumption, current smoking, diabetes, hypertension, heart failure, myocardial infarction, COPD, ictus, TIA, parkinsonism.

Result

Consent to blood sampling was obtained from 815 participants, 804 of whom had TSH, FT4 and FT3 measurements available (mean age 90.6 years [SD: 5.3]; 598 women [74.4%]; mean education 5.0 years [SD: 2.4]; 312 with dementia [38.8%]; 710 euthyroid individuals, 33 with subclinical‐hyperthyroidism; 41 with subclinical‐hypothyroidism). At the initial evaluation, neither subclinical‐hyperthyroidism (OR: 1.47, 95%CI: 0.72‐2.97; p = 0.28) nor subclinical‐hypothyroidism (OR: 0.65, 95%CI: 0.31‐1.26; p = 0.21) were significantly associated with dementia. The association remained non‐significant when adjusted for confounders (subclinical‐hyperthyroidism, fully adjusted OR: 1.31, 95%CI: 0.56‐3.02; p = 0.53; subclinical‐hypothyroidism, fully adjusted OR: 0.53, 95%CI: 0.22‐1.18; p = 0.13). At blood sample 418/432 participants with at least one follow‐up available were without dementia. In the following 6 years (median: 2.8 years), euthyroid individuals (N = 403) had similar occurrence of dementia (40.7%) as the 15 with subclinical‐hyperthyroidism (40.0%; fully adjusted HR: 1.08, 95% CI: 0.46‐2.53, p = 0.85) and the 29 with subclinical‐hypothyroidism (41.4%; fully adjusted HR: 0.98, 95% CI: 0.53‐1.84, p = 0.96).

Conclusion

In the present population‐based study, neither subclinical‐hyperthyroidism nor subclinical‐hypothyroidism were significantly associated with the risk of dementia in the very old. Although congruous with previous prevalence estimates, the low frequency of subclinical cases without dementia limited the longitudinal analyses.
Neural Imaging for Alzheimer’s Prediction using AI: Exploring CNNs and LIME Explanations
Authors: Varghese Abraham , Sherimon Vinu , Raja Xavier C. , Ephrem Ben George , Gouda Prasanth
Published: January 2025

Background

This study explores Alzheimer’s prediction through brain MRI images, utilizing Convolutional Neural Networks (CNNs) and Lime interpretability. Based on an extensive ADNI MRI dataset, we demonstrate promising results in predicting Alzheimer’s disease. Local Interpretable Model Agnostic Explanations (LIME) shed light on decision‐making processes, enhancing transparency. Using artificial intelligence to predict Alzheimer’s disease, this work emphasizes its importance in improving accuracy and interpretability, thereby advancing the field and improving diagnostics.

Method

Alzheimer’s Disease Neuroimaging Initiative (ADNI) brain MRI images undergo rigorous preprocessing, which includes focusing on brain regions, thresholding and morphological operations to improve image quality. The CNN model was constructed and trained to identify the features of diverse classes of AD, CN, EMCI, LMCI, and MCI in the dataset (Figure 1). With two convolutional layers (25 and 75 filters), maximum pooling, flattening, and dense layers (500, 250, 100 units), the CNN model was trained on a variety of ADNI classes (AD, CN, EMCI, LMCI, MCI). With 375,168,555 trainable parameters, the model is evaluated on split datasets, emphasizing interpretability through LIME analysis for transparent decision insight in neural imaging analysis. This comprehensive methodology ensures robust Alzheimer’s prediction, transparency, and interpretability in neural imaging analysis.

Result

The training procedure resulted in an impressive 98.75% training accuracy after 20 epochs. For the evaluation, 65 diverse images from various classes were used, and all images were accurately classified (Figure 2). Focusing specifically on the CN class data, LIME explanation was applied to identify and emphasize regions that significantly influenced the model’s predicted class. LIME delineates positive and negative regions in its output according to features that support or counter the predicted class (Figure 3). This thorough analysis contributes to a clearer understanding of prediction and promotes transparency in decision rationale.

Conclusion

AI is helpful for predicting AD using MRI, providing accurate diagnostics and allowing for the interpretation of complex imaging data to identify subtle patterns indicative of the progression of AD. By interpreting the LIME representation, we can gain a deeper understanding of how the neural network makes its predictions, by identifying key regions in the brain image that influence the model’s predictions.
Compound intervention affects pathology in a novel humanized APP Knock‐In mouse model (APPSAA), strengthening its relevance as a tool in preclinical research
Authors: Dejonckheere Wannes , Carmans Sofie , Cornelissen Tom
Published: January 2025

Background

To improve clinical translatability of non‐clinical in‐vivo Alzheimer’s disease (AD) models, a humanized APP knock‐in mouse model (APPSAA) was recently created (Xia, D. et al., 2022). The genetic modifications lead to increased Aβ42/40 ratios in AD relevant tissues, resulting in an age‐dependent amyloid deposition. Here we assess the value of this model for non‐clinical efficacy studies of experimental treatments with diverse mechanisms of action to facilitate the development of novel AD therapeutics.

Method

APPSAA mice and WT controls were aged and sacrificed at various time points. In addition, APPSAA mice were treated for 3 months from the age of 3 months onward with an NLRP3‐inhibitor, an in‐house developed calcium homeostasis modulator or vehicle. The major pathological hallmarks were investigated with biochemical and immunohistological assays. Additionally a preliminary screen for AD biomarkers was conducted in CSF samples. Since APPSAA mice lack an obvious behavioral phenotype, synaptic plasticity was investigated to serve as a functional readout.

Result

Cortical Aβ40, Aβ42 and pyroglutamate modified Aβ42 (N3pE‐42) levels were shown to be affected with age. In addition, cortical amyloid plaques, surrounded by activated microglia, were shown to be present already at an age of 3 months, albeit at a low level. With age, the number of cortical plaques increased. In addition, we were able to confirm the presence of endogenous phospho‐Tau positive dystrophic neurites within these plaques, clearly demonstrating the translational relevance of this model. Interestingly, several of the observed hallmarks were counteracted by compound intervention, including phospho‐Tau pathology. Finally, we show that several CNS biomarkers can be detected in mouse CSF.

Conclusion

These data lead us to conclude that this knock‐in model is a broadly applicable tool to investigate efficacy of disease‐modifying drugs with diverse mechanisms of action even without directly targeting protein aggregates.
Association Between in vivo Tau Deposition in the Pedunculopontine Nucleus and REM Sleep Alterations in Non‐demented Older Adults
Authors: Jeon So Yeon , Yi Dahyun , Byun Min Soo , Kong Nayeong , Jung Joon Hyung , Chang Yoon Young , Keum Musung , Ahn Hyejin , Lee Jun‐Young , Lee Yun‐Sang , Kim Yu Kyeong , Kang Koung Mi , Sohn Chul‐Ho , Lee Yu Jin , Lee Dong Young ,   KBASE Research Group
Published: January 2025

Background

Rapid eye movement(REM) sleep alterations are increasingly recognized as an early manifestation of Alzheimer's disease as well as Lewy body disease. The pedunculopontine nucleus(PPN), the main brain source of cholinergic innervation, is known to play an important role in the regulation of REM sleep and has been reported to be one of the early brainstem regions where hyperphosphorylated tau accumulates. Nevertheless, little information is available about the relationship between tau pathology in the PPN(PPN‐tau) and REM sleep disturbance. Therefore, we aimed to investigate the relationship between Tau‐PPN and REM sleep characteristics, alongside the modulating role of amyloid pathology.

Method

A total of 22 non‐demented older adults from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer’s Disease were included. All participants underwent [11C]‐PiB PET and [18F]‐AV1451‐PET. Sleep variables were measured through nocturnal polysomnography(PSG) over two consecutive nights at a center. Tau deposition in the PPN was measured in the ROI masks for each participant, prepared in native space using the Harvard arousal network atlas for the PPN. Linear regression analyses were performed with sleep variables as dependent variables and tau deposition levels as independent variables after controlling for age, sex, education, and apolipoprotein‐E ε4 positivity. In an exploratory analysis, sleep variables demonstrating significance at a threshold of p < 0.1 were further subjected to subgroup analysis based on amyloid positivity.

Result

PPN‐tau was significantly correlated with increased REM latency (p<0.001; Figure 1) and showed a trend‐level association with REM sleep percentage(REM %) (p=0.079). Even after controlling for global tau deposition and amyloid positivity, the significance did not change (p = 0.014). In addition, subgroup analyses according to Aβ positivity revealed that higher PPN‐tau was significantly related to increased REM latency (p = 0.001) and decreased REM % (p=0.011) in Aβ‐positive group but not in Aβ‐negative group (p=0.123 for REM latency and p=0.690 for REM %) (Figure 2).

Conclusion

Our findings support the possibility that tau pathology in the PPN underlies REM sleep alteration, more specifically, increased REM latency and decreased REM sleep in non‐demented older adults. Additionally, this relationship appears to be more prominent in individuals with brain Aβ pathology.
Association of Air Pollution with Memory Decline Later in Life in the United States
Authors: Zhang Boya , Weuve Jennifer , Langa Kenneth M , D'Souza Jennifer , Szpiro Adam , Faul Jessica D , de Leon Carlos Mendes , Gao Jiaqi , Kaufman Joel D. , Sheppard Lianne , Lee Jinkook , Hirth Richard A. , Adar Sara
Published: January 2025

Background

Emerging evidence suggests that air pollution exposure might diminish the cognitive health of older adults. Although many studies have reported that air pollution is associated with increased dementia risk, associations with the process of cognitive decline have been more heterogeneous.

Method

We used biennial data between 2000 to 2016 from respondents>65 years in the Health and Retirement Study (HRS), a national, population‐based cohort in the United States, to study associations of air pollution with cognitive decline. We assessed episodic memory as a composite score of performance on immediate and delayed recall tests combined with proxy‐reported memory function. We standardized the memory score at baseline and during follow‐up based on its baseline mean (0.66) and standard deviation (0.69). We used spatiotemporal models to predict 10‐year average particulate matter (PM2.5, PM10‐2.5), nitrogen dioxide (NO2) and ozone (O3) at participant residences before each interview. Associations with rates of memory decline were estimated by generalized estimating equation regression, adjusting for individual demographics, area‐level characteristics, time, and spatial trends.

Result

Among the 19,063 participants during an average of 7.4±5.3 years of follow‐up time, the mean age at baseline was 71.0±7.3 years. The mean (interquartile range, IQR) PM2.5, PM10‐2.5, NO2 and O3 concentrations were 12.2 (3.6) µg/m3, 9.4 (4.6) µg/m3, 11.2 (7.8) ppb and 26.6 (3.7) ppb respectively. In single‐pollution models, we observed consistently steeper decline in episodic memory scores with higher PM2.5, PM10‐2.5 and NO2 long‐term concentrations (all approximately ‐0.003 standard units/year per IQR, 95%CI: ‐0.006, ‐0.0004), whereas the reverse was observed with higher exposures to O3 (0.003 standard units/year per IQR, 95%CI: 0.001, 0.005). Associations were changed to null for PM2.5 and NO2, and slightly attenuated for O3 after adjustment for other pollutants in the multi‐pollutant model.

Conclusion

This study suggests that long‐term exposure to air pollution might be associated with cognitive decline among older adults though the results differed by pollutant.
Metabolic glutamate receptor 5 (mGluR5) is associated with tau pathology in mild Alzheimer's disease
Authors: Wang Yan , Xie Fang , Guan Yihui
Published: January 2025

Background

Alzheimer's disease (AD) is characterized by the deposition of amyloid plaques and tau neurofibrillary tangles in the brain with continuous cognitive impairment. Although the mechanism underlying AD pathogenesis remains unclear, more evidence suggests that synaptic dysfunction and loss may be an early event in disease progression. Metabotropic glutamate receptor 5 (mGluR5), a kind of G protein–coupled receptor, is involved in AD pathology through modulating synaptic transmission and plasticity and thus exhibits therapeutic effects. However, research on the associations of mGluR5 with the neuropathological hallmarks of AD needs to be completed.

Method

In this single‐center, cross‐sectional study, fifteen patients with mild AD and thirteen normal controls (CN) underwent a PET/MRI scan with [18F] PSS232 (mGluR5 availability) and trouble PET/CT scan with [18F] florbetapir (β‐amyloid) and [18F] MK6240 (tau deposition). The associations of [18F] PSS232 and [18F] MK6240 binding were investigated. We also investigated the correlations of tau deposition and mGluR5 availability with cognitive performance. Voxel‐wise and volume‐of‐interest (VOI) analyses were performed on PET data.

Result

Compared to CN, individuals with mild AD showed smaller clusters of [18F] PSS232 binding in the hippocampus and increased tau deposition in the hippocampus, lateral temporal, posterior cingulate, frontal, occipital, and parietal (Figure 1). Based on Voxel‐wise and VOI analyses, tau deposition in the hippocampus was negatively associated with [18F] PSS232 binding in the hippocampus (r = 0.56, p = 0.002, Figure 2). Lower neuropsychological test scores were associated with decreased [18F] PSS232 and increased [18F] MK6240 binding in the hippocampus (Figure 3).

Conclusion

Patients with mild AD have significant reductions in mGluR5 availability and have high tau deposition in the hippocampus, which is considered the critical region involved in early cognitive impairment. That means mGluR5 and tau were interrelated in the hippocampus and may apply in tau spreading. The correlation of mGluR5 availability and tau deposition in severe AD patients and more longitudinal data are needed to illustrate the role of mGluR5 in AD pathology.
Examining the Associations of Social Support on Later‐life Cognition in the Health and Aging Brain Study‐Health Disparities (HABS‐HD) Cohort
Authors: Lee Jillian K. , Johnson Leigh A. , O'Bryant Sid E. , Mielke Michelle M. ,   HABS‐HD Study Team
Published: January 2025

Background

Social support has been associated with a reduced risk of heart disease and stroke, higher cognitive function, less cognitive decline, and resilience to stress. Notably, social support differs by gender and race/ethnicity. However, it is not clear whether these factors modify the relationship between social support and cognition. In a large diverse cohort, we cross‐sectionally examined the association between social support and cognition and whether gender or race/ethnicity modified the associations.

Method

Participants included 2,831 older adults (mean [SD] age, 64.98 [8.53] years; 63% women, 39% Non‐Hispanic White, 39% Mexican American, 22% African American) enrolled in the Health and Aging Brain Study‐Health Disparities (HABS‐HD). Perceived social support was measured using the Interpersonal Support and Evaluation List. Comprehensive cognitive testing including multiple tests across the following domains: memory, language, processing speed, and attention/executive function. Linear mixed‐effect models evaluated the associations between social support and cognitive performance, adjusting for age, education, gender, and race/ethnicity, the Geriatric Depression Scale, and the Penn State Worrisome questionnaire. Interactions between social support and gender or race/ethnicity on cognition were assessed.

Result

Higher social support was significantly associated with most tests across the cognitive domains. With increasing social support, women performed significantly better than man on Digit Span Forward (b = 0.0391, p = 0.0019) and Backward (b = 0.0335, p = 0.0055), Digit Symbol Substitution (b = 0.1259, p = 0.03780), and Trails A (b = ‐0.2569, p = 0.0198). Increasing social support was more strongly associated with cognitive performance on the Digit Symbol Substitution for African Americans compared to non‐Hispanic whites (b = 0.1652, p = 0.0346). Race/ethnicity did not modify the association between social support and any other cognitive test.

Conclusion

In the cross‐sectional study, higher social support was associated with better cognitive performance across all domains. Associations appeared to be stronger for women versus men but generally did not differ by race/ethnicity. Future research is needed to evaluate the longitudinal associations of social support and changes in cognitive trajectories overtime.