bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Na/K‐ATPase Inhibitor Marinobufagenin on Gene Expression and Cognition in a Mouse Model of Alzheimer’s Disease
Authors: Fox Shanaya , Zahariadis Eleni N , McDevitt Ross A , Grigorova Yulia N , Wei Wen , Zernetkina Valentina I , Santos Carla Rocha Dos , Cezayirli Defne , Haghkar Mahdi , Shearon Jennifer , Lakatta Edward G , Fedorova Olga V 
Published: June 2023

AbstractBackgroundAlzheimer’s disease (AD) is characterized by brain amyloid‐β plaque formation, neuroinflammation and neurodegeneration, which lead to cognitive impairment (CI) and disruption of circadian rhythm. Bioactive steroidal Na/K‐ATPase inhibitor marinobufagenin (MBG) modulates neuroinflammation. In 16‐mo old double transgenic APPswe/PS1dE9 AD mice with advanced AD, treatment with MBG reduced mRNA expression of inflammatory markers. Here, we investigated whether treatment with MBG at early‐stage AD may impact AD manifestation in this AD mouse model.MethodsFive months old male AD mice (n = 15) and WT mice (n = 28) were administered MBG (100 µg/day/kg body weight) (AD‐MBG, n = 8; WT‐MBG, n = 14) or vehicle for control (AD‐C, n = 7; WT‐C, n = 14) via subcutaneous ALZET osmotic minipumps for 3 months. At 8‐mo of age, the mice underwent turn‐based discrimination learning in a water T‐maze (WTM) to assess procedural learning and 72‐hour home cage activity (HCA) analysis to assess circadian rhythm. The hippocampal inflammatory and AD mRNAs (by qPCR) and MBG levels (by immunoassay) were measured.ResultsMBG administration increased plasma MBG levels in WT and AD mice (Table 1). AD‐C mice exhibited greater home cage activity disruption vs. WT‐C (Fig.1a); in WTM, AD‐C required more trials to learn the turn‐based task than WT‐C (Fig. 1b). Though statistically insignificant, trends showed that MBG numerically worsened activity disruption by HCA and decreased ability to learn turn‐based task by WTM in WT mice, while numerically improving both measures in AD mice. During the reversal phase of WTM where response requirements were reversed, WT‐C mice performed significantly better than AD‐C mice, measured by the cumulative amount of time spent in the incorrect arm until reaching criterion performance (p = 0.038). Similar patterns of numerical improvement in AD‐MBG compared to AD‐C are shown (Fig. 1c). Hippocampal inflammatory and AD markers mRNAs were upregulated in AD‐C vs. WT‐C, and MBG treatment downregulated the expression of TNF and GFAP in AD mice (Table 1).ConclusionsBehavioral testing results illustrate CI and circadian impairment in 8‐mo old AD mice compared to WT. Numerical trends show a potential protective effect of MBG on AD CI likely via downregulation of hippocampal TNF and GFAP genes.0Supported by the NIH/NIA Intramural Research Program
Story memory in Alzheimer’s disease research: Concordance between logical memory and craft story 21 in a demographically diverse aging cohort
Authors: Nester Caroline O. , Qin Jiyue , Wang Cuiling , Katz Mindy J. , Lipton Richard B. , Rabin Laura 
Published: June 2023

AbstractBackgroundEpisodic memory loss, the hallmark symptom of Alzheimer’s Disease (AD), is frequently quantified by performance on story memory tasks. The National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) previously included Logical Memory (LM) as a story memory measure due to its widespread use in the field. Version 3 of the UDS shifted towards nonproprietary neuropsychological tests, hence the Craft Story 21 (CS) was introduced to replace LM. The concordance between LM and CS is poorly understood in demographically diverse older adults, possibly jeopardizing the integrity of longitudinal data in aging cohorts.MethodEinstein Aging Study participants (subsample, n = 300; Mage = 76.6; Myears education = 14.9; 66.3% women; 43.3% Non‐Hispanic White) completed measures from the UDS test battery, including two story measures of immediate recall (LM1 and CS1) and delayed recall (LM2 CS2). Classification as cognitively normal (CN; n = 201) or mild cognitive impairment (MCI; n = 98) was based on Jak/Bondi criteria. Analyses included correlations, linear regression, and equipercentile equating at baseline to characterize the relationship between LM and CS. Multivariate linear mixed effects (LME) models (for immediate and delay) explored LM and CS performance across follow‐up ‘waves’ of longitudinal data, controlling for gender, ethnicity, education level, baseline depressive symptoms, and baseline age, and were further stratified by baseline cognitive status (CN vs MCI).ResultLM1 and CS1 (r = 0.54) and LM2 and CS2 (r = 0.56) were moderately correlated, although the correlations were weaker in our sample than those previously reported by NACC (r = 0.73 and r = 0.77 respectively). Education, age, and depressive symptoms were significantly associated with story memory performance at baseline. Multivariate LME revealed significant interaction effects of follow‐up waves, depressive symptoms, and gender on story memory. These results were consistent regardless of baseline cognitive status.ConclusionWhile LM and CS are correlated they are not replicate measures. Our findings underscore the importance of taking into account key factors that may influence performance on story recall tests, including gender, depressive symptoms, and practice effects. Furthermore, the distinct content of the LM and CS stories may differentially impact learning and recall. These findings may aid in decision making about test selection in a given clinical or research sample.
Could microRNAs expressed in the tear fluids predict underlying molecular changes associated with Alzheimer’s disease (AD) at an early stage?
Authors: Wijesinghe Printha , Xi Jeanne , Cui Jing , Campbell Matthew , Pham Wellington , Matsubara Joanne A 
Published: June 2023

AbstractBackgroundNon‐coding small microRNAs (miRNAs) are a large family of post‐transcriptional regulators of gene expression and recent advances demonstrate their utility as disease biomarkers. Altered miRNA expression levels associated with AD have been reported in autopsy human brain samples, CSF and blood samples obtained from AD patients, and in AD animal models. However, due to the variabilities among samples and techniques from different labs, the potential applicability of miRNAs as biomarkers remains unclear. Here, we undertook a systematic study to assess the relative expression of ten candidate miRNAs in tear fluids and tissues obtained from eye and five brain regions of an AD mouse model at early and late stages. Our goal is to assess the unique differences among tear, eye and brain tissues to identify the most relevant miRNAs in tear fluids, which are collected non‐invasively, that best represent onset and progression of AD.MethodTransgenic (Tg, APP/PS1), non‐Tg sibling, and wildtype (WT, C57BL/6J) female mice (n = 24, 4 per group) at two ages were studied (3‐4 months and 9‐10 months). Ten selected mature miRNAs were determined using single tube TaqMan advanced miRNA assays. A statistically significant (p <0.05, 2‐tailed Welch’s t‐test) intergroup >2‐fold difference (FD) was used to determine the differentially expressed miRNAs.ResultEight of the ten miRNAs were expressed at Ct <35.0. miR‐101a, potentially targeting amyloid precursor protein (APP), was significantly downregulated in the neocortex‐hippocampus of both young (p = 9.2×10−7, FD = 8.1) and old (p = 3.0×10−3, 3.0) Tg mice compared with its age‐matched WT controls. Importantly miRNAs ‐125b, ‐15a and ‐374c were significantly and consistently upregulated in the neocortex‐hippocampus, eye and tears of old Tg mice compared with its age‐matched WT control. Whereas all the tested miRNAs were downregulated or nonsignificant in the neocortex‐hippocampus, eye and tears of young Tg mice compared with its age‐matched WT control.ConclusionOur systematic study of miRNAs shows a consistent pattern of expression in the brain, eye and tears of an AD mouse model at two different ages. It also demonstrates the translational potential of tear fluids’ miRNAs in a Tg AD model with changes over time.
Gene Expression Differences Between Symptomatic and Asymptomatic Individuals with Neuropathologically Confirmed Alzheimer’s Disease
Authors: Wang Yueh‐Ting , Li Donghe , Ang Ting Fang Alvin , Xia Weiming , Au Rhoda , Farrer Lindsay A. , Stein Thor D. , Jun Gyungah R 
Published: June 2023

AbstractBackgroundThere has been tremendous interest in molecular signatures of cognitively resilient individuals with neuropathologically confirmed Alzheimer disease. We sought to identify transcriptome signatures derived from brain that distinguish such individuals from those with AD diagnosed clinically and confirmed at autopsy.MethodsWe performed differential gene expression analysis in participants with neuropathologically confirmed AD who had a clinical diagnosis of AD (AD) and cognitively normal (AsymAD) prior to death using RNA sequencing data from 43 AD and 11 AsymAD participants of the Framingham Heart Study and Boston University Alzheimer’s Disease Research Center (FHS/ADRC) and from 155 AD and 208 AsymAD participants of the Religious Orders Study and Memory and Aging Project (ROSMAP). Differential gene expression transcritome‐wide was compared between AD and AsymAD subjects separately in each dataset using linear regression models including covariates for sex, age at death, and post‐mortem interval. Results were combined by meta‐analysis using sample size as a weight. Significantly (P<10−5) differentially expressed genes (DEGs) were subsequently tested for association with memory, language, executive function, and visuospatial performance, and neuropathological traits.ResultsWe identified 36 significant DEGs among which PPDPF, ZNF592, RPL17, MEIS3, and MTMR10 were transcriptome‐wide significant (P<10−6). Of the 36 DEGs, expression of PPDPF, SLC38A2, and PRELP was significantly associated with memory and language test scores (P<0.05). Expression of KCNJ10 was significantly associated with complement 4b protein (P<0.05) and phosphorylated Tau levels (P<10−3).ConclusionsThis study identified genes that may be involved in cognitive resilience. Our study also illustrated that expression differences of the top‐ranked genes are associated with cognitive performance in memory and language domains, Tau pathology, and neuroinflammation. These findings may provide insight about cognitive resilience mechanisms as well as novel targets for inhibiting cognitive decline.
The costs of treating dementia among American Indians with diabetes within the Indian Health Service and Tribal health programs
Authors: O'Connell Joan , Grau Laura , Goins R. Turner , Winchester Blythe , Corrada María M. M. , Manson Spero , Jiang Luohua 
Published: June 2023

AbstractBackgroundAmerican Indian and Alaska Native (AI/AN) adults have one of the highest prevalence of diabetes (14.7%) in the United States, nearly double that of the White population. As AI/ANs age, they are at high risk for chronic diseases that have diabetes as a well‐established risk factor, such as cardiovascular complications and dementia. Approximately half of AI adults with dementia have diabetes, but little is known about their treatment costs. Our aims were to profile treatment costs of AI adults with diabetes, with and without dementia, and to understand how dementia influences costs by type of service.MethodWe analyzed fiscal year 2013 treatment cost data from the Indian Health Service and Tribal health programs for American Indian (AI) adults aged ≥65 years with diabetes. Using data for 921 adults with dementia and a matched sample without dementia (n = 921), matched by age, sex, and location, we report actual and adjusted total treatment costs and costs by service type. Adjusted costs were estimated using a generalized linear model with a log link function and gamma distribution.ResultsThe morbidity burden of AI adults with both diabetes and dementia was high. Over seventy percent (71.4%) had cardiovascular disease (CVD) and 39.4% had renal disease. The prevalence of these conditions was lower (57.8% and 30.6%, respectively) among adults with diabetes without dementia. Mean total treatment cost was higher for adults with dementia ($15,978) than for adults without dementia ($8,857), a difference of $7,121. The difference in adjusted total treatment costs between adults with and without dementia was $3,891 (95% confidence interval [CI]: $2,122‐$5,659), most of which was due to the difference in hospital inpatient costs ($3,754; 95% CI: $2,221‐$5,286). Furthermore, among adults with both dementia and CVD, adjusted hospital inpatient costs were $8,114 (95% CI: $6,018‐$10,211), significantly higher than that among adults with dementia only ($2,075; 95% CI: $992‐$3,158) and among adults with CVD only ($3,050; 95% CI: $2,399‐$3,701) (Figure 1).ConclusionKnowing CVD is strongly associated with high inpatient costs among AI adults with both diabetes and dementia may inform enhancements to outpatient and home‐based services that address their CVD health risks.
Developing best practices for outreach and recruitment: Updates from the Asian Cohort for Alzheimer’s disease (ACAD) study
Authors: Park Van Ta , Tzuang Marian , Lu Anna T. , Lee Haeok , Wang Li‐San , Thomas Carlos , Chow Tiffany W , Jun Gyungah R , Yu W. Haung ,   ACAD Consortium
Published: June 2023

AbstractBackgroundDespite investments in AD research to combat this public health crisis, racial/ethnic minorities such as Asian Americans and Asian Canadians (ASACs) remain underrepresented in AD research including clinical trials, biomarker, and genome‐wide association studies. The Asian Cohort for Alzheimer’s Disease (ACAD) is the first large AD cohort for ASACs with a focus on recruiting Chinese, Korean and Vietnamese. We present the outreach and recruitment strategies employed by the ACAD Recruitment and Outreach Workgroup (Workgroup) during the ACAD’s pilot phase.MethodCommunity‐Based Participatory Research (CBPR) principles are embedded through all activities as a fundamental strategy to increase research participant engagement of ASACs. CBPR engages the community in all phases of research (i.e., recruitment; resource sharing; study design; data interpretation). The Workgroup was tasked with a) coordinating and monitoring recruitment activities across all 8 recruiting sites in the US and Canada; b) developing and disseminating recruitment and community outreach/education materials; c) convening the community advisory board (CAB) to elicit feedback on participant referrals, study processes, outreach/recruitment materials and to address community partner needs; d) collaborating with academic and community partners on outreach; and e) developing best practices for community outreach.ResultThe Workgroup developed multilingual and culturally adapted ACAD‐wide outreach, recruitment and retention materials including study flyers, presentation template materials, animated videos, e‐cards, social media accounts and ads. ACAD CAB provided valuable input regarding study procedures and materials as well as promoting ACAD to their respective communities and networks. During the ACAD pilot phase, 26 outreach activities were conducted across sites. Given that ACAD was launched during the COVID‐19 pandemic, many (n = 16) activities were conducted online and some at community centers, clinics, senior apartments, and outdoor events, with an estimated reach of 3,500+ community members. Many (62.5%) events were conducted in English (n = 17), and others in Asian languages such as Cantonese (n = 5), Korean (n = 2), Mandarin (n = 9) and Vietnamese (n = 2).ConclusionACAD’s multifaceted approach to outreach and recruitment aims to optimize community engagement and a step towards representation of ASACs in AD studies. The Workgroup will continue to monitor outreach/recruitment metrics and provide support for overall and site‐specific community engagement needs.
Supporting decision making among people living with dementia: Developing a DCE tool
Authors: Turner Anne M 
Published: June 2023

AbstractBackgroundPersons living with dementia (PLWD) face many decisions about transitioning to more supportive care as their disease progresses, but are often left out of the decision‐making process. The Decision‐Making in Alzheimer’s Research (DMAR) project is developing a tool, informed by stakeholder input, that uses images, story‐telling, and discrete choice experiments (DCEs) to unpack the preferences of PLWD about transitions in supportive care and facilitate their inclusion in the decision‐making process. This study describes the development and design of the DMAR tool.MethodWe conducted in‐depth interviews between September 2020 and December 2021 with 24 PLWD, 37 caregivers, and 18 direct care staff or providers to understand decisions that PLWD encounter as they transition to supportive care, and the related decision‐making factors. We recorded, transcribed, coded, and analyzed interviews for key themes and factors. We then used heat maps to determine the four key factors for making decisions about obtaining more supportive care.ResultsDecisions and roles in decision‐making differ depending on the stage of dementia. However, even persons with very early dementia had difficulty discussing plans regarding more supportive care. Early decision‐making centered on obtaining support around instrumental activities of daily living. Decisions to bring more supportive care into the home or seek supportive care outside the home were mentioned primarily by caregivers and staff members. Overall, the four most commonly mentioned factors influencing decision‐making were level of function, quality of life, out of pocket costs, and amount of supportive care.ConclusionThese four factors will be incorporated into a DCE tool to identify the relative importance of identified factors in making decisions regarding transitions to more supportive care. In this roundtable, we will further discuss plans to develop an electronically administered DCE tool to track the consistency of preferences of PLWD and their caregivers over time. We will also describe challenges encountered when eliciting preferences of PLWD, the role of technology in decision‐making, and creative methods, such as story‐telling and images, to enhance discussions with PLWD regarding supportive care.
Machine learning prediction model for cognitive dysfunction in older adults
Authors: Bae Suyeong , Lee Mi Jung , Hong Ickpyo 
Published: June 2023

AbstractBackgroundCognitive decline is a typical aging‐related condition in older adults. Maintaining or improving the cognitive function of older adults has been a major focus of older adults’ welfare policy. Examining predictors of deteriorating older adults’ cognitive decline is critical to support healthcare policies. This study aims to identify predictors of cognitive function in community‐dwelling older adults using machine learning algorithms.MethodWe extracted 6,940 older adults’ demographic and clinical characteristics from the 2018 Korean Longitudinal Study of Aging (KLoSA). We utilized the final sample of 4,282 older adults by removing the missing observations in the study variables (n = 2,658, 38.3%). The dependent variable was the Mini‐Mental State Examination‐K (MMSE‐K), and the independent variables included demographic characteristics, grip strength, the Center for Epidemiologic Studies Depression Scale (CES‐D) score, life habit, presence of chronic disease, and social participations. We used two machine learning (ML) algorithms: random forest and classification and regression tree (CART) to predict older adults’ cognitive function. Mean absolute error (MAE) and root mean square error (RMSE) were used to compare the model accuracy of those machine learning algorithms.ResultThe mean age was 75.7 years (SD = 8.1) with more females in the sample (n = 2,376, 55.5%). The random forest model performed better than CART (MSE: 3.0 and 3.3 and RMSE: 4.0 and 4.4 for random forest and CART sequentially). The random forest model identified the CES‐D, age, grip strength, educational attainment, self‐reported health, residential area, and social participations as predictors of older adults’ cognitive function (the degrees of predictor importance were in order).ConclusionThis study presents a list of predictors for cognitive function in community‐dwelling older adults. Among various predictors, depression in older adults was the most influential variable in predicting older adults’ cognitive function.
Associations of epigenetic age acceleration with cognitive function trajectories in the women’s health initiative memory study
Authors: Nguyen Steve , McEvoy Linda K. , Whitsel Eric A , Manson JoAnn E. , Rapp Stephen R. , LaCroix Andrea Z. , Shadyab Aladdin H. 
Published: June 2023

AbstractBackgroundEpigenetic age acceleration (AgeAccel) indicates faster biological aging relative to chronological age and has been independently associated with several age‐related outcomes. However, the cross‐sectional and longitudinal associations of AgeAccel with global cognitive function is understudied.MethodWe therefore studied 734 women (mean±SD baseline age = 70.3±4 years; 7.9% Black, 3.5% Hispanic/Latina, 88.6% White) who were free of cognitive impairment at the baseline examination of the Women’s Health Initiative (WHI) Memory Study (WHIMS,≥65 years enrolled in the WHI Hormone Therapy clinical trials between 1993‐1998). We measured global cognitive function annually with the Modified Mini Mental State Examination (3MS) through 2007 and the modified Telephone Interview for Cognitive Status (TICS‐m) from 2008‐2021. We measured extrinsic AgeAccel [EEAA] intrinsic AgeAccel [IEAA], AgeAccelPheno, and AgeAccelGrim in blood collected at baseline. AgeAccel measures were derived from chronological age and white blood cell counts (EEAA and IEAA), phenotypic age (AgeAccelPheno), or mortality (AgeAccelGrim). We estimated cross‐sectional AgeAccel‐3MS score associations in linear regression models and longitudinal AgeAccel‐3MS and TICS‐m score associations in linear mixed effects (LME) models adjusting for age, educational attainment, race, ethnicity, marital status, alcohol use, smoking, body mass index, comorbidities, hormone trial group assignment and physical activity.ResultAgeAccel measures were not cross‐sectionally associated with 3MS scores or longitudinally associated with 3MS or TICS‐m scores over a mean (SD) follow‐up of 6.4 (2.0) and 17.2 (3.6) years, respectively. Cross‐sectional AgeAccel‐3MS associations (95% confidence intervals) per 1‐year increment in AgeAccel were ‐0.03 (‐0.08, 0.02) for EEAA, ‐0.01 (‐0.08, 0.05) for IEAA, ‐0.02 (‐0.07, 0.03) for AgeAccelPheno, and 0 (‐0.10, 0.10) for AgeAccelGrim. Corresponding annual 3MS changes per 1‐year increment in AgeAccel were 0 (‐0.01, 0.01) for EEAA, 0 (‐0.01, 0.01) for IEAA, 0 (‐0.01, 0.01) for AgeAccelPheno, and 0 (‐0.02, 0.02) for AgeAccelGrim. Annual TICS‐m changes per 1‐year increment in AgeAccel were 0.01 (‐0.01, 0.03) for EEAA, 0 (‐0.02, 0.02) for IEAA, ‐0.01 (‐0.02, 0.01) for AgeAccelPheno, and 0.01 (‐0.02, 0.04) for AgeAccelGrim.ConclusionBlood‐based AgeAccel measures were not significantly associated with global cognitive function among older women. Larger studies are needed to further examine AgeAccel‐global cognitive function associations.