bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparing characteristics among ADRC cohorts stratified by percentage of autopsied cases that were normal versus demented at visit prior to death
Authors: Gauthreaux Kathryn , Nelson Peter T , Mock Charles , Kukull Walter A.
Published: June 2023

Background

Dementia‐enriched research studies and normal control‐enriched research studies have different recruitment models and thus may differ in clinical and demographic characteristics. These distinctions can contribute to different study findings and perspectives. We generated a novel operationalization for cohort status in NIA‐funded Alzheimer’s Disease Research Centers (ADRC), based on the proportion of research participants that were normal, or demented, prior to death. Based on that operationalization, we compared differences in the rates of several clinical features among participants who came to autopsy.

Method

Data were obtained from the National Alzheimer’s Coordinating Center (NACC). Eligibility criteria included participants with autopsy data available and ADRCs with > = 30 eligible participants. 31 different ADRC autopsy cohorts were thus included, and the total number of individual research participants was 6,722. The first 3 digits of participant zip codes were included in the study. ADRCs were assigned to two groups based on the proportion of participants with normal cognition to participants with dementia. The “more non‐demented “(MN; n = 18) group included ADRCs with >10% ratio of normal to dementia participants, while the “more dementia” (MD; n = 13) group included ADRCs with <10% ratio of normal to dementia participants. Clinical features and diagnoses were compared between the two groups using Pearson’s chi‐square for the categorical variables and two‐sample t‐tests for the continuous variables.

Result

The overall cohort sizes were similar between groups and clinical Alzheimer’s disease (AD) was diagnosed at similar rates in both MN and MD ADRCs. MD ADRCs had more frontotemporal lobar degeneration (FTLD) and Lewy body disease (LBD) diagnoses than MN centers, while MN centers had more cerebrovascular disease and participants were on average older at death than those in MD ADRCs. Other trends identified were that MN ADRCs had lower rates of APOEɛ4 and MD ADRCs tended to include cases from a larger number of different zip codes.

Conclusion

In this sample, we found differences in clinical features between MD and MN ADRCs that probably reflect study designs related to recruitment practices. Future research examining additional features may yield further elaborate discrepancies found between these types of autopsy cohorts.
Novel mathematical modeling approach finds Fortasyn Connect affects memory through reducing hippocampal atrophy in the LipiDiDiet trial
Authors: Hartmann Tobias , van Oudenhoven Floor M , Solomon Alina , Visser Pieter Jelle , Blennow Kaj , Kivipelto Miia , Soininen Hilkka
Published: June 2023

Background

LipiDiDiet is a 6‐year, randomized, double‐blind, placebo‐controlled intervention in 311 individuals with prodromal Alzheimer’s disease (AD)/mild cognitive impairment receiving the specific multinutrient combination Fortasyn Connect (Souvenaid) or a calorie‐matched placebo control once daily.1 AD is characterized by neurodegeneration including significant synapse loss, and the hippocampal formation is particularly vulnerable in the early stages of AD. Results over the first 2 and 3 years of intervention showed that Fortasyn Connect reduced hippocampal atrophy and slowed decline on clinical and other measures related to cognition, function, and disease progression.2,3 Here, possible mechanistic pathways through which the intervention may affect the risk of disease progression are being explored post‐hoc.

Method

A new type of multivariate joint model was applied to the 3‐year LipiDiDiet clinical trial data in which the longitudinal outcomes MRI hippocampal volume (HCV) and neuropsychological test battery (NTB)‐memory are allowed to be associated with disease progression and dropout, and affect each other directly. Specifically, for each longitudinal outcome a linear mixed‐effects model is used to estimate its trajectory, where, for the second longitudinal outcome, the linear predictor of the first outcome is included as time‐varying covariate. Results are compared for both pathways (HCV and NTB‐memory and vice versa), and with results of existing multivariate joint models that have the form of so‐called parallel mediator models (i.e. longitudinal outcomes are merely allowed to be correlated but not to influence each other causally).

Result

Comparing the models, we observed a strong association between changes in NTB‐memory and disease progression and no direct treatment effect on NTB‐memory. Notably, there was a strong direct treatment effect for HCV changes, together with a direct effect of HCV on disease progression. Moreover, indirect effects of HCV changes on disease progression were mediated through NTB‐memory.

Conclusion

This new multivariate joint model is useful in modeling possible mechanistic pathways. Overall results from application to the 3‐year data suggest that the observed intervention effects of Fortasyn Connect are partly mediated through reduction of hippocampal atrophy both directly and indirectly via NTB‐memory, in addition to yet to be defined other/complementary pathways.

1
Funding includes EU‐JPND.

2Lancet Neurol. 2017;16:965‐975.

3Alz & Dementia. 2021;17:29‐40.
Associations between repetitive negative thinking and segregation of the anterior salience network amongst healthy middle‐aged adults
Authors: Solé‐Padullés Cristina , Cattaneo Gabriele , Marchant Natalie L , Cabello‐Toscano María , Mulet‐Pons Lídia , Sánchez Javier Solana , Tormos‐Muñoz Josep Mª , Pascual‐Leone Alvaro , Bartrés‐Faz David
Published: June 2023

Background

Repetitive Negative Thinking (RNT) includes negative thoughts about the future (worry) and past (rumination), and has been associated with AD physiopathology (Marchant et al. Alzh&Dement 2020;16:1054). Prefrontal and anterior cingulate cortices play a major role in RNT (Demnitz‐King et al., Psychiatry Res Neuroimaging. 2021;316:111353). Nonetheless, RNT involves several brain regions within large‐scale networks (Makovac et al., Psychiatry Res Neuroimaging. 2020;295:111020), the efficiency of which depends on their ability to remain segregated (Tononi et al., PNAS, 1994;91:11). We investigated associations between RNT and system segregation (SyS) of the Anterior Salience Network (ASN), Default Mode Network (DMN) and Executive Control Network (ECN) in middle‐aged adults.

Method

248 healthy controls (mean age: 59.17 (SD 4.79), 50.61% women) from the Barcelona Brain Health Initiative (Cattaneo et al. Front Aging Neurosci. 2018;10:321) underwent resting‐state functional magnetic resonance imaging to compute SyS using a node‐based approach with the Shirer atlas (Shirer et al., Cereb Cortex. 2012;22:1). RNT was estimated from questionnaires as previously (Schlosser et al., BMC Psychiatry, 2020;20:1), and a global RNT score was computed. Regression analyses investigated associations between RNT and SyS of ASN, DMN and ECN, including age, depression and stress ratings, emotional stability and cognitive complaints.

Result

RNT was positively predicted by cognitive complaints (t = 3.18, p = 0.002) and depression (t = 6.55, p<0.0001), and negatively by emotional stability (t = ‐4.77, p<0.0001). Likewise, RNT was negatively associated with SyS_ASN (t = ‐2.57, p = 0.011; Fig1). Post‐hoc analyses revealed increased connectivity between ASN and ventral DMN (vDMN, t = 2.57, p = 0.01) and the reverse for ASN‐dorsal DMN (dDMN, t = ‐2.03, p = 0.04; Fig2).

Conclusion

Higher levels of RNT amongst middle‐aged subjects were related to less segregation of the ASN. Results are of importance considering that declining brain segregation predicts dementia severity (Chan et al. Nat Aging 2021;1:1053). Specifically, the ASN presented higher coupling with the vDMN (medial temporal lobe and precuneus), linked to self‐processing and autobiographical processes (Bayley et al., J Neurosci. 2006;26:51), and lower coupling with the dDMN (medial prefrontal regions) associated with cognitive control (Piguet et al., Biol Psychol. 2014;103:195). This dissociative connectivity may partially explain poorer cognitive control and increased self‐referential processes characteristic of RNT (Piguet et al., Biol Psychol. 2014;103:195).
Examining factors that influence African‐Americans and Blacks’ participation in Alzheimer’s biomarker research
Authors: Wang Sophia , Van Heiden Sarah , Saykin Andrew J. , Eliacin Johanne
Published: June 2023

Background

African Americans and Blacks in the US are less likely to engage in Alzheimer’s disease (AD) research studies, despite having two to three times higher risks of developing AD compared to Whites. Understanding the various factors influencing African Americans and Blacks’ participation in AD research, especially studies that involve biomarkers, is important for increasing equity in AD research, and advancing AD diagnosis and treatment for diverse populations.

Method

Study participants included 164 community‐dwelling African Americans and Blacks in the Indianapolis metropolitan area, aged 55 and older, and who had no prior participation in AD research. Participants were administered a 24‐item survey to examine their knowledge of AD, willingness to participate in biomarker research procedures (genetic testing, brain MRI, and PET Scan), and views of incentives for participation.

Result

Most participants were female (68%) and had less than 16 years of education (71%). About half were 65 years old or older. Most participants (84%) reported that they did not know what caused AD or how to manage it, and only 43% were aware that “Black people are at higher risk of developing dementia, including Alzheimer’s disease, compared to Whites.” Most participants were willing to do or consider participating in biomarker procedures common in AD research studies (90% genetic testing, 86% MRI, and 82% PET scan).The majority (85%) were agreeable to future contact for research participation. Most participants viewed return of test results, particularly from cognitive testing (81%) and brain scans (82%), and information about brain health (72%) as incentives to participate in research.

Conclusion

Our findings revealed that older African‐American and Black participants are willing to engage in Alzheimer’s disease biomarker research study procedures. They also viewed knowledge (in the form of return of results and information about brain health) as a major incentive for participation. Our findings suggest that future outreach and recruitment strategies tailored towards African Americans and Blacks may benefit from focusing on the value of knowledge these studies can provide to participants. We also identified opportunities to educate African Americans and Blacks about their increased risk for AD and the causes and prevention of AD.
Adiposity and the risk of dementia: A population‐based study
Authors: de Crom Tosca O.E. , Mooldijk Sanne S. , Ikram M. Arfan , Ikram M. Kamran , Voortman Trudy
Published: June 2023

Background

A higher body mass during mid‐life is a well‐established risk factor for dementia, while a higher body mass during late‐life has been linked to a decreased dementia risk. Yet, body mass may be an inaccurate measure of adiposity, especially in elderly. We therefore differentiated between body mass, fat mass, fat free mass, android fat mass and gynoid fat mass and examined the association between these measures and the risk of dementia. We also determined trajectories of body composition before the diagnosis of dementia.

Method

In the population‐based Rotterdam Study, body composition was measured using dual X‐ray absorptiometry every 4‐5 years between 2002‐2016. Incident dementia was recorded until 2020. We assessed the association between the first body composition measure and the risk of dementia using Cox models, adjusted for sex, age, height, education, smoking, alcohol intake, physical activity, depressive symptoms, and APOE ε4 status. Trajectories of body composition for patients before dementia diagnoses were constructed using linear mixed models and for dementia‐free participants, matched on birth year and sex. All analyses were done for men and women separately.

Result

Of the 3,408 men (mean age 66.4 years) and 4,563 women (mean age 66.5 years) with at least one body composition measure available, 293 men and 526 women developed dementia during a mean follow‐up of 10.3 years. Higher body mass, fat mass, android fat mass and gynoid fat mass, but not fat free mass, tended to associate with a decreased risk of dementia in both men and women (Figure 1). After excluding the first five years of follow‐up only the association of gynoid fat mass in women remained statistically significant (hazard ratio [95% confidence interval]: 0.85 [0.75‐0.97]). No major differences in trajectories of body composition were observed, although a slight trend of a decrease in total, android and gynoid fat mass was observed in women up to 2 years before diagnosis.

Conclusion

A higher body mass, fat mass, android fat mass and gynoid fat mass were associated with a decreased risk of dementia. These results may be explained by reverse causality or competing risks, although a protective effect of adiposity cannot be excluded.
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

Background

Alzheimer’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.

Methods

Five 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.

Results

MBG 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).

Conclusions

Behavioral 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

Background

Episodic 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.

Method

Einstein 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).

Result

LM1 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.

Conclusion

While 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

Background

Non‐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.

Method

Transgenic (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.

Result

Eight 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.

Conclusion

Our 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

Background

There 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.

Methods

We 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.

Results

We 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).

Conclusions

This 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

Background

American 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.

Method

We 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.

Results

The 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).

Conclusion

Knowing 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

Background

Despite 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.

Method

Community‐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.

Result

The 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).

Conclusion

ACAD’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

Background

Persons 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.

Method

We 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.

Results

Decisions 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.

Conclusion

These 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

Background

Cognitive 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.

Method

We 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.

Result

The 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).

Conclusion

This 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

Background

Epigenetic 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.

Method

We 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.

Result

AgeAccel 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.

Conclusion

Blood‐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.
SUVR cut off using Optimal time of the Early‐phase 18F‐florbetaben brain image compared to the 18F‐fluorodeoxyglucose brain image
Authors: Shin HyunJi , Kang Do‐Young
Published: June 2023

Background

Early phase amyloid positron emission tomography (PET) imaging is known to correlated with glucose metabolism. However, studies on the optimal time frame and SUVR cut off for early‐phase amyloid PET have not been sufficiently progressed. In this study, the optimal time of early‐phase 18F‐FBB was determined and SUVR cut off was obtained.

Method

To determine the optimal time frame, the correlation between FBB and FDG SUVR of 67 subjects(34, Alzheimer’s disease(AD), 4 mild cognitive impairment(MCI), and 29 health control(HC)) was compared. In this method, 83 brain regions were treated as gray matter masks using an integrated brain map of PMOD 3.6. After obtaining the optimal time of FBB, which has a high correlation compared to FDG, a total of 225 subjects(188 AD, 37 HC) were targeted. SUVR cut off of dual‐phase 18F‐FBB PET of 11 brain regions was obtained. Calculate the composite mean SUVR and regional SUVR using MedCalc.

Result

The highest correlation between early‐phase 18F‐FBB and 18F‐FDG peaked at ‐.8747 at 270‐330s. Considering the minimum time and correlation between image noise and visual analysis, 90 to 330 seconds were set as the optimal time frame(r‐ratio ≥0.875).

In the early‐phase FBB, cut off values in the order of HC>AD were valid. The classification accuracy of the composite mean SUVR was 72%(AD 69.15%, HC 86.49%), and the regional area accuracy was 85.78%(AD 93.62%, HC 45.95%). In the delay‐phase FBB, cut off vlaues in the order of AD>HC were valid. The classification accuracy of the composite mean SUVR was 77,33%(AD 72,87%, HC 100%), and the regional area accuracy was 84.89%(AD 86.17%, HC 78.38%). In the early and delay‐phase FBB, the classification accuracy of the composite mean SUVR was 90.67%(AD 92.02%, HC 86.49%), and the regional area accuracy was 88%(AD 98.4%, HC 37.84%).

Conclusion

In this study, it is possible to know the optimal time frame of the early‐phase 18F‐FBB showing a high correlation with 18F‐FDG. Composite mean SUVR and regional SUVR cut off of the dual‐phase 18F‐FBB are helpful for visually ambiguous analysis.
Association of sleep duration with cognitive performance and structural brain differences: A large population‐based cross‐sectional study
Authors: Wang Zhiyu , Wang Jiao , Yang Wenzhe , Dove Abigail , Qi Xiuying , Pan Kuan‐Yu , Xu Weili
Published: June 2023

Background

Sleep duration has been linked to dementia risk; however, its association with cognitive functioning in specific domains and the underlying mechanisms remain unclear. We aimed to examine the association of sleep duration with cognitive performance and structural brain differences using magnetic resonance imaging (MRI).

Methods

Within the UK Biobank, 43,255 dementia‐free participants (aged ≥44, 52.0% female) were included. Self‐reported sleep duration (hours/day) was recorded following a structured questionnaire and trichotomized as short (≤5), normal (6‐8), and long (≥9) sleep. Cognitive functioning (including fluid intelligence, pairs matching, reaction time, and numeric memory) was evaluated using a touchscreen test battery. MRI scans were performed, and total and regional brain volumes (including white matter, gray matter, and hippocampus), and white matter hyperintensities (WMH) were measured. Data on lifestyle factors and medical conditions were collected. Data were analyzed using linear regression.

Results

Of all participants, 2092 (4.8%) had short, 38,041 (87.9%) had normal, and 3122 (7.2%) had long sleep. In multi‐adjusted linear regression, compared with normal sleep duration, both short (β: ‐0.14, 95%, CI: ‐0.19 to ‐0.10) and long (β: ‐0.06, 95% CI: ‐0.10 to ‐0.03) sleep were related to poorer performance in fluid intelligence. Long sleep was also associated with poorer numeric memory (β: ‐0.06, 95% CI: ‐0.10 to ‐0.01). In MRI data analyses, compared with normal sleep duration, short sleep was related to a smaller hippocampus volume (β: ‐0.05, 95% CI: ‐0.09 to ‐0.01), while long sleep was associated with smaller total brain (β: ‐4.51, 95% CI: ‐6.82 to ‐2.21), gray matter (β: ‐3.32 95% CI: ‐4.70 to ‐1.94), and hippocampus (β: ‐0.06, 95% CI ‐0.09 to ‐0.02) volumes, but greater WMH (β: 0.05, 95% CI: 0.01 to 0.08), after adjusting for confounders.

Conclusions

Short and long sleep durations are associated with poorer cognitive performance in different domains. Short sleep may indicate neurodegeneration, and long sleep may implicate both neurodegenerative and vascular changes in the brain.
BMD‐001, a nanoparticle containing miR‐485‐3p antisense oligonucleotide, blocks Alzheimer's disease progression
Authors: Koh HanSeok , Min Hyun Su , Lim Yu Na , Jang Hannah , Yang Jinhee , Kim Daehoon , Cho HyunJeong , Ryu JinHyeob
Published: June 2023

Background

Alzheimer’s disease (AD) is a form of dementia characterized by progressive memory decline and cognitive dysfunction, which affects more than 44 million people worldwide. Currently, there is no effective therapy for AD despite its increasing global incidence; thus, effective treatment strategies for AD are urgently needed.

Method

In a previous report, we confirmed that expression of miR‐485‐3p was increased in the brain tissues, CSF, and plasma exosomes of AD patients than in healthy controls. In addition, the therapeutic potential of downregulation of miR‐485‐3p was also shown in 5XFAD AD model mice. Based on this target validation, we developed a nanoparticle containing antisense oligonucleotide (ASO) targeting miR‐485‐3p, named BMD‐001, which has a high CNS‐targeting ability to cross the blood‐brain barrier (BBB). BMD‐001 was injected into 10‐month‐old 5XFAD mice by intravenous injection, once weekly for four weeks. Behavioral tests were performed at 11 months and their brain pathology was examined after 8‐week‐washout at 13 months.

Result

To evaluate in vivo pharmacokinetics of BMD‐001, the plasma levels of Cy5‐labeled ASO encapsulated in the nanoparticle were measured after intravenous injection along with a naked ASO without formulation of nanoparticle. The half‐life of the ASO in the nanoparticle was 93 min while that of the naked ASO was only 43 sec. Furthermore, we also observed that the brain accumulation of the fluorescent ASO in the nanoparticle was 64‐fold higher than the naked ASO and was maintained up to 16 hours, as monitored by in vivo imaging. After BMD‐001 injection, miR‐485‐3p expression was decreased in the brain tissue. We found that BMD‐001 enhanced Aβ clearance via phagocytosis of Aβ in vitro and in vivo. Furthermore, BMD‐001 reduced Aβ plaques, tau pathology, inflammasome, neuroinflammation, and cognitive decline in the 5XFAD mice.

Conclusion

Collectively, our findings suggest that BMD‐001 is delivered to the brain through the efficient BBB penetration. Furthermore, BMD‐001 can be a promising candidate for treatment of AD pathology and cognitive decline, establishing a new paradigm in the AD field.
Multimorbidity patterns in people with Alzheimer’s disease
Authors: Chi Nai‐Ching , Lozier Patrick , Street Nick , Buckwalter Kathleen , Gardner Sue , Rakel Barbara , Perkhounkova Yelena , Hein Maria
Published: June 2023

Background

Multimorbidity is highly impactful for older adults, especially when it co‐occurs with Alzheimer’s disease (AD). However, scarce evidence is available about comorbid conditions co‐occurring with AD. We aimed to identify the most prevalent comorbid conditions and examine the common multimorbidity patterns in patients with AD.

Method

Using electronic health records of a university hospital, we extracted data from 2,646 older adults with AD (ICD‐10) using Calderón‐Larrañaga’s inventory of chronic conditions. Leverage correlation was performed to detect multimorbidity patterns.

Result

AD patients had on average 13 comorbid conditions and 50% of them had at least 10 comorbid conditions co‐occurring with AD. Hypertension (51.7%), lipoprotein metabolism disorders and other lipidemia (35%), depression (33.9%), general mental disorders (31.96%), sleep disorders (26%), urinary disorders (25.3%), anemia (24.6%), joint disorders (23.19%), chronic kidney disease (21.25%), and other functional intestinal disorders (20.66%) were the top 10 prevalent comorbid conditions. The common multimorbidity patterns were “disorders of lipoprotein metabolism and other lipidemia” and “hypertension” (frequency [n = 747, 30%]; leverage:0.09), followed by “hypertension” and “hypertensive kidney disease” (frequency [n = 189, 8%]; leverage:0.06), “presence of cardiac and vascular implants and grafts” and “disorders of lipoprotein metabolism and other lipidemias” (frequency [n = 181,7%; leverage:0.05), and “Type 2 diabetes” and “hypertension (frequency [n = 181,7%; leverage:0.05).”

Conclusion

Our results align with prior studies that cardiovascular disease, diabetes, osteoarthritis, and depression are common conditions in people with AD. These findings might support future studies investigating the mechanisms linking multimorbidity to AD, which ultimately can guide preventive actions and comprehensive approaches for managing these co‐occurring conditions.
Associations between hippocampal subfield volume and cognitive performance
Authors: Tan Jaclyn , Lim Mervyn Jun Rui , Chen Christopher , Hilal Saima
Published: June 2023

Background

It is well demonstrated that hippocampal atrophy is associated with cognitive impairment. Existing studies have associated smaller hippocampal volumes with dementia, and hippocampal volume reduction has been established as a biomarker for the conversion of mild cognitive impairment to Alzheimer’s Disease. Although some studies have examined correlations between hippocampal subfield volumes and cognitive domains such as memory, further research is needed to clarify the associations between the volume of each subfield and the various cognitive domains. So far a few studies have been conducted among Asian populations. A more specific understanding of these relationships is crucial given the functional and histological differences in the subfields and their distinct patterns of atrophy, which imply that the hippocampal subfields may affect cognition differentially. This study aimed to investigate the associations between the volumes of 12 hippocampal subfields on cognitive performance in a Singaporean sample.

Method

448 patients at a memory clinic in Singapore (97 with no cognitive impairment, 177 with CIND, and 174 with dementia) underwent magnetic resonance imaging (MRI) and a neuropsychological assessment. MRI was processed through free surfer (v.6.1) to extract volumes of 12 hippocampal subfields—the tail, subiculum, presubiculum, parasubiculum, CA1, CA3, CA4, fimbria, fissure, molecular layer, the molecular and granule cell layers of the of the dentate gyrus (GCMLDG), and the hippocampus‐amygdala transition area (HATA). Cognition was assessed using NINDS–Canadian Stroke Network harmonization neuropsychological battery.

Result

Global cognition was associated with the subiculum, presubiculum, CA1, CA3, CA4, molecular layer, and GCMLDG (all p‐values < .0005). Except for the fissure, all hippocampal subfields were associated with visuospatial skills (all p‐values < .05) and memory (all p‐values < .035). The fimbria was associated with the most cognitive domains, including executive dysfunction (p = .011), language (p = .006), visuomotor function (p = .003), visuospatial skills (p < .001), and memory (p < .001).

Conclusion

The current study builds on existing research on the associations between hippocampal subfield volumes and cognitive dysfunction. Longitudinal studies are required to investigate the volumetric reduction of hippocampal subfields as a biomarker of cognitive decline.