bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying priorities and supporting ADRD researchers through Alzheimer’s Disease Research Center Research Education Components
Authors: Spensley Sheryl B 
Published: December 2022

AbstractBackgroundIn 2018, The National Institute on Aging introduced Alzheimer’s Disease Research Center Research Education Components (RECs) to support research educational activities to complement the training of a workforce to meet the nation’s research needs in AD and related dementias, and develop the next generation of scientists to lead cross‐disciplinary, translational, team‐science projects on AD or AD‐related dementias. Identifying needs and priorities as well as determining the impact of RECs requires tracking of new initiatives, and collaboration between multiple supportive institutions.MethodIn September 2020, the ADRC REC Steering Committee was established. A major priority of the committee was to increase communication and collaboration between ADRC RECs and their trainees. To that end, the National Alzheimer’s Coordinating Center launched the ADRC REC website in 2021 (https://naccdata.org/adrc‐resources/rec‐home) to leverage existing training resources and share job and funding opportunities. To further assess needs, REC leaders were surveyed on how they defined, trained and supported their trainees. In September 2021, REC leaders met to discuss the survey results and inform the REC Steering Committee of ways that the RECs could collaborate and better support ADRD trainees.ResultsTwenty‐eight of the 32 (88%) approached ADRCs responded to the survey. The results (Figure 1) determined that 1) trainee mentoring, 2) increasing the diversity of trainees and 3) promoting and creating training opportunities were the top priorities of ADRC RECs. The REC Steering Committee has aligned its goals to support these topics. The REC Steering Committee has established a collaboration with the Alzheimer’s Association to create a core curriculum to support trainees and leverage the Association’s Professional Interest Areas to elevate trainees. Additionally, a Diversity Workgroup comprising REC leaders and ADRC affiliates has been established to develop approaches to attract, retain, mentor and support diverse trainees.ConclusionBringing together and seeking input from the ADRC RECs helped identify existing opportunities as well as areas of growth for ADRC RECs. Increasing communication between RECs and supportive entities in the ADRD field, and tracking new initiatives, will facilitate greater support of ADRD researchers. Collecting metrics of need and impact will facilitate evaluation of the RECs’ success over time.
Role of insulin resistance in relationship between cardiorespiratory fitness and cognitive speed/flexibility in older adults at risk for Alzheimer’s disease
Authors: McIntyre Clayton Connor , Gaitán Julian M. , Edmunds Kyle J , Okonkwo Ozioma C. 
Published: December 2022

AbstractBackgroundCardiorespiratory fitness (CRF) is thought to support cognition, though underlying mechanisms of this relationship are unclear. CRF is also negatively associated with insulin resistance, which is in turn damaging to cognition. We investigated the link between CRF and cognition and whether insulin resistance mediates this relationship.MethodWe included n = 1,157 cognitively unimpaired, nondiabetic participants. CRF was estimated using a validated equation that incorporates age, sex, BMI, resting heart rate, and physical activity as inputs. The Homeostatic Model Assessment for Insulin Resistance (HOMA‐IR) quantified insulin resistance. Standardized composite scores for global cognition (PACC3), delayed recall, immediate learning, and executive function (including factor scores for working memory and cognitive speed/flexibility) were calculated from a battery of neuropsychological tests administered by trained psychometricians. Linear regression models tested whether CRF predicted each cognitive measure. Mediation analyses determined whether HOMA‐IR was responsible for significant associations between CRF and cognition. All analyses controlled for age, sex, years of education, familial history of Alzheimer’s disease, and Apolipoprotein E4 (APOE4) carriage. Bootstrapped confidence intervals were used to estimate the effect of HOMA‐IR on the CRF‐cognition relationship.ResultThe sample was comprised of 69.8% females and 38.7% APOE4 carriers with a mean age of 64.5 ± 7.2 years and a mean of 16.3 ± 2.8 years of education. CRF was positively associated with executive function (total effect: B = .015, SE = .005, p = .003) and cognitive speed/flexibility (total effect: B = .013, SE = .006, p = .034). CRF and executive function remained positively associated when including HOMA‐IR in the regression model (direct effect: B = .012, SE = .006, p = .040) and the estimated indirect effect of HOMA‐IR on the relationship was insignificant (B = .0031, CI = [‐.0020, .0087]). The association between CRF and cognitive speed/flexibility was attenuated when HOMA‐IR was added to the regression model (direct effect: B = .006, SE = .007, p = .383) and the estimated indirect effect of HOMA‐IR on the relationship was significant (B = .007, CI = [.0007, .0147]). CRF was not associated with PACC3 (p = .258), delayed recall (p = .970), immediate learning (p = .920), or working memory (p = .236).ConclusionAmong older adults at heightened risk for AD, insulin resistance mediates the relationship between CRF and cognitive speed/flexibility but not the relationship between CRF and executive function.
Directly Including Data with Alzheimer’s Publications Through Augmented Reality and Web Technologies – Schol‐AR
Authors: Ard Tyler , Bienkowski Michael S , Pa Judy , Contreras Joey A , Sepehrband Farshid , Yan Lirong , Toga Arthur W. 
Published: December 2022

AbstractBackgroundAlzheimer’s disease research is multi‐disciplinary by nature and based on many forms of data, from MRI scans to microscopic image stacks. Much of this information is difficult to communicate through standard scientific articles and figures, often resulting in incomplete data reporting and suboptimal comprehension for many readers.MethodWe introduce a community‐accessible data layering approach for directly including modern digital information on top of scientific figures, enabling entire datasets to be included with scientific articles. Through this approach readers can easily view data associated with publications through mobile devices or web browsers, averting the need to simplify complex data into 2D static figures.ResultData layering facilitates communication and comprehension of Alzheimer’s research by enabling accessible viewing of complex information directly with scientific articles, posters, and other formats.ConclusionUsing augmented reality and web technologies we can modernize communication of Alzheimer’s research, bridging the gap between the digital basis of modern science and the natural limitations of journal articles.
A federated framework of brain image processing using the Global Alzheimer's Association Interactive Network
Authors: Pappas Ioannis , Xiao Cally , Toga Arthur W. 
Published: December 2022

AbstractBackgroundThe Global Alzheimer's Association Interactive Network (GAAIN) is a unique federated framework that allows users to explore clinical and biomarker data from 57 Alzheimer’s disease data repositories around the world. Integrating brain image processing pipelines with GAAIN data is an important next step that will allow users to derive imaging metrics based on their own analyses.MethodTo that end, we present a federated image processing framework that expands the current capabilities of GAAIN. Within this framework, GAAIN users can initiate image processing pipelines remotely on the data partners’ imaging data prior to requesting the data. Within the same framework, GAAIN users can also explore the results derived from each imaging pipeline and perform basic analyses. Finally, results from each analysis can be imported back to GAAIN and analyzed alongside existing GAAIN variables.ResultWe present a case study by initiating a volumetric analysis directly from GAAIN.ConclusionThis framework provides a solution for imaging data owners to house and protect their imaging data in compliance with the federated character of GAAIN, and, at the same time, for users to analyze imaging data relevant to their GAAIN cohort of interest. We believe that deploying brain image processing pipelines on existing GAAIN data repositories will be pivotal in terms of using big data to propel basic research and clinical trial design in Alzheimer’s disease.
Finding subtypes of nonlinear patterns in longitudinal cognition decline
Authors: Wang Tianhao 
Published: December 2022

AbstractBackgroundTo characterize subtypes of longitudinal cognition decline considering the possible nonlinear patterns.MethodOlder persons without dementia at study enrollment (n = 1,010) had annual cognitive testing for up to 24 years (mean = 9.9 years, SD = 5.0), died, and underwent a neuropathologic examination to quantify 9 postmortem markers of common neurodegenerative and cerebrovascular conditions. To accommodate the heterogeneity in cognitive trajectories and control for neuropathologic burden, we used a novel latent class functional mixed‐effects model which allows individuals to have different nonlinear patterns of cognitive decline under a unified model structure.ResultIn the latent class functional mixed‐effects model, postmortem markers (AD pathology, Lewy bodies, transactive response DNA‐binding protein 43 (TDP‐43) pathology, hippocampal sclerosis, atherosclerosis, gross infarcts) were associated with global cognitive decline. We found four subtypes of longitudinal cognition decline after adjustment for neuropathologic burden. The residual decline after adjustment was weakly related to age at death; it occurred in only about one third of participants, mostly proximate to death. Results were comparable after eliminating the initial cognitive assessments to minimize retest learning or controlling for frailty proximate to death. Analyses were also conducted with composite measures of episodic memory and perceptual speed. Residual decline not attributable to neuropathologic burden was confined to a subset for each outcome and was most evident proximate to death.ConclusionLate‐life cognitive loss involves heterogenous nonlinear patterns. It mainly reflects non‐normative pathologic and mortality‐related processes rather than normative age‐related processes.
Research‐based evaluation of a dementia support program through lived experiences
Authors: Tam Mallorie T , Jiang Yu Fei , Machado Angela , Robillard Julie M. 
Published: December 2022

AbstractBackgroundCommunity support programs can improve quality of life for people living with dementia (PLWDs) and their caregivers (CGs). Important to the successful implementation of such programs is close engagement with end‐users to gain a better understanding of their needs. This study describes the perspectives of PLWDs and CGs on the First Link® dementia support program provided by the Alzheimer Society of British Columbia.MethodFollowing a large‐scale survey (N = 1164), semi‐structured interviews were conducted with PLWDs and CGs who access and do not access the First Link® program to explore in greater detail the different needs and themes that emerged from the survey data. The interviews explored: 1) experiences with the program; 2) future planning; 3) meaning of independence; and 4) impact of the program on emotional and physical well‐being.ResultA total of 38 participants were interviewed (7 PLWDs, 31 CGs). Participants who found that the First Link® dementia program was helpful pointed to their experiences being validated and feeling that they were not alone in their journey. Knowledge and education were key factors that helped participants manage the impact of dementia. Learning about what dementia is, the experiences of others, strategies on how to manage symptoms, what to plan for in the future, and how to access different services in the community, were tied to increased feelings of confidence and comfort, and decreased stress.In terms of their future, participants expressed that it was important to have legal plans in place (e.g. power of attorney), organize personal finances, as well as prepare to manage their estate (e.g. downsizing), access home care, and transition to long‐term care facilities.Participants provided suggestions for improvement of the First Link® dementia program such as embedding the program into the patient journey, providing more services in remote areas, providing education for HCPs, and increasing awareness of the program.ConclusionBy emphasizing the lived experiences and needs of those living with dementia and their caregivers, this work will inform future research‐based program evaluations globally and in turn improve the existing services to support people living with and impacted by dementia.
Joint graph embedding applied to networks estimated from correlations in volumetric data reveal Alzheimers neurodegeneration patterns
Authors: He Rosemary Y , Tward Daniel J 
Published: December 2022

AbstractBackgroundNeurodegeneration measured through volumetry in MRI is recognized as a potential Alzheimer’s Disease (AD) biomarker, but its utility is limited by lack of specificity. Quantifying spatial patterns of neurodegeneration, rather than a few structures of interest, may help address this. We turn to network based analyses developed for studying functional connectivity from signal correlations, measured through fMRI on the time scale of seconds. Our contribution applies these methods to studying volume‐change correlations, measured through structural MRI on the time scale of years.MethodWe study the ADNI1 3Yr1.5T longitudinal dataset, with scans roughly every 6 months for 3 years, and FreeSurfer volumes shared publicly by UCSF. We formed two groups using clinical dementia rating thresholded at <=1. We measured correlation between 108 structure volumes for 494 (322 vs 172) individuals, and computed adjacency matrices by thresholding at magnitude 0.8 (Figure a).We model this dataset with the multiple random eigengraphs framework. Edge probabilities are computed from population‐specific network modes (i), and patient‐specific loadings (ii) (Figure b). We extend the method to guarantee meaningful finite‐sample results: a constant times identity is included to model the diagonal, and a sigmoid ensures probabilities are in [0,1].The parameter sets (i) and (ii) are estimated by maximum likelihood using gradient descent, and F statistics are computed to analyze group differences. Familywise error rate is controlled at 5% using permutation testing on the maximum statistic.ResultUsing a Scree plot, we found four network modes gave accurate graph embeddings (Figure c). We found three networks gave statistically significant differences. As seen in Figure d, limbic, temporal, and ventricular structures dominate these networks.ConclusionThe results reveal networks dominated by structures associated to AD neurodegeneration, indicating the framework has promise for studying AD. It provides an opportunity to leverage graph based tools, already well accepted in fMRI, to study neurodegeneration patterns. It has the potential to uncover networks that may increase the specificity of neurodegeneration biomarkers over those revealed from conventional mass‐univariate analysis.
Evidence for functional connectivity pattern changes in Frontotemporal dementia patients using connectome gradient mapping
Authors: Bouzigues Arabella , Russell Lucy L , Godefroy Valérie , Du Vincent Le , Saracino Dario , Ber Isabelle Le , Batrancourt Bénédicte , Levy Richard , Margulies Daniel , Rohrer Jonathan D. , Migliaccio Raffaella 
Published: December 2022

AbstractBackgroundFrontotemporal dementia (FTD) is a neurodegenerative syndrome with a broad range of clinical manifestations making its early detection and progression monitoring difficult. As we enter the first clinical trials, useful biomarkers are needed. It is believed that functional connectivity underlies cognitive function which makes it a potential meaningful biomarker of disease progression. Studies of functional connectivity in FTD have provided a range of findings suggesting changes in resting‐state networks. However, many of the analysis methods used are either far from the biological processes or restricted to a priori defined networks. Recent work has revealed the emergence of a brain network hierarchy during neurodevelopment, separating immediate environment processing from transmodal and integrative cortices. It is assumed that this organization supports higher order cognition.MethodWe included 36 behavioural FTD patients (bvFTD) and 50 controls. We applied a novel whole‐brain analysis approach, connectome gradient mapping, to resting‐state fMRI data. This approach extracts gradients representing measures of functional similarity. Results are presented as brain parcellations within connectivity space, where the distance between parcels describes the extent of segregation between networks (Fig A).ResultsbvFTD patients showed a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. Specifically, in bvFTD patients, we observed a significant shift of cognitive/behavioural networks, such as the Limbic and Default‐mode, which are less segregated from the primary function networks, such as visual and auditory (Fig B).ConclusionUsing this novel method, we found that the Default‐mode and Limbic networks seem particularly vulnerable in FTD whereby they lose their evolutionarily derived characteristics of segregation. These networks underlie the complex cognitive and behavioural phenotypes observed in FTD. In the near future, we will evaluate whether this model could explain the main symptoms of patients, such as cognitive disinhibition (Stroop/Hayling tests), alterations in social cognition (miniSEA) and worse general cognitive function (MMSE). Overall, this method applied to early and/or presymptomatic stages will be useful for early disease identification and predicting treatment outcomes, making it of interest in future therapeutic studies for neurodegenerative diseases.
Remotely administered computerized cognitive test battery with older adults
Authors: Chok Jas M. , Herron Tim , Schendel Krista , Lwi Sandy J. , Curran Brian , Hall Kathleen , Williams Garrett , Blank Michael , Geraci Kristin , Pebler Peter , Woods David L. , Baldo Juliana 
Published: December 2022

AbstractBackgroundComputerized cognitive assessments are an efficient and sensitive method of identifying cognitive impairments in aging and cognitively impaired populations. The current study examines the feasibility and reliability of remote, home testing with a new tool, the California Cognitive Assessment Battery (CCAB).MethodThe CCAB runs on a remote tablet platform (Figure 1) and includes telemedical interaction with an examiner via video chat (Figure 2). Examiners administer a comprehensive set of cognitive tests, including verbal, visual, memory, and processing speed tasks, as well as psychological questionnaires (Figure 3). The tasks are scored automatically, including consensus automated speech recognition (CASR) for the transcription of responses on verbal tasks (e.g., list‐learning memory tasks, picture description, verbal fluency). For the current study, the CCAB was administered remotely to 185 healthy older military veterans (aged 60–89; 18% women) in their homes, with testing sessions under video and audio supervision and assistance. The battery was administered three times within one week to assess test‐retest reliability.ResultReaction times, word onset latency, response accuracy, error types, and speech samples were collected and analyzed. Participant experience was generally favorable: 98% of participants completed all three testing sessions, with 99% of all tests in those sessions completed successfully. Additionally, after a mid‐year software and examiner procedure reformulation of a small subset of CCAB tests, there was a 42% decrease in test failures and a 6% decrease in repeated tests. Individual test times were overall highly uniform across participants (Figure 4), with an entire CCAB battery having low daily test time variability. Also, compared to home noise levels, recorded speech levels were sufficient to support CASR transcript generation for scoring verbal tasks (Figure 5). Finally, in a subset of 50 participants, similar test battery characteristics were found when a CCAB session was repeated later under laboratory conditions.ConclusionThe CCAB shows promise as an objective, reliable automated digital assessment tool to evaluate cognitive functioning in adults both at home and in the laboratory or clinic.
GWAS for CSF TREM2 levels identify new variants implicated on TREM2 biology and Alzheimer disease
Authors: Mafimoghaddam Samira , Wang Lihua , Gorijala Priyanka , Timsina Jigyasha , Nykanen Niko , Wang Fengxian , Marquié Marta , Boada Mercè , Alvarez Ignacio , Aguilar Miquel , Pastor Pau , Ruiz Agustín , Sung Yun Ju , Cruchaga Carlos 
Published: December 2022

AbstractBackgroundIt is demonstrated that the soluble TREM2 in the cerebrospinal fluid (CSF) is associated with Alzheimer disease (AD). Recent studies by our group found that it is the MS4A4A and/or MS4A6A locus that plays a role in modulating sTREM2 and is also associated with AD risk. The goal of this study is to validate and extend findings from previous studies using a larger cohort, identify functional genes, and determine the overlap of the genetic architecture of CSF TREM2 levels with other traits.MethodWe used 3,033 individuals from Knight ADRC, ADNI, DIAN, and PPMI, and 8,499,039 variants (MAF >0.01) to identify protein quantitative trait loci (pQTLs) that modify TREM2 levels via a linear regression including age, sex, first 10 genetic principal components and array/cohort as covariates. TREM2 protein measurements were obtained from SomaScan 7k platform. Colocalization analyses were conducted for AD risk as well as functional genes from eQTLGen. LDSC and GNOVA and Mendelian randomization (MR) is being used to determine the overlap of the genetic architecture of sTREM2 levels with those for AD risk, onset and progression, as well as cardiovascular and lipid traits.ResultThe pQTL analysis identified the previously discovered MS4A gene region on chr11 (rs72918674, P = 7.009e‐58) as well as a peak on chr3 (rs73823326, P = 2.227e‐09). The lead variant resides in the intron of MS4A6A gene. Conditional analysis on this variant revealed rs10897026 as an additional independent signal located in the intron of MS4A4A. Chr11 peak colocalized with AD risk (PP‐H4 = 0.97) and MS4AE and MS4A6A expression QTL in blood (PP‐H4 = 0.97 and 0.96, respectively). Four regulatory region variants are in high linkage disequilibrium (LD) with chr3 index variant. RBMS3 and TGFBR2 are two genes flanking the chr3 peak, both expressed in microglia.ConclusionThis is the largest study to date aiming at identifying genetic modifiers of CSF sTREM2. The findings validated discoveries from previous studies and identified a novel signal on chr3 at genome‐wide significance. We propose two new genes, RBMS3 and TGFBR2 on chr3, could be involved in TREM2 biology. Our findings provide new insight to unravel sTREM2 modulators and their role in AD.