bluuebunny/crossref_metadata_2025_split huggingface dataset:
Feasibility, reliability and predictive validity of digital cognitive assessments in a diverse cohort of community‐residing older adults
Authors: Katz Mindy J. , Garza Angel Garcia De La , Roque Nelson A , Derby Carol A. , Sliwinski Martin J. , Lipton Richard B. , Wang Cuiling 
Published: December 2023

AbstractBackgroundDigital cognitive assessments repeated over multiple days improve reliability compared to “single‐shot” assessments due to within person variability in function. Further, digital assessments are possible when clinic visits are not. We show the utility of digital approaches using data from the Einstein Aging Study (EAS) diverse cohort of community‐dwelling older adults.MethodParticipants were administered conventional and ambulatory digital assessments annually. The later consisted of a 2‐week burst of digital cognitive and behavioral/exposure measures obtained 6 times/day. Digital cognitive assessments included three tests (processing speed (Symbol Match), visual short‐term memory binding (Color Shape), and spatial working memory (Grid Memory)). Exposure assessment included daily stress, pain, and subjective sleep quality. Feasibility was measured as compliance defined as proportion of completed assessments. Frequency of annual assessments completed was evaluated throughout the COVID‐19 pandemic. For digital measures, reliability was calculated using intraclass correlations (ICCs) across days within a burst and across annual visits. ICCs for conventional measures across annual visits were also computed. To assess predictive validity, we used Cox proportional hazard models to examine whether mean and variability of performance on the 3 digital cognitive tasks predicted incident MCI.ResultCompliance rates overall were 88% and were ≥ 85% in strata based on MCI status, age, race/ethnicity, education or prior experience with smartphones (Table 1). Data collection was maintained throughout the pandemic (Figure 1). ICCs for the digital cognitive measures was consistently high (>0.93). The same was true for exposure measures of stress, subjective sleep and pain (>.88). ICCs across annual follow‐up for digital measures ranged from 0.87 to 0.96 compared to 0.51 to 0.87 for conventional cognitive measures. Regarding predictive validity, worse mean performance in all three digital cognitive measures and higher within‐person variability (SD) in symbol search and color shape were associated with higher risk of incident MCI.ConclusionDigital assessments are feasible to administer, have high reliability and show predictive validity for MCI. They may provide useful tools in observational studies and clinical trials due to improved classification of cognitive status and feasibility in situations where in person assessments are not possible.
Cognitive lapses reported by daily digital diary, and not by recall‐based questionnaires, predict future MCI in a demographically diverse cohort of community‐dwelling older adults
Authors: Rabin Laura , Mogle Jacqueline , Wang Cuiling , Nester Caroline O. , Derby Carol A. , Garza Angel Garcia De La , Lipton Richard B. , Katz Mindy J. 
Published: December 2023

AbstractBackgroundAlthough cognitive lapses are a daily occurrence for many older adults, widely used self‐reports of cognitive function ask respondents to recollect lapses occurring over months or years. We used daily diaries to capture memory and other cognitive difficulties close in time to their occurrence and determined whether daily reports predicted concurrent and/or new cases of mild cognitive impairment (MCI) in the next year (i.e., at annual follow‐up).MethodIn the Einstein Aging Study, daily digital diary indicators of cognitive lapses were assessed each evening over a two‐week period (82% of diaries completed). Conventional recall‐based indicators were the Cognitive Change Index total score and a single item capturing worsening memory (with/without worry), both assessed at each annual visit. Using time‐dependent lagged models with generalized estimating equations (GEE) to correct for within person correlation, we evaluated the association of current cognitive lapses with the probability of being MCI at the current or next annual visit among those diagnosed with MCI after baseline (n = 31 new cases).ResultIn 307 community‐dwelling participants (Mage = 77.05, SD = 4.95; 67% female, 47% White) who were free of MCI at baseline, higher numbers of daily problems significantly predicted the likelihood of being diagnosed with MCI at the next annual visit (average number of visits = 2.72, range 1‐6 years). For every additional daily cognitive lapse, there was a 5% greater odds of being classified at the next visit (OR = 1.05, 95% CI: 1.01‐1.09). By contrast, conventional indicators did not significantly predict transition to MCI at the next visit (ps = .48 and .62, respectively). However, the single item regarding worsening memory was related to concurrent MCI diagnostic status (p<.01). Sensitivity analyses examining the first 3 days or first 7 days to determine the number of daily reports required to identify new MCI cases indicated that both 3 and 7 days significantly predicted future MCI (OR = 1.34, 95% CI: 1.12‐1.61; OR = 1.07, 95% CI: 1.00‐1.14, respectively).ConclusionA brief daily diary assessment of cognitive lapses predicted new cases of MCI. The combination of daily and conventional methods may represent complementary approaches that offer the optimal approach for capturing self‐perceived cognitive deficits associated with current and future MCI.
Investigating the Genetics of Sporadic Early‐Onset Alzheimer’s Disease
Authors: Nudelman Kelly N. H. , Jackson Trever , Rumbaugh Malia C. , Eloyan Ani , Pentchev Julian V. , Faber Kelley M. , Snoddy Casey , Foroud Tatiana M. , Carrillo Maria C. , Dickerson Brad C. , Rabinovici Gil D. , Apostolova Liana G. ,   the LEADS Consortium
Published: December 2023

AbstractBackgroundOnly a small percentage of early‐onset Alzheimer’s disease (EOAD) participants are known to carry autosomal dominant pathogenic variants in the amyloid beta precursor protein (APP) gene or in presenilin 1 or 2 (PSEN1/2); more research is needed to identify additional causative genetic variants. This study presents results of the initial genetic analyses in the Longitudinal Early Onset Alzheimer’s Disease Study (LEADS) and planned next steps.MethodsWhole exome sequencing (WES) is being performed for all cognitively impaired participants, including individuals with EOAD or frontotemporal dementia. Sequencing data is processed using GATK best practices and all variants for APP, PSEN1/2, progranulin (GRN), and microtubule associated protein tau (MAPT) are reviewed for previously reported pathogenic variants. C9ORF72 is also assessed for pathogenic repeat expansions. WES was analyzed with CANOES and CoNIFER for copy number variants (CNVs). WES data has been reviewed for reported pathogenic variants in other neurodegenerative disease‐associated genes. Gene burden testing is being done for the LEADS cases and age‐matched controls from the Parkinson’s Progression Markers Initiative for rare variants in these genes.ResultsTo date, WES has been generated for 301 cases, and GWAS for 384 participants (290 cases, 89 controls). Reported pathogenic variants or repeat expansions in C9ORF72, PSEN1, GRN, and MAPT were identified in 2% of cases for the six screened genes. No CNVs were detected in APP, PSEN1/2, GRN, or MAPT. Review also identified individuals with pathogenic variants or CNVs in genes linked with diseases including Parkinson’s disease and Niemann‐Pick disease, including reported or predicted pathogenic variants in GBA, LRRK2, and SMPD1. Surprisingly, results do not show enrichment of functional TREM2 variants compared to population frequency.ConclusionsInitial results indicate that LEADS is strongly enriched for novel genetic risk and/or causative factors, as only 2% have a reported pathogenic variant or repeat expansion in APP, PSEN1/2, GRN, MAPT, or C9ORF72. Review of reported pathogenic variants in other neurodegenerative disease‐associated genes indicates that while a small portion of disease etiology may be explained by these variants, more research is needed to identify additional causative and risk factors contributing to EOAD.
Exploring specialist dementia nursing models and their impact on people living with dementia and their family: A systematic review
Authors: Brown Pat C , Burton Alexandra , Ayden Jordan , Harrison‐Dening Karen , Hoe Juanita , Cooper Claudia 
Published: December 2023

AbstractBackgroundEvidence that brings together the attributes, specialist knowledge, skills, and competencies required by specialist dementia nurses to fulfil their role is currently lacking, making it difficult to assess the effectiveness of specialist nurse‐led interventions. We systematically reviewed the evidence for specialist dementia nursing to determine how it is defined in terms of key skills, models of delivery, and the impact on families and people living with dementiaMethodWe searched for papers using three databases (MEDLINE, CINAHL, PsycINFO), grey literature (EThOS), and the National Institute for Health and Care Excellence (NICE) evidence search. Search terms related to ‘specialist nursing’ and ‘dementia’ were used. We screened titles and abstracts of identified articles and conducted forward searches for additional relevant studies. Two authors independently rated study quality. Findings were synthesised narratively.Result31 studies were included in the review; 26 were conducted in the UK or USA using a range of methodologies. Role titles varied to include “Admiral Nurses”, “Nurse Practitioners” and “Clinical Nurse Specialists”. We found limited evidence comparing the knowledge, skills, and competencies required by specialist nurses except Admiral Nursing where these were described in three studies. In RCTs (n = 2), specialist nursing did not improve donepezil adherence; and personalised emails to family carers from a nurse specialist did not increase carer self‐efficacy when compared to less intensive interventions. In non‐randomised studies, a USA Nurse Dementia Care Manager service was associated with fewer emergency room and hospital admissions; there were no differences in clinical or cost outcomes in an Admiral Nursing service; and training inpatient specialist nurses in a behavioural intervention increased use of pain‐ relief medication and reduced patient length of stay. Of the 31 studies, 4 reported high carer satisfaction with specialist nursing.ConclusionWe identified only one framework defining specialist dementia nursing competencies, and limited evidence for effectiveness of specialist nursing dementia services on families affected by dementia, despite care received being highly valued. No RCT has measured the impact of specialist nursing on family carer and client outcomes relative to less specialist care.
Modeling Alzheimer’s Disease: DNA damage response and MAPK‐DLK signaling in wild‐type tau‐induced neurodegeneration
Authors: Li Sanming , Roy Ethan , Watkins Trent , Cao Wei 
Published: December 2023

AbstractBackgroundDespite the well‐established link between tau aggregation and clinical progression of Alzheimer’s disease (AD), the major pathways driven by tau elevation to intrinsically damage neurons are incompletely understood. Vast majority of AD patients harbor wild‐type MAPT gene, a contrast to primary tauopathy conditions that are driven by mutant tau.MethodTo model AD‐relevant neurodegeneration compelled by tau, we overexpressed wild‐type full‐length human tau in mouse primary neurons and examined the morphological, cellular, and molecular changes after. We also treated the cells with selective inhibitors to examine the involvement of MAP kinase signaling pathway.ResultWe observed substantial axonal degeneration and cell death, a process accompanied by activated caspase 3. Mechanistically, we detected deformation of the nuclear envelope and increased DNA damage response in tau‐expressing neurons. Gene profiling analysis revealed significant alterations in the MAP kinase pathway; moreover, inhibitors of DLK and JNK were effective in alleviating wild‐type human tau‐induced neurodegeneration. In contrast, mutant P301L human tau elicited less cytotoxicity in primary neurons than wild‐type tau, despite producing a comparable DNA damage response.ConclusionWe have established a cellular tauopathy model highly relevant to AD and identified coupled DNA damage response and MAPK‐DLK pathway in the neuronal degenerative process induced by wild‐type human tau.
Association Between Neuroimaging Biomarkers, Plasma NfL, and Memory Performance in Adults With Down Syndrome With and Without Dementia
Authors: Queder Nazek , Adams Jenna N. , Keator David B. , McMillan Liv , Sathishkumar Mithra , Taylor Lisa M. , Doran Eric , Nguyen Dana , Hom Christy , Krinsky‐McHale Sharon J , Price Julie C , Lai Florence , Rosas H. Diana , Petersen Melissa , O'Bryant Sid E. , Brickman Adam M. , Head Elizabeth , Mapstone Mark , Schupf Nicole , Silverman Wayne , Lott Ira T , Yassa Michael A. 
Published: December 2023

AbstractBackgroundDown syndrome (DS) is associated with early development of Alzheimer’s disease pathology. Both the severity of tau pathology and the increase of neurofilament light chain (NfL) protein are correlated with cognitive decline in the neurotypical populations. Here, we assessed whether tau accumulation in the hippocampus and entorhinal cortex and plasma NfL concentrations were associated with memory performance in adults with DS.MethodWe used 18F‐AV‐1451 (FTP) positron emission tomography (PET) to assess tau accumulation in 44 participants enrolled in the multi‐site Alzheimer’s Disease in Down syndrome (ADDS) study (age 50.72 + 6.21). FTP‐PET scans were partial volume‐corrected, and weighted standardized uptake value ratio (SUVR) were calculated for each of the following regions of interests (ROIs): entorhinal cortex, hippocampus, and the precentral gyrus (control). Participants' plasma NfL concentration (in pg/mL) was measured on a single plex plate using the ultra‐sensitive single molecule array (Simoa) technology platform HD‐X. Memory performance was measured with the modified Cued Recall Test. We evaluated the relationship between FTP SUVRs, NfL, and memory performance using linear regression analysis. Sex and site were used as covariates.ResultIncreased FTP SUVR in the hippocampus and entorhinal cortex were associated with lower scores on free recall (hippocampus: r2 = 0.53, p <0.001; entorhinal: r2 = 0.35, p <0.001) and total recall (hippocampus: r2 = 0.46, p <0.001; entorhinal: r2 = 0.29, p <0.01). As expected, no association between FTP SUVRs and memory performance was found in the precentral gyrus. Additionally, higher plasma NfL concentrations were associated with lower free recall (r2 = 0.35, p <0.001) and total recall (r2 = 0.29, p <0.01). Further, increased levels of plasma NfL were associated with increased FTP SUVRs in the hippocampus (r2 = 0.38, p <0.001), entorhinal cortex (r2 = 0.28, p<0.01), and precentral gyrus (r2 = 0.19, p<0.05).ConclusionIncreased levels of both in‐vivo tau in medial temporal ROIs and NfL in plasma were associated with worse memory performance, consistent with observations in the neurotypical population. Future work will investigate the impact of tau accumulation and NfL concentration on longitudinal cognitive decline in older adults with DS.
Prognostic utility of plasma p217+tau vs amyloid and tau PET in the Alzheimer’s continuum
Authors: Feizpour Azadeh , Dore Vincent , Doecke James D , Saad Ziad S. , Triana‐Baltzer Gallen , Krishnadas Natasha , Fowler Christopher J , Ward Larry , Martins Ralph N , Masters Colin L , Villemagne Victor L , Fripp Jurgen , Kolb Hartmuth C. , Rowe Christopher C 
Published: December 2023

AbstractBackgroundWe evaluated the association of plasma p217+tau with longitudinal cognition and its comparative performance to amyloid‐β (Aβ) and tau PET in predicting prospective cognitive decline.Method153 cognitively unimpaired (CU) and 50 cognitively impaired (CI) participants underwent baseline p217+tau SIMOA assay, 18F‐MK6240 tau‐PET and 18F‐NAV4694 Aβ‐PET with neuropsychological follow‐up (MMSE, CDR‐SB, AIBL‐PACC) over 2.4 ± 0.8 years. The association of baseline biomarkers with cognitive decline was evaluated. Sample size to detect a 30% slowing in cognitive decline in a 2‐year trial and selection cost using p217+tau (pT+) were compared to Aβ‐PET (A+) and tau‐PET (T+) with and without p217+tau pre‐screening.ResultIn the CI, plasma p217+tau predicted change in MMSE (β = ‐0.55, p < 0.001) and CDR‐SB (β = 0.61, p < .001) with effect size larger than Aβ Centiloid (MMSE β = ‐0.48, p = 0.002; CDR‐SB β = 0.43, p = .004) but smaller than tauMetaT SUVR (MMSE: β = ‐0.62, p < .001; CDR‐SB: β = 0.65, p < .001). In the CU, only tauMetaT SUVR predicted change in AIBL‐PACC (β = ‐0.22, p = 0.008). Screening CI for pT+ led to 24% reduction in sample size compared to screening with PET for A+ and 6‐13% compared to T+ (different regions). This translated to an 80% biomarker test cost‐saving assuming p217+tau costed one‐fifth of PET. In a trial requiring PET T+ or A+, pT+ pre‐screening followed by PET would cost more in the CI group with AD prevalence of 70%, compared to ∼35% cost‐saving in the CU group with preclinical AD prevalence of 25%.ConclusionSubstantial cost reduction can be achieved using p217+tau alone to select participants with CI for a trial, compared to selection by PET. Pre‐screening with p217+tau followed by PET provides cost‐saving in preclinical AD trials but is questionable in MCI/AD trials.
Higher cortical thickness/volume in Alzheimer’s‐related regions: Protective factor or risk factor?
Authors: Williams McKenna E. , Elman Jeremy A. , Bell Tyler Reed , Fennema‐Notestine Christine , Franz Carol E , Hagler Donald J. , Kremen William S. 
Published: December 2023

AbstractBackgroundNeuroimaging signatures based on cortical thickness or volume in regions vulnerable to Alzheimer’s disease (AD) pathology are tools developed to identify brain changes specific to mild AD. Lower thickness/volume signatures (indicating comparatively thinner cortex) are commonly associated with risk of future decline. In contrast, some evidence suggests a biphasic pattern of changes wherein higher, rather than lower, cortical thickness is associated with very early AD pathology. Understanding the difference between high cortical thickness indicating a risk versus a protective factor carries important implications for early identification of AD. We examined whether integrating information from a novel AD brain signature based on gray matter mean diffusivity (MD)—previously shown by our group to be sensitive to early AD‐related changes and predictive of thickness/volume‐based signatures over a decade later—can aid in the interpretation of when high cortical thickness/volume is a risk versus a protective factor for future AD‐related changes.MethodParticipants were 572 men in the Vietnam Era Twin Study of Aging (VETSA) who were cognitively unimpaired (CU) at baseline (mean age = 56 years; range = 51‐60). A validated thickness/volume signature and novel gray matter MD signature, each a weighted average of MRI‐based morphometry in eight AD‐related brain regions, were used in longitudinal mixed models predicting brain and cognitive outcomes. Subgroup analyses included all CU participants with high baseline thickness/volume signatures, regardless of subsequent cognitive status (n = 147).ResultAmong individuals with high thickness/volume signature scores at baseline, those that additionally had high values on MD signature scores showed significantly lower thickness/volume signatures and lower episodic memory performance 12 years later compared to the high thickness/volume‐low MD group. In contrast, group differences in global mean cortical thickness remained stable across waves. Groups did not differ in level of young adult cognitive reserve.ConclusionGray matter MD differences may capture heterogeneous subgroups among individuals with high cortical thickness/volume. Findings are in line with a biphasic model in which increased cortical thickness in AD‐related regions may precede future decline. An AD signature based on cortical MD can be used alongside cortical thickness to identify subgroups with differential risk for poorer brain and cognitive outcomes.
Scaling Digital Biomarker Discovery with the Cloud and Wearable Devices
Authors: Ford Colby T , Corkey Jon 
Published: December 2023

AbstractBackgroundIn clinical trials and other disease research, biomarkers provide a valuable indication of drug performance and disease progression. Traditionally, these biomarkers may include genomic factors, lab test results, and more, but we now can easily expand into longitudinally collected digital biomarkers from consumer smart devices.MethodThe Amissa platform, built on the Microsoft Azure cloud, enables the collection of high frequency data from consumer smartwatches (such as the Apple Watch and Samsung Galaxy watch devices). The API‐driven cloud architecture enables secure sensor data collection including location, gyrometry/accelerometry, activity monitoring/pedometry, and biosensors such as oxygen saturation and heart rate. This solution allows for sub‐minute capture frequency while balancing device battery drain. The ISO 27001:2013‐compliant platform is globally scalable through an innovative cloud‐native design that ensures security and compliance.ResultCaregivers, researchers, and healthcare providers can now monitor loved ones/patients through consumer‐grade wearables, providing a cost‐effective, accurate, and flexible solution for biomarker discovery, data collection, and remote monitoring.ConclusionThe Amissa platform successfully enables digital biomarker development and helps to address disparities in clinical trials and research studies of underrepresented groups through decentralized data collection. Plus, the platform address security and privacy considerations while enables collaborative research participation and flexible study designs.
Note: In this presentation, we will discuss the NIH‐funded work of Amissa and the cloud‐first approach taken to build the world’s first global‐scale platform for disease research using wearable devices. We will cover technical design patterns, considerations for privacy and security, the effect of decentralized data collection on addressing health disparities and inclusion in clinical trials, and the future of digital biomarker discovery in Alzheimer’s disease and related dementias.