bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing the unsupervised assessment of cognition in web‐based registries of individuals at risk for Alzheimer’s disease: Results from the Healthy Brain Project
Authors: Lim Yen Ying , Perin Stephanie , Buckley Rachel F. , Pase Matthew P. , Yassi Nawaf , Lavale Alexandra , Schembri Adrian , Maruff Paul T.
Published: December 2020

Background

Web‐based platforms are used increasingly to assess cognitive function in unsupervised settings. However, methods for ensuring the validity of cognitive data arising from unsupervised assessments are limited. We applied Human Computer Interaction (HCI) concepts of acceptability and usability to examine the validity of unsupervised cognitive testing in middle‐aged adults enrolled in the Healthy Brain Project (HBP).

Method

A total of 1594 middle‐aged adults (mean age 56 years, SD 6.60 years) completed unsupervised assessments using a self‐administered version of the Cogstate Brief Battery (CBB) via our online platform, healthybrainproject.org.au. HCI acceptability was defined by the nature and amount of missing data, and HCI usability as (a) errors made during test performance, and (b) the time taken to read test instructions and complete the tests (learnability). We also explored whether cognitive performance varied across different testing environments (e.g., home/work alone, home/work with others around, public space).

Result

Overall, we observed high acceptability (98% complete data) and high usability (95% met criteria for low error rates and high learnability). Test validity was confirmed by observation of expected inverse relationships between performance and increasing test difficulty and age. When accounting for the effects of age, no general influence of testing environment was found for any of the cognitive outcome measures in this study. Testing environment also had no significant effect on the proportion of individuals who satisfied our pre‐specified acceptability and usability criteria.

Conclusion

With HCI acceptability and usability criteria considered, the data collected in this study retains similar psychometric characteristics to those collected from supervised testing of the same tests. The HCI definitions of acceptability and usability show great promise for use as real time algorithms for the collection of valid indices of cognition in unsupervised settings. This is of particular salience when considering the development of registries of individuals at risk for Alzheimer’s disease.
Dutch Brain Research Registry for online study participant recruitment: Design and first results
Authors: Zwan Marissa D , van Der Flier Wiesje , Cleutjens Solange , Vermunt Lisa , Jutten Roos J. , van Maurik Ingrid S , Sikkes Sietske AM , Weiner Michael W , Scheltens Philip , Prins Niels D
Published: December 2020

Background

Difficulty in participant recruitment is a significant barrier to clinical dementia studies. The Dutch Brain Research Registry (www.hersenonderzoek.nl) was set up for online recruitment of participants for neuroscience studies in the Netherlands. Here we present first results with respect to participant registration and enrollment in studies. To evaluate this process, we investigated which demographic, social and health‐related factors were related to study participation.

Method

Registrants were primarily recruited through social media. The online registration process consists of a 10‐minute questionnaire including demographics, medical history, subjective memory complaints, medication and substance use. Registrants eligible for studies were selected based on provided data and invited by email. Those who accepted the invitation were contacted by the study investigator for further evaluation and enrollment. The relation of participant factors with study participation was analyzed using multivariate regression analyses.

Result

In the first eighteen months, 17.218 registrants signed up (58±11 years old, 78% female). Twenty‐eight studies have recruited participants via our platform, including 9 online observational studies, 14 onsite observational studies and 5 onsite intervention studies. Prescreening identified 34.696 eligible registrants, of whom 12.637 (36%) accepted the study invitation. After further evaluation by the study investigator, 10.661 registrants (31%) were successfully enrolled in studies. Compared to non‐participants, participants enrolled in studies were more often older (OR=1.32, CI=1.23‐1.40), male (OR=1.07, CI=1.00‐1.13), higher educated (OR=1.29, CI=1.22‐1.36), retired or not working (OR=1.14, CI=1.06‐1.21), non‐smoking (OR=1.59, CI=1.45‐1.73), reported a better health (OR=1.29, CI=1.18‐1.39) and had a 1st degree family member with dementia (OR=1.17, CI=1.11‐1.24).

Conclusion

The Dutch Brain Research Registry facilitates effective matching of potential participants to brain research studies. Our findings demonstrate the feasibility to recruit participants via an online registry for a large number of studies with a high enrollment rate. In addition, participant factors related to study participation may reflect facilitators or barriers for study participation, as better self‐rated health and non‐smoking may express the participant’s interest in health‐related research. Furthermore, older age and a positive family history of dementia are associated with preclinical disease and therefore often used as prescreening for studies as well. These findings are useful for improving recruitment strategies.
Amyloid‐dependent association of grey matter network disruptions with phospho‐tau in preclinical Alzheimer’s disease
Authors: Lorenzini Luigi , Ingala Silvia , Wottschel Viktor , Wink Alle Meije , Mutsaerts Henri JMM , Haller Sven , Blennow Kaj , Schwarz Adam J. , Gispert Juan Domingo , Chetelat Gael , Waldman Adam , Visser Pieter Jelle , Tijms Betty M , Barkhof Frederik ,   the EPAD Consortium
Published: December 2020

Background

Structural Grey Matter Networks (GMN) show progressive disruptions in Alzheimer Disease (AD), starting from early, preclinical stages, and are related to amyloid aggregation. However, GMN associations with tau biomarkers remain unclear. Here, we investigated the relationship between GMN and phospho‐tau (p‐Tau) levels in CSF and whether this relationship was dependent on amyloid beta (Aβ), in a non‐demented population.

Method

We selected 423 individuals from the first data release of the European Prevention of Alzheimer Disease (EPAD, v500.0) that had MRI and CSF markers available; 84% were cognitively unimpaired (CDR=0) and 16% had CDR=0.5 (Table 1). Abnormal Aβ was defined by levels of <1025 pg/mL, and abnormal p‐Tau by levels of >24 pg/mL in the CSF. Single‐subject networks were extracted from 3D‐T1w structural MRI using a previously described method (Tijms BM et al., 2012), and for each individual we computed whole brain betweenness centrality, degree, density, clustering, modularity, path length and small world properties. Association of network metrics with Aβ and p‐Tau was investigated using linear models including Aβ, p‐Tau+ and Aβ‐p‐Tau interaction, both dichotomously (model 1) and continuously (model 2), adjusted for age, sex and Clinical Dementia Rating (CDR) scores.

Results

In total 154 (36%) of individuals had Aβ+ (Table 1). Abnormal Aβ (both dichotomously and countinuously) was associated with lower degree, density, clustering and small‐world network properties, independently of tau (p<0.001). Higher p‐Tau levels were related to a reduction in clustering, modularity and small‐worldness values in the Aβ+ group only (p<0.05).

Conclusion

In cognitively unimpaired subjects, grey matter networks show alterations in amyloid‐positive subjects, independently of tau, and within these individuals stronger GMN disruptions are related to higher p‐Tau levels. Our results indicate a relationship between molecular markers of AD and atrophy patterns at the single‐subject level, specifically going towards a more random and less clustered network topology, and suggest a possible role of GMN measures in identifying early stages of the pathology.
What patients want to know, and what we actually tell them: The ABIDE project
Authors: Fruijtier Agnetha D , Visser Leonie NC , Bouwman Femke , Lutz Rogier , Schoonenboom Niki SM , Kalisvaart Kees , Hempenius Liesbeth , Roks Gerwin , Boelaarts Leo , Claus Jules J , Kleijer Mariska , Beer Marlijn , van Der Flier Wiesje , Smets Ellen M
Published: December 2020

Introduction

We formerly identified 17 informational topics on which health care professionals, patients and care‐partners agree that these should be discussed during diagnostic consultations in memory clinics [1]. In addition, 8 topics were identified as highly relevant by at least one, but not all three groups. Here, we studied to what degree these 25 informational topics are actually discussed during diagnostic consultations and at whose initiative, i.e., the clinician, the patient or the care‐partner.

Methods

Audio‐recordings of pre‐ and post‐test clinician‐patient consultations of 71 patients, seen by 32 clinicians (sample descriptives in table 1), were collected in eight memory clinics and independently content‐coded by two coders [2]. The coding scheme encompassed the 25 informational topics, grouped into 4 categories; (i) diagnostic testing, (ii) test results, (iii) diagnosis and prognosis, and (iv) practical implications.

Results

Many topics were discussed frequently, though individual topics ranged from being discussed with 2/71 (3%) to 70/71 (99%) of the patients. On average, 12 (SD=4) of the 25 topics were discussed per patient, during the diagnostic process. Topics in the category ‘diagnosis and prognosis’ were discussed least frequently (see figure 1). Patients and/or care‐partners rarely initiated discussion of a topic (topic initiated by clinician: 90%). When they did, the topic was most often one of the least frequently addressed topics (see figure 2), as well as one of the eight topics deemed highly relevant by at least one group (mostly patients and/or care‐partners), but not all three.

Conclusion

We found most topics to be addressed quite frequently by clinicians in memory clinics, validating the feasibility of addressing these topics. Nevertheless, we observed considerable variation when looking at individual topics. Discussion of diagnostic or prognostic information was relatively limited, while patients and care‐partners consider this topic highly relevant, as substantiated by initiating discussion on diagnosis and/or prognosis. Hence, diagnostic or prognostic information should receive more attention in clinical practice. In addition, providing the topic list to patients prior to their visit could allow them to better prepare for the consultation and stimulate active participation.
Organizational, system, and policy level factors affecting dementia clinical research participation: Lessons from a pilot study
Authors: Bouranis Nicole , Gelmon Sherril B , Lindauer Allison , Waddell Elizabeth N , Richardson Dawn M , Woo Hyeyoung
Published: December 2020

Background

Finding a dementia intervention is contingent on research participation. Current literature focuses on general factors affecting dementia clinical research participation, which do not speak to specific state or local factors nor the effects of local recruitment efforts. This study identified organizational, system, and policy level factors affecting local ADRD clinical research participation in Portland, Oregon.

Method

A community advisory board (CAB) comprised of clinicians, researchers, advocates, people with dementia, family caregivers, and older African Americans was established for this project. Semi‐structured interviews were conducted with clinicians, advocates, and researchers. Interviews were audio‐recorded and coded; thematic analysis was used to allow themes to emerge from the data organically. The investigator was the single coder; the CAB then interpreted findings by identifying what was most important, surprising, or missing from the interviews.

Result

Nine clinicians, researchers, and advocates were interviewed. Interviewees were employed by or volunteered with health, research, and advocacy organizations of varying sizes and structures. Several findings emerged from the interviews. 1) Federal policy attempts to streamline research studies have not resulted in the intended outcomes at the local level. 2) People with ADRD and caregivers have a lack of awareness of research opportunities. In some cases, this was due to lack of provider knowledge; in others, it was due to organizational directives to not discuss or a provider’s personal preference. 3) Research opportunities are not shared in places where people with ADRD and their caregivers are likely to congregate. 4) Interviewees were often hesitant to join community collaborations or formal partnerships, and many were weary of including people with ADRD in their advisory boards.

Conclusion

Identifying how these factors affect the decision of a person with ADRD to participate in local dementia clinical research is an important first step to increasing participation rates. Based on these factors, strategies can be developed and implemented to improve the ability and motivation of people with ADRD to join research studies in the Portland metropolitan area. This study should be replicated in other communities to determine contextual relevance and generalizability for other areas. Implemented strategies should be routinely evaluated to determine their feasibility and effectiveness.
Regional white matter hyperintensities predict Alzheimer’s‐like neurodegeneration
Authors: Rizvi Batool , Lao Patrick J , Chesebro Anthony G , Igwe Kay C , Amarante Erica , Beato Juliet M , Rivera Andres , Gutierrez Jose , Schupf Nicole , Zahodne Laura B , Manly Jennifer J , Mayeux Richard , Brickman Adam M
Published: December 2020

Background

Small vessel cerebrovascular disease, best visualized as white matter hyperintensities (WMH) on T2‐weighted MRI scanning, is associated with cognitive decline and increases risk for clinical Alzheimer’s disease (AD), particularly when it is distributed in posterior brain regions. There is much debate, however, about whether cerebrovascular disease represents a comorbidity or whether it is more fundamental to the pathogenesis of AD. The purpose of this study was to examine whether regional WMH volume predicts neurodegeneration, operationally‐defined as longitudinal decline in cortical thickness, among community‐dwelling older adults.

Method

Two hundred thirty‐eight participants(73.18+5.23 years old, 60% women, 35% APOE‐ε4 carriers, 30% non‐Hispanic White/32% Hispanic/38% Black, 14% with MCI) from the Washington Heights Inwood Columbia Aging Project (WHICAP) received high‐resolution structural 3T MRI scans at baseline and 4.09+1.57 years later. Regional WMH volume was derived with in house developed software and the FreeSurfer (v6.0) longitudinal processing stream was used to calculate change in cortical thickness. Using QDEC, we examined the relationship of total and regional WMH volume with annualized rate of decline in cortical thickness (symmetrized across the two visits) with vertex‐wise general linear models adjusted for age, sex, and APOE status. We additionally adjusted for a baseline marker of AD‐related atrophy (entorhinal cortex thickness).

Result

Baseline total WMH volume predicted widespread cortical atrophy in a pattern consistent with AD‐associated atrophy, which included parahippocampal, temporal, and parietal regions. When examined regionally, the effects were most prominent for parietal lobe WMH, which predicted entorhinal cortex atrophy predominantly. Adjusting for baseline entorhinal cortical thickness did not alter the findings. In stratified analyses, the effects were strongest among Hispanic and Black participants compared with White participants, and similar across APOE groups.

Conclusion

White matter hyperintensity volume, especially in the parietal lobes, predicts Alzheimer’s‐like neurodegeneration, suggesting that small vessel cerebrovascular disease contributes to the ‘N’ aspect of the ‘A/T/N’ pathogenic models of AD. The results were independent of and stronger than baseline atrophy measures, suggesting that WMH are not simply a result of neurodegeneration. These effects may manifest differently across racial/ethnic groups, with small vessel cerebrovascular disease playing a more prominent role in future neurodegeneration among racial/ethnic minorities.
Serum glial fibrillary acidic protein and neurofilament light as prognostic biomarkers for clinical progression in subjective cognitive decline: The SCIENCe project
Authors: Verberk Inge M.W. , Laarhuis Malika B , van den Bosch Karlijn A. , Ebenau Jarith L. , Leeuwenstijn Mardou , Wesselman Linda M.P. , Prins Niels D. , Scheltens Philip , Teunissen Charlotte E. , van Der Flier Wiesje
Published: December 2020

Background

Blood‐based biomarkers might be easy‐to‐use tools for predicting future decline to dementia in cognitively normal individuals presenting at memory clinics (i.e. subjective cognitive decline; SCD). We previously found that glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) relate to neurodegenerative disease processes (Verberk, AAIC 2019). In this study we aimed to assess the prognostic value, by investigating the relation between baseline serum GFAP and NfL and cognitive decline in individuals with SCD.

Method

We included 303 individuals with SCD from the Amsterdam Dementia Cohort and SCIENCe project (age 61±9 years, 42% females, MMSE 28±2), who were followed annually for re‐evaluation of diagnosis and cognitive performance on a standardized neuropsychological test battery covering global cognition and the main cognitive domains (average follow‐up: 3.5 ± 2.6 years, median number visits: 3 (range 2‐12), total evaluations: 1014). Baseline serum NfL and GFAP were measured using Simoa, and Z‐transformed levels were associated with incident dementia in age and sex‐adjusted COX regression models, and with longitudinal neuropsychological test performance in age, sex and education‐adjusted linear mixed models.

Result

Upon follow‐up, 27(9%) individuals developed dementia (18 Alzheimer’s, 9 non‐Alzheimer’s). High baseline GFAP was associated with increased risk of progression to dementia (HR=3.5 (95%CI: 2.2–5.7); Figure 1A), as was high baseline NfL (HR=1.8 (95%CI: 1.2–2.8); Figure 1B). When simultaneously entering both serum markers, only GFAP remained independently associated with risk of dementia (HR=3.2 (1.9–5.4); NfL: HR=1.3 (0.8–2.0)). Additionally entering plasma amyloid showed that both GFAP (HR=2.6 (1.4–4.8) and amyloid (HR=2.4 (1.2–4.5)) independently associated with risk of dementia. Investigating trajectories of cognitive decline, we found that higher baseline GFAP was associated with a steeper rate of decline on tests for global cognition, memory, attention and executive functioning (range standardized betas: ‐0.03–‐0.17, all: p<0.05FDR), but not language, whereas for NfL, none of the associations were significant after multiple testing correction (Table 1).

Conclusion

Our results suggest that especially GFAP is a putative prognostic blood‐based biomarker for identifying individuals with SCD at‐risk for future clinical disease progression. Serum NfL proves to be less useful as a prognostic marker in these earliest disease stages.
Converging evidence for a “gray‐zone” of amyloid burden and its relevance
Authors: Bullich Santiago , Salvadó Gemma , Alves Isadora Lopes , Marquié Marta , Stephens Andrew W , Gispert Juan Domingo , Molinuevo Jose Luis , Buckley Christopher , Boada Mercè , Barkhof Frederik
Published: December 2020

Background

Traditional quantitative cut‐offs for amyloid PET positivity have been defined to discriminate Alzheimer’s dementia (AD) subjects from elderly Aβ‐negative non‐demented controls. Currently, observational and interventional studies focus on earlier stages of Aβ deposition, where established cut‐offs might not be appropriate. Here, we review recent developments on early pathology identification, and provide supporting evidence from three cohorts for the establishment of a “gray‐zone” of amyloid burden.

Method

Data from three cohorts of cognitively unimpaired individuals were included, namely ALFA+ (n=357), FACEHBI (n=228) and the AMYPAD Prognostic Study (n=122). PET scans ([18F]flutemetamol and [18F]florbetaben) were analyzed in Centiloid (CL) units. Gaussian Mixture Modelling was used to fit two/three Gaussians to the global CL values, and the cut‐off for early pathology detection was defined as two standard deviations above the mean of the left Gaussian. Then, the data was merged to derived a joint cut‐off. Finally, these data‐driven cut‐offs were compared to previously established thresholds in the context defining a range of CL values where pathology is emerging.

Result

GMM identified a cut‐off of CL=11 for FACEHBI, CL=14 for ALFA+, CL=17 for AMYPAD and CL=11 for the cohorts combined (Figure 1). Similarly, Salvadó et al identified two cut‐offs based on a direct comparison with established CSFAβ42 thresholds: CL=12 to rule out‐amyloid pathology and CL=29 to denote established pathology. With a different approach, the FACEHBI working group finds CL=13 as an early threshold defined based on young healthy controls, and CL=36 as an established cut‐off to separate healthy elderly from Aβ‐positive AD‐dementia subjects. In AMYPAD, where a more comprehensive sampling of the AD continuum is present, fitting 3 Gaussians through the data allows the identification of two data‐driven cut‐offs: CL=13 and CL=29.

Conclusion

A number of recent and current reports converge to the utility of two cut‐offs for amyloid PET abnormality, an early cut‐off around CL=11‐17 where pathology may be emerging, and a second around CL=29‐36 where amyloid burden levels greatly correspond to neuropathology findings. Together, these create a gray‐zone of CL values pre‐AD dementia levels of amyloid burden, which can improve the detection of emerging pathology in observational and secondary prevention trials.
Default mode network dedifferentiation predicts cognitive performance in Alzheimer disease
Authors: Meeker Karin L. , Ances Beau M. , Gordon Brian A. , Morris John C. , Benzinger Tammie L.S. , Waring Jill
Published: December 2020

Background

During aging, brain networks become less functionally specialized, known as dedifferentiation. When dedifferentiation occurs, brain networks become less adaptive, leading to failures in cognitive processing. Although global dedifferentiation occurs with age, it is unknown how global and local dedifferentiation change as a function of cognitive impairment (measured by the Clinical Dementia Rating Scale [CDR]). We assessed whether global and/or local dedifferentiation differ as a function of CDR status and predict cognitive performance in cognitively normal individuals (i.e., CDR=0) and those with mild symptomatic Alzheimer disease (AD; CDR>0).

Method

Neuroimaging and clinical data from 432 participants (CDR0=356; CDR0.5=63; CDR1=13) were analyzed. Graph theory analytic approaches were applied to RS‐FC data for global dedifferentiation and 7 individual association networks. In graph theory, dedifferentiation is measured by computing segregation, which quantifies the presence of specialized and densely interconnected brain regions. Segregation was computed as (within‐network mean minus between‐network mean)/within‐network mean. Cognitive performance was assessed using Preclinical Alzheimer Cognitive Composite (PACC). The association between age and global dedifferentiation and network specific dedifferentiation was assessed using Pearson’s r correlations. Changes in global and association network dedifferentiation as a function of CDR were evaluated using a multivariate analysis of variance (MANOVA). Individual regression models determined if global and/or network specific dedifferentiation predicted cognitive performance. Age was accounted for in all models.

Result

Global dedifferentiation increased with age (i.e., segregation decreased: r= ‐0.15, p<0.01; see Figure 1), as did dedifferentiation of the default mode network (DMN; r= ‐0.14, p<0.01) and ventral attention network (VAN; r= ‐0.11, p<0.05). No other networks were associated with age (ps>0.05). Dedifferentiation of DMN differed as a function of CDR with dedifferentiation higher (i.e., lower segregation) in cognitively impaired individuals compared to cognitively normal individuals (ps£0.01; see Figure 2). Greater DMN dedifferentiation also predicted poorer cognitive performance, i.e., lower PACC score; p=0.001. No other measure of dedifferentiation (i.e., global or network specific) differed by CDR or predicted cognitive performance.

Conclusion

Results suggest that global and focal dedifferentiation occurs with aging, but only focal dedifferentiation occurs in AD. Furthermore, dedifferentiation of the DMN is sensitive to decreases in cognitive performance.
Air pollution and biomarkers of Alzheimer’s disease in cognitively unimpaired individuals
Authors: Crous‐Bou Marta , Alemany Silvia , Vilor‐Tejedor Natalia , Milà‐Alomà Marta , Suárez‐Calvet Marc , Salvadó Gemma , Cirach Marta , Arenaza‐Urquijo Eider M , Sánchez‐Benavides Gonzalo , Grau‐Rivera Oriol , Minguillón Carolina , Fauria Karine , Gispert Juan Domingo , Nieuwenhuijsen Mark , Zetterberg Henrik , Blennow Kaj , Kollmorgen Gwendlyn , Eichenlaub Udo , Sunyer Jordi , Molinuevo Jose Luis ,   ALFA Study
Published: December 2020

Background

Air quality might contribute to incidence of dementia‐related disorders, including Alzheimer’s disease (AD). The aim of our study was to examine whether air pollution may be associated with abnormal concentrations of AD cerebrospinal fluid (CSF) and neuroimaging biomarkers in cognitively unimpaired individuals at increased risk of AD. Additionally, potential effect modification by amyloid‐β(Aβ) and APOE‐ɛ4 status was investigated.

Methods

The ALFA (ALzheimer and FAmilies) study is a prospective cohort of cognitively unimpaired, middle‐aged subjects, many AD patients’ offspring. Land Use Regression models were used to estimate residential exposure to air pollutants including nitrogen oxides (NO2, NOx) and particulate matter (PM2.5, PM2.5 abs, PM10, PM coarse). For a subset, we measured CSF levels of Aβ42, Aβ40, p‐tau, t‐tau and neurofilament light (NfL) using NeuroToolKit and Elecsys® immunoassays (Roche Diagnostics). They also underwent a [18F]flutemetamol amyloid PET scan to assess cerebral amyloid load (Centiloid). A total of 148 participants (all residents of Barcelona) with data available on exposure to air pollutants and core AD biomarkers were included in this cross‐sectional analysis. Multiple linear regression models were used to test the association between exposure to air pollutants and biomarkers. Age, sex, years of education and APOE‐ɛ4 status were included as potential confounders. To test for effect modification, Aβ positivity was defined by an Aβ42/Aβ40 ratio<0.071. Stratified analyses by APOE genotype were also performed.

Results

Greater exposure to air pollutants was associated with increased levels of CSF p‐tau, t‐tau and NfL, and reduced Aβ42/40 ratio. Additionally, higher exposure to nitrogen oxides was significantly associated with increased Aβ deposition in the brain (Figure1;*p<0.05). Such associations were driven by Aβ‐negative individuals (p‐interaction<0.05) (Figure 2;*p<0.05). Furthermore, the association between increased exposure to air pollutants and Ab deposition was only seen in APOE‐ɛ4 non‐carriers, while the positive association between exposure to air pollutants and CSF p‐tau, t‐tau and NfL was only observed among APOE‐ɛ4 carriers (Figure 3;*p<0.05).

Conclusion

In a population of cognitively unimpaired adults with increased risk of AD, exposure to air pollution is associated with abnormal core AD biomarker results. Further research is granted to elucidate the mechanisms involved in such associations.
Impact of putative cilia targeting sequences on APP trafficking
Authors: Swaminathan Swathi
Published: December 2020

Background

Primary cilia are non‐motile, sensory antennae protruding from most eukaryotic cells. These cilia are enveloped in plasma membrane that is adorned with an array of receptor proteins and are essential in regulating fundamental neurophysiological activities, including neurogenesis and memory encoding. In the mature brain, both neurons and astrocytes exhibit a single primary cilium. Defects in the primary cilia lead to a myriad of diseases, one such being impaired neuronal development and cognitive domains, also compromised in Alzheimer’s disease (AD). AD is primarily characterized by the accumulation of amyloid β plaques (Aβ) on the brain. Aβ plaques result from the proteolytic cleavage of the Aβ peptide, a product of the amyloid precursor protein (APP). In our lab, we have previously shown that increased Aβ disrupts primary cilia structure and APP co‐localization at the primary cilium, indicating a possible functional role of APP in AD pathogenesis. At the base of all primary cilia is a protein complex responsible for maintaining a distinct protein and lipid profile from the cytoplasm. Therefore, only those proteins intended for the primary cilia are trafficked from the Golgi to the base of the primary cilia, which is believed to be mediated by specific cilia targeting sequences.Examples of cilia targeting sequences include VxPx, RVxP, AxxxQ amino acid sequences.

Method

In order to characterize these putative cilia targeting sequences, we utilized site directed mutagenesis to create and compare mutants of all the putative sequences and confocal microscopy in multiple cell lines like MDCKs, astrocytes and neurons. These experiments were conducted to investigate the consequences of disrupting the cilia targeting sequences in APP 695.

Result

We have identified a total of 7 putative cilia targeting sequences in the human APP 695 isoform and also found that only one of the seven targeting sequences is located in the C‐terminal ectodomain of the isoform.

Conclusion

Since most motor proteins identified at the cytoplasmic C‐terminus are responsible for trafficking APP to its destination, we believe that this cilium targeting sequence may be responsible for APP localization at the primary cilia,thereby rendering them as a potential therapeutic target for AD.
Cumulative effects of sleep quality on risk for incident mild cognitive impairment (MCI): Results from the Einstein Aging Study (EAS) cohort
Authors: Derby Carol A , Wang Cuiling , Katz Mindy J , Lipton Richard B , Buxton Orfeu M
Published: December 2020

Background

Sleep deficiency and sleep disorders are common in older adults and have been linked to cognitive decline and dementia risk. Better understanding the association of sleep patterns over time with onset of early cognitive changes may facilitate interventions to prevent AD and dementia. Few studies have reported on the association of cumulative longitudinal measures of sleep quality with onset of mild cognitive impairment (MCI). The Einstein Aging Study (EAS) longitudinal cohort provided the opportunity to examine whether cumulative exposure to poor sleep quality predicts incident MCI in a community‐based cohort.

Method

Analyses include 639 EAS participants from Bronx, NY, age > 70 years (mean 78.6± 5.3, 62% female, 65% White/28% African American), without MCI or dementia at initial assessment and with at least one annual follow‐up. Sleep was assessed annually using the Medical Outcomes Study of Sleep (MOS‐S) questionnaire. Factor analysis of the 12 MOS‐S items yielded three factor scores based on the sum of items with loading ≥ 0.5, such that higher scores indicate better sleep quality. Factors included were: Daytime somnolence, Disturbed sleep and Perceived sleep adequacy. Trajectories of these indices over annual follow‐up were examined using linear mixed effects models. The associations of concurrent and cumulative sleep quality indices on MCI risk were estimated from Cox models with time dependent exposure, adjusting for age, sex, education and race/ethnicity.

Result

Over a mean of 4.4 annual assessments, 162 cases of incident MCI occurred. During follow‐up, sleep adequacy increased (p < 0.0001), daytime somnolence decreased (p = 0.025) and sleep disturbance showed no significant pattern of change (p > 0.05. Cox models showed no association between concurrent indices of sleep quality and incident MCI (all p > 0.05). However, cumulative effects of sleep quality on MCI risk were observed. Over time, less daytime somnolence, less frequent disturbed sleep and better sleep adequacy were associated with reduced risk of incident MCI (HR’s: Somnolence = 0.97, Disturbed = 0.98), Adequacy = 0.97; all p< 0.0001).

Conclusion

Adverse effects of poor sleep quality on cognition may be cumulative suggesting that improving sleep in older adults may prevent or delay MCI onset.
Distinct patterns of time spent together in older adult couples: The role of cognitive function, illness, and activity engagement
Authors: Miller Lyndsey M , Au‐Yeung Wan‐Tai M , Reynolds Christina L , Beattie Zachary , Kaye Jeffrey
Published: December 2020

Background

Previous research has indicated that the way in which older adults spend their time (i.e. together with a partner or outdoors) is indicative of cognitive function, overall health, and well‐being, but few studies have assessed time spent together objectively. Accordingly, we sought to characterize distinct patterns in the amount of time that couples spend together and out of home using data from unobtrusive in‐home sensors, and identify factors that differentiated couples in distinct patterns.

Method

Continuously‐assessed in‐home sensor data was obtained from 152 older adult participants with varying levels of cognitive function living independently as couples. An algorithm was created to divide the data into segments by day, occupancy time by room, and home exits. The data on time together, apart, and out of home was then used in a latent profile analysis.

Result

Two distinct patterns were identified (p = 0.05; entropy = 0.85; posterior probabilities > 0.90). Couples observed in the “together” pattern (n=60 homes) were together within the same room 55% of the time, out of the home 31% of the time, and were apart within different rooms 14% of the time. In the second “apart” pattern (n=16 homes), couples spent less time together, less time out of the home, and more time apart, when compared with the “together” pattern. Multivariable logistic regression indicated that couples were more likely to be observed in the ‘apart’ pattern when men exhibited higher cognitive function (OR = 1.23, 95% CI = 1.01‐1.53), had more health problems (OR = 1.25, 95% CI = 1.03‐1.54), and were more engaged in life activities such as hobbies and computer use (OR = 1.19, 95% CI = 1.02‐1.40). None of the variables derived from female participants significantly differentiated the patterns, nor did couples’ age, education, depressive symptoms, physical activity, or sleep duration.

Conclusion

Men may have a more influential role on time spent together within older adult couples. Since couples observed in the “together” pattern were differentiated by men with lower cognitive function and less activity engagement, future research will examine whether this pattern may be an objective indicator of waning independence and increased strain on their partners.
Cognitive status, brain amyloid pathology, and neurodegeneration are associated with altered white matter microstructure
Authors: Okonmah‐Obazee Stephanie , Craft Suzanne , Bateman James R. , Williams Benjamin J. , Cleveland MaryJo , Yang Mia , Haq Ihtsham , Rogers Samantha D. , Sachs Bonnie C. , Fischer Eric , Sai Kiran Solingapuram , Williamson Jeff D. , Whitlow Christopher T. , Lockhart Samuel N.
Published: December 2020

Background

Brain amyloid (AB) and neurodegeneration (assessed using PET and MRI) are key AD pathology biomarkers, particularly during transitions from cognitively unimpaired (CU) to cognitively impaired (CI) states. Importantly, the role of brain white matter microstructural measures in these changes, such as those derived from neurite orientation dispersion and density imaging (NODDI), are poorly understood. We explored roles of cognitive status, brain amyloid pathology, and neurodegeneration on NODDI Free Water (FW), a potential neuroinflammation biomarker.

Method

Participants enrolled in the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core cohort (N=74, Table 1) underwent neuropsychological assessment, T1/NODDI MRI, and PiB PET. Participants were adjudicated as cognitively impaired (MCI or AD) or unimpaired using NIA‐AA criteria. T1 MRI were processed (FreeSurfer v5.3) to generate regions of interest (ROIs). An “AD‐signature” cortical thickness value was calculated, and thresholded to classify participants as neurodegeneration‐positive (N+) or ‐negative (N‐). A set of AD‐sensitive cortical ROIs was used to extract mean PET signal, which was thresholded to adjudicate AB positivity (AB‐/AB+). NODDI was processed to yield parameter maps using AMICO; mean isotropic volume fraction (FW) was calculated over a set of white matter tract ROIs. A two‐way ANOVA/ANCOVA (covariates: age, sex, education) assessed effects of neurodegeneration and AB on FW (N+/N‐ x AB+/AB‐), and a two‐way ANOVA/ANCOVA assessed effects of cognitive impairment and AB on FW (CU/CI x AB+/AB‐).

Result

We first examined effects of neurodegeneration and AB on NODDI FW. We found a significant main effect of neurodegeneration (p=.042), such that N+ had higher FW; this was marginal after adjustment (p=.07). We also observed a significant main effect of AB (p<.001; adjusted p=.012), with AB+ having higher FW. There was no significant interaction. We next explored how cognitive status and AB interacted on FW. We found a significant main effect of cognitive impairment, with CI having higher FW (p=.018; adjusted p=.013). We also found an interaction between diagnosis and AB (p=.037; adjusted p=.044) such that among AB+ individuals, presence of CI related to increased FW (Figure 1).

Conclusion

NODDI FW increases were significantly affected by the presence of neurodegeneration, AB positivity, and cognitive impairment.
A novel approach to isolate brain‐cell–derived exosomes from plasma to better understand pathogenesis of Alzheimer’s disease
Authors: Kumar Ashish , Hughes Timothy M. , Craft Suzanne , Deep Gagan
Published: December 2020

Background

Exosomes are nano‐vesicles ∼30‐150 nm in diameter that are released by all cell types and present in all biofluids. Exosomes are loaded with unique cargo, including RNAs, proteins, lipids, and metabolites that relate to the cell of origin and the patho‐physiological state of the organism. Discovery of brain cells‐derived exosomes in the circulation led to studies examining their role as potential mediators as well as ‘liquid biopsies’ for Alzheimer’s disease and related dementias (ADRD). However, currently, most work with exosomes focus on one class of exosome subtype at a time. Here, we have developed a novel and sensitive method to simultaneously extract pure and biologically active exosomes secreted from various cells of the neurovascular unit, including: neuron‐derived exosomes (NDE), astrocytes‐derived exosomes (ADE), endothelial‐derived exosomes (EDE), pericyte‐derived exosomes (PDE), and oligodendrocyte‐derived exosomes (ODE).

Method

We employed ExoQuick precipitation method to isolate total exosomes from the plasma of age‐matched individuals with normal cognition or AD. We optimized methods to label specific antibody with photo‐cleavable (PC)‐biotin. Next, we extracted exosomes of the neurovascular unit from the total exosomes using streptavidin coated magnetic beads and biotin or PC‐biotin‐tagged antibodies (L1CAM for NDE; GLAST for ADE; PDGFRα for ODE; CD31 for EDE and PDGFRβ for PDE). To release the exosomes, magnetic beads were exposed to UV light (280 nm). We performed immunogold labelling, transmission electron microscopy (TEM), flow cytometry and ELISA to validate the isolated exosome populations.

Result

Following our novel methods, we extracted NDE, ADE, EDE, PDE, and ODE from total plasma exosomes. We validated the purity of each exosome population by flow cytometry, and confirmed the surface expression of exosomal biomarkers (CD63 and CD9) by immunogold labelling and TEM. Lastly, ELISA analyses showed that Aβ1‐42 was absent in all exosome populations from healthy individuals but significant level of Aβ1‐42 was detected in all the exosome populations (NDE, ADE, EDE, PDE, and ODE) from AD patients.

Conclusion

We have developed a novel, sensitive and reproducible method to isolate and characterize various brain cells‐derived exosomes from plasma which could lead to development of novel blood based exosomal biomarkers to better understand AD pathogenesis.
Exploring retinal imaging as a novel biomarker of Alzheimer’s disease
Authors: Young Kelly Z , Moinuddin Omar , Khandwala Nikhila , Albin Roger L , Barmada Sami , Besirli Cagri
Published: December 2020

Background

Alzheimer disease (AD) and frontotemporal dementias (FTD) exhibit distinct pathologies but are difficult to reliably differentiate on clinical grounds. Detailed neuropsychiatric evaluations, cerebrospinal fluid analysis, and anatomic or molecular imaging may improve diagnostic accuracy. Even so, these modalities are expensive, time‐consuming, and often inaccessible. The retina is a developmental outgrowth of the brain, and visual dysfunction is well documented in dementia subjects. As such, the retina may be a useful surrogate for diagnosing and monitoring the progression of dementias. We explored the potential role of multimodal retinal imaging for identifying ocular biomarkers of dementia and correlated our findings with cerebral amyloid burden.

Method

We recruited 5 participants with mid‐to‐late stage AD, 2 participants with mid‐to‐late stage FTD, as well as 9 age‐matched healthy controls. Each participant underwent comprehensive ophthalmologic examination and ocular imaging (Optical Coherence Tomography (OCT), OCT‐angiography (OCTA), wide‐field fundus photography, near‐infrared imaging, and fundus autofluorescence). Ocular findings were then correlated with cerebral amyloid burden, as detected by [11C]PiB PET.

Result

We did not observe significant differences in retinal layer thicknesses, retinal perfusion, or sizes of the superficial avascular zones between PET‐confirmed AD, clinically diagnosed FTD, and control subjects. AD subjects consistently demonstrated higher autofluorescence signal intensity (18.5 au), as detected by fundus autofluorescence imaging compared to FTD (16.0 au) and age‐matched control subjects (16.3 au). Near‐infrared ocular imaging also revealed a 1.95 fold increase in retinal reflectance in AD subjects compared to FTD and control subjects.

Conclusion

Identification of novel dementia biomarkers is essential for accurate diagnosis and monitoring of dementia progression. Recent studies highlighted the potential use of OCT and OCT‐A to identify retinal layer thickness changes in AD and FTD. Our pilot study suggests that autofluorescence and near‐infrared reflectance, but not OCT or OCT‐A, detect retinal imaging changes that correlate with cerebral amyloid burden. These modalities may thus serve as accurate dementia biomarkers to aid in diagnosis, assessing pathologic severity, and gauging response to therapy in AD and FTD.
How understudied populations leverage our understanding of Alzheimer’s disease genetics
Authors: Dehghani Nadia , Bras Jose , Guerreiro Rita
Published: December 2020

Background

The majority of genome‐wide association studies have been conducted using samples with a European genetic background. As a field, we acknowledge this limitation and the need to increase the diversity of populations studied. A major challenge when designing and conducting such studies is to assimilate large samples sizes to have enough statistical power to detect variants associated with disease, particularly when trying to identify variants with low and rare minor allele frequencies. In this study, we aimed to illustrate the benefits, to genetic characterization of Alzheimer’s disease (AD), in researching currently understudied populations. This is important for both fair representation of world populations and the translatability of findings.

Method

We have conducted a thorough literature search to understand the contributions of studies, on different populations, to AD genetics.

Result

To accomplish this, we have systematically quantified the number of studies identifying mutations in known disease‐causing genes, in all countries across the world, and discussed the contributions of research in understudied populations to the identification of novel genetic factors in this disease. Related to this, we compared the varied effects of genome‐wide significant SNPs across populations by focusing on loci that show different association profiles between populations (a key example being APOE).

Conclusion

This work functions to both highlight how understudied populations have furthered our understanding of AD genetics, and to help us gage our progress on understanding the genetic architecture of this disease in all populations.
Interactive associations of nocturnal sleep disturbance and vascular risk with prospective cognitive decline in clinically normal elderly individuals: Findings from the National Alzheimer's Coordinating Center Uniform Data Set
Authors: Bubu Omonigho M , Mbah Alfred , Umasabor‐Bubu Ogie Queen , Mukhtar Fahad , Turner Arlener D , Williams Natasha , Ogedegbe Gbenga , Jean‐Louis Girardin A , Osorio Ricardo S
Published: December 2020

Background

We determined whether Nocturnal Sleep Disturbance (NSD) and vascular risk act together to promote prospective cognitive‐decline in clinically normal older adults; and, evaluated the unique influence of their combined risk on prospective cognitive decline beyond that of commonly used Alzheimer’s disease (AD) biomarkers.

Method

Longitudinal study utilizing data from the National Alzheimer's Coordinating Center (NACC) Uniform Data set (UDS). Participants (N=361) were cognitively normal at baseline and had baseline medical data to quantify vascular risk, using an adaptation of the Framingham Heart Study general cardiovascular disease (aFHS‐CVD) risk‐score and CSF‐Aβ, CSF P‐tau, CSF T‐tau and MRI‐imaging data with at least one UDS follow‐up visit. The Neuropsychiatric Inventory Questionnaire characterized NSD and incident mild cognitive impairment (MCI) diagnosis during UDS follow‐up characterized prospective cognitive decline. Logistic mixed‐effects models with random intercept and slope, controlling for age, sex, education, APOE‐ε4 and their interactions with time examined associations between the NSD/ FHS‐CVD risk score and longitudinal cognitive‐decline.

Result

Of the 361 participants, 223 (62%) were women and 35 (9.7%) had NSD. The proportion of males versus females with sleep problems was 10.9% vs. 9.3% respectively. For participants with NSD and no NSD, the mean (SD) age was 71 (7.3) and 70 (5.7) years and average follow‐up time was 5.2 (2.6) and 4.9 (2.7) years, respectively. Both NSD (OR: 1.42, P < .003) and higher aFHS‐CVD risk score (OR; 1.63, P < .001) were significantly associated with increased/faster likelihood to develop incident MCI. The interaction of NSD and the aFHS‐CVD risk‐score with time was significant (P < .001) suggesting an increase in the likelihood of conversion to MCI increased over time. Stratifying aFHS‐CVD risk score into tertiles, NSD participants in the highest (OR: 2.82, P < .003) and middle tertile (OR: 2.38, P < .001) were significantly more likely to develop incident MCI, compared with participants without NSD in the lowest aFHS‐CVD risk score tertile, suggesting a synergistic effect. This effect remained robustly associated with incident MCI even after adjustment for AD biomarkers.

Conclusion

In elderly cognitive‐normal individuals, NSD and vascular risk may be alternate and non‐invasive measures of assessing risk of prospective cognitive‐decline in preclinical AD.