bluuebunny/crossref_metadata_2025 huggingface dataset:
The Amsterdam Experience: Insights from 7 years of retinal biomarker experience in a tertiary memory clinic
Authors: den Haan Jurre
Published: December 2021

Background

The retina, embryologically derived from the neural tube, contains neurons, glial cells and vasculature similar to the brain and as an extension of the central nervous system may provide patient friendly, inexpensive and disease specific biomarkers that could aid diagnosis for the clinician in current clinical practice and serve as therapeutic read‐out in clinical trials.

Methods

Over the last 7 years research in the Amsterdam Dementia Cohort using in‐vivo methods in the form of optical coherence tomography (OCT), fundus photography, OCT angiography and fluorescence imaging and ex‐vivo methods were used for biomarker discovery. These studies aimed to identify biomarkers for amyloid (A), tau (T), neurodegeneration (N) and vasculature (V).

Result and Conclusion

Here we present an overview of the data collected together with the valuable lessons learned from the specific projects. Caveats of the current methods and suggestions for future research will be presented to move the field of retinal biomarker discovery and validation further.
The shift to virtual, Part 1: Adoption of virtual options by older populations for clinical care, health education resources, and social interaction
Authors: Lock Sarah Lenz
Published: December 2021

Background

The pandemic has created new barriers for the delivery of healthcare resources and information, as well as in‐person delivery of health care, caregiving and social engagement. This is particularly true for people in nursing facilities, particularly those with dementia often resulting in tragic consequences. Social distancing, masks and lock downs along with lack and shortages of PPE prevented the physical presence and contact of people engaged in delivering dementia care causing greater suffering of people living with dementia, and enormous stress to providers, family and friends. This has necessitated a major shift in how people access both human interaction and healthcare information. This presentation will provide lessons learned from the transition to virtual‐based public education and virtual social interaction aimed at mitigating the risk of exposure to COVID‐19 and harms of social isolation.

Method

This dramatic shift has necessitated a explosive adoption of telemedicine and alternative, technological visitation as well as a more targeted approach to virtual public health campaigns focused on older adults. A natural experiment has been created as we rushed to adopt virtual communication methods to deliver vital services for older people, including those with cognitive impairment.

Result

Efforts will be made to track the results and long‐term implications for adoption of telehealth resources and virtual visitation for older populations concerned about cognitive health as well as those living with dementia and their caregivers.

Conclusion

Public policies are being developed to assist in the adoption and use of technology for delivery of health care information, telemedicine, visitation to combat social isolation. The lessons learned should inform the future of long term care policies for people with dementia and their caregivers.
An examination of atypical primary progressive aphasia variants
Authors: Botha Hugo , Duffy Joseph R , Utianski Rene L , Machulda Mary M. , Clark Heather M , Strand Edythe A , Boland Sarah , Ali Farwa , Martin Peter R , Buciuc Marina , Boeve Bradley F. , Schwarz Christopher G. , Senjem Matthew L. , Reid Robert I. , Jones David T. , Graff‐Radford Jonathan , Knopman David S. , Petersen Ronald C. , Bigio Eileen H , Lowe Val J , Reichard Ross R. , Jack Clifford R. , Ertekin‐Taner Nilufer , Rademakers Rosa , DeTure Michael , Ross Owen A. , Dickson Dennis W , Whitwell Jennifer L , Josephs Keith A
Published: December 2021

Background

The Neurodegenerative Research Group (NRG) at Mayo clinic has followed patients with degenerative speech and/or language disorders for over a decade. In this presentation I will present data from this cohort to inform a broader discussion about the importance of apraxia of speech (AOS) and its subtypes, heterogeneity within the agrammatic PPA variant, and perils of mixed phenotypes.

Method

We reviewed the NRG database to identify patients who initially presented with isolated (PPAOS), AOS in conjunction with agrammatic aphasia (AOS‐PAA), isolated agrammatic aphasia (PAA), and patients who had PAA or AOS overlapping with another degenerative diagnosis. Data from the following clinical instruments were abstracted: WAB AQ (aphasia severity), UPDRS III (parkinsonism), WAB Praxis (ideomotor apraxia), and the MoCA (cognitive ability). We assessed the effect of baseline diagnosis and AOS subtype on these outcomes over time using Bayesian linear mixed effects models. We qualitatively reviewed longitudinal diagnostic trajectories. Preliminary analyses were done on available autopsy data.

Result

PAA was associated with greater aphasia at baseline and more rapid decline; PPAOS was associated with normal language at baseline and slow decline; and PAA‐AOS with intermediate baseline aphasia and decline. However, for those with AOS longitudinal decline differed based on AOS subtype: prosodic PPAOS was associated with the slowest decline and phonetic PAA‐AOS with the fastest. Some patients met criteria for non‐PPA disorders during follow up. However, compared to patients who met criteria for these disorders at enrollment, the speech/language‐first patients remained qualitatively distinct, and neither resembled the cases that were mixed at onset. Preliminary autopsy data suggests that AOS is predictive of tau and that the specific tauopathy may be related to the initial syndrome and AOS subtype.

Conclusion

The differences between PAA, PAA‐AOS and PPAOS suggest that these disorders should not be lumped. In fact, the longitudinal trajectories are sufficiently different that doing so would add noise to observational and interventional studies. Instead, more detailed phenotyping, including AOS subtype, can aid prognostication and may improve prediction of the underlying pathology. Finally, caution should be exercised when considering PPAOS and PPA patients for other FTLD diagnostic categories.
A data‐driven latent atrophy factor model reveals differential associations between relative frontal atrophy patterns and specific neuropsychiatric symptoms in Alzheimer’s disease
Authors: Singleton Ellen H. , Groot Colin , Bader Ilse , Papma Janne M. , Scheltens Philip , Pijnenburg Yolande A.L. , Ossenkoppele Rik
Published: December 2021

Background

to examine the relative role of the frontal cortex in neuropsychiatric symptoms in Alzheimer’s disease (AD), we assessed associations between latent atrophy factors and neuropsychiatric symptoms in AD.

Method

We employed a data‐driven Bayesian modelling framework based on Latent Dirichlet Allocation (LDA) to identify latent atrophy factors in a cohort of 1135 Aβ‐positive MCI and AD patients from the Amsterdam Dementia Cohort (age: 66.4±7.44, 50% male, MMSE: 22.3±0.1). The model uses standardized gray matter density images as input, adjusted for age, sex, intracranial volume and scanner field strength, and yields voxelwise probabilistic maps for a predetermined number of atrophy factors, providing data–driven factor expression loadings per individual. These factor expressions were correlated to scores on the Neuropsychiatric Inventory (NPI) using general linear models, adjusting for sex, age, education and MMSE scores.

Result

the LDA model revealed a frontal (dorsolateral and insular), a medial temporal lobe (hippocampal and entorhinal), a temporoparietal and a late‐stage (sensorimotor and occipital) factor (Figure 1). The highest percentage of individual expressions was found in the late‐stage factor (34.0±0.6), followed by the MTL (27.3±0.6), TPC (22.0±0.5) and frontal (16.7±0.5) factors (Figure 2). Higher frontal expression relative to both the MTL and late‐stage factors was associated with a higher odds for apathy (MTL; OR=1.012, p=0.010, late‐stage; OR=1.011, p=0.046; Figure 3). Negative associations, however, were found between relative frontal atrophy and disinhibition, anxiety and nighttime behaviors (Figure 3); a higher frontal load relative to each reference factor related to a lower odds for disinhibition (frontal‐MTL: OR=0.978, p=0.035; frontal‐TPC: OR=0.969, p=0.042; frontal‐‘late‐stage’: OR=0.976, p=0.029), a higher frontal load relative to MTL and late‐stage factors were associated with a lower odd for anxiety (frontal‐MTL: OR=0.984, p=0.015; frontal‐‘late‐stage’: OR=0.983, p=0.003) and night‐time behaviors (frontal‐MTL: OR=0.982, p=0.023; frontal‐‘late‐stage’: OR=0.980, p=0.005).

Conclusion

Relative frontal atrophy was related to more frequent apathy and less frequent disinhibition, anxiety and night‐time behaviors and may point towards more AD‐typical regions as determining neurobiological regions for disinhibition, anxiety and night‐time behaviors than frontal regions in AD. Alternatively, disinhibition may be more dependent on the right frontal pole, less prominently involved in the current frontal factor.
Interactive care: A web‐based platform for remote caregiving and functional independence in older adults with cognitive impairment
Authors: Weakley Alyssa , Liu Xin , Duvvur Sanjna , Kaushal Harshita , Mussi Nicola , Namboodiri Sudev , Choi Yong , Farias Sarah Tomaszewski
Published: December 2021

Background

Remote family caregiving of cognitively impaired older adults has many challenges including lack of evidence‐based interventions that meets the needs of both stakeholders. Further, physical distance may lead to emotional distance including feelings of loneliness and depression in the care receiver as well as helplessness and burden in the caregiver. To fill this gap, our team sought to develop the Interactive‐Care (I‐Care) platform which transforms and augments the traditional whiteboard, a compensatory cognitive rehabilitation tool for dementia care, to a digital format accessible from any device. I‐Care provides 5 main functions: home page (orientation information), calendar, to‐do list, messaging hub, and brain health center. A beta version of I‐Care was developed based on usability principles from human‐computer interaction literature, caregiving needs assessments, and guidelines for creating technology for older adults with cognitive impairment. The current project focuses on the first of three rounds (1. experts, 2. caregivers, 3. individuals with mild cognitive impairment/mild dementia) of iterative interface design.

Method

Individual semi‐structured interviews were conducted with experts in dementia caregiving, gerontechnology, and digital health. Prior to each interview, experts were provided with the I‐Care weblink and a project summary for review. All interviews were conducted over live‐stream video and were audio recorded for transcription. The “share screen” function was used to demonstrate the different I‐Care components and feedback was solicited.

Results

On a scale from 1‐10, with 1 being not at all useful and 10 being very useful, experts rated I‐Care as a useful tool both for individuals with mild cognitive impairment/mild dementia (M = 8.33, SD = 1.53) and remote caregivers (M = 9.33, SD = 1.15). Recommended improvements included minor modifications to the user interface (e.g., text contrast, reorganization of visual components), functionality (e.g., ability to add or subtract features based on level of cognitive impairment), and expansion (e.g., medication tracking with pillbox sensor).

Conclusions

Although more data is needed, I‐Care is a promising remote caregiving tool with potential to reduce emotional distance despite physical divide. Next steps include conducting similar interviews with caregivers and individuals with cognitive impairment followed by a pilot study with 10 care dyads.
Higher dietary inflammatory index scores are associated with increased incidence of all‐cause dementia in the Framingham Heart Study
Authors: van Lent Debora Melo , Himali Jayandra J , Gokingco Hannah , Aparicio Hugo J , Gonzales Mitzi M , Salinas Joel , Beiser Alexa S , Seshadri Sudha , Jacob Mini Elizabeth
Published: December 2021

Background

Nutrition is hypothesized to protect against systemic chronic inflammation, which plays an important role in the development and progression of disease including dementia. We evaluated whether higher (i.e. pro‐inflammatory) Dietary Inflammatory Index (DII) scores were associated with increased incidence of all‐cause dementia and Alzheimer’s disease (AD) in the community‐based Offspring Framingham Heart Study (FHS).

Method

1021 older adults (mean age 69 years [standard deviation (SD)], 5;52.3% women]) completed a validated 126‐item Food Frequency Questionnaire (FFQ). We created a DII score (based on the published method by Shivappa et al. 2014) based on previous studies linking individual dietary factors to six inflammatory markers (i.e. C‐reactive protein, interleukin (IL)‐1β , IL‐4, IL‐6, IL‐10 and tumor necrosis factor‐alpha, consisting of 31 components. A cumulative DII score was calculated by averaging across a maximum of three FFQs (administered at FHS exams 5 (1991‐1995), 6 (1995‐1998), and 7 (1998‐2001)). Exam 7 was considered as study baseline and participants were followed over a mean 12.6 years (SD 5.5). We excluded participants aged <60 years, those with prevalent dementia and/or other neurological conditions, and/or no dementia follow‐up.

Result

150 participants developed all‐cause dementia (including 118 participants who developed AD). Higher DII scores were associated with an increased incidence of all‐cause dementia following adjustment for age and sex (HR1.11,95%CI 1.01‐1.22,p=0.03). The relationship remained after additional adjustment for education, apolipoprotein e4, body mass index, smoking status, physical activity index score, total energy intake, lipid lowering medication and total cholesterol:high‐density lipoprotein‐ratio (HR1.14,95%CI 1.01‐1.29,p=0.04). We observed no relationship between higher DII scores and incident AD. Additionally, we observed no significant interactions between higher DII scores and sex, the presence of an APOE ε4 allele, or physical activity in their associations with incident all‐cause dementia or AD.

Conclusion

Higher DII scores were associated with a higher risk of incident all‐cause dementia, but not incident AD. Although these promising findings need to be replicated and further validated, our results suggest that diets which correlate with low DII scores could prevent late‐life dementia. Further, future studies are encouraged to test our findings among older adults of other race and ethnic groups and over a longer follow‐up period.
Augmented reality to detect subtle alterations in the early stages of Alzheimer’s disease: Preliminary results of the RADAR‐AD study
Authors: Muurling Marijn , de Boer Casper , Bügler Maximilian , Harms Robbert , Tarnanas Ioannis , Kouzak Rouba , Verheij Herman , Nies Vera J.M. , Daskalova Yoanna , Stolk Pieter , Durudas Andre , Curcic Jelena , Hannesdottir Kristin , Erdemli Gul , Hinds Chris , Wu Yuhao , Lucivero Federica , Stavropoulos Thanos G. , Owens Andrew P. , Narayan Vaibhav A. , Aarsland Dag , Visser Pieter Jelle ,   the RADAR‐AD Consortium
Published: December 2021

Background

The ‘Remote Assessment of Disease and Relapse – Alzheimer’s Disease’ (RADAR‐AD) study is assessing functional decline in Alzheimer’s disease (AD) using remote monitoring techniques (RMT’s). Compared to traditional pen‐and‐paper clinical assessments, RMT’s can continuously and objectively monitor function during activities of daily living (ADL), which are arguably more sensitive to the earliest stages of AD. The aim of this abstract is to compare the results of the augmented reality task ‘Altoida’, that recreates an ADL requiring spatial navigation and memory, implemented as a tablet application, between 1) healthy controls, preclinical AD and prodromal AD, and with 2) standard clinical tests for cognitive and functional decline.

Method

We included amyloid negative cognitively normal (healthy controls, n=10), amyloid positive cognitively normal (preclinical AD, n=7) and amyloid positive mild cognitive impaired (prodromal AD, n=4) participants (Table 1) from the RADAR‐AD study. The outcome of the Altoida test, consisting of a motor task and two tasks in which participants have to hide‐and‐seek virtual objects, is the validated Neuromotor Index (NMI), with higher scores reflecting normative scoring, according to age, sex and education. Cognition was measured using a word‐list‐learning test, digit symbol substitution test (DSST), Rey complex figure, verbal fluency and Boston naming test. Functional decline was assessed using the Amsterdam Instrumented Activities of Daily Living (AIADL) questionnaire.

Result

In our preliminary sub‐sample, healthy controls showed higher NMI scores compared to the preclinical AD and prodromal AD participants (p=0.02) (Figure 1). The NMI was related to the DSST only (Figure 2).

Conclusion

NMI scores differed between cognitively normal healthy controls and cognitively normal preclinical AD participants, while no differences could be found in cognitive and functional tests between these groups. The sample size will increase in the coming months, but despite the currently small sample, the preliminary results are promising in evidencing that digital biomarkers are potentially more sensitive than standard clinical tests in detecting the early stages of AD, which could be helpful in developing new endpoints in clinical trials. This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking RADAR‐AD (grant No 806999) and their associated partners.
Cerebrovascular disease and depressive symptomatology in individuals with subjective cognitive decline: A community‐based study
Authors: Diaz‐Galvan Patricia , Cedres Nira , Figueroa Nerea , Barroso Jose , Westman Eric , Ferreira Daniel
Published: December 2021

Background

Subjective cognitive decline (SCD) may be the first sign of Alzheimer’s disease (AD), but it can also reflect other pathologies such as cerebrovascular disease or conditions like depressive symptomatology. The role of depressive symptomatology in SCD is controversial. In this study, we investigated the association between depressive symptomatology, cerebrovascular disease, and SCD. We hypothesized three different scenarios, where depressive symptomatology would co‐exist, contribute to, or be a consequence of SCD (Figure).

Method

We recruited 225 cognitively unimpaired individuals from a prospective community‐based study (mean age (SD) = 54.64 (10.18); age range 35 – 77 years; 55% women; 102 individuals without any subjective cognitive complaint, 123 individuals with one or more complaints). SCD was assessed with a scale of 9 memory and non‐memory subjective complaints. Depressive symptomatology was assessed with established questionnaires. We used magnetic resonance imaging markers of white matter signal abnormalities (WMSA) and mean diffusivity (MD) to assess cerebrovascular disease. We combined correlation, multiple regression, and mediation analyses to investigate the association between depressive symptomatology, cerebrovascular disease, and SCD.

Results

We found that SCD was associated with higher cerebrovascular disease (WMSA: r=0.210, p<0.002; MD: r=0.216, p=0.001), older age (r=0.373, p<0.001), and increased depressive symptomatology (r=0.340, p<0.001). In turn, depressive symptomatology was not associated with cerebrovascular disease (WMSA: r=0.003, p<0.961; MD: r=0.076, p<0.321) or age (r=0.069, p<0.030). We also studied whether abnormalities in white matter MD in SCD may be due to cerebrovascular disease. Results showed that variability in MD was mediated by WMSA burden (p=0.026), presumably reflecting cerebrovascular disease.

Conclusion

In our community‐based cohort, depressive symptomatology co‐exists with SCD and reflects emotional factors, but does not reflect cerebrovascular disease. In addition, depressive symptomatology did not influence the capacity of SCD to predict underlying cerebrovascular disease. We suggest that therapeutic interventions for depressive symptomatology could alleviate the psychological burden of negative emotions in people with SCD, and intervening on vascular risk factors to reduce cerebrovascular disease should be tested as an opportunity to minimize neurodegeneration in SCD.
Stability of the novel blood‐based biomarkers under pre‐analytical sample handling conditions: Results of the SABB‐GBSC working group
Authors: Verberk Inge M.W. , Misdorp Els O. , Koelewijn Jannet , Ball Andrew J. , Blennow Kaj , Dage Jeffrey L. , Fandos Noelia , Hansson Oskar , Hirtz Christophe , Janelidze Shorena , Lee Ryan , Rissman Robert A. , Shan Dandan , Shaw Leslie M. , Yarasheski Kevin E. , Zetterberg Henrik , Edelmayer Rebecca M. , Teunissen Charlotte E.
Published: December 2021

Background

Pre‐analytical sample handling might affect the results of Alzheimer’s blood‐based biomarkers. In this collaborative study of the SABB‐GBSC working group guided by the Alzheimer’s Association, we elucidate the effects of the most common sample handling variations on blood‐based amyloid and non‐amyloid biomarkers.

Method

Freshly collected blood was differentially treated, to create sample sets (n=10 per condition). We investigated the effect of collection tube type, and of EDTA plasma handling variations: delayed centrifugation, centrifugation temperature, aliquot volume, delayed storage, and freeze‐thawing. Frozen aliquots were shipped to participating labs, to measure amyloid beta (Abeta) peptides (with different technologies: C2N LS‐mass spectrometry (MS), Shimadzu MALID‐MS, N4PE and N3PA Simoa, Euroimmun and Araclon ELISA), Abeta oligomerization tendency (OAβ; PeopleBio), glial fibrillary acidic protein (GFAP; Quanterix), neurofilament light (NfL; Quanterix), total tau (tTau; Quanterix) and phosphorylated tau181 (pTau181; Eli Lilly Simoa assay). Data analysis was descriptive.

Result

Using other sample types than EDTA plasma resulted in different absolute levels for most of the measured biomarkers (figures 1‐4), with generally higher levels in lithium‐heparin plasma, lower levels in sodium‐citrate plasma, and variable but comparable levels in serum. Independent of the technology used, when EDTA plasma was kept at room temperature pre‐ or post‐centrifugation, Abeta42 and Abeta40 levels remained stable for up to 3 hours, while at 24 hours levels were decreased. When kept at 2‐8°C, Abeta levels were stable for up to 24 hours delayed centrifugation or storage (figure 1 and 2). The Abeta42/40 ratio mitigated some of the variability noted in Abeta42 and Abeta40 levels for some of the technologies and conditions, but not for all (figure 3). Abeta42 and Abeta40 levels were robust to differences in tube filling, short‐term ‐20°C storage, and up to 4 freeze‐thaw cycles (figure 1 and 2). While the other biomarkers OAβ, GFAP, NfL and pTau181 were mostly resistant to pre‐analytical sample handling variations, tTau levels were affected by delayed centrifugation and by centrifugation temperature (figure 4).

Conclusion

Based on the current findings, we construct a standardized operating procedure for pre‐analytical blood sample handling, that will facilitate swift introduction of blood‐based biomarkers into research and clinical settings.
Being a frail older person at the time of the COVID‐19 pandemic
Authors: Chen Yaohua Sophie , Rohr Susanne , Werle Berenice Maria , Romero‐Ortuno Roman
Published: December 2021

Background

During the COVID‐19 pandemic, frail older individuals have been identified as a particularly vulnerable group for poor health outcomes, including cognitive decline and dementia. We aimed to reflect on the interaction between frailty and COVID‐19 with regards to health consequences.

Method

Using a rapid literature review approach, we aimed to identify what it means to be a frail older individual in the COVID‐19 pandemic from the perspective of three different settings: community, hospitals, and nursing homes. Four researchers from 4 countries (Ireland, France, Germany, and Brazil) reviewed articles from the MEDLINE database and grey literature including public policy briefs from their countries.

Results

In the community, some governments advised to practice “cocooning”, i.e. stay‐at‐home‐orders for older individuals. This brought unprecedented restrictions to lifestyles, leading to a potential frailty cascade among older adults. Social frailty likely caused mental ill‐health, cognitive and functional decline, increasing the risk for dementia. In hospitals, frailty affected from disease onset to survivorship. The clinical presentation was rather atypical, and the biological findings were more heterogenous. Some resource allocation strategies based on the Clinical Frailty Scale remained questionable and should take into account patients’ and carers’ needs. A quarter of patients had increased care needs at discharge. However, availability of rehabilitation and support services in the community has been reduced. Frail older adults living in nursing homes were the most vulnerable group. Isolating residents and limiting the spread of COVID‐19 was a key difficulty. Reduced visits from relatives, cancelled physical activities, and lack of social engagement worsened cognitive, behavioral, and physical conditions of the residents. There were also positive aspects such as the boom of digital literacy and telemedicine and a renewed debate on age and ageing.

Conclusions

The COVID‐19 pandemic spotlights the ageing population that is rapidly growing worldwide. Prolonged lifestyle restrictions during the pandemic led to poor health outcomes in frail older individuals, including cognitive decline and dementia. Lessons learned from how frail older individuals are getting through the pandemic provide a unique chance to improve health outcomes, community and health services and how we want to live as ageing societies.
Predicting the risk of incident dementia in older adults: The ADNI‐dementia risk score
Authors: Ezzati Ali , Thompson Paul M , Davatzikos Christos , Harvey Danielle J , Lipton Richard B
Published: December 2021

Background

There are many risk factors associated with incident dementia in older adults, however predicting the timeframe of progression to dementia is difficult. We aimed to develop a novel, machine learning‐derived model to predict the risk of incident dementia among non‐demented older adults.

Method

Using data from 1837 non‐demented participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), we used random survival forest (RSF) methods, a nonparametric decision tree machine learning approach, to identify predictors of incident dementia. Three sets of features were used: Model 1: Demographics (age, sex, race/ethnicity, years of education, BMI, marital status); Model 2: Demographics + Neuropsychological test scores and depression (NP; Alzheimer's Disease Assessment Scale – Cognitive (ADAS‐cog), Mini‐Mental State Examination (MMSE), geriatric depression scale (GDS)); and Model 3: Demographics + NP + Biomarkers (APOE4 status, hippocampal volume, global β‐amyloid PET‐SUVR). An integer‐based score was developed to estimate the 10‐year risk of incident dementia using regression coefficients from Cox Proportional Hazard models.

Result

Over up to 10 years of follow up (mean = 3.19), 377 participants (20.5%) developed incident dementia. The RSF models 2 and 3 demonstrated good discrimination (C‐index for Model 1, 0.58 [95% CI 0.53–0.59]; model 2, 0.68 [95% CI 0.65–0.71]; and model 3, 0.66 [0.62–0.69]. Performance of RSF models was similar to Cox‐based models, which used the same features. From the identified top‐performing predictors (listed in figure 1), an integer‐based risk score for 10‐year dementia incidence was created: ADNI‐Dementia risk score 1, 2, and 3. The cumulative 10‐year incidence of dementia increased in a graded fashion from quartile 1 to quartile 4 for all risk scores (Figure 2). Risk score 3, which included biomarkers, was the most specific model for detecting individuals unlikely to progress to dementia.

Conclusion

We developed a new risk score that integrates readily available demographic, clinical, and biomarker data to predict the risk of dementia among non‐demented older adults. Using this simple tool is practical in clinical setting.
Gait speed is associated with changes in number of depression symptoms in older adults with type 2 diabetes
Authors: Lavie Inbar , Beeri Michal Schnaider , Schwartz Yonatan , Soleimani Laili , Heymann Anthony , Ravona‐Springer Ramit
Published: December 2021

Background

We examined the longitudinal relationships between motor function and number of depression symptoms, both important predictors of poor health‐related outcomes, including cognitive impairment, in old age. Analyses were based on initially cognitively normal older adults with type 2 diabetes (T2D) participating in the longitudinal Israel Diabetes and Cognitive Decline (IDCD) study.

Method

Subjects [n=984; mean age 72 (SD=5); 40.4% female] underwent evaluations of motor functions‐ gait speed, measured by time to walk 3 meters (mean = 4.37 seconds; SD=2.35) and handgrip strength (mean 29 Kg; SD=10), and number of depression symptoms, assessed by the 15‐item version of the Geriatric Depression Scale (GDS) (mean=2, SD=2), at baseline and approximately every 18 months thereafter. Hierarchical Linear Mixed Models (HLMM), adjusting for demographic and cardiovascular risk factors as well as overall cognition, modeled the effects of motor function on repeated GDS scores

Result

Lower mean gait speed (based on all gait speed measurements) was associated with higher mean GDS scores (p=0.003) (based on all GDS measurements). A greater change in gait speed between measurements was associated with greater degree of change in GDS scores over the study period (p=0.034). Handgrip strength was not associated with number of depression symptoms or with their change over time

Conclusion

In older adults with T2D, lower gait speed was associated with a greater number of depression symptoms. The degree of change in walking speed was associated with degree of change in GDS, such that greater increase in 3‐meters' walking time was associated with a greater increase in number of depression symptoms over time. Future studies should examine why gait speed, but not grip strength, was associated with depression. Slower gait speed due to depression, i.e. reverse causality, cannot be ruled out. Whether strategies for improvement of gait speed (e.g. physical activity) are effective in treatment or prevention of depressive symptoms in older adults with T2D merits investigation.
Comparative analytical performance of multiple plasma amyloid‐beta assays and their relationship to amyloid PET
Authors: Zicha Stephen , Bateman Randall J. , Shaw Leslie M. , Bannon Anthony W. , Zetterberg Henrik , Horton Wesley A. , Baratta Michael , Kolb Hartmuth C. , Dobler Iwona ,   Emmanouil (Manos) Spanakis, Wang Wenting , Raunig David L. , Saad Ziad S. , Mordashova Yulia , Li Yan , Bjorklund Nicole L. , Edelmayer Rebecca M. , Martone Robert L. , Rubel Carrie E. , Mawuenyega Kwasi G. , Bollinger James G. , Weber Christopher J. , Meyers Emily A. , Potter William Z. ,   BC‐NSC Plasma Abeta Project Team
Published: December 2021

Background

The National Institute on Aging and the Alzheimer’s Association framework for classifying Alzheimer’s disease (AD) utilizes measures of pathology for amyloid, tau, and neurodegeneration (ATN), that can identify participants for clinical trials. Currently, amyloid pathology is determined by costly PET or invasive CSF measurements. When applied to participant selection, these measures are associated with high screen failure rates and contribute to the high costs and long duration of recruitment of AD clinical trials. Recent reports indicate plasma amyloid beta (Aβ) peptides correlate highly with PET and CSF amyloid measures. This study aims to characterize novel assays as a screening tool that can quantify plasma Aβ peptides in a robust and reproducible manner.

Method

The project team consists of representatives from pharmaceutical industry, nonprofit/patient advocacy, and academic institutions. Six plasma Aβ assays were selected to be part of the comparison: three liquid chromatography–mass spectrometry (LC‐MS/MS) assays and three immunoassays. Plasma samples with corresponding amyloid PET data were selected from ADNI n=130 (50% Aβ+): cognitively normal n=54 (37% Aβ+), mild cognitive impairment n=54 (46% Aβ+), and AD n=22 (91% Aβ+). Each participant’s sample was tested in a blinded fashion on all six assays with analytical controls. Statistical tests were performed to identify which assays can significantly improve the Area Under the Receiver Operating Characteristic (AUROC) curve for predicting amyloid PET status compared to age and APOE ε4 status alone.

Result

The project tested 130 samples across assays with comparison to amyloid PET. Initial results from assay providers show AUROCs to predict amyloid status at levels consistent with performance in earlier publications. A comparison of results for the various assays will be presented with respect to their ability to classify amyloid PET status and whether they add significantly to the prediction of amyloid positivity beyond age and genotype.

Conclusion

Measurement of Aβ in plasma contributes to addressing the amyloid component of the ATN framework and can be a pre‐screen or a substitute for PET or CSF screening. Further clinical validation of these assays is planned to assess amyloidosis detection performance in a cognitively normal population.
Animal fluency improvements and confrontation naming declines over 6 months are associated with differential conversion from MCI to AD in ADNI
Authors: Foldi Nancy S. , Tommet Douglas , Rabin Laura , Lamar Melissa , Jones Richard N , Mungas Dan M. , Choi Seo‐Eun , Grandoit Evan , Mukherjee Shubhabrata , Jutten Roos J. , Sikkes Sietske A.M. , Zhu Ryoui , Crane Paul K.
Published: December 2021

Background

Not everyone with mild cognitive impairment (MCI) progresses to Alzheimer’s dementia (AD). Predicting who will decline is important. We previously reported that 6‐months change scores for language, but not for memory, executive functioning, or visuospatial functions, identified a high‐risk subgroup. Here we consider more specific language processes and consider AD fluid and imaging biomarkers.

Methods

We used longitudinal data from 764 ADNI participants enrolled with MCI and still had MCI at 6 months, which was our baseline for Cox proportional hazards modeling of conversion to AD. We derived scores for four aspects of language: confrontation naming, animal fluency, letter fluency tests, and other language tests. We evaluated changes from enrollment to month 6 for each of these scores. We also adjusted models for APOE genotype, entorhinal thickness and hippocampal volume, and CSF amyloid and tau biomarkers.

Results

The sample’s mean age was 73.2 years, and 59% were male. From over 2918 total follow‐up years (mean 3.8), there were 287 conversions to AD. Cox models controlling for demographic characteristics, showed improvements in animal fluency scores associated with lower risk (HR=0.58, p=.005), but declines in confrontation naming were associated with higher risk (HR=1.74, p<.001). The animal fluency finding was somewhat attenuated when further controlling the Cox model for hippocampal volume (HR=0.64, p=0.10) and CSF biomarker findings (HR=0.61, p=0.12). Confrontation naming was not impacted by any of the imaging or fluid biomarkers we considered.

Conclusions

In MCI, the association between six‐month changes in language, and the AD risk appears to be driven by animal fluency improvements and confrontation naming declines. Improvement in animal fluency may reflect still functional access to semantic networks. The attenuation of this signal when controlling for hippocampal volume and CSF biomarkers suggests inability to improve animal fluency may reflect processes associated with hippocampal volumes and CSF biomarkers. Declines in confrontation naming may represent impaired lexical access. The independence of this signal from hippocampal volumes and CSF biomarkers suggests declines in this network may act independently of these biomarkers. These findings suggest intriguing lines of research to further understand the importance of language abilities among people with MCI.
Discrepancy between plasma pTau181 and tau‐PET statuses
Authors: Tissot Cécile , Kunach Peter , Therriault Joseph , Lussier Firoza Z. , Benedet Andréa Lessa , Chamoun Mira , Pascoal Tharick A. , Servaes Stijn , Bezgin Gleb , Arias Jaime Fernandez , Wang Yi‐Ting , Stevenson Jenna , Rahmouni Nesrine , Gauthier Serge , Rosa‐Neto Pedro
Published: December 2021

Background

Assessments of tau usually come from cerebrospinal fluid or Positron Emission Tomography (PET). However, those methods are expensive and not readily available. Current research is focusing on cost‐effective blood‐based biomarkers, and a novel immunoassay for plasma pTau181 has been created. Even though there are strong associations between plasma pTau181 and PET, no study has yet investigated whether plasma pTau181 can be used to detect early AD‐pathology. Does the status of plasma pTau181 always correlate with tau‐PET status?

Method

We assessed 269 individuals from the TRIAD cohort (164 CU, 60 MCI and 45 AD) that underwent plasma pTau181 assessment, [18F]MK6240 tau‐PET scan, [18F]AZD4694 amyloid‐PET scan to assess their amyloid status, an MRI and a neuropsychological evaluation. We conducted statistical analyses using R, first to calculate the threshold values for positivity in both tau assessing methods and to make comparisons between the groups. For tau‐PET, we used [18F]MK6240 SUVR in the temporal meta‐ROI.

Result

Using Receiver Operating Characteristic (ROC) curves, we established that the cut‐off for positivity for plasma pTau181 was 11.1060 pg/mL, while for tau‐PET, it was 1.1827 SUVR. 182 individuals had concordant statuses for both plasma pTau181 and tau‐PET, while 87 were discrepant. 64 were plasma+/PET‐, with a majority cognitively unimpaired (CU) and 23 were plasma‐/PET+, with values close to the thresholds, and mostly MCI or AD (Figure1). Moreover, concomitant plasma/PET statuses were usually accompanied by a similar Ab status (Figure2). CU Ab+ individuals were found in high proportion in the plasma+/PET‐ group (Figure3).

Conclusion

Most of the participants had concordant statuses for plasma pTau181 and tau‐PET, which correlate well with memory scores and diagnoses. However, there was a significant portion of discordant individuals, which were predominantly plasma+/PET‐. This corroborates findings from comparisons between CSF pTau181 and tau‐PET, with CSF positivity coming before PET. Plasma pTau181 is also a great tool to assess Ab status, even before the onset of tau‐PET abnormalities. Assessing tau through plasma or PET is thought to suggest different stages of pathological progression.
Family stories: Subjective cognitive decline profile associated with a familial history of Alzheimer’s disease
Authors: Robertson Frank , Marx Hannah , Jacova Claudia
Published: December 2021

Background

Subjective Cognitive Decline (SCD) designates a self‐experienced worsening of cognition before that decline becomes detectable by objective cognitive assessment. SCD has been examined as an early stage of Alzheimer’s disease (AD), but the evidence linking self‐reported SCD features to clinical progression is inconsistent and the predictive validity of SCD presence and symptom burden remains uncertain. More nuanced measures of SCD which differentiate between domains of cognitive decline are needed. This study examined SCD across the domains of Memory, Language and Executive function to identify a pattern of decline associated with well‐established risk factors for AD: family history of AD, female gender, and older age.

Method

Community‐dwelling participants aged >50 years (M age=64, n=483) were recruited via the crowdsourcing website Amazon Mechanical Turk and completed a survey including demographic questions and the Subjective Cognitive Decline Questionnaire (SCD‐Q MyCog). Risk factors were binary (family history yes/no, female/male, age <70/=>70). Multivariate analysis of variance (MANOVA) was then performed for each risk factor grouping, with the three domains of SCD serving as dependent variables. Follow‐up discriminant analysis was performed on significant relationships

Result

The sample included 27% of participants with a positive family history, 66.5% female, and 14.5% aged >70 years. Those with a positive family history differed on a combination of SCD domain scores from those without family history, Pillai’s trace=‐.0.023, p=.011 (Memory M=2.6 vs. 1.8, Language M=2.0 vs. 1.4, Executive Function M=1.4 vs. 1.1). No other group differences reached statistical significance. Discriminant function coefficients showed that the memory domain was the strongest contributor (0.984), followed by language (0.849), and finally executive function (0.583).

Conclusion

A positive family history is a reliable predictor of future AD. We found that those with a positive family history reported a greater amount of subjectively experienced memory and language decline. Memory and language concerns may be helpful in assessing risk of AD in those endorsing SCD.
Plasma glial fibrillary acidic protein is an early and specific marker of amyloid‐β pathology in Alzheimer’s disease
Authors: Pereira Joana B. , Janelidze Shorena , Smith Ruben , Mattsson‐Carlgren Niklas , Palmqvist Sebastian , Zetterberg Henrik , Stomrud Erik , Ashton Nicholas J. , Blennow Kaj , Hansson Oskar
Published: December 2021

Background

Glial fibrillary acidic protein (GFAP) is a marker of astrogliosis, which is often observed surrounding amyloid‐β (Aβ) plaques in the brains of patients with Alzheimer’s disease (AD). GFAP can be measured both in plasma and cerebrospinal fluid (CSF). The aim of this study was to assess whether plasma and CSF GFAP are independently related to Aβ or tau burden in cognitively unimpaired (CU) and cognitively impaired (CI) individuals.

Method

We measured plasma GFAP and CSF GFAP using the Single molecule array (Simoa) and NeuroToolKit robust prototype assays (Roche Diagnostics) in a sample of 217 CU individuals without Aβ pathology, 71 CU individuals with Aβ pathology, as well as 78 CI subjects with Aβ pathology from the Swedish BioFINDER‐2 cohort. Aβ pathology was defined using CSF Aβ42/40 with a cutoff of < 0.752 determined using mixture modeling. All subjects underwent Aβ (18F‐flutemetamol) and tau (18F‐RO948) positron emission tomography (PET). Differences between groups in GFAP markers were assessed using an analysis of covariance, adjusting for age and sex. Linear regression analyses were performed within each group to assess the relationship between GFAP markers with neocortical Aβ‐PET and temporal tau‐PET.

Result

Plasma GFAP was significantly elevated in all Aβ‐positive groups compared to subjects without Aβ pathology (p<0.01). In addition, this marker was associated with higher Aβ‐PET burden in CU individuals (p<0.001), even in the subgroup with normal CSF Aβ42/40 values (p=0.022). Plasma GFAP was also associated with Aβ‐PET in the CI group (p<0.001). All of these associations remained significant after controlling for tau‐PET burden. Further, plasma GFAP could predict Aβ‐PET outcome in the CU and CI groups with an area under the curve of 71%. In contrast, although correlations were also observed between tau‐PET and GFAP, these were no longer significant after controlling for Aβ‐PET. CSF GFAP did not show any differences between groups and correlated with Aβ‐PET only in CI individuals (p=0.005).

Conclusion

These findings suggest that plasma GFAP is an early and specific marker associated with brain Aβ but not tau aggregation, even in cognitively normal individuals with normal CSF Aβ42/40.
Toward higher‐sensitivity, shorter‐interval MRI measures of atrophy in neurodegenerative dementias
Authors: Brickhouse Michael , Hanford Lindsay , Carvalho Nicole , Eldaief Mark C. , Mair Ross , Nielsen Jared , Touroutoglou Alexandra , Buckner Randy , Dickerson Brad C.
Published: December 2021

Background

Conventional single acquisition T1w structural MRI can detect significant change in brain structure given ample latency between scans; most contemporary studies of neurodegenerative dementias collect MRI scans at one‐year intervals and calculate annualized rates of atrophy. MRI methods to detect atrophy over shorter (3‐ or 6‐month) intervals would be extremely valuable for basic human neuroscience research about neurodegenerative disease mechanisms as well as for translation into clinical trials. Measurement of change over short intervals would allow neurodegeneration to be monitored in smaller, early‐phase therapeutic trials—potentially even as a marker of target engagement in trials of disease‐modifying interventions.

Method

Our pilot cohort consisted of 5 patients: 4 with primary progressive aphasia (2 semantic variant likely due to FTLD, 2 logopenic variant likely due to AD), 1 with posterior cortical atrophy likely due to AD. We collected 32 accelerated 1mm T1w scans in four 30‐minute blocks across two days for each of 3 timepoints (baseline, 3 months, 6 months). We used the FreeSurfer longitudinal processing stream to make robust estimates of the cortex and subcortical structures for each T1w volume. For each timepoint, cortical thickness and volume and subcortical volume estimates were derived from all 32 reconstructed scans. Rates of change were calculated from ROI measures. In addition, a cortical atrophy map was calculated for each subject at each timepoint in comparison with a group of age‐matched controls (N=32).

Result

Each of the patients exhibits a typical pattern of atrophy for their clinical syndrome. Cortical atrophy maps are highly reliable between timepoints, and for each subject show visibly apparent but small changes in the magnitude and spread of atrophy. ROI measures demonstrate a slight but observable decrease in the size of many brain structures, even across a 3‐month interval. Cortical thickness changes in regions implicated in the patient’s individual clinical syndrome show the greatest magnitude of change over time—detectable in each individual at 3‐month intervals.

Conclusion

This novel approach to MRI acquisition and analysis can sensitively measure neurodegeneration in individuals over shorter intervals of time, which could lead to substantial changes in methods for measuring disease mechanisms and in clinical trial design.