bluuebunny/crossref_metadata_2025 huggingface dataset:
Multivariate sleep health and cognitive functions in healthy older adults: results from partial least square correlation analysis
Authors: Qin Shuo , Ng Eric Kwun Kei , Soon ChunSiong , Chua XinYu , Zhou Juan Helen , Koh Woon‐Puay , Chee Michael Wei‐Liang
Published: January 2025

Background

Past studies examining sleep‐cognition relationships mostly employed univariate approaches, which are subject to problems such as multicollinearity and multiple comparisons. Further, results from small sample univariate analyses are difficult to compare, precluding the identification of the aspects of sleep health associated with a particular cognitive domain(s). The current study used a multivariate approach to identify key sleep metrics and cognitive domains that contribute to the maximum sleep‐cognition covariance in healthy older adults. From the reduced list of sleep metrics and cognitive domains, novel associations between different aspects of sleep health and cognitive domains can be uncovered.

Method

The current study is part of the ongoing SG70: Toward Healthy Longevity in Singapore study, which aims to comprehensively assess factors that affect aging health in over 1000 Singaporean older adults. From the SG70 study, 440 healthy older adults wore an Oura Ring (OuraHealth OY) for 14‐30 days. Twenty‐three metrics encompassing 4 major aspects of objective sleep health: duration, timing, regularity, and continuity were extracted (Figure 1). Cognition was assessed using a comprehensive battery that encompassed 7 domains. The overall covariance between sleep and cognition was examined by a partial least square correlation (PLSC) analysis. Sleep metrics and cognitive domains that contributed significantly to significant PLSC components were identified by bootstrapping.

Result

PLSC analysis identified a component that explained 68% of covariance between sleep and cognition matrices (r=0.17, p<0.001). Bootstrapping tests further identified 10 sleep continuity and regularity metrics and 4 corresponding cognitive domains that contributed significantly to the observed covariance (Figure 2). Post‐hoc univariate analyses showed that sleep continuity metrics correlated with speed of processing, while sleep regularity metrics correlated with verbal memory, visual‐spatial ability, executive functions, and speed of processing (Figure 3).

Conclusion

Our results suggest that sleep continuity and regularity may be more sensitive markers of impairments across multiple cognitive domains in healthy aging compared to sleep duration and timing. In addition, they support the utility of multivariate analyses in uncovering significant association patterns between sleep and cognition.
“Strengthening Dementia Care: Advancing Through ADI Accreditation for Excellence and Acknowledgment”
Authors: Utomo Amalia Fonk , Aguilar Diego
Published: January 2025

Background

The ADI Accreditation Programme, launched in December 2020, aims to support all Alzheimer and dementia associations and other organizations, in improving care for people living with dementia. By providing a standards‐based approach to knowledge and skills, ADI establishes benchmarks that program providers must adhere to. Successful completion of an evaluation allows carers, trainers & program providers to earn ADI Accreditation, indicating that they have reached the required global standard for their training and learning activities, including culturally appropriate context to improve care quality. This program is open to ADI members, and organizations including universities & training colleges.

Activities

Our Global Review Panel (GRP) Members consists of multi‐discipline, cultural and regional experts in the global dementia field. Successful completion of an evaluation process: initial application, evaluation report, virtual/in‐person or hybrid visit from our GRP Members, the program/providers can earn it.

The first provider accredited was Kiang Wu Nursing College (KWNC) of Macau on January 25, 2021. The project involved discussions on external‐internal governance, trainers‐program committees, students, graduates & other stakeholders. A 3‐day virtual visit to KWNC in September, including evaluation, involved carers, trainers, students & collaboration with other organizations and people living with dementia, followed by a final review by the GRP in October‐November.

Silverado Memory Care became the first program to be accredited for their Dementia Care Program on December 22, 2022. In‐person visits took place on August 16‐17 2022. University of Bradford UK, became the first university in Europe to be accredited their Centre for Dementia Applied Science on December 22, 2022. In‐person visit took place on June 20‐21 June 2023. Wicking Dementia Research & Education Centre University of Tasmania, received their accreditation after virtual visit on 29‐30 August 2023. All process involving trainers, stakeholders, associates & staff in 2024 Dementia Australia is currently on the process along with new potentials.

Results

KWNC Macau, Silverado, University of Bradford & University of Tasmania received ADI Accreditation. Throughout the program, there has been an increase in awareness and understanding of the importance of high‐quality culturally contextualized carer training achieved.
Caregivers’ perception of ageing, perceived health and strain in caregiving – The preliminary cross culture analysis
Authors: Lai Frank HY , Siu Andrew Man‐hong , Hai Eddie Yip‐kuen , Whittington Stephanie , Lai Cynthia Yuen‐yi , Chan Wallace Chi‐ho , Yip Ben Chi‐bun
Published: January 2025

Background

Understanding how caregivers perceive their own aging process is essential for addressing their well‐being and the quality of care they provide. This study aimed at exploring the relationship between caregivers’ self‐perception of ageing in relation to their strain experienced in caregiving, and their perceived physical and mental health symptoms. Moreover, to examine if the strain experience and perceived health condition were key predictors to their self‐perception of ageing. Additionally, to analyze how demographic variables, such as gender and cultural background, would impose influence on self‐perception of ageing

Method

A questionnaire was developed in collect data on the variables, including self‐perceptions of ageing (SPA), caregivers' perceived strain (PS), caregivers physical health symptoms (PHS), and mental health symptoms (MHS).

Result

60 spousal caregivers, 33 male and 27 female with (24 Western, 24 Asian, and 12 Black Asian) participated in a cross‐sectional survey. There was a strong negative correlation between the self‐perception of ageing and caregivers’ strain (r = −.55, p < .001), physical symptoms (r = −.67, p < .001), and mental health symptoms (r = −.36, p < .001). Results of multiple regression analysis showed that caregivers’ strain, physical symptoms, and mental health are good predictors of self‐perception of ageing, and the regression equation account for a significant proportion of variance in self‐perception of ageing (R2 = .56, Adjusted R2 = .53).

Conclusion

Cultural background imposes influence on self‐perception of ageing, and there are significant interactions between gender and cultural background. Post‐hoc multiple comparisons using Bonferroni tests showed that Western had significantly higher self‐perception of ageing scores than the other two culture groups, while the differences between Asian or Black Asian group are significant.
Alzheimer diseases CSF biomarkers correlate with systemic biomarkers in a cohort of Hispanics
Authors: Villarreal Alcibiades E , Oviedo Diana C , Carreira Maria B , Rangel Giselle , Araujo Pahola , de Roux Ricardo Williams , Balaguer Rainier Rodríguez , Díaz Marilisa , Novarro‐Escudero Nelson , Tamayo David Alberto Anguizola , Villarreal Julio , Dondis David , Benzadon Aron , Britton Gabrielle B
Published: January 2025

Background

We are conducting a biomarker‐based study to describe the demographic and biomarker profiles of Panamanians. The objective of this report is to present the main findings on CSF, genetic and serological biomarkers’ distribution and their association with cognition in a cohort of elderly people in Panama.

Method

Informed consent was applied to all participants, demographic data, medical history, and neuropsychological and functional status were collected, and non‐fasting blood samples were obtained. We performed a cross‐sectional analysis of aged individuals for blood and CSF biomarkers and Apolipoprotein E (ApoE) expression (N=45). The following measures were obtained: MMSE, Global Deterioration Scale, and Geriatric Depression Scale 30‐item version. The following biomarkers in CSF were analyzed: Ab1–42, T‐tau and P‐tau181.

Result

We performed group comparisons and analyzed in‐group correlations between blood‐based and CSF biomarkers. Group differences across three CFS profile categories (normal, plausible AD, and AD) were calculated using ANOVA. The Innotest Amyloid Tau Index (IATI) was used to assign 45 biochemical CSF profiles into: normal CSF profile (n=19), plausible AD profile (n=18) and AD profile (n=8). Groups did not differ with respect to age, sex, or education level. AD group expressed at least one copy of the allele 4 of ApoE significantly more than normal and plausible AD profile groups (p=0.017 and 0.035, respectively). Significant correlation between IL‐18 and Ab1–42 was observed in normal group, and no correlations were found between blood and CSF markers in plausible AD group. The greatest number of significant correlations was found in AD group: B2M, CRP, Eotaxin3, PPY, SAA, TARC correlated with P‐tau181; IL‐10, IL‐7 with Ab1–42; and FVII with T‐tau.

Conclusion

In this analysis we observed a strong correlation of systemic biomarkers with CSF profiles (IATI profiles), mainly in the Alzheimer's disease group. Blood‐based biomarkers might facilitate diagnosis and clinical design in the future, but further validation is required.
Unravelling excitation/inhibition imbalance in early and familial Alzheimer's Disease
Authors: van Nifterick Anne M
Published: January 2025

Background

An early disruption in excitation‐inhibition (E‐I) balance is believed to underlie abnormal local and global network dynamics in Alzheimer’s disease (AD). While prior studies proposed that changes in E‐I balance may underlie the established slowing of oscillatory activity and changes in functional connectivity in symptomatic AD, the specific alterations occurring in the presymptomatic stage of AD remain poorly understood. This study aims to identify local and global spectral power and functional connectivity changes in individuals with familial AD before the onset of clinical symptoms.

Method

Resting‐state magnetoencephalography (MEG) recordings were conducted in a unique cohort of cognitively unimpaired individuals carrying autosomal dominant mutations in the APP and PSEN1 genes (n = 11), leading to early‐onset AD. Each mutation carrier was demographically matched with three cognitively healthy subjects (HCs) without mutations and with available MEG. We compared source‐level whole‐brain average and regional spectral power and volume‐conduction corrected functional connectivity measures across different frequency bands. Hub vulnerability was assessed using the hub disruption index. Significant MEG measures were correlated with age, estimated years before symptom onset (EYBSO), and cognitive performance.

Result

Cognitively normal mutation carriers exhibited signatures of oscillatory slowing, characterized by a widespread higher relative power in the theta band (4‐8 Hz) and a lower parieto‐temporal‐occipital peak frequency compared to HCs. Additionally, they presented frequency‐ and degree‐dependent functional connectivity changes: higher phase‐based functional connectivity in the theta band in initial low‐degree regions (as determined by weighted degree in HCs), but lower global amplitude‐based functional connectivity in the alpha (8‐13 Hz) and beta (13‐30 Hz) bands compared to HCs, most strongly in initial high‐degree regions. No correlations between MEG measures and age, EYBSO, or cognitive indices were found after correction for multiple comparisons.

Conclusion

Neurophysiological changes occur before the onset of cognitive symptoms in individuals carrying mutations in the APP or PSEN1 genes. These changes include oscillatory slowing and frequency‐ and degree‐dependent functional connectivity alterations, mirroring alterations observed in clinical stages of AD and suggesting an early E‐I imbalance. These findings contribute to a comprehensive understanding of presymptomatic pathophysiological alterations in AD.
Validation of diffusivity along the perivascular space as a biomarker for vascular cognitive impairment and dementia
Authors: Liu Xiaodan , Barisano Giuseppe , Maillard Pauline , Arvind Caprihan , Cen Steven , Shao Xingfeng , Jann Kay , Ringman John M , Lu Hanzhang , Arfanakis Konstantinos , Decarli Charles , Gold Brian T , Satizabal Clandia L. , Fadaee Elyas , Habes Mohamad , Stables Lara , Singh Herpreet , van der Kouwe Andre J. , Schwab Kristin , Helmer Karl G , Greenberg Steven M. , Wang Danny JJ ,   MarkVCID Consortium
Published: January 2025

Background

To validate the index of diffusivity along the perivascular space (ALPS index) as a biomarker for vascular cognitive impairment and dementia (VCID).

Method

The participants and MRI data used in this study were acquired as part of the MarkVCID consortium, which consisted of seven sites. A total of 578 participants (72.5±7.2 years old, 232 Male) who received baseline and follow‐up cognitive evaluations (Montreal Cognitive Assessment (MoCA), Principal Component Analysis derived General Cognitive Function (GCF_PCA), and composite score of Executive Function (EFC)) and MRI examinations were included in this study. The diffusion tensor imaging (DTI) data were processed by using an in‐house automatic processing pipeline with FMRIB Software Library 6.0.6. The mean free water (mFW) and peak width of skeletonized mean diffusivity (PSMD) were computed in the white matter (WM). The ALPS index was defined as the average of bilateral ALPS indices which were calculated by the ratio of mean of x‐axis diffusivity in the projection fibers (Dxxproj) and x‐axis diffusivity in the association fibers (Dxxassoc) to the mean of y‐axis diffusivity in the projection fibers (Dyyproj) and z‐axis diffusivity in the association fibers (Dzzassoc). The WM hyperintensity volumes (WMHV) were calculated on FLAIR images and normalized by intracranial volume (ICV). Univariate correlation (Pearson or Spearman) was used to examine the associations between imaging markers (ALPS index, mFW, PSMD, and WMHV). Linear regression models were used to evaluate the associations of baseline ALPS index with baseline and longitudinal changes of cognitive outcomes, regressing out three types of covariates: 1) age, sex, and education, 2) added vascular risk factors (VRFs), including diabetes, hypertension and smoking, 3) further added mFW, PSMD and WMHV. SAS 9.4 software was used for all statistical analyses, and P<0.05 was regarded as statistical significance.

Result

The baseline ALPS index was significantly correlated with existing biomarkers of cerebral small vessel disease (cSVD)‐related VCID, i.e., mFW and WMHV (P<0.01) (Figure 1), and baseline cognitive performances, i.e., MoCA total score, GCF_PCA score, and EFC score (P<0.05) after adjusting for the demographics, VRFs, and existing biomarkers (Figure 2).

Conclusion

the ALPS index is an independent contributor to the cognitive decline in cSVD.
Potentially modifiable risk factors for dementia putting the evidence together: Total population attributable fraction
Authors: Livingston Gill , Huntley Jonathan D , Liu Kathy Y , Gonzalez Sergi Costafreda , Selbaek Geir , Alladi Suvarna , Ames David , Banerjee Sube , Burns Alistair , Brayne Carol , Fox Nick C , Ferri Cleusa P , Gitlin Laura N. , Howard Robert J , Kales Helen C , Kivimaki Mika , Larson Eric B , Nakasujja Noeline , Rockwood Kenneth , Samus Quincy M , Shirai Kokoro , Singh‐Manoux Archana , Schneider Lon S. S. , Walsh Sebastian , Yao Yao , Sommerlad Andrew , Mukadam Naaheed
Published: January 2025

Background

Our authors from around the world met to summarise the available knowledge, decide which potentially modifiable risk factors for dementia have compelling evidence and create the most comprehensive analysis to date for potentially modifiable risk factors to inform policy, give individuals the opportunity to control their risks and generate research.

Method

We incorporated all risk factors for which we judged there was strong enough evidence. We used the largest recent worldwide meta‐analyses for risk factor prevalence and relative risk and if not available the best data. We performed new meta‐analyses for depression and hearing loss relative risks.

We used all 37,000 participants aged ≥ 45 years from HUNT, Norwegian longitudinal population‐based study, to estimate communalities (risk factors clustering) as people frequently have multiple risk factors. Four principal components explained 51% of total risk factors variance. We then calculated weighted population attributable fraction (PAF) estimates.

Result

We will present each potentially modifiable dementia risk factor’s prevalence, communality, relative risk, unweighted and weighted PAFs and our new lifecourse infographic.

Conclusion

Our results give hope suggesting many dementias can be prevented or delayed. Many risk factors are linked to deprivation, for example, where people live and exposure to air pollution, or finding affordable healthy food within walking distance and having the resources and skills to prepare it. We have more evidence that longer exposure to a risk has more effect, for example in diabetes, and that risks have more effect in otherwise vulnerable people, for example air pollution. Thus, it is important to redouble efforts to treat existing conditions in communities and people with multiple risks where approaches beyond individual treatment or behaviour change have potentially larger impact. While association is not causation, the effect on cognition of multicomponent, hearing aid and hypertensions RCTs, and naturalistic changes with reduction in air pollution, cigarette smoking, social contact, hearing and vision corrections and work cognitive stimulation, continue to suggest causal relationships with dementia. Socially disadvantaged groups in all countries are more at risk and should be prioritised for intervention. There is more evidence that risks are also modifiable for people at increased genetic risk.
A Neuroimaging Perspective on Familial Alzheimer's Functional Data through Bayesian Eyes
Authors: Grazia Alice , Dyrba Martin , Nunzio Pomara , Temp Anna G.M. , Grothe Michel J. , Teipel Stefan
Published: January 2025

Background

Familial Alzheimer's disease research necessitates innovative methodologies to disentangle the intricate relationships between genetic factors and neuroimaging measures. Traditional frequentist approaches, often hampered by small sample sizes in this population and challenges in incorporating prior knowledge transparently, may limit the robustness of findings.

Methods

We analyzed neuroimaging data of preclinical PSNE1 single mutation carriers, utilizing the software JASP to test effects of carrier status on measures of basal forebrain functional connectivity using both frequentist and Bayesian approach. Bayesian Analysis of Covariance was first implemented to test the hypothesis of a basal forebrain functional connectivity reduction in mutation carriers compared to non‐mutation carriers. To get more precise information, Informative priors, derived from the existing literature on preclinical sporadic Alzheimer's disease, were integrated into post‐hoc Independent samples t‐tests. Student t‐tests were utilized for parameter estimation, using an Informed Cauchy specification of prior's location (‐0.7) and scale (0.707) allowing the derivation of posterior distributions.

Results

Our findings demonstrated that preclinical mutation carriers exhibited no significant alterations in basal forebrain functional connectivity compared to non‐carriers. However, the Bayesian analysis revealed distinct advantages over the traditional frequentist approach (anterior basal forebrain: t=‐1.126 (213), p= 0.131, Cohen's d = ‐0.165, 95 % CI for Cohen's d: [‐Inf., 0.077]; posterior basal forebrain: t=‐1.337 (213), p= 0.091, Cohen's d = ‐0.196, 95 % CI for Cohen's d: [‐Inf., 0.046]. Incorporating informative priors significantly improved the precision of parameter estimates, allowing us to reject our hypothesis with a relatively high degree of confidence, from anecdotal (anterior basal forebrain: BF10 = 1.167, δ = ‐ 0.319, 95 % CI: [‐0.599, ‐0.061]) to strong evidence (posterior basal forebrain: BF10 = 0.033, δ = ‐0.067, 95 % CI: [‐0.260, ‐0.003]).

Discussion

Our results underscore the importance of adopting Bayesian frameworks in familial Alzheimer's disease research. The explicit integration of prior knowledge, as facilitated by Bayesian analysis, enhances the reliability of conclusions drawn from neuroimaging data. These methodological advantages are crucial in advancing the field and encouraging replication efforts.
Hierarchical Bayesian continuous‐time dynamic modeling approach to investigate the dynamic interplay between aerobic exercise and time‐locked cognitive performance in older adults with AD and metabolic risk
Authors: Schwarck Svenja , Voelkle Manuel C , Bernal Jose , Berron David , Baumeister Hannah , Gellersen Helena M. , Daamen Marcel , Boecker Henning , Ziegler Gabriel , Düzel Emrah
Published: January 2025

Background

Training studies report beneficial effects of physical (PP) on cognitive performance (COG) in older adults, but are often accompanied by potentially biased parameters, conclusions, and lack of directionality. To address these issues, we used a dynamic Bayesian approach to analyse the dynamic session‐to‐session change and coupling of PP and COG over time.

Methods

We used two studies (N = 17 each): Study 1 contained 24‐weeks (72 sessions) of training of older adults with suspected Alzheimer’s disease (AD). Study 2 included four months (40 sessions) of training of older adults at metabolic risk. The hierarchical Bayesian continuous‐time dynamic modeling approach (R package ctsem) comprised: (i) A subject‐level latent dynamic model, (ii) subject‐level measurement model, and (iii) population model. The dynamic model was specified with two fully connected state variables enabling bidirectional coupling between PP and COG using default priors and starting values (4 chains and 8.000 iterations). Intercept and drift parameters were set to vary freely. Population and individual level parameters are estimated simultaneously using all data from all subjects. Second‐level models included MMSE, SF12 (physical health questionnaire) in study 1 and whole hippocampal volumes (wHCV: T2‐ASHS, longitudinal) and white matter hyperintensities (SAMSEG, longitudinal) in study 2 as time independent covariates.

Results

Study 1: Higher PP was dynamically linked to COG (‐1.335, 95%‐BCI [‐1.725, ‐0.954]). The effect was short‐term, lasting up to five days (‐0.368, 95%‐BCI [‐0.479, ‐0.266]). Study 2: PP improved COG in subsequent sessions (‐1.11, 95%‐BCI[‐1.22, ‐0.99]), which lasted for up to 15 days. Higher wHCV was associated with a stronger coupling‐effect of PP on COG (‐0.15, 95%‐BCI[‐0.18, ‐0.11] ) and lower persistence of COG (‐0.145, 95%‐BCI[‐0.21, ‐0.08]).

Discussion

Our results show immediate exercise‐induced improvements in COG, with a longer‐lasting effect for participants at metabolic risk compared to older adults with suspected AD. Despite impaired cognitive performance, the cognitive system was still able to fluctuate and change favorably. Physical exercise seems to mobilize capacities that would otherwise remain unused. Utilizing a Bayesian approach to examine time‐locked effects can provide insights for implementing individualized training approaches and guiding clinical decision‐making.
Using Bayesian statistics for longitudinal modelling and individual prediction in neuroimaging
Authors: Sala‐Llonch Roser , Pérez‐Millan Agnès
Published: January 2025

Large neuroimaging datasets play a crucial role in longitudinal modelling and prediction of neurodegenerative diseases, as they provide the opportunity to study biomarker trajectories over time. Noteworthy, the availability of these large datasets coexists with a paradigm shift in the theoretical understanding of these diseases: while classical studies aimed at defining disease signatures as group patterns obtained with static cross‐sectional analyses, novel approaches focus on providing individual predictions in the context of phenotypical and temporal heterogeneity. This scenario is often aggravated by the fact that datasets are not homogeneous and suffer from missing points and noisy data.

Given this complexity, Bayesian approaches appear as an elegant solution to model longitudinal data as they rely on the probabilistic distribution of the data rather than referring to a hypothesis derived from the sampling distribution. Here, we provide empirical examples together with a comprehensive state‐of‐the‐art review and future perspectives on the field.

In the first example, we compare Bayesian and frequentist approaches in a Linear Mixed Effects analysis using MRI‐derived hippocampal volumes, from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. We simulate different datasets resembling real‐life clinical scenarios. Our results show that in large homogeneous datasets, both approaches perform similarly in differentiating groups, being the frequentist approach simpler and computationally faster. However, the Bayesian approach was the preferred option with limited datasets with less homogeneous groups and large number of missing data [1].

In another example, we discuss the use of Gaussian Processes (GPs), a Bayesian non‐parametric model estimation technique that generates predictions based on the posterior distribution of functions using predefined kernels [2]. We show novel results on the ability of GPs to identify trajectories within the ADNI database.

Finally, we review the use of machine learning approaches to generate individual predictions. We discuss our own results [3], together with other promising tools that use novel approaches derived from Bayesian statistics that go beyond the classical group classifications [4].

References:

[1] Pérez‐Millan A, et al., Sci Rep. 2022.

[2] O'Muircheartaigh J, et al., Brain. 2020.

[3] Pérez‐Millan A, et al., Research Square. 2023.

[4] Azevedo T, et al., Commun Med. 2023
White matter hyperintensities in AD and bvFTD patients from Underrepresented countries
Authors: Altschuler Florencia , Canziani Veronica , Fraile‐Vazquez Matias , Ibáñez Agustín , Campo Cecilia Gonzalez
Published: January 2025

Background

White matter hyperintensities (WMH) are very common brain MRI signal abnormalities linked to age, small vessel cerebrovascular disease, cognitive impairment, and dementia. Despite extensive research on WMH in Alzheimer's disease (AD), their prevalence in behavioral variant Frontotemporal dementia (bvFTD) remains less explored. Additionally, Latin American countries (LA) exhibit a higher prevalence of cerebrovascular disease due to distinct demographic, socioeconomic, cultural, and ethno‐racial factors. However, limited research on WMH exists in this context. Our aim was to characterize the WMH burden and its relationship with neurodegeneration and cognition in healthy aging and dementia subjects from LA in comparison to the United States (US).

Methods

This cross‐sectional multicenter study involved 638 LA and 355 US subjects from the ReDLat consortium, including healthy controls (HC), bvFTD, and AD patients. Participants underwent brain MRI and neuropsychological assessments. Voxel‐based morphometry analysis was performed to calculate WMH load and distribution from T2‐FLAIR images, and gray matter (GM) atrophy from T1 images. To assess the differences in the spatial distribution of WMH, two sample t‐tests were run between HC and neurodegenerative groups (AD and bvFTD) for each region (LA and US). The association between total load of WMH with regional GM volume and the association between cognitive performance (MMSE) with tract‐specific WMH load was tested via voxel‐wise regression analyses. In all analysis significance was set at p<0.05 family‐wise error‐corrected for multiple comparisons with a cluster extent threshold of 50 voxels. Age, years of education, sex, TIV and scanner were included as covariates of no interest.

Results

bvFTD exhibited higher WMH load than AD in both regions (LA and US, Figure 1). Notably, the association between WMH burden and GM atrophy was substantially stronger for all LA groups (bvFTD, AD, and HC) compared to the US (Figure 2). Additionally, an association between WMH burden and cognitive impairment (MMSE) was found in all pathological groups (Figure 3).

Conclusion

This study highlights regional and disease‐specific effects of WMH burden in brain atrophy and cognition, emphasizing the importance of region‐adapted dementia research for a comprehensive understanding of these disparities.
What’s in a name? Terms persons supporting people living with MCI or dementia use to describe their role
Authors: Erickson Claire M , Clapp Justin , Gupta Anjali , Kleid Melanie , Harkins Kristin , Stites Shana D. , Peterson Andrew H , Karlawish Jason , Largent Emily A.
Published: January 2025

Background

Best practice recommendations suggest a person close to a patient with mild cognitive impairment (MCI) or dementia be involved in their care. This person is often referred to as a “caregiver,” though the term “care partner” has increasingly been used in research and care instead of “caregiver.” Unlike “caregiver,” “care partner” suggests a collaborative relationship between the patient and their support person, in which the patient actively participates rather than passively receives help. It is not known, however, what nomenclature people in this care role themselves use and why. Establishing terminology that accurately reflects the experiences of these individuals is important for research and care.

Method

Semi‐structured interviews were conducted with 14 people assisting patients with diagnoses of MCI or mild dementia, identified through an NIA‐funded Alzheimer’s Disease Research Center. Interviewees were asked if they identified as a caregiver, care partner, or something else. Data analysis was guided by a constructivist grounded theory approach and consisted of iterative rounds of coding with checks for intercoder reliability.

Result

Interviewees who provided relatively less assistance to patients, such as with activities of daily living (ADLs) and decision making, described themselves as a “care partner,” while those providing relatively more saw themselves as “caregivers” or “caretakers.” Preferred nomenclature may shift as the disease progresses and care needs change. Some interviewees currently preferring “care partner” suggested that “caregiver” was presently inappropriate because the patient was not yet that impaired. Support persons using “care partner” often highlighted the patient’s dignity and agency and emphasized their shared responsibility for ensuring the patient’s wellbeing. Finally, discussions of preferred nomenclature elicited reflections from the support person on how the patient’s cognitive and functional impairments have changed the dyad’s preexisting relationship (e.g., spousal, parental).

Conclusion

The terminology used to describe a person assisting in the care of a person with MCI or mild stage dementia has descriptive and normative dimensions. Asking support persons what label they use for themselves can provide insights into a patient’s current care needs, social and functional qualities of the dyadic relationship, and demonstrate respect for the support person.
Implementation and Validation of Face De‐Identification (de‐facing) in ADNI‐4
Authors: Schwarz Christopher G. , Tosun Duygu , Yushkevich Paul A. , Choe Mark , Rossi Stephanie , Das Sandhitsu R. , Ittyerah Ranjit , Fletcher Evan , Maillard Pauline , Singh Baljeet , Harvey Danielle J. , Malone Ian B. , Prosser Lloyd , Senjem Matthew L. , Matoush Leonard C. , Ward Chadwick P. , Prakaashana Carl M. , Decarli Charles , Weiner Michael S. W. , Jack Clifford R. ,   The Alzheimer's Disease Neuroimaging Initiative
Published: January 2025

Background

Recent advances in automatic face recognition have increased the risk that de‐identified research imaging data could be re‐identified from face imagery in brain scans.

Method

An ADNI committee of independent imaging experts evaluated 11 published techniques for face‐deidentification (“de‐facing”) and selected four algorithms (FSL‐UK Biobank, HCP/XNAT, mri_reface, and BIC) for formal testing using 183 longitudinal scans of 61 racially and ethnically diverse ADNI participants, evaluated by their facial feature removal on 3D rendered surfaces (confirming sufficient privacy protection) and by comparing measurements from ADNI routine image analyses on unmodified vs. de‐faced images (confirming negligible side effects on analyses).

Result

Effects of the de‐facing methods on FreeSurfer at UCSF (Figure 1‐top), ASHS at University of Pennsylvania (Figure 1 bottom‐left), and longitudinal atrophy at Mayo Clinic (Figure 1 bottom‐right) were comparable with each other and sufficiently small vs. unmodified scans to recommend de‐facing in ADNI‐4. The FSL and mri_reface methods were more thorough in removing facial features, partly because these also removed ears (Figure 2‐top). mri_reface was recommended for ADNI‐4 primarily because fewer (zero) images had modified brain (Figure 2‐bottom), and ADNI leadership approved de‐facing with mri_reface. ADNI performed a second validation of its latest version on another diverse sample of 100 ADNI‐3 participants. These analyses included: boundary shift interval at University College London, where average differences in measurements were all <0.05%; cortical white matter hyperintensities at UC Davis, where they found “minimum impact” (R>0.97); and others.

Conclusion

ADNI‐4 de‐faces all indicated image types (Table 1) before subsequent pre‐processing, analyses, and public release. Sites upload images to the central repository (LONI), where they are queued to the MRI Core at Mayo Clinic for de‐facing. Image types requiring de‐facing are de‐faced using mri_reface. Trained analysts inspect de‐faced images to confirm complete removal of the face and complete non‐modification of the brain, and any flagged images are re‐processed manually until issues are resolved. De‐faced images are converted back to DICOM and re‐uploaded for further distribution. Image types not requiring de‐facing are indicated to proceed directly to subsequent steps. In summary, ADNI‐4 has adopted mri_reface because it successfully de‐faces without substantially affecting brain measurements.
The Association of Nursing Home Residents’ Pain with Preference‐Based Recreational Activity Attendance over time
Authors: VanHaitsma Kimberly S , Heid Allison R. , Rovine Michael J , Eshraghi Karen , Akter Nahida , Abbott Katherine M
Published: January 2025

Background

Knowledge of nursing home (NH) residents’ everyday care preferences is foundational in that it allows for the delivery of person‐centered care and individualized care planning. However, little is known about how integrating preferences into care delivery impact outcomes of care. The Preference Match Tracker is an objective metric that tracks the number of recreation activities NH residents attend that match or is “congruent” with resident important preferences. Here, we explored how Preference Match Tracker data were linked to NH residents’ with and without dementia self‐reported pain over the course of one year.

Method

The Preferences for Everyday Living Inventory (PELI) was used to assess important activity preferences for N = 586 residents with varying levels of cognitive capacity from January 1, 2016, to March 13, 2020 (pre‐COVID‐19). Resident attendance at activities, as well as activities declined, per week was tracked as a metric for quality improvement. Pain data were collected from the MDS 3.0 and dichotomously coded as pain or no pain. We used PROC GLIMMIX in SAS 9.4, to model repeated measures logistic regression with time as the repeated measure, over 1 year. Covariates included age, gender, cognitive ability, length of stay, sensory impairment, and activities of daily living (ADL) functional ability.

Results

There were no associations of age, gender, or hearing impairment with pain. Pain reduced over time. Greater cognitive capacity and shorter length of stay in the NH (< 90 days) were associated with more pain over time. More resident vision impairment and less ADL disability were also associated with less pain. After accounting for covariates, attending recreational activities was associated with less pain over time. Specifically, greater attendance at preferred activities was associated with less pain.

Conclusion

Activity attendance may be beneficial for pain experience for NH residents with and without dementia, possibly by distracting residents from pain through meaningful engagement. Higher attendance, and specifically attendance in preferred activities, can support individuals experiencing pain, especially those new to a NH and in the early stages of dementia with greater cognitive capacity. Controlling pain may also promote residents’ capacity for engagement in activities, specifically preferred activities.
Analytical performance assessment and suitability of the plasma β‐Amyloid 1‐40 and 1‐42 assays on the Lumipulse G instrument from Fujirebio to support Alzheimer's Disease clinical trials
Authors: Dupont Magali , Frantz Philippe , Thabuis Séverine , Nalayanda Divya , Troksa Erica
Published: January 2025

Background

Alzheimer’s Disease (AD) is a major neurodegenerative disorder characterized by amyloid deposits in brain tissues and representing a continuously increasing global burden in need of disease‐modifying therapeutic options. Amyloid beta 1‐42 and 1‐40 peptides and the amyloid beta 1‐42/1‐40 ratio are hallmarks of AD and are commonly monitored in Cerebro‐Spinal Fluid (CSF) along other AD biomarkers, to support diagnosis and management of AD patients. Over the past few years, blood‐based AD biomarkers have emerged as highly relevant and more practical alternatives to CSF biomarkers, and further technical performance characterization of the associated assays would be beneficial to the AD research and medical community.

Method

The Lumipulse G β‐Amyloid 1‐42 and 1‐40 Plasma assays are two‐step chemiluminescent enzyme immunoassays (CLEIA) performed on the Lumipulse G system and designed for the quantitative measurement of amyloid beta 1‐42 and 1‐40 in plasma specimens. We evaluated these two assays in a CAP/CLIA environment, utilizing CLSI guidance to set validation parameters and acceptance criteria. Linearity of results, assay precision within and between analytical runs, functional sensitivity as well as other performance parameters were evaluated in endogenous samples, neat or spiked to obtain appropriate concentrations.

Result

Utilizing a set of samples from apparently healthy donors above 75 years old, we were able to show an expected reference range of 154.05 – 455.50 pg/mL and 12.57 – 42.43 pg/mL for amyloid beta 1‐40 and 1‐42, respectively. Our results support a linear measurement range of 0.57 – 3,404.60 pg/mL and 0.83 – 682.00 pg/mL for amyloid beta 1‐40 and 1‐42, respectively, hence covering appropriately the expected reference range of the healthy population and allowing to capture abnormally elevated or depressed concentrations. For amyloid beta 1‐40, experiments revealed CV% ranging from 3.3 to 3.7% for intra‐ and 5.5 to 7.0% for inter‐assay precision. For amyloid beta 1‐42, CV% ranged from 3.4 to 5.4% for intra‐ and 5.8 to 8.8% for inter‐assay precision.

Conclusion

Overall, these assays demonstrate technical robustness and reliability to support clinical trials for AD in the plasma matrix, which can offer a less invasive, yet valuable test to enrich for amyloid positivity in neurodegenerative clinical trials.
Amyloid‐associated hyperconnectivity drives tau spreading across connected brain regions in Alzheimer’s disease
Authors: Roemer Sebastian Niclas , Wagner Fabian , Evangelista Lisa , Rauchmann Boris‐Stephan , Dehsarvi Amir , Steward Anna , Dewenter Anna , Biel Davina , Zhu Zeyu , Pescoller Julia , Gross Mattes , Perneczky Robert , Malpetti Maura , Ewers Michael , Schöll Michael , Dichgans Martin , Höglinger Günter , Brendel Matthias , Jäkel Sarah , Franzmeier Nicolai
Published: January 2025

Background

In Alzheimer’s disease, Aβ triggers tau spreading which drives neurodegeneration and cognitive decline. However, the mechanistic link between Aβ and tau remains unclear, which hinders therapeutic efforts to attenuate Aβ‐related tau accumulation. Preclinical research could show that tau spreads across connected neurons in an activity‐dependent manner, and Aβ was shown to trigger neuronal hyperactivity and hyperconnectivity. Therefore, we hypothesized that Aβ induces neuronal hyperactivity and hyperconnectivity, thereby promoting tau spreading from initial epicenters across connected brain regions.

Methods

From ADNI, we included 140 Aβ‐positive subjects across the AD spectrum plus 69 Aβ‐negative controls, all with baseline amyloid‐PET, 3T resting‐state fMRI and longitudinal Flortaucipir tau‐PET data. For validation, we included cross‐sectional tau‐PET, amyloid‐PET and resting‐state fMRI data of 345 preclinical AD patients from A4. PET and fMRI data were parceled into 200 cortical ROIs, ROI‐wise longitudinal tau‐PET change rates were computed using linear mixed models. Resting‐state fMRI connectivity was computed across the 200 ROIs. Subject‐specific tau epicenters were defined as 5% of ROIs with highest baseline tau‐PET. Further, we included post‐mortem brain tissue from 5 AD patients vs. 4 controls stained for Aβ and c‐Fos, i.e. a marker of ante‐mortem neuronal activity.

Results

In the AD spectrum cohort, we confirmed that Aβ induces hyperconnectivity of temporal lobe tau epicenters (Figure 1) to posterior brain regions that are highly vulnerable to tau accumulation in AD (Figure 2A‐C). This was fully replicated in the validation cohort of preclinical AD patients with low cortical tau‐PET, suggesting that the emergence of Aβ‐related hyperconnectivity precedes neocortical tau spreading (Figure 2D). Supporting that Aβ‐associated fMRI‐based hyperconnectivity may mirror neuronal hyperactivity, we found that neurons in AD post‐mortem tissue expressed higher levels of c‐Fos compared to controls, i.e. a Calcium‐sensitive marker of ante‐mortem neuronal activity (Figure 3). Lastly, using longitudinal tau‐PET, we confirmed that Aβ‐related connectivity increases of the tau epicenters to posterior brain regions mediated the effect of Aβ on tau accumulation and triggered faster tau spreading (Figure 4).

Conclusions

Our translational results suggest that Aβ promotes tau spreading via increasing neuronal activity and connectivity. Therefore, Aβ‐associated neuronal hyperexcitability may be a promising target for attenuating tau spreading in AD.
Synaptic loss pattern is associated with functional connectivity in Alzheimer’s disease
Authors: Luan Ying , Wang Weiyi , Huang Qi , Guan Yihui , Li Binyin , Schöll Michael , Franzmeier Nicolai , Xie Fang
Published: January 2025

Background

Synaptic loss is identified as a strong correlate of cognitive impairment in Alzheimer’s disease (AD). Pathological tau can induce direct toxicity to synapse and spread trans‐synaptically across connected neurons. Recent neuroimaging evidence revealed that tau pathology propagates along interconnected brain regions throughout macroscale brain networks. However, whether synaptic loss propagates in AD follows a similar vein is unclear.

Method

Seventy‐six amyloid‐positive (Aβ+) subjects across AD spectrum and 48 cognitively normal (CN) Aβ‐ controls characterized by cross‐sectional [18F]florbetapir amyloid‐PET were included in the current study. The density of synaptic vesicle glycoprotein 2A (SV2A) was measured by [18F]SynVesT‐1 PET. A normative template of functional connectome distance across 200 neocortical regions of interest (ROIs) was generated using resting‐state fMRI data from 1000 subjects of the Human Connectome Project. We assessed the association between synaptic loss and functional connectivity by correlating the cross‐subject inter‐regional covariance with the normative functional connectivity template. In a next step, we tested whether the functional distance to synaptic loss epicenter (i.e., top 10% ROIs with greatest synaptic loss) is associated with synaptic loss in connected regions at both group‐ and subject‐level.

Result

Among Aβ+ subjects, inter‐regional covariance of SV2A‐PET‐assessed synaptic loss was associated with inter‐regional functional connectivity (Figure 1), suggesting that higher functional connectivity may facilitate the propagation of synaptic loss. At both group‐ and subject‐level, we found that shorter functional distance to synaptic loss epicenters is associated with greater levels of synaptic loss in connected regions (Figure 2).

Conclusion

We found that inter‐regional functional connectivity is associated with greater synaptic loss in AD, suggesting that synaptic loss may systematically propagate along brain connections.
Aging, musical rhythm, and functional connectivity in the brain
Authors: Colverson Aaron , Chen Yu , Williamson John B. , Cohen Ronald A. , Rankin Katherine P. ,   UCSF, Memory and Aging Center
Published: January 2025

Background

Aging associates with decreased functional connectivity between brain regions linked to musical rhythm perception. Producing rhythmic music may result in strengthened functional connectivity of these regions, but more evidence is needed to support intervention design. Currently, few studies directly contrast younger and older adults’ rhythmic music performance to understand brain‐behavior relationships. We used task‐based functional magnetic resonance imaging to examine aging‐related differences in connectivity among brain regions associated with perceiving and performing increasingly complex musical rhythms.

Method

Participants (younger = 14, ages 18‐35; older = 14, ages 55‐79) completed one imaging run, sequentially tapping along to simple (paced and unpaced metronome, and unsyncopated) and complex (syncopated) musical rhythms on a response box. Simple rhythms maintained metric regularity, whereas complex rhythms deviated from the main pulse. Behavioral performance measures included overall timing error for the unsyncopated and syncopated conditions, and averaged standard deviation from mean error for paced and unpaced metronome. We ran seed‐to‐voxel analyses of known brain correlates (cortical and subcortical) of musical rhythm, contrasting effects of rhythm performance from each seed to examine functional connectivity.

Result

Younger adults performed better than older during simple (paced metronome (F(1,26) = 20, p<0.001) and unsyncopated (F(1,26) = 13.2, p = 0.001)) rhythms, with a similar nonsignificant trend for complex rhythms (syncopated: F(1,26) = 3.77, p = 0.063). Seeding from the right cerebellar lobule VI, contrasting difference in performance during syncopated and unsyncopated blocks, a significant negative correlation was found with right pre‐ and post‐central gyri and right superior parietal lobule (cluster‐level, FDR corrected p<0.05, voxel threshold p<0.001). Applying the same contrasts while seeding from the left putamen yielded a significant negative correlation with the right cerebellum Crus I&II.

Conclusion

Older adults performed simple musical rhythms less accurately than younger, and trended toward poorer accuracy in performing complex rhythms. During perception and performance of more complex musical rhythms, greater activation was found in circuits connecting the cerebellum (pattern abstraction) to parietal (timing representation) and basal ganglia (discrepancy monitoring) regions. Though we found no age difference, larger studies may be better powered to discriminate age‐related neural patterns. Studies investigating how music‐making interventions strengthen these circuits may provide avenues for improving cognition in aging adults and possibly individuals with neurodegenerative disease.