bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of the hybrid model for developing the concept of dementia friendly in the context of hospitalization
Authors: Munsterman Ellen , Cacchione Pamela Z
Published: January 2025

Background

Persons living with dementia (PLwD) are hospitalized at greater rates than adults without dementia and experience more adverse outcomes. The use of dementia friendly practices is increasingly common, but definitions for the concept vary. This study describes the fieldwork phase of a hybrid approach to concept development. This phase followed an analysis of the literature that resulted in a working definition for the concept of dementia friendly in the context of hospitalization. This definition incorporates the major recurring attributes found in the literature, including dementia‐related knowledge and education, environmental modifications, person‐centered care, the role of nursing care, and the inclusion of family caregivers. The aim of this study was to refine and confirm the working definition for the concept of dementia friendly in the context of hospitalization, informed by the perceptions of Registered Nurses (RNs) and Certified Nursing Assistants (CNAs).

Methods

Semi‐structured interviews were conducted with RNs and CNAs employed on an Acute Care for Elders unit. Interviews were audio‐recorded and professionally transcribed. Directed content analysis was used to analyze the interview data. Transcriptions were coded independently by the two authors and reconciled until agreement was reached.

Results

Participant demographics are reported in Table 1. Participants were largely in agreement with the definition as written but contributed important nuance to several of the attributes. Regarding staff knowledge and education, participants highlighted the role of hands‐on experience, as well as the delivery and format: synchronous vs. asynchronous. They stressed other characteristics required to coincide with knowledge, including care, compassion, and patience. When discussing the inclusion of family caregivers, participants addressed challenges faced when visiting family members lacked dementia‐specific knowledge.

Conclusion

The hybrid approach to concept development is useful for refining complex concepts pertinent to the field of nursing, enabling measurement and further research. In this study, combining qualitative fieldwork with a review of the literature resulted in the refinement of a working definition of the concept of dementia friendly in the context of hospitalization. Dementia friendly practices are necessary to address the unique needs of PLwD in the hospital. A clear definition of the concept will facilitate widespread implementation.
Discovery plasma proteomics analyses identify proteins that interact with plasma ptau231 levels to predict longitudinal episodic memory trajectory over a 9‐year follow‐up period
Authors: Kresge Hailey A. , Tanriverdi Kahraman , Bolton Corey J , Risitano Antonina , Sun Yunyi , Liu Dandan , Pechman Kimberly R. , Gifford Katherine A. , Shah Ravi , Freedman Jane , Hohman Timothy J. , Jefferson Angela L.
Published: January 2025

Background

There has been great progress towards identifying plasma biomarkers for Alzheimer’s disease (AD), though few studies have investigated interactions between proteomic measures and AD pathology. We aimed to identify plasma proteins predictive of episodic memory decline, an early clinical sign of AD, and assess whether such associations were altered by the presence of AD pathology.

Method

Vanderbilt Memory and Aging Project participants (n=350, 73±7 years, 41% female) without dementia at baseline underwent blood draw and serial neuropsychological assessments over 9‐year follow‐up (mean=6.1 years). Proteins were quantified using Olink® Explore 3072. Linear mixed‐effects regressions related protein levels to longitudinal episodic memory composite scores, including interactions with follow‐up time as the terms of interest. Models adjusted for age, sex, race/ethnicity, education, baseline cognitive status, and apolipoprotein E‐ε4 status. Follow‐up analyses included plasma phosphorylated tau 231 (ptau231) as a covariate, tested proteins x ptau231 interactions, and stratified by ptau231 tertile.

Result

Higher levels of 15 proteins (GFAP, NEFL, KLK4, SPON1, GH1, CXCL1, OGN, EPHA2, EDA2R, SHBG, CKAP4, DSG2, CD300LG, CLEC5A, NOTCH3) predicted faster decline in episodic memory (pFDR<0.05). With ptau231 included as a covariate, associations between 5 of the proteins (SHBG, CKAP4, DSG2, CD300LG, NOTCH3) and memory attenuated (pFDR>0.05). 38 proteins interacted with ptau231 to predict memory trajectory (pFDR<0.05). Among participants with high ptau23, 24 proteins (LGALS3, FSTL1, SORT1, CHAD, ADAM23, SERPINA3, COL5A1, SYT1, PTPRZ1, CD34, DPP6, POLR2F, PLAUR, SPAG1, PDE4D, PTK7, CSPG4, LRTM2, MEGF10, MYOC, REG4, SPON1, WIF1, EDDM3B) were associated with memory trajectory. Higher protein levels predicted faster decline, except for EDDM3B, for which lower levels predicted faster decline (p<0.05, pFDR>0.05). Among participants with low ptau231, lower levels of 8 proteins (FSTL1, SORT1, IL6R, PTPRM, AHNAK, AMIGO2, IL1RAP, ROBO1) predicted faster decline in memory. Two proteins (FSTL1, SORT1) were associated with memory trajectory in both low and high ptau231 groups, exhibiting opposite directions of effects in the setting of low versus high ptau231 (see Figures).

Conclusion

Results demonstrate associations between plasma proteomic measures and longitudinal memory trajectory differ by level of AD pathology. To maximize clinical utility of potential biomarkers discovered in plasma proteomic analyses, future studies should assess interactions with AD core biomarkers.
Predicting Future Conversion from Amyloid‐β Negativity to Positivity: Time‐To‐Event Prediction with Machine Learning
Authors: Vahid Amirali , Zamani Jafar , Hosseini Hadi
Published: January 2025

Background

Alzheimer's disease (AD) is characterized by the gradual accumulation of amyloid‐β (Aβ) plaques and tau tangle pathologies in the brain. Extant studies highlight that Aβ deposition contributes significantly to tau accumulation, leading to neurodegeneration and cognitive decline. Individuals with positive Aβ are more susceptible to AD progression but the precise spatial and temporal pattern of Aβ leading to convergence from negative to positive status is unclear. This study aims to predict the likelihood and the number of years it would take for an individual to transition from baseline negative Aβ to positive (i.e., transition time) using Aβ PET measures with machine learning methods for time‐to‐event and to further identify the most predictive brain regions.

Method

PET measures for Aβ SUVR of 446 subjects (216 females, mean age 71 ± 7), initially presenting negative Aβ from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), were utilized. The subjects had a longitudinal follow‐up averaging 4.76 ± 3.5 years, ranging from 1 to 11 years, with 86 transitioning to positive Aβ. For time‐to‐event analysis, three machine learning models— CoxPH, Random Survival Forest (RSF) and Survival XGBoost—were employed to predict the transition time. Their performance was assessed using 5‐fold cross‐validation and evaluated by the concordance index (C‐index). The permutation method was used to determine feature importance as an explainable AI approach.

Result

The C‐index, were 0.71, 0.834, and 0.829 for CoxPH, RSF, and Survival XGBoost, respectively. In the RSF that resulted in the highest accuracy the permutation method highlighted the significant influence of Aβ load in the rostral/medial frontal regions, inferior temporal region and precuneus. Post‐hoc correlation analyses confirmed these results and showed significant negative correlations between Aβ load in these regions and the transition time. Furthermore, based on the Kaplan‐Meier estimate, the median duration for transition time was 3.94 years.

Conclusion

Elevated Aβ levels in the medial and rostral frontal regions strongly predict the time of transition from negative Aβ to preclinical AD (i.e., positive Aβ). These findings highlight the potential of these regions as biomarkers for transition to preclinical AD, emphasizing their prospective application in AD therapy and drug discovery.
A multiple cohort study exploring the influence of partial volume correction on age and sex effects on tau PET imaging
Authors: Hobbs Diana A , Flores Shaney , Keefe Sarah J. , Morris John C. , Benzinger Tammie L.S. , Gordon Brian A.
Published: January 2025

Background

Tau PET imaging has become pivotal in understanding the pathophysiological processes underlying Alzheimer disease (AD). In individuals without amyloid pathology, there is evidence tau levels are elevated with increase age and that females show greater levels of binding. An unknown question is how consistent these effects are, and whether they are susceptible to methodological choices impacting PET quantification. We explored the impact of partial volume correction (PVC) on tau regional values in data from the Charles F. and Joanne Knight Alzheimer Disease Research Center (ADRC) and the Alzheimer Disease Neuroimaging Initiative (ADNI).

Method

Data came from 323 participants (age: 67.89±8.57) at the Knight ADRC and 274 individuals (age: 70.14±6.61) from ADNI. Forty‐two regional values of tau PET binding were measured using flortaucipir with and without partial‐volume correction as implemented using study specific geometric transfer matrix approaches. Participants were selected to be amyloid‐negative. Similarity in regional estimates was determined using spatial permutation testing.

Result

Within the ADRC cohort the value of the regression coefficients changed with PVC by the spatial pattern of the effects remained highly similar for both age (Figure 1A: r=0.66, p<0.001) and sex (Figure 1C: r=0.85, p<0.001). In ADNI there were moderate association between the maps of age‐related effects (Figure 1B: r=0.36, p<0.05) and sex (Figure 1D: r=0.31, p<0.05). When comparing between the ADRC and ADNI cohorts using non‐PVC data there were highly significant associations for both age (Figure 2A: r=0.83, p<0.001) and sex (Figure 2C: r=0.95, p<0.001). When using PVC, data no significant associations were found for age (Figure 2B: r=0.32, p=0.06) or sex (Figure 2D: r=0.02, p=0.92).

Conclusion

The implementation of, and choice of PVC approach can drastically impact the detection of PET signals. This is a particular concern in the context of cohorts where there may be low to moderate levels of underlying pathology and where non‐specific binding may dominate the signal. These results emphasize the importance of considering PVC in tau PET analyses and highlight the reliability of observed age‐ and sex‐related effects across different cohorts.
The potential of plasma TDP‐43 as a biomarker for limbic predominant age related TDP‐43 encephalopathy
Authors: Sordo Lorena , Leiby Anne‐Marie C , Malhas Rond , Barlow James , Rissman Robert A. , Kawas Claudia H. , Corrada María M. M. , Head Elizabeth , Sajjadi S. Ahmad
Published: January 2025

Background

Despite recent advances in biomarkers discovery for neurodegenerative diseases, there are currently no in vivo biomarkers for limbic‐predominant age‐related TDP‐43 encephalopathy (LATE‐NC). A few studies have suggested that plasma TDP‐43 can be an in vivo marker of frontotemporal dementia due to TDP‐43 pathology and amyotrophic lateral sclerosis. In this pilot study, we aimed to assess plasma TDP‐43 concentrations as a biomarker in individuals with autopsy confirmed LATE‐NC.

Methods

We measured plasma TDP‐43 levels in a convenience sample of 48 participants of The 90+ study (n=40) and UCI Alzheimer’s Disease Research Center (n=8) with available brain autopsy results. Of these, 26 (54.2%) were TDP‐43(+) [LATE stages 2 (n=21) and 3 (n=5)], and 22 (45.8%) were TDP‐43(‐) cases. Cases with LATE Stage 1 were not included in this study. TDP‐43 levels were measured using the Simoa TDP‐43 Advantage kit on the HD‐X platform following manufacturer’s protocol.

Results

We were able to successfully measure TDP‐43 concentrations in all plasma samples. Samples with coefficient of variation (%CV) >20% were excluded from analysis (n=5). Participants ages ranged from 72 to 104 years old (mean=95.2, SD=7.3). Of these, 29 (67.4%) were female. Demographics and neuropathological characteristics stratified by LATE‐NC presence and stage are depicted in table 1. Although non‐parametric tests showed no statistically significant differences between the groups, we found that TDP‐43 levels were higher in LATE‐NC(+), relative to LATE‐NC(‐) cases [mean=626.7 (SD=557.4) vs. 449.6 (395.1) pg/mL]. Moreover, the mean concentration of TDP‐43 tended to increase with increased staging of LATE‐NC (Table 1 and Figure 1).

Conclusion

Our results provide preliminary evidence that plasma TDP‐43 levels have the potential to be an in vivo biomarker for LATE‐NC either in isolation or combined with other potential measures. To address this, our future work will include assessing plasma TDP‐43 levels in combination with measures of inflammation and/or neurodegeneration.
Precision Medicine for Treating Alzheimer’s Disease in Down Syndrome
Authors: Sukreet Sonal , Kim Elise K , Petersen Melissa , Zhang Fan , Sano Mary , Aisen Paul S. S. , Andrews Howard F , O'Bryant Sid E. , Rafii Michael , Rissman Robert A.
Published: January 2025

Background

Individuals with Down Syndrome (DS) exhibit a genetic form of Alzheimer's disease (AD). In this study, we leveraged biobanked plasma samples from a completed clinical trial focused on anti‐inflammatory treatment, Vitamin E, for DS. The trial's primary endpoint was on cognition, and Vitamin E treatment was not found to be significantly beneficial. We examined whether applying precision medicine using an established proinflammatory endophenotype algorithm for AD therapy would reveal responders to anti‐inflammatory therapy as we have with other AD within the DS trial sample.

Method

We utilized biobanked plasma samples from the Phase 3 clinical trial titled "Vitamin E in Aged Persons with Down Syndrome (NCT00056329)." A pro‐inflammatory panel of proteins, including pre‐defined predictive protein and neuropathology markers, were assayed in baseline (n=138) and 36‐month (n=138) plasma samples. Response status was determined by evaluating the annual rate of change as measured by a combination of primary and secondary endpoints (BPT, VT, and BFDS). The predictive biomarker profile was established through SVM analyses to predict treatment response (yes/no) as the outcome variable.

Result

Pro‐inflammatory biomarkers IFN, IL10, IL12p70, 1L13, IL1B, IL2, IL4, IL6, IL8, and TNF𝛼 (along with APOE4 and demographic factors) were highly accurate in predicting the treatment responders with an AUC of 99.41%. Neuropathology markers, including Aβ40, Aβ42, Aβ42/Aβ40 ratio, NfL, GFAP, total tau, pTau181, and pTau231 with added demographic and APOE factors, predicted the responder status with an AUC of 73.98%. When the inflammatory and neuropathological data were combined into one algorithm, it produced an AUC of 97.35% (sensitivity of 81.69%, specificity of 100%) with an optimized cut‐off of 0.442 for distinguishing responder status.

Conclusion

Our findings confirmed the utility of our established AD pro‐inflammatory endophenotype for use in the DS population. We demonstrate that a protein algorithm encompassing markers related to inflammation and neuropathology can be used to generate a predictive biomarker endophenotype that can identify DS participants who are more likely to respond and benefit from anti‐inflammatory treatment. Our results demonstrate the feasibility of using precision medicine approaches for treating AD in DS. Our ongoing studies focus on understanding how these predictive algorithms relate to neuropathological progression in DS.
Cognitive Assessment through Writing Tasks
Authors: Chen Casey , Thebaud Thomas , Butala Ankur , Dehak Najim , Moro‐Velazquez Laureano , Oh Esther S
Published: January 2025

Background

Alzheimer’s Disease (AD) is a neurodegenerative disease which affects motor‐cognitive abilities including handwriting.

Past studies have used simple writing tasks to analyze handwriting fluidity, while more complex tasks can detect visual‐spatial deficits through spatial organization analysis. In this study, we extracted explainable features from the handwriting of AD patients performing various writing tasks using signal processing techniques and analyzed their importance in the cognitive assessment of AD.

Method

We collected a dataset from 60 participants, 23 with AD or MCI due to AD and 37 controls (HC), using a digital tablet. The writing tasks used involved various degrees of freedom: In Copy Text and Copy Read Text participants copied a paragraph, with and without reading it out loud, adding a multi‐tasking complexity layer, and in Freewrite participants wrote a paragraph spontaneously. In‐air and on‐tablet movements and writing pressure were collected. Multiple explainable features were extracted, such as pressure standard deviation, writing time/completion time ratio, displacements between writing, and completion time. Features from AD and HC participants were compared using Welch’s t‐test and adjusted using the false discovery rate (FDR) correction.

Result

The results show that the on‐tablet time/completion time ratio was significantly different between AD and HC (p‐value < 0.05) across all three tasks, and pressure variation was significantly different between groups for the Freewrite and Copy Read Text tasks. For Copy Read Text, there was a significant difference between groups in completion time. AD patients spent more time in‐air than on‐tablet with greater writing pressure variation.

For Freewrite, in‐air displacements between writing segments were significantly different (p‐value < 0.01) between groups. AD patients had longer average in‐air time and smaller horizontal displacement.

The results suggest a possible hesitation effect and a visual‐spatial deficit in AD patients.

Conclusion

Analysis of writing tasks with varying complexity proved useful in assessing the motor cognitive abilities of AD patients. Our results show statistically significant differences between AD and HC participants for the on‐tablet time/total task time ratio and in‐air compared to on‐tablet times across all three writing tasks suggesting greater hesitance in writing among AD patients.
Using Machine Learning to Explore Multimodal Digital Markers for Early Detection of Cognitive Impairment in Alzheimer’s Disease
Authors: Geraci Joseph , Searls Edward , Qorri Bessi , Low Spencer , Li Zexu , Joung Philip , Gifford Katherine A. , Pratap Abhishek , Tsay Mike , Cumbaa Christian , Pani Luca , Alphs Larry , Au Rhoda
Published: January 2025

Background

Recent technological advancements have revolutionized our approach to healthcare, enabling us to harness the potential of smartphones and wearables to collect data that can be used to characterize Alzheimer’s disease (AD) heterogeneity and to develop digital biomarkers. Our focus is to create comprehensive cross‐domain digital datasets and establish an infrastructure that allows for seamless data sharing. Central to accelerating the potential of digital biomarkers for more accurate and early detection is privacy‐protecting data access, which when combined with deep molecular phenotyping, will enhance our understanding of the biological mechanisms underlying clinical expression.

Methods

In the preliminary phase of this project, we analyzed data from 64 participants from the Boston University Alzheimer’s Disease Research Center and encompassing approximately 1480 variables. Our analysis approach leverages a novel machine learning (ML) technology, Attractor AI, that is capable of differentiating causal and non‐causal subpopulations within small patient or study populations and large volumes of measures, enhancing the efficacy of predictive models.

Results

We were able to subcategorize 50% of the 27 cognitively impaired (CI) subjects. A notable discovery was a distinct subpopulation of 8 individuals, 7 of whom were CI, characterized significantly by higher sleep‐derived variables such as various desaturation thresholds and periodicity measures (p=0.008‐0.00007). Additionally, incorporating maximum heart rate, revealed another group of 8 subjects, 6 identified as CI, distinguished by elevated heart rate during one or more of their measuring instances (p=10‐10).

Conclusions

While these results are preliminary, they signal a promising direction to cluster subgroups of people along similar dimensions, laying the groundwork for a precision medicine solution. Our future endeavors include expanding the scope of multimodal digital data to encompass aspects like vocalization and speech patterns derived from cognitive assessments, gait analysis, physical activity, and other cognitive tests. The integration of these diverse data streams, coupled with our preliminary sleep analysis findings, has the potential to result in a robust and accurate subgrouping system for CI to help identification of AD risk pathways that might be amenable to early intervention and either delay or prevent potential transition to AD.
Cerebrospinal Fluid Neurogranin Levels and Cognitive Function in Alzheimer’s Disease and Frontotemporal Lobar Degeneration – Data from CBAS
Authors: Jurasova Vanesa , Andel Ross , Katonova Alzbeta , Zuntychová Terezie , Horakova Hana , Vyhnalek Martin , Matoska Vaclav , Veverova Katerina , Hort Jakub
Published: January 2025

Background

Synaptic dysfunction occurs in the early stages of neurodegenerative diseases and leads to the breakdown of connections within neuronal networks. Therefore, biomarkers reflecting this process, such as neurogranin (Ng), might be useful to study disease pathophysiology and aid in diagnostics. Ng is crucial for long‐term potentiation and memory consolidation, and plays a central role in synaptic plasticity. It has been reported that Ng levels in cerebrospinal fluid (CSF) are elevated in Alzheimer’s disease (AD), but also in frontotemporal lobar degeneration (FTLD). The aim of this study was to investigate levels of Ng in AD and FTLD, and to evaluate Ng levels and cognitive function in AD.

Method

Participants with aMCI due to AD (n = 109), AD dementia (n = 67), MCI due to FTLD (n = 25), and FTLD dementia (n = 29) were recruited from the Czech Brain Aging Study. All individuals underwent clinical evaluation, MRI and analysis of biomarkers in CSF (Aß42, pTau181, tTau). Levels of Ng in CSF were measured using the LUMIPULSE® G600II instrument (Fujirebio, Ghent, Belgium). A one‐way analysis of covariance (ANCOVA) with post hoc Tukey’s HSD and multivariate linear regression with age, sex, and years of education as covariates were performed using the R statistical software.

Result

Patients with aMCI due to AD and AD dementia had significantly higher Ng levels compared to patients with MCI due to FTLD and FTLD dementia. The association between Ng levels and assessments in memory, attention, executive, language, and visuospatial domains did not statistically differ between patients with AD dementia and those with aMCI due to AD.

Conclusion

Ng levels are higher in AD compared to FTLD both in aMCI and dementia stage, but are not related to cognition in AD individuals. Our results indicate that higher levels of Ng are specifically associated with AD pathology and these changes are more prominent in aMCI due to AD suggesting Ng as an early biomarker of AD.
Greater locus coeruleus integrity predicts less accumulation of plasma pTau231 and GFAP over time
Authors: Williams McKenna E. , Fennema‐Notestine Christine , Bell Tyler R. , Franz Carol E. , Glatt Stephen J. , Panizzon Matthew S. , Rissman Robert A. , Kremen William S. , Elman Jeremy A.
Published: January 2025

Background

The locus coeruleus (LC) is one of the earliest sites of tau accumulation and integrity of the rostral‐middle LC may be a particularly early marker of AD‐related changes. LC dysfunction may also promote further pathological accumulation. We examined relationships between LC integrity and plasma phospho‐tau (pTau) and the astrocytic marker glial fibrillary acidic protein (GFAP), and whether baseline LC integrity moderates subsequent change in biomarker levels.

Method

Participants were 669 men from waves 3 and 4 of the Vietnam Era Twin Study of Aging (VETSA) (wave 3 age=67.423 [SD=2.59], follow‐up interval=5.52 years [SD=0.39]). All were cognitively unimpaired at wave 3. Linear mixed effects models tested concurrent and longitudinal relationships between baseline MRI‐assessed LC rostral‐middle integrity and pTau231 and GFAP across level of genetic risk for AD (APOE‐ε4+ versus APOE‐ε4‐). Covariates included storage time, testing site, and age.

Result

Age was positively associated with pTau231 (β=0.11, p=0.024) and GFAP levels (β=0.26, p<0.001). APOE‐ε4+ carriers showed higher levels of GFAP compared non‐carriers (β=0.23, p=0.011); APOE‐ε4 groups did not differ in levels of pTau231 or LC integrity. Baseline LC integrity was not associated with concurrent biomarker levels in either APOE‐ε4 group. In longitudinal analyses, pTau231 and GFAP increased from waves 3 to 4 (β=0.94, p=0.006, β=1.23, p<0.001, respectively). However, baseline LC integrity moderated the rate of increases, such that higher LC integrity at wave 3 was associated with less pTau231 accumulation (interaction β=‐0.19, p=0.027) for both APOE‐ε4 groups. Additionally, baseline LC integrity moderated change in GFAP from waves 3‐4, and this effect significantly differed by APOE‐ε4 status (3‐way interaction β=‐0.38, p=0.004). Effects of baseline LC integrity on biomarker change were specific to rostral‐middle but not caudal regions. Wave 3 biomarker levels did not moderate longitudinal change in LC integrity.

Conclusion

Results support the idea that higher baseline rostral‐middle LC integrity is protective against factors that cause accumulation of pTau231 and GFAP. However, the nature of the moderating effect of LC integrity on change in GFAP may be dependent on APOE‐ε4 status. Baseline biomarker levels did not moderate change in LC integrity over time, suggesting changes in LC may be an upstream event.
Brain metabolic subtypes in Long Covid individuals from a Brazilian cohort
Authors: Jotz Arthur Viana , Bastiani Marco De , Machado Luiza Santos , Schlickmann Thomas Hugentobler , Silveira Maiele Dornelles , Senger Joana Emilia , Borelli Wyllians Vendramini , Ferrari‐Souza João Pedro , Povala Guilherme , da Silva Ana Paula Bornes , da Ros João Pedro Uglione , de Mello Guilherme Bastos , Kadan Matheus Fakhri , Kadan Matheus Fakhri , Radaelli Graciane , de Paula Faria Daniele de Paula , Coutinho Artur Martins , Lourenco Mychael V , Hernández Micaela A , Calandri Ismael Luis , Pascoal Tharick A. , Matushita Cristina Sebastião , Soder Ricardo Benardi , Schumacher‐Schuh Artur Francisco , Souza Diogo O. , da Costa Jaderson Costa , de Souza Débora Guerini , Zimmer Eduardo R.
Published: January 2025

Background

The Coronavirus disease 2019 (COVID‐19), caused by SARS‐CoV‐2, is one of the biggest health concerns of the century. Long COVID is one of the major sequelae from the infection and include persistent neurological manifestations. Brain images study suggest that Long COVID patients present distinct brain metabolic alterations. However, whether brain subtypes of Long COVID exist remains unclear. Here, we aimed to evaluate metabolic patterns in FDG‐PET imaging in a Brazilian cohort of individuals presenting with Long COVID.

Method

A total of 37 adult Brazilian individuals presenting with Long COVID symptoms were scanned with FDG positron emission tomography (FDG‐PET) and its standardized uptake value ratio (SUVr normalized by the whole brain) was obtained. Then, 89 volumes of interest (VOIs) were extracted and used as input features for a principal component analysis (PCA). Average silhouette method was used to determine the optimal number of clusters. K‐means clustering was used to split the dataset into a set of K groups. We employed ANCOVA and Tukey tests to compare the groups. Statistical analysis was made in the R environment, significance set at p <0.05.

Result

PCA analysis identified three different FDG‐PET subtypes: C1 (n=4), C2 (n=6), and C3 (n=27). In the ANCOVA comparison, the regions with the highest increase in the mean regional SUVr were left lingual gyrus for C1 compared to C2 and C3, and corpus callosum for C2 against C3. Conversely, the greatest regional decrease observed were: left caudate nucleus for C1 compared to C2 and right globus pallidus for C1 and C2 compared to C3.

Conclusion

These preliminary findings suggest that Long COVID individuals present a predominant metabolic signature (C3) but at least two variants. Our results corroborate that Long COVID is a heterogeneous condition that affects individuals in a different manner. More studies are needed to understand the regional brain vulnerability to Long COVID.
Association of CSF cortisol with cortical thickness in Alzheimer's disease continuum
Authors: Souza Laura Willers , Ros Lucas Uglione Da , Bieger Andrei , Ferrari‐Souza João Pedro , Borelli Wyllians Vendramini , de Bastiani Marco Antônio , Bauer‐Negrini Guilherme , DuBois Jonathan M. , Zimmer Eduardo R.
Published: January 2025

Background

Multiple studies have linked high cortisol levels, a frequently used biomarker of stress, with the Alzheimer's disease (AD) pathophysiology. However, the relationship between cerebrospinal fluid (CSF) cortisol levels and AD‐related brain atrophy is not fully understood. This study sought to investigate the cross‐sectional and longitudinal association between CSF cortisol levels and brain cortical thickness in patients across the biological and clinical continuum of AD.

Methods

We evaluated 310 individuals from the ADNI cohort with available baseline CSF cortisol concentrations, structural MRI and CSF Elecsys biomarkers (Aβ1‐42 and p‐tau181). Cross‐sectional analysis was conducted in Freesurfer (v7.1.1) through vertex‐wise analysis using general linear models (GLMs) corrected for multiple comparisons through cluster formation (p<0.01) and permutation (Monte Carlo simulation of 10,000 iterations). Longitudinal measures of an AD signature meta‐ROI were estimated from the surface area‐weighted average of the mean cortical thickness of the following ROIs: entorhinal, inferior temporal, middle temporal, and fusiform. Linear mixed‐effects (LME) models corrected for confounders were performed to evaluate cortical thickness longitudinal trajectories. The following models were used to assess the association between cortical thickness and cortisol levels: (1) cortisol as an independent variable; (2) cortisol, clinical diagnoses, and interaction; (3) cortisol, AD biomarkers positivity, and interaction.

Results

Demographics are depicted in Table 1. Cross‐sectional analysis revealed that higher cortisol levels were associated with higher brain atrophy in several brain regions, as depicted by cortical brain thickness measures (Figure 1). These analyses also showed that cortisol does not interact with clinical diagnoses or AD biomarkers to decrease cortical thickness. In the longitudinal analyses, the association between cortisol and cortical thickness and the interaction with clinical diagnoses were not significant. However, we found that cortisol significantly interacts with AD biomarkers positivity to reduce cortical thickness values over time (β=0.002, p=0.03; Figure 2).

Conclusions

Altogether, our results support that cortisol levels potentiate AD pathophysiology effects on AD‐related brain atrophy. These findings suggest that CSF cortisol levels may affect brain vulnerability to AD pathophysiology in the long term through neurodegeneration. Thus, our results have potential implications for understating AD‐related brain atrophy and developing innovative therapeutic strategies.
Predicting Mild Cognitive Impairment in Amyloid Beta Biomarker Positive Individuals Using Automated Speech‐Based Testing Procedures
Authors: Skirrow Caroline , Meepegama Udeepa , Ropacki Michael T. , Weston Jack , Fristed Emil
Published: January 2025

Background

New disease modifying treatments for Alzheimer’s Disease (AD) require confirmation of amyloid biomarkers and evidence of clinical and/or cognitive AD symptoms. Blood tests for AD biomarkers are poised to enter routine care. However, at‐risk individuals with positive biomarkers vary in their level of cognitive impairment, raising the need for sensitive and scalable cognitive assessments. Fully automated speech‐based testing to screen for Mild Cognitive Impairment (MCI) has shown promise to bridge this gap, but its efficacy specifically within amyloid beta positive (Aβ+) individuals is yet to be fully established.

Method

Data from Aβ+ participants in the AMYPRED‐UK (NCT04828122) and AMYPRED‐US studies (NCT04928976) with Clinical Dementia Score (CDR‐G) between 0‐0.5 were analyzed. Speech recordings from Storyteller, a test battery leveraging two immediate and one delayed recall conditions from Automated Story Recall Task (ASRT), were collected from 84 Aβ+ individuals (n=38 MCI; n=46 unimpaired) who completed in‐clinic visits. A subsample of 46 Aβ+ participants (n=17 MCI; n=29 unimpaired) also completed Storyteller in a separate optional remote assessment session. Spoken responses were automatically transcribed and analysed to obtain a measure of proportional recall, “G‐match”, averaged over the three recall trials separately for in‐clinic and remote sessions. Analyses included T‐test for quantifying group differences, and prediction of MCI using the Area Under the Receiver Operating Characteristic curve (AUC). Correlations with the Wechsler Logical Memory Delayed Recall (LMDR) test and the Preclinical Alzheimer’s Cognitive Composite with semantic processing (PACC5) were also evaluated.

Result

G‐match scores differed between MCI and cognitively unimpaired participants with large effect sizes for both in‐clinic (Cohen’s d=1.36) and remote assessments (d=2.07), Figure 1. Predictive ability for MCI was shown with AUC of 0.83 and 0.92 for in‐clinic and remote assessments respectively (Figure 2). Moderate‐to‐high correlations were observed between G‐match, LMDR, and PACC5 outcomes (r=0.73‐0.84).

Conclusion

Speech‐based screening shows good sensitivity for detecting MCI in at‐risk populations. This approach could support at‐scale screening for suitability for new disease modifying treatments and for new treatment and prevention trials, with assessments incorporated into routine clinical visits or completed remotely at home.
Ultra‐widefield retinal imaging in Down syndrome: A high‐risk population for Alzheimer's disease
Authors: Lengyel Imre , Mitchell Jamie , Threlfall Adam , Beresford‐Webb Jessica , Walpert Madeleine , Holland Tony , MacGillivray Tom , Peto Tunde , Csincsik Lajos
Published: January 2025

Background

People with Down syndrome (pwDS) have a high prevalence of early‐onset Alzheimer’s disease (AD). With the two‐fold increase in life expectancy for pwDS, identifying early biomarkers for AD in this patient population is needed (PMID: 32593336). Previously we have shown that phenotyping using ultra‐widefield retinal imaging (UWFI) has the potential to identify peripheral retinal biomarkers for AD, such as higher prevalence of peripheral hard drusen (pHD) and lower peripheral retinal vascular fractal dimension (RVFD) compared to controls (Ctrl) (PMID: 29621759, PMID: 34458553). In this cross‐sectional, case‐control study, the feasibility and the utility of UWFI in pwDS was investigated.

Method

UWFI was performed on 24 pwDS and 17 cognitively healthy, age‐ and sex‐matched Ctrl. The images were graded for central and peripheral retinal vascular changes using the VAMPIRE software.

Result

After quality control, 39 images of 20 patients and 34 images of 17 Ctrl were included in the study. pHD were detected on most of the images across both groups with no significant difference between pwDS and Ctrl. There was a higher arterial RVFD in the central zone (P<0.001) but no difference was observed in the peripheral zone. The venular RVFD were higher in the central zone (P<0.005) but lower in the peripheral zone (P<0.001) in pwDS compared to Ctrl. These results were the same with those diagnosed with and without AD. The arteriolar and venular width gradients were both significantly decreased in pwDS compared to Ctrl (P<0.02). This difference was only present in those with AD diagnosis.

Conclusion

This study proved that UWFI is feasible in pwDS, and there are vascular changes that are associated with DS, especially in those with the diagnosis of AD. Therefore, we propose that peripheral retinal vasculature changes may hold a potential to monitor the progression of AD in this patient population.
Reducing the Use of Physical Restraints in the care of Persons with Delirium and Dementia: A Quality Improvement Project
Authors: Houston Elizabeth Reaves , Mournighan Kimberly , Lynch David H
Published: January 2025

Background

Hospitalized older adults, especially those with Alzheimer’s Disease and Related Dementias (PwD), are at high risk for delirium and distressing behaviors. Using physical restraints leads to functional decline and increased mortality. Our project aims to reduce restraint use by implementing a 4Ms approach for enhanced delirium management.

Methods

Our interdisciplinary team used the Plan‐Do‐Study‐Act methodology over a 7‐month period (including 8 weeks of training) to introduce the 4Ms (Mentation, Mobility, Medication, what Matters) model in our 25‐bed Acute Care for Elders (ACE) unit. Nurses were trained in the Confusion Assessment Method (CAM) for delirium assessment, CAM‐S for delirium severity, and Six‐item Cognitive Impairment Test (6CIT) for cognitive impairment. Staff conducted the 6CIT per admission and CAM/CAM‐S per shift for patients aged ≥65, with electronic score documentation. Physical therapy assessed mobility within 24 hours of admission and during medical rounds. Medication reviews, led by the medical team and a geriatric pharmacist, occurred for new admissions. What Matters considerations were addressed through comprehensive geriatric assessments. Chart review collected data. An electronic record quantified physical restraint orders for six months pre‐ and post‐intervention, by patient days and distinct patients per month.

Results

In the 19 weeks following data collection initiation, ACE unit patients (n = 362) averaged 81 years old, 60% female, 83% white, 14% Black, 18% were PwD, and 24% had significant cognitive impairment (6CIT score). Twenty‐two percent experienced incident delirium during a mean 6‐day stay. Documentation improved: CAM (68% to 86%), CAM‐S (0% to 79%), 6CIT (0% to 89%). A 4Ms checklist achieved a 96% completion rate with 37.5% receiving a geriatric assessment, 25% were discharged with an ADL disability, and 12.5% had medication deprescribed. Restraint use decreased from 7.7 patient days per month to 2.2, distinct patients with restraints decreased from 2.7 to 1.7.

Conclusions

In a high‐risk older adult population, a low‐resource quality improvement intervention effectively implemented the 4Ms model of care, showing a positive trend in reducing restraint use.
Traditional Japanese Kampo Medicine Yokukansan decreases phosphorylated tau and oligomeric tau
Authors: Mori Chika , Yamamoto Ryota , Shirafuji Norimichi , Asano Rei , Sasaki Hirohito , Yamaguchi Tomohisa , Kitazaki Yuki , Endo Yoshinori , Enomoto Soichi , Hamano Tadanori
Published: January 2025

Background

One of the pathological hallmarks in Alzheimer’s disease (AD) brain is neurofibrillary tangles (NFTs) composed of highly phosphorylated tau protein. Clinical benefit of traditional Japanese Kampo Yokukansan for dementia patients, including AD was suggested. In this study, we investigated whether yokukansan participates in the degradation of phosphorylated tau and toxic oligomeric species of tau by using cell culture model of tauopathy, M1C cells.

Method

Neuronal cellular model of tauopathy, M1C cells which expresses wild type tau protein (4R0N) via tetracycline off induction (TetOff induction) was used in this study. M1C cells were treated with Ten to fifty ug/mL of Yokukansan and analyzed by Western blot analysis. Various phosphorylated tau antibodies (AT 180, AT270, and PS199/202) were used to detect phosphorylated tau. Oligomeric tau was examined by anti‐oligomeric tau specific antibody (TOC‐1) by dot blot analysis.

Result

Up to 100 µg/mL of Yokukansan has no cytotoxic effects on M1C cells examined by morphological study, and ATP assay. WB analysis disclosed that of 10 to 50 µg/mL of yokukansan decreased phosphorylated tau detected by AT180, AT270, and PS199/202. Oligomeric tau detected by TOC1 also decreased by Yokukansan treatment. Major tau phosphatase GSK3β was inactivated by Yokukansan treatment. Autophagy marker P62 was downregulated by Yokukansan treatment.

Conclusion

These results suggest that phosphorylated tau and oligomeric tau was reduced by Yokukansan via tau kinase inactivation and autophagy activation. Although the exact mechanisms of yokukansan on tau phosphorylation and oligomerization should be explored, these results shed light on the therapeutics of tauopathy, including AD.
Predicting Future Entorhinal Tau Levels through Amyloid PET Patterns: A Longitudinal Machine Learning Approach in Preclinical Alzheimer’s disease
Authors: Vahid Amirali , Zamani Jafar , Hosseini Hadi
Published: January 2025

Background

Amyloid‐β (Aβ) plaques and tau tangles represent pivotal hallmarks of preclinical Alzheimer's disease (AD). Accumulating studies highlight a potential association between Aβ and tau, suggesting that the progressive deposition of Aβ may significantly contribute to build up of tau in the entorhinal cortex which subsequently result in neurodegeneration and cognitive decline. However, pattern of Aβ depositions that would result in tau development or propagation remains elusive. This study aims to leverage advanced machine learning along with longitudinal PET measures of brain Aβ and tau load to identify the most critical brain regions where the presence of Aβ is predictive of levels of future entorhinal tau levels.

Method

An Elastic‐Net model was applied to baseline Aβ SUVR data to predict entorhinal tau levels across multiple tau‐PET acquisition time points (0 to 5 years from baseline). The study focused on 80 subjects (41 female, mean (SD) age 71.8 (6.7) years) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) who had longitudinal data at all specified time points. Additionally, explainable AI, particularly SHapley Additive exPlanations (SHAP), was utilized to discern the model's learning process and identify brain regions significantly contributing to predicting the longitudinal entorhinal tau levels.

Result

The R‐scores between actual and predicted entorhinal tau value for time points 0 to 5 were: 0.36, 0.42, 0.47, 0.38, 0.47, and 0.40 (all p‐values < 0.001), as depicted in Figure 1. Notably, SHAP measures revealed that Aβ load in the rostral middle frontal, superior frontal and frontal pole regions contributed the most to prediction of future entorhinal tau 0 to 4 years later (Figure 2). These regions accompanied with the left inferior parietal lobe as most significant predictors of entorhinal tau at time point 5 (Figure 2).

Conclusion

Our findings suggest that Aβ loud in the medial and rostral frontal regions are highly predictive the development of tau in the entorhinal cortex within four years and may signal progression to clinical AD, considering that entorhinal tau is the most proximal correlate of neurodegeneration and future cognitive decline
Blood‐based plasmatic aminoacid profiles as potential biomarkers for dementia
Authors: Palmeira André Luiz Rodrigues , Fernandez Liana Lisboa , Pachado Mayra Pacheco , de Paula Leonardo Martins , Fontela Carolina , Oliveira Tiago Gil , Eller Sarah
Published: January 2025

Background

The study of new blood biomarkers in addition to amyloid beta and hyperphosphorylated tau is fundamental to expanding the understanding of the pathophysiology of dementia, especially Alzheimer`s disease, in search of therapeutic approaches.

Method

In this study, we included individuals diagnosed with Alzheimer disease (AD), Mixed‐type dementia (MD), Vascular dementia (VD) and a control group of cognitively healthy individuals. Demographics, clinical characteristics, neuroimages and plasma samples were collected. We performed a metabolomic aminoacid analysis using High‐Performance Liquid Chromatography‐Mass Spectrometry (HPLC‐MS/MS). Analyses were performed with GraphPad Prism 9.0 (GraphPad Software, San Diego, USA) or SPSS v. 18 software. Depending on the group comparison type, one‐way analysis of variances with post‐hoc Tukey‐HSD test or independent samples t‐tests. We compared aminoacid levels between the different groups (controls, AD, MD or VD) and dementia severity, assessed by Clinical Dementia Rating (CDR) score.

Result

135 individuals were clinically assessed as 33 controls, 42 AD, 41 MD and 19 VD. There was a statistically significant difference between controls and individuals with dementia in the following amino acids: aspartic acid (p<0.0001), arginine (p<0.0001), glutamic acid (p<0.0001), glutamine (p<0.0001), isoleucine (p<0.0008), leucine (p<0.0001). However, only arginine proved to be a biomarker capable of differentiating AD from DV (p<0.0003)

Conclusion

These preliminary analyses show that leucine, isoleucine and glutamine were reduced in the plasma of patients with dementia, while aspartic acid, glutamic acid and arginine were increased. These markers can help us identify the underlying metabolic dysfunctions of different signaling pathways relevant to neuroprotection and vascular function.
Alzheimer's Disease cerebrospinal fluid Biomarkers and kidney function in normal and cognitively impaired older adults
Authors: Neal Reem M. , Yang zhiyi , Lah James J. , Hajjar Ihab
Published: January 2025

Background

Recent Alzheimer’s disease (AD) clinical trials have used CSF biomarker levels for screening and enrollment. Preliminary evidence suggests Alzheimer’s Disease (AD) risk may be related to impaired renal function but the association of variation in levels of biomarkers commonly used AD biomarkers with kidney function is unknown.

Method

We conducted an analysis using data from participants enrolled in two research protocols at the Goizueta Alzheimer’s Disease Research Center that had simultaneous measurements of serum creatinine at the time of their Cerebrospinal fluid (CSF) collection (N=970). The participants had a mean age of 66.5 years, with 52% showing mild cognitive impairment (MCI). Among them, 31% were of African American ethnicity, and 62% were women. Estimated glomerular filtration rate (eGFR) was obtained from chronic kidney disease‐epidemiology Collaboration. All participants had similar CSF collection procedures. Aβ42, Tau, or pTau were measured on the Luminex ALZBIO platform. General linear models and individual data were used to assess relationships between biomarkers and eGFR.

Result

The analysis revealed significant associations between all three biomarkers and eGFR. The slopes per unit of eGFR were as follows: 0.75 (p=0.002) for Aβ42, ‐0.39 (p<0.0001) for Tau, and ‐0.13 (p=0.0002) for pTau. The association between eGFR and AD biomarkers was independent of cognitive status. However, there was a notable interaction between MCI and eGFR, where the impact of eGFR on AD biomarker levels was more robust in individuals with cognitive impairment (interaction p‐values: MCI*GFR: 0.005, Tau: 0.04, pTau: 0.04)

Conclusion

We found a significant association between eGFR with CSF levels of Aβ42, tau, and pTau that were stronger in those with mild cognitive impairment. This suggests that kidney function should be considered in the context of interpreting the positivity of AD biomarkers in clinical evaluations and clinical trials, especially in those in the early symptomatic stage of AD. Future studies need to further explore the impact of kidney function and other comorbidities on the interpretation of AD Biomarkers.