bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of multiple ATN biomarker definitions for prediction of cognitive impairment
Authors: Earnest Tom , Yang Braden , Kothapalli Deydeep , Sotiras Aristeidis 
Published: January 2025

AbstractBackgroundApplication of the amyloid/tau/neurodegeneration (ATN) framework is varied, with some research relying on binary assessment of biomarkers and some using continuous or multidimensional measures. There are few investigations which directly evaluate how differing operationalizations of ATN affect prediction of cognitive impairment.MethodWe selected 473 individuals from ADNI who received PET imaging for amyloid‐beta (AV‐45) and tau (flortaucipir), as well as volumetric MRI. We evaluated a wide range of methods for deriving ATN biomarker assessments, spanning continuous, binary, and non‐binary categorical (i.e., staging models or quantiles of continuous values) measures (Table 1). We trained linear regression models to predict Preclinical Alzheimer Cognitive Composite (PACC) scores, combining different variations of ATN measures as predictors. We additionally used support vector machines (SVMs) to derive multivariate ATN measures; these models used regional PET uptakes or gray matter volumes (68 FreeSurfer regions) to predict PACC. A first set of experiments tested how addition of ATN improved prediction over a baseline model with just covariates (age, sex, APOE status), while a second set of experiments tested how models including non‐binary or SVM‐based ATN measures compared to ones using only binary measures. We used a repeated, nested, and cross‐validated design to evaluate the out‐of‐sample model performance as quantified by the root mean square error. Error estimates were compared using bias‐corrected t‐tests.ResultCompared to models with standard covariates, addition of any ATN measure resulted in an increase in accuracy for predicting cognitive ability (Figure 1A). Benefits were largest for models which included tau or all three ATN assessments. SVM‐based models also outperformed baseline models. However, when compared to models using all‐binary ATN measures, addition of categorical, continuous, or SVM‐based ATN measures did not significantly improve prediction accuracy in any combination (Figure 1B). Feature importance analysis indicated that some ATN definitions consistently outperformed others (Figure 2).ConclusionBinary measures of ATN may be sufficient for prediction of cross‐sectional cognitive impairment. Further work is required to evaluate if these results hold in specific subpopulations (e.g., preclinical AD) or for predicting other measures of interest (e.g., longitudinal cognitive decline).
Plasma ADRD biomarkers predict longitudinal declines in intra‐network functional brain connectivity, and baseline functional connectivity predicts longitudinal cognition
Authors: Dark Heather E , Shafer Andrea T , Cordon Jenifer , An Yang , Lewis Alexandria , Moghekar Abhay , Landman Bennett A. , Resnick Susan M. , Walker Keenan A. 
Published: January 2025

AbstractBackgroundAD is defined by cortical amyloid‐β (Aβ), tau neurofibrillary tangles, and neurodegeneration, pathological processes which may contribute to cognitive decline by altering large scale functional brain networks. To test this hypothesis, we examined whether plasma biomarkers of AD pathology (Aβ42/40, phosphorylated tau [pTau‐181]), astrogliosis (glial fibrillary acidic protein [GFAP]), and neuronal injury (neurofilament light chain [NfL]) related to longitudinal changes in resting‐state functional connectivity (rsFC) in cognitively unimpaired participants from the Baltimore Longitudinal Study of Aging.MethodBaseline plasma biomarkers were measured with Quanterix SIMOA assays. Functional connectivity (3T resting‐state fMRI) was derived using a predefined cortical parcellation mask from which intra‐network connectivity from seven functional networks was extracted for each participant. Amyloid status (positive/negative) was defined using plasma Aβ42/40 (Figure 1). Linear mixed effects models adjusted for age, sex, race, education, gray matter volume, and time‐covariate interactions were used to determine whether 1) baseline plasma biomarkers predicted longitudinal changes in rsFC, 2) the magnitude of the biomarker‐related rsFC changes differed by amyloid status, and 3) rsFC predicted longitudinal changes in cognition.ResultLongitudinal connectivity analyses (mean age±SD=65.49±16.17) included 490 participants (1190 visits; mean follow‐up time=4.31±1.68 years). Higher Aβ42/40, GFAP, and NfL were associated with faster declines in rsFC within several networks (P‐range=0.01‐0.04; Figure 2). Overall, plasma biomarker‐rsFC associations differed by amyloid status (P‐range=0.01‐0.045). Among amyloid‐positive participants, lower levels of Aβ42/40, and higher levels of GFAP, and NfL (Figure 2) were associated with faster declines in rsFC in the visual, dorsal and ventral attention, limbic, and frontoparietal networks (P range=<0.002‐0.04). There were no statistically significant associations between plasma biomarkers and rsFC change among amyloid‐negative participants. Among 760 participants with at least one rsFC scan (mean age±SD=67.21±14.93; 1550 visits, follow‐up time=3.94±1.60 years), we found that baseline rsFC in several networks predicted changes in cognition, e.g., working memory, verbal fluency, and visuospatial abilities (P range=0.02‐0.049; Figure 3).ConclusionAmong cognitively normal individuals, plasma biomarkers of Aβ42/40, astrogliosis, and neuronal injury are associated with future intra‐network functional brain changes, particularly in the context of elevated amyloid. Hypo‐ and hyper‐ intra‐network connectivity may drive changes in cognitive performance.
Serving the Underserved in an Underserved Setting
Authors: Tefera Ayda K , Grinberg Lea T. 
Published: January 2025

AbstractBackgroundThe COVID‐19 pandemic in Ethiopia posed additional challenges to an already strained mental health service. Eka Kotebe Hospital, the second‐largest mental health facility with a capacity of 175 beds, was transformed into a dedicated COVID‐19 treatment center, leaving mental health service users, especially vulnerable elderly patients with cognitive impairments, without adequate support.I had the challenge to implement alternatives to provide mental health services coverage to underserved elderly population. Here, I describe the process and results of a novel community outreach project done in partnership with a local nursing home (Mekedonia) which shelters homeless elderly and people with mental illness.MethodFollowing the formalization of MOU, our master’s level professionals and psychiatric nurses, started to conduct four visits per week to Mekedonia. The primary goal was to identify complex cases and tailor management plan.ResultsAt the program inception, the shelter housed approximately 5000 individuals, necessitating an initial task of conducting comprehensive health assessments and classifying patients based on their clinical conditions. Most of the residents in the shelter are persons with intellectual disabilities, elderly individuals with mental illness and dementia.The ongoing pandemic further compounded the difficulties in conducting thorough assessments, with majority of assessments relied heavily on clinical history, which was inaccurate due to lack of knowledgeable informant, and Mini‐Mental State Examination (MMSE).Remarkably, a significant portion of the clients had their first encounter with a medical personnel through our program, revealing a high prevalence of multiple medical comorbidity among this population. Management includes controlling aggression, treatment of insomnia, addressing comorbidity and facilitating referrals. The data indicated that most clients were 40 and above, In 2021 we were able to identify and manage 50 dementia patients and the number has doubled to 100 in 2022 and 153 cases people were identified in 2023. Currently the program has sustained on bigger scale, and we are deploying GPs, Neurologists and Psychiatrists to address the diverse health needs of this vulnerable population.ConclusionDespite all the challenges, the project underscored the importance of tailored outreach initiatives to address the unique needs of homeless elderly individuals during unprecedented times.
Microglial activation impacts amyloid‐β effects on reactive astrogliosis
Authors: Ferrari‐Souza João Pedro , Povala Guilherme , Bellaver Bruna , Ferreira Pamela C.L. , Lussier Firoza Z , Leffa Douglas Teixeira , Aguzzoli Cristiano Schaffer , Soares Carolina , Carello‐Collar Giovanna , Borelli Wyllians Vendramini , Therriault Joseph , Rahmouni Nesrine , Macedo Arthur C. , Servaes Stijn , Stevenson Jenna , Gauthier Serge , Souza Diogo O. , Schilling Lucas Porcello , Lourenco Mychael V , Tudorascu Dana , Rosa‐Neto Pedro , Pascoal Tharick A. , Zimmer Eduardo R. 
Published: January 2025

AbstractBackgroundGlial reactivity is a key phenomenon in Alzheimer’s disease (AD) and is closely associated with amyloid‐β (Aβ) pathology. Although compelling experimental data suggest that microglial activation modulates reactive astrogliosis, it remains to be elucidated whether microglial activation influences the association of Aβ pathology with reactive astrogliosis in the living AD human brain. Here, we tested the association of microglial activation and Aβ pathology with reactive astrogliosis in individuals across the aging and AD clinical spectrum.MethodWe studied 101 participants (62 cognitively unimpaired [CU], 26 with mild cognitive impairment [MCI], and 13 with AD dementia) from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort. Individuals had available positron emission tomography (PET) for Aβ ([18F]AZD4694) and microglial activation ([11C]PBR28), as well as magnetic resonance imaging. We further assessed reactive astrogliosis with plasma glial fibrillary acidic protein (GFAP). Linear regression analyses were used to investigate the associations between Aβ, microglial activation and GFAP.ResultDemographic characteristics of the study population are reported in Table 1. Regression analyses revealed a significant positive association between Aβ PET burden and plasma GFAP levels in microglial activation‐positive but not in microglial activation‐negative individuals (Figure 1A). A significant interaction between continuous values of Aβ PET burden and [11C]PBR28 PET uptake on plasma GFAP levels (Figure 1B) supported that microglial activation affects the association of Aβ pathology with reactive astrogliosis. Analysis of variance further confirmed that the model with the interaction term was the most adequate to describe the association of Aβ PET and microglial activation PET with plasma GFAP (P = 0.007). In additional analyses investigating the topography of the observed findings, we found that higher Aβ PET burden was associated with higher plasma GFAP levels only in the presence of microglial activation positivity across Aβ‐vulnerable cortical brain regions (Figure 1C).ConclusionOur results suggest that microglial activation impacts Aβ‐dependent reactive astrogliosis in the living AD brain. This can help to better understand the complementary roles of glial cells in neurodegenerative diseases, as well as provide insights for the development of novel therapeutic strategies for AD targeting the interplay between Aβ and glial reactivity.
Feasibility of using plasma p‐tau217 as a surrogate for brain Aβ PET in the community
Authors: Balogun Wasiu Gbolahan , Deek Rebecca A , Zeng Xuemei , Sehrawat Anuradha , Chen Yijun , Ferreira Pamela C.L. , Bellaver Bruna , Lafferty Tara K , Povala Guilherme , Kamboh M. Ilyas , Villemagne Victor L , Klunk William E , Pascoal Tharick A. , Ganguli Mary , Lopez Oscar L. , Cohen Ann D , Snitz Beth E. , Karikari Thomas K 
Published: January 2025

AbstractBackgroundPlasma p‐tau217 is probably the best‐performing blood biomarker to detect brain amyloid‐beta (Aβ) accumulation. However, previous studies were mostly performed in highly selected cohorts. Thus, it is unclear if it can be used independently of confirmatory neuroimaging tests to identify individuals with abnormal brain Ab load in the wider population where positron emission tomography (PET) may be unavailable. We evaluated the feasibility of plasma p‐tau217 replacing Ab PET in two population‐based cohorts.MethodsThis study used data from two population‐based cohorts; the Monongahela‐Youghiogheny Health Aging Team (MYHAT) Neuroimaging study (n=111, median age 76 IQR: 72‐80, 54% female), in a medically and economically‐depressed Rust Belt area of southwestern Pennsylvania, and the Human Connectome Project (HCP) (n=229, median age was 62 IQR: 56‐70, 65% female) of self‐identified Black and non‐Hispanic Whites in Pittsburgh city. Plasma p‐tau217 was measured using assays from the University of Pittsburgh, ALZpath Inc., and NULISA from Alamar Biosciences. Aβ imaging was performed with 11C‐PiB, where global Aβ+ was defined using a threshold of 1.346 SUVR.ResultsThe primary analysis used ALZpath p‐tau217 for both studies. Specifically, MYHAT‐NI reported a Positive Predictive Value (PPV) of 0.6 and Negative Predictive Value (NPV) of 0.92, as well as sensitivity and specificity of 0.82 and 0.80, respectively. PPV measures the probability a predicted positive patient has Ab accumulation, NPV is defined analogously for negative patients. Secondary subset analyses using the UPitt p‐tau217 and NULISA p‐tau217 assays showed similar performances (PPV: 0.56‐0.60, NPV: 0.89‐0.93). The primary analysis in HCP showed a PPV of 0.40 and NPV of 0.97, with corresponding sensitivity of 0.85 and specificity of 0.78. The secondary analysis using UPitt p‐tau217 performed comparably (PPV: 0.38 and NPV: 0.97).ConclusionThe consistently high NPV but poor PPV suggest that all the plasma p‐tau217 assays will be most useful as a first‐screening tool to identify individuals without pathological evidence of brain Ab for exclusion from clinical trials, therapeutic trials, and prescription of approved therapeutic agents. This would enable streamlined enrichment of individuals who would require confirmatory testing. Future research will investigate impacts of population health outcomes including comorbidities.
From glia to cytokine signatures across the Alzheimer’s spectrum
Authors: Malpetti Maura , Swann Peter , Chouliaras Leonidas , Jones P Simon , Mak Elijah , Bevan‐Jones W Richard , Su Li , Fryer Tim D , Hong Young T , Aigbirhio Franklin I , O'Brien John T , Rowe James B 
Published: January 2025

AbstractBackgroundEarly neuroinflammation is involved in pathophysiology of Alzheimer’s Disease (AD) and contributes to faster clinical decline. Thus, neuroinflammation has emerged as a promising therapeutic target for dementia. However, a better understanding of the interaction between central and peripheral inflammation in human disease and in vivo biomarkers are required for successful clinical trials. Here we assess inflammatory patterns of serum cytokines and their relationship with central inflammation as quantified by TSPO PET (PK11195) in participants on the aging‐AD spectrum.MethodBlood samples were obtained from 56 participants, including30 controls, 22 patients with MCI and 14 with AD) Serum cytokines were quantified using the MesoScale Discovery V‐Plex‐Human Cytokine panel. We applied a Principal Component Analysis (PCA) across all participants to identify inflammatory profiles, which were compared across groups with ANOVA and post hoc tests. Individual scores of the resulting components were correlated with regional TSPO PET binding potentials, as index of microglial activation, and cognitive impairment (MMSE scores).ResultAnalyses on 30 identified 2 components (explaining 19.4 % and 10.8% of the variance, respectively). Both components were strongly represented by pro‐inflammatory cytokines (Figure 1A). One‐way analyses of variance on the first component could not detected statistically significant differences across the groups (χ2(2)=1.69, p=0.193), while individual scores of Component 2 (χ2(2)=8.46, p<0.001) were statistically higher in patients with AD as compared to patients with MCI and to controls (Figure 1B). Correlation analyses with regional TSPO PET values identified positive widespread associations with individual Component 2 scores in frontal, temporal and parietal regions (r > 0.250, p < 0.05; while associations with Component 1 where limited to the anterior frontal/temporal regions (Figure 1C). Individual scores of Component 2 but not Component 1 were significantly associated with worse cognitive performance (lower MMSE; r = ‐0.315, p = 0.01).ConclusionOur approach identified proinflammatory blood signatures that relate to central inflammation and cognitive impairment across the aging‐AD spectrum. These findings encourage the combination of TSPO imaging and blood‐based markers to clarify the interaction between peripheral and central inflammation in AD, and to identify promising therapeutic targets.
A study and training of careers on effective cognitive therapy for elderly to prevent dementia in Lagos, Nigeria. (Proposed Project)
Authors: Akinyelure Feyikemi Mary , Adeyoola Tolulope , Adeife Adetayo Adetutu , Jet Lucky 
Published: January 2025

AbstractBackgroundThe immediate family members, trusted caregivers or the society often subject the elderly in Nigeria to abuse. The most vulnerable amongst the elderly are poor and disadvantaged ones who often times are on the receiving end. Effective cognitive training is a non‐pharmacology treatment that focuses on guided practice on cognitive tasks.AIMSTo train careers in effective cognitive therapy (graded table top activities, memory exercises activities, problem solving games) and activities of daily routine.To determine the effectiveness of cognitive therapy game impact on older adult in preventing Dementia, Alzheimer e.t, c.To evaluate the feasibility of the training intervention implementation.MethodsWe'll train 120 health care assistant annually in Lagos Nigeria.Training: Theoretical (Dementia knowledge), Practical (Dementia assessment and screening)Evaluation: Standardized Mini Mental‐State Examination and the clock drawing test (CDT)Expected outcomes.The primary outcome is to train careers in caring for the elderly effectively which would lead to prolong life.The secondary outcome is to reduce the impact of dementia through knowledge and skills the careers must have gained.
Large‐scale validation of an improved and resource‐saving immunoprecipitation‐mass spectrometry assay for plasma amyloid‐β biomarkers in Alzheimer's disease
Authors: Chen Yijun , Zeng Xuemei , Olvera‐Rojas Marcos , Sehrawat Anuradha , Lafferty Tara K , Klunk William E , Ikonomovic Milos D , Pascoal Tharick Ali , Erickson Kirk I. , Villemagne Victor L , Cohen Ann D , Yates Nathan , Esteban‐Cornejo Irene , Lopez Oscar L. , Snitz Beth E. , Berman Sarah , Sweet Robert , Karikari Thomas K 
Published: January 2025

AbstractBackgroundAmyloid β (Aβ) deposition in the brain is a pathological hallmark of Alzheimer's disease (AD). While immunoprecipitation‐mass spectrometry (IP‐MS) stands out as an accurate method for quantifying blood‐based Aβ peptides, its major limitations such as prolonged sample preparation, extensive analysis time, large specimen volume, and high costs, present opportunities for improvement. Consequently, we aimed to develop a novel plasma IP‐MS Aβ assay that employs simplified and significantly shorter analytical procedures, along with much‐reduced sample volumes.MethodWe evaluated effects of reducing the sample volume, changing the buffers, implementing heavy labeled internal standards, and switching to a more cost‐effective MALDI‐Tof mass spectrometer versus the original Shimadzu IP‐MS Aβ assay (Nakamura et al., 2018 Nature). This led to an improved assay, referred to as the Pittsburgh IP‐MS Aβ assay. Analytical validation covered linearity, accuracy, precision, and recovery. In clinical validation, we compared the new and original Aβ assays for identifying Aβ‐PET positivity and cognitive impairment in two independent cohorts.ResultThe Pittsburgh assay streamlined the immuno‐enrichment step with a novel binding buffer, cutting background noise and reducing processing time by 50%. Additionally, it allowed for potential sample volumes as low as 50 µl and decreased antibody and paramagnetic bead usage by 75% each. The assay utilized the cost‐friendly MALDI‐Tof instrument from Bruker, a departure from the AXIMA Performance platform used in the original assay.The analytical validation showed consistent signal linearity, improved spike recovery with heavy labeled Aβ1‐40 or Aβ1‐42, but equivalent precision between the two IP‐MS methods. In the AGUEDA cohort (n=148), the Pittsburgh assay demonstrated better AUCs than the older method for identifying Aβ‐PET‐positive individuals. This trend persisted in the University of Pittsburgh ADRC cohort (n=30) when comparing accuracy to identify patients with clinical assessed AD positive.ConclusionWe have developed a more efficient and cost‐effective IP‐MS plasma Aβ assay, outperforming the original Shimadzu assay in clinical utility, while upholding consistently high analytical performance. The cost, time, and reagent savings along with the utilization of a more affordable and widely available instrument will empower more research laboratories to conduct IP‐MS analysis of Aβ in blood more effectively.
The correlation between inflammatory marker and cognitive performance in TATA Longitudinal Study of Aging cohort
Authors: Arvind Prathima , M L Abhishek , Stezin Albert , Diwakar Latha , C M Amitha , Partha Ajith , Narayanasamy Rajitha , N M Divya , R Meghana , Menon Meenakshi , HS Sunitha , Velavarajan Goutham , Malo Palash K , Singh Sadhana , Vishwanath Vindhya , HS Dev Kumar , Hameed Shafeeq K Shahul , Sundarakumar Jonas S. , Issac Thomas Gregor 
Published: January 2025

AbstractBackgroundIn the scientific literatures, C‐reactive protein (CRP), a well‐known inflammatory biomarker1, has been closely examined in connection to cognitive function2. However, less knowledge on correlation study between the serum CRP level and different cognitive domain. Therefore, we aimed to study the relation between CRP level and cognition performance in TLSA cohort.MethodThe study involved 1164 participants from the TLSA cohort, an ongoing longitudinal study on aging in Indian urban populations. Cognitive performance was tested using ACE‐III and evaluated CRP levels. Spearman's correlation analysis was performed to see the relation between the CRP level and cognitive performance in whole cohort as well as to identify gender and age‐specific associations between inflammation and cognitive function.ResultThe mean age of the entire cohort was 61.72 ± 9.39 (N=1164), with a gender distribution of 50.5% male and 49.5% female. The median education level stood at 14.5, with a standard deviation (SD) of ± 4.26. Notably, ACE‐total, attention, and visuospatial domains exhibited significant inverse associations with CRP levels across the entire cohort (Table 1). In the subgroup analysis, individuals below 65 years of age showed significant inverse associations between CRP levels and ACE‐total, attention, memory, fluency, and visuospatial domains. However, in the above 65 years age group, only ACE‐Visuospatial demonstrated an inverse association with CRP levels (Table 2a). Further stratification by gender revealed ACE‐attention to be inversely associated in male participants, while ACE‐total and visuospatial domains exhibited associations in the female group (Table 2b).ConclusionThis study reveals significant inverse connections between CRP levels and cognitive domains, particularly in the younger population, suggesting potential hormonal influences. The findings underscore the need for tailored approaches to understand the complex interplay between inflammation and cognitive function across diverse demographic contexts.