bluuebunny/crossref_metadata_2025_split huggingface dataset:
Drug Trial Decision‐Making Among Patients with Mild Cognitive Impairment and their Study Partners
Authors: Cox Chelsea G , Salazar Christian R , Gillen Daniel L , Grill Joshua D 
Published: January 2025

AbstractBackgroundProdromal Alzheimer’s disease (AD) clinical trials of candidate treatments enroll individuals with mild cognitive impairment (MCI) and biomarker evidence of AD. These trials require co‐enrollment with a study partner and complex decision‐making, weighing potential risks and benefits of participation. Some patients with MCI lack capacity to provide trial informed consent.MethodWe performed structured interviews with patients with MCI and their study partners. We presented a description of a hypothetical prodromal AD drug trial, followed by questionnaires to assess (a) involvement of the study partner in trial decisions, (b) patient capacity to consent, and (c) patient performance in health numeracy. We assessed level of agreement among dyads using the weighted kappa statistic and examined the frequency with which patients demonstrated impaired health numeracy and lack of capacity to provide consent.ResultAmong 65 patients with MCI, most were male (66%) and non‐Hispanic White (88%) with a mean (SD) age of 74.9 (8.4) years. Among 57 study partners, most were spouses (83%), female (74%), and non‐Hispanic White (91%) with a mean (SD) age of 70.3 (13.6). Half of patients (51%) and 72% of study partners reported being very or extremely likely to participate in the trial. Most patients (66%) and study partners (72%) stated that they would make the decision to enroll in the trial in partnership, while 28% of patients said they would make the decision on their own with input from their partner. Half of dyads (50%) agreed the decision would be made in partnership, but we found limited dyadic agreement overall (kappa = 0.187, 95% CI: ‐0.057‐0.431). Thirty‐eight percent of patients lacked capacity to consent. Patient health numeracy scores ranged from 3‐12 with a mean (SD) of 8.6 (2.5); 38% demonstrated impaired health numeracy. Sixteen patients (25%) demonstrated both a lack of capacity and impaired health numeracy, among whom seven patients reported they would make trial decisions on their own with input from a partner.ConclusionSome patients with MCI may be at risk for decision errors in the informed consent process for a prodromal AD clinical trial.
Allostatic Load and its Impact on amyloid, tau, and hippocampus: a potential underlying mechanism explaining variability in Alzheimer's Disease pathology and progression
Authors: Souza‐Talarico Juliana Nery , Hein Maria , Perkhounkova Yelena , Lee Jihye 
Published: January 2025

AbstractBackgroundAccumulation of β‐amyloid (Aβ) and tau proteins can predict the risk of Alzheimer's disease (AD) at asymptomatic stages and are promising measures for screening individuals at risk. However, not all individuals with Aβ and tau pathology progress to AD; some remain cognitively healthy. That variability challenges prediction accuracy and incorporation of AD pathology into clinical practice. Identifying underlying mechanisms that accelerate AD progression is critical to understanding disease trajectories, assessing risk, and promoting timely intervention. Allostatic load (AL), or the "wear and tear" of chronic stress, has been linked to AD risk. However, whether AL influences AD pathology requires further investigation. We aimed to determine the relationship between AL, Aβ, tau, and hippocampus volume (HV).MethodsUsing the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we analyzed longitudinal data from 385 older adults. Blood neuroendocrine (cortisol, LH, prolactin, testosterone) and immunologic (C‐reactive protein, fibrinogen, IL‐13, IL‐16, IL‐18, IL‐3, IL‐6, MCP‐3, MCP4, TNF‐alpha, insulin‐like growth factor) stress‐related biomarkers obtained at baseline and 12 months were combined into an AL index. Aβ42 measured in the blood (Aβ42blood) and cerebrospinal fluid (Aβ42CSF), CSF p‐tau proteins, and HV from brain MRI were analyzed over 24 months. Linear mixed models were adjusted for socioeconomic and APOE4 covariates.ResultsHigher AL increases over 12 months were associated with higher elevation on p‐tau (p=.007; 95%CI [‐.927,‐.147]), and Aβ42blood (p=.01; 95%CI [.282, 2.54]), and a trend to lower Aβ42CSF (p=.07;95%CI [‐.032, .001]) over 24 months. An interaction between AL increase and APOE4 was observed, indicating that higher increases in AL were associated with higher Aβ42blood but for APOE4 with two E4 copies only (p=.03;95%CI [‐2.568, ‐0.0908]). No association was observed with HV (p=.435).ConclusionAmyloid and tau deposition over time was higher among participants with increases in AL, suggesting that elevated AL profiles might signal a potential underlying mechanism explaining AD pathology trajectories. Further research is needed to examine whether incorporating AL in AD models improves the prediction of cognitive decline. A critical step for non‐pharmacological clinical trials testing interventions to reduce dementia risk.
Correlation between cerebral small vessel disease biomarkers and blood‐brain barrier permeability in participants of the encephalopathy and memory clinic cohort
Authors: Pongpitakmetha Thanakit , Thanapornsangsuth Poosanu , Pornteparak Nattanich , Ongphichetmetha Tatchaporn , Rianaree Juthamas , Luechaipanit Watayuth , Haethaisong Thanaporn , Chongsuksantikul Adipa , Thanprasertsuk Sekh , Likitjaroen Yuttachai , Hemachudha Thiravat 
Published: January 2025

AbstractBackgroundThe blood‐brain barrier (BBB) is considered the crucial part of neuroprotection from various neurological insults including infection, inflammation, and neurodegeneration including Alzheimer’s disease (AD). The cerebral small vessel disease (CSVD) pathologies especially cerebral microbleeds (CMBs) and gadolinium enhancement might reflect the disruption of BBB. The correlation between BBB permeability measured by cerebrospinal fluid (CSF)/plasma albumin quotient (Qalb) and CSVD biomarkers is poorly understood. Thus, we aim to further evaluate this correlation in our cohort.MethodsPooling participants from preceding studies on individuals with encephalopathy and from patients attending a memory clinic, where both plasma and CSF were recruited. The magnetic resonance imaging (MRI) closest to the Qalb date was independently rated by the trained investigator using STRIVE‐2 criteria (Duering M, et al. Lancet Neurol. 2023) blinded from the clinical information. The composite total CSVD score (Staals J, et al. Neurology. 2014) ranging from 0‐4 was calculated. The presence of gadolinium enhancement was evaluated. The non‐parametric correlations between neuroimaging biomarkers and Qalb were examined.Results110 participants were enrolled. Clinical, laboratory, and neuroimaging biomarkers were summarized in Table 1. A notable positive correlation exists between Qalb and total CSVD score in the whole cohort (Spearman rho = 0.45, p‐value = 7.837e‐07) and encephalopathy cohort (Spearman rho = 0.59, p‐value = 3.347e‐08). The Spearman’s correlation between Qalb and each neuroimaging biomarker was shown in Table 2. Wilcoxon rank sum test with continuity correction between Qalb and presence of gadolinium enhancement was significantly difference (W = 474, p‐value = 0.015). The visualized correlation plots were shown in Figure 1.ConclusionThe total CSVD and Qalb showed a strong correlation in determining the BBB permeability only in encephalopathy population. The CSVD neuroimaging biomarkers and gadolinium enhancement, which reflect the BBB damage and risk of further neurological deterioration, should carefully be evaluated and considered in clinical practice. The strategies to slow the progression of CSVD including the optimized blood pressure control, avoiding the potential neurotoxic agents, etc. should be raised in this situation, resulting in slowing neuropathological progression. Further confirmatory validation studies, especially memory clinic settings, should be done.
Along‐Tract Analysis of White Matter Bundles in Alzheimer’s disease using Medial Tractography Analysis (MeTA)
Authors: Gari Iyad Ba , Narula Siddharth , Gadewar Shruti , Nir Talia M , Jahanshad Neda 
Published: January 2025

AbstractBackgroundAlong‐tract analysis of white matter (WM) bundles can help map detailed patterns of WM pathway degeneration in Alzheimer's disease. Here, we present Medial Tractography Analysis (MeTA), which aims to minimize partial voluming and microstructural heterogeneity in diffusion MRI (dMRI) metrics by extracting and parcellating the volume along the bundle length while preserving bundle shape and capturing variation within and along WM bundles. We evaluated along‐tract WM microstructure associations with clinical measures in ADNI using MeTA.MethodWe used dMRI and clinical data from 714 participants (aged 55‐96 years, 52% females) enrolled in ADNI3. The dMRI data were processed using: denoised using Local PCA, deGibbs, and corrected for eddy current and motion artifacts using FSL eddy. The fiber orientation distributions (iFOD2) were estimated using a multi‐tissue constrained spherical deconvolution approach. Whole brain probabilistic streamline tractography was generated. RecoBundles was used to identify and segment 12 WM bundles. We applied MeTA to the bundles and evaluated the diffusion tensor (DTI) fractional anisotropy (FA) and mean diffusivity (MD) associations with 1) clinical impairment (N=274) compared to cognitively normal (CN); 2) Clinical Dementia Rating Scale Sum of Boxes (CDR‐SB); 3) tau load indexed with AV‐1451; and 4) amyloid (Aβ) with FBB/FBP. Full details of the pipelines can be found in Figure 1. We used linear mixed models, with age and sex as fixed effects, and scan sites as nested random variables. We corrected for multiple comparisons across 315 tests (21 bundles x 15 regions) using the false discovery rate (FDR) procedure (q=0.05).ResultParticipants with cognitive impairment, higher CDR‐SB scores, tau and Aβ pathology showed negative associations with FA values and positive associations with MD measures across bundles such as IFOF_L, CPH_R, UF_R, AF_L, MdLF_L, EMC_L, CST, and CC as displayed in Figure 2. All the statistical tests were completed across 15 segments in one bundle in about 20 seconds.ConclusionMeTA is a fast and reliable approach for identifying regional WM brain abnormalities in neurodegenerative populations and can be used to map localized effects of disease progression. MeTA is a highly scalable approach that can be applied to large‐scale collaborative multisite AD efforts and consortia.
Performance of mutiple blood‐based biomarkers used in community Alzheimer’s disease screening via a new ultrasensitive micro‐array immunoassay platform
Authors: Cheng Peng , Zhang Minchao , Chen Hao , Li Hui 
Published: January 2025

AbstractBackgroundAD is a neurodegenerative disease characterized by progressive cognitive dysfunction and behavioral impairment. The use of biomarkers for early detection of AD is crucial for developing potential treatments. The benefit of using blood‐based biomarkers in screening for AD is that the collection of blood is less invasive than the collection of cerebrospinal fluid, and less costly than neuroimaging. Numerous studies have reported that certain biomarkers are good candidates for AD diagnostics. However, most of the studies utilized clinical cohorts which are less heterogenous than the community‐based population. In China, the number of AD patients is growing rapidly, which poses a considerable burden on society and families. There is a need to establish predictive values of blood‐based biomarkers. This study evaluates the potential of an ultrasensitive micro‐array immunoassay to measure plasma biomarkers and further used in screening AD among the community‐based population in China.MethodAn ultrasensitive micro‐array immunoassay, with a limit of detection (LOD) under 100 fg/mL was developed to measure AD related biomarkers. Blood‐based biomarkers (pTau181, Aβ1‐42, Aβ1‐40 etc.) were measured using this method. Above 1500 plasma samples (age>55) were analyzed. Some of the samples had Aβ‐PET data. Results were adjusted for age, sex and year of education.ResultThe population that involved in this study are retired hospital employees. The levels of the blood‐based biomarkers were measured. The level of these biomarkers showed associations with age, sex, education level, BMI, as well as other medical conditions (hypertension, diabetes, etc.) The associations of these variables were used to construct adjusted models. Comparison of different models were performed to evaluate the predictive performance. Model PAV II was chosen as the best model for predicting AD.ConclusionBy using an ultrasensitive micro‐array immunoassay, the levels of blood‐based biomarkers were evaluated. Models for predicting AD were constructed and evaluated. Model PAV II involve the levels of biomarkers, medical conditions and other variables showed the best result for predicting AD. The results from the community‐based population indicate that biomarkers in blood have high potential to be used as a screening tool for the detection of AD.
Utility of plasma GFAP as a biomarker for Alzheimer's Disease using chemiluminescent microparticle immunoassay
Authors: Pizarro Eduard Bargay , García Daniel Morell , Martin Ana García , Sanchez Susana Tarongi , Santos Lara Nuñez , Medina Lorena Garcia , Bertó María Santés , Ferrer Guillermo Amer 
Published: January 2025

AbstractBackgroundGlial fibrillary acidic protein (GFAP) is a putative blood biomarker for Alzheimer's disease (AD). Most studies measure plasma GFAP (pGFAP) utilizing the Single Molecule Array (Simoa) platform or other high‐cost platforms. However, we aim to validate the value of GFAP as a blood biomarker for AD using chemiluminescent microparticle immunoassay (CMIA), an ubiquitous lower‐cost platform.MethodA cohort of 56 subjects (from our memory clinic) with mild cognitive impairment (MCI) or dementia were analyzed retrospectively. Demographic and clinical data, neuroimaging, and neuropsychological test results were collected. AD cerebrospinal fluid biomarkers and pGFAP were simultaneously obtained from all patients between July 2022 and February 2023. pGFAP was measured using CMIA on the Alinity‐i‐series platform (Abbott, US), with a lower limit of quantification of 3.2pg/mL and an intra‐assay coefficient of variation <5%.Result38 patients were classified as part of the AD continuum: 21 dementia, 18 MCI. The remaining 18 were classified as non‐AD (FTLD, LBD and non‐neurodegenerative): 5 dementia, 13 MCI. The median age in the AD group was 75.7 (IQR: 71.3‐78.2), while in non‐AD it was 71.9 (IQR: 63.3‐73.8) in non‐AD, P=0.019. There were no differences between groups in other demographic factors. We found a significant correlation between age and pGFAP increase in all patients (P=0.035). In AD group median pGFAP was 54.4pg/ml (IQR: 41.8 ‐ 85.3), compared to 34.2pg/ml (IQR: 15.8 ‐ 40.7) in non‐AD, P<0.001. These results were consistent when adjusted for confounding variables (age and other clinical and demographic variables), P<0.001. There were several trends in pGFAP levels, although not significant: higher levels in AD dementia versus AD MCI (P=0.131) and in non‐AD dementia compared to non‐AD MCI (P=0.065), also an inverse correlation between pGFAP and MMSE score (P=0.104). Using a threshold of 46.3pg/ml, GFAP alone differentiated AD from non‐AD with an area under the curve (AUC) of 0.82 (CI: 0.71‐0.94), sensitivity of 89% and specificity of 68%.ConclusionOur findings obtained using a CMIA technique were similar to those found in the literature, in which other platforms have been used. This suggests that pGFAP measured using widely available low‐cost platform based on CMIA may have diagnostic utility for AD.
Patients’ perceptions and considerations regarding DNA testing in a memory clinic: DNA‐ABOARD
Authors: van der Schaar Jetske , van der Lee Sven J , Asscher Eva , van der Flier Wiesje M. , Pijnenburg Yolande A.L. , Bredenoord Annelien L. , van den Hoven Mariette A. , Smets Ellen M.A. , Visser Leonie N.C. 
Published: January 2025

AbstractBackgroundData‐driven criteria for DNA testing were implemented in routine care of Alzheimer Center Amsterdam. We aimed to explore patients’ perspectives and considerations regarding their decision to (not) be tested for a monogenic cause of their disease.MethodsIn this mixed method study, 150 of 519 new patients visiting Alzheimer Center Amsterdam who fulfilled the criteria were offered DNA‐diagnostics: 86(57%) accepted, 64(43%) did not. In 65/86(76%) cases results were negative, in 14/86(16%) a monogenic cause and in 7/86 (8%) variants of uncertain significance were found (Figure 1). Sex, age, education, family history of dementia, MMSE and diagnosis were retrieved. Before discussing DNA testing, patients completed a questionnaire assessing perceived risk of a genetic cause, susceptibility for, severity of, and experience with dementia, social support, coping strategies, anxiety, depression, and quality of life. Differences between those who did and did not consent to DNA testing were calculated using Pearson’s χ², Mann‐Whitney U or Independent Samples t‐tests; p‐values were FDR‐adjusted. A subset of 22 patients and/or relatives participated in semi‐structured interviews on motivations and considerations regarding their decision. Verbatim transcripts were analyzed inductively using MAXQDA‐software.ResultsParticipants (n = 150) were 46% female and aged 61±8 (MMSE = 22±6, 5 Subjective Cognitive Decline, 9 MCI, 104 dementia [69 AD, 13 FTD, 22 other], 32 other/undetermined). Adjusted for multiple testing, no demographic, medical or psychosocial factors were associated with the decision on DNA testing (all p>0.05). Twenty‐one interviewees who agreed to DNA testing were generally motivated by obtaining information on heredity for their relatives, contributing to scientific research into a treatment, and gaining insight in the cause of their disease. One patient had blood stored, allowing their children to test it when opportune. The majority decided quickly, mostly on intuitions (e.g., responsibility towards relatives) rather than facts (e.g., information on risk and consequences). They expected to feel reassured or relieved by negative test results, and sad or worried if a genetic cause was found.ConclusionsOver half of memory clinic patients eligible for DNA‐testing wanted to be tested. This decision was unrelated to demographic, medical or psychosocial characteristics, and mostly based on intuition and considerations regarding family.
A network approach to dementia care burden: exploring relationships between objective and subjective indicators of care burden in caregivers of community‐dwelling persons with dementia
Authors: Balvert Sanne C.E. , Butterbrod Elke , Sikkes Sietske A. M. , Dröes Rose‐Marie , Scherder Erik J. A. , Milders Maarten V. 
Published: January 2025

AbstractBackgroundTo support informal caregivers of persons with dementia (PwD), it is fundamental to understand how objective and subjective indicators of care burden are interrelated. This study used psychometric network analyses to explore care burden indicators and extend current models of care in informal caregivers of PwDs.MethodsBaseline data from an intervention study of 170 informal caregivers of community‐dwelling PwDs was used. Variables included (subscales of) the following measures: a) time since diagnosis, b) objective indicators of care burden: hours of care provided, dependence of the PwD for (Instrumental) Activities of Daily Living (Interview for Deterioration in Daily Living Activities; IDDD), and c) subjective indicators of care burden: caregiver sense of competence (SCQ), positive experiences of caregiving (Positive experiences Scale; POS), shared activities (Pleasant Events Schedule; PES), caregiver depressive symptomatology (Center for Epidemiologic Studies–Depression; CES‐D) and caregiver self‐rated health (VAS‐score). A Gaussian graphical model was employed to explore unique relationships between the measures while accounting for all other relationships in the network. Node strength (strongest total associations of an indicator with other indicators), betweenness and closeness were interpreted if the central stability coefficient was sufficient (>0.25).ResultsCaregivers (71.8% female, 69.5±11.0 years) provided 4.80±5.57 hours of care daily (Table 1 and 2). Node strength and edges reached sufficient stability. The strongest unique relationships existed mostly within objective and subjective measures (e.g., between CES‐D somatic and depressed subscales (r = 0.51); and between total hours of care and ADL‐dependence (r = 0.29), see Figure 1). No significant cross‐connections existed between objective and subjective measures. Within subjective measures, several interrelations were found: PES was associated with SCQ ‐ satisfaction with the PwD (r = 0.20), POS was associated SCQ ‐ satisfaction as caregiver (r = 0.17), and both PES and POS were associated with CES‐D affect (r = ‐0.17, r = ‐0.24). Caregiver’s self‐rated health was only associated with CES‐D somatic (r = ‐0.22).ConclusionOur results suggest that objective care burden and disease duration may not be strongly related to caregivers’ experiences, and highlight the interconnectedness of subjective indicators. These insights can contribute to better understanding of care burden and ultimately to more effective support for caregivers of PwD.