bluuebunny/crossref_metadata_2025_split huggingface dataset:
Engaging people with lived experience in a national research network: Experience from the Canadian Consortium on Neurodegeneration in Aging
Authors: Bethell Jennifer , Myers Karen , Norman Myrna , Snowball Ellen , McGilton Katherine S 
Published: January 2025

AbstractEngagement of People with Lived Experience of Dementia (EPLED) was a new cross‐cutting program introduced as part of the Canadian Consortium on Neurodegeneration in Aging (CCNA) for their second 5‐year phase (from 2019 to 2024). The initiative was supported by the Alzheimer Society of Canada as part of their commitment to the CCNA. EPLED had three objectives: (1) support persons with dementia and care partners to be actively involved in the CCNA research process; (2) work with CCNA research Teams, Cross‐cutting Programs and Partners to develop novel mechanisms and formats to further this collaboration; and, (3) advance the methods of patient engagement in research by embedding evaluation. One of the main activities of EPLED was to recruit and support an Advisory Group of people from across Canada with diverse lived experiences of dementia. Since 2020, EPLED Advisory Group members became involved in various CCNA central and research team activities as well as contributing as co‐presenters and co‐authors in academic and non‐academic venues and as co‐applicants and co‐investigators on research grants. Advisory Group members also took on roles advocating for more people living with dementia in research roles. Key factors described for the success of the Advisory Group were developing trusting relationships, providing education, offering support, being flexible and acknowledging tensions between research, practice and lived experience. Ongoing challenges often related to the gap between research and practice and balancing EPLED’s research objectives with aspirations for advocacy and system‐level change. Looking forward to the third phase of the CCNA, key challenges will include: developing capacity to meet increasing research funding expectations of engagement while also ensuring meaningful engagement, engaging new perspectives by recruiting new Advisory Group members while also retaining expertise from existing members, evaluating the impact of engagement and initiating EPLED‐driven research initiatives.
Synergic effect of tau tangles and cortical thinning on cognitive decline in aging and Alzheimer’s disease
Authors: Trudel Lydia , Therriault Joseph , Rahmouni Nesrine , Aumont Etienne , Wang Yi‐Ting , Servaes Stijn , Macedo Arthur C. , Chan Tevy , Arias Jaime Fernandez , Hall Brandon J , Hosseini Seyyed Ali , Socualaya Kely Monica Quispialaya , Mathotaarachchi Sulantha , Stevenson Jenna , Lussier Firoza Z , Gauthier Serge , Pascoal Tharick A. , Rosa‐Neto Pedro 
Published: January 2025

AbstractBackgroundTau burden has been found to be involved in brain atrophy during aging, especially in regions such as the parahippocampal gyrus. However, how tau levels at baseline are associated with trajectories of tau accumulation, cortical thinning and cognitive impairment remains poorly understood. The goal of this study was to assess tau rate of change in patients between baseline Tau+ and Tau‐ patients. We also aimed to determine if tau status at baseline or rate of accumulation of tau interacted with the rate of cortical thinning of the parahippocampal regions, leading to an increased rate of change in cognition.MethodWe assessed 133 participants from the TRIAD cohort (mean age = 68.5 ± 8.9, 85 females) with at least two visits with tau‐PET using [18F]MK6240 and cortical thickness extracted using FreeSurfer 7. Average time between visits was 25.6 months. Patients were classified according to clinical status, Amyloid‐β status and tau status at baseline (CU AB‐Tau‐, CU AB+Tau‐, CU AB+Tau+, MCI AB+Tau‐, MCI AB+Tau+, AD AB+Tau+). The tau‐PET rate of change was calculated for each participant, voxelwise and with temporal meta‐ROI. The MMSE rate of change was calculated to quantify cognitive decline over follow‐up period. We assessed the voxelwise relationship between baseline tau status and tau‐PET rate of change.ResultsWe found a voxelwise positive association between rate of accumulation of tau and tau status at baseline in both anterior temporal lobes. Furthermore, we found an interaction effect between tau‐PET at baseline and parahippocampal rate of atrophy on MMSE rate of change (standardized β = 0.48, p < 0.0001).ConclusionOur results suggest that tau status at baseline might impact the rate of accumulation of tau, and that higher baseline levels of tau interact with cortical thinning of parahippocampal regions, leading to faster rates of cognitive decline. Our results emphasize the importance of preventing tau burden to prevent faster pace of cognitive decline during the disease’s trajectory.
Comparison of amyloid positron emission tomography, hippocampal volume, and plasma biomarkers in predicting conversion to mild cognitive impairment
Authors: Bilgel Murat , An Yang , Shah Ishaan , Walker Keenan A. , Moghekar Abhay , Ashton Nicholas J. , Kac Przemyslaw Radoslaw , Karikari Thomas K , Blennow Kaj , Zetterberg Henrik , Thambisetty Madhav , Resnick Susan M. 
Published: January 2025

AbstractBackgroundWe examined whether brain amyloid PET, hippocampal volume, or plasma biomarkers are better predictors of conversion to mild cognitive impairment (MCI).MethodIn the Baltimore Longitudinal Study of Aging (BLSA), plasma Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) concentrations were measured using Quanterix Simoa Neurology 4‐plex E. Plasma p‐tau181 and p‐tau231 concentrations were measured using in‐house Simoa assays at University of Gothenburg. Brain amyloid was quantified using mean cortical 11C‐Pittsburgh compound B PET distribution volume ratio (mcDVR). Hippocampal volume was calculated from T1‐weighted MRI and adjusted for intracranial volume. Of 178 cognitively unimpaired (CU) participants with both plasma and neuroimaging measurements at baseline, 33 developed MCI during follow up (median time to MCI onset: 3.7 [interquartile range (IQR) 2.1–6.2] years), 17 of whom had elevated brain PET amyloid at baseline. We used Cox proportional hazards models to examine the association between risk of conversion to MCI (time to conversion right‐censored at death or last visit for CU participants) and baseline plasma or neuroimaging biomarker, adjusting for age, sex, race, and education. To enable comparison of hazard ratios (HRs), we negated plasma Aβ42/Aβ40 and hippocampal volume, and standardized each biomarker using statistics calculated in a cross‐sectional dataset of CU individuals aged 60–80 (preferring the visit closest to age 70 per participant) drawn from the larger BLSA. For standardization, we examined subtracting the median and dividing by the IQR and binarization (top tertile vs. not).ResultIn analyses using IQR normalized scores, mcDVR and plasma Aβ42/Aβ40 and GFAP had statistically significant HRs (Table 2). In binarized biomarker analyses, mcDVR and plasma GFAP, p‐tau181, and p‐tau231 were statistically significant. Using all plasma biomarkers together yielded the highest concordance: 0.877±0.026 and 0.861±0.026 for the continuous and binarized biomarker analyses, respectively.ConclusionPlasma biomarkers provide information beyond demographics regarding the prediction of MCI conversion within 4 years. Risk prediction conveyed by several individual plasma biomarkers exceeded that of brain amyloid PET. Plasma GFAP was consistently identified as contributing to the prediction of MCI conversion, with Aβ42/Aβ40 and p‐tau exhibiting statistically significant associations in a subset of analyses.
Can neuroimaging methods help us to disentangle WMH etiology in AD?
Authors: Dadar Mahsa , Parent Olivier 
Published: January 2025

AbstractWhite matter hyperintensities (WMHs) are frequently observed in ageing individuals, and have a higher prevalence in neurodegenerative disorders such as Alzheimer’s disease. Ex‐vivo assessments of the microstructural alterations within WMHs have reported heterogeneous tissue alterations, with demyelination, axonal loss, and inflammation presenting with various degrees of severity. There is a crucial need to better assess the severity of WMH microstructural alterations in vivo, in particular with the emergence of anti‐amyloid immunotherapies and the associated risk of Amyloid Related Imaging Abnormalities (ARIAs) in individuals with comorbid vascular disease. Recent in‐vivo and ex‐vivo investigations have revealed important aetiology differences in regional WMHs, linking frontal WMHs to more vascular factors (e.g. ischaemia) and posterior WMHs to neurodegenerative processes. Regional WMH features might therefore reveal additional information regarding their potential aetiologies in absence of postmortem neuropathology information. Novel neuroimaging techniques such as diffusion‐weighted imaging (DWI) and quantitative magnetic resonance imaging (qMRI) can also provide further insight into the specific pathophysiological properties of the WMHs. These microstructural MRI metrics allow for the characterization and measurement of iron and myelin density, axonal integrity, and water content, paving the way for deep phenotyping of the pathophysiology of WMHs in‐vivo. Using DWI and qMRI data from the UKBiobank, we assessed the differences in baseline volume, mean diffusivity (MD), isotropic volume fraction (ISOVF, an index of relative extracellular water diffusion), fractional anisotropy (FA), intracellular volume fraction (ICVF, an estimate of neurite density), orientation dispersion (OD, reflecting the directional complexity of diffusion), T2* relaxation, and quantitative susceptibility mapping (QSM, sensitive to myelin and iron) of periventricular, anterior, and posterior WMHs between those with a diagnosis of AD (N=15) and cerebrovascular disease (N=95) in their future visits (mean interval: 3.3years). Our results show differences in their baseline WMH pathophysiological and spatial patterns (Figure 1), with cerebrovascular pathologies having a higher WMH burden on most metrics, especially in anterior regions. Figure 2 shows the standardized beta coefficients of the models, controlling for age and sex. Combined, regional volumetric and signal measures might therefore be able to provide important additional information regarding the aetiology of WMHs at an individual level.
Differences in referral source across racial and ethnic groups at Alzheimer’s Disease Research Centers
Authors: Chan Carol , Lane Kathleen A. , Gao Sujuan , Adeoye‐Olatunde Omolola A , Biber Sarah A , Risacher Shannon L. , Saykin Andrew J. , Wang Sophia 
Published: January 2025

AbstractBackgroundDespite recognition of the need to increase underrepresented groups (URG) engagement in Alzheimer’s disease and related dementias (ADRD) studies, enrollment remains low. As a first step in examining these disparities, these analyses aimed to compare referral sources for Alzheimer’s Disease Research Centers (ADRC) enrollment of URG participants.MethodThese analyses included data from 48,330 participants across 46 ADRCs, obtained through the National Alzheimer’s Coordinating Center Uniform Data Set. Generalized logistic regression models with generalized estimating equations were used to examine the association of racial/ethnic group and professional vs non‐professional referral source. The ‘professional’ category included referrals made by healthcare professionals or ADRC staff, while the ‘non‐professional’ category included referrals made by self, family or friends. This association was examined across the entire sample, and then individuals who had completed magnetic resonance imaging (MRI). The analyses were adjusted for age, gender, education, visit year, and categorical CDR with random site effect to adjust for study site.ResultDescriptive statistics are shown in Table 1. Non‐Hispanic Black and Asian participants were less likely to have completed an MRI. Across the entire sample, Non‐Hispanic Black and Non‐Hispanic Asian participants were less likely to be referred by a professional contact than Non‐Hispanic White participants (Table 2). In those who had completed an MRI, there were no significant differences across the racial groups, although we note that the sample sizes for those with MRI were much smaller (Table 3). Results for both analyses were similar when only participants who had a diagnosis of MCI or dementia and a global CDR of 0.5 or 1 at baseline were included.ConclusionOne major factor leading to lower rates of URG participation in ADRD research is disproportionately fewer healthcare professional referrals. To develop and optimize ADRC recruitment strategies, future studies are needed to explore reasons for differences in URG referrals by healthcare professionals and non‐professionals.
Temporal order of gait speed decline relative to changes in measures affected early in Alzheimer’s disease
Authors: Bilgel Murat , Tian Qu , Walker Keenan A. , Moghekar Abhay , Ashton Nicholas J. , Kac Przemyslaw Radoslaw , Karikari Thomas K , Blennow Kaj , Zetterberg Henrik , Thambisetty Madhav , Resnick Susan M. 
Published: January 2025

AbstractBackgroundIndividuals with dual decline in gait and cognition have a greater risk of developing dementia. Understanding when gait speed declines relative to measures affected early in Alzheimer’s disease can improve risk assessment.MethodUsing data for 761 participants (1,108 cognitively unimpaired visits) from the Baltimore Longitudinal Study of Aging, we estimated the trajectories of gait speed, memory (California Verbal Learning Test [CVLT] immediate recall score), hippocampal volume, and plasma Aβ42/Aβ40, glial fibrillary acidic protein (GFAP), and p‐tau181.We fitted a progression score (PS) model that aligns individuals based on the similarity of their multivariate longitudinal observations to reveal long‐term biomarker trajectories, accounting for individual differences in baseline level and rate of progression. We included height as a covariate for gait speed, first administration versus not for CVLT (to control for practice effect), intracranial volume for hippocampal volume, and estimated glomerular filtration rate for each plasma biomarker.74 participants converted to mild cognitive impairment (MCI) or dementia after the last visit used for fitting the PS model and were used to verify that the estimated PS reflects neurodegenerative disease progression using a Cox proportional hazards model. We then examined the temporal ordering of the estimated biomarker trajectories by comparing the timing of peak relative changes.ResultGreater PS at last visit was associated with a higher risk of conversion to MCI/dementia (hazard ratio for interquartile range normalized PS = 6.1, P < 2×10‐16). The PS‐only model had a better concordance index compared to an age‐only model for predicting conversion (0.880 ± 0.016 vs. 0.852 ± 0.018). Estimated trajectories as a function of PS are shown in Figure 1. The peak relative change in hippocampal volume occurred prior to that of gait speed (difference in PS between peaks: ‐0.57 [95% confidence interval ‐1.32, ‐0.05]), whereas p‐tau181 changed later (difference in PS between peaks: 1.95 [1.19, 2.45]) (Figure 2).ConclusionDecline in gait speed occurs after hippocampal volume loss but alongside other biomarkers known to be affected early in Alzheimer’s disease and it can prove useful in individualized prediction. Alternative approaches for examining temporal ordering will help assess robustness of findings.
Effect of plant‐based diets on plasma biomarkers of Alzheimer's disease
Authors: Eslick Shaun , Austin Grace , Ferguson Jessica , Garg Manohar , Martins Ralph N 
Published: January 2025

AbstractBackgroundInterest and consumption of plant‐based diets (PBD) in the 21st century continued to increase, particularly in western societies, with the perception that PBDs are associated with beneficial health outcomes and a reduced environmental footprint. Evidence suggests that PBDs may be protective against neurodegenerative diseases, such as Alzheimer’s disease (AD). Health effects of PBDs such as reduction of inflammation, shift in gut microbiota composition, reduced risk of type 2 diabetes and cardiovascular disease are all believed to attribute to reduced AD risk. Therefore, we hypothesise that plasma amyloid beta (Aβ), glial fibrillary acidic protein (GFAP), neurofilament light (NFL) and phosphorylated tau (pTau) will be lower in individuals habitually following a vegan dietary pattern compared to those following a regular meat‐eating diet.MethodMen and women, 30‐75yrs without current or diagnosed CVD who followed a vegan (nil animal flesh or animal derived products) or regular meat (≥daily consumption of animal flesh) dietary pattern for a minimum of six months. Fasting blood was collected and plasma separated by centrifugation and stored at ‐80°. Biomarkers of AD including Aβ1‐40, Aβ1‐42, GFAP, and NFL and pTau181 were measured using ultra‐sensitive Single Molecule Array (SIMOA) assay platform.ResultA total of 94 plasma samples were analysed from the vegan (n=47) and the regular meat eaters (n=47) dietary pattern groups. In the vegan group, the mean plasma Aβ1‐42/Aβ1‐40 ratio (p=0.01), plasma GFAP (p=0.04) and plasma NFL (p<0.01) were significantly lower compared to the regular meat eaters’ group. However, plasma pTau181 was found to be similar between the two groups (p=0.29).ConclusionThis study demonstrated that blood‐based biomarkers are lower in individuals following a vegan dietary pattern compared to those following a regular meat‐eating diet, suggesting that PBDs may be protective against Alzheimer’s disease pathology.
Novel Diagnostic Tool for Detecting Cognitive Impairment by Integrating Functional Near‐infrared Spectroscopy and Plasma Biomarkers in a Large Chinese Cohort
Authors: Jiao Bin , Ouyang Ziyu , Zhang Sizhe , Zhang Cong , Xiao Xuewen , Liu Yiliang , Bei Yuzhang , Zhu Yuan , Yang Qijie , Xu Tianyan , Hao Xiaoli , Yang Xuan , Wan Meidan , Luo Shilin , Tang Beisha , Shen Lu 
Published: January 2025

AbstractBackgroundAn objective and effective screening tool for cognitive impairment (CI) is needed in the Chinese population. However, whether the integration of brain resting‐state functional connectivity (rs‐FC) and neurodegenerative plasma biomarkers can distinguish CI from cognitively normal (CN) individuals remains unclear.MethodA total of 1077 participants from a longitudinal Liuyang community cohort were enrolled. The rs‐FC was collected using functional near‐infrared spectroscopy (fNIRS). Plasma biomarkers, including p‐tau181, p‐tau217, p‐tau231, Aβ40, Aβ42, NfL, and GFAP were detected using single molecule assay method.ResultThe average FC of the CI group was significantly lower than that of the CN group (p < 0.0001). The CI detection model based on the combined altered FCs, achieved an area under the curve (AUC) of 0.785, which showed better diagnostic performance than that of single plasma biomarker with AUC of 0.592‐0.631. However, the integration of altered FC and plasma biomarker presented the best accuracy with AUC of 0.887‐0.933. Totally, 27 FCs were correlated with plasma biomarkers, and among them, the strength of right part of Brodmann's area 6 vs. right part of Brodmann's area 1+2 (BA6R.vs.BA1+2R) was negatively associated with p‐tau231, p‐tau217 and GFAP. Additionally, 13 FCs could mediate the effects of three plasma biomarkers on cognition, including p‐tau217 (n = 3), NfL (n = 10), and GFAP (n = 1).ConclusionRs‐FC based on fNIRS combined with plasma biomarkers is feasible and effective for non‐invasive CI screening.
Blood biomarkers of amyloid and tau pathologies, brain degeneration, inflammation, and oxidative stress in early‐ and late‐onset Alzheimer's disease
Authors: Xia Xinyi , Qin Qi , Tang Yi 
Published: January 2025

AbstractBackgroundBlood biomarkers provide a non‐invasive and accessible means of detection for Alzheimer's disease (AD). Specifically, biomarkers associated with early‐onset AD (EOAD) illuminate the underlying mechanisms and provide valuable guidance for potential therapies. We aim to present blood biomarker evidence in individuals with both EOAD and late‐onset AD (LOAD), as well as in age‐matched healthy controls.MethodsA total of 95 participants were enrolled in the study. We assessed levels of 18 distinct blood biomarkers, and concurrently examined cerebrospinal fluid amyloid and tau markers, neuropsychological test scores, APOEε4 carrier status, and neuroimaging markers. Group disparities, correlations, and the diagnostic utility of these biomarkers were investigated.ResultsIn patients with EOAD, levels of blood IL‐4, IL‐6, and TNF‐α were notably lower when compared to LOAD. AD patients exhibited higher blood levels of p‐tau181, NfL, GFAP, tAOC, and MDA, as well as lower levels of Aβ1‐42, SOD, and IL‐12p70. Intricate interactions were observed among these blood biomarkers, with inflammatory markers demonstrating correlations with neuroimaging markers within the AD cohort. Individuals carrying the APOEε4 allele displayed elevated levels of GFAP and IL‐4 in comparison to non‐carriers. Additionally, blood levels of Aβ1‐42, p‐tau181, NfL, and GFAP were found to correlate with neuropsychological scores and proved effective in distinguishing AD, with GFAP exhibiting particular relevance in early‐onset cases.ConclusionThe study demonstrated that individuals with EOAD may experience less inflammatory responses than older patients. Peripheral inflammation was associated with amyloid and tau pathologies, astrogliosis, oxidative stress, and alterations in brain structure and function. Blood Aβ1‐42, p‐tau181, NfL, and GFAP showed promise in detecting cognitive decline and AD, with GFAP exhibiting relevance in early‐onset cases.
Changes in peripheral AD biomarkers in a randomized controlled trial of Yoga vs. memory training in older women at risk for Alzheimer’s disease
Authors: Lavretsky Helen 
Published: January 2025

AbstractBackgroundBiomarkers such as amyloid beta (Aβ) peptides and tau protein can correlate with changes in cognition and mood symptoms associated with AD. We aimed to investigate the blood biomarker response to a Kundalini Yoga (KY) compared to Memory Enhancement Training (MET) intervention as well as determine the predictive value of blood biomarkers on outcomes in a randomized trial targeting women at risk for Alzheimer's disease.MethodWomen aged 60 years old and older with subjective memory complaints and high cardiovascular risk score were randomized to a 12‐week RCT of Kundalini yoga or Memory enhancement training (MET). We obtained blood samples at baseline and week 24 (6 months) to measures AB40; AB42 and p‐Tau. Participants completed the Beck Depression Inventory (BDI) for depressive symptoms, and Memory Functioning Questionnaire (MFQ) for subjective memory reports. Regression models were used to examine whether baseline and changes in biomarker levels including Aβ40, Aβ42, Aβ42/40 ratio and tau were associated with changes in outcomes at 24 weeks.ResultA total of 79 patients (KY=40; MET=39) were randomized, and 63 completed the 24‐week follow‐up. There were no group differences in AD biomarkers at baseline or at 24‐week follow‐up. Baseline levels of Aβ40 were significantly associated with an increase in subjective memory (MFQ Frequency of Forgetting; r = 0.27, p=0.04). An increase in Aβ40 levels was significantly associated with a decrease in BDI (r = ‐0.33, p=0.02). There was no significant association of changes in Aβ42, Aβ42/40 ratio and tau with any outcomes.ConclusionOur findings indicate that greater levels of Aβ40 at baseline are associated with an increase in subjective memory at follow‐up and an increase in Aβ40 levels is correlated to a decrease in depressive symptoms as expected. It has been established that a low ratio of Aβ42/Aβ40 may reflect selective depletion of Aβ42 due to deposition in the growing plaques and subsequent AD pathology, while Aβ40 may have opposing effects on amyloid deposition and be neuroprotective. Our findings support the evidence that yoga can reduce stress, depression, and anxiety and may have an impact on peripheral AD biomarkers.