ArticleBrain communications2024
Comparison of cerebrospinal fluid, plasma and neuroimaging biomarker utility in Alzheimer's disease.
Article in Brain communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 19 citations in OpenAlex.
- Structural MRI in frontotemporal dementia and Alzheimer's disease: stage-dependent atrophy patterns.Journal of neural transmission (Vienna, Austria : 1996) · 2026Review
- Associations between self-reported change in lifestyle behaviors and brain health: Findings from the Healthy Brain Initiative.Journal of Alzheimer's disease : JAD · 2026Article
- Reference proteins to improve Core 1 and Core 2 Alzheimer's disease CSF and plasma biomarkers.Brain : a journal of neurology · 2026Article
- Associations of amyloid biomarkers with brain and cognitive changes from imaging, spinal fluid, and plasma.medRxiv : the preprint server for health sciences · 2026Article
- Logopenic variant of primary progressive aphasia in a bilingual non-Alzheimer's disease octogenarian.Dementia & neuropsychologia · 2026Article
- Explainable machine learning for Alzheimer's disease characterization using small-sample EEG data.Frontiers in aging neuroscience · 2026Article
- Elevated functional magnetic resonance imaging activity in cognitively normal participants predicts future dementia.Brain communications · 2026Article
- The Knight Alzheimer Research Imaging (KARI) dataset: a comprehensive multimodal resource for exploring aging, preclinical, and symptomatic Alzheimer disease pathology.Research square · 2025Article
- Optimizing timing and cost-effective use of plasma biomarkers in Alzheimer's disease.Alzheimer's research & therapy · 2025Article
- Plasma MTBR-tau243 biomarker identifies tau tangle pathology in Alzheimer's disease.Nature medicine · 2025Article
- The interactome of tau phosphorylated at T217 in Alzheimer's disease human brain tissue.Acta neuropathologica · 2025Article
- Cutting through the noise: A narrative review of Alzheimer's disease plasma biomarkers for routine clinical use.The journal of prevention of Alzheimer's disease · 2025Review
- Association of plasma biomarkers of Alzheimer's pathology and neurodegeneration with gait performance in older adults.Communications medicine · 2025Article
- Association between estimated glucose disposal rate and cardiovascular diseases in patients with diabetes or prediabetes: a cross-sectional study.Cardiovascular diabetology · 2025Article
- Article
- Peptide-Bound Glycative, AGE and Oxidative Modifications as Biomarkers for the Diagnosis of Alzheimer's Disease-A Feasibility Study.Biomedicines · 2024Article
- Predicting continuous amyloid PET values with CSF tau phosphorylation occupancies.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- P-tau217 as a Reliable Blood-Based Marker of Alzheimer's Disease.Biomedicines · 2024Review
- Application of machine learning to blood-based biomarkers of Alzheimer's disease in Down syndrome.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
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Authors and funding
22 authors at 1 institution in 1 country.
Funding
Abstract
Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning. Data were obtained from 527 community-dwelling volunteers enrolled in studies at the Charles F. and Joanne Knight Alzheimer Disease Research Center at Washington University in St Louis. We used hierarchical clustering to group 27 imaging, CSF and plasma measures of amyloid beta, tau [phosphorylated tau (p-tau), total tau t-tau)], neuronal injury and inflammation drawn from MRI, PET, mass-spectrometry assays and immunoassays. Neuropsychological and genetic measures were also included. Random forest-based feature selection identified the strongest predictors of amyloid PET positivity across the entire cohort. Models also predicted cognitive impairment across the entire cohort and in amyloid PET-positive individuals. Four clusters emerged reflecting: core Alzheimer's disease pathology (amyloid and tau), neurodegeneration, AT8 antibody-associated phosphorylated tau sites and neuronal dysfunction. In the entire cohort, CSF p-tau181/A
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.