Article

A leakage-controlled multi-compartment benchmark of fluid biomarkers for predicting mild cognitive impairment to Alzheimer’s disease conversion: plasma, CSF, and high-plex omics in a single cohort

2026-08-05

Abstract excerpt

<title>Abstract</title> <p>Approved disease-modifying therapies have made it a practical priority to predict, early and at low cost, who among people with mild cognitive impairment (MCI) will progress to Alzheimer's disease (AD) dementia. The candidate biomarkers sit across biological compartments that differ sharply in invasiveness and cost: blood plasma, cerebrospinal fluid (CSF, via lumbar puncture), and high-...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 029bd4db-2be4-5465-badf-6f05055ce25d
DOI: 10.21203/rs.3.rs-10580655/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A leakage-controlled multi-compartment benchmark of fluid biomarkers for predicting mild cognitive impairment to Alzheimer’s disease conversion: plasma, CSF, and high-plex omics in a single cohortDOI 10.21203/rs.3.rs-10580655/v1Read

Multi-Omics Modelling of Plasma pTau181, GFAP, and Metabolic Features Enables Risk Stratification in Prodromal Alzheimer’s DiseaseSemantic proximity Read

Multiomics machine learning identifies inflammation molecular pathways in prodromal Alzheimer’s DiseaseSemantic proximity Read

Multi-Omics Integration of Transcriptomics and Metabolomics with Machine Learning Uncovers Novel Risk Factors for Alzheimer’s diseaseSemantic proximity Read

Dementia etiology classification using NULISA plasma biomarkers and machine learningSemantic proximity Read

Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures across the Alzheimer disease continuumSemantic proximity Read

Blood-Based RNA Biomarkers and Machine Learning Approaches for Alzheimer’s DiseaseSemantic proximity Read

Machine Learning-Based Multiclass Classification of Cognitive Stages Using Plasma Biomarkers, Clinical Assessments, and Genetic Features: A Repeated Nested Cross-Validation Study in ADNI with External Validation in CNTNSemantic proximity Read

Multiomics profiling of human plasma and CSF reveals ATN derived networks and highlights causal links in Alzheimer’s diseaseSemantic proximity Read

Brain cross-omics integration in Alzheimer’s diseaseSemantic proximity Read

High-sensitivity plasma proteomics reveals disease-specific signatures and predictive biomarkers of Alzheimer’s disease phenotypes in a large mixed dementia cohortSemantic proximity Read

Mapping the circulating proteome across neurodegeneration: A harmonized, consortium-scale framework for uncovering molecular pathophysiologySemantic proximity Read

Fluid Candidate Biomarkers for Alzheimer’s Disease: A Precision Medicine ApproachSemantic proximity Read