ArticleJournal of Alzheimer's disease : JAD2020
Metabolic Profiles Help Discriminate Mild Cognitive Impairment from Dementia Stage in Alzheimer's Disease.
Article in Journal of Alzheimer's disease : JAD, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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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
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Feasibility of Using Magnetic Resonance Spectroscopy Test Biomarkers to Diagnose Alzheimer's Disease: Systematic Evaluation and Meta-Analysis.Actas espanolas de psiquiatria · 2024Pooled it
- Systematic review: fluid biomarkers and machine learning methods to improve the diagnosis from mild cognitive impairment to Alzheimer's disease.Alzheimer's research & therapy · 2023Pooled it
- Genetic regulation of the metabolome differs by sex, Alzheimer's disease stage, and plasma biomarker status.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Genetic Regulation of the Metabolome Differs by Sex, Alzheimer's Disease Stage, and Plasma Biomarker Status.medRxiv : the preprint server for health sciences · 2025Article
- Studying Alzheimer's disease through an integrative serum metabolomic and lipoproteomic approach.Journal of translational medicine · 2025Article
- Article
- Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024Article
- Increased serum phenylalanine/tyrosine ratio associated with the psychiatric symptom of anti-NMDAR encephalitis.Frontiers in neurology · 2024Article
- Article
- Machine Learning Selection of Most Predictive Brain Proteins Suggests Role of Sugar Metabolism in Alzheimer's Disease.Journal of Alzheimer's disease : JAD · 2023Article
- Metabolomic profiling of CSF and blood serum elucidates general and sex-specific patterns for mild cognitive impairment and Alzheimer's disease patients.Frontiers in aging neuroscience · 2023Article
- Review
- Metabolomic alterations in the blood plasma of older adults with mild cognitive impairment and Alzheimer's disease (from the Nakayama Study).Scientific reports · 2022Article
- A Nuclear Magnetic Resonance Spectroscopy Method in Characterization of Blood Metabolomics for Alzheimer's Disease.Metabolites · 2022Article
- Classifying mild cognitive impairment and Alzheimer's disease by constructing a 14-gene diagnostic model.American journal of translational research · 2022Article
- Multi-omic evaluation of metabolic alterations in multiple sclerosis identifies shifts in aromatic amino acid metabolism.Cell reports. Medicine · 2021Article
- Article
- The "develOpment of metabolic and functional markers of Dementia IN Older people" (ODINO) Study: Rationale, Design and Methods.Journal of personalized medicine · 2020Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Accurate differentiation between neurodegenerative diseases is developing quickly and has reached an effective level in disease recognition. However, there has been less focus on effectively distinguishing the prodromal state from later dementia stages due to a lack of suitable biomarkers. We utilized the Disease State Index (DSI) machine learning classifier to see how well quantified metabolomics data compares to clinically used cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD). The metabolic profiles were quantified for 498 serum and CSF samples using proton nuclear magnetic resonance spectroscopy. The patient cohorts in this study were dementia (with a clinical AD diagnosis) (N = 359), mild cognitive impairment (MCI) (N = 96), and control patients with subjective memory complaints (N = 43). DSI classification was conducted for MCI (N = 51) and dementia (N = 214) patients with low CSF amyloid-β levels indicating AD pathology and controls without such amyloid pathology (N = 36). We saw that the conventional CSF markers of AD were better at classifying controls from both dementia and MCI patients. However, quantified metabolic subclasses were more effective in classifying MCI from dementia. Our results show the consistent effectiveness of traditional CSF biomarkers in AD diagnostics. However, these markers are relatively ineffective in differentiating between MCI and the dementia stage, where the quantified metabolomics data provided significant benefit.
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