ArticleJournal of Alzheimer's disease : JAD2024
Discovery of novel metabolic biomarkers in blood serum for diagnosis of Alzheimer's disease.
Article in Journal of Alzheimer's disease : JAD, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Long-term risk of dementia following encephalitis: a large-scale retrospective cohort study of electronic health records.Journal of neurology · 2026Article
- Association between serum lactoferrin concentrations and the prevalence of mild cognitive impairment among Chinese adults: a cross-sectional study.European journal of nutrition · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundBlood metabolites have emerged as promising candidates in the search for biomarkers for Alzheimer's disease (AD), as evidence shows that various metabolic derangements contribute to neurodegeneration in AD.
objectiveWe aim to identify metabolic biomarkers for AD diagnosis.
methodsWe conducted an in-depth analysis of the serum metabolome of AD patients and age, sex-matched cognitively unimpaired older adults using ultra-high-performance liquid chromatography-high resolution mass spectrometry. The biomarkers associated with AD were identified using machine learning algorithms.
resultsUsing the discovery dataset and support vector machine (SVM) algorithm, we identified a panel of 14 metabolites predicting AD with a 1.00 area under the curve (AUC) of receiver operating characteristic (ROC). The SVM model was tested against the verification dataset using an independent cohort and retained high predictive accuracy with a 0.97 AUC. Using the random forest (RF) algorithm, we identified a panel of 13 metabolites that predicted AD with a 0.96 AUC when tested against the verification dataset.
conclusionsThese findings pave the way for an efficient, blood-based diagnostic test for AD, holding promise for clinical screenings and diagnostic procedures.
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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 Socratic graph.