Blood-based metabolic signatures in Alzheimer's disease

• Published in: arXiv.org 2017-09
• Main Authors: de Leeuw, Francisca A, Peeters, Carel F W, Kester, Maartje I, Harms, Amy C, Struys, Eduard A, Hankemeier, Thomas, Herman W T van Vlijmen, Sven J van der Lee, van Duijn, Cornelia M, Scheltens, Philip, Demirkan, Ayşe, Mark A van de Wiel, Wiesje M van der Flier, Teunissen, Charlotte E
• Format: Article
• Language: English
• Subjects: Alzheimer's disease; Biomarkers; Blood; Classification; Glutamine; Lipids; Mass spectrometry; Metabolism; Metabolites; Patients; Tyrosine
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.1709.07285

Introduction: Identification of blood-based metabolic changes might provide early and easy-to-obtain biomarkers. Methods: We included 127 AD patients and 121 controls with CSF-biomarker-confirmed diagnosis (cut-off tau/A\(\beta_{42}\): 0.52). Mass spectrometry platforms determined the concentrations of 53 amine, 22 organic acid, 120 lipid, and 40 oxidative stress compounds. Multiple signatures were assessed: differential expression (nested linear models), classification (logistic regression), and regulatory (network extraction). Results: Twenty-six metabolites were differentially expressed. Metabolites improved the classification performance of clinical variables from 74% to 79%. Network models identified 5 hubs of metabolic dysregulation: Tyrosine, glycylglycine, glutamine, lysophosphatic acid C18:2 and platelet activating factor C16:0. The metabolite network for APOE \(\epsilon\)4 negative AD patients was less cohesive compared to the network for APOE \(\epsilon\)4 positive AD patients. Discussion: Multiple signatures point to various promising peripheral markers for further validation. The network differences in AD patients according to APOE genotype may reflect different pathways to AD.