Alzheimers Dement (Amst) 2017 6;8:196-207. Epub 2017 Sep 6.
Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center Amsterdam, Amsterdam, The Netherlands.
Introduction: Identification of blood-based metabolic changes might provide early and easy-to-obtain biomarkers.
Methods: We included 127 Alzheimer's disease (AD) patients and 121 control subjects with cerebrospinal fluid biomarker-confirmed diagnosis (cutoff tau/amyloid β peptide 42: 0.52). Mass spectrometry platforms determined the concentrations of 53 amine compounds, 22 organic acid compounds, 120 lipid compounds, 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 five hubs of metabolic dysregulation: tyrosine, glycylglycine, glutamine, lysophosphatic acid C18:2, and platelet-activating factor C16:0. The metabolite network for apolipoprotein E () ε4 negative AD patients was less cohesive compared with the network for ε4 positive AD patients.
Discussion: Multiple signatures point to various promising peripheral markers for further validation. The network differences in AD patients according to genotype may reflect different pathways to AD.