Blood-based metabolic signatures in Alzheimer's disease.

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.