Identification of altered metabolic pathways in plasma and CSF in mild cognitive impairment and Alzheimer's disease using metabolomics

Background: Research evidence suggests that pathophysiological changes associated with Alzheimer’s Disease (AD) begin at least 10 to 25 years before the dementia onset. Compelling data demonstrate that increased levels of amyloid beta (Ab) compromise multiple cellular mechanisms. The ability to monitor changes in a variety of pathways including non-amyloid pathways is essential to advance our understanding of the early disease mechanisms and to identify novel therapeutic targets to treat and modify the disease progression. Application of metabolomics, a powerful tool that allows detecting perturbations in the metabolome and represents an accurate biochemical profile of the organism in health and disease, offers new opportunities in biomedical research. Methods: We applied a liquid chromatography/mass spectrometry-based non-targeted metabolomics approach to determine metabolic changes in plasma and cerebrospinal fluid (CSF) from the same individuals with different AD severity. Results: Metabolic profiling detected a total of 342 plasma and 351 (P 0.05) CSFmetabolites, of which 22% were identified. Based on the changes of >150 metabolites, we found 23 altered canonical pathways (P 0.05) in plasma and 20 in CSF (P 0.05) in mild cognitive impairment (MCI) vs. cognitively normal (CN) individuals with a false discovery rate (FDR)<0.05. The number of affected pathways increased with disease severity in both fluids. Lysine metabolism (P 10 -5) in plasma and the TCA cycle (P 10 -5) in CSF were significantly affected in MCI vs. CN. Cholesterol and sphingolipids transport (P 10 -8) was altered in both CSF and plasma of AD vs. CN. Other 30 canonical pathways significantly affected in MCI and AD patients included energy metabolism, Krebs cycle, mitochondrial function, neurotransmitter and amino acid metabolism, and lipid biosynthesis. Pathways in plasma that discriminated between all groups included polyamine, lysine, tryptophan metabolism, and aminoacyl-tRNA biosynthesis; and in CSF included cortisone and prostaglandin 2 biosynthesis and metabolism. Conclusions: Our data suggest AD pathogenesis involves early changes in multiple functionally connected networks shared in progression from MCI to AD. Our data validate plasma as reliable source for metabolomic profiling and suggest that metabolomics is a valuable tool for the identification of molecular mechanisms involved in the etiology of AD.