Alterations in metabolic pathways and networks in Alzheimer's disease

Abstract

The pathogenic mechanisms of Alzheimer's disease (AD) remain largely unknown and clinical trials have not demonstrated significant benefit. Biochemical characterization of AD and its prodromal phase may provide new diagnostic and therapeutic insights. We used targeted metabolomics platform to profile cerebrospinal fluid (CSF) from AD (n=40), mild cognitive impairment (MCI, n=36) and control (n=38) subjects; univariate and multivariate analyses to define between-group differences; and partial least square-discriminant analysis models to classify diagnostic groups using CSF metabolomic profiles. A partial correlation network was built to link metabolic markers, protein markers and disease severity. AD subjects had elevated methionine (MET), 5-hydroxyindoleacetic acid (5-HIAA), vanillylmandelic acid, xanthosine and glutathione versus controls. MCI subjects had elevated 5-HIAA, MET, hypoxanthine and other metabolites versus controls. Metabolite ratios revealed changes within tryptophan, MET and purine pathways. Initial pathway analyses identified steps in several pathways that appear altered in AD and MCI. A partial correlation network showed total tau most directly related to norepinephrine and purine pathways; amyloid-β (Ab42) was related directly to an unidentified metabolite and indirectly to 5-HIAA and MET. These findings indicate that MCI and AD are associated with an overlapping pattern of perturbations in tryptophan, tyrosine, MET and purine pathways, and suggest that profound biochemical alterations are linked to abnormal Ab42 and tau metabolism. Metabolomics provides powerful tools to map interlinked biochemical pathway perturbations and study AD as a disease of network failure.

Figure 1

Changes in the methionine (a), tryptophan (b), purine (c) and tyrosine (d) pathways in Alzheimer's disease (AD). Red metabolites: significantly increased in AD; dark metabolites: not measured. Red and green pathways: significantly up- and downregulated in AD, respectively, implicated by ratios. For expansions of the metabolite abbreviations, see Table 2.

Figure 2

Changes in the methionine (a), tryptophan (b), purine (c) and tyrosine (d) pathways in mild cognitive impairment (MCI). Red metabolites: significantly increased in MCI; dark metabolites: not measured. Red and green pathways: significantly up- and downregulated in MCI, respectively, implicated by ratios. For expansions of the metabolite abbreviations, see Table 2.

Figure 3

PLS-DA models for separation between AD, MCI and CN. (a) Separation between AD and CN; (b) separation between MCI and CN. Examples of PLS-DA models cross-validation: (c) AD versus CN and (d) MCI versus CN. A, Alzheimer's disease; AD, Alzheimer's disease; C, normal cognition; CN, normal cognition; M, mild cognitive impairment; MCI, mild cognitive impairment; PLS-DA, partial least square-discriminant analysis.

Figure 4

A partial correlation network among clinical AD biomarkers and MMSE (red) and known (green) and important unknown (blue) CSF metabolites in all the participants. AD, Alzheimer's disease; CSF, cerebrospinal fluid; MMSE, Mini-Mental State Exam. For expansions of the metabolite abbreviations, see Table 2.