Metabolome in progression to Alzheimer's disease

Abstract

Mild cognitive impairment (MCI) is considered as a transition phase between normal aging and Alzheimer's disease (AD). MCI confers an increased risk of developing AD, although the state is heterogeneous with several possible outcomes, including even improvement back to normal cognition. We sought to determine the serum metabolomic profiles associated with progression to and diagnosis of AD in a prospective study. At the baseline assessment, the subjects enrolled in the study were classified into three diagnostic groups: healthy controls (n=46), MCI (n=143) and AD (n=47). Among the MCI subjects, 52 progressed to AD in the follow-up. Comprehensive metabolomics approach was applied to analyze baseline serum samples and to associate the metabolite profiles with the diagnosis at baseline and in the follow-up. At baseline, AD patients were characterized by diminished ether phospholipids, phosphatidylcholines, sphingomyelins and sterols. A molecular signature comprising three metabolites was identified, which was predictive of progression to AD in the follow-up. The major contributor to the predictive model was 2,4-dihydroxybutanoic acid, which was upregulated in AD progressors (P=0.0048), indicating potential involvement of hypoxia in the early AD pathogenesis. This was supported by the pathway analysis of metabolomics data, which identified upregulation of pentose phosphate pathway in patients who later progressed to AD. Together, our findings primarily implicate hypoxia, oxidative stress, as well as membrane lipid remodeling in progression to AD. Establishment of pathogenic relevance of predictive biomarkers such as ours may not only facilitate early diagnosis, but may also help identify new therapeutic avenues.

Figure 1

Metabolomic profiles across the three diagnostic groups at baseline. (a) Mean metabolite levels within each cluster. Error marks show s.e.m. (^*P<0.05). When correcting for age and ApoE genotype, only LC4 remained statistically significant, whereas LC1 was marginally significant (P=0.07). (b) Profiles of selected representative metabolites from different clusters in control and Alzheimer's disease (AD) groups at baseline. The metabolite levels are shown as beanplots, which provide information on the mean level (solid line), individual data points (short lines), and the density of the distribution. The concentration scale in beanplots is logarithmic for some metabolites.

Figure 2

Feasibility of predicting Alzheimer's disease (AD), based on concentrations of three metabolites (2,4-dihydroxybutanoic acid, unidentified carboxylic acid, phosphatidylcholine (PC (16:0/16:0)) in subjects at baseline, who were diagnosed with mild cognitive impairment (MCI). (a) The characteristics of the model were determined by independent testing in one out of three of the sample across 2000 cross-validation runs. (b) Beanplots of the three metabolites included in the model. (c) Two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC–TOFMS) spectra of the two metabolites included in the model, 2,4-dihydroxybutanoic acid and an unidentified carboxylic acid. Acc=classification accuracy; AUC=area under the receiver operating characteristic (ROC) curve; OR=odds ratio.