We used a metabolomics approach to identify potential metabolic pathways implicated in the mechanisms of AD and MCI. Different perturbations in one-carbon metabolism, tyrosine, TRP and purine pathways were identified in CSF from AD and MCI patients. These findings complement and expand upon prior reports of alterations in neurotransmitter, purine and cysteine metabolism in AD and MCI, and provide some new insights. We have confirmed that all key metabolites that contribute to separation of groups are not confounded by gender differences.
Earlier studies indicated that blood levels of homocysteine and cysteine were increased in AD patients; it was also shown that increased homocysteine is associated with an increased risk of cognitive impairment and dementia,16
and alterations in the homocysteine metabolism are related to increased accumulation of p-tau and could contribute to the neurofibrillary pathology in normal aging and AD.17
Recently, a significant increase of cysteine in the CSF of AD patients has been reported.8
MET, the key metabolite of one-carbon metabolism, which provides the methyl groups for numerous methyl transferase reactions via S
-adenosylmethionine, is the precursor for homocysteine and cysteine, the rate-limiting amino acid in glutathione synthesis. Synthesis of glutathione involves formation of γ-glutamylcysteine from glutamate and cysteine (catalyzed by γ-glutamylcysteine synthetase), followed by the addition of glycine to γ-glutamylcysteine (catalyzed by glutathione synthetase). The role of glutathione depletion in AD and in dementia has been documented.18
In this study, we found for the first time that in both AD and MCI participants, the levels of MET—the precursor of homocysteine—are increased whereas the MET/GSH ratio is decreased. These findings suggest that the glutathione depletion in AD could result from perturbations within this pathway, probably occurring at the level of synthesis of glutathione from cysteine. Supporting this hypothesis are reports that upregulation of glutathione by γ-glutamylcysteine in primary neuronal cultures protects against Ab42-mediated oxidative stress and neurotoxicity,19
and that GSH delivery systems prevent amyloid-induced oxidative stress and cholinergic dysfunction in AD models in vitro
AD is associated with dysfunction of catecholaminergic and serotoninergic neurotransmitter systems. Post-mortem studies in AD have found the loss of noradrenergic (NE) neurons in locus coeruleus with corresponding decreases of NE levels in the cortical and subcortical projection areas, and have demonstrated that severity of AD correlated with the degree of NE neuron loss in locus coeruleus.21
Our previous metabolomic study found significant decreases in NE levels in ventricular CSF from autopsy-confirmed AD participants.7
NE was not measured in this study because of its very low levels in lumbar CSF; however, VMA levels (end product of the NE pathway) were found to be significantly increased in AD, as noted in previous ventricular CSF studies.7
The observed increases in VMA levels could be a result of medication, as approximately 15% of the AD participants were treated with the N
-aspartate antagonist, memantine, which was shown to increase the release and metabolism of NE.22
However, we found no differences in VMA levels between AD participants who received memantine and those who did not (data not shown). NE is metabolized by catechol-O
-methytransferase (COMT) and monoamine oxidase (MAO) with VMA as the end product. Therefore, it is possible that upregulation of COMT and/or MAO in AD patients could result in the observed increases of VMA in AD. Indeed, activation of MAO in the AD brain was recently demonstrated.23
COMT, in addition to the metabolism of monoamines, is the principal enzyme in the metabolism of estrogens that have recently been implicated in the AD pathogenesis through the ApoE-dependent mechanism.24, 25
The COMT GG genotype and APOE
4 allele have been found to have a synergistic effect upon the risk of AD, and COMT genetic variations could be associated with psychoses in AD.26
Therefore, the elevated levels of VMA in AD found in this study suggest upregulated COMT that, in turn, could result in the increased metabolism of estrogens. In this respect, it is interesting that levels of VMA were the highest among the
4 participants as compared with
4 and non-ApoE participants (data not shown). Further studies with larger cohorts of well-defined ApoE AD participants are necessary to elucidate the potential role of COMT in the mechanisms of AD.
The main metabolite of 5-HT metabolism, 5-HIAA, was increased in both AD and MCI participants. Potential mechanisms could involve upregulation of MAO activity in AD,23
or antidepressant therapy in these patients. No correlation was found between use of medications and levels of 5-HIAA (data not shown). We also observed an increased 5-HIAA/5-HTP ratio in AD and MCI groups, and an increased KYN/TRP ratio in MCI participants. These findings, combined with previous reports, provide further evidence for the involvement of TRP and KYN branch of its metabolism in mechanisms of neurodegeneration and in depression.27
We found increased XAN levels in AD and an increased ratio of URIC/XAN in MCI, which is in accordance with our previous studies in AD.7
Several studies have implicated mitochondrial dysfunction, oxidative stress and related perturbations in purine metabolism in the mechanisms of neurodegenerative disorders, including AD. Additionally, there is growing evidence for the involvement of purinergic transmission in the mechanisms of AD and in Ab42 processing. Post-mortem brain tissue from patients with a confirmed diagnosis of AD showed a loss of A1 adenosine receptors in the hippocampus, and an increased density of A1 and A2 receptors in the frontal cortex.28
In post-mortem neocortical and hippocampal tissue from patients with AD, a colocalization of A1 receptors with Ab42 in senile plaques was reported, and in human neuroblastoma cells, activation of A1 receptors was linked to increased formation of soluble Ab42; it was also found that purinergic receptors are involved in α-secretase-dependent processing of the Ab42.29, 30
In addition, novel purine-based γ-secretase modulators were introduced as selective agents toward Ab42.31
A partial correlation network has revealed new insights about links between protein markers of AD and metabolites. The correlation of t-tau to VMA and XAN suggests that the NE pathway and purine pathway might be implicated in t-tau pathology and that the MET pathway one-carbon metabolism and methylation might link to Ab42 pathology through the unknown compound 15–65.533. A new perspective emerging from recent research is that AD is a network disorder that affects a large number of neuronal cell types, is organized into functionally connected networks across many brain regions and is not simply a disease of discrete lesions limited to specialized brain regions associated with cognition and learning. Within this concept, AD is believed to be a response to a shift from normal to pathological networks, and hence the emerging recognition that we must understand the disease at a systems level. Metabolomics provides powerful tools to enable this systems approach.
In this study we used a targeted metabolomics approach to map biochemical pathways that could be implicated in the mechanisms of AD pathogenesis. CSF samples were analyzed as it is generally believed that CSF more closely reflects metabolic processes in the brain because of the free exchange of several molecules between the brain and CSF. Obviously, blood samples easily available in clinical setting would be more suitable for developing biomarkers for monitoring/predicting progression of the disease. However, the extent to which metabolic changes in blood reflect changes in CSF remains to be investigated and we will establish relationships between changes in central and peripheral compartments in future studies; most likely, for different classes of metabolites the relationships between central and peripheral compartments would be different. In this study, matching plasma and CSF samples from same subjects were not available; currently, we are collecting such samples for our next study. Integration of data obtained using different metabolomics and lipidomics platforms (both targeted and nontargeted) for central and peripheral samples with genetic, imaging and proteomic data for all AD subjects is our ultimate goal and focus of our current investigations. For MCI subjects involved in this study, no sufficient clinical data to enable us to define metabolic signatures of progression from MCI to AD were available. Currently, we are in the process of getting this information and are recruiting more MCI subjects to address this topic in subsequent studies.
The strength of our study is the careful and rigorous selection of participants and prospective nature of our cohort. However, there are limitations to our study. Although our approach was targeted, we did perform a large number of preplanned and exploratory analyses on a relatively small sample. However, within the logistics of obtaining CSF studies in a prospective cohort of AD and MCI patients, ours is one of the largest CSF metabolomics studies in at-risk and AD participants to date. We were unable to replicate some prior findings because of low levels of some metabolites in lumbar CSF compared with ventricular CSF (for example, NE). Yet, our findings complement prior findings in pointing to changes within key pathways; for example, studies have reported changes in cysteine levels in AD,32, 33
which seem related to our observation of alteration in MET and the GSH/MET ratio, although we could not measure cysteine. The same applies for observations with the VMA end product, NE. Previously, in post-mortem ventricular CSF, we measured NE and implicated it in AD pathogensis.7
Its levels were much lower in lumbar CSF (this study), and hence we could not measure it yet. Still, both studies pointed to the same pathway as being affected in AD. Differences in exogenous factors (diet, medications and comorbidities) between study samples might account for some of the variations, and are difficult to control for across studies. We have checked for possible effects of key drugs used in this patient population. We used Fisher's Exact Test to look for statistically significant associations between cognitive outcomes (AD vs MCI vs CN) and use of several medication classes. As expected, there was a statistically significant difference in the use of cholinesterase inhibitors (unadjusted P
<0.0001) as well as memantine (unadjusted P
=0.003), the two types of drugs commonly used to treat Alzheimer-type dementias, among the diagnostic groups. Use of antidepressants, antipsychotics, anxiolytics, corticosteroids and statins did not differ significantly between the diagnostic groups. Therefore, only the cholinesterase inhibitors and memantine were further examined for correlation with the metabolites. We did note marginal effects of these agents on a few metabolites including MET, MET/GSH ratio, and several unknown metabolites. None of these effects fully accounted for the reported metabolic differences between diagnostic groups. We have also performed analysis on metabolomics data that have been adjusted for drug effects and our reported findings remain highly significant. Our results should be viewed as hypothesis-generating comparisons rather than definitive findings. Therefore, our findings and theoretical speculations should be viewed as exploratory until replicated in larger independent studies.
In summary, our study reveals alterations in several functionally relevant metabolic networks and pathways in AD, with some overlapping changes in MCI. Further study of such findings might yield new insights about the mechanisms that underlie AD and novel targets for development as diagnostic or predictive markers.