Systemic and central nervous system metabolic alterations in Alzheimer's disease - PubMed (original) (raw)

doi: 10.1186/s13195-019-0551-7.

Tony Teav 1, Héctor Gallart-Ayala 1, Florence Mehl 1, Ioana Konz 1, Christopher Clark 2, Aikaterini Oikonomidi 3, Gwendoline Peyratout 3, Hugues Henry 4, Mauro Delorenzi 5 6, Julijana Ivanisevic 7, Julius Popp 8 9

Affiliations

Systemic and central nervous system metabolic alterations in Alzheimer's disease

Vera van der Velpen et al. Alzheimers Res Ther. 2019.

Abstract

Background: Metabolic alterations, related to cerebral glucose metabolism, brain insulin resistance, and age-induced mitochondrial dysfunction, play an important role in Alzheimer's disease (AD) on both the systemic and central nervous system level. To study the extent and significance of these alterations in AD, quantitative metabolomics was applied to plasma and cerebrospinal fluid (CSF) from clinically well-characterized AD patients and cognitively healthy control subjects. The observed metabolic alterations were associated with core pathological processes of AD to investigate their relation with amyloid pathology and tau-related neurodegeneration.

Methods: In a case-control study of clinical and biomarker-confirmed AD patients (n = 40) and cognitively healthy controls without cerebral AD pathology (n = 34) with paired plasma and CSF samples, we performed metabolic profiling, i.e., untargeted metabolomics and targeted quantification. Targeted quantification focused on identified deregulated pathways highlighted in the untargeted assay, i.e. the TCA cycle, and its anaplerotic pathways, as well as the neuroactive tryptophan and kynurenine pathway.

Results: Concentrations of several TCA cycle and beta-oxidation intermediates were higher in plasma of AD patients, whilst amino acid concentrations were significantly lower. Similar alterations in these energy metabolism intermediates were observed in CSF, together with higher concentrations of creatinine, which were strongly correlated with blood-brain barrier permeability. Alterations of several amino acids were associated with CSF Amyloidβ1-42. The tryptophan catabolites, kynurenic acid and quinolinic acid, showed significantly higher concentrations in CSF of AD patients, which, together with other tryptophan pathway intermediates, were correlated with either CSF Amyloidβ1-42, or tau and phosphorylated Tau-181.

Conclusions: This study revealed AD-associated systemic dysregulation of nutrient sensing and oxidation and CNS-specific alterations in the neuroactive tryptophan pathway and (phospho)creatine degradation. The specific association of amino acids and tryptophan catabolites with AD CSF biomarkers suggests a close relationship with core AD pathology. Our findings warrant validation in independent, larger cohort studies as well as further investigation of factors such as gender and APOE genotype, as well as of other groups, such as preclinical AD, to identify metabolic alterations as potential intervention targets.

Keywords: Alzheimer’s disease; CSF AD biomarkers; Energy metabolism; Metabolomics; Tryptophan pathway.

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Conflict of interest statement

JP received consultation honoraria from Nestle Institute of Health Sciences, Innovation Campus, EPFL, Lausanne, Switzerland, Ono Pharma and from Fujirebio Europe. The other authors declare that they have no competing interests.

Figures

Fig. 1

Fig. 1

Study design and metabolic profiling workflow. Plasma and CSF samples were collected concomitantly, from the same subject. Metabolic signatures acquired by the untargeted profiling were explored using the pathway enrichment and topology analysis to identify the biochemical pathways affected in AD. Targeted quantification of metabolites implicated in these identified affected pathways was then performed to obtain the accurate and precise measurement of metabolite concentrations. The clinical phenotype comparison was followed by paired blood plasma vs. CSF comparison and correlation with QAlb to assign the origin of the observed changes. Finally, the associations with known CSF markers of AD pathology were investigated to link the identified changes at the metabolite and pathway level with the clinical outcome. LC-HRMS – liquid chromatography coupled to high-resolution mass spectrometry, LC-MS/MS – liquid chromatography coupled to tandem mass spectrometry, KEGG – Kyoto Encyclopedia of Genes and Genomes, SMPDB – Small Molecule Pathway Data Base

Fig. 2

Fig. 2

Systemic and central nervous system alterations in AD in the energy metabolism hub; the TCA cycle and its anaplerotic pathways (i.e., amino acid metabolism, glycolysis and beta-oxidation). For a direction of metabolite alterations in AD patients versus control in plasma (PL) and CSF, ↑ higher concentrations in AD vs control, ↓ lower concentrations in AD vs control, “-“ indicates “not detected” or below limit of quantification, * statistically significant higher or lower concentrations in AD vs control P < 0.05 (T-test). For b to e, * statistically significant P < 0.05 (_T_-test), **P < 0.01, n.s. not significant

Fig. 3

Fig. 3

Systemic and central nervous system alterations in products of tryptophan breakdown in AD. Direction of metabolite alterations in AD patients versus control in plasma (PL) and CSF; ↑ higher concentrations in AD vs control, ↓ lower concentrations in AD vs control, “-“ indicates “not detected” or below limit of quantification, * statistically significant higher or lower concentrations in AD vs control P < 0.05 (T-test)

Fig. 4

Fig. 4

Correlations of metabolite concentrations in CSF with Qalb in control (a) and AD patients (b) and boxplots of metabolites with significantly different CSF/plasma ratios between control and AD patients (c). For a and b, significantly different metabolites in dark blue with –log_P_ value > 3 (represents P value < 0.05). For c, *P < 0.05 and **P < 0.001

Fig. 5

Fig. 5

Associations of plasma (left) and CSF (right) metabolite concentrations with core AD pathology as measured by CSF biomarker concentrations. Results from linear regression analysis are presented; colors represent beta-coefficients of the CSF biomarker estimate (red for positive association, blue for negative association), circle size represents P value of the CSF biomarker estimate (P < 0.01 or P < 0.05, for large and small respectively). Figure depicts the results of linear metabolite concentration ~ CSF biomarker model that remained significant after the correction for age and gender. Detailed results for age- and gender-corrected models are given in Additional file 1: Table S7

References

    1. Herholz K. Cerebral glucose metabolism in preclinical and prodromal Alzheimer’s disease. Expert Rev Neurother. 2010;10(11):1667–1673. doi: 10.1586/ern.10.136. - DOI - PubMed
    1. Talbot K, Wang HY, Kazi H, Han LY, Bakshi KP, Stucky A, et al. Demonstrated brain insulin resistance in Alzheimer's disease patients is associated with IGF-1 resistance, IRS-1 dysregulation, and cognitive decline. J Clin Invest. 2012;122(4):1316–1338. doi: 10.1172/JCI59903. - DOI - PMC - PubMed
    1. Steen E, Terry BM, Rivera EJ, Cannon JL, Neely TR, Tavares R, et al. Impaired insulin and insulin-like growth factor expression and signaling mechanisms in Alzheimer's disease--is this type 3 diabetes? J Alzheimers Dis. 2005;7(1):63–80. doi: 10.3233/JAD-2005-7107. - DOI - PubMed
    1. Cadonic C, Sabbir MG, Albensi BC. Mechanisms of mitochondrial dysfunction in Alzheimer’s disease. Mol Neurobiol. 2016;53(9):6078–6090. doi: 10.1007/s12035-015-9515-5. - DOI - PubMed
    1. Mathys J, Gholamrezaee M, Henry H, von Gunten A, Popp J. Decreasing body mass index is associated with cerebrospinal fluid markers of Alzheimer's pathology in MCI and mild dementia. Exp Gerontol. 2017;100:45–53. doi: 10.1016/j.exger.2017.10.013. - DOI - PubMed

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