Hector Gallart-Ayala (Presenter)
Metabolomics Platform, University of Lausanne
Bio: Hector Gallart-Ayala is a Senior Scientist at the Metabolomics Platform, University of Lausanne. His research expertise is in targeted and non-targeted mass spectrometry-based metabolomics application to biomedical research (inflammation and cancer metabolism), large clinical studies and the effect of environmental exposures to human health. He obtained his PhD in Analytical Chemistry from the University of Barcelona (Spain) in 2010. He joined UNIL in April 2017 after working as a postdoctoral researcher in Laboratory for the study of residues and contaminants in food (LABERCA) (Nantes, France) and Wheelock’s Lab at Karolinska Institute (Stockholm, Sweden). He also worked as a Senior Support Specialist Academia-OMICS at SCIEX.
Authorship: Héctor Gallart-Ayala (1), Tony Teav (1), Florence Mehl (1,2), Aikaterini Oikonomidi (3), Gwendoline Peyratout (3), Hugues Henry (4), Julijana Ivanisevic (1) and Julius Popp (3,5)
(1) Metabolomics Platform, Lausanne University, Faculty of Biology and Medicine, university of Lausanne, Lausanne, Switzerland. (2) Vital-IT – Swiss Institute of Bioinformatics, Lausanne, Switzerland. (3) Old Age Psychiatry, Department of Psychiatry, CHUV, Lausanne, Switzerland. (4) Clinical Chemistry Laboratory, Lausanne University Hospital, Lausanne, Switzerland. (5) Leenards memory Center, Department of Clinical Neurosciences, CHUV, Lausanne, Switzerland.
Here we present a non-targeted metabolomics approach to identify a metabolic signature of Alzheimer disease (AD). This approach was applied to paired samples of peripheral plasma and CSF of cognitively impaired subjects with AD pathology confirmed by CSF biomarkers and healthy aged controls without cerebral AD pathology. Results obtained indicate common and distinctive metabolic alterations in plasma and in CSF, outlining significantly affected amino acid metabolism. Both, plasma and CSF imply the amino acid catabolism or degradation.
Alzheimer disease (AD) is the most common cause of dementia affecting more than 46.8 million people worldwide and in ageing societies this prevalence is forecast to double every 20 years together with already heavy costs of care (1). Clinical studies indicate that the pathophysiological cascade or changes in the brain associated with disease begin more than two decades before the clinical onset of dementia. The hallmarks of this pathophysiological cascade comprise amyloidosis (abnormal β-amyloid (Aβ) protein metabolism followed by extracellular deposition of amyloid oligomer plaques), tauopathy (hyperphosphorylation of tau protein followed by misfolding and intracellular formation of neurofibrillary tangles), decreased glucose metabolism (reduced uptake and oxidation due to mitochondrial dysfunction) and brain atrophy (shrinkage of brain tissue, primarily cortex and hippocampus, due to nerve cell death).1 These changes interfere with nutrient transport, neurotransmission and cell-to-cell communication across brain, leading to synapse loss and neuronal death. Amyloid-β1-42, total-tau and phosphorylated tau at threonine 181 (p-tau181) are the only currently available biomarkers of cerebral AD pathology whose levels are monitored in plasma and cerebrospinal fluid (CSF). However, several approved therapies targeting amyloid and/or tau, as consequences rather than causes of disease progressions, have so far been unsuccessful – treating the symptoms but not the disease to slow down or indeed prevent cognitive decline. Besides, autopsies reveal that still up to 30% of clinical diagnoses are inconsistent due to complex set of drivers implicated in AD related cognitive decline. Therefore, the identification of markers in readily available biofluids suitable for large-scale clinical diagnostics using methods that could provide global information on the metabolic networks with high accuracy and reduced cost is of great interest.
Metabolomics is a powerful tool to investigate perturbations in the metabolome, which reflects the up-stream changes at the gene and protein level thus representing an accurate biochemical phenotype of the organism in health and disease. The field of metabolomics has greatly evolved in the last decade principally due to the advances in mass spectrometry (MS) technology and back-end bioinformatics (2). Metabolic profiling of CSF and plasma is a valuable minimally invasive approach for clinical applications in terms of high-throughput personalized diagnostics. Currently, two complementary approaches are applied, the hypothesis driven targeted approach and global non-targeted approach that tends to measure as many metabolites as possible without an a priori hypothesis bias (3).
A global non-targeted high resolution MS-based metabolic profiling was combined with targeted quantification to characterize a metabolic signature of AD. This combined approach was applied to paired samples of peripheral plasma and CSF of cognitively impaired subjects with AD pathology confirmed by CSF biomarkers (N=38) and healthy aged controls without cerebral AD pathology (N=34).
Prior to statistical analyses, systematic experimental variation (or signal intensity drift) was corrected by applying cubic spline regression on defined clusters of features using quality control (QC) samples. Then univariate and multivariate statistical analysis (including Principal Component Analysis - PCA and Orthogonal Projections to Latent Structures - OPLS-DA) were used to select discriminant metabolite features between control and confirmed AD patients. These discriminant features were annotated based on both accurate mass (AM) and MS/MS using available databases (HMDB and Metlin) and finally validated and quantified using targeted tandem MS approach.
The results of this pilot study with a focus on polar metabolome indicate common and distinctive metabolic alterations in plasma and in CSF, outlining significantly affected amino acid metabolism. Both, plasma and CSF imply the amino acid catabolism or degradation which is mainly mirrored in significantly depleted levels of charged basic (lysine, histidine) and aromatic (phenylalanine, tryptophan) amino acids in AD patients when compared to controls.
Conclusions & Discussion
In plasma, the alterations in lysine degradation pathway seem to lead to significant depletion of L-carnitine, which, as the only transporter of fatty acids to mitochondria for beta-oxidation, together with the production of unusual long chain acylcarnitines, also implies the perturbed energy production in mitochondria. On the other hand, the specific changes measured in CSF emphasize the upregulated glycine metabolism and purine nucleotide synthesis and degradation. Overall the observed changes at the metabolite level in peripheral blood and central CSF strongly suggest the perturbed central carbon energy metabolism and induced amino acid catabolism as a compensatory response to reduced glucose uptake and oxidation. In addition to the central carbon metabolism study and considering the key role of sphingolipids in selected CNS pathologies such as ischemia/hypoxia, AD and Parkinson disease, a targeted sphingolipid analysis was performed on the same sample cohort (plasma and CSF). This targeted approach included the measurement of sphingomyelins (SM C6:0 to SM C24:0), ceramides (Cer C2:0 to Cer C24:0), hexosylceramides (HexCer) and sphingoid bases. The alteration of sphingomyelins (SM) and ceramides (Cer) in both plasma and CSF, in addition to amino acid metabolism is currently further explored and correlated with CSF markers of the “core” AD pathology (Aβ1–42, tau, and P-tau181) and clinical assessment data, including the patient’s age, gender, body mass index (BMI), and blood-brain-barrier (BBB) permeability. The association of peripheral metabolic changes with central metabolism and clinical meta-data will allow for the identification of metabolic biomarker signatures of AD pathology and better understanding their impact on the clinical manifestation.
References & Acknowledgements:
1. Bateman, R. J., Xiong, C., Benzinger, T. L., Fagan, A. M., Goate, A., Fox, N. C., Marcus, D. S., Cairns, N. J., Xie, X., Blazey, T. M., Holtzman, D. M., Santacruz, A., Buckles, V., Oliver, A., Moulder, K. et al. Clinical and biomarker changes in dominantly inherited Alzheimer's disease. N Engl J Med 367, 795-804, doi:10.1056/NEJMoa1202753 (2012).
2. Johnson, C. H., Ivanisevic, J. & Siuzdak, G. Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol 17, 451-459, doi:10.1038/nrm.2016.25 (2016).
3. Ivanisevic, J., Elias, D., Deguchi, H., Averell, P. M., Kurczy, M., Johnson, C. H., Tautenhahn, R., Zhu, Z., Watrous, J. & Jain, M. Arteriovenous blood metabolomics: a readout of intra-tissue metabostasis. Scientific reports 5, 12757 (2015).
The authors wish to thanks Foundation Pierre-Mercier pour la Science for the financial support.
IP Royalty: no
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