Power of a Metabonomic Approach to Investigate an Unknown Nervous Disease

Domange, Céline; Paris, Alain; Schroeder, Henri; Priymenko, Nathalie

doi:10.5772/30963

Cited by 2 publications

(4 citation statements)

References 81 publications

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“…One notable obstacle to the use of biofluids to reflect nervous system pathobiology is the blood-brain barrier (BBB) that serves to limit the passage of metabolites from the periphery. Thus, the degree to which biofluids (specifically plasma and urine) mirror brain health or disease, in particular, is contested (Domange, et al, 2011; Griffin and Salek, 2007). Indeed, to unequivocally gain access to the brain metabolome the tissue must be considered.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, studies in relevant animal models of human health and disease are crucial. Animal models, including transgenic and humanized mice, can mirror human disease events (Gorantla, et al, 2012) and enable the “true” metabolomics expressed in the phenotype to assess complex neural processes (Domange, et al, 2011). …”

Section: Introductionmentioning

confidence: 99%

“…Among the analytical techniques used in metabolomics, high resolution proton NMR ( 1 H NMR) and liquid-chromatography coupled to mass spectrometry (LC/MS) are widely applied for biofluid profiling whereas high resolution magic angle spinning (HR-MAS) NMR and magnetic resonance spectroscopy (MRS) are used to analyze brain tissue (Bluml, et al, 2013; Domange, et al, 2011). Among molecular imaging assays, magnetic resonance imaging (MRI) and positron emission tomography (PET) have enabled in vivo anatomical and functional studies (Rae, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Brain Region Mapping Using Global Metabolomics

Ivanišević¹,

Epstein²,

Kurczy³

et al. 2014

Chemistry & Biology

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SUMMARY Historically, studies of brain metabolism have been based on targeted analyses of a limited number of metabolites. Here we present a novel untargeted mass spectrometry-based metabolomics approach that has successfully uncovered differences in broad array of metabolites across anatomical regions of the mouse brain. The NSG immunodeficient mouse model was chosen because of its ability to undergo humanization leading to numerous applications in oncology and infectious disease research. Metabolic phenotyping by hydrophilic interaction liquid chromatography and nanostructure imaging mass spectrometry revealed unique water-soluble and lipid metabolite patterns between brain regions. Neurochemical differences in metabolic phenotypes were mainly defined by various phospholipids and several intriguing metabolites including carnosine, cholesterol sulfate, lipoamino acids, uric and sialic acid whose physiological roles in brain metabolism are poorly understood. This study lays important groundwork by defining regional homeostasis for the normal mouse brain to give context to the reaction to pathological events.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Brain Region Mapping Using Global Metabolomics

Ivanišević¹,

Epstein²,

Kurczy³

et al. 2014

Chemistry & Biology

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“…Metabolomics has become a promising tool for the research of etiology, biomarker discovery, early diagnosis, and treatment response biomarkers for neuropsychiatric disorders [ 7 ]. Previously, metabolomic strategies have been widely used to characterize human metabolic status in the field of central nervous system disorders such as Parkinson's, Alzheimer's, and Huntington's diseases, as well as various neuroinflammatory disorders [ 8 – 10 ]. Metabolomics has also gradually been applied towards the research area of neurodevelopmental disorders including bipolar disorder, autism spectrum disorder (ASD), Rett syndrome (RTT), and schizophrenia [ 11 – 14 ].…”

Section: Introductionmentioning

confidence: 99%

Untargeted Metabolomic Profiling Using UHPLC-QTOF/MS Reveals Metabolic Alterations Associated with Autism

Liang

Xiao

et al. 2020

BioMed Research International

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Autism spectrum disorder (ASD) is a clinical spectrum of neurodevelopment disorder characterized by deficits in social communication and social interaction along with repetitive/stereotyped behaviors. The current diagnosis for autism relies entirely on clinical evaluation and has many limitations. In this study, we aim to elucidate the potential mechanism behind autism and establish a series of potential biomarkers for diagnosis. Here, we established an ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry- (UHPLC-QTOF/MS-) based metabonomic approach to discriminate the metabolic modifications between the cohort of autism patients and the healthy subjects. UHPLC-QTOF/MS analysis revealed that 24 of the identified potential biomarkers were primarily involved in amino acid or lipid metabolism and the tryptophan kynurenine pathway. The combination of nicotinamide, anthranilic acid, D-neopterin, and 7,8-dihydroneopterin allows for discrimination between ASD patients and controls, which were validated in an independent autism case-control cohort. The results indicated that UHPLC-QTOF/MS-based metabolomics is capable of rapidly profiling autism metabolites and is a promising technique for the discovery of potential biomarkers related to autism.

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Power of a Metabonomic Approach to Investigate an Unknown Nervous Disease

Cited by 2 publications

References 81 publications

Brain Region Mapping Using Global Metabolomics

Brain Region Mapping Using Global Metabolomics

Untargeted Metabolomic Profiling Using UHPLC-QTOF/MS Reveals Metabolic Alterations Associated with Autism

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